Abstract
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Driven by mounting customer expectations and intensified competition, service organizations are increasingly deploying human resources practices and leveraging technology for frontline employee (FLE) service enhancement (Huang et al. 2021; Subramony et al. 2021). Yet, artificial intelligence-powered automated service technologies (AI-AST) have the potential to either substitute or augment employees in service encounters (De Keyser et al. 2019; Larivière et al. 2017). Moreover, service organizations seeking to complement operational transformations through targeted human resource systems improve their employees’ service performance, while simultaneously putting employee well-being at risk (Jo et al. 2020). These changes in service provision uniformly impact the nature of frontline work and customer experiences (Subramony and Groth 2021). With FLE striving to fulfil customers’ highest demands, their perspective on these persistent disruptions causes a ripple effect jeopardizing their work affect, service behaviors, and organizational outcomes.
To anchor this phenomenon, we position the future of frontline services as a reshaping of services in response to the emerging service paradigm shifts. Our multilevel framework considers the trickle-down effects precipitated by the combination of FLE internal attributions of (1) service-oriented high-performance work systems (SHPWS) and (2) AI-AST characteristics at the individual level; and (3) AI and SHPWS intended strategic decisions at the unit level. FLE service role performance behaviors complete the framework, representing the heightened stakes service organizations must grapple with to adapt to customers’ changing needs (Jo et al. 2021).
This study has two primary objectives: to explore the impact of the future of frontline services phenomenon on FLE, and to explicate effects on the proposed service profit chain (SPC) reimagining’s organizational outcomes. We ground our study in the human resources and service research literatures to highlight the frontline perspective of the focal phenomenon.
Through internal attributional processes (Nishii, Lepak and Schneider 2008), we identify antecedents to the three dimensions of employee well-being . Our study proposes that control-oriented SHPWS and substituting AI-AST are likely to negatively impact FLE attributions, while conversely commitment-oriented SHPWS and augmenting AI-AST having a positive effect on the same. Anchored on social exchange theory, FLE well-being dimensions are positively linked to service role performance behaviors.
By addressing technology-induced changes on the nature of work and customer experiences, we respond to recent service research priorities on technology leveraging for service provision and consumption (Ostrom et al. 2021). Thus, we theorize the neglected FLE perspective by providing a multidisciplinary roadmap on changes impacting their service delivery through an organizational frontline research lens (Subramony et al. 2021). In so doing, we extend human resources internal attributional mechanisms (Nishii 2008) and explore FLE attributions of AI-ST.
This study also echoes a recent call on SPC reimagining (Hogreve, Iseke and Derfuss 2021), thereby evolving the satisfaction mirror through new indirect linkage between FLE well-being and customer satisfaction. We suggest alternative paths to customer loyalty via AI marketing actions cross-level effects on customer outcomes (Briggs, Deretti and Kato 2020; Huang and Rust 2021). We broaden the mutual gains and conflicting outcomes discourse by identifying trade-off effects of intended and perceived SHPWS on employee well-being (Ogbonnaya and Messersmith 2019). We highlight the business imperative of exceeding customers to increase financial performance through the pivotal contribution of service role performance behaviors in SPC.
Finally, our study provides practical guidance for future SHPWS and AI-ST efforts in a climate that has intensified the use of technology and customer expectations
Driven by mounting customer expectations and intensified competition, service organizations are increasingly deploying human resources practices and leveraging technology for frontline employee (FLE) service enhancement (Huang et al. 2021; Subramony et al. 2021). Yet, artificial intelligence-powered automated service technologies (AI-AST) have the potential to either substitute or augment employees in service encounters (De Keyser et al. 2019; Larivière et al. 2017). Moreover, service organizations seeking to complement operational transformations through targeted human resource systems improve their employees’ service performance, while simultaneously putting employee well-being at risk (Jo et al. 2020). These changes in service provision uniformly impact the nature of frontline work and customer experiences (Subramony and Groth 2021). With FLE striving to fulfil customers’ highest demands, their perspective on these persistent disruptions causes a ripple effect jeopardizing their work affect, service behaviors, and organizational outcomes.
To anchor this phenomenon, we position the future of frontline services as a reshaping of services in response to the emerging service paradigm shifts. Our multilevel framework considers the trickle-down effects precipitated by the combination of FLE internal attributions of (1) service-oriented high-performance work systems (SHPWS) and (2) AI-AST characteristics at the individual level; and (3) AI and SHPWS intended strategic decisions at the unit level. FLE service role performance behaviors complete the framework, representing the heightened stakes service organizations must grapple with to adapt to customers’ changing needs (Jo et al. 2021).
This study has two primary objectives: to explore the impact of the future of frontline services phenomenon on FLE, and to explicate effects on the proposed service profit chain (SPC) reimagining’s organizational outcomes. We ground our study in the human resources and service research literatures to highlight the frontline perspective of the focal phenomenon.
Through internal attributional processes (Nishii, Lepak and Schneider 2008), we identify antecedents to the three dimensions of employee well-being . Our study proposes that control-oriented SHPWS and substituting AI-AST are likely to negatively impact FLE attributions, while conversely commitment-oriented SHPWS and augmenting AI-AST having a positive effect on the same. Anchored on social exchange theory, FLE well-being dimensions are positively linked to service role performance behaviors.
By addressing technology-induced changes on the nature of work and customer experiences, we respond to recent service research priorities on technology leveraging for service provision and consumption (Ostrom et al. 2021). Thus, we theorize the neglected FLE perspective by providing a multidisciplinary roadmap on changes impacting their service delivery through an organizational frontline research lens (Subramony et al. 2021). In so doing, we extend human resources internal attributional mechanisms (Nishii 2008) and explore FLE attributions of AI-ST.
This study also echoes a recent call on SPC reimagining (Hogreve, Iseke and Derfuss 2021), thereby evolving the satisfaction mirror through new indirect linkage between FLE well-being and customer satisfaction. We suggest alternative paths to customer loyalty via AI marketing actions cross-level effects on customer outcomes (Briggs, Deretti and Kato 2020; Huang and Rust 2021). We broaden the mutual gains and conflicting outcomes discourse by identifying trade-off effects of intended and perceived SHPWS on employee well-being (Ogbonnaya and Messersmith 2019). We highlight the business imperative of exceeding customers to increase financial performance through the pivotal contribution of service role performance behaviors in SPC.
Finally, our study provides practical guidance for future SHPWS and AI-ST efforts in a climate that has intensified the use of technology and customer expectations
Original language | English (Ireland) |
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Publication status | Published - 16 Jun 2022 |
Event | SERVSIG Conference 2022 - University of Strathclyde, Glasgow, United Kingdom Duration: 16 Jun 2022 → 18 Jun 2022 Conference number: 12th https://www.servsig2022.org/ |
Conference
Conference | SERVSIG Conference 2022 |
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Country/Territory | United Kingdom |
City | Glasgow |
Period | 16/06/2022 → 18/06/2022 |
Internet address |