Bayesian Belief Network Approach for Supply Risk Modelling

View Sample PDF

Author(s): Anil Jindal (Giani Zail Singh Campus College of Engineering and Technology, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India), Satyendra Kumar Sharma (Birla Institute of Technology and Science, Pilani, India)and Srikanta Routroy (Birla Institute of Technology and Science, Pilani, India)
Copyright: 2022
Volume: 15
Issue: 1
Pages: 17
Source title: International Journal of Information Systems and Supply Chain Management (IJISSCM)
Editor(s)-in-Chief: John Wang (Montclair State University, USA)
DOI: 10.4018/IJISSCM.2022010102

Keywords: Business & Management / Business Information Systems / Business Science Reference / Supply Chain Management

Purchase

View Bayesian Belief Network Approach for Supply Risk Modelling on the publisher's website for pricing and purchasing information.

Abstract

Today’s global and complex world increased the vulnerability to risks exponentially and organizations are compelled to develop effective risk management strategies for its mitigation. The prime focus of research is to design a supply risk model using Bayesian Belief Network bear in mind the tie-in of risk factors (i.e. objective and subjective) those are critical to a supply chain network. The proposed model can be re-engineered as per new information available at disclosure, so risk analysis will be current and relevant along the timeline as so situation is strained. The top three factors which influenced profitability were transportation risk and price risks. Netica is the platform used for designing and running simultaneous simulations on the Bayesian Network. The proposed methodology is demonstrated through a case study conducted in an Indian manufacturing supply chain taking inputs from supply chain/risk management experts. .

The IRMA Community

Research IRM

Bayesian Belief Network Approach for Supply Risk Modelling

Purchase

Abstract

Related Content

IRMA Sponsors