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Use of Partial Least Squares (PLS) in TQM Research: TQM Practices and Business Performance in SMEs

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Handbook of Partial Least Squares

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

Abstract

Advances in structural equation modeling (SEM) techniques have made it possible for management researchers to simultaneously examine theory and measures. When using sophisticated SEM techniques such as covariance-based structural equation modeling (CBSEM) and partial least squares (PLS), researchers must be aware of their underlying assumptions and limitations. SEM models such as PLS can help total quality management (TQM) researchers achieve new insights. Researchers in the area of TQM need to apply this technique properly in order to better understand the complex relationships proposed in their models. This paper attempts to apply PLS in the area of TQM research. Consequently, special emphasis is placed on identifying the relationships between the most prominent TQM constructs and business performance based on a sample of SMEs operating in the Turkish textile industry. The analysis of PLS results indicate that a good deal of support is found for the proposed model where a satisfactory percentage of the variance in the dependent constructs is explained by the independent constructs.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Fatih University, Buyukcekmece, Istanbul, 34500, Turkey

    Ali Turkyilmaz & Selim Zaim

  2. Faculty of Economics and Administrative Sciences, Chair of International Trade and Business, Bahcesehir University, Besiktas, Istanbul, Turkey

    Ekrem Tatoglu

  3. Department of Industrial Engineering, Kocaeli University, Veziroglu Yerleskesi, 41040, Kocaeli, Turkey

    Coskun Ozkan

Authors
  1. Ali Turkyilmaz
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  2. Ekrem Tatoglu
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  3. Selim Zaim
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  4. Coskun Ozkan
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Corresponding author

Correspondence to Ali Turkyilmaz .

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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Turkyilmaz, A., Tatoglu, E., Zaim, S., Ozkan, C. (2010). Use of Partial Least Squares (PLS) in TQM Research: TQM Practices and Business Performance in SMEs. 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_27

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