Browse > Article

Estimation of a Structural Equation Model Including Brand Choice Probabilities  

Lee, Sang-Ho (Department of Industrial and Management Engineering POSTECH)
Lee, Hye-Seon (Department of Industrial and Management Engineering POSTECH)
Kim, Yun-Dae (Department of Industrial and Management Engineering POSTECH)
Jun, Chi-Hyuck (Department of Industrial and Management Engineering POSTECH)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.36, no.2, 2010 , pp. 87-93 More about this Journal
Abstract
The partial least squares (PLS) method is popularly used for estimating the structural equation model, but the existing algorithm may not be directly implemented when probabilities are involved in some constructs or manifest variables. We propose a structural equation model including the brand choice as one construct having brand choice probabilities as its manifest variables. Then, we develop a PLS-based algorithm for the structural equation model by utilizing the multinomial logit model. A case is introduced as an application and simulation studies are performed to validate the proposed algorithm.
Keywords
Customer Equity; Multinomial Logit; Partial Least Squares; Simulation; Structural Equation Model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Fornell, C. and Bookstein, F. L. (1982), Two structural equation models : LISREL and PLS applied to consumer exit-void theory, Journal of Marketing Research, 19, 440-452.   DOI   ScienceOn
2 Hulland, J. (1999), Use of partial least squares (PLS) in strategic management research : a review of four recent studies, Strategic Management Journal, 20, 195-204.   DOI   ScienceOn
3 Hellier, P. K., Geursen, G. M., Carr, R. A., and Rickard, J. A. (2003), Customer repurchase intention : a general structural equation model, European Journal of Marketing, 37, 1762-1800.   DOI   ScienceOn
4 Guinot, C., Latreille, J. and Tenenhaus, M. (2001), PLS path modeling and multiple table analysis, Application to the cosmetic habits of women in Ile-de-France, Chemometrics and Intelligent Laboratory Systems, 58, 247-259.   DOI   ScienceOn
5 Joreskog, K. A. and Sorbom, D. (1989), LISREL 7 User's Reference Guide, 1st ed., Scientific Software, Mooresville, IN, USA.
6 Berger, P. D. and Nasr, N. I. (1998), Customer lifetime value : marketing models and applications, Journal of Interactive Marketing, 12(Winter), 17-30.   DOI
7 Blattberg, R. C. and Deighton, J. (1996), Manage marketing by the customer equity test, Harvard Business Review, 74(4), 136-144.
8 Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., and Bryant, B. E. (1996), The American customer satisfaction index : nature, purpose, and findings, Journal of Marketing, 60, 7-18.   DOI   ScienceOn
9 Fornell, C. and Larcker, D. F. (1981), Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 39-50.   DOI   ScienceOn
10 Bagozzi, R. P. (1980), Causal Models in Marketing, John Wiley and Sons, New York.
11 Martensen, A., Gronholdt, L., and Kristensen, K. (2000), The drivers of customer satisfaction and loyalty : cross-industry findings from Denmark, Total Quality Management, 11, S544-553.   DOI   ScienceOn
12 Noonan, R. and Wold. H. (1982), "PLS path modeling with indirectly observed variables : A comparison of alternative estimates for the latent variable," In Joreskog, K., and H. Wold, (Eds.), Systems under indirect observation : Causality, structure, prediction, Amsterdam : North Holland Publishing, 1-54.
13 Rust, R. T., Lemon, K. N., and Zeithaml, V. A. (2004), Return on marketing : using customer equity to focus marketing strategy, Journal of Marketing, 68, 109-127.   DOI   ScienceOn
14 Tenenhaus, M., Vinzi, V. E., Chatelin, Y., and Lauro, C. (2005), PLS path modeling, Computational Statistics and Data Analysis, 48, 159-205.   DOI   ScienceOn