The power of sophistication: How service design cues help in service failures

By analyzing three experimental studies, this research tests how and when sophisticated service environment designs (compared to modest service designs) can minimize consumers’ negative emotions and increase repurchase intentions after a failure. Drawing on part-list cueing literature, this research proposes that when a service failure occurs in a sophisticated (vs. modest) environment, consumers will rely on the sophisticated style of design as cues for service quality. We argue that sophisticated (vs. modest) service designs work as strong cues for quality that restrict the retrieval of negative information by consumers and can minimize the negative impacts of service failure, reducing consumers’ negative emotions and increasing repurchase intentions. We further advance our theorizing by showing how choice failure consequences (i.e., the risk or consequence related to the service choice) moderate the effects via associative pathways of retrieval. The findings contribute to theory and practice by revealing how service designs can serve as cues to mitigate adverse consequences of service failure.

Introduction
Companies use service environment designs as cues to build positive sensory impressions in consumers in the hopes of improving customer experience and outcomes (Berry et al., 2002;Bitner, 1992;Chang, 2016;Dean, 2014;DiPietro and Campbell, 2014;Durna et al., 2015;Kotler, 1973;Sweeney et al., 2016;Walsh et al., 2011). Service providers using sophisticated designs are known for creating incredible customer experiences and building an emotional connection with consumers to improve loyalty. According to Forbes (2018), brands like Ritz-Carlton use service designs to signal consumers their sophistication and to assure their service quality cues match the brand's reputation. For Harvard Business Review (2016), managers of companies oriented towards sophistication need to use any business opportunity to deliver high-quality cues (e.g., a luxurious service design experience) to be knowledgeable enough to go beyond the standard. The extant literature has also highlighted the positive impact of service environment designs (e.g., ambient, design, and social factors) on consumer outcomes such as perceived quality, emotional response, and repurchase intentions (Bitner, 1990;Hooper et al., 2013;Kearney et al., 2013;Shostack, 1977;Sweeney at al., 2016;Westbrook and Oliver, 1991;Kumar and Kim, 2014;Robert and John, 1982).
Nevertheless, while the body of research suggests the important role played by service environment designs on consumer emotions and behavioral intentions (Pullman and Gross, 2004;Petzer et al., 2012;Sengupta et al., 2015), insights into whether service designs can influence consumers' responses after service failures remain unknown. Service failures occur when providers fail to meet consumers' expectations (Zeithaml et al., 2011), generating adverse effects on consumer behavior (e.g., Bonifield and Cole, 2007;Harrison-Walker, 2012;Reynolds and Harris, 2009). From a practical standpoint, service failures cost businesses around $62 billion per year due to the loss of disappointed clientele (Forbes, 2016). Thus, understanding how service designs can work as cues to influence consumers' responses to service failures is a key factor for marketing theory and practice.
In order to fill this gap, this research tests how and when sophisticated service environment designs (compared to modest service designs) can minimize consumers' negative emotions and increase repurchase intentions after a failure. Drawing on part-list cueing literature (e.g., Garcia-Marques and Hamilton, 1996;Lindsey and Krishnan, 2007), this research proposes that when a service failure occurs in a sophisticated (vs. modest) environment, consumers will rely on the sophisticated style of design as cues for service quality to decide whether to repurchase or not from the same service provider. We argue that sophisticated (vs. modest) service designs work as strong cues for quality that restrict the retrieval of negative information by consumers and can minimize the negative impacts of service failure, reducing consumers' negative emotions and increasing repurchase intentions.
That is because service environment designs generate positive expectations of service quality on consumers (Zeithaml et al., 2011) helping customers regulate their emotional response by reinterpreting the negative event positively (Balaji et al., 2017). We further advance our theorizing by showing how choice failure consequences (i.e., the risk or consequence related to the service choice) moderate the effects via associative pathways of retrieval (Garcia-Marques and Hamilton, 1996).
By doing so, this research makes three contributions to the literature. First, it advances the understanding of consumer reactions to service failures by showing how sophisticated (vs. modest) service environment designs help to shape consumers' repurchase intentions after a service failure. In doing so, this research goes beyond previous research in service systems (e.g., Santos-Vijande et al., 2013) to reveal the important role of service environment designs in the post-failure recovery. Second, it provides evidence for the mediating role of negative emotions, suggesting that sophisticated (vs. modest) service designs work as quality cues that restrict the retrieval of negative information by consumers and can minimize the negative impacts of service failure. In doing so, this research contributes to the more recent stream of research on service environment designs (Balaji et al., 2017;Choi, 2014, Patrício et al., 2018) aimed at uncovering the emotional mechanisms underlying consumer reactions to service failure. Third, it broadens the extant understanding of the boundary conditions that affect service failures by introducing the moderating role of choice failure consequences. By doing so, we contribute to the marketing literature on consumer's information retrieval (e.g., Alba and Chattopadhyay, 1985;Lindsey and Krishnan, 2007;Stocchi et al., 2016), uncovering retrieval processes that might explain under which conditions service design cues mitigate negative effects of service failure.

Service Environment Design Cues and Service Failure
Service environment designs refer to a combination of ambient (e.g., temperature, music, odor), design (e.g., architecture, equipment, furnishing), and social factors (e.g., staff, other customers) (Bitner, 1992). The ambient factor implies background conditions such as air quality (temperature, humidity, and circulation), noise, scent, and cleanliness. The design factor relates to the visual stimuli component in terms of functional cues that includes layout (space arrangement) and comfort and aesthetic cues that include architecture, décor, and furniture. The social factor is the human component of the environment, that is the audience (other customers in the service environment), and service personnel. Consumers' perceptions of social factors also include appearance, behavior, and contact with people in the environment (Baker et al., 1994;Dagger et al., 2013). Extant research has demonstrated the relevance of service designs in producing positive customer reactions such as emotions and behavioral intentions (e.g., Baker et al., 1994;Bitner, 1990Bitner, , 1992Ellen and Zhang, 2014;Hooper et al., 2013;Kearney et al., 2013;Kotler, 1973).
Consumers evaluate the service designs as "indicators in forming beliefs about service quality and other attributes of the service" (Bitner, 1992, p. 63). The part-list cueing literature (e.g., Garcia-Marques and Hamilton, 1996;Lindsey and Krishnan, 2007) suggests that the information describing a target (service design cues) is encoded and stored in memory in a representation identified with that target (i.e., this service provider has high or low quality).
Thus, consumers use service designs as cues of expected service quality (Reimer and Kuehn, 2005), impacting their behavioral intentions (Durna et al., 2015).
In the occurrence of failure, consumers need to deal with the negative service encounter to manage their emotions and reinterpret events positively (Gabbott et al. 2011;Balaji et al., 2017). This research draws from part-list cueing literature (e.g., Garcia-Marques and Hamilton, 1996;Lindsey and Krishnan, 2007) to argue that sophisticated service designs (compared to modest service designs) can signal stronger quality cues to consumers, minimizing the negative effects of service failure. This reaction is because the degree of fit between a retrieval cue (sophisticated design) and the stored memory (associations with high quality) traces as a whole as a clue to some aspect of memory content (e.g., associations between sophistication and better quality). This retrieval process favors expectancy-congruent behaviors (Garrido et al., 2012), which makes consumers overestimate frequency judgments that sophisticated designs and high quality are usually congruent (and much more frequent compared to a given episodic failure event). Thus, consumers will tend to repurchase more from sophisticated (vs. modest) service designs since it signals stronger quality cues (expectancy-congruent behaviors). More formally, we hypothesize that: H 1 : Sophisticated (vs. modest) service environment designs reduce the dampening effect that service failure has on repurchase intentions.

The Mediating Role of Negative Emotions
The importance of emotions on the human experience is crucial in that what we notice and remember, exerting a powerful influence on consumer evaluations (Dolan, 2002).
More recent emotion theories emphasize the adaptive value of emotions and the need for emotional regulation in certain circumstances (Gross, 1999;Gyurak et al., 2011). For instance, Kozub et al. (2014) indicate that emotions explain consumers' future behavioral intentions after a service failure. In addition, Varela-Neira et al. (2010) found that emotions play a mediating role in the relationship between cognitive evaluations (i.e., disconfirmation of expectations) and customer satisfaction.
Negative emotions underlie the effects of consumers' appraisals about service failure on post-purchase behaviors, from retaliatory behaviors to conciliatory behaviors (Bonifield and Cole, 2007). The intensity of their negative emotional responses depends on whether the failure leads to functional, monetary, or psychological losses (McColl-Kennedy and Sparks, can minimize the negative impacts of service failure, reducing consumers' negative emotions and increasing repurchase intentions. We propose that when a service failure occurs, sophisticated (vs. modest) service environment designs will reduce consumers' negative emotions because it helps in the reappraisal process after the failure. This consequence might happen because sophisticated environment designs (vs. modest) offer strong quality cues for consumers to "re-construe the service failure encounter with positive meaning, thereby increasing the likelihood to repurchase from the service provider" (Balaji et al., 2017, p. 975).
For instance, Pullman and Gross (2004) found that service design elements elicit positive emotional and behavioral responses from consumers. Also, Namkung and Jang (2010) suggested that high-quality cues are critical to evoke positive emotions and generate future favorable behaviors. Thus, we argue that sophisticated service designs stem high-quality cues for consumers, such that when a failure occurs, they will try to protect expectancy-congruent behaviors by undervaluing their negative emotional responses towards the provider, impacting their behavioral intentions. More formally, we hypothesize that: H2: Negative emotions mediate the effects of sophisticated (vs. modest) service environment designs on repurchase intentions.

Choice Failure Consequences and Associative Pathways of Retrieval
Service exchanges differ in complexity, and consumer responses to service failures may vary according to its consequences (Shocker et al., 1991;Swait and Adamowicz, 2001).
Research shows that consumers' coping strategies change depending on the consequence of the service failure (i.e., the risk or consequence related to the service choice - Sengupta et al., 2015). For instance, when services have high (vs. low) choice consequences (e.g., choosing a catering service for marriage, or a restaurant for a CEO meeting), consumers often feel more stressed (Botti et al., 2009;Kahn and Luce, 2003), generating strong emotional reactions (Kunreuther et al., 2002;Terres et al., 2013). Likewise, service failures with high (vs. low) choice consequences have an important effect on customer outcomes, such as the likelihood of engaging in negative word-of-mouth after the service failure (Weun et al., 2004).
In this research, we propose that choice failure consequences might be an important moderator of service designs (sophisticated vs. modest) effects on repurchase intentions. That is because service environment designs positively influence perceived quality cues (Hooper et al., 2013;Kearney et al., 2013), and may counter the effects of choice failure consequences.
We draw on the associative pathways model (Garcia-Marques and Hamilton, 1996;Garcia-Marques et al., 2002;Garrido et al., 2012) to show two different retrieval processes that underlie different choice failure consequences (high vs. low). We contend that failures with high choice consequences (e.g., a haircut for a wedding) might trigger a more dense retrieval process via negative emotions, whereas failures with low choice consequences might facilitate the retrieval for expectancy-congruent behaviors (i.e., sophisticated designs and high quality), directly improving consumers' repurchase intentions. We argue that in situations with high choice failure consequences (i.e., greater risk to the consumer), consumers elaborate the retrieval process in a more an exhaustive way (e.g., why did I choose this hairdresser for my wedding?) and a nonselective manner (e.g., do sophisticated hairdressers always produce high-quality haircuts?). Because expectancy-incongruent behaviors are more densely interconnected than are expectancy-congruent behaviors (Garcia-Marques and Hamilton, 1996;Garrido et al., 2012), we anticipate that under high choice failure consequences, there will be greater likelihood of consumers recalling incongruent behaviors (sophisticated service designs and failures), triggering a stronger retrieval process via negative emotions.
However, in situations where the choice failure consequences are low (i.e., lower risk to the consumer), we propose that sophisticated (vs. modest) service environment designs can alleviate the negative effects of service failure. We argue that under low choice failure consequences, consumers' retrieval process of service cues is heuristic (not exhaustive) and selective (i.e., based on expectancy-congruency behaviors). This process is heuristic because frequency estimates will be influenced by the ease of retrieval (i.e., based on expectancycongruent behaviors). Since expectancy-congruent behaviors are easier to be retrieved and estimated as more frequent than are incongruent behaviors (Garcia-Marques and Hamilton, 1996), we anticipate that under low choice failure consequences, there will be greater likelihood of consumers recalling congruent behaviors (sophisticated service designs have better quality and lower chances of failures), directly improving consumers' repurchase intentions. Thus, we hypothesize:

Overview of the Studies
The present research comprises three experimental studies to test our hypotheses.
Study 1 provides preliminary evidence of the sophisticated service environment designs (sophisticated vs. modest) influence on repurchase intentions after a service failure. Study 2 explores the mediating role of negative emotions on service environment design effects on repurchase intentions. Study 3 further refines our predictions by exploring how choice failure consequences moderate the influence of sophisticated service environment designs on repurchase intentions. The results, taken together, determine the effects of sophisticated service environment designs in increasing consumers' repurchase intentions and in mitigating consumers' negative reactions to service failures. The set of findings supports the service environment design effect that is consistent with our theoretical account and the moderating role played by choice failure consequences. Appendix A provides a summary of the studies.

Failure
Study 1 examines the effects of service environment designs on consumers' repurchase intentions when a service failure occurs. The objective of Study 1 is to provide a test of our prediction that sophisticated service environment designs will increase repurchase intentions compared to modest service environment designs in a service failure situation (H1). We test our prediction by asking consumers to evaluate a movie session failure considering the cinema with sophisticated service environment designs (e.g., upscale cinema) and with modest service environment designs (e.g., simple cinema) in terms of repurchase intentions.

Participants and procedure
Two hundred U.S. residents (58.4% men, mean age = 34.7, SD = 10.9) completed the study in Amazon Mechanical Turk. Participants completed the study individually and were unaware of its purpose. One of the main advantages of this online platform is that the demographic data on Amazon Mechanical Turk is representative of the U.S. population as traditional subject pools, with gender, race, age and education of samples all matching the population more closely than undergraduate college samples (Paolacci et al., 2010). In our studies using Mturk, we have used a filter on the online panel to get participants from the United States only. We also asked that the participants must be Americans in the studies' instructions, and they confirmed this request by accepting the consenting form (before starting the studies). Besides that, we checked the participants' country information (IP address and self-report). Thus, those who were non-Americans did not participate in the studies. In addition, to avoid nationality perception issues, we included questions, in the demographic information section in the study, regarding the participant's nationality ("country where you were born" and "country of residence"). We only considered participants that informed "USA" in these two questions. Therefore, all participants included in our analysis for studies using online panel samples are Americans according to these verifications (filters, informed consent form, IP address, and self-reported demographic information). Furthermore, to avoid potential issues, we analyzed all data by verifying open-ended questions while checking IPs and duplicate responses. As a cover story, participants received instructions concerning a survey about a service evaluation in a 10-minute session.
Participants were randomly assigned to one of the two experimental conditions that asked them to imagine themselves in a cinema theater to watch a debut movie. The sophisticated (vs. modest) service environment designs described the cinema theater as sophisticated, elegant, and stylish (vs. basic, modest, and humble). Afterward, participants filled three open-boxes by answering how they imagined the cinema theater (ambient factor), the decor (design factor), and the customer service of employees (social factor) (Bitner, 1992).
Examples of sophisticated environment design descriptions are: "The theater is spacious," "somewhat art deco," "it is a luxurious, relaxing environment," "very high-quality sound," "extremely comfortable seating." Examples of modest environment design descriptions are: "old, not many people, not exciting," "red and burgundy plastic chairs and sofas," "dingy red carpet," "the seats were old made of that tough plastic, and red cloth," "the theater itself was smaller than usual," "chairs squeak with the slightest movement." After participants described the cinema service environment, for the manipulation of the service failure, they were informed that while watching the movie, in the best scene, the projection stops presenting the movie once the screen goes dark. Participants did not receive information about the reason the service failure occurred. We use cinema as a service context in Study 1 because this is a common service consumed globally.

Measures
Repurchase intentions were measured in three items (α = .867), according to Magini et al. (2007) and Maxham III (2001). Participants evaluated repurchase intentions with a 7-point Likert scale (1 -do not agree at all; 7 -completely agree). The items evaluated were: "I would choose this service again in the future," "I will choose this service provider another time if I need," and "I'm likely to choose this service in the future." The manipulation check for the service environment verified participants evaluations across ambient (α = .907, 4 items), design (α = .956, 9 items), and social factors (α = .928, 7 items) (Baker et al., 2002;Bitner, 1990Bitner, , 1992Bojanic and Rosen, 1994;Fu and Parks, 2001;Madanoglu, 2006). Participants rated each item using a 7-point Likert scale (1 -do not agree at all; 7 -completely agree).

Discussion
Study 1 suggests that repurchase intentions for a service failure depend on the service environment: sophisticated vs. modest service environment designs. Whereas sophisticated service environment designs elicit higher post-failure repurchase intentions, modest service environment designs present lower levels of convincing consumers to repurchase again, which provides support for our prediction (H1). In Study 2, we extend these findings by also testing the mediating role of negative emotions on service environment design effects on repurchase intentions (H2).

Study 2: The Mediating Role of Negative Emotions
The objective of Study 2 is to test our prediction that negative emotions mediate the effects of service environment designs from service environments on repurchase intentions (H2). We test our hypothesis that consumers reduce negative emotions, as a result of a service failure, in a sophisticated than in a modest service environment design that will then enhance repurchase intentions. Study 2 extends Study 1 by providing evidence for service environment design effects using a party as a new service context and a student sample, increasing the generalizability of the findings.

Participants and Procedure
One hundred and one undergraduate students (51.5% men, mean age = 25.53, SD = 8.5) completed the study individually in a major University. According to Paolacci et al. (2010), the benefits of undergraduate samples, compared to online panels, is the reduction of risks of multiple responses, and non-response error. Besides, although undergraduate samples are less representative than online panels, they are a more controlled environment to conduct experiments (for a full comparison, please see Paolacci et al., 2010). As in Study 1, Study 2 is a between-subjects experimental design that examined service environment design effects in two levels (sophisticated vs. modest). Participants were randomly assigned to the experimental conditions and completed the study individually, being unaware of conditions.
The cover story stated that the study was about a service evaluation in a 15-minute session.
Participants were asked to evaluate their experience in relation to a party situation. In this study, we asked participants to describe the service environment related to the party. The party description presented information about the service environment design dimensions defined by Bitner (1992) for the ambient factor (i.e., room and noise), design factor (i.e., decor), and social factor (i.e., customer service of employees).
Specifically, we gave participants the following instructions in the sophisticated service environment design condition: "Imagine you decide to go to a party with your friends.
The place where the party will take place is sophisticated, comfortable, and very modern. We would like you to describe in detail the ambiance of this party. For example, what would the decoration of this place be? What would the waiters look like? Think about these elements and describe the location of this sophisticated party." Participants in the modest service environment design condition read a similar description, but with a small change regarding the service environment designs: "The place where the party will occur is simple, not very comfortable and a bit older." After describing the party service environment in an open-box, participants were informed that a service failure occurred during the party. The service failure included in this study was presented as the following: "Imagine you're in the middle of the party when the lighting goes off. The place gets dark, and no one knows what is going on. Someone from the organization informs that the party will be closed due to a problem in the electricity supply, which could not be foreseen."

Measures
As in Study 1, the dependent variable repurchase intentions was measured across three statements (α = .887): "I would choose this service again in the future," "I will choose this service another time if I need," and "I'm likely to choose this service in the future." Participants evaluated each statement using a 7-point Likert scale (1 -do not agree at all; 7 -completely agree).
Negative emotions were included in Study 2 as a mediator variable. Participants evaluated five statements (α = 0.618) regarding regret, a common negative emotion associated with service failure, over the party choice (Bonifield and Cole, 2007).
Participants rated the statements across a 7-point Likert scale (1 -do not agree at all; 7completely agree).

Discussion
Study 2 replicates the findings of the service environment design effects on repurchase intentions, as reported in Study 1. Study 2 demonstrates that consumers are more willing to repurchase again from a service provider after a failure if the service was performed in a service environment with sophisticated service environment designs, than with modest service environment designs. Study 2 also explains this relation by revealing the mediating role of negative emotions. We find that consumers are more likely to repurchase from a provider with sophisticated (vs. modest) service environment designs, because it helps consumers reduce their negative emotions caused by the failure, which, in turn, will increase repurchase intentions. In Study 3, we extend these findings by testing choice failure consequences as a moderation for service environment design effects.

Study 3: The Moderation of Choice Failure Consequences
The objective of Study 3 is to provide a test of our prediction that sophisticated (vs. modest) service environment designs have a positive effect on repurchase intentions by reducing negative emotions depending on the choice failure consequences (H3). Study 3 extends the previous studies by examining how choice failure consequences and service environment designs interact to influence consumers' repurchase intentions. We observed a nonstudent sample to enhance the validity of the findings. We tested our prediction by analyzing the influence of a failure during a restaurant dinner with high (vs. low) consequences for the consumer.

Participants and Procedure
One hundred fifty-three U.S. residents (56.9% male, M = 31.3, SD = 11.15 years old) took part in the study in Amazon Mechanical Turk. As per Study 1, all the procedures to the inclusion of participants followed strict guidelines for studies using online panel samples (filters, informed consent form, IP address, and self-reported demographic information). Also, to avoid potential issues, we analyzed all data by verifying the questions while checking IPs and duplicate responses. Study 3 examined the interaction effect of choice failure consequences and service environment designs on consumers' repurchase intentions mediated by negative emotions. Study 3 is a 2 (service environment designs: sophisticated vs. modest) x 2 (choice failure consequences: high vs. low) between-subjects experimental design.
In Study 3, we chose a restaurant context because it should be a familiar service context to consumers in general. Participants were randomly assigned to the experimental conditions and completed the study individually, being unaware of conditions. The cover story stated that the study was about a service evaluation in a 15-minutes session. Participants were first assigned to one of the two choice failure consequences manipulation (high vs. low).
Choice failure consequences were manipulated by asking participants to imagine themselves going out for dinner with their boss (high choice failure consequences) or alone (low choice failure consequences). In the high choice failure consequences condition, the scenario was as the following: "You are doing very well in your job. Then one day, your boss invites you to dinner and tells you to choose the restaurant on the Internet. You believe that your boss will promote you." In the low choice failure consequences condition, the participants were informed that "they want to eat something different and thus decided to look for restaurant options on the Internet." After reading the choice failure consequences manipulation, participants were assigned to the service environment design conditions (sophisticated vs. modest). The manipulation of service environment designs informed participants that to find a restaurant option, they have searched for more information on the Internet and found some online reviews presenting descriptions about service environment designs of the chosen restaurant.
In the sophisticated (vs. modest) service environment design condition, the online reviewers indicated that the restaurant was sophisticated and elegant (vs. basic and modest), had modern (vs. humble) décor and furnishing, was very quiet (vs. little noisy), the waiter was polite (vs. distracted) in explaining details about the dishes, and the staff uniforms were stylish (vs. basic). The online reviews, collectively, described the ambient factor (i.e., noise), design factor (i.e., décor and furnishing), and social factor (i.e., customer service of employees) that according to Bitner (1992) comprise the service environment designs. A 30 minutes delay manipulated the service failure on the dinner order, and the waiter did not apologize for the inconvenience.

Measures
Repurchase intentions were measured by the same three items (α = 0.955) used in previous studies. Participants evaluated the items using a 7-point Likert scale (1 -do not agree at all; 7 -completely agree). As in Study 2, negative emotions were rated in Study 3 as the mediation variable. Negative emotions were measured into the same five (α = 0.843) statements regarding regret over the choice of the restaurant as used in Study 2 (Bonifield and Cole, 2007). Participants rated the statements on a 7-point Likert scale (1do not agree at all; 7 -completely agree).
To check the service environment designs manipulation, we measured the same items adopted in the earlier studies: ambient (α = 0.951, 4 items), design (α = 0.983, 9 items), and social (α = 0.970, 7 items). We implemented a 7-point Likert scale (1 -do not agree at all; 7completely agree) to assess the service environment design items.
In Study 3, we included the general perception of choice failure consequences to check where the failure consequence is low, the service environment designs can directly influence consumers' decision to repurchase again from the service provider in the future.

General Discussion
Recently, service providers are raising their attention to failures and, so they are investing more in post-failure strategies (Balaji et al., 2017). We expand previous literature regarding the integrated service system (Santos-Vijande et al., 2013) and the importance of post-failure (Hocutt et al., 1997;Mattila and Wirtz, 2004;Smith, 1999) by demonstrating the importance of sophisticated (vs. modest) service environment designs in increasing repurchase intentions after service failures. This paper contributes to the literature in three main ways.
First, it provides insight into the service environment designs of service environment effects on repurchase intentions. The results go beyond the service environment designs and are an essential cue for service experience (Zeithaml et al., 2011). The findings show that when consumers face a service failure, they are likely to stronger intentions to repurchase again from a service environment with sophisticated cues of quality. The results highlight the importance of managing the service environment to increase positive behavioral intentions toward service providers when failures occur. The negative effect of service failures can be attenuated by the presence of a service environment with sophisticated designs. These findings advance research from Bhandari et al. (2007), who argued that consumers form a set of expectations about how they should be treated when a service failure occurs based on past experience. In the case of the present research, we reveal how the sophisticated service environment forms quality cues, driving positive expectations about the service recovery process.
Second, this paper explores the importance of service environment designs from the service environment in relation to the emotional consequences of service failure, a topic rarely investigated (except for Shocker et al., 1991;Swait and Adamowicz, 2001). The findings reveal that sophisticated (vs. modest) service environment designs, and high (vs. low) service failures consequences interact, increasing repurchase intentions mediated by negative emotions. In doing so, this research contributes to the more recent stream of research on service environment designs (Balaji et al., 2017;Choi and Choi, 2014) aimed at uncovering the emotional mechanisms underlying consumer reactions to service failure. Balaji et al. (2017) investigated the emotion regulation of customers through suppression and reappraisal of repurchase intentions using a correlational study (scenario-based survey). We contribute to these authors by showing in three experiments the role of service design cues in helping consumers cope with the failure. In particular, we advance Balaji et al. (2017) by showing that sophisticated (vs. modest) service designs work as strong cues for quality that restrict the retrieval of negative information by consumers and can minimize the negative impacts of service failure, reducing consumers' negative emotions and increasing repurchase intentions.
Moreover, we contribute to Choi and Choi's (2014) correlational study that suggests that the emotional responses of customers towards companies are crucial after service failure and recovery. We advance those findings showing how service designs underlie the changes in emotional responses from consumers to service failures. Since in sophisticated service designs, customers are more likely to have positive expectations for the recovery of "failed" encounters regulating their emotions through reappraisal, they rebuilt the service failure encounter with positive meaning (Bhandari et al., 2007).
Third, this research broadens the extant understanding of the boundary conditions that affect service failures by introducing a new service environment designs effect conceptualization, which depends on choice failure consequences. In the present study, we extend previous views on how consumers cope with service failures (e.g., Sengupta et al., 2015), uncovering the moderating role of choice failure consequences on service designs cueing effects via associative pathways (Garcia-Marques and Hamilton, 1996;Garcia-Marques et al., 2002;Garrido et al., 2012). In particular, we show two different retrieval processes that underlie different choice failure consequences: a more dense retrieval process via negative emotions (high choice consequences) or a facilitated retrieval process for expectancy-congruent behaviors that directly affect repurchase intentions (low choice consequences).

Managerial Implications
This research fills a gap in the literature regarding the service environment as a strategic element in consumers' response to a service failure, identifying important boundary conditions for managers (choice failure consequences). Managers should be attentive to focus on continuous improvements of their quality cues to mitigate adverse effects of service failures, considering the importance of service environment designs revealed in the present study. For managers of sophisticated designs, it is important that their environment designs signal high-quality cues that match the brand's reputation (Forbes, 2018). That is because consumers will look for expectancy-congruent behaviors to recover from a service failure. In our studies, we showed the effects of sophisticated service designs on fine dining and entertainment (cinema for adult consumers or a party for students). Service providers can try to work on the combination these factors of ambient (e.g., temperature, music, odor), design (e.g., architecture, equipment, furnishing), and social (e.g., staff, other customers) (Bitner, 1992) to ensure the retrieval process of quality cues follow congruency expectations from consumers (i.e., sophistication cues usually lead to better quality).
However, for providers of modest service designs, there are at least two insights from our research to improve their responses to service failures. First, since our results suggest that retrieval of quality cues drive positive service failure outcomes, modest service designs might improve service design effects by using explicit cues about quality (Luchs et al., 2010).
Second, managers of modest service designs might focus on offering services with low choice consequences (e.g., a regular, but high-quality restaurant), to facilitate the retrieval process for expectancy-congruent behaviors that directly affect repurchase intentions, instead of relying on a retrieval process via negative emotions (high choice consequences).
Finally, the findings also provide an important warning for sophisticated service providers, primarily those offering services with high choice consequences for consumers (e.g., wedding or fine dining). For example, if a customer makes reservations for an important dinner (with high choice consequences) in a restaurant with a sophisticated design and the food is disappointing or delivered late, consumers will engage in a dense retrieval process via negative emotions. Thus, it is important to have outstanding service recovery strategies that match the brand's sophistication reputation.

Limitations and Future Research
Besides the theoretical and managerial contributions, this research presents limitations that might stimulate future research. Although scenario-building experimental techniques are widely used, they cannot simulate important service environment design aspects such as odor or temperature that influence service experiences (Mattila and Wirtz, 2001;Morrison et al., 2011;Spangenberg et al., 2005). Thus, future studies could focus on real service environments to holistically capture the effects of service environment designs on post-failure outcomes. Future studies could also explore how the recovery effort effect decreases consumers' negative emotions and increases conciliatory behaviors depending on service environment design.
Besides, in our studies, we collected data from an online survey panel of U.S. residents (Studies 1 and 3) and a sample of undergraduate students (Study 2). Further research could use field data (e.g., data from fine dining restaurants) or run experimental field studies (e.g., conduct the study in a real movie theater), extending the validity of our findings to other samples.
Finally, sophisticated service environment designs can play a role depending on the compensation for service failures offered to consumers. Future studies could test the effects of diverse types of compensation, such as monetary, psychological, or product exchange, and types of failure such as monetary losses, lack of attention, and flawed products (Roschk and Gelbrich, 2014) on sophisticated service designs. Also, further research could explore other post-failure variables besides repurchase intentions, such as word-of-mouth and retaliation behavior, to extend our findings.


extfieldsofstudy: Physics Business

text:
Research on the pricing of the double-competition closed-loop supply chain with uncertain recycling quantity

In order to solve the uncertainty impact of recycled products on pricing decision-making and financial intervention policy in double competition closed-loop supply chain, a pricing decision-making model is built by using the game theory and MATLAB numerical simulation. The model analyses and verifies the impact of the uncertain quantity upon the competition intensity, sale and recycling prices, supply chain node companies’ profits and social welfare, recovery rate of the closed-loop supply chain from four dimensions. The research results show that the recycling and repurchase prices are increasing when the quantity of recycled products shows significant fluctuation. The profit of social welfare and sellers are increasing, but manufacturer’s profit is decreasing, which means the uncertainty on recovery quantity directly affects the manufacturers, who play a leading role in implementing remanufacturing.

Introduction
The construction of a sustainable green ecological circular economy meets the requirement of social progress, and the closed-loop supply chain is an important carrier of the sustainable development of a green ecological circular economy. The research on the closed-loop supply chain system has become a major subject for developing a green ecological circular economy, and the selection of fiscal intervention strategies and closed-loop supply chain pricing decisions under government regulation are the core issues of the research in this field. Some researches on the pricing decision-making of closed-loop supply chain had been made. For example, Xing Guangjun [1], Cheng Faxin [2], etc. studied the optimal pricing decisions of closed-loop supply chains by considering consumer's green preference. Their study shows that: there is a positive correlation between product pricing and consumer's green preference; under the centralized decision-making mode, comparing with the decentralized decision-making mode, the retail price of green products is far lower while the recovery rate of waste products is much higher. Gao Honghong [3] analyzed the impact of consumer's market change on pricing decisions in the context of the buyer's market. Their studies show that the stronger consumer's preference for second-hand goods could result in a better quality of waste products. but lower Closed-loop supply chain profit; Zhao Jing [4], based on consumers' different preferences for traditional retail channels and online direct sale channels as well as different channel operating costs, researched the retailers who sell new products and recycle obsolete products and the manufacturers who open up online direct sale channels. In addition, some  Huang[5] studied the closed-loop supply chain competition under the coexistence of three recycling channels; George [6] and others used a system dynamics method to study the impact of recycling competition on re-manufacturing; Jiuh-Biing Sheu [7] studied the cooperation relationship when there is competition in the reverse supply chain; Tolga Aydinliyim [8] studied the management of recycling competition. Regarding the competition in closed-loop supply chains, most studies have focused on recycling competition in reverse supply chains, but the studies on dual competition are rarely reported in related literature. Luis J [9]'s research shows that the uncertainty of recycling quantity is related to the quantity and quality of reverse supply chain products which are directly affected by consumers and recyclers. Li Xiang [10] studied the closed-loop supply chain consisting of distributors and re-manufacturers, which shows that recycling price can influence the quantity of waste products and the recycling quantity changes in a random manner. The researchers, who used game theory and optimization theory to obtain the optimal decision under the decentralized and centralized supply chain system, proved that the lower remanufacturing quantity and recycling price in the decentralized system further lead to the higher selling price. Wang Daoping [11] found that the higher the expectation of recovery quantity, the greater the reduction of the unit carbon emission. Existing studies on the uncertainty of the recovered quantity has revealed the root cause of the uncertainty of the recovered quantity and the impact of the uncertainty of the recovered quantity on the objective functions such as pricing decision and expected profit. However, above mentioned studies also have certain limitations. For example, on the one hand, the wide impact of recycling rate and social welfare are not involved. On the other hand, considering the changes in the business environment of the closed-loop supply chain, the research on the uncertainty of recycling volume in a complex environment needs to be further conducted. Based on existing studies, this paper takes the double competition closed-loop supply chain as the research object, explores the government financial intervention strategy and pricing decision-making mechanism by using the method of Game Theory and MATLAB numerical simulation in the case of uncertain recovery quantity and discusses the impact of the recovery quantity uncertainty on the double competition of the closed-loop supply chain.

Double-competition closed-loop supply chain model with uncertain recycling quantity
Closed-loop supply chain, in its operation process, presents the dual competition phenomenon, namely retailer and third-party recycler recycling competition, new product and remanufactured product sale competition. Both retailers and third-party recyclers have uncertainties about the quantity of recycled products in the recycling process. By setting up a disturbance of the recycled quantity, this paper studies the uncertainty of the recycled quantity and the change law of dual competition.

Symbol definition
The definition of the parameter symbols used in this research is shown in Table 1.  Recycler unit product recycling price( , Production cost of new products δ Government subsidies for waste products Among the above symbols, the decision variables are: government subsidy amount per unit product δ , wholesale price per unit product i w , retail price per unit product i p , repurchase price and recovery price per unit product b and j b . In the forward supply chain, manufacturers sell new products and remanufactured products to retailers at wholesale price 1 w and 2 w , respectively, and retailers sell new products and remanufactured products to consumers at retail price 1 p and 2 p , respectively. In the reverse supply chain, manufacturers repurchase waste products at recovery price b from retailers and third-party recyclers. Green products are produced from raw materials at unit cost m c , or useful components are extracted and recycled at unit cost r c and used to make green products. Due to their own interests, the two recyclers play a game of recycling waste products. The competition between recyclers, recyclers' recycling decisions, the choice of brand new products and remanufactured products in market sales and financial intervention strategies, as well as pricing decisions, will affect the interests of the supply chain node companies. The uncertainty of the quantity of recycled product will lead to fluctuations in recycling price and remanufacturing cost. The relationship of decision variables in a closed-loop supply chain is shown in Figure 1.

Model assumptions
In order to make the research more scientific and targeted, the following relevant assumptions are established for the specific situations of waste electronic product industry: Hypothesis 1: The information about the market among the members of the closed-loop supply chain is symmetrical and risk-neutral. In non-cooperative situations, manufacturers, retailers, and third-party recyclers are rationally pursuing their own maximum profits [12]. Hypothesis 2: There is a quality difference between new and remanufactured products. In other words, the market deals with the two types of products differently. The market demands for new and remanufactured products are related to the sale price and affected by the sale price of the other party. There is no functional difference between remanufactured products and new products. To some extent, they can replace each other, but consumers have different Willingness to Pay (WTP) towards new products and remanufactured products. Therefore, they are priced differently by both manufacturers and retailers. Retailers purchase new and remanufactured products at wholesale prices 1 w and 2 w from manufacturers, respectively, and sell them at retail prices 1 p and 2 p separately ( 1 The new product and remanufactured product are related to each other through the Bertrand Duopoly Model of price competition, from which the demand function between the new product and remanufactured product can be expressed as: a > represents the market size of new and remanufactured products, and the value range of θ is (0, 1), which represents the substitution coefficient between new products and remanufactured products. The demand function for new and remanufactured products expresses that when new product price fall or remanufactured product price increase, the demand for new products increases, and vice versa. Therefore, the quantity of sales can be expressed as a function of price behavior. Assumption 3: Assume that the unit production cost of the new product is m c , the production cost of the remanufactured product is r c and 0 r m c c ≤ ≤ , and that the production of a unit remanufactured product can save the production cost ∆ [13]. Hypothesis 4: All node companies in the closed-loop supply chain are willing to cooperate with each other as a whole, which means 0 Hypothesis 5: Build a recycling function according to the sales function, and then the retailer recycling function can be expressed as ( , ) ( ) β and the third-party recycler recycling function can be expressed as , where 0 k > represents the recycling market size and 0 1 < < β represents the consumer's sensitivity coefficient to the difference between the retailer's and the third-party recycler's recycling prices. Although the total recovery function seems to be a function of R b , due to competition, the total recovery function is a function of the recovery price of both parties, which is ( , ) Hypothesis 6: The quantity of waste products repurchased by the manufacturer is random  ( , ) q b ε , and affected by the repurchase price, and let  ( , ) The random disturbance ε describes the impact of the external environment (such as sale market conditions and relevant government policies) on the waste product recycling market normally. Assume that ε , is defined within the interval [A, B] with the mean value of 1 and the variance of 2 σ , and the distribution function and density function are ( ) F ε and ( ) f ε , respectively. Assumption 7: Assume that the recycled products are manufacturable, which means the uncertainty or difference in the quality of the recycled products is not considered. In reality, to optimize inventory, many companies manufacture the products based on placed orders, which means remanufacturing waste products after the demand is realized [14]. Hypothesis 8: In a closed-loop supply chain system, it is assumed that manufacturers, sellers, and third-party recyclers are risk-neutral and fully rational. In other words, decisions are made to maximize their expected profits. There is a Stackelberg relationship between upstream manufacturer, downstream seller and the third-party recycler. The manufacturer is the leader of the game, and the seller, the third-party recycler and the government are the followers [15]. Hypothesis 9: In the process of recycling by retailers and third-party recyclers, the unit cost of labor, storage and transportation required for each recycled product can be considered together with the repurchase price or recycling price [16]. Based on the above assumptions, the function of expected profit and social welfare expectation can be expressed as;

Calculation and analysis of the optimal decision solution
The inverse induction method is adopted to calculate the solution of the model. The closed-loop supply chain dominated by the manufacturer will determine the impact of the uncertainty of the recycling quantity on the decision of the closed-loop supply chain. Therefore, ε is regarded as an independent variable and the expected value of the optimal solution is a function of ε .

Stage 3 decision
Manufacturers first determine their own optimal strategies 1 2 w w 、 、b to maximize their own profits, and then sellers and the third parties determine their optimal strategies, respectively. For a given b , the expected profit of a third-party recycler is: ( ) ( into the model, Let The results show that the relationship between the optimal expected profit of the third party recycler and the repurchase price is a quadratic function, and the third-party recycler's optimal recycling price is linear with the manufacturer's repurchase price. Therefore, the manufacturer must set a repurchase price. Similarly, according to the retailer's profit expectations: , we can get:

Stage 2 decision
It is assumed that manufacturer's production capacity is fixed and the manufacturer can complete the production of new and remanufactured products on 1 2 Q Q + quantity; when the quantity of recycled waste products is larger than its maximum production quantity, namely  1 2 ( , ) q b Q Q ≥ + ε , the manufacturer does not need to use new raw materials to produce. All are remanufactured with waste products. In addition, the manufacturer can obtain residual value h from unused waste products. However, when the quantity of recycled waste products is less than its maximum production quantity, namely , part of the manufacturer's production is made from new raw materials and part of it is remanufactured with waste products, so the manufacturer's profit function is: 6( ) , the optimal solution can be calculated. Although it's analytical solution is difficult to calculate, it is easy to calculate it's numerical optimal solution, with which further analysis can be made through numerical simulation.

Stage 1 decision
For the government, the optimal amount of financial subsidy is also calculated by . It is also difficult to find its analytical solution, so further analysis will be made through numerical simulation.

Numerical sensitivity analysis
In this paper, Matlab numerical simulation is adopted to conduct numerical sensitivity analysis, of which the main procedures are: first, with a fixed competition coefficient θ and β , the change rule of the quantity coefficient of recycled product ε to the financial intervention strategy, pricing decision, expected profit, social welfare expectation and recovery rate of the supply chain node enterprises are obtained through numerical sensitivity analysis; Then, the change rules of financial intervention strategy, pricing decision, expected profit, social welfare expectation value and recovery rate of the closed-loop to the supply chain node enterprises under the uncertainty of the quantity of recovered products are obtained; Finally, according to a certain value of the calculation, find the influence rule of the variation coefficient of the recycled product ε on the recycling competition coefficient β , and obtain the influence rule of the uncertainty of the recycled product quantity on the recycling competition. In order to simplify the calculation, set double competition parameters 0.6 = θ , 0.6 = β , 3 h = , and discuss the change rule of recovery quantity ε in the range of [5,20], as shown in Table 2.

Changes in wholesale price and retail price
According to Figure 2 and figure 3, the wholesale price and retail price display a decreasing trend in the face of increasing volatility of product recycling market, and when the volatility of recycled quantity increases to a certain amount, the price relationship between the sale price of the original new product and that of the remanufactured product will be broken, and the sale price of new product will decrease rapidly, while the decrease of the sale price of remanufactured product will slow down, This is because when the number of recycled products increases, manufacturers will mainly use recycled products as the source materials, so the sale price will fluctuate accordingly. The economic theory analysis of the change law of the quantity of recycled product is [17] wwhen the amount of recycled product is very high, the economic way is to completely remanufacture without any waste; when the amount of recycled product is very low, the economic way is not to remanufacture but completely waste; partial remanufacturing is the least economic way and should be avoided. The quantity of recycled products should be large enough so as to enable the remanufacture to have certain scale and form industrialization, only by which enterprises can gain profit. Therefore, the closed-loop supply chain can be called sustainable supply chain only when the quantity of recycled product grows large enough to form a virtuous circular economy in which the sale price of new product decreases and remanufactured product maintains a relatively stable sale price and certain quantity and occupies a certain position in the entire social market. Enlightenment from management can be obtained from the above conclusions: Due to the different consumers' Willingness to Pay (WTP) and the influence of the change of recycled product quantity, the wholesale price and retail price of new products and remanufactured products fluctuate, so the sale quantity and profit of new products and remanufactured products in the closed-loop supply chain market become the basis for manufacturers to control the price; In addition, when the quality of remanufactured product reaches or approaches that of the new product, remanufactured product still needs coordination or necessary policy support to obtain market recognition.  benefits and reduce risks, it is necessary to encourage the recycling of waste products by improving the recycling price of waste product. The third-party recycler's recycling price is always lower than the retailer's recycling price, because the third-party recycler's profit mainly comes from the difference between the recycling price and the manufacturer's repurchase price. On the premise that the repurchase price is determined by the manufacturer, in order to obtain the maximum profit, the third-party recycler can only increase the recycling volume by reducing the recycling price. The increase of the recycling price increases manufacturer's production cost, which in turn leads to the increase of retail price and decrease of market demand. Consequently, manufacturers' profit is directly affected by the changes. The change law of the recycling price and the repurchase price reflects the practice of risk transfer in the closed-loop supply chain economic practice when retailers and third-party recyclers face the increase of recycling quantity, which leads to the adverse changes in the recycling price and the loss of profits. From the above conclusions, management enlightenment can be obtained: the third-party recycler is always at a disadvantage position in recycling activities. In order to prevent companies with professional recycling and dismantling technologies from losing the market, necessary coordination and subsidy measures should be in place to keep and boost the third-party recycler's vitality. Particularly, in the case of the continuous increase of the waste product quantity, the professional recycling and dismantling enterprises are needed. Therefore, maintaining the vitality of a closed-loop supply chain with professional recycling and dismantling companies, such as third-party recyclers, is one of the key issues for building a virtuous cycle of the closed-loop supply chain.  figure 8 show that encouraging the recycling of waste products will increase the quantity of recycled products and reduce the manufacturing cost. However, the continuous decrease of the manufacturer's profit and constant increase of the recycler's profit mean, that the recycler successfully transferred the risk to the manufacturer. Figure 9 shows that increasing the recycling price of waste products can encourage recycling activity in the market. The increase in the quantity of recycling leads to a decline in wholesale price and a reduction in sale price of sellers. On the other hand, for sellers, in order to improve service level and meet market demand, the reduction of sale price will inevitably lead to an increase of the quantity ordered. When the recycling quantity is uncertain, the change in the expected profit of the supply chain node enterprises reflects the risk transferred by both recyclers to the manufacturer. Therefore, the increase of the recycling quantity will result in the increment of recycler's, profit but the reduction of manufacturer's profit, namely manufacturer taking all risks. This phenomenon will reduce the manufacturer's enthusiasm to produce remanufactured products and hinder a virtuous circular economy. Therefore, it is necessary to study the control scheme of supply chain risk transfer, and encourage manufacturers who play a leading role in the closed-loop supply chain to remanufacture. Figure 10 shows that the recovery rate increases with the increase of the recovery quantity. When recovery quantity increases significantly, the competition between recyclers is no longer a significant influencing factor. This phenomenon also fully demonstrates that when the whole society's awareness of environmental protection increases, leading to the increase of recovery quantity, the recovery rate will see a remarkable growth, and thus, a virtuous circle of economic situation is formed. In addition, the change rule of recovery rate caused by the change of recovery quantity can also prove the economic theory demonstrated in Figure 2 and Figure 3 [18]. Figure 11 and Figure12 show the change law of the manufacturer's profit with the recycling parties' competition coefficients and recycling quantities. To be specific, as the recycling competition strengthens, manufacturer's profit increases; within a certain range of recycling quantity, manufacturer's profit increase, but out of the above range limits, manufacturer's profit will show a downward trend. In addition, conclusion can be drawn from the analysis and comparison of Figure 11 and Figure 12, when the quantity of recycled products is greater than the sale quantity, the manufacturer's profit is greater than the profit he/she earns when the quantity of recycled products is less than the sale quantity. The economic explanation of this phenomenon is that when the quantity of    10 recycled products is greater than the sale quantity, the recycled products can meet the manufacturer's production capacity because remanufacture is mainly conducted from recycled products, which leads to the increment of the manufacturer's profit. This phenomenon also proves that the circular economy will bring greater profit to manufacturers [19].

Summary
This paper studies the change law of closed-loop supply chain decision variables with uncertain recovery quantities under dual competition and builds a manufacturer-dominated dual-competition closed-loop supply chain financial intervention strategy and pricing decision model. The game theory method and Matlab numerical simulation are used to solve the problem. The analysis and comparison of the change laws of wholesale and retail price expectations, recycling and repurchase price expectations, closed-loop supply chain node enterprise profit and social welfare expectations, as well as recovery rate expectations, show that when the quantity of recycled products fluctuates greatly, remanufacturer's recycling price and repurchase price will also increase; in the closed-loop supply chain with uncertain recycling quantity, the recyclers' and the sellers' profits and social welfare are increasing, but the manufacturers' profit will see a declining trend, which means, in the closed-loop supply chain, the uncertainty of recycling quantity directly affects the enthusiasm of manufacturers who play a leading role in remanufacturing. In addition, when the recycling rate increases significantly, the recycling rate will no longer be the main factor affecting the recyclers' profit. Combining the above results with economic theoretical analysis, we can draw the following conclusions: When the recycling quantity of closed-loop supply chain is uncertain under dual competition, supply chain node companies would adjust the recycling price to transfer and control market risks. Therefore, only when the quantity of recycled products is sufficient enough to enable the remanufacturing companies to keep a certain business scale and form industrialization, the remanufacturing and recycling companies can really gain profit and, in order to improve social welfare, the government can promote the remanufacturing through financial subsidies. Only in this way, a virtuous economic cycle system can be built in a closed-loop supply chain which also becomes a continuous supply chain [20]. This paper will provide theoretical basis for government fiscal intervention policy formulation and closed-loop supply chain recycling, offer guidance for supply chain companies to avoid the risk resulted from uncertain recycling quantities and further improve the theory of supply chain management.