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Integrated assessment of auto industries by principal component analysis

Author

Listed:
  • A. Azadeh
  • S.F. Ghaderi
  • A. Vazifeh

Abstract

The ever-increasing growth and development of the automotive industry all over the world requires continuous assessment through robust scientific methodologies. This study introduces an integrated model for assessment and analysis of automotive industries on the basis of international and standard indicators. This study, for the first time, evaluates and analyses automotive industries according to a set of standard economic indicators by Principal Component Analysis (PCA). The validity of the PCA model is examined by numerical taxonomy and non-parametric Spearman and Kendall-Tau correlation techniques. The economic indicators are identified by an extensive international review. This study considers auto industries of various developed and developing countries with respect to the selected indicators. To have an accurate assessment of the automotive industries and also to minimise the bias, a five-year period (1996–2000) is considered. The results of the modelling approach would help policymakers and top managers to have better understand and improve existing systems with respect to the integrated performance of auto industries.

Suggested Citation

  • A. Azadeh & S.F. Ghaderi & A. Vazifeh, 2007. "Integrated assessment of auto industries by principal component analysis," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 2(3), pages 348-362.
    • Handle: RePEc:ids:ijisen:v:2:y:2007:i:3:p:348-362
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    Cited by:

    1. Azadeh, A. & Skandari, M.R. & Maleki-Shoja, B., 2010. "An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation," Energy Policy, Elsevier, vol. 38(10), pages 6307-6319, October.
    2. Madjid Tavana & Salman Nazari-Shirkouhi & Amir Mashayekhi & Saeed Mousakhani, 2022. "An Integrated Data Mining Framework for Organizational Resilience Assessment and Quality Management Optimization in Trauma Centers," SN Operations Research Forum, Springer, vol. 3(1), pages 1-33, March.

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