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Robust global sourcing under compliance legislation

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  • Mazahir, Shumail
  • Ardestani-Jaafari, Amir

Abstract

Concerns about the environment, public health, and safety are driving governments around the world to restrict access to their markets of products, which may present environmental/health risks. As a result, legislation in many countries requires that firms comply with specific environmental and safety standards before introducing their products in these markets. However, there is no unified global standard, and a set of local rules governs most of the markets. Therefore, products complying with the regulations of one market may not be compliant with the standards laid out in the other. This means that large firms must include the local regulatory requirements of their targeted markets into account when making their sourcing decisions. The rise in the enforcement of compliance legislation has overlapped with an increase in the trend of global sourcing, where manufacturers have opted for a diversified and offshore supplier base. With the issue of compliance legislation in place, the suppliers who otherwise would produce functionally identical products become differentiable based on their ability to fulfill compliance requirements of the targeted markets. Also, the suppliers have incentives to exaggerate their compliance ability or may lack the technical capability to ascertain this information completely. Therefore, there always resides a degree of uncertainty about a supplier’s actual compliance capability. On the market side, there is uncertainty concerning product demand in individual markets. These two sources of uncertainty make this a rather challenging problem. We propose a formulation of supplier selection and product allocation decisions in this problem based on a two-stage robust optimization method. Through a set of numerical experiments, we discuss some exciting insights about the role of uncertainty in compliance failure on overall profitability and flexibility in the supply chain. We show that 3% supply-side uncertainty has almost the same effect on the quality of worst-case profit as 30% deviation from the nominal demand.

Suggested Citation

  • Mazahir, Shumail & Ardestani-Jaafari, Amir, 2020. "Robust global sourcing under compliance legislation," European Journal of Operational Research, Elsevier, vol. 284(1), pages 152-163.
  • Handle: RePEc:eee:ejores:v:284:y:2020:i:1:p:152-163
    DOI: 10.1016/j.ejor.2019.12.017
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    References listed on IDEAS

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    1. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. David Simchi‐Levi & He Wang & Yehua Wei, 2018. "Increasing Supply Chain Robustness through Process Flexibility and Inventory," Production and Operations Management, Production and Operations Management Society, vol. 27(8), pages 1476-1491, August.
    3. Dagmara Nawrocka, 2008. "Environmental supply chain management, ISO 14001 and RoHS. How are small companies in the electronics sector managing?," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 15(6), pages 349-360, November.
    4. Michael K. Lim & Achal Bassamboo & Sunil Chopra & Mark S. Daskin, 2013. "Facility Location Decisions with Random Disruptions and Imperfect Estimation," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 239-249, May.
    5. David Simchi-Levi & Nikolaos Trichakis & Peter Yun Zhang, 2019. "Designing Response Supply Chain Against Bioattacks," Operations Research, INFORMS, vol. 67(5), pages 1246-1268, September.
    6. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    7. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    8. An, Yu & Zeng, Bo & Zhang, Yu & Zhao, Long, 2014. "Reliable p-median facility location problem: two-stage robust models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 54-72.
    9. Cheng, Chun & Qi, Mingyao & Zhang, Ying & Rousseau, Louis-Martin, 2018. "A two-stage robust approach for the reliable logistics network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 185-202.
    10. Joel Goh & Melvyn Sim, 2011. "Robust Optimization Made Easy with ROME," Operations Research, INFORMS, vol. 59(4), pages 973-985, August.
    11. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    12. Maqbool Dada & Nicholas C. Petruzzi & Leroy B. Schwarz, 2007. "A Newsvendor's Procurement Problem when Suppliers Are Unreliable," Manufacturing & Service Operations Management, INFORMS, vol. 9(1), pages 9-32, August.
    13. Plambeck, Erica L. & Taylor, Terry A., 2015. "Supplier Evasion of a Buyer's Audit: Implications for Motivating Supplier Social and Environmental Responsibility," Research Papers 3176, Stanford University, Graduate School of Business.
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    3. Judit Oláh & Nemer Aburumman & József Popp & Muhammad Asif Khan & Hossam Haddad & Nicodemus Kitukutha, 2020. "Impact of Industry 4.0 on Environmental Sustainability," Sustainability, MDPI, vol. 12(11), pages 1-21, June.
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