A DEA-based approach for competitive environment analysis in global operations strategies

Jiawen Liu, Yeming Gong (), Joe Zhu and Jinlong Zhang
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Jiawen Liu: HUST - Huazhong University of Science and Technology [Wuhan], Worcester Polytechnic Institute
Yeming Gong: EM - EMLyon Business School
Joe Zhu: Worcester Polytechnic Institute
Jinlong Zhang: HUST - Huazhong University of Science and Technology [Wuhan]

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Abstract: While competitive environment analysis is critical to a global retailing operations strategy, there exist research gaps from perspectives of operational performance, retailing industrial environment, and nondiscretionary factors. Therefore, our research objective is to propose a new approach to conduct competitive environment analysis for a global operations strategy in retailing, by examining relationships between discretionary inputs of the supply chain, nondiscretionary inputs of the environment, and performance of retailing. We develop a nondiscretionary data envelopment analysis model to assess performance in retailing and integrate it with econometric analysis. Using multisource data of 124 organizations in the global retailing industry, it is interesting to find: while nondiscretionary factors significantly influence the operational performance of global retailers, firms in an environment with a higher market concentration, larger consumer spending per capita, and smaller inhabitants' population are more likely to achieve a higher operational efficiency in retailing. Another interesting finding with practical implication is: inputs relevant to outside environment (e.g., suppliers in upstream and outlets in downstream supply chain) can influence operational efficiency more than inputs in internal supply chain (e.g., warehouses).

Keywords: Data envelopment analysis; Global operations strategy; Competitive environment analysis; Operational performance; Multi-method approach (search for similar items in EconPapers)
Date: 2018-09-01
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Citations: View citations in EconPapers (14)

Published in International Journal of Production Economics, 2018, 203, 110-123 p. ⟨10.1016/j.ijpe.2018.05.029⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02312151

DOI: 10.1016/j.ijpe.2018.05.029

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