Investigating the drivers of student satisfaction : the application of regression analysis

Greenland, Steve (2005) Investigating the drivers of student satisfaction : the application of regression analysis. Investigations in university teaching and learning, 2 (2). pp. 46-53. ISSN 1740-5106


Many organisations strive to enhance service quality in order to increase customer satisfaction. This strategy is widely recognised as improving both customer retention and post consumption attitudes (Mittal and Kamakura 2001). Accordingly many different approaches for evaluating service quality have been developed. Quantitative studies frequently employ either gap analysis (Greenland 2003) or regression analysis in this regard, with many considering the latter to be one of the more statistically reliable methods (e.g., Bolton and Drew 1994; Chu 2002; Desarbo et al. 1994; Lassar et al., 2000). Regression can be used to determine the significant drivers of customer satisfaction by linking ratings of various aspects of service (the independent variables) to an overall measure of satisfaction (the dependent variable). Some consider its application to be particularly relevant to university teaching (e.g., Liaw and Goh 2003). The main criticisms of the approach concern the level of explanation of the regression equation, which may be low, and multicolliniarity, which can mean attributes are highly correlated with one another. However, this latter problem is readily overcome by application of the Ridge Regression method (Coshall 1993, Hoerl and Kennard 1970) available in SPSS (Statistical Package for the Social Sciences). This paper investigates the application of regression analysis to an appraisal of classroom teaching, in order to explore the key drivers of satisfaction for business students. After a description of the research method and results, recommendations for improving student satisfaction, as well as implications for classroom teaching evaluation are discussed.

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