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

Chin, Wynne W.; Dibbern, Jens (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: Vinzi, Vincenzo Esposito; Chin, Wynne W.; Henseler, Jörg; Wang, Huiwen (eds.) Handbook of Partial Least Squares Concepts, Methods and Applications (pp. 171-193). Heidelberg: Springer Verlag 10.1007/978-3-540-32827-8_8

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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).

Item Type:

Book Section (Book Chapter)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Engineering
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Dibbern, Jens

ISBN:

978-3-540-32827-8

Publisher:

Springer Verlag

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:08

Last Modified:

17 Jun 2018 01:33

Publisher DOI:

10.1007/978-3-540-32827-8_8

URI:

https://boris.unibe.ch/id/eprint/404 (FactScience: 198524)

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