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Exoskeletons are characterized as wearable, mechanical orthoses that augment the physical performance of the wearer, enhance productivity and employee well-being when used in value producing contexts. However, limited research involving exoskeleton usage by service employees in frontline contexts has been undertaken within service research. The purpose of this paper is to provide an overview of exoskeleton research undertaken within the context of value-producing roles, introduce exoskeletons conceptually to the service research domain, provide new conceptualizations of service exchange interactions involving physically augmented service actors and propose future avenues of exoskeleton research in alignment with key service theories.

A multi-disciplinary structured literature review based on the preferred reporting items for systematic reviews and meta-analyses method was undertaken across a variety of literature fields. A final selection of n = 25 papers was selected for analysis from an initial sample of N = 3,537. Given the emergent nature of exoskeleton research and the variety of methodology types used between literature fields, a thematic analysis approach was used for analysing identified papers.

The literature review identified four main themes within role-focused exoskeleton research. These themes informed proposals for future exoskeleton research with respect to key service theories and typologies. The findings demonstrate that the presence of an exoskeleton changes the behaviours and interactions of service employees. The augmented social presence AugSP typology is conceptualized to explain the influences of human enhancement technologies (HETs) within service actor interactions.

This research introduces the AugSP typology to conceptualize the impacts that exoskeletons and HETs impose within technologically mediated service interactions and provides a service-specific definition of exoskeleton technology to guide future service research involving the technology.

With the advent of increasingly sophisticated AI, the nature of work in the service frontline is changing. The next frontier is to go beyond replacing routine tasks and augmenting service employees with AI. The purpose of this paper is to investigate whether service employees augmented with AI-based emotion recognition software are more effective in interpersonal emotion regulation (IER) and whether and how IER impacts their own affective well-being.

For the underlying study, an AI-based emotion recognition software was developed in order to assist service employees in managing customer emotions. A field study based on 2,459 call center service interactions assessed the effectiveness of the AI in augmenting service employees for IER and the immediate downstream consequences for well-being relevant outcomes.

Augmenting service employees with AI significantly improved their IER activities. Employees in the AI (vs control) condition were significantly more effective in regulating customer emotions. IER goal attainment, in turn, mediated the effect on employee affective well-being. Perceived stress related to exposure to the AI augmentation acted as a competing mediator.

Service firms can benefit from state-of-the-art AI technology by focusing on its capacity to augment rather than merely replacing employees. Furthermore, signaling IER goal attainment with the help of technology may provide uplifting consequences for service employee affective well-being.

The present study is among the first to empirically test the introduction of an AI-fueled technology to augment service employees in handling customer emotions. This paper further complements the literature by investigating IER in a real-life setting and by uncovering goal attainment as a new mechanism underlying the effect of IER on the well-being of the sender.

Robots are predicted to have a profound impact on the service sector. The emergence of robots has attracted increasing interest from business scholars and practitioners alike. In this article, we undertake a systematic review of the business literature about the impact of service robots on customers and employees with the objective of guiding future research.

We analyzed the literature on service robots as they relate to customers and employees in business journals listed in the Financial Times top 50 journals plus all journals covered in the cross-disciplinary SERVSIG literature alerts.

The analysis of the identified studies yielded multiple observations about the impact of service robots on customers (e.g. overarching frameworks on acceptance and usage of service robots; characteristics of service robots and anthropomorphism; and potential for enhanced and deteriorated service experiences) and service employees (e.g. employee benefits such as reduced routine work, enhanced productivity and job satisfaction; potential negative consequences such as loss of autonomy and a range of negative psychological outcomes; opportunities for human–robot collaboration; job insecurity; and robot-related up-skilling and development requirements). We also conclude that current research on service robots is fragmented, is largely conceptual in nature and focused on the initial adoption stage. We feel that more research is needed to build an overarching theory. In addition, more empirical research is needed, especially on the long(er)-term usage service robots on actual behaviors, the well-being and potential downsides and (ethical) risks for customers and service employees.

Our review focused on the business and service literature. Future work may want to include additional literature streams, including those in computer science, engineering and information systems.

This article is the first to synthesize the business and service literature on the impact of service robots on customers and employees.

The objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an overview of explored contexts and research foci, identifying gaps in the literature and setting a comprehensive agenda for future research.

Combining database (i.e. Scopus, Web of Science, EBSCO, ScienceDirect) and manual journal search, the authors identify 90 articles published in Australian Business Deans Council (ABDC) journals for investigation, using the TCCM (Theory, Context, Characteristics and Methodology) framework.

The results indicate a split between data-driven and theory-driven research, with most studies either adopting an experimental research design focused on testing the accuracy and performance of AI algorithms to assist with credit scoring or investigating AI consumer adoption behaviors in a banking context. The authors call for more research building overarching theories or extending existing theoretical perspectives, such as actor networks. More empirical research is required, especially focusing on consumers' financial behaviors as well as the role of regulation, ethics and policy concerned with AI in financial service contexts, such as insurance or pensions.

The review focuses on AI in customer-facing financial services. Future work may want to investigate back-office and operations contexts.

The authors are the first to systematically synthesize the literature on the use of AI in customer-facing financial services, offering a valuable agenda for future research.

Service robots are now an integral part of people's living and working environment, making service robots one of the hot topics for service researchers today. Against that background, the paper reviews the recent service robot literature following a Theory-Context-Characteristics-Methodology (TCCM) approach to capture the state of art of the field. In addition, building on qualitative input from researchers who are active in this field, the authors highlight where opportunities for further development and growth lie.

The paper identifies and analyzes 88 manuscripts (featuring 173 individual studies) published in academic journals featured on the SERVSIG literature alert. In addition, qualitative input gathered from 79 researchers who are active in the service field and doing research on service robots is infused throughout the manuscript.

The key research foci of the service robot literature to date include comparing service robots with humans, the role of service robots' look and feel, consumer attitudes toward service robots and the role of service robot conversational skills and behaviors. From a TCCM view, the authors discern dominant theories (anthropomorphism theory), contexts (retail/healthcare, USA samples, Business-to-Consumer (B2C) settings and customer focused), study characteristics (robot types: chatbots, not embodied and text/voice-based; outcome focus: customer intentions) and methodologies (experimental, picture-based scenarios).

The current paper is the first to analyze the service robot literature from a TCCM perspective. Doing so, the study gives (1) a comprehensive picture of the field to date and (2) highlights key pathways to inspire future work.

The purpose of this paper is to investigate the relationship between diversity management (i.e. diversity-focused human resource (HR) practices related to recruitment and selection, training and development, performance appraisal and compensation) and perceived firm performance, and the mediating effect of procedural justice.

Primary data based on 400 respondents of 162 organizations operating in India were analysed using statistical tools such as factor analysis, analysis of variance (ANOVA) and multiple regression analysis.

Multiple regression analysis indicated that diversity-focused HR practices had a positive association with perceived firm performance. Further, it was found that procedural justice played a partially mediating in the relationship between diversity-focused HR practices and perceived firm performance.

This paper relied on self-report surveys for data collection, and there laid a possibility of common method variance in the result findings. Hence, future studies should collect data from multiple sources by using multiple methods (e.g. interviews, surveys, peer reports, etc.).

The first implication highlights that senior management’s support is a prerequisite to execute justice-based diversity management processes, which in turn aid in harvesting the true potentials of diversity. Second, organizations should adopt an egalitarian approach while formulating and implementing diversity management initiatives to accentuate the fair and just perceptibility of procedures among employees.

This study sheds new light on the effects of diversity-focused HR practices on firm performance (perceived) in Indian context.

This paper aims, first, to examine artificial intelligence (AI) vs human delivery of financial advice; second, to examine the serial mediating roles of emotion and trust between AI use in the financial service industry and their impact upon marketing outcomes including word of mouth (WOM) and brand attitude; and third, to examine how political ideology moderates' consumers' reactions to AI financial service delivery.

A review of the extant literature is conducted, yielding seven hypotheses underpinned by affect-as-information theory. The hypotheses are tested via three online scenario-based experiments (n = 801) using Process Macro.

The results of the three experiments reveal consumers experience lower levels of positive emotions, specifically, affection, when financial advice is provided by AI in comparison to human employees. Secondly, across the three experiments, conservative consumers are shown to perceive somewhat similar levels of affection in financial advice provided by AI and human employees. Whereas liberal consumers perceive significantly lower levels of affection when serviced by AI in comparison to conservatives and human employee financial advice. Thirdly, results reveal affection and trust to be serial mediators which explain consumers' WOM and brand attitudes when financial services are provided by AI. Fourthly, the investment type plays an important role in consumers’ reactions to the use of AI.

To the best of the authors’ knowledge, this research is one of the first to study political ideology as a potential moderator of consumers’ responses to AI in financial services, providing novel contributions to the literature. It further contributes unique insights by examining emotional responses to AI and human financial advice for different amounts and types of investments using a comprehensive approach of examining both valence and discrete emotions to identify affection as a key explanatory emotion. The study further sheds insights relating to how emotions (affection) and trust mediate the relationship between AI and WOM, and brand attitudes, demonstrating an affect-attitude psychological sequence that explains consumers’ reactions to AI in financial services.

The emergence of artificial intelligence (AI) is leading to a job transformation within the service ecosystem in which issues related to AI governance principles may hinder the social sustainability of the sector. The relevance of AI startups in driving innovation has been recognized; thus, this paper aims to investigate whether and how AI startups may influence the sustainable social development (SSD) of the service sector.

An empirical study based on 24 in-depth interviews was conducted to qualitatively explore the perceptions of service sector facing AI policymakers, AI consultants and academics (n = 12), as well as AI startups (founders, AI developers; n = 12). An inductive coding approach was used to identify and analyze the data.

As part of a complex system, AI startups influence the SSD of the service sector in relation to other stakeholders’ contributions for the ethical deployment of AI. Four key factors influencing AI startups’ ability to contribute to the SSD of the service sector were identified: awareness of socioeconomic issues; fostering decent work; systematically applying ethics; and business model innovation.

This study proposes measures for service sector AI startups to promote collaborative efforts and implement managerial practices that adapt to their available resources.

This study develops original guidelines for startups that seek ethical development of beneficial AI in the service sector, building upon Ethics as a Service approach.

With the ever-increasing adoption of technology and automation radically changing the nature of service delivery, the purpose of this paper is to explore the role of human touch, introducing hospitable service as an enhancement for value creation in service organizations.

Drawing on management, social sciences and hospitality literatures, a four-configuration model is presented to illustrate dimensions which arise from the confluence of different degrees of relationship orientation – shared mental models held by the host organization (self- or other-oriented), and guests’ service preferences (transactional or relational).

A theoretically grounded model of configurations resulting from variations on three key dimensions is offered. These are: employee organization relationships – social exchange processes governing the interactions between employees and their employers; HRM systems – internally consistent combinations of HR practices; and tech-touch trade-off – prioritization of technology vs employees to deliver services.

Embedding hospitable service as a construct to support the leveraging of human touch in service organizations opens up new research opportunities including avenues to further conceptualize the nature and dimensions of hospitable service. Future research that supports further understanding about the role of human touch and value creation in service organizations is proposed.

Through the value-enhancing capability of human in the service encounter, firms can be enabled to accurately position themselves in one of the four relational configurations on offer and then identify opportunities for managers to leverage human touch to combat the diminishing role of the human touch in a technology-ubiquitous service context.

This is among the first papers to explore the influence of technology on the degree of human touch in the interface between hospitality employee and customer, and to develop a configuration model through which researchers and practitioners can operate during this declining era of human to human service interactions.

In the era of technological advancements such as artificial intelligence and robotics, the working environment of service employees is changing, and the need to self-regulate their learning efforts has reached a pinnacle. The purpose of this study is to investigate how supportive resources (organizational investments in social capital, supervisor support and favorable customer feedback) facilitate service employees' self-regulated learning competencies (SRLCs) and how individual factors (self-efficacy and goal orientation) regulate service employee performance outcomes (commitment to service quality and job performance).

Drawing on the social cognitive theory and social capital perspectives, a quantitative survey was implemented with 516 service employees of a corporation operating in Turkey in various service sectors (i.e. retailing, health and technology). The data are analyzed through a covariance-based structural equation model.

Results showed that organizational, supervisory and customer-level supportive resources improved SRLCs and subsequently performance outcomes. Service employees' goal orientation and self-efficacy attenuate the relationship between supportive resources and SRLCs.

This paper enhances the current literature by investigating SRLCs of frontline service employees who need more dynamic and adaptive self-managed self-regulated learning rather than passive training activities. Moreover, the unexpected negative effect of regulatory mechanisms (goal orientation and self-efficacy) on the relationship between supportive resources and SRLCs opens new avenues for managers.