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Modeling to Achieve Area Business Continuity Management Implementation via a Fuzzy Cognitive Map

Author

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  • Kunruthai Meechang

    (Department of Architecture, Civil Engineering and Industrial Management Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Aichi, Japan)

  • Kenji Watanabe

    (Department of Architecture, Civil Engineering and Industrial Management Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Aichi, Japan)

Abstract

Area business continuity management (Area-BCM) is introduced to enhance sustainable economic growth by building public–private partnerships. It is implemented in pilot industrial zones in disaster-prone regions to tackle problems beyond a single organization’s capacity. The framework emphasizes multiple stakeholders in the decision-making process, but participation and implementation remain major challenges for many practitioners in the search for potential pathways. Therefore, this study presents a model of causal relationships between concepts to achieve the implementation of Area-BCM. To capture expert perceptions and visualize relationships, a fuzzy cognitive map (FCM) is deployed. The use of fuzzy logic facilitates the integration of diverse viewpoints and the representation of ambiguous and complex scenarios. Initially, 28 appropriate concepts were identified by reviewing the literature on practical Area-BCM cases, which were then scrutinized by experts, including eight driving causes, eleven required actions, and nine outcome variables. Subsequently, FCMs were constructed through individual interviews. Since the FCMs had been aggregated, a scenario analysis was performed under five different conditions to evaluate potential strategies. The simulation results present promising concepts that could improve Area-BCM implementation. The findings emphasize that these strategies will have a positive influence when top management is committed, government support is achieved, and workshops exist.

Suggested Citation

  • Kunruthai Meechang & Kenji Watanabe, 2023. "Modeling to Achieve Area Business Continuity Management Implementation via a Fuzzy Cognitive Map," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13531-:d:1236874
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    References listed on IDEAS

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    1. Falcone, Pasquale Marcello & De Rosa, Salvatore Paolo, 2020. "Use of fuzzy cognitive maps to develop policy strategies for the optimization of municipal waste management: A case study of the land of fires (Italy)," Land Use Policy, Elsevier, vol. 96(C).
    2. Chen, Chen-Tung & Chiu, Yen-Ting, 2021. "A study of dynamic fuzzy cognitive map model with group consensus based on linguistic variables," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    3. Asmaa Mourhir & Elpiniki I. Papageorgiou & Konstantinos Kokkinos & Tajjeeddine Rachidi, 2017. "Exploring Precision Farming Scenarios Using Fuzzy Cognitive Maps," Sustainability, MDPI, vol. 9(7), pages 1-23, July.
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