Development of a mobile commerce system with an automatic merchandise recommendation mechanism- A case study on the shopping mall of Taiwan Sugar Company

• Main Authors: Jun-tsung Ke, 柯榮宗
• Other Authors: Gwo-Jen Hwang
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/81850589954201278161

碩士 === 國立臺南大學 === 數位學習科技學系碩士班 === 100 === With the advance of wireless technology and widespread use of mobile devices, mobile commerce (m-commerce) has been an emerging industry following the e-commerce. In this study, an m-commerce platform is proposed and an application that provides personalized service in a shopping mall of Taiwan Sugar Company in Tainan city by integrating mobile and QR code technologies is reported, The m-commerce system is able to recommend personalized merchandise to individual customers based on their shopping behaviors or records; in the meanwhile, the system records customers’ shopping portfolios in the field for further analysis. It is expected that the system can provide marketing manager the information of potential customers by matching the merchandise characteristics and the customers’ shopping preferences and logs. Accordingly, the messages of merchandises can be delivered to potential customers via e-mail or SMS, such that personalized service can be offered to customers instantly to increase their purchasing willingness and hence strengthens the competitiveness of the merchandises. To evaluate the proposed approach, 42 shopping mall members participated in the experiment to experience the m-commerce system. Their responses to the questionnaires before and after the experiment were collected and analyzed. The experimental results showed that the system was easy-to-use, even for those novice users, in obtaining the merchandize information. As to the marketing aspect, most of customers tended to accept advertising messages via emails. Moreover, most participants agreed that the service quality had been significantly promoted by employing the m-commerce approach with the personalized recommendation mechanism.