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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

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Handbook of Partial Least Squares

Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

Abstract

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).

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Author information

Authors and Affiliations

  1. Department of Decision and Information Sciences, Bauer College of Business, University of Houston, Houston, TX, USA

    Wynne W. Chin

  2. Department of Information Engineering, Institute of Information Systems, University of Bern, Engehaldenstr. 8, Room 204, 3012, Bern, Switzerland

    Jens Dibbern

Authors
  1. Wynne W. Chin
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  2. Jens Dibbern
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Correspondence to Wynne W. Chin .

Editor information

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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Chin, W.W., Dibbern, J. (2010). 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. 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_8

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