Data analysis techniques in service quality literature: Essentials and advances

What is it about?

Academic and business researchers have for long debated on the most appropriate data analysis techniques that can be employed in conducting empirical researches in the domain of services marketing. On the basis of an exhaustive review of literature, the present paper attempts to provide a concise and schematic portrayal of generally followed data analysis techniques in the field of services quality literature. Collectively, the extant literature suggests that there is a growing trend among researchers to rely on higher order multivariate techniques viz. confirmatory factor analysis, structural equation modeling etc. to generate and analyze complex models, while at times ignoring very basic and yet powerful procedures such as mean, t-Test, ANOVA and correlation. The marked shift in orientation of researchers towards using sophisticated analytical techniques can largely be attributed to the competition within the community of researchers in social sciences in general and those working in the area of service quality in particular as also growing demands of reviewers of journals. From a pragmatic viewpoint, it is expected that the paper will serve as a useful source of information and provide deeper insights to academic researchers, consultants, and practitioners interested in modelling patterns of service quality and arriving at optimal solutions to increasingly complex management problems.

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Why is it important?

From a pragmatic viewpoint, it is expected that the paper will serve as a useful source of information and provide deeper insights to academic researchers, consultants, and practitioners interested in modelling patterns of service quality and arriving at optimal solutions to increasingly complex management problems.

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