An assessment of the use of partial least squares structural equation modeling in marketing research

Author:

Hair Joe F.,Sarstedt Marko,Ringle Christian M.,Mena Jeannette A.

Publisher

Springer Science and Business Media LLC

Subject

Marketing,Economics and Econometrics,Business and International Management

Reference103 articles.

1. Babakus, E., Ferguson, C. E., & Jöreskog, K. G. (1987). The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions. Journal of Marketing Research, 24(2), 222–228.

2. Babin, B. J., Hair, J. F., & Boles, J. S. (2008). Publishing research in marketing journals using structural equation modeling. Journal of Marketing Theory & Practice, 16(4), 279–285.

3. Bagozzi, R. P. (1994). Structural equation models in marketing research: Basic principles. In R. P. Bagozzi (Ed.), Principles of marketing research (pp. 317–385). Oxford: Blackwell.

4. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

5. Barclay, D. W., Higgins, C. A., & Thompson, R. (1995). The partial least squares approach to causal modeling: personal computer adoption and use as illustration. Technology Studies, 2(2), 285–309.

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