Differential games in the supply chain of innovative products with consumer purchase regret induced returns

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible.

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Publication Details

Journal
PLoS ONE
Published
2024-08-05
DOI
https://doi.org/10.1371/journal.pone.0302154
Citations
1
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
0.49

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article

Differential games in the supply chain of innovative products with consumer purchase regret induced returns

Junjie Liu, Yutao Pu, Xianping Mu
1 citations
PLoS ONE
Innovation Diffusion and Forecasting
0.49
article

Differential games in the supply chain of innovative products with consumer purchase regret induced returns

Junjie Liu, Yutao Pu, Xianping Mu
article en
1 citations

Abstract

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible.

PLoS ONEVol. 19(8)
East China Jiaotong University (CN), Guizhou Academy of Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 32%
Innovation Diffusion and Forecasting
0.49
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Differential games in the supply chain of innovative products with consumer purchase regret induced returns — Junjie Liu, Yutao Pu, et al. · PLoS ONE (2024) | TGRS Research Map | TGRS