engaging customers with employees in service encounters

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Engaging customers with employees in service encounters Linking employee and customer service engagement behaviors through relational energy and interaction cohesion Haw-Yi Liang, Chih-Ying Chu and Jiun-Sheng Chris Lin Department of International Business, National Taiwan University, Taipei, Taiwan Abstract Purpose Keeping both employees and customers highly engaged has become a critical issue for service firms, especially for high-contact and highly customized services. Therefore, it is essential to engage employees and customers during service interactions for better service outcomes. However, past research on employee and customer engagement has primarily focused on brands and organizations. Little research has concentrated on service interactions as the objects of engagement. To fill this research gap, this study aims to clarify and define service engagement behaviors (SEBs), identify various employee and customer SEBs and develop a model to investigate the relationships between these behaviors. Design/methodology/approach A theoretical framework was developed based on social contagion theory and service-dominant (S-D) logic to explore the effects of employee SEBs on customer SEBs through customer perceptions of relational energy and interaction cohesion. Dyadic survey data collected from 293 customer- employee pairs in various high-contact and highly customized service industries were examined through structural equation modeling. Findings Results show that employee SEBs (service role involvement, customer orientation behavior and customer empowerment behavior) positively influence relational energy and interaction cohesion, which in turn affect customer SEBs (service exploration behavior and service coordination behavior). Originality/value This study represents pioneering research to conceptualize SEBs. Different from the extant literature on engagement, SEBs capture the proactive and collaborative engagement behaviors of employees and customers in service interactions. Various employee and customer SEBs were identified and an empirical model was proposed and tested to investigate the effect of employee SEBs on customer SEBs through relational energy and interaction cohesion. Keywords Customer service engagement behavior, Employee service engagement behavior, Interaction cohesion, Relational energy Paper type Research paper Introduction In the current service era where many customers no longer settle for impersonalized service experiences (Bock et al., 2016; Wilder et al., 2014), the success of services requires all interactants to engagingly take initiatives during service encounters (Chan et al., 2010; Guo et al., 2017). As service encounters involve both employees and customers as interactants (Bitner, 1990; Gallan et al., 2013; Lloyd and Luk, 2011), not only are the acts of employees critical in service delivery but also how customers act during the processes is significant for service outcomes (Dellande et al., 2004; Dong and Sivakumar, 2015; Sim et al., 2018). The phenomenon is especially crucial in high-contact and highly customized services, where identifying an individual customers explicit and implicit requirements and preferences and, subsequently, integrating the information into service delivery has become central for fulfilling customer needs (Homburg et al., 2009; Lim et al., 2019; Wilder et al., 2014). That is to say, the proactive and collaborative engagement of both employees and customers is crucial for the creation of such individualized service experiences, in which service provision and customersunique needs are matched (Auh et al., 2007; Bendapudi and Leone, 2003; Service engagement behaviors The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/1757-5818.htm Received 23 June 2018 Revised 31 May 2019 2 November 2019 Accepted 4 December 2019 Journal of Service Management © Emerald Publishing Limited 1757-5818 DOI 10.1108/JOSM-06-2018-0175

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Engaging customers withemployees in service encounters

Linking employee and customer serviceengagement behaviors through relational energy

and interaction cohesion

Haw-Yi Liang, Chih-Ying Chu and Jiun-Sheng Chris LinDepartment of International Business, National Taiwan University, Taipei, Taiwan

Abstract

Purpose – Keeping both employees and customers highly engaged has become a critical issue for servicefirms, especially for high-contact and highly customized services. Therefore, it is essential to engage employeesand customers during service interactions for better service outcomes. However, past research on employeeand customer engagement has primarily focused on brands and organizations. Little research has concentratedon service interactions as the objects of engagement. To fill this research gap, this study aims to clarify anddefine service engagement behaviors (SEBs), identify various employee and customer SEBs and develop amodel to investigate the relationships between these behaviors.Design/methodology/approach –A theoretical frameworkwas developed based on social contagion theoryand service-dominant (S-D) logic to explore the effects of employee SEBs on customer SEBs through customerperceptions of relational energy and interaction cohesion. Dyadic survey data collected from 293 customer-employee pairs in various high-contact and highly customized service industries were examined throughstructural equation modeling.Findings – Results show that employee SEBs (service role involvement, customer orientation behavior andcustomer empowerment behavior) positively influence relational energy and interaction cohesion, which inturn affect customer SEBs (service exploration behavior and service coordination behavior).Originality/value – This study represents pioneering research to conceptualize SEBs. Different from theextant literature on engagement, SEBs capture the proactive and collaborative engagement behaviors ofemployees and customers in service interactions. Various employee and customer SEBs were identified and anempiricalmodelwas proposed and tested to investigate the effect of employee SEBs on customer SEBs throughrelational energy and interaction cohesion.

Keywords Customer service engagement behavior, Employee service engagement behavior, Interaction

cohesion, Relational energy

Paper type Research paper

IntroductionIn the current service era where many customers no longer settle for impersonalized serviceexperiences (Bock et al., 2016; Wilder et al., 2014), the success of services requires allinteractants to engagingly take initiatives during service encounters (Chan et al., 2010; Guoet al., 2017). As service encounters involve both employees and customers as interactants(Bitner, 1990; Gallan et al., 2013; Lloyd and Luk, 2011), not only are the acts of employeescritical in service delivery but also how customers act during the processes is significant forservice outcomes (Dellande et al., 2004; Dong and Sivakumar, 2015; Sim et al., 2018). Thephenomenon is especially crucial in high-contact and highly customized services, whereidentifying an individual customer’s explicit and implicit requirements and preferences and,subsequently, integrating the information into service delivery has become central forfulfilling customer needs (Homburg et al., 2009; Lim et al., 2019; Wilder et al., 2014). That is tosay, the proactive and collaborative engagement of both employees and customers is crucialfor the creation of such individualized service experiences, in which service provisionand customers’ unique needs are matched (Auh et al., 2007; Bendapudi and Leone, 2003;

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The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/1757-5818.htm

Received 23 June 2018Revised 31 May 2019

2 November 2019Accepted 4 December 2019

Journal of Service Management© Emerald Publishing Limited

1757-5818DOI 10.1108/JOSM-06-2018-0175

Coelho and Henseler, 2012; Dong and Sivakumar, 2017; Gwinner et al., 2005; Johnston andKong, 2011; Vargo and Lusch, 2016;Wilder et al., 2014). Such customized services bring aboutabundant positive service outcomes, such as customer satisfaction, loyalty, delight, trust,relationship longevity and high perceived service quality (Coelho and Henseler, 2012; Dongand Sivakumar, 2017; Gwinner et al., 2005; Kumar and Pansari, 2016; Wilder et al., 2014).Therefore, it is important for service firms to keep both service employees and customershighly engaged during service interactions.

Engagement behavior represents one’s pattern of action with respect to a target object(PhamandAvnet, 2009; Schaufeli et al., 2002; vanDoorn et al., 2010). It is an important elementin an interpersonal interaction (Smith and Gallicano, 2015). During an interaction, when focalparticipants proactively contribute to the relational activities and engage in the interaction,more positive perceptions and interaction outcomes may result (Jang et al., 2004; Runhaaret al., 2013). Similarly, as service interactants take initiatives to shape service offerings andcoordinate the delivery processes, theymay jointly create services to better fit customer needsand establish more effective communication in achieving customization (Bernardes, 2010;Field et al., 2018; J€a€askel€ainen and Heikkil€a, 2019; Patel et al., 2019). In the meantime, serviceemployees play an integral role in customer interactions, and their acts consequently shapecustomer perceptions, which, in turn, lead to various behavioral reactions of customers(Bitner, 1990; Keh et al., 2013; Mills and Morris, 1986; Zhao et al., 2018). Moreover, Kumar andPansari (2016) have clearly proposed that firms should engage customers through employeeengagement. Therefore, it is essential for both researchers and service practitioners tounderstand and explore the service engagement behaviors (SEBs) of both employees andcustomers, and how they are connected during service encounters. However, this issue is yetto be clearly identified and investigated in past studies.

Despite the increasing interest in the literature on engagement, existing service researchprimarily focuses on brands and/or organizations as the engagement objects in enhancingfirm performance (e.g. Brodie et al., 2011; Gong, 2017; Kumar et al., 2010; Leckie et al., 2018;Vivek et al., 2012). Even though the interactive and experiential nature of service deliveryprocesses plays an integral role in creating customer value, and such processes could bejointly shaped through employee and customer behaviors (Neghina et al., 2017; Ng et al.,2019; Subramony et al., 2017; Vargo and Lusch, 2008), extant research has overlookedservice interactions as focal objects of engagement (Kumar and Pansari, 2016). While pastresearch on service management also attempts to address the issue of enhancing valuethrough employee and/or customer behaviors (e.g. Chan et al., 2010; Fisk et al., 2018; Yimet al., 2012), it has yet to capture the proactive and collaborative engagement of bothinteractants in service interactions, least yet the linking mechanism between employee andcustomer SEBs.

To fill these research gaps, this study examines SEBs based on both service interactants’proactive investment of effort in and collaborative contributions to the service interactions,which the extant literature has ignored. This research first defines SEB as the behavioralmanifestations of a service participant’s (i.e. employee and customer) proactive involvementdedicated to the service interaction (Cullen-Lester et al., 2016; Jaakkola and Alexander, 2014;van Doorn et al., 2010). Furthermore, this study explores how employee and customer SEBsare linked through customers’ positive perceptions resulting from the interactions withservice employees. Drawing on theoretical lenses of social contagion and service-dominant (S-D) logic, this paper proposes that employee SEBs influence customer SEBs throughcustomer-perceived relational energy and interaction cohesion.

In the following sections, this study first reviews the theoretical background and conceptsthat are central to employee and customer SEBs. Next, a conceptual framework andhypotheses are presented, along with the research methodology and data collection. Finally,the empirical results, implications and future research directions are discussed.

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Conceptual backgroundAs a service interaction encompasses both the service offering and the service process (Bradyand Cronin, 2001; Helkkula et al., 2018), the participants not only have to devote themselves tocrafting superior core service but also need to develop close collaboration to enhance theservice delivery procedure (H€ulsheger et al., 2015; Oertzen et al., 2018). During serviceencounters, engagement behaviors are essentially important because more positiveperceptions and interaction outcomes may follow as the focal participants (i.e. employeesand customers) jointly take charge of the service tasks and collaboratively engage in theservice processes as a team (Huetten et al., 2019; McColl-Kennedy et al., 2019; Mullins et al.,2015). In otherwords, once the service employees and customers engage in contributing to theservice interactions, more effective service dialog is likely to be achieved (Mustak et al., 2016;Sharma and Conduit, 2016), while services could be more personalized, better fit customerneeds and generate greater service value (Hollebeek et al., 2019; Torres et al., 2018).

However, the extant literature on engagement of employees and customers has primarilyfocused on brands and organizations as objects rather than service interactions (e.g. Brodieet al., 2011; Hollebeek et al., 2019; Kumar and Pansari, 2016; Kumar et al., 2019; Macey et al.,2009; Pansari and Kumar, 2017). Research pertaining to how service interactants proactivelycontribute to and collaboratively engage in service interactions also remains scarce.Specifically, past research on employee engagement has primarily emphasized employees’work-related psychological states (e.g. Barrick et al., 2015; Byrne et al., 2016; Salanova et al.,2005), neglecting the actual engagement behaviors they display in service encounters.Moreover, studies on customer engagement behaviors have also centered only on customeracts after transactions with the firms or brands, such as spreading positive word-of-mouthand exhibiting brand loyalty (Beckers et al., 2018; Gong, 2017; Jaakkola and Alexander, 2014;Leckie et al., 2018; Pansari and Kumar, 2017; van Doorn et al., 2010; Verleye et al., 2014). Littleresearch has been done to simultaneously examine the engagement behaviors of bothemployees and customers for enhancing the service interaction processes and offerings.

Despite the importance of engagement behaviors in the service processes, few studieshave examined and clarified the engagement behaviors displayed by both employees andcustomers in service encounters. The link between employee and customer SEBs is alsounderexplored. To bridge the research gap, the current research aims to define SEBs, developand empirically test a model that identifies various employee and customer SEBs andexamine the relationships between these behaviors.

Service engagement behavior (SEB)Engagement behavior refers to an individual’s pattern of action associated with a targetobject (Pham andAvnet, 2009). This study then defines SEB as the behavioral manifestationsof a service participant’s (i.e. employee and customer) proactive involvement dedicated to theservice interaction (Cullen-Lester et al., 2016; Jaakkola and Alexander, 2014; van Doorn et al.,2010). The SEBs of employees and customers are discussed as follows.

Employee SEBAs indicated by Fleck and Inceoglu (2010), engaged employees are likely to display threetypes of behavior that benefit their organizations: (1) investing effort, (2) making extracontributions and (3) stretching beyond typical activities. Investing effort implies thatengaged employees tend to exert a great deal of effort on their core tasks. As serviceemployees, they may devote themselves and infuse energy into the service roles (Kahn, 1990;Rich et al., 2010; Young et al., 2018). Making extra contributions refers to the willingness ofemployees to go the extra mile when accomplishing their jobs. In service interactions, suchemployees likely care more about customers’ needs and try to better serve customers (Anazaand Rutherford, 2012; Gazzoli et al., 2013). Stretching beyond typical activities means

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employees’ tendency to act as trustworthy partners toward customers. During servicedelivery, when an employee assumes the mantle of service partner rather than being limitedto the label of service provider, they aremore inclined to involve customer collaboration in theservice content (McColl-Kennedy et al., 2017; Sharma and Conduit, 2016). Thus, on the basis ofthe theoretical background provided by Fleck and Inceoglu (2010), this study proposes threedistinctive types of employee SEBs.

First, engaged service personnel may exert considerable effort on the core service tasks asthey tend to recognize their responsibility to serve customers (Crawford et al., 2010; Yagil andMedler-Liraz, 2013) and regard involvement in their work roles as an essential act towardenhancing service content (Bakker et al., 2012; Raub and Liao, 2012; Rich et al., 2010). Engagedemployees are alsomore energetic, enthusiastic and deeply engrossed in the service processes(Salanova et al., 2005; Sonnentag et al., 2019). They would naturally and genuinely interprettheir roles with passion because they enthusiastically engage themselves in the service tasks(Wilk andMoynihan, 2005). In other words, they are prone to investing their energy and fullyinhabiting their roles instead of simply performing their jobs (Kahn, 2010). Accordingly, theengaged service personnel are more likely to demonstrate service role involvement, whichrepresents their dedication to their service roles and their effort exerted on the core servicetasks (Kahn, 2010; Schaufeli and Bakker, 2004; Schneider et al., 2018).

Second, engaged service personnel may be more willing to contribute extra effort for theircustomers (Chan and Lam, 2011). The mindset of “going the extra mile to serve customers” isreflected in their customer-oriented acts (Rafaeli et al., 2008). In particular, engaged serviceemployees are likely to bemore alert to various customer needs (Homburg et al., 2009;Mengucet al., 2013; Young et al., 2009) and bemoremotivated to offer personalized services (Jung et al.,2017). To make customers feel that they are unique, the engaged employees tend to exertextra effort on acts such as accommodating customer requests and providing customizedservice suggestions (Eldor and Harpaz, 2016; Payne and Webber, 2006; Wieseke et al., 2009).In other words, the dedicated employees are likely to display customer orientation behavior,which refers to employee’s behavior of making extra effort toward satisfying customer needsin the service encounters (Rafaeli et al., 2008; Stock and Hoyer, 2005).

Third, engaged service personnel are more likely to broaden their behavioralcontributions beyond ordinary service activities by acting as customers’ supportiveservice partners to involve customers in the service processes (McColl-Kennedy et al., 2017;Sharma and Conduit, 2016) since they realize that superior service performance would not beachieved without the aid of customers (Xie et al., 2008; Yi et al., 2011). That is to say, in pursuitof excellent service delivery, these engaged personnel may perceive customers as proactiveco-creators rather than passive receivers of services (McColl-Kennedy et al., 2017; Payne et al.,2008). Therefore, they tend to provide avenues for customers to connect and collaborate withthem (Auh et al., 2007; Ramani and Kumar, 2008), encourage suggestions and ideas (Bakker,2010; Dean, 2007) and seek customer feedback and opinions (Auh et al., 2019). That is,engaged service employees are more likely to exhibit customer empowerment behavior,which represents an employee’s endeavors to actively stretch beyond regular serviceactivities by encouraging customer collaboration in the service processes (Ouschan et al.,2006; Ramani and Kumar, 2008).

With the notion that engaged frontline employees are prone to take on their roles, payparticular attention to customer needs and proactively engage customers during serviceencounters, this study proposes that employee SEBs consist of three vital behaviors: servicerole involvement, customer orientation behavior and customer empowerment behavior.

Customer SEBAs suggested by Sonnentag (2003), to achieve higher team performance, engaged individualsare more likely to search for learning opportunities, taking personal initiatives to coordinate

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interaction processes with the interacting counterparts. In high-contact and highlycustomized service interactions, where individualized services are jointly crafted (Auhet al., 2007; Moeller et al., 2013), customers tend to acknowledge their influence on servicedelivery and regard themselves as indispensable collaborators with service personnel (Donget al., 2015; Kelleher et al., 2019; Moeller et al., 2013; Oertzen et al., 2018). That is to say,customers consider themselves to be service collaborators with employees. Therefore, toachieve better service outcomes, engaged customers tend to explore and coordinate more inservice interactions. Following such a theoretical rationale, this study proposes two types ofcustomer SEBs.

First, with stronger tendency toward learning, engaged customers tend to be moreexplorative; they are more inclined to seek service-related information in service encounters,since they are more willing to learn through interpersonal interactions (Gong et al., 2012;McColl-Kennedy et al., 2017; Tang et al., 2014). Moreover, engaged individuals also tend tosearch for better solutions (Heidenreich and Handrich, 2015; van Doorn et al., 2010). In serviceencounters, engaged customers would learn more about various service options (Jaakkolaand Alexander, 2014; Lakshmanan and Krishnan, 2011), exploring various servicepossibilities and combinations (Cui and Wu, 2016). Consequently, engaged customers aremore likely to demonstrate service exploration behavior, indicating their devotion towardexploring service-related knowledge and delving into better service experiences (Hibbertet al., 2012; Hollebeek et al., 2019).

Second, engaged customers tend to be good coordinators. They may demonstrateproactivity by affirming their personal preferences and offering service-related information(Fisher et al., 2012; Raub and Liao, 2012), participating in integrative decision-making(Sweeney et al., 2015), investing great effort to achieve service mastery through mutualcommunication (Hollebeek et al., 2019) and dynamically adjusting their behaviors toaccommodate the personnel’s ongoing service activities to achieve better interactions (Fisher,2014). If required, engaged customers will voluntarily propose, discuss and negotiate serviceimprovement opportunities with employees to receive more personalized and satisfactoryservices (Bradley and Sparks, 2002; Gong et al., 2012). That is, the dedicated customers willexhibit service coordination behavior, which demonstrates their initiation of proactivecommunication as well as adjustments better orchestrating the service interactions (Cullen-Lester et al., 2016; Parker and Collins, 2010).

Overall, as engaged customers tend to further explore the service offerings andcollaboratively arrange service processes with service employees to generate morepersonalized service experiences; this research proposes that customer SEBs encompasstwo critical behaviors: service exploration behavior and service coordination behavior.

Linkage between employee and customer SEBsA rich body of the service literature has emphasized the influence of frontline employeebehaviors on customers via interactions (Bitner, 1990; Bove et al., 2009; Chebat and Kollias,2000; Groth et al., 2009; Kumar and Pansari, 2016; Lechner and Paul, 2019; Tsai and Huang,2002; Wieseke et al., 2012). Social contagion implies behavioral changes after interactingwith other individuals because of aroused feelings through the process of relating(Hirshleifer and Teoh, 2009; Latane, 2000; Owens et al., 2016; Paxton et al., 1999; Radel et al.,2010; Rapp et al., 2013; Van den Bulte and Wuyts, 2007). In particular, behaviors could bespread among interacting individuals and cause similar behaviors by affecting thecounterparts’ perceptions (Crandall, 1988; Hatfield et al., 1994; Hirshleifer and Teoh, 2009;Owens et al., 2016; Paxton et al., 1999; Radel et al., 2010). The more vigorous the behaviorsand more empathic the communication that people are exposed to, more likely the socialcontagion will occur (Burt, 1987; Contractor and Eisenberg, 1990; Rapp et al., 2013). Inservice encounters, employee SEBs effectively create enthusiastic, caring and

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individualized service interactions with customers; in such an atmosphere, customers aremore likely to be affected and influenced to demonstrate similar behaviors. Therefore, thisstudy adopts the theoretical view of social contagion to explain the influence of employeeSEBs on customer SEBs.

Based on S-D logic, customer engagement behaviors are suggested to be highly related totheir psychological states, which are activated by interactive experiences in service processes(Brodie et al., 2011; Hollebeek et al., 2019; Kumar and Pansari, 2016; Vargo and Lusch, 2004,2008). Moreover, the extant literature has emphasized that the antecedents of customers’proactive involvement in service encounters include intrapersonal- and interpersonal-levelpromoting factors (Auh et al., 2007; Bettencourt, 1997; Bitner et al., 1990; Liao and Chuang,2004; Owens et al., 2016; Zhao et al., 2018). Thus, combining social contagion theory and S-Dlogic, customer SEBswhich require an individual’s “proactive” input of effort, are proposed tobe triggered by infectious and inspiring perceptual factors at both intrapersonal andinterpersonal levels as a result of interactions with engaged service employees (Harmelinget al., 2017; Hollebeek et al., 2019; Moliner et al., 2018; Pansari and Kumar, 2017; van Doornet al., 2010).

At the intrapersonal level, past research has indicated that the perception of psychologicalresourcefulness generated from interactions is highly associated with individual engagement(Baker, 2019; Hobfoll and Shirom, 2001; Owens et al., 2016; Quinn et al., 2012; Saks, 2006).According to Owens et al. (2016), relational energy—depicted as the perception of vitality,vigor and enthusiasm resulting from interpersonal interactions—represents a positivepsychological state that is aroused by interpersonal contact. Such energy, spreadingcontagiously from a vigorous and dedicated interacting counterpart (Baker, 2019; Hatfieldet al., 1994; Owens et al., 2016; Wang et al., 2018), enriches one’s capacity to engage in theinteraction (McDaniel, 2011; Quinn et al., 2012). Thus, relational energy serves as a criticalconcept that links employee and customer SEBs.

At the interpersonal level, the extant literature has suggested that the perception ofcohesion derived from interactive experiences contributes to collaborative and contributivebehaviors within a social group (Den Hartog et al., 2007; Farmer et al., 2015; Mathieu et al.,2015; Zaccaro et al., 2001). Interaction cohesion—defined as the sense of being connectedwith, supported by, and mutually attentive to the one with the same goal (Coleman, 1988;Jonczyk et al., 2016; Nahapiet and Ghoshal, 1998; Post, 2015)—is likely to be perceivedthrough the interactant’s effort to work on the shared tasks (Salanova et al., 2005). Such asense of cohesion would enhance an individual’s desire to be associated and engaged (Miller,2015; Rosenbaum, 2008). In the service context, customer engagement behaviors refer tocustomers’ proactive actions to improve their service experiences and outcomes with serviceemployees, denoting the roles of customers as active service partners (Auh et al., 2007; Dongand Sivakumar, 2017; Lengnick-Hall et al., 2000; Lovelock and Wright, 2002; McKee et al.,2006; Mills and Morris, 1986). Given that engaged service employees build up enthusiasticinteractions and devote extra effort toward fulfilling customer needs, customers are morelikely to feel connected and share goals with them (Barrick et al., 1998; Mathieu et al., 2015;Rosenbaum, 2008). Consequently, customer SEBs are more likely to be triggered. That is tosay, interaction cohesion also acts as a crucial mechanism of the contagious flow fromemployee SEBs to customer SEBs. With these theoretical notions, this study proposes thatemployee SEBs influence customer SEBs through customer-perceived relational energy andinteraction cohesion.

HypothesesEmployee SEBs and relational energyRelational energy is highly related to personal behaviors and could be amplified andmanifested through social interaction processes (Baker, 2019; Cole et al., 2012; Morgeson and

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Hofmann, 1999; Owens et al., 2016). In other words, the perception of relational energy shouldbe a social experience rather than an individual occurrence (Quinn, 2007; Yang et al., 2019).Moreover, Owens et al. (2016) mentioned that people can be energized by interacting withothers. The positive interactions or exchanges with an energetic party have been proposed asthe sill upon which such energy is created (Cole et al., 2012; Dutton and Heaphy, 2003). Thesocial contagion literature has also indicated that the sense of energy can be transmittedthrough interpersonal interactions with energetic, enthusiastic and exciting counterparts(Hatfield et al., 1994; Owens et al., 2016). Therefore, employee SEBs, which display proactiveinvolvement dedicated to the service jobs and customers, should be treated as a critical sourceof relational energy to customers.

During service encounters, when employees immerse themselves in their service roles,they will be perceived as energetic people because they perform their jobs vigorously andenthusiastically, greet customers with smiles, maintain eye contact and even make routineprocesses fun and enjoyable (McDaniel, 2011; Menguc et al., 2013; Vallerand et al., 2007). Suchbehaviors bring a positive atmosphere to service interactions, and customers may feelenergized because of the ripple effect of arousal-based perceptions (Langford, 2010;Otterbring, 2017; S€oderlund and Sagfossen, 2017). In other words, as customers perceive theemployees’ dedication to their service roles, they will have a heightened level of relationalenergy. Therefore, the following hypothesis is proposed:

H1. Employee’s service role involvement is positively related to customer-perceivedrelational energy.

Customer orientation behavior is characterized by an employee’s devotion to a customer’sinterests and endeavors geared toward meeting the customer’s needs and solving his/herproblems by going beyond formal service requirements (Lin and Hsieh, 2011; Rafaeli et al.,2008; Stock and Hoyer, 2005). Such behavior instills a customer perception that the serviceemployee is caring and supportive (Beck et al., 2002; Labig et al., 2005), which makes theservice encounter meaningful. As past studies have indicated that relational energy can bestrengthened, recharged or created through meaningful and vigorous interactions, it islikely that customers feel a higher level of relational energy during service encounters withcustomer-oriented employees (Holland et al., 2017; Hoppe et al., 2017). Moreover, Bock et al.(2016) reported that frontline employees’ provision of customized service offerings cancheer up customers and generate a sense of energy during the service interactions.Therefore, this study proposes that customer orientation behavior enhances relationalenergy:

H2. Employee’s customer orientation behavior is positively related to customer-perceived relational energy.

Customer empowerment behavior represents service personnel’s effort to solicitcustomers’ opinions and encourage their collaboration in service delivery processes(Ouschan et al., 2006; Ramani and Kumar, 2008). As customers are exposed to opencommunication, in which they are invited or encouraged to voice their opinions and makeservice decisions together, the bonding with employees and their vigor toward theinteractions are strengthened (Bolton and Saxena-Iyer, 2009; Carmeli et al., 2009a; Mengucet al., 2017). This may then cause customers to feel more energetic during serviceencounters (Salanova et al., 2005; Ugwu et al., 2014; Yang et al., 2019). Therefore, it isexpected that service employees’ customer empowerment behavior leads to customer-perceived relational energy:

H3. Employee’s customer empowerment behavior is positively related to customer-perceived relational energy.

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Employee SEBs and interaction cohesionIn service delivery, when engaged employees express enthusiasm, make additional effort toprovide customized services and display eagerness for the participation of customers (Kumarand Pansari, 2016; Salanova et al., 2005), it is contributive to developing effective interactions,making customers feel supported and having someone to work together on problem solving(Barrick et al., 1998; Mathieu et al., 2015; Rosenbaum, 2008). Under such circumstances,customers would psychologically connect the fulfillment of their needs with serviceemployees, considering both sides as a collective team to achieve mutual goals. Hence,employee SEBs should be deemed as important factors bringing about customer perceptionsof interaction cohesion.

When employees are deeply involved in their roles, they are more likely to link theirpersonal success to task performance and consider their goal accomplishments moreseriously (Courtright et al., 2017; Morgeson et al., 2005). During service encounters,such employees are more likely to perform their service tasks with greater effort,efficiency, conscientiousness and empathy, thus reflecting a desire to keep organizationalservice promises and fulfill customer needs. As customers perceive the supportfrom service employees, they tend to treat them as partners working together towardthe mutual goals in the service interactions (Lakey et al., 2016; Rhoades et al., 2001).Therefore, it is proposed that employee’s service role involvement will increase interactioncohesion:

H4. Employee’s service role involvement is positively related to customer-perceivedinteraction cohesion.

Past research has indicated that employees with higher customer orientation are moreaccustomed to the effect their personalized behaviors might have on customers; they aremore flexible in service delivery and are more engaged in showing positive attitudes,behaviors and expertise to serve customers (Gazzoli et al., 2013; Nguyen et al., 2014).Therefore, customer-oriented frontline employees may create more enjoyable serviceinteractions by anticipating customer needs, providing customized suggestions andoffering adapted services rather than performing and following a scripted routine (Rafaeliet al., 2008; Schau et al., 2007). In the service encounters, when customers feel that they areunderstood, treated personally and pampered with care, they are likely to form positiveperceptions of interactions, consider the association with this employee to be satisfyingand have a sense of belonging (Gazzoli et al., 2013; Post, 2015). Therefore, this researchproposes that employee’s displayed customer orientation behavior will enhance relationalcohesion.

H5. Employee’s customer orientation behavior is positively related to customer-perceived interaction cohesion.

Past research has suggested that positive customer perceptions about service encounters arelikely to be achieved when frontline employees seek to empower customers by expressingopenness and encouraging them to participate in the service processes (Sharma andPatterson, 1999; Webster and Sundaram, 2009). Furthermore, previous studies have reportedthat once customers perceive that they are valued and influential to the service deliveryprocesses and are encouraged to join, a sense of inclusion and togetherness within the groupoccurs (Farmer et al., 2015; Martin and Bush, 2006). In other words, a positive perception ofcohesion results as service employees invite customers to collaborate with them. Therefore,the following hypothesis is proposed:

H6. Employee’s customer empowerment behavior is positively related to customer-perceived interaction cohesion.

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Relational energy and customer SEBsAccording to the extant literature, aroused relational energy in human interactions attracts asense of capability as well as motivation to improve individuals’ psychological states anddrive people to perform dedication behaviors in social interactions (Brodie and Hollebeek,2011; Hollebeek et al., 2019; Owens et al., 2016; Qin et al., 2018). The more energizedinteractions one experiences, themorewilling and volitional they are to invest their own effortand time to perform proactive behaviors (Cullen-Lester et al., 2016; Dutton andHeaphy, 2003).

As customers perceive the positive psychological state of relational energy resultingfrom service interactions, their exploratory mindsets are thereby enhanced (Fredrickson,1998; Zaman et al., 2010). Thus, such customers are more inclined to seek serviceinformation and pursue opportunities for better service solutions (Liu et al., 2011; Shalleyet al., 2004). That is, energized customers are motivated to allocate more resources, such astime and effort, to explore various service possibilities and search for better servicesolutions (Ashby et al., 2002; Cui and Wu, 2016; Heidenreich and Handrich, 2015; Zamanet al., 2010). Therefore, this paper proposes that relational energy will lead to customers’service exploration behavior:

H7. Customer-perceived relational energy is positively related to service explorationbehavior.

Besides exploring the possibility of better service solutions, energized customers are alsomore eager to play proactive roles as service coordinators (Cullen-Lester et al., 2016; Richet al., 2010). The extant literature indicated that when people are positively aroused andperceive relational energy, they are more likely to actively engage in thought-provokingcommunication, service mastery and behavioral adjustments according to the pace ofservice progress (Kark and Carmeli, 2009; Owens et al., 2016). Therefore, in serviceencounters, relational energy will activate customers to demonstrate coordinationbehaviors, such as initiating discussions about personal preferences (Baker, 2019; Brownand Leigh, 1996; Rich et al., 2010), attentively monitor and collaborate in the serviceprocesses (Grodal et al., 2015) and thoughtfully integrate mutual interests and adapt one’sacts to the ongoing service activities (Fan and Zietsma, 2017; Rico et al., 2008). Thus, thisresearch proposes that perceived relational energy will influence customers’ servicecoordination behavior:

H8. Customer-perceived relational energy is positively related to service coordinationbehavior.

Interaction cohesion and customer SEBsPeople who experience cohesion with others are believed to be more likely to workcollaboratively and proactively in the team (Farmer et al., 2015; Jonczyk et al., 2016; Malhotraand Lumineau, 2011; Martin and Good, 2015). In other words, individuals working in acohesive team will engage more deeply with the aim to obtain better outcomes (Fisheret al., 2012).

When people feel connected with each other, they are more motivated to pursue betterinformation exchange and knowledge creation (Gully et al., 2002; Lester et al., 2002; Stajkovicet al., 2009). For customers in service encounters, the sense of togetherness in achievingsuperior service outcomeswith service employees enables them to enact explorative practices(Spreitzer et al., 2005). They may make inquiries and seek opportunities to acquire specificservice-related knowledge for developing better service programs with the service provider(Carmeli et al., 2009b; Carmeli and Gittell, 2009; Edmondson, 2004). Since such cohesiveperception motivates customers to discover more out of the service content and to exploreinnovative service experiences, this research proposes that interaction cohesion is positively

Serviceengagementbehaviors

related to customers’ service exploration behaviors. Therefore, the following hypothesis isproposed:

H9. Customer-perceived interaction cohesion is positively related to service explorationbehavior.

Coordination refers to individuals within a group communicating intensively with the aimof understanding each other and finding activities conducive to reach their desired goals(Cullen-Lester et al., 2016; Lester et al., 2002). In the service interaction context, perceivedcohesiveness may propel customers to exhibit coordinative acts (Keyton, 1999; Martin andGood, 2015). Initially, the cohesive perception will motivate customers to bettercommunicate their own preferences and work cooperatively with service employees tomaster the service processes (Farmer et al., 2015; Mathieu et al., 2015). Furthermore, beingon the same page with the service personnel enables customers to heedfully cope withthem (Farmer et al., 2015; Fisher et al., 2012). As these customers consider themselves andthe service employees as a team, they will effectively adjust their own behaviors to jointlyperform better service tasks (Ahn and Rho, 2016; Kim and Choi, 2016). Since interactioncohesion drives customers to initiate proactive communication and behavioraladjustments that enhance service effectiveness, this study proposes the followinghypothesis:

H10. Customer-perceived interaction cohesion is positively related to service coordinationbehavior.

Control variablesTo further strengthen the robustness of the conceptual model and reduce possible spuriousrelationships resulting from unmeasured variables, this research incorporates relationshipduration (the length of time that the relationship between the interactants has existed) andcontact frequency (the number of interactions per unit of time between the interactingparticipants) as control variables, since these two relational factors have been suggested toaffect how customers behave in and contribute to service encounters (Bolton et al., 2004;Huang et al., 2018; Lin and Hsieh, 2011; Palmatier et al., 2006). Moreover, this study controlsfor customer knowledge (customers’ general understanding of the service), since differentknowledge levels may affect customers’ contributions to service delivery processes (Auhet al., 2007; Chang and Taylor, 2016; Dong et al., 2008; Santos and Spring, 2015). Additionally,customer-perceived employee deep acting (customer perceptions of employee’s modificationof actual feelings to match the required emotional display) is also controlled, on account of itspotential influences on customers’ sense of energy and belonging in service interactions(Groth et al., 2009; Lechner and Paul, 2019; Yoo and Arnold, 2016).

Figure 1 presents the hypotheses in the conceptual framework. The relationships amongthe constructs were empirically tested in the following sections.

MethodResearch frame and proceduresAn empirical study was conducted to test the conceptual model and hypothesizedrelationships. Dyadic data were collected from service employees and customers in high-contact and highly customized service industries, which involve more intensive interactionsand discussions to achieve customers’ service consumption goals (Bowen, 1990; Guo et al.,2017; Ng et al., 2007; Yee et al., 2008). Data gathered from service employees include servicerole involvement and customer empowerment behavior, while customer data includes

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perceived customer orientation behavior, relational energy, interaction cohesion, serviceexploration behavior, service coordination behavior, as well as customer knowledge,perceived employee deep acting, relationship duration, and contact frequency.

A total of 20 research assistants were recruited and grouped into ten teams, eachconsisting of two field observers. These teams observed service interactions and collecteddata from both service employees and customers (Pugh, 2001; Tsai and Huang, 2002). Theresearch assistants first chose a target customer and observed his/her service interactionwith a service employee. Only service interactions that lasted for at least 10 min were used inthe analysis to ensure that customer-employee interactions were not affected by timepressure (Lin and Lin, 2017). Employees and customers were not aware of the presence of theresearch assistants during the interactions, and each store was visited only once to ensurethat employees were not aware of the observations in advance (Lin and Lin, 2011). Uponexiting the store, the customer was approached by one of the assistants and was requested tofill out a questionnaire regarding various perceptions and behaviors. Simultaneously, theother assistant requested the employee’s cooperation after the service interaction in ratinghis/her displayed behaviors toward the specific customer. If the employee was busy withsubsequent customers and unable to finish the survey immediately after the serviceinteraction, the research assistant waited until he/she had time to finish the survey.Respondents (either the customers or employees) who declined or could not complete thesurvey in a reasonable time were excluded from this study’s sample (Lin and Lin, 2011).

A random sample of service firms from multiple high-contact and highly customizedservice industries (e.g. beauty care services, hair styling, fashion retailing, optical servicesand fitness training) [1] were selected for this research. First, five cities were chosen for datacollection [2]. Using commercial directories, 90 stores were randomly selected per city (a totalof 450 stores) (Stock and Bednarek, 2014). Each team, comprising two research assistants,visited each store during regular business hours (Finn and Kayand�e, 1999), randomlyselecting customers and time frames based on a sampling schedule, where various timeframes (peak/off-peak; morning/afternoon/evening and weekdays/weekends) were employedto increase randomness (Lin and Lin, 2017; Lin and Liang, 2011; Lin and Lin, 2011; Tsai, 2001;Tsai and Huang, 2002).

Customer ServiceEngagement Behaviors

Employee ServiceEngagement Behaviors

Customer Orientation

Behavior

Customer Empowerment

Behavior

Service Role Involvement

Relational Energy

Interaction Cohesion

Service Exploration

Behavior

Service Coordination

Behavior

H1

H4

H2

H5

H3

H6

H7

H9

H10

H8

Control VariablesRelationship Duration, Contact Frequency,

Customer Knowledge, Customer-perceived Employee Deep Acting

Figure 1.Conceptual framework

Serviceengagementbehaviors

This study yielded a response rate of 77.3 percent and 80.4 percent from employees andcustomers, respectively. The final sample consisted of 293 pairs of employees and customers.Of the 293 service employees, 71.7 percent were female and 68.9 percent were full-timeemployees. Of the 293 customers, 38.2 percent were male, the overall customer age range was18–65 years, and customer education level ranged from high school to graduate school.

This research also tested for non-response bias. The demographic information (genderand age) of the non-respondents (including those who did not completely finish thequestionnaires) was collected and compared with that of the final sample (Pugh, 2001). Aseries of chi-square and t-tests indicated no significant differences between respondents andnon-respondents, suggesting that non-response bias was minimal.

MeasuresMulti-item scales from previous research were adopted for this study. A questionnaire wasconstructed and pretested four times to ensure that the questions were understood asintended and to assess the feasibility of the survey approach. The four pretests wereconducted before the formal data collection, with 93 participants in total. The participantsresponded to the items, shared their understanding, explained their responses, and reportedany problems they encountered. The feedback from the pretest was then utilized to confirmwhether the meaning of the questions was fairly understood. Minor adjustments in wordingwere then made according to the feedback, and the items were finalized to be used in theresearch (Lin andHsieh, 2011). The finalized itemswere displayed in seven-point Likert scalesanchored from “strongly disagree” (1) to “strongly agree” (7).

This study measured service role involvement with three items derived from Langford(2010). While customer orientation behavior was operationalized through five items based onLin and Hsieh (2011), customer empowerment behavior measured with three items wasadapted from O’Cass and Ngo (2011) and Ramani and Kumar (2008). To measure customer-perceived relational energy, this paper used five items adapted from Owens et al. (2016).Three items of interaction cohesion were adapted from Mathieu et al. (2015). Moreover,service exploration behavior measured with three items was adapted from Kashdan et al.(2004), Niessen et al. (2012), and Stumpf et al. (1983). Regarding service coordination behavior,four items were adapted from Fisher et al. (2012).

For the control variables, relationship duration wasmeasured with a single item followingDagger et al. (2009): “Approximately how long have you been coming to this serviceemployee?” Answers were coded into years for analysis. Following Dagger et al. (2009), thesingle-item measure of contact frequency asked respondents, “Approximately howfrequently have you been coming to this service employee?” Response options includedthe number of contacts per week, month or year, allowing respondents to reply based on ageneral estimate over a period of time (Dagger et al., 2009). These were then standardized asthe number of contacts per year. As regards customer knowledge, two items were adoptedfrom Eisingerich and Bell (2008); while for customer-perceived employee deep acting, it wasmeasured with three items adopted from Groth et al. (2009). For the list of all items, please seethe Appendix.

ResultsTotal measurement model estimationThe theoretical model was tested using LISREL 9.2. A confirmatory factor analysis (CFA)(including the items listed above) was employed. Results suggest a good fit overall(χ25 509.92, df5 442, RMSEA5 0.024, SRMR5 0.04, NFI5 0.97, NNFI5 0.99, CFI5 0.99and IFI 5 0.99). Regarding reliability, Cronbach’s alpha, composite reliability (CR) andmaximum reliability were evaluated (Chin, 1998; Fornell and Larcker, 1981; Hair et al., 2010).As shown in Table I, all the Cronbach’s alpha, CR and maximum reliability were well above

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the cut-off value of 0.70, exhibiting satisfactory reliability. In addition, all factor loadings inthe CFA for the total measurement model were significant (with all t values at p < 0.01 level)(Anderson and Gerbing, 1988; Kumar et al., 1998), demonstrating convergent validity.Moreover, the average variance extracted (AVE) for each factor was all above 0.50, furthersupporting convergent validity (Fornell and Larcker, 1981).

Discriminant validity was then examined. As shown in Table II, the maximum sharedvariance (MSV) for each constructwas smaller than itsAVE,while the square root of theAVE

Construct Cronbach’sα CRMaximumreliability

Standardizedloading

Service role involvement 0.87 0.84 0.84 –SRI1 0.79SRI2 0.83SRI3 0.77Customer orientation behavior 0.90 0.87 0.88 –COB1 0.72COB2 0.77COB3 0.75COB4 0.79COB5 0.78Customer empowerment behavior 0.90 0.87 0.88 –CEM1 0.80CEM2 0.90CEM3 0.80Relational energy 0.90 0.88 0.88 –RE1 0.78RE2 0.75RE3 0.80RE4 0.80RE5 0.72Interaction cohesion 0.90 0.87 0.89 –IC1 0.79IC2 0.91IC3 0.81Service exploration behavior 0.86 0.83 0.84 –SEPB1 0.80SEPB2 0.85SEPB3 0.71Service coordination behavior 0.96 0.93 0.94 –COOR1 0.90COOR2 0.89COOR3 0.86COOR4 0.89Relationship duration – – – –Contact frequency – – – –Customer knowledge 0.95 0.91 0.91 –KNOW1 0.91KNOW2 0.91Customer-perceived employee deepacting

0.91 0.88 0.90 –

DAB1 0.76DAB2 0.85DAB3 0.91

Note(s): CR 5 composite reliability; χ2 5 509.92, d.f. 5 442, RMSEA 5 0.024, SRMR 5 0.04, NFI 5 0.97,NNFI 5 0.99, CFI 5 0.99, IFI 5 0.99

Table I.Reliability and

convergent validity ofthe

measurement model

Serviceengagementbehaviors

Mean

SD

MSV

AVE

12

34

56

78

910

11

1.Relationalenergya

5.13

1.18

0.28

0.60

0.77

2.Interactioncohesiona

5.28

1.12

0.53

0.70

0.40

0.84

3.Serviceexploration

behaviora

4.18

1.35

0.42

0.62

0.41

0.65

0.79

4.Servicecoordinationbehaviora

4.88

1.32

0.49

0.78

0.48

0.56

0.65

0.88

5.Serviceroleinvolvem

enta

5.42

1.07

0.12

0.63

0.27

0.27

0.12

0.17

0.80

6.Custom

erorientation

behaviora

4.74

1.40

0.49

0.58

0.53

0.58

0.56

0.70

0.12

0.76

7.Custom

erem

pow

ermentbehaviora

5.93

0.98

0.12

0.69

0.33

0.31

0.19

0.26

0.35

0.23

0.83

8.Relationship

duration

b0.07

0.34

––

0.10

0.16

0.23

0.18

0.02

0.13

0.03

–9.Contactfrequency

c0.57

2.78

––

0.13

0.15

0.18

0.16

0.03

0.16

0.07

0.39

–10.C

ustom

erknow

ledgea

5.56

0.96

0.53

0.83

0.33

0.73

0.52

0.58

0.30

0.56

0.28

0.12

0.12

0.91

11.C

ustom

er-perceived

employee

deepactinga

4.43

1.22

0.27

0.71

0.30

0.36

0.38

0.37

0.10

0.52

0.09

0.19

0.14

0.32

0.84

Note(s):AVE,averagevariancesextracted;M

SV,m

axim

um

shared

variance.Squarerootsof

AVEareindicated

ondiagonalin

italic.Noaveragevariancesextracted

andmaxim

um

shared

variance

wereapplicableto

theconstructsmeasuredwithsingle-item

scales.aItem

swereratedon

seven-pointscales;brelationship

duration

was

coded

asnumber

ofyears;ccontactfrequency

was

coded

asnumber

ofcontactsper

year

Table II.Correlations betweenconstructs

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for each construct was higher than its correlations with all other constructs (Fornell andLarcker, 1981; Hair et al., 2010), which supports discriminant validity. A χ2 test (with onedegree of freedom while constraining each path to 1.00 versus the same path unrestrained)provides evidence of discriminant validity (Anderson andGerbing, 1988).Moreover, all cross-construct correlations were significantly less than 1.00 (Bagozzi and Heatherton, 1994), testedvia the confidence interval for each pairwise correlation estimate (± 2 standard errors) notincluding the value of one, providing additional evidence of discriminant validity.Furthermore, the heterotrait-monotrait (HTMT) ratio of correlations was examined (Hairet al., 2017; Henseler et al., 2015; Voorhees et al., 2016). All inter-construct correlation ratioswere lower than 0.75, well below the threshold value of 0.85. In addition, none of theconfidence intervals of the HTMT statistics included the value 1.00, thus further supportingdiscriminant validity. Overall, these results demonstrate that the measures possessedadequate reliability and construct validity.

Tests for common method biasTo avoid common method bias, this research collected data from dyadic sources (Frey et al.,2013; Homburg and Stock, 2004; Podsakoff et al., 2003). Furthermore, Harman’s single factortest was employed to reconfirm the absence of common method bias. The first factorextracted explained only 35.06 percent of the variance, which was smaller than the 50 percentthreshold (Podsakoff et al., 2003). In addition, a CFA model where all items load on onecommon factor had poor fit ( χ2 5 3226.07, df 5 495, RMSEA 5 0.158, CFI 5 0.83 andNNFI5 0.82), and 18 items had loadings below 0.6. These results show that common methodvariance did not appear to be a problem (Drengner et al., 2018; Podsakoff et al., 2003; Walshet al., 2015).

Structural model resultsAfter confirming the total measurement model, the structural model was estimated. Theoverall fit statistics ( χ25 661.89, df5 458, RMSEA5 0.039, PCLOSE5 1.00, SRMR5 0.06,NFI 5 0.96, NNFI 5 0.99, CFI 5 0.99 and IFI 5 0.99) indicated satisfactory fit between thehypothesized model and the data. Estimated structural coefficients were then examined toevaluate individual hypotheses (see Table III).

As predicted, service role involvement (γ115 0.15, p<0.05), customer orientation behavior(γ12 5 0.46, p < 0.01) and customer empowerment behavior (γ13 5 0.17, p < 0.01) werepositively related to relational energy, providing support for H1, H2 and H3. Moreover,service role involvement (γ21 5 0.16, p < 0.01), customer orientation behavior (γ22 5 0.57,p < 0.01) and customer empowerment behavior (γ23 5 0.12, p < 0.05) were positivelyassociated with interaction cohesion, supporting H4, H5 and H6. Consistent with H7 and H8,relational energy had positive relationships with service exploration behavior (ß31 5 0.17,p < 0.01) and service coordination behavior (ß41 5 0.29, p < 0.01). Furthermore, interactioncohesion had positive influences on service exploration behavior (ß32 5 0.50, p < 0.01) andservice coordination behavior (ß42 5 0.25, p < 0.01), thereby confirming H9 and H10.

Testing rival modelsThis research followed Ramaswami and Singh’s (2003) procedure to test for mediation effectsby comparing the proposed model with rival models. The first rival model (Model 1: full-antecedent model) proposed that the three employee SEBs, relational energy and interactioncohesion all have direct effects on the two customer SEBs, while the second rival model(Model 2: non-mediation model) suggested that the employee SEBs directly influence thecustomer SEBs, completely eliminating the mediating effects of relational energy and

Serviceengagementbehaviors

interaction cohesion. The proposed model (Model 0) was compared with the rival models onthe following criteria based on the previous literature (Arnett et al., 2003; Browne and Cudeck,1989; J€oreskog and S€orbom, 1996; Morgan and Hunt, 1994): (1) overall fit of the model, asmeasured by the RMSEA and the CFI; (2) Akaike information criterion (AIC) and expectedcross-validation index (ECVI) and (3) percentage of the model’s significant structural paths(see Table IV).

First, the RMSEA of each rival model was larger than that of the proposed model (0.046,0.048 vs. 0.039), while the two rival models (1 and 2) also held smaller CFI values than Model0 (0.98, 0.98 vs. 0.99). These results indicated that the proposed model fit the data better thanthe rival models. Second, models 1 and 2 had greater AIC and ECVI values than the proposed

RelationshipCompletely standardized

Coefficient t-value

H1 Service role involvement → Relational energy 0.15** 2.36H2 Customer orientation behavior → Relational energy 0.46*** 5.87H3 Customer empowerment behavior → Relational energy 0.17*** 2.62H4 Service role involvement → Interaction cohesion 0.16*** 2.76H5 Customer orientation behavior → Interaction cohesion 0.57*** 7.23H6 Customer empowerment behavior → Interaction cohesion 0.12** 2.06H7 Relational energy → Service exploration behavior 0.17*** 2.66H8 Relational energy → Service coordination behavior 0.29*** 4.84H9 Interaction cohesion → Service exploration behavior 0.50*** 6.99H10 Interaction cohesion → Service coordination behavior 0.25*** 4.15

Control variablesRelationship duration → Service exploration behavior 0.12** 2.15Relationship duration → Service coordination behavior 0.07 1.32Contact frequency → Service exploration behavior 0.02 0.43Contact frequency → Service coordination behavior 0.03 0.58Customer knowledge → Service exploration behavior 0.14** 2.18Customer knowledge → Service coordination behavior 0.33*** 5.58Customer-perceived employee deep acting → Relational energy 0.04 0.52Customer-perceived employee deep acting → Interaction cohesion 0.05 0.81Model fitχ2 661.89df 458RMSEA 0.039PCLOSE 1.00SRMR 0.06CFI 0.99NFI 0.96NNFI 0.99IFI 0.99

Note(s): **p-value < 0.05; ***p-value < 0.01 (two-tailed)

Model specifications χ2 df CFI RMSEA AIC ECVI % of sig. path

Model 0 (PM) 651.25 458 0.99 0.039 867.89 2.97 100%Model 1 (FA) 758.76 458 0.98 0.046 947.96 3.25 60%Model 2 (NM) 802.25 462 0.98 0.048 964.30 3.30 33%

Note(s): PM 5 Proposed model; FA 5 Full-antecedent model; NM 5 Non-mediation model

Table III.Path estimates for theproposed model

Table IV.Comparisons of rivalmodels

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model (947.96, 964.30 vs. 867.89; 3.25, 3.30 vs. 2.97, respectively). Since lower AIC and ECVIvalues indicate a better fit (Browne and Cudeck, 1989; J€oreskog and S€orbom, 1996), the resultswere in favor of the proposed model. Lastly, in the proposed model (Model 0), all the tenstructural paths (100%) were significantly supported, while only six structural pathsremained significant (60%) in the full-antecedent model (Model 1), and two out of the sixstructural paths remained significant (33%) in the non-mediation model (Model 2). Overall,these results supported the proposed model over the rival models, showing that relationalenergy and interaction cohesion played significant mediating roles in the model.

DiscussionSEBs are critical in the high-contact and highly customized services as such behaviorscapture the proactive investment of effort and collaborative contributions of serviceinteractants (Cullen-Lester et al., 2016; Jaakkola and Alexander, 2014; van Doorn et al., 2010).As both employees and customers display SEBs in service interactions, intensive discussionsand information exchanges occur (Fliess et al., 2014; Mustak et al., 2016; Sharma and Conduit,2016). Under such circumstances, more personalized service experiences and individuallyfitted service outcomes are more likely to be achieved (Field et al., 2018; Patel et al., 2019),which, in turn, leads to customer delight, perceived quality, satisfaction and relationshiplongevity (Dong and Sivakumar, 2017; Gwinner et al., 2005; Kumar and Pansari, 2016; Wilderet al., 2014). However, the issue of SEB is yet to be explored. Thus, this study aims to defineSEB, identify various employee and customer SEBs and investigate how employee SEBsaffect customer SEBs through relational energy and interaction cohesion. The researchfindings also provide several contributions and implications to the engagement behavior andservices marketing literature.

First, this study represents pioneering research to conceptualize SEB. Different from theextant literature on engagement, which has mainly focused on brands and organizations asobjects (Brodie et al., 2011; Hollebeek et al., 2019; Kumar and Pansari, 2016; Kumar et al., 2019;Macey et al., 2009; Pansari and Kumar, 2017), this study extends to the realm of serviceinteraction as the target object of engagement behaviors.

Second, this research is also among the earliest to identify and validate variousengagement behaviors that service employees display during service encounters. Unlikeprevious studies, which focused on employee engagement as a psychological state ofimmersion and involvement toward the firms (Kumar and Pansari, 2016; Macey et al., 2009;Rich et al., 2010; Salanova et al., 2005), the current study sheds light on employees’ actualengagement behaviors toward service delivery and customers, as specified in service roleinvolvement, customer orientation behavior and customer empowerment behavior.

Third, this paper contributes to the extant literature by investigating different forms ofcustomer SEBs. Contrary to prior research on customer engagement behaviors associatedwith firms or brands after transactions (Gong, 2017; Jaakkola and Alexander, 2014; Leckieet al., 2018; van Doorn et al., 2010; Verleye et al., 2014), the customer SEBs in this researchfocused on and highlighted the on-site proactive acts that engaged customers display toacquire more service information and explore more service possibilities for achieving betterservice experiences (i.e. service exploration behavior), as well as to articulate personalpreferences, join integrative decision-making and adjust personal behaviors to betterorchestrate the service interactions (i.e. service coordination behavior).

Finally, this research provides empirical evidence regarding the manner in whichemployee SEBs influence customer SEBs. In keeping with social contagion theory and S-Dlogic, the results obtained in this study demonstrate engaged employees’ acts boostingcustomers’ similar engagement behaviors through the mediation of relational energy andinteraction cohesion. Such research findings not only fulfill the research gap of theunidentified linking mechanism between employee and customer engagement (Kumar and

Serviceengagementbehaviors

Pansari, 2016) but also reveal and highlight the activated customer psychological statesduring the spread of SEBs as opposed to the traditional ripple effects of emotional contagion(e.g. Barger and Grandey, 2006; Hennig-Thurau et al., 2006; Howard and Gengler, 2001; Pugh,2001). Overall, this research clarifies SEB, identifies various employee and customer SEBsand verifies the linking mechanism between them, thus making valuable contributions to theengagement behavior and services marketing literature.

Managerial implicationsThe findings of this study illustrate that employee SEBs are a vital trigger of customer SEBs.Such employee behaviors enhance customers’ perceptions of relational energy andinteraction cohesion, which are critical factors in activating customer SEBs. Therefore, tobenefit from customers’ engagement behaviors in service encounters, it is imperative tomanage and encourage frontline employees’ engagement behaviors, including service roleinvolvement, customer orientation behavior and customer empowerment behavior. Thisresearch provides strategic implications for service practitioners to better manage employeeSEBs for eliciting customer SEBs through relational energy and interaction cohesion.

First, service managers must ensure that employees are capable of genuinely engagingin their service roles. They should recruit employees who are competent and passionateabout human interactions and serving customers. Service employees should also beprovided with role instructions and be trained to master detailed service tasks (Chi andGrandey, 2016; Grandey et al., 2005; Hennig-Thurau et al., 2006). Besides managerialemphasis on basic display rules, service firms should further offer incentives and establisha supportive working climate to cheer employees up and motivate them to perform theirservice tasks better. As customers perceive the wholehearted service from employees, thefeelings of enthusiasm and caring will be aroused (Stanworth et al., 2015). Such positivefeelings will provide customers with more relational energy and a sense of interactioncohesion.

Second, service firms should seek ways to enhance the exhibition of service employees’customer orientation behaviors. Service companies could develop a system that records anarchive of customer needs, such as marketing intelligence system, and constantly updatefrontline personnel with such customer knowledge. Moreover, employees can be trained toexplore individual customer needs with the assistance of instruction sessions onconversational and observational skills that help them better understand the customers.Additionally, in highly customized service industries, it is important to listen to customersand display genuineness to provide tailored services. Most importantly, frontlineemployees should be authorized and provided with resources to adapt service offeringsaccording to individualized customer needs. As employees are encouraged and eager tosatisfy each customer’s need, the customer will feel that he/she is unique, valued andsupported, which in turn can enhance his/her energetic feelings and perceptions ofinteraction cohesion.

Third, service managers should ensure that contact personnel are willing and able toempower customers in service interactions. The personnel should be trained in social skillsthat encourage customers to express themselves and guide them to concretize their needs,such as initiating small talks, establishing rapport and naturally guiding conversation toservice-related topics (Gremler and Gwinner, 2008; Macintosh, 2009; Ouschan et al., 2006).Moreover, to motivate service employees to work collaboratively with their customers,service managers should seriously consider customers’ opinions collected and reflected byfrontline employees and revise the service design accordingly. As employees empowercustomers to actively join the service processes, it strengthens customers’ bonding with themand makes customers feel more energetic. Meanwhile, customers will feel more connectedwith service employees and have the same goal to fulfill their needs.

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The research findings also confirm that relational energy and interaction cohesionenhance customer SEBs. Under this notion, service organizations should create moreopportunities for the contagion of energy from employees to customers and the sense ofcollaboration between employees and customers through service interactions. For example,service processes should allow for more intimate and individualized employee-customerinteractions, which are conducive to the delivery of service enthusiasm from employees tocustomers. Furthermore, service firms should try to enhance the degree of customerinvolvement in the decision-making processes. In service interactions, employees shouldinvite customers to express their thoughts, and enthusiastically discuss with them to figureout the best service solutions for customers’ personal needs.While being invited to the servicedecision-making, customers will strongly feel the sense of cohesion with the serviceemployees.With such effort, service organizations can further promote customer perceptionsof relational energy and interaction cohesion, leading to positive customer SEBs.

As customers engage in service exploration and coordination behaviors, there will be ahigher possibility to achieve more tailor-made services. Particularly in the highly customizedservice conditions, the proactivity of customers is critical in shaping the service provision,which could truly be effective. Therefore, the importance of customer SEBs should beespecially highlighted to service employees. Moreover, when customers demonstrate SEBs,employees should be able to respond properly and be capable of maintaining the momentumof customers’ proactivity. Training sessions regarding interaction and communicationtechniques in response to proactive customer behaviors are thus recommended to be added,so that service employees can be better equipped with the knowledge and skills to achievesuperior service outcomes with their engaged customers.

Limitations and future researchThis research contains a number of limitations, which provide avenues for further research.First, this study adopts a cross-sectional approach to explore the SEBs displayed by bothemployees and customers in service interactions. Further research with longitudinal designswould be valuable for understanding whether employee SEBs, relational energy, interactioncohesion and customer SEBs persist on a long-term basis.

Second, this study focuses solely on the influence of employee SEBs on customer SEBs.Future research can further examine the antecedents of employee SEBs, such as leadership,service climate, socialization approaches and/or other organizational factors, as well as theconsequences of customer SEBs, such as perceived service quality, satisfaction and serviceinnovation.

Third, this research mainly focuses on high-contact and highly customized services.However, as the context of services can possibly influence how employees and customersinteract, future studies should further consider service context, such as search-based,experience-based and credence-based services. Fourth, this research investigates the effectsof employee SEBs on customers’ perceptions and SEBs; on the other hand, customer SEBsmay possibly further influence employee behaviors. Therefore, investigating the impact ofcustomer SEBs on employees may result in interesting and fruitful findings.

Fifth, although customer SEBs can bring positive effects in high-contact and highlycustomized services, in rare cases, customer SEBs may result in unexpected outcomes foremployees. Future research can examine such unique scenarios through exploratory studiesto enrich further understanding of the SEB issue.

Finally, human attitudes and behaviorsmay varywidely across cultures (Chan et al., 2010;Mattila, 1999; Patterson et al., 2006). For example, high power distance might obstruct therelationships or social bonds built among service employees and customers, since their rolesmight be perceived to have unequal status (Chan et al., 2010; Patterson and Smith, 2001).Therefore, the degree of engagement might vary between these two parties due to cultural

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factors. Future studies can examine the impact of cultural norms on employee and customerSEBs within the context of service encounters.

Notes

1. Professional services (e.g. legal, financial, medical and healthcare services) were excluded, sincemostof these services require higher level of customer privacy, where employee-customer interactionscould not be observed in public.

2. The five cities were Taipei, Taoyuan, Taichung, Tainan and Kaohsiung, the major metropolitancities in Taiwan. These cities were chosen because the studied service context is more salient in suchhighly populated urban cities (e.g. Brady and Cronin, 2001; Daniels, 2004; Lin and Lin, 2011).

References

Ahn, J. and Rho, T. (2016), “Influence of customer–firm relationships on customer participation in theservice industry”, Service Business, Vol. 10 No. 1, pp. 113-133.

Anaza, N.A. and Rutherford, B. (2012), “How organizational and employee-customer identification, andcustomer orientation affect job engagement”, Journal of Service Management, Vol. 23 No. 5,pp. 616-639.

Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review andrecommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-423.

Arnett, D.B., German, S.D. and Hunt, S.D. (2003), “The identity salience model of relationshipmarketing success: the case of nonprofit marketing”, Journal of Marketing, Vol. 67 No. 2,pp. 89-105.

Ashby, F.G., Valentin, V.V. and Turken, A. (2002), “The effects of positive affect and arousal onworking memory and executive attention”, in Moore, S.C. and Oaksford, M. (Eds), EmotionalCognition: From Brain to Behaviour, John Benjamins, Amsterdam, pp. 245-287.

Auh, S., Bell, S.J., McLeod, C.S. and Shih, E. (2007), “Co-production and customer loyalty in financialservices”, Journal of Retailing, Vol. 83 No. 3, pp. 359-370.

Auh, S., Menguc, B., Imer, P. and Uslu, A. (2019), “Frontline employee feedback-seeking behavior: howis it formed and when does it matter?”, Journal of Service Research, Vol. 22 No. 1, pp. 44-59.

Bagozzi, R.P. and Heatherton, T.F. (1994), “A general approach to representing multifacetedpersonality constructs: application to state self-esteem”, Structural Equation Modeling: AMultidisciplinary Journal, Vol. 1 No. 1, pp. 35-67.

Baker, W.E. (2019), “Emotional energy, relational energy, and organizational energy: toward amultilevel model”, Annual Review of Organizational Psychology and Organizational Behavior,Vol. 6, pp. 373-395.

Bakker, A.B. (2010), “Engagement and “job crafting”: engaged employees create their own great placeto work”, in Albrecht, S.L. (Ed.), Handbook of Employee Engagement: Perspectives, Issues,Research and Practice, Edward Elgar, Northampton, MA, pp. 229-244.

Bakker, A.B., Demerouti, E. and Lieke, L.T.B. (2012), “Work engagement, performance, and activelearning: the role of conscientiousness”, Journal of Vocational Behavior, Vol. 80 No. 2,pp. 555-564.

Barger, P.B. and Grandey, A.A. (2006), “Service with a smile and encounter satisfaction: emotionalcontagion and appraisal mechanisms”, Academy of Management Journal, Vol. 49 No. 6,pp. 1229-1238.

Barrick, M.R., Stewart, G.L., Neubert, M.J. and Mount, M.K. (1998), “Relating member ability andpersonality to work-team processes and team effectiveness”, Journal of Applied Psychology,Vol. 83 No. 3, pp. 377-391.

Barrick, M.R., Thurgood, G.R., Smith, T.A. and Courtright, S.H. (2015), “Collective organizationalengagement: linking motivational antecedents, strategic implementation, and firmperformance”, Academy of Management Journal, Vol. 58 No. 1, pp. 111-135.

JOSM

Beck, R.S., Daughtridge, R. and Sloane, P.D. (2002), “Physician-patient communication in the primary careoffice: a systematic review”, Journal of theAmericanBoard of Family Practice, Vol. 15No. 1, pp. 25-38.

Beckers, S.F.M., van Doorn, J. and Verhoef, P.C. (2018), “Good, better, engaged? The effect of company-initiated customer engagement behavior on shareholder value”, Journal of the Academy ofMarketing Science, Vol. 46 No. 3, pp. 366-383.

Bendapudi, N. and Leone, R.P. (2003), “Psychological implications of customer participation in co-production”, Journal of Marketing, Vol. 67 No. 1, pp. 14-28.

Bernardes, E.S. (2010), “The effect of supply management on aspects of social capital and the impacton performance: a social network perspective”, Journal of Supply Chain Management, Vol. 46No. 1, pp. 45-55.

Bettencourt, L.A. (1997), “Customer voluntary performance: customers as partners in servicedelivery”, Journal of Retailing, Vol. 73 No. 3, pp. 383-406.

Bitner, M.J. (1990), “Evaluating service encounters: the effects of physical surroundings and employeeresponses”, Journal of Marketing, Vol. 54 No. 2, pp. 69-82.

Bitner, M.J., Booms, B.H. and Tetreault, M.S. (1990), “The service encounter: diagnosing favorable andunfavorable incidents”, Journal of Marketing, Vol. 54 No. 1, pp. 71-84.

Bock, D.E., Mangus, S.M. and Folse, J.A.G. (2016), “The road to customer loyalty paved with servicecustomization”, Journal of Business Research, Vol. 69 No. 10, pp. 3923-3932.

Bolton, R. and Saxena-Iyer, S. (2009), “Interactive services: a framework, synthesis and researchdirections”, Journal of Interactive Marketing, Vol. 23 No. 1, pp. 91-104.

Bolton, R.N., Lemon, K.N. and Verhoef, P.C. (2004), “The theoretical underpinnings of customer assetmanagement: a framework and propositions for future research”, Journal of the Academy ofMarketing Science, Vol. 32 No. 3, pp. 271-292.

Bove, L.L., Pervan, S.J., Beatty, S.E. and Shiu, E. (2009), “Service worker role in encouragingcustomer organizational citizenship behaviors”, Journal of Business Research, Vol. 62 No. 7,pp. 698-705.

Bowen, J. (1990), “Development of a taxonomy of services to gain strategic marketing insights”,Journal of the Academy of Marketing Science, Vol. 18 No. 1, pp. 43-49.

Bradley, G.L. and Sparks, B.A. (2002), “Service locus of control: its conceptualization andmeasurement”, Journal of Service Research, Vol. 4 No. 4, pp. 312-324.

Brady, M.K. and Cronin, J.J. (2001), “Some new thoughts on conceptualizing perceived service quality:a hierarchical approach”, Journal of Marketing, Vol. 65 No. 3, pp. 34-49.

Brodie, R.J. and Hollebeek, L.D. (2011), “Advancing and consolidating knowledge about customerengagement”, Journal of Service Research, Vol. 14 No. 3, pp. 283-284.

Brodie, R.J., Hollebeek, L.D., Juri�c, B. and Ili�c, A. (2011), “Customer engagement: conceptual domain,fundamental propositions, and implications for research”, Journal of Service Research, Vol. 14No. 3, pp. 252-271.

Brown, S.P. and Leigh, T.W. (1996), “A new look at psychological climate and its relationship tojob involvement, effort, and performance”, Journal ofApplied Psychology, Vol. 81No. 4, pp. 358-368.

Browne, M.W. and Cudeck, R. (1989), “Single sample cross-validation indices for covariancestructures”, Multivariate Behavioral Research, Vol. 24 No. 4, pp. 445-455.

Burt, R.S. (1987), “Social contagion and innovation: cohesion versus structural equivalence”, AmericanJournal of Sociology, Vol. 92 No. 6, pp. 1287-1335.

Byrne, Z.S., Peters, J.M. and Weston, J.W. (2016), “The struggle with employee engagement: measuresand construct clarification using five samples”, Journal of Applied Psychology, Vol. 101 No. 9,pp. 1201-1227.

Carmeli, A., Ben-Hador, B., Waldman, D.A. and Rupp, D.E. (2009a), “How leaders cultivate socialcapital and nurture employee vigor: implications for job performance”, Journal of AppliedPsychology, Vol. 94 No. 6, pp. 1553-1561.

Serviceengagementbehaviors

Carmeli, A., Brueller, D. and Dutton, J.E. (2009b), “Learning behaviours in the workplace: the role ofhigh-quality interpersonal relationships and psychological safety”, Systems Research andBehavioral Science: the Official Journal of the International Federation for Systems Research,Vol. 26 No. 1, pp. 81-98.

Carmeli, A. and Gittell, J.H. (2009), “High-quality relationships, psychological safety, and learningfrom failures in work organizations”, Journal of Organizational Behavior, Vol. 30 No. 6, pp. 709-729.

Chan, K.W. and Lam, W. (2011), “The trade-off of servicing empowerment on employees’ serviceperformance: examining the underlying motivation and workload mechanisms”, Journal of theAcademy of Marketing Science, Vol. 39 No. 4, pp. 609-628.

Chan, K.W., Yim, C.K. and Lam, S.S.K. (2010), “Is customer participation in value creation a double-edged sword? Evidence from professional financial services across cultures”, Journal ofMarketing, Vol. 74 No. 3, pp. 48-64.

Chang, W. and Taylor, S.A. (2016), “The effectiveness of customer participation in new productdevelopment: a meta-analysis”, Journal of Marketing, Vol. 80 No. 1, pp. 47-64.

Chebat, J.-C. and Kollias, P. (2000), “The impact of empowerment on customer contact employees’ rolesin service organizations”, Journal of Service Research, Vol. 3 No. 1, pp. 66-81.

Chi, N.W. and Grandey, A.A. (2016), “Emotional labor predicts service performance depending onactivation and inhibition regulatory fit”, Journal of Management, Vol. 45 No. 2, pp. 673-700.

Chin, W.W. (1998), “The partial least squares approach to structural equation modeling”, inMarcoulides, G.A. (Ed.), Modern Methods for Business Research, Lawrence Erlbaum Associates,Mahwah, NJ, pp. 295-336.

Coelho, P.S. and Henseler, J. (2012), “Creating customer loyalty through service customization”,European Journal of Marketing, Vol. 46 Nos 3/4, pp. 331-356.

Cole, M.S., Bruch, H. and Vogel, B. (2012), “Energy at work: a measurement validation and linkage tounit effectiveness”, Journal of Organizational Behavior, Vol. 33 No. 4, pp. 445-467.

Coleman, J.S. (1988), “Social capital in the creation of human capital”, American Journal of Sociology,Vol. 94, pp. S95-S120.

Contractor, N.S. and Eisenberg, E.M. (1990), “Communication networks and new media inorganizations”, in Fulk, J. and Steinfield, C.W. (Eds), Organizations and CommunicationTechnology, Sage, Thousand Oaks, CA, pp. 143-172.

Courtright, S.H., McCormick, B.W., Mistry, S. and Wang, J. (2017), “Quality charters or qualitymembers? A control theory perspective on team charters and team performance”, Journal ofApplied Psychology, Vol. 102 No. 10, pp. 1462-1470.

Crandall, C.S. (1988), “Social contagion of binge eating”, Journal of Personality and Social Psychology,Vol. 55 No. 4, pp. 588-598.

Crawford, E.R., LePine, J.A. and Rich, B.L. (2010), “Linking job demands and resources to employeeengagement and burnout: a theoretical extension and meta-analytic test”, Journal of AppliedPsychology, Vol. 95 No. 5, pp. 834-848.

Cui, A.S. and Wu, F. (2016), “Utilizing customer knowledge in innovation: antecedents and impact ofcustomer involvement on new product performance”, Journal of the Academy of MarketingScience, Vol. 44 No. 4, pp. 516-538.

Cullen-Lester, K.L., Leroy, H., Gerbasi, A. and Nishii, L. (2016), “Energy’s role in the extraversion (dis)advantage: how energy ties and task conflict help clarify the relationship betweenextraversion and proactive performance”, Journal of Organizational Behavior, Vol. 37 No. 7,pp. 1003-1022.

Dagger, T.S., Danaher, P.J. and Gibbs, B.J. (2009), “How often versus how long: the interplay of contactfrequency and relationship duration in customer-reported service relationship strength”,Journal of Service Research, Vol. 11 No. 4, pp. 371-388.

Daniels, P.W. (2004), Services and Metropolitan Development: International Perspectives, Routledge,New York, NY.

JOSM

Dean, A.M. (2007), “The impact of the customer orientation of call center employees on customers’affective commitment and loyalty”, Journal of Service Research, Vol. 10 No. 2, pp. 161-173.

Dellande, S., Gilly, M.C. and Graham, J.L. (2004), “Gaining compliance and losing weight: the role of theservice provider in health care services”, Journal of Marketing, Vol. 68 No. 3, pp. 78-91.

Den Hartog, D.N., De Hoogh, A.H. and Keegan, A.E. (2007), “The interactive effects of belongingnessand charisma on helping and compliance”, Journal of Applied Psychology, Vol. 92 No. 4,pp. 1131-1139.

Dong, B., Evans, K.R. and Zou, S. (2008), “The effects of customer participation in co-created servicerecovery”, Journal of the Academy of Marketing Science, Vol. 36 No. 1, pp. 123-137.

Dong, B. and Sivakumar, K. (2015), “A process-output classification for customer participation inservices”, Journal of Service Management, Vol. 26 No. 5, pp. 726-750.

Dong, B. and Sivakumar, K. (2017), “Customer participation in services: domain, scope, andboundaries”, Journal of the Academy of Marketing Science, Vol. 45 No. 6, pp. 944-965.

Dong, B., Sivakumar, K., Evans, K.R. and Zou, S. (2015), “Effect of customer participation on serviceoutcomes: the moderating role of participation readiness”, Journal of Service Research, Vol. 18No. 2, pp. 160-176.

Drengner, J., Jahn, S. and Furchheim, P. (2018), “Flow revisited: process conceptualization and a novelapplication to service contexts”, Journal of Service Management, Vol. 29 No. 4, pp. 703-734.

Dutton, J.E. and Heaphy, E.D. (2003), “The power of high-quality connections at work”, in Cameron,K.S., Dutton, J.E. and Quinn, R.E. (Eds), Positive Organizational Scholarship, Berrett-Koehler,San Francisco, CA, pp. 263-278.

Edmondson, A.C. (2004), “Psychological safety, trust, and learning in organizations: a group-levellens”, in Kramer, R.M. and Cook, K.S. (Eds), Trust and Distrust in Organizations: Dilemmas andApproaches, Russell Sage Foundation, New York, NY, pp. 239-272.

Eisingerich, A.B. and Bell, S.J. (2008), “Perceived service quality and customer trust: does enhancingcustomers’ service knowledge matter?”, Journal of Service Research, Vol. 10 No. 3, pp. 256-268.

Eldor, L. and Harpaz, I. (2016), “A process model of employee engagement: the learning climate and itsrelationship with extra-role performance behaviors”, Journal of Organizational Behavior, Vol. 37No. 2, pp. 213-235.

Fan, G.H. and Zietsma, C. (2017), “Constructing a shared governance logic: the role of emotions inenabling dually embedded agency”, Academy of Management Journal, Vol. 60 No. 6,pp. 2321-2351.

Farmer, S.M., Van Dyne, L. and Kamdar, D. (2015), “The contextualized self: how team–memberexchange leads to coworker identification and helping OCB”, Journal of Applied Psychology,Vol. 100 No. 2, pp. 583-595.

Field, J.M., Victorino, L., Buell, R.W., Dixon, M.J., Meyer Goldstein, S., Menor, L.J., Pullman, M.E., Roth,A.V., Secchi, E. and Zhang, J.J. (2018), “Service operations: what’s next?”, Journal of ServiceManagement, Vol. 29 No. 1, pp. 55-97.

Finn, A. and Kayand�e, U. (1999), “Unmasking a phantom: a psychometric assessment of mysteryshopping”, Journal of Retailing, Vol. 75 No. 2, pp. 195-217.

Fisher, D.M. (2014), “Distinguishing between taskwork and teamwork planning in teams: relationswith coordination and interpersonal processes”, Journal of Applied Psychology, Vol. 99 No. 3,pp. 423-436.

Fisher, D.M., Bell, S.T., Dierdorff, E.C. and Belohlav, J.A. (2012), “Facet personality and surface-leveldiversity as team mental model antecedents: implications for implicit coordination”, Journal ofApplied Psychology, Vol. 97 No. 4, pp. 825-841.

Fisk, R.P., Dean, A.M., Alkire, L., Joubert, A., Previte, J., Robertson, N. and Rosenbaum, M.S. (2018),“Design for service inclusion: creating inclusive service systems by 2050”, Journal of ServiceManagement, Vol. 29 No. 5, pp. 834-858.

Serviceengagementbehaviors

Fleck, S. and Inceoglu, I. (2010), “A comprehensive framework for understanding and predictingengagement”, in Albrecht, S.L. (Ed.), Handbook of Employee Engagement: Perspectives, Issues,Research and Practice, Edward Elgar, Northampton, MA, pp. 31-42.

Fliess, S., Dyck, S. and Schmelter, M. (2014), “Mirror, mirror on the wall – how customers perceive theircontribution to service provision”, Journal of Service Management, Vol. 25 No. 4, pp. 433-469.

Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservablevariables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.

Fredrickson, B.L. (1998), “What good are positive emotions?”, Review of General Psychology, Vol. 2No. 3, pp. 300-319.

Frey, R.V., Bay�on, T. and Totzek, D. (2013), “How customer satisfaction affects employee satisfactionand retention in a professional services context”, Journal of Service Research, Vol. 16 No. 4,pp. 503-517.

Gallan, A.S., Jarvis, C.B., Brown, S.W. and Bitner, M.J. (2013), “Customer positivity and participation inservices: an empirical test in a health care context”, Journal of the Academy of MarketingScience, Vol. 41 No. 3, pp. 338-356.

Gazzoli, G., Hancer, M. and Kim, B. (2013), “Explaining why employee-customer orientation influencescustomers’ perceptions of the service encounter”, Journal of Service Management, Vol. 24 No. 4,pp. 382-400.

Gong, T. (2017), “Customer brand engagement behavior in online brand communities”, Journal ofServices Marketing, Vol. 32 No. 3, pp. 286-299.

Gong, Y., Cheung, S.Y., Wang, M. and Huang, J.-C. (2012), “Unfolding the proactive process forcreativity: integration of the employee proactivity, information exchange, and psychologicalsafety perspectives”, Journal of Management, Vol. 38 No. 5, pp. 1611-1633.

Grandey, A.A., Fisk, G.M., Mattila, A.S., Jansen, K.J. and Sideman, L.A. (2005), “Is “service with asmile” enough? Authenticity of positive displays during service encounters”, OrganizationalBehavior and Human Decision Processes, Vol. 96 No. 1, pp. 38-55.

Gremler, D.D. and Gwinner, K.P. (2008), “Rapport-building behaviors used by retail employees”,Journal of Retailing, Vol. 84 No. 3, pp. 308-324.

Grodal, S., Nelson, A.J. and Siino, R.M. (2015), “Help-seeking and help-giving as an organizationalroutine: continual engagement in innovative work”, Academy of Management Journal, Vol. 58No. 1, pp. 136-168.

Groth, M., Hennig-Thurau, T. and Walsh, G. (2009), “Customer reactions to emotional labor: the rolesof employee acting strategies and customer detection accuracy”, Academy of ManagementJournal, Vol. 52 No. 5, pp. 958-974.

Gully, S.M., Incalcaterra, K.A., Joshi, A. and Beaubien, J.M. (2002), “A meta-analysis of team-efficacy,potency, and performance: interdependence and level of analysis as moderators of observedrelationships”, Journal of Applied Psychology, Vol. 87 No. 5, pp. 819-832.

Guo, L., Gruen, T.W. and Tang, C. (2017), “Seeing relationships through the lens of psychologicalcontracts: the structure of consumer service relationships”, Journal of the Academy ofMarketing Science, Vol. 45 No. 3, pp. 357-376.

Gwinner, K.P., Bitner, M.J., Brown, S.W. and Kumar, A. (2005), “Service customization throughemployee adaptiveness”, Journal of Service Research, Vol. 8 No. 2, pp. 131-148.

Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis: A GlobalPerspective, 7th ed., Pearson, Upper Saddle River, NJ.

Hair, J.F., Hult, G.T.M., Ringle, C.M. and Sarstedt, M. (2017), A Primer on Partial Least SquaresStructural Equation Modeling (PLS-SEM), 2nd ed., Sage, Thousand Oaks, CA.

Harmeling, C.M., Moffett, J.W., Arnold, M.J. and Carlson, B.D. (2017), “Toward a theory of customerengagement marketing”, Journal of the Academy of Marketing Science, Vol. 45 No. 3,pp. 312-335.

JOSM

Hatfield, E., Cacioppo, J.T. and Rapson, R.L. (1994), Emotional Contagion, Cambridge University Press,New York, NY.

Heidenreich, S. and Handrich, M. (2015), “Adoption of technology-based services: the role ofcustomers’ willingness to co-create”, Journal of Service Management, Vol. 26 No. 1, pp. 44-71.

Helkkula, A., Kowalkowski, C. and Tronvoll, B. (2018), “Archetypes of service innovation: implicationsfor value cocreation”, Journal of Service Research, Vol. 21 No. 3, pp. 284-301.

Hennig-Thurau, T., Groth, M., Paul, M. and Gremler, D.D. (2006), “Are all smiles created equal? Howemotional contagion and emotional labor affect service relationships”, Journal of Marketing,Vol. 70 No. 3, pp. 58-73.

Henseler, J., Ringle, C.M. and Sarstedt, M. (2015), “A new criterion for assessing discriminant validityin variance-based structural equation modeling”, Journal of the Academy of Marketing Science,Vol. 43 No. 1, pp. 115-135.

Hibbert, S., Winklhofer, H. and Temerak, M.S. (2012), “Customers as resource integrators: toward amodel of customer learning”, Journal of Service Research, Vol. 15 No. 3, pp. 247-261.

Hirshleifer, D. and Teoh, S.H. (2009), “Thought and behavior contagion in capital markets”, in Hens, T.and Schenk-Hopp�e, K.R. (Eds), Handbook of Financial Markets: Dynamics and Evolution,Elsevier, Amsterdam, pp. 1-56.

Hobfoll, S.E. and Shirom, A. (2001), “Conservation of resources theory: applications to stress andmanagement in the workplace”, in Golembiewski, R.T. (Ed.), Handbook of OrganizationalBehavior, Marcel Dekker, New York, NY, pp. 57-80.

Holland, P., Cooper, B. and Sheehan, C. (2017), “Employee voice, supervisor support, and engagement:the mediating role of trust”, Human Resource Management, Vol. 56 No. 6, pp. 915-929.

Hollebeek, L.D., Srivastava, R.K. and Chen, T. (2019), “S-D logic–informed customer engagement:integrative framework, revised fundamental propositions, and application to CRM”, Journal ofthe Academy of Marketing Science, Vol. 47 No. 1, pp. 161-185.

Homburg, C. and Stock, R.M. (2004), “The link between salespeople’s job satisfaction and customersatisfaction in a business-to-business context: a dyadic analysis”, Journal of the Academy ofMarketing Science, Vol. 32 No. 2, pp. 144-158.

Homburg, C., Wieseke, J. and Bornemann, T. (2009), “Implementing the marketing concept at theemployee-customer interface: the role of customer need knowledge”, Journal of Marketing,Vol. 73 No. 4, pp. 64-81.

Hoppe, A., Toker, S., Schachler, V. and Ziegler, M. (2017), “The effect of change in supervisor supportand job control on change in vigor: differential relationships for immigrant and nativeemployees in Israel”, Journal of Organizational Behavior, Vol. 38 No. 3, pp. 391-414.

Howard, D.J. and Gengler, C. (2001), “Emotional contagion effects on product attitudes”, Journal ofConsumer Research, Vol. 28 No. 2, pp. 189-201.

Huang, H.C., Cheng, T.C.E., Huang, W.F. and Teng, C.I. (2018), “Who are likely to build strong onlinesocial networks? The perspectives of relational cohesion theory and personality theory”,Computers in Human Behavior, Vol. 82, pp. 111-123.

Huetten, A.S.J., Antons, D., Breidbach, C.F., Piening, E.P. and Salge, T.O. (2019), “The impact ofoccupational stereotypes in human-centered service systems”, Journal of Service Management,Vol. 30 No. 1, pp. 132-155.

H€ulsheger, U.R., Lang, J.W., Schewe, A.F. and Zijlstra, F.R. (2015), “When regulating emotions at workpays off: a diary and an intervention study on emotion regulation and customer tips in servicejobs”, Journal of Applied Psychology, Vol. 100 No. 2, pp. 263-277.

Jaakkola, E. and Alexander, M. (2014), “The role of customer engagement behavior in value co-creation: aservice system perspective”, Journal of Service Research, Vol. 17 No. 3, pp. 247-261.

J€a€askel€ainen, A. and Heikkil€a, J. (2019), “Purchasing and supply management practices in customervalue creation”, Supply Chain Management: International Journal, Vol. 24 No. 3, pp. 317-333.

Serviceengagementbehaviors

Jang, Y., Mortimer, J.A., Haley, W.E. and Graves, A.R.B. (2004), “The role of social engagement in lifesatisfaction: its significance among older individuals with disease and disability”, Journal ofApplied Gerontology, Vol. 23 No. 3, pp. 266-278.

Johnston, R. and Kong, X. (2011), “The customer experience: a road-map for improvement”, ManagingService Quality: International Journal, Vol. 21 No. 1, pp. 5-24.

Jonczyk, C.D., Lee, Y.G., Galunic, C.D. and Bensaou, B.M. (2016), “Relational changes during roletransitions: the interplay of efficiency and cohesion”, Academy of Management Journal, Vol. 59No. 3, pp. 956-982.

J€oreskog, K.G. and S€orbom, D. (1996), LISREL 8: User’s Reference Guide, 2nd ed., Scientific SoftwareInternational, Chicago, IL.

Jung, J.H., Brown, T.J. and Zablah, A.R. (2017), “The effect of customer-initiated justice on customer-oriented behaviors”, Journal of Business Research, Vol. 71, pp. 38-46.

Kahn, W.A. (1990), “Psychological conditions of personal engagement and disengagement at work”,Academy of Management Journal, Vol. 33 No. 4, pp. 692-724.

Kahn, W.A. (2010), “The essence of engagement: lessons from the field”, in Albrecht, S.L. (Ed.),Handbook of Employee Engagement: Perspectives, Issues, Research and Practice, Edward Elgar,Northampton, MA, pp. 20-30.

Kark, R. and Carmeli, A. (2009), “Alive and creating: the mediating role of vitality and aliveness in therelationship between psychological safety and creative work involvement”, Journal ofOrganizational Behavior, Vol. 30 No. 6, pp. 785-804.

Kashdan, T.B., Rose, P. and Fincham, F.D. (2004), “Curiosity and exploration: facilitating positivesubjective experiences and personal growth opportunities”, Journal of Personality Assessment,Vol. 82 No. 3, pp. 291-305.

Keh, H.T., Ren, R., Hill, S.R. and Li, X. (2013), “The beautiful, the cheerful, and the helpful: the effects ofservice employee attributes on customer satisfaction”, Psychology and Marketing, Vol. 30 No. 3,pp. 211-226.

Kelleher, C., Wilson, H.N., Macdonald, E.K. and Peppard, J. (2019), “The score is not the music:integrating experience and practice perspectives on value co-creation in collective consumptioncontexts”, Journal of Service Research, Vol. 22 No. 2, pp. 120-138.

Keyton, J. (1999), “Relational communication in groups”, in Frey, L.R., Gouran, D. and Poole, M.S.(Eds), The Handbook of Group Communication Theory and Research, Sage, Thousand Oaks,CA, pp. 192-222.

Kim, H.S. and Choi, B. (2016), “The effects of three customer-to-customer interaction quality types oncustomer experience quality and citizenship behavior in mass service settings”, Journal ofServices Marketing, Vol. 30 No. 4, pp. 384-397.

Kumar, N., Scheer, L.K. and Steenkamp, J.B.E.M. (1998), “Interdependence, punitive capability, and thereciprocation of punitive actions in channel relationships”, Journal of Marketing Research,Vol. 35 No. 2, pp. 225-235.

Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T. and Tillmanns, S. (2010), “Undervaluedor overvalued customers: capturing total customer engagement value”, Journal of ServiceResearch, Vol. 13 No. 3, pp. 297-310.

Kumar, V. and Pansari, A. (2016), “Competitive advantage through engagement”, Journal of MarketingResearch, Vol. 53 No. 4, pp. 497-514.

Kumar, V., Rajan, B., Gupta, S. and Dalla Pozza, I. (2019), “Customer engagement in service”, Journalof the Academy of Marketing Science, Vol. 47 No. 1, pp. 138-160.

Labig, C.E., Zantow, K. and Peterson, T.O. (2005), “Factors affecting students’ medicine-taking habits”,Journal of American College Health, Vol. 54 No. 3, pp. 177-183.

Lakey, B., Vander Molen, R.J., Fles, E. and Andrews, J. (2016), “Ordinary social interaction and the maineffect between perceived support and affect”, Journal of Personality, Vol. 84 No. 5, pp. 671-684.

JOSM

Lakshmanan, A. and Krishnan, H.S. (2011), “The aha! experience: insight and discontinuous learningin product usage”, Journal of Marketing, Vol. 75 No. 6, pp. 105-123.

Langford, P.H. (2010), “The nature and consequences of employee engagement: searching for ameasure that maximizes the prediction of organizational outcomes”, in Albrecht, S.L. (Ed.),Handbook of Employee Engagement: Perspectives, Issues, Research and Practice, Edward Elgar,Northampton, MA, pp. 375-384.

Latane, B. (2000), “Pressures to uniformity and the evolution of cultural norms: modeling dynamicsocial impact”, in Ilgen, D. and Hulin, C. (Eds), Computational Modeling of Behavior inOrganization: The Third Scientific Discipline, American Psychological Association,Washington, DC, pp. 189-220.

Lechner, A.T. and Paul, M. (2019), “Is this smile for real? The role of affect and thinking style incustomer perceptions of frontline employee emotion authenticity”, Journal of Business Research,Vol. 94, pp. 195-208.

Leckie, C., Nyadzayo, M.W. and Johnson, L.W. (2018), “Promoting brand engagement behaviors andloyalty through perceived service value and innovativeness”, Journal of Services Marketing,Vol. 32 No. 1, pp. 70-82.

Lengnick-Hall, C.A., Claycomb, V. and Inks, L.W. (2000), “From recipient to contributor: examiningcustomer roles and experienced outcomes”, European Journal of Marketing, Vol. 34 Nos 3/4,pp. 359-383.

Lester, S.W., Meglino, B.M. and Korsgaard, M.A. (2002), “The antecedents and consequences of grouppotency: a longitudinal investigation of newly formed work groups”, Academy of ManagementJournal, Vol. 45 No. 2, pp. 352-368.

Liao, H. and Chuang, A. (2004), “A multilevel investigation of factors influencing employee serviceperformance and customer outcomes”, Academy of Management Journal, Vol. 47 No. 1, pp. 41-58.

Lim, C., Kim, M.J., Kim, K.H., Kim, K.J. and Maglio, P. (2019), “Customer process management: aframework for using customer-related data to create customer value”, Journal of ServiceManagement, Vol. 30 No. 1, pp. 105-131.

Lin, C.Y. and Lin, J.S.C. (2017), “The influence of service employees’ nonverbal communication oncustomer-employee rapport in the service encounter”, Journal of Service Management, Vol. 28No. 1, pp. 107-132.

Lin, J.S.C. and Hsieh, C.C. (2011), “Modeling service friendship and customer compliance in high-contact service relationships”, Journal of Service Management, Vol. 22 No. 5, pp. 607-631.

Lin, J.S.C. and Liang, H.Y. (2011), “The influence of service environments on customer emotion andservice outcomes”, Managing Service Quality: International Journal, Vol. 21 No. 4, pp. 350-372.

Lin, J.S.C. and Lin, C.Y. (2011), “What makes service employees and customers smile: antecedents andconsequences of the employees’ affective delivery in the service encounter”, Journal of ServiceManagement, Vol. 22 No. 2, pp. 183-201.

Liu, D., Chen, X.-P. and Yao, X. (2011), “From autonomy to creativity: a multilevel investigation of themediating role of harmonious passion”, Journal of Applied Psychology, Vol. 96 No. 2, pp. 294-309.

Lloyd, A.E. and Luk, S.T.K. (2011), “Interaction behaviors leading to comfort in the service encounter”,Journal of Services Marketing, Vol. 25 No. 3, pp. 176-189.

Lovelock, C. and Wright, L. (2002), Principles of Service Marketing and Management, 2nd ed., PrenticeHall, Upper Saddle River, NJ.

Macey, W.H., Schneider, B., Barbera, K.M. and Young, S.A. (2009), Employee Engagement: Tools forAnalysis, Practice, and Competitive Advantage, Wiley-Blackwell, Malden, WA.

Macintosh, G. (2009), “The role of rapport in professional services: antecedents and outcomes”, Journalof Services Marketing, Vol. 23 No. 2, pp. 70-78.

Malhotra, D. and Lumineau, F. (2011), “Trust and collaboration in the aftermath of conflict: the effectsof contract structure”, Academy of Management Journal, Vol. 54 No. 5, pp. 981-998.

Serviceengagementbehaviors

Martin, C.A. and Bush, A.J. (2006), “Psychological climate, empowerment, leadership style, andcustomer-oriented selling: an analysis of the sales manager–salesperson dyad”, Journal of theAcademy of Marketing Science, Vol. 34 No. 3, pp. 419-438.

Martin, E. and Good, J. (2015), “Strategy, team cohesion and team member satisfaction: the effects ofgender and group composition”, Computers in Human Behavior, Vol. 53, pp. 536-543.

Mathieu, J.E., Kukenberger, M.R., D’innocenzo, L. and Reilly, G. (2015), “Modeling reciprocal teamcohesion–performance relationships, as impacted by shared leadership and members’competence”, Journal of Applied Psychology, Vol. 100 No. 3, pp. 713-734.

Mattila, A.S. (1999), “The role of culture in the service evaluation process”, Journal of Service Research,Vol. 1 No. 3, pp. 250-261.

McColl-Kennedy, J.R., Snyder, H., Elg, M., Witell, L., Helkkula, A., Hogan, S.J. and Anderson, L. (2017),“The changing role of the health care customer: review, synthesis and research agenda”,Journal of Service Management, Vol. 28 No. 1, pp. 2-33.

McColl-Kennedy, J.R., Zaki, M., Lemon, K.N., Urmetzer, F. and Neely, A. (2019), “Gaining customerexperience insights that matter”, Journal of Service Research, Vol. 22 No. 1, pp. 8-26.

McDaniel, D.M. (2011), Energy at Work: A Multinational, Cross-Situational Investigation of RelationalEnergy, Doctoral Dissertation, University of California, Irvine, CA.

McKee, D., Simmers, C.S. and Licata, J. (2006), “Customer self-efficacy and response to service”, Journalof Service Research, Vol. 8 No. 3, pp. 207-220.

Menguc, B., Auh, S., Fisher, M. and Haddad, A. (2013), “To be engaged or not to be engaged: theantecedents and consequences of service employee engagement”, Journal of Business Research,Vol. 66 No. 11, pp. 2163-2170.

Menguc, B., Auh, S., Yeniaras, V. and Katsikeas, C.S. (2017), “The role of climate: implications forservice employee engagement and customer service performance”, Journal of the Academy ofMarketing Science, Vol. 45 No. 3, pp. 428-451.

Miller, J.B. (2015), The Healing Connection: How Women Form Relationships in Therapy and in Life,Beacon, Boston MA.

Mills, P.K. and Morris, J.H. (1986), “Clients as ‘partial’ employees of service organizations: roledevelopment in client participation”, Academy of Management Review, Vol. 11 No. 4, pp. 726-735.

Moeller, S., Ciuchita, R., Mahr, D., Odekerken-Schr€oder, G. and Fassnacht, M. (2013), “Uncoveringcollaborative value creation patterns and establishing corresponding customer roles”, Journal ofService Research, Vol. 16 No. 4, pp. 471-487.

Moliner, M.�A., Monferrer-Tirado, D. and Estrada-Guill�en, M. (2018), “Consequences of customerengagement and customer self-brand connection”, Journal of Services Marketing, Vol. 32 No. 4,pp. 387-399.

Morgan, R.M. and Hunt, S.D. (1994), “The commitment-trust theory of relationship marketing”, Journalof Marketing, Vol. 58 No. 3, pp. 20-38.

Morgeson, F.P. and Hofmann, D.A. (1999), “The structure and function of collective constructs:implications for multilevel research and theory development”, Academy of Management Review,Vol. 24 No. 2, pp. 249-265.

Morgeson, F.P., Reider, M.H. and Campion, M.A. (2005), “Selecting individuals in team settings: theimportance of social skills, personality characteristics, and teamwork knowledge”, PersonnelPsychology, Vol. 58 No. 3, pp. 583-611.

Mullins, R.R., Bachrach, D.G., Rapp, A.A., Grewal, D. and Beitelspacher, L.S. (2015), “You don’t alwaysget what you want, and you don’t always want what you get: an examination of control–desirefor control congruence in transactional relationships”, Journal of Applied Psychology, Vol. 100No. 4, pp. 1073-1088.

Mustak, M., Jaakkola, E., Halinen, A. and Kaartemo, V. (2016), “Customer participation management:developing a comprehensive framework and a research agenda”, Journal of ServiceManagement, Vol. 27 No. 3, pp. 250-275.

JOSM

Nahapiet, J. and Ghoshal, S. (1998), “Social capital, intellectual capital, and the organizationaladvantage”, Academy of Management Review, Vol. 23 No. 2, pp. 242-266.

Neghina, C., Bloemer, J., van Birgelen, M. and Cani€els, M.C.J. (2017), “Consumer motives andwillingness to co-create in professional and generic services”, Journal of Service Management,Vol. 28 No. 1, pp. 157-181.

Ng, S., Russell-Bennett, R. and Dagger, T. (2007), “A typology of mass services: the role of servicedelivery and consumption purpose in classifying service experiences”, Journal of ServicesMarketing, Vol. 21 No. 7, pp. 471-480.

Ng, S.C., Sweeney, J.C. and Plewa, C. (2019), “Managing customer resource endowments anddeficiencies for value cocreation: complex relational services”, Journal of Service Research,Vol. 22 No. 2, pp. 156-172.

Nguyen, H., Groth, M., Walsh, G. and Hennig-Thurau, T. (2014), “The impact of service scripts oncustomer citizenship behavior and the moderating role of employee customer orientation”,Psychology and Marketing, Vol. 31 No. 12, pp. 1096-1109.

Niessen, C., Sonnentag, S. and Sach, F. (2012), “Thriving at work—a diary study”, Journal ofOrganizational Behavior, Vol. 33 No. 4, pp. 468-487.

O’Cass, A. and Ngo, L.V. (2011), “Achieving customer satisfaction in services firms via brandingcapability and customer empowerment”, Journal of Services Marketing, Vol. 25 No. 7, pp. 489-496.

Oertzen, A.S., Odekerken-Schr€oder, G., Brax, S.A. and Mager, B. (2018), “Co-creating services—conceptualclarification, forms and outcomes”, Journal of Service Management, Vol. 29 No. 4, pp. 641-679.

Otterbring, T. (2017), “Smile for a while: the effect of employee-displayed smiling on customer affectand satisfaction”, Journal of Service Management, Vol. 28 No. 2, pp. 284-304.

Ouschan, R., Sweeney, J. and Johnson, L. (2006), “Customer empowerment and relationship outcomesin healthcare consultations”, European Journal of Marketing, Vol. 40 Nos 9/10, pp. 1068-1086.

Owens, B.P., Baker, W.E., Sumpter, D.M. and Cameron, K.S. (2016), “Relational energy at work:implications for job engagement and job performance”, Journal of Applied Psychology, Vol. 101No. 1, pp. 35-49.

Palmatier, R.W., Dant, R.P., Grewal, D. and Evans, K.R. (2006), “Factors influencing the effectivenessof relationship marketing: a meta-analysis”, Journal of Marketing, Vol. 70 No. 4, pp. 136-153.

Pansari, A. and Kumar, V. (2017), “Customer engagement: the construct, antecedents, andconsequences”, Journal of the Academy of Marketing Science, Vol. 45 No. 3, pp. 294-311.

Parker, S.K. and Collins, C.G. (2010), “Taking stock: integrating and differentiating multiple proactivebehaviors”, Journal of Management, Vol. 36 No. 3, pp. 633-662.

Patel, P.C., Pearce, J.A. and Guedes, M.J. (2019), “The survival benefits of service intensity for newmanufacturing ventures: a resource-advantage theory perspective”, Journal of Service Research,Vol. 22 No. 4, pp. 352-370.

Patterson, P.G., Cowley, E. and Prasongsukarn, K. (2006), “Service failure recovery: the moderatingimpact of individual-level cultural value orientation on perceptions of justice”, InternationalJournal of Research in Marketing, Vol. 23 No. 3, pp. 263-277.

Patterson, P.G. and Smith, T. (2001), “Modeling relationship strength across service types in an Easternculture”, International Journal of Service Industry Management, Vol. 12 No. 2, pp. 90-113.

Paxton, S.J., Schutz, H.K., Wertheim, E.H. and Muir, S.L. (1999), “Friendship clique and peer influenceson body image concerns, dietary restraint, extreme weight-loss behaviors, and binge eating inadolescent girls”, Journal of Abnormal Psychology, Vol. 108 No. 2, pp. 255-266.

Payne, A.F., Storbacka, K. and Frow, P. (2008), “Managing the co-creation of value”, Journal of theAcademy of Marketing Science, Vol. 36 No. 1, pp. 83-96.

Payne, S.C. and Webber, S.S. (2006), “Effects of service provider attitudes and employment status oncitizenship behaviors and customers’ attitudes and loyalty behavior”, Journal of AppliedPsychology, Vol. 91 No. 2, pp. 365-378.

Serviceengagementbehaviors

Pham, M.T. and Avnet, T. (2009), “Rethinking regulatory engagement theory”, Journal of ConsumerPsychology, Vol. 19 No. 2, pp. 115-123.

Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases inbehavioral research: a critical review of the literature and recommended remedies”, Journal ofApplied Psychology, Vol. 88 No. 5, pp. 879-903.

Post, C. (2015), “When is female leadership an advantage? Coordination requirements, teamcohesion, and team interaction norms”, Journal of Organizational Behavior, Vol. 36 No. 8,pp. 1153-1175.

Pugh, S.D. (2001), “Service with a smile: emotional contagion in the service encounter”, Academy ofManagement Journal, Vol. 44 No. 5, pp. 1018-1027.

Qin, X., Huang, M., Johnson, R.E., Hu, Q. and Ju, D. (2018), “The short-lived benefits of abusivesupervisory behavior for actors: an investigation of recovery and work engagement”, Academyof Management Journal, Vol. 61 No. 5, pp. 1951-1975.

Quinn, R.W. (2007), “Energizing others in work connections”, in Dutton, J.E. and Ragins, B.R. (Eds),Exploring Positive Relationships at Work: Building a Theoretical and Research Foundation,Lawrence Erlbaum Associates Publishers, Mahwah, NJ, pp. 73-90.

Quinn, R.W., Spreitzer, G.M. and Lam, C.F. (2012), “Building a sustainable model of human energy inorganizations: exploring the critical role of resources”, The Academy of Management Annals,Vol. 6 No. 1, pp. 337-396.

Radel, R., Sarrazin, P., Legrain, P. and Wild, T.C. (2010), “Social contagion of motivation betweenteacher and student: analyzing underlying processes”, Journal of Educational Psychology,Vol. 102 No. 3, pp. 577-587.

Rafaeli, A., Ziklik, L. and Doucet, L. (2008), “The impact of call center employees’ customer orientationbehaviors on service quality”, Journal of Service Research, Vol. 10 No. 3, pp. 239-255.

Ramani, G. and Kumar, V. (2008), “Interaction orientation and firm performance”, Journal ofMarketing, Vol. 72 No. 1, pp. 27-45.

Ramaswami, S.N. and Singh, J. (2003), “Antecedents and consequences of merit pay fairness forindustrial salespeople”, Journal of Marketing, Vol. 67 No. 4, pp. 46-66.

Rapp, A., Beitelspacher, L.S., Grewal, D. and Hughes, D.E. (2013), “Understanding social media effectsacross seller, retailer, and consumer interactions”, Journal of the Academy of Marketing Science,Vol. 41 No. 5, pp. 547-566.

Raub, S. and Liao, H. (2012), “Doing the right thing without being told: joint effects of initiative climateand general self-efficacy on employee proactive customer service performance”, Journal ofApplied Psychology, Vol. 97 No. 3, pp. 651-667.

Rhoades, L., Eisenberger, R. and Armeli, S. (2001), “Affective commitment to the organization: thecontribution of perceived organizational support”, Journal of Applied Psychology, Vol. 86 No. 5,pp. 825-836.

Rich, B.L., Lepine, J.A. and Crawford, E.R. (2010), “Job engagement: antecedents and effects on jobperformance”, Academy of Management Journal, Vol. 53 No. 3, pp. 617-635.

Rico, R., S�anchez-Manzanares, M., Gil, F. and Gibson, C. (2008), “Team implicit coordination processes:a team knowledge–based approach”, Academy of Management Review, Vol. 33 No. 1,pp. 163-184.

Rosenbaum, M.S. (2008), “Return on community for consumers and service establishments”, Journal ofService Research, Vol. 11 No. 2, pp. 179-196.

Runhaar, P., Sanders, K. and Konermann, J. (2013), “Teachers’ work engagement: consideringinteraction with pupils and human resources practices as job resources”, Journal of AppliedSocial Psychology, Vol. 43 No. 10, pp. 2017-2030.

Saks, A.M. (2006), “Antecedents and consequences of employee engagement”, Journal of ManagerialPsychology, Vol. 21 No. 7, pp. 600-619.

JOSM

Salanova, M., Agut, S. and Peiro, J.M. (2005), “Linking organizational resources and work engagementto employee performance and customer loyalty: the mediation of service climate”, Journal ofApplied Psychology, Vol. 90 No. 6, pp. 1217-1227.

Santos, J.B. and Spring, M. (2015), “Are knowledge intensive business services really co-produced?Overcoming lack of customer participation in KIBS”, Industrial Marketing Management,Vol. 50, pp. 85-96.

Schau, H.J., Dellande, S. and Gilly, M.C. (2007), “The impact of code switching on service encounters”,Journal of Retailing, Vol. 83 No. 1, pp. 65-78.

Schaufeli, W.B. and Bakker, A.B. (2004), “Job demands, job resources, and their relationship withburnout and engagement: a multi-sample study”, Journal of Organizational Behavior, Vol. 25No. 3, pp. 293-315.

Schaufeli, W.B., Mart�ınez, I.M., Pinto, A.M., Salanova, M. and Bakker, A.B. (2002), “Burnout andengagement in university students: a cross-national study”, Journal of Cross-CulturalPsychology, Vol. 33 No. 5, pp. 464-481.

Schneider, B., Yost, A.B., Kropp, A., Kind, C. and Lam, H. (2018), “Workforce engagement: what it is,what drives it, and why it matters for organizational performance”, Journal of OrganizationalBehavior, Vol. 39 No. 4, pp. 462-480.

Shalley, C.E., Zhou, J. and Oldham, G.R. (2004), “The effects of personal and contextual characteristicson creativity: where should we go from here?”, Journal of Management, Vol. 30 No. 6,pp. 933-958.

Sharma, N. and Patterson, P.G. (1999), “The impact of communication effectiveness and servicequality on relationship commitment in consumer, professional services”, Journal of ServicesMarketing, Vol. 13 No. 2, pp. 151-170.

Sharma, S. and Conduit, J. (2016), “Cocreation culture in health care organizations”, Journal of ServiceResearch, Vol. 19 No. 4, pp. 438-457.

Sim, M., Conduit, J. and Plewa, C. (2018), “Engagement within a service system: a fuzzy set analysis ina higher education setting”, Journal of Service Management, Vol. 29 No. 3, pp. 422-442.

Smith, B.G. and Gallicano, T.D. (2015), “Terms of engagement: analyzing public engagement withorganizations through social media”, Computers in Human Behavior, Vol. 53 No. 1, pp. 82-90.

S€oderlund, M. and Sagfossen, S. (2017), “The depicted service employee in marketing communications:an empirical assessment of the impact of facial happiness”, Journal of Retailing and ConsumerServices, Vol. 38, pp. 186-193.

Sonnentag, S. (2003), “Recovery, work engagement, and proactive behavior: a new look at the interfacebetween nonwork and work”, Journal of Applied Psychology, Vol. 88 No. 3, pp. 518-528.

Sonnentag, S., Eck, K., Fritz, C. and K€uhnel, J. (2019), “Morning reattachment to work and workengagement during the day: a look at day-level mediators”, Journal of Management, doi: 10.1177/0149206319829823.

Spreitzer, G., Sutcliffe, K., Dutton, J., Sonenshein, S. and Grant, A.M. (2005), “A socially embeddedmodel of thriving at work”, Organization Science, Vol. 16 No. 5, pp. 537-549.

Stajkovic, A.D., Lee, D. and Nyberg, A.J. (2009), “Collective efficacy, group potency, and groupperformance: meta-analyses of their relationships, and test of a mediation model”, Journal ofApplied Psychology, Vol. 94 No. 3, pp. 814-828.

Stanworth, J.O., Hsu, R.S. and Chang, H.-T. (2015), “Interpersonal service quality of the Chinese:determinants and behavioral drivers”, Service Business, Vol. 9 No. 3, pp. 515-540.

Stock, R.M. and Bednarek, M. (2014), “As they sow, so shall they reap: customers’ influence oncustomer satisfaction at the customer interface”, Journal of the Academy of Marketing Science,Vol. 42 No. 4, pp. 400-414.

Stock, R.M. and Hoyer, W.D. (2005), “An attitude-behavior model of salespeople’s customerorientation”, Journal of the Academy of Marketing Science, Vol. 33 No. 4, pp. 536-552.

Serviceengagementbehaviors

Stumpf, S.A., Colarelli, S.M. and Hartman, K. (1983), “Development of the career exploration survey(CES)”, Journal of Vocational Behavior, Vol. 22 No. 2, pp. 191-226.

Subramony, M., Ehrhart, K., Groth, M., Holtom, B.C., van Jaarsveld, D.D., Yagil, D., Darabi, T., Walker,D., Bowen, D.E. and Fisk, R.P. (2017), “Accelerating employee-related scholarship in servicemanagement: research streams, propositions, and commentaries”, Journal of ServiceManagement, Vol. 28 No. 5, pp. 837-865.

Sweeney, J.C., Danaher, T.S. and McColl-Kennedy, J.R. (2015), “Customer effort in value cocreationactivities: improving quality of life and behavioral intentions of health care customers”, Journalof Service Research, Vol. 18 No. 3, pp. 318-335.

Tang, C., Liu, Y., Oh, H. and Weitz, B. (2014), “Socialization tactics of new retail employees: a pathwayto organizational commitment”, Journal of Retailing, Vol. 90 No. 1, pp. 62-73.

Torres, E.N., Lugosi, P., Orlowski, M. and Ronzoni, G. (2018), “Consumer-led experience customization:a socio-spatial approach”, Journal of Service Management, Vol. 29 No. 2, pp. 206-229.

Tsai, W.C. (2001), “Determinants and consequences of employee displayed positive emotions”, Journalof Management, Vol. 27 No. 4, pp. 497-512.

Tsai, W.C. and Huang, Y.M. (2002), “Mechanisms linking employee affective delivery and customerbehavioral intentions”, Journal of Applied Psychology, Vol. 87 No. 5, pp. 1001-1008.

Ugwu, F.O., Onyishi, I.E. and Rodr�ıguez-S�anchez, A.M. (2014), “Linking organizational trust with employeeengagement: the role of psychological empowerment”, Personnel Review, Vol. 43 No. 3, pp. 377-400.

Vallerand, R.J., Salvy, S.J., Mageau, G.A., Elliot, A.J., Denis, P.L., Grouzet, F.M. and Blanchard, C.(2007), “On the role of passion in performance”, Journal of Personality, Vol. 75 No. 3, pp. 505-534.

Van den Bulte, C. and Wuyts, S. (2007), Social Networks and Marketing, Marketing Science Institute,Cambridge, MA.

van Doorn, J., Lemon, K.N., Mittal, V., Nass, S., Pick, D., Pirner, P. and Verhoef, P.C. (2010), “Customerengagement behavior: theoretical foundations and research directions”, Journal of ServiceResearch, Vol. 13 No. 3, pp. 253-266.

Vargo, S.L. and Lusch, R.F. (2004), “Evolving to a new dominant logic for marketing”, Journal ofMarketing, Vol. 68 No. 1, pp. 1-17.

Vargo, S.L. and Lusch, R.F. (2008), “Service-dominant logic: continuing the evolution”, Journal of theAcademy of Marketing Science, Vol. 36 No. 1, pp. 1-10.

Vargo, S.L. and Lusch, R.F. (2016), “Institutions and axioms: an extension and update of service-dominant logic”, Journal of the Academy of Marketing Science, Vol. 44 No. 1, pp. 5-23.

Verleye, K., Gemmel, P. and Rangarajan, D. (2014), “Managing engagement behaviors in a network ofcustomers and stakeholders: evidence from the nursing home sector”, Journal of ServiceResearch, Vol. 17 No. 1, pp. 68-84.

Vivek, S.D., Beatty, S.E. and Morgan, R.M. (2012), “Customer engagement: exploring customerrelationships beyond purchase”, Journal of Marketing Theory and Practice, Vol. 20 No. 2,pp. 122-146.

Voorhees, C.M., Brady, M.K., Calantone, R. and Ramirez, E. (2016), “Discriminant validity testing inmarketing: an analysis, causes for concern, and proposed remedies”, Journal of the Academy ofMarketing Science, Vol. 44 No. 1, pp. 119-134.

Walsh, G., Yang, Z., Dose, D. and Hille, P. (2015), “The effect of job-related demands and resources onservice employees’ willingness to report complaints: Germany versus China”, Journal of ServiceResearch, Vol. 18 No. 2, pp. 193-209.

Wang, L., Owens, B.P., Li, J.J. and Shi, L. (2018), “Exploring the affective impact, boundary conditions, andantecedents of leader humility”, Journal of Applied Psychology, Vol. 103 No. 9, pp. 1019-1038.

Webster, C. and Sundaram, D.S. (2009), “Effect of service provider’s communication style on customersatisfaction in professional services setting: the moderating role of criticality and servicenature”, Journal of Services Marketing, Vol. 23 No. 2, pp. 103-113.

JOSM

Wieseke, J., Ahearne, M., Lam, S.K. and Van Dick, R. (2009), “The role of leaders in internalmarketing”, Journal of Marketing, Vol. 73 No. 2, pp. 123-145.

Wieseke, J., Geigenm€uller, A. and Kraus, F. (2012), “On the role of empathy in customer–employeeinteractions”, Journal of Service Research, Vol. 15 No. 3, pp. 316-331.

Wilder, K.M., Collier, J.E. and Barnes, D.C. (2014), “Tailoring to customers’ needs: understanding howto promote an adaptive service experience with frontline employees”, Journal of ServiceResearch, Vol. 17 No. 4, pp. 446-459.

Wilk, S.L. and Moynihan, L.M. (2005), “Display rule“regulators”: the relationship betweensupervisors and worker emotional exhaustion”, Journal of Applied Psychology, Vol. 90 No. 5,pp. 917-927.

Xie, C., Bagozzi, R.P. and Troye, S.V. (2008), “Trying to prosume: toward a theory of consumers as co-creators of value”, Journal of the Academy of Marketing Science, Vol. 36 No. 1, pp. 109-122.

Yagil, D. and Medler-Liraz, H. (2013), “Moments of truth: examining transient authenticity andidentity in service encounters”, Academy of Management Journal, Vol. 56 No. 2, pp. 473-497.

Yang, F., Liu, J., Wang, Z. and Zhang, Y. (2019), “Feeling energized: a multilevel model of spiritualleadership, leader integrity, relational energy, and job performance”, Journal of Business Ethics,Vol. 158 No. 4, pp. 983-997.

Yee, R.W., Yeung, A.C. and Cheng, T.E. (2008), “The impact of employee satisfaction on quality andprofitability in high-contact service industries”, Journal of Operations Management, Vol. 26No. 5, pp. 651-668.

Yi, Y., Nataraajan, R. and Gong, T. (2011), “Customer participation and citizenship behavioralinfluences on employee performance, satisfaction, commitment, and turnover intention”, Journalof Business Research, Vol. 64 No. 1, pp. 87-95.

Yim, C.K., Chan, K.W. and Lam, S.S. (2012), “Do customers and employees enjoy service participation?Synergistic effects of self-and other-efficacy”, Journal of Marketing, Vol. 76 No. 6, pp. 121-140.

Yoo, J. and Arnold, T.J. (2016), “Frontline employee customer-oriented attitude in the presence of jobdemands and resources: the influence upon deep and surface acting”, Journal of ServiceResearch, Vol. 19 No. 1, pp. 102-117.

Young, G.J., Meterko, M.M., Mohr, D., Shwartz, M. and Lin, H. (2009), “Congruence in the assessmentof service quality between employees and customers: a study of a public health care deliverysystem”, Journal of Business Research, Vol. 62 No. 11, pp. 1127-1135.

Young, H.R., Glerum, D.R., Wang, W. and Joseph, D.L. (2018), “Who are the most engaged at work? Ameta-analysis of personality and employee engagement”, Journal of Organizational Behavior,Vol. 39 No. 10, pp. 1330-1346.

Zaccaro, S.J., Rittman, A.L. and Marks, M.A. (2001), “Team leadership”, The Leadership Quarterly,Vol. 12 No. 4, pp. 451-483.

Zaman, M., Anandarajan, M. and Dai, Q. (2010), “Experiencing flow with instant messaging and itsfacilitating role on creative behaviors”, Computers in Human Behavior, Vol. 26 No. 5, pp. 1009-1018.

Zhao, Y., Yan, L. and Keh, H.T. (2018), “The effects of employee behaviours on customer participationin the service encounter: the mediating role of customer emotions”, European Journal ofMarketing, Vol. 52 Nos 5/6, pp. 1203-1222.

AppendixMeasurement items

Service role involvement

SRI1: When I serve the customer, I really exert myself as much as I can

SRI2: I put in extra efforts whenever necessary

SRI3: I work harder than is required during the service delivery

Serviceengagementbehaviors

Customer orientation behavior

COB1: The service employee makes recommendations that match my needs

COB2: The service employee offers tailor-made services for me

COB3: The service employee offers promotions that are tailored to my situation

COB4: The service employee makes me feel that I am a unique customer

COB5: I believe that the service employee offers services customized to my needs

Customer empowerment behavior

CEM1: I interact with the customer to design service offerings that meet his/her unique needs

CEM2: I co-opt customer involvement in providing services for the customer

CEM3: I provide the customer with support to help him/her get more value from the serviceinteraction.

Relational energy

RE1: I feel invigorated when I interact with the service employee

RE2:When interacting with the service employee, I feel more energy to engage in the service process

RE3: I feel increased vitality when I interact with the service employee

RE4: An interpersonal exchange with the service employee makesme feel more stamina to engage inthe service process

RE5: I feel “pepped up” when I interact with the service employee

Interaction cohesion

IC1: There is a feeling of unity and cohesion in the service interaction

IC2: There is a strong feeling of belongingness between the service employee and me

IC3: The service employee and I feel close to each other

Service exploration behaviour

SEPB1: During service interaction, I actively investigate service possibilities

SEPB2: During the service encounter, I actively explore information on services and products

SEPB3: During the service encounter, I actively seek information on specific areas of my interest

Service coordination behavior

COOR1: I provide service-related information to the service employee without being asked

COOR2: I proactively help the service employee when he/she needs assistance

COOR3: I monitor the progress of service delivery

COOR4: I effectively adapt my behaviors to the actions of the service employee

Relationship durationApproximately how long have you been coming to this service employee?

Contact frequencyApproximately how frequently have you been coming to this service employee?

JOSM

Customer knowledge

KNOW1: I can understand almost all the aspects of the services

KNOW2: I possess good knowledge of the services and products

Customer-perceived employee deep acting

DAB1: The employee works hard to feel the emotions that he/she needs to show to me

DAB2: The employee tries to actually experience the emotions he/she has to show to me

DAB3: The employee makes a strong effort to actually feel the emotions that he/she needs to displaytoward me

About the authorsHaw-Yi Liang is a PhD Candidate at the Department of International Business, National TaiwanUniversity. Her research interests focus on services marketing and internal marketing. Her work hasappeared in Managing Service Quality: An International Journal.

Chih-Ying Chu is a PhD Candidate at the Department of International Business, National TaiwanUniversity. Her research interests focus on services marketing and customer relationship management.Chih-Ying Chu is the corresponding author and can be contacted at: [email protected]

Jiun-Sheng Chris Lin is a professor of marketing at the Department of International Business,National Taiwan University. He received his PhD from Smith School of Business, University ofMaryland at College Park. His research areas include services marketing, branding strategies andcustomer relationship management. He has published papers in Journal of Retailing, Journal of ServiceManagement, Supply Chain Management, Journal of Business and Industrial Marketing, Journal ofService Theory and Practice and other journals.

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Serviceengagementbehaviors