FACTORS AFFECTING THE PERFORMANCE OF LISTED REAL ESTATE ENTERPRISES IN VIETNAM

FACTORS AFFECTING THE PERFORMANCE OF LISTED REAL ESTATE ENTERPRISES IN VIETNAM

FACTORS AFFECTING THE PERFORMANCE OF LISTED REAL ESTATE ENTERPRISES IN VIETNAM

FACTORS AFFECTING THE PERFORMANCE OF LISTED REAL ESTATE ENTERPRISES IN VIETNAM

Nguyen Thi Thanh Duong

Le Quoc Binh

National Economics University

Abstract: Performance results are one of the essential indicators reflecting the financial health of an enterprise. Identifying the factors affecting this indicator plays an important role for businesses in developing their strategic plans.

With a research sample comprising 42 listed real estate enterprises from 2013-2023, the study identifies groups of factors affecting business performance, including: board size, gender diversity in the board, number of board meetings, audit firm’s reputation, capital structure, and company size. Among these, the variables of board size, number of board meetings in the year, and company size have a positive impact on performance.

The variables of audit firm’s reputation and capital structure have a negative impact on the dependent variable. Additionally, the study focuses on determining the optimal board size. Results indicate that for companies in the research sample, when the board size is between 4-6 members, this variable has a significant and positive impact on business performance.

Keywords: Real estate, Board of directors, Performance results.

I. Introduction

Business performance is always considered one of the core issues of corporate finance. Measuring a company’s performance is crucial for timely improvements within the organization. Analyzing the factors affecting performance helps businesses understand which factors play significant roles, thereby formulating reasonable business strategies to optimize profits and minimize risks.

Numerous international studies have been conducted on this topic. However, according to Anh et al. (2021), differences in financial systems lead to each country’s financial market having its own characteristics. Therefore, business performance also varies based on these characteristics. Consequently, international studies may not be suitable for application in Vietnam.

Moreover, one of the most examined factors when it comes to changes in performance is the size of the board of directors. To date, many global studies have indicated that the board size impacts business performance within a certain range.

However, due to market and legal differences regarding board size in each country, foreign research results on optimal board size cannot be applied to domestic enterprises. Furthermore, in Vietnam, there are very few studies focusing on optimal board size, particularly in the real estate sector.

The article is divided into five parts: introduction, theoretical basis and research overview; hypotheses, model, and research methodology; research results; and finally, conclusions and recommendations.

II. Research Overview and Theoretical Basis

  1. Performance Results

Neely et al. (1995) define performance results as referring to the process of evaluating the effectiveness and efficiency of activities. In modern business management, this term is considered to play a more important role than merely providing quantitative and accounting figures (Koufopoulos et al., 2008). A company with good performance results creates opportunities for the company to expand and develop its business activities, enhance its competitiveness, ensure financial autonomy, maintain and control its operations, and mitigate business difficulties and risks.

Al-Matari et al. (2014) categorized these indicators into two groups:

(i) Accounting-based measures: Including ROA, ROE, ROS, etc.

(ii) Market-based measures: Including Tobin’s Q, MVA, MTBV, etc.

Among these, ROA, ROE, and Tobin’s Q are the most commonly used indicators. These are also the three performance measurement indicators used in this study.

  1. Board of Directors

– Board Size:

Guest (2009) utilized an OLS model with data collected from 2,746 listed companies in the UK from 1981-2002, finding a strong inverse correlation between board size and performance. Shakir (2015) and Paniagua et al. (2018) also indicated that larger board sizes correlate with lower performance, while the study by Mai et al. (2022) suggested the opposite, arguing that a larger board benefits from better information gathering and improved management skills, thereby enhancing performance.

However, this also has several drawbacks. Coordination costs increase as members struggle to reach consensus, leading to delayed and inefficient decision-making (Jensen, 1993). Additionally, the “free rider” phenomenon occurs when individual members reduce their responsibility due to the increased number of members (Lipton et al., 1992).

– Gender Diversity on the Board:

Many studies have shown that the presence of women on the board of directors positively impacts company performance. Carter et al. (2003) used OLS regression and found a positive effect of the proportion of female board members on performance. The authors also noted that companies with at least two female board members perform better.

Ngo et al. (2019) reported similar results, suggesting that gender diversity enhances creativity, increases meticulousness, attention to detail, and innovation in governance. Moreover, companies with gender-diverse boards tend to improve their public image and attract customers more effectively.

However, Smith et al. (2006) pointed out that this diversity might also lead to conflicts if members have different goals, or if female members have familial ties to the owner, which could reduce transparency and decision-making efficiency. Therefore, the impact of gender diversity depends on the competency and harmony of the board members.

– Number of Board Meetings in a Year:

Lipton et al. (1992) argued that the number of board meetings is a measure of the board’s strength and effectiveness in managing the company. Vafeas (1999) also emphasized that a higher frequency of board meetings helps improve oversight and reduce agency costs, thereby enhancing performance.

Al-Daoud et al. (2016) conducted a study on the relationship between board meetings and company performance. The research data was collected from 118 companies listed on the Amman Stock Exchange (ASE) in Jordan from 2009-2013. The regression results using the GMM method showed that the variable of board meeting frequency has a strong and positive impact on company performance.

The authors suggested that board meetings play a crucial role in supervising and effectively managing the company. However, having more meetings is not always better. The key is that the meetings should have clear content and plans to address the company’s core issues, rather than being held just to comply with regulations.

  1. Audit Firm Reputation

The quality of auditing significantly impacts a company’s performance. Brown et al. (2004) indicated that auditors from large firms tend to have more experience, thereby providing valuable advice to improve internal control systems and the reliability of financial reports.

Al-Daoud et al. (2016) also found a positive relationship between the reputation of the audit firm and company performance. The authors argued that large and reputable audit firms generally provide higher quality services, ensuring accurate and transparent financial information for stakeholders, while also protecting their own reputation.

  1. Capital Structure

Jensen (1986) suggested that high debt levels can pressure managers to focus on profitable projects to pay interest, thereby reducing agency costs and improving performance.

Conversely, Zeitun et al. (2007) conducted a study on factors affecting corporate performance in the Jordan market from 1989-2003 and found that capital structure had a strong and inverse effect, where higher short-term debt ratios led to lower business performance.

The authors noted that using substantial debt to benefit from tax shields might reduce profits due to increased bankruptcy costs. In Vietnam, Hau et al. (2021) found a similar result, indicating that F&B businesses in Vietnam use debt inefficiently, as the benefits from debt do not compensate for the arising costs.

  1. Company Size

Company size has a significant impact on performance. Larger companies often have lower productivity but achieve higher profits due to their ability to influence the market and negotiate with suppliers (Majumdar, 1997).

Pervan et al. (2012) studied the impact of company size on the performance of manufacturing companies in Croatia from 2002-2010, with a sample size of 18,492 observations. The results indicated that larger companies have higher performance. The authors emphasized that larger companies have advantages in negotiation, cost reduction, and better capital mobilization compared to small and medium-sized enterprises.

Additionally, larger companies have more market experience, favorable conditions for accessing financial resources, and investing in R&D, which helps them achieve sustainable growth and weather market fluctuations. These findings are consistent with previous studies by Zeitun et al. (2007) and Guest (2009).

III. Hypotheses, Model, and Research Methodology

  1. Model and Research Hypotheses

The author identifies the factors affecting the performance results of listed real estate companies on the Vietnam Stock Exchange, including: (1) Board size, (2) Gender diversity on the board, (3) Number of board meetings in a year, (4) Audit firm reputation, (5) Capital structure, and (6) Company size. The proposed regression model is as follows:

FPit = β1 + β2 BSIZEit + β3 PWOMit + β4 MEETINGit + β5 AUDITit + β6 LEVit + β7 SIZE+ uit (1)

Where:

– FP (Firm Performance) represents the performance results of the company

– i = 1, 2, 3, 4, . . . represents the companies in the research sample

– t = 2013, 2014, . . ., 2023 represents the research years

The author formulates six research hypotheses presented in Table 1:

Table 1. Summary of Research Hypotheses

Board Size (-)

Financial Performance

Number of Board Meetings (+)

Gender Diversity on the Board (+)

Audit Firm Reputation (+)

Capital Structure (-)

Company Size (+)

(Source: Compiled by the author)

  1. Variables and Measurement Scales

Table 2. Summary of Variables Used in the Study

Variable Name

Abbreviation

Calculation

Source

Return on Assets

ROA

Net Income / Total Assets

Carter (2003), Zeitun et al. (2007)

Return on Equity

ROE

Net Income / Shareholder’s Equity

Hau et al. (2021)

Tobin’s Q

TOBINQ

(Market Value of Equity + Book Value of Liabilities) / Book Value of Total Assets

Carter (2003), Guest (2009)

Board Size

BSIZE

Number of Board Members

Shakir (2015), Mai et al. (2023)

Gender Diversity on the Board

PWOM

Number of Female Board Members / Total Board Members

Carter et al. (2003), Ngo et al. (2019)

Number of Board Meetings

MEETING

Number of Board Meetings in a Year

Carter et al. (2003), Al-Daoud et al. (2016)

Audit Firm Reputation

AUDIT

Dummy Variable: 1 if audited by Big-4, 0 if audited by others

Al-Daoud et al. (2016)

Capital Structure

LEV

Total Debt / Total Assets

Zeitun et al. (2007)

Company Size

SIZE

Ln(Total Assets)

Zeitun et al. (2007), Pervan et al. (2012)

(Source: Compiled by the author)

  1. Data and Research Methodology

– Data: The research utilizes the FiinGroup database to collect data from listed real estate companies on Vietnam’s two stock exchanges, HNX and HOSE, during the 2013-2023 period. The author filters the data, removing incomplete and unreliable observations, resulting in a sample of 42 companies with a total of 462 observations over the 11-year period from 2013 to 2023.

– Research Methodology: The study uses econometric software, Stata and Eviews, to estimate the correlation between factors affecting company performance. Panel data regression analysis is considered, including OLS regression, fixed effects model (FEM), and random effects model (REM). Breusch & Pagan Lagrangian tests are conducted to choose between OLS and REM, and Hausman tests to choose between FEM and REM. The results indicate that REM is the most suitable model.

IV. Research Results

  1. Descriptive Statistics

Table 3. Descriptive Statistics

Variable Name

Observations

Mean

Standard Deviation

Minimum

Maximum

ROA

462

.0362223

.0560836

-.5172

.2845

ROE

462

.0846158

.1254972

-.9981

.6593

Tobin’s Q

462

1.010282

.3898898

.0255088

3.134827

BSIZE

462

6.495671

1.676358

4

12

PWOM

462

.179973

.1581393

0

.6666667

MEETING

462

15.19481

12.40132

4

75

AUDIT

462

.4155844

.4933567

0

1

LEV

462

.1520155

.1256984

0

.5268219

SIZE

462

12.42631

.5978982

11.20769

14.82455

(Source: Compiled by the author)

Table 4. Correlation coefficient matrix

 

ROA

ROE

TOBINQ

BSIZE

PWOM

MEETING

AUDIT

LEV

SIZE

ROA

1.0000

 

 

 

 

 

 

 

 

ROE

0.8934

1.0000

 

 

 

 

 

 

 

TOBINQ

0.1144

0.1778

1.0000

 

 

 

 

 

 

BSIZE

-0.0513

0.0637

0.1987

1.0000

 

 

 

 

 

PWOM

0.0458

0.0321

0.0371

-0.0335

1.0000

 

 

 

 

MEETING

0.0314

0.0949

0.1173

0.0478

0.0296

1.0000

 

 

 

AUDIT

-0.1644

-0.0939

0.1714

0.2041

-0.0084

0.2261

1.0000

 

 

LEV

-0.1408

-0.0218

0.1182

0.0849

0.1031

0.2329

0.2079

1.0000

 

SIZE

0.0168

0.1382

0.2753

0.3017

0.1684

0.3162

0.4303

0.4021

1.0000

(Source: Compiled by the author)

The correlation analysis in Table 4 shows that most variable pairs have correlation coefficients less than 0.8. However, there is one exception: the pair of ROA and ROE has a correlation coefficient of 0.8934, which is greater than 0.8 due to the formulas used to determine these two variables. Nevertheless, since these are dependent variables representing two different performance measurement scales and are regressed in separate models, this does not affect the research results.

  1. Regression Results

The regression results for the REM model are presented in Table 5:

Table 5. Regression Results of the REM Model

Source: Compiled by the author

Variable Name

ROA

ROE

Tobin’s Q

BSIZE

– 0.00135

0.00016

0.01967

PWOM

– 0.00173

– 0.01956

– 0.16046

MEETING

0.00030

0.00127 **

0.00217

AUDIT

– 0.01270 *

– 0.02748

– 0.02266

LEV

– 0.07062 ***

– 0.08794

– 0.21638

SIZE

0.01818 **

0.05525 ***

0.21986 ***

R-squared

2.08%

4.92%

5.77%

Note: *,**,*** correspond to significance levels of 10%, 5%, 1%, respectively.

The regression results in Table 5 show that only the company size (SIZE) variable has a positive impact on company performance across all three measurement scales. The remaining variables mostly lack statistical significance or are significant on only one measurement scale. This indicates the heterogeneous impact of the variables on the dependent variable.

To provide a more accurate view of the REM regression model results, the author conducts four tests to check for model specification issues, including the Breusch–Pagan test for heteroskedasticity, Wooldridge test for autocorrelation, and Variance Inflation Factor (VIF) test for multicollinearity. The results show that the REM model suffers from autocorrelation and heteroskedasticity. To address these issues, the study uses the Feasible Generalized Least Squares (FGLS) estimation method. The regression results are presented in Table 6.

Table 6. FGLS model regression results

(Source: Compiled by the author)

 

Variable Name

ROA

ROE

Tobin’s Q

BSIZE

– 0.00085

0.00455

0.03057 ***

PWOM

0.01387

0.00727

0.01055

MEETING

0.00022

0.00072 *

0.00117

AUDIT

– 0.02306 ***

– 0.05028 ***

– 0.04303

LEV

– 0.08151 ***

– 0.09649 *

0.02361

SIZE

0.01898 ***

0.05404 ***

0.12359 ***

Note: *,**,*** correspond to significance levels of 10%, 5%, 1%, respectively.

The board size (BSIZE) has a positive impact on company performance at the Tobin’s Q measurement scale with a significance level of 1%. This result aligns with Mai et al. (2023), suggesting that an increase in the number of board members enriches business connections, provides valuable information, and enhances resources and experience.

However, for the other two measurement scales, the coefficients are not statistically significant, indicating insufficient evidence to evaluate the positive impact of this variable on company performance.

The number of board meetings in a year (MEETING) positively affects the dependent variable ROE at the 10% significance level. Board meetings are seen as opportunities for board members to fulfill their duties, and holding these meetings regularly can reduce agency costs, as shareholders can better assess managers and address issues promptly and effectively.

Al-Daoud et al. (2016) found similar results in their empirical research. Like the BSIZE variable, MEETING is only significant at the ROE measurement scale, so it is premature to conclude that more frequent board meetings lead to better performance.

The reputation of the audit firm (AUDIT) has an inverse relationship with company performance at the ROA and ROE measurement scales with a significance level of 1%. This finding contrasts with Al-Daoud et al. (2016), which found that companies audited by Big-4 firms had better performance.

Big-4 firms include large, experienced audit companies. However, this does not necessarily mean that the quality of audits by Big-4 firms is always high. History has shown many scandals where companies received unqualified opinions from their auditors.

For example, the recent case involving three Big-4 firms (KPMG, Deloitte, EY) failing to detect irregularities at SCB and Vạn Thịnh Phát, or PwC being accused of not detecting fraud leading to Colonial Bank’s collapse in 2009.

Similarly, the capital structure (LEV) variable shows an inverse impact on the ROA and ROE indices at 1% and 10% significance levels, respectively. This means that the more a company relies on debt, the worse its performance. This finding is consistent with Zeitun et al. (2007) and Hau et al. (2021). The reason is that if companies over-rely on debt and use it inefficiently, the benefits from borrowing do not offset the arising costs, leading to a risk of insolvency and negatively affecting performance.

Company size (SIZE) positively impacts company performance at the 1% significance level across all three measurement scales, consistent with Zeitun et al. (2007), Guest (2009), and Pervan et al. (2012). Larger companies have greater influence and more market experience than medium and small ones. They also can leverage economic advantages such as negotiating prices with suppliers to reduce costs, easily mobilize large capital, and benefit from R&D, which helps them grow and improve overall performance.

The proportion of female board members (PWOM) shows a positive regression coefficient. However, the P-value is not statistically significant at the 10% level, indicating no evidence that increasing the number of female board members positively affects the performance of listed real estate companies in the Vietnamese stock market.

  1. Testing the Impact of Board Size on Performance

With the board size in the sample ranging from 4 to 12 members, the FGLS model is regressed according to two percentiles: 50% and 100% of the BSIZE variable, corresponding to two board size ranges of 4-6 members and 7-12 members. The regression results are presented in Table 7.

Table 7. Testing the Impact of Board Size on Performance

(Source: Compiled by the author)

 

 

ROA

ROE

TOBINQ

Percentile

50%

100%

50%

100%

50%

100%

BSIZE

0.01272***

 0.00536**

0.01669*

0.00162

0.07982**

0.01302

PWOM

0.01623

0.04595

– 0.00583

0.13183

0.07031

-0.06486

MEETING

0.00053*

– 0.00013

0.00119**

0.00011

0.00195

0.00012

AUDIT

-0.01038

-0.02672***

-0.01900

-0.05970**

0.05060

0.06318

LEV

-0.14344***

– 0.02179

-0.24214***

0.05744

– 0.09871

0.11979

SIZE

0.00353

0.02907 ***

0.02414 *

0.07394***

0.09729*

0.12390*

Note: *,**,*** correspond to significance levels of 10%, 5%, 1%, respectively.

Based on the results presented in Table 7, we can observe that at the 100th percentile, the board size (BSIZE) variable has a negative impact on the dependent variable at the ROA measurement scale. This means that a board size of 7-12 members negatively affects the company’s performance.

For the 50th percentile, the independent BSIZE variable shows a statistically significant positive correlation across all three measurement scales, with significance levels of 10%, 1%, and 5%. This implies that a smaller board size of 4-6 members yields the best performance for companies.

The rationale behind this is that a smaller board facilitates better communication and coordination among members, allowing for easier consensus and more efficient decision-making. Additionally, the “free rider” problem is minimized, as each member in a smaller board feels a greater sense of responsibility and is less likely to rely on others for oversight and decision support.

V. Conclusion and Recommendations

  1. Conclusion

The study focused on examining the impact of board size, gender diversity, number of board meetings per year, audit firm reputation, capital structure, and company size on the performance of listed real estate companies in Vietnam. Using the FGLS regression model with panel data, the results show that the number of board members, number of board meetings per year, and company size positively affect performance, while the variables of audit firm reputation and capital structure negatively impact the dependent variable.

Additionally, the study focuses on determining the optimal board size that impacts company performance. The results indicate that for companies in the research sample, a board size of 4-6 members has a positive relationship with company performance.

  1. Recommendations

– Enhancing the Role of the Board of Directors:

Board Size:

According to the Enterprise Law 2020, the number of board members can range from 3 to 11, but some companies have boards with up to 12 members.

The research indicates that an excessively large board size reduces operational efficiency due to decision-making difficulties. Therefore, companies should select a number of members appropriate to their actual situation and legal requirements, encouraging members with expertise.

Additionally, companies might consider the recommended board size of 4-6 members proposed in this study to leverage diverse knowledge and improve the decision-making process.

Gender Diversity on the Board:

The study did not find a clear impact of female board members on performance, but previous research has shown that the presence of women can enhance creativity and adaptability of the enterprise.

Companies should have at least two female board members to take advantage of diverse perspectives, enhance detail-oriented and meticulous governance, and improve the company’s public image. However, careful selection based on business environment and professional qualifications is necessary, avoiding selection based on personal relationships.

Number of Board Meetings:

According to the Enterprise Law 2020, the board must meet at least once every quarter, equivalent to four times a year. However, these meetings also incur costs and require at least 3/4 of members to participate for validity.

Therefore, optimizing meetings is crucial to ensure that the benefits outweigh the costs, contributing to improved company performance.

– Enhancing the Quality of Independent Audits:

The results show that audits by Big-4 firms do not guarantee absolute audit quality. Companies need to thoroughly check the audit firm’s operational history and auditor qualifications rather than relying solely on the firm’s reputation.

Moreover, establishing a robust internal control system helps minimize errors in financial reports and supports auditors in working more effectively. Companies should periodically rotate audit firms to avoid familiarity, provide new perspectives, and apply updated audit methods, reducing legal risks and increasing transparency.

– Choosing an Appropriate Capital Structure:

Inefficient capital structures can negatively impact real estate business operations. To reduce financial pressure, companies should focus on managing working capital, limit short-term borrowing, and use retained earnings to stabilize capital and reduce interest costs.

Companies can also raise capital from large investment funds such as ASCF and DCVFM to improve management and reduce risks. Transparency in financial reporting is crucial to building investor trust.

To attract investment from these sources, companies need to build credibility, maintain transparency in financial reporting, and demonstrate clear management capabilities, thereby creating confidence among investors and stakeholders.

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