An Introduction to 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

  • Wynne W. ChinEmail author
  • Jens Dibbern
Part of the Springer Handbooks of Computational Statistics book series (SHCS)


To date, multi-group comparison of Partial Least Square (PLS) models where differences in path estimates for different sampled populations have been relatively naive. Often, researchers simply examine and discuss the difference in magnitude of specific model path estimates from two or more data sets. When evaluating the significance of path differences, a t-test based on the pooled standard errors obtained via a resampling procedure such as bootstrapping from each data set is made. Yet problems can occur if the assumption of normal population or similar sample size is made. This paper provides an introduction to an alternative distribution free approach based on an approximate randomization test – where a subset of all possible data permutations between sample groups is made. The performance of this permutation procedure is tested on both simulated data and a study exploring the differences of factors that impact outsourcing between the countries of US and Germany. Furthermore, as an initial examination of the consistency of this new procedure, the outsourcing results are compared with those obtained from using covariance based SEM (AMOS 7).


Transaction Cost Partial Little Square Average Variance Extract Data Permutation Partial Little Square Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50, 179–211.CrossRefGoogle Scholar
  2. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NY: Prentice Hall.Google Scholar
  3. Ang, S., & Straub, D. W. (1998). Production and transaction economies and IS outsourcing: a study of the U.S. banking industry. MIS Quarterly, 22(4), 535–552.CrossRefGoogle Scholar
  4. Apte, U. M., Sobol, M. G., Hanaoka, S., Shimada, T., Saarinen, T., Salmela, T., & Vepsalainen, A. P. J. (1997). IS outsourcing practices in the USA, Japan and Finland: a comparative study. Journal of Information Technology, 12, 289–304.CrossRefGoogle Scholar
  5. Bagozzi, R. P., & Phillips, L. (1982). Representing and testing organizational theories: a holistic construal. Administrative Science Quarterly, 27, 459–489.CrossRefGoogle Scholar
  6. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16, 74–94.CrossRefGoogle Scholar
  7. Barthelemy, J., & Geyer, D. (2001). IT outsourcing: evidence from France and Germany. European Management Journal, 19(2), 195–202.CrossRefGoogle Scholar
  8. Chin, W. W. (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), VII–XVI.Google Scholar
  9. Chin, W. W. (1998b). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  10. Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: relative importance of beliefs. The data base for advances in information systems, 26(2), 42–63.Google Scholar
  11. Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling: analysis with small samples using partial least squares. In R. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). Thousand Oaks, CA: Sage.Google Scholar
  12. Compeau, D. R., & Higgins, C. A. (1991). A social cognitive theory perspective on individual reactions to computing technology. International conference on information systems (ICIS), New York, 187–198.Google Scholar
  13. Cordano, M., & Frieze Hanson, I. (2000). Pollution reduction preferences of U.S. environmental managers: applying Ajzen’s theory of planned behavior. Academy of Management Review, 43(4), 627–641.CrossRefGoogle Scholar
  14. Dibbern, J., Goles, T., Hirschheim, R. A., & Jayatilaka, B. (2004). Information systems outsourcing: a survey and analysis of the literature. The DATA BASE for Advances in Information Systems, 35(4), 6–102.Google Scholar
  15. Dibbern, J., & Heinzl, A. (2001). Outsourcing der informationsverarbeitung im mittelstand: test eines multitheoretischen kausalmodells. Wirtschaftsinformatik, 43(4), 339–350.Google Scholar
  16. Dibbern, J., Heinzl, A., & Leibbrandt, S. (2003). Interpretation des sourcing der informationsverarbeitung: hintergründe und grenzen ökonomischer einflussgrößen. Wirtschaftsinformatik, 45(5), 533–540.Google Scholar
  17. DiRomualdo, A., & Gurbaxani, V. (1998). Strategic intent for IT outsourcing. Sloan Management Review, Summer, 67–80.Google Scholar
  18. Edgington, E. S. (1987). Randomization tests. New York: Marcel Dekker Inc.zbMATHGoogle Scholar
  19. Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. In monographs on statistics and applied probability, No. 57. New York: Chapman & Hill.Google Scholar
  20. Fornell, C. (1989). The blending of theoretical empirical knowledge in structural equations with un-observables. In H. Wold (Ed.), Theoretical empiricism: a general rationale for scientific model-building (pp. 153–174). New York: Paragon House.Google Scholar
  21. Fornell, C., & Bookstein, F. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452.CrossRefGoogle Scholar
  22. Good, P. (2000). Permutation tests, a practical guide to resampling methods for testing hypotheses. New York: Springer.zbMATHGoogle Scholar
  23. Hamilton, S., & Chervany, N. L. (1981). Evaluating information system effectiveness part I: comparing evaluation approaches. MIS Quarterly, 5(3), 55–69.CrossRefGoogle Scholar
  24. Hampden-Turner, C., & Trompenaars, A. (1993). The seven cultures of capitalism: value systems for creating wealth in the United States, Japan, Germany, France, Britain, Sweden, and the Netherlands. New York: Doubleday.Google Scholar
  25. Hirschheim, R. A., & Lacity, M. C. (2000). The myths and realities of information technology in-sourcing. Communications of the ACM, 43(2), 99–107.CrossRefGoogle Scholar
  26. Hofstede, G. (1980). Culture’s consequences, international differences in work-related values. Beverly Hills: Sage.Google Scholar
  27. Hofstede, G. (1983). National culture in four dimensions. International Studies of Management and Organization, 13(2), 46–74.Google Scholar
  28. Hofstede, G. (1991). Cultures and organizations: software of the mind. London: McGraw-Hill.Google Scholar
  29. Hui, C. H., & Triandis, H. C. (1986). Individualism-collectivism: a study of cross-cultural research. Journal of Cross-Cultural Psychology, 17, 222–248.CrossRefGoogle Scholar
  30. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195–204.CrossRefGoogle Scholar
  31. Jöreskog, K., & Sörbom, D. (1996). PRELIS 2: User’s reference guide. Chicago: Scientific Software International.Google Scholar
  32. Murphy, C., Ker, S., & Chen, S. (1999). IDC: U.S. and worldwide outsourcing markets and trends, 1998–2003. International data corporation, No. 19322Google Scholar
  33. Keil, M., Tan, B. C. Y., Wei, K. -K., Saarinen, T., Tuunainen, V., & Wassenaar, A. (2000). A cross-cultural study on escalation of commitment behavior in software projects. MIS Quarterly, 24(2), 299–325.CrossRefGoogle Scholar
  34. Lacity, M. C., & Hirschheim, R. A. (1993). The information systems outsourcing bandwagon. Sloan Management Review, 35(1), 73–86.Google Scholar
  35. Lacity, M. C., & Hirschheim, R. A. (1995). Beyond the information systems outsourcing bandwagon : the insourcing response. Chichester, New York: Wiley.Google Scholar
  36. Lytle, A. L., Brett, J. M., Barsness, Z. I., Tinsley, C. H., & Maddy, J. (1995). A paradigm for confirmatory cross-cultural research in organizational behavior. In B. M. Staw and L. L. Cummings (Eds.), Research in organizational behavior (Vol. 17, pp. 167–214). Greenwich, CT: JAI.Google Scholar
  37. Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.CrossRefGoogle Scholar
  38. McLellan, K. L., Marcolin, B. L., & Beamish, P. W. (1995). Financial and strategic motivations behind IS outsourcing. Journal of Information Technology, 10, 299–321.CrossRefGoogle Scholar
  39. Mohr, L. B. (1991). Understanding significance testing, series: quantitative applications in the Social Sciences. Newbury Park, CA: Sage.Google Scholar
  40. Noreen, E. W. (1989). Computer intensive methods for testing hypotheses, an introduction. New York: Wiley.Google Scholar
  41. OECD (2000). Information technology outlook: 2000. Paris: OECD.Google Scholar
  42. Osgood, C. E., Suci, G. J., & Tannenmann, P. H. (1957). The measurement of meaning. Urbana, IL: University of Illinois Press.Google Scholar
  43. Peter, J. (1981). Reliability: a review of psychometric basics and recent marketing practices. Journal of Marketing Research, 16, 6–17.CrossRefGoogle Scholar
  44. Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations: a resource dependence perspective. New York: Harper & Row.Google Scholar
  45. Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS Quarterly, 19(2), 173–187.CrossRefGoogle Scholar
  46. Ramberg, J. S., Dudewicz, E. J., Tadikamalla, P. R., Pandu, R., & Mykytka, E.F. (1979). A probability distribution and its uses in fitting data. Technometrics, 21, 201–214.CrossRefzbMATHGoogle Scholar
  47. Reinartz, W. J., Echambadi, R., & Chin, W. W. (2002). Generating non-normal data for simulation of structural equation models using Mattson’s method. Multivariate Behavioral Research, 37(2), 227–244.CrossRefGoogle Scholar
  48. Richardi, R. (1990). Labour Right. In C. E. Poeschel (Ed.), Handbook of German business management (Vol. 2, pp. 1278–1290). Stuttgart: Verlag.Google Scholar
  49. Sambamurthy, V., & Chin, W. W. (1994). The effects of group attitudes toward alternative GDSS designs on the decision-making performance of computer-supported groups. Decision Sciences, 25(2), 215–241.CrossRefGoogle Scholar
  50. Sobol, M. G., & Apte, U. M. (1995). Domestic and global outsourcing practices of America‘s most effective IS users. Journal of Information Technology, 10, 269–280.CrossRefGoogle Scholar
  51. Teng, J. T. C., Cheon, M. J., & Grover, V. (1995). Decisions to outsource information systems functions: testing a strategy-theoretic discrepancy model. Decision Sciences, 26(1), 75–103.CrossRefGoogle Scholar
  52. Thompson, R. L. (1967). Organizations in action. New York: McGraw-Hill.Google Scholar
  53. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1994). Influence Of experience on personal computer utlization: testing a conceptual model. Journal of Management Information Systems, 11(1), 167–187.Google Scholar
  54. Triandis, H. C. (1996). The psychological measurement of cultural syndromes. American Psychologist, 51(4), 407–415.CrossRefGoogle Scholar
  55. Trompenaars, A., & Hampden-Turner, C. (1994). Riding the waves of culture : understanding diversity in global business. Burr Ridge, Ill: Irwin Professional Pub.Google Scholar
  56. Wade, M., & Hulland, J. (2004). Review: The resource-based view and information systems research: review, extension, and suggestions for future research. MIS Quarterly, 18(1), 107–142.Google Scholar
  57. Williamson, O. E. (1981). The Economics of organization: the transaction cost approach. American Journal of Sociology, 87(3), 548–577.CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of Decision and Information SciencesBauer College of Business, University of HoustonHoustonUSA
  2. 2.Department of Information EngineeringInstitute of Information Systems, University of BernBernSwitzerland

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