Group service recovery strategies effectiveness: The moderating effects of group size and relational distance

Journal of Business Research xxx (2014) xxx–xxx

JBR-08045; No of Pages 6

Contents lists available at ScienceDirect

Journal of Business Research

Group service recovery strategies effectiveness: The moderating effects of group sizeand relational distance☆

Yuanyuan Zhou a, Alex S.L. Tsang b, Minxue Huang c,⁎, Nan Zhou c,d

a School of Management, Huazhong University of Science and Technology, Wuhan, Chinab Department of Marketing, School of Business, Hong Kong Baptist University, Hong Kongc School of Economics and Management, Wuhan University, Wuhan, Chinad Department of Marketing, College of Business, City University of Hong Kong, Hong Kong

☆ This research was supported by grants from GRF HNSFC-71372127, NCET-12-0420, and SRFDP- 201301421Woodside and reviewers for providing valuable comments⁎ Corresponding author. Tel.: +86 18607147300.

E-mail addresses: [email protected] (Y. Zho(A.S.L. Tsang), [email protected] (M. Huang), na

http://dx.doi.org/10.1016/j.jbusres.2014.03.0080148-2963/© 2014 Elsevier Inc. All rights reserved.

Please cite this article as: Zhou, Y., et al., Grdistance, Journal of Business Research (2014)

a b s t r a c t
a r t i c l e i n f o
Article history:Received 1 December 2012Received in revised form 1 January 2014Accepted 1 January 2014Available online xxxx

Keywords:Social impact theoryService recoveryService failureSocial distance

The extant service recovery literature focuses on consumers' responses to individual failures. However, groupservice failures are in fact common, but they have received insufficient research attention. This study contributesto theory and practice by applying social impact theory to explain the social nature of group failures. Findingsfrom two studies show that group size and relational distance substantially affect consumers' response togroup service recovery strategies. Specifically, private economic recovery creates less consumer satisfaction asgroup size increases, whereas consumers with a distant social relationship are more satisfied with public recov-ery for both economic recovery and social recovery. However, consumers with close relationships are more sat-isfiedwith public economic recovery and private social recovery. Apart fromoffering practical insights, this studyexpands the theoretical understanding of service failures, suggesting that they occur in a complex social ecologyinstead of relatively simple dyadic interactions between service providers and consumers.

© 2014 Elsevier Inc. All rights reserved.

Introduction

Group service failures are common in the marketplace, but theyreceive scant attention in the service literature. Continuous costreduction pressures and technological advancements (includinginformation and automation technologies) have encouraged firmsto standardize their service offerings for a mass group of customers.However, when a service component fails, a large group of con-sumers suffers. Flight delays are a common example.

What can a firm do to recover if its service failure affects a group ofconsumers? The extant literature mainly focuses on resolutions for fail-ures that involve just a single customer (Grégoire, Tripp, & Legoux,2009; Hess, Ganesan, & Klein, 2003; Smith, Bolton, & Wagner, 1999).The literature includes limited discussion of the social nature of groupfailures. Social presences, regardless of whether they are interactive(Argo, Dahl, &Manchanda, 2005), influence how consumers react to re-covery offers. Zhou, Huang, Tsang, and Zhou (2013) identified individu-al and group service recovery strategies. However, what they proposedare only general approaches; the complex social ecology of a group

KBU-250212, NSFC-71302092,20052. The authors thank Archto earlier versions of this paper.

u), [email protected]@cityu.edu.hk (N. Zhou).

oup service recovery strategi, http://dx.doi.org/10.1016/j.jb

further influences the effectiveness of recovery strategies. Building onsocial impact theory (SIT; Latané, 1981), this paper contributes by iden-tifying two situational factors, group size and relational distance, thatmoderate consumer response to marketers' recovery efforts.

This research empirically tested hypotheses via two studies. Study 1tests the effect of group size on consumers' satisfaction with group ser-vice recovery strategies. Results show that private economic recoverycreates significantly less consumer satisfaction as group size increases.Study 2 verifies the impact of relational distance and confirmed thatconsumers who share a distant relationship are more satisfied with apublic recovery strategy for both economic recovery and social recov-ery, while consumers sharing a close relationship are more satisfiedwith public economic recovery and private social recovery.

This paper contributes to the service recovery literature byhighlighting the social nature of group failures. The study increases un-derstanding of the complex social ecology of group failures. Becausegroup service failures are increasingly common in today's marketplace,our findings should be highly relevant for academic researchers as wellas practitioners.

Theoretical background and research framework

Individual and group service recovery strategies

The highly personal and interactive nature of service makes itvulnerable to failures (Chebat & Slusarczyk, 2005; Hess et al., 2003;

es effectiveness: The moderating effects of group size and relationalusres.2014.03.008

http://dx.doi.org/10.1016/j.jbusres.2014.03.008

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2 Y. Zhou et al. / Journal of Business Research xxx (2014) xxx–xxx

Magnini & Karande, 2009). Service failures cause economic, physical,and/or psychological losses for consumers and lead to numerous adver-sarial consumer responses, including complaining, brand switching,negative word-of-mouth, and retaliation (Bitner, Booms, & Tetreault,1990; Grégoire et al., 2009; Zhou, Tsang, Huang, & Zhou, 2014). Howto make an effective recovery is a topic of great interest to marketingexecutives.

The extant studies focus on individual service recovery strategiesand suggested that remedies can be provided through two major re-covery dimensions: economic recovery and social recovery (Bitneret al., 1990). Examples of economic recovery include monetary com-pensation, partial refunds, and discounts for future purchases. Regard-less of whether the failures cause economic loss or psychologicalsuffering, economic recovery offers direct and quantifiable compensa-tion and, thus, is commonly viewed as a basic recovery strategy(Boshoff, 1997; Smith et al., 1999). Social recovery includes explanationand apology that can comfort customers and compensate for their psy-chological distress (Hart, James, & Sasser, 1990; Michel, 2001); botheconomic recovery and social recovery positively contribute to recoveryeffectiveness.

In the extant literature, whether to offer economic and/or socialrecovery depends mainly on individual factors. For example, aconsumer's encounter with failures of different natures (Hesset al., 2003; Kelley, Hoffman, & Davis, 1993; Smith & Bolton, 1998;Smith et al., 1999), how an individual consumer attributes a servicefailure (Hess et al., 2003; Swanson & Kelley, 2001), his/her prefer-ences (Ringberg, Odekerken-Schröder, & Christensen, 2007), expecta-tions (Andreassen, 1999; McCollough, Berry, & Yadav, 2000), andrelationship with the firm (Grégoire et al., 2009; Hoffman & Kelley,2000; Kwon & Jang, 2012).

Apart fromwhat (economically or socially) to recover, an additionalissue that group service recovery must consider is how a firm offersrecovery. In a group failure, a firm has the option to recover each af-fected customer through individual means (private recovery) or torecover the whole group with mass means (public recovery). Gener-ally speaking, consumers are more satisfied with public economic re-covery and private social recovery (Zhou et al., 2013). However, agroup exists in a complex ecology; does this general understandingapply to groups with specific characteristics, including variousgroup sizes and participants with differing intimacy in the social re-lationship? Our research sheds light on this issue.

Social impact theory

Latané offers a general theory of social influence through socialimpact theory (SIT). Social impact, in Latané's conceptualization,means “changes in physiological states and subjective feelings, mo-tives and emotions, cognitions and beliefs, and values and behavior,that occur in an individual, human or animal, as a result of the real,implied, or imagined presence or actions of other individuals.”(Latané, 1981, p. 343). Simply speaking, SIT explains how a sourceinfluences a target, but more importantly, as Latané argued, SIT iscapable of integrating two historically separate research streams: so-cial influence from the majority (e.g., group pressure, social validation)and social influence from the minority (e.g., opinion leadership) intoone general theory (Latané & Wolf, 1981). Latané explained theapplication of SIT in various social-influence contexts, including con-formity, diffusion of responsibility, and embarrassment. Otherscholars (e.g., Argo et al., 2005) have applied SIT in consumer re-search, arguing that a non-interactive social presence is sufficientto create social impact.

SIT argues that social impacts are determined by threemultiplicativesocial forces: (1) Strength of the source. Strength refers to “salience,power, importance, or intensity of a given source to the target”(Latané, 1981, p. 344). Latané used a relatively loose definition of thisconcept. Strength can be sourced from age, knowledge, power,

Please cite this article as: Zhou, Y., et al., Group service recovery strategidistance, Journal of Business Research (2014), http://dx.doi.org/10.1016/j.j

authority, and socioeconomic status and its influence iswell document-ed in the literature related to conformity, celebrity endorsement, obedi-ence, and opinion leadership, among others. (2) Immediacy. Immediacyrefers to “closeness in space or time and absence of intervening barriersor filters” (Latané, 1981, p. 344). (3) Number of people present. “Num-ber” simplymeans “howmany people are there” (Latané, 1981, p. 344).

Social impact theory in group service recovery: group size and relationaldistance

Weapplied SIT and identified two social forces that differentiate indi-vidual recovery from group recovery: group size and relational distance.When Latané proposed his social forces in SIT, they were presented in arelatively abstract form. We refined his definition for a group recoverycontext: “Group size” refers to the number of affected consumers in agroup service failure; “relational distance” is the level of intimacyamong affected consumers in a service failure.

Group sizemay represent amajor antecedent condition that enablesor prevents successful outcomes of specific customer recovery strate-gies. Prior research has demonstrated that the greater the number ofpeople present, the more significant the social influence on outcomesis (Griffitt & Veitch, 1971; Jackson & Latané, 1981; Langer & Saegert,1977; Latané & Harkins, 1976). Research related to group service recov-ery has shown that consumers are more satisfied with public economicrecovery and private social recovery (Zhou et al., 2013). Hence, we hy-pothesized that:

H1. Group size positively affects consumers' responses to recoverymodes. Specifically, (a) public (private) economic recovery createsmore (less) consumer satisfaction as group size increases and (b)public (private) social recovery creates less (more) consumer satis-faction as group size increases.

With respect to relational distance, consumers sharing distant rela-tionships form a specific group due to incidental factors (i.e., group fail-ure). Members in such groups have no intrinsic links. This kind ofrelationship is loose, resulting in instability in the group structure. Af-fected consumers sharing a close relationship have been more intrinsi-cally linked. Compared to the loose structure, the intimate groupstructure exertsmore significant social influence (Latané, 1981). For ex-ample, themore intimate one party iswith another person, the less psy-chologically distant that person typically seems, and vice versa. Usually,people perceive psychologically distant events in terms of relatively ab-stract features. In contrast, psychologically close events are perceived interms of detailed features (Trope, Liberman, & Wakslak, 2007).

According to relational distance theory, affected consumers sharinga distant relationship may pay more attention to the big picture of therecovery offer (what a firm offers) and assess whether or not the con-tent can recover their loss. Customers in a failure group sharing a closerelationship will, in addition to what is offered, pay attention to howthey are recovered (recovery modes). Thus,

H2. Increases in relational distance positively affect consumers' re-sponses to recovery modes. Specifically, only for affected consumerssharing a close relationship in a service failure group, (a) public (pri-vate) economic recovery creates more (less) consumer satisfactionand (b) public (private) social recovery creates less (more) consumersatisfaction.

Study 1: group size and recovery effectiveness

Design and participants

The objective of study 1 was to test H1, which hypothesized thatgroup size positively affects consumers responses to recoverymodes. Study 1 was a 2 (group size: small group, big group) × 2

es effectiveness: The moderating effects of group size and relationalbusres.2014.03.008


social recovery

3

3.5

4

4.5

5

5.5

6

recoveryrecovery private

recoveryprivate

public

recoverypublic

Sati

sfac

tion

a: small group

economic recovery

*5.86(0.09, 30) 5.50(0.21, 32)

3.84(0.31, 31)

5.26(0.20, 31)

social recovery

3

3.5

4

4.5

5

5.5

6

Sati

sfac

tion

b: big group

economic recovery

5.67(0.17, 30) 3.97(0.24, 32)

4.10(0.29, 31)

5.55(0.17, 31)

Fig. 1. Group size and recovery effectiveness.

3Y. Zhou et al. / Journal of Business Research xxx (2014) xxx–xxx

(recovery modes: public recovery, private recovery) × 2 (recoverydimensions: economic recovery, social recovery) between-subjectsdesign in the context of group tours. Two hundred and forty-eightundergraduate students from amainland Chinese university (60% fe-male, average age 22) participated in the study. They received extracourse credit for their participation.

Materials

The scenario included two parts. The first part let the participantsimagine that they were performing an academic investigation of city Gwith their classmates. Before leaving their home city, they booked ahotel via a well-known travel agency. However, when they arrived attheir accommodations, they found that the hotel was not as good asthe agency promised. They had to walk almost 20 min to the bus stopevery day. Thus, upon returning to their home city, all the participantscomplained to the agency together. We manipulated 5 persons as asmall failure group and 50 as a big one.

The second part of the scenario described the travel agency's re-covery for this group failure. We manipulated refund (10% of accom-modation payment) as economic recovery and apology as socialrecovery. We designed recovery modes with the travel agency send-ing e-mails that differed in perceived scope. In the public recoveryversion, the participants were able to see the e-mail address of theother members when reading the e-mail from the travel agencythat contained information about its recovery strategy. In the privaterecovery version, the recipient was only able to see his or her own e-mail address, and not the other e-mail addresses.

Procedures and variables

The participants were assigned randomly to one of the eight sce-narios. The participants projected themselves into the role of a cus-tomer who experienced the group service failure in which groupsize was manipulated. Participants then read the firm's resolutionin which recovery modes and dimensions were manipulated.

After that, they indicated the extent of their satisfaction with thetravel agency's resolution of the service failure through three items(be satisfied with/accord with my expectation/be pleased with,α = 0.83), which are revised from Chan,Wan, and Sin (2009). Lastly,participants conducted the manipulation check, answered questionsincluding their perceptions of (1) recovery dimensions (apologize inthe e-mail/make compensation in the e-mail), (2) recovery modes,which are revised from Chan et al. (2009) and Jing and Xie (2011)(respond privately, respond individually; α = 0.87), and (3) groupsize (this event involved a large number of consumers). All ratingsused a 7-point Likert scale (1 = strongly disagree; 7 = stronglyagree).

Findings

We checked the effectiveness of the manipulation in study 1. TheANOVA showed: (1) Group size. Participants in the 50-person conditionperceive group size as significantly bigger than in the 5-person condi-tion (M5 = 4.27, SD = 1.47; M50 = 4.81, SD = 1.38; F (1, 247) =9.19, p b 0.01). (2) Recovery dimension. There is a significant differencein participants' perception of the presence of the recovery dimension.Participants in the social recovery condition perceive that the travelagency provided social recovery (Msocial = 5.31, SD = 1.29; Mecon =3.19, SD = 1.73; F (1, 247) = 119.10, p b 0.001) and not economic re-covery (Msocial= 2.25, SD= 1.27;Mecon= 5.48, SD= 1.07; F (1, 247)=471.60, p b 0.001). The participants in the economic recovery conditionfollow the opposite pattern. (3) Recovery modes. Participants perceivedpublic recovery as more conspicuous than private recovery (Mprivate =4.80, SD = 1.40; Mpublic = 2.32, SD = 1.21; F (1, 247) =221.10,p b 0.001). Therefore, the manipulation was successful.

Please cite this article as: Zhou, Y., et al., Group service recovery strategidistance, Journal of Business Research (2014), http://dx.doi.org/10.1016/j.jb

The three-way ANOVA identified significant interaction effectsamong group size, recovery dimensions, and recovery modes in ex-periment 1 (F(1, 240) = 4.78, p b 0.05). Further analyses revealed(Fig. 1) that in the small group condition, the interaction between re-covery mode and recovery dimension is significant for satisfaction(F(1, 240) = 16.40, p b 0.001). For social recovery, participants aremore satisfied when recovery is delivered in a private way than ina public way (Mprivate = 5.26, SD = 1.12; Mpublic = 3.84, SD =1.70; F (1, 240) = 20.72, p b 0.0001). However, for economic recov-ery, there are no significant differences between public recovery andprivate recovery (Mprivate = 5.50, SD = 1.19; Mpublic = 5.86, SD =0.51; F (1, 240) = 1.61, p = 0.21).

In the big group condition, the interaction between recovery modeand recovery dimension is significant for satisfaction (F (1, 240) =50.99, p b 0.001). For social recovery, participants are more satisfiedwhen recovery is delivered in a private way than in a public way(Mprivate = 5.55, SD = 0.93; Mpublic = 4.10, SD = 1.60; F (1, 240) =21.67, p b 0.05). In contrast, for economic recovery, participants aremore satisfied when recovery is delivered in a public way than ina private way (Mprivate = 3.97, SD = 1.38; Mpublic = 5.67, SD =0.93; F (1, 216) = 29.62, p b 0.001).

Another pair of interaction contrasts was examined. The interactionbetween group size and recovery mode is significant when economicrecovery is provided (F (1, 240) = 9.10, p b 0.01) but not when socialrecovery is provided (F (1, 240)= 0.01, p= 0.97). These results revealthat for social recovery, group size has no significant impact on recoverymode choice (public recovery: Msmall = 3.84, SD = 1.70; Mbig = 4.10,SD = 1.60; F (1, 240) = 0.68, p = 0.41; private recovery: Msmall =5.26, SD = 1.12; Mbig = 5.55, SD = 0.93; F (1, 240) = 0.87, p =0.35). However, for economic recovery, group size has a significanteffect on recovery mode choice (public recovery: Msmall = 5.86, SD =0.51;Mbig= 5.67, SD= 0.93; F (1, 240)= 0.40, p= 0.53; private recov-ery: Msmall = 5.50, SD = 1.19; Mbig = 3.97, SD = 1.38; F (1, 240) =24.89, p b 0.001).



social recovery

3

3.5

4

4.5

5

5.5

6

Sati

sfac

tion

a: distant relationship

economic recovery

*5.40(0.16, 28)

3.93(0.21, 28)

4.21(0.23, 28)

3.29(0.25, 28)

social recovery

3

3.5

4

4.5

5

5.5

6

Sati

sfac

tion

b: close relationship

economic recovery

5.50(0.16, 28)

4.11(0.26, 28)

3.43(0.19, 28)

4.10(0.19, 28)

recoverypublic recoverypublic

recoverypublic recoverypublic

* Means (Standard Errors, Sample Sizes)

Fig. 2. Relational distance and recovery effectiveness.


Discussion

Results of study 1 partially support H1. Group size partially affectsconsumers' responses to recovery modes positively. Specifically, in asmall failure group, there is no significant difference in consumers'responses to recovery modes for economic recovery. For social re-covery, group size has no significant impact for consumers' re-sponses to recovery modes; while, for economic recovery, groupsize has a significant effect on consumers' responses to recoverymodes. One possible reason is that public recovery is best for eco-nomic recovery to reduce consumers' negative conjecture (i.e., un-fairness). However, private recovery is better for social recovery toenhance consumers' positive feelings (i.e., sincerity; Zhou et al.,2013). According to prospect theory, variables avoid negative factorsthat exert more influence and enhance positive factors (Kahneman &Tversky, 1979).

Study 2: relational distance and recovery effectiveness

Design and participants

The objective of study 2 was to verify that relational distance pos-itively affects consumers' responses to recovery modes. Study 2 wasa 2 (relational distance: distant, close) × 2 (recovery modes: publicrecovery, private recovery) × 2 (recovery dimensions: economic re-covery, social recovery) between-subjects design in the context ofgroup tours. Two hundred and twenty-four undergraduate studentsin mainland China (64% female, average age 22) participated in study2. The students received extra course credit for their participation.

Materials and procedures

The scenario in study 2 included two parts. The first part describedparticipants as a group of persons deciding to travel to city B. The fol-lowing description was the same as that used in study 1. We manip-ulated the relational difference in this part. The distant relationshipgroup did not know each other and came together as a tour groupthrough a website. The close relationship group was made up offriends who had known each other for many years. They always or-ganized group activities. The second part described the travelagency's solution for this group complaint. This part was the sameas in experiment 1. Procedures of experiment 2 were also the sameas those for study 1. The difference involved the relational distancemanipulation check (members in this group have known eachother for many years/members in this group share a close relation-ship; α = 0.92). Other variables for recovery modes (α = 0.88)and satisfaction (α = 0.85) were the same as in study 1.

Findings

We checked the effectiveness of the manipulation in study 2. TheANOVA showed that: (1) Relational distance. Participants in theclose relationship condition perceive members as closer than in thedistant relationship condition (Mdistant = 2.29, SD = 1.33; Mclose =5.61, SD = 0.99; F (1, 223) = 448.36, p b 0.001). (2) Recovery di-mension. There is significant difference in participants' perceptionof the presence of the recovery dimension. Participants in the social re-covery condition perceive that the travel agency provided social recovery(Msocial = 5.01, SD = 1.36; Meconomic = 3.51, SD = 1.84; F (1, 223) =48.48 p b 0.001) and not economic recovery (Msocial =2.13, SD =1.07; Meconomic = 5.62, SD = 1.09; F (1, 23) = 585.59, p b 0.001).Participants in the economic recovery condition follow the oppositepattern. (3) Recovery modes. Participants perceive public recoveryas more conspicuous than private recovery (Mprivate =4.52, SD =1.60; Mpublic = 2.10, SD = 1.17; F (1, 223) = 166.120, p b 0.001).Therefore, the manipulation was successful.


The three-way ANOVA identified significant interaction effectsamong relational distance, recovery dimensions, and recoverymodes in experiment 2 (F (1, 216) = 6.535, p b 0.05). Further anal-yses (Fig. 2) revealed that in the distant relationship condition, theinteraction between recovery mode and recovery dimension is notsignificant for satisfaction (F (1, 216) = 1.72, p= 0.19). Participantsare more satisfied when recovery is delivered in a public way than ina private way regardless of social recovery (Mprivate = 3.29, SD =1.34; Mpublic = 4.21, SD = 1.21; F (1, 216) = 9.86, p b 0.05) or eco-nomic recovery (Mprivate = 3.93, SD = 1.10; Mpublic = 5.40, SD =0.82; F (1, 216) = 24.92, p b 0.001).

In the close relationship condition, the interaction between re-covery mode and recovery dimension is significant for satisfaction(F (1, 216) = 24.26, p b 0.001). For social recovery, participants aremore satisfied when recovery is delivered privately than publicly(Mprivate = 4.10, SD = 1.02; Mpublic = 3.43, SD = 0.99; F (1, 216) =5.08, p b 0.05). In contrast, for economic recovery, participants aremore satisfied when recovery is delivered publicly than privately(Mprivate = 4.11, SD = 1.37; Mpublic = 5.50, SD = 0.87; F (1, 216) =22.19, p b 0.05).

Discussion

The findings of study 2 support H2. Increases in relational distancepositively affect consumers' responses to recovery modes. Specifically,only for affected consumers sharing a close relationship in a service fail-ure group, public (private) economic recovery creates significantlymore (less) consumer satisfaction and public (private) social recoverycreates significantly less (more) consumer satisfaction.

This pattern is not significant for affected consumers sharing adistant relationship. Consumers sharing a distant relationship in a



5Y. Zhou et al. / Journal of Business Research xxx (2014) xxx–xxx

failure group are more satisfied with a public recovery strategy forboth economic recovery and social recovery. One possible reason isthat in loose conditions, consumers need reference points to reducetheir negative feelings (i.e., uncertainty; Hui, Zhao, Fan, & Au,2004). Following this logic, consumers sharing a distant relationshipneed a public recovery mode to know clearly what other peoplereceive, regardless of whether for social recovery or economicrecovery.

General discussion

This investigation is based on social impact theory and demonstratesthe effects of group size and relational distance on consumers' re-sponses to recovery modes. First, to some extent, group size positivelyaffects consumers' responses to recovery modes. Specifically, no signif-icant difference exists in consumers' responses to recovery modes foreconomic recovery in a small failure group. For social recovery, groupsize has no significant impact on consumers' responses to recoverymodes. Private economic recovery creates significantly less consumersatisfaction as group size increases.

Second, relational distance positively affects consumers' responsesto recovery modes. Specifically, only for affected consumers sharing adistant relationship in a service failure group, public (private) economicrecovery creates significantly more (less) consumer satisfaction andpublic (private) social recovery creates significantly less (more) con-sumer satisfaction. Consumers sharing a distant relationship in a failuregroup are more satisfied with a public recovery strategy for both eco-nomic recovery and social recovery.

This research enriches the theory in service recovery literature. Priorstudies explored how to devise an effective individual service recoverystrategy (Grégoire et al., 2009; Hess et al., 2003; Ringberg et al., 2007;Smith et al., 1999). However, group service failures are in fact common,but they have received insufficient research attention. The presentstudy contributes to the servicemarketing literature by putting forwardthe social nature of failure groups.

This study further enriches social impact theory by investigatingthe moderating effects of the social forces in the theory. We opera-tionalized these forces into applicable concepts for group service re-covery to provide further evidence supporting the validity andpracticality of social impact theory. The study also contributes to so-cial impact theory by examining the moderating effects, instead ofthe main effects, of social forces. Increasing cost pressures is makingmore firms to offer standardized services to a large group of cus-tomers. Standardization saves money, but when a failure occurs, alarge number of customers suffer. Our research provides sugges-tions for service firms to manage group service recovery. The moreconsumers in a failure group, the more private economic recoveryis avoided. For failure groups in which affected consumers share adistant relationship, it is better to deliver recovery in a public way,regardless of whether for economic recovery or social recovery.

Future research is recommended to extend the scope of this re-search and resolve some of its limitations. Our experiments ofgroup failure were conducted in the context of travel. Group failuresoccur inmany industries, includingmedicine, online retailing, and fi-nance, among others. Future research must capture the nature of dif-ferent industries to generalize research findings. Also, this researchtested hypotheses using a scenario-based approach. Future researchis necessary that relies on real-life settings. Another valuable direc-tion for future research is the role of culture in moderating consumerresponse to recovery efforts. While Chinese andWestern cultures aredifferentiated in their collectivism versus individualism, do cus-tomers from these cultures react differently to group size and rela-tional distance? Our data, which were collected in China, haveprovided valuable evidence for a facet of the group failure recoveryphenomenon; generalizability can be further enhanced if samplescover consumers from various cultural groups.

Please cite this article as: Zhou, Y., et al., Group service recovery strategidistance, Journal of Business Research (2014), http://dx.doi.org/10.1016/j.jb

Appendix A. Scenarios for group service failure in study 1

Imagine you are Yu Li who experiences the following story.Five persons (fifty persons), including Yu Li, will be undertaking an

important academic investigation in City G. They would like to book ahotel in advance and thus consult ABC Agency, which is famous intheir community of City W for providing this kind of service. Theychoose a four-star hotel with convenient transportation, well-equippedaccommodations, and free Wi-Fi upon ABC Agency's recommendation.

Arriving in City G, they find that theymustwalk almost 20min fromthe hotel to the nearest bus stop. Since they have a tight schedule, theyhave to stay.

“The inconvenient transportation is troublesome for us after everyday's busy investigation” says Chai, one member of the investigationgroup.

Another member, Zhou, also says “The ABC Agency says that thehotel is convenient. It is not the case. We should complain to it.”

They all agree and complain to the ABCAgency after their return. Thecompany promises to follow up on their case.

Appendix B. Scenarios for group recovery in study 1

Then Li receives the following e-mail from ABC Agency.xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

From: ABC AgencySent: Wednesday, August 25, 2010, 10:26 p.m.To: Yu Li (Small group: Hongmin Bai, Haiyan Chai, Yu Li, Lexin Zhou,

Xinchen Zhu)(Big Group: Hongmin Bai, Zili Bi, HaiyanChai, Ceng Chen, Chen Chen,

Libin Chen, Shaoquan Chen, Ting Chen, Yimin Chen, Ling Deng,Shanshan Dong, Wenyu Fan, Guoqin Guo,Ru Guo, Hao He, ShenliangHong, Jinhua Huang, Li Huang, Xia Huang, Huifen Jin, Fei Kang, Dan Li,Hairong Li, Hong Li, Ming Li, Yu Li, Guoying Liu, Hongyang Liu, QianqianLiu, Binxin Lu, Hua Lu, Min Qian, Zixuan Shao, Xianyong Tang, LeiWang,XinjianWang, FengWei, Xiao Xiao, Jing Xu, Na Yu, Yufan Yu, Yifan Zeng,JianQing Zhang, Jing Zhang, Peng Zhang, Xiaoling Zhang, Lexin Zhou, LinZhou, Ning Zhu, Xincheng Zhu)

Subject: hotel issues in City GDear Yu Li (Dear Customers),Our company is deeply concerned about your case. After investiga-

tion, we have learned that the local road is being repaired; thus, thebuses had to be rerouted during your stay in City G. We apologize forour inadequate communication with the hotel (Economic recovery:We have decided to refund 10% of your paid fee as compensation. Wewill send a check to you).

We promise we will improve our services and hope you willrepatronize ABC Agency. We will surely provide you with the bestservices.

Yours sincerely,Mingli GuoCustomer Service Manager of ABC Agency

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Appendix C. Scenarios for group service failure in study 2

Imagine you are Yu Li who experiences the following story.Yu Li and other persons organize a tour group to City B. They are

close friends and have known each other for many years. Theyalways plan activities together. This time they have an interest intraveling to City B (They are in the same city, but have not met eachother before. They organized together from the tourism website due tothe same interest in traveling to City B). They would like to book ahotel in advance and thus consult ABC Agency, which is famous in theircommunity of City W for providing this kind of service. They choose afour-star hotel with convenient transportation, well-equipped accom-modation, and free Wi-Fi upon ABC Agency's recommendation.




Arriving in City B, they find that theymust walk almost 20min fromthe hotel to the nearest bus stop. Since they have a tight schedule, theyhave to stay. However, the inconvenient transportation is troublesomefor them.

They complain to the ABC Agency after their return. The companypromises to follow up on their case.

References

Andreassen, T. W. (1999). What drives customer loyalty with complaint resolution?Journal of Service Research, 1, 324–332.

Argo, J. J., Dahl, D. W., & Manchanda, R. V. (2005). The influence of a mere social presencein a retail context. Journal of Consumer Research, 32, 207–212.

Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: Diagnosing fa-vorable and unfavorable incidents. Journal of Marketing, 54, 71–84.

Boshoff, C. (1997). An experimental study of service recovery options. InternationalJournal of Service Industry Management, 8, 110–130.

Chan, H., Wan, L. C., & Sin, L. Y. M. (2009). The contrasting effects of culture on consumertolerance: Interpersonal face and impersonal fate. Journal of Consumer Research, 36,292–304.

Chebat, J., & Slusarczyk, W. (2005). How emotionsmediate the effects of perceived justiceon loyalty in service recovery situations: An empirical study. Journal of BusinessResearch, 58, 664–673.

Grégoire, Y., Tripp, T. M., & Legoux, R. (2009). When customer love turns into lasting hate:The effects of relationship strength and time on customer revenge and avoidance.Journal of Marketing, 73, 18–32.

Griffitt, W., & Veitch, R. (1971). Hot and crowded: Influence of population density andtemperature on interpersonal affective behavior. Journal of Personality and SocialPsychology, 17, 92–98.

Hart, C. W. L., James, L. H., & Sasser, J. W. E. (1990). The profitable art of service recovery.Harvard Business Review, 68, 148–157.

Hess, R. L., Ganesan, J. S., & Klein, N. N. (2003). Service failure and recovery: The impact ofrelationship factors on customer satisfaction. Journal of the Academy of MarketingScience, 31, 127–145.

Hoffman, K. D., & Kelley, S. W. (2000). Perceived justice needs and recovery evaluation: Acontingency approach. European Journal of Marketing, 34, 418–432.

Hui, M. K., Zhao, X., Fan, X., & Au, K. (2004). When does the service process matter? A testof two competing theories. Journal of Consumer Research, 31, 465–475.

Jackson, J. M., & Latané, B. (1981). All alone in front of all those people: Stage fright as afunction of number and type of co-performers and audience. Journal of Personalityand Social Psychology, 40, 73–85.


Jing, X., & Xie, J. (2011). Group-buying: A newmechanism for selling through social inter-actions. Management Science, 57, 1354–1372.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk.Econometrica, 47, 263–292.

Kelley, S. W., Hoffman, K. D., & Davis, M.A. (1993). A typology of retail failures and recov-eries. Journal of Retailing, 69, 429–452.

Kwon, S., & Jang, S. (2012). Effects of compensation for service recovery: From the equal-ity theory perspective. International Journal of Hospitality Management, 31,1235–1243.

Langer, E. J., & Saegert, S. (1977). Crowding and cognitive control. Journal of Personalityand Social Psychology, 35, 175–182.

Latané, B. (1981). The psychology of social impact. American Psychologist, 36, 343–356.Latané, B., & Harkins, S. (1976). Cross-modality matches suggest anticipated stage fright a

multiplicative power function of audience size and status. Perception andPsychophysics, 20, 482–488.

Latané, B., & Wolf, S. (1981). The social impact of majorities and minorities. PsychologicalReview, 88, 438–453.

Magnini, V. P., & Karande, K. (2009). The influence of transaction history and thank youstatements in service recovery. International Journal of Hospitality Management, 28,540–546.

McCollough,M.A., Berry, L. L., & Yadav, M. S. (2000). An empirical investigation of custom-er satisfaction after service failure and recovery. Journal of Service Research, 3,121–137.

Michel, S. (2001). Analyzing service failures and recoveries: A process approach.International Journal of Service Industry Management, 12, 20–33.

Ringberg, T., Odekerken-Schröder, G., & Christensen, G. L. (2007). A cultural models ap-proach to service recovery. Journal of Marketing, 71, 194–214.

Smith, A. K., & Bolton, R. N. (1998). An experimental investigation of customer reactionsto service failure and recovery encounters: Paradox or peril? Journal of ServiceResearch, 1, 65–81.

Smith, A. K., Bolton, R. N., & Wagner, J. (1999). A model of customer satisfaction with ser-vice encounters involving failure and recovery. Journal of Marketing Research, 6,356–372.

Swanson, S. R., & Kelley, S. W. (2001). Service recovery attributions and word-of-mouthintensions. European Journal of Marketing, 35, 94–211.

Trope, Y., Liberman, N., &Wakslak, C. (2007). Construal levels and psychological distance:Effects on representation, prediction, evaluation, and behavior. Journal of ConsumerPsychology, 17, 83–95.

Zhou, Y., Huang, M., Tsang, A. S. L., & Zhou, N. (2013). Recovery strategy for group servicefailures: The interaction effects between recovery modes and recovery dimensions.European Journal of Marketing, 47, 1133–1156.

Zhou, Y., Tsang, A. S. L., Huang, M., & Zhou, N. (2014). Does delaying service-failure reso-lution ever make sense? Journal of Business Research, 67, 159–166.


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Group service recovery strategies effectiveness: The moderating effects of group size and relational distance