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Call for Papers of the Journal of Business Research<\/p>\nCall for Papers of the Journal of Business Research<\/p>\n
“Customer Engagement and Relationships in Multi-Actor Service Ecosystems”<\/strong><\/p>\n Major dates<\/strong> Guest co-editors<\/strong> Introduction<\/strong> Recent research focuses on advancing the knowledge about customer engagements in a multifactor service ecosystem, which is theoretically grounded within the S-D logic (Alexander, Jaakkola & Hollebeek, 2018; Fehrer, Woratschek, Germelmann & Brodie, 2018; Vargo & In an increasingly networked environment, the customer \u2013 service provider relationships are With rapid growth of technology-enabled interfaces such as the social media or customer Literature Review<\/strong> Another niche areas that may require special attention is the role of other customers or fellow The effect of social presence on focal customer\u2019s reaction to service failure has been studied In a social networking context, Pan, Hou, Lin and Niu (2018) study the impact of friends\u2019 and Based on the above review, there seems to be a pertinent and persistent need to widen the lens Research Gaps<\/strong> 1) Customer to customer (C2C) interactions:<\/strong> C2C interaction is a way of co-creating and 2) Role of fellow customers in inferring justice-related outcomes:<\/strong> Following a recent 3) Role of fellow customers in pre- and post- service delivery situation:<\/strong> One might think 4) Role of other customers in causing service failures:<\/strong> Service failures are inevitable in 5) Influence of other customers on customer brand relationships:<\/strong> Other customers\u2019 Scope<\/strong> Procedure<\/strong> Major dates<\/strong> Guest co-editors<\/strong> <\/p>\n <\/p>\n References<\/strong> Call for Papers of the Journal of Business Research “Customer Engagement and Relationships in Multi-Actor Service Ecosystems” Major dates Submission Deadline: April 30, 2019 Guest co-editors Piyush Sharma, Kokil Jain, Russel PJ Kingshott, Akiko Ueno Introduction Early research on service encounters defines these as dyadic interactions between customers and service providers who both play specific […]<\/p>\n","protected":false},"author":1,"featured_media":3649,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5,10],"tags":[],"_links":{"self":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/7408"}],"collection":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/comments?post=7408"}],"version-history":[{"count":9,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/7408\/revisions"}],"predecessor-version":[{"id":7444,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/7408\/revisions\/7444"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/media\/3649"}],"wp:attachment":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/media?parent=7408"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/categories?post=7408"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/tags?post=7408"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nSubmission Deadline: April 30, 2019<\/p>\n
\nPiyush Sharma, Kokil Jain, Russel PJ Kingshott, Akiko Ueno<\/p>\n
\nEarly research on service encounters defines these as dyadic interactions between customers
\nand service providers who both play specific roles (Suprenant & Solomon, 1987). However,
\nbroader interpretation have become more common subsequently, moving beyond the service
\ndyad, and including customer interactions with elements other than the frontline service
\nemployees, such as the physical environment, service processes, other customers and
\ntechnology (Patr\u00edcio et al., 2011). Moreover, relationships beyond the dyad are being regarded\u00a0from the perspective of service dominant logic (S-D logic) (Chandler & Vargo, 2011).<\/p>\n
\nLusch, 2017). An extended view of the service eco-system highlights the interdependent role
\nof different participants that may be engaged in multiple co-existing processes, indicating a
\nmany-to-many service experience (Vargo & Lusch, 2016). Future direction in service
\nengagement research, therefore calls for exploring how different service engagement contexts
\nare interconnected and how different individuals within the service ecosystem coordinate their
\nengagement with multiple objects at the same time (Dessart, Veloutsou & Morgan-Thomas,
\n2015), as observed by Vargo and Lusch\u2019s (2017, p. 13) \u2013 \u201cone cannot fully understand the
\nactivity at one level without viewing it from another\u201d.<\/p>\n
\nwitnessing changing dynamics. A service eco-system consists of multiple participants, the
\nemployees, the focal customer, the fellow customers, social media communities and
\ntechnology that are constantly interacting with each other. With such interdependent
\nrelationships, it has become crucial for managers to take into account the role of multiple actors
\nwhen framing strategies for service encounters as well as recovery in case of service failure.
\nFor example, service consumption may take place in the presence of an audience, many of
\nwhom may be fellow customers. The experiences of the focal customers and their subsequent
\nemotions may influence the fellow customer\u2019s perceptions about the service delivery process
\nand outcomes. This influence, however, is not only restricted to an interactive and experiential
\nservice setting or during the consumption process.<\/p>\n
\ncomplaint forums in recent years, the impact of a customer\u2019s experience on other potential
\ncustomers may transcend beyond the service setting, through e-Word-of-Mouth (eWOM),
\nwhich is emerging as a very powerful social tool. Additionally, the rapid growth of Artificial
\nIntelligence (AI) and new intervening digital technologies and devices such as smartphones
\napps, advanced robotics, Intelligent Agents, the Internet of Things (IoT) and Self-serving
\ntechnologies (SST), are fundamentally altering the interplay between customers and
\norganizations \u2013 thereby changing the roles of all involved actors (Larivi\u00e8re et al., 2017).<\/p>\n
\nResearch on customer engagement generally focuses on dyadic interactions, a micro-level
\nengagement that involves customers\u2019 relationships with specific focal objects such as the
\nproduct, the firm or the frontline employees (Alexander et. al., 2017). In this context, Larivi\u00e8re
\net. al. (2017) indicate that \u201cservice encounter 2.0\u201d is paving way for changing interdependent
\nroles of technology, employees, and customers as enabler, innovator, coordinator and
\ndifferentiator. However, exploring a broader context of service encounter within which
\nindividuals operate and interact influencing each other is still overlooked. A recent research
\nstream calls for broadening the scope of engagement research in multi-actor service encounters
\n(e.g., Alexander et al., 2017; Breidbach & Brodie, 2017; Li, Juric & Brodie, 2017).<\/p>\n
\ncustomers within a service ecosystem because customers may affect each another directly
\nthrough interpersonal encounters or indirectly by being a part of the environment (Martin,
\n1996). Similarly, Tombs and McColl-Kennedy (2003) indicate that by being a part of the
\nservice environment, other customers may affect the focal customer\u2019s affective and cognitive
\nresponses. More recently, Ludwig, Barnes and Gouthier (2017) evaluate the emotional and
\ncognitive reactions of the observing customers and suggest that firms should embrace the
\npositive contagion that occurs between the delighted customer and observer while attempting
\nto minimize the impact of jealousy.<\/p>\n
\nby He, Hu, Chen, Alden and He (2017), who found that social presence may lead to higher
\nnegative word-of-mouth (NWOM) intentions for customers after a service failure compared
\nwith when they are alone. Another stream of literature focuses on individual customers\u2019
\nreactions to justice directed towards other customers during service recovery (Mattila, Hanks
\n& Wang, 2013) and suggests that the strength of the recovery attempt influences the observing
\ncustomer\u2019s reactions and evaluations. Through a series of experimental studies, Hillebrandt
\nand Barclay (2017) show that individuals make judgments about the overall justice and
\noutcome satisfaction based on other people\u2019s emotions like anger or guilt.<\/p>\n
\ncrowd\u2019s reviews on customers\u2019 posting behavior. Weitzl and Hutzinger (2017) investigate the
\neffect of firm generated responses to negative comments posted online on bystanders\u2019
\nfavorable and unfavorable brand-related reactions. Others explore the growing importance of
\ncustomer \u2013 to \u2013 customer interaction (C2C) and inter customer helping during service failures
\nand its impact on focal customer\u2019s satisfaction with the brand (Yi & Kim, 2016; Kim, 2017).
\nHowever, despite the growing influence of third parties in service research, the role of other
\ncustomers has received limited attention, possibly because it is not easy to predict or manage
\nthe reactions of other customers in any service settings (Kim & Baker, 2017).<\/p>\n
\nof service encounters beyond a one-to-one interaction perspective and to accommodate the role
\nof other customers in customer engagement and relationships research. We aim to address this
\nneed in this special issue of the Journal of Business Research by identifying the following
\nspecific gaps in the customer engagement and relationships literature about the role of the other
\ncustomers; the ways in which they interact with the firm and the focal customers; the impact
\nof the interdependent nature of their relationships with each other on the service delivery
\nprocess and outcomes, and the responses from all the participants involved in these interactions.<\/p>\n
\nRecent research emphasizes the importance of a holistic engagement involving other actors and
\nnot just the customers (Harmeling, Moffett, Arnold & Carlson 2017; Alexander et al., 2018).
\nThere are multiple aspects that need to be investigated when studying the role of fellow
\ncustomers, in order to provide a holistic view of the multi-actor service ecosystems.<\/p>\n
\nco-producing service experience (McColl-Kennedy, Vargo, Dagger, Sweeney & van
\nKasteren, 2012). For example, Yi and Kim (2016) study inter-customer helping as a form
\nof C2C interaction in the context of self-service technology failure. There is, however, a
\ngrowing need to explore the importance of C2C interaction in other service recovery
\ncontexts (e.g., shared service space like hospitality). Potential areas of future research may
\ninclude the following topics, among others:
\na. Factors that promote or inhibit C2C interactions
\nb. Different motives that encourage inter-customer helping
\nc. Customers characteristics that influence their preference for receiving or refusing
\nhelp from other customer or from frontline employees
\nd. How inter-customer helping can influence focal customer behavior?
\ne. Customer citizenship behavior (CCB) from the perspective of other customers
\nf. Potential use of C2C interactions as a service recovery strategy<\/p>\n
\nincident, where United Airlines violently yanked a passenger from an overbooked flight,
\nbacklash erupted from other passengers who were present during the incident. In no time,
\nthe video went viral on social media and soon other customers, who were not present during
\nthe incident, joined the flurry of outrage. Days after the incident, United, the world\u2019s third
\nlargest airline in terms of revenue and fourth-largest in terms of passengers carried, suffered
\na $1.3 billion drop in market value. This clearly suggests the growing power of the \u2018other\u2019
\ncustomer on social media and impact it can have on the brand value. This incident throws
\nlight on the significant role of fellow customers in forming justice perceptions based on
\nother\u2019s emotions, even when they themselves were not the subject of unfair treatment. This
\nprovides for the following possible avenues for future research:
\na. Impact of fellow customers\u2019 and other employees\u2019 presence on the affective
\nreactions and cognitive responses of the focal customers
\nb. Impact of focal customers\u2019 emotions and actions on third-party observers (e.g.,
\nempathy, jealousy or even disgust) depending on their nature
\nc. Social effects of the focal customers\u2019 emotions and actions on the fairness and
\njustice perceptions of the other customers.<\/p>\n
\nthat the role of fellow customer is relevant only during the service consumption process.
\nHowever, with technology playing the role of an enabler of connections and relationships,
\nthe role of fellow customers has gained salience even in pre- and post- service encounters.
\nA pre-service encounter may involve focal customer seeking advice on a service provider
\nfrom other customers (a customer asking for hotel suggestions on trip-advisor for example).
\nA post-service encounter may be a situation where the customer shares his\/her
\n(un)favorable experiences online. In both situations, the other customers can influence the
\nfocal customer\u2019s perception about the service firm. Hence, future research may explore the
\nfollowing topics to provider deeper insights into this phenomenon:
\na. Impact of other customer\u2019s presence or experiences on the focal customer\u2019s
\nevaluations and judgments during their decision-making process
\nb. Effects of the focal customer\u2019s experiences on the other customers\u2019 evaluations and
\njudgments about their own experiences<\/p>\n
\nservice encounters due to intangibility and heterogeneity of services. Dysfunctional
\ncustomer behavior or negative C2C interaction in a service environment can cause
\nperception of negative service experience, and has a direct influence on the focal
\ncustomer\u2019s overall service experience and may lead to decreased loyalty and repurchase
\nintentions and increased negative word-of-mouth (Harris & Reynolds, 2004; Huang, 2010)
\nand customer cynicism (Balaji, Jha, Sengupta & Krishnan, 2018). Hence, future research
\nmay explore the following topics:
\na. Possible antecedents of service failures caused by other customers (e.g., perceived
\nincompatibility, types of customers, susceptibility to emotional contagion, social
\nnorms conformation and other individual as well as contextual factors
\nb. How to formulate and manage recovery strategies pertaining to service failures
\ncaused by other customers?<\/p>\n
\nperceptions may also influence customer brand relationship (Sreejesh et al., 2017).
\nPrevious research shows that an individual\u2019s evaluation of fellow customers can
\nsignificantly influence focal customer\u2019s satisfaction (Grove & Fisk, 1997; Wu, 2007) but
\nthere is still limited research on the effects of fellow customers\u2019 perceptions on the focal
\ncustomer\u2019s relationship with the brand or service satisfaction. This is another potential topic
\nfor future research that may be included in this special issue.<\/p>\n
\nWe welcome papers with a wide range of contributions, including new theoretical insights,
\nnew concepts or models as well as new methods of data collection and analysis. We welcome
\nboth conceptual and empirical papers; however we discourage simple literature reviews that do
\nnot synthesize the current research and do not present any conceptual framework or testable
\npropositions. We would also not accept simple descriptive or case studies or mere empirical
\nreplications of existing theories or models. We are particularly keen to publish papers that
\nprovide insights that can be generalized to broader services context and not those that are
\nspecific to a particular service category or target customer segment.<\/p>\n
\nAll the authors will need to submit manuscripts for this special issue on the submission system
\nfor the Journal of Business Research. Please indicate that it is a submission for the special issue
\n(e.g., Article Type: \u201cSI: Multi-actor Ecosystems\u201d). All submissions will go through the regular
\nJBR review process with at least two rounds of double-blind peer reviews of each manuscript.
\nEach submitted manuscript would be randomly assigned to one of the four guest co-editors to
\nensure complete fairness and transparency in the review process. All the guest co-editors would
\ndeclare their conflict of interest if they know or are working with any of the contributing authors
\nfor the manuscripts assigned to them. Each guest co-editor would handle the complete review
\nprocess for the manuscripts assigned to them but the final recommendations would be made in
\nconsultation with all the guest co-editors and the chief editors would make the final decisions.<\/p>\n
\nSubmissions Open: January 1, 2019
\nSubmission Deadline: April 30, 2019
\nFinal Acceptance Deadline: March 31, 2020<\/p>\n
\n1) Piyush Sharma, Curtin University, Australia
\n2) Kokil Jain, Amity International Business School, India
\n3) Russel PJ Kingshott, Curtin University, Australia
\n4) Akiko Ueno, Middlesex University, UK<\/p>\n
\nAlexander, M. J., Jaakkola, E., & Hollebeek, L. D. (2018). Zooming out: actor engagement
\nbeyond the dyadic. Journal of Service Management, 29(3), 333-351.
\nhttps:\/\/doi.org\/10.1108\/JOSM-08-2016-0237.
\nBalaji, M. S., Jha, S., Sengupta, A. S., & Krishnan, B. C. (2018). Are cynical customers
\nsatisfied differently? Role of negative inferred motive and customer participation in
\nservice recovery. Journal of Business Research, 86, 109-118.
\nhttps:\/\/doi.org\/10.1016\/j.jbusres.2018.01.023.
\nBreidbach, C. F., & Brodie, R. J. (2017). Engagement platforms in the sharing economy:
\nconceptual foundations and research directions. Journal of Service Theory and Practice,
\n27(4), 761-777. https:\/\/doi.org\/10.1108\/JSTP-04-2016-0071.
\nChandler, J. D., & Vargo, S. L. (2011). Contextualization and value-in-context: how context
\nframes exchange. Marketing Theory, 11(1), 35-49.
\nhttps:\/\/doi.org\/10.1177\/1470593110393713.
\nDessart, L., Veloutsou, C., & Morgan-Thomas, A. (2015). Consumer engagement in online
\nbrand communities: a social media perspective. Journal of Product & Brand
\nManagement, 24(1), 28-42. https:\/\/doi.org\/10.1108\/JPBM-06-2014-0635.
\nFehrer, J. A., Woratschek, H., Germelmann, C. C., & Brodie, R. J. (2018). Dynamics and
\ndrivers of customer engagement: within the dyad and beyond. Journal of Service
\nManagement, 29(3), 443-467. https:\/\/doi.org\/10.1108\/JOSM-08-2016-0236.
\nGrove, S. J., & Fisk, R. P. (1997). The impact of other customers on service experiences: a
\ncritical incident examination of \u201cgetting along\u201d. Journal of Retailing, 73(1), 63-85.
\nhttps:\/\/doi.org\/10.1016\/S0022-4359(97)90015-4.
\nHarmeling, C. M., Moffett, J. W., Arnold, M. J., & Carlson, B. D. (2017). Toward a theory of
\ncustomer engagement marketing. Journal of the Academy of Marketing Science, 45(3),
\n312-335. https:\/\/doi.org\/10.1007\/s11747-016-0509-2.
\nHarris, L. C., & Reynolds, K. L. (2004). Jay customer behavior: an exploration of types and
\nmotives in the hospitality industry. Journal of Services Marketing, 18(5), 339-357.
\nhttps:\/\/doi.org\/10.1108\/08876040410548276.
\nHe, Y., Hu, M., Chen, Q., Alden, D. L., & He, W. (2017). No man is an island: the effect of
\nsocial presence on negative word of mouth intention in service failures. Customer Needs
\nand Solutions, 4(4), 56-67. https:\/\/doi.org\/10.1007\/s40547-017-0078-7.
\nHillebrandt, A., & Barclay, L. J. (2017). Observing others\u2019 anger and guilt can make you feel
\nunfairly treated: the interpersonal effects of emotions on justice-related reactions. Social
\nJustice Research, 30(3), 238-269. https:\/\/doi.org\/10.1007\/s11211-017-0290-5.
\nHuang, W. H. (2010). Other-customer failure: effects of perceived employee effort and
\ncompensation on complainer and non-complainer service evaluations. Journal of Service
\nManagement, 21(2), 191-211. https:\/\/doi.org\/10.1108\/09564231011039286.
\nKim, K., & Baker, M. A. (2017). The influence of other customers in service failure and
\nrecovery. In, Koc, Erdogan. (Ed). Service failures and recovery in tourism and
\nhospitality: a practical manual (pp. 122-134). Boston, MA: CAB International.
\nKim, S. Y. (2017). Inter-customer helping during service failures: the mediating role of
\ndisappointment. Journal of Service Science Research, 9(1), 61-71.
\nhttps:\/\/doi.org\/10.1007\/s12927-017-0004-4.
\nLarivi\u00e8re, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C.,
\nW\u00fcnderlich, N.V. & De Keyser, A. (2017). \u201cService Encounter 2.0\u201d: An investigation
\ninto the roles of technology, employees and customers. Journal of Business Research, 79,
\n238-246. https:\/\/doi.org\/10.1016\/j.jbusres.2017.03.008.
\nLi, L. P., Juric, B., & Brodie, R. J. (2017). Dynamic multi-actor engagement in networks: the
\ncase of united breaks guitars. Journal of Service Theory and Practice, 27(4), 738-760.
\nhttps:\/\/doi.org\/10.1108\/JSTP-04-2016-0066.
\nLudwig, N. L., Barnes, D. C., & Gouthier, M. (2017). Observing delightful experiences of
\nother customers: the double-edged sword of jealousy and joy. Journal of Service Theory
\nand Practice, 27(1), 145-163. https:\/\/doi.org\/10.1108\/JSTP-07-2015-0171.
\nMartin, C. L. (1996). Consumer\u2010to\u2010consumer relationships: satisfaction with other consumers’
\npublic behavior. The Journal of Consumer Affairs, 30(1), 146-169.
\nhttps:\/\/doi.org\/10.1111\/j.1745-6606.1996.tb00729.x.
\nMattila, A., Hanks, L., & Wang, C. (2014). Others service experiences: emotions, perceived
\njustice, and behavior. European Journal of Marketing, 48(3\/4), 552-571.
\nhttps:\/\/doi.org\/10.1108\/EJM-04-2012-0201.
\nMcColl-Kennedy, J. R., Vargo, S. L., Dagger, T. S., Sweeney, J. C., & Kasteren, Y. V.
\n(2012). Health care customer value cocreation practice styles. Journal of Service
\nResearch, 15(4), 370-389. https:\/\/doi.org\/10.1177\/1094670512442806.
\nPan, X., Hou, L., Liu, K., & Niu, H. (2018). Do reviews from friends and the crowd affect
\nonline consumer posting behaviour differently? Electronic Commerce Research and
\nApplications, 29, 102-112. https:\/\/doi.org\/10.1016\/j.elerap.2018.01.007.
\nPatr\u00edcio, L., Fisk, R. P., Falc\u00e3o e Cunha, J., & Constantine, L. (2011). Multilevel service
\ndesign: from customer value constellation to service experience blueprinting. Journal of
\nService Research, 14(2), 180-200. https:\/\/doi.org\/10.1177\/1094670511401901.
\nSreejesh S., Sarkar J.G, Sarkar, A., Eshghi, A., Anusree M.R., (2017). The impact of other
\ncustomer perception on consumer-brand relationships. Journal of Service Theory and
\nPractice, 28(2), 130-146. https:\/\/doi.org\/10.1108\/JSTP-11-2016-0207.
\nSurprenant, C. F., & Solomon, M. R. (1987). Predictability and personalization in the service
\nencounter. Journal of Marketing, 51(2), 86-96. https:\/\/www.jstor.org\/stable\/1251131.
\nTombs, A., & McColl-Kennedy, J. R. (2003). Social-servicescape conceptual model.
\nMarketing Theory, 3(4), 447-475. https:\/\/doi.org\/10.1177\/1470593103040785.
\nVargo, S. L., & Lusch, R. F. (2016). Institutions and axioms: an extension and update of
\nservice-dominant logic. Journal of the Academy of Marketing Science, 44(1), 5-23.
\nhttps:\/\/doi.org\/10.1007\/s11747-015-0456-3.
\nVargo, S. L., & Lusch, R. F. (2017). Service-dominant logic 2025. International Journal of
\nResearch in Marketing, 34(1), 46-67. https:\/\/doi.org\/10.1016\/j.ijresmar.2016.11.001.
\nWeitzl, W., & Hutzinger, C. (2017). The effects of marketer-and advocate-initiated online
\nservice recovery responses on silent bystanders. Journal of Business Research, 80, 164-
\n175. https:\/\/doi.org\/10.1016\/j.jbusres.2017.04.020.
\nWu, C. H. J. (2007). The impact of customer-to-customer interaction and customer
\nhomogeneity on customer satisfaction in tourism service\u2014the service encounter
\nprospective. Tourism Management, 28(6), 1518-1528.
\nhttps:\/\/doi.org\/10.1016\/j.tourman.2007.02.002.
\nYi, Y., & Kim, S. Y. (2017). The role of other customers during self-service technology
\nfailure. Service Business, 11(4), 695-715. https:\/\/doi.org\/10.1007\/s11628-016-0325-2.<\/p>\n","protected":false},"excerpt":{"rendered":"