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Handbook of Partial Least Squares pp 691–711Cite as

Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach

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Abstract

This paper gives a basic comprehension of the partial least squares approach. In this context, the aim of this paper is to develop a guide for the evaluation of structural equation models, using the current statistical methods methodological knowledge by specifically considering the Partial-Least-Squares (PLS) approach’s requirements. As an advantage, the PLS method demands significantly fewer requirements compared to that of covariance structure analyses, but nevertheless delivers consistent estimation results. This makes PLS a valuable tool for testing theories. Another asset of the PLS approach is its ability to deal with formative as well as reflective indicators, even within one structural equation model. This indicates that the PLS approach is appropriate for explorative analysis of structural equation models, too, thus offering a significant contribution to theory development. However, little knowledge is available regarding the evaluating of PLS structural equation models. To overcome this research gap a broad and detailed guideline for the assessment of reflective and formative measurement models as well as of the structural model had been developed. Moreover, to illustrate the guideline, a detailed application of the evaluation criteria had been conducted to an empirical model explaining repeat purchasing behaviour.

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References

  • Albers, S. (2010). PLS and Success Factor Studies in Marketing. In: V. Esposito Vinzi, W. Chin, J. Hensler, and H. Wold (Eds.,) Handbook of partial least squares, (pp.411–427), Heidelberg: Springer.

    Google Scholar 

  • Alpert, F., Kamins, M., Sakano, T., Onzo, N., & Graham, J. (2001). Retail buyer beliefs, attitude and behavior toward pioneer and me-too follower brands. International Marketing Review, 18, (2), 160–187.

    Article  Google Scholar 

  • Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12, pp. 125–143.

    Article  Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1991). Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities. Journal of Applied Psychology, 76, (5), pp. 732–740.

    Article  Google Scholar 

  • Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2003). Multivariate analysemethoden: eine anwendungsorientierte einführung (10th ed.). Berlin: Springer.

    Google Scholar 

  • Bagozzi, R. P. (1979). The role of measurement in theory construction and hypothesis testing: toward a holistic model. In O. C. Ferrell, S. W. Brown, C. W. Lamb (Eds.), Conceptual and theoretical developments in marketing (pp. 15–32). Chicago: American Markting Association.

    Google Scholar 

  • Bagozzi, R. P., & Baumgartner, H. (1994). The evaluation of structural equation models and hypothesis testing. In R. P. Bagozzi (Ed.), Principles of marketing research (pp. 386–422). Cambridge: Blackwell.

    Google Scholar 

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

    Article  Google Scholar 

  • Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modelling in marketing and consumer research: a review. International Journal of Research in Marketing, 13, 139–161.

    Article  Google Scholar 

  • Berscheid, E.; Snyder, M., & Omoto, A. M. (1989). The relationship closeness inventory: assessing the closenness of interpersonal relationships. Journal of Personality and Social Psychology, 57, 792–807.

    Article  Google Scholar 

  • Bitner, M. J. (1990). Evaluating service encounters: the effects of physical surroundings and employee responses. Journal of Marketing, 54(2), 69–82.

    Article  Google Scholar 

  • Bohrnstedt, G. W. (1970). Reliability and validity assessment in attitude measurement. In G. F. Summers (Ed.), Attitude measurement (pp. 80–99). London: Rand McNally.

    Google Scholar 

  • Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

    MATH  Google Scholar 

  • Bollen, K. A., & Lennox, R. (1991). Conventional wisdom on measurement: a structural equation perspective. Psychological Bulletin, 110(2), 305–314.

    Article  Google Scholar 

  • Bollen, K. A., & Ting, K. (2000). A tetrad test for causal indicators. Psychological Methods, 5, 3–22.

    Article  Google Scholar 

  • Bontis, N. (1998). Intellectual capital: an exploratory study that develops measures and models. Management Decision, 36(2), 63–76.

    Article  Google Scholar 

  • Boulding, W., Kalra, A., Staelin, R., & Zeithaml, V. A. (1993). A dynamic process model of service quality: from expectations to behavioral intentions. Journal of Marketing Research, 30, 7–27.

    Article  Google Scholar 

  • Bucic, T., & Gudergan, S. P (2004). Formative versus reflective measurement implications for explaining innovation in marketing partnerships. In: Proceedings of the Australia New Zealand Marketing Academy Conference.

    Google Scholar 

  • Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs – A typology, antecedents and consequences. Journal of the Academy of Marketing Science, 31(2), 109–126.

    Article  Google Scholar 

  • Chin, W., & Fry, T. A. (2004). PLS-Graph 3.0 Build 1126. Houston: Department of Decision and Information Science, University of Houston.

    Google Scholar 

  • Chin, W. W. (1998a). Issues and opinion on structural equation modeling. Management Information Systems Quarterly, 22(1), 7–16.

    MathSciNet  Google Scholar 

  • Chin, W. W. (1998b). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336) Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Chin, W.W. (2010). Bootstrap Cross-Validation Indices for PLS Path Model Assessment. In: V. Esposito Vinzi, W. Chin, J. Hensler, and H. Wold (Eds.,) Handbook of partial least squares, (pp. 83–97), Heidelberg: Springer.

    Google Scholar 

  • Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: relative importance of beliefs. DATA BASE for Advances in Information Systems, 26(2 & 3), 42–64.

    Google Scholar 

  • Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing, 16, 64–73.

    Article  Google Scholar 

  • Churchill, G. A. (1987). Marketing research: methodological foundations (4th ed.). Fort Worth: Dryden Press.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.

    MATH  Google Scholar 

  • Cohen, P., Cohen, J., Teresi, J., Marchi, M., & Velez, C. N. (1990). Problems in the measurement of latent variables in structural equations causal models. Applied Psychological Measurement, 14(2), 183–196.

    Article  Google Scholar 

  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.

    Article  Google Scholar 

  • Cronin, J. J. J., & Taylor, P. A. (1992). Measuring service quality. A Re-examination and Extension, Journal of Marketing, 56(3), 55–68.

    Google Scholar 

  • Diamantopoulos, A. (1999). Export performance measurement: reflective versus formative indicators. International Marketing Review, 16(6), 444–457.

    Article  Google Scholar 

  • Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: an alternative to scale development. Journal of Marketing Research, 38, 269–277.

    Article  Google Scholar 

  • Eckey, H. F.; Kosfeld, R. Draeger, C. (2001). Ökonometrie (2nd ed.), Wiesbaden: Gabler.

    Google Scholar 

  • Fassott, G. (2006). Operationalisierung latenter variablen in strukturgleichungsmodellen: eine standortbestimmung. Zeitschrift für betriebswirtschaftliche Forschung, 58, 67–88.

    Google Scholar 

  • Festinger, L. (1978). Theorie der kognitiven dissonanz. Bern: Verlag Hans Huber.

    Google Scholar 

  • Fornell, C., & Bookstein, F. L. (1982). A comparative analysis of two structural equation models: lisrel and pls applied to market data. In C. Fornell (Ed.), A second generation of multivariate analysis (pp. 289–323). New York, Praeger.

    Google Scholar 

  • Fornell, C., & Cha, J. (1994). Partial least squares. In R. P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 52–78). Cambridge: Blackwell.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18, 39–50.

    Article  Google Scholar 

  • Fornell, C., Lorange, P., & Roos, J. (1990). The cooperative venture formation process: a latent variable structural modeling approach. Management Science, 36(10), 1246–1255.

    Article  Google Scholar 

  • Ganesh, J., Arnold, M. J., & Reynolds, K. E. (2000). Understanding the customer base of service providers: an examination of the difference between switchers and stayers. Journal of Marketing, 64(30), 1–78.

    Google Scholar 

  • Geisser, S. (1975). A predictive approach to the random effect model. Biometrika, 61(1), 101–107.

    Article  MathSciNet  Google Scholar 

  • Giering, A. (2000). Der Zusammenhang zwischen Kundenzufriedenheit und Kundenloyalität Eine Untersuchung moderierender Effekte. Wiesbaden: Gabler.

    Google Scholar 

  • Götz, O., & Liehr-Gobbers, K. (2004). Analyse von Strukturgleichungsmodellen mit Hilfe der Partial-Least-Squares (PLS)-Methode. Die Betriebswirtschaft (DBW), 24(6), 716–740.

    Google Scholar 

  • Green, P. E., Tull, D. S., & Albaum, G. (1988). Research for marketing decisions (5th ed.), Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Gudergan, S. P.; Devinney, T. Ellis, R. S. (2003). A Competence-innovation framework of non-equity alliance performance, institute for the study of business markets. University Park: The Pennsylvania State University.

    Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Tatham, R. L. (2006). Multivariate Data Analysis (6th ed.), Upper Saddle River: Pearson.

    Google Scholar 

  • Hauser, R. M., & Goldberger, A. S. (1971). The treatment of unobservable variables in path analysis. In H. L. Costner (Ed.), Sociological methodology (pp. 81–117). London: Jossey-Bass

    Google Scholar 

  • Heskett, J. L., Sasser, W. E., & Schlesinger, L. A. (1997). The service profit chain. New York: The Free Press.

    Google Scholar 

  • Homburg, C., & Baumgartner, H. (1995). Die kausalanalyse als instrument der marketingforschung: eine bestandsaufnahme. Zeitschrift für Betriebswirtschaft, 65(10), 1091–1108.

    Google Scholar 

  • Homburg, C., & Giering, A. (1996). Konzeptualisierung und operationalisierung komplexer konstrukte. Marketing ZFP, 18(1), 5–24.

    Google Scholar 

  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(4), 195–204.

    Article  Google Scholar 

  • Jarvis, C. B., Mackenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model specification in marketing and consumer research. Journal of Consumer Research, 30, 199–218.

    Article  Google Scholar 

  • Kotler, P. (1994). Marketing management – analysis, planning, implementation and control (8th ed.), Englewood Cliffs, NJ, Prentice-Hill.

    Google Scholar 

  • Krafft, M. (1999). An empirical investigation of the antecedents of sales force control systems. Journal of Marketing, 63, 120–134.

    Article  Google Scholar 

  • Krafft, M., Haase, K., & Siegel, A. (2003). Statistisch-ökonometrische BWL-forschung: entwicklung, status quo und perspektiven. In M. Schwaiger; D. Harhoff (Eds.), Empirie und Betriebswirtschaft (pp. 83–104) Schäffer-Poeschel, Stuttgart: Entwicklungen und Perspektiven.

    Google Scholar 

  • Mathieson, K., Peacock, E., Chin, W. W. (1996). Extending the technology acceptance model: The influence of perceived user resources. Alberta, Canada: University of Calgary.

    Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory. (2nd ed.), New York: McGraw-Hill Book Company.

    Google Scholar 

  • O’Cass, A. (2002). Political advertising believability and information source value during elections. Journal of Advertising, 31(1), 63–74.

    Google Scholar 

  • Olsen, P. O. (2002). Comparative evaluation and the relationship between quality, satisfaction and repurchase loyality. Journal of Academy of Marketing Science, 30(3), 240–249.

    Google Scholar 

  • Peter, J. P. (1981). Construct validity: a review of basic issues and marketing practices. Journal of Marketing Research, 18, 133–145.

    Article  Google Scholar 

  • Peterson, R. A. (1994). A meta-analysis of cronbach’s coefficient alpha. Journal of Consumer Research, 21, 381–391.

    Article  Google Scholar 

  • Reichheld, F. F. (1993). Loyalty-based management. Harvard Business Review, 71, 64–73.

    Google Scholar 

  • Reinartz, W., Krafft, M., & Hoyer, W. D. (2004). The customer relationship management process: its measurement and impact on performance. Journal of Marketing Research, 41, 293–305.

    Article  Google Scholar 

  • Reinartz, W. Kumar, V. (2000). On the profitability of long-life customers in a noncontractual setting: an empirical investigation and implications for marketing. Journal of Marketing, 64(4), 17–35.

    Google Scholar 

  • Rindskopf, D. (1984). Using phantom and imaginery latent variables to parameterize constraints in linear structural models. Psychometrika, 49 37–47.

    Article  Google Scholar 

  • Rodgers, W., & Pavlou, P. (2003). Developing a predictive model: a comparative study of the partial least squares vs maximum likelihood techniques. (Working Paper). Graduate School of Management, University of California, Riverside.

    Google Scholar 

  • Rossiter, J. R. (2002). The C-OAR-SE procedure for scale development in marketing. International Journal of Research in Marketing, 19(4) 305–335.

    Article  Google Scholar 

  • Sambamurthy, V., & Chin, W. W. (1994). The effects of group attitudes towards alternative gdss designs on the decision-making performance of computer-supported groups. Decision Sciences, 25(2) 215–242.

    Article  Google Scholar 

  • Sarkar, M. B., Echambadi, R., Cavusgil, S. T., & Aulakh, P. S. (2001). The influence of complementarity, compatibility, and relationship capital on alliance performance. Journal of the academy of marketing science, 29(4), 358–373.

    Article  Google Scholar 

  • Sheth, J., & Parvatiyar, A. (1995). Relationship marketing in consumer markets: antecedents and consequences. Journal of the Academy of Marketing Science, 23(4), 255–271.

    Article  Google Scholar 

  • Soo, C. W., Midgley, D. F., & Devinney, T. M. (2002). The Process of Knowledge Creation in Organizations. (Working Paper). INSEAD, Fontainebleau.

    Google Scholar 

  • Sriram, V., Mummalaneni, V. (1990). Determinants of Source Loyalty in Buyer-Sellers Relationships. Journal of Purchasing and Materials Management, 26(4), 21–26.

    Google Scholar 

  • Stone-Romero, E. F., Stone, D. L. (1997). Development of a multidimensional measure of perceived product quality. Journal of Quality Management, 2(1), 87–111.

    Article  Google Scholar 

  • Stone, M. (1975). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–133.

    Google Scholar 

  • Tan, W. G., Chan, T., & Gable, G. G. (1999). A structural model of software maintainer effectiveness. In Proceedings of the 10th Australasian Conference on Information Systems, Wellington, pp. 943–954.

    Google Scholar 

  • Taylor, P., & Baker, T. (1994). An assessment of the relationship between service quality and customer satisfaction in the formation of consumers’ purchase intention. Journal of Retailing, 70, 163–178.

    Article  Google Scholar 

  • Temme, D., Kreis, H., & Hildebrandt, L. (2010). A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance. In: V. Esposito Vinzi, W. Chin, J. Hensler, and H. Wold (Eds.,) Handbook of partial least squares, (pp. 741–760), Heidelberg: Springer.

    Google Scholar 

  • Venaik, S., Midgley, D. F., & Devinney, T. (2004). A new perspective on the integration-responsiveness pressures confronting multinational firms. Management International Review, 44(1), 15–48.

    Google Scholar 

  • Venaik, S., Midgley, D. F., & Devinney, T. M. (2001). Autonomy, Networking and Interunit Learning in a Model of MNC Subsidiary Innovation and Performance. http://www.agsm.edu.au/∼timdev/research/VMD.PDF.

  • Vinzi, V. E., Lauro, C., & Tenenhaus, M. (2003). PLS Path Modeling. (Working Paper). DMS – University of Naples, HEC – School of Management, Jouy-en-Josas.

    Google Scholar 

  • Woodside, A. G., & Taylor, J. L. (1978). Consumer purchase intention of product quality and national advertising. Journal of Advertising, 7(1), 48–51.

    Google Scholar 

  • Yi, Y., Jeon, H. (2003). Effects of loyality programs on value perception, program loyalty and brand loyalty. Journal of Academy of Marketing Science, 31(3), 229–40.

    Article  Google Scholar 

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Authors and Affiliations

  1. Marketing Centrum Münster, University of Münster, Am Stadtgraben 13-15, 48143, Münster, Germany

    Oliver Götz & Manfred Krafft

  2. Hering Schuppener Consulting, Kreuzstraße 60, 40210, Düsseldorf, Germany

    Kerstin Liehr-Gobbers

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  1. Oliver Götz
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  2. Kerstin Liehr-Gobbers
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  3. Manfred Krafft
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Correspondence to Oliver Götz .

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Editors and Affiliations

  1. Dept. Inf. Systems & Decision Sciences, ESSEC Business School of Paris, av. Bernard Hirsch, Cergy Pontoise CX, 95021, France

    Vincenzo Esposito Vinzi

  2. Bauer College of Business, University of Houston, Houston, 77204-6282, U.S.A.

    Wynne W. Chin

  3. Nijmegen School of Management, Radboud University, Nijmegen, Netherlands

    Jörg Henseler

  4. School of Economics & Management, BeiHang University, XueYuan Road 37, Beijing, 100083, China, People's Republic

    Huiwen Wang

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Götz, O., Liehr-Gobbers, K., Krafft, M. (2010). Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach. In: Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds) Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_30

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