Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry

碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 91 === As the dramatic changes of the marketing environment, the customers whom enterprises treat are not homogenous but heterogonous. Thus, how to identify the heterogeneity of the customers and apply clustering method to identify the difference between the custo...

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Main Authors: Yu,Chun-Yuan, 游濬遠
Other Authors: CHIU, CHIH-CHOU
Format: Others
Language:zh-TW
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/79293440150766390829
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spelling ndltd-TW-091TIT006820322015-10-13T13:35:32Z http://ndltd.ncl.edu.tw/handle/79293440150766390829 Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry 異質性分析在商業智慧之應用--以流通業及製造業為例 Yu,Chun-Yuan 游濬遠 碩士 國立臺北科技大學 商業自動化與管理研究所 91 As the dramatic changes of the marketing environment, the customers whom enterprises treat are not homogenous but heterogonous. Thus, how to identify the heterogeneity of the customers and apply clustering method to identify the difference between the customers has become critical point of successful marketing activities. Practitioners always use RFM method to evaluate customer value and segment the customers. But RFM method can’t explain the difference between different groups and evaluate the result. As a result, we define interpurchase time as the heterogeneity of the customers and estimate it by using hierarchical Bayesian method in order to overcome the disadvantage of the RFM method. After the verifying of the method, we found that RFM method can be applied successfully in 3C logistic industry. In addition, the result estimated by the hierarchical Bayesian method can help us to evaluate the result of the clustering from RFM method and to describe the different behavior of transaction of each person. Moreover, practitioners in 3C logistic industry can build up the appropriate mechanism of marketing segmentation based on our proposed approach as soon as they conduct customer relationship management. Finally, we have applied the similar approach in manufacture industry to identify the products heterogeneity. Based on the results, we found that heterogeneity analysis method can be applied as well. After modeling the failure time of the objectives, we can predict the reliability of the objectives, which is contributed to the practitioners in manufacture industry. CHIU, CHIH-CHOU 邱志洲 2003 學位論文 ; thesis 65 zh-TW
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language zh-TW
format Others
sources NDLTD
description 碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 91 === As the dramatic changes of the marketing environment, the customers whom enterprises treat are not homogenous but heterogonous. Thus, how to identify the heterogeneity of the customers and apply clustering method to identify the difference between the customers has become critical point of successful marketing activities. Practitioners always use RFM method to evaluate customer value and segment the customers. But RFM method can’t explain the difference between different groups and evaluate the result. As a result, we define interpurchase time as the heterogeneity of the customers and estimate it by using hierarchical Bayesian method in order to overcome the disadvantage of the RFM method. After the verifying of the method, we found that RFM method can be applied successfully in 3C logistic industry. In addition, the result estimated by the hierarchical Bayesian method can help us to evaluate the result of the clustering from RFM method and to describe the different behavior of transaction of each person. Moreover, practitioners in 3C logistic industry can build up the appropriate mechanism of marketing segmentation based on our proposed approach as soon as they conduct customer relationship management. Finally, we have applied the similar approach in manufacture industry to identify the products heterogeneity. Based on the results, we found that heterogeneity analysis method can be applied as well. After modeling the failure time of the objectives, we can predict the reliability of the objectives, which is contributed to the practitioners in manufacture industry.
author2 CHIU, CHIH-CHOU
author_facet CHIU, CHIH-CHOU
Yu,Chun-Yuan
游濬遠
author Yu,Chun-Yuan
游濬遠
spellingShingle Yu,Chun-Yuan
游濬遠
Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
author_sort Yu,Chun-Yuan
title Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
title_short Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
title_full Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
title_fullStr Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
title_full_unstemmed Apply Heterogeneity Analysis on Business Intelligence— Case Study of Logistics Industry and Manufacture Industry
title_sort apply heterogeneity analysis on business intelligence— case study of logistics industry and manufacture industry
publishDate 2003
url http://ndltd.ncl.edu.tw/handle/79293440150766390829
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