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The purpose of this study is to critically reflect on visually impaired customers’ technology assistance needs and the perceptions of existing technologies’ performance in the contexts of hospitality and tourism.

Following a qualitative approach, this study used in-depth semistructured interviews with 19 participants with visual impairments.

Positive and negative sides of technology-assisted experiences in the hotel, restaurant, and travel domains were summarized, and room for improvement was discussed to enhance the quality of life and travel experience of visually impaired customers.

Findings from this study offer actionable implications and future directions to technicians and managers to make hospitality and travel experiences more inclusive.

This timely reflection addresses a critical situation by offering original ideas and calling for more discussion of under-represented groups with visual impairments.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

The purpose of this study is to explore customer-artificial intelligence (AI) service technology engagement and relationship development drivers, as well as potential negative consequences in the context of social chatbots.

A sequential mixed-method approach combined exploratory qualitative and confirmatory quantitative analyses. A conceptual model developed from Study 1 qualitative content analysis of in-depth interviews with active users of the AI social chatbot Replika was tested in Study 2 by analyzing survey data obtained from current Replika users.

Loneliness, trust and chatbot personification drive consumer engagement with social chatbots, which fosters relationship development and has the potential to cause chatbot psychological dependence. Attachment to a social chatbot intensifies the positive role of engagement in relationship development with the chatbot.

This study was the first to combine qualitative and quantitative approaches to explore drivers, boundary conditions and consequences of relationship and dependence formation with social chatbots. The authors proposed and empirically tested a novel theoretical model that revealed an engagement-based mechanism of relationship and dependence formation with social chatbots.

This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

Powered by artificial intelligence, voice assistants (VAs), such as Alexa, Siri and Cortona, are at early-stage adoption rates in service contexts. Customers express hesitance in using the technology. Furthermore, the effect of a relevant variable (VA empathy) as a determinant of VAs is not widely researched. This study aims to extend the unified theory of acceptance and use of technology (UTAUT) and social response theory (SRT) to propose and test a conceptual model of the role of customer perceptions of VA empathy and risk on VA adoption and usage intensity.

In this study, data were collected from 387 VA users in the USA using a survey administered through Amazon MTurk. Data cleaning retained a final n = 318 for structural equation modeling analysis.

Findings show that perceived VA empathy enhances customers’ attitude toward VA and drives adoption, thereby increasing VA usage intensity. Perceived risk is a moderator; users with high perceptions of VA empathy have greater VA adoption rates when they have high (vs low) risk perceptions of using VA.

This research is one of the first known studies to provide empirical evidence of the role of customer perceptions of VA empathy and risk on VA adoption in service delivery. It goes beyond VA adoption research to provide empirical evidence of the impact of VA adoption on actual usage intensity. By extending the UTAUT and SRT, this research adds to the theoretical foundation for research on VA adoption, offering practical insights for firms regarding empathetic VA design to enhance customer service delivery.

Using retail banking as a setting and focusing specifically on elderly customers (i.e. individuals aged 60 or more), this study aims to deepen the current understanding of how the physical context and the need for human interaction influence elderly customers' attitudes toward self-service technologies (SSTs) and their behavior.

Using face-to-face questionnaires, a sample of 505 elderly bank customers was collected. Data were analyzed using a multi-method approach, combining a moderated mediation analysis with a fuzzy-set qualitative comparative analysis.

The findings suggest that a pleasant retail space may result in a positive attitude toward SSTs, which increases their co-creation intention. It also highlights that need for interaction of elderly customers with employees has detrimental effects on their attitude toward SSTs.

The current analysis was carried out among Italian elderly banks' customers. Thus, the results are highly dependent on the context of the analysis. In addition, it does not consider the different degrees of knowledge and experience the elderly may have with technology.

This study suggests that providing access and support for using technology may be essential for banks to facilitate SSTs adoption in elderly customers.

To the best of the authors' knowledge, this study represents the first attempt to examine the influence of the physical context on elderly customers' attitudes toward SSTs and their consequent behavioral intentions. Furthermore, it highlights the importance of the human touch for these particular customers.

By extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.

By using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.

Findings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.

The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.

This is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.

The socioeconomically deprived segment called bottom of pyramid lives in extreme resource-constrained environments and is being excluded from having access to many services. This study aims to investigate the role played by virtual engagement platforms in bringing well-being to base of the pyramid (BoP) customers. This study also uses transformative service research and service ecosystem-based approach.

The study uses qualitative approach. Data was collected and analyzed through 16 in-depth interviews with BoP service actors.

Present study explains the role played by virtual engagement platforms as an intermediator between farmers and the service entity. Herein, it may be noted that the role of virtual platforms contributes to the well-being of the BoP community.

The authors’ research work broadens service organizations’ reach by better serving people in the BoP, which ultimately helps in removing unfairness and establishes service inclusion.

The COVID-19 pandemic has disrupted various systems that drove people to adapt to certain technologies, such as electronic government services, for daily survival and to meet social distancing requirements. Therefore, this study aims to determine the antecedents of e-government use based on prospect theory and modified unified theory of acceptance use of technology (UTAUT) during a pandemic.

Convenience sampling of 368 respondents from Vietnam was conducted, and questionnaires were distributed personally or by email. The data were analyzed following a two-stage structural equation modeling (SEM) using SPSS v23 and AMOS v23. The validity and reliability of the instrument were tested and ensured.

Results show that perceived severity drives government support and social influence while perceived security drives government support, social influence and trust. Social influence enhances government support and trust, which both drives e-government use. Mediation analysis shows that government support mediates perceived the influence of perceived severity on e-government use.

The integration of prospect theory and UTAUT brings into light what will drive the adoption of e-government in the context of Vietnam. Supporting mechanisms, such as security measures, trust-building, government support and social influence, will drive citizens to adapt to technologies provided by the government but would also rely on the perceived risks and benefits.

This study integrates prospect theory and a modified version of UTAUT to explain the drivers of e-government use. The results reveal that under uncertainties, government support is critical in driving the use of e-government for people to manage the daily lives for survival.

This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW).

One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed.

TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2.

This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW.

Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).