Supply chain performance measurement on small medium enterprise garment industry: application of supply chain operation reference

  • Qurtubi Qurtubi Universitas Islam Indonesia, Indonesia
  • Roaida Yanti Universitas Islam Indonesia, Indonesia
  • Meilinda F.N. Maghfiroh Department of Industrial Engineering, Universitas Islam Indonesia, Indonesia https://orcid.org/0000-0003-4228-1544
Abstract views: 849 , PDF downloads: 13407
Keywords: Garment industry, Performance measurement, Supply chain management, Supply chain operation reference, Analytical hierarchy process

Abstract

In 2020, the textile industry contributed nearly 7% of Indonesia's gross domestic product. The garment industry is still dominated by small and medium enterprises (SMEs) among the textile products. Although these SMEs are considered one of the economic pillars in Indonesia, many challenges require strategical scale-up to improve their competitiveness. One of the aspects to be improved is supply chain performance, as the supply chain controls material, information, and financial flow from both supply and demand sides. This study seeks to measure and evaluate supply chain performance in the garment industry, focusing the case on small and medium-scale enterprises. The Supply Chain Operation Reference (SCOR) is used for Key Performance Index (KPI) determinants. Performance measurement starts by determining the criteria based on the performance measurement literature and expert opinion. Then, the weight of each criterion on the performance score is determined using the Analytical Hierarchy Process (AHP). Paired comparison questionnaires for the criteria weighting were distributed to experts, and the answers were analyzed. The final performance value is obtained by multiplying the weight with the normalized performance value using the Snorm-De Boer formula. This study obtained 23 indicators from five processes: plan, make, source, deliver, and return, with the final value of SCM performance classified as good. The result can evaluate the company's current condition and propose a strategy to improve its performance.

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References

Indonesia Investments, “Textile and Garment Industry of Indonesia; More than Just Clothes, but Challenges Persist,” 2016. Available: https://www.indonesia-investments.com/news/todays-headlines/textile-and-garment-industry-of-indonesia-more-than-just-clothes-but-challenges-persist/item9405.

The Conference Board of Canada, “An Analysis of the Global Value Chain for Indonesian Apparel Exports,” 2018. Available: https://www.tpsaproject.com/research-report-an-analysis-of-the-global-value-chain-for-indonesian-apparel-exports/.

VisiGlobal, “The Crisis of Textile and Apparel Industry in Indonesia,” VisiGlobal.co.id, 2021. https://visiglobal.co.id/cantingnews/the-crisis-of-textile-and-apparel-industry-in-indonesia/2021/05/.

J. Ploenhad, P. Laoprawatchai, C. Thongrawd, and K. Jermsittiparsert, “Mediating role of competitive advantage on the relationship of supply chain management and organizational performance on the food industry of Thailand,” Int. J. Supply Chain Manag., vol. 8, no. 4, pp. 216–226, 2019. Available: http://ojs.excelingtech.co.uk/index.php/IJSCM/article/view/3452.

M. Mukhsin and T. Suryanto, “The Effect of Sustainable Supply Chain Management on Company Performance Mediated by Competitive Advantage,” Sustainability, vol. 14, no. 2, p. 818, Jan. 2022, doi: https://doi.org/10.3390/su14020818.

A. A. Khaddam, H. J. Irtaimeh, and B. S. Bader, “The effect of supply chain management on competitive advantage: The mediating role of information technology,” Uncertain Supply Chain Manag., vol. 8, no. 3, pp. 547–562, 2020, doi: https://doi.org/10.5267/j.uscm.2020.3.001.

A. Handayani and C. Y. Setyatama, “Analysis of Supply Chain Management Performance using SCOR and AHP Methods In Green Avenue Apartments of East Bekasi,” J. Appl. Sci. Eng. Technol. Educ., vol. 1, no. 2, pp. 141–148, 2019, doi: https://doi.org/10.35877/454ri.asci1241.

M. Tracey, J. Lim, and M. A. Vonderembse, “The impact of supply‐chain management capabilities on business performance,” Supply Chain Manag. An Int. J., vol. 10, no. 3, pp. 179–191, Jan. 2005, doi: https://doi.org/10.1108/13598540510606232.

A. Neely, M. Gregory, and K. Platts, “Erratum,” Int. J. Oper. Prod. Manag., vol. 25, no. 12, pp. 1228–1263, Dec. 2005, doi: https://doi.org/10.1108/01443570510633639.

D. Papakiriakopoulos and K. Pramatari, “Collaborative performance measurement in supply chain,” Ind. Manag. Data Syst., vol. 110, no. 9, pp. 1297–1318, Jan. 2010, doi: https://doi.org/10.1108/02635571011087400.

M. Comelli, P. Féniès, and N. Tchernev, “A combined financial and physical flows evaluation for logistic process and tactical production planning: Application in a company supply chain,” Int. J. Prod. Econ., vol. 112, no. 1, pp. 77–95, Mar. 2008, doi: https://doi.org/10.1016/j.ijpe.2007.01.012.

H. Chen, L. Amodeo, F. Chu, and K. Labadi, “Modeling and Performance Evaluation of Supply Chains Using Batch Deterministic and Stochastic Petri Nets,” IEEE Trans. Autom. Sci. Eng., vol. 2, no. 2, pp. 132–144, Apr. 2005, doi: https://doi.org/10.1109/TASE.2005.844537.

X. Fan, S. Zhang, L. Wang, Y. Yang, and K. Hapeshi, “An Evaluation Model of Supply Chain Performances Using 5DBSC and LMBP Neural Network Algorithm,” J. Bionic Eng., vol. 10, no. 3, pp. 383–395, Sep. 2013, doi: https://doi.org/10.1016/S1672-6529(13)60234-6.

W. Peng Wong and K. Yew Wong, “Supply chain performance measurement system using DEA modeling,” Ind. Manag. Data Syst., vol. 107, no. 3, pp. 361–381, Apr. 2007, doi: https://doi.org/10.1108/02635570710734271.

M. Tavana, H. Mirzagoltabar, S. M. Mirhedayatian, R. Farzipoor Saen, and M. Azadi, “A new network epsilon-based DEA model for supply chain performance evaluation,” Comput. Ind. Eng., vol. 66, no. 2, pp. 501–513, Oct. 2013, doi: https://doi.org/10.1016/j.cie.2013.07.016.

D. Kumar, J. Singh, O. P. Singh, and Seema, “A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices,” Math. Comput. Model., vol. 57, no. 11–12, pp. 2945–2960, Jun. 2013, doi: https://doi.org/10.1016/j.mcm.2013.03.002.

J. Jasbi, S. M. Seyed Hosseini, and N. PilehvariI, “An Adaptive Neuro Fuzzy Inference System for Supply Chain Agility Evaluation,” Int. J. Ind. Eng. Prod. Res., vol. 20, no. 4, pp. 187–196, 2010. Available: https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=171771.

J. Yang, “Integrative performance evaluation for supply chain system based on logarithm triangular fuzzy number-AHP method,” Kybernetes, vol. 38, no. 10, pp. 1760–1770, 2009, doi: https://doi.org/10.1108/03684920910994277.

S. Varma, S. Wadhwa, and S. G. Deshmukh, “Evaluating petroleum supply chain performance,” Asia Pacific J. Mark. Logist., vol. 20, no. 3, pp. 343–356, Jul. 2008, doi: https://doi.org/10.1108/13555850810890093.

S. K. Jakhar and M. K. Barua, “An integrated model of supply chain performance evaluation and decision-making using structural equation modelling and fuzzy AHP,” Prod. Plan. Control, vol. 25, no. 11, pp. 938–957, Aug. 2014, doi: https://doi.org/10.1080/09537287.2013.782616.

G. Stewart, “Supply‐chain operations reference model (SCOR): the first cross‐industry framework for integrated supply‐chain management,” Logist. Inf. Manag., vol. 10, no. 2, pp. 62–67, Jan. 1997, doi: https://doi.org/10.1108/09576059710815716.

M. A. Sellitto, G. M. Pereira, M. Borchardt, R. I. da Silva, and C. V. Viegas, “A SCOR-based model for supply chain performance measurement: application in the footwear industry,” Int. J. Prod. Res., vol. 53, no. 16, pp. 4917–4926, Aug. 2015, doi: https://doi.org/10.1080/00207543.2015.1005251.

F. R. Lima-Junior and L. C. R. Carpinetti, “Predicting supply chain performance based on SCOR ® metrics and multilayer perceptron neural networks,” Int. J. Prod. Econ., vol. 212, no. February, pp. 19–38, 2019, doi: https://doi.org/10.1016/j.ijpe.2019.02.001.

E. Kusrini, Q. Qurtubi, and N. H. Fathoni, “Design Performance Measurement Model for Retail Services Using Halal Supply Chain Operation Reference (SCOR): A Case Study in a Retail in Indonesia,” J. Adv. Manag. Sci., vol. 6, no. 4, pp. 218–221, 2018, doi: https://doi.org/10.18178/joams.6.4.218-221.

A. N. Waaly, A. Y. Ridwan, and M. D. Akbar, “Development of sustainable procurement monitoring system performance based on Supply Chain Reference Operation (SCOR) and Analytical Hierarchy Process (AHP) on leather tanning industry,” in MATEC Web of Conferences, Sep. 2018, vol. 204, p. 01008, doi: https://doi.org/10.1051/matecconf/201820401008.

P. Akkawuttiwanich and P. Yenradee, “Fuzzy QFD approach for managing SCOR performance indicators,” Comput. Ind. Eng., vol. 122, no. May, pp. 189–201, 2018, doi: https://doi.org/10.1016/j.cie.2018.05.044.

I. B. Bukhori, K. H. Widodo, and D. Ismoyowati, “Evaluation of Poultry Supply Chain Performance in XYZ Slaughtering House Yogyakarta Using SCOR and AHP Method,” Agric. Agric. Sci. Procedia, vol. 3, pp. 221–225, 2015, doi: https://doi.org/10.1016/j.aaspro.2015.01.043.

A. Moharamkhani, A. B. Amiri, and H. Mina, “Supply chain performance measurement using SCOR model based on interval-valued fuzzy TOPSIS,” Int. J. Logist. Syst. Manag., vol. 27, no. 1, p. 115, 2017, doi: https://doi.org/10.1504/IJLSM.2017.083225.

K. McCormack, M. Bronzo Ladeira, and M. Paulo Valadares de Oliveira, “Supply chain maturity and performance in Brazil,” Supply Chain Manag. An Int. J., vol. 13, no. 4, pp. 272–282, Jun. 2008, doi: https://doi.org/10.1108/13598540810882161.

R. Y. Kuswandi, A. Yanuar Ridwan, and R. M. El Hadi, “Development of Monitoring Reverse Logistic System for Leather Tanning Industry using Scor Model,” in 2018 12th International Conference on Telecommunication Systems, Services, and Applications (TSSA), Oct. 2018, pp. 1–5, doi: https://doi.org/10.1109/TSSA.2018.8708836.

S. Karami, R. Ghasemy Yaghin, and F. Mousazadegan, “Supplier selection and evaluation in the garment supply chain: an integrated DEA–PCA–VIKOR approach,” J. Text. Inst., vol. 112, no. 4, pp. 578–595, Apr. 2021, doi: https://doi.org/10.1080/00405000.2020.1768771.

V. D. Cruz, J. D. German, and M. E. G. Fenix, “Green supply chain operations reference (G-SCOR): An application for small garment manufacturers in the Philippines,” in Proceedings of the International Conference on Industrial Engineering and Operations Management, 2021, no. 2019, pp. 4187–4198. Available: http://www.ieomsociety.org/singapore2021/papers/749.pdf.

I. Vanany, P. Suwignjo, and D. Yulianto, “Design of Supply Chain Performance,” in International Conference on Operations and Supply Chain Management, 2005, no. January, pp. 78–86. Available: https://www.researchgate.net/publication/229035317.

P. K. Dey and W. Cheffi, “Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations,” Prod. Plan. Control, vol. 24, no. 8–9, pp. 702–720, Sep. 2013, doi: https://doi.org/10.1080/09537287.2012.666859.

A. Hasibuan et al., “Performance analysis of Supply Chain Management with Supply Chain Operation reference model,” J. Phys. Conf. Ser., vol. 1007, no. 1, 2018, doi: https://doi.org/10.1088/1742-6596/1007/1/012029.

Yuniaristanto, N. Ikasari, W. Sutopo, and R. Zakaria, “Performance Measurement in Supply Chain Using SCOR Model in the Lithium Battery Factory,” IOP Conf. Ser. Mater. Sci. Eng., vol. 943, no. 1, 2020, doi: https://doi.org/10.1088/1757-899X/943/1/012049.

P. W. Hapsari, H. Santoso, and D. Nurkertamanda, “SCOR and ANP methods for measuring supplier performance with sustainability principle of green supply chain management in furniture company PT. XYZ,” in Proceedings of the International Conference on Industrial Engineering and Operations Management, 2021, pp. 2203–2211. Available: http://www.ieomsociety.org/brazil2020/papers/698.pdf.

T. L. Saaty, Decision making for leaders: the analytic hierarchy process for decisions in a complex world. RWS publications, 1990. vailable: https://books.google.co.id/books?id=c8KqSWPFwIUC&dq

B. W. Permadi, A. Y. Ridwan, and W. Juliani, “SCOR-BSC Integrated Model for A Small Medium Enterprise Clothing Industry Using MTS-based Production Strategy in Indonesia,” IOP Conf. Ser. Mater. Sci. Eng., vol. 598, no. 1, pp. 1–9, 2019, doi: https://doi.org/10.1088/1757-899X/598/1/012079.

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Published
2022-06-14
How to Cite
[1]
Q. Qurtubi, R. Yanti, and M. F. Maghfiroh, “Supply chain performance measurement on small medium enterprise garment industry: application of supply chain operation reference”, j. sist. manaj. ind., vol. 6, no. 1, pp. 14-22, Jun. 2022.
Section
Research Article