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A Review and Classification Framework of Traceability Approaches for Identifying Product Supply Chain Counterfeiting

Author

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  • Sotiris P. Gayialis

    (Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Evripidis P. Kechagias

    (Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Georgios A. Papadopoulos

    (Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Dimitrios Masouras

    (Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

Abstract

Counterfeiting is found today in many industries and in various forms with severe consequences for supply chain operations. Products counterfeiting can be detected in consumer goods such as clothing, food and beverages, accessories, pharmaceuticals, electronics, and luxury goods. The continuous violations in the supply chain have led to the need for mobilization of all involved stakeholders to overcome counterfeiting challenges. Effective traceability seems to be the only way to combat this phenomenon, ensuring safe and sustainable supply chain operations. This paper presents a structured literature review on traceability approaches for combatting the product supply chain counterfeiting phenomenon that led to forming a structured classification framework. The performed analysis aims to identify trends and good practices and can be used as a guideline for real-life projects against supply chain counterfeiting. The results show that traditional traceability methods are not effective as they can be easily falsified using today’s technological advancements. However, these same advancements also present valuable technologies such as blockchain and the internet of things to ensure safe and sustainable supply chain operations.

Suggested Citation

  • Sotiris P. Gayialis & Evripidis P. Kechagias & Georgios A. Papadopoulos & Dimitrios Masouras, 2022. "A Review and Classification Framework of Traceability Approaches for Identifying Product Supply Chain Counterfeiting," Sustainability, MDPI, vol. 14(11), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6666-:d:827540
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    References listed on IDEAS

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    1. Li, Ling, 2013. "Technology designed to combat fakes in the global supply chain," Business Horizons, Elsevier, vol. 56(2), pages 167-177.
    2. Alba J. Collart & Elizabeth Canales, 2022. "How might broad adoption of blockchain‐based traceability impact the U.S. fresh produce supply chain?," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(1), pages 219-236, March.
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    3. Syaiful Anwar & Tomy Perdana & Meddy Rachmadi & Trisna Insan Noor, 2023. "Product Traceability and Supply Chain Sustainability of Black Soybeans as Raw Materials for Soy Sauce in Maintaining Quality and Safety," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
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    10. Syaiful Anwar & Tomy Perdana & Meddy Rachmadi & Trisna Insan Noor, 2022. "Traceability Information Model for Sustainability of Black Soybean Supply Chain: A Systematic Literature Review," Sustainability, MDPI, vol. 14(15), pages 1-19, August.
    11. Khushboo E-Fatima & Rasoul Khandan & Amin Hosseinian-Far & Dilshad Sarwar, 2023. "The Adoption of Robotic Process Automation Considering Financial Aspects in Beef Supply Chains: An Approach towards Sustainability," Sustainability, MDPI, vol. 15(9), pages 1-34, April.
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