The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

Jun Sun, Ruben Xing
DOI: 10.4018/978-1-5225-9621-9.ch020
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Abstract

This research paper is to use a method of Evolutionary Game to investigate the relationship between a large supplier and a franchised supermarket in China. The authors would like to go through their empirical study with their filtered answers from the survey using SPSS software on agricultural supply chain for their quality safety factors. Their research is using factor analysis with five target factors which are: the excess return, cost, the relative size of cooperative enterprises, hitchhiking, and overflows income. Applying these factors to the evolutionary game model, analyze the earning status from the both players under their own policies, then make suggestions or proposals for quality and safety issues of agricultural supply chain management.
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3. Data Collection

This investigation was conducted mainly in the form of issuing questionnaires and field random sampling survey. Our insurance of questionnaires went through with the main respondents. Based on Lianshan Town area, they were selected from the reginal farmers, suppliers, vendors, consumers and regulators as well (see Figure 1). Total 278 of 320 issued questionnaires were recovered, and 261 responses were confirmed the valid ones after effective screening. The recovery rate was 86.875% with the effective rate of 81.56%. There were 96 males and 165 females among the effective respondents. After issuing, recovering the questionnaires, and excluding invalid ones through initial screening, and analyzed by SPSS18.0 data analytics software. Subjects of the investigation are mainly farmers, suppliers, sellers, customers, regulators. The proportion and numbers of the respondents are listed in Table 1.

Table 1.
The fieldwork investigation object of the quality-safety of agricultural products supply chain
RespondentsProportion
Farmer16.9%
Supplier19.5%
Sellers15.7%
Consumer41.8%
Regulators6.1%

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