The quick development of artificial intelligence has contributed to the use of chatbots as alternative methods for collecting information within organizations. However, empirical studies that combine technology acceptance and system success perspectives to clarify chatbot usage remain lacking. This study analyzes the adoption of chatbots as information search engines by integrating the Technology Acceptance Model (TAM) and the DeLone and McLean Information Systems Success Model (ISSM) through a quantitative approach involving the distribution of questionnaires to 400 employees who have experience interacting with chatbots. The research model includes Information Quality, System Quality, Service Quality, Perceived Ease of Use, Perceived Usefulness, Intention to Use, and Actual Use, and the data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results indicate that System Quality and Service Quality substantially impact Perceived Ease of Use and Perceived Usefulness. Perceived Ease of Use significantly influences Perceived Usefulness, which eventually impacts Intention to Use and Actual Use. However, Information Quality doesn't significantly impact Perceived Ease of Use or Perceived Usefulness. These results provide theoretical and practical insights for improving chatbot adoption for employees.
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