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Mechanisms of cognitive trust development in artificial intelligence among front line employees: An empirical examination from a developing economy

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  • Shamim, Saqib
  • Yang, Yumei
  • Ul Zia, Najam
  • Khan, Zaheer
  • Shariq, Syed Muhammad

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.

Suggested Citation

  • Shamim, Saqib & Yang, Yumei & Ul Zia, Najam & Khan, Zaheer & Shariq, Syed Muhammad, 2023. "Mechanisms of cognitive trust development in artificial intelligence among front line employees: An empirical examination from a developing economy," Journal of Business Research, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:jbrese:v:167:y:2023:i:c:s0148296323005271
    DOI: 10.1016/j.jbusres.2023.114168
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    References listed on IDEAS

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    1. Khan, Zaheer & Lew, Yong Kyu & Marinova, Svetla, 2019. "Exploitative and exploratory innovations in emerging economies: The role of realized absorptive capacity and learning intent," International Business Review, Elsevier, vol. 28(3), pages 499-512.
    2. Zeng, Jing, 2022. "Orchestrating ecosystem resources in a different country: Understanding the integrative capabilities of sharing economy platform multinational corporations," Journal of World Business, Elsevier, vol. 57(6).
    3. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    4. Hsiao-Lan Wei & Eric T G Wang & Pei-Hung Ju, 2005. "Understanding misalignment and cascading change of ERP implementation: a stage view of process analysis," European Journal of Information Systems, Taylor & Francis Journals, vol. 14(4), pages 324-334, December.
    5. Huimin Gu & Tingting (Christina) Zhang & Can Lu & Xiaoxiao Song, 2021. "Assessing Trust and Risk Perceptions in the Sharing Economy: An Empirical Study," Journal of Management Studies, Wiley Blackwell, vol. 58(4), pages 1002-1032, June.
    6. Abraham, Rene & Schneider, Johannes & vom Brocke, Jan, 2019. "Data governance: A conceptual framework, structured review, and research agenda," International Journal of Information Management, Elsevier, vol. 49(C), pages 424-438.
    7. Canhoto, Ana Isabel & Clear, Fintan, 2020. "Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential," Business Horizons, Elsevier, vol. 63(2), pages 183-193.
    8. Hengstler, Monika & Enkel, Ellen & Duelli, Selina, 2016. "Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 105-120.
    9. Yang, Yumei & Secchi, Davide & Homberg, Fabian, 2018. "Are organisational defensive routines harmful to the relationship between personality and organisational learning?," Journal of Business Research, Elsevier, vol. 85(C), pages 155-164.
    10. Sven Laumer & Christian Maier & Andreas Eckhardt & Tim Weitzel, 2016. "Work routines as an object of resistance during information systems implementations: theoretical foundation and empirical evidence," European Journal of Information Systems, Taylor & Francis Journals, vol. 25(4), pages 317-343, July.
    11. Johnson, Devon & Grayson, Kent, 2005. "Cognitive and affective trust in service relationships," Journal of Business Research, Elsevier, vol. 58(4), pages 500-507, April.
    12. Martha S. Feldman, 2000. "Organizational Routines as a Source of Continuous Change," Organization Science, INFORMS, vol. 11(6), pages 611-629, December.
    13. Braganza, Ashley & Chen, Weifeng & Canhoto, Ana & Sap, Serap, 2021. "Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust," Journal of Business Research, Elsevier, vol. 131(C), pages 485-494.
    14. Siew Kien Sia & Christina Soh, 2007. "An assessment of package–organisation misalignment: institutional and ontological structures," European Journal of Information Systems, Taylor & Francis Journals, vol. 16(5), pages 568-583, October.
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