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Survival analysis of Thai micro and small enterprises during the COVID-19 pandemic

    Supanika Leurcharusmee Affiliation
    ; Paravee Maneejuk Affiliation
    ; Woraphon Yamaka Affiliation
    ; Nalitra Thaiprasert Affiliation
    ; Nathapong Tuntichiranon Affiliation

Abstract

Micro and small enterprises (MSEs) are important to the local economy and are the most crucial source of employment in Thailand. Using the three-round survey data, we assess the impact of COVID-19 on the survival probability of MSEs in the tourism and manufacturing sectors. Enterprise characteristics such as owner characteristics, employment and business strategies are examined as potential factors to mitigate or stimulate business failures. The Cox proportional hazards model and Kaplan–Meier estimator are employed. Our findings reveal that the survival probability paths from the three rounds of survey show a gradual decrease of survival probability from the first week of interview and approximately 50% of MSEs could not survive longer than 52 weeks during the COVID-19 pandemic. We also find that the survival of MSEs mainly depends on location, number of employees, and business model adjustment, namely operation with social distancing and online marketing. Particularly, retaining employees and not reducing the working hours are one of the key factors increasing the survivability of MSEs. However, the longer length of the crisis reduces the contribution of these key factors. The longer the period of the COVID-19 pandemic, the lower the chance of MSEs survivability.

Keyword : business survival, COVID-19, Cox proportional hazards model, Kaplan–Meier estimator, survey data, Thailand

How to Cite
Leurcharusmee, S., Maneejuk, P., Yamaka, W., Thaiprasert, N., & Tuntichiranon, N. (2022). Survival analysis of Thai micro and small enterprises during the COVID-19 pandemic. Journal of Business Economics and Management, 23(5), 1211–1233. https://doi.org/10.3846/jbem.2022.17875
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Nov 16, 2022
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References

Allison, P. D. (2010). Survival analysis. In The reviewer’s guide to quantitative methods in the social sciences (pp. 413–425). Routledge.

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

Babucea, A. G., & Danacica, D. E. (2010). Using survival analysis in economics. Analele Stiintifice ale Universitatii “Alexandru Ioan Cuza” din Iasi – Stiinte Economice (1954–2015), 57, 439–450.

Bartik, A. W., Bertrand, M., Cullen, Z., Glaeser, E. L., Luca, M., & Stanton, C. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the National Academy of Sciences, 117(30), 17656–17666. https://doi.org/10.1073/pnas.2006991117

Boel, A., Navarro-Compįn, V., Landewé, R., & van der Heijde, D. (2021). Two different invitation approaches for consecutive rounds of a Delphi survey led to comparable final outcome. Journal of Clinical Epidemiology, 129, 31–39. https://doi.org/10.1016/j.jclinepi.2020.09.034

Breier, M., Kallmuenzer, A., Clauss, T., Gast, J., Kraus, S., & Tiberius, V. (2021). The role of business model innovation in the hospitality industry during the COVID-19 crisis. International Journal of Hospitality Management, 92, 102723. https://doi.org/10.1016/j.ijhm.2020.102723

Cox, D. R. (1972). Regression models and life-tables. In Breakthroughs in statistics (pp. 527–541). Springer. https://doi.org/10.1007/978-1-4612-4380-9_37

Dai, R., Feng, H., Hu, J., Jin, Q., Li, H., Wang, R., Wang, R., Xu, L., & Zhang, X. (2021). The impact of COVID-19 on small and medium-sized enterprises (SMEs): Evidence from two-wave phone surveys in China. China Economic Review, 67, 101607. https://doi.org/10.1016/j.chieco.2021.101607

Gémar, G., Moniche, L., & Morales, A. J. (2016). Survival analysis of the Spanish hotel industry. Tourism Management, 54, 428–438. https://doi.org/10.1016/j.tourman.2015.12.012

Giunipero, L. C., Denslow, D., & Rynarzewska, A. I. (2022). Small business survival and COVID-19 – An exploratory analysis of carriers. Research in Transportation Economics, 93, 101087. https://doi.org/10.1016/j.retrec.2021.101087

Gregurec, I., Tomii Furjan, M., & Tomii-Pupek, K. (2021). The impact of COVID-19 on sustainable business models in SMEs. Sustainability, 13(3), 1098. https://doi.org/10.3390/su13031098

Gunsel, N. (2010). Determinants of the timing of bank failure in North Cyprus. Journal of Risk Finance, 11(1), 89–106. https://doi.org/10.1108/15265941011012705

Guerra-Marrero, A., Couce-Montero, L., Jiménez-Alvarado, D., Espino-Ruano, A., Nśńez-Gonzįlez, R., Sarmiento-Lezcano, A., & Castro, J. J. (2021). Preliminary assessment of the impact of Covid-19 Pandemic in the small-scale and recreational fisheries of the Canary Islands. Marine Policy, 133, 104712. https://doi.org/10.1016/j.marpol.2021.104712

Fan, J., & Li, R. (2002). Variable selection for Cox’s proportional hazards model and frailty model. Annals of Statistics, 30(1), 74–99. https://doi.org/10.1214/aos/1015362185

Friedman, J., Hastie, T., & Tibshirani, R. (2009). glmnet: Lasso and elastic-net regularized generalized linear models. R Package Version, 1(4), 1–24.

Fu, M., & Shen, H. (2020). COVID-19 and corporate performance in the energy industry. Energy Research Letters, 1(1), 12967. https://doi.org/10.46557/001c.12967

Hu, S., & Zhang, Y. (2021). COVID-19 pandemic and firm performance: Cross-country evidence. International Review of Economics & Finance, 74, 365372. https://doi.org/10.1016/j.iref.2021.03.016

Jiang, J., Hou, J., Wang, C., & Liu, H. (2021). COVID-19 impact on firm investment – Evidence from Chinese publicly listed firms. Journal of Asian Economics, 75, 101320. https://doi.org/10.1016/j.asieco.2021.101320

Jin, X., Zhang, M., Sun, G., & Cui, L. (2022). The impact of COVID-19 on firm innovation: Evidence from Chinese listed companies. Finance Research Letters, 45, 102133. https://doi.org/10.1016/j.frl.2021.102133

Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. https://doi.org/10.1080/01621459.1958.10501452

Kim, N. Y. (2019). Do reputable underwriters affect the sustainability of newly listed firms? Evidence from South Korea. Sustainability, 11(9), 2665. https://doi.org/10.3390/su11092665

Kim, M. H. Y., Ma, S., & Zhou, Y. A. (2016). Survival prediction of distressed firms: Evidence from the Chinese special treatment firms. Journal of the Asia Pacific Economy, 21(3), 418–443. https://doi.org/10.1080/13547860.2016.1176645

Lane, W. R., Looney, S. W., & Wansley, J. W. (1986). An application of the Cox proportional hazards model to bank failure. Journal of Banking & Finance, 10(4), 511–531. https://doi.org/10.1016/S0378-4266(86)80003-6

Luoma, M., & Laitinen, E. K. (1991). Survival analysis as a tool for company failure prediction. Omega, 19(6), 673–678. https://doi.org/10.1016/0305-0483(91)90015-L

Maneejuk, P., & Yamaka, W. (2021). The impact of higher education on economic growth in ASEAN-5 countries. Sustainability, 13(2), 520. https://doi.org/10.3390/su13020520

Marjański, A., & Sułkowski, Ł. (2021). Consolidation strategies of small family firms in Poland during Covid-19 crisis. Entrepreneurial Business and Economics Review, 9(2), 166–181. https://doi.org/10.15678/EBER.2021.090211

Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109–131. https://doi.org/10.2307/2490395

Office of SMEs Promotion. (2020). MSME 2020. New normal brings opportunities (Executive summary: White paper on MSME 2020). https://www.sme.go.th/upload/mod_download/download-20201005123037.pdf

National Economic and Social Development Council. (2021). The Thai Economy in Q3/2021 and the Outlook for 2021–2022. https://www.nesdc.go.th/nesdb_en/article_attach/article_file_20211115094447.pdf

Pelaez-Verdet, A., & Loscertales-Sanchez, P. (2021). Key ratios for long-term prediction of hotel financial distress and corporate default: Survival analysis for an economic stagnation. Sustainability, 13(3), 1473. https://doi.org/10.3390/su13031473

Puttachai, W., Yamaka, W., Maneejuk, P., & Sriboonchitta, S. (2019). Analysis of the global economic crisis using the Cox proportional hazards model. In International Econometric Conference of Vietnam (pp. 863–872). Springer, Cham. https://doi.org/10.1007/978-3-030-04200-4_62

Rashid, S., & Ratten, V. (2021). Entrepreneurial ecosystems during COVID-19: The survival of small businesses using dynamic capabilities. World Journal of Entrepreneurship, Management and Sustainable Development, 17(3), 457–476. https://doi.org/10.1108/WJEMSD-09-2020-0110

Salinas-Escudero, G., Carrillo-Vega, M. F., Granados-Garcķa, V., Martķnez-Valverde, S., Toledano-Toledano, F., & Garduńo-Espinosa, J. (2020). A survival analysis of COVID-19 in the Mexican population. BMC Public Health, 20(1), 1–8. https://doi.org/10.1186/s12889-020-09721-2

Shafi, M., Liu, J., & Ren, W. (2020). Impact of COVID-19 pandemic on micro, small, and medium-sized Enterprises operating in Pakistan. Research in Globalization, 2, 100018. https://doi.org/10.1016/j.resglo.2020.100018

Shen, H., Fu, M., Pan, H., Yu, Z., & Chen, Y. (2020). The impact of the COVID-19 pandemic on firm performance. Emerging Markets Finance and Trade, 56(10), 2213–2230. https://doi.org/10.1080/1540496X.2020.1785863

Shih, R., & Giles, D. E. (2009). Modelling the duration of interest rate spells under inflation targeting in Canada. Applied Economics, 41(10), 1229–1239. https://doi.org/10.1080/00036840701721232

The Asia Foundation. (2021). Revisiting the pandemic: Surveys on the impact of COVID-19 on small businesses and workers. Bangkok.

Tam, K. Y., & Kiang, M. Y. (1992). Managerial applications of neural networks: The case of bank failure predictions. Management Science, 38(7), 926–947. https://doi.org/10.1287/mnsc.38.7.926

Tibshirani, R. (1997). The lasso method for variable selection in the Cox model. Statistics in Medicine, 16(4), 385–395. https://doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3

Weaver, R. L. (2020). The impact of COVID-19 on the social enterprise sector. Journal of Social Entrepreneurship. https://doi.org/10.1080/19420676.2020.1861476

Woldehanna, T., Amha, W., & Yonis, M. B. (2018). Correlates of business survival: empirical evidence on youth-owned micro and small enterprises in Urban Ethiopia. IZA Journal of Development and Migration, 8(1), 1–26. https://doi.org/10.1186/s40176-018-0122-x

Wu, Y. (2012). Elastic net for Cox’s proportional hazards model with a solution path algorithm. Statistica Sinica, 22, 27. https://doi.org/10.5705/ss.2010.107

Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(2), 301–320. https://doi.org/10.1111/j.1467-9868.2005.00503.x