Volume 5 Number 8 (Aug. 2010)
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JCP 2010 Vol.5(8): 1264-1272 ISSN: 1796-203X
doi: 10.4304/jcp.5.8.1264-1272

Applying Rough Set Theory to Evaluate Network Marketing Performance of China’s Agricultural Products

Hua Jiang and Junhu Ruan
School of Economics and Management, Hebei University of Engineering, Handan, China

Abstract—Agricultural products network marketing means fully introducing e-commerce systems into the sale process of agricultural products, using information technologies to publish and collect the demand and price information, and relying on agricultural production bases and logistics distribution systems to enhance brand images, improve customer services, develop online marketing channels and ultimately expand marketing activities. It is very important to evaluate the performance of agricultural products network marketing. The paper proposed a performance evaluation model of agricultural products network marketing based on rough set theory. The model used genetic algorithm to reduce the initial decision table and, through calculating the importance of the decision attributes in the reduced decision table, identified the weight coefficients of various influencing indexes, effectively overcoming the subjectivity of weight coefficient determination in the current evaluation models. In the same time, the paper evaluated the network marketing performance of six agricultural enterprises and the results were in line with the actual results, which verified the validity of the proposed evaluation model. Lastly, the paper, according to the reduced results of the initial index system, proposed specific measures and suggestions to improve the network marketing performance of agricultural products.

Index Terms—agricultural products; network marketing; performance evaluation; rough set theory; measures and suggestions

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Cite: Hua Jiang and Junhu Ruan, " Applying Rough Set Theory to Evaluate Network Marketing Performance of China’s Agricultural Products," Journal of Computers vol. 5, no. 8, pp. 1264-1272, 2010.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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