Data-driven robust strategic sourcing considering supply-side competition: Insights into blockchain adoption for coordination

• Exploring blockchain’s role in establishing long-term partnerships among stakeholders. • Incorporating competitive dynamics into the buyer-vendor coordination problem. • Integrating data-driven robust optimization to model multidimensional uncertainties. • Enhancing supply chain resilience through strategic sourcing and information sharing. Given the increasing vulnerability of global supply chains (SCs) to disruptions, improving resilience through strategic sourcing is crucial for maintaining continuity and adaptability in dynamic markets. Integrating blockchain technology (BT) can further support these efforts by ensuring data integrity, transparency, and real-time visibility across SCs. This study develops a data-driven robust multi-objective programming (DDRMOP) model to explore the role of BT in designing sourcing strategies and creating effective partnerships in the face of uncertainties. The DDRMOP employs a data-driven robust optimization approach utilizing principal component analysis and robust kernel density estimation to formulate uncertainty sets for market demand. The model aims to minimize SC coordination costs, defective rates, and delivery delays while enhancing sourcing efficiency by selecting the most sustainable and BT-friendly suppliers. A Nash game-enabled data envelopment analysis is incorporated into this model to investigate sourcing efficiency under competitive dynamics and demand uncertainty simultaneously. This integration provides insights into how these dynamics influence the trade-off between cost efficiency and SC resilience. As the DDRMOP model includes three conflicting objectives, the augmented ε-constraint method is adopted to analyze the impact of each function on strategic sourcing across multiple products. The findings highlight the importance of BT and sustainability in forming reliable partnerships between the buyer and suppliers to enhance dynamic SC capabilities during disruptions. BT-friendly suppliers are preferred for their alignment with sustainability and information coordination goals. Although supply-side competition may increase coordination costs and operational complexities, it ultimately improves overall sourcing efficiency.

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Institutions

Publication Details

Journal
Transportation Research Part E Logistics and Transportation Review
Published
2025-03-16
DOI
https://doi.org/10.1016/j.tre.2025.103977
Citations
4
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
12.98

Funders

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article

Data-driven robust strategic sourcing considering supply-side competition: Insights into blockchain adoption for coordination

Babak Mohamadpour Tosarkani, Mohammad Reza Khodoomi, Samuel Yousefı
4 citations
Transportation Research Part E Logistics and Transportation Review
Blockchain Technology Applications and Security
12.98
article

Data-driven robust strategic sourcing considering supply-side competition: Insights into blockchain adoption for coordination

Babak Mohamadpour Tosarkani, Mohammad Reza Khodoomi, Samuel Yousefı
article en
4 citations

Abstract

• Exploring blockchain’s role in establishing long-term partnerships among stakeholders. • Incorporating competitive dynamics into the buyer-vendor coordination problem. • Integrating data-driven robust optimization to model multidimensional uncertainties. • Enhancing supply chain resilience through strategic sourcing and information sharing. Given the increasing vulnerability of global supply chains (SCs) to disruptions, improving resilience through strategic sourcing is crucial for maintaining continuity and adaptability in dynamic markets. Integrating blockchain technology (BT) can further support these efforts by ensuring data integrity, transparency, and real-time visibility across SCs. This study develops a data-driven robust multi-objective programming (DDRMOP) model to explore the role of BT in designing sourcing strategies and creating effective partnerships in the face of uncertainties. The DDRMOP employs a data-driven robust optimization approach utilizing principal component analysis and robust kernel density estimation to formulate uncertainty sets for market demand. The model aims to minimize SC coordination costs, defective rates, and delivery delays while enhancing sourcing efficiency by selecting the most sustainable and BT-friendly suppliers. A Nash game-enabled data envelopment analysis is incorporated into this model to investigate sourcing efficiency under competitive dynamics and demand uncertainty simultaneously. This integration provides insights into how these dynamics influence the trade-off between cost efficiency and SC resilience. As the DDRMOP model includes three conflicting objectives, the augmented ε-constraint method is adopted to analyze the impact of each function on strategic sourcing across multiple products. The findings highlight the importance of BT and sustainability in forming reliable partnerships between the buyer and suppliers to enhance dynamic SC capabilities during disruptions. BT-friendly suppliers are preferred for their alignment with sustainability and information coordination goals. Although supply-side competition may increase coordination costs and operational complexities, it ultimately improves overall sourcing efficiency.

Transportation Research Part E Logistics and Transportation ReviewVol. 197
University of British Columbia (CA), University of British Columbia, Okanagan Campus (CA), Okanagan University College (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 2%
Blockchain Technology Applications and Security
12.98
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