Determinants of ChatGPT Adoption in Academe & Other Fields – A Review on Theoretical Perspective

Abstract

ChatGPT has been showing promising advantages including its capability to optimize work and converse like human being. In the academe, ChatGPT was seen to have the capability to answer formative assessments, aid in research, and act as virtual tutor. However, ChatGPT is also being criticized for its misleading and inaccurate responses. This led the scientific community to further study its adoption factors. This review discussed and analyzed 53 empirical studies that aimed to determine the factors influencing ChatGPT adoption and use in the academe and other fields. Performance expectancy, personal innovativeness, trust, attitude, and self-efficacy were identified as common determinants of ChatGPT adoption in various fields. To add, experience and presence of Generative Al policy also determine ChatGPT adoption. Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT/UTUAT2) are the most widely used frameworks found in this review. Practically, this review recommends that ChatGPT adoption and use be further studied in educational sector focusing on the contrasting results of significant factors found. Policy on how academic institutions will adopt and use ChatGPT is also highly recommended. With respect to other areas, studies on ChatGPT adoption and use in other economic institutions (healthcare, business, law, software development, dentistry, etc.) are recommended. Theoretically, this review recommends use of TAM and UTUAT/UTUAT2 in future studies of ChatGPT adoption considering personal innovativeness, trust, and self-efficacy as extension constructs and focusing on experience and policy as moderating constructs.

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