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Modelling drivers and inhibitors of the automotive belt industry in India: an ISM-ANN approach

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  • Sushant Kumar
  • Atul Singh

Abstract

The study aims to identify critical factors influencing the automotive belt industry in India, which is one of the largest manufacturers and consumers of power transmission belts. The multi-method analysis is followed for this study. First, a review of literature and Delphi techniques with industry experts are used to identify the relevant factors. Then, interpretive structural modelling (ISM) approach is employed to create models exhibiting the linear relationships among them. The second stage includes using artificial neural network (ANN) on models identified using ISM approach. ISM analysis identified six growth-inhibiting factors (GIF) extended over five levels and nine growth-driving factors (GDF) developed over six levels. Further, the results of ANN offered the factors having greater relative importance for GIF and GDF models. This model presents the most influential factors by using the ANN approach that guides managers to take necessary action to ensure the industry's growth.

Suggested Citation

  • Sushant Kumar & Atul Singh, 2026. "Modelling drivers and inhibitors of the automotive belt industry in India: an ISM-ANN approach," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 37(1), pages 38-61.
    • Handle: RePEc:ids:ijicbm:v:37:y:2026:i:1:p:38-61
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