The Contrasting Effects of Culture onConsumer Tolerance: Interpersonal Faceand Impersonal Fate

000
2009 by JOURNAL OF CONSUMER RESEARCH, Inc. ● Vol. 36 ● August 2009 All rights reserved. 0093-5301/2009/3602-0014$10.00. DOI: 10.1086/597329 The Contrasting Effects of Culture on Consumer Tolerance: Interpersonal Face and Impersonal Fate HAKSIN CHAN LISA C. WAN LEO Y. M. SIN* This research highlights two cultural tendencies—concern for face and belief in fate—that are characteristic of Asian (vs. Western) consumers. In three crosscultural studies on service failures, we show that these cultural tendencies have contrasting effects on consumer tolerance, such that Asian (vs. Western) consumers are more dissatisfied with social failures but less dissatisfied with nonsocial failures. We further demonstrate that these contrasting effects of culture are sensitive to pertinent contextual factors such as the presence of other consumers or a fate-suggestive brand name. Overall, our research evinces the multidimensionality of cultural influence and points to the need for a sharper focus in conceptualizing cross-cultural consumer behavior. Much of cross-cultural consumer research “focuses, implicitly or explicitly, on the contrast between . . . Eastern-collectivist-interdependent societies and . . . Western-individualist-independent societies” (Maheswaran and Shavitt 2000, 61). Despite its widespread appeal, this generalized cultural framework may have obscured a range of finer concepts (Triandis 2001). Pioneered by Hofstede (1980) and extended to the individual level by Triandis et al. (1985), the individualismcollectivism (I-C) framework contrasts an independent versus interdependent construal of the self. Relative to individualists, collectivists tend to have an interdependent view of the self, which fosters a sensitivity to the needs of others *Haksin Chan is an adjunct assistant professor in the Department of Marketing, The Chinese University of Hong Kong, Shatin, Hong Kong (hchan@cuhk.edu.hk). Lisa C. Wan is currently a visiting lecturer in the Department of Marketing and International Business, Lingnan University, Tuen Mun, Hong Kong (lisawanwan@ln.edu.hk). As of September 1, 2009, she will be an assistant professor at Lingnan University. Leo Y. M. Sin is a professor in the Department of Marketing, The Chinese University of Hong Kong, Shatin, Hong Kong (leo@baf.msmail.cuhk.edu.hk). The authors thank the editor, associate editor, and three reviewers for their feedback and guidance. The authors also acknowledge the assistance of Wai Chan, Jeremy Cheng, Binhnguyen Le, Linda Lee, and Victor Reynolds in data collection and analysis and the comments from Michael Bond, Gerry Gorn, Michael Hui, and Bob Wyer on previous versions of this article. John Deighton served as editor and Ann McGill served as associate editor for this article. Electronically published January 27, 2009 and, at the same time, a need for sensitivity from others (Markus and Kitayama 1991). However, the literature seems to ignore the demanding side of collectivist consumers, mostly portraying them as caring and understanding. In particular, a recent review of cross-cultural services research unequivocally concludes that Asian, collectivist consumers are easier to satisfy than Western, individualist consumers (Zhang, Beatty, and Walsh 2008). As the argument goes, the collectivist “we” (vs. the individualist “I”) mind-set is more conducive to a tolerance for subpar performance. We depart from the prevailing view by highlighting a different aspect of collectivism: the need for attention and care. When this social need is salient during service encounters, we expect collectivist consumers to be less tolerant than individualist consumers. There is strong support for this position in the literature on face, which suggests that the social need for face is a cornerstone of Asian, collectivist cultures (Ho 1976; Hwang, Francesco, and Kessler 2003). When the focal issues are nonsocial, we expect the prevailing view to hold true. Nonetheless, we propose an alternative rationale for the prediction that collectivists are more tolerant of service failures. This rationale builds on consistent cross-cultural findings that Asian, collectivist societies are characterized by higher fatalistic tendencies (Pepitone 1997; Schutte and Ciarlante 1998). Since fatalistic thinking helps alleviate discontent (Cohen 1960; Yau 1988), a higher fatalistic tendency should manifest in a higher consumer tolerance. This cultural tendency is particularly im- 000 JOURNAL OF CONSUMER RESEARCH portant for understanding service consumers, whose consumption experience is marked by heterogeneity (Zeithaml, Parasuraman, and Berry 1990). This article highlights the contrasting effects of culture on consumer responses to service failures. We demonstrate in three studies that Asian, collectivist consumers are less (more) tolerant than Western, individualist consumers when the social (nonsocial) aspects are salient and that the influence of culture is contingent on both service attributes and contextual factors. Overall, we advance consumer research on two fronts. First, we specify boundary conditions of a prevailing view in the cross-cultural literature. Second, we identify two smaller-range constructs (as opposed to I-C) that facilitate a more refined understanding of the multifaceted influence of culture. CONCERN FOR FACE (CFF) The concept of face underlies the human need for social acceptance (Brown and Levinson 1987; Hwang et al. 2003). According to Goffman (1967), face refers to a positive image of self that is affirmed through interaction with others. As a social resource, it cannot be claimed unilaterally. Rather, it is maintained, enhanced, or lost through interpersonal interactions. More specifically, face is the public, social, and fluid aspect of the self-concept that is contingent on others’ attitudes and behaviors (Ting-Toomey and Kurogi 1998). Since face contributes to a sense of self-worth, failure to have one’s face preserved leads to negative responses “ranging from slight discomfort or embarrassment, to mild annoyance, anger, and outright hostility” (White et al. 2004, 103). In contrast to individualists, collectivists tend to view the self relationally and situationally (Triandis 2001). Hence, face as the socially defined aspect of the self should take on greater significance in collectivist cultures (Hwang et al. 2003). Indeed, face is a major concern in many Asian cultures (Oetzel et al. 2001; Ting-Toomey and Kurogi 1998). Recently, this cultural concern has been used as an explanatory variable for differences between Asian and Western consumers (Bao, Zhou, and Su 2003; Wong and Ahuvia 1998). The value of face also differs across individuals. For example, White et al.’s (2004) research shows stable individual differences in sensitivity to face threats. Geared more toward face gain, Bao et al.’s (2003) study implies significant differences in face wants within cultures. To capture both the negative and the positive dimensions, we define concern for face (CFF) as the extent to which an individual shows regard for and interest in the protection and the enhancement of face. BELIEF IN FATE (BIF) Fate is one of the most pervasive and influential concepts in all cultures. Unlike the concept of God, which varies between faith traditions, fate is generally regarded as referring to “a mysterious force, generated and directed by an impersonal transcendental power or law, such as that which governs the movement of the stars” (Pepitone 1997, 256). According to Cohen (1960), individuals often cope with negative situations by invoking fate/luck because fatalistic notions such as “it is meant to be” or “I am just unlucky” can help alleviate discontent in these situations. In Rotter’s (1966) classic work on locus of control, fate/ luck is synonymous with chance. More recent research, however, views the reliance on fate/luck as a human tendency to make sense of events that have occurred against “the fair and balanced working of chance” (Friedland 1998, 162). In this view, chance and fate/luck are fundamentally different, with the former “[distributing] events fairly and evenly” and the latter “shaping [outcomes]” (162–63). As conceptualized in this article, fate has a stable dimension (often labeled “fate”) and a variable dimension (often labeled “luck”). It refers to an impersonal power that is thought to bring about different events and outcomes—by virtue of a predestined order or a transient condition characterized by good or ill fortune. Comparatively, fate carries a sense of predestination (Pepitone and Saffiotti 1997), whereas luck is perceived as transitory (Darke and Freedman 1997; Mowen and Carlson 2003). All in all, however, fate and luck are quite similar. Recently, Leung and Bond (2004) have used the two terms interchangeably in conceptualizing “fate control” as a general belief for all cultures. Likewise, we define belief in fate (BIF) as the extent to which an individual believes in fate as a powerful force shaping events and outcomes. Not surprisingly, BIF is more strongly held in Asian, collectivist societies (Pepitone 1997; Yau 1988). Their faith traditions espouse a variety of impersonal transcendental laws that are believed to govern the universe and the things that happen to individuals (Ho 1995; Schutte and Ciarlante 1998). In contrast, Western, individualist societies place a high value on science and rationality—as opposed to fate as a mystical explanation (Pepitone 1997). This long-standing Western value is grounded in the Christian faith, as many have argued (e.g., Jaki 2000). There is also evidence of stable individual differences in BIF. In the realm of consumer behavior, BIF has been found to be an antecedent of superstitious behavior (Mowen and Carlson 2003) and to influence risk-taking behavior (Darke and Freedman 1997; Friedland 1998). THE CONTRASTING EFFECTS OF CULTURE ON SERVICE CONSUMERS Our review of the literature suggests two contrasting effects of culture on consumer tolerance: Asian, collectivist consumers may be (1) less tolerant because they are higher in CFF or (2) more tolerant because they are higher in BIF. Given the interpersonal (impersonal) nature of face (fate), we expect the CFF (BIF) effect to prevail when the social (nonsocial) elements are salient. The dual focus of service consumption makes it an ideal context for examining these contrasting effects. Previous CONTRASTING EFFECTS OF CULTURE 000 research has dichotomized service quality along the social and nonsocial dimensions (e.g., “soft” vs. “hard” attributes [Driver and Johnston 2001] and “process” vs. “outcome” failures [Smith, Bolton, and Wagner 1999]). As conceptualized in this article, a social failure refers to a service failure in which the consumer suffers a loss of social resources (e.g., status, esteem) due to interaction with the service staff. In contrast, a nonsocial failure refers to a service failure in which the consumer suffers a loss of nonsocial resources (e.g., money, time) due to the service environment or service outcome. These definitions draw on Smith et al.’s idea of matching failure types to resource types, as well as Brady and Cronin’s (2001) three-factor model of service quality: interaction, physical environment, and outcome. Unlike Brady and Cronin, who view other consumers as a part of the “physical environment,” we confine the term only to the nonsocial aspects of the environment. The following examples illustrate social versus nonsocial failures. A hotel guest experiences a social failure if the front-desk clerk is unfriendly and a nonsocial failure if the room is unclean. By the same token, a restaurant patron experiences a social failure if the waitperson is inattentive and a nonsocial failure if a desired dish is unavailable. Individual-Level Hypotheses Human elements are an integral part of services (Zeithaml et al. 1990). Typically, service encounters involve interpersonal interactions in which face issues “must be constantly attended to” (Brown and Levinson 1987, 61). A service failure thus poses a face threat, since the consumer’s desire for service is ignored or thwarted. We expect CFF, the consumer’s value judgment of the importance of face, to influence the reaction to a service failure. Specifically, we predict an aggravating effect of CFF on service dissatisfaction. Moreover, face is a more salient issue in a social failure than in a nonsocial failure. It follows that CFF should exert a stronger influence on consumer reaction to the former than to the latter. Formally, we predict an interaction between CFF and failure type, such that the aggravating effect of CFF on consumer dissatisfaction would be more pronounced for a social (vs. nonsocial) failure. H1: There is an aggravating effect of CFF on consumer dissatisfaction with a service failure, and this effect is stronger for a social failure than for a nonsocial failure. Due to the inherent variability of service performance, consumers must accommodate the fact that airline flights may be delayed, hotel rooms may be unclean, and restaurant dishes may not be cooked to order. In these circumstances, fatalistic thinking is often invoked as a coping mechanism (Cohen 1960). At the culture level, a positive relationship between BIF and consumer tolerance has been proposed (Yau 1988). We expect the same pattern at the individual level. In other words, we predict an alleviating effect of BIF on service dissatisfaction. However, fatalistic thinking tends to be suppressed when an explicit cause is available (Pepitone and Saffiotti 1997). This is the case with a social failure, which involves an obvious causal agent—the service staff. In contrast, a nonsocial failure is more ambiguous and hence more open to fatalistic interpretations. For example, a flight delay may be due to bad weather, mechanical problems, congested air space, security measures, late passengers, and so on; some of which are beyond human control. Therefore, we predict an interaction between BIF and failure type, such that the alleviating effect of BIF on consumer dissatisfaction would be more pronounced for a nonsocial (vs. social) failure. H2: There is an alleviating effect of BIF on consumer dissatisfaction with a service failure, and this effect is stronger for a nonsocial failure than for a social failure. Culture-Level Hypotheses Taken together, hypotheses 1 and 2 point to an interesting pattern of cross-cultural behavior. As the literature suggests, Asian (vs. Western) consumers are higher in both CFF and BIF. Hence, Asian consumers are subject to a stronger CFF (BIF) effect that is expected to aggravate (alleviate) dissatisfaction. Since we also expect the CFF (BIF) effect to be more pronounced in a social (nonsocial) failure, it follows that Asian (vs. Western) consumers should experience higher dissatisfaction in a social failure and lower dissatisfaction in a nonsocial failure. H3: Asian (vs. Western) consumers are more dissatisfied with a social failure. H4: Asian (vs. Western) consumers are less dissatisfied with a nonsocial failure. THE CFF AND BIF SCALES We adapted eight CFF items from Cocroft and TingToomey (1994) and White et al. (2004) and 10 BIF items from Leung and Bond (2004) and Mowen and Carlson (2003). Two hundred and fifty undergraduate students (50% male) at a Hong Kong university participated in a pretest for item refinement. They responded to the 18 items on 10- point Likert scales ( disagree; 1 p strongly 10 p strongly agree). Three factors emerged from exploratory factor analysis. Six CFF items loaded on the first factor, and six BIF items loaded on the second factor. All loadings on these two factors exceeded .50. Items that cross-loaded on the third factor were dropped. Confirmatory factor analysis was performed on the revised scales with two new samples from the same university. The first sample consisted of 210 local students (48% male). The goodness-of-fit index ( ), nonnormed fit index GFI p .88 ( ), and comparative fit index ( ) in- NNFI p .92 CFI p .94 dicated satisfactory fit, and the percentage of variance extracted for each factor exceeded .50. Reliability was high for 000 JOURNAL OF CONSUMER RESEARCH both scales ( ; ). There was no corre- aCFF BIF p .92 a p .86 lation between CFF and BIF ( , NS). The second sam- r p .08 ple consisted of 206 international students (39% male) from Europe and North America. The GFI (.85), NNFI (.91), and CFI (.93) statistics were comparable to those of the local sample, and the percentage of variance extracted for each factor also exceeded .50. Reliability was high for both scales ( ; ). There was no correlation between aCFF BIF p .89 a p .88 CFF and BIF ( , NS). Appendix A contains the scale r p .03 items. The scales attained a satisfactory level of cross-cultural comparability. First, CFF and BIF were likely understood in the same ways by all participants because of the universal nature of these constructs. Second, the scale items were adapted from research conducted across many cultures. The fact that all participants were undergraduate students proficient in the English language also helped assure item equivalence. Third, confirmatory factor analyses were used to cross-validate the scales in different cultural samples. No differences between the reliability statistics were found. STUDY 1 Method Participants were 244 undergraduate students at a Hong Kong university. About half of them (52% male) were local East Asians, and the rest (43% male) were Caucasian North Americans on short-term exchange (82% American and 18% Canadian). Participants were recruited on campus and paid HK$30 (approximately US$4). Prior to the study, they were classified as either East Asian (in short, Asian) or North American (in short, American) and assigned to either a social failure or a nonsocial failure condition. Their CFF and BIF scores were measured during the study. Participants read a restaurant scenario adapted from Smith et al. (1999) depicting either a social or a nonsocial failure (see app. B). To facilitate interpretation, we conducted pretests to ensure that the failures were perceived as equally severe by the Asian participants. The failure type manipulation was assessed with a social failure measure and a nonsocial failure measure modified from Brady and Cronin (2001) and Hui et al. (2004). The dependent variable was then captured with a three-item dissatisfaction index. Following a distractor task, the CFF and BIF scales were administered. All the above items were measured with 10- point Likert scales ( disagree; 1 p strongly 10 p strongly agree). Finally, participants provided demographic data and commented on the study. The vast majority found the scenarios realistic, and none were able to guess the real purpose of the study. Appendix C contains the manipulation check and dissatisfaction items. Results Manipulation Checks. Participants in the social (vs. nonsocial) failure condition scored higher on the social failure measure ( ; vs. ; a p .93 MSF NF p 8.21 M p 3.89 F(1, 242) p 733.71, ), and those in the nonsocial p ! .001 (vs. social) failure condition scored higher on the nonsocial failure measure ( ; vs. ; a p .91 MSF NF p 4.86 M p 8.37 F(1, 242) p 481.14, ). Hence, participants per- p ! .001 ceived the two failure scenarios as intended. The overall mean dissatisfaction rating was 6.91 ( ). As in the a p .95 pretests, the two failure conditions provoked similar dissatisfaction levels for the Asian participants (MSF p 6.95 vs. ; ). MNF p 6.74 F ! 1 CFF and BIF Scores. The CFF scores were higher for Asians than for Americans ( vs. ; MAsian Amer p 7.02 M p 6.06 F(1, 242) p 28.94, ), and so were the BIF scores p ! .001 ( vs. ; , MAsian Amer p 6.09 M p 4.06 F(1, 242) p 92.04 p ! .001). Therefore, we replicated the results of prior research. In both cultural groups, there was no correlation (r Asian p .06, NS; , NS) between the CFF scale ( r Amer Asian p .08 a p .92; ) and the BIF scale ( ; aAmer Asian Amer p .89 a p .90 a p .88). Individual-Level Hypotheses. Hierarchical regressions were performed to assess the effects of the independent variables on dissatisfaction. The within-subjects variables, CFF and BIF, were continuous. The between-subjects variables, failure type (social ; nonsocial ) and failure p 0 failure p 1 culture ( ; ), were categorical. We Asian p 0 American p 1 first examined the individual-level hypotheses using the whole data set and then reexamined them within each cultural group. Pooling the data from both cultures, we found support for hypotheses 1 and 2. As predicted by hypothesis 1, there was a CFF main effect ( , , ), qual- b p .52 t p 8.44 p ! .001 ified by a CFF # failure type interaction ( , b p
.49 t p
4.60, ). The positive CFF coefficient showed that p ! .001 CFF had a magnifying effect on dissatisfaction. Since social failure was coded 0 and nonsocial failure was coded 1, the negative interaction term (given a positive CFF main effect) indicated a stronger CFF effect in a social failure than in a nonsocial failure. Hence, hypothesis 1 received full support. Consistent with hypothesis 2, there was a BIF main effect ( , , ), qualified by a BIF b p
.36 t p
6.95 p ! .001 # failure type interaction ( , , ). b p
.46 t p
4.95 p ! .001 The negative BIF coefficient showed that BIF had an alleviating effect on dissatisfaction. In view of the failure type coding, the negative interaction term (given a negative BIF main effect) revealed a stronger BIF effect in a nonsocial failure than in a social failure. These findings confirmed hypothesis 2. Apart from the hypothesized effects, there was also a failure type main effect ( , , ). Since b p .63 t p 3.70 p ! .001 the Asian participants found both failure conditions equally dissatisfying (as manipulated), the failure type main effect was indicative of the American participants’ higher dissatisfaction with a nonsocial failure (coded 1) than with a social failure (coded 0). However, the culture # failure type interaction was not significant. This was likely due to the mediating roles of CFF and BIF in explaining the effects of culture (see mediation analysis below). In the presence CONTRASTING EFFECTS OF CULTURE 000 TABLE 1 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—OVERALL RESULTS (STUDY 1) Source Estimate SE t-statistic Intercept 5.09 .53 9.65*** CFF .52 .06 8.44*** BIF
.36 .05
6.95*** Culture
.11 .21
.53 Failure type .63 .17 3.70*** CFF # BIF .01 .04 .27 CFF # culture .14 .13 1.01 BIF # culture
.12 .10
1.19 CFF # failure type
.49 .11
4.60*** BIF # failure type
.46 .09
4.95*** Culture # failure type .41 .37 1.10 CFF # BIF # culture
.04 .08
.56 CFF # BIF # failure type
.10 .08
1.29 CFF # culture # failure type
.13 .27
.48 BIF # culture # failure type .17 .20 .87 CFF # BIF # culture # failure type
.08 .16
.49 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted . 2 R p .52 *** . p ! .001 of these mediators, the culture # failure type interaction was reduced to nonsignificance. Hypotheses 1 and 2 held up when the cultural groups were analyzed separately. All pertinent coefficients were significant and in the predicted directions for Asians ( ) and p’s ! .01 Americans ( ). Tables 1 and 2 summarize the re- p’s ! .05 gression results. Table 3 displays the pattern of means (not analyzed above) based on a median-split procedure that dichotomized CFF and BIF. Culture-Level Hypotheses. To examine hypotheses 3 and 4, we performed two ANOVAs, one for each failure condition (see table 4). As expected, a social failure provoked greater dissatisfaction in Asians ( vs. MAsian p 6.95 MAmer p 6.04; , ), and the reverse F(1, 120) p 8.98 p ! .01 was true for a nonsocial failure ( vs. MAsian Amer p 6.74 M p 7.89; , ). Thus, both cross-cultural F(1, 120) p 22.40 p ! .001 hypotheses were supported. Conceptually, the cross-cultural pattern was driven by individual differences in CFF and BIF between the two cultures. To verify this, we performed mediation analysis following Baron and Kenny (1986). For the social failure condition, we first demonstrated significant effects of culture ( ; ) on dissatisfaction and also on Asian p 0 American p 1 CFF ( ). Then we included both culture and CFF p’s ! .01 in the regression model for dissatisfaction. As expected, the effect of CFF was significant ( ), whereas the effect p ! .001 of culture was reduced to nonsignificance ( ). These p 1 .20 results provided strong evidence that CFF mediated the effect of culture on dissatisfaction with a social failure. A similar test confirmed the mediating role of BIF in the nonsocial failure condition. Details of the mediation tests can be found in table 5. Further analysis revealed that the mediating influence of CFF (BIF) was specific only to a social (nonsocial) failure. Discussion Converging evidence from Asian and Western consumers confirms our hypotheses that higher levels of CFF (BIF) lead to higher (lower) levels of service dissatisfaction and that the CFF (BIF) effect is stronger for a social (nonsocial) failure than for a nonsocial (social) failure. At the culture level, Asian (vs. Western) consumers are, as predicted, more dissatisfied with a social failure but less dissatisfied with a nonsocial failure. Mediation analysis supports our view that the culture-level results are driven by individual-level CFF and BIF tendencies. One weakness of study 1 is that the nonsocial failure scenario involved a rather rare event (two preferred dishes unavailable) relative to the social failure scenario (being served by an unfriendly, inattentive waiter). To rule out event frequency as a potential confound, we conducted a follow-up study using failure scenarios matched in both frequency and severity (one preferred dish unavailable vs. order taken by an unfriendly waiter). The follow-up study was carried out as an extra-credit assignment at the same university with 118 local students (46% male). The results mirrored those of study 1 ( ), thus ruling out event p’s ! .05 frequency as an alternative explanation. We also employed a new set of manipulation check items that directly measured the loss of social resources (“did not show you respect” and “threatened your status”) versus nonsocial resources (“lacked efficiency” and “wasted your time”). Participants showed differential responses to the direct measures ( ) in the p’s ! .001 same way as they did the indirect measures of study 1. Study 1 highlights a boundary condition of the prevailing view (that Asian consumers are more tolerant) by showing that it holds true for a nonsocial failure but not for a social failure (in which Asian consumers are less tolerant). More important, these contrasting effects are attributable to the CFF and BIF tendencies underlying the respective cultures. Although both CFF and BIF are chronically higher for Asian (vs. Western) consumers, they have opposite effects on consumer tolerance across cultures. Moreover, the CFF (BIF) effect is dominant in a social (nonsocial) failure. The multifaceted influence of culture calls for a more refined approach to conceptualizing cross-cultural behavior than the generalized I-C framework. In a social (nonsocial) failure, the dominance of the CFF (BIF) effect suggests that CFF (BIF) is salient relative to BIF (CFF). Given the conceptual independence between CFF and BIF, an intriguing question remains: What happens when they are both salient? Arguably, when CFF also becomes salient in a nonsocial failure, the heightened CFF effect may negate the BIF effect found to be dominant. This being the case, the prevailing view (that Asian consumers are more tolerant) is refutable even in a nonsocial failure. Conversely, the finding that Asians are less tolerant of a social failure may not be sustainable when BIF also becomes salient. Against this background, we replicate and extend the results of study 1 by highlighting two contextual factors that moderate the overall effect of culture. By manipulating the pres- 000 JOURNAL OF CONSUMER RESEARCH TABLE 2 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—RESULTS BY CULTURE (STUDY 1) Source Asian American Estimate SE t-statistic Estimate SE t-statistic Intercept 4.82 .66 7.29*** 4.50 .61 7.44*** CFF .51 .08 6.83*** .55 .09 6.14*** BIF
.24 .07
3.39**
.39 .07
5.67*** Failure type
.31 .23
1.37 1.51 .23 6.55*** CFF # BIF .04 .06 .72
.00 .05
.08 CFF # failure type
.54 .14
3.88***
.46 .17
2.72** BIF # failure type
.60 .13
4.61***
.34 .14
2.51* CFF # BIF # failure type
.06 .11
.52
.13 .11
1.24 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted (Asian group); adjusted (American group). 2 2 R p .46 R p .56 * . p ! .05 ** . p ! .01 *** . p ! .001 TABLE 3 MEAN DISSATISFACTION RATINGS (INDIVIDUAL-LEVEL DATA) CFF BIF High Low High Low Study 1: Social failure 7.53 5.72 6.39 6.74 Nonsocial failure 7.02 6.85 6.21 7.84 Study 2: Private setting 5.85 5.71 5.20 6.41 Public setting 7.44 5.76 6.04 7.03 Study 3: Fate-unrelated brand name 8.43 7.27 7.78 7.82 Fate-suggestive brand name 7.57 6.92 6.78 7.81 NOTE.—CFF p concern for face; BIF p belief in fate. Higher means indicate higher dissatisfaction. The means are presented for easy comparison. All individual-level data were analyzed with hierarchical regressions. TABLE 4 MEAN DISSATISFACTION RATINGS (CULTURE-LEVEL DATA) Culture Asian Western Study 1: Social failure 6.95 6.04 Nonsocial failure 6.74 7.89 Study 2: Private setting 5.24 6.37 Public setting 6.46 6.59 Study 3: Fate-unrelated brand name 8.23 7.31 Fate-suggestive brand name 7.18 7.16 NOTE.—Higher means indicate higher dissatisfaction. ence (vs. absence) of other consumers in study 2, we suggest that Asian consumers are not necessarily more tolerant of a nonsocial failure. By manipulating a fate-suggestive (vs. fateunrelated) brand name in study 3, we argue that Asian consumers are not necessarily less tolerant of a social failure. SOCIAL PRESENCE AND BRAND NAME EFFECTS Social Presence Effects in a Nonsocial Failure (Study 2) Service consumption often takes place in the presence of other consumers. Their presence has been shown to elicit impression management behavior (Argo, Dahl, and Manchanda 2005), which is indicative of a heightened awareness of face threats (Goffman 1967). In other words, face threats loom large when other consumers are nearby. The implication is a larger CFF effect in a public (vs. private) setting. In particular, a contextually enhanced CFF effect sheds new light on consumer behavior in a nonsocial failure, in which the BIF effect has been shown to be dominant. Note that BIF reflects the perceived influence of an impersonal transcendental power (Pepitone 1997). Social presence is therefore not expected to have any impact on the BIF effect. H5: Given a nonsocial failure, the aggravating effect of CFF on consumer dissatisfaction is stronger in a public (vs. private) setting, but the alleviating effect of BIF on consumer dissatisfaction does not differ between the two settings. Cross-culturally, hypothesis 5 adds a new twist to the prevailing view (that Asian consumers are more tolerant), which apparently holds up well for a nonsocial failure, as study 1 has found in a private setting. According to hypothesis 5, however, a public setting magnifies the aggravating CFF effect but not the alleviating BIF effect. The magnification should be stronger for Asian consumers because of their greater emphasis on face. This counteracts the powerful BIF effect on Asian consumers in a nonsocial failure, so the overall effect of culture should diminish. H6: Given a nonsocial failure, Asian (vs. Western) consumers are less dissatisfied in a private setting, but this cultural difference diminishes in a public setting. CONTRASTING EFFECTS OF CULTURE 000 TABLE 5 SUMMARY OF MEDIATION ANALYSIS (STUDY 1) Failure type Step Dependent variable Independent variable Estimate t-statistic Social 1 Dissatisfaction Culture
.91
3.00** 2 CFF Culture
.86
3.25** 3 Dissatisfaction Culture
.26
1.09 CFF .75 9.47*** Nonsocial 1 Dissatisfaction Culture 1.15 4.73*** 2 BIF Culture
2.56
8.29*** 3 Dissatisfaction Culture
.12
.52 BIF
.50
8.90*** NOTE.—CFF p concern for face; BIF p belief in fate. ** . p ! .01 *** . p ! .001 Brand Name Effects in a Social Failure (Study 3) The name of a brand is often rich in associations. It may enhance retrieval of affect (Stayman and Batra 1991), suggest specific benefits and facilitate recall of related claims (Keller, Heckler, and Houston 1998), and increase sensitivity to particular linguistic elements (Zhang and Schmitt 2001). In this light, we propose that a fate-suggestive (vs. fate-unrelated) brand name heightens the impact of BIF but not CFF, which is conceptually unrelated to fate. A heightened BIF effect is of theoretical interest in a social failure, in which the CFF effect has been shown to be dominant. H7: Given a social failure, the alleviating effect of BIF on consumer dissatisfaction is stronger when the brand name is fate suggestive (vs. fate unrelated), but the aggravating effect of CFF on consumer dissatisfaction does not differ between the two brand names. Contrary to the prevailing view, study 1 has shown that Asian consumers are less tolerant of a social failure—without taking brand name into account. For a fate-unrelated brand name, we expect to replicate this pattern. According to hypothesis 7, however, a fate-suggestive brand name enhances the alleviating BIF effect but not the aggravating CFF effect. In all likelihood, the enhancement is stronger for Asian consumers because they are more receptive to the concept of fate. This enhanced BIF effect should mitigate the powerful CFF effect on Asian consumers in a social failure, resulting in a diminished effect of culture overall. H8: Given a social failure, Asian (vs. Western) consumers are more dissatisfied when the brand name is fate unrelated, but this cultural difference diminishes when the brand name is fate suggestive. STUDY 2 Method Participants comprised 120 undergraduate students (62% male) from a Hong Kong university and 118 undergraduate students (53% male) from a university in the United States. They were paid the comparable amounts of HK$30 and US$4, respectively. Participants were assigned to either a private or a public condition involving a nonsocial failure. The procedure was similar to that of study 1. Participants read either a private or a public scenario about a movie theater (see app. B). A pretest confirmed that the scenarios depicted a nonsocial failure rather than a social failure ( ). p’s ! .001 Note three modifications in the procedure: (1) the dependent measure was taken immediately after the scenario, (2) a confound check for event frequency was added (see app. C for all the measures), and (3) the self-construal scale (Singelis 1994) was administered—subsequent to the CFF and BIF scales. Results Manipulation Checks. The consumption setting manipulation was successful. The public setting was perceived as more conspicuous than the private setting for Asians ( vs. ; , MPublic Priv p 6.53 M p 5.22 F(1, 118) p 12.97 p ! .001) and for Americans ( vs. ; MPublic Priv p 7.07 M p 5.80 F(1, 116) p 8.76, ). The scenarios were perceived as p ! .01 equally likely to occur ( for both cultural groups). p 1 .60 The self-construal scale ( ; ) con- aAsian Amer p .70 a p .72 firmed that Asian participants had lower independent ratings ( , ; ) but higher inter- MAsian Amer p 6.37 M p 7.07 p ! .001 dependent ratings ( , ; ). MAsian Amer p 6.85 M p 6.04 p ! .001 CFF and BIF Scores. As in study 1, Asians had higher CFF scores ( vs. ; MAsian Amer p 7.06 M p 6.16 F(1, 236) p 23.99, ) and BIF scores ( vs. p ! .001 MAsian Amer p 5.72 M p 3.94; , ). The CFF scale ( F(1, 236) p 72.17 p ! .001 aAsian p .88; ) and the BIF scale ( ; aAmer Asian Amer p .85 a p .87 a p .83) were uncorrelated in both cultural groups ( , r Asian p .04 NS; , NS). r Amer p .06 Individual-Level Hypothesis. We tested hypothesis 5 with hierarchical regressions. Pooling the data from both cultures, we found three main effects: one for CFF ( , b p .34 t p 4.41, ), one for BIF ( , , p ! .001 b p
.39 t p
5.88 p ! .001), and one for setting ( , , ). b p .75 t p 3.48 p ! .01 There was also a CFF # setting interaction ( , b p .62 t p 4.13, ). No other effects were significant. p ! .001 The CFF and BIF coefficients indicated an aggravating CFF effect and an alleviating BIF effect. The main effect of setting ( ; ) was such that a public private p 0 public p 1 setting elicited a stronger dissatisfaction response. More important, the CFF # setting interaction was positive, indicating a stronger CFF effect in the public setting. This, together with a uniform BIF effect across settings, as evidenced by the lack of a BIF # setting interaction, confirmed hypothesis 5. 000 JOURNAL OF CONSUMER RESEARCH TABLE 6 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—OVERALL RESULTS (STUDY 2) Source Estimate SE t-statistic Intercept 5.34 .68 7.89*** CFF .34 .08 4.41*** BIF
.39 .07
5.88*** Culture .24 .25 .94 Setting .75 .22 3.48** CFF # BIF .07 .04 1.72 CFF # culture .11 .17 .68 BIF # culture .09 .14 .62 CFF # setting .62 .15 4.13*** BIF # setting
.00 .13
.01 Culture # setting
.13 .50
.27 CFF # BIF # culture
.05 .09
.49 CFF # BIF # setting
.02 .09
.23 CFF # culture # setting
.27 .35
.78 BIF # culture # setting .21 .28 .75 CFF # BIF # culture # setting
.08 .18
.44 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted . 2 R p .26 ** . p ! .01 *** . p ! .001 Hypothesis 5 was also supported when the data were split by culture ( ). Tables 6 and 7 present the different p’s ! .01 regression analyses. The pattern of means (not analyzed) obtained from median splitting the CFF and BIF scores can be found in table 3. Culture-Level Hypothesis. A ANOVA yielded 2 # 2 a main effect of culture ( vs. ; MAsian Amer p 5.85 M p 6.48 F(1, 234) p 7.33, ), a main effect of setting p ! .01 ( vs. ; , MPriv Public p 5.81 M p 6.52 F(1, 234) p 9.36 p ! .01), and a culture # setting interaction (F(1, 234) p 4.49, ). Supporting hypothesis 6, a private setting p ! .05 elicited lower dissatisfaction for Asians than for Americans ( vs. ; , MAsian Amer p 5.24 M p 6.37 F(1, 234) p 23.45 p ! .001), whereas a public setting reduced the cultural difference to nonsignificance ( vs. ; MAsian Amer p 6.46 M p 6.59 F ! 1; see table 4). Conceptually, the cross-cultural pattern was driven by individual differences in CFF across the two cultures. To verify that the culture # setting interaction was mediated by a CFF # setting interaction, we conducted a mediated moderation test (Baron and Kenny 1986). First, we regressed dissatisfaction on the main and interactive effects of culture ( ; ) and setting ( Asian p 0 American p 1 private p 0 public ; ). Second, we added the main effect of CFF p 1 to show that CFF alone did not mediate the culture # setting effect on dissatisfaction. Indeed, the culture # setting interaction remained strong ( ) despite a significant CFF p ! .05 main effect ( ). After confirming a significant rela- p ! .001 tionship between CFF # setting and culture # setting ( ), we finally showed that the culture p ! .001 # setting interaction was no longer significant ( ) in the pres- p 1 .30 ence of a significant CFF # setting interaction ( ). p ! .001 Hence, the mediated moderation test was successful (see table 8). Discussion Study 2 partially replicates study 1 by confirming in a private setting that Asian (vs. Western) consumers are less dissatisfied with a nonsocial failure—due to the dominant BIF effect. As a point of departure, study 2 demonstrates that a public setting heightens the CFF effect but not the BIF effect, thus negating the BIF effect induced by a nonsocial failure. In a public setting, the prevailing view (that Asian consumers are more tolerant) is refutable even for a nonsocial failure. In summary, the first two studies suggest that the overall effect of culture reflects the relative impacts of CFF and BIF, which are contingent on service attributes (study 1) as well as contextual factors (study 2). Study 1 establishes the prominent role of CFF (BIF) in a social (nonsocial) failure. Study 2 further reveals that CFF also plays an important role in a nonsocial failure that occurs in a public setting. As far as study 2 is concerned, the contextually enhanced CFF effect is strong enough to neutralize the failure-induced BIF effect. STUDY 3 Method Participants were recruited and compensated as in study 1. The 106 Asian participants (40% male) and 106 American participants (47% male) were assigned to a social failure scenario about a computer service with either a fate-suggestive or a fate-unrelated brand name. The procedure of study 3 was identical to that of study 2. Participants read a scenario about a computer service named either Lucky Star or Double Star (see app. B). A series of pretests established that (1) Lucky Star evoked more fate-related thoughts than did Double Star (p’s ! .001), (2) familiarity and favorability ratings of the brand names did not differ ( ) between a high BIF group p’s 1 .60 ( ) and a low BIF group ( ), and (3) MBIF BIF p 6.77 M p 4.28 the scenarios depicted a social failure rather than a nonsocial failure ( ). See appendix C for study 3 measures. p’s ! .001 Results Manipulation Checks. Apart from the checks performed via pretests, study 3 participants rated the scenarios as equally likely to occur ( ). The self-construal p’s 1 .50 scale ( ; ) confirmed that Asians had aAsian Amer p .71 a p .74 lower independent ratings ( , ; MAsian Amer p 6.27 M p 7.01 p ! .001) but higher interdependent ratings ( , MAsian p 6.99 MAmer p 6.28; ). p ! .001 CFF and BIF Scores. As before, Asians had higher CFF scores ( vs. ; MAsian Amer p 7.17 M p 6.41 F(1, 210) p 25.06, ) and higher BIF scores ( vs. p ! .001 MAsian p 5.50 MAmer p 4.10; , ). There was no F(1, 210) p 41.25 p ! .001 correlation ( , NS; , NS) between the r Asian Amer p
.01 r p .03 CONTRASTING EFFECTS OF CULTURE 000 TABLE 7 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—RESULTS BY CULTURE (STUDY 2) Source Asian American Estimate SE t-statistic Estimate SE t-statistic Intercept 4.73 1.04 4.55*** 5.95 .72 8.22*** CFF .38 .12 3.24** .30 .10 3.01** BIF
.38 .10
3.82***
.38 .09
4.17*** Setting 1.11 .31 3.62*** .38 .30 1.25 CFF # BIF .10 .08 1.39 .06 .05 1.19 CFF # setting .77 .25 3.11** .53 .19 2.74** BIF # setting
.12 .19
.63 .11 .18 .62 CFF # BIF # setting .03 .15 .22
.05 .11
.44 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted (Asian group); adjusted (American group). 2 2 R p .28 R p .21 ** . p ! .01 *** . p ! .001 TABLE 8 SUMMARY OF MEDIATION ANALYSIS (STUDY 2) Step Dependent variable Independent variable Estimate t-statistic 1 Dissatisfaction Culture 1.13 3.41** Setting 1.21 3.68*** Culture # setting
.99
2.12* 2 Dissatisfaction Culture 1.40 4.26*** Setting 1.27 3.98*** Culture # setting
.98
2.15* CFF .31 3.87*** 3 Dissatisfaction Culture 1.15 3.50** Setting
2.87
2.50** Culture # setting
.45
.97 CFF .02 .19 CFF # setting .59 3.74*** NOTE.—CFF p concern for face. * . p ! .05 ** . p ! .01 *** . p ! .001 TABLE 9 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—OVERALL RESULTS (STUDY 3) Source Estimate SE t-statistic Intercept 5.44 .71 7.67*** CFF .50 .09 5.84*** BIF
.19 .06
3.10** Culture
.35 .22
1.60 Brand name
.64 .19
3.36** CFF # BIF .02 .05 .32 CFF # culture .07 .18 .40 BIF # culture
.11 .13
.83 CFF # brand name
.09 .17
.56 BIF # brand name
.42 .12
3.59*** Culture # brand name .46 .43 1.05 CFF # BIF # culture .16 .10 1.58 CFF # BIF # brand name .07 .10 .66 CFF # culture # brand name
.06 .38
.16 BIF # culture # brand name
.19 .25
.75 CFF # BIF # culture # brand name .11 .21 .55 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted . 2 R p .27 ** . p ! .01 *** . p ! .001 CFF scale ( ; ) and the BIF scale aAsian Amer p .80 a p .81 ( ; ). aAsian Amer p .85 a p .84 Individual-Level Hypothesis. Hierarchical regressions on dissatisfaction revealed a CFF main effect ( , b p .50 t p 5.84, ), a BIF main effect ( , , p ! .001 b p
.19 t p
3.10 p ! .01), a brand name main effect ( , , b p
.64 t p
3.36 p ! .01), and a BIF # brand name interaction ( , b p
.42 t p
3.59, ). No other effects were significant. p ! .001 Apart from an aggravating CFF main effect and an alleviating BIF main effect, the main effect of brand name ( unrelated; suggestive) was such that a 0 p fate 1 p fate fate-suggestive brand name lowered dissatisfaction. Hypothesis 7 received support from two interaction terms: (1) the significantly negative BIF # brand name interaction indicating a stronger BIF effect for a fate-suggestive (vs. fateunrelated) brand name and (2) the nonsignificant CFF # brand name interaction indicating a uniform CFF effect across brand names. Hypothesis 7 was also supported when the data were split by culture ( ). Tables 9 and 10 present the different p’s ! .01 regression analyses. The pattern of means (not analyzed) obtained from median splitting the CFF and BIF scores can be found in table 3. Culture-Level Hypothesis. A ANOVA yielded 2 # 2 a main effect of culture ( vs. ; MAsian Amer p 7.70 M p 7.24 F(1, 208) p 5.22, ), a main effect of brand name p ! .05 ( vs. ; , ), Msugg unrel p 7.17 M p 7.77 F(1, 208) p 8.57 p ! .01 and also a culture # brand name interaction (F(1, 208) p 4.67, ). Consistent with hypothesis 8, a fate-unrelated p ! .05 brand name elicited higher dissatisfaction for Asians than for Americans ( vs. ; MAsian Amer p 8.23 M p 7.31 F(1, 208) p 20.56, ), whereas a fate-suggestive brand name elic- p ! .001 ited equivalent levels of dissatisfaction for both cultural groups ( vs. ; ; see table 4). MAsian Amer p 7.18 M p 7.16 F ! 1 We also performed a mediated moderation test as we did 000 JOURNAL OF CONSUMER RESEARCH TABLE 10 SUMMARY OF HIERARCHICAL REGRESSION ANALYSIS—RESULTS BY CULTURE (STUDY 3) Source Asian American Estimate SE t-statistic Estimate SE t-statistic Intercept 5.51 .80 6.93*** 5.33 .99 5.39*** CFF .51 .10 5.23*** .49 .14 3.52** BIF
.16 .06
2.60*
.30 .11
2.71** Brand name
1.17 .22
5.36***
.01 .32
.04 CFF # BIF
.04 .05
.86 .13 .09 1.39 CFF # brand name
.08 .20
.39
.24 .29
.83 BIF # brand name
.34 .12
2.70**
.58 .22
2.67** CFF # BIF # brand name .03 .10 .27 .14 .20 .72 NOTE.—CFF p concern for face; BIF p belief in fate; adjusted (Asian group); adjusted (American group). 2 2 R p .37 R p .19 * . p ! .05 ** . p ! .01 *** . p ! .001 TABLE 11 SUMMARY OF MEDIATION ANALYSIS (STUDY 3) Step Dependent variable Independent variable Estimate t-statistic 1 Dissatisfaction Culture
.91
3.14** Brand name
1.04
3.60*** Culture # brand name .89 2.16* 2 Dissatisfaction Culture
1.33
4.29*** Brand name
1.11
3.91*** Culture # brand name 1.12 2.76** BIF
.22
3.33** 3 Dissatisfaction Culture
.86
2.64** Brand name 1.47 1.98* Culture # brand name .46 1.06 BIF .03 .29 BIF # brand name
.47
3.74*** NOTE.—BIF p belief in fate. * . p ! .05 ** . p ! .01 *** . p ! .001 for hypothesis 6. The results are tabulated in table 11. In short, the culture # brand name interaction was mediated by the BIF # brand name interaction. This substantiated the conceptual argument for hypothesis 8. Discussion Study 3 is a mirror image of study 2. First, it replicates an important finding of study 1 with a fate-unrelated brand name, showing that Asian (vs. Western) consumers are more dissatisfied with a social failure—due to the dominant CFF effect. Second, it demonstrates that a fate-suggestive brand name heightens the BIF effect but not the CFF effect. The contextually heightened BIF effect negates the CFF effect induced by a social failure, making Asian consumers as tolerant as Western consumers. Overall, studies 2 and 3 illustrate that service attributes and contextual factors together determine the relative impacts of CFF and BIF and, in turn, consumer tolerance across cultures. GENERAL DISCUSSION Our research indicates that Asian consumers are not necessarily “soft” as portrayed in the services literature. Their higher tolerance, attributable to a stronger BIF, is confined to nonsocial failures. When confronted with social failures, Asian consumers actually take more serious offense because of a higher CFF. Notably, these contrasting effects of culture are sensitive to contextual factors such as the presence of other consumers or a fate-suggestive brand name. This article adds to a growing body of research that takes a dynamic view of culture (e.g., Aaker and Lee 2001; Briley, Morris, and Simonson 2000; Chan and Wan 2008; Chiu et al. 2000; Lau-Gesk 2003). We highlight the fact that culture consists of different values and beliefs, some of which may be more salient than others in a given situation. Although Asian consumers are higher in CFF and BIF, these chronic tendencies only exert a strong influence when they are pertinent to a consumption situation. Depending on the relative impacts of CFF and BIF, Asian consumers may be more or less tolerant than their Western counterparts. One distinguishing feature of our research is the conceptual independence of CFF and BIF. Based on I-C or related constructs, previous research typically examines the effects of cultural tendencies that are polar opposites of each other (e.g., independent vs. interdependent self-views). Not surprisingly, the result is that only one tendency—chronic or recently activated—is driving consumer behavior in a given situation. In contrast, our research evinces the multidimensionality of cultural influence with two variables that are conceptually independent. We show that CFF and BIF can simultaneously exert a strong influence on consumer tolerance across cultures, as different aspects of a consumption situation are conducive to the CFF and BIF effects. These findings demonstrate that the influence of culture is multidimensional as well as dynamic. Furthermore, our research establishes CFF and BIF as viable alternatives to the generalized I-C construct. As a “cultural syndrome,” I-C subsumes a range of finer concepts (Triandis 2001). For example, two aspects of collectiv- CONTRASTING EFFECTS OF CULTURE 000 ism—a heightened sensitivity to others and a heightened need for sensitivity from others—depict the consumer as, respectively, both understanding and demanding. To enhance conceptual clarity, we suggest the wider use of smaller-range variables such as CFF and BIF as building blocks of cross-cultural theory. Several limitations of our research warrant attention. Based on dissatisfaction data, we infer that the impacts of CFF and BIF are elevated in different conditions. Despite the robust findings, direct evidence that CFF and BIF actually become salient in those conditions is lacking. Thus, a natural extension of our research is to illuminate the processes underlying the contrasting effects of culture with thought-listing data (Mandel 2003) or attribution data (Mattila and Patterson 2004). As in Goffman (1967), we conceptualize face as a transient social resource. Although this situational view is appropriate for a single service encounter, a long-term view is needed for repeated or extended service encounters in which the consumer’s claim to face is more enduring. Note that we focus on the loss of face in service encounters, which also afford ample opportunity for face enhancement. This little-explored psychosocial benefit of service consumption is likely emphasized in cultures that place a high value on face. For example, anecdotal evidence suggests that Asian airlines tend to promote social attributes such as attentive flight attendants, rather than nonsocial attributes such as convenient schedules (Schmitt and Pan 1994). Following the locus of control literature, we define fate/luck as external to the consumer. But some researchers (e.g., Darke and Freedman 1997; Weiner 1986) consider it more appropriate to conceptualize fate/luck as an internal or personal attribute. The “internal” view sheds new light on our research, as culture is known to influence the extent to which fate/luck is personalized (Weisz, Rothbaum, and Blackburn 1984). In this view, our research offers a conceptual alternative to Hsee and Weber’s (1999) “cushion hypothesis”—that Chinese are more tolerant of financial risk than Americans because of the strong social networks among Chinese. Namely, a strong belief in personalized fate/luck may give the Chinese a sense of immunity from financial risk. Lay epistemology suggests that fate/luck is thought to be at least partially controllable, so the conventional social scientific position “may be missing an important [dimension] with respect to [its] controllability” (Leung and Bond 2004, 156). Although labeled as irrational or unscientific, consumer practices for managing fate/luck have been widely documented (e.g., Cohen 1960; Darke and Freedman 1997; Mowen and Carlson 2003). Capturing this neglected dimension may open a new door to research on consumer preferences and choice. In conclusion, our research has only scratched the surface of the subtle yet pervasive influence of CFF and BIF. The time is ripe for advancing the field of cross-cultural consumer research with these and other conceptual alternatives to the I-C framework. APPENDIX A THE CFF AND BIF SCALE ITEMS CFF Items 1. I care about praise and criticism from others. 2. I care about others’ attitudes toward me. 3. I hate being taken lightly. 4. I will be very angry if others are impolite to me. 5. I will be very happy if I am treated with respect. 6. I will be very upset if I am criticized in public. 7. I am concerned with my self-image.a 8. I am concerned with my social status.a a Items dropped after exploratory factor analysis. BIF Items 1. Many things in life are predetermined. 2. Fate determines one’s successes and failures. 3. Bad things happen to me mostly because of bad luck. 4. Many things in life are beyond my control. 5. Many important life outcomes are predestined. 6. Luck, rather than effort, is crucial to success. 7. Good luck follows if one survives a disaster.a 8. Individual characteristics, such as appearance and birth date, affect one’s fate.a 9. A person’s talents are inborn.a 10. Getting a good job or promotion in the future will depend on my getting the right turn of events.a a Items dropped after exploratory factor analysis. APPENDIX B SCENARIOS FOR STUDY 1 You go to an American-style restaurant for lunch. It is a nice restaurant in a good neighborhood. You are seated at your table. The waiter comes to take your order. You place your order. (Social failure: The waiter does not smile while taking your order. The waiter brings your food but not your beverage. You ask the waiter about it. The waiter then brings your beverage but does not offer an apology or explanation.) [Nonsocial failure: The waiter informs you that the restaurant is out of the food you selected. You make another selection. The waiter informs you that the restaurant is also out of your second choice of food.] SCENARIOS FOR STUDY 2 You have a 50% off coupon from a new movie theater. You go to the theater alone to see a movie that you like. The clerk at the ticket counter scans the coupon. The scanner cannot read the barcode on the coupon. The clerk checks with the manager over the phone. (Private setting: No one else is around while you wait.) [Public setting: A small, curious crowd gathers while you wait.] The clerk finally sells you a movie ticket at half price after a 5-minute delay. 000 JOURNAL OF CONSUMER RESEARCH SCENARIOS FOR STUDY 3 Your computer has broken down. You take the machine to (Fate-suggestive brand name: Lucky Star Computer Services) [Fate-unrelated brand name: Double Star Computer Services] for repair. You talk to the technician on duty. He looks impatient. He does not bother to listen to you. Instead, he starts performing tests on the computer before you have a chance to describe all the problems you have with the computer. APPENDIX C TABLE C1 MEASURES Measures for study 1 Measures for study 2 Measures for study 3 Manipulation check—social failure: 1. The waiter’s attitude was poor. 2. The waiter’s attitude was acceptable.a 3. The waiter’s attitude was not professional. Manipulation check—nonsocial failure: 1. The selection/availability of food was not good enough. 2. The selection/availability of food was proper.a 3. The selection/availability of food was not acceptable. Dissatisfaction measure: 1. As a whole, you are not satisfied with the restaurant. 2. You are unhappy about your overall experience with the restaurant. 3. You are satisfied with the overall quality of the restaurant.a Manipulation check—social failure (pretest): 1. The clerk did not show you respect. 2. The attitude of the clerk threatened your status. Manipulation check—nonsocial failure (pretest): 1. The coupon validation system wasted your time. 2. The coupon validation system lacked efficiency. Manipulation check—consumption setting: 1. The incident may be characterized as a public event. Confound check—event frequency: 1. The incident may happen to any moviegoer. 2. The incident is likely to happen anywhere. Dissatisfaction measure: 1. As a whole, you are not satisfied with the movie theater. 2. You are unhappy about your overall experience with the movie theater. 3. You are satisfied with the overall quality of the movie theater.a Manipulation check—social failure (pretest): 1. The technician did not show you respect. 2. The attitude of the technician threatened your status. Manipulation check—nonsocial failure (pretest): 1. The repair service did not give you your money’s worth. 2. The repair service lacked efficiency. Manipulation check—brand name (pretest): 1. Please take 3 minutes to write down any thoughts you have about the following brand name. Confound check—brand familiarity and favorability (pretest): 1. The brand name is familiar. 2. I like the brand name. Confound check—event frequency: 1. The incident may happen to any consumer. 2. The incident is likely to happen anywhere. Dissatisfaction measure: 1. As a whole, you are not satisfied with Lucky Star/Double Star. 2. You are unhappy about your overall experience with Lucky Star/Double Star. 3. 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