Customer Behavior and Decision Making in the Refurbishment Industry‐a Data Mining Approach

Abstract

Abstract. The study of consumer behavior in the refurbishment industry is crucial to the business operation of firms, but there is a lack of research in this regard. With reference to the EKB model specific to consumer behavior, this paper discusses the relationship among consumption characteristics, firm selection behavior and satisfaction degree of refurbishment customers. 242 valid questionnaire copies were collected from refurbishment customers, and analyzed using Decision Tree Analysis and Association Rules in Data Mining. The research results show that, over half of the customers tend to entrust the refurbishment to well-reputed firms. Moreover, the integrity of refurbishment equipment, response of refurbishment personnel, professionalism and confidence are key elements in service quality (SQ). The best marketing policy for the customers is one which provides more attractive services. These research findings may provide a useful reference for innovative refurbishment firms in their decision-making.

Heterogeneity in Perceptions of Service Quality among Groups of Railway Passengers

“…Decision trees have been also adopted for analyzing quality of service in industries other than transportation. Huang and Hsueh (2010) analyzed the overall service quality satisfaction on a refurbishment industry, considering 22 items describing the service. In the field of public transportation, decision trees are relatively new.…”

A classification tree approach to identify key factors of transit service quality

“…The method has also been used for analysing other aspects of traffic engineering: used decision trees to forecast trip generation; considered using trees to determine modal correction factors for motor vehicle emissions; and Hallmark et al (2002) used trees to identify geometric and operational roadway characteristics that influenced vehicle activity. Although there are some recent decision tree applications for analysing quality of service in others industries (Wong and Chung, 2007;Huang and Hsueh, 2010), the authors have not found any application of CART to analyse quality of service for bus transit operation. Therefore, the main purpose of this study is to examine whether or not the CART model can effectively identify the key factors affecting bus transit SQ.…”

A Comprehensive Framework for Evaluating Key Project Requirements

“…Additionally, a review of the literature suggests that RDM effort may improve requirements quality in terms of correctness, consistency, and completeness, which subsequently affecting the performance of a project (Damian, Chisan 2006;Procaccino et al 2002;Brooks 1987;Kauppinen et al 2004;Herbsleb, Goldenson 1996;Radujković et al 2010;Huang, Hsueh 2010;Toor, Ogunlana 2010). This study extends previous studies by addressing the impact of requirements completeness on project performance in the building industry.…”

“…Thus, requirements definition is often cited as one of the most important, but difficilt, phases of a project (Brooks 1987). The results of previous studies indicated a correlation between requirements definition effort and project performance (Damian, Chisan 2006;Procaccino et al 2002;Brooks 1987;Kauppinen et al 2004;Herbsleb, Goldenson 1996;Huang, Hsueh 2010;Radujković et al 2010;Toor, Ogunlana 2010;Yang et al 2011).…”