Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/302512 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
24th Biennial Conference of the International Telecommunications Society (ITS): "New bottles for new wine: digital transformation demands new policies and strategies", Seoul, Korea, 23-26 June, 2024
Verlag: 
International Telecommunications Society (ITS), Calgary
Zusammenfassung: 
In the digital age, users in China are increasingly inclined to adopt taskoriented chatbots for task-driven work. This study, based on the Task Technology Fit model combined with the UTAUT model, collected 700 valid questionnaires. It employed Amos 24.0 for descriptive statistical analysis, reliability and validity testing, and correlation analysis of the collected data. The Harman single-factor test method was used to examine common method bias, and the Bootstrap method and simple slope analysis method were applied to verify hypotheses. SPSS 28.0 was used for multiple linear regression analysis and mediation effect analysis to test hypotheses. The study empirically investigated the factors influencing users' behavior in using task-oriented chatbots in China, focusing on seven impact factors: two dependent variables of AI communication anthropomorphism and interactivity, one independent variable of behavior, two mediating variables of performance expectancy and usage intention, and three moderating variables of task characteristics, technology characteristics, and task-technology fit. The results indicate that the factors of AI anthropomorphism and interactivity have a significant impact on the residents of the Yangtze River Delta region using task-driven Chatbots for task-driven work. Moreover, through the mediating effects and moderating roles of other variables, a complex networked structure is formed. The adaptability of technology and the individual's willingness to use it in varying scenarios together constitute the influencing factors of behavior.
Schlagwörter: 
Task-Driven chatbots
User Behavior
Influencing Factors
TTF Model
UTAUT Model
Dokumentart: 
Conference Paper

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