Abstract
The customer behavior in shopping were changing the demand disruptions when the COVID-19 pandemic attacked the countries. Retail industries are one of business sectors which were directly impacted the availability of item products. The purpose of this study is to understand the level of demand disruptions of COVID-19 pandemic using Bayesian Network (BN). BN method is powerful method to assess and decide the uncertainly of demand and risk. Based on relevant literature and interviews, the hierarchy of BN were developed and stock out data to represent the product of availability in 5 case study were collected in case study. Finally, the analysis to understand the level of demand disruptions each item products, product family and categories have been performed. This paper provides a new evidence by changing of shopping behavior when the COVID-19 pandemic attached in Indonesia and presents the BN application could be used to handle risk assessment based on stock out data systematically and comprehensively.
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