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How does heavy haze weather impact operational efficiency? An empirical study of Chinese manufacturing firms

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  • Yang, Yefei
  • Wang, Ziwei
  • Dong, Ciwei
  • Cheng, T.C.E.

Abstract

Global warming has escalated the frequency of extreme climate events. Considering the escalating severity of air pollution, investigating its potential to cause operational problems is of value. Some studies have explored air pollution's effects from individual perspectives, including emotions, attitudes, and decision-making behaviors. Yet, the influence of heavy haze weather on firm performance from an operations management viewpoint remains uninvestigated. This study seeks to address this research gap. Utilizing a longitudinal dataset from 2255 manufacturing firms between 2014 and 2020, this study empirically examines heavy haze weather's impact on operational efficiency. Three contingency categories are identified: strategic positioning, structural contingency, and institutional factors. The findings suggest that heavy haze weather adversely impacts operational efficiency, notably for firms with cost leadership strategies and high labor productivity, whereas such effect can weaken in the firms with process standardization and governmental environment inspection. Enhancing the understanding about the effect of heavy haze weather on operational performance, these findings offer strategic insights for firms to mitigate heavy haze weather and provide empirical support for government to make environmental policy-making.

Suggested Citation

  • Yang, Yefei & Wang, Ziwei & Dong, Ciwei & Cheng, T.C.E., 2024. "How does heavy haze weather impact operational efficiency? An empirical study of Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 273(C).
    • Handle: RePEc:eee:proeco:v:273:y:2024:i:c:s092552732400121x
    DOI: 10.1016/j.ijpe.2024.109264
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    1. Bertrand, Jean-Louis & Chabot, Miia & Brusset, Xavier & Courquin, Valentin, 2024. "Identifying assets exposed to physical climate risk: A decision-support methodology," International Journal of Production Economics, Elsevier, vol. 276(C).

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