可用性
感知
技术接受模型
价值(数学)
过程(计算)
知识管理
生成模型
生成语法
营销
结果(博弈论)
质量(理念)
心理学
业务
计算机科学
人工智能
经济
人机交互
哲学
数理经济学
认识论
神经科学
机器学习
操作系统
作者
Varun Gupta,Hongji Yang
标识
DOI:10.1080/10875301.2023.2300114
摘要
This article presents an extensive Generative AI Technology Adoption Model intended to elucidate the complex process that entrepreneurs and other innovation ecosystem actors, for instance, libraries, go through for its adoption. The model suggests that the adoption process happens in three stages: Pre-Perception & Perception, Assessment, and Outcome. During the Pre-Perception & Perception Phase, entrepreneurs initiate their technology exploration by navigating social factors, domain experience, technological familiarity, system quality, training and support, interaction convenience, and anthropomorphism; with utilitarian value and hedonic values playing an important role. As they transition to the Assessment Stage, perceived usefulness, ease of use, and a novel addition, perceived enjoyment, shape their evaluations, leading to generations of emotions toward it, with utilitarian value overweighting hedonic values. The model finishes with the Outcome Stage, where emotions developed in the Assessment Stage become tangible intentions to switch (use technology or switch to human services). The adoption model highlights the adoption factors (also called latent variables) and their relationships grounded on researcher's professional experiences and need to be further empirically validated. Entrepreneurial implications highlight the strategic insights of the model, providing a decision-making roadmap and highlighting the interaction between utilitarian and hedonistic values. Entrepreneurs can create well-informed technological integrations that are in line with business objectives by using the incremental decision-making process. The model's focus on comparative evaluations gives entrepreneurs the ability to strategically map the usability of technology for the best possible commercial results. The Generative AI Technology Adoption Model offers a nuanced understanding of entrepreneurs' technology adoption processes, which is also applicable to other actors in the innovation ecosystem.
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