An Application of Logit Model and Genetic Algorithm on the Optimal Price Promotion Mix Strategies: A Case Study of Online Fashion Clothing Websites

• Main Authors: Jie-Siou Wu, 吳杰修
• Other Authors: 張淳智
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/2rfpzb

碩士 === 國立臺中科技大學 === 流通管理系碩士班 === 103 === This study aims to discover the strategies of firms’ optimal price promotion mix by considering preference of consumer demand. This study adopts questionnaire data in Feb. 2013 of SBIR. The responders are consumers with the experiences of purchasing products on the specific clothing website. The model was conducted in two phase to obtain the optimal price promotion mix under firm’s profit maximization. First, we used binary logit model to build the discrete demand model of customers’ purchase intention. The discount methods, discount level, discount frequency, shipping fee free with certain expenditure and lifestyles. Afterward, we apply variables as decision variables such as discount methods, discount level and shipping fee free with certain expenditure to construct the optimization models under firm’s profit maximization in various scenarios and solved by genetic algorithms. The empirical results show as following: 1.Customer&;apos;&;apos;s purchase preference: The factors influencing customers’ purchase preference are discount methods, discount level, discount frequency and shipping fee free with certain expenditure. 2.Optimal price promotion mix: (1)Direct price reduction is suggested when customers executing coupons with high probability, while coupons is suggested when customers applying coupons with low probability. (2)When firms apply direct price reduction as discount method, we suggest firms do not discount. (3)The solution framework proposed in this study is able to resolve optimal values of price promotional variables in various scenarios.