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<p>Consumer perceptions and purchasing decision-making have been significantly impacted by the rapid use of artificial intelligence (AI) in the online retail sector. The online shopping experience has been transformed by AI technologies, which include sophisticated product evaluation algorithms, individualized purchasing recommendations, and improved customer care. To better understand the deep interactions between factors linked to artificial intelligence and customer decision-making processes, this study investigates the complex adoption landscape of AI within the Delhi-NCR online retail industry using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework. The research employs a quantitative methodology by applying Structural Equation Modelling (SEM) through SmartPLS 4 to evaluate key behavioral variables. The results reveal that Behavioral Intention (BI) has a strong and significant impact on Usage Behavior (UB). Trust in AI systems emerged as a critical factor affecting BI. Significant factors like Habit, Hedonic Motivation, Trust, and Personal Innovativeness emerged as pivotal in shaping consumers’ Behavioral Intentions towards AI in online shopping. Perceived Risk showed a marginally negative effect on BI, suggesting consumers’ hesitation in adopting AI for online shopping. However, factors such as Social Influence and Effort Expectancy had negligible impacts on BI, contrasting with prior research. These findings suggest that consumer trust, delight, and habitual AI usage are more influential than usability or social pressures for AI enabled e-commerce landscape.</p>

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Analyzing the impact of artificial intelligence on the online purchase decision-making process through the lens of the UTAUT 2 model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月23日

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  • Rinku Sharma Dixit,
  • Shailee Lohmor Choudhary,
  • Nikhil Govil

摘要

Consumer perceptions and purchasing decision-making have been significantly impacted by the rapid use of artificial intelligence (AI) in the online retail sector. The online shopping experience has been transformed by AI technologies, which include sophisticated product evaluation algorithms, individualized purchasing recommendations, and improved customer care. To better understand the deep interactions between factors linked to artificial intelligence and customer decision-making processes, this study investigates the complex adoption landscape of AI within the Delhi-NCR online retail industry using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework. The research employs a quantitative methodology by applying Structural Equation Modelling (SEM) through SmartPLS 4 to evaluate key behavioral variables. The results reveal that Behavioral Intention (BI) has a strong and significant impact on Usage Behavior (UB). Trust in AI systems emerged as a critical factor affecting BI. Significant factors like Habit, Hedonic Motivation, Trust, and Personal Innovativeness emerged as pivotal in shaping consumers’ Behavioral Intentions towards AI in online shopping. Perceived Risk showed a marginally negative effect on BI, suggesting consumers’ hesitation in adopting AI for online shopping. However, factors such as Social Influence and Effort Expectancy had negligible impacts on BI, contrasting with prior research. These findings suggest that consumer trust, delight, and habitual AI usage are more influential than usability or social pressures for AI enabled e-commerce landscape.