Factors affect the competitiveness of vietnamese commercial banks in context of ASEAN economic community

Nội dung text: Factors affect the competitiveness of vietnamese commercial banks in context of ASEAN economic community

1. FACTORS AFFECT THE COMPETITIVENESS OF VIETNAMESE COMMERCIAL BANKS IN CONTEXT OF ASEAN ECONOMIC COMMUNITY Author: Ph.D. Nguyen Thi Bich Vuong Hanoi Industrial and Commercial College Email: Violet1072007@gmail.com Abstract Banking competitiveness has long been a hot topic, attracting attention not only of scholars, researchers, but also of interest of bank administrators. Especially in the context of the integration of the ASEAN economic community and the explosion of the industrial revolution 4.0, the competition between commercial banks has become more and more intense not only within the country but also spread to the international scope. Many empirical studies have shown that the competitiveness of banks is affected by many different factors. Therefore, the project has conducted a survey of 278 officers and employees working in 10 typical commercial banks in Vietnam (BIDV, VCB, Vietinbank, Agribank, Techcombank, VIB, MSB, LPB, ACB, MB) to analyze and assess the influence of factors on the competitiveness of Vietnamese commercial banks. The article conducts testing of Cronbach’s Alpha coefficients, Exploratory Factor Analysis (EFA), Pearson correlation analysis and regression analysis; The research results showed that all respondents confirmed all 7 factors including: Financial capacity, technological capacity, service fee, brand of the bank, transaction network, service quality, intellectual capital are positively affecting the competitiveness of Vietnamese commercial banks. With these research results, the article will be a scientific basis for the State management agencies to have support policies to improve the competitiveness of Vietnam's banking sector during the ASEAN community integration period. Keywords: Competitiveness, influencing factors, Vietnamese commercial banks. 1. Introduction Vietnam officially became the seventh member of ASEAN since July 28, 1995 and since then the competitive pressure in the banking sector has begun to appear and increase significantly. Over the past 20 years, Vietnamese commercial banks have actively sought and implemented many measures to improve their competitiveness before the requirements of the ASEAN economic community integration and international economic integration. However, after more than 20 years of joining 316
2. ASEAN, Vietnamese commercial banks still show many of their weaknesses such as: Financial capacity is low; Competitiveness is not high; Management capacity and technology are weak; Reforms are slow and lack transparency. Under this situation, the Government issued the Decision No. 254/QD-TTg dated 1 March 2012 on approving the project of restructuring the system of credit institutions in the 2011- 2015 period. Over 5 years of implementing restructuring, the system of Vietnamese commercial banks has obtained some certain successes such as: ensuring the liquidity of the system and creating conditions for macroeconomic stability; controlling weak commercial banks through mergers or allowing to restructure themselves; Establishing a debt trading company VAMC to allow bad debt settlement of credit institutions to stabilize operations. However, there are still many shortcomings that need to be solved to strengthen the health of the banking system such as: Bad debt is still high; Cross-ownership issues, cross-investment in credit institutions is still lack of transparency; Charter capital in some joint stock commercial banks does not reflect the true nature, leading to the risk of controlling and manipulating banking activities. This affects the operation and competitiveness of banks. Moreover, with the explosion of the 4.0 industrial revolution that has pulled the world economies together and the distance has been eliminated, the playing field will become more and more equal. Vietnam is not an exception, in the process of integrating into the world economy, Vietnamese commercial banks have many opportunities but also face many challenges. Compared to commercial banks in the ASEAN community and around the world, Vietnamese commercial banks are still very young in terms of qualifications, scale as well as business skills. With pressure in the period of international economic integration, Vietnamese commercial banks must constantly innovate to improve their competitiveness in the market. 2. Overview of the factors affecting the competitiveness of commercial banks One of the famous models in analyzing competitiveness in general is the model of Michael E. Porter. This model has been revised many times from 1979 to 1998 and is considered as one of the fundamental theoretical models for research on competitiveness. Firstly, he introduced the model "Five competitive forces" for all sectors in general including banking sector. Next, he introduced the "Diamond Model" with 4 groups of factors affecting the competitiveness of businesses in general, arranged in the form of diamonds including: (i) Conditions on production and business factors (human, material and intellectual resources), (ii) Conditions of demand with contents about the size, structure and complexity of domestic market demand for a given industry's goods and services, (iii) Strategies, structures and competition of businesses, (iv)Related industries and supporting industries. Finally, 317
3. in 1998 he developed his diamond model into a model of 9 subjective and objective factors affecting the competitiveness of the banking sector. Unlike Michael E. Porter, Thompson and Strickland (1990) proposed a method to assess the competitiveness of an organization through a matrix of internal factors. Accordingly, he proposed a model consisting of factors affecting competitiveness of enterprises and banks. For the banking sector, the influencing factors include: financial capacity, service quality, capital mobilization capacity, lending capacity, executive management capacity, interest rate competitiveness, technological capacity, quality of human resources, development capacity network, service capacity. Mary E. Barth et al (2003) conducted research on the competitiveness of commercial banks in the US and Canada. According to Barth (2003), the competitiveness of commercial banks is measured by six influencing factors: Quality of human resources, equipment and facilities, working system, understanding, capacity of technology, administrative and legal procedures. In addition, Barth (2003) said that it is necessary to add the "Prestige of the bank" factor to the model. Givi et al. (2010) developed a model of factors affecting the competitiveness of commercial banks in Iran. By using the Exploratory Factor Analysis (EFA) and Confirming Factor Analysis (CFA) through LISREL 8.5 software, the study results show 5 factors affecting the competitiveness of the Commercial banks in Iran include: financial capacity, market share, human resources, technological capacity and international exchange activities. Darshani (2013) investigated the factors affecting the competitiveness of bank branch Kahawatta of Ceylon Leasing Bank in Sri Lanka. The author has pointed out four factors affecting the competitiveness of banks including: quality of banking services, bank promotion efforts, banking technology capabilities and rental service fees. Hoang Nguyen Khai (2014) has built a model of 5 factors affecting competitiveness of Vietnam Joint Stock Commercial Bank for Foreign Trade: Bank scale, service quality, sales promotion efforts, banking technology, bank service fees. Doan Thi Thuy Anh (2016) builds a model of 8 factors affecting competitiveness in retail banking services of commercial banks in Hanoi city: quality of banking products, retail banking services, reputation of banks, banking transaction network, financial capacity, banking technology, trade promotion activities, intellectual capital 3. Research Model and Hypothesis Through an overview of the factors affecting the competitiveness of commercial banks in general, with the topic of the article are the factors affecting the competitiveness of Vietnamese commercial banks, therefore research model is as follows: 318
4. Y = β0 + β1 *X1+ β2 *X2 + β3 *X3 + β4 *X4 + β5 *X5 + β6 *X6 + β7 *X7 In which: - Dependent variable Y = Competitiveness - β0 is the intercept, β1 → β7 is the slope of the relationship between the independent variable Xi and the dependent variable Y. - Independent variables: X1, X2, X3, X4, X5, X6, X7 with: X1 is the financial capacity of the Bank X2 is the technology capacity of the Bank X3 is the brand of the Bank X4 is the service quality of the Bank X5 is the transaction network of the Bank X6 is the intellectual capital X7 is the service fee of the Bank The above independent variables are the factors affecting the competitiveness of the subjects surveyed in the study. The coefficients βi will be determined after analyzing the data collected through SPSS 22.0 software. Thus, the linear regression equation in this research model can be as follows: Competing capability = β0 + β1 * Financial capacity + β2 * Technology capacity + β3 * Brand of the bank + β4* Service quality + β5 * Transaction Network + β6 * Intellectual capital + β7 * Service fee + ɛ From the above research model, the author makes research hypotheses including: Hypothesis H1: The factor of "Financial capacity" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H2: The factor of "Technology capacity" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H3: The factor "Brand of the bank" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H4: The factor "Quality of service" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H5: The factor "Transaction network" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H6: The factor "Intellectual capital" has a positive impact on Competitiveness of Vietnamese commercial banks. Hypothesis H7: The factor "Service fee" has a positive impact on Competitiveness of Vietnamese commercial banks. 319
5. 4. Research Methods The study was conducted in two steps: preliminary research and formal research. Preliminary research is done by qualitative method through open-type group discussion with 2 target groups: Group 1: consists of 15 experts, including 5 people who are lecturers or scientific researchers with a doctorate or higher who are teaching and researching on Banking and Finance majors in some universities great study of Vietnam (National Economics University, Banking Academy, Ho Chi Minh City University of Banking, Foreign Trade University ) and 10 senior leaders of 10 typical commercial banks in Vietnam (Joint Stock Commercial Bank for Investment and Development of Vietnam - BIDV, Joint Stock Commercial Bank for Foreign Trade of Vietnam - VCB, Vietnam Joint Stock Commercial Bank for Industry and Trade - Vietinbank, Vietnam Bank for Agriculture and Rural Development - Agribank, Asia Joint Stock Commercial Bank- ACB, Lien Viet Commercial Joint Stock Bank - LPB, Vietnam Technological and Commercial Joint Stock Bank - Techcombank, Military Joint Stock Commercial Bank - MB, Maritime Commercial Joint Stock Bank - MSB, International Joint Stock Commercial Bank - VIB). Group 2: consists of those who need to conduct surveys, including officials and employees of 10 typical commercial banks in Vietnam (BIDV, VCB, Vietinbank, Agribank, Techcombank, VIB, MSB, LPB, ACB, MB). This discussion aims to develop scales appropriate to the context of the study. Scale in research using Likert form 5 levels from 1- Strongly disagree 5- Very agree, and 3- Normal. The discussion results of qualitative research have provided 33 scales to measure 7 factors affecting the competitiveness of commercial banks, including: The factor "Financial capacity" includes 6 scales that are coded from TC_1 to TC_6; The factor "Technology capacity" includes 5 scales that are coded from CN_1 to CN_5; The factor “Brand of the bank” includes 5 scales that are coded from TH_1 to TH_5; The factor “Service fee” includes 3 scales that are coded from PDV_1 to PDV_3; The factor “Quality of service” includes 6 scales that are coded from CL_1 to CL_6; The factor “Transaction network” includes 4 scales that are coded from ML_1 to ML_4; The factor “Intellectual capital” includes 4 scales that are coded from VTT_1 to VTT_4. Formal research is carried out by quantitative methods by self-filling questionnaire with the surveyed subjects. Data of this study were conducted to measure scale, Exploratory Factor Analysis (EFA), Pearson correlation analysis, regression analysis and testing model and hypotheses by SPSS 22.0 software. 320
6. 5. Research results The author conducted a survey of 300 officials and employees in 10 typical commercial banks in Vietnam (BIDV, VCB, Vietinbank, Agribank, Techcombank, VIB, MSB, LPB, ACB, MB) and collected 278 valid questionnaires. Data collected from these 278 votes will be used to analyze the influence of factors on the competitiveness of Vietnamese commercial banks based on the evaluation of the above objects. Research results are as follows: 5.1. The results of assessing the reliability of the scales Cronbach’s Alpha coefficients are a statistical test of how closely the items asked in the scale correlate. This relates to two aspects of the correlation between variables and the correlation of each variable with the overall score of each respondent. This method allows analysts to remove unsuitable variables for garbage processing in the research model because otherwise we cannot know the exact variability as well as the error of the variables. Accordingly, only variables with a correlation of the total positive variable greater than 0.3 and having a Cronbach’s Alpha coefficient greater than 0.6 will be considered acceptable and appropriate for subsequent analysis steps. Table 1: Results of Cronbach's Alpha coefficient of scales Corrected Item- Cronbach's Alpha if Cronbach's Item Total Correlation Item Deleted Alpha FINANCIAL CAPACITY TC_1 0.663 0.886 TC_2 0.684 0.883 TC_3 0.775 0.864 0.884 TC_4 0.808 0.865 TC_5 0.672 0.887 TC_6 0.711 0.874 TECHNOLOGY CAPACITY CN_1 0.706 0.814 CN_2 0.687 0.813 CN_3 0.652 0.826 0.857 CN_4 0.644 0.827 CN_5 0.645 0.822 321
7. Corrected Item- Cronbach's Alpha if Cronbach's Item Total Correlation Item Deleted Alpha BRAND OF THE BANK TH_1 0.731 0.875 TH_2 0.763 0.866 TH_3 0.775 0.867 0.891 TH_4 0.727 0.872 TH_5 0.724 0.874 SERVICE FEE PDV_1 0.763 0.885 PDV_2 0.826 0.833 0.876 PDV_3 0.804 0.847 QUALITY OF SERVICE CL_1 0.683 0.885 CL_2 0.737 0.875 CL_3 0.764 0.872 0.893 CL_4 0.786 0.866 CL_5 0.697 0.882 CL_6 0.651 0.884 TRANSACTION NETWORK ML_1 0.726 0.863 ML_2 0.643 0.895 0.881 ML_3 0.865 0.817 ML_4 0.798 0.841 INTELLECTUAL CAPITAL VTT_1 0.692 0.813 VTT_2 0.665 0.826 0.859 VTT_3 0.663 0.831 VTT_4 0.749 0.783 COMPETITIVENESS OF BANK CT_1 0.573 0.694 CT_2 0.481 0.748 0.755 CT_3 0.536 0.705 CT_4 0.625 0.653 Source: Research results of the author 322
8. The analysis results shown in Table 1 show that: Cronbach's Alpha coefficient of all survey scales is greater than 0.7, of which the lowest is the measurement scale of the dependent variable "Competitiveness of banks" with Cronbach's Alpha coefficient = 0.755. This shows that survey data is completely reliable. Furthermore, the correlation coefficient of the sum of all the variables observed with the factor that the variables represent is greater than 0.3. This shows that respondents have a concept of the set of factors given by the observed scales/variables that express that factor, so the scales are to ensure reliability. Therefore observed scales/variables and factors are retained for further analysis. 5.2. Result of Exploratory Factor Analysis (EFA) After the data has ensured reliability, the next analytical work is to analyze the exploratory factor (EFA) to make an assessment of the convergence of factors and the number of factors given from survey data. In the factor analysis results need to ensure the requirements: KMO coefficient (Kaiser - Meyer - OlKIN) ≥ 0.5, significance level of Bartllett test ≤ 0.05. Factor Loading ≥ 0.50, if any observed variable has Factor Loading < 0.50 will be eliminated. The scale is accepted when the total variance extracted ≥ 50%. Eigenvalue coefficient must be valued ≥ 1. In this study, the Principal Component method with Varimax rotation will be used to analyze the discovery factor. Table 2. Matrix rotating scales of variables Item 1 2 3 4 5 6 7 CL_4 0.841 CL_3 0.846 CL_2 0.825 CL_5 0.793 CL_1 0.789 CL_6 0.746 TC_4 0.871 TC_3 0.856 TC_6 0.805 TC_2 0.782 TC_5 0.763 TC_1 0.767 TH_3 0.865 TH_2 0.850 323
9. Item 1 2 3 4 5 6 7 TH_1 0.834 TH_4 0.828 TH_5 0.819 CN_1 0.826 CN_2 0.801 CN_4 0.782 CN_3 0.765 CN_5 0.769 ML_3 0.937 ML_4 0.892 ML_1 0.843 ML_2 0.778 VTT_4 0.864 VTT_1 0.823 VTT_3 0.805 VTT_2 0.797 PDV_2 0.913 PDV_3 0.912 PDV_1 0.895 Variances 12.135 24.167 34.893 44.548 53.789 62.294 69.912 Eigenvalues 4.756 3.813 3.617 3.332 2.827 2.423 2.306 KMO = 0.805, Sig = 0.000 Source: Research results of the author According to the analysis results in Table 2 shows that: - Bartlett's test results show that there is a correlation between the variables in the overall (Sig = 0.000 <0.05) and KMO coefficient = 0.805, showing that the results of factor analysis to group the variables together are guaranteed reliability. - The above observed variables have Factor Loading greater than 0.5 to ensure the standard, while the difference between Factor Loading of the observed variables is greater than 0.3. Therefore, it is not necessary to remove the observed variable in the analysis. - The Eigenvalues coefficient of the fifth factor is 2,306, confirming that there are 07 factors drawn from the analysis; The total coefficient of variance extracted by 324
10. 07 factors by 69,912, showing the variation of the factors derived from the analysis, can explain 69,912% of the variation of the original survey data. The value of variance extracted is greater than 50%, thus ensuring the requirement of analysis. 5.3. The result of the Pearson correlation test Before conducting regression analysis to assess the influence of factors in the regression model on the dependent variable is the competitiveness of Vietnamese commercial banks, the necessary work is level verification the correlation between the independent variables and between the independent variable and the dependent variable. The type of test that is often applied in this case is the Person correlation test. Pearson correlation test is used to test the linear relationship between independent variables and dependent variables. If the variables are closely correlated, attention should be paid to the problem of multicollinearity when regression analysis (hypothesis H0: correlation coefficient is 0). Table 3. Person correlation matrix TC CN TH PDV CL ML VTT CT TC 1 CN 0.006 1 TH -0.02 0.032 1 PDV 0.047 0.062 0.098 1 CL .147* 0.027 0.022 0.043 1 ML 0.041 0.091 -0.03 0.093 -0.03 1 VTT 0.106 .159 0.07 0.097 0.084 0.083 1 CT .374 .362 .371 .400 .353 .261 .447 1 *. Correlation is significant at the 0.05 level (2-tailed). . Correlation is significant at the 0.01 level (2-tailed). Source: Research results of the author The results of the correlation test in Table 3 show that: The variables are correlated and significant at 0.01 level. The correlation coefficients of the dependent variable and the independent variables are relatively high; Preliminary, we can conclude that these independent variables can be included in the model to consider the influence of these variables on the competitiveness of banks. Besides, the independent variables are mostly expressed without correlation, there are only two factors: "Technology capacity" and "Intellectual capital" have significant correlation, but the low correlation coefficient is 0.159, so it is necessary to consider whether or not multicollinearity affects the regression results. 325
11. 5.4. Results of regression analysis The results of the correlation analysis show that there is a correlation of the independent variables to the dependent variable, the regression analysis will confirm this correlation, and give the degree of influence of each factor with that dependent variable. The results of regression analysis are as follows: Table 4. Results of regression analysis Adjusted R Std. Error of Durbin- Model R R Square Square the Estimate Watson 1 .840a 0.706 0.697 0.26572 1.974 ANOVA Sum of Squares df Mean Square F Sig. Regression 47.125 7 6.732 95.352 .000b Residual 19.629 278 0.071 Total 66.754 285 Regression Coefficient Unstandardize Standardized d Coefficients Coefficients t Sig. VIF B Beta (Constant) -0.278 -1.911 0.057 TC 0.167 0.284 8.667 0.000 1.035 CN 0.153 0.260 7.928 0.000 1.035 TH 0.175 0.324 9.768 0.000 1.017 PDV 0.155 0.280 8.524 0.000 1.030 CL 0.152 0.266 8.048 0.000 1.030 ML 0.095 0.195 5.867 0.000 1.025 VTT 0.168 0.283 8.573 0.000 1.057 Source: Research results of the author The analytical results in Table 4 show that: - Coefficient R squared = 0.697, this shows the variation of the independent variables in the model can explain 70% of the evaluation results of the bank's competitiveness. 326
12. - Durbin-Watson coefficient = 1.974, close to value 2 shows the remainder of independent variables without self-correlation. - The coefficient F = 95.352, Sig = 0.000 in ANOVA test shows that the reliability in the regression analysis results is guaranteed with low errors. - The Sig coefficient of the factors in the regression coefficient is also lower than 0.05, which confirms the factors that affect the dependent variable are the competitiveness of banks. - VIF coefficients of all factors are less than 2, so there is no multicollinearity phenomenon between independent variables. Thus, the test results for the regression model have achieved good results, this shows that the construction of the regression function represents the influence of independent variables on the dependent variable in the model is degree high reliability. Regression equation is built based on the adjusted regression coefficients as follows: Competing capability = 0.284* Financial capacity + 0.260* Technology capacity + 0.324 * Brand of the bank + 0.266* Service quality + 0.195* Transaction Network + 0.283* Intellectual capital + 0.280* Service fee 6. Conclusion Research results show that the research hypotheses H1, H2, H3, H4, H5, H6, H7 are accepted with high reliability. That is the factors include: Financial capacity, Technology capacity, Service fee, Brand of the bank, Transaction Network, Service quality, Intellectual capital have a positive impact on the competitiveness of Vietnamese commercial banks. In particular, the most influential factor is the "Brand of the bank" with the coefficient of 0.324, followed by the factor "Financial capacity" with coefficient 0.284 and "Intellectual capital" with a coefficient of 0.283. The fourth influential factor is the "Service fee" with the coefficient of 0.280, the fifth influencing factor is "Service quality" with the coefficient of 0.266, The sixth influencing factor is "Technology capacity" with a coefficient of 0.260 and the lowest influencing factor is "Transaction network" with 0.195 coefficient. 7. References 1. Anh Doan Thi Thuy (2016), Research on factors affecting competitiveness of retail banking services at commercial banks in Hanoi city. The doctoral thesis in Economics. National Economics University. Hanoi. 327
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