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A Hybrid Supply Chain Risk Management Approach for Lean Green Performance Based on AHP, RCA and TRIZ: A Case Study

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  • Fatima Ezzahra Essaber

    (LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim AL Khattabi, Marrakech 40000, Morocco)

  • Rachid Benmoussa

    (LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim AL Khattabi, Marrakech 40000, Morocco)

  • Roland De Guio

    (ICube Laboratory, National Institute of Applied Sciences of Strasbourg, 24 Boulevard de la Victoire, 67084 Strasbourg, France)

  • Sébastien Dubois

    (ICube Laboratory, National Institute of Applied Sciences of Strasbourg, 24 Boulevard de la Victoire, 67084 Strasbourg, France)

Abstract

The purpose of this research work is to provide supply chain managers with a formal and generalizable approach that furnishes accurate guidelines to achieve a 2D performance integrating both Lean and Green. Despite the fact that several research works have been conducted in the framework of Lean and Green, at a conceptual level, the relationship between both paradigms is still ambiguous. Furthermore, the literature revealed a lack of relevant and generalizable approaches that explicitly demonstrate how to successfully implement Lean and Green in a relevant and integrated way. Since risks are the main obstacles disrupting performance, this research work addresses the identified gap by proposing a risk management approach (RMA) for Lean Green performance in a supply-chain context. Risk cannot be managed if not well-identified; hence, a rigorous literature investigation was conducted to define this concept in a supply-chain context. Later, risk was introduced into Lean and Green aspects. Subsequently, through a comprehensive review of previous risk identification studies, a novel classification of supply chain risks in a Lean Green context was provided. At a corporate level, risks often include several sources that cannot be treated at once. Therefore, a risk assessment analysis was performed, employing an analytic hierarchy process for its ease of use and broad adaptability. The output of this analysis provides visibility for an organization’s position toward performance goals and underlines crucial risks to be addressed. The risk treatment process was upgraded in this approach to a detailed analysis that aims at investigating the root causes behind the prioritized risks. Deployment of the approach on a corporate level revealed that treating a risk may negatively affect treating another. Indeed, thinking Lean is not necessarily Green, which stands with the fact that Lean Green supply chain challenges may outstrip classic optimization methods and techniques; therefore, its management requires innovative approaches. Thereby, our findings support the applicability and efficiency of the Theory of Inventive Problem Solving (TRIZ) in this setting. Although the case study focused on a specific company, the developed framework can be customized to fit different cases.

Suggested Citation

  • Fatima Ezzahra Essaber & Rachid Benmoussa & Roland De Guio & Sébastien Dubois, 2021. "A Hybrid Supply Chain Risk Management Approach for Lean Green Performance Based on AHP, RCA and TRIZ: A Case Study," Sustainability, MDPI, vol. 13(15), pages 1-41, July.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8492-:d:604344
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    References listed on IDEAS

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    1. Jean Noël Ouraga Breka & Sophie Gaultier-Gaillard, 2013. "La supply chain verte dans les entreprises agroalimentaires françaises : freins et motivations," Post-Print hal-03029463, HAL.
    2. Scott DuHadway & Steven Carnovale & Benjamin Hazen, 2019. "Understanding risk management for intentional supply chain disruptions: risk detection, risk mitigation, and risk recovery," Annals of Operations Research, Springer, vol. 283(1), pages 179-198, December.
    3. Giannakis, Mihalis & Papadopoulos, Thanos, 2016. "Supply chain sustainability: A risk management approach," International Journal of Production Economics, Elsevier, vol. 171(P4), pages 455-470.
    4. Garvey, Myles D. & Carnovale, Steven & Yeniyurt, Sengun, 2015. "An analytical framework for supply network risk propagation: A Bayesian network approach," European Journal of Operational Research, Elsevier, vol. 243(2), pages 618-627.
    5. Lin Wu & Nachiappan Subramanian & Muhammad D. Abdulrahman & Chang Liu & Kee-hung Lai & Kulwant S. Pawar, 2015. "The Impact of Integrated Practices of Lean, Green, and Social Management Systems on Firm Sustainability Performance—Evidence from Chinese Fashion Auto-Parts Suppliers," Sustainability, MDPI, vol. 7(4), pages 1-21, March.
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    Cited by:

    1. Wilson Kosasih & I Nyoman Pujawan & Putu Dana Karningsih, 2023. "Integrated Lean-Green Practices and Supply Chain Sustainability for Manufacturing SMEs: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    2. Fahim ul Amin & Qian-Li Dong & Katarzyna Grzybowska & Zahid Ahmed & Bo-Rui Yan, 2022. "A Novel Fuzzy-Based VIKOR–CRITIC Soft Computing Method for Evaluation of Sustainable Supply Chain Risk Management," Sustainability, MDPI, vol. 14(5), pages 1-15, February.

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