As intelligent agents become increasingly prevalent on online platforms, understanding how users perceive and respond to agent behavior is critical for effective system design. Although prior research has examined negotiation power primarily through explicit communication, comparatively little attention has been given to implicit power cues embedded in interaction design. This study introduces implicit power as a conceptual framework to explain how users infer power from an agent's behavior and appearance during negotiation. Agent anchors, concession strategies, avatar gender, and facial expressions are conceptualized as implicit power signals. Using a controlled human–agent negotiation experiment, the study empirically validates a structural model that integrates agent design cues with human individual differences. The findings demonstrate that implicit power significantly shapes negotiation outcomes and that the proposed model explains a substantial proportion of variance in user responses. This study provides both theoretical and practical implications for the design of intelligent interactive systems.
This study investigates the asymmetrical effects of information and communication technologies (ICTs) on women's self-employment in 33 sub-Saharan African countries. Based on data obtained from the World Bank for the period 1996–2022, a non-linear autoregressive distributed lag model was applied to achieve the research objective. Specifically, the mean group and pooled mean group estimators were used. Regarding short-run asymmetric responses, the results show that positive shocks to ICTs have a positive impact on women's self-employment. However, in the long run, positive ICT shocks exert a negative effect. From a policy perspective, interventions to improve ICT adoption among women in sub-Saharan African countries are crucial. This study is the first to examine the asymmetrical relationship between ICTs and women's self-employment.
As intelligent agents become increasingly prevalent on online platforms, understanding how users perceive and respond to agent behavior is critical for effective system design. Although prior research has examined negotiation power primarily through explicit communication, comparatively little attention has been given to implicit power cues embedded in interaction design. This study introduces implicit power as a conceptual framework to explain how users infer power from an agent's behavior and appearance during negotiation. Agent anchors, concession strategies, avatar gender, and facial expressions are conceptualized as implicit power signals. Using a controlled human-agent negotiation experiment, the study empirically validates a structural model that integrates agent design cues with human individual differences. The findings demonstrate that implicit power significantly shapes negotiation outcomes and that the proposed model explains a substantial proportion of variance in user responses. This study provides both theoretical and practical implications for the design of intelligent interactive systems.
This study explores how smart service innovation reshapes human-technology interaction in technology-enabled hospitality environments. As hotels adopt smart services, understanding how users perceive and interact with these technologies becomes essential. Using smart hospitality as the context, this research examines how service innovation influences user perceptions and behavioural continuity through technology acceptance mechanisms. A survey conducted in 2025 produced 410 valid responses, analysed with confirmatory factor analysis and structural equation modelling. Results show that service innovation enhances perceived usefulness and perceived ease of use, which shape user attitudes and continued engagement. The findings emphasize that interaction quality and user perception-rather than technology alone-determine smart service success. The study contributes to technology and human interaction research by explaining how smart service design influences user cognition, acceptance, and sustained use in digital service environments.
This study investigates the potential of generative artificial intelligence (AI) in enhancing institutionalized political participation willingness. By comparing public use scenarios of government service chatbots with and without the deployment of generative AI, the study examines whether generative AI can promote institutionalized political participation willingness among Chinese citizens. The researchers employed a model with political efficacy as a mediator and conducted a scenario-based experiment in Beijing. The results indicate that although the deployment of generative AI in government service chatbots increased institutionalized political participation willingness, it simultaneously reduced political efficacy. This reduction in political efficacy, however, led to a higher level of institutionalized political participation willingness.
The restaurant industry widely employs self-ordering kiosks (SOKs). However, the increased use of automation in restaurants is causing job displacement, raising concerns about the lack of sufficient human support in restaurants. The study examined variables influencing customer willingness to use SOKs while considering how staff replacement perceptions alter these effects. Partial least squares structural equation modeling reveals that performance expectancy, effort expectancy, social influence, and perceived security significantly influence behavioral intention to use SOKs, and behavioral intention strongly predicts actual kiosk usage behavior. Among the moderating effects, only perceived staff replacement likelihood significantly influences the relationship between perceived security and behavioral intention. Specifically, customers who believe SOKs are likely to replace human staff rely more heavily on the kiosk's perceived security when deciding whether to use them. Based on the findings, the study suggests effective strategies for employing SOKs to enhance customer usage.
The restaurant industry widely employs self-ordering kiosks (SOKs). However, the increased use of automation in restaurants is causing job displacement, raising concerns about the lack of sufficient human support in restaurants. The study examined variables influencing customer willingness to use SOKs while considering how staff replacement perceptions alter these effects. Partial least squares structural equation modeling reveals that performance expectancy, effort expectancy, social influence, and perceived security significantly influence behavioral intention to use SOKs, and behavioral intention strongly predicts actual kiosk usage behavior. Among the moderating effects, only perceived staff replacement likelihood significantly influences the relationship between perceived security and behavioral intention. Specifically, customers who believe SOKs are likely to replace human staff rely more heavily on the kiosk’s perceived security when deciding whether to use them. Based on the findings, the study suggests effective strategies for employing SOKs to enhance customer usage.
This study adapts an Abbreviated Technology Anxiety Scale (ATAS) into Arabic to serve as a measurement tool for assessing technology anxiety among native Arabic speakers. The adapted tool is called the Arabic-Abbreviated Technology Anxiety Scale (A-ATAS), which was psychometrically validated in this research. Using Google Maps as an example of a technology tool, a psychometric evaluation was conducted with 342 participants, assessing the validity and reliability of the A-ATAS tool. The results indicated that A-ATAS has an acceptable value of reliability with a Cronbach's alpha value of 0.866, in addition to acceptable values for both the scale-level content validity index (0.883), the face validity index (0.864) and factor analysis were also conducted. The findings indicated that abbreviated versions of the adapted A-ATAS suggested acceptable psychometrically evaluated properties for the abbreviated version of the adapted A-ATAS. The implications of these findings are substantial for both academic research and professional practice in software development and design.
Social networking sites have been seamlessly integrated into e-commerce technology, creating a novel model that is revolutionizing business operations. However, limited studies have explained how this integration affects consumer behaviors. This study developed a research model to investigate the impact of customers' perceptions of Instagram's social commerce design on their perceived trust, purchase intentions and subsequent purchasing behaviors, employing the task-technology fit (TTF), stimulus-organism-response, and motivation models. Cross-sectional data was collected from 393 Instagram social commerce users in Iran through an online survey. The findings of partial least squares structural equation modeling analysis revealed that perceived sociability, enjoyment, functionality, and and trust were found to significantly increase customers' purchase intention. In addition, customers' perceptions of the sociability, trust, and TTF of Instagram commerce significantly affect their purchasing behaviors.
This study adapts an Abbreviated Technology Anxiety Scale (ATAS) into Arabic to serve as a measurement tool for assessing technology anxiety among native Arabic speakers. The adapted tool is called the Arabic-Abbreviated Technology Anxiety Scale (A-ATAS), which was psychometrically validated in this research. Using Google Maps as an example of a technology tool, a psychometric evaluation was conducted with 342 participants, assessing the validity and reliability of the A-ATAS tool. The results indicated that A-ATAS has an acceptable value of reliability with a Cronbach’s alpha value of 0.866, in addition to acceptable values for both the scale-level content validity index (0.883), the face validity index (0.864) and factor analysis were also conducted. The findings indicated that abbreviated versions of the adapted A-ATAS suggested acceptable psychometrically evaluated properties for the abbreviated version of the adapted A-ATAS. The implications of these findings are substantial for both academic research and professional practice in software development and design.
Social networking sites have been seamlessly integrated into e-commerce technology, creating a novel model that is revolutionizing business operations. However, limited studies have explained how this integration affects consumer behaviors. This study developed a research model to investigate the impact of customers’ perceptions of Instagram’s social commerce design on their perceived trust, purchase intentions and subsequent purchasing behaviors, employing the task–technology fit (TTF), stimulus–organism–response, and motivation models. Cross-sectional data was collected from 393 Instagram social commerce users in Iran through an online survey. The findings of partial least squares structural equation modeling analysis revealed that perceived sociability, enjoyment, functionality, and TTF significantly enhance customers’ perceived trust. Perceived sociability, enjoyment, functionality, and trust were found to significantly increase customers’ purchase intention. In addition, customers’ perceptions of the sociability, trust, and TTF of Instagram commerce significantly affect their purchasing behaviors.
This bibliometric analysis of 239 articles from 2016 to 2025 maps the trends, gaps, and challenges of generative artificial intelligence (GenAI) in English-as-a-foreign-language education. Since 2024, research has surged due to technological progress and student-centered learning trends. Asian countries, notably China, lead in output, driven by high English proficiency demands and proactive technology integration. Leading journals such as Education and Information Technologies, System, and Computer Assisted Language Learning dominate the scholarly landscape. Research themes highlight GenAI tools' effectiveness in language acquisition, while challenges such as academic integrity and the digital divide persist. Scholars advocate for teacher training in technology use and ethics. Future research should explore GenAI's role in cross-cultural interactions, marginalized engagement, and long-term impacts and acceptance among teachers and students. Promoting collaboration, ethical use, and pedagogical innovation would enhance GenAI's potential to meet the evolving needs of English-as-a-foreign-language learners.
This qualitative study explores the effect of artificial intelligence (AI)-managed sleep pods on passenger stress and satisfaction in Chinese airports. Thirty interviews at Xi'an International Airport revealed that personalization, comfort, and privacy were significant qualities to possess. The findings indicate decreased stress, increased well-being, and the crucial role of cultural acceptance and trust in technology. Hence, a theoretical model generated by grounded theory plays the role of linking AI personalization to well-being, implying valuable knowledge for airport operators and AI-service designers. This study highlights the potential for AI to create personalized, stress-reducing environments, potentially offering practical solutions to enhance airport hospitality.
Despite being available for over two decades, the acceptance of Smart Home Technology (SHT) remains slower than anticipated, with technophobia acting as a significant barrier. This study integrates the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT) to investigate how psychological and cultural factors influence SHT acceptance. A mediation analysis involving English (N = 284) and Spanish (N = 230) participants assessed whether technophobia, perceived ease of use, and perceived usefulness mediate the relationship between the frustration of psychological needs and behavioural intention. The findings suggest indirect effects through technophobia and usability factors, with Spanish participants reporting greater frustration yet a higher intention to adopt. These results underscore the need for culturally tailored interventions, such as localised education and improved usability, to enhance confidence and support broader SHT adoption.
Metaverse education is one of the most promising applications of the web and information technology and one of the newest applications of the metaverse. Considering that the metaverse is a virtual and real internet application and social structure created by integrating cutting-edge technologies, whether technology can be adapted to the task is one of the critical factors for the sustainable development of the platform. This study adopted the task-technology fit theory (TTF) to investigate the use of metaverse education. The results showed that both personalized learning and incarnational interactivity significantly affect TTF and actual use, and TTF significantly affects user satisfaction and continues to affect final performances. This study enriches the empirical research on metaverse education and provides a new entry point for subsequent research.
This bibliometric analysis of 239 articles from 2016 to 2025 maps the trends, gaps, and challenges of generative artificial intelligence (GenAI) in English-as-a-foreign-language education. Since 2024, research has surged due to technological progress and student-centered learning trends. Asian countries, notably China, lead in output, driven by high English proficiency demands and proactive technology integration. Leading journals such as Education and Information Technologies, System, and Computer Assisted Language Learning dominate the scholarly landscape. Research themes highlight GenAI tools' effectiveness in language acquisition, while challenges such as academic integrity and the digital divide persist. Scholars advocate for teacher training in technology use and ethics. Future research should explore GenAI's role in cross-cultural interactions, marginalized engagement, and long-term impacts and acceptance among teachers and students. Promoting collaboration, ethical use, and pedagogical innovation would enhance GenAI's potential to meet the evolving needs of English-as-a-foreign-language learners.
This qualitative study explores the effect of artificial intelligence (AI)-managed sleep pods on passenger stress and satisfaction in Chinese airports. Thirty interviews at Xi'an International Airport revealed that personalization, comfort, and privacy were significant qualities to possess. The findings indicate decreased stress, increased well-being, and the crucial role of cultural acceptance and trust in technology. Hence, a theoretical model generated by grounded theory plays the role of linking AI personalization to well-being, implying valuable knowledge for airport operators and AI-service designers. This study highlights the potential for AI to create personalized, stress-reducing environments, potentially offering practical solutions to enhance airport hospitality.
Being overweight or obese raises the chances of developing a number of illnesses. Maintaining a healthy weight can help avoid these health problems, halt their progression, or resolve them. A variety of intervention strategies and digital tools have been implemented for obesity prevention. However, these strategies and tools often are not designed in consideration of the end users' needs and preferences. To overcome this limitation, the study proposes an integrated participatory design process based on the design thinking and user-centered design methods, which involves end-users and the wider community in a synergistic dialogue. This dialogue can help define intervention strategies and technological tools for obesity prevention.
Despite being available for over two decades, the acceptance of Smart Home Technology (SHT) remains slower than anticipated, with technophobia acting as a significant barrier. This study integrates the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT) to investigate how psychological and cultural factors influence SHT acceptance. A mediation analysis involving English (N = 284) and Spanish (N = 230) participants assessed whether technophobia, perceived ease of use, and perceived usefulness mediate the relationship between the frustration of psychological needs and behavioural intention. The findings suggest indirect effects through technophobia and usability factors, with Spanish participants reporting greater frustration yet a higher intention to adopt. These results underscore the need for culturally tailored interventions, such as localised education and improved usability, to enhance confidence and support broader SHT adoption.
In this paper, the authors examined the structure and relationship between followers and leaders in Twitter followership to find similarities in personality. Specifically, they focused on the relationships between Twitter (now X) influencers and their followers through an extensive analysis of millions of tweets using IBM Watson Personality Insights. The results are founded on the relationships between two major social media influencers and their respective followers. The present research informs marketing practitioners on using IBM Watson to find congruence between social media influencers and followers for the most effective and compelling marketing strategies to sell products.
