Price Game Model and Competitive Strategy of Agricultural Products Retail Market in the Context of Blockchain

doi:10.12133/j.smartag.SA202309027

Abstract

Abstract:

[Objective] In the retail market for agricultural products, consumers are increasingly concerned about the safety and health aspects of those products. Traceability of blockchain has emerged as a crucial solution to address these concerns. Essentially, a blockchain functions as a dynamic, distributed, and shared database. When implemented in the agricultural supply chain, it not only improves product transparency to attract more consumers but also raises concerns about consumer privacy disclosure. The level of consumer apprehension regarding privacy will directly influence their choice to purchase agricultural products traced through blockchain-traced. Moreover, retailers' choices to sell blockchain-traced produce are influenced by consumer privacy concerns. By analyzing the impact of blockchain technology on the competitive strategies, pricing, and decision-making among agricultural retailers, they can develop market competition strategies that suit their market conditions to bolster their competitiveness and optimize the agricultural supply chain to maximize overall benefits. [Methods] Based on Nash equilibrium and Stackelberg game theory, a market competition model was developed to analyze the interactions between existing and new agricultural product retailers. The competitive strategies adopted by agricultural product retailers were analyzed under four different options of whether two agricultural retailers sell blockchain agricultural products. It delved into product utility, optimal pricing, demand, and profitability for each retailer under these different scenarios. How consumer privacy concerns impact pricing and profits of two agricultural product retailers and the optimal response strategy choice of another retailer when the competitor made the decision choice first were also analyzed. This analysis aimed to guide agricultural product retailers in making strategic choices that would safeguard their profits and market positions. To address the cooperative game problem of agricultural product retailers in market competition, ensure that retailers could better cooperate in the game, blockchain smart contract technology was used. By encoding the process and outcomes of the Stackelberg game into smart contracts, retailers could input their specific variables and receive tailored strategy recommendations. Uploading game results onto the blockchain network ensured transparency and encouraged cooperative behavior among retailers. By using the characteristics of blockchain, the game results were uploaded to the blockchain network to regulate the cooperative behavior, to ensure the maximization of the overall interests of the supply chain. [Results and Discussions] The research highlighted the significant improvement in agricultural product quality transparency through blockchain traceability technology. However, concerns regarding consumer privacy arising from this traceability could directly impact the pricing, profitability and retailers' decisions to provide blockchain-traceable items. Furthermore, an analysis of the strategic balance between two agricultural product retailers revealed that in situations of low and high product information transparency, both retailers were inclined to simultaneously offer sell traceable products. In such a scenario, blockchain traceability technology enhanced the utility and profitability of retail agricultural products, leading consumers to prefer purchase these traceable products from retailers. In cases where privacy concerns and agricultural product information transparency were both moderate, the initial retailer was more likely to opt for blockchain-based traceable products. This was because consumers had higher trust in the initial retailer, enabling them to bear a higher cost associated with privacy concerns. Conversely, new retailers failed to gain a competitive advantage and eventually exit the market. When consumer privacy concerns exceeded a certain threshold, both competing agricultural retailers discovered that offering blockchain-based traceable products led to a decline in their profits. [Conclusions] When it comes to agricultural product quality and safety, incorporating blockchain technology in traceability significantly improves the transparency of quality-related information for agricultural products. However, it is important to recognize that the application of blockchain for agricultural product traceability is not universally suitable for all agricultural retailers. Retailers must evaluate their unique circumstances and make the most suitable decisions to enhance the effectiveness of agricultural products, drive sales demand, and increase profits. Within the competitive landscape of the agricultural product retail market, nurturing a positive collaborative relationship is essential to maximize mutual benefits and optimize the overall profitability of the agricultural product supply chain.

Key words: blockchain, supply chain, retailers of agricultural products, consumer privacy, game theory

XUE Bing, SUN Chuanheng, LIU Shuangyin, LUO Na, LI Jinhui. Price Game Model and Competitive Strategy of Agricultural Products Retail Market in the Context of Blockchain[J]. Smart Agriculture, doi: 10.12133/j.smartag.SA202309027.

Figures/Tables 14

Table 1

Main character meaning description table in game model

字符	字符表示含义
$M 1$ 、 $M 2$	两家零售企业分别为 $M 1$ （已存在）、 $M 2$ （新进入）
v	消费者对 $M 1$ 零售产品的估值
qv	消费者对 $M 2$ 零售产品的估值
k	信息透明度的提升程度
T	消费者承受的隐私关注成本
P	农产品零售商的零售价格
D	消费者需求
$π$	农产品零售商的利润

Table 1

Table 2

The demands of two agricultural retailers in various decision selection situations

案例	条件	$D 1$	$D 2$
AA	$p 2 ≤ q p 1$	$1 - p 1 - p 2 1 - q$	$p 1 - p 2 1 - q - p 2 q$
AA	$p 2 > q p 1$	$1 - p 1$	0
BA	$k p 2 ≤ q p 1 + T$	$1 - p 1 + T - p 2 k - p$	$p 1 + T - p 2 k - p - P 2 q$
BA	$k p 2 > q (p 1 + T)$	$1 - p 1 + T k$	0
AB	$k q < 1;$ $p 2 + T ≤ k q p 1$	$1 - p 1 - p 2 - T 1 - k q$	$p 1 - p 2 - T 1 - k q - P 2 + T k q$
	$k q < 1;$ $p 2 + T > k q p 1$	$1 - p 1$	0
	$k q > 1;$ $p 2 + T ≤ k q p 1$	0	$1 - p 2 + T k q$
	$k q > 1;$ $p 2 + T > k q p 1$	$p 2 + T - p 1 k q - 1 - p 1$	$1 - p 2 + T - p 1 k q - 1$
	$k q = 1;$ $p 2 + T ≤ k q p 1$	0	$1 - p 2 + T k q$
	$k q = 1;$ $p 2 + T > k q p 1$	$1 - p 1$	0
BB	$p 2 + T ≤ q (p 1 + T)$	$1 - p 1 - p 2 k (1 - q)$	$p 1 - p 2 k (1 - q) - P 2 + T k q$
BB	$p 2 + T > q (p 1 + T)$	$1 - p 1 + T k$	0

Table 2

Table 3

The retailer's optimal pricing and corresponding demand and profit in case AA

零售商	p ^AA	D ^AA	π^AA
$M 1$	$2 (1 - q) 4 - q$	$2 4 - q$	$4 (1 - q) 4 - q 2$
$M 2$	$q (1 - q) 4 - q$	$1 4 - q$	$q (1 - q) 4 - q 2$

Table 3

Table 4

Retailer's optimal strategy and corresponding demand and profit in case BA

零售商		$P B A$	$D B A$	$π B A$
$M 1$	$T ≤$ $2 k (k - q) 2 k - q$	$2 k k - q - T + q T 4 k - q$	$2 k k - q - T + q T (4 k - q) (k - q)$	$2 k k - q - T + q T 2 4 k - q 2 (k - q)$
$M 2$	$T ≤$ $2 k (k - q) 2 k - q$	$q k - q + T 4 k - q$	$k k - q - T (4 k - q) (k - q)$	$k q (k - q + T) 2 4 k - q 2 (k - q)$
$M 1$	$T >$ $2 k (k - q) 2 k - q$	0	0	0
$M 2$	$T >$ $2 k (k - q) 2 k - q$	$q 2$	$12$	$q 2$

Table 4

Fig. 1

Table 5

Retailer's optimal strategy， demand and profit in case AB

零售商	条件	$p A B$	$D A B$	$π A B$
$M 1$	$T ≤ k q (1 - k q) 2 - k q$ $且 k q < 1$	$2 1 - k q + T 4 - k q$	$2 1 - k q + T (4 - k q) (1 - k q)$	$(2 1 - k q + T) 2 (4 - k q) 2 (1 - k q)$
$M 2$	$T ≤ k q (1 - k q) 2 - k q$ $且 k q < 1$	$k q 1 - k q + T - 2 T 4 - k q$	$k q 1 - k q + T - 2 T k q (4 - k q) (1 - k q)$	$(k q 1 - k q + T - 2 T) 2 k q (4 - k q) 2 (1 - k q)$
$M 1$	$T > k q (1 - k q) 2 - k q$ $且 k q < 1$	$12$	$12$	$14$
$M 2$	$T > k q (1 - k q) 2 - k q$ $且 k q < 1$	（0，1）	0	0
$M 1$	$T ≤ k q (1 - k q) 2 - k q$ $且 k q > 1$	$k q - 1 + T 4 k q - 1$	$k q k q + T - 1 (4 k q - 1) (k q - 1)$	$(k q k q + T - 1) 2 4 k q - 1 2 (k q - 1)$
$M 2$	$T ≤ k q (1 - k q) 2 - k q$ $且 k q > 1$	$2 k q k q - T - 1 + T 4 k q - 1$	$2 k q k q - T - 1 + T (4 k q - 1) (k q - 1)$	$(2 k q k q - T - 1 + T) 2 4 k q - 1 2 (k q - 1)$
$M 1$	$T > k q 1 - k q 2 - k q$ $且 k q > 1$	$12$	$12$	$14$
$M 2$	$T > k q 1 - k q 2 - k q$ $且 k q > 1$	0	0	0
$M 1$	$T < 12$ $且 k q = 1$	$12$	$14$	$18$
$M 2$	$T < 12$ $且 k q = 1$	$12 - T$	$14$	$18 - T 4$
$M 1$	$T ≥ 12$ $且 k q = 1$	$12$	$12$	$14$
$M 2$	$T ≥ 12$ $且 k q = 1$	（0，1）	0	0

Table 5

Fig. 2

Table 6

Retailer's optimal strategy and corresponding demand and profit in case BB

零售商	条件	$p B B$	$D B B$	$π B B$
$M 1$	$T ≤ k q 2$	$(2 k - T) (1 - q) 4 - q$	$2 k - T k (4 - q)$	$(2 k - T) 2 (1 - q) k (4 - q) 2$
$M 2$	$T ≤ k q 2$	$(k q - 2 T) (1 - q) 4 - q$	$k q - 2 T k q (4 - q)$	$(k q - 2 T) 2 (1 - q) k q (4 - q) 2$
$M 1$	$T > k q 2$	$k - T 2$	$k - T 2 k$	$(k - T) 2 4 k$
$M 2$	$T > k q 2$	（0，1）	0	0

Table 6

Fig. 3

Fig. 4

Table 7

Cooperative game for determining policies

输入输出

伪代码描述

输入：k值（k>1）、q值（q<1）、零售商 $M 1$ 和零售商 $M 2$ 对应T值（T<=k）

输出：合作博弈均衡策略结果

Begin

T1=根据输入由T1公式（19）计算T1值

T5=根据输入由T5公式（23）计算T1值

if k×q<1

if T<=T5 || ［k>=2/（2‒q）² && k×q/2<T && T<=k‒sqrt（k）］

return“方案BB为均衡策略”

else if ［k>=2/（2‒q）² && T5<T && T<=k×q/2］ || ［k‒sqrt（k）<T && T<=T1］ || ［k<2/（2‒q）² && T5<T && T<=T1］

return“方案BA为均衡策略”

else if ［k>=2/（2‒q）² && T>T1］ || ［k<2/（2‒q）² && T>T1］

return“方案AA为均衡策略”

else if k×q>1

if T<=T5

return“方案BB为均衡策略”

else if T5<T && T<=T1

return“方案BA为均衡策略”

else if T>T1

return“方案AA为均衡策略”

else if k×q=1

if T<=T5

return“方案BB为均衡策略”

else if T5<T && T<=T1

return“方案BA为均衡策略”

else if ｛k<=3/2 && 2×k‒（4×k‒1）/sqrt［8×（k‒1）］<=T && T<（16×k ² ‒16×k+9）/2×（4×k‒1）²｝

return“方案AB为均衡策略”

else if ｛k<=［2+sqrt（3）］/2 && T>=（16×k ²‒16×k+9）/2×（4×k‒1）² || k>［2+sqrt（3）］/2 && T>T1｝

return“方案AA为均衡策略”

return“无法得出均衡策略”

End

Table 7

Fig. 5

Fig. 6

Fig. 7

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