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Neural Computing and Applications

, Volume 32, Issue 1, pp 213–222 | Cite as

Research on cold chain logistic service pricing—based on tripartite Stackelberg game

  • Yajuan ZhangEmail author
  • Fang Rong
  • Zhuang Wang
Brain- Inspired computing and Machine learning for Brain Health

Abstract

Fresh e-commerce cannot be separated from cold chain logistics as a guarantee when supplying fresh agricultural products in different places. On the one hand, the high cost of cold chain logistics requires the cold chain logistic enterprises to price their services provided by cold chain logistic enterprises. On the other hand, it requires fresh e-commerce to reprice their products considering cold chain logistic cost. Whether the pricing strategies of both are proper affects the income of both sides, and also affects the consumers’ willingness to pay. Based on Steinberg game model and benefit equilibrium analysis, a three-stage pricing model with third-party cold chain logistic enterprise as leader, fresh e-commerce company as follower and consumer as secondary follower is established. Through the analysis of cooperative game and non-cooperative game, the optimal pricing and the best income of the cold chain logistic enterprises and the fresh e-commerce enterprises in the process of using cold chain logistics are obtained. Taking two different types of fresh products as an example, this paper simulates two kinds of fresh products based on pricing model, compares the two strategies of cooperative game and non-cooperative game, probes into the change of profit between fresh e-commerce and cold chain enterprises in different price ranges and selects pricing strategy.

Keywords

Cold chain logistics Stackelberg game Three-phase pricing model Non-cooperative game Cooperative game 

Notes

Acknowledgements

The authors acknowledge the Natural Science Foundation of Heilongjiang Province(Grant: G201403), the Young Talent Project of Northeast Agricultural University (Grant:14QC56), the National Natural Science Foundation of China(Grant: 71403047). the China Postdoctoral Science Foundation Project (Grant: 2014M561322), Postdoctoral Science Foundation Funded Project of Heilongjiang Province (Grant: LBH-Z14037).

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.College of Economics and ManagementNortheast Agricultural UniversityHarbinChina
  2. 2.College of ScienceNortheast Agricultural UniversityHarbinChina

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