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An Integrated DEA–Porter Decision Support Framework for Enhancing Supply Chain Competitiveness in the Muslim Fashion Industry: Evidence from Indonesia

Author

Listed:
  • Jilly Ayuningtias

    (Doctoral Program in Business Management, School of Business, IPB University, Bogor 16128, Indonesia)

  • Marimin Marimin

    (Department of Agroindustrial Technology, Faculty of Agricultural Engineering and Technology, IPB University, Bogor 16128, Indonesia)

  • Agus Buono

    (School of Data Science, Mathematics and Informatics, IPB University, Bogor 16128, Indonesia)

  • Arif Imam Suroso

    (School of Business, IPB University, Bogor 16128, Indonesia)

Abstract

Background: The competitiveness of Indonesia’s Muslim fashion industry requires evaluation through both internal efficiency and external strategic factors, yet existing approaches often assess these dimensions separately. Methods: This study develops a Weighted Efficiency Competitive Score (WECS) that integrates Data Envelopment Analysis (DEA) to measure operational efficiency and Porter’s Five Forces to capture market pressures. The weights of α and β were calibrated through sensitivity analysis under the constraint α + β = 1, with values ranging from α = 0.3 to 0.7 and β = 0.7 to 0.3, using data from 23 Muslim fashion businesses in Jakarta. Results: The analysis identified α = 0.6 and β = 0.4 as the most stable configuration, and only 30% of firms achieved both high efficiency and strong market positioning. Strategic leaders such as JT. Co and PM. Co demonstrated that digital transformation, disciplined cost structures, and strong supply chain partnerships foster sustainable competitiveness. Conclusions: The WECS framework offers a replicable method to quantitatively integrate micro and macro determinants of competitiveness, contributes to the literature by bridging efficiency and strategy evaluation, and provides practical guidance for managers and policymakers to enhance decision support systems in strengthening the Muslim fashion industry’s global positioning.

Suggested Citation

  • Jilly Ayuningtias & Marimin Marimin & Agus Buono & Arif Imam Suroso, 2025. "An Integrated DEA–Porter Decision Support Framework for Enhancing Supply Chain Competitiveness in the Muslim Fashion Industry: Evidence from Indonesia," Logistics, MDPI, vol. 9(3), pages 1-30, September.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:3:p:129-:d:1748375
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    References listed on IDEAS

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    1. Jiasen Sun & Guo Li & Ming K. Lim, 2025. "China’s power supply chain sustainability: an analysis of performance and technology gap," Annals of Operations Research, Springer, vol. 349(2), pages 849-877, June.
    2. Talluri, Srinivas & Narasimhan, Ram & Nair, Anand, 2006. "Vendor performance with supply risk: A chance-constrained DEA approach," International Journal of Production Economics, Elsevier, vol. 100(2), pages 212-222, April.
    3. Enrique Delahoz-Domínguez & Adel Mendoza-Mendoza & Rohemi Zuluaga-Ortiz, 2024. "A Six Sigma and DEA Framework for Quality Assessment in Banking Services," Administrative Sciences, MDPI, vol. 14(11), pages 1-12, November.
    4. Cong Wang & Zongbao Zou & Shidao Geng, 2021. "Green Technology Investment in a Decentralized Supply Chain under Demand Uncertainty," Sustainability, MDPI, vol. 13(7), pages 1-25, March.
    5. Francisco Zabala Aguayo & Beata Ślusarczyk, 2020. "Risks of Banking Services’ Digitalization: The Practice of Diversification and Sustainable Development Goals," Sustainability, MDPI, vol. 12(10), pages 1-10, May.
    6. Hyun Jung Kim & Jiyoon Son & Soo Wook Kim, 2016. "Strategy for Improving Efficiency of Supply Chain Quality Management in Buyer-Supplier Dyads: The Suppliers’ Perspective," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, March.
    7. Bin Shen, 2014. "Sustainable Fashion Supply Chain: Lessons from H&M," Sustainability, MDPI, vol. 6(9), pages 1-14, September.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    9. Shuaiyu Yao & Mengmeng Chen & Dmitri Muravev & Wendi Ouyang, 2021. "Eco-Efficiency Analysis for the Russian Cities along the Northern Sea Route: A Data Envelopment Analysis Approach Using an Epsilon-Based Measure Model," IJERPH, MDPI, vol. 18(11), pages 1-16, June.
    10. 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.
    11. Boussofiane, A. & Dyson, R. G. & Thanassoulis, E., 1991. "Applied data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 52(1), pages 1-15, May.
    12. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    13. Toshiyuki Sueyoshi & Mika Goto, 2019. "Comparison among Three Groups of Solar Thermal Power Stations by Data Envelopment Analysis," Energies, MDPI, vol. 12(13), pages 1-20, June.
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