Volume 13 Issue 3
Jul.  2022
Turn off MathJax
Article Contents
Lijiao Yang, Yu Chen, Xinyu Jiang, Hirokazu Tatano. Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises[J]. International Journal of Disaster Risk Science, 2022, 13(3): 401-414. doi: 10.1007/s13753-022-00414-5
Citation: Lijiao Yang, Yu Chen, Xinyu Jiang, Hirokazu Tatano. Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises[J]. International Journal of Disaster Risk Science, 2022, 13(3): 401-414. doi: 10.1007/s13753-022-00414-5

Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises

doi: 10.1007/s13753-022-00414-5
Funds:

This study was supported by the National Natural Science Foundation of China (Grant Numbers 41907393, 42177448, and 41807504), China.

  • Available Online: 2022-07-06
  • The Covid-19 pandemic has severely affected enterprises worldwide. It is thus of practical significance to study the process of enterprise recovery from Covid-19. However, the research on the effects of relevant determinants of business recovery is limited. This article presents a multistate modeling framework that considers the determinants, recovery time, and transition likelihood of Chinese enterprises by the state of those enterprises as a result of the pandemic (recovery state), with the help of an accelerated failure time model. Empirical data from 750 enterprises were used to evaluate the recovery process. The results indicate that the main problems facing non-manufacturing industries are supply shortages and order cancellations. With the increase of supplies and orders, the probability of transition between different recovery states gradually increases, and the recovery time of enterprises becomes shorter. For manufacturing industries, the factors that hinder recovery are more complex. The main problems are employee panic and order cancellations in the initial stage, employee shortages in the middle stage, and raw material shortages in the full recovery stage. This study can provide a reference for enterprise recovery in the current pandemic context and help policymakers and business managers take necessary measures to accelerate recovery.
  • loading
  • Aalen, O.O., Ø. Borgan, and H.K. Gjessing. 2008. Survival and event history analysis. New York:Springer.
    Adam, A., R. Hassan, and H. Abdullah. 2021. Maintaining the survival of Malaysian SMEs during Covid-19 outbreak:Challenges and suggestion for management. ASEAN Entrepreneurship Journal 7(1):27-33.
    Andersen, P.K., and N. Keiding. 2002. Multi-state models for event history analysis. Statistical Methods in Medical Research 11(2):91-115.
    Asgary, A., M.I. Anjum, and N. Azimi. 2012. Disaster recovery and business continuity after the 2010 flood in Pakistan:Case of small businesses. International Journal of Disaster Risk Reduction 2:46-56.
    Battisti, M., and D. Deakins. 2017. The relationship between dynamic capabilities, the firm's resource base and performance in a post-disaster environment. International Small Business Journal 35(1):78-98.
    Blackman, D., H. Nakanishi, and A.M. Benson. 2017. Disaster resilience as a complex problem:Why linearity is not applicable for long-term recovery. Technological Forecasting and Social Change 121:89-98.
    Bradburn, M.J., T.G. Clark, S.B. Love, and D.G. Altman. 2003a. Survival analysis part II:Multivariate data analysis-An introduction to concepts and methods. British Journal of Cancer 89(3):431-436.
    Bradburn, M.J., T.G. Clark, S.B. Love, and D.G. Altman. 2003b. Survival analysis part III:Multivariate data analysis-Choosing a model and assessing its adequacy and fit. British Journal of Cancer 89(4):605-611.
    Carobbio, A., P. Guglielmelli, E. Rumi, C. Cavalloni, V.D. Stefano, S. Betti, A. Rambaldi, M.C. Finazzi, et al. 2020. A multistate model of survival prediction and event monitoring in prefibrotic myelofibrosis. Blood Cancer Journal 10(10):Article 100.
    Chang, S.E. 2010. Urban disaster recovery:A measurement framework and its application to the 1995 Kobe earthquake. Disasters 34(2):303-327.
    Chatterjee, R., K. Okazaki, and R. Shaw. 2018. Understanding recovery process of small- and medium-scale enterprises after 2015 Nepal earthquake and impact on resilience building. In Science and technology in disaster risk reduction in Asia:Potentials and challenges, ed. R. Shaw, K. Shiwaku, and T. Izumi, 253-272. Amsterdam:Elsevier.
    Clark, T.G., M.J. Bradburn, S.B. Love, and D.G. Altman. 2003. Survival analysis part I:Basic concepts and first analyses. British Journal of Cancer 89(2):232-238.
    Coibion O., G. Yuriy, and W. Michael. 2020. The cost of the Covid-19 crisis:Lockdowns, macroeconomic expectations, and consumer spending. Working paper 27141. Cambridge, MA:National Bureau of Economic Research.
    Cowling, M., R. Brown, and A. Rocha. 2020. Did you save some cash for a rainy Covid-19 day? The crisis and SMEs. International Small Business Journal:Researching Entrepreneurship 38(7):593-604.
    Crowther, M.J., and P.C. Lambert. 2017. Parametric multistate survival models:Flexible modelling allowing transition-specific distributions with application to estimating clinically useful measures of effect differences. Statistics in Medicine 36(29):4719-4742.
    Dahles, H., and T.P. Susilowati. 2015. Business resilience in times of growth and crisis. Annals of Tourism Research 51(C):34-50.
    De Mel, S., D. McKenzie, and C. Woodruff. 2012. Enterprise recovery following natural disasters. The Economic Journal 122(559):64-91.
    Dhulipala, S.L.N., and M.M. Flint. 2020. Series of semi-Markov processes to model infrastructure resilience under multihazards. Reliability Engineering & System Safety 193(C):Article 106659.
    Eid, M.S., and I.H. El-adaway. 2017. Integrating the social vulnerability of host communities and the objective functions of associated stakeholders during disaster recovery processes using agent-based modeling. Journal of Computing in Civil Engineering 31(5):Article 04017030.
    Gémar, G., L. Moniche, and A.J. Morales. 2016. Survival analysis of the Spanish hotel industry. Tourism Management 54(C):428-438.
    George, B., S. Seals, and I. Aban. 2014. Survival analysis and regression models. Journal of Nuclear Cardiology 21(4):686-694.
    Ghaffarian, S., D. Roy, T. Filatova, and N. Kerle. 2021. Agent-based modelling of post-disaster recovery with remote sensing data. International Journal of Disaster Risk Reduction 60:Article 102285.
    Gran, J.M., S.A. Lie, I. Øyeflaten, Ø. Borgan, and O.O. Aalen. 2015. Causal inference in multi-state models-sickness absence and work for 1145 participants after work rehabilitation. BMC Public Health 15:Article 1082.
    Han, C., Y. Liu, J. Tang, Y. Zhu, C. Jaeger, and S. Yang. 2020. Lessons from the mainland of China's epidemic experience in the first phase about the growth rules of infected and recovered cases of Covid-19 worldwide. International Journal of Disaster Risk Science 11(4):497-507.
    Jackson, C. 2016. flexsurv:A platform for parametric survival modeling in R. Journal of Statistical Software 70(8):1-33.
    Kachali, H., Z.R. Whitman, J.R. Stevenson, J. Vargo, E. Seville, and T. Wilson. 2015. Industry sector recovery following the Canterbury earthquakes. International Journal of Disaster Risk Reduction 12:42-52.
    Kajitani, Y., and H. Tatano. 2009. Estimation of lifeline resilience factors based on surveys of Japanese industries. Earthquake Spectra 25(4):755-776.
    Kajitani, Y., and H. Tatano. 2014. Estimation of production capacity loss rate after the Great East Japan Earthquake and Tsunami in 2011. Economic Systems Research 26(1):13-38.
    Leelawat, N., A. Suppasri, and F. Imamura. 2015. Disaster recovery and reconstruction following the 2011 Great East Japan Earthquake and Tsunami:A business process management perspective. International Journal of Disaster Risk Science 6(3):310-314.
    LeSage, J.P., R.K. Pace, N. Lam, R. Campanella, and X. Liu. 2011. New Orleans business recovery in the aftermath of Hurricane Katrina. Journal of the Royal Statistical Society:Series A 174(Part 4):1007-1027.
    Lin, P., and N. Wang. 2017. Stochastic post-disaster functionality recovery of community building portfolios I:Modeling. Structural Safety 69:96-105.
    Liu, H., H. Tatano, Y. Kajitani, and Y. Yang. 2021. Modelling post-disaster recovery process of industrial sectors:A case study of 2016 Kumamoto earthquakes. International Journal of Disaster Risk Reduction 61:Article 102385.
    Lu, Y., J. Wu, J. Peng, and L. Lu. 2020. The perceived impact of the Covid-19 epidemic:Evidence from a sample of 4807 SMEs in Sichuan Province, China. Environmental Hazards 19(4):323-340.
    Marshall, M.I., and H.L. Schrank. 2014. Small business disaster recovery:A research framework. Natural Hazards 72(2):597-616.
    McKibbin, W., and R. Fernando. 2021. The global macroeconomic impacts of Covid-19:Seven scenarios. CAMA Working Paper No. 19/2020. https://ssrn.com/abstract=3547729. Accessed 20 Apr 2022.
    Mikucka, M. 2012. The transition to insecurity. International Journal of Sociology 42(4):71-99.
    Monteil, C., J. Barclay, and A. Hicks. 2020. Remembering, forgetting, and absencing disasters in the post-disaster recovery process. International Journal of Disaster Risk Science 11(2):287-299.
    Nicola, M., Z. Alsafi, C. Sohrabi, A. Kerwan, A. Al-Jabir, C. Iosifidis, M. Agha, and R. Agha. 2020. The socio-economic implications of the coronavirus pandemic (Covid-19):A review. International Journal of Surgery 78:185-193.
    Pathak, S., and M.M. Ahmad. 2016. Flood recovery capacities of the manufacturing SMEs from floods:A case study in Pathumthani province, Thailand. International Journal of Disaster Risk Reduction 18:197-205.
    Presutti, M., C. Boari, and L. Fratocchi. 2016. The evolution of inter-organisational social capital with foreign customers:Its direct and interactive effects on SMEs' foreign performance. Journal of World Business 51(5):760-773.
    Putter, H., M. Fiocco, and R.B. Geskus. 2007. Tutorial in biostatistics:Competing risks and multi-state models. Statistics in Medicine 26(11):2389-2430.
    Rose, A. 2004. Defining and measuring economic resilience to disasters. Disaster Prevention and Management:An International Journal 13(4):307-314.
    Rose, A., and E. Krausmann. 2013. An economic framework for the development of a resilience index for business recovery. International Journal of Disaster Risk Reduction 5:73-83.
    Stevenson, J.R., Y. Chang-Richards, D. Conradson, S. Wilkinson, J. Vargo, E. Seville, and D. Brunsdon. 2014. Organizational networks and recovery following the Canterbury earthquakes. Earthquake Spectra 30(1):555-575.
    Titman, A.C., and L.D. Sharples. 2010. Model diagnostics for multi-state models. Statistical Methods in Medical Research 19(6):621-651.
    Webb, G.R., K.J. Tierney, and J.M. Dahlhamer. 2002. Predicting long-term business recovery from disaster:A comparison of the Loma Prieta earthquake and Hurricane Andrew. Global Environmental Change Part B:Environmental Hazards 4(2):45-58.
    Yang, L., X. Ding, and X. Jiang. 2020. Shutdown and recovery time of enterprises under flood disaster scenario based on survival analysis model:An empirical study on the damaged enterprises in Yuyao City after Typhoon Fitow. Journal of Catastrophology 35(3):110-117 (in Chinese).
    Yang, L., Y. Kajitani, H. Tatano, and X. Jiang. 2016. A methodology for estimating business interruption loss caused by flood disasters:Insights from business surveys after Tokai heavy rain in Japan. Natural Hazards 84(S1):411-430.
    Yang, L., Y. Qi, and X. Jiang. 2021. An investigation of the initial recovery time of Chinese enterprises affected by Covid-19 using an accelerated failure time model. International Journal of Environmental Research and Public Health 18:Article 12079.
    Zhang, Y., and J.D. Fricker. 2020. Multi-state semi-Markov modeling of recurrent events:Estimating driver waiting time at semi-controlled crosswalks. Analytic Methods in Accident Research 28:Article 100131.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (546) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return