Design and Formulation of Strategic Liquidity Management Strategies in the Banking Industry (Case study: Rafah Bank)
محورهای موضوعی : Financial AccountingAlirahm Bagheri 1 , Azar Moslemi 2 , Masoud Taherinia 3 , Ebrahim Givaki 4
1 - Department of Accounting, Faculty of Humanities, Khomein Branch, Islamic Azad University, khomein, Iran
2 - Department of Accounting, Faculty of Humanities, Khomein Branch, Islamic Azad University, khomein, Iran
3 - Department of Accounting, Lorestan University, khoramabad, Iran.
4 - Department of Accounting, Faculty of Humanities, Khomein Branch, Islamic Azad University, khomein, Iran
کلید واژه: strategic management, strategy, Liquidity Management, Banking industry,
چکیده مقاله :
The purpose of this study was to design and formulate strategic liquidity management strategies in the banking industry. In this research, in order to combine qualitative and quantitative data, a sequential integrated exploratory method will be used, according to the classification model with emphasis on qualitative data. Therefore, according to its objectives, the present study is part of applied research and in terms of the research process is part of descriptive and exploratory research that was conducted in two parts: qualitative and quantitative. The statistical population of the present study was the qualitative part of the managers of the Welfare Bank. The sampling method was to achieve theoretical saturation and 25 people were selected as the sample size. Therefore, a survey was used to collect information and according to the data collection, two types of tools were used to review documents, interviews, and questionnaires, and the evaluation method of the questionnaire was performed with a 5-point Likert scale. The Cronbach's alpha questionnaire was used. SWOT analysis was used to analyze the data. The results showed that the Welfare Bank has many opportunities to develop appropriate liquidity management strategies. As it was observed, the chart stretches towards the opportunities and strengths of the offensive situation, which requires strategic planning to use the strengths and opportunities, and 11 strategies were developed for this purpose.
The purpose of this study was to design and formulate strategic liquidity management strategies in the banking industry. In this research, in order to combine qualitative and quantitative data, a sequential integrated exploratory method will be used, according to the classification model with emphasis on qualitative data. Therefore, according to its objectives, the present study is part of applied research and in terms of the research process is part of descriptive and exploratory research that was conducted in two parts: qualitative and quantitative. The statistical population of the present study was the qualitative part of the managers of the Welfare Bank. The sampling method was to achieve theoretical saturation and 25 people were selected as the sample size. Therefore, a survey was used to collect information and according to the data collection, two types of tools were used to review documents, interviews, and questionnaires, and the evaluation method of the questionnaire was performed with a 5-point Likert scale. The Cronbach's alpha questionnaire was used. SWOT analysis was used to analyze the data. The results showed that the Welfare Bank has many opportunities to develop appropriate liquidity management strategies. As it was observed, the chart stretches towards the opportunities and strengths of the offensive situation, which requires strategic planning to use the strengths and opportunities, and 11 strategies were developed for this purpose.
[1] Ismailzadeh, A., Javanmardi, H., Designing a suitable model for liquidity management and risk fore-casting in Bank Saderat Iran. Financial Economics Quarterly, 2017; 11 (39): 197-171.
[2] Beykzadeh Abbasi, F., Ramezanian, A., Claims-based financing; A Modern Tool for Liquidity Man-agement, Fourth National Conference on Research in Accounting and Management, Tehran, Adiban Uni-versity, 2020, https://civilica.com/doc/1036615/
[3] Chalaki P, Heidari M, Dadashzadeh A. The Investigation of Factors Affecting the Liquidity of Banks and Financial Credit Institutions in Iran. Financial Management Strategy, 2016; 4(1): 59-76. doi: 10.22051/jfm.2016.2375
[4] Azadi, M., Izadikhah, M., Ramezani, F., Hussain, FK., A mixed ideal and anti-ideal DEA model: an application to evaluate cloud service providers, IMA Journal of Management Mathematics, 2020; 31 (2): 233-256, doi: 10.1093/imaman/dpz012
[5] Hosseinzadeh, M., Khodadadi, A., Compilation of Credit Risk Strategy based on SWOT Model at Bank Melli of Iran. New Marketing Research Journal, 2018; 8(2): 55-68. Doi: 10.22108/nmrj.2018.106242.1401
[6] Hosseini, Y., Ayoubi, K., Banking and liquidity management. Samat, first edition, Tehran, 2015.
[7] Rahmati, H., Khodaparasti, S., Afifian, E., Khodaparast, S., Development of Saderat Bank strategy based on service quality using SERVQUAL network analysis technique and fuzzy taps, International Con-ference on Industrial Management and Engineering, Vira Capital Ideas Managers Institute, 2014. https://civilica.com/doc/415489/
[8] Zalaghi, H., Bayat, M., Accounting Conservatism and Liquidity Management. Empirical Research in Accounting, 2015, 5(4): 15-28. Doi: 10.22051/jera.2015.626
[9] Qanad, M., Mahmoud Lari, H., Risk management in Islamic financial instruments, Entrepreneur. 2017; 14(41): 31-15.
[10] Gofli, A., Development of SWOT matrix based on FMEA and SMEA models in banks; Case study of Mehr Eghtesad Bank of Guilan province. Master Thesis in Business Management, Financial Orientation, Islamic Azad University, Kermanshah Branch, 2014.
[11] Ehsanbakhsh, H., Izadikhah, M., Applying BSC-DEA model to performance evaluation of industrial cooperatives: an application of fuzzy inference system, Applied research journal, 2015; 1(1): 9-26.
[12] Mohammadi, M., Investigating the Factors Affecting Liquidity Management and Cash Flow in the Social Security Organization, Fourth International Conference on Modern Studies in Economics, Man-agement and Accounting in Iran, University of Applied Sciences-Municipalities Cooperation Organiza-tion and Center for Development of Creativity and Innovation of Modern Sciences, 2020, https://civilica.com/doc/1036293/
[13] Ebrahimi, A., Investigating the negative effects of stock liquidity and risk of the waiting period be-tween the purchase and issuance of shares of companies listed on the Tehran Stock Exchange, Master Thesis in Accounting, Allameh Tabatabai University, 2004.
[14] Darabi, R., Molaei, M., Effect of liquidity, inflation, capital preservation, GDP on Bank Mellat profit-ability. Financial Knowledge of Securities Analysis, 2011; 4(10): 139-182.
[15] Rostamian, F., Haji Babaei, F., Measuring Bank Liquidity Risk Using the Risk Value Model (Case Study: Saman Bank). Journal of Financial Accounting and Auditing, 2009; 1(3): 175-198.
[16] Sarmad, Z., Bazargan, A., Hejazi, E., Research Methods in Behavioral Sciences in Tehran, Agah Pub-lications, 2009.
[17] Izadikhah, M., Deriving weights of criteria from inconsistent fuzzy comparison matrices by using the nearest weighted interval approximation, Advances in Operations Research, 2012, Doi: 10.1155/2012/574710
[18] Saeeda Ardakani, S., Farhadipour, M., Jafari Nodooshan, M., Studying Relationship between Liquidi-ty Risk of Demand Coverage Criterion and Credit Risk of Banks. Journal of Development in Monetary and Banking Management, 2015, 2(3): 1-22.
[19] Ajlafi, M., Investigating the Relationship between Bank Centralization and Financial Stability in Iran, M.Sc. Thesis, Institute of Higher Education in Banking Sciences, Tehran, Iran, 2013.
[20] Central Bank of the Islamic Republic of Iran, National Accounts of Iran and economic report and balance sheet of the Central Bank, different years.
[21] Khosh-sima, R., Shahiki-Tash, M., The Impact of Credit, Operational and Liquidity Risks on the Effi-ciency of Banking System in Iran. JPBUD. 2013; 17(4): 69-95, dor: 20.1001.1.22519092.1391.17.4.4.0
[22] Khoshroo, A., Izadikhah, M., Improving efficiency of farming products through benchmarking and data envelopment analysis, International Journal of Management and Decision Making, 2019; 18(1): 15-30. doi: 10.1504/IJMDM.2019.096691
[23] Khoshnood, Z., Esfandiari, M., Analysis of the mechanism of adjusting the ratio of capital adequacy in the transition from banking health to financial stability. Monetary-Banking Research Quarterly, 2015, 8(25): 401-427, dor: 20.1001.1.26453355.1394.8.25.4.2
[24] Talebi, M., and Shirzadi, N., Credit risk, measurement and management, Samat Publishing, Tehran, 2011.
[25] Nadiri, M., Mohammadi, T., Estimating an Institutional Structure in Economic Growth Using GMM Dynamic Panel Data Method. Economical Modeling, 2011, 5(15): 1-24.
[26] Yazdanpanah, A., Shakib, S., Effective factors on banks liquidity risk (Bank mellat case study). Financial Knowledge of Securities Analysis, 2009, 2(3), P. 27-54.
[27] Fardar D. Strategic Management, translated by Parsaian, A., and Aarabi, M., Tehran, 2013.
[28] Walker, AC., Marketing Strategy, translated by Arabi, S.M., and Izadi, D., Qoghnous. Tehran, 2014.
[29] Seyed Salehi, SR., Investigating the Barriers to Applying Strategic Management in Tehran Munici-pality, Master Thesis, Imam Sadegh (AS) University, 2016.
[30] Shokri, M., Exploration in understanding strategic management, Management Journal (Iranian Man-agement Association), 2019; 54(1): 31-44.
[31] Izadikhah, M., Financial Assessment of Banks and Financial Institutes in Stock Exchange by Means of an Enhanced Two stage DEA Model, Advances in Mathematical Finance and Applications, 2021, 6(2): 207-232. doi: 10.22034/amfa.2020.1910507.1491
[32] Yamani doozi Sorkhabi, M., Salehi, M., From Strategic planning to Adaptive design at the University. IHEJ. 2014, 6(3): 1-30 URL: http://ihej.ir/article-1-368-en.html
[33] Aliannejadi, M., Explanation of the concept of strategic learning in Khatam-all-Anbiya air defense Headquarters, C4I Journal, 2020, 3(4): 92-107 URL: http://ic4i-journal.ir/article-1-165-fa.html
[34] Bassey, GE., & Moses, CE., Bank Profitability and Liquidity Management: A Case Study of Selected Nigerian Deposit Money Banks, International Journal of Economics, Commerce And Management, 2017; 3(4): 1-24.
[35] Bord, V.M., Santos, J.A., Banks' liquidity and the cost of liquidity to corporations. Journal of Money, Credit and Banking, 2016, 46: 13-45, doi: 10.1111/jmcb.12076
[36] Imbierowicz, B., Rauch, C., The relationship between Liquidity Risk and Credit Risk in Banks, Journal of Banking & Finance, 2014; 40(1): 242-256, doi: 10.1016/j.jbankfin.2013.11.030
[37] Konovalova, N., Zarembo, J., Imbalanced Liquidity Risk Management: Evidence from Latvian and Lithuanian Commercial Banks, Copernican Journal of Finance and accounting, 2018, 4(1): 109-130, doi: 10.12775/CJFA.2015.008.
[38] Luqman, OS., The Effect of Credit Risk on the Performance of Commercial Banks in Nigeria. African Journal of Accounting, Auditing and Finance, 2015; 4(1): 29-52, http://www.inderscience.com/link.php?id=71754
[39] Scannella, E., Theory and Regulation of Liquidity Risk Management in Banking, International Jour-nal of Risk Assessment and Management, 2019; 19(1/2): 4-21, doi: 10.1504/IJRAM.2016.074433
[40] Xiao, Y., The Research on Liquidity Risk Management of China’s Commercial Banks, Open Journal of Social Sciences, 2016; 4: 251-259, Doi: 10.4236/jss.2016.43031
[41] Poordavoodi, A., Moazami Goudarzi, MR., Haj Seyyed Javadi, H., Rahmani, AM., Izadikhah, M., To-ward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs, Computer Modeling in Engineering & Sciences, 2020; 123(2): 525-570, doi: 10.32604/cmes.2020.08854
[42] Agénor, PR., Aizenman, J., and Hoffmaister Alexander, W., The redit Crunch in East Asia: What Can Bank Excess Liquid Assets Tell Us? Journal of International Money and Finance, 2004; 23(1): 27–49. doi: 10.1016/j.jimonfin.2003.08.008
[43] Athanasoglou, P.P., Brissmis, SN., Delis, M.D., Bank-specific, industry-specific and macroeconomic determinants of bank profitability, Journal of International Financial Markets, Institutions and Money, 2008; 18(2): 121-36. doi: 10.1016/j.intfin.2006.07.001
[44] Ben Moussa, MA., The Determinates of Bank Liquidity: Case of Tunisia, International Journal of Economics and Financial Issues, 2015, 5(1): 249-259.
[45] Deléchat C, Henao C, Muthoora P, Vtyurina S. The Determinants of Banks' Liquidity Buffers in Cen-tral America, Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, 2014; 1, P. 83-129.
[46] Dinger, V., Do Foreign-owned Banks Affect Banking System Liquidity Risk? Journal of Comparative Economics, 2009; 37(4): 647–57. Doi: 10.1016/j.jce.2009.04.003
[47] Fola, B., Factors Affecting Liquidity of Selected Commercial Banks in Ethiopia. Masters of Science in Accounting and Finance Thesis, Addis Ababa University, Addis Ababa, Ethiopia, 2015.
[48] Izadikhah, M., A Fuzzy Goal Programming Based Procedure for Machine Tool Selection, Journal of Intelligent & Fuzzy Systems, 2015; 28(1): 361–372. doi: 10.3233/IFS-141311
[49] Giovannini, R., Capizzi, V., Chiesi, G.M., Investment Banking Services: Ownership Structures, Finan-cial Advisory and Corporate Governance Models. 2010; P. 49-63, Doi: 10.5430/ijba.v1n1p49
[50] Tan, Y., and Floros, C., Bank profitability and inflation: the case of China, Journal of Economic Stud-ies, 2012; 39(6): 675-696. P. 10.1108/01443581211274610
[51] Tavakoli, A., Schlagwein, D., Schoder, D., Open strategy: Literature review, re-analysis of cases and conceptualisation as a practice. The Journal of Strategic Information Systems, 2017, 26(3): 163-184. doi: 10.1016/j.jsis.2017.01.003
[52] Zare, R., Izadikhah, M., Multi-criteria decision making methods for comparing three models of alu-minum ingot production through life cycle assessment, Applied Ecology and Environmental Research, 2017, 15(3): 1697-1715, Doi: 10.15666/aeer/1503_16971715
[53] Van Eck, N.J., Waltman, L., Text mining and visualization using VOSviewer. arXiv preprint, 2011, doi: 10.48550/arXiv.1109.2058
[54] Van Eck, N.J., Waltman, L., Dekker, R., Van den Berg, J., A comparison of two techniques for biblio-metric mapping: Multidimensional scaling and VOS. Journal of the American Society for Information Science and Technology, 2010; 61(12): 2405-2416. doi: 10.1002/asi.21421.
