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Journal of Marketing Research
Vol. XLIX (June 2012), 336–348

*Jing Lei is Senior Lecturer, Faculty of Business and Economics, Uni-
versity of Melbourne (e-mail: leij@unimelb.edu.au). Niraj Dawar is the
Barford Professor of Marketing, Richard Ivey School of Business, Univer-
sity of Western Ontario (e-mail: ndawar@ivey.uwo.ca). Zeynep Gürhan-
Canli is Migros Professor of Marketing, Koç University (e-mail: zcanli@
ku.edu.tr). The authors contributed equally to this project. They thank June
Cotte, Robert Fisher, and three anonymous reviewers for valuable com-
ments. They also thank Charan Bagga for part of the data collection. Gita
Johar served as associate editor for this article.

JING LEI, NIRAJ DAWAR, and ZEYNEP GÜRHAN-CANLI*

Consumers spontaneously construct attributions for negative events
such as product-harm crises. Base-rate information influences these
attributions. The research findings suggest that for brands with positive
prior beliefs, a high (vs. low) base rate of product-harm crises leads to
less blame if the crisis is said to be similar to others in the industry
(referred to as the “discounting effect”). However, in the absence of
similarity information, a low (vs. high) base rate of crises leads to less
blame toward the brand (referred to as the “subtyping effect”). For
brands with negative prior beliefs, the extent of blame attributed to the
brand is unaffected by the base-rate and similarity information.
Importantly, the same base-rate information may have a different effect
on the attribution of a subsequent crisis depending on whether
discounting or subtyping occurred in the attribution of the first crisis.
Consumers who discount a first crisis also tend to discount a second
crisis for the same brand, whereas consumers who subtype a first crisis
are unlikely to subtype again.

Keywords: base-rate information, consumer attributions, product-harm
crises

Base-Rate Information in Consumer
Attributions of Product-Harm Crises

Product-harm crises, or well-publicized instances of
defective or dangerous products, have become common-
place because of the increasing complexity of products and
more stringent product-safety legislation (Dawar and Pil-
lutla 2000). Mattel’s toy hazards, Toyota’s sudden accelera-
tion problem, and the many baby car seats, cribs, food prod-
ucts, and medicines that were recalled in 2011 due to design
and quality flaws are just a few of the more prominent
examples of the recent incidents. While recalls are expen-
sive for firms, the immediate expense of product replace-
ment and consumer compensation may pale in comparison
with the loss of consumer trust and damage to brand evalua-

tions. The extent of such damage largely depends on the
extent to which consumers attribute the blame to internal
firm-related factors (Folkes 1984).

One important cue that influences consumers’ attribution
is the base-rate (consensus) information, or how common
the focal behavior or event is among the population of inter-
est. Base-rate information is intuitively appealing as a basis
for attribution (Kassin 1979; Pilkonis 1977), especially in a
consumer setting (Kardes 1988). In judging a behavior/
event, consumers often ask if others would do the same. In
the context of a product-harm crisis, base-rate information
may describe the frequency of crises or recalls in the indus-
try. This simple statistic tends to be commonly available to
consumers from various sources, influencing their crisis
attribution. However, findings on the use of base-rate infor-
mation are decidedly mixed. Some studies (e.g., Folkes and
Kotsos 1986; Kelley 1972; Pilkonis 1977) suggest that a
high (vs. low) base rate leads to less attribution to actor-
related internal factors, because widespread prevalence sug-
gests that external factors may be to blame for the incident.
However, there is also considerable evidence that base rate
has little or no effect on attributions (e.g., Kardes 1988;
Kassin 1979; Nisbett and Borgida 1975). Given this incon-

Consumer Attributions of Product-Harm Crises 337

sistency of findings, it is unclear whether base rate (e.g.,
industry frequency) influences attribution of a product-harm
crisis. For example, would a “not just me” response (Johar,
Birk, and Einwiller 2010), suggesting the prevalence of
recalls in the auto industry, help alleviate consumers’ blame
of Toyota, and if so, under what circumstances?

The objective of this research is to examine whether
base-rate information affects consumers’ attribution of a
product-harm crisis, and if so, how? Findings from two
experimental studies and follow-up experiments contribute
to understanding of attributions and the effects of product-
harm crises in several ways. First, we demonstrate that the
effect of base-rate information does not always conform to
the conventional prediction that a high (vs. low) base rate
leads to less blame being attributed to the actor (in our set-
ting, the focal brand). Instead, the effect of base-rate infor-
mation on consumers’ attribution of a product-harm crisis
depends on (1) consumers’ prior beliefs about the brand and
(2) the similarity of the focal crisis to other crises in the
industry. For brands with positive prior beliefs, high (vs.
low) industry frequency leads to less blame attributed to the
brand, but only when the crisis is considered similar to other
crises in the industry. When similarity information is absent,
the effect is reversed, and low (vs. high) industry frequency
leads to less blame toward the brand. For brands with nega-
tive prior beliefs, the extent of brand-directed blame is
affected by neither base-rate nor similarity information.
Moreover, we show that a high base rate leads to less blame
attributed to the brand through a discounting effect, whereas
a low base rate leads to less blame through a subtyping
effect. While both effects may help alleviate consumers’
blame of the brand, their impact goes well beyond the
immediate crisis. We find that those who had discounted a
first crisis would also discount a subsequent crisis, whereas
consumers who had subtyped the former are unlikely to
subtype the latter. Theoretically, these results specify condi-
tions under which base-rate information does or does not
affect attributions of a product-harm crisis and shed new
light on the different patterns of effects that base-rate infor-
mation may have on attributions. Managerially, these results
suggest different outcomes on brand evaluations depending
on the attribution process that was engaged. We draw impli-
cations for how these effects can help firms effectively
respond to the focal crisis and preempt and manage possible
subsequent crises.

We organize the remainder of the article as follows: First,
we discuss the importance of base-rate information in attri-
bution and the conditions under which consumers will
likely use it in crisis attribution. We then discuss two pat-
terns of effects for how (a high vs. low) base rate affects
consumer attributions of a crisis (Experiment 1) and the dif-
ferential impacts of the two effects on consumer attributions
of a subsequent crisis (Experiment 2).

THE USE OF BASE-RATE INFORMATION IN
ATTRIBUTIONS

Informational Bases of Attributions
In Kelley’s (1967) widely accepted attribution framework,

three types of information serve as input to observers’ attri-
butions about an actor’s behavior or an event: consensus
(base rate), or how common the behavior or event is in the

population of interest;1 distinctiveness, or whether the actor
behaves similarly toward other stimuli; and consistency, or
whether the actor behaves similarly in other situations. In a
product-harm crisis setting, the actor is the firm or brand in
crisis, and consumers make attributions about the affected
product. Examples of the three types of information are how
common recalls are in the industry (base rate), whether the
firm recalls other products as well (distinctiveness), and
whether the firm also recalls the product in other situations
(consistency). We focus on the impact of base-rate informa-
tion for several reasons. First, although all three types of
information serve as inputs to attributions, base-rate infor-
mation is considered to have a stronger link to actor infer-
ence (e.g., whether the crisis is attributed to the firm/brand),
whereas distinctiveness has a stronger link to stimulus infer-
ence (e.g., whether the crisis is attributed to the nature of the
product) and consistency has a stronger link to situation
inference (e.g., whether the crisis is attributed to the situa-
tion) (Hilton, Smith, and Kim 1995). To examine the impact
of a product-harm crisis on brands, we focus on the extent
to which a crisis is attributed to the actor-related factors
rather than the differentiation between various external fac-
tors (e.g., stimulus, situational factors). Second, compared
with the generally consistent findings about the impact of
distinctiveness and consistency on attributions, findings
about base-rate information are mixed. Contextual factors
that affect the impact of base-rate information on attribu-
tions may help explain why (Higgins and Bryant 1982;
Kardes 1988). Finally, the base rate of crises often varies
significantly across industries (e.g., food products, toys, and
automobiles are more prone to product-harm crises than fur-
niture), making it a particularly useful source of informa-
tion for attribution judgments in this context.
The Use of Base-Rate Information and Influential Factors

While there is strong empirical evidence showing the
impact of base-rate information on attributions in both
social psychology (e.g., Feldman et al. 1976; Pilkonis 1977)
and consumer research (e.g., Folkes and Kotsos 1986;
Sparkman and Locander 1980), some studies find little or
no effect (e.g., Kardes 1988; Kassin 1979). Research exam-
ining this inconsistency suggests that, in addition to
methodological issues (as Kelley and Michela 1980 point
out), several factors may influence the neglect or use of
base-rate information.

First, Higgins and Bryant (1982) indicate that the
observer–actor similarity may influence the use of base-rate
information. They find that observers are less likely to use
experimenter-provided base-rate information when judging
behaviors of in-group peers than when judging those of out-
group nonpeers. This is because observers tend to derive
their own base rate from the knowledge of their own behav-
ior when judging behaviors of actors similar to them. The
use of self-derived base-rate information makes the pro-
vided base-rate information seem redundant, and therefore
it has little impact on attributions (Kassin 1979; Kelley and
Michela 1980).

Second, Hilton and Slugoski (1986) suggest that the use
of base-rate information also depends on whether observers

1“Consensus,” used in some studies, refers to the same type of informa-
tion as base rate (e.g., Kardes 1998; Kelley 1980).

perceive the actor’s behavior to be normal or unexpected
according to their prior knowledge about the actor. If the
behavior is normal (vs. unexpected), the base-rate informa-
tion is considered uninformative and is less likely to affect
attributions (see also Jackson et al. 1993). Despite this find-
ing, most prior studies do not include prior beliefs about the
actor in their analysis of base-rate information (e.g., Folkes
and Kotsos 1986; Hilton, Smith, and Kim 1995; Nisbett and
Borgida 1975; Sparkman and Locander 1980). This could
be because they examine attributions in person perception,
a context in which observers often have no strong or stable
prior beliefs about the actor (e.g., a buyer’s attributions
about a salesperson’s behavior; Folkes and Kotsos 1986).

Third, Lynch and Ofir (1989) suggest that the use of base-
rate information is a function of the characteristics (e.g.,
specificity) of such information (see also Bar-Hillel 1980,
1990; Ofir and Lynch 1984). Specifically, consumers often
perceive “abstract and pallid” base-rate information to be
less causally relevant than the “concrete and vivid” case
information (about the behavior to be attributed), leading to
neglect of base-rate information. However, base-rate infor-
mation can be made more relevant if it pertains specifically
to the individual case (Lynch and Ofir 1989).

According to these findings, we expect the use of base-
rate information to be more prevalent in crisis attribution
than in person perception, because consumers’ knowledge
of their own behavior is often insufficient for them to derive
their own base rate for firm crises. However, we expect that
consumers’ use of base-rate information in crisis attribution
depends on their prior beliefs about the brand and the speci-
ficity of the base-rate information. In the next section, we
develop these predictions.

THE EFFECT OF BASE-RATE INFORMATION ON
CRISIS ATTRIBUTION

Default Attributions and Attribution Adjustment
Consumers spontaneously engage in reasoning about

unexpected negative events such as a product-harm crisis
(Folkes 1988; Wong and Weiner 1981). This attribution
process typically involves identifying the locus of cause and
assessing who to blame for the event (McGill 1990; Weiner
1980). Whereas locus measures how consumers locate the
cause to different parties involved, blame measures con-
sumers’ evaluative judgment of each party’s liability for
censure (Bradbury and Fincham 1990). In general, blame
directly follows locus so that more (less) cause attribution
leads to more (less) blame (Folkes 1988; Weiner 1980).
However, studies have also shown that observers may, at
times, not blame the actor, despite perceiving the actor as
the cause, when the outcome or event caused is viewed as
acceptable or excusable (Bradbury and Fincham 1990; Fin-
cham, Beach, and Nelson 1987; Folkes and Kotsos 1986;
McGill 1990). Thus, compared with locus, blame is concep-
tualized as a more accurate and direct attribution variable in
forming the basis of consumers’ brand judgment and behav-
ior (Klein and Dawar 2004; McGill 1990).

Research shows that observers tend to make default attri-
butions to the actor (Gilbert, Pelham, and Krull 1988; Trope
1986) and that this tendency is even stronger for negative
(vs. positive) behaviors (Bernard 1998; Ybarra 2002). Con-
sistent with this view, research indicates that consumers tend

to believe that crises are generally firm related and blame
the firm as a result of the motivation for self-protection,
their dependency on the firm for positive service outcomes,
and their belief that most consumers use a product intend-
ing, or even devoting effort toward, its success (Cowley
2005; Folkes 1988). However, these default attributions
may be adjusted if the contextual information (e.g., base
rate) leads consumers to acknowledge the external con-
straints facing the brand (Gilbert, Pelham, and Krull 1988).
While the primary response of default attribution is auto-
matic, the secondary response of attribution adjustment may
or may not occur, depending on the characteristics of con-
textual information and the observer’s motivation and ability
(e.g., cognitive capacity) to process it (Gilbert and Malone
1995; Gilbert, Pelham, and Krull 1988). Given sufficient
processing ability, we expect that consumers are more moti-
vated to process the base-rate information for brands with
positive (vs. negative) prior beliefs, and the effect pattern of
(high vs. low) base-rate information depends on the speci-
ficity of the information.
The Effect of Prior Beliefs on the Use of Base-Rate
Information

Consumers’ prior beliefs about a brand are formed on the
basis of their experience with and exposure to the brand’s
past actions (Krishnan 1996). When formed, prior beliefs
bias consumers’ interpretation of new information (Johar
1996). Crisis information confirms negative prior beliefs
and reinforces the default attributions initially made to the
brand. In contrast, when prior beliefs are positive, the crisis
information challenges the beliefs and presents an informa-
tion inconsistency. To resolve this inconsistency and main-
tain (positive) beliefs, people tend to elaborate on belief-
inconsistent information and may seek information that
helps refute the negative (e.g., crisis) information (Edwards
and Smith 1996; Kunda 1990). A possible consequence of
this search for refutational evidence is that consumers are
more receptive to, and even actively seek, (contextual)
information (e.g., base rate) that could explain the crisis.
This prediction is also in line with prior research, which
suggests that the use of base-rate information is more likely
when the behavior or event (e.g., a crisis) is unexpected (vs.
normal) according to observers’ prior beliefs about the actor
(e.g., consumers’ positive prior brand beliefs) (Hilton and
Slugoski 1986; Jackson et al. 1993).
The Effect Pattern of High Versus Low Base-Rate
Information

Given sufficient processing ability and motivation, what
is the effect pattern of a high versus low base rate on attri-
butions? Previous predictions about the effect of base-rate
information are mainly based on its causal role in attribu-
tions. Specifically, a cause is defined as the factor that “is
present when the effect is present and … is absent when the
effect is absent” (Kelley 1967, p. 154). Thus, if a behavior
occurs only when the actor is present (low base rate), the
cause is likely to be attributed to the actor. For example,
consider the 2001 Firestone tire blowout product crisis. If
such events are rare in the industry, consumers may reason
that the cause of the crisis is specific to the brand, in line
with their default attributions. In contrast, information about
equally widespread defects in tires made by other firms may

338 JOURNAL OF MARKETING RESEARCH, JUNE 2012

Consumer Attributions of Product-Harm Crises 339

lead consumers to reason that the vehicles or roads, not nec-
essarily the tires, caused the blowouts, giving consumers a
reason to adjust their attribution to the brand. This process
of adjustment is commonly referred to as “discounting”
(Kelley 1972, p. 8), meaning that “the role of a given cause
(e.g., brand) is discounted if other plausible causes are pres-
ent.” In this case, discounting leads to less blame attributed
to the brand and better brand evaluations.

However, in the context of product-harm crises, the pres-
ence of base-rate information itself may not be sufficient to
discount the default attributions to the brand. This is
because negative events (e.g., crises) are often construed as
a violation of social code requiring volition and intentional-
ity (or, at the very least, acts of omission) and are likely to
induce strong beliefs that the behavior is actor related
(Ybarra 2002). Only if base-rate information can provide
clear causal links between external factors and the crisis are
the default attributions to the brand likely to be discounted.
However, base-rate information may appear particularly
abstract and pallid compared with the often dramatic case
information of a crisis, making the former seem irrelevant
to the attribution task at hand (Bar-Hillel 1980; Koehler
1996). A major factor that influences base-rate utilization is
whether the base-rate pertains specifically and is related
directly to the focal case (Bar-Hillel 1980; Lynch and Ofir
1989; Ofir and Lynch 1984). Bar-Hillel (1980) indicates
that the most straightforward way to bring specificity is to
provide a base rate for the subset of the population that is
directly related to the focal case (see also Koehler 1996).
For example, Lynch and Ofir (1989) find that a base rate
described as pertaining to the focal case of Peugeot automo-
biles in particular is more causally relevant and used in
judgment than the base rate described as pertaining to for-
eign cars in general (see also Ofir and Lynch 1984). In the
context of our study, industry frequency information would
pertain specifically to the focal crisis if the information is
about crises similar to the focal case (referred to as “simi-
larity information”). It is more plausible for consumers to
infer from this specific base-rate information (i.e., the focal
crisis is similar to those in the industry) that common exter-
nal factors, rather than the brand, may have caused the cri-
sis.2 Thus, when similarity information is present, we
expect that a high (vs. low) base rate leads to less blame
attributed to the brand and better brand evaluations.

However, when the similarity information is absent, the
lack of specificity in base-rate information makes it less
causally relevant to discount the default attribution to the
brand. Yet the information inconsistency between the crisis
and positive prior beliefs remains unresolved. If the use of
base-rate information rests on the assumption that con-
sumers are motivated to resolve this inconsistency and
maintain (positive) beliefs, a different resolution route may
be employed. Specifically, instead of serving as a basis to
infer other causes of the crisis, a (low or high) base rate can
be a simple statistical cue suggesting the rarity or common-
ality of such crises for brands in the industry. When a crisis
is perceived as generally rare, and conflicts with consumers’
(positive) beliefs about a brand, they may simply consider it

an exception to the otherwise well-behaved brand. For
example, in schema research, studies have shown that infor-
mation that is inconsistent with an existing schema (about a
social group, a product category, or a brand) may be consid-
ered an exception to the rule and be subtyped as an instance
that is unrepresentative of the schema (Crocker and Weber
1983; Romeo 1991; Taylor and Crocker 1981). This effect
of subtyping is more likely when the instance of disconfir-
mation is rare versus prevalent (Richard and Hewstone
2001; Sujan and Bettman 1989). Similarly, some studies in
attribution research also indicate that an unexpected, rare
behavior may be dismissed as an accident or a fluke of
chance rather than a reflection of the actor’s true qualities
(Bradbury and Fincham 1990; Kaltcheva and Weitz 1999;
Taylor, Lichtman, and Wood 1984; Wilder, Simon, and
Faith 1996). On the basis of these studies, we propose that
consumers may view a rare crisis as an exception or accident
to an otherwise good brand and excuse the brand from blame
by reasoning that “things happen.” That said, although a
low base rate may not allow consumers to explain away the
crisis with other factors, it may help resolve the information
inconsistency between the crisis and positive brand beliefs
by treating the crisis as an unrepresentative case of the
brand’s normal behavior. We borrow the term “subtyping”
from schema research to label this effect. In general, sub-
typing is theorized as a mechanism that people use to recon-
cile inconsistent information and maintain their beliefs
about a schema (Taylor and Crocker 1981), although it is
more often discussed in person perception and product cate-
gorization research. In the context of this research, we
define subtyping as an effect in which consumers treat a rare
crisis as an exception to the brand’s normal behavior and
excuse the brand from blame.

In summary, the presence of base-rate (industry fre-
quency) information may help adjust the default attributions
to the brand. Adjustment occurs when consumers can either
attribute the crisis to external factors (discounting) or con-
sider it an exception to the rule (subtyping). If the base rate
pertains specifically to the focal case (similarity informa-
tion present), it helps consumers determine the locus of the
cause. High (vs. low) industry frequency suggests that other
causes may be at play, leading to less brand blame and bet-
ter brand evaluations. However, if the base-rate information
lacks specificity (similarity information absent), it may
serve as a statistical cue. Low (vs. high) industry frequency
prompts consumers to perceive the event as an exception to
the rule, resulting in less brand blame and better brand
evaluations. Regardless of whether the effect of discounting
or subtyping is at play, the use of base-rate information in
attribution adjustment is more likely for brands with positive
(vs. negative) prior beliefs. In line with previous research
(e.g., Klein and Dawar 2004), we gauge the effect of attribu-
tions by measuring blame assignment as well as a specific
(brand trustworthiness) and an overall evaluation (brand
evaluation) of the brand. We hypothesize the following:

H1: The effect of base-rate information (industry frequency) on
crisis attribution (as measured by blame assignment, brand
trustworthiness, and brand evaluation) is moderated by
similarity information and prior brand beliefs.

(a) When similarity information is present, high (vs. low)
industry frequency information leads to less attribution to
the brand (discounting). However, when similarity informa-

2A pilot test (n = 68) showed that the base rate with similarity informa-
tion was perceived as more causally relevant than that without similarity
information (4.94 vs. 4.26; t(66) = 2.16, p < .05).

tion is absent, low (vs. high) industry frequency leads to
less attribution to the brand (subtyping).

(b) The effect of base-rate information (either discounting or
subtyping) is more pronounced for brands with positive (vs.
relatively negative) prior beliefs.

EXPERIMENT 1
The purpose of Experiment 1 is to test H1 which exam-

ines the different effects of base-rate information on con-
sumer attributions in a product-harm crisis. Student respon-
dents participated in the experiment in exchange for partial
course credit.
Stimulus Development

The experimental stimulus used in this study was beer, a
product that is relevant and familiar to student participants.
We used fictitious brand names to avoid the confounds of
the specificities of real brand names. Twenty-four partici-
pants were asked to evaluate five fictitious beer brands, and
the name “Stiegal” was selected because it was considered
a suitable name for both a premium and a low quality prod-
uct. Next, we developed several descriptions to manipulate
positive or negative brand beliefs, including a Consumer
Reports article, classification of the brand, and sample
online consumer reviews. Specifically, Stiegal was described
as a premium (nonpremium) beer brand that is rated as one
of the best beer brands (has received weak ratings) in a Con-
sumer Reports article. The article rated the brand on four
commonly discussed beer attributes (quality, flavor, fresh-
ness, and overall satisfaction) on a ten-point scale, and con-
sumer testers also provided verbal evaluations on each
attribute. In addition, the brand was classified in the same
quality tier as several well-known premium (low-quality)
beer brands in the market to help participants remember and
build positive (or relatively negative) associations to the
brand. Peer communication is reported to have a strong
influence on consumers’ brand evaluations, especially when
they have no experience with the brand (Herr, Kardes, and
Kim 1991). Therefore, we provided fictitious positive
(negative) online consumer reviews to reinforce the image
of a well-regarded (poor) brand. Finally, two groups of par-
ticipants (n1 = 21, n2 = 20) evaluated the Stiegal brand
described in positive or negative descriptions, respectively,
using a composite scale (Keller 2003) including dimensions
of brand evaluation (“negative/positive,” “bad/good,” and
“unfavorable/favorable”), brand trust (“not at all trustworthy/
very trustworthy,” “not at all reliable/very reliable,” “not at
all dependable/very dependable”), perceived quality of the
brand and the product (“low quality/high quality”), brand
purchase likelihood (“not at all likely/very likely”) and
brand desirability (“not at all desirable/very desirable”)
(Cronbach’s  = .96).3 The results confirmed that the posi-
tive descriptions generated significantly more positive
beliefs than the negative descriptions (5.05 vs. 3.22; t(39) =
5.93, p < .001). Experimental Procedure

One hundred ninety-two participants were assigned ran-
domly to the experimental conditions in a 2 (prior beliefs:

positive vs. negative) ¥ 2 (industry frequency: high vs. low) ¥
2 (similarity information: present vs. absent) between-subjects
design. First, participants were instructed to read the book-
let of positive or negative descriptions of the Stiegal brand
and asked to remember as much information as possible. To
add realism to the scenario, participants were informed that
the Stiegal brand had just entered the market, so they might
or might not be familiar with it. Next, participants were pro-
vided with paper and a pencil to write down their “overall
impressions” about Stiegal after reading the information
booklet. This step helps internalize the positive or negative
descriptions of the brand as the participants’ own opinions,
facilitating the manipulation of prior beliefs. Next, partici-
pants completed the first part of an unrelated filler question-
naire. In the third step, they were presented with the key
stimulus in the experimental task, a fictitious but realistic
newspaper article about a recall of [brand] beer. The article
described a brand’s recall of its beer after a few consumers
reportedly fell ill from drinking the beverage. Under high
(low) industry frequency, participants were told that in
recent years, product recalls in the beer industry “have been
very common (rare), averaging more than one recall every
two weeks (averaging less than one recall every two
years).” We manipulated similarity information either by
stating that the focal crisis “is similar to earlier incidents
that have occurred in the industry” or by not presenting such
information. After reading the article, participants were
asked to fill out the second part of the filler questionnaire
and then respond to the scaled dependent measures of the
main study. Next, participants stated what they thought the
purpose of the study was. We found that participants
believed the purpose was about either the filler study or the
effect of the described crisis. No participant guessed the real
purpose of the study. Finally, participants were debriefed
and informed about the fictitious nature of the brand and the
crisis incident.
Dependent Variables

We measured blame assignment on a three-item, seven-
point scale (“Stiegal is to blame for consumers’ illness,”
“Stiegal is responsible for consumers’ illness,” and “Stiegal
is at fault for consumers’ illness”) anchored by “strongly
disagree” and “strongly agree” (Klein and Dawar 2004) ( =
.87). We averaged these items to form a blame index. We
measured brand trustworthiness on a three-item, seven-
point scale anchored by “not at all/very trustworthy,” “not
at all/very dependable,” and “not at all/very reliable” ( =
.95). We measured brand evaluations on a three-item, seven-
point scale anchored by “very unfavorable/very favorable,”
“very bad/very good,” and “very negative/very positive” (
= .95). We averaged these items to form a brand trustwor-
thiness index and a brand evaluation index, respectively. In
addition, to assess the participants’ tendency to consider the
crisis an exception, we measured their agreement with the
statements “This incident is an exception for [the brand]”
and “This incident is an isolated event for [the brand],”
anchored by “strongly disagree/strongly agree” (adapted
from Sujan and Bettman 1989). We averaged these items to
form a subtyping index (r = .69, p < .001).

We performed manipulation checks by asking partici-
pants to indicate how common product recalls are in the
beer industry on a three-item, seven-point scale (anchored

340 JOURNAL OF MARKETING RESEARCH, JUNE 2012

3A factor analysis of these items yields one factor (explained variance of
78.9%, Kaiser–Meyer–Olkin = .90), enabling us to average these items.

Consumer Attributions of Product-Harm Crises 341

by “not at all common/very common,” “not at all frequent/
very frequent,” and “not at all widespread/very wide-
spread”) ( = .96). Finally, participants stated their level of
agreement with two statements (“According to the newspa-
per article this incident is identical to previous incidents,”
and “According to the newspaper article this incident and
previous incidents are alike”) anchored by “strongly dis-
agree/strongly agree” (r = .77, p < .01). Results Manipulation check. The analysis of variance (ANOVA)

test on the industry frequency index indicated only a main
effect of industry frequency (F(1, 184) = 420.23, p < .001). Participants in the high (vs. low) industry frequency condi- tion reported that recalls in the industry were more common (5.16 vs. 2.30). Similarly, an ANOVA on the similarity index revealed only a main effect of similarity information (F(1, 184) = 119.22, p < .001). Participants reported that this incident was more similar to previous ones when similarity information was present versus absent (5.68 vs. 3.68). Blame assignment. We analyzed the data using a 2

(industry frequency: high vs. low) ¥ 2 (similarity informa-
tion: present vs. absent) ¥ 2 (prior beliefs: positive vs. nega-
tive) between-subjects ANOVA. First, the ANOVA test
revealed a significant three-way interaction on blame
assignment (F(1, 184) = 4.63, p < .05). The interaction between industry frequency and similarity information was significant for brands with positive prior beliefs (F(1, 184) = 17.70, p < .001) but not so for brands with negative prior beliefs (F(1, 184) = 1.43, p > .20). Planned contrast tests for
simple effects showed that, for the positive brand, partici-
pants assigned less blame to the brand in the high (vs. low)
industry frequency condition when similarity information
was present (5.29 vs. 5.91; F(1, 184) = 5.50, p < .05). How- ever, when similarity information was absent, they assigned less blame in the low (vs. high) industry frequency condi- tion (4.78 vs. 5.74; F(1, 184) = 12.90, p < .01). For the nega- tive belief condition, the blame assignment was not signifi- cantly different between the high and low industry frequency conditions when similarity information was either present (5.68 vs. 5.83; F < 1) or absent (6.11 vs. 5.82; F(1, 184) = 1.22, p > .20).
Brand trustworthiness and evaluation. We then examined

the effect of the crisis on brand trustworthiness and evalua-
tion. First, the ANOVA test revealed a significant three-way
interaction on brand trustworthiness (F(1, 184) = 5.70, p < .05). The interaction between industry frequency and simi- larity information was significant for brands with positive prior beliefs (F(1, 184) = 13.18, p < .01) but not so for brands with negative prior beliefs (F < 1). Specifically, when prior beliefs are positive, participants rated the Stiegal brand as more trustworthy in the high (vs. low) industry fre- quency condition when similarity information was present (3.45 vs. 2.60; F(1, 184) = 6.82, p < .05). However, when similarity information was absent, the brand’s trustworthi- ness was rated higher in the low (vs. high) industry fre- quency condition (3.28 vs. 2.44; F(1, 184) = 6.37, p < .05). When prior beliefs are negative, the brand’s trustworthiness was not significantly different between the high and low industry frequency conditions either when similarity infor- mation was present (2.20 vs. 2.01; F < 1) or absent (2.27 vs. 2.22; F < 1). The analysis of brand evaluations revealed the

same pattern of results with similar levels of significance
(Table 1, Panel A). These results support H1.
Likelihood of considering the crisis an exception. In addi-

tion, we examined the extent to which participants were
likely to consider a crisis an exception under different con-
ditions. The ANOVA revealed a significant three-way inter-
action on the participants’ likelihood of considering the cri-
sis an exception (F(1, 184) = 4.38, p < .05). The interaction between industry frequency and similarity information was significant for brands with positive prior beliefs (F(1, 184) = 5.96, p < .01) but not for brands with negative prior beliefs (F < 1). Specifically, for the positive brand, partici- pants considered the crisis more an exception in the low (vs. high) industry frequency condition when similarity infor- mation was absent (5.25 vs. 3.97; F(1, 184) = 15.82, p < .001). However, when similarity information was present, the likelihood of considering the crisis an exception was below the neutral point (4) and did not vary across different industry frequency conditions (3.94 vs. 3.76; F < 1). For the negative brand, the likelihood of considering the crisis an exception was below the neutral point (4) in all conditions (Table 1, Panel A). These results suggest that consumers consider the crisis an exception only when the crisis is rare, when the similarity information is absent, and when they have positive brand beliefs. The results also indicate that only in this condition did the likelihood of considering the crisis an exception have a significant impact on blame assignment ( = –.51, t = –2.80, p < .05), brand trustworthi- ness ( = .49, t = 2.68, p < .05) and evaluation ( = .41, t = 2.16, p < .05). Follow-up experiment.4 We work under the assumption

that people spontaneously engage in attributional activity
following negative and unexpected outcomes. Although
prior research has empirically supported this assumption
(e.g., Folkes 1984; Wong and Weiner 1981), we examine the
assumption in the specific context of a product-harm crisis.
Furthermore, in Experiment 1, we set the base-rate informa-
tion at two distinct levels: high (product recalls averaging
more than one recall every two weeks) and low (product
recalls averaging less than one recall every two years).
Although this was in line with most prior studies’ manipula-
tion of base-rate information, we generalize our findings by
varying the base-rate at a different (weaker) magnitude.5 A
follow-up study (n = 106) using the same fictitious brand
(Stiegal) replicated the four experimental conditions with
positive prior beliefs (because most of our findings were in
these conditions). Participants followed a similar procedure
as in Experiment 1 with a few notable changes. First, we set
the two levels of base rate at a different magnitude than
Experiment 1: high (averaging about one recall every two
months) and low (averaging about one recall every two
years). Second, after reading the crisis story, participants
listed their thoughts and questions before responding to the

4We are grateful to an anonymous reviewer for the suggestions.
5Previous research has typically manipulated the magnitude of base-rate

information at two distinct levels. At the high level, several people perform
the same behavior as the actor (e.g., “John, George, Ringo, and Paul all
help Linda”). At the low level, only the actor performs the behavior (e.g.,
“Paul helps Linda; hardly anyone else helps Linda”) (Hilton, Smith, and
Kim 1995; see also Feldman et al 1976; Higgins and Bryant 1982; Jackson
et al. 1993; Kardes 1988; Kassin 1979; Nisbett and Borgida 1975; Sparks-
man and Locander 1980).

scaled dependent variables on the next page. Third, partici-
pants responded to the dependent variables of brand trust-
worthiness and evaluation directly without first responding
to the blame assignment variable, because questions about
blame assignment may prime the attribution process. These
last two changes were designed to examine whether con-
sumers spontaneously engage in attributional activities fol-
lowing a product-harm crisis.

According to Wong and Weiner (1981), we coded five
categories of thoughts in the verbal protocols of participants’
thoughts after reading the crisis story: affective reactions
(expressions of emotions such as anger, frustration), attribu-
tional thoughts (causes/ blame of the recall), action-related
thoughts (actions in reaction to the recall), reevaluation
thoughts (reassessment of the brand/product), and miscella-
neous thoughts. Consistent with the findings in Wong and
Weiner, we found that participants engaged in spontaneous
attributions: Attributional thoughts comprised the largest pro-
portion of the total thoughts listed (affective reactions: 4.12%;
attributional thoughts: 41.82%; action-related thoughts:
16.27%; reevaluation thoughts: 33.19%; and miscellaneous
thoughts: 4.60%). We then coded the attributional thoughts
into subtyping-related thoughts (consider the crisis an
exception/accident), discounting-related thoughts (consider
possible non-brand-related causes), and other thoughts. We
found 20.34% of the attributional thoughts were subtyping
related in the low industry frequency/ similarity information–
absent condition (the subtyping condition), but fewer than
3% of such thoughts were subtyping related in all other con-

ditions. In addition, we found that 29.41% of the attribu-
tional thoughts were discounting related in the high indus-
try frequency/ similarity information–present condition (the
discounting condition), but fewer than 7% of such thoughts
were discounting related in all other conditions. These
results offer further evidence of the subtyping and discount-
ing effects we hypothesized under the different conditions.
Furthermore, the results reveal a significant interaction of
industry frequency and similarity information on both brand
trustworthiness (F(1, 102) = 15.51, p < .001) and evaluation (F(1, 102) = 18.81, p < .001) with the same pattern of means as in Experiment 1 (Table 1, Panel B). Overall, these results support the assumption of spontaneous attributional search following negative and unexpected outcomes (e.g., a crisis) and help corroborate the findings in Experiment 1. Discussion

These results support our propositions that base-rate
information is more likely to affect attribution to brands
with positive (vs. negative) prior beliefs and that the effect
pattern of (high vs. low) base-rate information depends on
similarity information. For brands with positive prior
beliefs, participants attributed less blame and had higher rat-
ings of brand trustworthiness and evaluation in the high (vs.
low) industry frequency condition when the crisis was said
to be similar to others in the industry. However, when the
similarity information was absent, participants attributed
less blame and had higher ratings of brand trustworthiness
and evaluation in the low (vs. high) industry frequency con-

342 JOURNAL OF MARKETING RESEARCH, JUNE 2012

Table 1
MEANS (STANDARD DEVIATION) OF DEPENDENT VARIABLES IN EXPERIMENT 1

A: Main Experiment
Similarity Information Present Similarity Information Absent

High Industry Frequency Low Industry Frequency High Industry Frequency Low Industry Frequency
Positive Prior Beliefs

Blame assignment 5.29 (1.00) 5.91 (.78) 5.74 (1.05) 4.78 (.73)
Brand trustworthiness 3.45 (1.38) 2.60 (1.32) 2.44 (1.05) 3.28 (1.19)
Brand evaluations 3.65 (1.11) 2.81 (1.31) 2.94 (1.06) 3.56 (1.07)
Sub-typing index 3.76 (1.08) 3.94 (.65) 3.98 (1.20) 5.25 (.94)

Negative Prior Beliefs
Blame assignment 5.68 (1.08) 5.83 (.79) 6.11 (.83) 5.82 (1.03)
Brand trustworthiness 2.20 (1.04) 2.01 (.90) 2.27 (.98) 2.22 (1.07)
Brand evaluations 2.09 (.75) 1.94 (.62) 2.11 (1.00) 2.19 (1.02)
Sub-typing index 2.82 (1.42) 3.56 (.94) 2.85 (1.15) 3.37 (1.13)

B: Follow-Up Experiment
Similarity Information Present Similarity Information Absent

High Industry Frequency Low Industry Frequency High Industry Frequency Low Industry Frequency
Positive Prior Beliefs

Brand trustworthiness 3.28 (1.21) 2.41 (1.16) 2.25 (1.13) 3.13 (1.07)
Brand evaluations 3.60 (1.14) 2.56 (1.24) 2.35 (1.26) 3.42 (1.36)

C: Post-Hoc Experiment in the Discussion
Similarity Information Present Similarity Information Absent

High Industry Frequency Low Industry Frequency High Industry Frequency Low Industry Frequency
Positive Prior Beliefs (Heineken)

Brand trustworthiness 4.74 (.98) 4.02 (.86) 3.84 (1.54) 4.60 (.94)
Brand evaluations 5.02 (1.18) 4.26 (1.27) 3.97 (1.41) 4.84 (1.14)

Negative Prior Beliefs (Lakeport)
Brand trustworthiness 3.17 (1.18) 3.19 (1.59) 3.40 (1.34) 3.28 (.97)
Brand evaluations 2.92 (1.31) 2.78 (1.45) 3.07 (1.15) 2.86 (1.09)

Consumer Attributions of Product-Harm Crises 343

dition. For brands with negative prior beliefs, the blame
assignment and the ratings of brand trustworthiness and
evaluation were not significantly affected by the industry
frequency and similarity information. To generalize our
findings in a more naturalistic setting, we conducted an
additional experiment (n = 257) with two existing brands
(Heineken and Lakeport) using the same 2 (prior beliefs:
positive vs. negative) ¥ 2 (industry frequency: high vs. low) ¥
2 (similarity information: present vs. absent) between-subjects
design as Experiment 1. A pretest (n = 32) showed that
Heineken and Lakeport were similarly familiar to partici-
pants (4.18 vs. 4.60; t (30) = –.82, p > .40) but with positive
and relatively negative prior beliefs, respectively (5.25 vs.
3.72; t(30) = 3.67, p < .01). We manipulated industry fre- quency and similarity information as in Experiment 1. At the end of the study, participants were debriefed and informed of the fictitious nature of the incident. The results showed significant interactions and the same pattern of means (Table 1, Panel C) on brand trustworthiness and evaluation as Experiment 1, providing additional support for H1.

Although the results in Experiment 1 showed that both
the discounting and subtyping effects lead to less blame
being attributed to the brand than in other conditions, we
suggest that the two effects are the result of different pro-
cesses. Specifically, discounting helps divert the cause away
from the brand to other factors, whereas subtyping simply
allows consumers to excuse the brand by treating the crisis
as an exception or accident. If this is the case, we should
observe less cause attributed to the brand in the discounting
condition, though not necessarily in the subtyping condi-
tion. Despite similar outcomes, the differences in process
are important. The reasoning by which the attribution
occurs may have different implications for consumers’ treat-
ment of subsequent crisis events. All else being equal, will
the same base-rate information that helped alleviate con-
sumers’ blame in the first crisis have a similar effect on the
second one? Multiple product-harm crises are not uncom-
mon for brands. For example, Tylenol experienced a second
crisis in 1986 after its well-publicized crisis in 1982 (and a
third one in 2010), and Firestone’s 2001 recall was not its
first. We address this question in Experiment 2.

EXPERIMENT 2
In reasoning about an event, observers are often guided

by their own beliefs and assumptions about what happened
(Reeder 1993). As we discussed previously, consumers tend
to make default attributions to the firm (e.g., Folkes 1988).
This schematic assumption is so strong that consumers may
ignore the contextual information (e.g., base-rate) when
attributing the event (Gawronski 2003; Reeder 1993). How-
ever, consumers do use the (high) base-rate information to
discount the default attribution when the base-rate informa-
tion pertains specifically to the focal case, as Experiment 1
shows. We propose that when consumers question their
implicational schema by acknowledging possible external
causes implied by (high) base-rate information, they may be
more receptive to base-rate information in attributions of
subsequent events. Therefore, although multiple crises may
imply a cause inherent to the brand, we expect that if con-
sumers had discounted a crisis under the high base-rate and

similarity information present condition, they may also dis-
count a similar subsequent crisis under the same conditions.

However, when consumers subtype a crisis under the low
base-rate and similarity information absent condition, they
are unlikely to subtype a similar subsequent crisis under the
same conditions. Recall that subtyping occurs when con-
sumers consider the crisis an exception to an otherwise
well-behaved brand. However, when a similar subsequent
crisis occurs, it is difficult for consumers to consider repeat-
ing occurrences as exceptions or accidents (Wilder, Simon,
and Faith 1996). Moreover, although a low base rate leads
consumers to subtype the crisis as an unrepresentative
exception to the brand’s normal behavior, it may not exon-
erate the brand fundamentally by diverting the cause to
other factors as happens under discounting. Instead, the sub-
typed information (e.g., crisis) may stand out as a unique,
salient episode (e.g., Crocker 1984) reminding consumers
of the possible (quality) issues with the brand. Therefore,
when a similar subsequent crisis occurs, together with the
subtyped prior occurrence, it raises questions about the
brand and makes it difficult for consumers to subtype again.
We hypothesize the following:

H2: Consumers are (a) likely to discount a second crisis if they
had discounted the first crisis and (b) less likely to subtype a
second crisis if they had (vs. had not) subtyped the first crisis.

Experimental Procedure
The results of Experiment 1 show that discounting and

subtyping effects only occur for brands with positive prior
beliefs. Therefore, we only used a brand with positive prior
beliefs (Heineken) in Experiment 2. Two fictitious crisis
stories were required as stimuli: one for the first crisis
manipulation and one for the subsequent crisis manipula-
tion. The crisis story used in Experiment 1 served as the first
crisis, and we created a new crisis story similar (but not
identical) to the first one for the second occurrence.

In the first part of the experiment, 134 participants were
randomly assigned to a 2 (industry frequency: high vs. low) ¥
2 (similarity information: present vs. absent) between-subjects
design with a control group (Control Group 1). Participants
in the four experimental groups were presented with the
first crisis with the industry frequency and similarity infor-
mation manipulation as in Experiment 1. Participants in the
control group were presented with the first crisis without
industry frequency or similarity information, to measure
their default (baseline) attributions of the crisis. We designed
the experiment to include the control group so we could
compare attributions in each experimental group directly
with the default attributions and measure the extent of attri-
bution adjustment. Our aim with this part of the experiment
was to induce the subtyping effect in the low industry fre-
quency and similarity information absent condition, and the
discounting effect in the high industry frequency and simi-
larity information present condition for the first crisis.

Three days later, participants in the subtyping condition
(low industry frequency, similarity information absent) and
the discounting condition (high industry frequency, similar-
ity information present) were asked to participate in the sec-
ond part of the experiment, in which they were presented
with the second crisis. Participants were told that the article
they had read in the first part of the experiment had been
published several years earlier, but they were not reminded

of the content of the article.6 They were then presented with
a recent newspaper article describing the second crisis. In
the subtyping condition, participants were presented with
the low industry frequency and similarity information
absent manipulation to test whether they would subtype the
second crisis. Similarly, in the discounting condition, par-
ticipants were presented with the high industry frequency
and similarity information present manipulation to deter-
mine whether they would discount the second crisis. No
participant guessed the real purpose of the study. In addi-
tion, another control group (control group 2) (n = 25) was
recruited to measure the default (baseline) attributions of
the second crisis (no industry frequency or similarity infor-
mation was present).
Dependent Variables

We measured blame assignment and brand evaluation as
in Experiment 1.7 In addition, we measured the locus of
cause by asking participants to assign a percentage of cause
to “the brand” and “factors other than the brand” with totals
summing to 100 percent (Folkes and Kotsos 1986). Includ-
ing the locus measurement enables us to compare how con-
sumers attribute the cause to the brand in the discounting
versus subtyping condition.
Results
Induce subtyping and discounting effects on the first crisis.8

We used an ANOVA test with Type IV sums of squares

(Norusis 2003) to analyze the 2 (industry frequency: high
vs. low) ¥ 2 (similarity information: present vs. absent)
between-subjects design with a single control group (no
industry frequency and similarity information). The results
showed a significant interaction term between industry fre-
quency and similarity information on blame assignment
(F(1, 129) = 14.33, p < .001). Planned contrast tests for sim- ple effects showed that participants assigned less blame to the brand in the high (vs. low) industry frequency condition (4.38 vs. 5.31; F(1, 129) = 9.41, p < .01) when similarity information was present but assigned less blame in the low (vs. high) industry frequency condition (4.58 vs. 5.27; F(1, 129) = 5.22, p < .05) when similarity information was absent. This result replicates the findings in Experiment 1 and sug- gests that the subtyping and discounting effects were suc- cessfully induced for the first crisis. In addition, compared with the baseline effect in Control Group 1, participants attributed less blame to the brand in both the subtyping con- dition (low industry frequency similarity information absent) (4.58 vs. 5.20; F(1, 129) = 4.27, p < .05) and the dis- counting condition (high industry frequency similarity information present) (4.38 vs. 5.20; F(1, 129) = 7.55, p < .01) but not so in the other two conditions (F < 1). As cor- roborative evidence, we obtained the same pattern of results with similar levels of significance for brand evaluations (see the results in Table 2, Panel A). Furthermore, the results show that participants attributed a lower percentage of cause to the brand in the discounting condition than in the control group (46% vs. 69%; F(1, 129) = 12.89, p < .001), but this is not the case for the subtyping condition (63% vs. 69%; F < 1). The loci of cause in the other two conditions (67% and 60%) were not significantly different from those in the control group (ps > .10). These results showed that
participants deflected the cause to other factors when dis-
counting but not when subtyping.
Effects of the second crisis.9 To examine whether partici-

pants would subtype or discount the second crisis, we com-

344 JOURNAL OF MARKETING RESEARCH, JUNE 2012

9The manipulation check for industry frequency and similarity informa-
tion was successful. The independent t-tests showed that participants in the
discounting condition (high industry frequency/similarity information
present) rated the recalls as more common (5.26 vs. 2.47; t(59) = 11.20,
p < .001) and more similar to other occurrences (5.11 vs. 3.82; t(59) = 4.13, p < .001) than did participants in the subtyping condition (low industry frequency/ similarity absent).

6We designed Experiment 2 to examine the consequence of discounting
versus subtyping in the first crisis on consumers’ attribution of a second
crisis. To avoid the possible impact of crisis frequency at the focal brand,
we set a large time span between the first and second crises. A pretest
showed that participants who saw both crises rated the crisis frequency at
the focal brand as equally infrequent (3.26) as participants who only saw
the second crisis (3.10; p > .10).

7We eliminated brand trustworthiness because it led to results similar to
brand evaluation in Experiment 1.

8The manipulation check for industry frequency and similarity informa-
tion was successful. The ANOVA on industry frequency showed only a
main effect of industry frequency (F(1, 106) = 279.58, p < .001). Partici- pants in the high (vs. low) industry frequency condition rated the recalls as more common (5.23 vs. 2.17). In addition, the ANOVA on similarity infor- mation showed only a main effect of similarity information (F(1, 106) = 50.79, p < .001). Participants rated the incident as more similar to other occurrences in the industry when similarity information was present (vs. absent; 5.34 vs. 3.73).

Table 2
MEANS (STANDARD DEVIATION) OF DEPENDENT VARIABLES IN EXPERIMENT 2

A: Effects of the First Crisis
Similarity Information Present Similarity Information Absent

High Industry Low Industry High Industry Low Industry
Control Group 1 Frequency Frequency Frequency Frequency

Brand blame 5.20 (1.24) 4.38 (1.12) 5.31 (.99) 5.27 (1.06) 4.58 (1.14)
Brand evaluations 3.99 (1.20) 4.73 (.98) 4.12 (1.14) 4.05 (1.13) 4.81 (1.05)
Locus of cause .69 (.22) .46 (.24) .67 (.18) .60 (.22) .63 (.28)

B: Effects of the Second Crisis
Similarity Information Present Similarity Information Absent

Control Group 2 High Industry Frequency (Discounting) Low Industry Frequency (Subtyping)
Brand blame 5.15 (1.05) 4.45 (1.20) 5.08 (1.13)
Brand evaluations 3.89 (1.22) 4.67 (.93) 4.03 (1.32)
Locus of cause .67 (.20) .55 (.22) .72 (.25)

Consumer Attributions of Product-Harm Crises 345

pared the effect of the second crisis under the subtyping
condition and discounting condition with that in Control
Group 2 (baseline effect of the second crisis). Planned con-
trasts show that participants assigned less blame to the
brand in the discounting condition than in Control Group 2
(4.45 vs. 5.15; F(1, 83) = 5.19, p < .05) but not so in the sub- typing condition (5.08 vs. 5.15; F < 1). As corroborative evidence, the results also showed a higher rating of brand evaluation in the discounting condition than in Control Group 2 (4.67 vs. 3.89; F(1, 83) = 6.11, p < .05) but not so in the subtyping condition (4.03 vs. 3.89; F < 1). These results support H2 in that consumers who had discounted a first crisis are likely to discount a second crisis, but those who had subtyped the first crisis are less likely to subtype the second one. Furthermore, we found that participants attributed less cause to the brand in the discounting condi- tion than that in Control Group 2 (55% vs. 67%; F(1, 83) = 4.07, p < .05), but this was not the case in the subtyping condition (72% vs. 67%; F < 1). Discussion

The results of Experiment 2 replicate and extend our
findings in Experiment 1 to show that participants attribute
less blame to the brand and have more favorable brand
evaluations in both the discounting and subtyping condi-
tions than in the control group in which no base-rate infor-
mation is provided. More important, the results suggest that
while a high base rate with similarity information present
(the discounting condition) can lead consumers to discount
the attributions to the brand for both the first and second cri-
sis, a low base rate with similarity information absent (the
subtyping condition) only leads consumers to subtype the
first crisis, not the second. The results of Experiment 2 sug-
gest that despite the similar outcome of the discounting ver-
sus the subtyping effect after the first crisis, the process
matters because a second crisis may or may not receive the
same treatment depending on how it was attributed in the
first instance.

GENERAL DISCUSSION
Base-rate information is a simple yet important source of

information that influences consumers’ inference judg-
ments. Previous research has shown mixed findings on
whether this information affects attribution. In this research
we show that base-rate information affects consumers’ attri-
bution of a product-harm crisis, but this effect is more
salient for brands with positive (vs. negative) prior beliefs.
In addition, we find that base-rate information may have a
different pattern of effects on attributions than previously
examined, and we specify the conditions under which these
effects occur. Finally, we show that the same base-rate infor-
mation may have a different impact on a subsequent crisis
depending on how it affects the attribution of the first crisis.
From these results, we draw theoretical implications for the
effect of base-rate information in attribution and sugges-
tions for the management of the negative impact of product-
harm crises.

First, our findings carry implications for how base-rate
information affects attribution in different contexts. We
show that base-rate information has a much greater impact
on attributions for brands with positive (vs. negative) prior
beliefs. This finding supports Johar, Birk, and Einwiller’s

(2010) managerial advice regarding the “not just me”
response, suggesting the prevalence of crises in the industry
should be more effective for consumers who identify with
the brand than those who do not. Our finding specifies a
boundary condition for the use of base-rate information in
the context of a brand-related (negative) event. In addition,
this finding may explain why not all brands are found to be
equally affected by a crisis, even though consumers make
default attributions to the brand in case of a negative event
(Ybarra 2002). For example, Klein and Dawar (2004) find
that a firm is less affected by a crisis when consumers have
positive (vs. negative) prior beliefs about the firm’s corpo-
rate social responsibility. Similarly, Johar (1996) shows that
negatively (vs. positively) evaluated advertisers are more
likely to be held responsible for a deceptive advertisement.
Our findings suggest that brands with positive (vs. negative)
beliefs are less affected by a crisis, but not because the posi-
tive beliefs merely “insulate” the brand from negative infor-
mation; rather, these positive beliefs make consumers more
receptive to the influence of contextual information (e.g.,
base-rate information), reducing the default attributions to
the brand. Further research could explore whether base-rate
information would also contribute to adjustment in the
default attributions to a negative brand when such informa-
tion is made more salient to consumers. Managerially, these
results suggest that investment in forming consumers’ posi-
tive brand beliefs is paid back in case of an adverse event,
but the positive beliefs alone do not predict consumers’
attribution about the crisis. Managers should be aware of the
dual effect of both the characteristics of the affected brand
and the context of the crisis to predict consumers’ attribu-
tions accurately.

Next, we show that when base-rate information affects
consumers’ crisis attribution, the pattern of effects does not
always conform to the predictions from previous research.
Previous research has primarily examined the causal role of
base-rate information. Specifically, a high (vs. low) base
rate leads to less blame attributed to the brand because it
implies that external factors may have caused the event. In
the context of a product-harm crisis, we show that high
base-rate information alone does not affect attributions. In
particular, a high (vs. low) base-rate leads to less blame
toward the brand only when the focal crisis is said to be
similar to other cases in the industry. This result suggests
that the causal role of base-rate information may be weak-
ened in the face of strong default attributions initiated by a
crisis incident. Unless the base-rate information pertains
specifically to the focal case and provides strong alternative
explanations for the causes of the incident, this information
is unlikely to affect consumers’ default attributions. This
finding does not nullify the previous prediction about the
causal role of base-rate information. Instead, it offers sup-
port by specifying conditions under which it occurs in a
product-harm crisis.

Besides the previously predicted causal route, we show
that a different route through which base-rate information
affects attribution may be at play. In particular, a low base
rate can suggest the rarity of a crisis and lead consumers to
excuse an otherwise well-regarded brand by considering the
event an exception, which we term the “subtyping effect.”
Our finding of the subtyping effect corroborates previous
research that shows that consumers may at times not blame

the brand despite perceiving it as the cause of the incident
(e.g., Folkes and Kotsos 1986; McGill 1990). This finding
suggests that attribution adjustment does not invariably take
the causal route, according to which consumers are only
likely to adjust their default attributions to the brand when
they can shift the perceived cause to external factors.
Instead, when base rate suggests the rarity of crises, con-
sumers reduce blame toward the brand because they con-
sider the crisis an exception that is unrepresentative of the
brand’s normal behavior.

From a marketing standpoint, the different patterns of
base-rate effect on attributions carry implications for the
management of the negative impact of product-harm crises.
Conventional wisdom suggests that highlighting the general
prevalence of a behavior/event helps reduce the blame
attributed to the focal firm by getting consumers to consider
the external causes. In the context of a product-harm crisis,
our results show that simply suggesting the industrywide
prevalence of a crisis does not help reduce the blame attrib-
uted to the brand for the crisis. Unless there are clear, strong
alternative explanations to the causes of the incident, con-
sumers are unlikely to deflect attribution from the brand.
Indeed, Folkes (1988) suggests that a causal inference,
when formed toward one party, is often difficult to change
to other parties (see also Folkes and Kotsos 1986). In com-
parison, subtyping does not require consumers to find other
causes to explain the incident. Thus, emphasizing the rarity
of a crisis may be an “easier” path for managers to dampen
the negative impact of a crisis on a brand. Where industry
prevalence is engaged as an explanation, managers should
ensure that the base-rate information is perceived as rele-
vant by specifying the similarities/links between the focal
crisis and previous crises that occurred in the industry. By
doing so, managers urge consumers to view the crisis as
caused by common factors that affect the industry, not just
the focal firm. At one point during the Toyota recalls in
early 2010, the company highlighted the recall record of its
competitors, which indicated that North American car com-
panies topped the list of recalls. In response, however, the
press questioned the similarity of Toyota’s recall to previ-
ous recalls in the industry.

Furthermore, we show that the same base-rate informa-
tion may have a different impact on a subsequent crisis
depending on how it affects the attribution of the first crisis.
We find that consumers who had discounted a previous cri-
sis under the high base-rate with similarity information
present condition would still discount a subsequent crisis
under the same condition. However, consumers who had
subtyped the previous crisis under the low base rate in the
similarity information–absent condition do not subtype the
subsequent crisis under the same conditions. These results
show the dynamic nature of consumer attribution and sug-
gest that attributions develop in a more complex pattern
than has been previously assumed. Managerially, these
results highlight the importance of understanding not only
the attribution outcomes but also the process of attribution
for managers to preempt and respond to consumer reactions
to multiple product-harm crises. Prior research on consumer
attribution of negative events has primarily focused on the
impact of a single event. However, the increasing use of
umbrella and family brand strategies has led to large num-
bers of products manufactured under a single brand name or

are linked under an umbrella brand. Even well-regarded
brands may experience multiple crises (e.g., multiple recalls
by Firestone, Toyota, and Tylenol). Our results show that
although these brands with positive prior beliefs may be
protected through both discounting and subtyping effects,
the former sustains the protection afforded by the positive
beliefs, whereas the latter consumes and depletes it. This
implies that crises may require very different communica-
tion and handling depending on whether they are first or
repeat incidents.

In our research, we controlled for or kept constant
consumer-related and crisis-related factors that might poten-
tially moderate the effects in our findings. First, research
suggests that observers are unable to take contextual infor-
mation into consideration when their cognitive capacity is
taken up by other tasks (Gilbert 2002). Previous research
has shown that discounting requires cognitive effort (e.g.,
Gilbert 1989; Gilbert and Malone 1995). We expect that
subtyping also requires cognitive effort, as the use of con-
textual (base-rate) information, whether to discount or sub-
type, would require the observer to spend cognitive effort
assessing covariation between the case information and the
base-rate information to adjust the default attribution. Sec-
ond, research suggests that as the consequences of an event
become more unpleasant, observers’ defenses are raised,
and they are more likely to attribute the causes to the actor
because the same thing might befall the self (Fiske and Tay-
lor 1991). Thus, as the consequences of a crisis become
increasingly severe, contextual information should have less
impact on adjusting the default attributions to the brand. For
example, Johar, Birk, and Einwiller (2010) suggest that, if a
crisis is severe, the “not just me” response may not be effec-
tive, as consumers are less likely to shift the blame. Thus, in
addition to the characteristics of the brand (e.g., consumers’
prior brand beliefs) involved in the crisis, the characteristics
of the consumers (e.g., cognitive capacity) and the crisis
(e.g., crisis severity) can also affect the use of base-rate
information in the attribution of a product-harm crisis. Fur-
ther research could examine more systematically the inter-
active impact of the crisis, the consumers, and the brand on
the use of base-rate information in attribution. Furthermore,
in this research, we examined the impact of a crisis on con-
sumers by placing participants in the role of observers not
directly affected by the crisis. Consumers who are directly
affected by the crisis may develop even stronger default
attributions to the brand (Folkes 1988) and be less likely to
be affected by contextual cues such as base-rate informa-
tion. Further research is needed to examine how base-rate
information affects consumers’ attribution of a product-
harm crisis when they are in an observer’s versus victim’s
role.

Finally, our findings regarding the different effects of
base-rate information also have broader implications for its
impact in other contexts. Kardes (1998) suggests that base-
rate information may have multiple, opposing effects
instead of one pattern of unified effect. For example, a high
base rate of product adoption suggests desirable attributes
of the product, whereas a low base rate suggests the unique-
ness of a product. Thus emphasizing a high or low base rate
of a behavior/event may be effective in different conditions
to influence consumers’ judgment and behavior. Our study
corroborates this proposition by investigating two different

346 JOURNAL OF MARKETING RESEARCH, JUNE 2012

Consumer Attributions of Product-Harm Crises 347

effects of base-rate information in consumer attribution of a
product-harm crisis and suggests conditions under which
each occurs. Further research could examine how multiple
effects of base-rate information affect consumers’ judg-
ments in other research contexts such as message framing
in advertising.

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AsianAcademy of Management Journal, Vol. 18, No. 1, 1 –17, 2013

CHALLENGES TO TOYOTA CAUSED BY RECALL
PROBLEMS, SOCIAL NETWORKS AND DIGITISATION

Jay Rajasekera

International University of Japan

Graduate School of International Managemen

Minamiuonuma City, Niigata, Japan 949-727

E-mail: jrr@iuj.ac.jp

ABSTRACT

The recent recall problems that shook Toyota raised questions about the company’

openness with the public. Media attention and the intervention by governments in
Toyota’s largest markets in North America, Europe, China, and Japan kept Toyota’s
management in the spotlight. The crisis also exposed the power of social media. Although
authoritarian regimes can control social media, public companies cannot. They have to
live with it by either countering effectively when a crisis begins to brew or suffering the
consequences when it grows out of proportion. If Toyota manages social media
strategically, can it overcome the recall debacle and protect the reputation it has built
over decades as the top-quality automaker in the world? What challenges does the
increasingly digitalised auto industry present to Toyota? These are the main subjects of
this paper.

Keywords: social media, crisis management, Toyota, recall, social networks, Facebook,
Twitter, digitisation

INTRODUCTION

Social media, including social networking sites (SNS) such as Facebook and
Twitter, have added new meaning to the spread of news and information.
Whereas traditional information channels, such as newspapers, radios and TV, are
one-way mediums, the dawn of the Internet and social media has made
communication a two-way medium. The lack of official control, supervision and
regulation has fuelled a social media frenzy, which has proven to be an effective
method of rallying crowds for any significant (or even insignificant) issue.

The recent bans on Facebook and other types of social media by certain
governments are proof that social media cannot be ignored. Although
authoritarian governments can resort to such drastic methods, public corporations
cannot afford to do so. Corporations have no other option than to live with social
media phenomena, either countering them effectively when a crisis begins to
brew or suffering the consequences when it grows out of proportion.

Jay Rajasekera

In this context, it is interesting to explore how recall-troubled Toyota has handled
social media and what options are available for Toyota to prevent the situation
from going out of control and harming the worldwide reputation as a top-quality
automaker that the company has worked for decades to develop.

Toyota’s recall exposed some “digitisation” in the automobile industry as well.
Digital technology in the music and video industries and its exploitation by Apple
in the Internet and social media essentially pushed Sony, an old industry
heavyweight, to the sidelines (Rajasekera, 2010; Chang, 2008). Could the same
thing happen to Toyota? Could a newcomer exploit digitisation in automobiles, in
conjunction with the Internet and social media, to dethrone an established giant
such as Toyota?

The Recall Crisis at Toyota: Rise and Fall

Since its founding in 1937, Toyota Motor Corporation has strived to build quality
automobiles. Capitalising on the Japanese concept of Kaizen, or continuous
improvement, and Just in Time (JIT), the company has built a worldwide
reputation for manufacturing affordable quality automobiles. Considered a
conservative company, Toyota capitalised on quality and competed directly with
established and well-known brands in Europe, the U.S. and elsewhere (Morgan &
Liker, 2006; Magee, 2007).

Figure 1. In the last decade, Toyota rapidly increased its market share

(Source: WardsAuto, 2010)

0.0

2.00%
4.00%
6.00%
8.00%

10.00%
12.00%
14.00%
16.00%

2002 2003 2004 2005 2006 2007 2008 2009

%
S

ha
re

o
f U

.S
. M

ar
ke

Year

Toyota’s Market Share Growth in U.S.

Challenges to Toyota Caused by Recall Problems

After its entry to the U.S. market in 1957, it took Toyota more than 40 years to
take a 10% share of its most important U.S. market. Toyota has seemed more
focused on rapid growth since the beginning of the last decade (Figure 1). Almost
50 years after entering the U.S. market, the Japanese company surpassed Ford
and Chrysler in 2007 to become the second most popular automotive brand in
America. The year 2007 was also a landmark year for Toyota because the
company earned US$15.1 billion in profits, the largest amount in the company’s
history and the largest ever for a Japanese company.

The next year, 2008, was a recession year worldwide, and automobile sales
dropped everywhere. However, Toyota managed to increase its global market
share and became the largest automaker in the world, a record held by GM for 77
years (Time Magazine, 2010a).

Although Toyota became the world’s largest automaker, the No. 1 spot did not
bring much solace to the company. After reporting a record profit the year before,
the global recession of 2008 brought bad news to Toyota: the company reported
the first loss, US$1.5 billion, in its corporate history.

Financial loss aside, the larger shock for Toyota was the seemingly unstoppable
stream of recalls that accompanied a streak of emotionally charged accidents,
including 52 deaths allegedly attributed to a sudden acceleration problem (CBS
News, 2010).

Recalls are nothing new for the automotive industry, especially in the U.S., where
the first recall law went into effect in 1966. Over a span of approximately 40
years, 400 million motor vehicles, including cars, buses and motorcycles, were
recalled in the U.S. alone, according to U.S. government data (National Highway
Traffic Safety Administration [NHTSA], 2010). Thus, approximately 10 million
vehicles, on average, are recalled every year for various reasons. What made the
Toyota case different was the significance of the image that the company had
produced for itself over the years and the damage to the perceived notion that the
name Toyota meant quality.

It was almost 50 years ago, in 1961, that Toyota addressed the importance of
product quality in its adoption of “Total Quality Control” as a way to compete
against well-established car manufacturers (Toyota Motors Corporation, 1961;
Ohno, 1988). Damage to the reputation that Toyota had built since that time
stunned the general public; especially the Japanese, for whom Toyota is the
commercial face that proudly represents the country to the outside world.

Jay Rajasekera

Figure 2. Sudden jump in Toyota’s safety-related recalls
(Source: Minto, 2010; author’s research)

The vehicle recall law divides recalls into two categories depending on the type
of defect: a defect related to safety (one that can cause injury or death) and a
defect not related to safety (such as a defective radio or air-conditioning system).
The defects in Toyota vehicles that allegedly caused a number of deaths were
related to safety and thus are considered serious (Figure 2). The unprecedented
media coverage around the world was due to Toyota’s brand name, its newly
acquired title as the “No. 1 automaker in the world,” and its rather lethargic
response time to the incidents, some of which reportedly happened several years
earlier.

On 21 January 2010, media around the world began presenting the stunning news
of Toyota’s recall of 2.9 million vehicles in addition to the 3.9 million recalled
just a few months earlier. The reaction from all corners, including Toyota’s own
customers, the general public, politicians, and the financial markets, was
unprecedented in Toyota’s history (Figure 3). The total number of Toyota’s recalls
related to the serious safety defect connected to sudden acceleration would
eventually climb to 8.6 million globally (Minto, 2010; CNN Online, 2010).

Safety-related recalls

Challenges to Toyota Caused by Recall Problems

Figure 3. Recalls cost Toyota 20% of market value

(Source: NYSE [New York Stock Exchange], 2010)

Toyota, the company that made “Total Quality Control,” “Quality Circles” and
the “Toyota Way” mantras for any CEO, suffered a severe setback to its long-
cultivated image.

In the U.S., where recalls of all types, from drugs to baby food to dog food, were
nothing new, the media were quick with sensational stories linked to the now-
infamous “sudden acceleration” problem.

With the Internet and social media such as Facebook and Twitter in full force, the
negative news spread at unprecedented speed to Europe, China, and around the
world, including Toyota’s home market of Japan. Toyota may be facing the
greatest challenge to its future. The consequences could be severely damaging
unless Toyota reacts prudently.

WHAT TOYOTA HAS TO PROTECT

The world’s automobile industry is undergoing historic changes. In the U.S., the
major story is the bankruptcy of two of the “Big Three” automakers amid a
historic recession; both GM and Chrysler are operating under U.S. government
control. For decades, these two companies, along with Ford, defined America’s
manufacturing prowess. However, almost half a century since its entry to the U.S.

-2

-20%

-15%

-10%

-5%

0%
5%

25-Feb-1021-Jan-1

Toyota Stock Performance in NYSE

Toyota Ford
Honda

Jay Rajasekera

market, Toyota had become the top auto manufacturer globally and was on the
verge of becoming the market leader in the U.S. by overtaking GM.

The auto industry has become extremely competitive, with new low-cost
automobile manufacturers, such as Chery and Tata, entering the scene from China
and India, respectively. Korea’s Hyundai has built new factories in the U.S. and is
competing aggressively with the established Japanese automakers (CBS News,
2010).

With significantly decreased sales due to the global recession, there is no room
for any automaker, no matter how well positioned it has been, to make a mistake.
Toyota’s position as the global leader means that it has the most to lose from a
recall as severe as the one that just occurred.

In the U.S., where hordes of lawyers are waiting eagerly to help victims or their
families against Toyota, financial and punitive damages may be severe.

The usual apologies characteristic of Japanese companies can only go so far. As
soon as the large recall of 2.3 million vehicles was announced in January 2010,
Toyota ordered dealers to temporarily suspend the sales of eight models involved
in the recall for a sticking accelerator pedal. Moreover, to maintain a balance of
inventory, several factories had to be closed for specific periods.

Nonetheless, the greatest challenge for Toyota is to maintain the public trust.
Voluntary recalls, if conducted in a timely manner, can help to boost trust in a
company, as was the case in previous Toyota recalls. However, the situation was
different this time because the company was forced by the U.S. government,
which had received a significant influx of complaints. This forced recall did not
create a positive image for Toyota’s reputation, which had been created
meticulously over several decades through a carefully planned strategy and
public relations campaigns.

Since the days of so-called “Japan Bashing” in the U.S. during the 1980s, Toyota
had endeavoured to create an image of an all-American company by designing
and building its cars in the American heartland. Toyota’s factories provide direct
employment to 35,000 Americans and indirect employment to approximately
115,000 Americans through its 1,400 dealerships, according to company
information (Toyota USA, 2010a). Over a 50-year period, Toyota claims to have
invested US$17 billion in the U.S., and its dealerships have invested another
US$15 billion. Toyota has aggressively promoted “social contribution activities
that help strengthen communities and contribute to the enrichment of society” not
only by itself but also through its suppliers and dealer networks (Toyota Motors
Corporation, 2009).

Challenges to Toyota Caused by Recall Problems
7

Toyota has enormous brand value in the U.S. The reputed JD Power often ranks
Toyota vehicles near the top in terms of quality. Even in its most recent ranking,
Toyota received four first-place awards, more than any other automotive brand.
Furthermore, the U.S. is Toyota’s most profitable overseas market. Consequently,
there are high stakes for Toyota if the recall is not handled carefully.

CRISIS MANAGEMENT

Since its founding in 1933, Toyota has weathered numerous crises. Although the
present crisis did not force the resignation of Toyota’s president, previous
situations have led to the downfall of the company’s upper management; for
example, the founding president, Kiichiro Toyoda, resigned in 1950 to take
responsibility for a labour dispute and sagging sales during a severe Japanese
recession (Hosoda, 2009; Magee, 2007). Another crisis, Toyota’s first corporate
loss since the 1950 crisis, forced the departure of the then-president Katsuaki
Watanabe, bringing Akio Toyoda, the current president, to the top post at Toyota.

With only one year of job experience as president, Akio Toyoda, armed with an
MBA from a U.S. business school, faced perhaps the most difficult task in his
business career when he was called to testify before the U.S. Congress on 23
February 2010. Already under fire by the U.S. media for not apologising early or
sufficiently, his performance, broadcast live around the world, was a defining
moment for Toyota and for corporate Japan. Did he apologise sufficiently? Was
his performance sincere? Did it look like he was trying to conceal something?
The verdict may be yet to come because the response is not delivered only by TV
or newspapers.

In a survey conducted by the TV broadcaster CBS News in the U.S. following
Mr. Toyoda’s testimony, the public did not rate Toyota’s explanation very
positively: overall, only 27% believed that Toyota was telling the truth, and
almost 50% said that Toyota was hiding something (CBS News, 2010).

In a case reminiscent of the Toyota crisis, Audi, the high-end German automaker,
had to manage a recall catastrophe in 1986 caused by sudden acceleration of its
automobiles sold in the U.S. Of course, the Internet was non-existent at that time,
and television was the most prominent media. It was believed that Audi did not
handle the media properly, and the public became distrustful of the company. It
took fifteen long years for Audi to improve its sales to the level prior to the recall
(Figure 4).

Jay Rajasekera

Figure 4. Audi took 15 years to recover from U.S. recall

(Source: WardsAuto, 2010; author’s research)

Toyota is quite a different company compared to Audi. Toyota is well established
in the U.S. market and has a loyal customer base in the millions. With thousands
of Americans designing and building automobiles within the U.S., Toyota has
cultivated a loyal following that includes some key politicians from the heartland.
In fact, several of these politicians came forward during this crisis to tone down
the U.S. government’s outcry against Toyota’s allegedly slow response.

The media itself has undergone dramatic changes since the Audi debacle in 1986.
With the explosion of the Internet, media has become much more interactive.
Social media, such as Facebook and Twitter, have demonstrated that people rely
on them during crises. As a corporate utility, social media is an excellent way to
disseminate company messages to the public (Qualman, 2009). Alternatively,
social media, if properly used, is a way to keep an eye on the public mood when a
significant issue occurs that affects a large number of people, such as the present
recall, which raised emotions among many of Toyota’s customers.

POWER OF SNS

Social networking sites, or SNSs, are web portals that allow users to become
members and create their own profiles. SNSs also allow members to form

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Recall Effect on Audi and US Auto Market

Audi Toyota US Total

Audi took 15 years to recover

Toyota recovered from 2005 recall

Challenges to Toyota Caused by Recall Problems

relationships. Members can post and share messages, photos, and videos
instantly, and members have the option of making these postings available only
to the member’s friends or to general members of the SNS (Knoke & Yang,
2007).

Social networking sites can be used as community-based Web sites, online
discussion forums, chat-rooms, and spaces to discuss a certain social topic. One
recent example in which SNSs were cited as a playing a critical role is the so-
called “Arab Spring,” which saw many entrenched regimes in the Arab world fall
due to popular uprisings fuelled by social media (Ghannam, 2011).

With more than 800 million active users around the world, Facebook is the most
dominant SNS in existence today. If Facebook were a country, it would be the
third most populated in the world, behind only China and India
(http://www.insidefacebook.com). Facebook originated in the U.S. in 2004 and
has grown dramatically. With more than 150 million active users, the U.S. is its
largest customer base. Non-English-speaking countries, such as Indonesia,
Turkey, Mexico and Brazil, each have more than 25 million active subscribers to
Facebook (http://www.insidefacebook.com). Fearing the power of Facebook to
gather crowds, some countries have censored access to Facebook.

Other SNSs that have gained wide popularity are YouTube and Twitter. YouTube
allows videos to be shared. Owned by Google, it is said that YouTube receives
more than 3 billion views per day, and close to 50 hours of videos are uploaded
by members every minute (Henry, 2011). Twitter, which originated in the U.S. in
2006, has over 300 million active users worldwide. Twitter is an SNS for short
messaging and has become quite popular in the case of disasters, such as
earthquakes, when regular phone lines are disrupted (Sakaki, Okazaki, & Matsuo,
2010).

With the prominent role of SNSs as media where any popular topic can galvanise
a movement, it would be wise for Toyota, with its large customer base
worldwide, to consider using it.

TOYOTA’S SNS STRATEGY

With manufacturing operations in 27 countries and a dealer network in 170
countries, Toyota is a giant organisation. In any large organisation, media releases
for newspapers, television, or SNSs such as Facebook, Twitter, or YouTube must
be coordinated carefully to prevent public confusion. Indeed, Toyota seems to
have realised the importance of SNSs early on. As soon as the recall crisis began
receiving media attention, Toyota quickly put together an “Online Newsroom”

Jay Rajasekera

and a “social media strategy team” to coordinate all the media releases from
different organisations of the company, such as public relations, customer
services and dealers (Toyota USA, 2010b).

The SNS sites Toyota is operating include the following:

1. Facebook: www.facebook.com/toyota
2. Twitter feeds: www.twitter.com/TOYOTA
3. YouTube: www.youtube.com/toyota
4. YouTube USA: www.youtube.com/user/ToyotaUSA
5. Pressroom Toyota: www.pressroom.toyota.com

In addition to Toyota’s own efforts, anyone interested in expressing an opinion
has the option of using any SNS media to exchange opinions. On Facebook itself,
the author found ten active anti-Toyota social groups (more detail later in this
section).

Reasoning that the company had not had a major backlash from its customers,
especially in the U.S., where media was providing sensational coverage around
the clock, Toyota stated that it had increased the number of customers on its
Facebook page. It is true that Toyota fans to this SNS site increased by
approximately 10% monthly. However, all of the other major U.S. brands had
also been adding fans to their Facebook SNS sites (Figure 5).

Figure 5. Ford and Hyundai adding fans faster on Facebook

(Source: http://www.insidefacebook.com; author’s research)

100.00%

110.00%

120.00%

130.00%

140.00%

150.00%

160.00%

170.00%

2/15/2010 2/25/10 3/6/2010 3/17/2010

Date

Toyota on Facebook: Growth of Number of Fans

Toyota GM Ford Hyundai

Hyundai is the winner on Facebook

Challenges to Toyota Caused by Recall Problems

In terms of the number of fans, GM is the leader on Facebook, followed by Ford,
with Toyota at number three. However, the up-and-coming Korean automaker
Hyundai is adding fans at the fastest rate. Thus, Toyota’s claim that it does not
observe customers losing faith or abandoning the company may be a premature
judgment.

A key advantage of tapping into SNS is that a company can gather nearly real-
time information about customers’ feelings or complaints. According to a recent
study, consumers use SNS when making decisions to buy automobiles (Chen,
Fay, & Wang, 2011). However, the automobile industry in general has not
significantly used SNSs as major communication media (MH Group, 2009), with
the exception of fan clubs. A Toyota fan club, such as the one on Facebook, may
not reflect all sides because the people who join the club are likely to already
have a positive opinion about the brand or the company.

In fact, the recall process produced quite a few SNS groups attacking Toyota. The
company may want to periodically tap into such groups to follow up on their
messages. On Facebook itself, one can find more than ten such SNS groups, with
revealing names such as “anti-Toyota,” “anti-Toyota Prius Group!,” and “anti-
Prius movement” (Facebook, data on 26 May 2010). However, the total number
of members of these groups is quite small, less than 1% of the number on
Toyota’s official Facebook SNS. Toyota may be concerned about the growth of
the membership of these SNSs and the rate at which members post messages as
well as the content of these messages.

One SNS site that was in operation well before the current round of recalls
threatened Toyota is a public site called PRIUSchat (http://priuschat.com/). It is
interesting to observe the traffic and the number of SNS groups on this site
(Figure 6).

Jay Rajasekera

Figure 6. Number of messages increases with bad news

(Source: http://priuschat.com/; author’s research)

The peak observed in the traffic line on this exhibit is the result of a sudden recall
announcement associated with one of Toyota’s most popular hybrid models, the
Prius. A careful analysis of these messages can explain the seriousness of this
concern.

LONG-TERM EFFECTS OF SNSs ON TOYOTA

A comparison of traffic to Toyota’s SNS site and anti-Toyota sites on Facebook,
as explained in the previous section, reveals that Toyota strategically managed its
SNS media with regard to the current recall. However, associated problems with
the recall have brought to light a more serious threat that is directly related to the
digitisation of the automobile (Figure 7).

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Bad news brings traffic to an SNS

Number of messsages peak
when bad news spreads

Challenges to Toyota Caused by Recall Problems

Figure 7. Automobiles are increasingly becoming digitised
(Source: Chang, 2008; Whitfield, 2002; author’s research)

With the advances of the computer, automobile manufacturers around the world
adopted many computerised methods to control and optimise the function and
performance of their vehicles. This is very similar to what occurred when analog
music devices gradually became digital. Sony was clearly the leader in analog
music, but, by strategically exploiting SNSs and software, Apple came from
nowhere to lead the digital music world. Could Toyota experience something
similar?

Despite the long span of time that the recall problem has threatened Toyota, the
cause of the problem or problems remains somewhat unclear. Blame has often
been placed on a faulty electronic system. The National Highway Traffic Safety
Administration has sought the help of NASA and the National Academy of
Sciences in the U.S. to identify the problem (Time Magazine, 2010b).

A modern automobile has several systems that are controlled digitally by
computer chips and software:

1. Electronic Throttle Control
2. Electronic Stability Control
3. Electronic Brake Control
4. Electronic Fuel Injection
5. Electronic Speed Control

800

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Analog TV Automobile Digital TV PC

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Transistor Intensity (in 1000s)

Jay Rajasekera

Of course, there are many other functions, such as air conditioning and safety
monitoring, that may be controlled by a computer mechanism. It is said that a
modern automobile has, on average, 70 to 100 microprocessors and millions of
lines of software code (Charette, 2009; ScienceDaily, 2010).

Although there are common electronic parts used across many manufacturers,
some key control systems are proprietary. Whether a problem with these systems
is hardware-related or software-related, customers have no choice but to take the
whole vehicle to a dealer. In Toyota’s sudden acceleration problem, some experts
suggested that the problem could be a software problem. When such a software
problem occurs in a modern electronic device, the solution can often be
downloaded from the Internet quickly and easily. Although there are onboard
diagnostic systems in vehicles, including Toyota’s problem models, accessing
them often requires taking the car to a dealership.

If a car behaves like a modern electronic gadget that is connected to the Internet –
and automobiles are increasingly becoming web-enabled – the problems can be
monitored to varying degrees in real time, and fixes can be accomplished cheaply
and swiftly. This may present a threat to an established player such as Toyota.

In 2005, Toyota was embarrassed by several recalls. In Japan, the total number of
recalls, including Toyota’s, multiplied 40 times in comparison with 2001 levels,
causing serious concern to the Japanese government. The government asked
Toyota for an explanation, and the company promised to create a defect-reporting
database so that it could monitor vehicle-related complaints from customers in a
timely manner.

However, the current problems with Toyota revealed that either the company did
not create a system to accumulate data into such a database or the company did
not pay attention to the data gathered in this database in a timely manner.

In his testimony to the U.S. Congress, President Toyoda admitted that the
company was growing too fast and that it may have focused on selling cars rather
than paying sufficient attention to quality. According to a statement from a
Toyota employee union, only 60% of vehicles are completely tested at the final
stage, compared to 100% a few years ago. It is possible that Toyota did not pay
sufficient and timely attention to customer complaints and may not have analysed
the complaint database (if it had one) carefully.

For the company that pioneered Just-in-Time manufacturing, Toyota’s response to
the faults and problems was far from being JIT. This situation may present new
opportunities for companies that have the means to observe customer behaviour
almost in real time, such as through Facebook and Google.

Challenges to Toyota Caused by Recall Problems

Toyota’s situation is similar to the situation at Sony. The company was growing
rapidly in the areas of television and music CD players, but it did not realise the
importance of the Internet and social media or that its customers were moving to
such sites. Apple saw the opportunity and seized it, and the rest is history.

Whether a similar thing could happen to Toyota and whether Toyota can prevent
a demise like the one Sony experienced remain open questions.

CONCLUSION

Although recalls are not new for automobile companies, including Toyota, the
recalls since 2009 were the largest in Toyota’s history. The historic crisis created
by these recalls raised many questions about the openness of the company. In
particular, the delay by the company’s president Akio Toyoda in providing
explanations raised public doubts about the company’s sincerity. The crisis also
exposed the power of social media. SNSs had recently gained prominence in
rallying audiences around hot social issues, and Toyota seemed to have realised
their importance early on. Based on the data collected on Facebook, Toyota did
well; even during the crisis, Toyota managed to add fans to its Facebook site.
However, observing one’s own performance on an SNS does not tell the whole
story. Toyota must carefully watch its competitors. As shown in this analysis, the
Korean automobile company Hyundai is adding fans to its SNS at the fastest rate.
There must be a reason for this growth, and Toyota will be challenged to find it.
Another challenge to Toyota, as highlighted in this study, is the digitisation of
automobile functionalities, which is increasing rapidly. Even the recall problems
in Toyota vehicles were believed to be related to digitisation. The solutions for
these problems are software issues. This is where SNSs can again play a key role.
Apple used SNSs and software applications (called apps, in Apple’s terminology)
to unseat Sony from the music gadget industry. Unless Toyota realises this, it
could face serious challenges to its supremacy in the world automobile industry
from existing or new automakers.

ACKNOWLEDGEMENT

Author would like to express his sincere appreciation to Mr. Oscar Manuel
Mendoza, MBA Class of 2010, International University of Japan, for the
numerous and constructive comments made on a draft version of this paper.

Jay Rajasekera

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TheInternational Journal of Organizational Innovation Vol 7 Num 2 October 2014 63

A CASE STUDY OF THE CORPORATE TURNAROUND STRATEGIES

Wei-Hwa Pan

Department of Management

National Yunlin University of Science and Technology, Taiwan

panwh@yuntech.edu.tw

Yih-Lang Chen*

Department of Food and Beverage Management

National Kaohsiung University of Hospitality and Tourism, Taiwan

Department of Management
National Yunlin University of Science and Technology, Taiwan

*(Corresponding Author) chenalan99@gmail.com

Abstract

This paper adopts a case study approach to identify the turnaround actions of a restaurant firm

that affect its capability to launch turnaround strategies when encountering different corporate

crisis contexts. The study ascertains key factors that could optimally be applied as a best prac-

tice framework for change management leading to corporate turnaround in a highly volatile

restaurant business.

Since turnaround strategies have not been pursued vigorously as a stream of research within

the hospitality industry, this approach would afford a framework for hospitality researchers to

commence similar future research processes, which in turn would help the industry cope with

turnaround.

Keywords: Corporate Turnaround, Entrepreneurship, Organizational Strategy, Restaurant In-

dustry, Strategic Turnaround.

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 64

Introduction

Company growth has continually been the

topic of concern for company founders and

operators and the core of management stud-

ies. For company organizations that continu-

ally seek growth, company growth becomes

particularly crucial when companies achieve

a stable profit and a leading status in the in-

dustry. On the other hand, companies that op-

erate in a volatile environment confront the

challenge of keeping pace with constant

changes in their external environment. While

companies that are able to respond the threats

they encounter in such environments are al-

lowed to remain still their competitive ad-

vantage, those that are not able to cope with

the environment either perish or face the in-

surmountable task of turnaround.

In this paper, we inquire into how the

unique characteristics of established a restau-

rant firm affect its ability to fulfill turnaround

strategies when facing two critical organiza-

tional crises. The topic of turnaround strate-

gies is of substantial interest not only for our

conceptual understanding but also for the

management of restaurant firms. Empirical

studies have long documented that hospital-

ity operators frequently encounter organiza-

tional crises and demonstrate a high rate of

firm failure (Elwood, & Tse, 1991; Ibrahim,

Soufani, & Lam, 2001; Tse, & Olsen, 1999;

Umbreit, 1996). A deeper comprehension of

turnaround strategies in this firm promises

improved organizational abilities to success-

fully employ such strate

gies.

This paper contributes to the emergent

research that argues against the simple appli-

cation of standard turnaround strategies to

hospitality-related businesses (Elwood, &

Tse, 1991; Hambrick, & Schecter, 1983; Tse,

& Olsen, 1999; Umbreit, 1996). Given the

limited prior research that directly connects

hospitality firm characteristics with the im-

plementation of turnaround strategies, we in-

vestigated realistic turnaround behavior in an

established restaurant firm that had been

faced two organizational crises. Based on an

iterative approach of data interpretation and

further data collection, we developed specific

propositions with respecting to how firm

characteristics influence the firms’ ability to

endure retrenchment, implement top-man-

agement change, and to draw on corporate

entrepreneurship. The propositions outlined

in this study contribute to the development of

more fine-grained models of strategic turna-

round in restaurant firms.

Literature Review

Definition of Corporate

Turnaround

Typically, most turnaround situations

result not only owing to external factors but

also due to the incompetence and inexpertise

of the organizational management. Research-

ers have described turnaround as a multi-

stage process (Bibeault, 1982; Pearce and

Robbins, 1993). Bibeault (1982) indicates

that a firm’s primary objective of turnaround

is to prevent the downturn, which should be

followed by actions that either seek profita-

bility with changed resource commitment or

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 65

search new growth avenues. In other words,

these are long-term actions engaged by firms

that include investments aimed at motiving

financial improve

ments.

Bruton and Rubanik (1997) define turn-

around as ‘‘the reversal in a firm’s decline in

performance’’. Other definitions of turna-

round include those activities that support

firms in the regeneration of their busi

nesses.

Schendel et al. (1976) introduced their con-

cept on the cause of the turnaround situation

and its effect on the selection of appropriate

turnaround strategies, while Hofer (1980)

stated the aspect of severity of the turnaround

situation and the selection of adequate turna-

round strategies. Hambrick and Schecter

(1983) empirically tested the notions asserted

by Schendel et al. (1976) and Hofer (1980).

Suzuki (1985) pointed out the types of strat-

egies involved in turnaround. These strategy

choices include:

(1) Top management replace-

ment.

(2) Financial strategy (inventory

control, liquidity management, debt

management and equity management).

(3) Personnel strategy (trimming

of workforce).

(4) Marketing strategy (product

and market diversification).

According to Bruton and Rubanik

(1997), generic rules that apply to a turna-

round situation include:

(1) A crises (as a motivator for

management to adopt necessary actions

to reverse the situation).

(2) Retrenchment effort (to con-

trol cash flows).

(3) Operating, strategic and/or a

mixture of the two (initiated after step

2).

(4) Corporate culture (shapes

turnaround strategy).

(5) Leadership

Influence Turnaround Factors

In the light of Sloma (1985), the factors

that influence turnaround can be categorized

into internal and external factors. External

factors are forces that affect the organization

from the external environment vis-a`-vis eco-

nomic problems, competitive problems, tech-

nological change and social change. There-

fore, Scherrer (2003) proposed external fac-

tors include increased competition, rapidly

changing technology and economic fluctua-

tions. While describing the stages in turna-

round, Scherrer asserts that the business

should be able to stabilize within 6 months to

1 year after implementation of the plan. Be-

sides, it should be able to return to growth

within 1 to 2 years after stabilization.

On the other hand, internal factors are

symptoms that firms show from within the

organization that can range from problems

such as inability to pay taxes and debt ser-

vices to eroding gross margin, decreasing ca-

pacity utilization, increased turnover of man-

agement and staff and lack of competence

and expertise to instruct the organization on

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 66

the part of top management. There are sev-

eral main internal factors of decline include

increasing inventory while sales growth de-

creases, cash flow problems and manage-

ment’s inability to cope up with growth.

Therefore, Allaire and Firsirotu (1985)

divided company crisis into current company

status and company’s ability to coordinate

with the future environment. When the time

given is limited during a crisis, decision mak-

ers must consider the degree of influence that

the crisis has on the company and adopt four

major reform strategies: reorientation, trans-

formation, turnaround, and revitalization.

These strategies are described as fol-

lows:

(1) Reorientation

Reorientation is the easiest one to ac-

complish among the four major strate-

gies. When performance is expected to

stagnate or decline as the current market

reaches maturity, corporations can

transfer a portion of their resources to

increasingly attractive markets or indus-

tries, take disciplinary action against

current business departments, or acquire

new business departments. This process

involves various business departments

or domains. However, experiences of

past success cannot necessarily be ap-

plied; corporations must adapt to differ-

ent cultures or organizational structures.

(2) Transformation

Transformation strategies must be ex-

ecuted by effective leaders who are will-

ing to fulfill company goals and spear-

head reform in corporations. However,

transformation strategies are typically

used during periods in which the com-

pany performs favorably. Therefore,

leaders who can develop goals to be

achieved in the future are necessary be-

cause these periods lack clear incentives

for reform.

(3) Turnaround

Corporations adopt turnaround,

which is the act of promoting substantial

reform over a considerable period, when

they encounter survival threats.

(4) Revitalization

Revitalization is when operating per-

formance, such as profitability and the

market share of the corporation, de-

clines without the occurrence of an im-

mediate crisis or when the operating

conditions of a corporation stabilize af-

ter turnaround. Strategy reform for

eliminating the causes of performance

decline must be executed during this pe-

riod to restore profitability and adjust

the direction of the corporation.

Consequently, Lee (1987) categorized

crisis response into three basic strategies: re-

duction, restructure, and growth. These three

basic strategies are also implemented in steps

together with periods of withdrawal,

strengthening, and progress during a com-

pany’s crisis response.

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 67

Company Background

Wowprime Corp was established by

President Day in 1990. Originally an amuse-

ment park business, it was subsequently

transformed into a chain restaurant.

Wowprime adopted a development method

similar to internal entrepreneurship in which

all executives at a level above store managers

and chefs are shareholders. On the other

hand, Wowprime is firmly anchored on three

ancient Chinese philosophers’ schools of

thought: Han Fei Zi’s Legalism, Laozi’s Tao-

ism and Confucianism. The firm president

credits their respective focus on discipline,

nonaction by the ruler (collective leadership)

and humanity (treating colleagues like family

members) for propelling the company’s rapid

expansion in the past decade.

Wowprime is a multi-brand operation

and owns 14 restaurant brands. Each brand

displays distinct product characteristics and

holds a certain consumer group position. The

services provided comprise Western-style

steaks, creative Washoku (Japanese cuisine),

grills, Hokkaido kelp pot, kaiseki cuisine,

teppanyaki, Japanese-style pork curry, and

vegetarian cuisine. In China, Wang Steak and

TASTy are in service with the addition of two

new brands to the China business group: the

teppanyaki restaurant, LAMU Teppanyaki,

and the kaiseki restaurant, Zen Cuisine. A to-

tal of 13 restaurant brands across the Taiwan

Strait provide these services. Thus,

Wowprime’s cross-strait expansion strategy

is to adopt regular chain operations instead of

developing franchisees to maintain service

quality. By 2013, a total of 359 restaurants

were in service, which comprised 273 restau-

rants in Taiwan and 86 restaurants in China.

Thus, there are ambitious growth plans un-

derpin the company’s listing, which will

make franchising overseas more transparent

and –accountable, thus, the firm intend to

raise its number of outlets and franchises to

1,000 by 2020 and 10,000 by 2030.

In addition to cross-strait international

layout development, Tokiya has been author-

ized by Mai Tan corporations in Thailand to

engage in brand operation in September

2011. Tokiya currently operates two stores

and is expected to open 20 branches before

2016. In 2012, Wowprime advanced into

China’s affordable catering market through a

joint venture with the Philippines’ largest

chain restaurant group, Jollibee Foods Cor-

poration, in which the 12Hotpot brand was

established. At the end of November 2013,

Wowprime agreed with Singapore’s Chinese

restaurant chain, Pu Tien Restaurant Pte Ltd,

to a joint venture that introduced

Wowprime’s vegetarian restaurant brand,

Sufood, into Singapore.

Research Method

Research Design

According to Yin (1994), case studies

are rich, empirical descriptions of particular

instances of a phenomenon, or underline the

rich, real-world context in which the phe-

nomena occur. Therefore, the primary notion

of employing a case study is to adopt cases as

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 68

the basis for developing theory inductively

(Eisenhardt and Graebner, 2007).

A case approach adopting content anal-

ysis of longitudinal data and information was

applied to explore and analyze the firm’s

turnaround strategies. This approach helps

look into the actions of the firm over time in

terms of the strategies that were used to de-

scribe the external and internal factors influ-

encing decline over the period. Case study

methods have been employed in studying

turnaround strategy over the past three dec-

ades (Schendel et al., 1976; Hofer, 1980;

Bruton and Rubanik, 1997; Chowdhurry,

2002). This provides the validity of case

study methods for documenting the turna-

round actions of firms. Likewise, it should be

emphasized that these studies were published

in top-tier management journals.

In this research plan, a longitudinal in-

terpretive and exploratory case study ap-

proach was used to develop its function of

theories construction (Eisenhardt, 1989; Yin,

1994; Eisenhardt and Graebner, 2007),

which was consistent with the process orien-

tation of the study. The Wowprime catering

company was chosen as the research subject

of this single-case study based on several

considerations. According to Yin (1994), the

selection of a single case can be based on the

whether the case is a well-formulated key

theoretical case, an extreme or unique case,

or a revelatory case. Analyzing such cases

can reveal special effects for further study in

the future (i.e., multicase studies).

Data Collection

We employed multiple approaches dur-

ing data collection to meet criteria for rust-

worthiness (Lincoln and Guba, 1985; Yin,

1994), including semi-structured interviews,

archival data, and observation. To acquire in-

formation on the actions taken by Wowprime

Corp, over 200 related articles from second-

ary sources, i.e., Business Weekly, company

websites as well as databases such as ABI-

Inform were scrutinized. These actions were

then compared to the operating turnaround

measures and strategic turnaround measures

in order to evaluate objectively whether this

firm’s moves resembled turnaround strate-

gies.

Data Analysis

We used MAX.Qualitative Data Analy-

sis software (MAXQDA) (Kuckartz, 2001)

to content analyze the interview transcripts to

find out patterns, core consistencies, and im-

plications related to turnaround activities.

The analyses generated a set of themes and

clusters of thoughts and phrases that had

been expressed by several of the respondents,

not just by one or two individuals. We pro-

gressed this set of themes further over a pe-

riod of several months into the model of turn-

around strategy introduced in this paper. Fi-

nally, we shared our results with the top-

management teams of the firm and incorpo-

rated their feedback.

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 69

Discussion

Antecedents of the First Turnaround

Wowprime originated through the oper-

ation of an amusement park business, which

quickly gained profit through the creation of

an ostrich-riding South African theme park in

1990. Immediately, three new theme parks

emphasizing novel experiences were succes-

sively established within half a year. How-

ever, revenue quickly decreased because of a

lack of control over the fickle interests of do-

mestic (Taiwan) citizens.

Subsequently, Wowprime established

an all-you-can-eat National Steak House in

1993. However, a lack of understanding of

the restaurant business resulted in financial

losses, which subsequently caused the restau-

rant to rapidly lose business. In November of

the same year, Wang Steak, an up-scale steak

restaurant was established under the largest

corporation in Taiwan: Formosa Plastics

Group. Adopting the marketing practice of

applying unique private guest house receipts

and serving Chinese-style well-done steaks

created new business opportunities for

Wowprime.

Upon market stabilization and succes-

sive branching, Wowprime further devel-

oped five major business areas including

Mongolian Whole Sheep Barbecue, No. 1

Zongzi, the Guinness World Records Mu-

seum, and former theme parks. Thus,

Wowprime has become a multibusiness

group involved in the catering, leisure, and

recreation business industries.

However, industrial hollowing occurred

after a series of events including an economic

crisis in 1997, known as the Asian financial

crisis, reduced consumer intentions caused

by the 1999 921 earthquake that produced a

7.3 on the Richter scale, and accelerated out-

flow from Taiwanese manufacturers to China

that began in 2000. This domino effect nega-

tively affected economic growth, which was

the first time this had occurred over the pre-

vious 30 years in Taiwan. The catering indus-

try, which has traditionally been considered

as a domestic demand industry, was also in-

evitably influenced by this negative effect on

the economy. Consequently, Wowprime’s

overall revenue between 2000 and 2001 de-

creased by 25%. In 2000, Wang Steak, which

persisted in the high-priced business market,

was forced to consecutively close three

branches and layoff 50 staff members; em-

ployees throughout the company were un-

easy during this period.

Turnaround Process

Under unstable operating conditions

caused by simultaneously managing com-

pound diversified businesses, Wowprime’s

executives made the following decisions re-

garding the future direction of the company:

(1) Retain the currently profitable

vertical brand extension strategy in

multibusiness operations (i.e., retain the

individual operation of the low-priced

No. 1 Zongzi restaurant and high-priced

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 70

Wang Steak establishment).

(2) Eliminate the relatively less

profitable brands and retain the thriving

Wang Steak brand as the brand exten-

sion strategy (focused cultivation).

Through debates and discussions in the

company’s “Central Standing Committee”

(an imitation of the Kuomingtang’s highest

decision-making mechanism, which com-

prises high-level group executives above the

level of directors who form a collective lead-

ership system and serve as the company’s de-

cision-making center), a final resolution was

established, which was to retain the brand

that demonstrated optimal performance and

the greatest prospective profit, Wang Steak,

and quickly close and sell the other four still-

profiting business bodies within a year. The

entire corporation cut back and concentrated

on Wang Steak operations by immediately

conducting a series of thorough and in-depth

standardized operations in which McDon-

ald’s efficient training structure and The Lan-

dis’s (domestically renowned for their high-

quality services) unique service philosophy

was fully imported.

Thus, the storefronts were divided into

six sections, which comprised scheduling,

training, maintenance, ordering, reception,

and administration. Additionally, Wang

Steak has an internal culinary department,

which is absent at the McDonald’s Corpora-

tion. Conducting focused operations enabled

Wang Steak to stay quiet and make adjust-

ments without opening additional restaurants

for over a year. Consequently, from the orig-

inal seven restaurants established in the

struggle for expansion, Wang Steak suddenly

expanded to 14 branches. This enabled

Wowprime to establish an unreachable lead-

ing status in the industry of domestic high-

priced steak restaurant chains.

Turnaround Analysis and

Propositions

Since the company was established,

Wowprime has adopted compound diversifi-

cation operations by combining the amuse-

ment park business with the catering indus-

try. Upon the formation of a diversified busi-

ness body, Wowprime ceased to encounter

the strategic competitiveness problem faced

by single companies, and instead pursued the

overall comprehensive performance of a

group operation within each business body.

Therefore, diversified companies must

plan various aspects of establishments and

extensions including resource distribution,

future development directions, and core com-

petitiveness from the company perspective as

a whole instead of simply opportunistically

seek and identify solutions.

The initial development of Wowprime

involved continual setbacks because of inef-

fective strategies, maladministration, im-

proper resource configuration, as well as the

lack of and inability to establish core compe-

tences in a timely manner. Therefore, if di-

versified operation is to be adopted in com-

pany strategies, the resource distribution and

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 71

comprehensive performance coordination

and creation between business units must

first be determined. In addition, coordination

with the original group constitution and stra-

tegic requirements must be considered prior

to choosing and developing new businesses.

Therefore, through group decisions, the

company decided to focus on a single restau-

rant brand in the company expansion strat-

egy. Organization resources were compiled,

the process of establishing core competence

began, and irrelevant business bodies were

eliminated within a year. Moreover,

Wowprime could no longer solely rely on op-

portunistic wealth for its long-term survival

and instead had to depend on a set of feasible

chain replication operation models (core

competence) to maintain profits and establish

a competitive edge. Thus, McDonald’s train-

ing, grouping, and operation structures and

The Landis’s service concept were intro-

duced to achieve “backend process industri-

alization and frontend service customeriza-

tion.” This has substantially increased cater-

ing quality, customer satisfaction, and opera-

tional efficiencies. Moreover, prior limita-

tions on up-scale steakhouse store counts

have been overcome, which followed the

sudden expansion to the highest number of

high-priced steakhouses in Taiwan.

Proposition 1-a: When the company encoun-

ters drastic changes in external opera-

tion environments that result in poor

internal profits and operation crises,

reform strategies must be immediately

executed to restore operational perfor-

mance and make a fresh start.

Proposition 1-b: Company operational re-

form strategies must implement the

necessary control and reduction of

company assets and overhead costs be-

fore pursuing increased revenue.

Antecedents of the Second

Turnaround

Ninety-nine percent of approximately

100,000 restaurants registered in Taiwan

have turnovers below NT$100 million. These

restaurants primarily belong to small and me-

dium corporations or common micro-entre-

preneurships. Notable restaurants operate un-

der famous regional or local brands. From the

market perspective, various domestic cater-

ing patterns are readily available; thus, alter-

natives can be easily selected. Additionally,

other retails and retailers (i.e., convenience

stores, wholesale stores, and superstores)

successively provide cooked food and ready-

to-eat food products (e.g., microwave meals

and meal packs). The successive entrance of

these businesses divided the market and

caused intense competition within the restau-

rant market. This caused a common effect in

the industrial environment to occur, in which

entrance requirements are low and employee

turnover rate is high.

After a total transformation was

achieved after a year of focusing on restau-

rant businesses, Wowprime established oper-

ation models of restaurant management and

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 72

systems. In addition to the gradually satu-

rated domestic high-priced steak market, the

operation risks and future development

against intense domestic competition and

various possible considerations such as up-

flowing internal talents have become chal-

lenges that the company must consider exten-

sively.

Turnaround Process

The process of retaining talents and in-

creasing the internal strength of the company

while expanding external development led

President Day to recollect the qualities of the

Cantonese dragon dance, which features

uniquely styled dragons dancing on a stage

that attracts the attention of the crowd and

motivates the dancers through cheers. This

type of motivation can be observed in the

field of business and results in a company’s

external growth and staff members’ internal

entrepreneurship. In 2001, the Lion Dance

Project was promoted to implement

Wowprime’s new internal entrepreneurship

plan.

In this plan, the president identifies tal-

ents with entrepreneur qualities and charac-

teristics in the group and provides them with

a business stage on which to develop their

own restaurants. Moreover, multibrand ex-

pansion is supported by the company’s inter-

nal resources. Thus, the core concept of the

Lion Dance Project is to continually replicate

success experiences achieved by the brand

and the operation of Wang Steak and adopt

the multibrand direction. In summary, all

staff members in the Wowprime group have

the opportunity to become the company’s

shareholder; through the Lion Dance Project,

everyone has the opportunity to engage in in-

ternal entrepreneurship in this group.

Vice President Chen, who exhibited the

most courage and enthusiasm as an entrepre-

neur, became the group pioneer who created

the mid-scale Western steak establishment,

TASTy, and became the first lion king to suc-

ceed in entrepreneurship. The following

year, General Manager Wang, who managed

the company’s staff department operations,

established Tokiya, which is primarily based

on creative Japanese cuisine. Within the

same year, another general manager, Lee,

traveled to the United States and established

Porterhouse Bistro in Beverly Hills and initi-

ated overseas business on behalf of

Wowprime. In 2003, Vice President Chen es-

tablished Wang Steak in China by success-

fully opening the first restaurant in Shanghai.

The encouragement of domestic and in-

ternational entrepreneurship success pro-

vided by the first-generation lion kings

prompted the company to proceed with the

second phase of the brand placement process.

In 2004, General Manager Tsao established

Yakiyan, which features table grill. Subse-

quently, Giguo, a Hokkaido kelp pot restau-

rant, was established by General Manager

Lee, who already had entrepreneurial experi-

ence. In the following year, General Manager

Wang introduced ikki, which offers creative

Japanese kaiseki cuisine. In the same year,

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 73

Chief Financial Officer Yang, who had an ac-

counting background, successfully estab-

lished the Chamonix, a teppanyaki restaurant

based on the demand for a romantic French

setting.

Encouraged by the Lion Dance Project,

Wowprime expects two new innovative pat-

terned restaurant brands to be introduced

within 2 years. Through this plan, new lion

kings (new brands) and lion king candidates

(determined by the president; a year is re-

quired to plan a new brand) will successively

emerge every year.

Turnaround Analysis and
Propositions

In the turnaround scenario, Wowprime

adopted the Lion Dance Project’s turnaround

strategy. The characteristics of the project are

multibrand derived product differentiation,

market segmentation, and company growth

strategies integrated with the internal entre-

preneurship system. Thus, Wowprime

adopted entrepreneurial oriented strategies

focused on reorienting the product market

and increasing revenue.

The actual processes conducted in the

Lion Dance Project involved the chairman

selecting the company’s most capable entre-

preneur and the most courageous staff mem-

bers who would dare to produce innovations

to create new restaurant brands and engage in

restaurant expansion. The company head-

quarters provides support in operation man-

agement including production, sales, human

resources, research and development, and fi-

nance. Additionally, tacit knowledge is trans-

ferred and learning curve effectiveness is en-

hanced through cross-holding, collective de-

cision making, and the sharing of experi-

ences with branch expansion among various

branches. This increases the company’s

economies of scale and expands the econo-

mies of scope of the operation types.

In summary, this is a strategy in which

entrepreneurship opportunities are increased

during the entrepreneurship process. Addi-

tionally, financial and management operation

risks are minimized and prevented to achieve

the up-flow of various levels of internal staff

members and external lateral expansion to in-

crease the number of additional startup busi-

nesses.

Proposition 2-a: Strategic turnaround strat-

egies must focus on reorienting the

company’s product market, developing

niche markets, and integrating internal

resources for maximal utilize.

Proposition 2-b: Strategic turnaround strat-

egies can be combined with the com-

pany’s internal entrepreneurship system

and become an entrepreneurial-oriented

strategy.

Strategic Implications for Both

Turnarounds

Wowprime’s reform response strategy

was inspected and verified in this study. In

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 74

summary, the two response strategies en-

countered by Wowprime verified Allaire’s

(1985) results. Based on current conditions

and the degree of coordination in future en-

vironments, decision makers must determine

the degree of influence that company crises

exert on the organization during urgent

times. Table 1. describes the four major re-

form strategies of reorientation, transfor-

mation, turnaround, and revitalization and

the corresponding strategies used by

Wowprime.

Additionally, the results of this case

study agreed with those of Lee (1987), in

which crisis response strategies were divided

into the three basic strategies of reduction

(discard useless portions and keep essential

portions), restructuring (focused operation

and internal entrepreneurship), and growth

(multibrand, multiproduct, and multimarket).

The steps executed in these strategies also

conformed to and coordinated with the three

processes (i.e., withdrawal, strengthening,

and progress) executed in crisis response.

Proposition 3-a: During crisis response, the

company can execute responses to

changes in crisis during the with-

drawal, strengthening, and progress

periods.

Proposition 3-b: During the strategic pro-

cess of crisis response, the company

can respond to changes in crisis during

the three strategic-reform periods of

reduction, restructuring, and growth.

Corporation bodies are not solely man-

agement units but centers of resource pool-

ing. The resource distribution and application

timing are decided through management

strategies. If firm executives can adopt suita-

ble strategies, corporation resources can be

fully used to initiate corporate growth. Thus,

support for corporate growth can be provided

by managers who wish to fully use the com-

pany’s current resources to enhance organi-

zational performance. Furthermore, strategic

choices and changes can reflect the develop-

ment of an organization over time. Managers

who consider the limitations of the existing

business scope or are motivated by various

strategic intentions choose specific strategies

to sustain corporate growth.

Proposition 4: The leadership pattern and

style of the company’s entrepreneurs can be

adjusted in accordance with differences in

companies’ organizational process.

Conclusion

Based on the aforementioned research

results, the following conclusion and recom-

mendations (consisting of three points de-

rived from the implications of practical oper-

ations) are proposed.

First, a standard model for new prod-

ucts and market operations should be estab-

lished as a basis for replicating brands by

systemizing and establishing ability and ex-

perience transfer mechanisms. In addition,

various standard operating procedures in-

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 75

volving the use of the most suitable operat-

ing methods, determined through the expan-

sion process, should be established as a ba-

sis for future internationalization. Before the

domestic market becomes saturated, over-

seas markets and internationalization pro-

cesses should be planned and platforms

should be simultaneously provided to core

executive members for enhancing future

Table 1. Key reform strategies and the corresponding strategies in the Case Study

Reform strat-
egy

Status Characteristics

1. Pro-
gressive
change

Harmony,
consistency

� Organizational strategy matches the current
environment and can be used to predict future
environmental changes.

2. Tempo-
rary
change

Temporary
imbalance

� Organizational strategy cannot match the
current environment, which causes a tempo-
rary decrease in performance level. However,
the strategy adopted by the organization
matches future environmental changes, and
current environmental changes are temporary
when organizations do not require to make
substantial changes to their current strategic
directions.

3. Trans-
formation
or reorien-
tation

Transfor-
mation or re-
orientation

� Organizational strategy matches the current
environment and provides satisfactory perfor-
mance, but the organization predicts drastic
changes in future environments (i.e., fluctuat-
ing competition in the international and do-
mestic catering industry, deregulation in
China). Organizations quickly respond to envi-
ronmental changes to maintain a competitive
edge and sustain growth.
� Wowprime case: Organizational strategy
based on various operation models or the
transfer of portions of company resources to
attractive target markets or industries.

4. Revital-
ization
and turna-
round

Turnaround,
revitalization

� Organizational strategy cannot match the
current environment and performance (perfor-
mance declines) and cannot be used to coordi-
nate future environmental changes. A lack of
immediate improvement can result in survival
crisis. Thus, the organization must adopt
timely response actions to prevent further de-
terioration and reverse situations.
� Wowprime case: The Lion Dance Project
turnaround strategy.

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 76

prospects and realizing personal goals. This

can increase the input of organizational com-

mitments. Moreover, the leadership pattern

and style of company entrepreneurs can be

adjusted in accordance with the varying or-

ganizational process of companies.

This study was limited to partial subjec-

tive classification for the growth period of an

individual corporation, and limited by the in-

ability to gain insight into the actual deci-

sion-making process of firm executives.

Nevertheless, the study provided the follow-

ing contributions: In addition to integrating

the currently constructing theory of the entre-

preneurial process and determining the vari-

ous resources required in specific growth pe-

riods of the corporation, the results of this

study expanded the research on organiza-

tional growth, which primarily concerns the

evolution of firm capabilities.

Second, we followed Ahuja and Lam-

pert (2001) introduced their suggestion and

disregarded positivistic research programs

(i.e., causality is determined using variables

and hypothesis verification). By contrast, a

historical review and analysis explanation

from an overall perspective was conducted to

investigate mutual relationships between so-

cial contexts and corporation actions taken

by corporations during strategy changing

processes. Regarding management implica-

tions, this study confirmed and further em-

phasized the long-valued corporation unique-

ness of corporations in the strategic field.

This revealed strategies adopted by corpora-

tion organizations, on which the in-depth in-

fluences were influenced by factors such as

operational background, historical tracks,

company resources, and strategic intentions.

Therefore, strategic growth is also path de-

pendent and reflected to a certain degree by

the company’s various strategic development

tracks.

Third, relevant directions for future

studies are recommended as follows.

First, Ahuja and Lampert (2001) proposed

that procedural studies can be summarized

based on three methods: procedures can be

considered as (a) causal relationships be-

tween variables; (b) personal or organiza-

tional conceptual scopes; and (c) a historical

record describing changes caused by certain

events. As presented in this study, the third

method allowed enabled researchers to di-

rectly and entirely describe changing pro-

cesses of that occur during events. However,

relevant studies are scarce and, therefore, un-

warranted, which awaits scholarly commit-

ments.

Second, this study adopted a procedural per-

spective and qualitative methods to investi-

gate topics concerning corporate growth and

strategy change. However, researchers must

understand that the variation theory remains

crucial in the study of management. Thus, the

causal relationship between development and

measures of corporate growth variables (i.e.,

using independent variables such as opera-

tional background, organization

The International Journal of Organizational Innovation Vol 7 Num 2 October 2014 77

paths, resource requirements, and strategic

intentions as causes and dependent variables

such as strategic choices and changes as ef-

fects) remains a viable research direction.

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The International Journal of Organizational Innovation Vol 8 Num 3 January 2016

282

INNOVATIVE THINKING OF FOOD SAFETY MANAGEMENT FOR
TRADITIONAL BAKING INDUSTRY IN TAIWAN –

YU JAN SHIN THE BUTTER SHORTBREAD

Han Sheng Lei
Department of Business Administration,

National Yunlin University of Science & Technology, Taiwan ROC
hslei@yuntech.edu.tw

Su Chuan Chang*

Department of Business Administration,
National Yunlin University of Science & Technology, Taiwan ROC

(Corresponding Author)* luan9@mail2000.com.tw

Abstract

Yu Jan Shin, a pastry baking business in Taiwan, has been operated for a half century and
proud of the products with high production quality. Nonetheless, it unprecedentedly
dropped into the food safety issue in 2014. The 1% miss of fried shallot spice

incident

has the enterprise immediately became the topic of public discussion in the media report.
After the 10 – day return storm and the crisis of financial bankruptcy, Chen Yu – Hsien,
the second – generation manager and the chairman & general manager, led the family
management team to rapidly recover the normal business operation of retail sales. How
do they grow together and face the food safety issue together, turn peril into safety to
present the magnificence of butter shortbread in Dajia, and round off the incident by go-
ing through the food safety issue without doing “face losing” things? This study contrib-
utes to provide several models, which are worth learning for the financial management,
quality management, customer relationship management, family business management,
and corporate social responsibility in the crisis management, of the case company, in
spite that it is a small family business.

Key words: baking industry, family business, food safety management, crisis manage-
ment, enterprise value

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283

Research Background

In such an era, when various in-
formation industries of information,
network, computer, video, and elec-
tronic media are advanced, global dis-
asters or major events are immediately
delivered to the world. Such crisis in-
cidents test the response and manage-
ment abilities of local governments,
enterprise organizations, or institutions.
In face of technology replacing tradi-
tion and machinery substituting labor
in baking industry, it is necessary to
invest in time and efforts for continu-
ously maintaining the competitiveness.
The engagement of industries in the
baking market results in the fierce
competition. The factors of increasing
raw material costs, inadequate labor
force, increasing wages, and prosperity
fluctuation have food – related busi-
nesses encounter great difficulties.
High business costs and low product
price are not common phenomena.
Increasing store rental and indirect
costs are also the operation dilemma
for businesses. The emergence life-
styles of e – generation enhance the
changes of consumer habits. Further-
more, the enhancing consumer aware-
ness of environmental protection and
health has the request for products con-
stantly improving from production
process to innovative technology R&D
and broadening to those strict regula-
tions and rules that need to be fol-
lowed. In the changeable and compli-
cated global business environment,
crisis management has become the
essential management skill for enter-
prises and professional managers as
well as the professional knowledge for
public relation practitioners. Especial-

ly, an enterprise in Taiwan, where con-
sumer rights and corporate image are
emphasized, faces various possible
crises, which are closely related to sus-
tainable management. In this case, un-
der the internal and external environ-
mental pressure, a corporate manager
has to present the idea of crisis man-
agement. Enterprises have established
public relation practitioners and crisis
management team in past years to face
crises and cope with crisis issues in
order to predict and prevent crises in
possible ranges and rapidly propose
coping strategies and regularly simu-
late various crises to train internal em-
ployees’ coping capacity.

In consideration of consumers’
concern of food safety resulted from
the requirement for self – health aware-
ness and the lifestyle to eat healthily,
consumers’ crisis awareness is con-
stantly enhanced and the request for
food safety sanitation and the

sources

become a concerned issue of the pub-
lic. Relative to consumers selecting
food for personal preference and health
considerations, food safety is also em-
phasized. Accordingly, this study in-
tends to discuss the food safety man-
agement in traditional baking industry
in Taiwan.

Literature Review

Definition of Crisis

Karl (1982) proposed four charac-
teristics for crises, covering the inclu-
sion of an important turning point to
result in different incident develop-
ment, making certain decisions, at least
a major value being threatened, and

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284

being determined under time pressure
(Chu, 2002). Ler – binger (1997) point-
ed out crises as the potential threats to
the future profitability, growth, and
even survival of a company, with the
characteristics of a manager being
aware of threats and believing that such
threats would hinder the development
of the company, an organization being
aware that the situation would get
worse and be irreparable when no ac-
tion is adopted, and the sudden encoun-
ter of an organization (Chu, 2002).
Fearn – Banks (1996) defined that cri-
ses were the major event which could
result in potential negative effects on
an organization or an industry; such an
incident could influence the organiza-
tion’s publicity, product, service, or
reputation to impact the normal opera-
tion and even threat the survival
(Coombs, 1999). Huang et al. (2009)
considered that crises presented the
properties of stage, threat, uncertainty,
and urgency. Liu (2004) divided the
characteristics of crises into incident
suddenness, time management urgency,
institutional threats, management
chance, and universality.

Crisis Management

Crisis management, referring to
the management of crises and the re-
duction of damage, aims to avoid or
reduce the negative results of crises
and protect institutions, personnel, or
enterprises from being damaged. Fink
(1986) defined crisis management as
the continuous and dynamic manage-
ment process, which focused on proac-
tive management and discontinuous
learning mechanism. Fink (1986) indi-
cated that effective crisis management

should contain prediction of crises,
establishment of crisis responses, early
discovery of crises, keeping away from
crises, face of crises, and good interac-
tion with media. Huang (2004) divided
crisis management into the detection of
crisis message, preparation and preven-
tion of crises, control and management
of crisis damage, recovery from crisis,
and afterward review and learning. Wu
(2002) regarded crisis management as
a critical issue for an organization after
the occurrence of crises, and an enter-
prise’s crisis management ability as the
test of the sustainable management.
The factors in frequent crisis incidents
and the expanding influence on an or-
ganization contain 1.the report of mass
media accelerating the spread and im-
pact of crises (Cohn, 2000), 2.the ad-
vance of technology hastening increas-
ing crises and risks (including human
operating losses and technology risks)
in an organization (Covello, 1992 ),
3.globalization resulting in organiza-
tional changes, including the risks of
business expansion, merge, restructur-
ing, lay – off, and even close – down
(Augustine, 2000 ), 4.increasing re-
quirements and monitoring of the pub-
lic for the government, political fig-
ures, and various organizations reduc-
ing personal mental and moral ac-
ceptance of risks (Ogrizek & Guillery,
1999), 5.promoting public rights to
strive for personal equity and express
dissatisfaction to governmental de-
partments or enterprises through law-
yers and legislators for the deserved
welfare, and 6.the advance of Internet
allowing crisis incidents instantly
spreading to the world and causing
challenges in crisis communication and

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285

management (DiFonzo& Bordia,
2000).

Food Safety

Food safety refers to food for hu-
man health (Chang, 2011). Chen (2011)
defined it as to guarantee the safety of
food, without poisonous or harmful
materials, ensure food being produced,
processed, stored, and sold in proper
environments, and reduce pollution at
different stages so as to guarantee con-
sumers’ physical health. Grunert (2005)
regarded food safety as a primary con-
sideration in food policies to affect
consumers’ choice of food. Food poli-
cies could be combined with other fac-
tors, such as the safety of microorgan-
ism and animal diseases (Mad Cow
Disease and Foot – and – mouth Dis-
ease). The use of food additives, chem-
ical pesticide, chemical, preservative,
and hormone in vegetables, fruits, and
processed food in the agricultural in-
tensification process was the major
food safety issue (De Jonge, Van Trijp,
Goddard & Frewer, 2008; Mergenthal-
er, Weinberger & Qaim, 2009). In addi-
tion to freshness, flavor, and nutrition,
sanitation and safety were also the fac-
tors in food quality (Wu, 2010). In ei-
ther media or academic circles, food
safety has attracted more concerns, and
the risk of food pollution has become
globalized. Meanwhile, consumers pay
more attention to the sources of food
materials, safety, and authenticity. Such
potential risks in food safety or food
sanitation problems have food – related
value and choice become complex.

Research Methodology

With Case Study, a special enter-
prise was selected as the subject for
collecting data and analyzing problems
according to the antecedents. Yin
(1994) regarded Case Study as an em-
pirical survey applied to unobvious
limits between research phenomenon
and real environments. The characteris-
tics covered to deal with specific issues
or variables and relied on multiple data
sources to explain the research phe-
nomenon. The studied subject about
food safety issues in traditional baking
industry in Taiwan is a specific phe-
nomenon in baking industry. Research
on such a phenomenon is rare current-
ly. The content, to some degree, is the
pioneering. The collected data through
Case Study could present the causal
relation and critical factors in details.
According to the key incident, the food
manufacturer and the employees of Yu
Jan Shin are proceeded the pre – de-
signed structural interview in order to
present the participants’ responses to
the same question.

Case Description

When the food safety issue of
Ting Hsin oil emerged, the highlighted
media reports in Mainland China, and
even European and American countries
resisted to food safety in Taiwan, Dajia
Yu Jan Shin, famous of butter short-
bread, actively and rapidly started the
strict “quality safety mechanism” for
self – examination on September 5th.
The continuous incident of cooking oil
made of cooked waste resulted in me-
dia reports boiling in the entire island.
To reduce consumers’ doubts, 8 lard –
oil made products were automatically
taken off shelves for the prevention on

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286

September 13th; the product materials
were publicly explained on

September

14th, including (1)egg and milk vege-
tarian products (about 98.7% sales vol-
ume): natural butter (Anchor butter
imported from New Zealand) +flour
+sugar+others, (2)”fried shallot” prod-
ucts, and (3)non – vegetarian with fried
shallot products (about 1.3% sales vol-
ume): lard oil (Cheng – Yi pure lard oil,
non – lard oil)+fried shallot (Cheng
Agricultural Product Store) – Fangfu
(pure lard oil+green onion)+other ma-
terials; it automatically reported to
Health Bureau of Tai

chung City Gov-

ernment on the same day that the used
Cheng’s fried shallot seemed to have
cross infection during

production.

Health Bureau immediately went for
the investigation. The owner explained
on the media that total six lard – oil –
used products “seemed” to be polluted,
while the famous product “butter
shortbread” was not influenced as it
used butter. Since food safety is a key
factor in the industry, it is the most
important product quality for the busi-
ness management of Yu Jan Shin. The
annual food sanitation education in-
tends to build correct food sanitation
concepts of the personnel. What is
more, the constant examination and
communication to continuously im-
prove problems reduce the damage
caused by bad sanitation down to the
lowest.

Apple Daily real – time reported
on September 15th that

Chang Guann

Co. recycled cooling oil made of
cooked waste to produce bad – quality
lard oil and was suspected to import
animal feed oil from Hong Kong to
produce edible oil. It resulted in the

second food safety crisis. Food and
Drug Administration further announced
several problematic products with the
list up to 183 items after the investiga-
tion; Yu Jan Shin was also influenced.
Several media further reported the lat-
est list of products using Fangfu lard
oil and Chang Guann oil;

Cheng’s fried

shallot also appeared in the list. Chen,
the chairman of Yu Jan Shin, stated that
Cheng’s oil was confidential in the past
20 – year cooperation and was sur-
prised with the cross pollution. After
receiving Cheng’s information, the
products with fried shallot were taken
off shelves and stopped production and
automatically reported to the sanitation
unit. Chen emphasized that the egg and
milk vegetarian products, e.g. butter
shortbread, were made with Anchor
butter from New Zealand, without lard
oil and fried shallot, that consumers
could be confident. The owner of
Cheng Agricultural Product Store indi-
cated that he asked Fangfu to offer
evidence of not using Chang Guann’s
cooling oil made of cooked; unexpect-
edly, the uncleaned pipes were suspect-
ed to mix such oil with the pure lard
oil. The products were therefore taken
off shelves, and total 68 buckets of oil
were recycled by Fangfu. In the food
safety crisis management process of
fried shallot, Yu Jan Shin automatically
reported to the sanitation unit promptly
and practically and “sincerely” used
the self – produced lard – oil fried shal-
lot for the products on October 8th, and
the products were 98.7% made with
“Anchor natural butter from New Zea-
land” on October 18th. Among the an-
nual 195 tons purchase, self – made
lard oil and fried shallot were merely
used in few products. The information

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287

was announced on the official website
of the company.

Effects Of Media On Food Safety
Issues

Although the media reports
provided consumers with more space
and rights to know in the fried

shallot

incident, the audience measurement
guided random exposure of extreme or
unproven information. It was wondered
if the incident parties were objectively
concerned, whether larger unnecessary
social panic and turbulence were in-
duced, and how journalists were regu-
lated. Business Today reported on Vol-
ume 935 that Yu Jan Shin family busi-
ness was proud of not doing “face los-
ing” things, but it was criticized be-
cause of Chang Guann oil incident in
the previous September. Not only did
the owner become the public target, the
employees also became the focus. The
management team described the expe-
rience in the incident that the media
reports in Taiwan revealed lots of incit-
ing speeches and threats to the parties
and continuously expanded the issue to
have the public be threatened in the
uneasy environment.

In short, the public has to pay for
the generation and management of so-
cial incidents. Consequently, people
should be responsible for taking the
lessons and avoiding the reoccurrence
in order to share the healthy society
and economic prosperity.

Crisis Management Inspiration And

Enterprise Value

Yu Jan Shin, operated for a half
century, is a famous bakery in Dajia
because of the carefulness from the
materials to the production of pastry.
Unfortunately, the old bakery suffered
from the recycled oil issue. To avoid
similar crises in the future and to step
toward excellence with quality, not
only does the management team have
to make efforts, the customers also
expect to continuously share the fa-
mous pastry in Taiwan. To follow the
family property, the “butter shortbread”
has to sincerely use “natural butter”.
The natural butter shortbread, which
was 5 times higher price than those
with artificial butter, seemed to be a
fool decision; however, it was a wise
and far – sighted action and established
the “sincerity” and “responsibility” of
Yu Jan Shin (Yu Jan Shin, 2014). The
enterprise value appeared on the em-
ployees being able to unite and fight
with managers to resolve crises with a
happy ending. In sum, going through
the fried shallot incident was a major
disaster for Yu Jan Shin in the five dec-
ades. Although it was satisfactorily
rounded off, the management team,
especially the chief executives, devel-
oped the abilities after the impact.
However, there were still recovery,
including the reconstruction of morale
and the reengineering of overall quali-
ty. Starting from a stall in front of the
temple, it experienced the deserted
dilemma to an old brand with the an-
nual revenue up to several hundred
million dollars in the half century. The
consumers do not simply buy the flavor
of butter shortbread, but the emotion
between both parties generates from
none to some, from main streets to
alleys, and from implicit to explicit,

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288

Table 1. Major fried shallot crisis incidents

Date Incident Management Effects on businesses

Relevant

personnel to

incident
September

Chang Guann

oil polluted

The government

examined the oil

sources

Confirmed the safety

Purchase

and produc-

tion de-

partment

September

Cheng Yi lard

oil suspected

to use animal

feed oil

Taken off shelves

and stopped pro-

duction for the

prevention

Retail sales closed and stopped

production
All staff

September

Cheng’s fried
shallot

Automatically

reported to Health

reau of Tai-

chung City Gov-

ernment, and

used Cheng’s

fried shallot was

suspected of cross

infection during

production.

Lard – oil – made products were

urgently taken off shelves, in-

cluding cheese sesame pastry,

green – bean cake, oil – skin

skewed meat, skewed meat bean

cake, salty cake

Health Bu-

reau of Tai-

chung City

Government

September

Started return

and refund

Both on – site and

communication
Return and refund

All staff and

customers

October 8

Secure infor-

mation an-

nouncement

Sincerely self –

produced
Lard – oil fried shallot consumers

October 18

Secure infor-
mation an-
nouncement

Oil use
98.7% Anchor natural butter

from New Zealand
consumers

Data source: Self – organized in this study from YU Jan Shin (2014a

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289

covering priceless customer loyalty and
integrating managers’ sincere concerns
about products. Unexpectedly, the food
safety issue resulted in the brand expe-
riencing great test. After the training
day of “double compensation”, it was
concerned how the chairman led the
family management team to the stable
and quality business. It is believed that
there must be something left at some-
where people had been through. The
fried shallot incident had the manage-
ment team and the customers perceive
“heartfelt” in between; and, the com-
pany actively informed the consumer
for return but was refused by the cus-
tomer and received the comfort to pre-
vent the finance from dilemma. The
brand director Chen Yu – min pointed
out the double control of production
after the fried shallot incident, includ-
ing:

(1) Control of raw materials: Lard oil

and fried shallot were self – pro-
duced, the suppliers were re-
quested to provide traceability of
pork, and the preservation and
use safety of goods were whole –
day controlled.

(2) Regular and irregular visit and

inspection of suppliers: To ensure
the stability and security of mate-
rial quality.

(3) Introduction of monitoring sys-

tem in all plant: The production
personnel, machine, materials,
environments, and operation
were 24 hour controlled and
would be completed in July,
2016.

(4) Reinforcement of food safety
center: The self – inspection cen-
ter was established with expand-
ed function and permanently co-
operated with professors in food
department in Hung Kuang Uni-
versity (the past inspection sys-
tem completely depended on the
government – approved SGS sys-
tem).

(5) Strict request for traceability

from suppliers: It was expected
that the customers could realize
the material source of each prod-
uct for consumers’ safety and
health.

Reviewing the return of fried shal-

lot, it could be reflected that although
Yu Jan Shin was a small – scale enter-
prise, the manpower in the return pro-
cess was orderly arranged and the fi-
nancial management was smoothly
operated. With the practice of man-
agement system, the return process
from the opening of receipts, the check
of products, and the flexible mobility
of personnel could be rounded off
within 10 days. Such a management
model led several models for learning
management in the incident.

Conclusion

Yu Jan Shin learned the lessons

(1) of how to interact with media and
(2) that an enterprise should be well
managed and be the optimal state, from
the experience in the fried shallot inci-
dent. In the incident, if it was not the
ordinary practice of systems and man-
agement, it would have to introduce
expert guidance, like Nomura Research

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290

Institute, and actively apply the gov-
ernmental resources to build the solid
business. Moreover, the family man-
agement team collaboratively resolved
crises day and night to recover the
business within few days from the ma-
jor food safety disaster. The fried shal-
lot incident was not purposively
caused, the sincere and active behav-
iors appeared great difference from the
evasion and cheating of other enter-
prises for the food safety crisis man-
agement and the managers sought
nothing but profits. A lot of enterprises
therefore were ruined and could not
survive; but, Yu Jan Shin relatively
provided the optimal model.

Yu Jan Shin replaced traditional

lark – oil shortbread with natural butter,
which not only made the famous “but-
ter shortbread”, but also famed of the
hometown of butter shortbread. During
the time, the management team was not
afraid of failure, learned from doing
and did from learning, and continuous-
ly researched and innovated to accu-
mulate decades of baking experiences.
The insistence on raw materials and
quality created fresh brand image on
the consumers. Butter shortbread is not
simply made with real materials, but
the delicious flavor reveals culturally
inherited pastry in Taiwan. The cus-
tomers could perceive the steady busi-
ness of Yu Jan Shin to support the em-
ployees with “heartfelt” in the crisis.
The enterprise value of Yu Jan Shin
was presented from the employees
sending the owner flowers, the em-
ployees uniting to fight for the dilem-
ma, and the customers showing trust
and consideration.

Yu Jan Shin is a traditionally
small family business. In the food safe-
ty issue, it is commendable to receive
support from the customers and the
employees and presents several models
for managers in other enterprises. Un-
der the firm business basis in tradition-
al pastry industry, how to avoid disas-
ters and expand excellent quality man-
agement is important for the sustaina-
bility of family business.

Reviewing the fried shallot inci-

dent, even the famous old store is
harmed (Yu Jan Shin website, 2015).
However, several unscrupulous enter-
prises have not been punished. It is
doubted whether people could get rid
of the fear of edible oil. Several causal
relations and effects on the food safety
issue are worth considering.

(1) What are the regulations and the

monitoring function of govern-
mental units and social groups?

(2) Consumer demands for cheap

goods result in enterprises misus-
ing or abusing food ingredients.
In this case, should consumer at-
titudes be changed?

(3) How to have an enterprise prac-

tice the business idea, rather than
being a slogan?

(4) How to awake corporate manag-

ers rooting and practicing busi-
ness ethics?

(5) An enterprise encountering crises

tests the management team. It is
the key in the organizational

The International Journal of Organizational Innovation Vol 8 Num 3 January 2016

291

management going through the
dilemma.

To sum up, sincere Yu Jan Shin
focuses on the cake art, combines his-
tory, culture, and local characteristics,
builds the brand on products, services,
activities, buildings, journals, and

stores, applies humanities and history
to inherit the family business, expects
to concern the society, deeply manages
the brand to improve the localization to
international vision, copes with the
Internet information in the practical
action of global village, and stabilizes
the international food stage.

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58
Journal of Marketin

Volume 77 (March 2013), 58 –77

Kathleen Cleeren, Harald J. van Heerde, & Marnik G. Dekimpe

Rising from the Ashes: How Brands
and Categories Can Overcome

Product-Harm Crises
Product-harm crises are omnipresent in today’s marketplace. Such crises can cause major revenue and market-
share losses, lead to costly product recalls, and destroy carefully nurtured brand equity. Moreover, some of these
effects may spill over to nonaffected competitors in the category when they are perceived to be guilty by
association. The extant literature lacks generalizable knowledge on the effectiveness of different marketing
adjustments that managers often consider to mitigate the consequences of such events. To fill this gap, the authors
use large household-scanner panels to analyze 60 fast-moving consumer good product crises that occurred in the
United Kingdom and the Netherlands and resulted in the full recall of an entire variety. The authors assess the
effects of postcrisis advertising and price adjustments on the change in consumers’ brand share and category
purchases. In addition, they consider the extent to which the effects are moderated by two key crisis characteristics:
the extent of negative publicity surrounding the event and whether the affected brand had to publicly acknowledge
blame. Using the empirical findings, the authors provide context-specific managerial recommendations on how to
overcome a product-harm crisis.

Keywords: product-harm crisis, product recall, defective product, purchase behavior, negative publicity, blame

Kathleen Cleeren is an Assistant Professor, Maastricht University (e-mail:
k.cleeren@maastrichtuniversity.nl). Harald J. van Heerde is Research
Professor of Marketing, Massey University (e-mail: heerde@massey.ac.
nz). Marnik G. Dekimpe is Research Professor of Marketing, Tilburg Uni-
versity, and Professor of Marketing, Catholic University Leuven (e-mail: m.g.
dekimpe@uvt.nl). The authors are indebted to AiMark for data access.
They also thank participants at the 2010 Copenhagen Emac Conference,
the 2010 Cologne Marketing Science Conference, the 2011 Jaipur Mar-
keting Dynamics Conference, and the marketing seminar series at Singa-
pore Management University for several useful comments. The second
and third authors thank the New Zealand Royal Society Marsden Fund
(UOW1004) for research support. Part of the article was written while the
third author was the Tommy Goh Visiting Professor in Entrepreneurship
and Business at Singapore Management University.

P
roduct-harm crises are omnipresent in today’s market-
place. Recent notable examples include Toyota’s world-
wide recall of more than seven million cars because

of technical problems, the melamine contamination in sev-
eral Chinese baby-formula brands, and Mattel’s toy recalls
because of a lead paint hazard. These crises can cause major
revenue and market-share losses and destroy carefully nur-
tured brand equity (Chen, Ganesan, and Liu 2009; Thiru-
malai and Sinha 2011). Moreover, a product-harm crisis not
only may be devastating for the affected brand but can also
affect the entire category when other brands are perceived
guilty by association (Roehm and Tybout 2006). Because of
the increasing complexity of products, more stringent prod-
uct-safety legislation, and more demanding customers,
product-harm crises are expected to occur ever more fre-
quently (Dawar and Pillutla 2000).

When faced with a product-harm crisis, managers need
to make informed decisions on their marketing variables to
attenuate the negative impact of the crisis. In summer 2006,
several Cadbury chocolate products had to be withdrawn
from the U.K. market because of a serious salmonella cont-
amination. While the brand’s relative price remained at a
comparable level, management dramatically increased its
advertising support, leading to 30% more share of voice in
the postcrisis year. When Princess, a canned pilchards
brand, had to be removed from the shelves because of a
packaging fault, it also increased its advertising support
substantially. However, it also increased its relative price by
more than 25%, perhaps in an attempt to recoup lost reve-
nues. In contrast, when a plastic contamination led to the
recall of candy manufacturer Basset’s milky-baby lollies,
Basset followed an entirely different strategy of decreasing
both its advertising share of voice and its relative price.
While there is increasing research interest in the impact of
product-harm crises, little empirical evidence is available
on the relative effectiveness of these different recovery
strategies (Liu et al. 2012).

There is an extensive literature stream (which uses
mostly experiments and/or surveys) that focuses on how
consumers deal with the negative publicity typically sur-
rounding product-harm crises (see, e.g., Ahluwahlia,
Burnkrant, and Unnava 2000; Griffin, Babin, and Attaway
1991) and/or how consumers are influenced by blame attri-
butions (e.g., Dutta and Pullig 2011; Klein and Dawar
2004). Research on the impact of these factors is important
given that not all companies choose to take the blame in a
crisis context, and the amount of negative publicity sur-

rounding a crisis can be very different. Although both Cad-
bury and Basset acknowledged that they were to blame, the
amount of negative publicity surrounding the crises differed
substantially: whereas the Cadbury crisis was covered in all
major U.K. newspapers, the recall of Basset’s milky-baby
candy was only picked up in one. Although previous studies
have discussed the impact of both crisis characteristics
(blame and publicity) on postcrisis consumer attitudes and
behavior, they remain agnostic with regard to what extent
managers should adjust their marketing variables depending
on these crisis characteristics.

Another set of studies uses empirical purchase and sales
data to assess how the effectiveness of advertising and/or
price changes due to a crisis (see, e.g., Cleeren, Dekimpe,
and Helsen 2008; Van Heerde, Helsen, and Dekimpe 2007;
Zhao, Zhao, and Helsen 2011). For example, Van Heerde,
Helsen, and Dekimpe (2007) document that the salmonel

contamination of an Australian peanut butter brand reduced
its advertising effectiveness (from a significant precrisis
level to a nonsignificant postcrisis level) but not its price
elasticity. Studying the same case, Cleeren, Dekimpe, and
Helsen (2008) confirm that postcrisis advertising was inef-
fective to induce renewed trial of the affected brand, while
Zhao, Zhao, and Helsen (2011) report, using a consumer-
learning model on the same case again, a significant drop in
advertising elasticity of the affected brand along with a
slightly decreased postcrisis price sensitivity. Therefore, all
three studies cast doubt on the usefulness of increased
advertising support following the crisis and report mixed
results on the effectiveness of postcrisis price changes.

Still, given that all three studies investigated the same
product-harm crisis, little is known about whether the
reported postcrisis marketing effectiveness remains idiosyn-
cratic to that specific crisis,1 whether this generalizes to
other settings, or whether crisis characteristics such as the
extent of negative publicity and/or the acknowledgment of
blame moderate the ultimate effectiveness of different mar-
keting adjustments. If a product recall causes extensive
media coverage (e.g., the Cadbury crisis described previ-
ously), does this call for more advertising after the product
returns to the shelves, or is it better to stay out of the public
eye? Similarly, if the company had to take the blame for the
recall, does it reduce a firm’s ability to raise prices to
recoup some of the lost revenues?

In this study, we take a contingency-based view and
allow the effectiveness of marketing changes—which often
take place in the wake of a product-harm crisis—to depend
on both the extent of the negative publicity (which can vary
widely from one crisis to another) and whether the
firm/brand needed to acknowledge that the crisis was its
fault. Apart from its high managerial relevance, developing
hypotheses about, and empirically testing the role of, mod-
erators is also important from an academic point of view in
that it advances theory development by identifying bound-
ary conditions for existing theory. For example, Whetten

Rising from the Ashes / 59

(1989, p. 492) argues that “contextual factors set the bound-
aries of generalizability and, as such, constitute the range of
the theory.” (For more arguments in support of the role of
moderators in theory development, see, e.g., MacInnis
2011, p.144; Yadav 2010, p. 7.) Moreover, in contrast to
prior research that has treated marketing adjustments as
exogenous, we explicitly account for the endogenous nature
of the changes managers make when confronted with a
major product-recall situation.

Finally, unlike prior research that has focused almost
exclusively on the performance implications for the
affected brand(s), we also consider the implications on the
category as a whole. Because of the increasing prevalence
of product-harm crises, even the most cautious brand may
be confronted with a worst-case scenario in which con-
sumers perceive the problem as potentially industrywide
when it occurs to one of its (perhaps less cautious) competi-
tors. Again, the effectiveness of postcrisis price and adver-
tising may depend on the type of crisis facing the category.

This study contributes new insights along two dimen-
sions: It develops a contingency framework that (1) bridges
research on crisis characteristics and the postcrisis effec-
tiveness of advertising and price, and (2) it studies their
main and interactions effects on, respectively, brand share
and category purchases. Moreover, given that we empiri-
cally test this framework on a unique data set covering 60
full recalls in the fast-moving consumer goods (FMCG)
sector, we considerably add to the empirical knowledge
base for the phenomenon.

We organize the rest of the article as follows: We first
present our conceptual framework. Next, we discuss our
modeling approach, describe the operationalization of the
variables, and report the results. The final section summa-
rizes the findings and offers managerial implications.

Conceptual Framework
Product-harm crises can seriously hurt a firm’s performance
(e.g., Chen, Ganesan, and Liu 2009). Apart from the obvi-
ous impact on the affected brand, the entire category may
be affected when the inadequacy of the production process
is perceived as an industrywide problem (De Alessi and
Staaf 1994). Therefore, we focus on two key performance
metrics: the affected brand’s share and the level of category
purchases, both at the individual household level. We study
crisis characteristics and their moderating impact on the
effectiveness of marketing adjustments. We also include
several control variables. Figure 1 summarizes our concep-
tual framework. In what follows, we discuss the rationale of
the variables in our framework and develop hypotheses on
the interactions between crisis characteristics (negative
publicity and blame) and the marketing variables (price and
advertising).2

1A recent exception is Liu and Shankar’s (2012) study, which
investigates advertising effectiveness and the moderating impact
of the severity of the crisis for different recalls in the automobile
industry.

2Given our main interest in the contingency effects, we develop
formal hypotheses for the various interaction effects. For the main
effects, we briefly review prior evidence on their impact and
include them in our empirical testing. However, we develop no
formal hypotheses for the main effects.

60 / Journal of Marketing, March 2013

FIGURE 1
Conceptual Framework

Notes: A solid arrow indicates an effect that is part of the main model in Equations 1 and 2. The dashed arrow indicates the effect of the crisis
on the change in marketing variables. Because we use 2SLS to account for the endogeneity of marketing variables, this effect is part of
the first-stage regression of the estimation procedure.

Marketing Variables Before
Product-Harm Crisis

•Advertising
•Price

Control Variables
Consumer Characteristics

•Brand loyalty/category
usage

Product Characteristics
•Price premium of affected
brand(s)
•Private label versus national
brand

Category Characteristics
•Competition density
•Number of affected brands

Country Characteristics
•Country dummy

Crisis Characteristics

•Publicity
•Blame acknowledgment

Purchase Behavior Before
Product-Harm Crisis

Brand share
•Category purchases

Purchase Behavior After
Product-Harm Crisis

•Brand share
•Category purchases

Marketing Variables After
Product-Harm Crisis

•Advertising
•Price

BEFORE PRODUCT-HARM CRISIS AFTER PRODUCT-HARM CRISIS

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Crisis Characteristics

Negative publicity. Negative publicity is the extent to
which the media report on the product-harm crisis. Nega-
tive news is weighted more heavily in product evaluations
than positive news, because consumers perceive it as more
diagnostic and surprising (Herr, Kardes, and Kim 1991).
Moreover, negative news is typically broadcast by news
media and not by the brand itself, and audiences tend to
perceive media as more trustworthy (Wang 2006). Negative
publicity has been shown to hurt firm performance in a
variety of contexts such as critical movie reviews (Basuroy,
Chatterjee, and Ravid 2003) and negative online book
reviews (Chevalier and Mayzlin 2006). Moreover,
researchers have discussed the potentially detrimental effect
of bad publicity in the context of product-harm crises (e.g.,
Lei, Dawar, and Lemmink 2008).

However, recent research has suggested that negative
publicity need not always be bad, in line with the age-old
phrase “Any news is good news.” Berger, Sorensen, and
Rasmussen (2010) find that publicity may increase aware-
ness and accessibility, regardless of the valence of the mes-
sage. Their reasoning behind this result is that people may
forget over time the valence of the information, but the
awareness remains, and the product (category) may become
more top of mind. Therefore, in the case of negative public-
ity surrounding product-harm crises, merely mentioning a
brand or category may increase its awareness and accessi-
bility in consumers’ minds. Prior research has often dis-
cussed this phenomenon in the context of book or movie
reviews; however, Skurnik et al. (2005) report a similar dis-
sociation of awareness and valence of information in the
context of false claims for different noncultural products
(e.g., aspirin, corn chips), and Moore and Hutchinson
(1985) report the same results for negative advertising.

Blame. Blame accounts for whether the company
acknowledges responsibility for the product-harm crisis.
When a product fails, consumers are likely to search for
attributions of blame (Lei, Dawar, and Gürhan-Canli 2012).
Blame attributions can have serious consequences for a
company because they can lead to anger toward the com-
pany and to negative word of mouth (Folkes 1984, 1988).
Because blame attributions can cause a decrease in future
purchase intentions (Folkes 1988), we expect that acknowl-
edging blame will affect brand share negatively. With
regard to category purchases, it could be argued that con-
sumers will perceive the problem as less diagnostic for the
category when one specific company takes the blame for
the crisis. This decreases the likelihood of spillover to non-
affected competitors (Roehm and Tybout 2006): it not only
reduces the uncertainty with regard to the locus of fault but
also implicitly suggests that the others are not to blame.
Still, the perception that an industry member was to blame
may well be more serious than if a third (outside) party was
the culprit, because it may indicate that the industry’s (self)
regulation was insufficient to prevent the problem from
occurring.

Rising from the Ashes / 61

The Effectiveness of Marketing Adjustments

Managers often increase advertising support or decrease the
price in the wake of a product-harm crisis in an attempt to
regain lost consumers (Cleeren, Dekimpe, and Helsen
2008). Competitors in the same category may also boost
advertising expenditures or lower their prices to benefit
from the misfortune of the affected brand(s). Alternatively,
firms may well consider raising their prices in the wake of
the crisis. Indeed, research shows that managers very often
increase price (p) when demand (q) is unexpectedly low
(Marn, Roegner, and Zawada 2003), in an attempt to avoid
revenue (p q) losses (see also Rotemberg and Saloner
1986). We test whether the effectiveness of postcrisis adver-
tising and price adjustments is moderated by the crisis char-
acteristics, that is, the amount of negative publicity sur-
rounding the crisis and whether the affected brand had to
acknowledge blame.

Advertising negative publicity. Traditionally, researchers
have posited that negative publicity can damage brand
equity (Dawar and Pillutla 2000; Liu and Shankar 2012)
and credibility (Erdem and Swait 1998) and thus the effec-
tiveness of brand advertising. More recently, however,
Berger, Sorensen, and Rasmussen (2010) have shown that,
in some instances, negative publicity can increase product
awareness. In addition, Dawar (1998) argues that the
heightened brand awareness and media attention translates
into a higher return on advertising investments than if they
were part of routine equity-building activities. Moreover,
Wang (2006) shows that inconsistent messages in product
publicity versus advertising increase the perceived message
believability for advertising because consumers are more
motivated to process the information in an attempt to recon-
cile the differences (Maheswaran and Chaiken 1991).
Moreover, because of the media scrutiny, customers may
focus their attention on the focal or similarly categorized
brands, which could also enhance their ad effectiveness
(Rubel, Naik, and Srinivasan 2011). As such, negative pub-
licity can increase advertising effectiveness for the brand
and/or category. In line with this reasoning, we expect the
following:

H1: The effectiveness of brand advertising is greater when
there is a higher level of negative publicity surrounding
the crisis.

H2: The effectiveness of category advertising is greater when
there is a higher level of negative publicity surrounding
the crisis.

Price negative publicity. Apart from a tremendous
impact on brand equity (Dawar and Pillutla 2000) and firm
credibility (MacKinsey and Lutz 1989), negative publicity
may also decrease the perceived differentiation of the
affected brand (Ahluwalia, Burnkrant, and Unnava 2000).
Indeed, the brand’s relative position in the category might
have been negatively affected (Leclerc, Hsee, and Nunes
2005) because consumers might subsequently classify it in
a lower-quality tier, which could lead to an increase in the

magnitude of its price elasticity (Boulding, Lee, and Staelin
1994). Moreover, the consistency of the brand’s quality sig-
nal has been affected (Erdem, Swait, and Louviere 2002).
Therefore, we expect the following:

H3: Brand price sensitivity is greater when there is a higher
level of negative publicity surrounding the crisis.

Given that negative news may also affect the equity of non-
affected brands (Roehm and Tybout 2006), we expect a
similar effect for category price:

H4: Category price sensitivity is greater when there is a higher
level of negative publicity surrounding the crisis.

Advertising blame. A brand’s equity is a function of
consumers’ confidence in the brand’s ability to fulfill
expected/ promised benefits (e.g., Aaker 1996; Keller 1993).
As Gürhan-Canli and Fries (2010) articulate it, branding is
about creating and consistently delivering a promise to tar-
get customers. The product crisis may lead customers to
question this ability (Dutta and Pullig 2011). By acknowl-
edging blame for the product-harm crisis, a firm makes
clear that it failed to fulfill its promise (Riordan, Marlin,
and Kellogg 1983). Put differently, “concomitant confirma-
tion of guilt should lower trust by making clear that the mis-
trusted party was to blame” (Kim et al. 2006, p. 51). This
reduced trust translates into a lowered postcrisis advertising
effectiveness for the brand. Therefore, we hypothesize the
following:

H5: The effectiveness of brand advertising is lower when the
affected brand acknowledges blame than when it does not.

If the focal brand admits blame, it means that one of the
category members (rather than an external party) is to
blame (Siomkos et al. 2010). Moreover, consumers fre-
quently question the motivations of marketing actions.
When competitors launch extra advertising campaigns in
the aftermath of a crisis, consumers may believe this to be
an opportunistic attempt to take advantage of the misfor-
tune of the “wounded” brand (Siomkos et al. 2010), espe-
cially when the latter’s position has suffered even more
because of a forced blame acknowledgment. Given that
inferred motivations influence the effectiveness of advertis-
ing spending (Campbell 1999; Eagly, Wood, and Chaiken
1978), we hypothesize the following:

H6: The effectiveness of category advertising is lower when
the affected brand acknowledges blame than when it does
not.

Price blame. Confirming guilt makes clear that the
mistrusted party is to blame, which lowers a brand’s credi-
bility substantially (Kim et al. 2006). Lower brand credibil-
ity increases the required information search and processing
costs and reduces the perceived quality of the brand
(Erdem, Swait, and Louviere 2002), both of which increase
its price sensitivity. Thus, we hypothesize the following:

H7: Brand price sensitivity is greater when the affected brand
acknowledges blame than when the brand does not.

As we mentioned previously, one brand’s acknowledgment
of blame may taint competitors by association (Siomkos et
al. 2010). Thus:

62 / Journal of Marketing, March 2013

H8: Category price sensitivity is greater when the affected
brand acknowledges blame than when the brand does not.

Control Variables

Consumer heterogeneity. To account for heterogeneity
across consumers, we control for a household’s precrisis
brand loyalty and category usage. Arguments can be formu-
lated for both a positive and a negative impact of brand loy-
alty and category usage on how consumers react to a crisis.
On the one hand, not only are consumers with positive atti-
tudes toward a target likely to resist counterattitudinal crisis
information, but they also weigh this information less in
their product evaluations (Ahluwalia, Burnkrant, and
Unnava 2000). Thus, they may react less negatively to the
crisis. On the other hand, research has shown that extremely
negative information is highly diagnostic (Herr, Kardes,
and Kim 1991) and might therefore be difficult to refute
(Ahluwalia, Burnkrant, and Unnava 2000). Moreover, Gré-
goire and Fisher (2008) show that customers who are
treated poorly by a firm with which they feel a strong con-
nection can feel even more disconcerted and hurt than oth-
ers because of a greater sense of betrayal. When a similar
“love becomes hate” effect happens in a product-harm cri-
sis, brand loyalty and category usage will have a negative
impact on brand share and category purchases.

Price premium. Brands with a high price premium tend
to have a higher brand equity and thus typically have very
committed consumers (Aaker 1996). This may offer
resilience in the face of misfortune (Hoeffler and Keller
2003). Indeed, on the one hand, committed consumers are
more likely to counterargue with negative information
(Ahluwalia, Burnkrant, and Unnava 2000), while they
attempt to confirm prior expectations (Dawar and Pillutla
2000). On the other hand, the likelihood that the crisis is
noticed is greater for high-equity brands given that they
receive more media attention and that consumers tend to
pay more attention to, and retain more information on,
familiar brands (Hoeffler and Keller 2003). In addition, the
category may suffer more from a crisis affecting a premium
brand, given that negative information on these brands gen-
erates more attention (Hoeffler and Keller 2003). Therefore,
product harm for a premium brand is more likely to spill
over to the category (Roehm and Tybout 2006).

Number of affected brands. A particular product-harm
crisis may affect multiple brands because of, for example, a
shared manufacturer or ingredients’ supplier. The effect on
category purchases of a crisis including multiple brands is
likely to be larger, as it becomes more likely that the crisis
reflects an industrywide (production) problem (Roehm and
Tybout 2006). Furthermore, a larger fraction of the cus-
tomer base will find their most preferred brand taken from
the shelves, making them more likely to defect from the
category (Campo, G

sbrechts, and Nisol 2003). In contrast,
we expect the impact on the share of each individual brand
to be smaller because the attention will be focused less on
any single brand and also because the set of unaffected
brands to which consumers can switch becomes smaller.

Private label versus national brand. Consumers view
store brands as inferior in quality to national brands
(Ailawadi, Neslin, and Gedenk 2001; Steenkamp, Van
Heerde, and Geyskens 2010). Therefore, quality expecta-
tions for private labels are lower, and a product-harm crisis
will be less likely to be perceived in conflict with the qual-
ity signal of the brand (Zhao, Zhao, and Helsen 2011). We
thus expect the loss in brand share after a crisis to be
smaller for private labels. In addition, the distribution of
private labels is more limited than that of national brands.
Therefore, we expect the impact of a private-label recall on
category purchases to be smaller.

Competition density. To account for differences in cate-
gory structure across product-harm crises, we control for
precrisis competition density. In the literature, researchers
have shown that the extent of concentration of the brands in
the market is an important antecedent of market conduct
and outcomes (Steenkamp, Van Heerde, and Geyskens
2005). Finally, we control for differences between the (two)
countries we study by including a country dummy.

Model

As argued previously, a product-harm crisis might affect not
just the brand itself but also the entire category. Therefore,
our key focus is on the changes in households’ brand shares
and category purchases across a large panel of households.
To adequately capture both dependent variables, our model-
ing approach should address four issues. First, the model
should account for heterogeneity across households. Sec-
ond, the model should account for the potential endogeneity
of the marketing variables. Third, the approach should
allow for potential correlations between (1) observations of
the same household across different product-harm crises
and (2) observations of different households within the
same product-harm case. Finally, the measures should cap-
ture enough purchases for reliable estimation of brand
shares and category purchases.

Next, we discuss how we address each of these issues.
First, individual-level consumption is influenced by several
fixed consumer characteristics. To control for this source of
heterogeneity across households, we use a difference
approach and model the difference between a household’s
post- and precrisis brand share and category purchases. This
approach is similar in spirit to a fixed-effect approach that
controls for unobserved time-invariant effects of the cross-
sectional units (indeed, by differencing, the time-invariant
or fixed effects disappear). Ailawadi, Lehmann and Neslin
(2001), for example, follow this approach to control for
brand-specific fixed effects while examining the impact of a
major policy change. Because we consider full (all batches
across the entire country) product recalls, no control group
can be considered, precluding the difference-in-difference
approach Ailawadi et al. (2010) use.

Second, omitted variables may cause the marketing
variables to be correlated with the error terms for both the
brand-share and category-purchase models. Indeed, man-
agers may base their advertising and pricing response on
factors they observe but not the researcher. To accommo-

Rising from the Ashes / 63

date potential endogeneity of advertising, price, and all
interaction effects involving these marketing variables, we
use a two-stage least squares (2SLS) estimation technique
(for a recent review on endogeneity issues in marketing,
see, e.g., Ebbes, Papies, and Van Heerde 2011). As a by-
product of the estimation, we obtain the first-stage regres-
sion results for the endogenous regressor’s price and adver-
tising. Although these first-stage regressors are not of
primary interest, they do give some insights into the
dynamic price and advertising responses in the wake of a
product-harm crisis (for the recommended use of 2SLS for
an endogenous mediator, see Shaver 2005, pp. 338–39; for
recent marketing applications of this procedure, see Ata-
man, Mela, and Van Heerde 2008; Ataman, Van Heerde,
and Mela 2010; Leenheer et al. 2007). We discuss these
effects in the “Results” section.

Third, we measure both the changes in brand share and
category purchases for a given crisis and household. One
particular household is likely to be observed in multiple cri-
sis cases, while each crisis case affects multiple households.
In line with Mizik and Jacobson’s (2009) recommendation,
we use a robust clustered error-term estimation. Specifi-
cally, we adopt the procedure Lin (1994) proposes and
Cameron, Gelbach, and Miller’s (2011) extension to two-
way clustering to estimate robust standard errors.

Finally, to obtain reliable measures for the changes in
brand share and category purchases, we must use a suffi-
ciently long period before and after the crisis to ensure that
we observe enough purchases in both periods. In line with
Gielens and Steenkamp (2007) and given that we study fre-
quently purchased consumer goods with differing interpur-
chase times, we use an observation period of one year
before and one year after the crisis. Moreover, prior
research on product-harm crises (e.g., Van Heerde, Helsen,
and Dekimpe 2007) has shown that the dust inherently sur-
rounding such crisis situations has settled well within a year
after the crisis. We offer more details on the exact opera-
tionalizations of the variables in the “Data” section.

Model Specification

Following an established tradition in the market-response
literature (see, e.g., Leeflang et al. 2000, p. 167), we
decompose sales into primary demand (category purchases)
and selective demand (brand share). We use a regression
framework to assess the impact of crisis characteristics,
marketing variables, control variables, and the interaction
effects. We model the (transformed3) change in brand share
for household i and crisis j as follows:

Δ = β + β + β
+ β Δ
+ β Δ
+ β Δ ×
+ β Δ ×
+ β Δ ×
+ β Δ × + β + ε

(1) BS Publicity Blame

Relative brand advertising

Relative brand price

Relative brand advertising Publicity

Relative brand price Publicity

Relative brand advertising Blame

Relative brand price Blame X ,

0
BS

1
BS

j 2
BS

3
BS

4
BS

5
BS

j j

6
BS

j j

7
BS

j j

8
BS

j j 9
BS

1ij

3To account for the bounded range of this variable, we use a
logit-type transformation, as explained in the “Data” section.

where the X1ij vector includes the control variables—that is,
brand loyalty, price premium, number of affected brands, a
private-label dummy, competition density, and a country
dummy variable (1 = the Netherlands, 0 = United King-
dom). Similar to the brand-share model, the (transformed4)
change in category purchases for household i and crisis j is
specified as follows:

where X2ij are the control variables category usage, price
premium, number of affected brands, the private-label
dummy, competition density, and the country dummy.

Model Estimation

To accommodate the potential endogeneity of advertising,
price, and the interaction effects involving these marketing
variables, we estimated Equations 1 and 2 with 2SLS. We
use five broad categories of instrumental variables (IVs).
Table 1 summarizes the main IVs used for each model and
indicates the operationalization and data source.

In line with Villas-Boas and Winer (1999) and Dhar and
Hoch (1997), we use the lagged changes in the marketing
variables as a first set of IVs. Given that the marketing
variables measure the change in the year following the cri-

Δ = β + β + β
+ β Δ + β Δ
+ β Δ ×
+ β Δ ×
+ β Δ ×
+ β Δ × + β + ε

(2) CP Publicity Blame

Category advertising Category price

Category advertising Publicity

Category price Publicity

Category advertising Blame

Category price Blame X ,

ij
*

0
CP

1
CP

j 2
CP

3
CP

j 4
CP

5
CP

j j

6
CP

j j

7
CP

j j

8
CP

j j 9
CP

2 ij ij
CP

64 / Journal of Marketing, March 2013

sis when compared with before the crisis, the IVs capture
the corresponding change in the two years preceding the
crisis. Second, we include the lagged changes in the rele-
vant performance metrics (i.e., change in brand share for
the affected brand-share model and change in category pur-
chases for the category-purchases model). These IVs cap-
ture the distinction that the main drivers of marketing
changes are demand based (Srinivasan, Pauwels, and Nijs
2008). In the third set of IVs, we use several variables to
capture the evolution in the overall production costs, fol-
lowing Luan and Sudhir’s (2010) recommendation. To that
extent, we account for changes in the overall consumer
price index, fuel prices (for the importance of this factor in
the marketing adjustments of retailers, see, e.g., Ma et al.
2011), labor costs, and rental prices. Fourth, in line with Ma
et al. (2011), we include a fixed-effects correction to
account for systematic differences between major groups
not yet captured by the previous sets of IVs. Following
Steenkamp, Van Heerde, and Geyskens (2010), we control
for differences between beverages and other categories. As
a final set of IVs, we include the interaction effects of all
IVs identified previously with negative publicity and
blame. Following Wooldridge (2002, pp. 121–22) and Luan
and Sudhir (2010), we include these IVs because the mod-
els include interactions between exogenous variables (the
two crisis characteristics) and endogenous variables (adver-
tising and price). In the “Results” section, we report tests
that confirm the strength and validity of the IVs.

Data
To calibrate the models, we collected a unique and compre-
hensive data set. We study all major FMCG product-harm
crises that occurred in the United Kingdom and the Nether-
lands between 2000 and 2007. We define “major” in the sense
that all units of at least one variety were fully recalled. Thus,

4To make the measure comparable across categories, we divided
the change in category purchases by the average of the pre- and
postcrisis purchases. To overcome the bounded range of this
variable, we again used a logit-type transformation, as explained
in the “Data” section.

IV Operationalization Data Source

Lagged advertising
change

Change in relative brand advertising/ total category
advertising between one and two years before the crisis

AC Nielsen advertising data

Lagged price change Change in relative brand price/total category price
between one and two years before the crisis

TNS UK/ GfK Netherlands household-
panel data

Lagged brand share/
category sales

Change in brand share of the affected brands/category
purchases between one and two years before the crisis
(based on the full panel)

TNS UK/ GfK Netherlands household-
panel data

Change in consumer
price index

Change in country-specific consumer price index between
the year of the crisis and one year before

Organisation for Economic Coopera-
tion and Development statistics

Change in fuel prices Change in country-specific fuel price between the year of
the crisis and one year before

International Labor Organization

Change in rental prices Change in country-specific rental prices between one year
and two years before the crisis

International Labor Organization

Change in labor costs Change in country-specific unit labor costs between the
year of the crisis and one year before

Organisation for Economic Coopera-
tion and Development statistics

Category dummy Dummy variable that indicates whether the category is a
beverage

TNS UK/ GfK Netherlands household-
panel data

TABLE 1
Operationalizations and Data Sources of IVs

we exclude cases in which only certain batches are recalled.
Using the recall records of governmental and consumer
organizations,5 we identified 60 major (voluntary) product
recalls in this period, of which 36 took place in the United
Kingdom and 24 in the Netherlands. We study a large range
of product-harm crises, ranging from cereals to ice cream
and from mineral water to liquor. Examples of cases include
salmonella-contaminated Cadbury dairy milk chocolate, the
detection of glass inside Olvarit baby food, pieces of plastic
in Basset’s milky babies (lollies), and bursting bottles of
Bacardi Breezer premixed spirits. Because several of these
product-harm crises affect the same category, we identify 40
unique cases for the category-purchase model. The Appen-
dix provides a description of all cases.

We combined data from different sources. We obtained
household scanner data for these crises from TNS UK
(gross panel size = 25,000 households) and GfK Nether-
lands (gross panel size = 6000 households). We purchased
advertising expenditure data for all relevant brands and
categories from ACNielsen UK and the Netherlands. Fur-
thermore, we obtained information on crisis characteristics
from the recall announcements and through an extensive
media search on the specific crisis cases in the top news –
papers using the Lexis Nexis (the Netherlands) and Factiva
(United Kingdom) databases.6 We gathered all variables
during the period of one year before and one year after the
crisis. In line with Cleeren, Dekimpe, and Helsen (2008),
the beginning of the crisis is the date mentioned on the offi-
cial recall announcement, and the end of the crisis is the
date of the first purchase of the affected variety in the
household panel after the beginning of the crisis. In all
cases, all batches of the affected variety were recalled at the
same time. As such, the beginning of the crisis could easily
be identified, and it applied to all panel members.

Dependent Variables

The change in category purchases for household i in crisis j
is the difference between a household’s category-purchase
volume in the year after versus the year before the crisis.
The difference approach controls for potential heterogene-
ity across households (e.g., Ailawadi, Lehmann, and Neslin
2001; Cameron and Trivedi 2005). To make our purchase
measure comparable across categories, we divide the

Rising from the Ashes / 65

change by the average of the category purchases (CP)
before and after the crisis7:

For the category-purchase model, our sample consists of all
households that made at least three purchases in the cate-
gory during the total observation period (one year before
until one year after the crisis). This ensures that we exclude
the very light or accidental users of the category. It is evi-
dent that not every customer was “active” (i.e., had three
purchases in the observation period) in every category
(indeed, only households with small children will buy baby
food, and not every household will have three purchases of
a particular type of liquor). On average, panelists were
active in seven categories. Per category, an average of
approximately 10,300 households was available, leading to
a total number of 411,266 observations for the category-
purchase model (Equation 2).

For the brand-share model, we selected households that
made at least three purchases of the affected brand within
the observation period of two years (one year prior and one
year after). Again, we did this to exclude very light or acci-
dental brand buyers. Because not every consumer in a cate-
gory will buy the affected brands, the sample sizes are
lower in the brand-share equation. On average, panelists
contributed two observations to the brand-share equation.
Approximately 746 observations were available for each of
the 60 affected brands, for a total of 44,743 observations for
the brand-share equation (Equation 1).

We define the change in affected brand share for house-
hold i and crisis case j as the difference between the volume
share of the affected brand in the category purchases during
one year after and one year before the crisis8:

Δ = −(4) BS BS BS .ij

ij
AFTER

ij
BEFORE

( )
Δ =

−

+
(3) CP

CP CP

CP CP 2
.ij

ij
AFTER
ij
BEFORE
ij
BEFORE
ij
AFTER

5For the United Kingdom, we investigated the archives of the
Food Standards Agency and the Trading Standards Institute. For
the Dutch recall cases, we consulted the archives of the Voedsel
Waren Autoriteit (Food Products Authority) and the Consumenten-
bond (Consumer Reports).

6We limited our media search to newspapers with a circulation
of at least 1% of the population. This includes, for the United
Kingdom, both the weekly and Sunday editions of (in alphabetical
order) Daily Express, Daily Mail, Daily Mirror, Daily Star, The
Daily Telegraph, The Independent, News of the World, The
People, The Sun, and The Times, for a total of 17 newspapers. For
the Netherlands, we included Algemeen Dagblad, de Telegraaf,
NRC Handelsblad, and De Volkskrant. Free newspapers are not
part of the electronic databases, and thus, we could not include
them in the media search.

7 CPij, as specified in Equation 3, is constrained to the interval
[–2, 2]. To account for the bounded nature of this measure, we
apply the logit-type transformation Lesaffre, Rizopulos, and Tson-
aka (2007) describe for a response U that is limited to the interval
(a, b): Z = ln[(U – a)/(b – U)]. Given that CPij is limited to the
interval [–2, 2], we add a small amount to a and b to avoid the
expression taking the log of zero (cf. Bass et al. 2009). The trans-
formation results in the following dependent variable:

8Because brand share is a ratio, this measure is already compa-
rable across categories. Because this variable is constrained to [–1,
1], we again apply the logit-type transformation Lesaffre, Rizopu-
los, and Tsonaka (2007) describe:

Note that this measure becomes zero if the household never
switches brands.

Δ ≡
Δ +

− Δ
⎛

⎝
⎜

⎞

⎠
⎟CP ln

CP 2.01

2.01 CP
.ij

* ij

ij
Δ ≡
Δ +
− Δ
⎛
⎝
⎜
⎞

⎠
⎟BS ln

BS 1.01

1.01 BS
.ij

* ij
ij

Table 2 provides the definitions and summary statistics for
the dependent and independent variables.

Crisis Characteristics

Crisis characteristics are based on the media search we con-
ducted. We measured negative publicity as the fraction of
newspapers among the (country-specific) considered set that
reported on the crisis. All 17 newspapers in the research set
covered the salmonella contamination in Cadbury choco-

66 / Journal of Marketing, March 2013

late, whereas only one newspaper covered the bursting Bac-
ardi Breezer bottles. Blame is a dummy variable, indicating
whether the company acknowledged the blame for the crisis
either in the recall announcement or in the surrounding pub-
licity. For example, whereas Bacardi-Breezer’s recall
announcement attributed the blame of the bursting bottles
to its packaging supplier, Cadbury acknowledged that the
salmonella contamination in its chocolate was due to a
problem in its own production process.

Description M SD

Dependent Variables
Change in brand share

(N = 44,743)
Difference in the postcrisis (one year) and precrisis (one year) volume share
of the affected brand (Equation 4)

–.34 .34

Change in category
purchases (N = 411,266)

Difference in the postcrisis (one year) and precrisis (one year) category-pur-
chase volume of the household (Equation 3)

.26 1.38

Independent Variables
Crisis Characteristics (N = 60)

Publicity Fraction of newspapers that reported on the crisis during a time span of
three months before and one year after the recall announcement

.23 .34

Blamea Dummy for whether the company acknowledged the blame for the crisis
either in the recall announcement or in the surrounding publicity

20% 40%

Marketing Variables

Change in relative brand

advertising (N = 60)
Difference in the post- and precrisis share of voice, expressed relative to the
expenditures of the five largest nonaffected competitors and the brand itself

–.03 .12

Change in relative brand
price (N = 60)

Difference in the post- and precrisis average (per volume unit) brand price,
relative to the weighted average price of the five main competitors

–.02 .23

Change in category
advertising (N = 40)

Difference in the post- and precrisis total advertising expenditures of all
affected brands and the five largest nonaffected competitors, normalized by
the average of their total advertising expenditures before and after

.10 .86

Change in category price
(N = 40)

Difference in average category price (per volume unit) of all affected brands
and the five largest nonaffected competitors, normalized by their average
price before and after

.01 .05

Control Variables

Brand loyalty (N = 44,743) Precrisis within-household market share (in volume) .39 .35
Category usage

(N = 411,266)
Precrisis total volume purchased by the household in the category, normal-
ized by category average across households

1.00 1.55

Price premiumb:
•Brand-share model

(N = 40)
•Category-purchase

model (N = 60)

Difference in the precrisis (weighted) average price of the affected brand(s)
and the cheapest private label in the category, normalized by the precrisis
(weighted) average price of the affected brand(s)

.46

.42

.30

Number of affected brands
(N = 60)

Number of brands that were recalled in the crisis 5.17 6.14

Private-label dummya
(N = 60)

Dummy for private label ( = 1) or national brand ( = 0) 72% 45%

Competition density
(N = 60)

Sum of market shares of the largest four players in the market .73 .15

Country dummyb (N = 60) Dummy: 1 for the Netherlands, 0 for United Kingdom 40% 49%

TABLE 2
Variable Definitions and Summary Statistics

aFor these, dummy variables, we report the percentage of observations having the value of 1.
bThe price premium for the brand-share model (vs. the category-purchase model) is based on the difference in average price between the
brand under inspection (vs. all affected brands in the category) and the cheapest private label in the category. Therefore, we obtain slightly dif-
ferent summary statistics.

Notes: We report the statistics for the dependent variables before the logistic transformation and for the independent variables before mean-
centering. The sample size for the brand-level variables is lower than the sample size of the category variables, because there are fewer
households buying a certain brand than households buying in the category. At the brand level, there are 60 unique cases; at the cate-
gory level, there are 40 unique cases.

Marketing Variables

For the marketing variables in the brand-share equation
(Equation 1), we use the change in relative advertising and
relative price (see, e.g., Leeflang et al. 2000; Zenor, Bron-
nenberg, and McAlister 1998). The change in relative brand
advertising is specified as the difference between the post-
and precrisis share of voice, expressed relative to the expen-
ditures of the five largest nonaffected competitors and the
brand itself.9 We define the change in relative brand price
as the difference between the relative brand price (per vol-
ume unit) after and before the crisis, expressed in relation to
the weighted average price of the five main nonaffected
competitors. Given that the recorded prices are net prices,
they also reflect the discounts that brands may have offered
after the crisis.

For the category-purchase equation (Equation 2), we
use the change in total category advertising expenditures
(Schultz and Wittink 1976) and average category price (Nijs
et al. 2001) per volume of all affected brands and the five
largest nonaffected competitors. To make these measures
comparable across categories, we divided them by the aver-
age of total advertising expenditures before and after and
average price before and after, respectively.

Control Variables

We measured the price premium as the difference between
the (weighted) average price of the affected brand(s) and
the least expensive private label in the category (for a simi-
lar procedure, see Ailawadi, Lehmann, and Neslin 2003).
To standardize the measure over the different categories, we
divided this difference by the affected brand’s price before
the crisis. Because of potentially different effects of crises
involving multiple brands, we account for the number of
affected brands in the crisis. We account for the effect of
private label with a dummy variable that indicates whether
the affected brand was a private label (PL).

Our measures for household heterogeneity ([brand] loy-
alty and [category] usage) are based on the household-panel

Rising from the Ashes / 67

scanner data during the initialization period (one year
before the crisis). We explicitly chose to measure these
household characteristics before the crisis to avoid a con-
found with the dependent variable brand share and category
purchases. In line with Cleeren, Dekimpe, and Helsen
(2008), we specify precrisis (behavioral) loyalty to the
affected brand as its within-household market share (in vol-
ume), while we operationalize category usage as the precri-
sis total volume purchased in the category (normalized by
the category average across households). Finally, in line
with Moorman et al. (2012), we control for the competition
density within the affected category with the sum of market
shares of the largest four players in the market (C4) and
include a country dummy for the Dutch cases to control for
potential differences between the two examined countries
(i.e., the United Kingdom and the Netherlands). Following
Steenkamp, Van Heerde, and Geyskens (2010), we group
mean-centered the household characteristics (within crisis
cases) and grand mean-centered all other continuous inde-
pendent variables (across crisis cases).

Results
We first tested the extent of multicollinearity in the models.
In Table 3, we report the correlations between the different
crisis characteristics, which are all .62 or less, well below .8
(Judge et al. 1998, p. 868). The maximum variance inflation
factor value for the brand-share model is 5.68 and 2.38 for
the category-purchase model. Both values are well below
10 (Hair et al. 2010, p. 204), mitigating multicollinearity
concerns.

In addition, we tested both the strength and validity of our
IVs (in line with Bascle’s [2008] recommendations). To check
for the strength of the IVs, we used the Angrist-Pischke
(2009, pp. 217–18) multivariate F-statistic, which is recom-
mended in applications with multiple endogenous variables.
In both the market-share and category-purchase models, the
p-values corresponding to the multivariate F-statistic in all
first-stage regressions are smaller than .01, rejecting the
null hypothesis that the IVs do not explain the endogenous
variables. In other words, the IVs are sufficiently strong. As
for the validity condition, the Hansen J test (which is robust

9We identified the largest nonaffected competitors using the
total volume sold during the year before the crisis.

TABLE 3
Correlation Matrix

Number of Private-
Price Affected Label Competition

Publicity Blame Premium Brands Dummy Advertising Price Density

Publicity
Blame .17
Price premium –.03 –.34***
Number of affected brands .08 –.32** .28**
Private label dummy –.12 –.61*** .38*** .27**
Advertising –.09 –.07 –.14 .16 .11
Price –.10 .07 –.36*** –.37*** –.17 –.05
Competition density .27** .14 –.53*** –.33** –.22* .10 .17
Country (the Netherlands = 1) .62*** .02 .11 .55*** –.02 .06 –.29** .13

*Correlations significant at 10%.
**Correlations significant at 5%.
***Correlations significant at 1%.
Notes: The matrix shows the correlations between the crisis characteristics (N = 60).

to clustered error terms) is not significant for both models
(p > .15). This indicates that the null hypothesis, that the
IVs are uncorrelated with the error term, cannot be rejected.
In other words, the IVs are sufficiently valid. Tables 4 and 5
show the parameter estimates for the brand-share (Equation
1) and category-purchase (Equation 2) equations.

Crisis Characteristics

While the impact on the affected brand’s share is not sig-
nificant ( = p > .1), the category benefits from blame
acknowledgment by the affected brand ( = p < .01). By acknowledging blame, the other brands in the category

68 / Journal of Marketing, March 2013

have been moved out of harm’s way. However, the extent of
negative publicity has no significant main effect on either
the change in brand share ( = p > .1) or category pur-
chases ( = p > .1). The inherent negative impact of
the bad news surrounding the crisis (Herr, Kardes, and Kim
1991) may be nullified by the increase in awareness caused
by the mere mention of the brand or category (Berger,
Sorensen, and Rasmussen2010).

Marketing Variables and Interactions

The change in relative brand advertising has the expected
positive impact on the change in brand share ( = p <

TABLE 4
Empirical Results for the Brand-Share Model

Hypotheses

Intercept –.112
(.098)

Crisis Characteristics
Negative publicity .001

(.056)
Blame .079

(.111)
Marketing Variables

Relative brand .535***
advertising (.190)
Relative brand price .292

(.292)
Interaction Effects

Relative brand 1.221* H1(+): supported
advertising (.661)
negative publicity
Relative brand .006 H3(–): not supported
price negative (.878)
publicity
Relative brand –.456** H5(–): supported
advertising blame (.200)
Relative brand –.962* H7(–): supported
price blame (.574)

Control Variables
Brand loyalty –1.838***

(.072)
Price premium of –.138

affected brand (.162)
Number of affected –.002

brands (.005)
Private-label dummy .141*

(1 for private label, (.084)
and 0 for national
brand)

Competition density –.257**
(.129)

Country dummy –.025
(the Netherlands = 1) (.067)

Number of observations 44,743
R-square .277

*Significant two-tailed result at 10% significance level.
**Significant two-tailed result at 5% significance level.
***Significant two-tailed result at 1% significance level.
Notes: Robust standard errors are in parentheses.

TABLE 5
Empirical Results for the Category-Purchase

Model
Hypotheses

Intercept –.315
(.194)

Crisis Characteristics
Negative publicity .423

(.290)
Blame 1.173***

(.267)
Marketing Variables

Category advertising .813***
(.238)

Category price –5.827*
(3.580)

Interaction Effects
Category 3.373* H2(+): supported
advertising (1.865)
negative publicity
Category price –13.154** H4(–): supported
negative publicity (6.128)
Category –2.053*** H6(–): supported
advertising blame (.537)
Category price 5.158 H8(–): not supported
blame (4.478)

Control Variables
Category usage –.728***

(.035)
Price premium of –.081

affected brand (.334)
Number of affected .025

brands (.018)
Private-label dummy 1.125***

(1 for private label, (.184)
and 0 for national
brand)

Competition density –.686
(.639)

Country dummy –.506**
(the Netherlands = 1) (.223)

Number of observations 411,266
R-square .138

.01), while the change in relative brand price is not signifi-
cant ( = p > .1). With regard to the category, we find
that both category advertising ( = p < .01) and cate- gory price ( = p < .1) have the expected signifi- cant effects.

Advertising negative publicity. Negative publicity
increases the brand’s advertising effectiveness ( = p < .1), consistent with the heightened brand awareness identi- fied in Berger, Sorensen, and Rasmussen (2010). It also enhances category advertising effectiveness ( = p < .1). These findings are consistent with H1 and H2, confirm- ing Dawar’s (1998) proposition that increased media atten- tion in a crisis context might not be all bad for companies, given that it could translate into a higher return on advertis- ing investments.

Price negative publicity. Negative publicity has no
significant effect on the price sensitivity of brand share ( =

p > .1), thus rejecting H3. However, we do find sup-
port for H4, because the price sensitivity of postcrisis cate-
gory purchases increases with the extent of negative public-
ity ( = p < .05). This finding corroborates the notion that the crisis causes a loss in equity for the category as a whole (Roehm and Tybout 2006), making consumers more price sensitive.

Advertising blame. When the affected brand takes the
blame for the crisis, its advertising effectiveness decreases
( = p < .05), in support of H5. This finding is con- sistent with a loss in trust in the brand’s ability to fulfill its promises (Aaker 1996; Keller 1993). We also find that cate- gory advertising becomes less effective when the affected brand has taken the blame for the crisis ( = p < .01), in support of H6. When a category member (rather than an outside party) was responsible for the crisis, the credibility for the whole category may be affected; in addi- tion, the underlying motive for competitors’ advertising may be questioned.

Price blame. Price sensitivity increases following
blame acknowledgement ( = p < .1), in support of H7. When a brand acknowledges guilt in a crisis, brand credibility decreases (Kim et al. 2006), producing a nega- tive impact on the effectiveness of both marketing variables (Erdem, Swait, and Louviere 2002). Notably, category price sensitivity is not influenced by blame acknowledgment ( =

p > .1), which is at odds with H8.

Control Variables

The household characteristics brand loyalty and category
usage have significant negative effects on the change in
brand share ( = p < .01) and category purchases ( = p < .01). Thus, the decrease in brand share is especially strong for brand-loyal consumers when a product- harm crisis strikes. Similarly, the category purchases by heavy users are especially vulnerable to such a crisis. These results are in line with Grégoire and Fisher (2008), who show that consumers with a strong connection to a brand or category feel a stronger sense of betrayal and hurt when treated poorly.

Rising from the Ashes / 69

While both the price premium and the number of affected
brands have no significant effect on either the change in
brand share (respectively, = p > .1 and =
p > .1) and category purchases (respectively, = p >
.1 and = p > .1), the type of brand matters in both
models. Indeed, private labels suffer less from product harm
( = p < .1), in line with their lower quality expecta- tions (Zhao, Zhao, and Helsen 2011), while the spillover to the category is reduced, in line with the more limited distri- bution of private labels ( = p < .01). Although brands suffer more when the category is more concentrated ( = p < .05), competition density has no significant impact on the category ( = , p > .1). In highly con-
centrated markets, each of the competing (nonaffected)
brands is more powerful (Nijs et al. 2001) and better able to
take advantage of the weakened position of the affected
brand. This may explain the higher brand-share loss in con-
centrated settings. Finally, while the change in brand share is
not significantly different in the two included countries ( =

p > .1), category purchases decrease more in the
Netherlands ( = p < .05).

First-Stage Regression Results

We obtained first-stage regression results for the endoge-
nous price and advertising variables as a function of the
exogenous variables, including characteristics of the prod-
uct-harm crisis, and the IVs. Although these auxiliary
results are not of primary interest, they do provide insights
into the dynamics of price and advertising responses in the
wake of the crisis.10 We find that brands increase their
advertising in case they are to blame for the crisis (p < .05), which supports the idea that firms believe that a stronger corrective action is required in such instances (Chen, Gane- san, and Liu 2009). Moreover, an affected brand reacts less in concentrated markets both in terms of advertising (p < .01) and price cuts (p < .10). In concentrated markets, profit margins tend to be higher (Steenkamp et al. 2005), and companies may be less motivated to cut prices because this could cause these attractive high margins to dissipate (Ramaswamy, Gatignon, and Reibstein 1994). In contrast, brands use more price cuts to differentiate themselves more from other affected brands in case several of them are affected (p < .05).

We find that competitors chose not to retaliate with
advertising when there is a great deal of publicity surround-
ing the crisis (p < .01) or when the affected brand is strong, as evidenced by a high price premium (p < .01). Indeed, the

10For the sake of readability, we focus on the effects of the
exogenous variables on the change in relative brand/category
advertising and price. We do not report the effects of the IVs,
because (1) their substantive managerial relevance is much lower
and (2) their large number prohibits us from doing so. For example,
for the endogenous variable category advertising in the category-
purchases model, we include main effects for eight IVs and 2 8 =
16 interaction effects, for a total of 24 effects involving IVs for
one endogenous variable alone. Across all endogenous variables in
both the brand-share and category-purchase models, there are 192
main and interaction effects involving IVs. The full set of first-
stage regression results is available on request from the first
author.

damage to the category in these cases may be so severe that
advertising messages may no longer be able to restore the
lost trust, and companies may deem it better to stay out of
the public’s eye. In addition, in highly concentrated markets,
competitors are less likely to react with advertising (p < .05). Moreover, competitors especially try to attack affected pri- vate labels with price cuts (p < .01) but do so less when the crisis involves more affected brands (p < .01).

Additional Model Checks

We now report on several additional model checks to
demonstrate the robustness of our results to our modeling
choices. First, we determined the correlation between the
error terms ij

BS and ij
CP of the brand-share (Equation 1) and

the category-purchase (Equation 2) equations, respectively.
Because the sample sizes for the estimation of these equa-
tions differ (N = 44,743 for the brand-share equation and N
= 411,266 for the category-purchase equation), we can only
calculate the correlation across the overlapping observa-
tions. The error correlation is ultimately small: –.109. Thus,
the potential for efficiency gains (lower standard errors)
from estimating the two equations simultaneously with a
seemingly unrelated regressions–type of approach is limited
(for similar reasoning, see Chandrashekaran and Sinha
1995, p. 446).

As a second robustness check, we determined how
brand share and category purchases are affected by other
potential drivers, such as the length of the recall period, the
year of the crisis, and the underlying cause of the crisis. On
the one hand, consumers may use the length of the recall
period as a sign of the severity of the problem given that
companies may need a longer time to overcome more seri-
ous problems. On the other hand, short recall periods may
also be perceived as untrustworthy. We find no evidence for
such effects in that neither the recall period nor its square is
significant (p > .1). Furthermore, we controlled for the year
of the crisis. The number of crises has increased every year
(PWC 2006), which may cause different consumer reac-
tions to recent recalls compared with older cases. However,
the year of the crisis did not have a significant effect on the
change in brand share or category purchases (p > .1).

We also tested whether yet another indicator of the
severity of the crisis (in addition to the ones that are already
in the model) has an impact on consumer decisions. We
identified three types of crises: (1) content-related prob-
lems, (2) labeling mistakes, and (3) package failures. To test
for the impact of the type of the crisis, we added two
dummy variables indicating whether the crisis was of type 1
and type 2. None of the dummy variables was significant in
either of the models (p > .1).

Third, we zoomed in on our operationalization of the
marketing variables. Marketing activities of the five leading
nonaffected brands are reflected in our current operational-
izations. Indeed, in the brand-share model, competitive
advertising and price are captured in the denominator of the
relative variables, while for category purchases, we use the
combined (i.e., the sum or average) marketing efforts of the
affected and five largest nonaffected brands. An alternative
(but less parsimonious) specification is one in which the

70 / Journal of Marketing, March 2013

own effect is modeled separately from the cross effects. We
estimated a (main-effects-only) model with separate
endogenous own and (combined across all competitors)
cross effects.11 Splitting the own and cross effects leads to
an increase in the root mean square error from .901 to .902
for the brand-share model and from 3.508 to 3.515 for the
category-purchases model; thus, this operationalization did
not result in an improved fit relative to our specification.

In the absence of a control group, we cannot assess
what would have happened if the product-harm crisis had
not taken place. Still, to approximate this scenario, we reran
our models while controlling for the t-values of precrisis
trends in brand share and category purchases (for a similar
practice, see Pauwels and Hanssens 2007). These t-values
capture the direction and extent of precrisis tendencies in
brand share and category purchases. None of these trend
terms was significant (p > .1).12

Conclusions
Product-harm crises occur ever more frequently in today’s
marketplace, and they can seriously damage both the
affected brand and the category as a whole. Managers of
both affected and nonaffected brands often increase their
advertising support or decrease their price substantially in
the wake of a product-harm crisis in an attempt to regain
lost customers or to benefit from the misfortune of their
competitor(s). An alternative strategy is to hike prices in an
effort to safeguard the brands’ revenues. However, little is
known about the relative effectiveness of these strategies.
Indeed, prior studies that have quantified the postcrisis
effectiveness of marketing adjustments using actual con-
sumer purchase data following a real-life crisis (rather than
stated intentions following a description of a hypothetical
crisis) primarily focused on one single crisis, namely, a
peanut-butter contamination case in Australia. As such, gen-
eralizable knowledge on the phenomenon is still missing,
especially on the moderating impact of crucial crisis charac-
teristics such as the amount of negative publicity and blame
acknowledgment.

In the current study, we extend the existing knowledge
base considerably, as we analyze, using large household-
scanner data sets, 60 major FMCG product-harm crises that
recently occurred in the United Kingdom and the Nether-
lands. We examine, at the individual-household level, how
brand share and category purchases change in the year after
the crisis compared with the year before and relate this

11We thus estimated four (rather than two) endogenous variables
per model and also adapted the IVs accordingly. As such, for
brand share, we used the change between period t* – 1 and t* – 2
in both own brand advertising (price) and the advertising (price) of
the five largest nonaffected competitors, rather than a single
change in relative brand advertising (price) during the same
period. For category purchases, the included IVs are the change
between period t* – 1 and t* – 2 in both the advertising (price) of
the affected brands and the combined advertising (price) of the
five largest nonaffected competitors, rather than the single sum
across affected and nonaffected brands.

12Detailed results for all robustness checks are available on
request from the first author.

change to crisis characteristics (i.e., negative publicity and
blame acknowledgment), marketing variables (i.e., price
and advertising), and their interaction effects. We thus
obtain a contingency framework indicating what marketing
actions work more or less effectively under what type of
crisis. This framework not only contributes to the theoreti-
cal knowledge base on product-harm crises by exploring
various boundary conditions to previous main-effects-only
results but also makes the recommendations for managers
confronted with a specific crisis scenario much more
actionable.

Our empirical findings show that the effects are much
more intricate than a sole focus on the main effects would
suggest. Considering the main effect of blame acknowledg-
ment only, we might recommend acknowledging blame: we
observed no negative main effect on the acknowledging
brand’s market share, and the category as a whole benefits.
However, taking the interaction effects into account indi-
cates that there is no such thing as a free lunch. Van Heerde,
Helsen, and Dekimpe (2007) point out two additional jeop-
ardies that brand managers face when their brand is
involved in a product-harm crisis: a decrease in advertising
effectiveness (making it more difficult to recover lost mar-
ket positions) and an increased price sensitivity (making it
more difficult to raise prices to safeguard revenues). Our
results show that these additional jeopardies become partic-
ularly pronounced when the brand was to blame. Although
managers may feel an even stronger urge to increase their
advertising support when the crisis was their firm’s fault,
the effectiveness of that marketing variable is more seri-
ously damaged if blame must be acknowledged. Thus, the
risk of “spoiled arms” (Leeflang and Wittink 1996;
Steenkamp et al. 2005) increases considerably when blame
must be taken.

In addition, for competitors, increasing their advertising
may be a double-edged sword. Some nonaffected competi-
tors might view the crisis as an opportunity and ramp up
their advertising. For example, Michelin North America
hiked up its advertising budget to run a print campaign
emphasizing tire safety and quality following Bridge-
stone/Firestone’s 2000 recall of 6.5 million tires following
accidents involving defective tires (Dodosh 2000). More
recently, GM launched a campaign offering Toyota owners
an extra $1,000 rebate to switch following Toyota’s
repeated recalls (Valdes-Dapena 2010). Our findings show
that such a strategy will not work and may even backfire, if
the affected brand must publicly acknowledge blame.
Indeed, the effectiveness of category advertising under the
blame condition is significantly reduced. Thus, consumers
may view the competitors’ strategy of “chasing ambu-
lances” as being overly opportunistic.

The findings involving the negative publicity surround-
ing product-harm crises are also intriguing. Prior studies
often have not distinguished the extent of negative publicity
surrounding the event. For example, Dawar and Pillutla
(2000) and Van Heerde, Helsen, and Dekimpe (2007) both
define product-harm crises as well-publicized events
wherein products are found to be defective or even danger-
ous (italics added). However, the extent of this negative
publicity may differ widely across crises. For example,

Rising from the Ashes / 71

whereas Morrison’s recall of its tin-contaminated tomato
soup was only covered in 18% of the major U.K. newspa-
pers, the glass particles in Olvarit’s baby food attracted the
attention of all major Dutch newspapers. Notably, this dif-
ferential coverage affects the effectiveness of the response
strategies. Increased media scrutiny increases the price sen-
sitivity of the category, making across-the-board price hikes
to protect sales revenue more likely to backfire. However,
in line with Berger, Sorensen, and Rasmussen’s (2010) the-
orizing, we find that an increase in postcrisis advertising
becomes a more attractive option, for both the affected
brand and the category as a whole. Our finding of an
increase in advertising effectiveness with more publicity is
in line with the idea that the heightened awareness caused
by the media attention tends to be more persistent than the
negative valence of its content.

Table 6 offers recommendations based on our results for
brands and categories faced with a product-harm crisis. It
indicates that the relative attractiveness of changes in the
decision variables price and advertising under different cri-
sis settings. Managers should hope to never be confronted
with a product-harm crisis. However, if they are, they
would prefer that the blame is not theirs and that the crisis
does not generate a great deal of negative publicity. We use
this scenario as our base case (first line in Table 6) and eval-
uate how to use advertising and price in different circum-
stances. Advertising appears to be a tool that indeed can be
used to stimulate both primary and secondary demand
(given the significance of the respective parameters). A
price decrease, however, represents spoiled arms (Leeflang
and Wittink 1996; Steenkamp et al. 2005), given that it will
not lead to a corresponding increase in brand share. How-
ever, in the base case, price is ultimately an effective instru-
ment to protect/stimulate category consumption.

When the brand must acknowledge blame and/or when
the extent of publicity changes, the recommendations may
change, as summarized in Cases 2–4 of Table 6. Table 6
identifies settings in which advertising becomes more or
less effective and price decreases may be used as an addi-
tional instrument to protect the brand or category. For
example, in a low-publicity product-harm case in which
blame must be admitted, brands and categories are not
advised to increase advertising, because the instrument
becomes considerably less effective for both performance
metrics. However, in the opposite case (high publicity, no
blame), we definitely recommend an advertising increase.
As for price, brand price decreases are only recommended
when blame must be acknowledged, whereas category price
decreases are recommended in all cases and even more so
in case of high publicity.

While the focus of our analysis is on the actionable
interaction effects between crisis characteristics and mar-
keting adjustments, the control variables lead to some addi-
tional, managerially relevant insights. First, our results
warn managers to not take their most valuable customers
for granted (i.e., the ones that showed most behavioral loy-
alty before the crisis and/or those that have a higher cate-
gory usage). Indeed, these customers show a more negative
reaction to the crisis, supporting the notion (e.g., Grégoire
and Fisher 2008) that these customers feel particularly dis-

concerted because of the crisis. Lost trust is notoriously dif-
ficult to recover (Nooteboom, Berger, and Noorderhaven
1997); therefore, it may well take a prolonged effort.

Our results also provide additional insights into the
ongoing battle between private labels and national brands.
A great deal of crises in our sample involved private labels
that had to be taken off the shelves. It is unclear whether
this is due to an inherently lower quality (which makes
them more prone to product-harm crises) or because it is
logistically easier to recall all items from a single retailer
than from multiple retailers (as would be the case when
national brands are affected). Still, given the increasing
presence of private labels and the danger of spillover effects
to the rest of the category (see also Szymanowski and Gijs-
brechts 2012), this should be an additional concern to
national-brand manufacturers: not only do private labels
increasingly gain market share, frequent quality problems
requiring a recall may undermine the consumers’ confi-
dence in the category and thus erode category sales. This
concern is mitigated somewhat, in that we find that both the
brand and the category are hurt less when the affected brand
is a private label. This latter finding could be due to the
more limited distribution of the private-label brands (so that
only a smaller fraction of customers is exposed to the cri-
sis), but it could also be driven by consumers a priori
expecting lower quality with private labels (which reduces
the signaling value of the crisis). However, given their
higher frequency, private-label-induced product-harm crises
may well contribute considerably to the war chest national-
brand managers should put together in anticipation (for an
in-depth discussion on this issue, see Rubel, Naik, and
Srinivasan 2011) of a crisis hitting their category, which is
hardly a comforting thought.

72 / Journal of Marketing, March 2013

While we provide new, actionable insights into how to
overcome a product-harm crisis, this research is subject to
some limitations that offer opportunities for further
research. One limitation is that we study product-harm
crises in the context of FMCGs. The frequent-purchase
nature of these goods allows consumers to adjust their pur-
chase behavior rapidly, which can be readily observed in
the type of household scanner panels we used for this study.
The question remains, however, whether purchase behavior
for recalled products with longer interpurchase times (e.g.,
durables such as Toyota automobiles) shows a similar
adjustment pattern and the same sensitivity to the drivers as
we observed (for recent research on the impact of recalls in
the automobile and medical-device industries, respectively,
see Liu and Shankar 2012; Thirumalai and Sinha 2011).

Moreover, our sample of crises consisted of cases in
which at least one variety was fully recalled, and the recall
was voluntary in all instances. We thus excluded from our
analyses cases that were more limited in extent and poten-
tially issued in different batches. In addition, because our
sample solely consisted of voluntary recalls, we were not
able to examine the difference between voluntary and
forced recalls. Insights for these types of crises might be
different, which may also be the case if the crisis was so
extreme that it led to (multiple) casualties.

In line with previous research in the marketing-mix
effectiveness arena (for a review, see Leeflang et al. 2000),
we investigated both primary and selective demand. How-
ever, other sales decompositions could be considered as well.
For example, researchers could incorporate intervention
(crisis) dummies in the modeling framework of Bucklin,
Gupta, and Siddarth (1998) to assess whether marketing’s
influence as a driver of consumers’ category incidence,

Type of Product-Harm Crisis
Postcrisis Recommendations

for the Brand
Postcrisis Recommendations

for the Category

Case
Extent of Nega-

tive Publicity
Blame Must Be
Acknowledged Advertising Brand Price Category Advertising Category Price

1 (base) Low No Increase brand
advertising: effective
instrument

Keep brand
price: spoiled
arms

Increase category
advertising: effective
instrument

Decrease
category price:
effective
instrument

2 Low Yes

Do not increase
advertising: less
effective than in base
case

Decrease
price: more
effective than
in base case

Do not increase
advertising: less
effective than in base
case

Decrease price:
as effective as
in base case

3 High No

Increase advertising
even more: more
effective than in base
case

Keep price:
spoiled arms

Increase advertising
even more: more
effective than in base
case

Decrease price
even more:
more effective
than in base
case

4 High Yes

Increasing advertising
might be attractive,
depending on the net
impact of the two
opposing forces
on advertising
effectiveness

Decrease price
more: more
effective than
in base case

Increasing advertising
might be attractive,
depending on the net
impact of the two
opposing forces
on advertising
effectiveness
Decrease price
even more:
more effective
than in base
case

TABLE 6
How Brands and Categories Can Overcome Product-Harm Crises

brand choice, and quantity decisions changes when faced
with a product-harm scenario.

Moreover, it would be worthwhile to study the origin of
the product-harm crisis. When different brands (e.g., private
labels and national brands) are manufactured in the same
plant, this may affect the magnitude of spillover effects.
However, it is difficult (if not impossible) to control for this
phenomenon in the empirical analysis. For example, retail-
ers and national brand manufacturers are very secretive as
to who is involved in private label production (Gomez-
Arias and Bello-Acebron 2008; Kumar and Steenkamp
2007). Because this information is also unavailable to the
population at large, there is little a priori reason to expect
spillover effects between specific national brands and pri-
vate labels on the assumption that they could be produced
in the same plant.

More research is also needed on how national-brand
manufacturers should react to a product-harm crisis with
private labels. Given that retailers are both customer and
competitor to national-brand manufacturers, even more care
should be exercised not to display a too opportunistic behav-
ior in the case of private-label misfortune. Conversely,
national-brand recalls have a strong positive impact on the
private-label share in the category. Using an independent-
sample t-test, we found evidence of a more pronounced
growth in private-label share after a crisis with a national
brand (t = 2.509, p = .017, d.f. = 58). The product-harm cri-
sis may induce some national-brand consumers to try out
the private label, and subsequently, some of them may
remain with the private label even when the national brand
becomes available again. Lamey et al. (2007) document a
similar phenomenon following an economic crisis. More
research is needed on this phenomenon.

Our study determines the effects of product-harm crises
on both the core (the affected brand) and the next layer (the

Rising from the Ashes / 73

category). In theory, it is possible that the crisis within one
category causes spillover effects onto other categories
because of umbrella branding, complementarity or substi-
tutability of categories, comparable interpurchase times,
common use of ingredients, and/or similarities in manufac-
turing procedures. The effects on this further layer, how-
ever, are arguably smaller than the more focal effects,
whereas the number of potential intercategory effects is
potentially very large.

We concentrate on the impact of the crisis on the cate-
gory as a whole; future researchers could investigate poten-
tial differences in the after-crisis performance of specific
nonaffected competitors. Depending on the initial position-
ing (e.g., because of a perceived similarity to the affected
brand), some brands may be affected disproportionately.
Because of the crisis, individual brand shares may shift sub-
stantially, which may, in turn, lead to changes in competi-
tive structure.13 Finally, rather than focusing on the result in
the year following the crisis, researchers could consider the
more detailed (e.g., weekly) adjustments that take place
shortly after the crisis to capture in more depth the dynamic
interplay between different demand- and supply-side
mechanisms.

Despite these limitations, we believe that our study
offers several new empirical generalizations about how
product-harm crises affect consumer behavior. We hope that
firms and categories that face the challenge to overcome a
product-harm crisis benefit from our recommendations.

13In a follow-up analysis, we regressed the change in competition
density (C4) on various crisis characteristics. We found that the mar-
ket becomes more concentrated when the crisis affects a stronger
brand. In addition, Dutch categories become less concentrated after
a crisis than UK categories. Given our limited sample of affected
categories (N = 40), we were not able to explore this further.

Product-Harm Crisis Date

Number of Affected Brands
(Number of Brands Included

in Brand-Share Equation)

Sauerkraut (NL): Albert Heijn had to recall its canned sauerkraut (520g)
because of glass contamination.

01/11/2000 1 (1)

Liquor (NL): Bacardi-Breezer orange and lemon bottles (70 cl) were recalled
because of reported bursts.

10/07/2003 1 (1)

Sugar (NL): Caribbean Gold had to recall the 1kg packages and 500g cubes
packages of cane sugar because of chemical contamination.

07/13/2004 1 (1)

Baby food (NL): All varieties of Olvarit and Bebirix baby food needed to be
recalled because of glass contamination.

12/22/2005 2 (2)

Fruit for babies (NL): Olvarit and Bebirix recalled different flavors of their baby
fruit gamma because of glass contamination.

12/22/2005 2 (2)

Filet d’Ardenne (NL): Filet d’Ardenne of Albert Heijn was recalled due to
incorrect label information.

01/06/2006 1 (1)

Yorkham (NL): Albert Heijn recalled all packages of Yorkham because of
mislabeling.

01/06/2006 1 (1)

Chicken rolled meat (NL): All packages of chicken rolled meat were recalled by
Albert Heijn because of label errors.

01/06/2006 1 (1)

Minced meat (NL): Albert Heijn recalled all packages of AH minced meat
because of wrong label information.

01/06/2006 1 (1)

APPENDIX
Product-Harm Crisis Descriptions, Listed Chronologically per Country

74 / Journal of Marketing, March 2013

Product-Harm Crisis Date
Number of Affected Brands
(Number of Brands Included
in Brand-Share Equation)

Syrup (NL): Sixteen private label brands had to recall different varieties of
syrup because of the detection of particles of glass inside. We observe
purchases of Albert Heijn, Edah, Etos, Kruidvat, Markant, O’Lacy’s, Perfekt,
Plus, Spar, Vitafit (Lidl), C1000, Dixap (Covelt), and Super de Boer.

11/29/2006 16 (13)

Chicken nuggets (UK): Sainsbury recalled its 18 fresh nuggets variety (312g)
because of quality defects.

04/21/2000 1 (1)

Canned pilchards (UK): The Namibian South Atlantic pilchards in tomato sauce
(425g) of the brands Glenryck and Princes had to be recalled because of a
fault in the manufacture of the can.

06/14/2000 2 (2)

Tomato soup (UK): 15 private labels had to recall their cans of tomato soup
(410g) because of elevated levels of tin. We only include Morrisons in our
analysis because it was the only brand that had to fully recall this variety.

11/16/2000 15 (1)

Butter (UK): Kerrygold spreadable butter was recalled because of glass
contamination.

07/28/2001 1 (1)

Flavored mineral water (UK): Sainsbury recalled its strawberry-flavored
Caledonian still water (2 l) because of deficient quality.

08/10/2001 1 (1)

Custard (UK): Ambrosia Devon had to recall all custard varieties of 1kg and
500g because of deterioration before use-by date.

08/24/2001 1 (1)

Spring water (UK): Chiltern Hills and Ashridge Spring recalled their bottles of
water after they were found to be contaminated with feces. Ashridge Spring
was not observed in the purchase database, so it is not included in our
analysis.

11/23/2001 2 (1)

Dairy-free iced dessert (UK): Sainsbury dairy-free chocolate iced dessert (500
ml) was recalled because of the detection of traces of milk even though it
was labeled milk-free.

12/10/2001 1 (1)

Profiteroles (UK): Co-op’s frozen dairy cream profiteroles (280g) were recalled
because of the detection of traces of nut even though it was labeled nut-free.

07/18/2002 1 (1)

Baby Food (UK): Heinz recalled different varieties of baby food because they
were incorrectly labeled as milk-free.

08/29/2002 1 (1)

Canned soup (UK): Sainsbury had to recall its cream of potato and leek
canned soup (400g) because of bursting cans and evidence of spoilage.

03/14/2003 1 (1)

Liquor (UK): Bacardi Breezer and Coomira Coast recalled all 70cl bottles
because of bursting bottles. We focus on Bacardi Breezer because Coomira
Coast was not observed in the purchase database.

10/08/2003 2 (1)

Pesto Sauce (UK): Different brands of pesto sauce were recalled after the cancer-
causing chemical Sudan 1 was discovered. We include only the Bertolli
brand in the analysis because Safeway and Sainsbury’s only recalled parts
of their varieties and the Al Cirio brand was not observed in the purchase
database.

09/16/2003 4 (1)

Muffins (UK): Six private labels brands of white muffins had to be recalled
because of mislabeling. Only Asda recalled the entire variety.

10/28/2004 6 (1)

Cookies (UK): Sainsbury freefrom coconut and raspberry cookies (200g) were
recalled because of mislabeling.

01/28/2005 1 (1)

Ice cream (UK): Sainsbury recalled its frozen freefrom raspberry iced dessert
(500 ml) because of mislabeling.

04/28/2005 1 (1)

Pasta salad (UK): Sainsbury recalled its tuna and sweet corn pasta salad
(300g) because of inconsistencies between the allergy information on the
package and the ingredient list.

09/23/2005 1 (1)

Candy (UK): Basset’s milky babies (165 and 200g) had to be recalled because
of the presence of pieces of plastic in the candy.

10/05/2005 1 (1)

Chocolate (UK): The basic plain chocolate (100g) variety of Sainsbury was
taken off the shelves because of mislabeling.

10/06/2005 1 (1)

Toothbrushes (UK): Boots smile toothbrushes were recalled because of
choking hazard linked to potential breaks of the product.

10/27/2005 1 (1)

Yogurt (UK): Brooklea (Aldi) thick and creamy strawberry yogurt (150g) was
recalled because of glass contamination.

02/06/2006 1 (1)

APPENDIX
Continued

Rising from the Ashes / 75

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03/19/2007 6 (4)

APPENDIX
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articles for individual use.

Product recalls and the moderating role
of brand commitment

Frank Germann & Rajdeep Grewal &
William T. Ross Jr. & Rajendra K. Srivastava

Published online: 6 July 201

# Springer Science+Business Media New York 2013

Abstract We assess attenuating and augmenting effects of brand commitment on
consumer responses when product recalls occur. Consistent with our theorization,
results from a laboratory experiment and an event study show that high levels of
brand commitment attenuate negative consumer responses in low-severity product
recalls but augment them in high-severity product recalls. Thus, while brand com-
mitment seems to provide a reservoir of goodwill in the former case, it acts as a
liability in the latter. These findings add to the extant brand and product recall
literature by demonstrating that brand commitment has a complex effect on consumer
responses when product recalls occur. Because product recalls are widespread, these
findings also have managerial relevance.

Keywords Brand commitment . Product recall . Corporate crises . Experiment .

Event study

Mark Lett (2014) 25:179–19

DOI 10.1007/s11002-013-9250-5

F. Germann (*)
395 Mendoza College of Business, University of Notre Dame, Notre Dame, IN 46556, USA
e-mail: fgermann@nd.edu

R. Grewal
Smeal College of Business, Pennsylvania State University, 407 Business Building, University Park,
PA 16802, USA
e-mail: rgrewal@psu.edu

W. T. Ross Jr.
School of Business, University of Connecticut, 2100 Hillside Road Unit 1041, Storrs, CT 06269, USA
e-mail: bill.ross@business.uconn.edu

R. K. Srivastava
Lee Kong Chian School of Business, Singapore Management University, 50 Stamford Road,
Singapore 178899, Singapore
e-mail: rajs@smu.edu.sg

1 Introduction

Product recalls are ubiquitous and familiar, including toys with toxic paint,
seafood contaminated with dangerous antibiotics, and cars that accelerate seem-
ingly on their own (e.g., Cleeren et al. 2013). In 2012 alone, the US Consumer
Products Safety Commission announced more than 250 product recalls, and the
Food and Drug Administration reported on over 300 such events. These
numbers are sobering and suggest that no manufacturing firm is immune to
product recalls.

The prevalence and potential harmfulness of product recalls has prompted several
streams of research in Marketing, including investigations of their performance
consequences (e.g., van Heerde et al. 2007), comparisons of proactive, firm-
initiated recall strategies with reactive, passive approaches (Chen et al. 2009), and
examinations of how consumer-level differences affect recall perceptions and re-
sponses (e.g., Cleeren et al. 2008).

Most research indicates that consumers respond negatively to product recalls (e.g.,
Lei et al. 2012), and one research stream focuses specifically on how industry-, firm-,
and/or consumer-related factors influence consumer responses. For example, in
studying product recalls in the U.S. automobile industry, Rhee and Haunschild
(2006) examine the moderating role of firm quality reputation on future product
sales, Klein and Dawar (2004) note how corporate social responsibility affects
consumers’ attributions in product harm crises, Lei et al. (2012) examine how the
frequency of such crises in an industry influences consumers’ attributions for failure,
and Ahluwalia et al. (2000) examine brand commitment’s role when brands receive
negative publicity and find that brand commitment attenuates consumers’ responses
to negative information.

In this research, we examine how brand commitment moderates negative infor-
mation effects of product recall announcements. Specifically, building on Ahluwalia
et al. (2000), we investigate whether brand commitment provides a “reservoir of
goodwill” (Jones et al. 2000) for the recalling firm by attenuating the generally
negative consumer responses to product recalls.

In addition, we reason that brand commitment might also augment the negative
information effects of a product recall. For example, highly committed consumers
may experience a feeling of betrayal and hence be especially disappointed when the
products they feel close to get recalled. Thus, departing from Ahluwalia et al. (2000)
and adding to the extant literature, we also examine whether brand commitment
might in fact serve as a liability for the recalling firm.

To unravel these seemingly contradictory effects of brand commitment (i.e.,
reservoir of goodwill or liability), we recognize that product recalls are not homoge-
neous events and suggest that product recall severity—defined as the consumer-based
tribulations (or potential thereof) caused by the recalled product—is an important
distinguishing factor of product recalls. To understand the role of brand commitment,
we examine how product recall severity interacts with brand commitment during a
product recall event. We posit that brand commitment can have both attenuating and
augmenting effects on negative consumer responses to recalls, and we predict that,
while brand commitment should provide a reservoir of goodwill in low severity
recalls, it likely becomes a liability in high severity recalls.

180 Mark Lett (2014) 25:179–191

We use a laboratory experiment and an event study to test our ideas. Confirming
the theorized effect, our results from the experiment indicate that high levels of brand
commitment attenuate negative consumer responses in low severity recalls but
augment them in high severity recalls. Moreover, the results from the event study
suggest that the stock market responds in a manner consistent with the expected
consumer responses to product recalls.

2 Conceptual background and hypotheses

In this section, we describe the conceptual background of the research. We begin by
describing our two focal constructs, brand commitment, and product recall severity and
then present our hypotheses regarding brand commitment’s dual role in product recalls.

2.1 Brand commitment

Consumers can become attached to brands, form close relationships with them (e.g.,
Fournier 1998), and have a general desire to maintain this close relationship (e.g.,
Beatty et al. 1988). In line with extant research (e.g., Ahluwalia et al. 2000), we
define a consumer as committed to a brand if s/he displays these characteristics.

2.2 Product recall severity

Product recalls are not homogeneous but rather vary in their severity, among other
factors. Consistent with Cheah et al. (2007), we define recall severity as the
consumer-based tribulations (or potential thereof) caused by the recalled product.
For example, considering past product recalls, some products had caused serious
health problems (e.g., Toyota’s recall at the end of 2009 after reports that vehicles
experienced unintended acceleration; the error has been linked to over 20 deaths and
many severe injuries); others were responsible for only minor injuries or caused no
harm at all (e.g., Chrysler’s recall in 2004 because of a wiring issue; no injuries or
deaths were linked to the error). The Toyota recall can be classified as a high- and the
Chrysler recall as a low-severity recall.

An important dimension of recall severity is the recall’s perceived ambiguity. In
particular, the level of recall severity correlates with the perceived ambiguity of the
recall event (e.g., Cheah et al. 2007), such that a non-severe recall tends to appear
ambiguous whereas a severe one does not. Consumers may not be able to determine
the extent to which the firm has committed a transgression when recall severity is low.
In fact, the recall even may suggest that the recalling firm is acting responsibly and
putting customers’ needs first. In contrast, high-severity recalls do not seem ambig-
uous, because, at least, some consumers experience significant tribulations in these
cases, including injuries or even death.

2.3 Brand commitment’s role when product recalls occur

Most research indicates that consumers respond negatively to product recalls (e.g.,
Lei et al. 2012). However, Ahluwalia et al. (2000) show that committed consumers

Mark Lett (2014) 25:179–191 181

exhibit greater resistance to negative information about well-liked brands. They
also show that committed consumers engage in biased processing of negative
information by counterarguing the negative information, which, in turn, atten-
uates negative consumer responses (i.e., negative attitude change) following the
learning of the negative information. In addition, Ahluwalia et al. (2000) show
that when commitment to a brand is lower, consumers process the negative
information more objectively. Consequently, counterarguing is less and negative
attitude change is more prevalent among less committed consumers. This
finding is particularly relevant for our study because it suggests that brand
commitment attenuates the generally negative consumer responses to product
recall announcements.

Yet, research has also identified mechanisms by which high brand commitment
may augment the negative consumer responses to a product recall announcement.
Specifically, building on the well-established expectancy–disconfirmation effect
(Oliver 1993), committed consumers may come to expect more from the brand they
like and thus feel especially disappointed when the brand gets recalled. Indeed,
committed consumers might view a product recall as a “breach of contract,” and
hence might exhibit more negative responses following a recall announcement than
their less committed counterparts.

The preceding discussion outlines two conceivable logics for predicting how brand
commitment affects consumer responses to product recalls. Given the conflicting
nature of these logics, the question arises whether a moderator might help disentangle
the contradictory perspectives. We posit such a moderator in recall severity, and we
outline our reasoning below.

As noted above, perceived ambiguity is an important dimension of recall
severity such that a low-severity recall tends to appear ambiguous whereas a
high-severity recall does not. Building on the ambiguity dimension, we posit
that highly committed consumers should tend to counterargue the negative
information of a low-severity recall and thus discount the recall as an aberrant
one-off event unlikely to reoccur. In contrast, lacking the strong positive
associations, less committed consumers should handle the negative information
more objectively and counterargue it less. Accordingly, and consistent with
Ahluwalia et al. (2000), we expect that highly committed consumers should
experience less negative attitude change than less committed consumers in low-
severity recalls.

However, for a high-severity recall, we posit that the brand’s unambiguous
negative performance impedes counterarguing and instead refutes the generally
high expectations of the committed consumers which, in turn, should provoke
disconfirmation effects. This disconfirmation effect might feel personal for
committed consumers, like a feeling of betrayal, and we thus expect them to
express thoughts suggesting that the recall is not at all consistent with their
expectations (referred to as incongruity thoughts in the following). In contrast,
without strong positive associations, less committed consumers should lack
expectations about the brand’s performance, so the disconfirmation effect
should be weaker for them. Accordingly, we also expect less committed
consumers to express significantly fewer incongruity thoughts. As a result,
we expect that highly committed consumers should experience more negative

182 Mark Lett (2014) 25:179–191

attitude change than less committed consumers in high-severity recalls. Thus,
we propose:

H1: Brand commitment attenuates negative consumer responses in low severity
product recalls but augments negative consumer responses in high severity
product recalls.

H2: The effect of brand commitment on negative consumer responses is medi-
ated by counterarguments in low severity product recalls and by incongruity
thoughts in high severity product recalls.

In what follows, we first test our hypotheses in a laboratory setting (i.e., test H1
and H2) and then using an event study (i.e., (re-)test H1).

3 Laboratory experiment

A total of 133 students from a U.S. university participated for extra credit. The
participants were randomly assigned to one of two conditions (recall severity: high
versus low).

3.1 Procedure

When they arrived for the experiment, participants were told that they would be
participating in a media study, in which they would evaluate “breaking news articles”
published online on the morning of the experiment by a well-known news provider
(CNN.com). We also indicated that the news articles contained information about
brands and that we would ask them to evaluate these brands. We administered the
experiment using Qualtrics, and the experiment included three contiguous sections. In
the first section, participants were asked to evaluate the brands prior to learning more
about them in the news articles. We also measured participants’ commitment to the
brands in the news articles in this section using the three-item brand commitment
measure developed by Beatty et al. (1988).1

In the second section, we provided three news articles for participants to read. To
control for position effects, the focal, fictional article about a product recall always
appeared second. The remaining two articles that served as filler were based on real
articles and served to reduce the likelihood of ceiling effects due to excessive
attention focused on the target message (Ahluwalia et al. 2000). After reading each
of the three articles, the participants were instructed to take 2 min to list all their
thoughts while reading the article. As we describe in more detail, we used these
thought protocols for our process test.

Finally, in the third section, participants were asked again to evaluate the brands
mentioned in the previous news articles. We debriefed participants after they finished

1 The three items are (1) “If brand X were not available at a store, it would make little difference to me if I
had to choose another brand”; (2) “I consider myself to be highly loyal to brand X”; and (3) “When another
brand is on sale, I would purchase it rather than brand X.” (coefficient alpha=0.87). Ahluwalia et al. (2000)
used the same scale to measure brand commitment.

Mark Lett (2014) 25:179–191 183

by stating that the target article was fictional and that they should therefore ignore the
information it presented.

3.2 Stimuli and variables

We selected smartphones as the target product category, because the student respon-
dents were familiar with this product category. We fabricated target messages on the
basis of a series of pretests. The high-severity message focused on a recent scientific
report that indicated that iPhone smartphone users were 207 times more likely to
suffer from life-threatening brain hemorrhages. The message also indicated that a
recall was unavoidable. The low-severity report stated that about 10,000 iPhone5s
were being recalled over a battery issue. In a pretest, 62 participants read either the
high- or low-severity message, in relation to an unknown brand of smartphones, and
rated event severity on a seven-point scale (1–7). They considered the messages
significantly different in severity (meanhemorrhages=6.53; meanbattery=3.36; t=9.72,
p<0.001). The target messages are available from the authors.

We measured consumer responses to the recall (i.e., our dependent variable) by
assessing the degree to which the participants’ attitude toward the iPhone changed
from before they read the message to after. Specifically, for each participant, we
subtracted the postmessage mean attitude score from the premessage mean attitude
score; these scores came from four seven-point Likert scales (anchored by
“good/bad,” “beneficial/harmful,” “desirable/undesirable,” “favorable/unfavorable”)
(coefficient alpha=0.96), adapted from Ahluwalia et al. (2000).

3.3 Results

Our prediction that brand commitment attenuates negative consumer responses (i.e.,
attitude change in the experiment) for low-severity recalls but augments them for
high-severity recalls implies an interaction between recall severity and brand com-
mitment. To test our prediction, we performed an ordinary least squares regression on
attitude change with independent variables (1) brand commitment, (2) a dummy
variable for high (=1) and low (=0) recall severity, and (3) their interaction.
Overall, the model was significant (F (3, 129)=43.21, p<0.001), and the results showed a significant interaction (bBrand Commitment×Recall Severity=0.26, t=2.44, p<0.05). To further explore the interaction, we next examined the slopes of brand commitment at each level of severity. As we predicted, the slope of brand commit- ment was (marginally) significant and negative (bBrand Commitment=−0.076, t=−1.89, p<0.10) in the low-severity condition and (marginally) significant and positive (bBrand Commitment=0.185, t=1.78, p<0.10) in the high-severity condition. We also conducted a spotlight analysis at one standard deviation above and below the mean of brand commitment. We present the results from the spotlight analysis in Fig. 1 which

2 Measuring attitude change as a difference raises the issue of whether the difference scores are reliable.
Extant research (e.g., Collins 1996) has shown that difference scores are unreliable only when the pretest (x)
and posttest (y) standard deviations are equal (i.e., 1=σx/σy=1) and when the correlation between the two
scores is high (ρxy≈1). Considering our data, 1=0.57 and ρxy=0.47, in support of the reliability of our
measure. The temporal proximity of the pre- and posttest scores remains a limitation.

184 Mark Lett (2014) 25:179–191

illustrates that the highly committed consumers experienced less (more) attitude
change in the low (high) severity condition than the less committed consumers.

3.4 Process tests

As outlined above, we expect that committed consumers express significantly more
counterarguments in the low-severity recall condition than their less committed
counterparts. Furthermore, we reason that these counterarguments account for (i.e.,
mediate) the observed difference in attitude change between high- and low-
commitment consumers. We also expect that committed consumers express signifi-
cantly more incongruity thoughts in the high-severity recall condition than less-
committed consumers, and we again anticipate that these incongruity thoughts
account for (i.e., mediate) the observed difference in attitude change between the
high- and low-commitment consumers.

Two judges coded participants’ listed thoughts related to the focal article using two
categories: counterarguments and incongruity thoughts. We followed Ahluwalia et
al.’s (2000) approach for the coding of the counterarguments. The judges achieved
high intercoder reliability (agreement>83 %) and resolved disagreements through
discussion. We used these thought protocols in our process analysis.

Considering the low-severity recall scenario, counterarguments were more preva-
lent among high- rather than low-commitment consumers (meanlow BC=0.71,
meanhigh BC=1.34; t=2.44, p<0.05). A different pattern emerged in the high-severity condition: Again as predicted, incongruity thoughts were much more prevalent among high- than low-commitment consumers (meanlow BC=1.06, meanhigh BC=1.87; t=2.76, p<0.01).

We conducted the mediation analysis separately for the low- and the high-severity
conditions. To test if counterarguments mediate the identified attenuating effect of
brand commitment in low-severity recalls, we included the number of counterargu-
ments as mediators of the effect of brand commitment on attitude change. Following
Zhao et al. (2010), we assessed mediation using the bias corrected bootstrap test of

0.3267

2.9364

0.4628

2.6045

0.599

2.2727

0.5

1.5

2.5

3.5

Low Severity High Severity

A
tt

it
u

d
e

ch
an

ge
(

at
ti

tu
d

e
b

ef
or

e-
at

ti
tu

d
e

af
te

Brand Commitment (+1 SD) Brand Commitment (Mean) Brand Commitment (-1 SD)

Fig. 1 Spotlight analysis: illustrating the attenuating and augmenting effects of brand commitment

Mark Lett (2014) 25:179–191 185

the indirect effect. As expected, counterarguments emerged as a significant mediator
of brand commitment’s effect on attitude change. Using 5,000 bootstrap samples, the
bias corrected 95 % confidence interval for the indirect effect of the path through
counterarguments was [−0.051; –0.001] with a point estimate of −0.019. We note
that, since the 95 % confidence interval does not include zero, we can conclude that
the estimate of the indirect path from brand commitment to attitude change through
the number of counterarguments is significant at p<0.05. Thus, counterarguments mediate the difference in attitude change between high- and low-commitment con- sumers in low-severity recalls.

We then repeated the mediation analysis for the high severity condition and
included the number of incongruity thoughts as mediators of the effect of brand
commitment on attitude change. As predicted, incongruity thoughts emerged as a
significant mediator of brand commitment’s effect on attitude change. Again using
5,000 bootstrap samples, the bias-corrected 95 % confidence interval for the indirect
effect of the path through incongruity thoughts was [0.061; 0.262] with a point
estimate of 0.147. The confidence interval again did not include zero. Thus, incon-
gruity thoughts mediate the difference in attitude change between high- and low-
commitment consumers in high severity recalls.

In summary, the experiment provides empirical support for both H1 and H2.

4 Event study

To increase the external validity of our study, we also conducted an event study consid-
ering product recalls in the automobile industry. To ensure that stock market returns offer a
good measure of consumer responses to product recalls, we turn to Wiles et al.’s (2010)
study of deceptive advertising. In their survey of stock analysts, they find that the
respondents attended assiduously to the effects of the transgression on consumers’
perceptions of the firm, in the belief that those perceptions would affect sales and thus
financial performance. This reasoning is even more applicable for product recalls because,
in this case, the products themselves fail, not just the communication. Thus, we assert that
a product recall may be even more susceptible to negative reactions by consumers.

4.1 Sampling procedures

Similar to other event studies (e.g., Chu et al. 2005), we used the Wall Street Journal
(WSJ) index to identify car manufacturer product recalls that the WSJ reported between
2001 and 2009. Our initial sample consisted of 66 recalls. We then excluded any
duplicate announcements due to repeated recalls and conducted a Factiva database
search (e.g., McWilliams and Siegal 1997) to remove firms with confounding events.
Our final sample consists of 55 recalls of seven publicly traded car manufacturers. The
seven firms are General Motors, Ford, Nissan, Daimler, Honda, Chrysler, and Toyota.

4.2 Variables and analysis

Our dependent variable is the firm’s cumulative average abnormal return (CAAR)
resulting from a recall event. We used the Fama-French four-factor model (Fama and

186 Mark Lett (2014) 25:179–191

French 1993; Srinivasan and Bharadwaj 2004) to generate the expected return for
security i on day t.

Brand commitment We used Interbrand’s “Best Global Brands” ranking and its brand
values as a measure of the focal firms’ brand commitment. According to Interbrand,
two key aspects of their brand value measure are (1) the brand’s ability to create
loyalty and (2) the portion of purchase decisions that can be attributed to the brand
(Interbrand 2013). Thus, while certainly not a perfect measure, we reason that
Interbrand’s brand value measure is an acceptable surrogate measure of brand
commitment.

Interbrand makes the ranking and values of the top 100 brands available on
its website going back to 2001 (Interbrand 2013). Five of the seven car
manufacturers that form our sample appear in the top 100 ranking during the
focal years, and we used the respective yearly brand values listed as an
estimate of the recalling firm’s brand commitment. We note that the brand
values of our sample firms varied over time. Furthermore, we used a brand
value of zero for the two firms (General Motors and Chrysler) that did not
appear in any of the yearly rankings. We note that Daimler does not appear in
the ranking either; however, its main car brand, Mercedes, does. Hence, we use
the respective Mercedes brand value as the brand value for Daimler. We view
this as unproblematic as all Daimler recalls involved the Mercedes brand. We
also note that Chrysler and Daimler were one legal entity during parts of our
observation period. However, given the different brand values attached to the
two companies’ cars, we treated the two as separate entities in our analysis. As
we mention later, we control for firm specific heterogeneity, which should parse
out firm specific idiosyncrasies.

Recall severity Objective and/or third-party severity scores for our sample recalls were
not available. We hence relied on three expert coders who rated our sample recalls as
either high or low in recall severity based on the information provided in the WSJ
articles. The inter-coder reliability was 86 %, and all disagreements were resolved
through discussion. Of the 55 recalls in our sample, 28 (51 %) were coded as high-
severity recalls and 27 (49 %) as low-severity recalls. We used an indicator variable for
recall severity (high-severity recall=1; low-severity recall=0) in our analysis.

Modeling approach The typical approach in event studies is to regress abnormal returns
on a set of explanatory variables (MacKinlay 1997). We follow this approach here.
Furthermore, each of our sample firms issued at least three recalls during our observation
period on which the WSJ reported (Ford, 15, General Motors, 12, Toyota, 11, Chrysler,
7, Daimler, 4, Nissan, 3, and Honda, 3). Thus, we have repeated observations per sample
firm, and we hence estimated a random-effects regression model as specified below to
test our hypothesis.3 Using a random-effects regression model greatly reduces the
possibly pernicious effect of an omitted variable bias.

3 We also estimated a fixed-effects model and then conducted the Hausman test to determine whether the
random effects model is appropriate. The Hausman test yielded a statistically non-significant χ2 (χ2=0.296)
suggesting that the random effects model is appropriate.

Mark Lett (2014) 25:179–191 187

CAARit ¼ β0 þ β1Brand Commitmentit þ β2Recall Severityit
þβ3Brand Commitmentitx Recall Severityit þ αi þ εit

ð1Þ

where CAARit is the cumulative average abnormal return for firm i at time t, β’s are
coefficients to be estimated, αi is the random intercept for each firm (i.e., the between-
firm error), and εit is the within-firm error. We present descriptive statistics in Table 1.

4.3 Event study results

Consistent with prior event studies (e.g., Wiles et al. 2010), we employed the CAAR
from the [−1,0] event window in our analysis. The test statistics revealed a
(marginally) significant, negative CAAR for the [−1,0] event window (−0.37 %;
generalized sign test z=−1.913; p<0.10). We show our regression results in Table 2.

Overall, the model is significant (Wald χ2 (3)=15.90, p<0.01). Moreover, we again find empirical support for H1. First, the brand commitment main-effect was positive and significant (bBrand Commitment=0.000068, z=2.03, p<0.05) suggesting that high levels of brand commitment attenuate negative returns in low-severity recalls. Note that, due to our coding structure (i.e., high severity recalls are coded as 1), the brand commitment main effect captures brand commitment’s impact on abnormal returns in low-severity recalls. Second, the interaction term between brand commitment and recall severity was negative and significant (bBrand Commitment×Recall Severity=−0.00016, z=−3.67, p<0.01). We also investigated the nature of the slope of abnormal returns in high-severity recall cases considering brand commitment by adding the bBrand Commitment and the bBrand Commitment x Recall Severity coefficients and calculating the standard error for the expression. As expected, the combined coefficient was negative and significant (bCombined=−0.000094, z=−3.24, p<0.01), suggesting that brand com- mitment augments negative returns in high-severity recalls. We also reversed the recall severity coding structure (i.e., we coded low severity recalls as 1) and re-ran the model. In this case, the brand commitment main effect captures brand commitment’s impact on abnormal returns in high severity recalls. The results, of course, were the same (i.e., bBrand Commitment=−0.000094, z=−3.24, p<0.01).

Table 1 Correlations and summary statistics

Correlations

1 2 3

Variables

1. Cumulative average abnormal return [−1, 0] 1.000
2. Brand commitment −0.105 1.000
3. Recall severity −0.137 −0.198 1.000

Summary statistics

Mean −0.370 12045 0.509
Standard deviation 1.902 10850 0.505

None of the correlations are significant at p<0.05

188 Mark Lett (2014) 25:179–191

5 Conclusions

Our study contributes to marketing theory in two ways. First, we extend the product
recall literature by revealing the importance of brand commitment in product recall
incidents. Product recalls are increasingly rampant in the marketplace, and they have
provoked a significant amount of research attention (e.g., Cleeren et al. 2008; Chen et
al. 2009; van Heerde et al. 2007). In this study, we systematically explore how brand
commitment, in combination with recall severity, affects consumer responses to
product recalls. We find that, while brand commitment attenuates negative consumer
responses in low-severity recalls, it augments them in high-severity recalls. Thus,
while brand commitment seems to provide a reservoir of goodwill in the former case,
it acts as a liability in the later. Second, our study contributes to the brand commit-
ment literature. To the best of our knowledge, this investigation is one of the first to
pinpoint circumstances under which brand commitment constitutes a liability.

We believe that our findings also offer useful implications for marketing practice. We
show that brand commitment can produce negative outcomes, so marketing managers
must take our findings into consideration. Noting the value of brand commitment,
common beliefs seem to imply that a brand with many committed consumers enjoys a
reservoir of goodwill, regardless of negative events. Specifically, we surveyed 35 U.S.
executives about whether brand commitment should help or hurt when product recalls
occur; most (81 %) asserted that brand commitment would be advantageous for a
recalling firm. Our study contests this widespread conventional wisdom.

While we believe that we have broken some new ground with this work, there are
clear limitations, several of which provide avenues for further research. First, we
consider consumer responses immediately following the recall announcement; we thus
cannot examine how the firm’s handling of the recall might affect consumer responses.
A well-managed, high brand commitment/high-severity recall may offset the
augmenting effects of brand commitment, whereas a poorly managed, high brand
commitment/high-severity recall could evoke even more negative consumer responses.
Also, perhaps a well-managed, high brand commitment/low-severity recall could lead to
positive consumer responses. Additional research should examine how brand commit-
ment, recall severity, and recall management jointly affect consumer responses.

Table 2 Random-effects regression results with cumulative average abnormal return as the dependent
variable

Variable β SE z

Brand commitment 0.000068 0.000033 2.03

Recall severity 1.381041 0.7203483 1.92

Brand commitment×recall severity −0.000162 0.000044 −3.67
Constant −1.066828 0.5752478 −1.85
n 55

Wald χ2 15.9

df 3

Pvalue <0.01

Mark Lett (2014) 25:179–191 189

Second, product recalls are multi-faceted, heterogeneous events, and they vary
across several factors, with recall severity being one of them. For example, some
recalls involve more than 100,000 units whereas others only involve 10,000 units.
Also, some recalls involve convenience products (e.g., toothpaste), and others in-
volve shopping products (e.g., cameras). It is conceivable that consumers might
respond differently depending on, e.g., the amount and type of product involved,
and future research might examine additional dimensions of recall events.

Third, our results suggest that product recalls must stem from a serious, potentially
life-threatening offense for the augmenting effect of brand commitment to play a role.
This raises questions of whether the augmenting effect also manifests in less egre-
gious recall events and, more generally, where the “tipping point” is, beyond which
brand commitment acts as a liability.

Finally, we believe that it would be interesting to examine whether brand com-
mitment’s dual role also occurs in other types of negative firm events besides product
recalls. For example, what happens when the firm is accused of having polluted the
environment? Will brand commitment attenuate or augment potentially negative
consumer responses? Future research should test whether brand commitment’s atten-
uating and augmenting effects also manifest in other types of firm events.

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Product recalls and the moderating role of brand commitment

Abstract
Introduction
Conceptual background and hypotheses
Brand commitment
Product recall severity
Brand commitment’s role when product recalls occur
Laboratory experiment
Procedure
Stimuli and variables
Results
Process tests
Event study
Sampling procedures
Variables and analysis
Event study results
Conclusions
References

Studying the International Crisis
Group
Berit Bliesemann de Guevara*
Department of International Politics, Aberystwyth University, Wales, UK

This special issue studies the International Crisis Group (ICG), one of
the most notable and widely referenced producers of knowledge
about conflict areas, used extensively by policy makers, the media
and academics. The authors take different theoretical and methodo-
logical approaches to make sense of this hard-to-ignore conflict
expert, exploring the ICG’s daily operations and role in international
politics. This introduction sets the scene by offering a critical explora-
tion of the organisation and its approach to the construction of politi-
cal knowledge. It analyses the ICG’s position in the conflict-related
knowledge market and the sources of its expert authority. It then dis-
cusses the organisation’s roles – from mediation to instrumentalisation
– in the ‘battlefield of ideas’ in conflict and intervention contexts and
its potential to make an impact on policy framings and outcomes. It
shows that studies of the ICG need to ‘unpack’ the organisation in
order to account for it as both a highly successful international expert
brand and a very heterogeneous actor in specific contexts and at
specific times.

Keywords: International Crisis Group (ICG); political knowledge;
expert authority; conflict; intervention; crisis; advocacy; symbolic
capital

Introduction
This issue of Third World Quarterly is dedicated to the study of one of the most
notable and widely referenced producers of knowledge about conflict areas, used
extensively by policy makers, the media and academics: the International Crisis
Group (ICG). Policy-relevant ‘conflict knowledge’ is produced and distributed by
many actors. These include state ministries and (intelligence) agencies, interna-
tional organisations’ lessons learned units, branch offices and field missions,
fact-finding missions, contracted consultants, NGOs working in conflict areas, and
traditional and new media, to name just some of the more prominent ones.
While it is just one voice in this mixed choir of conflict-related knowledge pro-
ducers, the ICG is without question one that has very influential listeners.
Founded in 1995 as ‘an independent organisation that would serve as the

*Email: beb14@aber.ac.uk

Third World Quarterly, 2014
Vol. 35, No. 4, 545–562, http://dx.doi.org/10.1080/01436597.2014.924060

mailto:beb14@aber.ac.uk

http://dx.doi.org/10.1080/01436597.2014.924060

world’s eyes and ears on the ground in countries in conflict while pressing for
immediate action’,1 the ICG is a paramount example of a highly visible, vocal,
hard-to-ignore conflict expert.

In a 2013 global think-tank ranking, the ICG was sixth among top-think tanks
in Western Europe,2 and 10th among non-US think-tanks worldwide, with the
Stockholm International Peace Research Institute (SIPRI) (no. 3) and the Interna-
tional Institute for Strategic Studies (no. 4) being the only war-related think-
tanks ahead of it.3 In the combined list of US and non-US top think-tanks, the
ICG ranks 16th, now additionally outranked by the Carnegie Endowment for
International Peace (no. 3) and the German Institute for International and
Security Affairs (no. 15).4

The ICG describes itself on its website as ‘an independent, non-profit, non-
governmental organisation committed to preventing and resolving deadly con-
flict’. Currently it is ‘covering some 70 areas of actual or potential conflict
(through analysts operating from regional or field bases, or consultants)’.5 In
addition to its Brussels headquarters, ‘the organisation has offices or representa-
tion in 34 locations: Abuja, Bangkok, Beijing, Beirut, Bishkek, Bogotá,
Bujumbura, Cairo, Dakar, Damascus, Dubai, Gaza, Guatemala City, Islamabad,
Istanbul, Jakarta, Jerusalem, Johannesburg, Kabul, Kathmandu, London,
Moscow, Nairobi, New York, Port-au-Prince, Pristina, Rabat, Sanaa, Sarajevo,
Seoul, Tbilisi, Tripoli, Tunis and Washington DC’ – with Brussels, New York,
Washington, London, Moscow and Beijing serving as advocacy offices. In total
the ICG employs ‘some 130 permanent staff worldwide, from 53 nationalities
speaking 50 languages’.6 ICG reports and briefings are known to be timely,
detailed and useful, and their generally good reputation among the policy
community is based on their perceived accuracy, insight and objectivity.7 ICG
reports claim, and are perceived, to represent ‘authentic’ knowledge about
conflicts (see Bøås in this issue). Or, as the ICG words it on its website, the
organisation plays a key role by ‘providing objective analysis and detailed actor
mapping unobtainable elsewhere on developments regarding conflict, mass
violence and terrorism’.

The ICG aims to exert influence on agenda setting, policy making and policy
implementation in post-/conflict areas. It does so not only by providing policy
makers with information in the form of detailed analyses and early warning
alerts and by publishing widely through traditional and electronic media. Impor-
tantly the organisation also lobbies more directly for certain agendas and poli-
cies. According to its website, it ‘conducts some 5000 advocacy meetings with
policymakers and other decision-makers’ per year.8 In the eyes of peers and
experts the ICG’s advocacy efforts seem to pay off: the think-tank report ranks
the ICG eighth for best advocacy campaign.9 The ICG attributes its influence on
policy makers to ‘key roles being played by senior staff highly experienced in
government and by an active Board of Trustees’,10 whose composition of former
high-level statespersons and other influential personalities resembles a ‘who’s
who of influential power brokers’ in international politics, as a 2005 Time Asia
article described it.

The ICG’s more general information dissemination strategies and media lob-
bying campaigns aim to raise awareness about emerging wars, ongoing conflicts
and areas forgotten by the ‘international community’. Especially in cases where

546 B. Bliesemann de Guevara

the ICG has been among the first vocal experts reporting on a conflict, it is
highly plausible that the organisation has had some influence on how these con-
flicts have been labelled and framed (see Simons and Bøås in this issue). The
ICG claims on its website that every year it ‘publishes around 90 reports and
briefings, containing between them some 800 separate policy recommendations’,
with ‘over 159,000 people subscribing online to receive reports’ and 132,000
receiving the monthly CrisisWatch bulletin. It ‘authors more than 200 opinion
pieces in major international newspapers, with nearly half in languages other
than English’ and it ‘garners more than 5000 media mentions in print and elec-
tronic media’. The organisation is also present on Facebook (nearly 40,000
‘likes’ in March 2014) and Twitter (over 70,000 followers). Overall the ICG’s
media efforts are judged by peers and experts as quite successful: among all
global think-tanks it is ranked 12th for ‘best use of social networks’, 14th for
‘best external relations/public engagement programme’, 15th for ‘best use of the
media (print or electronic)’, and 23rd for ‘best use of the Internet’.11

In view of its presence in and possible influence on policy circles, media
and academia, it is surprising that the ICG has not attracted more attention as an
object of study.12 Apart from the selected information that the ICG itself provides
about its organisational development and political role, we know little about
how the organisation works. This pertains, first, to its daily operations: how is
information gathered and interpreted? Who takes part and decides in the process
from report drafting to final product to policy recommendations? And which
quality controls exist? Second, we also know very little about the ICG’s role in
international politics, about its ‘impact’ on political perceptions, processes and
outcomes: how did the organisation establish (the perception of) itself as a cen-
tral ‘conflict expert’ in the field of conflict-related policy knowledge? In how far
has ICG-produced knowledge shaped the perceptions of conflicts and legitimate
solutions? What formal and informal relations exist between ICG experts, local
stakeholders and international decision makers? And what role has the organisa-
tion (or its representatives) played in conflicts and peacebuilding processes?

The fact that we have only a few answers to these questions to date, and that
academics using ICG reports have not even asked them in the first place,13 hints
at a lack of critical engagement with this central actor in the field of conflict-
related knowledge production and policy making. Aiming to fill this void, the
contributions in this issue are first attempts at answering questions and opening
up routes for further study.

The ICG and the construction of ‘conflict knowledge’
Politically relevant knowledge is understood here as socially constructed in
power struggles between actors resorting to specific technologies and bound
together through the structures of the policy field. Politics can thus not be seen
as having one specific ‘reality’; rather, ‘the reality of politics is a politics with
“realities”’.14 From this perspective (the construction of) knowledge is both
object and resource of political power struggles.

Political struggles over the construction of reality can be observed, on the
one hand, with regard to descriptive–ontological knowledge about how the
world is, was or will be.15 Knowledge about the past interprets bygone political
events and experiences and constructs causal relationships with the present. In

Third World Quarterly 547

the context of this study this rather persistent form of knowledge concerns, for
example, the way international policy makers interpret a conflict area’s colonial
past and its meaning for the current situation. The ICG ventured into this type of
knowledge in 2005 by announcing a new type of publication, the ‘background
report’, whose function would be ‘scene-setting reports, not focused on detailed
recommendations though often indicating preferred directions, 10–50 pages as
the subject matter demands’. However, not many of these reports have been pro-
duced since. The general lack of analysis of the historical and socioeconomic
context is one major criticism of the ICG’s work among the wider academic com-
munity and many of the authors in this issue (see especially contributions by
Bøås, Grigat, Hochmüller and Müller, and Koddenbrock).

Knowledge about the future revolves around practices like simulations, prog-
noses, risk analyses and probability measurements regarding politically relevant
events in the future and how they are related to present action. The most obvi-
ous example in the present context is early warning mechanisms, which assess
situations of latent or acute conflict based on qualitative and/or quantitative
models of data collection and analysis and make predictions about potential
deterioration, stagnation or improvement.16 The ICG provides such knowledge
through its CrisisWatch bulletin, a monthly publication giving brief estimations
of conflict situations, alerting readers to ‘conflict risk’, pointing out ‘conflict res-
olution opportunities’, and labelling conflict situations as ‘improved’ or ‘deterio-
rated’ (see Kosmatopoulos and Simons in this issue). ‘Conflict risk alerts’ are a
second way in which future-related appraisals of political events are delivered,
highlighting stirred-up political situations that might lapse into more widespread
violent conflict. Both CrisisWatch and risk alerts are condensed forms of conflict
evaluation and offer little or no space for detailed analysis – a problem
acknowledged by some ICG staff:

In fact, this format is, in my experience, not favorably looked upon by researchers
‘in the field’, as they give much more value to the detailed, more qualified and
less rigid perspectives offered in ICG’s full length reports. For that reason, and
when I was researcher […] I barely worked on these CrisisWatch reports and
merely had a glance at them after they were prepared by someone browsing the
media in Brussels to make sure there wasn’t anything evidently incorrect.17

Future research should assess how policy makers and journalists, to whom these
early warning products are aimed, make use of and perceive these brief ten-
dency indicators – ie whether they are seen merely as ‘press clippings’ from a
non-profit information provider or whether the (perceived) authority of the
authoring organisation confers specific value or meaning on these products and,
if so, with what effects (see further Kosmatopoulos in this issue).18

Knowledge about the present, finally, includes all statements about functional
or causal relationships, causal determinisms, necessity constructions, interests
and expertise revolving around a current political issue. How a current situation
– in this case, in a violent conflict or post-conflict space – is interpreted deter-
mines the repertoire of legitimate action and ‘solutions’.19 While established
knowledge about causal relationships, determinisms and necessity constructions
tends to lead to closure and thus to the reduction of alternatives for political
action, new interpretations, not least through highly regarded expert knowledge,

548 B. Bliesemann de Guevara

can open up space for differing policy options.20 ICG reports and briefings, as
well as op-eds and other media pieces authored by ICG representatives, are
mostly concerned with this sort of knowledge, analysing and giving policy rec-
ommendations about immediate political situations to which their reporting
attaches some urgency (see Simons in this issue).

The other main instrument and object of knowledge constructions in political
struggles apart from ontological knowledge is normative–practical knowledge,
which determines what actors want to do (wishes, interests, passions, prefer-
ences, etc), must do (imperatives, duties, stringent necessities, etc), or should do
(norms, conventions, traditions, moral or ethical considerations, etc).21 When it
comes to the policy recommendations in ICG reports, normative–practical knowl-
edge is used to derive prescriptions for concrete political action from the conflict
analysis. Especially where the connection between a report’s analysis and its
policy recommendations is not straightforward, a possible explanation is that
(implicit) normative–practical knowledge has trumped descriptive–ontological
interpretation.

Indeed, it is an oft-heard complaint among academics that ICG policy recom-
mendations seem ‘decoupled’ from the analytical parts of its reports: while anal-
yses account for political paradoxes and dilemmas, the recommendations are,
rather, complexity reducing and formulaic. Grigat (in this issue), for instance,
shows that in the case of Indonesia ‘the ICG mantra-like recommends measures
to reform the security sector, notably the police’, no matter which issue it has
been reporting about over the past 15 years. Drawing on Foucauldian notions of
power/knowledge, Grigat’s explanation for this finding is that:

ICG reporting fulfils a function that transcends the immediate contribution to
preventing and resolving violent conflicts. ICG publications essentially aim at dis-
cursively disciplining their audience through practices and procedures characteris-
tic of liberal governance into this specific form of social action and corresponding
mind-sets, thus perpetuating liberalism as the global ‘regime of power’.

In this interpretation of ICG reporting as education, the normative dimension of
knowledge production clearly outweighs other dimensions. Another explanation
for disconnects between analysis and policy recommendations lies in think-
tanks’ interest in securing access to and influence on policy makers, which can
only be achieved through information and policy advice that is ‘useful’ in the
eyes of the users. As Fisher (in this issue) shows in the case of Uganda, the
urge to have ‘impact’ may well trump conclusions derived from previous analy-
sis, if this aids the search for a sympathetic ear among, and access to, policy
makers (cf also Koddenbrock on the DRC and Bliesemann de Guevara for a
more general discussion, both in this issue).

Nullmeier and Rüb have suggested understanding the struggles over these
different forms of knowledge in the construction of political realities in terms of
sectoral ‘knowledge markets’, in which different suppliers of knowledge
compete with each other, sometimes forming oligopolies, sometimes even
creating a knowledge monopoly.22 From such a market perspective politically
relevant knowledge production is seen not as ‘problem-oriented’ but as
‘success-oriented’: knowledge ‘must be “marketable”, that is, it must be able to
compete with other knowledge stocks. The design, marketing strategies, the

Third World Quarterly 549

knowledge management and the emotionality related to the product knowledge
play an important role in this.’23 Knowledge entrepreneurs are strategic actors in
knowledge markets who stand out because of their success in acquiring a
prominent, influential position. From the ICG’s (self-)description above it can be
inferred that the organisation has managed to establish itself as such a
knowledge entrepreneur in the market of conflict/violence-related knowledge.
One central question is how it has succeeded in doing so.

Constructing ‘expert authority’: conflict-related knowledge production as
social field
The idea of knowledge markets resembles Bourdieu’s social fields, where actors
in different social positions and disposing of different sorts and amounts of capi-
tal struggle for influence according to the field’s specific rules of the game.24

‘Capital’ in Bourdieu’s sense is not only economic or monetary in form; it can
also be social (eg connections, networks), cultural (eg education, titles) or sym-
bolic (specifically value-laden forms of the economic, social or cultural capital).
Being seen as a knowledge entrepreneur, that is, as a leading knowledge pro-
vider in a specific knowledge market, is a manifestation of symbolic capital.
The currency value and exchange rates of the capital in a social field depend on
its specific rules, and while it is not impossible for actors to change them in the
long run, the normal situation is that both access to and accession within a field
are very much determined by existing rules.

The ICG’s self-description hints at the capital forms with the highest value in
the field of conflict-related knowledge production: social and, to a lesser extent,
cultural capital. While the organisation’s funding base is arguably not negligible,
with an ‘annual budget for 2012–2013 [of] $20.6 million’ according to its web-
site, it is small when compared, for instance, with the research budgets of Wes-
tern governments’ ministries and agencies. The British development agency
‘DFID’s Research and Evidence Division spends just under 10% of its total
research expenditure on governance, conflict and social development, and for
2014/15 this is projected to be around £29 million’.25 It is thus not via the
amount of economic capital that the ICG gains its position in the field of conflict
knowledge, although money is arguably a necessary condition for its activities
and fundraising thus a constant factor in its daily operations and public
relations.

Critics have argued that it is not the amount but the sources of the ICG’s
funding which have opened Western policy makers’ doors to its advocacy, while
at the same time (possibly) compromising the ICG’s political independence.26

The organisation’s funding ‘comes from governments (49%), institutional foun-
dations (20%), and individual and corporate donors (31%)’, but as the ICG
emphasises on its website, ‘mostly in the welcome form of core funding (over
70%) rather than being earmarked for specific programs’. Governmental donors
exclusively comprise development agencies and the ministries of foreign affairs
of OECD countries. The list of corporate private sector donors includes big multi-
nationals, business consultancies, legal advisors and investment managers, and
among the foundations making donations are well known names such as
Carnegie Corporation, George Soros’s Open Society Foundations and the

550 B. Bliesemann de Guevara

Rockefeller Brothers Fund.27 Since it is a Western think-tank targeting a
Western and international policy audience, the funding structure may not come
as a surprise, however, and the ICG has countered the critique of possible donor
influences by pointing to the diversity of funding sources and attached interests
among Western donors, which at least contradicts the idea of simple, straightfor-
ward connections between donors and reporting.28

The most outstanding form of capital valued in the field of conflict-related
knowledge production, however, is social capital – both with regard to contacts ‘on
the ground’ in post-/conflict spaces, which are necessary to the gathering of infor-
mation, as well as regarding high-level contacts in the ‘highest echelons’ of decision
making, which ensure the possibility of influence and impact. In the ICG’s narrative
this is what differentiates the organisation from standard Western think-tanks, which
lack the permanent field presence that forms a cornerstone of the ‘ICG methodol-
ogy’(see also Bliesemann de Guevara in this issue). Or, as a former field-based ICG
analyst puts it, noting the importance of field presence in terms of symbolic capital:

ICG presents itself as unlike ‘armchair’ think tanks in DC and other Western
capitals by way of its presence in ‘the field’ […] [T]his needs to be emphasized
as it leads (policy) audiences to attribute (rightly or wrongly) much more authority
to ICG’s reports than to others’. This way ICG’s reports can be viewed as a tool in
(western) foreign policy bureaucracies’ internal debates and competition over
conflicting policy views.29

Its permanent field presence is also claimed to make the ICG superior to report-
ing by traditional media outlets, which lack the means to deploy or contract
journalists in crisis areas all over the world and especially to cover conflicts
over an extended period of time.30

With regard to high-level political contacts the ICG profits from its staff’s pre-
vious and/or subsequent jobs. An analysis of 74 LinkedIn profiles of former and
current ICG staff has revealed that 33 individuals working for the ICG had also
worked for at least one other NGO, 16 for an international organisation (predomi-
nantly UN bodies, but also NATO and OSCE), 16 in the private sector, 14 in the
media sector, and 12 for state institutions and agencies.31 The job profiles sug-
gest an ICG staff membership in broader professional networks of the Western
and international policy community that can be activated if needed. The other
main channel of contacts is the ICG’s abovementioned Board of Trustees,
comprising a number of prominent former statespersons.

In addition to, or in spite of, its heavy reliance on its social capital, the ICG
is also eager to emphasise its organisational ‘independence’ and the ‘objectivity’
of its reports. This is where the importance of cultural capital comes into the
picture. While emphasising its own advocacy capacity, the organisation distances
itself from other advocacy organisations, especially explicitly norm-based NGOs
like Human Rights Watch or Amnesty International.32 The ICG furthermore high-
lights the ‘expert’ character of its staff and the ‘research’ character of their field
activities, thus making use of the cultural capital that dominates the field of aca-
demia. Unsurprisingly ICG analysts usually have a university education. In addi-
tion, 22 out of the 74 ICG staff whose LinkedIn profiles were analysed for this
research have also held professional positions in academia in the course of their
career. At the same time, however, the ICG makes clear that its field-based

Third World Quarterly 551

research and analysis is better than that of academics by being a ‘unique combi-
nation of field-based analysis, practical policy prescriptions and high-level advo-
cacy’, the latter two aspects of which are often lacking in politics-related
academic knowledge production.33

Some have argued that the sole concentration on human action and interaction
in a social field is too narrow to fully explain its dynamics, and that technologies
– in this case the ICG’s different report formats – may also gain a sort of actor qual-
ity. In this sense Kosmatopoulos (in this issue) argues with regard to the ‘crisis
report’ that, in order to explore the dialectics of enchantment of crisis experts, it is
necessary to look ‘at the world of experts through the lens of techno-politics’,
because technologies and sovereign actors ‘stand in dialectic and intertwined rela-
tionship with each other’, through which one might influence the other rather
‘than adopting a unilateral causality that emanates from the experts and ends in
their nonhuman practices and products’. Through such technologies – for
instance, the ‘size, scale and sentinel’ of the crisis report – the ‘report presents
itself as an assemblage of a series of technical characteristics that help to shrink
the world overall and make it fit into the model format of the crisis expert’, an
effect on knowledge production that also needs to be accounted for.

That the ICG is currently ranked among the world’s top think-tanks is not,
however, predominantly a reflection of its ‘real’ success in ‘working to prevent
conflict worldwide’ or some sort of ‘objective usefulness’ of its reports to Wes-
tern and international policy circles. Rather, it testifies to the organisation’s suc-
cess in accumulating symbolic capital – above all expert authority – that
differentiates it from similar organisations and elevates it in the perception of
peers, policy makers and public. Its field presence is a crucial aspect of the ICG’s
practices and image in this respect, as it makes the organisation stand out among
its ‘armchair’ competitors.

The other major contribution to the ICG’s symbolic value charging is its
Board of Trustees. Although the role of most board members can hardly be
called active,34 the impressive list of names and functions in itself already lends
importance to the organisation: the board comprises ‘two former prime minis-
ters, two former presidents, eight former foreign ministers, one former European
Commissioner, one Nobel Peace Prize winner and many other leaders from the
fields of politics, diplomacy, business and the media’.35 The board is predomi-
nantly (but not exclusively) a male affair, with only a quarter of female mem-
bers. The age distribution further contributes to the impression of a ‘council of
wise old men’,36 with the majority of members between 61 and 70 years old,
followed by the 71–80 and 51–60 age brackets. At the time of analysis the
youngest member was 43, the oldest, ICG co-founder George Soros, 82. The
board is also a ‘club of the wealthy’: 28 members come from high-income OECD
countries and only nine, seven and two members from high middle-income, low
middle-income and low-income countries, respectively.37 Taken together, the
board symbolises international power and influence, lending weight to the ICG’s
work.38

While not part of the everyday workings, at times the role of the board can
be more active and influential, as a former ICG researcher describes:

For one, the board members’ interference and say in the reports is not even and
clear-cut, and in many cases does not materialize at all. Yet with regards to reports

552 B. Bliesemann de Guevara

involving topics of high western policy concern […] there is such interference.
The [country] report – to which I contributed – is a good (but exaggerated) exam-
ple; its original draft argued against [a specific policy], after which the Board dis-
agreed so strongly that the report was watered down, while inviting the reader to
derive his/her own policy conclusions.39

Reports without (or with only vague) policy recommendations for international
action hint at strong disagreements among, and interference by, board
members;40 tracing such reports may allow some insight into the internal power
relationships between and among the organisation’s staff and its directorate.

In addition to its field presence and its Board of Trustees, many ICG actions
– from the type, amount and frequency of its information products and advocacy
campaigns to the countries and political events covered and policy recommenda-
tions given – can be read as attempts to maintain or enhance its symbolic capital
and expert authority. For instance, Hochmüller and Müller (in this issue) argue
that the ICG’s decision to cover the ‘drug war’ in Mexico can be explained by
the organisation’s need to position itself in the international competition over
policy knowledge.

As shown, employing Bourdieu’s field theory can help us map the social
field of conflict-related knowledge production and explain the accumulation of
symbolic capital among a Western (policy) audience.

Between mediation and instrumentalisation: conflict experts in the
‘battlefield of ideas’
A central question with regard to conflict-related knowledge production concerns
the role of violence. The economic language of ‘knowledge markets’, employed
to describe competition over legitimate problem interpretations, resembles the
debates of the late 1990s about wars as ‘markets of violence’. Early promoters
of the concept defined a market of violence as a conflict dominated by economic
motives and material profits, contributing to the complexity-reducing view of
modern civil wars as driven by ‘greed and grievance’ (see Bøås in this issue for
a critique). The general observation, however, that violent actors are also eco-
nomic players was also taken up by more nuanced works, which emphasised
the political causes of violent conflict, while at the same time highlighting the
role of economic factors in conflict dynamics. The literature specifically high-
lighted the ambiguous role of international actors, such as humanitarian aid
agencies, which, while trying to alleviate the needs of populations in war zones,
simultaneously became part of violent actors’ economic, war-prolonging calcula-
tions.41

By analogy it can be argued that knowledge experts are far from the objec-
tive, outside observers with insider contacts that their self-description would
want us to believe. The ICG describes its field presence in terms which imply the
possibility of an independent outsider position for analysts looking at clearly
identifiable problems:

Our analysts are based in or near many of the world’s trouble spots, where there
is concern about the possible outbreak of conflict, its escalation or recurrence.
Their main task is to find out what is happening and why. They identify the

Third World Quarterly 553

underlying political, social and economic factors creating conditions for conflict,
as well as the more immediate causes of tension. They find the people who matter
and discover what or who influences them.42

From the perspective of ICG field analysts the process of information gathering
and report writing is more complicated, however, as they get entangled with
their object of study: they become part of the political process, ie the battle of
ideas organised around storylines that help actors with a wide range of interests
to form discourse coalitions and establish a dominant reading of an event.43 A
former field analyst describes how important her role of information gathering
and report writing was for actors in a specific peace process and how she
became both the target of other actors’ versions of the story and a mediator
between different stories:

In the process […] I was accused of being close to people on the whole spectrum
– from the [ethnic] rebels to the president of [the country], the whole spectrum of
positions […] They instrumentalise. But at the same time they keep talking to me,
because […] all the people appreciate the fact that I am faithful to it […] You
know, they got used to me, they got used to having a coffee or tea […], they got
used to me hanging out in or close to the negotiation room. They knew also that I
had access to the other side, to all sides, so every party would talk to me […] it
was in their interest also to talk to me. […] What they would do when an ICG
report came out was to look at the report itself and then see whether their names
were quoted and in what way they were quoted. […] And one of them said to me
one time, it was an officer from the army, he said, ‘You know, so many times
when I was at the officers’ mess, I was talking to colleagues and I was saying
how we need another report from [her] because we are really lost right now’.44

For this analyst the positive aspects of being an active part of the knowledge pro-
duction process on the ground clearly outweigh the negative aspects of being part
of political power struggles about framings of conflict and peace. Accordingly, she
comes to a positive assessment of her overall role in the conflict space:

It was very gratifying, very gratifying to be part of something that at the end of the
day went somewhere […]. I had a small role in it […] My reports made sense to
[the people], they projected a certain analysis – right or wrong – of a process that
for them was confusing […] They themselves were transforming, this country was
transforming; they could not always understand what their own politicians had
decided to do. And they were all really scared [because of the violent history of the
country and the violence in neighbouring countries]. From that point of view, just to
see how this process of talking and discussing and negotiating – and then the circu-
lation of information to which I contributed – how it demystified some of these
issues and at the end of the day helped create an atmosphere that was more condu-
cive to political settlement, I witnessed it and it was an incredible experience.45

There is no reason to doubt that experts’ work can have positive effects on
peace processes, although a detailed study would be needed to reconstruct how
far this specific analyst contributed to the peace process by reducing
informational uncertainty and co-writing a shared story.

The general perspective on knowledge as political power struggles introduced
above, however, suggests that there is also another, less harmonious dimension to

554 B. Bliesemann de Guevara

expert knowledge production. If struggles over knowledge determine which
actors, claims and supporting narratives are seen as legitimate, then determining
the process of knowledge production is likely to become the strategic goal of the
different actors involved. In the case of post-/conflict spaces this may include the
definition of what is seen as legitimate violence – be it in the form of blaming,
scapegoating or victimising certain actors, or be it by providing arguments for or
against an external (military) intervention (see Bøås, Fisher and Koddenbrock in
this issue).46 Kosmatopoulos (in this issue) furthermore argues that the monitoring
of what the ICG – following central western actors’ readings – considers as ‘rebels’
is a basic function of the organisation and as such a crucial component of its over-
all ethical and political take on violence. Knowledge production can ultimately
have severe consequences for the balance of power between groups of actors:
rather than being a market, it can become a ‘battlefield of ideas’ (Kostić in this
issue), which may ultimately involve the threat or use of violence. And, indeed,
the analyst cited above received death threats, hinting at the importance that others
attached to her role as knowledge producer (cf also Grigat in this issue).

These observations raise important questions regarding the role of informants
and ‘stakeholders’ in a post-/conflict space, who may well intend to steer or
manipulate the process of knowledge production in their favour or for their pur-
poses. Kostić (in this issue) points to the crucial role that knowledge experts’
belonging to socio-political actor networks plays in this regard. His analysis of
ICG reporting in Bosnia and Herzegovina shows that:

the ICG’s work in the early 2000s in BiH was seemingly part of a broader knowledge
production flex-network united by a common effort to promote the position of the
US Department of State. It seems to have consisted of US military and intelligence
representatives […] US diplomats […] and ICG Balkans director James Lyon.
Combining access to privileged micro-level information, analysis and internal policy
debates among internationals allowed the ICG-linked flexians to cut through the inter-
national bureaucracy and connect different levels of international policy making.

Kostić emphasises the crucial need to account for the involvement of think-tank
experts in wider informal networks of collaboration and loyalty beyond their own
organisation. These ‘flex networks’ may encompass international organisations,
governments, academia and the media, who use experts’ services in a way that is
reminiscent of the ‘revolving door’ effect: the movement of personnel between
politics and economy, which may be questionable depending on whether and how
it is regulated by formal as well as informal rules, norms and institutions. Contacts
and shifting roles allow for insider information and a position in which the expert
can be instrumental in streamlining policies in favour of certain allies.

Viewed in this way, the ICG staff’s contacts not only constitute the basis for the
organisation’s political lobbying through access to policy makers, they also actu-
ally represent a major power source for certain individuals to play a central part in
the ‘battlefield of ideas’. This renders the ICG’s own image as ‘independent organi-
sation’ and coherent actor an illusion. It also means that its role and influence in a
specific context may well change over time, based on the shifting composition of
staff and their networks. Finally, it demonstrates the need to account for the many
roles the reports and representatives of the organisation may play in different
settings.

Third World Quarterly 555

Behind the logo: unpacking the ICG
As the discussion has shown, there is an urgent need to ‘unpack’ the ICG and
analyse its workings and role on a micro rather than a macro level. The ICG is
not a homogeneous actor, and the question of how it produces its organisational
brand, while at the same time being extremely heterogeneous in its role in spe-
cific contexts and at specific times, is but one of the puzzles that needs to be
addressed.

The heterogeneity of its role in specific cases can be attributed, first, to the
fact that its working contexts differ quite considerably, explaining why ICG
reports evoke a loud echo in some cases while withering unheard in others. In
Indonesia, for example, the ICG is highly visible through its advocacy work and
national media coverage; however, the group is largely a sound provider of
argumentative support for human rights activists, whereas Indonesian policy
making seems to reflect its analysis and recommendations to a negligible
degree.47 In West Africa, by contrast, ICG reports are not only widely read, but
also carry the largest clout compared with those by other knowledge producers.
Next to policy makers academics read ICG analyses with considerable interest
and make extensive use of them, even though at times they disagree with con-
tent, conclusions or recommendations.48 In the Democratic Republic of the
Congo (DRC), too, the ICG plays an important role alongside the United Nations
Group of Experts, which publishes intelligence reports biannually. Asked which
sources of information they refer to frequently, Western UN or NGO staff unani-
mously referred to the ICG as the most, or second-most important source.49 In
Mexico the ICG is a relative ‘newcomer’ among transnational NGOs working on
(in)security problems. However, already during its first year it was successful in
interviewing politicians from all major parties of the highly factionalised and
conflictive Mexican party landscape and had a visible presence in leading
national newspapers and magazines. Its relevance is likely to increase with the
opening of its Mexico City field office.50 In Uganda ICG reports have paid only
limited attention to the ongoing war against Joseph Kony’s Lord’s Resistance
Army in recent years. An advocacy-driven offshoot of the ICG, however, the
Enough Project, has rapidly become a major source of influence over
Washington policy makers and played a role in persuading the Obama
administration to dispatch 100 US military advisers to central Africa to assist
regional forces in hunting down Kony.51

A second dimension that needs unpacking concerns the relationship (and
unquestioned dichotomy) between ‘the local’ and ‘the global’ in ICG expert
knowledge production. Contributions in this issue focusing on report content
tend all to come to the conclusion that ICG reporting plugs into, or is shaped by,
dominant global discourses. Indeed, some of its reports cannot be explained
other than as an attempt to ride a wave, eg a short report series about Islam in
Germany, France and the UK, which plugged into the ‘Islamist threat’ discourse
accompanying the global war on terrorism (cf Kosmatopoulos in this issue).52

Such reports may be trial and error processes but they also show the organisa-
tion’s high flexibility in adopting new themes – and letting them go if they do
not evoke much resonance. Who takes the initiative in choosing a reporting
topic or who engages in advocacy work within the ICG is not necessarily a mat-
ter of hierarchy or clear-cut roles, but depends on the conflict at hand and the

556 B. Bliesemann de Guevara

individuals involved. As a former ICG analyst remembers regarding the role of
ICG advocacy offices in Western capitals:

I – and many of my colleagues with ICG at the time – didn’t take [its advocacy
managers based in Western capitals that ‘matter’] very seriously unless a report
that was supposed to be publicized was primarily directed at Western policy audi-
ences. When that was not the case, I simply embarked on my own ad hoc ‘advo-
cacy’ policy directed at local audiences, in [the country] and the region as a
whole, by approaching my network of contacts, writing in the local [language]
press and sending around ICG reports.53

Third, as the contributions by Kostić, Fisher and Koddenbrock show, local
power constellations (eg among the intervening agencies in Bosnia) or local
agency (eg of the Ugandan and Congolese governments) should not be underes-
timated and need unpacking, too. An analytical focus on experts’ social net-
works and recipient countries’ governments and other national actors may well,
in some cases, lead to other conclusions than a critical content analysis of ICG
texts and their embedding into global discourses would allow. An important
research task is thus to combine formal and informal network analysis with con-
tent analysis of expert reports and broader argumentative analysis around certain
policy issues in order to understand the different dimensions of the process of
knowledge production and the possible variety of messages and audiences.

Finally, analyses need to unpack shifts in the ICG’s workings and influence
over time. The most obvious shifts are those that can be traced back to person-
nel changes in the ICG presidency, most notably the change from Gareth Evans
(2000–09) to Louise Arbour (2009–present). Not only has the broad strategic
focus shifted since human rights expert Arbour took over; ICG staff also speak
of a noticeable shift in internal leadership style.54 Evans, former Australian For-
eign Minister and co-chair of the International Commission on Intervention and
State Sovereignty, which coined the ‘Responsibility to Protect’ concept, is
described as a micro-manager involved in internal discussion from the early
stages of reports. Louise Arbour, by contrast, former UN High Commissioner
for Human Rights, Justice of the Canadian Supreme Court and Chief Prosecutor
for the International Criminal Tribunals for the former Yugoslavia and Rwanda,
is known to be less hands-on and more consultative, involving senior advisors
at the Brussels office in final decisions. The idea of informal networks of knowl-
edge experts and other relevant actors discussed above further hints at the possi-
ble role that changes of personnel may play in the ICG’s field presence, as
different staff members may be part of different networks, thus either enforcing
or weakening the overall role played by the ICG in each case.

Overstated impact? The ICG and global politics
A final important question concerns the possible and actual impact of conflict
knowledge producers on policy processes. The ICG claims that:

Over the past eighteen years, Crisis Group’s reports and the advocacy associated
with them have had a significant direct impact on conflict prevention, management
and resolution across the world. Crisis Group has been visible and effective in
assisting policymakers determine how best to handle terrorism, nuclear

Third World Quarterly 557

proliferation, impunity for international crimes, trafficking in arms and drugs and
other problems associated with fragile or conflict-prone states. Increasingly,
high-level interlocutors tell Crisis Group that its work in support of international
peace and security has become indispensable.55

From the perspective of knowledge production as a competitive marketplace of
ideas and a contested social field, this ‘impact statement’ is not surprising.
Highlighting an organisation’s effectiveness and impact is a crucial form of mar-
keting, which affects donor contributions and the future potential to be heard as
an ‘expert’. Similarly, ‘having an impact’ and being endorsed for this by people
with names and titles is yet another component contributing to symbolic capital.
The impact statements in the ICG’s annual reports have to be read accordingly.
In these reports the organisation summarises its main activities in different
countries and reflects on the impact they have had on policy makers and
stakeholders. In the 2006 annual report, for example, the ICG’s impact on events
in Kosovo were summarised as follows:

In January, Crisis Group launched a fresh advocacy campaign focusing on resolv-
ing Kosovo’s final status, releasing a major report, Kosovo: Toward Final Status.
US officials engaged with Crisis Group on alternative policy options, and state-
ments by the Contact Group and the EU in April, ruling out partition and union
with any other state, lifted text directly from the report’s recommendations […]
The report had a tangible galvanising effect on the final status debate, with Bel-
grade reacting by recalibrating its position on the issue. The Contact Group’s set-
tlement parameters essentially reflect long-argued Crisis Group positions.56

While it is not possible to say without further research whether the causal rela-
tions between ICG reporting and policy processes claimed above are correct, the
way the group’s ‘impact’ is presented leaves many questions unanswered. Apart
from the broad consensus in the social sciences that impact measurement is
among the most daunting, if not impossible tasks, because of the complex nat-
ure of social interactions and their direct and indirect, intended and unintended
repercussions and effects, the impact narrative above lacks evidence for some
claims. That an idea was ‘long-argued’ by the ICG does not necessarily imply a
causal relationship. Likewise the text does not solve the ‘chicken and egg’ prob-
lem attached to ideas and conflict reporting: while ICG reports diffuse certain
ideas through reporting, the ideas themselves are gathered through talking to
those involved in a fluid process – leaving the question of ‘who invented them’
open to interpretation. To some extent the ICG has acknowledged this problem
by regularly stating in its annual reports:

Measuring the progress of an organisation such as ICG […] is inevitably an inexact
science. Quantitative measures provide some sense of the level of activity of the
organisation, and of others’ response, but have their limitations. Qualitative judge-
ments are necessarily subjective: it is difficult for anyone to establish a close cau-
sal relationship between any given argument and outcome, particularly if the
desired outcome is for something – here, conflict – not to happen.57

It might be because of the missing links in the causal chains constructed in
earlier impact statements that recent reports seem to have been formulated more

558 B. Bliesemann de Guevara

carefully, now only claiming that the ICG may determine through its reports and
advocacy what policy makers talk about, rather than claiming credit for the
practical outcomes of these debates. In terms of influencing what policy makers
talk about the ICG attributes its influence not least to sound and convincing
arguments:

All too often the missing ingredient is the ‘political will’ to take the necessary
action. Crisis Group’s task is not to lament its absence but to work out how to
mobilise it. That means persuading policy-makers directly or through others who
influence them, not least the media. That in turn means having the right argu-
ments: moral, political, legal and financial. And it means having the ability to
effectively deploy those arguments, with people of the right credibility and
capacity.58

The emphasis on ‘the right arguments’, however, is as compelling as it is mis-
leading. As policy analysts of the ‘argumentative turn’ have shown, arguments
do not derive from facts or static positions; it is the argumentative interaction
which forms discursive positions and discourse coalitions among a number of
different actors who cluster around inter-subjectively constructed and agreed, but
rather vague storylines.59 This means that, while the ICG can show that policy
makers and other actors pick up its reports, the organisation cannot influence
how and for what ends the information, arguments and recommendations are
used – a usage that might be quite contrary to the ICG’s intentions. Focusing on
the EU’s use of expert knowledge, Boswell has shown, for instance, that expert
knowledge can have three main functions. Next to the instrumental role of
providing policy makers with ‘facts’, it may serve two symbolic purposes:

The first of these is a legitimizing function. By being seen to draw on expert
knowledge, an organization can enhance its legitimacy and bolster its claim to
resources or jurisdiction over particular policy areas. In this sense knowledge can
endow organizations with ‘epistemic authority’. The second is a substantiating
function. Expert knowledge can lend authority to particular policy positions, help-
ing to substantiate organizational preferences in cases of political contestation.60

Waldman’s findings from a study of the use of state-building research by British
policy makers based in Afghanistan, Nepal and Sierra Leone confirm these
functions. The policy makers interviewed stated that they often used research
selectively to justify certain programmes (substantiating function) and as ‘ammu-
nition’ in struggles within their own organisation or with other intervention
agencies, as research ‘can add weight, credibility and persuasiveness to support
a line on a specific issue’ (legitimacy function).61

Studies should therefore also focus on the ways in which ICG expert
knowledge is taken up and transformed by its recipients to fit their purposes.
As the contributions to this issue show, the possibilities for impact range
widely from negligible to instrumental, depending on the respective context –
and this can only be analysed through in-depth case studies. What seems clear,
however, is that it would be misleading to take the ICG’s self-description of its
important role in international policy making at face value and overestimate
its influence.

Third World Quarterly 559

Acknowledgements

The idea for this special issue emerged from the cooperative research of the academic network ‘Knowledge
and Power in International Security Governance’, funded by the German Research Foundation (DFG). Thanks
to all involved for being such brilliant colleagues. Thanks are also due to Nadja Zimmermann at Bremen
University and Jana Wattenberg at Frankfurt University for their sterling research contributions: the analysis of
ICG staff’s LinkedIn profiles, of the composition of ICG’s Board of Trustees, and of an immense number of
WikiLeaks cables for mentions of ICG reports and staff. Last but not least, I am very grateful to interview and
correspondence partners among (former) ICG staff for very informative conversations.

Notes

on Contributor

Berit Bliesemann de Guevara is Senior Lecturer in peace building, post-war
reconstruction and transitional justice in the Department of International Politics,
Aberystwyth University. She heads the international and interdisciplinary
research network ‘Knowledge and Power in International Security Governance’,
funded by the German Research Foundation (DFG), from which this special issue
emerged. Her research interests include knowledge production in conflicts and
peace building, international politics of state building, dynamics of state- and
society-formation, intra-state armed conflicts, and charisma and politics. She is
editor of Statebuilding and State-formation: The Political Sociology of Interven-
tion (Routledge, 2012), among many other publications.

Notes
1. ICG, Fifteen Years on the Frontlines, 10.
2. McGann, 2013 Global Go To Think Tanks, 47. For the ranking methodology see pp 11–16.
3. Ibid., 27. Transparency International (no. 5) and Amnesty International (no. 7) may also count as ICG

competitors in some respects. Ibid., 71.
4. Ibid., 30.
5. For the following statistics, see ICG, “About.” The numbers on the ICG website are contradictory; else-

where it talks about ‘over 50 conflict and potential conflict situations’.
6. For a list of staff, see http://www.crisisgroup.org/en/about/staff.aspx.
7. A former UN assistant secretary-general and special adviser named three main information sources for

staff in the UN Departments of Political Affairs and Peacekeeping Operations: international press clip-
pings, UN mission reports and ICG (plus other INGO) reports. Interview, New York, March 2012. WikiLe-
aks cables suggest that ICG reports are widely read by US embassies. See also endorsements by policy
makers, at ICG, “About.”

8. WikiLeaks cables confirm that meetings between US embassies and ICG representatives take place fre-
quently.

9. McGann, 2013 Global Go To Think Tanks, 72. For campaigns, see also ICG, Fifteen Years on the Front-
lines, passim.

10. For a list of Board of Trustee members, see http://www.crisisgroup.org/en/about/board.aspx.
11. McGann, 2013 Global Go To Think Tanks, 91, 95, 97, 98.
12. Some academics have dedicated article sections to in-depth discussions of ICG reports. See, for example,

Heathershaw, “Tajikistan”; and Lemay-Hébert, “The ‘Empty-shell’ Approach.” Hofmann analyses the ICG
rather superficially as an example of learning in international society. Hofmann, Learning in Modern
International Society.

13. I have to plead guilty: in my book on statebuilding in Bosnia, I gratefully relied on 12 ICG reports and a
further seven reports from its strongest competitor in the Balkans at the time, the European Stability Ini-
tiative (ESI), without exploring how the reports’ information had been gathered and processed.

14. Rüb, “Wissenspolitologie,” 345.
15. The following discussion of different forms of knowledge is based on the categories set out in ibid.,

348–349.
16. E.g. FIRST3.0, a database run by SIPRI, to which the ICG contributes. http://first.sipri.org.
17. Email correspondence, former ICG field analyst, March 2014.
18. Cf. ICG, Fifteen Years on the Frontlines, 30: ‘one of the organisation’s most valued products’.
19. Stone, Policy Paradox, 269–378.
20. Rüb, “Wissenspolitologie,” 349.
21. Ibid., 350.

560 B. Bliesemann de Guevara

http://www.crisisgroup.org/en/about/staff.aspx

http://www.crisisgroup.org/en/about/board.aspx

http://first.sipri.org

22. Nullmeier and Rüb, Die Transformation der Sozialpolitik; and Rüb, “Wissenspolitologie.”
23. Rüb, “Wissenspolitologie,” 350 (author’s translation).
24. Bourdieu, Practical Reason; and Bourdieu and Wacquant, An Invitation.
25. Waldman, “The Use of Statebuilding Research,” endnote 2.
26. Oberg, “The International Crisis Group”; and Bliesemann de Guevara, Gebrauchshinweise beachten!, 5.
27. ICG, Financial Statements; and ICG, “Who Supports Crisis Group?” http://www.crisisgroup.org/en/support/

who-supports-crisisgroup.aspx.
28. Interviews, ICG senior staff and founder, New York and Washington DC, March 2012. The founding

member recalled, however, that in the early years dependence on a few donors (especially George Soros)
was much higher and their influence on where to take the organisation geographically and strategically
was crucial.

29. Email correspondence, March 2014.
30. Interview, senior ICG staff member, New York, March 2012.
31. These numbers can only be approximations, of course: not all staff are represented on LinkedIn and, of

those who are, we only know the career information they have chosen to make public. The profiles differ
accordingly, from very detailed CVs to profiles which only display a minimum presence on the social net-
work.

32. This distinction has not been clear-cut in recent practice, however. In the case of Sri Lanka the ICG has
been involved in a vocal post-conflict campaign to bring to light the Sri Lankan government’s war
crimes. ICG, War Crimes in Sri Lanka. This rather new involvement in human rights issues, possibly a
result of president Arbour’s initiative, was judged as positive by a senior ICG staff member, while rejected
as ‘not ICG’s business’ by one of the organisation’s founders. Interviews, New York and Washington DC,
March 2012.

33. Waldman, “The Use of Statebuilding Research.” Practitioners generally perceive even research projects
and centres aimed explicitly at producing policy-relevant research as ‘not useful enough’.

34. Interviews and email correspondence with various (former) ICG staff, March 2012 and March 2014.
35. ICG, “About.”
36. Cf. the ‘king’ archetype of leadership in Steyrer, “Charisma.”
37. Categories based on World Bank classification available from its website.
38. The Board’s symbolic capital also seems to work within the ICG among staff. ICG, Fifteen Years on the

Frontlines, 8.
39. Email correspondence, March 2014. (emphasis in the original)
40. The Middle East in general, Iraq specifically. ICG, Fifteen Years on the Frontlines, 25, 27.
41. Elwert, “Gewaltmärkte”; and Rufin and Jean, Economie des guerres civiles.
42. ICG, Annual Report 2013, 5.
43. Hajer, The Politics of Environmental Discourse, 42–72.
44. Interview, former ICG field analyst, March 2012.
45. Ibid.
46. Heathershaw and Lambach, “Introduction.”
47. Grigat’s assessment. See also her contribution in this issue.
48. Bøås’s assessment. See also his contribution in this issue.
49. Koddenbrock’s assessment. See also his contribution in this issue.
50. Hochmüller and Müller’s assessment. See also their contribution in this issue.
51. Fisher’s assessment. See also his contribution in this issue.
52. For example, ICG, Islam.
53. Email correspondence, former ICG analyst, March 2014. He added, ‘Having said this, one ICG officer once

told me that ICG reports receive the largest Internet hits in Langley, Virginia’.
54. Interviews, ICG staff, New York and Washington DC, March 2012; and ICG, Fifteen Years on the

Frontlines, 23, 43.
55. ICG, “About.”
56. ICG, Annual Report 2006, 21.
57. ICG, Annual Report 2004, 26.
58. ICG, Annual Report 2013, 5.
59. Hajer, The Politics of Environmental Discourse, 42–72.
60. Boswell, “The Political Functions of Expert Knowledge,” 472.
61. Waldman, “The Use of Statebuilding Research,” 5. (emphasis in the original)

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Abstract
Introduction
The icg and the construction of `conflict knowledge`
Constructing `expert authority`: conflict-related knowledge production as social field
Between mediation and instrumentalisation: conflict experts in the `battlefield of ideas`
Behind the logo: unpacking the icg
Overstated impact? The icg and global politics

Acknowledgements
Notes on Contributor
Notes
Bibliography

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