Appling Data Mining Research on Consumer Electronic Commerce of Agricultural Products for an Agricultural E-store

• Main Authors: Tseng, Chunfeng, 曾羣峰
• Other Authors: Dr. Peng, Kechung
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/73168979726867510474

碩士 === 國立屏東科技大學 === 農企業管理系所 === 100 === The e-commerce market in Taiwan is growing year by year, and becoming one of the main access for consumers. Such huge business opportunities attracts many industrial companies to put into operation. So it is very important to have a competitive advantage in such a competitive market. Companies can identify the useful information hidden in the numerous and jumbled data through data mining. For example, they can explore the shopping tendency hidden in consumer behaviors. As a result, the enterprises can recommend the appropriate goods in a proactive attitude to meet the consumer needs. They can enhance the loyalty and satisfaction of the customers, and grasp the hearts of customers effectively. Two data mining techniques, decision tree and Association Rule Analysis of Microsoft SQL Server 2008R2 software, were used to the members’ database of an online store of agricultural products, and explored three cluster members. After using the Decision Tree Analysis, we can find that the main factors influencing the consumers on buying the commodity categories were age,income, and gender. For example, Customer populations such as processing of agricultural products would purchase for less than 55 years of age, and female customers, 63.38% of people will buy. The case company can use these features and lock the different influencing factors, to send the E-DM to improve the efficiency and save the cost. The Association Rule Analysis had mined 13 useful association rules. For example, consumers who purchased pasta and soy sauce will be 100% to buy soy sauce. So we can link the web links between the relational commodities items, or unify placed in the pages of the specified zone. Thus we can provid consumers with intimate services, to stimulate the customers to increase the amount of consumption. According to the study, data mining can help companies to understand customers’buying behaviors, find the right customers, and to develop suitable marketing strategies to save the marketing costs to create the largest profit purposes.