Banking resilience and government response during the COVID-19 pandemic: Evidence from Nigeria
-
Author(s)Taofeek Sola AfolabiLink to ORCID Index: https://orcid.org/0000-0002-9371-6176
,
Thomas Duro AyodeleLink to ORCID Index: https://orcid.org/0000-0002-0070-2948
,
Oyinlola Morounfoluwa AkinyedeLink to ORCID Index: https://orcid.org/0000-0001-6587-0531
,
Olanrewaju David AdeyanjuLink to ORCID Index: https://orcid.org/0000-0003-0041-1929
,
Harley Tega WilliamsLink to ORCID Index: https://orcid.org/0000-0003-1348-4369
-
DOIhttp://dx.doi.org/10.21511/bbs.18(2).2023.18
-
Article InfoVolume 18 2023, Issue #2, pp. 214-227
- 259 Views
-
175 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
In a global pandemic, there is a need for banks to improve service delivery through financial technologies. Since the fight against COVID-19 is the community responsibility, the role of banks in channeling cash to all stakeholders is essential for the contemporary human race. This study investigated the impact of the government response to COVID-19 on the resilience of banks. A multivariate Structural Equation Model (SEM) was used to specify the links between the exogenous factors (government’s social and financial responses) and the endogenous variables (resilience of bank customers, employees and investors). A research survey approach was used where 543 respondents were sampled. A self-constructed online questionnaire was used to harvest responses from customers, employees and investors of the selected banks. The result of the analysis showed a significant relationship between government’s social response and the resilience of bank customers. However, such a relationship does not hold between government’s social responses and other resilience indicators (employees and investors). Furthermore, the result revealed that government’s financial responses do not affect the resilience of banks. The study concluded that the government’s social response during the COVID-19 pandemic influenced bank customers’ resilience in Nigeria. It was recommended that banks, as part of the policy, develop tools to complement government actions during the pandemic, thereby ameliorating its impact on their customers.
Acknowledgment
The authors will like to acknowledge all respondents who took part in the survey.
- Keywords
-
JEL Classification (Paper profile tab)G20, I18, I38
-
References28
-
Tables17
-
Figures2
-
- Figure 1. Path diagram showing the relationship between government responses and banking resilience
- Figure A1. Path Diagram
-
- Table 1. Demographic characteristics of respondents
- Table 2. Descriptive statistics
- Table 3. Standardized factor loadings
- Table 4. Composite reliability and average variance extracted
- Table 5. Model fit indices
- Table 6. R-Squared estimates of the model
- Table 7. Estimates of the regression coefficients
- Table A1. Regression weights: (Group number 1 – Default model)
- Table A2. Standardized regression weights: (Group number 1 – Default model)
- Table A3. Covariances: (Group number 1 – Default model)
- Table A4. Correlations: (Group number 1 – Default model)
- Table A5. Variances: (Group number 1 – Default model)
- Table A6. Squared Multiple Correlations: (Group number 1 – Default model)
- Table A7. CMIN
- Table A8. Baseline comparisons
- Table A9. RMSEA
- Table A10. Demographic Distribution
-
- Al-Nawayseh, M. K. (2020). Fintech in COVID-19 and beyond: What factors are affecting customers’ choice of FinTech applications? Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 153.
- AlZgoola, M. R. H., Ahmedb, U., Pahic, M. H., & Ammar, A. (2020). COVID-19 and Work Engagement: Understanding the Nexus of Leaders Emotional Intelligence, Self-efficacy and Resilience in the Banking Sector of Bahrain. Revista Argentina de Clínica Psicológica, 29(3), 568-586.
- Aumann, R. J. (1987). Game Theory. In J. Eatwell, M. Milgate, and P. Newman (Eds), The New Palgrave, A Dictionary of Economics, (Vol. 2, pp. 460-482). Macmillan.
- Awofeso, O., & Irabor, P. A. (2020). Assessment of government response to socio-economic impact of COVID-19 Pandemic in Nigeria. Journal of Social and Political Sciences, 3(3), 677-686.
- Ayodele, T. D., Akinyede, O. M., Ojedele, M. I., & Afolabi, T. S. (2021). COVID-19 pandemic and the Nigerian financial market. Journal of Management Information and Decision Sciences, 24(4), 1-10.
- Bank of International Settlements. (2009). Strengthening the resilience of the banking sector. Basel, Switzerland.
- Bedford, D. (2020). COVID-19 Pandemic: How banks can increase Resilience Against Financial Crime. Ernst & Young Global Limited, UK.
- Bertalanffy, L. (1950). An Outline for General Systems Theory. British Journal for the Philosophy of Science, 1(2), 134-165.
- Camerer, C. (2003). Behavioral Game Theory: Experiments in Strategic Interaction. Russell Sage Foundation.
- Cheng, C., Barceló, J., Hartnett, A. S., Kubinec, R., & Messerschmidt, L. (2020). COVID-19 Government Response Event Dataset (Corona Net v.1.0). Nature Human Behaviour, 4, 756-768.
- Chin, W. W. (1998). The Partial Least Squares Approach for Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295-336). Lawrence Erlbaum Associates Publishers.
- Courtemanche, C., Garuccio, J., Le, A., Pinkston, J., & Yelowitz, A. (2020). Chance Elections, Social Distancing Restrictions and Kentucky’s early Covid-19 Experience. PLOS ONE, 16(7), e0250152.
- D’Orazio, P., & Dirks, M. W. (2021). COVID-19 and Financial Markets: Assessing the Impact of the Coronavirus on the Eurozone (Ruhr Economic Paper No. 859). Essen: RWI – Leibniz-Institut fur Wirtschaftsforschung.
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
- Garson, G. D. (2016). Partial Least Squares: Regression and Structural Equation Models (2016 Eds). Asheboro, USA: Statistical Associates Publishing.
- Giese, J., & Haldane, A. (2020). COVID-19 and the Financial System: A Tale of Two Crises. Oxford Review of Economic Policy, 36(1), 200-214.
- Ikeda, Y., Kerry, W., Lewrick, U., & Schmieder, C. (2021). Covid-19 and bank resilience: Where do we stand. BIS Bulletin, 44.
- Korzeb, Z., & Niedziólka, P. (2020). Resistance of Commercial Banks to the Crisis caused by the Covid-19 Pandemic: The Case of Poland. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(2), 205-234.
- Madabhavi, I., Sarkar, M., & Kadakol, N. (2020). COVID-19: a review. Monaldi Archives for Chest Disease, 90(2), 248-258.
- Morens, D. M., & Taubenberger, J. K. (2018). The Mother of All Pandemics Is 100 Years Old (and Going Strong)! American Journal of Public Health, 108(11), 1449-1454.
- Siahaan, M. (2020). Dampakpandemi Covid-19 terhadap dunia pendidikan. Jurnal Kajian Ilmiah, 1(1).
- The World Bank. (2020). The Global Economic Outlook During the COVID-19 Pandemic: A Changed World.
- U.S. Department of Labour. (2020). COVID-19 Impact. Washington, DC: Employment and Training Administration.
- Wang, N., Shi, X., Jiang, L., Zhang, S., Wang, D., Tong, P., Guo, D., Fu, L., Cui, Y., Liu, X., Arledge, K. C., Chen, Y. H., Zhang, L., & Wang, X. (2013). Structure of MERS-CoV spike receptor-binding domain complexed with human receptor DPP4. Cell Research, 23(8), 986-993.
- World Health Organization. (2020). Coronavirus Disease 2019 (COVID-19): Situation Report 100. Geneva.
- Yamey, G., Schäferhoff, M., Aars, O. K., Bloom, B., Carroll, D., Chawla, M., Dzau, V., Echalar, R., Gill, I. S., Godal, T., Gupta, S., Jamison, D., Kelley, P., Kristensen, F., Mundaca-Shah, C., Oppenheim, B., Pavlin, J., Salvado, R., Sands, P., ...& Whiting, E. (2017). Financing of international collective action for epidemic and pandemic preparedness. Lancet Global Health, 5(8), 742-744.
- Zheng, B. J., Guan, Y., Wong, K. H., Zhou, J., Wong, K. L., Young, B. W. Y., Lu, L. W., & Lee, S. S. (2004). SARS-related virus predating SARS outbreak, Hong Kong. Emerging Infectious Diseases, 10(2), 176-178.
- Zhong, N., Zheng, B., Li, Y., Poon, L., Xie, Z., Chan, K., Li, P. H., Tan, S. Y., Chang, Q., Xie, J. P., Liu, X. Q., Xu, J., Li, D. X., Yuen, K. Y., Peiris, J., & Guan, Y. (2003). Epidemiology and cause of severe acute respiratory syndrome (SARS) in Guangdong, People’s Republic of China in February, 2003. The Lancet, 362(9393), 1353-1358.
-
The impact of COVID-19 on the transportation and logistics industry
Dalia Perkumiene ,
Agbonmere Osamede ,
Regina Andriukaitienė ,
Olegas Beriozovas
doi: http://dx.doi.org/10.21511/ppm.19(4).2021.37
Problems and Perspectives in Management Volume 19, 2021 Issue #4 pp. 458-469 Views: 5651 Downloads: 9944 TO CITE АНОТАЦІЯIn this present age of globalization, the logistics and transportation industry has become an integral part of most businesses/firms as it is aimed at ensuring the effective movement of people, distribution of goods and services from one location to another on time. Therefore, this paper aims to analyze the impact of COVID-19 on the logistics and transportation sectors. The qualitative research approach was adopted using analysis and synthesis of scientific literature, data from news reports, organizational sites, and a case study of data contents. The paper presented the analysis of negative and positive effects of COVID-19 on the logistics and transportation industry. The study also discusses possible strategies and further steps for improvement of the logistics and transportation sector, including the automation and introduction of other technologies, a sustainable and flexible transportation system, cooperation of logistics and transportation business. Findings regarding the positive implications of COVID-19 show noticeable advancements in the logistics and transportation sector, such as the rise of e-commerce businesses with efficient delivery options, and the development of 3rd party logistics services as more companies outsource supply chain operations. The study revealed the importance of strategic planning with a joint effort from the research centers, public sector, private sector, and educational institutions as one of the proposed solutions for the logistics and transportation industry.
-
The impact of social distancing policy on small and medium-sized enterprises (SMEs) in Indonesia
Muhtar Lutfi ,
Pricylia Chintya Dewi Buntuang ,
Yoberth Kornelius ,
Erdiyansyah ,
Bakri Hasanuddin
doi: http://dx.doi.org/10.21511/ppm.18(3).2020.40
Problems and Perspectives in Management Volume 18, 2020 Issue #3 pp. 492-503 Views: 3409 Downloads: 1267 TO CITE АНОТАЦІЯThis study aims to investigate the impact of social distancing policies on SMEs in Indonesia. It used a quantitative method with a survey design. Respondents were all SMEs in Indonesia that are affected by social distancing policies during the COVID-19 pandemic. It involved a total of 587 SME samples selected randomly. The data were collected through observations, questionnaires, and literature studies. The collected data were analyzed using descriptive statistics with SPSS software to determine the mean value. The result showed that social distancing policies affect SMEs during the COVID-19 pandemic. This is indicated by the decreasing income and demand for SMEs products, and even some have no income (mean values of 2.40) due to the social distancing policies. Besides, the policy’s impact is also shown in the increasing cost of raw materials and production costs due to supply chain problems (mean values of 4.79). The policy’s impact raises anxiety for SMEs to survive so that business actors change their plans by utilizing information technology (mean values of 4.81). This change is a strategy to survive due to the impact of the applied policies. Although social distancing policies affect SMEs’ survival during the pandemic, research findings show that SMEs in Indonesia did not terminate employment (mean values of 4.37) due to the presence of economic stimulus policies that helped SMEs survive and grow during the COVID-19 pandemic.
-
The influence of servant leadership on job satisfaction with individual character as a moderating variable
Bakri Hasanuddin ,
Mustainah M ,
Pricylia Chintya Dewi Buntuang
doi: http://dx.doi.org/10.21511/ppm.19(1).2021.37
Problems and Perspectives in Management Volume 19, 2021 Issue #1 pp. 445-455 Views: 3147 Downloads: 1468 TO CITE АНОТАЦІЯThis study aims to investigate the influence of servant leadership on job satisfaction with individual character as a moderating variable. It used a quantitative approach with multiple linear regression analysis. The population of this study were employees of the Central Sulawesi province industry and trade office. It involved 72 samples selected using a purposive sampling technique. The results showed that servant leadership significantly influence job satisfaction with a value of 82.5%. The most significant factor affecting job satisfaction is wisdom (correlation coefficient = 0.863) in which the higher the wisdom, the higher the job satisfaction. The next factor is persuasive mapping in which the higher the persuasive mapping, the higher the job satisfaction (correlation coefficient = 0.697). Then, it was followed by altruistic calling with the correlation coefficient value of 0.524 in which the higher the altruistic calling, the higher the job satisfaction. The last is emotional healing with a correlation coefficient value of 0.291 in which the higher the emotional healing, the higher the job satisfaction. On the other hand, organizational stewardship is the only factor does not influence the job satisfaction (correlation coefficient = 0.009).
