Skip to main content
SpringerLink
Log in

Do We Fully Understand the Critical Success Factors of Customer Satisfaction with Industrial Goods? - Extending Festge and Schwaiger’s Model to Account for Unobserved Heterogeneity

  • Research Article
  • Published:
Journal of business market management

Abstract

This paper extends Festge and Schwaiger’s (2007) model of customer satisfaction with industrial goods by accounting for unobserved heterogeneity. The application of a novel response-based segmentation approach in partial least squares path modeling (PLS-PM) - the finite mixture partial least squares (FIMIX-PLS) methodology - opens the way for the effective identification of distinctive customer segments. In comparison to previous studies in this field, group-specific path model estimates reveal each customer segment’s particular characteristics as well as other differentiated findings. Hence, this contribution demonstrates that structural equation modeling studies on the aggregate data level can be seriously misleading and makes a strong case for segment-specific customer satisfaction analyses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. “Note that this presentation slightly differs from Hahn et al.’s (2002) original presentation”

  2. Even though recent research shows that single items lag significantly behind multi-item measures in terms of criterion validity (Sarstedt and Wilczynski 2009), a single item may still be used as a measure to assess a construct on an aggregate level, as all respondents can simultaneously consider all those parts of the construct that they consider important (Nagy 2002).

  3. The authors would like to thank the anonymous reviewer for this helpful remark.

References

  • Anderson EW, Fornell C, Mazvancheryl SK (2004) Customer satisfaction and shareholder value. J Mark 68(4):172–185

    Article  Google Scholar 

  • Andrews RL, Currim IS (2003) Retention of latent segments in regression-based marketing models. Int J Res Mark 20(4):315–321

    Article  Google Scholar 

  • Backhaus K, Bauer M (2000) The impact of critical incidents on customer satisfaction in business-to-business relationships. J Bus-Bus Mark 8(1):25–54

    Article  Google Scholar 

  • Bauer DJ, Curran PJ (2004) The integration of continuous and discrete latent variable models: Potential problems and promising opportunities. Psychol Methods 9(1):3–29

    Article  Google Scholar 

  • Bayes T (1763/1958) Studies in the history of probability and statistics: IX. Thomas Bayes’s essay towards solving the problem in the doctrine of chances; Bayes’s essay in modernized notation. Biometrika 45:296–315

    Article  Google Scholar 

  • Becker J-M, Ringle CM, Völckner F (2009) Prediction-oriented segmentation: A new methodology to uncover unobserved heterogeneity in PLS path models. Proceedings of the 38th annual conference of the European Marketing Academy, CD-Rom proceedings

  • Bergkvist L, Rossiter JR (2007) The predictive validity of multi-item versus single-item measures of the same construct. J Mark Res 44(2):175–184

    Article  Google Scholar 

  • Biggs D, de Ville B, Suen E (1991) A method of choosing multiway partitions for classification and decision trees. J Appl Stat 18(1):49–62

    Article  Google Scholar 

  • Bingham FG, Raffield BT (1990) Business to business marketing management. Irwin Professional Publishing, Homewood, IL

    Google Scholar 

  • Chin WW (1998) The partial least squares approach for structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Lawrence Erlbaum Associates, London, pp 295–336

    Google Scholar 

  • Chin WW, Dibbern J (2009) A permutation based procedure for multi-group PLS analysis: Results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between germany and the USA. In: Esposito Vinzi V, Chin WW, Henseler J, Wang H (eds) Handbook of partial least squares: concepts, methods and applications in marketing and related fields. Springer, Berlin et al

    Google Scholar 

  • Esposito Vinzi V, Ringle CM, Squillacciotti S, Trinchera L (2007) Capturing and treating heterogeneity by response based segmentation in PLS path modeling. A comparison of alternative methods by computational experiments. Essec Research Center, Research paper DR-07019, ESSEC business school, Cergy Pontoise Cedex

  • Esposito Vinzi V, Trinchera L, Squillacciotti S, Tenenhaus M (2008) REBUS-PLS: A response-based procedure for detecting unit segments in PLS path modelling. Appl Stoch Model Bus 24(5):439–458

    Article  Google Scholar 

  • Festge F, Schwaiger M (2007) The drivers of customer satisfaction with industrial goods. Adv Int Market 18:179–207

    Article  Google Scholar 

  • Fornell C, Johnson MD, Anderson EW, Cha J, Bryant BE (1996) The american customer satisfaction index: Nature, purpose, and findings. J Mark 60(4):7–18

    Article  Google Scholar 

  • Fraley C, Raftery AE (2002) Model-based clustering, discriminant analysis, and density estimation. J Am Stat Assoc 97(2):611–631

    Article  Google Scholar 

  • Frühwirth-Schnatter S (2006) Finite mixture and markov switching models. Springer, New York, NY

    Google Scholar 

  • Gudergan SP, Ringle CM, Wende S, Will A (2008) Confirmatory tetrad analysis in PLS path modeling. J Bus Res 61(12):1238–1249

    Article  Google Scholar 

  • Hackl P, Westlund AH (2000) On structural equation modeling for customer satisfaction measurement. Total Qual Manage 11(4–6):820–825

    Google Scholar 

  • Hahn CH, Johnson MD, Herrmann A, Huber F (2002) Capturing customer heterogeneity using a finite mixture PLS approach. Schmalenbach Bus Rev 54(3):243–269

    Google Scholar 

  • Henseler J (2007) A new and simple approach to multi-group analysis in partial least squares path modeling. In: Martens H, Naes T, Martens M (eds) PLS and related methods proceedings of the PLS’07 international symposium. Matforsk, Ås

  • Henseler J, Ringle CM, Sinkovics RR (2009) The use of partial least squares path modeling in international marketing. Adv Int Mark 20:277–319

    Google Scholar 

  • Höck C, Ringle CM, Sarstedt M (2009) Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. Int J Serv Technol Manage

  • Höck M, Ringle CM (2009) Local strategic networks in the software industry: An empirical analysis of the value continuum. Int J Knowl Manage Stud

  • Homburg C, Rudolph B (2001) Customer satisfaction in industrial markets: Dimensional and multiple role issues. J Bus Res 52(1):15–33

    Article  Google Scholar 

  • Jedidi K, Jagpal HS, DeSarbo WS (1997) Finite-mixture structural equation models for response-based segmentation and unobserved heterogeneity. Market Sci 16(1):39–59

    Article  Google Scholar 

  • Keil M, Tan BCY, Wei K-K, Saarinen T, Tuunainen V, Wassenaar A (2000) A cross-cultural study on escalation of commitment behavior in software projects. Manag Informat Syst Q 24(2):299–325

    Google Scholar 

  • Lohmöller J.-B. (1989) Latent variable path modeling with partial least squares. Physica, Heidelberg

    Google Scholar 

  • McLachlan GJ, Peel D (2000) Finite mixture models. Wiley, New York, NY

    Book  Google Scholar 

  • McCutcheon AL (2002) Basic concepts and procedures in single- and multiple-group latent class analysis. In: Hagenaars JA, McCutcheon AL (eds) Applied latent class analysis. Cambridge University Press, Cambridge, pp 56–85

    Google Scholar 

  • Muthén BO (1989) Latent variable modeling in heterogeneous populations. Psychometrika 54(4):557–585

    Article  Google Scholar 

  • Nagy MS (2002) Using a single-item approach to measure facet job satisfaction. J Occup Organ Psych 75(1):77–86

    Article  Google Scholar 

  • Palumbo F, Romano R, Esposito Vinzi V (2008) Fuzzy PLS path modeling: a new tool for handling sensory data. In: Preisach C, Burkhardt H, Schmidt-Thieme L, Decker R (eds) Data analysis, machine learning, and applications. Proceedings of the 31st annual conference of the German Classification Society, Springer, Berlin, pp 689–696

  • Qualls WJ, Rosa JA (1995) Assessing industrial buyers perceptions of quality and their effects on satisfaction. Ind Market Manag 24(5):359–368

    Article  Google Scholar 

  • Ramaswamy V, DeSarbo WS, Reibstein DJ, Robinson WT (1993) An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Market Sci 12(1):103–124

    Article  Google Scholar 

  • Ringle CM (2006) Segmentation for path models and unobserved heterogeneity: the finite mixture partial least squares approach. Research papers on marketing and retailing, No 35, University of Hamburg (accessed May 28, 2009) [available at http://www.ibl-unihh.de/RP035.pdf]

  • Ringle CM, Schlittgen R (2007) A genetic segmentation approach for uncovering and separating groups of data in PLS path modeling. In: Martens H, Naes T, Martens M (eds) PLS and related methods proceedings of the PLS’07 international symposium, Matforsk, Ås

  • Ringle CM, Wende S, Will A (2005a) Customer segmentation with FIMIX-PLS. In: Aluja T, Casanovas J, Esposito Vinzi V, Morrineau A, Tenenhaus M (eds) PLS and related methods – proceedings of the PLS’05 international symposium, Decisia, Paris, pp 507–514

  • Ringle CM, Wende S, Will A (2005b) SmartPLS 2.0 (M3) Beta, (accessed May 28, 2009). [http://www.smartpls.de]

  • Ringle CM, Sarstedt M, Mooi EA (2009a) Response-based segmentation using finite mixture partial least squares: Theoretical foundations and an application to american customer satisfaction index data. Ann Informat Syst

  • Ringle CM, Sarstedt M, Schlittgen R (2009b) Finite mixture and genetic algorithm segmentation in partial least squares path modeling. In: Fink A, Lausen B, Seidel W, Ultsch A (eds) Studies in classification, data analysis, and knowledge organization. Proceedings of the 32nd annual conference of the German Classification Society, Springer, Berlin et al

  • Ringle CM, Wende S, Will A (2009c) The finite mixture partial least squares approach: Methodology and application. In: Esposito Vinzi V, Chin WW, Henseler J, Wang H (eds) Handbook of partial least squares: concepts, methods and applications in marketing and related fields, Springer, Berlin et al

    Google Scholar 

  • Rossiter JR (2002) The C-OAR-SE procedure for scale development in marketing. Int J Res Mark 19(4):305–335

    Article  Google Scholar 

  • Sánchez G, Aluja T (2006) PATHMOX: A PLS-PM segmentation algorithm. In: Proceedings of the IASC symposium on knowledge extraction by modelling, 2006 (September), provisional chapter, (accessed May 28, 2009), [available at http://www.iasc-isi.org/Proceedings/2006/COMPSTAT_Satellites/KNEMO]

  • Sarstedt M (2008a) A review of recent approaches for capturing heterogeneity in partial least squares path modelling. J Model Manage 3(2):140–161

    Article  Google Scholar 

  • Sarstedt M (2008b) Market segmentation with mixture regression models. Understanding measures that guide model selection. J Target Meas Anal Mark 16(3):228–246

    Article  Google Scholar 

  • Sarstedt M, Ringle CM (2010) Treating unobserved heterogeneity in PLS Path modelling: a comparison of FIMIX-PLS with different data analysis strategies. J Appl Stat

  • Sarstedt M, Wilczynski P (2009) More for less? A comparison of single-item and multi-item measures. Bus Adm Rev 9(2):211–227

    Google Scholar 

  • Sarstedt M, Schwaiger M, Ringle CM (2009) Determining the number of segments in FIMIX-PLS. In: Robinson L (ed) Proceedings of the 2009 annual conference of the Academy of Marketing Science, CD-Rom proceedings

  • Sarstedt M, Ringle CM, Schloderer MP, Schwaiger M (2008) Accounting for unobserved heterogeneity in the analysis of antecedents and consequences of corporate reputation: an application of FIMIX-PLS. In: Perks KJ, Shukla P (eds) Proceedings of the 37th annual conference of the European Marketing Academy, CD-Rom proceedings

  • Spiro RL, Weitz BA (1990) Adaptive selling: Conceptualization, measurement and nomological validity. J Marketing Res 60(3):61–69

    Article  Google Scholar 

  • Steenkamp J-B, Baumgartner H (1998) Assessing measurement invariance in cross-national consumer research. J Consum Res 25(1):78–107

    Article  Google Scholar 

  • Steinmetz H, Schmidt P, Tina-Booh A, Wieczorek S, Schwartz SH (2009) Testing measurement invariance using multigroup CFA: differences between educational groups in human values measurement. Qual Quant 43(4):599–616

    Article  Google Scholar 

  • Tanner JF (1996) Buyer perceptions of the purchase process and its effect on customer satisfaction. Ind Market Manag 25(2):125–133

    Article  Google Scholar 

  • Tenenhaus M, Mauger E, Guinot C (2009) Use of ULS-SEM and PLS-SEM to measure interaction effect in a regression model relating two blocks of binary variables. In: Esposito Vinzi V, Chin WW, Henseler J, Wang H (eds) Handbook of partial least squares: concepts, methods and applications in marketing and related fields, Springer, Berlin et al

    Google Scholar 

  • Vandenberg RJ, Lance CE (2000) A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research. Organ Res Methods 3(1):4–70

    Article  Google Scholar 

  • Wedel M, Kamakura WA (2000) Market segmentation: conceptual and methodological foundations, 2nd edn. Kluwer Academic Publishers, Boston, NE

    Google Scholar 

  • Williams LJ, Edwards JR, Vandenberg RJ (2003) Recent advances in causal modeling methods for organizational and management research. J Manage 29(6):903–936

    Google Scholar 

  • Wold H (1974) Causal flows with latent variables: partings of the ways in light of NIPALS modelling. Eur Econ Rev 5(1):67–86

    Article  Google Scholar 

  • Wu J, DeSarbo WS (2005) Market segmentation for customer satisfaction studies via a new latent structure multidimensional scaling model. Appl Stoch Model Bus 21(4/5):303–309

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Market-Based Management, Ludwig-Maximilians-University Munich, Munich, Germany

    Marko Sarstedt & Manfred Schwaiger

  2. Institute of Industrial Management, University of Hamburg, Hamburg, Germany

    Christian M. Ringle

  3. Centre for Management and Organisation Studies (CMOS), University of Technology Sydney (UTS), Sydney, Australia

    Christian M. Ringle

Authors
  1. Marko Sarstedt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manfred Schwaiger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christian M. Ringle
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marko Sarstedt.

Appendix

Appendix

Table 3 Evaluation results of the formative measurement models
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sarstedt, M., Schwaiger, M. & Ringle, C. Do We Fully Understand the Critical Success Factors of Customer Satisfaction with Industrial Goods? - Extending Festge and Schwaiger’s Model to Account for Unobserved Heterogeneity. J Bus Mark Manag 3, 185–206 (2009). https://doi.org/10.1007/s12087-009-0023-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12087-009-0023-7

Keywords

Search

Navigation