Factors affecting the business performance of pharmaceutical enterprises listed on Vietnam’s stock market



The article focuses on the impact of internal factors on business performance of pharmaceutical companies listed on Vietnam's stock market. With a sample of pharmaceutical companies listed on Vietnam's stock market in the period of 2014–2018, by applying the least- squares method using E-view software and data structured according to Panel data, the study proposes 5 internal factors are debt ratio, firm size, growth rate, solvency, ratio of long-term assets on the regression model to evaluate the impact of factors on business efficiency of trading pharmaceutical enterprises listed on Vietnam's stock market. The research results show that there are 3 factors: debt ratio, firm size, growth rate affecting business performance of these enterprises, while the other factors have no impact on the performance of the businesses.

Keywords: business efficiency, debt ratio, growth rate, firm size, pharmaceutical enterprises.

1. Rationale

Currently, the business market in Vietnam is always considered as an opportunity for businesses to invest and develop, but it also contains many potential threats for businesses. In order to maintain the stability and development in the market with many competitive rules, businesses must always operate and find the right direction for their development. Each enterprise must determine its specific plans and strategies to improve business efficiency because high efficiency is one of the most important goals determining the existence and survival of businesses. Over the past years, the effects of the economic downturn and the strong competition from foreign companies have caused Vietnamese enterprises in general to experience a decrease in business efficiency. The pharmaceutical industry in Vietnam is of no exception, and the fact that the number of international pharmaceutical corporations in recent years has been increasing in Vietnam. This is an opportunity but also a challenge for the domestic pharmaceutical industry with low competitiveness, which may reduce the business efficiency, the profitability and the market value of enterprises. Therefore, it is necessary to find solutions to improve business efficiency for Vietnam's pharmaceutical enterprises.

In the world and in Vietnam, there have been many studies on business performance of enterprises. In the study “Determinants of the profitability of China’s regional SOEs”, Shuanglin LIN, Wei ROWE (2005) identified the determinants of the profitability of state-owned enterprises in China.

Haitham Nobanee, Modar Abdullatif, Maryam AlHajjar (2011) in “Cash conversion cycle and firm’s performance of Japanese firms” study the relationship between currency conversion cycle and business performance of companies in Japan. Research results indicate that cash flow cycle is one important measure of working capital management ability.

The thesis of Duong Van Chung (2003) «Research on business efficiency and some solutions to improve the efficiency of production among transport and construction enterprises” made assessments on business efficiency of small and medium-sized enterprises in Vietnam and propose groups of solutions to improve business efficiency of small and medium enterprises in Vietnam.

The PhD dissertation of Nguyen Dinh Hoan (2017) «Solutions to improve business efficiency of Vietnamese construction enterprises” used econometric model to analyze the impact of factors on production efficiency of listed construction companies and proposing solutions to improve business efficiency of listed construction enterprises on Vietnam's stock market.

Although there have been many studies on business performance of enterprises, there have not been any studies on business performance of pharmaceutical enterprises since 2014. Pharmaceutical enterprises have an important position and role in Vietnam's economy, therefore it is essential to study the factors affecting the business efficiency of Vietnamese pharmaceutical enterprises to find solutions to improve their efficiency.

2. Content
   1. Research Methods

The research sample includes data from 2014 to 2018 of 13 pharmaceutical companies listed on Vietnam's stock market. Data used in the study were collected from financial statements (including balance sheet and income statement) of these enterprises.

Regression analysis with the following overall regression model:

(1)

In which:

1) Dependent variable : The dependent variable in the study is business performance, which is represented by the return on assets of enterprises, determined by the ratio of after-tax profit on assets of each enterprise in the sample.

2) Group of independent variables: Reflecting the factors whose statistics are taken from the financial statements of 13 pharmaceutical companies listed on Vietnam's stock market:

— : The firm's debt ratio variable is measured by the ratio of liabilities and total assets over 5 years of the firm i.

— : The firm's size variable, measured by the logarithm of the five-year asset value of the firm i.

— :Ggrowth rate variable of enterprises, measured by the growth rate of total assets of enterprise i over 5 years.

— : The variable of solvency ratio of short-term debt, which is determined by the ratio of short-term assets over short-term debts of enterprise i in 5 years.

— : The variable of tangible asset structure, which is determined by the ratio of long-term assets to total assets of the enterprise i in 5 years.

— : The partial regression coefficient measures the change in the mean of the ROA dependent variable when the independent variable changes one unit and the other independent variables remain constant.

— : Errors in the model.

2.2. Research results

The study conducted statistics describing observed variables. The statistics are presented in table 1 below:

Table 1

DescriptiveStatistics

	N	Minimum	Maximum	Mean	Std. Deviation
ROA	65	-,0736	,2812	,097534	,0725591
DA	65	,1718	,9691	,434657	,2279365
SIZE	65	8,0573	9,9830	8,909075	,4654531
GRO	65	-,2124	,5345	,118202	,1301513
LIQ	65	,9811	4,9131	2,282992	1,0805635
TANG	65	,0177	,6985	,296672	,1522103
Valid N (listwise)	65

Source: Calculated from E-view software

Run the model using E-view software according to the least-square method to determine the regression coefficient qui . Based on the obtained results, we write down the equation of the factors affecting business performance. Then check the model's suitability, that is, to test the _i to know if the independent variable can explain the dependent variable or not. Assess the model's suitability using Adjusted R Square (R²) to determine the model's interpretability in practice.

Run the model using E-view software applying the Data panel, shown in Table 2:

Table 2

Regression results with Fixed Effect

Dependent Variable: ROA
Method: Panel Least Squares
Date: 02/25/20 Time: 22:06
Sample: 2014 2018
Periods included: 5
Cross-sections included: 13
Total panel (balanced) observations: 65
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	1.523122	0.717269	2.123501	0.0390
DA	-0.133269	0.069833	-1.908388	0.0625
LOG(SIZE)	-0.607186	0.330708	-1.836016	0.0727
GRO	0.039915	0.028432	1.403845	0.1669
LIQ	-0.008828	0.009113	-0.968690	0.3377
TANG	-0.084534	0.075279	-1.122933	0.2672
	Effects Specification
Cross-section fixed (dummy variables)
R-squared	0.915291	Mean dependent var		0.097534
F-statistic	29.87313	Durbin-Watson stat		1.332270
Prob(F-statistic)	0.000000

Source: Calculated from E-view software

Regression with Random Effect, we have table 3:

Table 3

Regression results with Random Effect

Dependent Variable: ROA
Method: Panel EGLS (Cross-section random effects)
Date: 02/25/20 Time: 22:08
Sample: 2014 2018
Periods included: 5
Cross-sections included: 13
Total panel (balanced) observations: 65
Swamy and Arora estimator of component variances
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.982551	0.470305	2.089180	0.0410
DA	-0.186763	0.055859	-3.343466	0.0014
LOG(SIZE)	-0.344662	0.215004	-1.603050	0.1143
GRO	0.035241	0.027925	1.261985	0.2119
LIQ	-0.008146	0.008815	-0.924095	0.3592
TANG	-0.121574	0.059037	-2.059294	0.0439
	Weighted Statistics
R-squared	0.261817	Mean dependent var		0.020562
F-statistic	4.185204	Durbin-Watson stat		1.017076
Prob(F-statistic)	0.002539

Source: Calculated from E-view software

Use the Hausman Test to select a model:

Test hypothetical pairs:

H₀: No correlation between explanatory variables and random components (choose Random Effect)

H₁: correlation between the explanatory variables and the random component (choose Fixed Effect)

Table 4

Hausman test results

Correlated Random Effects — Hausman Test
Equation: Untitled
Test cross-section random effects
Test Summary		Chi-Sq. Statistic	Chi-Sq. d.f.	Prob.
Cross-section random		9.743693	5	0.0332
Cross-section random effects test comparisons:
Variable	Fixed	Random	Var(Diff.)	Prob.
DA	-0.133269	-0.186763	0.001756	0.2018
LOG(SIZE)	-0.607186	-0.344662	0.063141	0.2961
GRO	0.039915	0.035241	0.000029	0.3822
LIQ	-0.008828	-0.008146	0.000005	0.7680
TANG	-0.084534	-0.121574	0.002182	0.4278

Source: Calculated from E-view software

Because the results show that P-value (Hausman) = 0.0332 <0.05, H₀ is rejected, choosing H₁, that is, the Fixed Effect model is selected.

— The test removes 2 variables LIQ and TANG from the original regression model:

Testing hypotheses:

H₀: β₅ = β₆ = 0

H₁: β_j ≠ 0 (j = 5,6)

Table 5

Test results remove 2 variables LIQ and TANG from the model

Redundant Variables: LIQ TANG
F-statistic	0.871717	Prob. F(2,47)		0.4249
Log likelihood ratio	2.367488	Prob. Chi-Square(2)		0.3061
Test Equation:
Dependent Variable: ROA
Method: Panel Least Squares
Date: 02/25/20 Time: 22:12
Sample: 2014 2018
Periods included: 5
Cross-sections included: 13
Total panel (balanced) observations: 65
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	1.661670	0.699833	2.374380	0.0215
DA	-0.121090	0.056506	-2.142958	0.0409
LOG(SIZE)	-0.693607	0.320741	-2.162514	0.0355
GRO	0.038396	0.017983	2.135128	0.0417
	Effects Specification
Cross-section fixed (dummy variables)
R-squared	0.912149	Mean dependent var		0.097534
F-statistic	33.91758	Durbin-Watson stat		1.313381
Prob(F-statistic)	0.000000

Source: Calculated from E-view software

With Prob. F = 0.4249>0,05 no evidence to reject H₀.

So it is possible to remove 2 variables LIQ, TANG from the model. The model of factors affecting the profit after tax ratio on business capital is:

Sample regression function:

ROA = 1.661670–0.121090DA_i — 0.693607.LOG(SIZE)_i + 0.038396.GRO_i

Due to Prob(F-statistic) < 0,05 the regression function is appropriate.

In table 5, R² = 0.912149 shows that in the regression model, 3 variables DA, LOG (SIZE) and GRO have a great influence on ROA, to explain 91.2149 % for the fluctuations of ROA, which means 91.2149 % of changes in ROA of listed industry enterprises are due to the effects of 3 variables DA, LOG (SIZE), GRO.

+= — 0.121090 means the debt ratio has a negative impact on business performance, when other factors are constant and if the debt ratio increases by 1 %, the business efficiency decreases by 0.121090 % and vice versa.

+= — 0.693607 means that the size of enterprises has the opposite effect on business performance, when the other factors are constant and if the logarithm of the asset value increases by 1 %, the business efficiency decreases by 0.693607 % and vice versa.

+= 0.038396 means that the growth rate of enterprises has a positive impact on business performance, when other factors are constant and if the growth rate of enterprises increases by 1 %, the business efficiency increases by 0.038396 % and vice versa.

2.3. Solutions to improve business efficiency of listed pharmaceutical companies

Empirical research shows that the debt ratio has a negative effect on business performance, while the growth rate of enterprises has a positive impact on business performance. This is relatively similar to the theory and practice of other industry enterprises. However, the size of enterprises in the empirical research model for listed pharmaceutical industry firms has a negative impact on business performance, this result is contrary to the theoretical studies. The reason is that the level of enterprise management in Vietnam is still not good enough, so the bigger the size of the enterprise, the more difficult the management will be leading to the reduction of the enterprise's performance results.

There are two independent variables, the solvency ratio and the ratio of tangible assets structure, do not give correlation with business performance of listed pharmaceutical companies. Based on these conclusions, we can propose some solutions to help listed pharmaceutical enterprises improve business efficiency as follows:

Firstly, build up an appropriate capital structure: Regression results show that the debt ratio and business performance of enterprises have a negative relationship. Therefore, to increase business efficiency, businesses need to limit the use of debt to finance their activities. Instead, businesses can use other forms of capital mobilization such as: Issuing additional shares to current shareholders, strategic investors or widely issuing on the stock market; Raising capital from investment funds... In addition, businesses can reduce the debt ratio in their capital structure by increasing the rate of retained earnings, stock dividends or raising financing through seeking investment partners in the form of joint ventures or associates.

Secondly, increase the reasonable size of enterprises: When listed pharmaceutical enterprises reach a certain threshold, the increase in enterprise size will lead to a decrease in business efficiency due to low management level. Therefore, listed pharmaceutical enterprises need to improve the capacity of managers by encouraging leaders to study, gain experience, improve skills to know how to cover general operations and make important decisions in management.

Thirdly, speed up the growth: The growth variable has a positive impact on the performance of listed pharmaceutical companies. Therefore, in order to increase the operational efficiency of listed pharmaceutical enterprises, it is necessary to accelerate the growth rate. To do this, businesses can implement measures such as: Improving marketing effectiveness, market research, promotion and brand positioning to expand market share; building an appropriate distribution system and pricing strategy; developing human resources, research and application of science and technology to improve product quality and reduce production costs; having a business plan closely related to the market...

3. Conclusion

Improving business efficiency is a very important issue for pharmaceutical enterprises. The business performance of pharmaceutical enterprises is affected by many factors, but the main factors are debt ratio, firm size and growth rate. Through the research and analysis of these factors, the article has proposed some solutions to improve the business efficiency of pharmaceutical enterprises listed on Vietnam stock market.

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