Resilience, efficiency fluctuations, and regional heterogeneity in disaster: An empirical study on logistics

Longfei Xue, Yeming Gong (), Bingnan Yang and Xianhao Xu
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Longfei Xue: HUST - Huazhong University of Science and Technology [Wuhan]
Yeming Gong: EM - EMLyon Business School
Bingnan Yang: HUST - Huazhong University of Science and Technology [Wuhan]
Xianhao Xu: HUST - Huazhong University of Science and Technology [Wuhan]

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Abstract: While resilience analysis can provide important insights into risk management strategies, research gaps exist in terms of logistics efficiency, regional economic environment, and spatial clustering patterns. Therefore, our study capitalizes on the dramatic variations in logistics activities among regions during COVID-19 to examine regional logistics resilience in the disaster and explore potential spatial clustering patterns. We measure regional logistics resilience through changes in performance outcomes, specifically efficiency fluctuation. To analyze spatial clustering patterns, (regional heterogeneity) presented by logistics efficiency, we propose a new multi-stage approach that integrates the data envelopment analysis with the K-medoids algorithm and analyzes data from the Chinese logistic industry. The results reveal that efficiency fluctuations exhibit distinct spatial distribution characteristics, with more pronounced negative fluctuations in areas of important logistics activities nodes and islands, and more widespread negative trends in coastal areas. Moreover, regions with high freight volumes and logistics specialization demonstrate a sustained high level and quality of logistics efficiency. Furthermore, consumption capacity and economic development appear to positively influence fluctuations in logistics efficiency. The findings hold implications for enhancing regional logistics resilience in the disaster and contribute valuable insights to regional logistics risk management.

Keywords: Data envelopment analysis; Resilience Efficiency; Logistics (search for similar items in EconPapers)
Date: 2024-06-01
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Published in Socio-Economic Planning Sciences, 2024, 93, 12 p. ⟨10.1016/j.seps.2024.101854⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04692532

DOI: 10.1016/j.seps.2024.101854

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