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1 – 10 of over 63000Wajeeha Aslam, Danish Ahmed Siddiqui, Imtiaz Arif and Kashif Farhat
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…
Abstract
Purpose
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.
Design/methodology/approach
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
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.
Practical implications
The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.
Originality/value
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.
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Lisa Schuster, Judy Drennan and Ian N. Lings
This study aims to employ the Model of Goal-Directed Behaviour (MGB) to examine the consumer acceptance of technology-based self-service (TBSS) for a credence service instrumental…
Abstract
Purpose
This study aims to employ the Model of Goal-Directed Behaviour (MGB) to examine the consumer acceptance of technology-based self-service (TBSS) for a credence service instrumental to a social goal. Credence services are increasingly delivered via self-service technology and in social marketing, the achievement of social goals can be contingent on consumer acceptance of these services. However, little is known about the determinants of acceptance and extant marketing literature fails to account for emotional and goal influences which are likely to be important.
Design/methodology/approach
The authors interviewed 30 young adults with self-reported stress, anxiety or depression as potential users of a self-help mental health service delivered via mobile phone. The data were analysed deductively and inductively with the assistance of NVivo.
Findings
The findings generally support using the MGB to enhance understanding of consumers' acceptance of TBSS. The paper also found evidence of the importance of maintenance self-efficacy, the self-evaluation of the ability to continue using the service, and a previously ignored element of consumer level competition that arises between alternatives that achieve the same goal.
Originality/value
This study is the first to examine factors that influence consumers' acceptance of TBSS for credence services aimed at achieving a social goal. It builds on understanding of consumer decision making in social marketing, particularly the influence of self-efficacy and competition. It also contributes to attitudinal research by providing initial evidence for deepening and broadening the MGB in the context of TBSSs.
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Lina Zhong, Xiaoya Zhang, Jia Rong, Hing Kai Chan, Jinyu Xiao and Haoyu Kong
Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using…
Abstract
Purpose
Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.
Design/methodology/approach
This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.
Findings
The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.
Practical implications
This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.
Originality/value
The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.
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The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and…
Abstract
Purpose
The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.
Design/methodology/approach
The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.
Findings
Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.
Practical implications
The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.
Originality/value
The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.
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This paper aims to create a conceptual model that connects learning organizations, service innovation and technology acceptance.
Abstract
Purpose
This paper aims to create a conceptual model that connects learning organizations, service innovation and technology acceptance.
Design/methodology/approach
The importance of the interaction of variables benefiting both individuals and organizations has been comprehensively explained by combining two well-known theories – learning organizational theory and service innovation theory – with the technology acceptance model. In the first part of the study, conceptual model has been constructed and then applied to the hospitality industry of which results have been presented in the second part of this paper.
Findings
It is hypothesized that learning organization, service innovation and technology acceptance have significant relationships. It is also suggested that the learning organization plays an intermediary role in the relationship between technology acceptance and service innovation. Empirical results in this regard have been presented in the second part of the paper.
Research limitations/implications
The relations have been established and tested in the hospitality industry in Antalya. However, the model can be applied and established relations tested in other industries.
Originality/value
This research contributes to our knowledge of the intricate linkages that exist between learning organizations, technology acceptance and service innovation. Originality of the paper is related to the novel multilayered model illustrating three-way interactions between the three dimensions of learning organization, technology acceptance and service innovation.
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Amy Wong and Jimmy Wong
This study aims to apply the service robot acceptance model (sRAM) to examine how attitude toward human–robot interaction (HRI) and engagement influence consumer acceptance of…
Abstract
Purpose
This study aims to apply the service robot acceptance model (sRAM) to examine how attitude toward human–robot interaction (HRI) and engagement influence consumer acceptance of service robots in a frontline setting.
Design/methodology/approach
Data was collected from 255 visitors who interacted with a robotic tour guide at a city museum. The data was analyzed using smart PLS 4.0.
Findings
The findings show the positive effects of subjective norms, appearance, perceived trust and positive emotion on both attitude toward HRI and engagement. In addition, social capability impacted attitude toward HRI, whereas perceived usefulness affected engagement.
Practical implications
To deliver engaging museum experiences that bring about positive word-of-mouth and intention to visit, managers need to incorporate the sRAM dimensions in the design and deployment of service robots.
Originality/value
This research uses field data to empirically validate the sRAM in the context of service robot acceptance. It introduces engagement as a novel mediating variable, enriching current understanding of human-like qualities in HRIs.
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Thabet Albastaki, Allam Hamdan, Yousif Albastaki and Ali Bakir
Consumers frequently use electronic payments (e-payment) as their first step into formal financial services. The advancement of information and communication technology, on the…
Abstract
Purpose
Consumers frequently use electronic payments (e-payment) as their first step into formal financial services. The advancement of information and communication technology, on the other hand, has resulted in several achievements for human civilization, altering people’s lives, behaviors and societal measures. This study’s main aim is to investigate issues and identify the factors that are likely to influence customers’ acceptance of implementing e-payment in the Kingdom of Bahrain.
Design/methodology/approach
A quantitative research approach was adopted to test the influence of e-payment data security, trust, ease of use, usefulness and accessibility on customers’ acceptance of the service. A questionnaire survey was electronically administered to a purposive sample, and 531 responses were returned, achieving the required sample size for the study. Descriptive statistics analysis was used to ascertain data validity and consistency, and regression analysis was used to test the model’s hypotheses.
Findings
The findings of this study demonstrated a high influence of the mentioned factors on the e-payment acceptance of the customers in the Kingdom of Bahrain. The main recommendations are to increase the adoption of e-payment; focus highly on the security factor in e-payment adoption; create a trustworthy e-payment service; strive to make the e-payment services more user-friendly; increase the longevity of the e-payment services by focusing on usefulness; and make e-payment services more accessible.
Originality/value
This study’s potential contribution is to identify the factors that influence e-payment acceptance by customers in Bahrain and draw attention to issues to be considered in adopting new e-payment services.
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Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service…
Abstract
Purpose
Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service efficiency but has certain risks, thus having a dual impact on the public. For a responsible and democratic government, it is necessary to fully understand the factors influencing public acceptance and their causal relationships to truly encourage the public to accept and use government ChatGPT-type services.
Design/methodology/approach
This study used the Latent Dirichlet allocation (LDA) model to analyze comment texts and summarize 15 factors that affect public acceptance. Multiple-related matrices were established using the grey decision-making trial and evaluation laboratory (grey-DEMATEL) method to reveal causal relationships among factors. From the two opposite extraction rules of result priority and cause priority, the authors obtained an antagonistic topological model with comprehensive influence values using the total adversarial interpretive structure model (TAISM).
Findings
Fifteen factors were categorized in terms of cause and effect, and the antagonistic topological model with comprehensive influence values was also analyzed. The analysis showed that perceived risk, trust and meeting demand were the three most critical factors of public acceptance. Meanwhile, perceived risk and trust directly affected public acceptance and were affected by other factors. Supervision and accountability had the highest driving power and acted as the causal factor to influence other factors.
Originality/value
This study identified the factors affecting public acceptance of integrating the ChatGPT-type model with government services. It analyzed the relationship between the factors to provide a reference for decision-makers. This study introduced TAISM to form the LDA-grey-DEMATEL-TAISM method to provide an analytical paradigm for studying similar influencing factors.
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Amelia Amelia, Christine Mathies and Paul G. Patterson
The purpose of this paper is to explore what drives customer acceptance of frontline service robots (FSR), as a result of their interaction experiences with FSR in the context of…
Abstract
Purpose
The purpose of this paper is to explore what drives customer acceptance of frontline service robots (FSR), as a result of their interaction experiences with FSR in the context of retail banking services.
Design/methodology/approach
Applications of the unified theory of acceptance and use of technology and service robot acceptance model frame the exploration of customers’ interaction experiences with physical FSR to explain acceptance. A thematic analysis of information obtained through observations, focus groups and participant interviews was applied to identify themes.
Findings
This study identifies 16 dimensions that group into five main themes that influence customer acceptance of FSR in retail banking services: (1) utilitarian aspect, (2) social interaction, (3) customer responses toward FSR, (4) customer perspectives of the company brand and (5) individual and task heterogeneity. Themes 1 and 2 are labeled confirmed themes based on existing theoretical frameworks used; themes 3–5 are additional themes.
Practical implications
This study provides actionable suggestions to allow managers to reflect on their strategy and consider ways to design and improve the delivery of services that involve FSR.
Originality/value
This study adds to our limited knowledge of how human-robot interaction research in robotics translates to a relatively new research area in frontline services and provides a step toward a comprehensive FSR acceptance model.
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Dan Huang, Qiurong Chen, Songshan (Sam) Huang and Xinyi Liu
Drawing on the cognitive–affective–conative framework, this study aims to develop a model of service robot acceptance in the hospitality sector by incorporating both cognitive…
Abstract
Purpose
Drawing on the cognitive–affective–conative framework, this study aims to develop a model of service robot acceptance in the hospitality sector by incorporating both cognitive evaluations and affective responses.
Design/methodology/approach
A mixed-method approach combining qualitative and quantitative methods was used to develop measurement and test research hypotheses.
Findings
The results show that five cognitive evaluations (i.e. cuteness, coolness, courtesy, utility and autonomy) significantly influence consumers’ positive affect, leading to customer acceptance intention. Four cognitive evaluations (cuteness, interactivity, courtesy and utility) significantly influence consumers’ negative affect, which in turn positively affects consumer acceptance intention.
Practical implications
This study provides significant implications for the design and implementation of service robots in the hospitality and tourism sector.
Originality/value
Different from traditional technology acceptance models, this study proposed a model based on the hierarchical relationships of cognition, affect and conation to enhance knowledge about human–robot interactions.
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