Optimal Quality Inspections of Agricultural Foods in Farm-to-Consumer Direct Selling: Game-Based Approach

Document Type : Original Research

Authors
G. Han
K. Li
School of International Relations and Public Affairs, Fudan University, 220 Hadan Road, Shanghai 200433, P. R. China.
10.22034/JAST.26.5.929
Abstract
Farm-to-Consumer Direct Selling (F2C) programs allow consumers to pre-order a share of a farm’s produce so that the farmer benefits from guaranteed sales at a pre-agreed price, while the consumer benefits from receiving produce with a certain quality and the knowledge that they are supporting a local farmer. However, agricultural foods are a type of credence goods, and consumers have to trust that the supplied produce is indeed, as claimed, cultivated on the farm in accordance with the agreed cultivation practices, such as organic. In this study, we attempt to provide inspection bodies with a strategic inspection rate that respects the quality commitments of farms and examine how the inspection strategy influences consumers’ benefits. We derive the equilibrium decisions of inspection bodies and farms based on a game model, using a closed-form analysis to develop the optimal inspection rate at which a farm maintains its commitment to food quality. Specifically, the inspection rate increases with food quality when the inspection cost is below a certain threshold. However, inspection bodies tend to dispense when the inspection cost exceeds a specified value. The consumer surplus in quality increases with the inspection rate when the inspection rate is below a certain threshold. However, when the inspection rate exceeds the threshold, additional inspections do not have marginal effects on consumer surplus in quality.

Keywords

Subjects

1. Cechin A, da Silva Araújo V, Amand L. Exploring the synergy between Community Supported Agriculture and agroforestry: Institutional innovation from smallholders in a brazilian rural settlement [J]. Journal of Rural Studies, 2021, 81: 246-258.
2. Lacoste M, Cook S, McNee M, et al. On-Farm Experimentation to transform global agriculture[J]. Nature Food, 2022, 3(1): 11-18.
3. Chenarides L, Grebitus C, Lusk J L, et al. Food consumption behavior during the COVID‐19 pandemic[J]. Agribusiness, 2021, 37(1): 44-81.
4. Hang L, Ullah I, Kim D H. A secure fish farm platform based on blockchain for agriculture data integrity[J]. Computers and Electronics in Agriculture, 2020, 170: 105251.
5. Wang M, Kumar V, Ruan X, et al. Sustainability concerns on consumers’ attitude towards short food supply chains: An empirical investigation[J]. Operations Management Research, 2022, 15(1-2): 76-92.
6. Zhang T, Choi T M. Optimal consumer sales tax policies for online‐offline retail operations with consumer returns[J]. Naval Research Logistics (NRL), 2021, 68(6): 701-720.
7. Ecfr, Code of federal regulations, available at https://www.Ecfr.Gov/current/title-7/subtitle-A/part-3#3.91. Last accessed on 2022.8.13
8. Liebman, J. B., Mahoney, N. Do expiring budgets lead to wasteful year-end spending? Evidence from federal procurement. American Economic Review, 2017,107(11) : 3510-3549.
9. Zhai, Y., Han, G.The effect of the inspection information sharing policy on quality‐oriented food production in online commerce. Managerial and Decision Economics, 2022, 43(1) :84-96.
10. Hansen, D. R., Mowen, M. M., Heitger, D. L. Cost management. Cengage Learning, 2021.
11. Hobbs, B. F., Pang, J. S. Nash-Cournot equilibria in electric power markets with piecewise linear demand functions and joint constraints. Operations Research, 2007, 55(1):113-127.
12. Liu, W., Kong, N., Wang, M., Zhang, L. Sustainable multi-commodity capacitated facility location problem with complementarity demand functions. Transportation Research Part E: Logistics and Transportation Review, 2021, 145:102165.
13. Cárdenas-Barrón, L. E., Mandal, B., Sicilia, J., San-José, L. A., & Abdul-Jalbar, B. Optimizing price, order quantity, and backordering level using a nonlinear holding cost and a power demand pattern. Computers & Operations Research, 2021, 133: 105339.
14. Deutsch L, Dyball R, Steffen W. Feeding cities: food security and ecosystem support in an urbanizing world[J]. Urbanization, biodiversity and ecosystem services: Challenges and opportunities: A global assessment, 2013: 505-537.
15. Van Dooren W, De Caluwe C, Lonti Z. How to measure public administration performance: A conceptual model with applications for budgeting, human resources management, and open government[J]. Public Performance & Management Review, 2012, 35(3): 489-508.
16. Fournier A J. Direct-selling farming and urban externalities: What impact on product quality and market size?[J]. Regional Science and Urban Economics, 2018, 70: 97-111.
17. USDA (United States Department of Agriculture), 2020 Local Food Marketing Practices Survey, available at https://www.nass.usda.gov/Publications/Highlights/2022/local-foods.pdf
18. Hansen A S. Subsistence solidarity and the extension of trust: Moral economies of organic farming in Northern China[J]. Journal of Current Chinese Affairs, 2019, 48(3): 301-321.
19. USDA (U.S. Department of Agriculture), A quarterly review of National Organic Program Enforcement Activities 2022, available at https://www.ams.usda.gov/sites/default/files/media/QuarterlyEnforcementReport2qt2022.pdf
20. FDA (U.S. Food and Drug Administration), Compliance & Enforcement (Food) 2023, available at https://www.fda.gov/food/compliance-enforcement-food
21. MARA (Ministry of Agriculture and Rural Affairs of the Peoples’ Republic of China), Implementation Rules for the Assessment Method of the Mayor's Responsibility System for the "Vegetable Basket" 2023, available at http://www.moa.gov.cn/govpublic/SCYJJXXS/202303/t20230302_6422087.htm
22. Aubert M, Enjolras G. Which Incentives for Direct Selling?-An Analysis of French farms[J]. Systèmes alimentaires, 2017, 2017(2): 115-141.
23. AP news (The Associated Press), Leader of largest US organic food fraud gets 10-year term, 2019 August 17. Available at https://apnews.com/article/9dbce7d3c042402b92ab5dfcce7e3cb9
24. Sharifzadeh MS, Abdollahzadeh G, Rezaei, R , Use of Biological Pest Control among Rice Farmers in Simorgh County of Mazandaran Province: Assessing Behavior Change for Promoting Adoption, Journal of Agricultural Science and Technology, 2021, 23(3): 515-530.
25. Malekhoseini A, Mirakzadeh AA, Salmanzadeh S. Study of Farmers' View on Ethics in Agriculture: The Case of Sonqur County, Journal of Agricultural Science and Technology, 2019,21:1721-1736.
26. Lotfi M, Shariatmadari F, Ahmadi H, et al. Estimation and prediction of metabolizable energy contents of wheat bran for poultry[J]. Journal of Agricultural Science and Technology, 2020, 22(4): 965-976.
27. Han X, Guang Y, Hang X. Optimal Decision of Fresh Agricultural Products’ Supply Chain Under Stochastic Demand and Online Pre-selling[C]//International conference on Variability of the Sun and sun-like stars: from asteroseismology to space weather. Singapore: Springer Nature Singapore, 2022: 231-241.
28. Filippi P, Jones E J, Wimalathunge N S, et al. An approach to forecast grain crop yield using multi-layered, multi-farm data sets and machine learning[J]. Precision Agriculture, 2019, 20: 1015-1029.
29. Akbarpour O, Dehghani H, Sorkhi B, et al. Evaluation of genotype× environment interaction in barley (Hordeum Vulgare L.) based on AMMI model using developed SAS program[J]. Journal of Agricultural Science and Technology, 2014, 16(4): 909-920.
30. Lotfi M, Shariatmadari F, Ahmadi H, et al. Estimation and prediction of metabolizable energy contents of wheat bran for poultry[J]. Journal of Agricultural Science and Technology, 2020, 22(4): 965-976.
31. Peng, Y., Yan, X., Zhou, A., Cheng, T. C. E., & Ji, M. (2023). Entry game in supply chains with yield uncertainty. Journal of Industrial and Management Optimization, 19(7) :4989-5010.
32. Yano C A, Lee H L. Lot sizing with random yields: A review[J]. Operations research, 1995, 43(2): 311-334.
33. Lau H, Shum P K C, Nakandala D, et al. A game theoretic decision model for organic food supplier evaluation in the global supply chains[J]. Journal of Cleaner Production, 2020, 242: 118536.
34. Tang S Y, Kouvelis P. Supplier diversification strategies in the presence of yield uncertainty and buyer competition[J]. Manufacturing & service operations management, 2011, 13(4): 439-451.
35. Rossiter A, Hester S M. Designing biosecurity inspection regimes to account for stakeholder incentives: An inspection game approach[J]. Economic Record, 2017, 93(301): 277-301.
36. Song C, Zhuang J. Modeling a Government-Manufacturer-Farmer game for food supply chain risk management[J]. Food control, 2017, 78: 443-455.
37. Lau H, Shum P K C, Nakandala D, et al. A game theoretic decision model for organic food supplier evaluation in the global supply chains[J]. Journal of Cleaner Production, 2020, 242: 118536.
38. Yao S, Zhu K. Combating product label misconduct: The role of traceability and market inspection[J]. European Journal of Operational Research, 2020, 282(2): 559-568.
Journal of Agricultural Science and Technology
Volume 26, Issue 5
September and October 2024
Pages 929-944