Utilizing People, Analytics, and AI for Decision Making in the Digitalized Retail Supply Chain

Keywords

digitalization, human–AI collaboration, supply chain management

Abstract

Our research reveals the continued and evolving role of the human factor in decision making in digitalized retail supply chains. We compare managerial roles in a pre- and post-COVID era through conducting in-depth interviews of 25 executives spanning the retail supply chain ecosystem. We use grounded theory to develop four main contributions. First, we find that the involvement of managerial judgment is found to be progressively greater moving up the retail supply chain, away from the customer and the demand signal. Second, integration of analytics and judgment is now the primary method of decision making, and we identify elements needed for success. Third, we develop an essential framework for a successful integration process. Fourth, we isolate the necessary components of a successful process for analytics/artificial intelligence (AI) implementation. Our paper offers important insights into how analytics and AI are—and should be used—in judgment and decision making and opportunities for researchers to understand the changing role of the human factor in digitalized retail supply chains.

Original Publication Citation

"Brau, R.I., Sanders, N., Aloysius, J., & Williams, D. (2024) Utilizing People, Analytics, and AI for Decision-Making in the Digitalized Retail Supply Chain. Journal of Business Logistics, 45(1). https://doi.org/10.1111/jbl.12355"

Document Type

Peer-Reviewed Article

Publication Date

2020

Publisher

Journal of Business Logistics

Language

English

College

Marriott School of Business

Department

Marketing

University Standing at Time of Publication

Assistant Professor

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