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A SCOR-Based Two-Stage Network Range-Adjusted Measure Data Envelopment Analysis Approach for Evaluating Sustainable Supply Chain Efficiency: Evidence from the Korean Automotive Parts Industry

Author

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  • Sungmook Lim

    (Department of Business Administration, Dongguk Business School, Dongguk University, Seoul 04620, Republic of Korea)

  • Yue Luo

    (Department of Business Administration, Dongguk Business School, Dongguk University, Seoul 04620, Republic of Korea)

Abstract

This study evaluates the economic dimension of sustainable supply chain efficiency among Korean automotive suppliers using an SCOR-aligned two-stage Network Range-Adjusted Measure (NRAM) Data Envelopment Analysis (DEA) model. The framework separates performance into Stage 1 (internal operations: Plan/Source/Make/Deliver) and Stage 2 (external outcomes: sales and profitability), enabling stage-specific assessment of operational versus market-facing efficiency. Firm-level financial data for about 1200 suppliers annually from 2021 to 2024, spanning five sectors, were analyzed with descriptive statistics, visualizations, and non-parametric tests. Results show that Stage 1 efficiency was consistently high and stable, while Stage 2 efficiency was lower, more variable, and declined in 2022 and 2024, revealing vulnerability to systemic market disruptions. Overall efficiency mirrored Stage 2, underscoring the fact that downstream financial outcomes drive total performance. Rather than introducing a new methodology, the contribution of this study lies in applying an established two-stage NRAM DEA within an SCOR-aligned framework to a large-scale longitudinal dataset. This application provides sectoral and temporal benchmarks on a national scale, offering evidence-based insights into how structural interdependence and systemic shocks influence supply chain efficiency. While the scope is limited to the economic pillar of sustainability, the findings contribute contextualized benchmarks that can inform managerial practice and future research integrating environmental and social performance dimensions.

Suggested Citation

  • Sungmook Lim & Yue Luo, 2025. "A SCOR-Based Two-Stage Network Range-Adjusted Measure Data Envelopment Analysis Approach for Evaluating Sustainable Supply Chain Efficiency: Evidence from the Korean Automotive Parts Industry," Sustainability, MDPI, vol. 17(19), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8607-:d:1758017
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    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Illi Kim & Changhee Kim, 2018. "Supply Chain Efficiency Measurement to Maintain Sustainable Performance in the Automobile Industry," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    3. Chen, Ci & Yan, Hong, 2011. "Network DEA model for supply chain performance evaluation," European Journal of Operational Research, Elsevier, vol. 213(1), pages 147-155, August.
    4. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    5. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    6. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    7. Saranga, Haritha, 2009. "The Indian auto component industry - Estimation of operational efficiency and its determinants using DEA," European Journal of Operational Research, Elsevier, vol. 196(2), pages 707-718, July.
    8. David J. Teece, 2007. "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance," Strategic Management Journal, Wiley Blackwell, vol. 28(13), pages 1319-1350, December.
    9. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    10. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    11. Li, Suhong & Ragu-Nathan, Bhanu & Ragu-Nathan, T.S. & Subba Rao, S., 2006. "The impact of supply chain management practices on competitive advantage and organizational performance," Omega, Elsevier, vol. 34(2), pages 107-124, April.
    12. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    13. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    14. Kathleen M. Eisenhardt & Jeffrey A. Martin, 2000. "Dynamic capabilities: what are they?," Strategic Management Journal, Wiley Blackwell, vol. 21(10‐11), pages 1105-1121, October.
    15. Alnafrah, Ibrahim, 2025. "Evaluating efficiency of green innovations and renewables for sustainability goals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    16. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    17. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    18. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
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