Science China Information Sciences, Год журнала: 2025, Номер 68(2)
Опубликована: Янв. 17, 2025
Язык: Английский
International Journal of Information Management, Год журнала: 2022, Номер 69, С. 102568 - 102568
Опубликована: Авг. 29, 2022
There is an exponential growth of the use AI applications in organisations. Due to machine learning capability artificial intelligence (AI) applications, it critical that such systems are used continuously order generate rich data allow them learn, evolve and mature into a better fit for their user organisational context. This research focuses on actual conversational AI, particular chatbot, as one type workplace application answer question: how do employees experience chatbot day-to-day work? Through qualitative case study large international organisation by performing inductive analysis, uncovers different ways which users appropriate identifies two key dimensions determine use: dominant mode interaction understanding technology. Based these dimensions, taxonomy presented, classifies chatbots four types: early quitters, pragmatics, progressives, persistents. The findings contribute particularly chatbots, organisations pave way further this regard. implications practice also discussed.
Язык: Английский
Процитировано
85
Journal of Retailing and Consumer Services, Год журнала: 2023, Номер 75, С. 103456 - 103456
Опубликована: Июнь 15, 2023
Язык: Английский
Процитировано
79
Psychology and Marketing, Год журнала: 2023, Номер 40(7), С. 1372 - 1387
Опубликована: Март 24, 2023
Abstract The present research focuses on the interplay between two common features of customer service chatbot experience: gaze direction and anthropomorphism. Although dominant approach in marketing theory practice is to make chatbots as human‐like possible, current study, built humanness‐value‐loyalty model, addresses chain effects through which chatbots' nonverbal behaviors affect customers' willingness disclose personal information purchase intentions. By means experiments that adopt a real simulated shopping environment (i.e., car rental travel insurance), work allows us understand how reduce individuals' tendency see conversational agents less knowledgeable empathetic compared with humans. results show warmth perceptions are affected by direction, whereas competence Warmth found be key drivers consumers’ skepticism toward chatbot, which, turn, affects trust provider hosting ultimately leading consumers more willing their repatronize e‐tailer future. Building Theory Mind, our perceiving from makes individuals skeptical long they feel good at detecting others’ ultimate
Язык: Английский
Процитировано
78
Computers & Education, Год журнала: 2023, Номер 203, С. 104862 - 104862
Опубликована: Июнь 7, 2023
Язык: Английский
Процитировано
74
Technological Forecasting and Social Change, Год журнала: 2023, Номер 193, С. 122634 - 122634
Опубликована: Май 20, 2023
The social companionship (SC) feature in conversational agents (CAs) enables the emotional bond and consumer relationships. heightened interest SC with CAs led to exponential growth publications scattered across disciplines fragmented findings, thus limiting holistic understanding of domain warrants a macroscopic view guide future research directions. present study fills void by offering comprehensive literature review entailing science performance intellectual structure mapping. revealed domain's major theories, constructs, thematic structure. Thematic content analysis resulted conceptual framework encompassing antecedents, mediators, moderators, consequences CAs. discusses directions guiding practitioners academicians designing efficient ethical AI companions.
Язык: Английский
Процитировано
72
Psychology and Marketing, Год журнала: 2023, Номер 40(8), С. 1593 - 1614
Опубликована: Июнь 2, 2023
Abstract Recent advancements in artificial intelligence (AI) and the emergence of AI‐based social applications market have propelled research on possibility consumers developing relationships with AI. Motivated by diversity approaches inconsistent findings this emerging stream, systematic literature review analyzes 37 peer‐reviewed empirical studies focusing human–AI published between 2018 2023. We identify three major theoretical domains (social psychology, communication media studies, human–machine interactions) as foundations for conceptual development, detail theories used reviewed papers. Given radically new nature AI innovation, we recommend a novel approach that would synergistically utilize cross‐disciplinary literature. Analysis methodology indicates quantitative dominate while qualitative, longitudinal, mixed‐method are infrequently. Examination models variables suggests need to reconceptualize factors processes relationship, such agency, autonomy, authenticity, reciprocity, empathy, better correspond context. Based our analysis, propose an integrative framework offer directions future incorporate develop comprehensive theory human ‐ relationships, explore nomological networks its key constructs, implement methodological variety triangulation.
Язык: Английский
Процитировано
65
Education and Information Technologies, Год журнала: 2023, Номер 29(5), С. 6357 - 6382
Опубликована: Авг. 3, 2023
Язык: Английский
Процитировано
62
Information, Год журнала: 2024, Номер 15(1), С. 33 - 33
Опубликована: Янв. 8, 2024
Artificial intelligence has been attracting the attention of educational researchers recently, especially ChatGPT as a generative artificial tool. The context could impact different aspects students’ learning, such motivational aspect. present research intended to investigate characteristics task motivation in context, specifically context. interviewed 15 students about their experiences with collect data. used inductive and deductive content analysis when learning ChatGPT. To arrive at categories sub-categories motivation, MAXQDA 2022. Five main emerged: enjoyment, reported effort, result assessment, perceived relevance, interaction. Each category comprised least two sub-categories, each sub-category was further organized into codes. results indicated more positive than negative ones. previous be due conversational or social aspect chatbot, enabling relationships humans maintenance good quality conversations them. We conclude that AI utilized settings promote learn thus raise achievement.
Язык: Английский
Процитировано
53
International Journal of Information Management, Год журнала: 2023, Номер 76, С. 102679 - 102679
Опубликована: Июль 11, 2023
Leveraging the computers are social actors theory, in this study, we explore traits of artificial intelligence-based chatbots that make them perceived as trustworthy, drive consumers to forgive firm for service failure, and reduce their propensity spread negative word-of-mouth against firm. Across two scenario-based studies with UK consumers: one a utilitarian product category (n = 586) another hedonic 508), qualitative our findings suggest safety enhances consumers' ability empathy, anthropomorphism benevolence integrity chatbots, i.e., three affect components trustworthiness differently. Further, these have positive influence on customer forgiveness word-of-mouth.
Язык: Английский
Процитировано
48
Behaviour and Information Technology, Год журнала: 2024, Номер unknown, С. 1 - 22
Опубликована: Фев. 16, 2024
The present research aims to highlight the underlying factors that drive students' adoption of ChatGPT chatbot in higher education. This study extends meta-UTAUT framework by including additional exogenous anthropomorphism, trust, design novelty, and institutional policy. Empirical examination with Structural Equation Modelling among 355 students Dutch education institutions revealed attitude behavioural intention as significant positive predictors use behaviour. Institutional policy negatively moderated effect on Behavioural was significantly positively influenced attitude, performance expectancy, social influence, facilitating conditions. Anthropomorphism, effort expectancy were unveiled antecedents attitude. central theoretical contributions this include investigating behaviour instead intention, establishing a core construct, underlining highlighting importance contributes prior technology adoption, especially area artificial intelligence findings yield valuable insights for designers, product managers, writers.
Язык: Английский
Процитировано
48