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基于消费者效用的生鲜农产品供应链生鲜度激励机制研究

曹裕1 李业梅1 万光羽2

(1.中南大学商学院, 湖南长沙 410083)
(2.湖南大学经济与贸易学院, 湖南长沙 410083)

【摘要】生鲜供应链整体生鲜度的提升对减少浪费、提高供应链整体盈利水平及社会福利有重要意义。本文基于消费者效用理论研究了两供应商和单一零售商组成的供应链系统, 构建了单周期下生鲜农产品生鲜度激励模型, 模型以供应商为领导者, 采用Stackelberg博弈方法求解得到了均衡状态下供应商、零售商的最优定价策略及供应商新鲜度努力选择。研究结果表明, 供应商和零售商利润与消费者价格敏感系数呈反向变化, 与新鲜度敏感系数呈同向变化。在价格竞争市场, 供应商保鲜努力程度和利润与价格替代率呈反向变化;在生鲜度竞争市场, 供应商保鲜努力程度和利润与新鲜度替代率呈同向变化。基于研究结论, 厂商及政府应当联手引导消费者的消费观念, 尽可能减少由于信息不对称引致的道德风险, 在市场价格替代率不变甚至降低的情形下, 提高生鲜度替代率, 使得消费者的意愿支付价格上升, 提高自身讨价还价能力, 获取更多利润。

【关键词】 消费者效用;生鲜供应链;保鲜努力程度;定价策略;

【DOI】

【基金资助】 国家自然科学基金资助项目 (71573281) ; 中南大学创新驱动项目 (2016CX040) ; 湖南省社会科学成果评审委员会重大课题 (XSP17ZDA011) ;

Study on the fresh degree incentive mechanism of fresh agricultural product supply chain based on consumer utility

CAO Yu1 LI Ye-mei1 WAN Guangyu2

(1.Business School, Central South University, Changsha, China 410083)
(2.School of Economics & Trade, Hunan University, Changsha, China 410083)

【Abstract】With continuous improvement of consumers’ living standards, consumers’ demand for food safety has converted into the demand of both safety and high quality. Food fresh degree is widely arising consumers’ concern. Changes in consumers’ demand for fresh food makes a great many retailers and suppliers increasingly concerned about perishable goods and strengthen the management of fresh food supply chain. However, as a result of the attributes of perishable food itself and the lagging development of cold chain logistics technology, its management result is far from expectation. According to the data of CECRC, the loss rate of fruits and vegetables reaches 30% per year, which causes around CNY 1 billion per year. Based on the statement above, the improvement of whole fresh degree on fresh supply chain is chosen as research topic. The fresh degree advancement is of great significance to reduce waste, as well as improve the overall profitability of the supply chain and social welfare. The supply chain system composed of two suppliers and one retailer is mainly studied based on the consumer utility theory. The fresh degree incentive model of fresh agricultural products under single cycle is constructed. In the model, supplier is the leader. With the Stackelberg game method, manufactures’ optimal pricing and optimal freshness effort selection strategy under the equilibrium state are obtained. Results show that supplier, retailer profit and consumer price sensitivity coefficient are in reverse change. In the price competition market, the degree of preservation effort, profit and price substitution factor of the supplier show a reverse change. In the fresh degree competition market, the degree of preservation effort and profit, with the substitution rate of fresh degree change are in the same direction. Based on research conclusions, manufacturers and the government should cooperate to guide the consumer’s consumption concept jointly, reduce the moral hazard caused by information asymmetry as far as possible and avoid the phenomenon of Gresham.

【Keywords】 consumer utility; fresh supply chain; degree of freshness preservation effort; pricing strategy;

【DOI】

【Funds】 National Natural Science Foundation of China (71573281); Innovation-Driven Project of Central South University (2016CX040); Major Project of Hunan Provincial Social Science Achievement Review Committee (XSP17ZDA011);

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    References

    [1] Wang Xiaojun, Li Dong. A dynamic product quality evaluation based pricing model for perishable food supply chains. Omega, 2012, 40 (6): 906–917.

    [2] Lee Y P, Dye C Y. An inventory model for deteriorating items under stock-dependent demand and controllable deterioration rate. Computers & Industrial Engineering, 2012, 63 (2): 474–482.

    [3] Abad P L. Optimal price and order size under partial backordering incorporating shortage, backorder and lost sale costs. International Journal of Production Economics, 2008, 114 (1): 179–186.

    [4] Lotfi M M, Rabbani M, Ghaderi S F. A weighted goal programming approach for replenishment planning and space allocation in a supermarket. Journal of the Operational Research Society, 2011, 62 (6): 1128–1137.

    [5] Jia, T., Zheng, Y., Xu, Y. et al. Operations Research and Management Science (运筹与管理), 22 (2): 150–158 (2013).

    [6] Feng, H., Li, J. & Zeng, Y. Systems Engineering-Theory & Practice (系统工程理论与实践), 33 (6): 1411–1423 (2013).

    [7] Zhu, C. Rural Economy (农村经济), (6): 106–109 (2015).

    [8] Li, Y. & Qin, M. Journal of Agrotechnical Economics (农业技术经济), (4): 54–60 (2015).

    [9] Wang, J. & Chen, X. Systems Engineering-Theory & Practice (系统工程理论与实践), 32 (7): 1408–1414 (2012).

    [10] Deng, Q. Statistics & Decision (统计与决策), (6): 41–44 (2013).

    [11] Tang, L. & Zhao, L. Journal of Southeast University (Natural Science Edition) (东南大学学报(自然科学版)), 52 (4): 677–680 (2006).

    [12] Bulut Z, GrülerÜ, Sen A. Bundle pricing of inventories with stochastic demand. European Journal of Operational Research, 2009, 197 (3): 897–911.

    [13] Maihami R, Karimi B. Effect of two-echelon trade credit on pricing-inventory policy of non-instantaneous deteriorating products with probabilistic demand and deterioration functions. Annals of Operations Research, 2016: 1–37.

    [14] Ghoreishi M, Mirzazadeh A, Weber G W. Optimal pricing and ordering policy for non-instantaneous deteriorating items under inflation and customer returns. Optimization, 2014, 63 (12): 1785–1804.undefined

    [15] Wang, D., Li, X. & Zhang, B. Industrial Engineering and Management (工业工程与管理), 21 (5): 16–22 (2016).

    [16] Li, L. & Fan, T. Chinese Journal of Management Science (中国管理科学), 23 (12): 113–123 (2015).

    [17] Pu, X., Fang, W. & Wu, Y. Chinese Journal of Management Science (中国管理科学), 23 (12): 105–112 (2015).

    [18] Cai Xiaoqiang, Chen Jian, Xiao Yongbo, et al. Optimization and coordination of fresh product supply chains with freshness-keeping effort. Production and Operations Management, 2010, 19 (3): 261–278.

    [19] Wang, L. & Dan, B. Journal of Industrial Engineering and Engineering Management (管理工程学报), 29 (1): 200–206 (2015).

    [20] Xiong, F., Peng, J., Jin, P. et al. Chinese Journal of Management Science (中国管理科学), 23 (8): 102–111 (2015).

    [21] González-Araya M C, Soto-Silva W E, Espejo L G A. Harvest planning in apple orchards using an optimization model // Plà-Aragonés handbook of operations research in agriculture and the agri-food industry. New York: Springer, 2015: 79–105.

    [22] Nadal-Roig E, Plà-Aragonés L M. Optimal transport planning for the supply to a fruit logistic centre // LM. Handbook of Operations Research in Agriculture and the Agri-Food Industry. New York: Springer 2015: 163–177.

    [23] Yu Yugong, Wang Zheng, Liang Liang. A vendor managed inventory supply chain with deteriorating raw materials and products. International Journal of Production Economics, 2012, 136 (2): 266–274.

    [24] Soto-Silva W E, Nadal-Roig E, González-Araya M C, et al. Operational research models applied to the fresh fruit supply chain. European Journal of Operational Research, 2015, 251 (2): 345–355.

    [25] Wang, C., Tang, M. & Wang, L. China Soft Science (软科学), 27 (4): 99–101, 105 (2013).

    [26] Yang, Y., Fang, T. & Zhang, L. ChineseJournal of Management Science (中国管理科学), 24 (9): 147–155 (2016).

    [27] Gan, X., Qian, L. Ma, L. et al. Journal of Systems & Management (系统管理学报), 22 (5): 655–664 (2013).

This Article

ISSN:1003-207X

CN: 11-2835/G3

Vol 26, No. 02, Pages 160-174

February 2018

Downloads:2

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Article Outline

Abstract

  • 1 Introduction
  • 2 Model symbols and assumptions
  • 3 Fresh agricultural product supply chain decision model
  • 4 Sensitivity analysis
  • 5 Comparative analysis
  • 6 Conclusion
  • References