A correlated uniqueness model of service quality measurement among users of cloud-based service platforms

This research furthers understanding of whether consumers of cloud-based service platforms can distinguish between gap theory dimensions (i.e., expectation and performance) on these platforms. We build upon and extend the work of (Natesan and Aerts, 2016) by applying confirmatory factor analysis on gap scores from survey data to develop and test an improved approach of measuring service system quality in cloud-based service platforms. Using the IS-adapted SERVQUAL instrument, we apply the correlated uniqueness model, which is part of the multitrait-multimethod (MTMM) framework, to evaluate the validity of using GAP scores and account for the effect of the method. There is significant support for method effects as shown by our suggested model paths in the trait convergent validity model with medium-large factor coefficients. Additionally, the fit of the correlated uniqueness model indicates respondents can distinguish between the gap theory dimensions of the IS-adapted SERVQUAL instrument. The praxis of service quality measurement could benefit by using our measurement approach of incorporating error correlations.