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

Authors: Norita Ahmad, M.J. Piovoso

Addresses: Penn State University, School of Graduate Professional Studies, 30 E. Swedesford Road, Malvern, PA, USA. ' Penn State University, School of Graduate Professional Studies, 30 E. Swedesford Road, Malvern, PA, USA

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.

Keywords: partial least squares; PLS; small and medium-sized enterprises; SMEs; performance measurement; manufacturing enterprises; enterprise efficiency; data mining.

DOI: 10.1504/IJSOI.2007.012691

International Journal of Services Operations and Informatics, 2007 Vol.2 No.1, pp.38 - 52

Published online: 08 Mar 2007 *

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