不同权力结构下考虑智慧农业技术的生鲜农产品供应链定价与协调研究

doi:10.16381/j.cnki.issn1003-207x.2024.1149

Abstract

Abstract:

Smart agriculture technology offers significant benefits， including the loss-reduction effect and premium effect of fresh agricultural products. However， supply chain members often hold differing views on its implementation under varying power structures—supplier dominance， equal power， and retailer dominance. It is a problem for scholars to study the pricing and coordination of fresh agricultural product supply chains under different power structures considering whether to apply smart agriculture technology. Specifically， the following key questions are addressed：（1） How do the characteristics of fresh agricultural products， such as quantity loss and freshness decay， affect the sales price， sales quantity， and profit of the supply chain？（2） How do the loss-reduction effect and premium effect affect the decision to apply smart agriculture technologies in the fresh agricultural product supply chain？ What are the critical factors guiding these decisions， and how can coordination contracts be designed to effectively promote the adoption of these technologies？（3） In what ways do different power structures affect sales prices， sales quantities， and overall profits in the supply chain？It focuses on the fresh agricultural product supply chain consisting of one supplier and one retailer in this research， analyzing the dynamics based on differing power structures. It is considered that the fresh agricultural products demand is linked to both product freshness and sales price. By considering the impact of smart agriculture technology on the loss-reduction effect and premium effect， a centralized decision-making model and decentralized decision-making models （i.e. a Supplier-led Stackelberg game， a Vertical Nash game， and a Retailer-led Stackelberg game） are developed. Comparing the centralized and the decentralized decision-making equilibrium results， the existence of double marginalization in the supply chain is found. To mitigate the double marginalization and encourage the adoption of smart agriculture technology， cost-sharing contracts， two-part pricing contracts， and profit-sharing contracts are proposed under different power structures. Finally， two extended cases are built to verify the robustness of the above models.The results reveal that （1） In a decentralized decision-making model without smart agriculture technology， equilibrium profits for the supplier and retailer positively correlate with freshness but negatively correlate with the circulation time. Leaders are more motivated than followers to shorten circulation time， reduce quantity losses， and enhance freshness. With the implementation of smart agriculture technology， both the supplier and retailer can synchronously benefit. The decision on whether to adopt smart agriculture technology in the supply chain hinges on the loss-reduction effect， premium effect， and tag cost. Higher tag costs increase the challenges of technology implementation， with the premium effect being more critical than the loss reduction effect for driving technology adoption. （2） Not all contracts can effectively drive the adoption of smart agriculture technology. Only the two-part tariff contract （profit-sharing contract） that boosts profits and derives the synchronous application by the supplier and retailer， creating "excess momentum"， can effectively promote the application of smart agriculture technology. （3） Leaders wield pricing authority and obtain the highest profits. Under a decentralized decision-making model， a supply chain system with equal power can achieve the maximum profit. Notably， under a centralized decision-making model， the power structure has little impact on the equilibrium profit of the supply chain.These findings provide theoretical basis and decision support for addressing the pricing and coordination issues of fresh agricultural product supply chains considering smart agriculture technology under different power structures.

Key words: power structure, smart agriculture technology, fresh agricultural product, supply chain pricing, supply chain coordination contract

CLC Number:

F270

Shuai Zhao, Xiaoning Cao, Wenli Li. Research on Pricing and Coordination of Fresh Agricultural Product Supply Chain Considering the Smart Agriculture Technology under Different Power Structures[J]. Chinese Journal of Management Science, 2025, 33(2): 262-278.

Figures/Tables 8

符号	含义
参数/变量：涉及到供应商
S	供应商
$Π S$	供应商期望利润
$c (c ∈ [0, 1])$	生产成本
$c u (c u ∈ [0, 1])$	标签成本
$λ 21 S * (λ 21 S * > 0)$	S的技术接受可能性
$ψ (ψ ∈ (0, 1))$	成本分担比例
$F 21 S S T T (F 21 S S T T > 0)$	供应商主导时补偿费用
$k 21 S (k 21 S ∈ [0, 1))$	S的相对议价能力
$ξ (ξ ∈ (0, 1))$	利润分享比例
参数/变量：涉及到零售商
R	零售商
$Π R$	零售商期望利润
$λ 21 R * (λ 21 R * > 0)$	R的技术接受可能性
$F 21 V N T T (F 21 V N T T > 0)$	权力对等时补偿费用
$F 21 S R T T (F 21 S R T T > 0)$	零售商主导时补偿费用
$k 21 R (k 21 R ∈ [0, 1))$	R的相对议价能力
参数/变量：涉及到消费者及其市场
$t (t ∈ [0, T])$	流通时间
$T$	生产周期
$e$	自然指数
$δ$	损耗改善效应
$v$	溢价值
$ϕ$	衰变率
$ε$	恶化率
$θ (t) (θ (t) ∈ [0, 1])$	新鲜度函数
$φ (t) (φ (t) ∈ [0, 1])$	农产品存活率
$β (β ∈ [0, 1))$	溢价效应
$b v$	溢价敏感系数
$b p$	价格敏感系数
$D$	需求数量
上标符号
B	临界值
C	集中式决策模型
SS	供应商主导
VN	权力对等
SR	零售商主导
CS	成本分担契约
TT	两部定价契约
PS	利润分享契约
下标符号
1	未应用智慧农业技术时
2	应用智慧农业技术时
决策变量
$p$	销售价格
$ω$	批发价格
$m$	边际利润

均衡策略	分散式决策模式			集中式决策模式
均衡策略	$i = S S$	$i = V N$	$i = S R$	集中式决策模式
$m 2 i *$	$θ (t 2) - (c + c u) (1 - β) 4 θ (t 2) (1 - β)$	$θ (t 2) - (c + c u) (1 - β) 3 θ (t 2) (1 - β)$	$θ (t 2) - (c + c u) (1 - β) 2 θ (t 2) (1 - β)$	—
$p 2 i *$	$3 θ (t 2) + (c + c u) (1 - β) 4 θ (t 2) (1 - β)$	$2 θ (t 2) + (c + c u) (1 - β) 3 θ (t 2) (1 - β)$	$3 θ (t 2) + (c + c u) (1 - β) 4 θ (t 2) (1 - β)$	$θ (t 2) + (c + c u) (1 - β) 2 θ (t 2) (1 - β)$
$ω 2 i *$	$θ (t 2) + (c + c u) (1 - β) 2 θ (t 2) (1 - β)$	$θ (t 2) + 2 (c + c u) (1 - β) 3 θ (t 2) (1 - β)$	$θ (t 2) + 3 (c + c u) (1 - β) 4 θ (t 2) (1 - β)$	—
$D 2 i *$	$θ (t 2) - (c + c u) (1 - β) 4$	$θ (t 2) - (c + c u) (1 - β) 3$	$θ (t 2) - (c + c u) (1 - β) 4$	$θ (t 2) - (c + c u) (1 - β) 2$
$Π 2 S i *$	$(θ (t 2) - (c + c u) (1 - β)) 2 8 θ (t 2) (1 - β)$	$(θ (t 2) - (c + c u) (1 - β)) 2 9 θ (t 2) (1 - β)$	$(θ (t 2) - (c + c u) (1 - β)) 2 16 θ (t 2) (1 - β)$	—
$Π 2 R i *$	$(θ (t 2) - (c + c u) (1 - β)) 2 16 θ (t 2) (1 - β)$	$(θ (t 2) - (c + c u) (1 - β)) 2 9 θ (t 2) (1 - β)$	$(θ (t 2) - (c + c u) (1 - β)) 2 8 θ (t 2) (1 - β)$	—
$Π 2 i *$	$3 (θ (t 2) - (c + c u) (1 - β)) 2 16 θ (t 2) (1 - β)$	$2 (θ (t 2) - (c + c u) (1 - β)) 2 9 θ (t 2) (1 - β)$	$3 (θ (t 2) - (c + c u) (1 - β)) 2 16 θ (t 2) (1 - β)$	$(θ (t 2) - (c + c u) (1 - β)) 2 4 θ (t 2) (1 - β)$

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Research on Pricing and Coordination of Fresh Agricultural Product Supply Chain Considering the Smart Agriculture Technology under Different Power Structures

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