Utilizing people, analytics, and AI for decision making in the digitalized retail supply chain

被引:15
作者
Brau, Rebekah I. [1 ,6 ]
Sanders, Nada R. [2 ]
Aloysius, John [3 ]
Williams, Donnie [4 ,5 ]
机构
[1] Brigham Young Univ, Marriott Sch Business, Global Supply Chain Management, Provo, UT USA
[2] Northeastern Univ, DAmore McKim Sch Business, Supply Chain Management, Boston, MA USA
[3] Univ Arkansas, Walton Coll Business, Logist, Fayetteville, AR USA
[4] Univ Arkansas, Walton Coll Business, Supply Chain Management, Fayetteville, AR USA
[5] Univ Arkansas, Walton Coll Business, Supply Chain Management Res Ctr, Fayetteville, AR USA
[6] Brigham Young Univ, Marriott Sch Business, Provo, UT 84602 USA
关键词
analytics; artificial intelligence; grounded theory; human judgment; retail supply chain; BIG DATA; PREDICTIVE ANALYTICS; MANAGEMENT; OPERATIONS; LOGISTICS; FORECASTS;
D O I
10.1111/jbl.12355
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页数:20
相关论文
共 80 条
[51]   HUMANS AND TECHNOLOGY: FORMS OF CONJOINED AGENCY IN ORGANIZATIONS [J].
Murray, Alex ;
Rhymer, Jen ;
Sirmon, David G. .
ACADEMY OF MANAGEMENT REVIEW, 2021, 46 (03) :552-571
[52]  
Ng A., 2016, Harvard Business Review
[53]   Trust in Forecast Information Sharing [J].
Oezer, Oezalp ;
Zheng, Yanchong ;
Chen, Kay-Yut .
MANAGEMENT SCIENCE, 2011, 57 (06) :1111-1137
[54]   The human factor in supply chain forecasting: A systematic review [J].
Perera, H. Niles ;
Hurley, Jason ;
Fahimnia, Behnam ;
Reisi, Mohsen .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2019, 274 (02) :574-600
[55]   Do 'big losses' in judgmental adjustments to statistical forecasts affect experts' behaviour? [J].
Petropoulos, Fotios ;
Fildes, Robert ;
Goodwin, Paul .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2016, 249 (03) :842-852
[56]  
Reavie V., 2018, Forbes
[57]   A global exploration of Big Data in the supply chain [J].
Richey, Robert Glenn, Jr. ;
Morgan, Tyler R. ;
Lindsey-Hall, Kristina ;
Adams, Frank G. .
INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT, 2016, 46 (08) :710-739
[58]  
Sanders N., 2019, Supply Chain Manag. Rev., P30
[59]  
Sanders N.R., 2017, Martin Starr and Sushil Gupta, in Routledge Companion for Production and Operations Management (POM), P45, DOI [10.4324/9781315687803.ch3, DOI 10.4324/9781315687803.CH3]
[60]   Sustainable Supply Chains in the Age of AI and Digitization: Research Challenges and Opportunities [J].
Sanders, Nada R. ;
Boone, Tonya ;
Ganeshan, Ram ;
Wood, John D. .
JOURNAL OF BUSINESS LOGISTICS, 2019, 40 (03) :229-240