Affiliation:
1. Graduate School of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0693, Japan
Abstract
Owing to the coronavirus disease 2019 (COVID-19), many companies experienced a sharp and significant decline in sales, resulting in a major crisis. This study proposes a method for estimating the risk of a sudden and significant decline in sales to tackle the aforementioned issue. The method is based on the distributional characteristics calculated from historical data of companies mainly in the transportation industry, which are vulnerable to disasters, using the damage caused by COVID-19 as a lesson. Furthermore, we conduct an empirical analysis using the proposed stochastic model for the case of the All Nippon Airways Co., Ltd. (ANA), a major Japanese airline company. The results are as follows: (1) the sales change rates are normally distributed before COVID-19, but inclusion of post-COVID-19 data produced asymmetric distribution of sales change rates; (2) the proposed statistic is log-normally distributed (including post-COVID-19 data) for a time interval of two or three years; (3) the probability of actual sales decline was estimated to be between 0.1% and 1.6% in fiscal year (FY) 2020 and FY2021 post-COVID-19; (4) the estimated risk of future sales decline is well-grounded in light of past actual values.
Funder
Japan Society for the Promotion of Science
Publisher
Fuji Technology Press Ltd.
Subject
Engineering (miscellaneous),Safety, Risk, Reliability and Quality
Reference24 articles.
1. M. Shiiba, Y. Tachikawa, and Y. Ichikawa, “Hydrology and Hydraulic Engineering Planning,” Kyoto University Press, 2013 (in Japanese).
2. S. A. Klugman, H. H. Panjer, and G. E. Willmot, “Loss Models from Data to Decisions,” 3rd edition, Wiley, 2008.
3. R. Takahashi and T. Shimura, “Extreme Value Statistics,” Kindai Kagaku Sha, 2016 (in Japanese).
4. L. Wu and H. Hayashi, “The Impact of Disasters on Japan’s Inbound Tourism Demand,” J. Disaster Res., Vol.9, No.sp, pp. 699-708, 2014. https://doi.org/10.20965/jdr.2014.p0699
5. A. J. McNeil, R. Frey, and P. Embrechts, “Quantitative Risk Management: Concepts, Techniques and Tools,” Princeton University Press, 2005.