Analyzing the contributing factors of the rice supply chain in Gorontalo using SEM-PLS method
Ria Indriani, Supriyo Imran
Abstract: This research aims to analyze the factors that influence the performance of the rice supply chain in Gorontalo Province. The data was analyzed using the Structural Equation Model based on Partial Least Squares (SEM-PLS) method. The results indicate that rice availability, agility distribution, and interaction of rice prices affected the performance of the rice supply chain. The agility affects the availability and distribution of rice, and the rice prices impact consumers' satisfaction. However, this relationship is not always linear. Several external factors, such as the economic situation, technological developments, market competition, and consumer preference changes, can also impact the rice supply chain. In addition, the faster the flow of information, the more opportunistic nature and the independence of capital, causing farmers disloyal to one rice distributor, even though the integration process and long-term relationships have been intertwined.
Keywords: consumer satisfaction; distribution agility; integration process; rice supply chain; SEM-PLS
Citation: Indriani, R. & Imran, S. (2025). Analyzing the contributing factors of the rice supply chain in Gorontalo using SEM-PLS method. Bulg. J. Agric. Sci., 31(2), 261–273.
References: (click to open/close) | Ariani, D. & Dwiyanto, B. M. (2013). Analysis of the influence of supply chain management on company performance. A Study on small and medium enterprises in processed food industry with Padang Specialty, West Sumatra. Diponegoro Journal of Management, 2(3), 30-39. Asrin, S., Putri, T. A. & Utami, A. D. (2022). Transmission of rice prices in Indonesia during the Covid-19 Pandemic. Jurnal Agribisnis Indonesia,Journal of Indonesian Agribusiness, 10(1), 159-168. Bodendorf, F., Dentler, S. & Franke, J. (2023). Digitally enabled supply chain integration through business and process analytics. Industrial Marketing Management, 114(3),14-31. Brusset, X. & Teller, C. (2017). Supply chain capabilities, risks, and resilience. International Journal of Production Economics, 184, 59-68. Chang, H. H., Tsai, Y. C. & Hsu, C. H. (2013). E‐procurement and supply chain performance. Supply Chain Management: An International Journal, 18(1), 34-51. Chopra, S. & Meindl, P. (2016). Supply chain management: strategy. Planning and Operation, 15(5), 71-85. Courtonne, J. Y., Alapetite, J., Longaretti, P. Y., Dupré, D. & Prados, E. (2015). Downscaling material flow analysis: The case of the cereal supply chain in France. Ecological Economics, 118, 67-80. De Souza Miguel, P. L. & Brito, L. A. L. (2011). Supply chain management measurement and its influence on operational performance. Journal of Operations and Supply Chain Management, 4(2), 56-70. Dissanayake, C. K. & Cross, J. A. (2018). Systematic mechanism for identifying the relative impact of supply chain performance areas on the overall supply chain performance using SCOR model and SEM. International Journal of Production Economics, 201, 102-115. Djama, A., Indriani, R. & Moonti, A. (2023). Optimizing rice supply chain management for food security. A case study of Perum Bulog, Gorontalo Branch. Media Agribisnis, 7(1), 107-115. Djuric, I. & Götz, L. (2016). Export restrictions–Do consumers benefit? The wheat-to-bread supply chain in Serbia. Food Policy, 63, 112-123. Elyasi, A. & Teimoury, E. (2023). Applying Critical Systems Practice Meta-Methodology to improve sustainability in the rice supply chain of Iran. Sustainable Production and Consumption, 35, 453-468. Fitrawaty, H., W., Yusuf, M., & Maipita, I. (2023). A simulation of increasing rice price toward the disparity of income distribution: An evidence from Indonesia. Heliyon, 9(3). Geyi, D. A. G., Yusuf, Y., Menhat, M. S., Abubakar, T. & Ogbuke, N. J. (2020). Agile capabilities as necessary conditions for maximising sustainable supply chain performance: An empirical investigation. International Journal of Production Economics, 222, 107501. Ghozali, I. (2014). Structural Equation Modeling. Metode Alternatif dengan Partial Least Square. Badan Penerbit Universitas Diponegoro. Semarang. Hair, J. F., Hult, G. T. M., Ringle, C. M. & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modelling (PLS-SEM) (3e). Thousand Oaks, CA, Sage. Hermawan, W., Yusuf, M. & Maipita, I. (2023). A simulation of increasing rice price toward the disparity of income distribution: An evidence from Indonesia. Heliyon, 9(3), 1-14. Hu, B. & Feng, Y. (2017). Optimization and coordination of supply chain with revenue sharing contracts and service requirement under supply and demand uncertainty. International Journal of Production Economics, 183, 185-193. Indriani, R., Tenriawaru, A. N., Darma, R., Musa, Y. & Viantika, N. (2019). Supply chain mechanism of Chili in the Province of Gorontalo. Jurnal Sosial Ekonomi Pertanian, 15(1), 31-41. Indriani, R., Darma, R., Musa, Y., Tenriawaru, A. N. & Arsyad, M. (2020). Policy design of cayenne pepper supply chain development. Bulg. J. Agric. Sci., 26(3), 499–506. Jain, V., Kumar, S., Mostofi, A. & Arab Momeni, M. (2022). Sustainability performance evaluation of the E-waste closed-loop supply chain with the SCOR model. Waste management (New York, N.Y.), 147, 36–47. Kurtaliqi, F. C. L., Miltgen, G. & Viglia, G. P. S. (2024). Using advanced mixed methods approaches: Combining PLS-SEM and qualitative studies. Journal of Business Research, 172, 1-14. Lantarsih, R., Widodo, S., Darwanto, D. H., Lestari, S. B. & Paramita, S. (2011). National food security system: contributions of energy availability and consumption, and optimization of rice distribution. Analisis Kebijakan Pertanian, 9(1), 33-51. Liu, X., Guo, J., Xue, L., Zhao, D. & Liu, G. (2023). Where has all the rice gone in China? A farm-to-fork material flow analysis of rice supply chain with uncertainty analysis. Resources, Conservation and Recycling, 190, 106853. Maghfiroh, N. & Bantacut, T. (2023). Sustainable value of rice supply chain: A Systematic literature review and research agenda. Jurnal Teknologi Industri Pertanian, 33(1), 70-95. Marinagi, C., Trivellas, P. & Reklitis, P. (2015). Information quality and supply chain performance: The mediating role of information sharing. Procedia-Social and Behavioral Sciences, 175, 473-479. Maulana, A., Sjafruddin, A., Frazila, R. B. & Zukhruf, F. (2023). Rice supply chain network equilibrium optimization using the successive average method. Asian Transport Studies, 9, 199-204. Munir, M. M. & Dwiyanto, B. M. (2018). Analysis of factors affecting supply chain performance in micro, small, and medium culinary businesses in Kendal Regency. Jurnal Studi Manajemen Organisasi, 15(1), 44-54. My, N. H., Demont, M. & Verbeke, W. (2021). Inclusiveness of consumer access to food safety: Evidence from certified rice in Vietnam. Global Food Security, 28, 100491. Ngadino, S., Suharno, P. & Farida, L. (2017). The effect of products, price and service quality on customer satisfaction in “rice for the poors” program. Russian Journal of Agricultural and Socio-Economic Sciences, 72(12), 6-18. Perdana, T., Onggo, B. S., Sadeli, A. H., Chaerani, D., Achmad, A. L. H., Hermiatin, F. R. & Gong, Y. (2022). Food supply chain management in disaster events: A systematic literature review. International Journal of Disaster Risk Reduction, 79, 103183. Prajogo, D. & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514-522. Putro, P. A. W., Purwaningsih, E. K., Sensuse, D. I., Suryono, R. R. & Kautsarina (2021). Model and implementation of rice supply chain management: A literature review. Procedia Computer Science, 197, 453-460. Ringle, C., Silva, D. D. & Bido, D. (2015). Structural Equation Modeling with the SmartPLS. Brazilian Journal Of Marketing, 13(2). Soni, U., Jain, V. & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modelling approach. Computers & Industrial Engineering, 74, 11-25. Statistics Indonesia (2003). BPS. Gorontalo. Sugiyono, P. D. (2017). Research Methods: quantitative, qualitative, and R&D. Penebit CV. Alfabeta Bandung, 225(87), 48-61. Suliyanto, S. (2011). Differences in views on Likert Scale as Ordinal or Interval Scale. In: Prosiding Seminar Nasional Statistika Universitas Diponegoro 2011, 51-60. Program Studi Statistika FMIPA Undip. Suryaningrat, I. B., Amilia, W. & Choiron, M. (2015). Current condition of agroindustrial supply chain of cassava products: a case survey of East Java, Indonesia. Agriculture and Agricultural Science Procedia, 3, 137-142. Suud, N. R., Indriani, R. & Bakari, Y. (2021). Performance of coconut supply chain management in Central Sulawesi Province. Jurnal Sosial Ekonomi Pertanian, 17(1), 27-37. Tedjo, M., Sugito, S. & Suparti, S. (2017). Analysis of factors influencing the decision to use private transportation by students using the Partial Least Squares Approach. Case study at Diponegoro University, Semarang. Jurnal Gaussian, 6(2), 211-219. Umar, H. (2019). Research methods in company management. Jakarta, Gramedia Pustaka Utama. Vorst, V. D. (2006). Performance measurement in agri food supply chain networks. Netherlands: Logistics and Operations Research Group. Wong, K. K. K. (2013). Partial least squares structural equation modelling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32. Yi, Q., Sun, X., Tang, S., Xu, P., Pang, Y., Huang, X., Huang, Q., Huang, J. & Zhang, M. (2022). Comparation of Se accumulation and distribution of two rice (Oryza sativa L.) cultivars with high-and low-Se efficiency as affected by exogenous application of selenite. Journal of Cereal Science, 105, 103475. Zhao, N., Hong, J. & Lau, K. H. (2023). Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model. International Journal of Production Economics, 259, 108817. Zhong, T., Crush, J., Song, Y., Si, Z., Scott, S. & Peng, Y. (2023). Urban food insecurity and the impact of China's affordable food shop (AFS) program: A case study of Nanjing City. Applied Geography, 154, 102924. Zhou, Y. W., Fu, Y. S. & Wu, X. (2023). Value analysis with block chain-based information transparency system to eliminate information distortion. International Journal of Production Economics, 265, 109008. |
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| Date published: 2025-04-28
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