Authors: Satyendra Kumar Sharma; Ravinder Singh; Vishad Bhalotia
Addresses: Department of Management, BITS Pilani, Pilani Campus, Rajasthan, India ' Department of Management, BITS Pilani, Pilani Campus, Rajasthan, India ' Department of Economic and Finance, BITS Pilani, Pilani Campus, Rajasthan, India
Abstract: The aim of this research is to construct a Bayesian belief network (BBN) model, which encompasses all the risk factors relevant to the Indian automotive sector that can give a fair, empirical idea as to how much the risk factors drive down the gross turnover of the industry. The BBN model is used to gauge business, economic and external risks and evaluate its impact on gross turnover of the industry. Empirical model draws a lot of implications to streamline the risk effects in the industry, but it clearly shows that the three factors - business risks, economic risks and external risks are not entirely independent and are positively correlated with each other. Bayesian networks provide a very useful risk assessment tool that takes into account the advantages of both quantitative and qualitative risk assessment methods. This is a novel, empirical effort to provide a generalised model to integrate all risks - domestic, global, economic, legal - relevant to the automotive industry.
Keywords: risk assessment; automobile industry; Bayesian belief network; risk propagation; sensitivity analysis.
International Journal of Logistics Systems and Management, 2019 Vol.34 No.4, pp.457 - 485
Available online: 04 Nov 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article