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Measuring efficiency of small and medium-sized manufacturing enterprises using partial least squares

Measuring efficiency of small and medium-sized manufacturing enterprises using partial least squares This work involves an application of a data mining technique called Partial Least Squares (PLS) to a QuickView database to compare a Small and medium-sized Manufacturing Enterprise (SME), to other SMEs in the same industry. PLS models some quantitative measure of the company's performance based on the responses to a questionnaire. This approach often provides a more accurate model than conventional regression in that the problems of collinearity and noisy data are not as disruptive on the regression estimates. The result of this analysis provides information about SMEs' operation and performance and therefore, can be used to help SMEs identify their own weaknesses and strengths with respect to their competitors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Services Operations and Informatics Inderscience Publishers

Measuring efficiency of small and medium-sized manufacturing enterprises using partial least squares

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1741-539X
eISSN
1741-5403
Publisher site
See Article on Publisher Site

Abstract

This work involves an application of a data mining technique called Partial Least Squares (PLS) to a QuickView database to compare a Small and medium-sized Manufacturing Enterprise (SME), to other SMEs in the same industry. PLS models some quantitative measure of the company's performance based on the responses to a questionnaire. This approach often provides a more accurate model than conventional regression in that the problems of collinearity and noisy data are not as disruptive on the regression estimates. The result of this analysis provides information about SMEs' operation and performance and therefore, can be used to help SMEs identify their own weaknesses and strengths with respect to their competitors.

Journal

International Journal of Services Operations and InformaticsInderscience Publishers

Published: Jan 1, 2007

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