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Title: | Mechanisms of cognitive trust development in artificial intelligence among front line employees: An empirical examination from a developing economy | ||||||||||
Author: | Shamim, Saqib; Yang, Yumei; Zia, Najam Ul; Khan, Zaheer; Shariq, Syed Muhammad | ||||||||||
Document type: | Peer-reviewed article (English) | ||||||||||
Source document: | Journal of Business Research. 2023, vol. 167 | ||||||||||
ISSN: | 0148-2963 (Sherpa/RoMEO, JCR) | ||||||||||
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DOI: | https://doi.org/10.1016/j.jbusres.2023.114168 | ||||||||||
Abstract: | Drawing upon insights from the trust literature, we conducted two empirical surveys with the front-line employees of firms in Pakistan investigating the factors influencing cognitive trust in artificial intelligence (AI). Study1 consisted of 46 in-depth interviews aimed at exploring factors influencing cognitive trust. Based on the findings of Study 1, we developed a framework to enhance employees’ cognitive trust in AI. We then conducted a quantitative survey (study 2) with 314 employees to validate the proposed model. The findings suggest that AI features positively influence the cognitive trust of employees, while work routine disruptions have negative impact on cognitive trust in AI. The effectiveness of data governance was also found to facilitate employees' trust in data governance and subsequently, employees' cognitive trust in AI. We contribute to the technology trust literature, especial in developing economics. We discuss the implications of our findings for both research and practice. | ||||||||||
Full text: | https://www.sciencedirect.com/science/article/pii/S0148296323005271 | ||||||||||
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