Shelf Space Management based on Association Rules

• Main Authors: Chen Shoei-Cherng, 陳水成
• Other Authors: Dr.Chien-Wen Wu
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/02460261699500938400

碩士 === 國立臺北科技大學 === 生產系統工程與管理研究所 === 91 === Understanding the segmentation of customers, the need of customers, and the preferences of customers is always the first concern for retailing management. Due to the rapid progress of computers, customer transactions can be recorded and analyzed. How to extract the embedded knowledge from the huge amount of customer transactions and utilize the knowledge to improve retailing management becomes very important. Shelf spaces are the most important resources for retailing business.Excellent shelf space management can help attract the customers and increase sales. This thesis is to apply the association rules mining technique to analyze the transactions data of a retailing business. The mined association rules reveal the customer knowledge. We then employ the mined association rules to assist in the allocation and arrangement of the shelf spaces. This thesis provides a systematic framework for shelf space management. Experiments are performed to apply the proposed framework to a large local snacks retailing business with more than 60,000 customer transactions. Experimental results are reported in the thesis.