Strategies for Enhancing Supply Chain Efficiency in the Agricultural Sector Through the Implementation of the SCOR Racetrack Method
Keywords:
supply chain, SCOR racetrack, efficiency, logistics, agriculturalAbstract
Supply chain efficiency in the agricultural sector is a key factor in enhancing productivity and competitiveness. This study aims to analyze strategies for improving supply chain efficiency through the implementation of the SCOR Racetrack method using a quantitative and descriptive approach. Data were collected through surveys and interviews with 150 respondents, consisting of farmers, distributors, and retailers in several agricultural regions in Indonesia. The analysis was conducted using Quantitative Method with Descriptive and Analytical Design methods and supply chain efficiency. The results indicate that the SCOR Racetrack method can improve operational efficiency by 30%, reduce delivery cycle time by 25%, and increase customer satisfaction by up to 40%. The implementation of digital technology in the supply chain contributes to an efficiency increase of 50.9%, while logistics costs decreased by 28% and product damage rates were reduced by 41.6%. Regional analysis shows that South Sulawesi exhibits the highest efficiency level, while West Sumatra still faces challenges in distribution optimization. Key factors influencing the success of implementation include collaboration among stakeholders, adoption of information technology, and enhancement of human resource capabilities. Thus, this study emphasizes that the SCOR Racetrack method can serve as a strategic solution in building a more efficient, sustainable, and competitive agricultural supply chain. Recommendations for future research include the development of an adaptive model based on artificial intelligence to improve demand forecasting and inventory management in the agricultural sector.
References
Adwiyah, R., Syaukat, Y., Indrawan, D., & Mulyati, H. (2023). Examining Sustainable Supply Chain Management (SSCM) Performance in the Palm Oil Industry with the Triple Bottom Line Approach. Sustainability, 15(18), 13362. https://doi.org/10.3390/su151813362
Agata, D. F., Winarno, S. T., & Indah, P. N. (2024). Planning The Needs Of Jackfruit Chips Using The Material Requirement Planning (MRP) Method At Cv Puri Pangan Lestari Malang City. Agroindustrial Technology Journal, 8(2), 112–122. https://doi.org/10.21111/atj.v8i2.12636
Ahmad, T. B. (2022). The Implementation Of Scor 12.0 Racetrack Model In Improving. https://dspace.uii.ac.id/handle/123456789/53214
Alimo, P. K. (2021). Reducing postharvest losses of fruits and vegetables through supply chain performance evaluation: an illustration of the application of SCOR model. International Journal of Logistics Systems and Management, 38(3), 384. https://doi.org/10.1504/IJLSM.2021.113438
Anggraeni, E. W., Handayati, Y., & Novani, S. (2022). Improving Local Food Systems through the Coordination of Agriculture Supply Chain Actors. Sustainability, 14(6), 3281. https://doi.org/10.3390/su14063281
Arjuna, A., Santoso, S., & Heryanto, R. M. (2022). Green Supply Chain Performance Measurement using Green SCOR Model in Agriculture Industry: A Case Study. Jurnal Teknik Industri, 24(1), 53–60. https://doi.org/10.9744/jti.24.1.53-60
Cao, Y., Yi, C., Wan, G., Hu, H., Li, Q., & Wang, S. (2022). An analysis on the role of blockchain-based platforms in agricultural supply chains. Transportation Research Part E: Logistics and Transportation Review, 163, 102731. https://doi.org/10.1016/j.tre.2022.102731
Chairany, N., Mail, A., & Fole, A. (2019). Evaluation of Supply Chain Performance through Integration of Hierarchical Based Measurement System and Traffic Light System: A Case Study Approach to Iron Sheet Factory. In Int. J Sup. Chain. Mgt (Vol. 8, Issue 5). https://doi.org/10.59160/ijscm.v8i5.2584
Chopra, S., Sodhi, M., & Lücker, F. (2021). Achieving supply chain efficiency and resilience by using multi‐level commons. Decision Sciences, 52(4), 817–832. https://doi.org/10.1111/deci.12526
Chu, T. T., & Pham, T. T. T. (2024). Vertical coordination in agri‐food supply chain and blockchain: A proposed framework solution for Vietnamese cashew nut business. Regional Science Policy & Practice, 16(3), 12576. https://doi.org/10.1111/rsp3.12576
Djekic, I., Batlle-Bayer, L., Bala, A., Fullana-i-Palmer, P., & Jambrak, A. R. (2021). Role of the Food Supply Chain Stakeholders in Achieving UN SDGs. Sustainability, 13(16), 9095. https://doi.org/10.3390/su13169095
Dong, Y., Ahmad, S. F., Irshad, M., Al-Razgan, M., Ali, Y. A., & Awwad, E. M. (2023). The Digitalization Paradigm: Impacts on Agri-Food Supply Chain Profitability and Sustainability. Sustainability, 15(21), 15627. https://doi.org/10.3390/su152115627
Fole, A. (2022). Peningkatan Kinerja Pada Industri Kerajinan Songko Recaa (Studi Kasus : UKM ISR Bone). https://dspace.uii.ac.id/handle/123456789/39404
Fole, A., Immawan, T., Kusrini, E., Mail, A., Dahlan, M., Alisyahbana, T., Pawennari, A., & Malik, R. (2024). Gap Analysis And Enhancement Strategy For Supply Chain Performance In The Handicraft Industry of ISR Bone SMES: A SCOR Racetrack Approach. Journal of Industrial Engineering Management, 9(3), 23–32. https://doi.org/10.33536/jiem.v9i3.1865
Fu, S., Liu, J., Tian, J., Peng, J., & Wu, C. (2023). Impact of Digital Economy on Energy Supply Chain Efficiency: Evidence from Chinese Energy Enterprises. Energies, 16(1), 568. https://doi.org/10.3390/en16010568
Ganeshkumar, C., Jena, S. K., Sivakumar, A., & Nambirajan, T. (2023). Artificial intelligence in agricultural value chain: review and future directions. Journal of Agribusiness in Developing and Emerging Economies, 13(3), 379–398. https://doi.org/10.1108/JADEE-07-2020-0140
Hermawan, D., Ginantaka, A., & Syarbaini, A. (2024). Risk Analysis Of Production Machinery Maintenance At Pt. Xyz Uses Fuzzy Failure Mode And Effect Analysis Method: Case Study In Amdk Industry. Agroindustrial Technology Journal, 8(2), 94–111. https://doi.org/10.21111/atj.v8i2.12116
Huo, Y., Wang, J., Guo, X., & Xu, Y. (2022). The Collaboration Mechanism of Agricultural Product Supply Chain Dominated by Farmer Cooperatives. Sustainability, 14(10), 5824. https://doi.org/10.3390/su14105824
Iffah, N., Lamatinulu, L., Rauf, N., Fole, A., & Erniyani, E. (2024). Redesain Kemasan Produk Bolu Cukke Dengan Menggunakan Metode QFD (Quality Function Deployment) pada Bolu Cukke Berkah Makassar. Journal of Industrial Engineering Innovation, 2(02), 49–55. https://doi.org/10.58227/jiei.v2i02.122
Juan, S.-J., Li, E. Y., & Hung, W.-H. (2022). An integrated model of supply chain resilience and its impact on supply chain performance under disruption. The International Journal of Logistics Management, 33(1), 339–364. https://doi.org/10.1108/IJLM-03-2021-0174
Khandelwal, C., Singhal, M., Gaurav, G., Dangayach, G. S., & Meena, M. L. (2021). Agriculture Supply Chain Management: A Review (2010–2020). Materials Today: Proceedings, 47, 3144–3153. https://doi.org/10.1016/j.matpr.2021.06.193
Khanfar, A. A. A., Iranmanesh, M., Ghobakhloo, M., Senali, M. G., & Fathi, M. (2021). Applications of Blockchain Technology in Sustainable Manufacturing and Supply Chain Management: A Systematic Review. Sustainability, 13(14), 7870. https://doi.org/10.3390/su13147870
Kramer, M. P., Bitsch, L., & Hanf, J. (2021). Blockchain and Its Impacts on Agri-Food Supply Chain Network Management. Sustainability, 13(4), 2168. https://doi.org/10.3390/su13042168
Krishnan, R., Yen, P., Agarwal, R., Arshinder, K., & Bajada, C. (2021). Collaborative innovation and sustainability in the food supply chain- evidence from farmer producer organisations. Resources, Conservation and Recycling, 168, 105253. https://doi.org/10.1016/j.resconrec.2020.105253
Kusrini, E., Helia, V. N., Miranda, S., & Asshiddiqi, F. (2023a). SCOR Racetrack to Improve Supply Chain Performance. Mathematical Modelling of Engineering Problems, 10(3), 915–920. https://doi.org/10.18280/mmep.100322
Kusrini, E., Helia, V. N., Miranda, S., & Asshiddiqi, F. (2023b). SCOR Racetrack to Improve Supply Chain Performance. Mathematical Modelling of Engineering Problems, 10(3), 915–920. https://doi.org/10.18280/mmep.100322
Kusrini, E., Safitri, K. N., & Fole, A. (2020). Design Key Performance Indicator for Distribution Sustainable Supply Chain Management. 2020 International Conference on Decision Aid Sciences and Application, DASA 2020, 738–744. https://doi.org/10.1109/DASA51403.2020.9317289
Marques-Perez, I., Rodríguez-Mañay, L., & Guaita-Pradas, I. (2022). Management improvement of the supply chain of perishable agricultural products by combining the Scor model and AHP methodology. The ecuadorian flower industry as a case study. Revista de La Facultad de Ciencias Agrarias UNCuyo, 54(2), 73–82. https://doi.org/10.48162/rev.39.084
Nha Trang, N. T., Nguyen, T.-T., Pham, H. V., Anh Cao, T. T., Trinh Thi, T. H., & Shahreki, J. (2022). Impacts of Collaborative Partnership on the Performance of Cold Supply Chains of Agriculture and Foods: Literature Review. Sustainability, 14(11), 6462. https://doi.org/10.3390/su14116462
Perdana, T., Kusnandar, K., Perdana, H. H., & Hermiatin, F. R. (2023). Circular supply chain governance for sustainable fresh agricultural products: Minimizing food loss and utilizing agricultural waste. Sustainable Production and Consumption, 41, 391–403. https://doi.org/10.1016/j.spc.2023.09.001
Putri, A. R. (2022). Strategi Mitigasi Risiko Pada Produksi Sayuran Organik Dari Aspek Ekonomi. Agroindustrial Technology Journal, 6(1), 79–88. https://doi.org/10.21111/atj.v6i1.7289
Rahmawan, A., Ma’rifat, T. N., & Azka, A. B. F. (2021). Efisiensi Proses Produksi Melalui Analisis Downtime Pada Proses Packaging (Studi Kasus: Cargill Indonesia Plant). Agroindustrial Technology Journal, 4(2), 157–166. https://doi.org/10.21111/atj.v4i2.5044
Ronaghi, M. H. (2021). A blockchain maturity model in agricultural supply chain. Information Processing in Agriculture, 8(3), 398–408. https://doi.org/10.1016/j.inpa.2020.10.004
Subhaktiyasa, P. G. (2024). Menentukan Populasi dan Sampel: Pendekatan Metodologi Penelitian Kuantitatif dan Kualitatif. Jurnal Ilmiah Profesi Pendidikan, 9(4), 2721–2731. https://doi.org/10.29303/jipp.v9i4.2657
Syufrian, B. (2022). Peningkatan Kinerja Perusahaan Pertanian Organik Dengan Metode Scor Racetrack (Studi Kasus : CV. Tani Organik Merapi). 1–102. https://dspace.uii.ac.id/handle/123456789/37948
Taşkıner, T., & Bilgen, B. (2021). Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review. Logistics, 5(3), 52. https://doi.org/10.3390/logistics5030052
Wang, G., Zhang, Z., Li, S., & Shin, C. (2023). Research on the Influencing Factors of Sustainable Supply Chain Development of Agri-Food Products Based on Cross-Border Live-Streaming E-Commerce in China. Foods, 12(17), 3323. https://doi.org/10.3390/foods12173323
Wibowo Putro, P. A., Purwaningsih, E. K., Sensuse, D. I., Suryono, R. R., & Kautsarina. (2022). Model and implementation of rice supply chain management: A literature review. Procedia Computer Science, 197, 453–460. https://doi.org/10.1016/j.procs.2021.12.161
Yadav, V. S., Singh, A. R., Raut, R. D., Mangla, S. K., Luthra, S., & Kumar, A. (2022). Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: A systematic literature review. Computers & Industrial Engineering, 169, 108304. https://doi.org/10.1016/j.cie.2022.108304
Yang, B., Subramanian, N., & Al Harthy, S. (2024). Are gender diversity issues a hidden problem in logistics and supply chain management? Building research themes through a systematic literature review. Journal of Purchasing and Supply Management, 30(5), 100937. https://doi.org/10.1016/j.pursup.2024.100937
Yang, Y., Pham, M. H., Yang, B., Sun, J. W., & Tran, P. N. T. (2022). Improving vegetable supply chain collaboration: a case study in Vietnam. Supply Chain Management: An International Journal, 27(1), 54–65. https://doi.org/10.1108/SCM-05-2020-0194
Yazdani, M., Gonzalez, E. D. R. S., & Chatterjee, P. (2021). A multi-criteria decision-making framework for agriculture supply chain risk management under a circular economy context. Management Decision, 59(8), 1801–1826. https://doi.org/10.1108/MD-10-2018-1088
Zheng, Y., Xu, Y., & Qiu, Z. (2023). Blockchain Traceability Adoption in Agricultural Supply Chain Coordination: An Evolutionary Game Analysis. Agriculture, 13(1), 184. https://doi.org/10.3390/agriculture13010184
Zhong, J., Cheng, H., Chen, X., & Jia, F. (2023). A systematic analysis of quality management in agri-food supply chains: a hierarchy of capabilities perspective. Supply Chain Management: An International Journal, 28(3), 619–637. https://doi.org/10.1108/SCM-12-2021-0547
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