考虑农户心理成本与合作社损失的农业服务平台定价策略研究

doi:10.16381/j.cnki.issn1003-207x.2023.2086

摘要/Abstract

摘要：

农业服务平台（简称农服平台）是连接农户与农业服务提供商，并将分散的农业资源进行供需匹配的网络系统。农服平台为农业服务匹配与交易提供了崭新的模式。如何制定农服平台的启动定价策略与可持续定价策略是其发展必须解决的关键问题。本研究在考虑农户使用平台的心理成本与合作社对外服务的内部损失存在异质性的情况下，建立了最大化社会福利的定价模型与最大化平台利润的定价模型。结果表明：农户对农服平台的信任水平对平台的定价策略选择具有决定性作用，信任水平较低时，应该实施让利性定价策略；信任水平较高时，应该实盈利性定价策略。让利性策略下的服务价格低于盈利性策略下的服务价格，让利性策略下的服务报酬高于盈利性策略下的服务报酬。农户对平台的规避较大时，让利性定价策略对双边用户更具有吸引力；农户对平台的规避较小时，盈利性定价策略对双边用户更具有吸引力。

关键词: 农服平台, 运营管理, 异质性用户, 定价策略, 均衡分析

Abstract:

Agricultural service platforms （ASPs） are network systems that connect farmers with agricultural service providers， facilitating the supply-demand matching of dispersed agricultural resources. ASPs offer a novel model for agricultural service matching and transactions. Although scholars have extensively studied the pricing strategies of platform enterprises， the focus has primarily been on sectors such as food delivery， e-commerce， and short videos. The development of pricing strategies to promote ASPs has not yet received adequate scholarly attention. Unlike the pricing strategies of general platforms， ASPs have distinctive characteristics. General platforms typically set usage or intermediary fees without having the authority to price goods or services. In contrast， ASPs determine the fees charged to farmers for machinery services and the payments made to service providers， as exemplified by the "Farm Steward" model. Establishing initial pricing strategies and sustainable pricing strategies is a critical issue for the development of ASPs. When farmers need agricultural services （such as spraying， irrigation， harvesting， etc.）， they can purchase these services through ASPs or seek services via rural social networks. However， farmers may incur psychological costs when using ASPs， which vary due to differences in digital literacy among farmers. To characterize this heterogeneity， it is assumed that the mental cost $θ$ follows a uniform distribution over ［ $- θ ˙, θ ¯$ ］. Cooperatives accepting online orders may experience a decrease in response speed to their internal members， causing internal losses. Due to significant differences in operational area and the number of agricultural machines among cooperatives， the losses incurred by providing online services are also heterogeneous， assumed to follow a uniform distribution over $γ 1 - γ 2, γ 1 + γ 2$ . Considering the heterogeneity of bilateral users， a selection model for farmers and cooperatives is established. Next， pricing models are developed for ASPs in the startup and growth phases， aiming to maximize social welfare and platform profit， respectively. Finally， the profit， pricing， and user demand under different objectives are compared to determine the applicable conditions for both pricing strategies. The results indicate that the pricing strategy of ASPs is predominantly influenced by the trust level of farmers towards the platform. For regions where farmer trust is low， ASPs should adopt a pricing strategy that aims to maximize social welfare. Conversely， in regions where farmer trust is high， ASPs should implement a pricing strategy focused on maximizing their own profits. Under the concessional strategy， service prices are lower， and service remuneration is higher compared to the profit-driven strategy. When farmers have low aversion to the platform， the concessional pricing strategy is more attractive to both users. However， when farmer aversion is high， the profit-driven pricing strategy is more appealing to both users.

Key words: agricultural service platform, operation management, heterogeneous users, pricing strategy, equilibrium analysis

中图分类号:

F272

刘欣欣,孙自来,韩继良, 等. 考虑农户心理成本与合作社损失的农业服务平台定价策略研究[J]. 中国管理科学, 2026, 34(7): 323-335.

Xinxin Liu,Zilai Sun,Jiliang Han, et al. Research on Pricing Strategy of Agricultural Service Platform Considering Farmers’ Mental Cost and Cooperative Loss[J]. Chinese Journal of Management Science, 2026, 34(7): 323-335.

图/表 12

图1

表1

符号及含义"

类型	符号	含义
参数	$n f$	服务区域内的潜在农户数量
	$n p$	平台上注册的合作社数量
	$p 0$	乡村社会网络渠道的单位服务价格
	$S$	每名农户的经营面积
	$θ$	农户使用农服平台的心理成本
	$γ$	合作社损失
	$C 0$	合作社的单位服务成本
决策变量	$p s i$	第 $i$ 阶段平台对农户收取的单位服务价格， $i = 1$ 表示初创期， $i = 2$ 表示发展期
决策变量	$w s i$	第 $i$ 阶段平台支付给合作社的单位服务报酬， $i = 1$ 表示初创期， $i = 2$ 表示发展期

表1

图2

图3

表2

初创阶段农服平台的最优定价与社会福利"

变量	区间
变量	$0 < θ ¯ ≤ h 1$	$h 1 < θ ¯ < m i n {h 2, h 3, h 4$	$θ ¯ ≥ m a x {h 2, h 3, h 4$
$p s 1 *$	$p 0 - θ ¯ / S$	$C 0 + γ 1 + γ 2 / S$	$p 0 - θ ¯ / S$
$w s 1 *$	$C 0 + γ 1 + γ 2 / S$	$C 0 + γ 1 + γ 2 / S$	$p 0 - θ ¯ / S$
$S W 1 *$	$n p γ 2 + 12 n f θ ¯ + θ ˙ + m i n {n f, n p k 1$	$n p γ 2 + n f k 1 + θ ¯ + θ ˙ 2 2 θ ¯ + θ ˙$	$n p k 1 + 2 γ 2 2 4 γ 2 + n f θ ¯ + θ ˙ 2$

表2

表3

农户心理成本对平台定价策略的影响"

变量	$θ ˙$		$θ ¯$
变量	$S ≤ S ̂$	$S > S ̂$	$S ≤ S ̂$	$S > S ̂$
$p s 2 *$	$↑ θ ¯ ≤ θ 2 ↓ θ ¯ > θ 2$	$↑$	$↓$	$↓$
$w s 2 *$	$↑ ξ 1 ≥ 0 ↓ ξ 1 < 0$	-	$↓$	-
$r *$	$↓$	$↓$	$↓$	$↑$
$π *$	$↑ ξ 1 ≥ 0 ↓ ξ 1 < 0$	$↑$	$↓$	$↓$

表3

表4

合作社损失对平台定价策略的影响"

变量	$γ 1$			$γ 2$
	$S ≤ S ̂$	$S > S ̂$	$S ≤ S ̂$ $S > S ̂$
				$n f ≤ n p$	$n f > n p$
$p s 2 *$	$↑$	-	$↑ γ 1 ≤ γ 3 ↓ γ 1 > γ 3$	-	-
$w s 2 *$	$↑$	$↑$	$↑ ξ 3 ≥ 0 ↓ ξ 3 < 0$	$↑ n f ≥ n p / 2 ↓ n f < n p / 2$	$↑$
$r *$	$↑$	$↑ S ≥ S 1 ↓ S < S 1$	$↑ ξ 4 ≥ 0 ↓ ξ 4 < 0$	$↑ n f ≥ n p / 2 ↓ n f < n p / 2$	$↑$
$π *$	$↓$	$↓$	$↑ γ 1 ≥ γ 3 ↓ γ 1 < γ 3$	$↑ n f ≤ n p / 2 ↓ n f > n p / 2$	$↓$

表4

表5

用户规模对平台定价策略的影响"

变量	$n f$			$n p$
	$S ≤ S ̂$	$S > S ̂$		$S ≤ S ̂$	$S > S ̂$
		$n f ≤ n p$	$n f > n p$		$n f ≤ n p$	$n f > n p$
$p s 2 *$	$↑$	-	$↑$	$↓$	-	$↓$
$w s 2 *$	$↑$	$↑$	-	$↓$	$↓$	-
$r *$	$↑$	$↑$	$↓$	$↓$	$↓$	$↑$

表5

图4

图5

图6

图7

参考文献 41

[1]	李广泳，姜广辉，张永红，等. 我国耕地撂荒机理及盘活对策研究［J］. 中国国土资源经济， 2021， 34（2）： 36-41.
	Li G Y， Jiang G H， Zhang Y H， et al. Research on the mechanism of cultivated land abandonment and the countermeasures of revitalization in China［J］. Natural Resource Economics of China， 2021， 34（2）： 36-41.
[2]	Springer V， Petrik D. Towards a taxonomy of impact factors for digital platform pricing［M］//Gregory P， Kruchten P.Agile Processes in Software Engineering and Extreme Programming-Workshops. Cham： Springer International Publishing， 2021： 115-124.
[3]	张蕴萍，栾菁. 数字经济赋能乡村振兴：理论机制、制约因素与推进路径［J］. 改革， 2022（5）： 79-89.
	Zhang W P， Luan J. Digital economy enables rural revitalization： Theoretical mechanism， restrictive factors and implementation path［J］. Reform， 2022（5）： 79-89.
[4]	Tang C S， Wang Y， Zhao M. The implications of utilizing market information and adopting agricultural advice for farmers in developing economies［J］. Production and Operations Management， 2015， 24（8）： 1197-1215.
[5]	Naik B J， Rao B M， Rambabu P， et al. Attitude of farmers towards information and communication technology （ict） tools［J］. Current Journal of Applied Science and Technology， 2020，39（43）， 72-81.
[6]	Aldosari F， Al Shunaifi M S， Ullah M A， et al. Farmers’ perceptions regarding the use of Information and Communication Technology （ICT） in Khyber Pakhtunkhwa， Northern Pakistan［J］. Journal of the Saudi Society of Agricultural Sciences，2019，18（2）： 211-217.
[7]	Brandão J B， Breitenbach R. What are the main problems in the management of rural cooperatives in Southern Brazil？［J］. Land Use Policy， 2019， 85： 121-129.
[8]	阮俊虎，刘天军，冯晓春，等. 数字农业运营管理：关键问题、理论方法与示范工程［J］. 管理世界， 2020， 36（8）： 222-232.
	Ruan J H， Liu T J， Feng X C， et al. Digital agriculture operation and management： Problems， methods and demonstration［J］.Journal of Management World， 2020， 36（8）： 222-232.
[9]	Han J， Li L， Sun Z， et al. An integrative decision-making model for the Internet of Things-enabled supply chains of fresh agri-product［J］. International Journal of Production Research， 2023， 61（13）： 4358-4373.
[10]	林晓刚，黄海玲，李文卓，等. 混合销售模式下农产品电商的区块链技术提供策略研究［J］. 中国管理科学， 2025， 33（10）： 259-268.
	Lin X G， Huang H L， Li W Z， et al. Blockchain provision strategy in agricultural products E-commerce under hybrid sales model［J］. Chinese Journal of Management Science， 2025， 33（10）： 259-268.
[11]	Yi Z， Wang Y， Chen Y J. Financing an agricultural supply chain with a capital-constrained smallholder farmer in developing economies［J］. Production and Operations Management， 2021， 30（7）： 2102-2121.
[12]	王俊斌，张立冬. 订单农业供应链的区块链溯源技术引入策略研究［J］. 系统工程理论与实践， 2024， 44（2）： 612-628.
	Wang J B， Zhang L D. Blockchain traceability technology introduction strategy in the contract-farming supply chain［J］. Systems Engineering —Theory & Practice， 2024， 44（2）： 612-628.
[13]	Fu J， Zhang Z， Lyu D. Research and application of information service platform for agricultural economic cooperation organization based on Hadoop cloud computing platform environment： Taking agricultural and fresh products as an example［J］. Cluster Computing， 2019， 22（S6）： 14689-14700.
[14]	Ibrahim I A， Truby J M. FarmTech： Regulating the use of digital technologies in the agricultural sector［J］. Food and Energy Security， 2023， 12（4）： 1-15.
[15]	Omulo G， Kumeh E M. Farmer-to-farmer digital network as a strategy to strengthen agricultural performance in Kenya： A research note on ‘Wefarm’ platform［J］. Technological Forecasting and Social Change， 2020， 158： 120120.
[16]	陈卫洪，王莹. 数字化赋能新型农业经营体系构建研究——“智农通”的实践与启示［J］. 农业经济问题， 2022（9）： 86-99.
	Chen W H， Wang Y. A study on the construction of a new agricultural management system with digital empowerment： Practice and enlightenment of “Zhinongtong”［J］. Issues in Agricultural Economy， 2022（9）： 86-99.
[17]	Kung L C， Zhong G Y. The optimal pricing strategy for two-sided platform delivery in the sharing economy［J］. Transportation Research Part E： Logistics and Transportation Review， 2017， 101： 1-12.
[18]	李宗活，李善良，刘丽雯. 面向潜在竞争者异质品引入的零售商平台定价策略与模式选择研究［J］. 中国管理科学， 2025， 33（9）： 269-279.
	Li Z H， Li S L， Liu L W. Platform pricing strategies and mode selection of retailers facing potential competitors’Heterogeneous product introduction［J］. Chinese Journal of Management Science， 2025， 33（9）： 269-279.
[19]	Basu A， Bhaskaran S， Mukherjee R. An analysis of search and authentication strategies for online matching platforms［J］. Management Science， 2019， 65（5）： 2412-2431.
[20]	桂云苗，程静，龚本刚. 不同信息策略下竞争型网络货运平台定价研究［J］. 中国管理科学， 2023， 31（5）： 176-186.
	Gui Y M， Cheng J， Gong B G. Research on pricing of competitive network freight platform under different information strategy［J］. Chinese Journal of Management Science， 2023， 31（5）： 176-186.
[21]	林徐勋，王海燕. 在线健康信息服务动态定价与推广策略［J］. 管理科学学报， 2020， 23（11）： 23-46.
	Lin X X， Wang H Y. Dynamic pricing and promotion strategy of online health information service［J］. Journal of Management Sciences in China， 2020， 23（11）： 23-46.
[22]	王勇，刘乐易，迟熙，等. 流量博弈与流量数据的最优定价——基于电子商务平台的视角［J］. 管理世界， 2022， 38（8）： 116-132.
	Wang Y， Liu L Y， Chi X， et al. Traffic game and the optimal pricing of traffic data： Based on the perspective of E-commerce platform［J］. Journal of Management World， 2022， 38（8）： 116-132.
[23]	Wang X， He F， Yang H， et al. Pricing strategies for a taxi-hailing platform［J］. Transportation Research Part E： Logistics and Transportation Review， 2016， 93： 212-231.
[24]	Cachon G P， Daniels K M， Lobel R. The role of surge pricing on a service platform with self-scheduling capacity［J］. Manufacturing & Service Operations Management， 2017， 19（3）： 368-384.
[25]	Bai J， So K C， Tang C S， et al. Coordinating supply and demand on an on-demand service platform with impatient customers［J］. Manufacturing & Service Operations Management， 2019， 21（3）： 556-570.
[26]	Zhong Y， Pan Q， Xie W， et al. Pricing and wage strategies for an on-demand service platform with heterogeneous congestion-sensitive customers［J］. International Journal of Production Economics， 2020， 230： 107901.
[27]	Taylor T A. On-demand service platforms［J］. Manufacturing & Service Operations Management， 2018， 20（4）： 704-720.
[28]	Armony M， Haviv M. Price and delay competition between two service providers［J］. European Journal of Operational Research， 2003， 147（1）： 32-50.
[29]	Zhou W， Chao X， Gong X. Optimal uniform pricing strategy of a service firm when facing two classes of customers［J］. Production and Operations Management， 2014， 23（4）： 676-688.
[30]	李冬冬，商辰宣，吕宏军，等. “后补贴”时代考虑消费者需求异质性的新能源汽车推广政策研究［J］. 中国管理科学， 2024， 32（4）： 141-152.
	Li D D， Shang C X， Lv H J， et al. Adoption of new energy vehicle in the post-subsidy erawith heterogeneous consumer demand［J］. Chinese Journal of Management Science， 2024， 32（4）： 141-152.
[31]	Liu Z， Zhao R， Liu X， et al. Contract designing for a supply chain with uncertain information based on confidence level［J］. Applied Soft Computing， 2017， 56： 617-631.
[32]	阮海波. 社会交往能促进土地流转吗？——基于农业社会化服务的中介效应［J］.农村经济，2022（6）： 27-36.
	Ruan H B. Can social interaction promote land circulation？Based on the intermediary effect of agricultural socialization services［J］. Rural Economy， 2022（6）： 27-36.
[33]	潘嗣同，龚教伟，高叙文，等. 电商进村政策实施的就业效应与机制分析［J］.中国农村经济， 2024（4）： 141-162.
	Pan S T， Gong J W， Gao X W， et al. The employment effects and mechanisms of the implementation of rural E-commerce development policy in China［J］. Chinese Rural Economy， 2024（4）： 141-162.
[34]	Feng T， Zhang Y. Modeling strategic behavior in the competitive newsvendor problem： An experimental investigation［J］. Production and Operations Management， 2017， 26（7）： 1383-1398.
[35]	Dong Z， Leng M. Managing on-demand ridesharing operations： Optimal pricing decisions for a ridesharing platform［J］. International Journal of Production Economics， 2021， 232： 107958.
[36]	Kalish S. Monopolist pricing with dynamic demand and production cost［J］. Marketing Science， 1983， 2（2）： 135-159.
[37]	Bonus H. The cooperative association as a business enterprise： A study in the economics of transactions［J］. Journal of Institutional and Theoretical Economics， 1986， 142（2）： 310-339.
[38]	郑风田，崔梦怡，郭宇桥，等. 家庭农场领办合作社对农场绩效的影响——基于全国556个家庭农场两期追踪调查数据的实证分析［J］. 中国农村观察， 2022（5）： 80-103.
	Zheng F T， Cui M Y， Guo Y Q， et al. The impact of family farm-led cooperatives on farm performance： An analysis based on two-phase tracking survey data of 556 family farms in China［J］. China Rural Survey， 2022（5）： 80-103.
[39]	Dou Y， Wu D J. Platform competition under network effects： Piggybacking and optimal subsidization［J］. Information Systems Research，2021，32（3）： 820-835.
[40]	Li F， Du T C， Wei Y. Offensive pricing strategies for online platforms［J］. International Journal of Production Economics， 2019， 216： 287-304.
[41]	Choi T M， Guo S， Liu N， et al. Optimal pricing in on-demand-service-platform-operations with hired agents and risk-sensitive customers in the blockchain era［J］. European Journal of Operational Research， 2020， 284（3）： 1031-1042.