FORMULATING AN EXPANDED UTAUT2 MODEL TO INVESTIGATE DETERMINANTS IMPACT ON CONSUMER ADOPTION OF ARTIFICIAL INTELLIGENCE

This research aims to enhance the adoption of AI in Pakistan to increase their work performance. The researcher expands the UTAUT2 model with perceived trust in this current research. In methodology, the researcher used a non-probability sampling method for data collection, and the unit of analysis was the user of Artificial Intelligence devices. This research used a survey method and data were collected through the online Google form. The sample size was 357, for data analysistwo software were used first one is SPSS and Smart-Pls, structural equational model (SEM). SEM is used for measurement and structural modeling. The measurement model was used for validity and reliability, and the structural model was used for testing the hypotheses. The finding of this research is that all factors like performance expectancy, effort expectancy, facilitating condition, hedonic motivation, perceived trust, and behavioral intention play a major role in adopting artificial intelligence. The originality of this research conducted in Pakistan expands the utaut2 model with perceived trust. The primary objective is to gain valuable insight into organizations, specifically consumer adoption of AI. This study is conducted on the comprehension of consumer behavior to spare the adoption of AI.Keywords: Performance expectancy, effort expectancy, Hedonic motivation, Adoption, Artificial intelligence, perceived trust

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-30
DOI
https://doi.org/10.5281/zenodo.14629320
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

FORMULATING AN EXPANDED UTAUT2 MODEL TO INVESTIGATE DETERMINANTS IMPACT ON CONSUMER ADOPTION OF ARTIFICIAL INTELLIGENCE

Zenodo (CERN European Organization for Nuclear Research)
Technology Adoption and User Behaviour
article

FORMULATING AN EXPANDED UTAUT2 MODEL TO INVESTIGATE DETERMINANTS IMPACT ON CONSUMER ADOPTION OF ARTIFICIAL INTELLIGENCE

article en

Abstract

This research aims to enhance the adoption of AI in Pakistan to increase their work performance. The researcher expands the UTAUT2 model with perceived trust in this current research. In methodology, the researcher used a non-probability sampling method for data collection, and the unit of analysis was the user of Artificial Intelligence devices. This research used a survey method and data were collected through the online Google form. The sample size was 357, for data analysistwo software were used first one is SPSS and Smart-Pls, structural equational model (SEM). SEM is used for measurement and structural modeling. The measurement model was used for validity and reliability, and the structural model was used for testing the hypotheses. The finding of this research is that all factors like performance expectancy, effort expectancy, facilitating condition, hedonic motivation, perceived trust, and behavioral intention play a major role in adopting artificial intelligence. The originality of this research conducted in Pakistan expands the utaut2 model with perceived trust. The primary objective is to gain valuable insight into organizations, specifically consumer adoption of AI. This study is conducted on the comprehension of consumer behavior to spare the adoption of AI.Keywords: Performance expectancy, effort expectancy, Hedonic motivation, Adoption, Artificial intelligence, perceived trust

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 40%
Technology Adoption and User Behaviour
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