Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices

Purpose: This study illustrates the experience of scholar–practitioner collaboration for data-driven decision-making through the problematic of optimizing facility locations and minimizing logistics costs for La Palette Rouge (LPR) of Portugal. Design/methodology/approach: The authors used a mixed m...

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Main Authors: Rohani, Vala Ali, Peerally, Jahan Ara, Moghavvemi, Sedigheh, Guerreiro, Flavio, Pinho, Tiago
Format: Article
Published: Emerald Group Holdings Ltd. 2022
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Online Access:http://eprints.um.edu.my/43406/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122126385&doi=10.1108%2fTQM-06-2021-0194&partnerID=40&md5=6850349630b42f22eb3ff5da2def81be
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spelling my.um.eprints.434062023-11-08T01:50:59Z http://eprints.um.edu.my/43406/ Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices Rohani, Vala Ali Peerally, Jahan Ara Moghavvemi, Sedigheh Guerreiro, Flavio Pinho, Tiago Business Purpose: This study illustrates the experience of scholar–practitioner collaboration for data-driven decision-making through the problematic of optimizing facility locations and minimizing logistics costs for La Palette Rouge (LPR) of Portugal. Design/methodology/approach: The authors used a mixed mixed-method approach involving (1) a quantitative exploratory analysis of big data, which applied analytics and mathematical modeling to optimize LPR's logistics network, and (2) an illustrative case of scholar–practitioner collaboration for data-driven decision-making. Findings: The quantitative analysis compared more than 20 million possible configurations and proposed the optimal logistics structures. The proposed optimization model minimizes the logistics costs by 22. Another optimal configuration revealed that LPR can minimize logistics costs by 12 through closing one of its facilities. The illustrative description demonstrates that well-established resource-rich multinational enterprises do not necessarily have the in-house capabilities and competencies to handle and analyze big data. Practical implications: The mathematical modeling for optimizing logistics networks demonstrates that outcomes are readily actionable for practitioners and can be extended to other country and industry contexts with logistics operations. The case illustrates that synergistic relationships can be created, and the opportunities exist between scholars and practitioners in the field of Logistics 4.0 and that scientific researcher is necessary for solving problems and issues that arise in practice while advancing knowledge. Originality/value: The study illustrates that several Logistics 4.0 challenges highlighted in the literature can be collectively addressed through scholar–practitioner collaborations. The authors discuss the implications of such collaborations for adopting virtual and augmented reality (AR) technologies and to develop the capabilities for maximizing their benefits in mature low-medium technology industries, such as the food logistics industry. © 2021, Emerald Publishing Limited. Emerald Group Holdings Ltd. 2022 Article PeerReviewed Rohani, Vala Ali and Peerally, Jahan Ara and Moghavvemi, Sedigheh and Guerreiro, Flavio and Pinho, Tiago (2022) Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices. TQM Journal, 34 (2). 280 -302. ISSN 1754-2731, DOI https://doi.org/10.1108/TQM-06-2021-0194 <https://doi.org/10.1108/TQM-06-2021-0194>. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122126385&doi=10.1108%2fTQM-06-2021-0194&partnerID=40&md5=6850349630b42f22eb3ff5da2def81be 10.1108/TQM-06-2021-0194
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic Business
spellingShingle Business
Rohani, Vala Ali
Peerally, Jahan Ara
Moghavvemi, Sedigheh
Guerreiro, Flavio
Pinho, Tiago
Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
description Purpose: This study illustrates the experience of scholar–practitioner collaboration for data-driven decision-making through the problematic of optimizing facility locations and minimizing logistics costs for La Palette Rouge (LPR) of Portugal. Design/methodology/approach: The authors used a mixed mixed-method approach involving (1) a quantitative exploratory analysis of big data, which applied analytics and mathematical modeling to optimize LPR's logistics network, and (2) an illustrative case of scholar–practitioner collaboration for data-driven decision-making. Findings: The quantitative analysis compared more than 20 million possible configurations and proposed the optimal logistics structures. The proposed optimization model minimizes the logistics costs by 22. Another optimal configuration revealed that LPR can minimize logistics costs by 12 through closing one of its facilities. The illustrative description demonstrates that well-established resource-rich multinational enterprises do not necessarily have the in-house capabilities and competencies to handle and analyze big data. Practical implications: The mathematical modeling for optimizing logistics networks demonstrates that outcomes are readily actionable for practitioners and can be extended to other country and industry contexts with logistics operations. The case illustrates that synergistic relationships can be created, and the opportunities exist between scholars and practitioners in the field of Logistics 4.0 and that scientific researcher is necessary for solving problems and issues that arise in practice while advancing knowledge. Originality/value: The study illustrates that several Logistics 4.0 challenges highlighted in the literature can be collectively addressed through scholar–practitioner collaborations. The authors discuss the implications of such collaborations for adopting virtual and augmented reality (AR) technologies and to develop the capabilities for maximizing their benefits in mature low-medium technology industries, such as the food logistics industry. © 2021, Emerald Publishing Limited.
format Article
author Rohani, Vala Ali
Peerally, Jahan Ara
Moghavvemi, Sedigheh
Guerreiro, Flavio
Pinho, Tiago
author_facet Rohani, Vala Ali
Peerally, Jahan Ara
Moghavvemi, Sedigheh
Guerreiro, Flavio
Pinho, Tiago
author_sort Rohani, Vala Ali
title Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
title_short Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
title_full Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
title_fullStr Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
title_full_unstemmed Illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of AR and VR practices
title_sort illustrating scholar–practitioner collaboration for data-driven decision-making in the optimization of logistics facility location and implications for increasing the adoption of ar and vr practices
publisher Emerald Group Holdings Ltd.
publishDate 2022
url http://eprints.um.edu.my/43406/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122126385&doi=10.1108%2fTQM-06-2021-0194&partnerID=40&md5=6850349630b42f22eb3ff5da2def81be
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score 13.188404