15Nov 2019


  • STMI Polytechnic Jakarta, Ministry of Industry, Republic of Indonesia
  • Department of Agroindustrial Technology, IPB University (Bogor Agricultural University), Dramaga Bogor,West Java, Indonesia
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This study aims to measure the performance of the internal supply chain in Small and Medium Enterprises (SMEs) of footwear industry with the Data Envelopment Analysis (DEA) approach. The object of research in SMEs used six inputs and three outputs as indicators of supply chain performance. The inputs used were order fulfillment time, order fulfillment cycle, supply chain flexibility, total supply chain costs, cash to cash cycle time, and daily inventory. The output used, were delivery performance, order fulfillment and compliance with standards. This research had 21 Decision Making Units (DMU). The efficiency results obtained from the twenty-first was the average efficiency value of 0.721. There were five SMEs that already have an efficiency value of 1 which showed the highest efficiency, namely SMEs numbers 11, 14, 15 17 and 19. Those SMEs that had the highest efficiency have advantages compared to other SMEs, such as having inventory, chain costs low supply and fairly short footwear production cycle

  1. Amirteimoori, A., & Khoshandam, L. (2011). A Data Envelopment Analysis Approach To Supply Chain Efficiency, 2011. Https://Doi.Org/10.1155/2011/608324.
  2. Bai, C., & Sarkis, J. (2014). Determining and applying sustainable supplier key performance indicators. Supply Chain Management, 19(3), 275?291. https://doi.org/10.1108/SCM-12-2013-0441.
  3. Charnes, A. (1978). Measuring The Efficiency Of Decision Making Units, 2, 429?444.
  4. Cox, A. (N.D.). Power , Value And Supply Chain Management, (4), 167?175.
  5. Dev, N. K., Shankar, R., & Debnath, R. M. (2014). Supply Chain Efficiency: A Simulation Cum DEA Approach. International Journal Of Advanced Manufacturing Technology. Https://Doi.Org/10.1007/S00170-014-5779-6
  6. Herminiwati, H., & Lestari, S. B. P. (2016). The Effect of Added Aluminum Silicate and Azodicarbonamide On Production Of Microcellular Rubber For Light Sole. Leather, Rubber and Plastic Magazine. Https://Doi.Org/10.20543/Mkkp.V25i1.230.
  7. Khezrimotlagh, D. (2014). How to deal with numbers of decision making units and variables in data envelopment analysis, (1989), 1?11.
  8. Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA Models For Supply Chain Efficiency Evaluation, (July), 35?49. Https://Doi.Org/10.1007/S10479-006-0026-7.
  9. Marimin, Maghfiroh N. 2010. Application of Decision Making Techniques in Supply Chain Management. IPB Press, Bogor.
  10. Nurzamzami, Ayatusyifa; Siregar, E. H. (2014). Increased Competitiveness of Footwear MSMEs in Ciomas District, Bogor Regency and Their Implications for Marketing Strategies. Journal of Management and Organization Vol V, No 1, 85(1), 129?133. Https://Dorg/10.29244/jmo.v5i1.12127
  11. Pujawan IN. ? Supply Chain Management. Surabaya: Publisher Guna Widya.
  12. Warsito and Suparno. (2008). Supply Chain Efficiency Evaluation with Data Envelopment Analysis (Dea) Model (Case Study in Pt Paramithatama Asriraya). Proceedings of the National Seminar on Technology Management VIII. MMT-ITS Study Program, Surabaya 2 August 2008.
  13. Thanh Phan, X. T., Pham, C. H., & Pham, L. (2016). The Competitive Advantages Of Vietnam Footwear Industry: An Analysis. International Journal Of Financial Research, 7(3), 65?80. Https://Doi.Org/10.5430/Ijfr.V7n3p65.
  14. Tajbakhsh, A., & Hassini, E. (2015). A data envelopment analysis approach to evaluate sustainability in supply chain networks. Journal of Cleaner Production, 105, 74?85. https://doi.org/10.1016/j.jclepro.2014.07.054.
  15. The Conference Board Of Canada. (2018). An Analysis Of The Global Value Chain For Indonesian Coffee Exports. The Canada?Indonesia Trade And Private Sector Assistance (TPSA) Project, (February).
  16. Wong, W. P., & Wong, K. Y. (2007). Supply chain performance measurement system using DEA modeling. Industrial Management and Data Systems, 107(3), 361?381. https://doi.org/10.1108/02635570710734271
  17. Wong, W. P. (2008). A review on benchmarking of supply chain performance measures, 15(1), 25?51. https://doi.org/10.1108/14635770810854335
  18. (2017). Competitiveness Of Export Footwear Industry Between Indonesia And China In The United States Market In 2011-2014. JOM FISIP Vol. 4 No. 2, 4(2), 1?16.
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[Wilda Sukmawati, Machfud, Ono Suparno and Aji Hermawan (2019); MEASUREMENT OF SUPPLY CHAIN PERFORMANCE USING DATA ENVELOPMENT ANALYSIS (DEA) METHOD IN THE DISTRICT AND CITY OF BOGOR Int. J. of Adv. Res. 7 (Nov). 222-227] (ISSN 2320-5407). www.journalijar.com

Wilda Sukmawati
Departement of Agricultural Industrial Technology, Bogor Agricultural University, Dramaga, Bogor-West Java, Indonesia


Article DOI: 10.21474/IJAR01/9996       DOI URL: http://dx.doi.org/10.21474/IJAR01/9996

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