Performance-Based Adaptive Revenue Sharing in the Indonesian Natural Rubber Supply Chain: Model Design, AHP Calibration, and Simulation Evidence
DOI:
https://doi.org/10.56294/saludcyt20262594Keywords:
adaptive revenue sharing, dry rubber content, performance-based contracting, supply chain coordination, smallholders, IndonesiaAbstract
Introduction: The study addressed income inequities in Indonesia’s natural rubber supply chain by redesigning revenue sharing among farmers, collectors, processors and exporters in Padang Lawas, North Sumatra, aligning income allocation with observable contributions and risk.
Methods: The study employed a developmental research approach to specify a performance-based, adaptive revenue-sharing model, calibrate it with Analytic Hierarchy Process (AHP) weights, and test it through multi-scenario simulations using field parameters on dry rubber content, market price, on-time delivery and actor-specific risk; the stability and consistency of the AHP weighting vector were assessed.
Results: The AHP weights were stable, prioritising product quality, followed by price and timeliness, while risk received a smaller but meaningful weight; the consistency ratio remained below 0,10. Relative to a fixed baseline split, the adaptive mechanism reallocated income toward verified performance improvements, increasing farmers’ share from 11 % to 22 % under a moderate-price scenario with high on-time delivery, while preserving incentive compatibility and channel coordination.
Conclusions: The study transformed revenue sharing from a static proportional rule into a transparent, auditable, learning-oriented mechanism that operationalised distributive justice through normalised performance indices. The model could be encoded in contract clauses with measurable quality metrics and public price benchmarks and implemented with low-cost traceability; broader field pilots and multi-region validation were required to generalise the results.
References
1. Sudaryanto T, Erwidodo, Dermoredjo SK, Purba HJ, Rachmawati RR, Irawan AR. Regional rural transformation and its association with household income and poverty incidence in Indonesia in the last two decades. Journal of Integrative Agriculture. 2023;22(12):3596–609. https://doi.org/10.1016/j.jia.2023.11.029 DOI: https://doi.org/10.1016/j.jia.2023.11.029
2. Enahoro D, Mason-D’Croz D, Mul M, Rich KM, Robinson TP, Thornton P, et al. Supporting sustainable expansion of livestock production in South Asia and Sub-Saharan Africa: Scenario analysis of investment options. Global Food Security. 2019;20:114–21. https://doi.org/10.1016/j.gfs.2019.01.001 DOI: https://doi.org/10.1016/j.gfs.2019.01.001
3. Gereffi G, Lee J. Economic and Social Upgrading in Global Value Chains and Industrial Clusters: Why Governance Matters. Journal of Business Ethics. 2016;133(1):25–38. https://doi.org/10.1007/s10551-014-2373-7 DOI: https://doi.org/10.1007/s10551-014-2373-7
4. Ningsih RD, Yasin Muhammad, Noor A. Rice productivity on tidal swampland in the agricultural assisitance area program in Barito Kuala Regency South Kalimantan. IOP Conf Ser Earth Environ Sci. 2020 Apr;484(1):12123. https://doi.org/10.1088/1755-1315/484/1/012123 DOI: https://doi.org/10.1088/1755-1315/484/1/012123
5. Hidayati DR, Garnevska E, Childerhouse P. Sustainable agrifood value chain—transformation in developing countries. Sustainability. 2021;13(22):12358. https://doi.org/10.3390/su132212358 DOI: https://doi.org/10.3390/su132212358
6. Peña-Orozco DL, Desgourdes C, Gonzalez-Feliu J, Velez-Osorio E, Cardona-Muñoz JD. Harvest planning for efficient and integrated food supply chains: A combined project-operations management approach. Supply Chain Forum: An International Journal. 2025;26(1):73–87. https://doi.org/10.1080/16258312.2024.2433940 DOI: https://doi.org/10.1080/16258312.2024.2433940
7. Kissi EA, Herzig C. The implications of governance factors for economic and social upgrading in Ghana’s cocoa value chain. Agricultural and Food Economics. 2024;12(1):1. https://doi.org/10.1186/s40100-024-00295-w DOI: https://doi.org/10.1186/s40100-024-00295-w
8. Perdana T, Tjahjono B, Kusnandar K, Sanjaya S, Wardhana D, Hermiatin FR. Fresh agricultural product logistics network governance: insights from small-holder farms in a developing country. International Journal of Logistics Research and Applications. 2023 Dec 2;26(12):1761–84. https://doi.org/10.1080/13675567.2022.2107625 DOI: https://doi.org/10.1080/13675567.2022.2107625
9. Brander M, Bernauer T, Huss M. Trade policy announcements can increase price volatility in global food commodity markets. Nat Food [Internet]. 2023;4(4):331–40. https://doi.org/10.1038/s43016-023-00729-6 DOI: https://doi.org/10.1038/s43016-023-00729-6
10. Wu D, Lv S, Jiang M, Song H. Using channel pruning-based YOLO v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments. Computers and Electronics in Agriculture. 2020;178:105742. https://doi.org/10.1016/j.compag.2020.105742 DOI: https://doi.org/10.1016/j.compag.2020.105742
11. Cohen AJ, Vicol M, Pol G. Living under value chains: The new distributive contract and arguments about unequal bargaining power. Journal of Agrarian Change. 2022 Jan 1;22(1):179–96. https://doi.org/10.1111/joac.12466 DOI: https://doi.org/10.1111/joac.12466
12. Montoro P, Alami S, Haris U, Nababan CR, Oktavia F, Penot E, et al. Co-designing sustainable and resilient rubber cultivation systems through participatory research with stakeholders in Indonesia. Sustainability. 2025;17(15):6884. https://doi.org/10.3390/su17156884 DOI: https://doi.org/10.3390/su17156884
13. Cui W, Xie N, Lam EWF, Hahn-Stromberg V, Liu N, Zhang H, et al. High expression of cytoplasmic FOXO3 protein associated with poor prognosis of rectal cancer patients: A study from Swedish clinical trial of preoperative radiotherapy to big database analysis. Heliyon. 2023 May 1;9(5). https://doi.org/10.1016/j.heliyon.2023.e15342 DOI: https://doi.org/10.1016/j.heliyon.2023.e15342
14. Lorenzen M, Orozco-Ramírez Q, Ramírez-Santiago R, Garza GG. The forest transition as a window of opportunity to change the governance of common-pool resources: The case of Mexico’s Mixteca Alta. World Development. 2021;145:105516. https://doi.org/10.1016/j.worlddev.2021.105516 DOI: https://doi.org/10.1016/j.worlddev.2021.105516
15. Rostami S, Zór K, Zhai DS, Viehrig M, Morelli L, Mehdinia A, et al. High-throughput label-free detection of ochratoxin A in wine using supported liquid membrane extraction and Ag-capped silicon nanopillar SERS substrates. Food Control. 2020;113:107183. https://doi.org/10.1016/j.foodcont.2020.107183 DOI: https://doi.org/10.1016/j.foodcont.2020.107183
16. Springer E. Caught between winning repeat business and learning: Reactivity to output indicators in international development. World Development. 2021;144:105506. https://doi.org/10.1016/j.worlddev.2021.105506 DOI: https://doi.org/10.1016/j.worlddev.2021.105506
17. Dixit V, Verma P, Tiwari MK. Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure. International Journal of Production Economics. 2020;227:107655. https://doi.org/10.1016/j.ijpe.2020.107655 DOI: https://doi.org/10.1016/j.ijpe.2020.107655
18. Kyriakakis NA, Aronis S, Marinaki M, Marinakis Y. A GRASP/VND algorithm for the energy minimizing drone routing problem with pickups and deliveries. Computers & Industrial Engineering. 2023;182:109340. https://doi.org/10.1016/j.cie.2023.109340 DOI: https://doi.org/10.1016/j.cie.2023.109340
19. Wu W, Ma J, Liu R, Jin W. Multi-class hazmat distribution network design with inventory and superimposed risks. Transportation Research Part E: Logistics and Transportation Review. 2022;161:102693. https://doi.org/10.1016/j.tre.2022.102693 DOI: https://doi.org/10.1016/j.tre.2022.102693
20. Yang T, Sun Y, Li X, Li Q. An ecosystem elasticity perspective of paddy ecosystem sustainability evaluation: The case of China. Journal of Cleaner Production. 2021;295:126292. https://doi.org/10.1016/j.jclepro.2021.126292 DOI: https://doi.org/10.1016/j.jclepro.2021.126292
21. Chen KS, Wang CH, Tan KH, Chiu SF. Developing one-sided specification six-sigma fuzzy quality index and testing model to measure the process performance of fuzzy information. International Journal of Production Economics. 2019;208:560–5. https://doi.org/10.1016/j.ijpe.2018.12.025 DOI: https://doi.org/10.1016/j.ijpe.2018.12.025
22. Shi Y, Wang F. Revenue and risk sharing mechanism design in agriculture supply chains considering the participation of agricultural cooperatives. Systems. 2023;11(8):423. https://doi.org/10.3390/systems11080423 DOI: https://doi.org/10.3390/systems11080423
23. Ramos E, Coles PS, Chavez M, Hazen B. Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry. Benchmarking: An International Journal. 2021 Aug 13;29(5):1484–512. https://doi.org/10.1108/BIJ-10-2020-0544 DOI: https://doi.org/10.1108/BIJ-10-2020-0544
24. Noviyanti, Rumengan AE, Khadaffi M, Wibisono C, Dewi NP, Satriawan B, et al. Enhancing job satisfaction in hospitals: The role of communication, career development, continuous dedication and compensation by productivity as a mediator. Int Res J Multidiscip Scope. 2025;6(3):187–200. https://doi.org/10.47857/irjms.2025.v06i03.04443 DOI: https://doi.org/10.47857/irjms.2025.v06i03.04443
25. Irawati I, Hermansyah, Dewi FS, Sari CY, Parisma WI, Maulina D, et al. The role of individual characteristics and personal hygiene with dermatitis complaints in fishermen. Univ J Public Health. 2024;12(6):1166–73. https://doi.org/10.13189/ujph.2024.120613 DOI: https://doi.org/10.13189/ujph.2024.120613
26. Ufer D, Ortega DL, Wolf CA. Economic foundations for the use of biotechnology to improve farm animal welfare. Trends in Food Science & Technology. 2019;91:129–38. https://doi.org/10.1016/j.tifs.2019.07.002 DOI: https://doi.org/10.1016/j.tifs.2019.07.002
27. Anizar A, Ishak A, Gurusinga RG, Hermansyah. Design of worker rotation for a precast concrete pole factory based on mental workload. Int J Saf Secur Eng. 2025;15(1):151–6. https://doi.org/10.18280/ijsse.150116 DOI: https://doi.org/10.18280/ijsse.150116
28. Ivanov D. Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Ann Oper Res. 2022;319(1):1411–31. https://doi.org/10.1007/s10479-020-03640-6 DOI: https://doi.org/10.1007/s10479-020-03640-6
29. Pexas G, Mackenzie SG, Wallace M, Kyriazakis I. Cost-effectiveness of environmental impact abatement measures in a European pig production system. Agricultural Systems. 2020;182:102843. https://doi.org/10.1016/j.agsy.2020.102843. DOI: https://doi.org/10.1016/j.agsy.2020.102843
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