Worker Displacement by Artificial Intelligence (AI): The Impact of Boundary-Spanning Employees

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Limited literature examines the impact of the displacement of boundary-spanning employees artificial intelligence (AI). Scholars and practitioners appear focused on tangible benefits of AI adoption, and do not seem concerned by any less tangible and possibly untoward implications of worker (particularly boundary-spanning worker) displacement. My dissertation addresses this gap in the literature. In Essay 1, a qualitative study is performed to anchor the research on the appropriate ethnographic setting, the firms where this displacement phenomenon is taking place, by utilizing the Straussian grounded theory approach. The outcome of iterative coding of the first order data collected from the interviews and … continued below

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Ekezie, Uchenna P. May 2023.

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This dissertation is part of the collection entitled: UNT Theses and Dissertations and was provided by the UNT Libraries to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 34 times. More information about this dissertation can be viewed below.

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  • Ekezie, Uchenna P.

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Limited literature examines the impact of the displacement of boundary-spanning employees artificial intelligence (AI). Scholars and practitioners appear focused on tangible benefits of AI adoption, and do not seem concerned by any less tangible and possibly untoward implications of worker (particularly boundary-spanning worker) displacement. My dissertation addresses this gap in the literature. In Essay 1, a qualitative study is performed to anchor the research on the appropriate ethnographic setting, the firms where this displacement phenomenon is taking place, by utilizing the Straussian grounded theory approach. The outcome of iterative coding of the first order data collected from the interviews and content analysis is a conceptual framework which amongst other findings shows how the unique competences of boundary-spanning employees and those of AI are best suited for different spectra of interorganizational collaborative activities. In Essays 2 and 3, I investigate major themes that emerged from Essay 1 utilizing quantitative and qualitative research methods in both studies. Initially I test research models using structural equation modelling on practitioner survey data, after which I probe further via focused interviews to better understand the survey results. The two papers allow us to put forth several theoretical and managerial contributions, specifically emphasizing the positive essential role of boundary-spanning employees on supply chain agility and innovation, even as AI displaces workers. These contributions provide insight into the optimal balance of human and artificial intelligence for today's highly dynamic marketplace.

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  • May 2023

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  • July 8, 2023, 11:42 p.m.

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  • Dec. 8, 2023, 5:10 p.m.

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Ekezie, Uchenna P. Worker Displacement by Artificial Intelligence (AI): The Impact of Boundary-Spanning Employees, dissertation, May 2023; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc2137652/: accessed May 26, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .

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