The numerous high-rise residential buildings and multi-house communities in urban and metropolitan areas have strained condominium management (CM) services. Contracting professionals in the building maintenance, management, and services delivery business is the most efficient and effective solution for managerial decisions related to residential community issues such as community safety, community interactions and co-owned community assets. The CM business thereby gains excellent prospects for future generations with numerous business opportunities in highly developed cities.
The capital requirements for market entry are low for CM businesses, as most services do not require highly specialized skills or advanced equipment to achieve an acceptable level of service quality; this has resulted in a highly competitive CM industry. This competitiveness and lack of a reliable system for measuring service quality have forced CM companies to pursue low-price strategies to increase market share.
Although some interviewed chief executive officers of CM companies address a significant need to improve service quality (SQ) to gain competitiveness, attempting to enhance SQ without knowledge of SQ and consumer satisfaction (CS) measurements is inefficient or frequently employed strategies that are then quickly abandoned. The current greatest challenge facing CM services in terms of improving service quality is a lack of information regarding SQ measurements, leading to insufficient comprehension of which services need to be set as first priority so as to increase resident satisfaction.
Service quality is a significant antecedent of CS, and strongly influences profitability, productivity, market share, return on investment, and cost reduction (Anderson and Fornell, 2000, Fornell et al., 1996, Lin, 2007, Oliver, 1997, Olsen, 2002, Park et al., 2006 and Wen et al., 2005). That is, improved SQ can increase, CS reduce the number of customer complaints and enhance customer loyalty. Continuously improving SQ is very important, especially for attributes affecting CS in strengthening the loyalty to CM businesses, as well as enhancing operations competency.
Prior to SQ improvements, decision-makers must determine the empirical relationships between SQ and CS, and their measurements. Empirical research demonstrated that CS is a function of both expectations related to certain service attributes and the assessment of attribute performance (Deng and Pei, 2009, Hawes and Rao, 1985, Martilla and James, 1977, Matzler et al., 2004 and Tao et al., 2009). Both relationships between SQ and CS or customer expectations provide information relevant to enhancing CS; however, these are complex relationships in the marketing field and require detailed analyses. To implement SQ measurements to improve CM businesses, the structural relationships between SQ attributes and CS are investigated in this study.
Importance–performance analysis (IPA) is a conventional means of evaluating or identifying service operations and attributes important to CS and perceived performance ratings (Deng, 2008, Martilla and James, 1977, Shieh and Wu, 2009 and Wu et al., 2009). Notably, IPA provides insight into which service attributes a firm should focus on and can identify problems such as inefficient resource utilization.
However, in conventional IPA studies and applications, respondents were typically asked to evaluate the importance of investigated attributes without consideration of interactive effects with other attributes. In some cases, multiple regression analysis (MRA) was employed to evaluate the importance of SQ predictor variables (PVs) to a CS criterion variable with an unrealistic assumption of independence. Neglecting the multicollinearity of multiple PVs can generate incorrect effects on the criterion variable. Additionally, when importance rates were evaluated without the clear defined purpose for improving CS, conventional IPA may not be an effective tool to develop management strategies (Oh, 2001).
This work presents novel procedures combining multiple methods, including factor analysis, the multivariate statistical technique, and IPA (Bacon, 2003, Martilla and James, 1977 and Wu et al., 2009), and then applies the service quality model adapted from Kano (Kano et al., 1984, Lin, 2007 and Yang et al., 2011) to effectively deploy service quality strategies so as to continuously improve resident satisfaction with CM services.
First, SQ attributes were identified on the basis of theoretical support and literature findings, and then narrowed down to a manageable size utilizing factor analysis. The relative importance rates of retained SQ attributes were explored using a multivariate statistical technique to investigate the contributions of interested attributes to total variance in the predicted resident satisfaction score (RSS). Then, IPA was employed to assess the relationship between relative importance rates and the performance of SQ attributes. Based on the theory of Kano’s model, reliable, effective and efficient management strategies can be deployed to enhance resident satisfaction.
The rest of this paper is organized as follows. Section 2 reviews literature and methods used to measure and investigate SQ and CS and to implement the importance–performance analysis (IPA) as the caution that must be employed when SQ and CS is measured and IPA is adopted. Section 3 then outlines the research methodology utilized for analyses. Next, Section 4 describes the profile of survey data and exploratory factor analysis (EFA), including empirical results of extracted SQ constructs and associated attributes. Section 5 presents an empirical assessment of the relative importance rates using IPA and Kano’s model. Conclusions are finally drawn in Section 6, along with managerial implications and recommendations for CM services.
