Browsing by Author "Chao, Chuang-Min"

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Applying loss aversion to investigate service quality in logistics A moderating effect of service convenience
(2010)
Hsu, Chia-Lin
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Chen, Mu-Chen
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Chang, Kuo-Chien
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Chao, Chuang-Min
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運輸與物流管理系註：原交通所+運管所
Purpose - Using the concept of loss aversion, this paper aims to investigate the relationship between service quality and customer loyalty in the home delivery industry. The second purpose of this paper is to investigate the moderating effect of service convenience in the relationship between service quality and customer loyalty. Furthermore, this paper attempts to demonstrate the existence of a moderating effect either on the service quality loss (SQLOSS)-customer loyalty link, or on the service quality gain (SQGAIN)-customer loyalty link, or on both. Design/methodology/approach - In this paper, the research model and hypotheses are constructed through a literature review. Data are collected by a questionnaire survey, and the adapted SERVQUAL scale is taken as the measurement instrument. Structural equation modeling is adopted to confirm the above relationships. Findings - From the results come the finding that a loss in service quality has a greater effect on customer loyalty than that of a SQGAIN in the home delivery industry. This paper also proves that the relationship between service quality and customer loyalty is moderated by service convenience. Originality/value - This paper demonstrates the effect of asymmetric response of service quality on customer loyalty.
Measuring the performance of financial holding companies
(2010)
Chao, Chuang-Min
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Yu, Ming-Miin
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Financial institutions have become larger and engage in a wider array of financial activities due to continuing consolidation. Since the financial holding companies face multiple production functions simultaneously, the traditional data envelopment analysis (DEA) approach is not suitable for investigating their efficiency. This study applies the multi-activity DEA model to explore the relative efficiency of 12 financial holding companies in Taiwan. The results show that the multi-activity DEA model is obviously more capable of identifying sources of inefficiency, thereby potentially yielding greater managerial insights into organisational improvements.
Pattern filtering and classification for market basket analysis with profit-based measures
(2012-05-01)
Chen, Mu-Chen
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Chao, Chuang-Min
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Wu, Kuan-Ting
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Market basket analysis is one of the typical applications in mining association rules. The valuable information discovered from data mining can be used to support decision making. Generally, support and confidence (objective) measures are used to evaluate the interestingness of association rules. However, in some cases, by using these two measures, the discovered rules may be not profitable and not actionable (not interesting) to enterprises. Therefore, how to discover the patterns by considering both objective measures (e. g. probability) and subjective measures (e. g. profit) is a challenge in data mining, particularly in marketing applications. This paper focuses on pattern evaluation in the process of knowledge discovery by using the concept of profit mining. Data Envelopment Analysis is utilized to calculate the efficiency of discovered association rules with multiple objective and subjective measures. After evaluating the efficiency of association rules, they are categorized into two classes, relatively efficient (interesting) and relatively inefficient (uninteresting). To classify these two classes, Decision Tree (DT)-based classifier is built by using the attributes of association rules. The DT classifier can be used to find out the characteristics of interesting association rules, and to classify the unknown (new) association rules.