THE IMPACT OF INFORMATION TECHNOLOGY ON IMPROVING BANKING PERFORMANCE EVIDENCE FROM VIETNAM

CONFERENCE PROCEEDINGS 4th International Conference on Contemporary Issues in ECONOMICS, MANAGEMENT AND BUSINESS November 11th – 12th, 2021, Hanoi - Vietnam NATIONAL ECONOMICS UNIVERSITY PUBLISHING HOUSE CONFERENCE PROCEEDINGS 4th International Conference on Contemporary Issues in ECONOMICS, MANAGEMENT AND BUSINESS November 11th – 12th, 2021, Hanoi - Vietnam NATIONAL ECONOMICS UNIVERSITY PUBLISHING HOUSE HUMAN RESOURCE MANAGEMENT AND INTRAPRENEURIAL BEHAVIORS IN VIETNAMESE SUBSIDIARIES OF JAPANESE MULTINATIONAL COMPANIES: DO WE NEED INNOVATIVE HUMAN RESOURCE MANAGEMENT? 1189 Tran Huy Phuong National Economics University THE INFLUENCE OF TALENT DEVELOPMENT PRACTICES ON TEACHER PERFORMANCE IN GENERAL SCHOOLS IN HANOI 1209 Nguyen Thuy Van Anh Faculty of Human Resource Management and Economics, National Economics University Pham Tung Anh International School of Management and Economics, National Economics University THE FACTORS AFFECTING DEVELOPMENT OF HIGH QUALITY HUMAN RESOURCE IN HIGH-TECH AGRICULTURAL ENTERPRISES IN VIETNAM 1233 Le Thi Hien Thuongmai University THE DIRECT AND INDIRECT EFFECTS OF GREEN HUMAN RESOURCE MANAGEMENT ON EMPLOYEES’ ORGANISATIONAL COMMITMENT 1252 Nguyen Ngoc Phu, Nguyen Ngoc Thang Hanoi School of Business and Management, Vietnam National University Tran Thi Van Hoa National Economics University Nguyen Thi Thu Huong Ghent University SESSION 16: TECHNOLOGY & INNOVATION OPEN INNOVATION AND INTERNAL R&D EXPENDITURES: THE MEDIATING ROLE OF ABSORPTIVE CAPACITY 1267 Tran Lan Huong, Le Tri Nhan Nguyen Thi Ngoc Anh, Nguyen Thuy Linh Faculty of Management Science, National Economics University THE IMPACT OF INFORMATION TECHNOLOGY ON IMPROVING BANKING PERFORMANCE: EVIDENCE FROM VIETNAM 1287 Vu Thi Huyen Trang Thuy Loi University THE IMPACT OF INFORMATION TECHNOLOGY ON IMPROVING BANKING PERFORMANCE: EVIDENCE FROM VIETNAM Vu Thi Huyen Trang Thuy Loi University Abstract: The paper analyses the impact of investment in information technology (IT) on the performance of Vietnamese commercial banks The study applies the random-effects model (REM) to the data of 30 Vietnam’s commercial banks in the period from 2016 to 2020 The results show that an increase (decrease) in IT investment (Technical infrastructure, IT human resource infrastructure, Online banking service) leads to an increase (decreased) ROA, ROE of Vietnamese commercial banks Based on the findings, the authors give some recommendations to Vietnamese commercial banks in case of investments in IT to improve performance Keywords: Commercial banks, information technology, performance, ROA, ROE Introduction Gunasekaran et al (2001) argue that because of globalization and development in information technology, thereby stimulating and strengthening the establishment of global competition As a result, businesses are forced to spend billions of dollars on investments in new IT infrastructure to remain sustainable and competitive in the market (Nustini, 2003) However, the economic recession of 2008, has compelled companies to reassess IT investments, the benefits or returns they are likely to derive in the future investments in IT infrastructures (Alves, 2010; Creswell, 2004; Czerwinski, 2008; Gunasekaran et al., 2001; Tynan, 2005) Many companies have responded to the changing business environment by transforming their IT strategies and investing significant sums in new IT infrastructure to improve their performance and stay competitive However, the returns from these IT expenditures are difficult to measure (Dehning and Richardson, 2002; Gunasekaran et al., 2001; Nustini, 2003) Lloyd-Walker and Cheung (1998) have shown that in the banking industry, IT can help deliver superior customer services by providing a fast, accurate, and reliable service Kim and Davidson (2004) stated that the banking industry environment has become IT-intensive Porter and Millar (1985) emphasizes that the banking industry has a high IT content in both products and processes, just like journalism and aviation Thus, the banking industry is one of the industries that use accounting information systems (AIS) with a very high IT content, which has contributed to banking operations, reducing costs, time and improving service quality offered to customers 1287 However, investing in information technology is an expensive process that requires considerable effort, time, and money at every stage (planning, analysis, design, development, implementation and upgrade) Many studies have tried to show the direct impact of accounting information systems, specifically investment in information technology on business performance, but the results of these studies are different The researchers conducted in the first half of the 1990s by Strassmann (1990), Weill (1992), Brynjolfsson (1993), and Landauer (1995) showed that there was no link between investments in IT and business performance However, the researchers conducted in the second half of the 1990s by Brynjolfsson (1995), Dewan (1997), Hitt (1996) concluded that there is a positive relationship between investment in IT and enterprise performance Because the research results on the relationship between IT investment and business performance in the world show many different results, so empirical studies in this area are still very necessary By interpreting the previous findings on "the productivity paradox", our research attempts to empirically validate the relationship between IT investment and performance in the context of the emerging country of Vietnam Our study is therefore devoted to examining the following key question: What is the impact of information technology on the performance of Vietnam commercial banks? To empirically validate the relationship between IT investment and the performance of Vietnam commercial banks, we use the most commonly used traditional measures such as ROA and ROE Thus, the objective of this work is to evaluate the performance of banks during the period 2016–2020 while identifying, the impact of different information technologies components introduced by banks on their performance The paper is organized as follows Section provides the theoretical Foundation and literature review for our study Section outlines the methodological approach and illustrates the sample and data Finally, Section describes the empirical results, and Section is the conclusion Literature review Through the review, the author found that there are many studies on the relationship between IT investment and performance, and these studies give different results Several studies examine the correlation between IT investment and ROA (Shin, 2001; Rai et al., 1997; Hitt and Brynjolfsson, 1996; Weill, 1992; Strassmann, 1997), between IT spending and ROE (Shin, 2001; Rai et al., 1997; Hitt and Brynjolfsson, 1996), and between investment in IT and intermediate variables of performance, which is turn drive profits (Markus and Soh, 1993; Barua et al., 1995) However, these studies only focus on other industries, but there are few studies in the banking industry 1288 Brynjolfsson and Hitt (1994) separate the benefits of investing in information technology into three distinct areas: increased productivity, improved business performance, and increased value for consumers The sample includes 367 Fortune 500 manufacturing and service companies in surveys conducted by the International Data Group and from Standard and Poor's Compustat The author's analysis is based on production theory, competitive advantage theory, and consumer theory The dependent variables measuring the business performance include value-added, total shareholder return, ROA, ROE The independent variables that measure investment in information technology are used by the same author in his research in 1993, including information system labor, non-information labor, computer capital, noncomputer capital, firm size, year, industry The research methods used by the author for each different data set are OLS regression analysis, estimation methods unrelated regressions (ISUR), 2-stage regression method (2SLS) The author finds that there are many contradictions around the Productivity Paradox, where IT spending has a positive impact on productivity and creates significant value for consumers However, IT expenditures have little, if any, positive impact on business performance and may have a negative impact Brynjolfsson and Hitt (1996) used 1000 observations between 1987 and 1991 that appeared simultaneously in the International Data Group (IDG) and Standard and Poor's Compustat II data sources The independent variable measuring IT spending in the study is IT stock - the market value of a company's IT systems plus three times the company's spending on IT personnel Dependent variables measure the performance of the business: ROA, ROE Research results show that there is a positive relationship between IT stocks and ROA for three consecutive years, but there is no relationship between IT stocks and ROE Shin (1997) studied the relationship between IT investment and coordination costs – selling and administrative costs minus non-administrative costs (e.g., advertising costs, research and development costs) Shin's research results are in contrast with the research results of Mitra and Chaya (1996) Shin (1997) shows that IT spending has a negative relationship with coordination costs Further, Shin (1997) found that there was a positive relationship between non-administrative expenses and administrative costs Therefore, Mitra and Chaya's (1996) finding was a result of the exclusion of non-administrative expenses from general and administrative Apparently, Mitra and Chaya's (1996) research design was based on scaling by sales, while Shin's (1997) research design was based on scaling by employees’ census To harmonize these conflicts in findings and obtain understandable relationships between IT expenditure and selling, general and administrative expenses, additional studies are inevitable (Dehning and Richardson, 2002) Further, Shin (1997) 1289 examined the combination of IT expenditure and coordination costs plus the cost of capital, cost of labor, and research and development costs in order to elucidate a company’s aggregate number, which is sales plus change in inventory number Shin found a company’s productivity is positively related to IT expenditure, costs of coordination, cost of capital, cost of labor, and research and development expenses Rai et al (1997) was an attempt to validate Shin’s findings and it, by and large, confirmed Shin’s findings Rai et al (1997) used a sample of 497 companies from 1994 Information Week and 1994 Compustat Selected companies are among the top 500 with the highest cost data for IT The independent variables used by the author to measure IT investment include IT capital, budget, server, staff training, hardware, software, telecommunication equipment Dependent variables to measure performance include company output (direct labor division revenue, total revenue), operating efficiency (ROA, ROE), intermediate operating efficiency (direct labor productivity, management productivity) Control variables: firm size and company sector Rai et al (1997) found a positive relationship between a company’s productivity and all expenditure measures Additionally, they found a positive relationship between IT capital, server expenses, and ROA Rai et al (1997) conducted a productivity test, and the results indicated that labor productivity is positively associated with IT capital, IT budget, server expenses, IT employee expenses, software expenses, and telecom expenses IT investment positively affects labor productivity directly but negatively affects the productivity of managers The limitation of this study is that it used crosssectional data at one point in time, not multiple time points According to the author's knowledge, there are some studies on the relationship between IT investment and bank performance The author focuses on studies that use the same research method in this research Beccalli (2007) expanded on previous studies on IT investment and performance of 737 banks in Europe (specifically in France, Germany, Italy, Spain, UK) for the period from 1995 to 2000 Independent variables: IT investment in hardware, software, and other IT services Dependent variables: ROA, ROE, costeffectiveness, profit efficiency The author uses methods: OLS regression, two-stage regression (2SLS), and SFA Despite banks being major investors in IT the research finds little relationship between total IT investment and improved bank profitability or efficiency indicating the existence of a profitability paradox The impact of different types of IT investments is heterogeneous: while investments in hardware and software reduce the efficiency of banks, IT services from external providers have a positive effect on ROA, ROE, and profit efficiency This study of the author has overcome some limitations of previous studies by using both a traditional accounting profit measure (ROA, ROE) and a more advanced measure of operational efficiency 1290 called X-efficiency Moreover, the author does not study investment in IT as a single variable like previous studies but has specifically divided it into three components of IT investment namely hardware, software and IT services to consider the IT investment in different areas have different effects on bank performance Karim and Hamdan (2010) studies the impact of IT investment on the performance of 15 Jordanian banks in the period from 2003 to 2007 Independent variables on IT investment in the article include investment in hardware, software, online banking, telephone banking, number of ATMs, use of online branches, and SMS banking Dependent variables include: financial performance such as market value added (MVA), return on investment (ROI), and return per share (EPS), and operating efficiency includes net profit margin (NPM), return on assets (ROA), and employee profitability (PE) Using the regression method, the research results show that IT affects market value added (MVA), return per share (EPS), and return on total assets (ROA) and net profit margin (NMP), but IT has no effect on return on equity (ROE) Kabiru (2012) studies the impact of IT investment on the performance of banks in Nigeria in the period from 2000 to 2010 Independent variables on IT investment include investment in hardware, software, and the number of ATMs The performance-dependent variable is a return on assets (ROA) The study used multivariate regression analysis Research results show that investment in software, investment in hardware, and the number of ATMs have a significant impact on return on assets (ROA) because the t-statistics are all significant at this point percent level Bilkisu and Kabiru (2015) studies the impact of IT investment on the performance of 10 banks in Nigeria in the period from 2006 to 2010 The independent variable of IT investment includes hardware investment, software investment, and ATMs The dependent variables include return on total assets (ROA), return on equity (ROE), net profit margin (NPM), and earnings per share (EPS) The control variables: total revenue (TR) and total cost (TC) Research using regression method, the results show that IT investment has a negative effect on ROA, ROE, and EPS at 5% significance level, but not statistically significant with NPM at 5% and 10% level significance This means that an increase in IT investment leads to a decrease in the performance of Nigerian banks, hence the IT productivity paradox in the Nigerian banking industry Tam (2015) researched the impact of technology investment on the performance of the commercial banking system in Vietnam, thereby assessing the impact of technology investment on banks At the same time, give recommendations to commercial banks on the level of investment in technology to improve the operational efficiency of Vietnamese commercial banks Using the GMM method for 1291 one-year lagged dynamic panel data of 15 commercial banks in Vietnam with data for six years (2009-2014), the study analyzed the impact of IT on ROE and ROA The resulting research showed that when other factors held constant, increasing IT (ratio of technology investment on fixed assets) by 1% will increase ROA (rate of return on total assets) by 10% In addition to IT, the operational efficiency of the commercial banking system in Vietnam was also affected by factors such as the ratio of liquid assets to total assets (liquidity) and macro factors such as economic growth rate (GDP), consumer price index (CPI) and exchange rate change (tygia), but the level of impact of these factors was quite low in the model Many researchers have researched the relationship between IT investment and operational performance However, the research results still lack consistent in research results and the author found that previous studies have the following limitations: - The cross-sectional research designs adopted and the nature of the problem also not make it possible to indicate the causality of any relationship It is conceivable that high performance causes high investment in IS A more historical approach is required that gathers time investment in IT A more historical approach is required that gathers time-series data and presents more cautious conclusions about the relationships involved - The variables chosen to represent IT investment and performance were different - The following three issues remain unresolved: (1) All companies were assumed to convert their IT investments to produce outputs with the same level of success, (2) All IT investments were treated equally, (3) The time lag between investment and performance was ignored The limitations of these prior studies are also the prior research gaps that this paper attempts to fill Our paper, therefore, aims to investigate the existence of the IT profitability paradox for the Vietnam banking industry, and to extend and integrate the above IT literature by focusing on the traditional profitability measures derived from the banking literature Methodology 3.1 Methodology The study uses a regression method to examine the relationship between IT investment and performance of Vietnamese commercial banks whether it follows the productivity paradox The author uses a model to analyze the relationship between IT investments and performance according to Strassmann (1990), Beccalli (2007) as follows: Pt = β0 + βtITt + Ɛt 1292 where: Pt: annual accounting performance ratios; ITt: IT capital investment or IT ratios (IT to various size measures); Ɛt: error term Each variable refers to the banking industry at time t It should be noted that the performance measure used in these models refers to financial profitability Two measures of bank performance have been employed here: 1- ROA, which measures how effectively a bank utilizes its assets to earn income 2- ROE, which provides a measure – increasingly examined by managers – of how well the bank is managing resources invested by shareholders In this research, similar to Beccalli's (2007) study, the author does not use only one overall IT variable, but the author will divide the IT variable into four component variables: technical infrastructure (TI), human resource infrastructure (HR), banking internal IT application (IA) and online banking services (OS) where: - Technical infrastructure (TI) is an average variable from indicators: Server and workstation infrastructure; Communication infrastructure, ATM/POS infrastructure; Deploying information security and data safety solutions; Datacenter and disaster recovery center - Human resource infrastructure (HR) is an average variable from indicators: Percentage of staff specialized in IT, Percentage of staff in charge of information security, Percentage of IT professionals with international information technology certificates/Total number of specialized IT staff - Bank's internal IT application (IA) is an average variable from indicators: deploy Core banking, deploy basic applications, deploy electronic payments - Online banking service (OS) is an average variable from indicators: website of the bank, internet banking for individual customers, internet banking for corporate customers, other e-banking services, other e-banking services The author chooses such IT investment variables to overcome two limitations in previous studies First, the previous studies assumed that all firms are converting their IT investments into outputs with the same degree of success (Huang, 2002) Previous studies were based on data on IT investment costs, but the results of the IT investment process could not be clarified Therefore, the use of IT investment performance indicators will overcome this limitation These are the general indicators developed by the Ministry of Information and Communications of Vietnam for the general assessment of commercial banks, so the indicators are comprehensive in terms of IT aspects and are quite reliable Second, many previous studies assume that all investments in IT are treated equally by using only one aggregate IT variable 1293 (Huang, 2002) In the study, the author uses four IT variables namely technical infrastructure, IT human resource infrastructure, banking internal IT application, and banking online services, so the specific impact of each type of IT investment will be measured on bank performance To consider the impact on the performance of the various categories of IT investments, the estimated equation is: Pt = β0 + βtTIt + βtHRt + βtIAt + βtOSt +Ɛt Where: TIt= Technical infrastructure; HRt= Human resource infrastructure; IAt= Bank's internal IT application; OSt= Online banking service Through the overview literature, the author adds some control variables including: a loan to total assets ratio (LOTA) (Isik and Hassan, 2003), equity to total assets (ETA) (Berger and DeYoung, 1997), the bank’s total asset to total assets of the bank industry over the same period (MARK) (Isik and Hassan, 2003), Deposit to loan (DLR) (Hung, 2008) 3.2 Data sources Research using the information on IT investment in banks in terms of technical infrastructure, human infrastructure, internal banking IT application, and banking online services from Vietnam IT index report as well as data from financial statements of 30 commercial banks for the period from 2016 to 2020 After excluding some banks that not participate in the Vietnam ICT index report and some banks that not disclose financial statement information, we have data include 138 observations presented in Table Table 1: The banks list during 2016 -2020 No Bank Code Observations Tien Phong Commercial Joint Stock Bank TBP Nam A Comercial Join Stock Bank NAB JSC Bank for Investment and Development of Vietnam BID VietNam Technological and Commercial Joint Stock Bank TCB 5 Military Commercial Joint Stock Bank MBB JSC Bank for Foreign Trade of Vietnam VCB Vietnam Thuong Tin Commercial Joint Stock Bank VBB Orient Commercial Joint Stock Bank OCB Sai Gon Joint Stock Commercial Bank SCB 1294 No Bank Code Observations 10 Sai Gon Thuong Tin Commercial Joint Stock Bank STB 11 Ho Chi Minh City Housing Development Bank HDB 12 Bac A Commercial Joint Stock Bank BAB 13 Southeast Asia Commercial Joint Stock Bank SSB 14 An Binh Commercial Joint Stock Bank ABB 15 Vietnam Prosperity Joint Stock Commercial Bank VPB 16 Kien Long Commercial Joint Stock Bank KLB 17 Vietnam International and Commercial Joint Stock Bank VIB 18 Vietnam Maritime Joint – Stock Commercial Bank MSB 19 Vietcapital Commercial Joint Stock Bank BVB 20 Joint Stock Commercia Petrolimex Bank PGB 21 Vietnam Bank for Agriculture and Rural Development AGB 22 Saigon – Hanoi Commercial Joint Stock Bank SHB 23 Asia Commercial Joint Stock Bank ACB 24 Vietnam Asia Commercial Joint Stock Bank VAB 25 Vietnam Public Joint Stock Commercial Bank PVB 26 Saigon Bank for Industry and Trade SGB 27 Vietnam Export Import Bank EIB 28 Vietnam Joint Stock Commercial Bank for Industry and Trade CTG 29 Bao Viet Joint Stock Commercial Bank BAO 30 National Citizen Commercial Joint Stock Bank NCB The study used STATA software to conduct correlation analysis between variables, build regression models, and test models The research study explains the level of impact of the independent variable on the dependent variable Finally, a predictive model from the research sample is given Empirical results The descriptive statistics of the independent and dependent variables shown in Table show the mean, standard deviation, maximum and minimum values of the variables The results show that the outliers were removed from the study sample 1295 Table 2: Descriptive statistics of variables Variables Code Mean Std.Dev Min Max Technical infrastructure TI 0.4583 0.1198 0.1535 0.7586 Human resource infrastructure HR 0.3876 0.2376 0.0000 1.0000 Bank's internal IT application IA 0.4913 0.2174 0.0000 1.0000 Online banking service OS 0.5809 0.1949 0.0150 1.0000 Loan to total assets ratio LOTA 0.6205 0.0923 0.3539 0.8006 Equity to total assets ETA 0.0770 0.0292 0.0262 0.1845 The bank’s total asset to total MARK 0.0362 assets of the bank industry over the same period 0.0425 0.0021 0.1479 Deposit to Loan DLR 1.1362 0.17098 0.7311 1.7231 Return on Asset ROA 0.0078 0.0068 0.0001 0.0286 Return on Equity ROE 0.0991 0.0715 0.0008 0.2583 Next, the study will test to assess whether the fixed effects model (FEM) or the random effects model (REM) is a suitable model for measuring the impact of IT investment on bank performance If the residuals and the independent variables not correlate with each other, choose the random-effects model (REM) and vice versa, choose the fixed effects model (FEM) The Hausman test is performed with the following hypothesis: H0: The REM model is the suitable model H1: The FEM model is the suitable model With the results of running the Hausman test according to Table 3, prob = 0.3272 < 0.05, so the hypothesis H0 is accepted, so the random effects model (REM) is suitable Table 3: The results of Hausman test Chi2(8) = 9.18 Prob > chi2 = 0,3272 1296 Sqrt (Diag (V_bV_B)) (b) (B) (b-B) Fem Rem Difference TI 0079514 0081922 -.0002408 0002149 HR 0031575 0022171 0009405 0006271 IA -.0025848 -.0024459 -.0001389 000206 S.E Sqrt (Diag (V_bV_B)) (b) (B) (b-B) Fem Rem Difference OS 0036122 0042793 -.0006671 00032 LOTA 0003739 -.0077944 0081683 0056112 ETA 0907751 0935383 -.0027631 0082505 MARK 0837439 0417718 0419721 0825756 DLR -.0105884 -.013843 0032546 0019444 S.E The results of the regression according to the random effects model (REM) are shown in Table Table 4: The regressions according to the random effects model (REM) Variables ROA ROE Coef (P>|t|) (Coef.) (P>|t|) TI 0.0082* 0.000 0.0778* 0.011 HR 0.0022*** 0.060 0.0197 0.231 IA -0.0024*** 0.091 -0.0355*** 0.083 OS 0.0043* 0.000 0.0507** 0.002 LOTA -0.0078 0.419 -0.0073 0.951 ETA 0.0935 0.000 -0.1475 0.577 MARK 0.0418 0.048 0.4403 0.111 DLR -0.0138 0.000 -0.1489 0.001 _cons 0.0136 0.161 0.2114 0.091 Observations 138 138 R-Squared 48.76% 36.82% Wald chi2(8) 145.56 73.32 p-value 0.0000 0.0000 Note: *, **, *** means statistically significant at the 1%, 5% and 10% The regression results according to REM are shown in Table First, there is a positive and statistically significant correlation between technical infrastructure (TI), online banking services (OS), and ROA at 1% statistically significant; human resource infrastructure (HR) and ROA at 10% statistically significant Meanwhile, there is a positive and statistically significant correlation between Bank's internal IT application (IA) and ROA at 10% statistically significant 1297 Similar results, there are three independent variables about IT, namely technical infrastructure (TI) and online banking services (OS), with p_value < 0.01 and p_value < 0.05, showing that these variables are statistically significant at the level of significance at 1% and 5% having a positive impact on the dependent variable ROE There is another independent variable, which is the online banking services, with p_value < 0.1, showing that this variable has statistical significance at the 10% significance level, the sign of the regression coefficients has a positive sign The human resource infrastructure (HR) variable had a negative impact on ROE but there is no statistical significance From the table of regression results, the study identifies a regression model that reflects the level of factors to the performance of Vietnamese commercial banks ROA = 0.0136 + 0.0082 TI + 0.0022HR – 0.0024IA + 0.0043OS – 0.0078LOTA + 0.0935 ETA + 0.0418 MARK - 0.0138 DLR (1) ROE = 0.2114 + 0.0778 TI + 0.0197HR – 0.0355IA + 0.0507OS – 0.0073LOTA - 0.1475 ETA + 0.4403MARK - 0.13489 DLR (2) From the regression equation (1), it shows that if other factors are constant, IT infrastructure increases by 1%, ROA will increase by 0.79%; internal IT applications increased by 1%, ROA decreased by 0.24%; Online banking services increased by 1%, ROA increased by 0.37% and IT personnel increased by 1%, ROA increased by 0.31% This result shows that IT variables such as IT technical infrastructure, Online banking service, and IT human resources have a positive influence on ROA and these variables are statistically significant That is, the investment of the bank's resources in these variables will increase the bank's performance Meanwhile, the internal IT application variable has a negative effect on ROA, the investment in IT internal application will reduce ROA due to the effect of the productivity paradox From the regression equation (2), it shows that if other factors are constant, IT infrastructure will increase by 1%, ROE will increase by 7.69%; internal IT applications increased by 1%, ROE decreased by 3.83%; Online banking services increased by 1%, ROE increased by 4.27% and IT personnel increased by 1%, ROE increased by 3.68% This result shows that IT variables such as IT technical infrastructure, Online banking service, and IT human resources have a positive influence on ROE and these variables are statistically significant That is, the investment of the bank's resources in these variables will increase the bank's operational efficiency Meanwhile, the variable IT internal application has a negative effect on ROE, the investment in IT internal application will reduce ROE due to the effect of the productivity paradox 1298 Conclusions This study aims to analyze the influence of IT investment on the performance (ROA, ROE) of Vietnamese commercial banks The research results show that three IT factors, namely IT technical infrastructure, online banking services, and IT human resource infrastructure, have an influence on ROA and ROE with statistical significance of 1%, 5%, and 10%, respectively The sign of the regression coefficients has a positive sign, showing a positive relationship between IT investment and ROA and ROE in Vietnamese commercial banks Only one IT factor, which is an internal application of banking IT, does not affect ROE and affects ROA with a statistical significance of 10% The sign of the regression coefficient has a negative sign, showing that there is a negative relationship between bank IT internal application and ROA, ROE There is exists a productivity paradox between investment in banking IT internal application and performance Based on these results, the author makes recommendations for banks to promote investment in IT in the aspects of IT technical infrastructure, banking online services, and IT human resource infrastructure because it increases performance However, it is necessary to study and consider carefully the investment in the internal application of banking IT because there is a productivity paradox, the investment in the internal application of banking IT can reduce ROA and ROE References Ali, B.J., Bakar, R and Omar, W.A.W (2016), ‘The critical success factors of accounting information system (AIS) and its impact on organizational performance of Jordanian commercial banks’, International Journal of Economics, Commerce and Management, 4(4), 658-677 Alves, M.C.G (2010), ‘Information technology roles in accounting tasks: A multiple case study’, International Journal of Trade, Economics and Finance, 1(1), 103-106 Barua, A., Kriebel, C.H and Mukhopadhyay, T (1995), ‘Information technologies and business value: An analytic and empirical investigation’, Information Systems Research, 6(1), 3-23 Brynjolfsson, E (1993), ‘The productivity paradox of information technology,’ Association for Computing Machinery, Communications of the ACM, 36(12), 67-78 Brynjolfsson, E (1995), Some Estimates of the Contribution of Report, Center for Coordinating Science, Sloan School of Management, MIT, Cambridge, MA Brynjolfsson, E and Hitt, L (1993), ‘Is information systems spending productive? 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OF INFORMATION TECHNOLOGY ON IMPROVING BANKING PERFORMANCE: EVIDENCE FROM VIETNAM 1287 Vu Thi Huyen Trang Thuy Loi University THE IMPACT OF INFORMATION TECHNOLOGY ON IMPROVING BANKING PERFORMANCE: ... the emerging country of Vietnam Our study is therefore devoted to examining the following key question: What is the impact of information technology on the performance of Vietnam commercial banks?... infrastructure, banking internal IT application, and banking online services, so the specific impact of each type of IT investment will be measured on bank performance To consider the impact on the performance