Open Access
RAIRO-Oper. Res.
Volume 58, Number 1, January-February 2024
Page(s) 881 - 908
Published online 22 February 2024
  • L.H. Wang, Research on farmers’ credit improvement mechanism for external financing of agricultural supply chain. Ph.D. thesis, China Agricultural University (2017). [Google Scholar]
  • T.R. Wang, Q.G. Lan and Y.Z. Chu, Supply chain financing model: based on China’s agricultural products supply chain. Appl. Mech. Mater. 380 (2013) 4417–4421. [CrossRef] [Google Scholar]
  • F. Ye, J.H. Huang and Q. Lin, Optimal decision making of farmers in a contract farming supply chain under financial constraints. Syst. Eng. Theory Pract. (2017) 1467–1478. [Google Scholar]
  • A. Mondal and S.K. Roy, Application of choquet integral in interval type-2 pythagorean fuzzy sustainable supply chain management under risk. Int. J. Intell. Syst. 37 (2022) 217–263. [CrossRef] [Google Scholar]
  • H. Barman, S.K. Roy, L. Sakalauskas and G.-W. Weber, Inventory model involving reworking of faulty products with three carbon policies under neutrosophic environment. Adv. Eng. Inf. 57 (2023) 102081. [CrossRef] [Google Scholar]
  • A. Mondal, B.K. Giri and S.K. Roy, An integrated sustainable bio-fuel and bio-energy supply chain: a novel approach based on dematel and fuzzy-random robust flexible programming with me measure. Appl. Energy 343 (2023) 121225. [CrossRef] [Google Scholar]
  • Q. Lin and F. Ye, Nash negotiation model of “company+farmers”-type order agriculture supply chain. Syst. Eng. Theory Pract. 4 (2014) 1769–1778. [Google Scholar]
  • H. Guo, R.W. Jolly and J. Zhu, Contract farming in china: perspectives of farm households and agribusiness firms. Comp. Econ. Stud. 49 (2007) 285–312. [CrossRef] [Google Scholar]
  • F. Ye and Z.G. Cai, Research on “company+farmer” contract farming supply chain decision model with two way compensation mechanism. Oper. Res. Manage. 27 (2018) 186–193. [Google Scholar]
  • L.M. Young and J.E. Hobbs, Vertical linkages in agri-food supply chains: changing roles for producers, commodity groups, and government policy. Appl. Econ. Perspect. Policy 24 (2002) 428–441. [Google Scholar]
  • G.H. Hu and M. Zheng, Discussion on the operation mode and revenue distribution of agricultural supply chain finance. Rural Econ. (2013) 45–49. [Google Scholar]
  • S.G. Timme and C. Williams-Timme, The financial-SCM connection. Supply Chain Manage. Rev. 4 (2000) 33–40. [Google Scholar]
  • C. Miller, Agricultural value chain finance strategy and design. Technical note (2012). [Google Scholar]
  • T. Breckwoldt, Management of grain storage in Old Babylonian Larsa. Archiv für Orientforschung (1995) 64–88. [Google Scholar]
  • P. Moers, Cereal banks: receipt of deposit as a method for improving liquidity at the local level. Fundation Desar-rollo Empresarial 6 (1999) 33–36. [Google Scholar]
  • C. Joerg, Securing the frontier supplies commodity financing. Trade Finan. 9 (2002) 6–8. [Google Scholar]
  • P. Bogetoft and H.B. Olesen, Ten rules of thumb in contract design: lessons from Danish agriculture. Eur. Rev. Agric. Econ. 29 (2002) 185–204. [CrossRef] [Google Scholar]
  • B. Kazaz and S. Webster, The impact of yield-dependent trading costs on pricing and production planning under supply uncertainty. Manuf. Serv. Oper. Manage. 13 (2011) 404–417. [CrossRef] [Google Scholar]
  • L. Dries, E. Germenji, N. Noev and J.F. Swinnen, Farmers, vertical coordination, and the restructuring of dairy supply chains in Central and Eastern Europe. World Dev. 37 (2009) 1742–1758. [CrossRef] [Google Scholar]
  • Y. Chen, H. Tu and Y. Zeng, Loan pricing and production regulation mechanism of agricultural supply chain finance. Syst. Eng. Theory Pract. 38 (2018) 1706–1716. [Google Scholar]
  • L. Deng, W. Xu and J. Luo, Optimal loan pricing for agricultural supply chains from a green credit perspective. Sustainability 13 (2021) 12365. [CrossRef] [Google Scholar]
  • S. Ji, L. Jiang and D. Zhao, A dual-channel supply chain ordering and pricing strategy considering consumer preferences under different financing models. Ind. Eng. Manage. 22 (2017) 1–9. [Google Scholar]
  • L. Zhu, G. Wang and C. Wang, Operation decision of “company+farmers” order agriculture supply chain under different financing models. Ind. Eng. Manage. 24 (2019) 16–21+31. [Google Scholar]
  • L. Shi, H. Peng and J. Cong, Research on internal and external financing strategies of order agriculture supply chain under financial constraints. Oper. Res. Manage. 29 (2020) 62–69. [Google Scholar]
  • N. Guo and W. Wang, Choice of supply chain financing methods for order agriculture under purchase price uncertainty-external financing vs. internal financing. Oper. Res. Manage. 29 (2020) 188–196+230. [Google Scholar]
  • C. O’Toole and T. Hennessy, Do decoupled payments affect investment financing constraints? Evidence from irish agriculture. Food Policy 56 (2015) 67–75. [CrossRef] [Google Scholar]
  • H. Peng and T. Pang, Research on financing and operation strategy of order agriculture supply chain under agricultural subsidy policy. J. Manage. Eng. 34 (2020) 155–163. [Google Scholar]
  • J. Huang and Q. Lin, Guaranteed insurance and government subsidy mechanism in order agriculture supply chain financing under output uncertainty, China. Manage. Sci. 27 (2019) 53–65. [Google Scholar]
  • S.S. Sana, Price competition between green and non green products under corporate social responsible firm. J. Retail. Consum. Serv. 55 (2020) 102118. [CrossRef] [Google Scholar]
  • S.S. Sana, The effects of green house gas costs on optimal pricing and production lotsize in an imperfect production system. RAIRO: Oper. Res. 57 (2023) 2209–2230. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • A. Haverkort and A. Verhagen, Climate change and its repercussions for the potato supply chain. Potato Res. 51 (2008) 223–237. [CrossRef] [Google Scholar]
  • J.-S. Song, C.A. Yano and P. Lerssrisuriya, Contract assembly: dealing with combined supply lead time and demand quantity uncertainty. Manuf. Serv. Oper. Manage. 2 (2000) 287–296. [CrossRef] [Google Scholar]
  • J.-S. Song and D.D. Yao, Performance analysis and optimization of assemble-to-order systems with random lead times. Oper. Res. 50 (2002) 889–903. [CrossRef] [MathSciNet] [Google Scholar]
  • G.A. De Croix, J.-S. Song and P.H. Zipkin, Managing an assemble-to-order system with returns. Manuf. Serv. Oper. Manage. 11 (2009) 144–159. [CrossRef] [Google Scholar]
  • L. Jiang and Y. Wang, Supplier competition in decentralized assembly systems with price-sensitive and uncertain demand. Manuf. Ser. Oper. Manage. 12 (2010) 93–101. [CrossRef] [Google Scholar]
  • W. Chen, J. Li and X. Jin, The replenishment policy of agri-products with stochastic demand in integrated agricultural supply chains. Expert Syst. App. 48 (2016) 55–66. [CrossRef] [Google Scholar]
  • H. Yang, D. Zhang and H. Wang, Research on benefit sharing in contract farming cooperation – an analysis based on price fluctuation and default risk of agricultural products. Price Theory Pract. 10 (2019) 38–42. [Google Scholar]
  • S.S. Sana, Sale through dual channel retailing system – a mathematical approach. Sustainability Anal. Model. 2 (2022) 100008. [CrossRef] [Google Scholar]
  • H. Gurnani and Y. Gerchak, Coordination in decentralized assembly systems with uncertain component yields. Eur. J. Oper. Res. 176 (2007) 1559–1576. [CrossRef] [Google Scholar]
  • F. Ye and J. Wang, Research on the negotiation model of “company+farmers” type order agriculture supply chain under output uncertainty. Oper. Res. Manage. 26 (2017) 82–91. [Google Scholar]
  • X. Zhou, Research on government subsidy mechanism in “enterprise+farmers” guaranteed price contract under output uncertainty (2020). [Google Scholar]
  • H. Liu, Research on agricultural insurance and government subsidy mechanism under agricultural supply chain (2022). [Google Scholar]
  • Y. Cao, Z. Dai and K. Wu, Research on pro-poor financing strategies for agricultural supply chains under output stochasticity. Oper. Res. Manage. 31 (2022) 131–138. [Google Scholar]
  • K. Inderfurth and S. Vogelgesang, Concepts for safety stock determination under stochastic demand and different types of random production yield. Eur. J. Oper. Res. 224 (2013) 293–301. [CrossRef] [Google Scholar]
  • K. Qin and T. Li, Research on order agriculture supply chain under multiple uncertainties. Econ. Issues 2 (2016) 111–116. [Google Scholar]
  • Y. Chen, The impact of different interest linkages on supply chain operation of contract farming under stochastic output and demand (2021). [Google Scholar]
  • S. Gokarn and T.S. Kuthambalayan, Creating sustainable fresh produce supply chains by managing uncertainties. J. Cleaner Prod. 207 (2019) 908–919. [CrossRef] [Google Scholar]
  • Q. Wang and D.-B. Tsao, Supply contract with bidirectional options: the buyer’s perspective. Int. J. Prod. Econ. 101 (2006) 30–52. [CrossRef] [Google Scholar]
  • A. Gomez Padilla and T. Mishina, Supply contract with options. Int. J. Prod. Econ. 122 (2009) 312–318. [CrossRef] [Google Scholar]
  • N. Xu and L. Nozick, Modeling supplier selection and the use of option contracts for global supply chain design. Comput. Oper. Res. 36 (2009) 2786–2800. [CrossRef] [Google Scholar]
  • H. Xu, Managing production and procurement through option contracts in supply chains with random yield. Int. J. Prod. Econ. 126 (2010) 306–313. [Google Scholar]
  • L. Ling, X. Guo, Z. Hu and L. Liang, Risk-sharing contract for agricultural supply chain based on stochastic output and stochastic demand. Chin. Manage. Sci. 21 (2013) 50–57. [Google Scholar]
  • S.S. Sana, A structural mathematical model on two echelon supply chain system. Ann. Oper. Res. 315 (2022) 1997–2025. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Jiang and S. Li, Green supply chain game model and revenue sharing contract considering product greenness. Chin. Manage. Sci. 23 (2015) 169–176. [Google Scholar]
  • Y. Chen, L. Xiong and J. Dong, A closed-loop supply chain coordination mechanism based on mean-CVaR. Chin. Manage. Sci. 25 (2017) 68–77. [Google Scholar]
  • B. Yang, W. Zhu and H. Zhao, Research on supplier-led supply chain finance model. Finan. Res. 12 (2016) 175–190. [Google Scholar]
  • X. Sun and G. Zhao, Research on inventory pledge rate considering supply chain credit level. Chin. Manage. Sci. 23 (2015) 77–84. [Google Scholar]
  • X. Jin, W. Yuan, J. Wu, J. Li and Y. Wang, Research on risk control of supply chain finance based on revenue sharing-bidirectional option contract. Chin. Manage. Sci. 28 (2020) 68–78. [Google Scholar]
  • X. Cai, J. Chen, Y. Xiao, X. Xu and G. Yu, Fresh-product supply chain management with logistics outsourcing. Omega 41 (2013) 752–765. [Google Scholar]
  • Y. Cao, Z. Dai and K. Wu, Research on pro-poor financing strategies for agricultural supply chains under output stochasticity. Oper. Res. Manage. 31 (2022) 131–138. [Google Scholar]
  • X. Cai, J. Chen, Y. Xiao and X. Xu, Optimization and coordination of fresh product supply chains with freshness-keeping effort. Prod. Oper. Manage. 19 (2010) 261–278. [CrossRef] [Google Scholar]
  • L. Peng, On the amplifying effects of financial moral hazard in the agricultural supply chain. Finan. Res. (2018) 88–103. [Google Scholar]
  • R.D. Raut, A. Gotmare, B.E. Narkhede, U.H. Govindarajan and S.U. Bokade, Enabling technologies for industry 4.0 manufacturing and supply chain: concepts, current status, and adoption challenges. IEEE Eng. Manage. Rev. 48 (2020) 83–102. [CrossRef] [Google Scholar]
  • A. Sharif, C. Aloui and L. Yarovaya, Covid-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the us economy: fresh evidence from the wavelet-based approach. Int. Rev. Finan. Anal. 70 (2020) 101496. [CrossRef] [Google Scholar]
  • H. Barman, M. Pervin and S.K. Roy, Impacts of green and preservation technology investments on a sustainable EPQ model during covid-19 pandemic. RAIRO: Oper. Res. 56 (2022) 2245–2275. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • A. Mondal and S.K. Roy, Multi-objective sustainable opened-and closed-loop supply chain under mixed uncertainty during covid-19 pandemic situation. Comput. Ind. Eng. 159 (2021) 107453. [CrossRef] [Google Scholar]

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