Factors affecting financial performance of information technology enterprises listed on the vietnam stock exchange

Model to evaluate factors affecting financial performance of Information and Technology enterprises in Vietnam in the period 2017-2022...38 3.2.1... Tables Table 1: Some studies on fina

BANKING ACADEMY ADVANCED PROGRAM FACULTY OF FINANCE

GRADUATION THESIS

FACTORS AFFECTING FINANCIAL PERFORMANCE OF INFORMATION TECHNOLOGY ENTERPRISES LISTED

ON THE VIETNAM STOCK EXCHANGE

Supervisor : PhD Tran Thi Thu Huong Class : K23CLC - TCB

Student : Nguyen Thi Phuong Thao Student ID : 23A4050332

Hanoi, May, 2024

DECLARATION

I hereby declare that this is my own research project, with support from my

instructor, Dr Tran Thi Thu Huong The research content and results in this topic are

honest and have never been published in any previous research work The data in the

tables for analysis, comments, and evaluation were collected by the author from

various sources listed in the reference section

If any fraud is discovered, I will be fully responsible to the Council as well as

the results of my thesis

Student

Thao Nguyen Thi Phuong Thảo

DEDICATION

First of all, I would like to send my sincere thanks to all the teachers at the

Banking Academy in general and the teachers in the Department of Finance in

particular for always being enthusiastic and dedicated to teaching students useful

knowledge and experience so that we can complete the bachelor's training program at

the Banking Academy

Furthermore, the practical experiences imparted by the teachers during the

classroom teaching process are useful lessons for me that I can apply during my

internship and future work I would also like to send special thanks to Ms Tran Thi

Thu Huong, who directly guided and supported me during the process of writing my

graduation thesis Thanks to her dedicated guidance, I was able to complete my thesis

in the most complete way

Thank you sincerely!

Student

Thao Nguyen Thi Phuong Thao

TABLE OF CONTENTS

CHAPTER 1: THEORETICAL BASIS FOR FACTORS AFFECTING FIRM’S

FINANCIAL PERFORMANCE AND LITERATURE REVIEW………4

1.1 Overview of financial performance 4

1.1.1 Concept of efficiency (performance) and financial performance 4

1.1.2 Financial performance measures 5

1.2 Factors affecting financial performance 8

1.2.1 Capital structure 8

1.2.2 Firm’s size 9

1.2.3 Firm’s growth rate 12

1.2.4 Firm’s operation year 13

1.3 Literature review: factors affecting financial performances 14

1.3.1 Foreign researches 14

1.3.1.1 Studies about firm’s financial performance 14

1.3.1.2 Studies about Information and Technology firms 15

1.3.1.3 Studies about factors affecting firms’ financial performance 16

1.3.2 Domestic researches 17

1.3.2.1 Studies about firm’s financial performance 17

1.3.1.2 Studies about Information and Technology firms 17

1.3.1.3 Studies about factors affecting firms’ financial performance 18

1.3.3 Research gap 19

CHAPTER 2 RESEARCH METHOD AND MODEL 21

2.1 Research methods 21

2.1.1 Qualitative method 21

2.1.2 Quantitative method 21

2.2 Research model 24

2.3 Research variables and hypotheses 25

2.4 Data 27

CHAPTER 3: ASSESSING FACTORS AFFECTING FINANCIAL PERFORMANCE OF INFORMATION AND TECHNOLOGY ENTERPRISES IN VIETNAM IN THE PERIOD 2017-2022 29

3.1 Current status of financial performance of IT enterprises in Vietnam 29

3.1.1 Overview of the IT industry in Vietnam 29

3.1.2 Current status of financial performance of IT enterprises in Vietnam in the period 2017-2022 36

3.2 Model to evaluate factors affecting financial performance of Information and Technology enterprises in Vietnam in the period 2017-2022 38

3.2.1 Descriptive statistics 38

3.2.2 Analyze correlation of variables in the model 42

3.2.3 Check for multicollinearity 43

3.2.4 Model results 44

3.2.5 Discuss the results of the model 53

CHAPTER 4: CONCLUSION AND RECOMMENDATIONS 57

4.1 Conclusion 57

4.1.1 Research summary 57

4.1.2 Research results 58

4.1.3 Research limitation 59

4.2 Recommendations for businesses, government and further researches 59

4.2.1 Recommendations for businesses 59

4.2.2 Recommendations for the government 61

4.2.3 Recommendations for further researches 63

REFERENCES 64

ADDENDUM 65

LIST OF ABBREVIATIONS

ICT Electronics - information technology -

communications industry

LIST OF TABLES

1 Tables

Table 1: Some studies on financial performance

Table 2: Some studies on company size

Table 3: Description of variables in the analysis

Table 4: Expected signs of variables in the model

Table 5: Statistics describe the variables used in the model

Table 6: Correlation between variables in the model

Table 7: Multicollinearity results

Table 8: Regression model results: ROA

Table 9: Regression model results: ROE

Table 10: Regression model results: ROS

Table 11: F-test result

Table 12: Hausman test result

Table 13: REM model result

Table 14: Heteroscedasticity test

Table 15: Autocorrelation test

Table 16: GLS model result

Table 17: GLS model result and expectation

Table 18: List of Information Technology enterprises listed on the stock exchange in Vietnam (2024)

2 Pictures

Picture 1: Implementation steps of quantitative method

Picture 2: Proposed model

Picture 3: Comparision between growth rate of GDP and ICT industry

Picture 4: Number of ICT firms 2017-2023

Picture 5: Chart comparing innovation capacity and information security level of ASEAN countries

Picture 6: Lack of human resources in IT industry

Picture 7: ICT industry revenue and growth

Picture 8: ROA – ROE – ROS of information and technology firms in vietnam 2022)

(2017-INTRODUCTION

1 Rationale

To survive and develop, businesses always need to improve the efficiency of their business operations Researching factors affecting firm financial performance is crucial due to its direct impact on the sustainability and competitiveness of businesses Understanding these factors allows firms to make informed strategic decisions, allocate resources effectively, and mitigate risks By identifying key drivers of financial performance, businesses can optimize their operations, enhance profitability, and maintain investor confidence Moreover, in a dynamic and competitive business environment, continuous research helps firms stay adaptive and responsive to changing market conditions, regulatory requirements, and technological advancements Ultimately, the urgency of researching factors affecting firm financial performance lies in its potential to drive long-term growth, resilience, and value creation for stakeholders

In the digital era, the information technology (IT) industry has become a key industry, guiding the development of each country Even during the extremely difficult time of the Covid-19 pandemic, IT in the world and in Vietnam has made great breakthroughs During the outbreak of the pandemic, in-person learning and working conditions were extremely limited, online working and learning methods have become an inevitable trend Since then, IT has further affirmed its leading position, meeting the transformation needs of all other professions in difficult times

In Vietnam, promoting the development of IT is one of the top goals How to promote growth in the IT industry is indeed an urgent issue that needs attention and development

However, numerous challenges and opportunities have emerged during this period, for instant economic growth, globalization, technological advancements,

policy and regulatory environment, infrastructure and connectivity, human capital and talent acquisition, and especially the fierce competition of businesses in the industry These challenges and opportunities require a comprehensive understanding of the factors affecting IT enterprise performance

Given the dynamic nature of the IT industry and the rapidly evolving business environment in Vietnam, understanding the factors affecting the performance of IT enterprises is crucial for policymakers, industry stakeholders, and investors Addressing these factors effectively can unlock the full potential of the IT industry, drive sustainable growth, and enhance Vietnam's position in the global digital economy Stemming from the importance and necessity of understanding the factors

that affect financial performance, the author chose the topic “Factors affecting

financial performance of Information Technology enterprises listed on the Vietnam stock exchange” for research

2 Aims of the thesis

 General goal: Study factors affecting financial performance of Information

and Technology firms

 Specific goals: Based on the theoretical basis, using research methods and

inheritance from previous studies, generalize and describe the factors affecting the financial performance of enterprises in the Information Technology industry in Vietnam, thereby offering a number of solutions to improve financial efficiency of enterprises in the Information Technology industry

3 Subject and scope of the thesis

Research subject

Factors affecting financial performance of Information Technology companies listed on the Vietnam stock market

Research scope

 Time scope: Within 6 years, from 2017 to 2022

 Spatial scope: 28 Information Technology companies listed on the Vietnam stock market

4 Research methods

The research method includes collecting data from financial reports of businesses in the period 2017 - 2022 The research was conducted using a quantitative method, through statistical methods such as descriptive statistics and modeling to determine the relationship between variables Moreover, the author uses appropriate research methods such as multivariate regression analysis, and other methods to draw appropriate conclusions and recommendations

5 Structure of the thesis

The thesis is divided into 4 chapters as follows:

Chapter I: Theoretical basis for firm performance and factors affecting financial performance

Chapter II: Research method and model

Chapter III: Assessing factors affecting business performance of IT enterprises in Vietnam in the period 2017-2022

Chapter IV: Conclusion and recommendations

CHAPTER 1: THEORETICAL BASIS FOR FACTORS AFFECTING FIRM’S FINANCIAL PERFORMANCE AND LITERATURE REVIEW 1.1 Overview of financial performance

1.1.1 Concept of efficiency (performance) and financial performance

1.1.1.1 The concept of efficiency

Efficiency is the desired result, which produces the results that people expect and aim for; it has different content in different areas In manufacturing, efficiency means efficiency and productivity In business, efficiency is interest rate and profit

In labor in general, efficiency is labor productivity, evaluated by the amount of time spent producing a unit of product, or by the number of products produced in a unit of time (Pham, 2022)

1.1.1.2 The concept of financial performance

First of all, the essence of financial performance is the business performance

of an enterprise Business efficiency of an enterprise is a comprehensive economic indicator that reflects the level of use of factors in the production process Business efficiency also demonstrates the skillful application of business managers between theory and reality to maximize the exploitation of factors in the production process such as machinery, equipment, raw materials, and labor to increase profits So business efficiency is an aggregate economic expenditure that reflects the level of use

of physical resources; business finances to achieve the highest efficiency (Nguyen, 2013)

The essence of financial performance is the comparison between output results and input factors of a business in a certain period, depending on the requirements of business administrators If H is called financial efficiency (business efficiency), then

H is expressed according to the following mathematical formula:

H = 𝑶𝒖𝒕𝒑𝒖𝒕 𝒓𝒆𝒔𝒖𝒍𝒕

𝑰𝒏𝒑𝒖𝒕𝒔

The above formula reflects how many units of output such as revenue and profit are created for each unit of input costs (capital, labor, raw materials, machinery and equipment ) In a business period, the higher this indicator, the better the financial performance of the business

In this thesis topic, the author will present previous research on metrics to measure financial performance, thereby stating the metrics that will be used in the research and analysis process Below are some studies on measuring the financial performance of businesses

1.1.2 Financial performance measures

Table 1: Some studies on financial performance

Dividend yield (DY) Ming et al (2008)

Ongore (2011)

Return on assets (ROA) Hu et al (2008)

Return on equity (ROE) Hu et al (2008)

Return on sales (ROS) Le et al (2011)

Jenkins et al (2011)

Return on investment (ROI) Shah et al (2011)

Market value coefficient (Marris

and Tobin’s Q)

Tian et al (2008)

(Source: Author compiled from previous studies)

First of all, which metrics to use to evaluate corporate financial performance plays a very important role There are many indicators to measure corporate financial performance, but the most commonly used indicators in research can be divided into two main categories: accounting value coefficients, also known as coefficients on profits and market value coefficients, also known as asset growth coefficients

According to Hu et al (2008), the most commonly used profit metrics include return

on assets (ROA) and return on equity (ROE) In addition, two studies by Ming et al (2008) and Ongore (2011) also use the dividend yield index (DY), the study by Le et

al (2011) uses the ratio of profit on revenue (ROS), or Shah et al (2011), they used the ratio of return on investment (ROI) to measure the financial performance of businesses

For the market value coefficient group, according to research by Tian et al (2008), two coefficients Marris and Tobin's Q are also used to evaluate corporate financial performance In which the Marris coefficient is calculated as the total market value of equity compared to the book value of equity, and the Tobin's Q coefficient is calculated as the market value of equity plus the book value of liabilities compared to book value of total assets However, these coefficients only evaluate the effectiveness

of State ownership capital, because it only directly reflects the level of growth in equity value in the enterprise capital structure

In general, ROS, ROA, ROE are the three most commonly used metrics in evaluating the financial performance of businesses In this thesis, the author will use the above three indicators to evaluate the financial performance of information technology enterprises listed on the Vietnamese stock market because these indicators

can reflect the past perspectives, show how the business is doing, and the ability to generate profits that companies have achieved in recent accounting periods Not only that, these indicators also help us have an easy way to compare businesses in the same industry Besides, the combination of these three groups of coefficients can provide managers, company leaders, shareholders and the market with comprehensive assessments of past and potential financial performance, future profits and growth of the business

1.1.2.1 Return on sales (ROS)

A business's ability to generate revenue is a long-term strategy that determines profits and improves business and financial performance But the ultimate goal of the administrator is not revenue but profit after tax Therefore, to increase profit after tax,

it is necessary to maintain the growth rate of revenue faster than the growth rate of costs, then there will be sustainable growth On the other hand, this indicator also shows the level of cost control of administrators to increase competition in the market This indicator is determined as follows:

ROS = 𝑷𝒓𝒐𝒇𝒊𝒕 𝒂𝒇𝒕𝒆𝒓 𝒕𝒂𝒙

𝑵𝒆𝒕 𝑹𝒆𝒗𝒆𝒏𝒖𝒆

This target shows that in an analysis period, if a business receives 1 dong of net revenue, how much profit it will earn after corporate income tax The higher this indicator proves the effective use of port costs, the higher the financial efficiency achieved That is a factor that helps administrators expand markets and increase revenue The lower this indicator is, the lower the financial efficiency achieved, so administrators need to strengthen cost control of departments

1.1.2.2 Return on Asset (ROA)

In the process of conducting business activities, businesses want to expand production scale and consumption markets to grow strongly and improve financial efficiency Therefore, market administrators often evaluate the efficiency of using invested assets, determined by the formula:

ROA = 𝑷𝒓𝒐𝒇𝒊𝒕 𝒂𝒇𝒕𝒆𝒓 𝒕𝒂𝒙

𝑻𝒐𝒕𝒂𝒍 𝒂𝒔𝒔𝒆𝒕𝒔

This expense shows that in an analysis period, for 1 VND of total assets invested, a business will earn how many VND in after-tax profit The higher this indicator shows the better the efficiency of asset use, the higher the financial efficiency achieved and vice versa

1.1.2.3 Return on equity (ROE)

The ability to generate profits from the equity that an enterprise uses for business activities is the goal of every administrator This target is determined as follows:

ROE = 𝑷𝒓𝒐𝒇𝒊𝒕 𝒂𝒇𝒕𝒆𝒓 𝒕𝒂𝒙

𝑻𝒐𝒕𝒂𝒍 𝒆𝒒𝒖𝒊𝒕𝒚

This indicator shows that in an analysis period, a business that invests 1 dong

of equity will earn how much profit after corporate income tax The higher this expenditure proves that the efficiency of using equity capital and the financial efficiency of the business is good, contributing to improving the investment ability of the business owner and vice versa That is also a factor that helps administrators increase equity for business activities and financial investments

1.2 Factors affecting financial performance

1.2.1 Capital structure

The capital structure of a business, which refers to the mix of debt and equity financing used to fund its operations, has a significant impact on its overall financial

health and performance A well-balanced capital structure can optimize the cost of capital, maximizing shareholder returns while minimizing financial risk High levels

of debt can increase financial leverage, potentially magnifying returns but also amplifying the risk of financial distress, especially during economic downturns On the other hand, relying too heavily on equity financing can dilute ownership and reduce earnings per share, affecting investor perceptions and stock valuation Striking the right balance in the capital structure is essential for ensuring financial stability, flexibility, and long-term sustainability for the business

Capital structure has been proven to affect financial performance of enterprises Several studies have explored the relationship between capital structure and financial performance

Prekazi (2023) measured the impact of the capital structure on the financial performance of commercial companies in Kosovo and found that there is a strong relationship between assets on the one hand and total capital and total liabilities on the other Dodoo (2023) concluded that capital structure, particularly short-term and long-term debt, negatively impacts firm performance in emerging economies like Ghana, as shown by the study on non-financial firms from 2008-2017 Khan (2012) studied the relationship between capital structure decisions and firm performance in the engineering sector of Pakistan, noting the dependence on short-term debt and its impact on firm performance Zeitun and Tian (2014) showed that debt ratio has the strongest negative influence while growth in total assets, size and tax ratio have a positive influence on ROA In the study of Onaolapo and Kajola (2010), debt ratio and fixed asset ratio have a negative effect on both ROA and ROE, whereas asset turnover has a positive effect on these indicators

1.2.2 Firm’s size

Table 2: Some studies on company size

Measure Studies

Simerly and Li (2000) Athanasoglou et al (2005) Papadognas (2007)

Amato and Burson (2007) Falope and Ajilore (2009) Amarjit et al (2010) Dr.Amal et al (2012)

(Source: Author compiled from previous studies)

Size is considered the first sign for investors to know about the company A large-scale company will have a more competitive advantage in the market Therefore, most companies aim to expand their size to take advantage of large scale advantages In Vietnam, large-scale listed enterprises are often enterprises with controlling shares held by the state, so these enterprises have more opportunities to mobilize capital from outside sources, especially State-owned credit institutions

There are many previous studies investigating the relationship between size and financial performance of the company Through these studies, the author has drawn two opposing theories about the relationship between scale and financial performance of companies

First, the company's size and financial performance have a positive relationship with each other According to the conclusion of Simerly & Li (2000), previous financial studies have shown that company size can predict future stock prices, which is why business management is easier and takes preventive measures to reduce risks for the company, thereby achieving better financial performance According to Flamini et al (2009), larger companies have higher competitiveness than smaller companies in doing business in the market and achieving higher profits Another study by Athanasoglou et al (2005) showed that scale expansion helps improve the financial efficiency of banks Papadognas (2017) conducted a financial performance analysis on a sample of 3,035 businesses in Greece that showed profits were influenced by company size Amato et al (2007) examined the relationship between size and profitability for firms operating in the financial services sector With linear analytical specifications in the firm model, the authors show that small size has

a negative effect on firm profitability In Vietnam, research on the financial performance of coconut fiber processing facilities in Tra Vinh province by Truong et

al (2015) showed that ROE is positively correlated with scale, specifically ROE will increase to 0.007% when muscle The facility employs an additional employee In addition, research by Doan Ngoc Phi Anh (2010) used a measure of total revenue to measure the scale of 428 enterprises listed on the Vietnam stock market, the results showed that scale has a positive impact on financial structure and financial performance of these enterprises

Second, the size and financial performance of the company are not related to each other as research by Amarjit et al (2010) shows that there is no relationship between business size and profit margin Research by Falope et al (2009) using a sample of 50 companies listed on the stock exchange in Nigeria also showed that there was no significant change in financial performance in capital management or scale expansion between large and small businesses Do (2011) came to a conclusion that size of businesses does not have an impact on financial performance, the reason is

that for large-scale businesses, profits will increase but the increase in profits is not large enough, leading to the profit ratio on total assets not increasing or insignificant increase Thus, even large-scale businesses are not necessarily more efficient than smaller-scale businesses

1.2.3 Firm’s growth rate

The growth rate of a business plays a pivotal role in shaping its financial performance and overall success Rapid growth can lead to increased revenue, market share expansion, and enhanced profitability, bolstering the firm's financial position However, sustaining high growth rates may require substantial investments in resources, infrastructure, and talent, which can strain cash flow and profitability in the short term Additionally, rapid growth can pose operational challenges, such as scalability issues, supply chain disruptions, and heightened competition, impacting efficiency and margins Conversely, slow or stagnant growth may signal market saturation, lack of innovation, or ineffective strategic execution, resulting in stagnating revenues and declining profitability over time

The relationship between firms’ growth rate and their financial performance has been shown in multiple studies Finally, two opposing views are raised

The first side believes that growth rate has a positive impact on the financial performance of the business Sawarni et al (2023) shows that firms growing at a high rate manage working capital more efficiently, positively impacting financial performance, with a stronger effect on highly growing firms compared to low-growth firms Heck (2023) concluded that Company growth has a positive but insignificant effect on financial performance in Indonesian automotive firms, as per the study's findings

The other side has the view that growth has a negative impact on the financial performance of businesses Pernille (2012) found that high initial growth negatively affects a firm's long-term survival and performance when using the Danish Integrated

Database for Labour Market Research Melinda (2023) stated that the growth rate of

a company has a negative effect on firm performance by using a simple regression model analysis to obtain empirical evidence regarding the factors that influence company performance Onyekwelu et al (2018) assumed that firms' growth indicators like size and profitability have a significant negative effect on Return on Assets, impacting financial performance in selected Nigerian firms

1.2.4 Firm’s operation year

Operating time can also be considered as one of the factors that can affect the financial performance of a business In this thesis, operating time is calculated from the time the business was established until the present Considering that the relationship between operating time and financial performance seems to be related in both theory and practice, there are two opposing views surrounding this issue

The first view is that if financial performance decreases the longer a business operates, there is a negative relationship between operating time and financial performance (Loderer et al., 2009) Uptime can really help businesses operate more efficiently However, some businesses that have been operating for too long can easily follow a rut, have difficulty adapting to changes in the business environment, and have poor ability and skills to grasp trends, causing their operations to decline Business activity declines and growth slows, thereby negatively affecting financial performance (Agarwal and Gort, 2002) Research by Sorensen & Stuart (2000) also suggests that when companies have been operating for a long time, organizational inertia within the company tends to make the operating system less flexible and impossible to accurately evaluate exactly when the economic environment is highly volatile

In contrast to the above view, the second view is that operating time and financial performance of an enterprise have a positive relationship Research by Liargovas and Skandalis (2008) suggests that larger companies will be highly skilled

because they have long-term experience and often these companies will have less debt

to pay, so the financial efficiency achieved will be higher than smaller businesses In Malik's (2011) study of companies in Pakistan, he found that the relationship between the size and age of companies and their financial performance is proportional to each other

In general, through past studies, the author hypothesizes that operating time and financial performance of companies have an unclear relationship, it can be in the same or opposite direction

1.3 Literature review: factors affecting financial performances

1.3.1 Foreign researches

1.3.1.1 Studies about firm’s financial performance

There are several studies about financial performance of firms in various contexts Pertiwi et al (2011) found that financial performance, measured by Return

on Assets (ROA), significantly influences the value of firms, while Good Corporate Governance did not moderate this relationship Wagner et al (2012) focused on supply chain fit and financial performance, revealing that a higher supply chain fit leads to higher ROA, with firms experiencing a negative misfit showing lower performance Guo et al (2012) examined corporate governance structures and firm performance in Sri Lanka, using multiple regression analysis to determine the impact

of existing mechanisms on firm performance In a study by Wang et al (2014), the impact of knowledge sharing on firm performance was investigated, with explicit knowledge sharing having a greater effect on financial performance than operational performance Feng et al (2017) delved into the relationship between Corporate Social Responsibility (CSR) and firm financial performance across industries and CSR categories, highlighting the differentiated influences of CSR practices on financial performance Kim et al (2018) provided a competitive-action perspective on the

relationship between CSR activities and firm financial performance, emphasizing the importance of considering competitive action as a contingency factor Le et al (2018) explored the impact of working capital management on financial performance, finding a positive relationship between the two Tihanyi et al (2019) analyzed the effects of state ownership and political connections on firm strategies and financial performance, revealing a small negative effect of state ownership on financial performance Lastly, Santosa et al (2020) examined the relationship between financial performance, firm value, and dividend policy in large Indonesian firms, concluding that financial performance has a significant influence on firm value, with less effect on dividend policy These studies collectively contribute to the understanding of the complex dynamics between financial performance and firm value in different organizational contexts

1.3.1.2 Studies about Information and Technology firms

Goswami et al (2022) explores technological efforts, firm ownership, and productivity in Indian IT service firms from 2000 to 2016, highlighting the impact of technology on firm productivity In this paper, the authors present differences in firm-level total factor productivity in the information technology (IT) service firms in India over the period 2000-2016, in conjunction with several other firm specific characteristics Amar (2021) shows how Information Technology firms can optimize revenue growth and performance through strategic capital allocation, focusing on R&D, capital expenditure, and operational expenses across different industries In this article, the authors employ multivariate data analysis techniques to identify and confirm the management decisions that could become the growth drivers, such as the allocations for research & development, capital expenditure, selling, general and administrative expenses, and property, plant and equipment Emmanuel et al (2023) assessed the influence of strategic management on the operational performance of IT firms in Nigeria and concluded that the presence of a sound SM would guarantee the improved operational performance Malik (2013) showed qualitative case study

evidence from four information technology (IT) enabled organizations in India was used to investigate the role of external business networks and the institutional ecosystems in fostering an organization's innovative capacity

1.3.1.3 Studies about factors affecting firms’ financial performance

Several studies have explored the various factors that can influence firms' financial performance Liao (2006) examined how corporate controls within conglomerates can impact subsidiaries' human resource management control and subsequent performance Soch et al (2008) focused on Customer Relationship Management (CRM) activities and their effects on firm performance in India Yaldiz

et al (2011) highlighted the importance of firm size, owners' gender, and location in determining firms' reliance on informal credit for fixed asset investments Mothilal et

al (2012) delved into the key success factors in the Indian Third-party Logistics (3PL) industry and their implications on operational and financial performance Jyoti et al (2013) studied the impact of client-vendor relationships on the financial performance

of outsourcing firms Demirhan et al (2014) investigated the factors influencing firm performance during financial crises, using market-to-book ratio and financial ratios

as measures Hutchinson et al (2015) explored the association between board selection, gender diversity, and firm outcomes, finding that greater gender diversity

on boards can moderate excessive firm risk and improve financial performance Tuân

et al (2016) focused on the effects of innovation on firm performance in supporting industries in Hanoi, Vietnam Raharjo (2017) analyzed the impact of company characteristics on financial reporting quality and its subsequent effect on investment efficiency Salah (2020) conducted a systematic review of the literature on the effects

of International Financial Reporting Standards (IFRS) on firms' financial performance The study highlighted the volatility in financial position and performance figures caused by the fair value orientation of IFRS These studies collectively provide insights into the diverse factors that can influence firms' financial performance across different industries and contexts

1.3.2 Domestic researches

1.3.2.1 Studies about firm’s financial performance

Nguyen (2023) evaluated intellectual capital's effect on service firms' financial performance in Vietnam In this paper, the effect of intellectual capital (IC) on firm financial performance in the service sector in an emerging country, Vietnam, was evaluated using a two-step system GMM model for the period 2005-2014 Dang (2023) explores the impact of capital investments on firm financial performance in listed food and agriculture companies in Vietnam, highlighting positive effects on long-term performance In this paper, the impact of capital investments on firm performance is investigated to provide an insight for future capital investment decisions of companies, and the results indicate that capital investments have statistically significant positive impact on long-term performance of the analyzed firms Vu (2022) explores the impact of public relations, innovation, and investment strategies on SMEs' financial performance in Vietnam, showing positive associations among these factors In this article, the impact of public relations, innovation practices, and investment strategies on SMEs' financial performance in the context of Vietnam is examined, where the authors employ both quantitative approaches with primary data to explore subjects and gain insightful information Pham (2023) evaluates the financial performance of 11 Vietnamese textile and apparel companies using the Entropy-TOPSIS method, providing insights for industry managers and officials In this article, the authors evaluated 11 Vietnamese textile and apparel companies based on their financial performance using the entropy-TOPSIS method and evaluated the degree of their business's financial stability and security using seven financial stability ratio data of these companies within the period 2016-2018 were formulated and used for ranking

1.3.2.2 Studies about Information and Technology firms

Le (2022) explores the impact of intellectual property management on firm performance in the Vietnamese Information and Communication Technology (ICT) industry, highlighting the importance of strategic IP management In this article, the authors examined the impacts of intellectual property management on firm performance in the information and communication technology (ICT) industry of Vietnam and found that each level of IP management has a positive impact on the firm performance IPBES (2022) discusses the impact of FDI on digital technology and ICT sectors in Vietnam, emphasizing the importance of foreign investment for technological advancement and economic growth In this paper, the authors evaluated the impact of FDI on the growth of digital technology, ICT, and the whole economy and proposed solutions to increase the efficiency of using capital and technology to develop the digital economy on the basis of taking advantage of digital technologies from countries and large economic groups Pham (2017) studied information technology and knowledge transfer in Vietnam's IT companies and showed a positive relationship between IT tools' ease of use and knowledge transfer frequency, enhancing organizational knowledge transfer processes

1.3.2.3 Studies about factors affecting firms’ financial performance

Several studies have been conducted to investigate the factors affecting financial performance in various industries and regions Hong (2017) examined the factors affecting the sustainable development of agricultural cooperatives in the Mekong River Delta, Vietnam, using multivariable regression analysis to identify the factors influencing financial performance Tran et al (2019) and Xuan et al (2020) both focused on small and medium-sized enterprises (SMEs) in Vietnam, identifying factors affecting financial efficiency and performance through multivariate linear regression models Tuan et al (2021) also investigated the factors affecting the financial performance of manufacturing enterprises These studies collectively contribute to the understanding of the various factors influencing financial performance across different industries and regions

1.3.3 Research gap

It can be said that the topic of research on factors affecting financial activities

in general, and factors affecting financial activities of information technology enterprises in particular, is no longer a topic looks new However, considering the constantly evolving context of the information technology industry, there are always new challenges and questions arising, requiring researchers and businesses to find solutions suitable for the new stage context

Not only that, the period 2017-2022 is a new period with many changes Many more challenges are posed, and researching the factors affecting the financial performance

of Information Technology enterprises during this period is extremely necessary to find factors that have a significant influence on the financial performance of businesses, thereby providing appropriate solutions to promote the financial performance of businesses in the information technology industry Thus, the research gap of the thesis lies in analyzing the factors affecting the financial performance of information technology enterprises in Vietnam in the new period

The thesis "Factors affecting the financial performance of information technology

enterprises in Vietnam" is based on previously conducted research, and from there

examine the factors affecting business performance in the new period - 2017-2022, and provide the latest updates

Chapter’s conclusion: The author provides theories and measures of financial performance, thereby selecting variables to include in the model, including dependent variables: ROA, ROE, ROS, and independent variables: Capital structure, Regulations Business size, Growth rate, Years of operation Through collecting and researching, the author found that there are many previous studies, both domestic and foreign, researching the topic of financial activities of businesses

in general, and information technology businesses in particular However, as an industry that is constantly developing, there is still a need for more research on

factors affecting the financial performance of information technology businesses

in the new era to draw conclusions and modern solution

CHAPTER 2 RESEARCH METHOD AND MODEL

2.1 Research methods

2.1.1 Qualitative method

In order to come up with variables as well as hypotheses to serve in building a research model, the thesis has learned about studies that have similarities in terms of loading, reinforcing the goal of understanding and clarifying the factors that affect the financial performance of the enterprise From there, we can analyze and compare those studies to get the most complete model for the research Next, the author collected data and financial information of information technology enterprises listed

on the Vietnam stock market to have an overview Then collect data on audited financial statements of businesses

2.1.2 Quantitative method

The thesis conducts research through estimating a panel data regression model, using Stata 17 software to perform regression of 3 models: Pooled OLS, Fixed Effects Model - FEM, and Random Effects Model - REM During the process of running the linear model, the relationship between variables is tested by the author, then the F-test and Hausman test is used to find a model that fits the research data Next, the author tests possible defects of the selected model and overcomes those defects with the GLS model, and finally draws conclusions based on the results of the research model

Pooled OLS regression model: The Pooled OLS model is based on the

assumption that usage data have been collected randomly and are independent of each other It synthesizes data from many observations or from many different sample groups and puts them into a matrix form to estimate regression parameters

The Pooled OLS regression model has the form:

Yit = β0 + β1Xit + εit

In there:

 Yit is the dependent sea at time for observation i

 β0 is the blocking coefficient

 Xit is the independent sea at time t for observation i

 β1 is the coefficient of the independent variable

 εit is the random error over time t for observation i

The Pooled OLS regression model assumes that the variation of independent variables is uniform across observations and uses the entire data If this assumption is not met, the estimates may be inaccurate Therefore, it is not suitable for studies with large differences between groups or variables

Fixed Effects Model – FEM: FEM assumes that the potential of the dependent

variable is unchanged over time and focuses on the differences between observations FEM defines a number of fixed effects to account for differences between observations The fixed effect is a component that is independent of the explanatory variables and is an assessment of the impact of other fixed factors outside the model

on the dependent variable

The FEM regression model has the form:

Yit = β0 + β1Xit + ai + εit

In there:

 Yit is the dependent sea at time for observation i

 β0 is the blocking coefficient

 Xit is the independent sea at time t for observation i

 β1 is the coefficient of the independent variable

 ai is the fixed effect of observation i

 εit is the random error over time t for observation i

The FEM regression method is a suitable estimation method for studies with time series data and some factors not included in the model, which can affect the dependent variable and is more accurate when making estimates of the model coefficients The results reflect effects that take into account fixed factors and provide

a better understanding of the correlation between variables

Random Effects Model – REM: The REM regression model assumes that the

fixed effects have a random distribution on our data set Next, REM assumes that the fixed effects and uniformity have a linear relationship between the independent and dependent variables

The REM regression model has the form:

Yit = β0 + β1Xit + ai + uit

In there:

 Yit is the dependent sea at time for observation i

 β0 is the blocking coefficient

 Xit is the independent sea at time t for observation i

 β1 is the coefficient of the independent variable

 ai is the fixed effect of observation i with a random distribution

 uit is the random error over time t for observation i

The REM regression model is often used when the fixed effects are not closely related to the independent variables or when the variance of the fixed effects is very large REM provides an average estimate of the fixed effects in a data set, converging

on the variance of the fixed effects

Picture 1: Implementation steps of quantitative method

(Source: Author compiled)

2.2 Research model

Based on previously conducted research, Le et al (2022) and Hoang et al (2023), the author proposes a model to research the business performance of companies in the IT sector on the Vietnam stock exchange as follows:

Picture 2: Proposed model

(Source: Author compiled)

The regression model that quantifies the relationship between the independent variables and the dependent variable is written as follows:

Yit = β0 + β1CSit + 2SIZEit + 3GROWTHit + 4AGEit + ε it

 Y is the dependent variable

 CS, SIZE, GROWTH, AGE are the independent variables

 β are the regression coefficients

 ε is random error

 i is the financial statement number, running from 1 to 28

 t is the number of years the financial statement, is taken, running from 1 to 6

2.3 Research variables and hypotheses

Table 3: Description of variables in the analysis

ROA Profit after tax/Total assets

ROE Profit after tax/Equity

ROS Profit after tax/Total net

revenue

Independent

variables

Capital structure

CS1 Liabilities/Total Assets

CS2 Short-term debt/Total assets

CS3 Liabilities/Equity

Firm’s size SIZE1 Ln(Total assets)

SIZE2 Ln(Net revenue)

Firm’s growth rate

GROWTH1 (Net revenue this year - Net

revenue last year)/Net revenue last year

GROWTH2 (Total assets this year - Total

assets last year)/Total assets last year

Operation years

AGE Year of taking financial

statements - Year of establishment

(Source: Author compiled)

Four hypotheses are set out as follows:

Table 4: Expected signs of variables in the model

H1 Capital structure negatively

affects business performance

Zeitun and Tian (2014)

Onaolapo and Kajola (2010)

H2 Enterprise size has a positive

impact on business performance

(2000) Athanasoglou et

al (2005) Doan (2010)

H3 Growth rate negatively affects

business performance

Melinda (2023) Onyekwelu et al (2018)

H4 Number of operation years has a

positive or negative impact on

business performance

+/- Sorensen & Stuart

(2000) Agarwal and Gort (2002)

Liargovas and Skandalis (2008) Malik (2011)

(Source: Author compiled)

2.4 Data

In the thesis, the indicators used to measure the variables are taken as secondary data, these data are collected by the author from published audited financial reports of companies The list of listed companies is also compiled from Vietstock, CafeF, and Investing.com website

From the financial report, the necessary data is entered into the Excel table, then Stata software is used to analyze and calculate Descriptive, comparative, and synthetic statistical methods are used to compile financial and non-financial indicators

of the company, analyze the increase or decrease of financial indicators and business results of companies over time

Data used in the study was collected from financial reports of 28 Information technology enterprises listed on the Vietnamese stock market from 2017 to 2022 with

168 observations in total

Chapter’s conclusion: Based on previous research, the author proposes a model for the study In addition, it also presents analysis methods, data collection, and selection of several models such as FEM, REM, OLS, and verification models

to conduct analysis

CHAPTER 3: ASSESSING FACTORS AFFECTING FINANCIAL PERFORMANCE OF INFORMATION AND TECHNOLOGY ENTERPRISES IN VIETNAM IN THE PERIOD 2017-2022

3.1 Current status of financial performance of IT enterprises in Vietnam 3.1.1 Overview of the IT industry in Vietnam

3.1.1.1 History of formation and development of the information technology industry in Vietnam

In Vietnam, the concept of information technology is understood and defined

in Government Resolution 49/CP signed on August 4, 1993: "Information technology

is a collection of scientific methods, means and technologies and modern technical tools - mainly computer and telecommunications techniques - to organize the effective exploitation and use of very rich and potential information resources in all fields of human activity and society."

Therefore, it can be said that, the history of the formation of the Information Technology (IT) industry in Vietnam can be traced back to the late 20th century, with significant developments occurring in several key stages:

Early Development (1980s-1990s): The initial groundwork for Vietnam's IT

industry began in the 1980s and 1990s when the country started investing in computer science education and infrastructure development Government initiatives aimed to promote computer literacy and establish basic IT infrastructure laid the foundation for future growth

Market Reforms and Foreign Investment (1990s-early 2000s): Vietnam's adoption

of market-oriented policies, known as Doi Moi, in the late 1980s led to economic reforms and increased foreign investment During this period, multinational IT

companies started to enter the Vietnamese market, bringing technology expertise, capital, and knowledge transfer

Emergence of Software Outsourcing (Early 2000s): Vietnam began to emerge as a

destination for software outsourcing and offshore development services in the early 2000s The country's abundant pool of young, educated talent and lower labor costs compared to traditional outsourcing destinations attracted international clients seeking cost-effective IT solutions

Government Support and Policy Initiatives (Mid-2000s-present): Recognizing

the potential of the IT industry to drive economic growth and innovation, the Vietnamese government implemented various policies and initiatives to support its development These included tax incentives for IT companies, investment in infrastructure, establishment of technology parks, and promotion of research and development activities

Startup Ecosystem Growth (2010s-present): The Vietnamese startup ecosystem

witnessed significant growth in the 2010s, fueled by a combination of factors such as increased access to capital, supportive regulatory environment, growing entrepreneurial culture, and advancements in technology Tech startups, particularly

in areas like e-commerce, fintech, and software-as-a-service (SaaS), began to thrive, contributing to the dynamism of the IT industry

Focus on Innovation and Digital Transformation (Present): In recent years, there

has been a growing emphasis on innovation and digital transformation across various sectors of the Vietnamese economy Businesses are increasingly adopting technologies such as cloud computing, big data analytics, artificial intelligence, and the Internet of Things to improve efficiency, productivity, and competitiveness

Overall, the formation of Vietnam's IT industry has been shaped by a combination of government support, foreign investment, talent development, entrepreneurial activity, and technological advancement The sector continues to