Ringle, Christian M. (2006): Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach. Published in: University of Hamburg: Research Papers on Marketing and Retailing No. 35 (November 2006)
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Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical data. The assumption that the data is collected from a single homogeneous population is often unrealistic. Identification of different groups of consumers in connection with estimates in the inner path model constitutes a critical issue for applying the path modeling methodology to form effective marketing strategies. Sequential clustering strategies often fail to provide useful results for segment-specific partial least squares analyses. For that reason, the purpose of this paper is fourfold. First, it presents a finite mixture path modeling methodology for separating data based on the heterogeneity of estimates in the inner path model, as it is implemented in a software application for statistical computation. This new approach permits reliable identification of distinctive customer segments with their characteristic estimates for relationships of latent variables in the structural model. Second, it presents an application of the approach to two numerical examples, using experimental and empirical data, as a means of verifying the methodology's usefulness for multigroup path analyses in marketing research. Third, it analyses the advantages of finite mixture partial least squares to a sequential clustering strategy. Fourth, the initial application and critical review of the new segmentation technique for partial least squares path modeling allows us to unveil and discuss some of the technique's problematic aspects and to address significant areas of future research.
|Item Type:||MPRA Paper|
|Original Title:||Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach|
|Keywords:||partial least squares; PLS; path modeling; segmentation; latent class; finite mixture; customer satisfaction; brand preference|
|Subjects:||M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M0 - General
M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M3 - Marketing and Advertising > M31 - Marketing
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C19 - Other
|Depositing User:||Christian M. Ringle|
|Date Deposited:||26. Oct 2008 03:40|
|Last Modified:||12. Feb 2013 17:22|
Allenby, G.M./Arora, N./Ginter, J.L. (1998): On the heterogeneity of demand, in: Journal of Marketing Research, Vol. 35, No. 3, pp. 384-389.
Anderson, E.W./Fornell, C./Lehmann, D.R. (1994): Customer satisfaction, market share, and profitability: findings from Sweden, in: Journal of Marketing, Vol. 58, No. 3, pp. 53-66.
Anderson, E.W./Sullivan, M.W. (1993): The antecedents and consequences of customer satisfaction for firms, in: Marketing Science, Vol. 12, No. 2, pp. 125-143.
Bagozzi, R.P. (1994): Structural equation models in marketing research: basic principles, Blackwell, Oxford.
Bagozzi, R.P./Yi, Y. (1994): Advanced topics in structural equation models, Blackwell, Oxford.
Baumgartner, H./Homburg, C. (1996): Applications of structural equation modeling in marketing and consumer research: a review, in: Journal of Marketing Research, Vol. 13, No. 2, pp. 139-161.
Bayes, T. (1763/1958): Studies in the history of probability and statistics : IX. Thomas Bayes's essay towards solving a problem in the doctrine of chances ; Bayes's essay in modernized notation, in: Biometrika, Vol. 45, No., pp. 296-315.
Chin, W.W. (1998a): Issues and opinion on structural equation modeling, in: MIS Quarterly, Vol. 22, No. 1, pp. VII-XVI.
Chin, W.W. (1998b): The partial least squares approach to structural equation modeling, Lawrence Erlbaum Associates, Mahwah.
Chin, W.W./Dibbern, J. (2006): A permutation based procedure for multi-group PLS analysis: results of tests of differences on simulated data, Springer, Berlin et al.
Chun, R./Davies, G. (2006): The influence of corporate character on customers and employees: exploring similarities and differences, in: Academy of Marketing Science Journal, Vol. 34, No. 2, pp. 138-146.
Cohen, S.H./Ramaswamy, V. (1998): Latent segmentation models: new tools assist researchers in market segmentation, in: Marketing Research, Vol. 10, No. 2, pp. 14-21.
Desarbo, W.S./Jedidi, K./Sinha, I. (2001): Customer value analysis in a heterogeneous market, in: Strategic Management Journal, Vol. 22, No. 9, pp. 845-857.
Diamantopoulos, A./Winklhofer, H. (2001): Index construction with formative indicators: an alternative to scale development, in: Journal of Marketing Research, Vol. 38, No. 2, pp. 269-277.
Dillon, W.R./White, J.B./Rao, V.R./Filak, D. (1997): Good science: use structural equation models to decipher complex customer relationships, in: Marketing Research, Vol. 9, No. 4, pp. 22-31.
Fornell, C./Bookstein, F.L. (1982): Two structural equation models: LISREL and PLS applied to consumer exit-voice theory, in: Journal of Marketing Research, Vol. 19, No. 4, pp. 440-452.
Fornell, C./Johnson, M.D./Anderson, E.W./Jaesung, C./Bryant, B.E. (1996): The American Customer Satisfaction Index: nature, purpose, and findings, in: Journal of Marketing, Vol. 60, No. 4, pp. 7-18.
Fornell, C./Larcker, D.F. (1981): Structural equation models with unobservable variables and measurement error: algebra and statistics, in: Journal of Marketing Research, Vol. 18, No. 3, pp. 328-388.
Fornell, C./Lorange, P./Roos, J. (1990): The cooperative venture formation process: A latent variable structural modeling approach, in: Management Science, Vol. 36, No. 10, pp. 1246-1255.
Fornell, C./Robinson, W.T./Wernerfelt, B. (1985): Consumption experience and sales promotion expenditure, in: Management Science, Vol. 31, No. 9, pp. 1084-1105.
Gray, P.H./Meister, D.B. (2004): Knowledge sourcing effectiveness, in: Management Science, Vol. 50, No. 6, pp. 821-834.
Hahn, C./Johnson, M.D./Herrmann, A./Huber, F. (2002): Capturing customer heterogeneity using a finite mixture PLS approach, in: Schmalenbach Business Review, Vol. 54, No. 3, pp. 243-269.
Hofstede, F.t./Steenkamp, J.-B.E.M./Wedel, M. (1999): International market segmentation based on consumer-product relations, in: Journal of Marketing Research, Vol. 36, No. 1, pp. 1-17.
Jarvis, C.B./MacKenzie, S.B./Podsakoff, P.M. (2003): A critical review of construct indicators and measurement model misspecification in marketing and consumer research, in: Journal of Consumer Research, Vol. 30, No. 2, pp. 199-218.
Jedidi, K./Jagpal, H.S./DeSarbo, W.S. (1997): Finite-fixture structural equation models for response-based segmentation and unobserved heterogeneity, in: Marketing Science, Vol. 16, No. 1, pp. 39-59.
Jöreskog, K.G. (1978): Structural analysis of covariance and correlation matrices, in: Psychometrika, Vol. 43, No. 4, pp. 443-477.
Jöreskog, K.G. (1993): Testing Structural Equation Models, Sage, Newbury Park.
Kamakura, W.A./Russell, G.J. (1989): A probabilistic choice model for market segmentation and elasticity structure, in: Journal of Marketing Research, Vol. 26, No. 4, pp. 379-390.
Kim, B.-D./Srinivasan, K./Wilcox, R.T. (1999): Identifying price sensitve consumers: the relative merits of domogrphic vs. purchase pattern information, in: Journal of Retailing, Vol. 75, No. 2, pp. 173-193.
Lohmöller, J.-B. (1989): Latent variable path modeling with partial least squares, Physica-Verlag, Heidelberg.
MacKenzie, S.B./Podsakoff, P.M./Jarvis, C.B. (2005): The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions, in: Journal of Applied Psychology, Vol. 90, No. 4, pp. 710-730.
McLachlan, G.J./Basford, K.E. (1988): Mixture models: inference and applications to clustering, Marcel Dekker, New York.
McLachlan, G.J./Krishnan, T. (2004): The EM algorithm and extensions, John Wiley & Sons, Chichester.
Mittal, V./Anderson, E.W./Sayrak, A./Tadikamalla, P. (2005): Dual emphasis and the long-term financial impact of customer satisfaction, in: Marketing Science, Vol. 24, No. 4, pp. 531-543.
Morgan, N./Anderson, E.W./Mittal, V. (2005): Understanding firms' customer satisfaction information usage, in: Journal of Marketing, Vol. 69, No. 3, pp. 121-135.
Muthén, L.K./Muthén, B.O. (1998): Mplus user's guide, 4th ed., Muthén & Muthén, Los Angeles.
Ramaswamy, V./DeSarbo, W.S./Reibstein, D.J./Robinson, W.T. (1993): An empirical pooling approach for estimating marketing mix elasticities with PIMS data, in: Marketing Science, Vol. 12, No. 1, pp. 103-124.
Ringle, C.M./Wende, S./Will, A. (2005): SmartPLS 2.0 (beta), www.smartpls.de, Hamburg.
Rossiter, J.R. (2002): The C-OAR-SE procedure for scale development in marketing, in: International Journal of Research in Marketing, Vol. 19, No. 4, pp. 305-335.
Sargeant, A./Ford, J.B./West, D.C. (2006): Perceptual determinants of nonprofit giving behavior, in: Journal of Business Research, Vol. 59, No. 2, pp. 155-165.
Schneeweiß, H. (1991): Models with latent variables: LISREL versus PLS, in: Statistica Neerlandica, Vol. 45, No. 2, pp. 145-157.
Steenkamp, J.-B./Baumgartner, H. (2000): On the use of structural equation models for marketing modeling, in: International Journal of Research in Marketing, Vol. 17, No. 2/3, pp. 195-202.
Tenenhaus, M./Vinzi, V.E./Chatelin, Y.-M./Lauro, C. (2005): PLS path modeling, in: Computational Statistics & Data Analysis, Vol. 48, No. 1, pp. 159-205.
Venkatesh, V./Agarwal, R. (2006): Turning visitors into customers: a usability-centric perspective on purchase behavior in electronic channels, in: Management Science, Vol. 52, No. 3, pp. 367-382.
Wedel, M./Kamakura, W. (2000): Market segmentation: conceptual and methodological foundations, 2nd ed., Kluwer Academic Publishers.
Wold, H. (1980): Model construction and evaluation when theoretical knowledge is scarce: theory and application of PLS, Academic Press, New York.
Wold, H. (1982): Soft modeling: the basic design and some extensions, North-Holland, Amsterdam.
Wold, H. (1985): Partial least squares, Wiley, New York.
Wu, J./Desarbo, W.S. (2005): Market segmentation for customer satisfaction studies via a new latent structure multidimensional scaling model, in: Applied Stochastic Models in Business and Industry, Vol. 21, No. 4/5, pp. 303-309.
Yoo, B./Donthu, N./Lee, S. (2000): An examination of selected marketing mix elements and brand equity, in: Academy of Marketing Science Journal, Vol. 28, No. 2, pp. 195-211.