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The purpose of this paper is to allow researchers, instructors, and students to comprehend the nature of exploratory factor analysis (EFA) from marketing perspective. In particular, the paper offer realistic information from marketing literature on developing valid instruments and making decision regarding factor extraction, factor rotation, and factor labeling. Since the items and factors identified through EFAs are using as an input for the measurement model in second generation structural equation modeling (SEM) technique. While so doing, a pilot test was conducted and items from marketing literature were analyzed via principal component analysis (PCA) using SPSS 20, the appropriateness of data for EFA was measured through KMO and Bartlett’s test of Sphericity. Based on parallel analysis three factors were extracted for further investigation. The three components explained a total of 62.6% of the variance. DOI: 10.5901/jesr.2016.v6n1p215
Hadia et al. (Tue,) studied this question.
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