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A Multianalytical SEM-ANN Approach to Investigate the Social Sustainability of AI Chatbots Based on Cybersecurity and Protection Motivation Theory

持续性 计算机安全 计算机科学 业务 工程类 知识管理 生态学 生物
作者
İbrahim Arpacı
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:71: 1714-1725 被引量:17
标识
DOI:10.1109/tem.2023.3339578
摘要

With a primary focus on cybersecurity risks, this study endeavors to explore the sustainable deployment of artificial intelligence (AI) chatbots and, ultimately, to promote their social sustainability. The study introduces an enhanced model built upon the "Protection Motivation Theory" (PMT) to explore the factors that predict the social sustainability of AI chatbots. The proposed model is evaluated using both "structural equation modeling" and "artificial neural network" (ANN) analyses, leveraging data obtained from 1741 participants. The findings reveal that PMT factors significantly predict the sustainable use of AI chatbots. Moreover, cybersecurity concerns, including confidentiality and privacy, have emerged as significant predictors of sustainable use, impacting the social sustainability of AI chatbots. The indicated paths in the model explain 70% and 74% of the variance in sustainable use and social sustainability, respectively. The results from the ANN analysis also emphasize the critical role of confidentiality as the primary predictor. The significance of this study lies in the development of a unified model that integrates cybersecurity and PMT, offering a distinctive framework. In addition to its theoretical contributions, the study offers practical insights for service providers, application developers, and decision-makers in the field, thereby influencing the future of AI chatbots.
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