Artificial intelligence and all AI-based tools have recently become a crucial part of everyday life both for individual users and businesses. Yet, with it have come the doubts and distrust toward AI, as well as the lack of awareness of the ways of using this tool. Inspired by the scale of research dedicated to the use of Technology Acceptance Models like TAM or UTAUT2, the authors have developed the Technology Readiness Index—Environment-Organization-Use (TRIEOUS) framework to measure the usage and adoption of generative AI, specifically for micro-enterprises. This paper presents the content of this framework and the procedure of validation of the framework with the help of EFA and CFA analysis methods. Results of the statistical validation, based on the pilot testing data, show that the TRIEOUS framework, combining TAM, TOE, and TRI models, in its current format, does not sufficiently match the phenomena it is supposed to analyze. Modifications of the framework, beginning with the decrease in the number of analyzed items, are required.

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Generative AI Adoption and Use by Micro-enterprises: Validation of the Measurement Instrument

  • Artur Strzelecki,
  • Małgorzata Pańkowska,
  • Mariia Rizun

摘要

Artificial intelligence and all AI-based tools have recently become a crucial part of everyday life both for individual users and businesses. Yet, with it have come the doubts and distrust toward AI, as well as the lack of awareness of the ways of using this tool. Inspired by the scale of research dedicated to the use of Technology Acceptance Models like TAM or UTAUT2, the authors have developed the Technology Readiness Index—Environment-Organization-Use (TRIEOUS) framework to measure the usage and adoption of generative AI, specifically for micro-enterprises. This paper presents the content of this framework and the procedure of validation of the framework with the help of EFA and CFA analysis methods. Results of the statistical validation, based on the pilot testing data, show that the TRIEOUS framework, combining TAM, TOE, and TRI models, in its current format, does not sufficiently match the phenomena it is supposed to analyze. Modifications of the framework, beginning with the decrease in the number of analyzed items, are required.