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Factors affecting firms’ performance: The case of Vietnam construction firms

Factors affecting firms’ performance: The case of Vietnam construction firms
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This study found the factors that positively impact on performance are asset structure, capital structure and firm size that negatively impact the performance of Vietnam listed construction firms. These findings support business administrators in selecting appropriate business and production plans to increase the operating performance of businesses in the construction industry.

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Factors affecting firms’ performance: The case of Vietnam construction firms

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Nội dung Text: Factors affecting firms’ performance: The case of Vietnam construction firms

Research Journal of Finance and Accounting www.iiste.org<br />
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)<br />
Vol.11, No.2, 2020<br />
<br />
<br />
Factors Affecting Firms’ Performance: The Case of Vietnam<br />
construction firms<br />
<br />
Nga Ngo Thi Thanh* Duong Phan Thuy Hang Dang Thu<br />
University of Transport Technology, 54 Trieu Khuc Street, Ha Noi, Viet Nam<br />
Abstract<br />
In the context of Vietnam’s international economic integration, improving the performance of enterprises is<br />
increasingly important because it not only affects businesses but also affects the development prospects of the<br />
economy. The purpose of the paper is to consider the impact of factors on the performance of listed construction<br />
companies in the period of 2012-2018. By means of an empirical analysis, this study uses Eviews econometric<br />
software and table data techniques. This study found the factors that positively impact on performance are asset<br />
structure, capital structure and firm size that negatively impact the performance of Vietnam listed construction<br />
firms. These findings support business administrators in selecting appropriate business and production plans to<br />
increase the operating performance of businesses in the construction industry.<br />
Keywords: Profitability, construction firms<br />
DOI: 10.7176/RJFA/11-2-15<br />
Publication date: January 31st 2020<br />
<br />
1. Introduction<br />
In the context of Vietnam’s international economic integration, improving the performance of enterprises is<br />
increasingly important because it not only affects businesses but also affects the development prospects of the<br />
economy.<br />
The global economic crisis has strongly affected the Vietnamese economy, causing all businesses to face many<br />
difficulties. And so do the construction industry. Vietnam construction industry has experienced the difficult time<br />
in 2009-2013. In the period of 2000-2009, the growth rate of construction industry was 9.6% / year and in the<br />
period of 2009-2013 reached 4.6% / year. In fact, many businesses have gone bankrupt, one of the reasons is the<br />
factors affecting the operational efficiency, which have not been taken seriously in the operation process of<br />
enterprises.<br />
Therefore, it is necessary to study the impact of factors on the performance of enterprises. The paper includes 4<br />
main contents: (1) Overview of the impact of factors on firm performance, (2) Research methodology, (3)<br />
Empirical results on the impact of factors to the performance of listed construction enterprises, (4) Some<br />
recommendations.<br />
<br />
<br />
2. Review of related literature<br />
There are plenty studies about the impact of factors on the performance of businesses in general.<br />
Performance is often determined by the return on total assets (ROA), such as Sivathaasan et al. (2013) conducted<br />
a research on factors affecting profitability of all manufacturing companies listed on the exchange for the period<br />
2008 – 2012; Khidmat and Rehman (2014) studied 9 chemical companies listed on the Pakistan Stock Exchange<br />
for the period 2001 – 2009; Bolek and Wiliński (2012) pointed out the impact of internal and external economic<br />
factors on the profitability of all construction companies listed on Warsaw Stock Exchange for the period 2000 –<br />
2010;<br />
Previous studies have considered many factors affecting the performance of enterprises such as capital<br />
structure, receivables management, solvency, asset structure, firm size, growth rate.<br />
The capital structure of enterprises<br />
The capital structure of enterprises is measured by debt-to-assets ratio. The research by Sivathaasan et al<br />
(2013) shows that capital structure has a positive effect on firm’s performance. Khidmat and Rehman (2014) point<br />
out that capital structure has a negative impact on firm performance. The research of Bolek and Wiliński (2012),<br />
and the research of Lazaridis and Tryfonidis (2006) (which used data from 131 Greek listed companies for period<br />
of 2001 – 2004) also have the same results with the research of Khidmat and Rehman (2014).<br />
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Receivables management<br />
Receivables management: The level of receivables management is measured through the average collection period.<br />
Research by Bolek and Wiliński (2012) suggests that the average collection period has a negative impact on the<br />
firm performance. Consistent with this research result, there are other studies: Gill et al. (2010) studied 88<br />
companies listed on the New York Stock Exchange for the period of 2005 – 2007; Napompech (2012) sampled 255<br />
companies listed on Thailand Stock Exchange for the period of 2007 – 2009; Addae and Nyarko-Baasi (2013)<br />
studied 125 listed companies on Ghana Stock Exchange for the period of 2004 -2009; Owolabi et al. (2012) studied<br />
processing enterprises listed on the Nigerian stock market in the period 2005-2009.<br />
Solvency<br />
Solvency: Solvency is the ability of a company to meet its long-term debts and financial obligations. Research by<br />
Khidmat and Rehman (2014) suggested that liquidity is a positive impact on ROA. While the study of Bolek and<br />
Wiliński (2012) suggested that the quick ratio has an opposite effect on ROA.<br />
Asset structure<br />
Asset structure: Asset structure is expressed by asset structure ratios (fixed asset ratio, current asset ratio).<br />
Sivathaasan et al. (2013) argues that asset structure has no effect on ROA. Bolek and Wiliński (2012) showed that<br />
asset structure has a negative impact on ROA.<br />
Firm size<br />
Firm size: firm size is expressed through the natural logarithm of the total assets. Sivathaasan et al. (2013) have<br />
demonstrated a positive relationship between firm size and performance. Similar results were shown by an<br />
empirical research of Bolek and Wiliński (2012). However, the research by Ramasamy (2005) about the oil and<br />
gas industry in Malaysia concluded that firm size has a negative impact on firm performance. The reason for this<br />
conclusion is that the bigger the size of an enterprise, the more difficult it is to manage and run the business.<br />
Moreover, the enterprise has to invest a lot not only for assets but also for other resources such as people. So the<br />
profitability ratio of the business per one asset is reduced.<br />
Growth rate<br />
Growth rate: A high revenue growth rate will increase the profit of the business, leading to an increase in<br />
performance. A study of Yazdanfar (2013) on Swedish SME companies and Vijayakumar (2011) on Indian<br />
automobile trading companies shows that revenue growth has a positive impact on firm performance. These results<br />
are consistent with the research results of Bolek and Wiliński (2012).<br />
In the above studies, mainly referring to the factors that affect firm performance of all listed companies, very few<br />
studies mention the factors affecting firm performance of enterprises in a certain industry, especially studies in<br />
Vietnam. Each sector has its own characteristics, factors affecting firm performance so need to be studied<br />
separately so that we can see the impact of factors on firm performance of different sector. Specifically,<br />
construction firms have very specific characteristics such as single products, large value of construction works,<br />
extensive working area. Moreover, construction firms also need a long time to change the scale and products, so<br />
they need to mobilize massive business resources.<br />
<br />
<br />
3. Research methodology<br />
Based on related reviews, the research model is constructed as follows (Figure 1):<br />
<br />
ACP QR<br />
<br />
<br />
Firms’<br />
DR Performance SIZE<br />
(ROA)<br />
<br />
AS GR<br />
<br />
Figure 1. Research model of factors affecting firms’ performance<br />
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Vol.11, No.2, 2020<br />
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Table 1. Variables in the research model<br />
Variables Code Measures<br />
Firms’ performance ROA ROA = Net income/ Average total assets<br />
Average cover period ACP = 360* receivables /net sales<br />
Debt ratio DR Total liabilities/total assets<br />
Asset Structure AS Current asset/total assets<br />
Quick Ratio QR (Current assets – inventory)/ current liabilities<br />
Firm size SIZE Firm size measured by log of total assets<br />
Sale Growth GR (Current period net sales – previous period net sales)/<br />
previous period net sales<br />
<br />
<br />
Research data<br />
The study relied on secondary data extracted from the audited financial statement of the selected companies. Data<br />
of these 40 companies is collected from 2012 to 2018. Audit Financial Statements of these companies will be<br />
acquired from the Hanoi stock exchange Library, Ho Chi Minh stock exchange Library, and websites of these<br />
companies listed on the Vietnam stock market.<br />
In the study, panel data regression models were employed to examine the determinants constructions companies'<br />
profitability in Vietnam. The panel data regression models were the Fixed effects model (FEM). Variables in the<br />
research model are shown in Table 1.<br />
<br />
<br />
4. Analysis findings and discussions<br />
Research results<br />
Table 2. Descriptive statistic<br />
ROA ACP DR AS QR SIZE GR<br />
Mean 0.021421 1125.615 0.773051 0.794036 0.960996 0.083444 69.62950<br />
Median 0.013000 139.0000 0.808450 0.850000 0.739000 0.083334 1.975000<br />
Maximum 0.235000 100540.0 1.045400 1.000000 9.437000 0.094045 13797.00<br />
Minimum -0.156000 1.010000 0.218200 0.120000 0.164000 0.075609 -100.0000<br />
Std. Dev. 0.037988 8591.307 0.139159 0.164275 1.033721 0.003238 839.9360<br />
Skewness 1.062606 9.978437 -1.255221 -1.728839 5.270493 0.388975 15.77095<br />
Kurtosis 11.67858 105.0126 4.855821 6.562846 35.03241 3.729683 256.9250<br />
Jarque-Bera 931.3997 126056.5 113.7079 287.5765 13267.19 13.27250 763849.3<br />
Probability 0.000000 0.000000 0.000000 0.000000 0.000000 0.001312 0.000000<br />
Sum 5.998000 315172.2 216.4542 222.3300 269.0790 23.36444 19496.26<br />
Sum Sq. Dev. 0.402628 2.06E+10 5.402888 7.529140 298.1335 0.002925 1.97E+08<br />
Observations 280 280 280 280 280 280 280<br />
<br />
<br />
Note. The descriptive statistic for the study presented in table1 was for constructions company for period of seven<br />
years covering 2012 to 2018. Statistical data (Table 2) show the mean value of ROA was 0.021421 of which the<br />
highest ROA was 0.235 and the lowest ROA was -0.156. Average collection period was 1125.61 and quick ratio<br />
was 0.960996 current assets over current liabilitiesof firms.<br />
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Vol.11, No.2, 2020<br />
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Table 3. Correlation matrix<br />
ACP DR AS QR SIZE GR<br />
ACP 1 0.1604 0.0516 0.0970 -0.0502 -0.0125<br />
DR 0.1604 1 0.1016 0.0009 -0.0953 0.0565<br />
AS 0.0516 0.1016 1 -0.1181 0.4169 0.0600<br />
LIQ 0.0970 0.0009 -0.1181 1 -0.2013 0.0239<br />
SIZE -0.0502 -0.0956 0.4169 -0.2013 1 0.0219<br />
GR -0.0125 0.0565 0.0600 0.0239 0.0219 1<br />
<br />
<br />
Note. The following Table 3 shows the correlation coefficients between variables. The purpose is to examine<br />
whether there is close correlation between independent variables and dependent variables to exclude variable that<br />
may lead to multi-collinearity. This is necessary step before running the regression. The results show that the<br />
correlation coefficient between any pair independent variables in the model is no less than 0.8 and therefore<br />
multicollinearity is unlikely to occur.<br />
<br />
<br />
Table 4. Model summary<br />
Indicators Coefficients<br />
R-squared 0.630506<br />
Adjusted R-squared 0.547856<br />
S.E. of regression 0.025544<br />
F-statistic 7.628640<br />
Prob(F-statistic) 0.000000<br />
Durbin-Watson stat 1.417533<br />
Note. R-square value was found to be 0.630506. This implies that the combined effects of Profitability was found<br />
to be negatively correlated with average cover period, debt ratio, asset structure, quick ratio, firm size and sale<br />
growth explained 63.05% of the variation in the profitability of constructions companies while the remaining<br />
36.95% was due to the other variables not captured in this study. F- value indicates that the model used in the study<br />
is significant (prob >F =0.0000).<br />
Table 5. Regression Results<br />
<br />
<br />
Variable Coefficient Std. Error t-Statistic Prob.<br />
C 1.027112 0.204397 5.025093 0.0000<br />
ACP -1.69E-07 2.67E-07 -0.633969 0.5267<br />
DR -0.279063 0.030392 -9.182095 0.0000<br />
AS 0.092118 0.021504 4.283791 0.0000<br />
QR -0.003338 0.002458 -1.357815 0.1759<br />
SIZE -10.30468 2.232357 -4.616056 0.0000<br />
GR 2.30E-06 2.18E-06 1.055036 0.2925<br />
Note.<br />
Results regarding the impact of firm size on the performance of listed constructions companies confirm the<br />
findings of previous studies conducted in Greece (i.e. Notta and Vlachvei 2014, Kontogeorgos et al 2017).<br />
Profitability was found to be negatively correlated with debt ratio and firm size.<br />
On the other hand, the relationship between profitability and asset structure was positive, it was found that profit<br />
increases as asset structure increases. This implies that an increase in asset structure to increase in production and<br />
revenue and thereby leads to increase in profitability.<br />
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Discussions<br />
This paper examines the effects of capital structure, asset structure, quick ratio, average payment period,<br />
firm size, and revenue growth rates on Vietnamese listed construction enterprises in the period of 2012 – 2018. In<br />
correlation with previous domestic and foreign studies, this study also contributes to a better explanation of the<br />
factors affecting firm performance.<br />
The represented variable is ROA. According to empirical research results, 3 of 6 independent variables<br />
included in the study affect ROA: capital structure, asset structure, firm size. Asset structure has a positive impact<br />
on performance. Vice versa, capital structure and firm size negatively impact on firm performance.<br />
<br />
<br />
5. Conclusion<br />
The results of this study show that it is always required large enough capital for long business cycles such as<br />
construction sector. The enterprises which have larger scale of business capital get the higher the profitability. Due<br />
to the ability to undertake large construction works, in the long run, and also easier to take advantage of<br />
opportunities business. In order to maintain a large scale of business capital, the enterprise cannot finance itself<br />
but then it needs to mobilize more capital from different sources. This will increase financial risk and affect the<br />
profitability of the business. Therefore, businesses need to be very careful in using the effects of financial leverage.<br />
This result can help construction enterprises explain the causes affecting the performance, thereby helping business<br />
administrators in selecting suitable business and production plans to increase profitability.<br />
<br />
<br />
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