The importance of social comparison in perceived justice during the service recovery process

Aguilar-Rojas, Óscar; Fandos-Herrera, Carmina; Pérez-Rueda, Alfredo Article The importance of social comparison in perceived justice during the service recovery process European Journal of Management and Business Economics (EJM&BE) Provided in Cooperation with: European Academy of Management and Business Economics (AEDEM), Vigo (Pontevedra) Suggested Citation: Aguilar-Rojas, Óscar; Fandos-Herrera, Carmina; Pérez-Rueda, Alfredo (2024) : The importance of social comparison in perceived justice during the service recovery process, European Journal of Management and Business Economics (EJM&BE), ISSN 2444-8451, Emerald, Leeds, Vol. 33, Iss. 4, pp. 488-504, https://doi.org/10.1108/EJMBE-02-2023-0056 This Version is available at: https://hdl.handle.net/10419/325581 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ The importance of social comparison in perceived justice during the service recovery process  Oscar Aguilar-Rojas Business Management School, University of Costa Rica, San Jos e, Costa Rica Carmina Fandos-Herrera Department of Marketing Management and Marketing Research, University of Zaragoza, Zaragoza, Spain, and Alfredo P erez-Rueda Department of Business Management, University of Zaragoza, Zaragoza, Spain Abstract Purpose –This study aims to analyse how consumers’perceptions of justice in a service recovery scenario vary, not only due to the company’s actions but also due to the comparisons they make with the experiences of other consumers. Design/methodology/approach –Based on justice theory, social comparison theory and referent cognitions theory, this study describes an eight-scenario experiment with better or worse interactional, procedural and distributive justice (better/worse interactional justice given to other consumers) 32 (better/worse procedural justice given to other consumers) 32 (better/worse distributive justice given to other consumers). Findings –First, consumers’perceptions of interactional, procedural and distributive justice vary based on the comparisons they draw with other consumers’experiences. Second, the results confirmed that interactional justice has a moderating effect on procedural justice, whereas procedural justice does not significantly moderate distributive justice. Originality/value –First, based on justice theory, social comparison theory and referent cognitions theory, we focus on the influence of the treatment received by other consumers on the consumer’s perceived justice in the same service recovery situation. Second, it is proposed that the three justice dimensions follow a defined sequence through the service recovery phases. Third, to the best of the authors’knowledge, this study is the first to propose a multistage model in which some justice dimensions influence other justice dimensions. Keywords Service failure, Service recovery, Justice theory, Consumer comparison, Social comparison theory, Referent cognitions theory, Airline companies Paper type Research paper Introduction The fierce competition in the service sector and highrates of customer loss after service failures haveincreased the attention paid to service recovery as a means of retaining customers (La and EJMBE 33,4 488 ©  Oscar Aguilar-Rojas, Carmina Fandos-Herrera and Alfredo P erez-Rueda. Published in European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode This study was supported by the Spanish Ministry of Science, Innovation and Universities under Grant PID2019-105468RB-I00 and European Social Fund and the Government of Aragon (“METODO” Research Group S20_23R and LMP51_21). Declaration of interest statement: The authors certify that this article is the authors’original work. The work is submitted only to this journal and has not been previously published. The authors also warrant that the paper contains no harmful statements, does not infringe on the rights or privacy of others, or contain material that might cause harm or injury. The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2444-8494.htm Received 28 February 2023 Revised 21 October 2023 30 November 2023 Accepted 15 February 2024 European Journal of Management and Business Economics Vol. 33 No. 4, 2024 pp. 488-504 Emerald Publishing Limited e-ISSN: 2444-8494 p-ISSN: 2444-8451 DOI 10.1108/EJMBE-02-2023-0056 Choi, 2019;S anchez-Garc ıa and Curras-Perez, 2020). Service failure arises in situations where businesses do not meet their customers’expectations (Sim~ oes-Coelho et al.,2023). This will happen, sooner or later, often with very negative results (La and Choi, 2019). When a service failure occurs, the probability of losing the customer is high, and the reputation of the company may be seriously affected (Gr egoire et al.,2018). Specifically, 86% of consumers leave brands they were once loyal to after only two to three bad customer service experiences, 63% leave because of poor customer experience and 49% stated that, during the previous 12 months, they had left a company they had been loyal to for that reason (Emplifi, 2022). The cost of poor customer service ranges from $75 billion to $1.6 trillion per year (McCain, 2023). To combat this situation companies have developed service recovery strategies to restore customer satisfaction, mainly through process-related treatments (e.g. explanations) and monetary compensation (Ahmad et al.,2023). Previous studies have shown that, when customers are compensated for service failures by receiving service better than they expected, they usually rate their satisfaction with companies and their services higher than prior to the failure (Cheng et al., 2015). One of the most common service failure research perspectives is the evaluation of customers’responses to failures based on their perceptions of the justice they receive (La and Choi, 2019). Justice theory proposes that customers’satisfaction increases when they experience “fair”recovery (Gr egoire et al.,2018). However, some studies have suggested that customers can affect one another in a service recovery scenario (Albrecht et al., 2019), because they are social comparers (Ludwig et al.,2017). Social comparison research has aroused special interest in the social sciences since Sherif (1936) showed that two people facing the same situation develop a point of reference through a process of mutual social influence (Buunk and Gibbons, 2007). However, relatively little research has examined how consumers perceive the outcome of system recovery processes when they compare their experiences with those of other consumers (Bonifield and Cole, 2008;Chen et al.,2023). This study makes three contributions. Based on justice theory (Rawls, 1971), social comparison theory (Festinger, 1954) and referent cognitions theory (Folger, 1986), we examine the influence of the treatment received by other consumers on the consumer’s perceived justice in the same service recovery situation. Second, it is proposed that the three justice dimensions follow a defined sequence during the service recovery phases (Murphy et al., 2015). Third, to the best of the authors’knowledge, this study is the first to propose a multistage model in which some justice dimensions influence other justice dimensions. Theoretical background and hypotheses development Perceived justice Kelley and Davis (1994) defined service recovery as the process by which firms attempt to rectify a service delivery failure. Service recovery includes all the activities/responses that service providers perform/make to repair losses experienced by customers (Gr€ onroos, 1998). Service research has adopted justice theory as the dominant theoretical framework (Huang, 2011). Justice has been said to be related to evaluations, based on moral criteria, of how the individual is treated by others (persons and entities) (Furby, 1986). Tax et al. (1998) proposed that perceived justice is a complex, tri-dimensional concept (interactional, procedural and distributive justice). Interactional justice relates to how the consumer is treated during a complaints process and includes elements such as the courtesy and kindness exhibited by company staff, empathy perceived, efforts made to resolve and willingness to provide reasons for the failure, for example, by an airline when a flight is cancelled (Schoefer and Ennew, 2005). Procedural justice, as the term suggests, relates to the perceived fairness of the processes applied by the company to recover the failure. It includes aspects such as delays in the processing of the complaint, response time to the complaint and the company’s flexibility in adapting to the consumer’s needs (Blodgett et al., 1997). Distributive justice is the degree to Social comparison in perceived justice 489 which consumers feel they have been treated fairly, specifically, what economic compensation the company offers for the failure. Distributive justice may result in refunds, discounts or other forms of compensation (Maxham and Netemeyer, 2002). The previous literature has found that perceived justice has a critical influence on the development of consumers’evaluative judgements (Schoefer and Ennew, 2005), influences behavioural reactions (Colquitt et al., 2006), creates trust and evokes positive emotions (La and Choi, 2012) and satisfaction (S anchez-Garc ıa and Curras-Perez, 2020). Specifically, consumers’ satisfaction with recovery service is significantly affected by procedural and interactional justice (Mohd-Any et al., 2019). Mathew et al. (2020) showed that perceived justice had a significant moderating effect on the relationship between e-service recovery quality and e-service recovery satisfaction. In a novel approach we suggest that the three perceived justice dimensions unfold in a particular order. Our sequential model is consistent with suggestions made by other authors in different research fields, such as organisational management, who have proposed that interactional justice is a precursor of procedural and distributive justice (Cohen-Charash and Spector, 2001;Tran et al.,2021). In the present study, it is expected that individuals affected by a service failure will primarily attribute any associated (in)justice to the person in the company responsible for the service at that moment. In fact, previous literature has affirmed that interactional justice relates to how individuals treat and communicate with, each other in the place where the problem occurred (Bies and Moag, 1986). Thus, the recovery process starts with the consumer’s first contact with the company’s customer service department. This initial contact, which is directly connected to the interpersonal treatment people receive during recovery procedures, is encompassed within the interactional dimension. Second, social psychology research has gradually shifted its emphasis from focussing solely on the outcomes of reward allocation (distributive justice) to a focus on an earlier stage in the process, that is, the company’s flexibility in adapting to consumers’needs (Blodgett et al., 1997;Wood et al.,2020), which has been described as an important dimension of their perceptions of justice (Thibaut and Walker, 1975). This process, related to the procedure through which the complaint is handled, is likely to unfold after the consumer has filed the complaint and before the company has resolved it. Finally, the consumer focuses on compensation, that is, the distributive justice dimension. As previously noted, distributive justice relates to the consumer’s perception of justice in the outcome of the process, so it seems logical to place it at the end of the sequence. In addition, like many of the personal evaluations that humans make, perceived justice can be strongly influenced by the individual’s way of thinking, perceptions and personal experiences (LaFave, 2008). In this regard, humans assess the experiences of their peers to evaluate their own experiences. Regardless of whether consumers have had much prior experience of any particular event/incident, the experiences of their peers will help them understand what has happened. However, little research has delved into the influence of other consumers on the consumer’s experience of the same system failure (Albrecht et al., 2019). Social comparisons Previous studies have shown that the presence of other consumers affects the individual’s behaviours (Albrecht et al., 2019). For example, Viglia and Abrate (2014) found that consumers are more influenced by social comparisons, for instance, price information given to them by friends, than they are when the information source is anonymous; in the latter case they are likely to lower their reference price (to be closer to average past prices). Social comparison theory argues that individuals evaluate their opinions and abilities by comparing them with those of other, similar individuals (Festinger, 1954). In the justice context, Greenberg (1982) argued that people perceive injustice when they receive dissimilar treatment, procedures or economic benefits to those received by others. Thus, individuals use social comparisons to associate with others, learn from others, self-assess against others (Taylor and Lobel, 1989)and EJMBE 33,4 490 to make sense of their own outcomes (Moore, 2007). This process, as it helps to reduce uncertainty, is a fundamental aspect of human experience (Suls and Wheeler, 2000) and has been explored in service recovery research. Indeed, social comparisons are an inevitable part of social intercourse (Brown et al.,2007) because, when people interact with others, consciously or unconsciously they compare themselves with these other people (Wheeler and Miyake, 1992). Steinhoff and Palmatier (2016) confirmed that comparing oneself to someone “worse”produces positive feelings and comparing oneself with someone “better”produces negative feelings, for example, in the context of hotels and flying. Referent cognitions theory (Folger, 1986) recognises the role of comparisons in perceived justice and proposes that procedures that affect oneself and others, are taken into account. Comparisons are important for establishing justice perceptions because they allow consumers to evaluate whether they received what they deserved (Chen et al., 2023). Furthermore, in the consumer’s evaluation of whether a deal is fair, knowing what others obtained is often more important than the procedural justice (s)he himself/herself received (Bonifield and Cole, 2008). Consumers use this information to assess justice and satisfaction (Chen et al., 2023). Therefore, we propose the following hypotheses: H1. The consumer’s perception of the interactional justice received by other consumers inversely influences his/her perceptions of the interactional justice s(he) has received. H2. The consumer’s perception of the procedural justice received by other consumers inversely influences his/her perceptions of the procedural justice s(he) has received. H3. The consumer’s perception of the distributive justice received by other consumers inversely influences his/her perceptions of the distributive justice s(he) has received. Many service encounters occur on what is known as the organisational frontline. Unlike other frontline interactions (e.g. in the sales/purchase process, which may develop over many interactions), on the service failure recovery frontline employees play a critical role in the provision of quality service (Carlzon, 1987;Lindsey-Hall et al.,2023). The first few moments of the interaction are very critical and have a great impact on how the customer perceives the whole service (Lin et al., 2016). Previous studies have concluded that, during customer-company face-to-face interactions, the customer’s initial impressions influence subsequent interactions and can, ultimately, influence customer outcomes (Anwar, 2023). Thus, on the basis that justice perceptions are based on the consumer’s perceptions ofthegains and losses (s)he experiences in a relationship with a provider (Kwon and Jang, 2012) and that equity theory (Adams, 1965) proposes that his/her perceptions during a recovery process take into account the company’s previous efforts to recover the situation, it is proposed that the consumer’s perceptions of the justice (s)he receives may be formed by his/her perceptions of the justice (s)he received in previous justice dimensions. Therefore, the following hypotheses are proposed: H4. The consumer’s perceptions of the interactional justice received by other consumers moderates the relationship between his/her perceptions of the procedural justice given to those consumers and his/her perceptions of the procedural justice (s)he has received, such that: The consumer’s perceptions of the procedural justice received by other consumers will have a greater influence on his/her perceptions of the procedural justice s(he) has received when the interactional justice received by others is worse (H4a) than when it is better (H4b). H5. The consumer’s perceptions of the interactional justice received by other consumers moderates the relationship between his/her perceptions of the distributive justice given to those consumers and his/her perceptions of the distributive justice (s)he has received, such that: Social comparison in perceived justice 491 The consumer’s perception of the distributive justice received by other consumers will have a greater influence on his/her perceptions of the distributive justice s(he) has received when the interactional justice received by others is worse (H5a) than when it is better (H5b). Finally, companies overemphasise distributive justice (the customer received the promised result) whilst neglecting procedural justice (Michel et al., 2009). Thus, companies tend to assume that the most important aspect of service failure recovery is monetary compensation, a form of distributive justice. However, the majority of the reasons given by consumers for their low levels of satisfaction after a service failure relate to procedural justice, overly complicated toll-free numbers, user-unfriendly websites and outsourced customer care contact centres (NCRS, 2020). This leads us to suggest that consumers’perceptions of the procedural justice they receive may influence their subsequent justice perceptions. H6. The consumer’s perceptions of the procedural justice received by other consumers moderates the relationship between his/her perceptions of the distributive justice given to those consumers and his/her perceptions of the distributive justice (s)he has received, such that: The consumer’s perceptions of the distributive justice received by other consumers will have a greater influence on his/her perceptions of the distributive justice s(he) has received when the procedural justice received by others is worse (H6a) than when it is better (H6b). Figure 1 depicts the proposed conceptual model. Research methodology To guarantee the validity of the data and the representativeness of the sample, the specialised market research company Netquest was hired. The company, at the end of 2019, used a consumer panel to randomly assign the participants to the different scenarios. The participants were remunerated. The vast majority of the panellists had taken part in previous studies and their prior participation had been considered satisfactory by the company. Figure 1. The proposed conceptual model EJMBE 33,4 492 Pre-test study Following Harris et al. (2006), a pre-test was conducted to assess the realism of the experimental setting and scenarios. Some 51 respondents participated in the pre-test, 56% women, 44% men, from 18 to 62 years old. Following receipt of the experimental instructions, the participants were randomly assigned to one of the eight experimental conditions. Subsequently, the participants were thanked, debriefed and asked to answer a short survey. We measured the realism of the scenarios (see Appendix 2) through four items, with 7-point bipolar scales, adapted from Collie et al. (2002). An example item is: “I believe that situations like this happen in real life”( α 50.73***). The participants reported that they perceived the scenarios as being realistic (Mean 55.93, Standard Deviation 51.05). Main study The airline sector has been growing. In 2022, it gained 64% in turnover over the previous year and is forecast to grow by 28.3% in 2023 (Statista, 2023). The experiment examined a recovery process after a service failure, that is, a baggage loss incident. This scenario was selected because baggage loss is one of the main service failures in the sector (Mohd-Any et al., 2019). To ensure the subjects could identify with the proposed scenario, a condition of participation was that they must have taken at least one flight in the previous six months. To test the research hypotheses, Netquest recruited 259 Spain-based panellists. Table 1 shows the socio-demographic characteristics of the sample. The participants were first told that the questionnaire was an academic-focused opinion survey about service recovery, and they were then asked to answer questions about the research framework’s variables. First, the survey described a baggage loss incident. Thereafter, the participants were randomly assigned to a condition in a 2 (better/worse interactional justice given to other consumers) 32 (better/worse procedural justice given to other consumers) 32 (better/worse distributive justice given to other consumers) design. At least 30 participants were used for each condition. As Table 2 shows, the researchers were particularly interested in ensuring that the groups consisted of similar numbers. Variable N Gender Men 137 Female 122 Marital status Married/coupled 148 Single 105 Divorced/separated 6 Occupation Housewife 23 Unemployed 15 Employed 113 Student 106 Retired 2 Studies Primary 21 High School 58 College 180 Age ≥18, <22 59 ≥22, <30 63 ≥30, <49 66 ≤49 71 Source(s): Authors’elaboration Table 1. Sample demographic characteristics Social comparison in perceived justice 493 The experiment described the following situation: a passenger arrives by plane at an airport, but his/her check-in luggage did not appear on the carousel. After submitting his/her complaint, (s)he sees that another passenger on the same flight has had the same problem and is also making a complaint. At that point the participant is randomly assigned to one of the eight possible scenarios (interpersonal, procedural and distributive justice), outlined in Appendix 1. As the central proposition of social comparison theory (Festinger, 1954) is the “similarity hypothesis”, which argues that individuals tend to compare themselves with similar people in similar situations, the traveller/participant then had to compare himself/ herself with someone who was travelling on the same flight, has the same problem and is even staying in the same hotel. The participants were asked to rate, on a scale of 1–7, their perceptions of interpersonal, procedural and distributive justice associated with the way the airline resolved the failure. Finally, they were asked to provide socio-demographic information. Measurement The measurement scales for the questionnaire were adopted from previous literature (see Appendix 2). We measured interactional justice using four items on 7-point bipolar scales, adapted from Karatepe (2006), for example, “The hotel employee was courteous” ( α 50.89). Procedural justice was measured using four items on 7-point bipolar scales, based on DeWitt et al. (2008), for example, “The policies and procedures the firm had in place were adequate for addressing my concerns”( α 50.91). Distributive justice was measured using three items on 7-point bipolar scales, also adapted from DeWitt et al. (2008), for example, “The outcome I received was fair”( α 50.92). Convergent validity was verified as the factor loading of each indicator was found to be above 0.5 and significant at the 0.01 level (Steenkamp and Van Trijp, 1991), and the statistical values of the AVEs were greater than 0.5 (Fornell and Larcker, 1981). Similarly, composite reliability exceeded the minimum recommended value of 0.65 (Bagozzi and Yi, 1988). Finally, to determine discriminant validity, we compared the square roots of the AVEs (the values on the diagonal, in bold) with the inter-construct correlations (values below the diagonal); to ensure discriminant validity, the on-diagonal values should be higher (Fornell and Larcker, 1981). The results from these analyses were satisfactory, as shown in Table 3. Results To test the effects proposed in the hypotheses we conducted three 2 32 analyses of variance (ANOVA), using IBM SPSS Statistics v.26 software. The results showed that the interactional justice given to other consumers during the recovery process inversely influenced the participants’perceptions of interactional justice they received (F(1, 257) 56.59, p5< 0.05), Interpersonal Procedural Distributive N Worse Worse Worse 31 Worse Worse Better 32 Worse Better Worse 36 Worse Better Better 35 Better Worse Worse 32 Better Worse Better 32 Better Better Worse 31 Better Better Better 30 Source(s): Authors’elaboration Table 2. Sample distribution (by scenarios) EJMBE 33,4 494 supporting H1. More specifically, the results showed that consumers perceived higher levels of interactional justice if others had been treated worse (M Other’sWorseInteractionalJustice 54.36; M Other’sBetterInteractionalJustice 53.93). Similarly, the procedural justice given to other consumers inversely influenced the respondents’procedural justice perceptions (F(1, 257) 58.44, p5< 0.01), supporting H2. Again, the participants perceived higher levels of procedural justice if others had been treated worse (M Other’sWorseProceduralJustice 53.43; M Other’sBetterProceduralJustice 52.94). Finally, supporting H3, the distributive justice given to other consumers inversely influenced the participants’distributive justice perceptions (F(1, 257) 525.43, p5< 0.01). In line with the previous results, the participants perceived higher levels of distributive justice if others had been treated worse (M Other’sWorseDistributiveJustice 53.50; M Other’sDistributiveJustice 52.58). As Table 4 shows, we checked for the presence of heteroscedasticity. First, we performed Levene’s test; this tests the null hypothesis that the error variance of the dependent variable is equal between groups. The results were not significant for the interactional justice and procedural justice variables, so it was concluded that the variance of the groups was equal, and thus, an analysis of variance (ANOVA) could be performed. As for the distributive justice variable, although a statistically significant p-value appeared in the analysis of variance, Levene’s test showed that heteroscedasticity is present. To remedy this heteroscedasticity problem, Welch’s test was applied; this test is more robust in these cases (Norusis, 2011). The levels of statistical significance observed for distributive justice using Welch’s tests were less than 0.05, therefore, the means of all groups are equal, allowing an analysis of variance (ANOVA) to be performed. The overall interaction effects show that consumers’perceptions of procedural justice vary when they believe that other consumers have received better, or worse, interpersonal justice (confirming H4), (F(1, 255) 511.01, p5< 0.01). Contrary to our expectations, when other consumers received worse interactional justice, the participants’procedural justice perceptions increased, but not significantly, supporting H4a (M Other’sWorseInteractional Other’sWorseProceduralJustice 53.18; M Other’sWorseInteractional M Other’sBetterProceduralJustice 53.22; t(132) 50.169, p>0.10). On the other hand, supporting H4b, when other consumers received better interactional justice, the participants’procedural justice perceptions decreased (M Other’sBetterInteractionalOther’sWorseProceduralJustice 53.67; M Other’sBetterInteractional Other’sBetterBetterProceduralJustice 52.60; t(123) 54.48, p<0.01); see Figure 2. With respect to H5, it was found that the moderating effects of the interactional justice received by other consumers on distributive justice perceptions was not significant (F(1, 255) 51.33, p5> 0.10). However, the results indicated that when other consumers received better interactional Interactional justice Procedural justice Distributive justice Levene’s test 0.66 0.24 0.07 Welch’s test ––0.00 Source(s): Authors’elaboration CR AVE Interactional justice Procedural justice Distributive justice Interactional justice 0.908 0.713 0.869 Procedural justice 0.903 0.702 0.440 0.885 Distributive justice 0.925 0.804 0.262 0.475 0.931 Note(s): The diagonal elements (in italic) are the square roots of the AVEs (variance shared between the constructs and their measures). Off-diagonal elements are the inter-construct correlations Source(s): Authors’elaboration Table 4. Homoscedasticity and heteroscedasticity test Table 3. Composite reliability and convergent and discriminant validity Social comparison in perceived justice 495 Gerber, J.P., Wheeler, L. and Suls, J. 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