Nalyzing the impact of financial structure on business efficiency of construction enterprises in Vietnam

Based on the theory of financial structure of enterprises, the thesis has synthesized then gave opinions and methods of

measuring financial structure and business efficiency of construction enterprises in Vietnam. Accordingly, this thesis has

analyzed the impact of financial structure on business efficiency of construction enterprises in Vietnam from 2012 to 2017.

Experimental results show that:

- The capital structure has a positive impact on the business efficiency of the construction enterprises, which means that

the more debts the enterprises use, the more effective their business is. However, it is the best when enterprises utilize the debt

at 0.1 quantile, at higher the quantile it will reduce the business efficiency of enterprises.

- The proportion of fixed assets in total assets is not large but has a positive impact on the business efficiency of

enterprises. The expansion of fixed assets in construction enterprises is necessary to enhance the position of enterprises as well

as contribute to improving labor productivity, speeding up progress of the construction, meeting the requirements of the

investors, and the best utilization of asset structure at 0.25 quantile.

- The value of inventories, which is mainly the value of unfinished products, also accounts for a large proportion of total

assets. The backlog of receivables and bad debt recovery have negative impacts on the business efficiency of enterprises.

- The larger the enterprise size is, the more opportunities they have in accessing more loans, hence this is a favorable

condition for enterprises to improve their competitiveness in the marke

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nagement agencies have grounds for the development policies of the construction industry in the coming time to ensure that the development is sustainable while ensuring the industry's contribution to the national economy; Investors have an additional solid basis for their investment decisions in the construction industry. Fifthly, the thesis uses a combination of quantitative and qualitative research. Qualitative research is an in-depth interview with business executives to evaluate the results of quantitative research, thereby suggesting policy implications related to financial structure to improve business efficiency of construction enterprises. Therefore, the thesis will be a reference source for methodology, research design, research models and research data processing for researchers, lecturers and students in the same field. 5. Thesis structure In addition to the table of contents, the list of abbreviations, the list of tables, the list of figures, the list of references and the Appendix, the thesis is structured into 5 chapters. Specifically, as follows: Chapter 1: Overview of the research situation 3 Chapter 2: Basic theoretical issues about financial structure and business efficiency of construction enterprises Chapter 3: Research methodology Chapter 4: Research results on the impact of financial structure on business efficiency of construction enterprises in Vietnam Chapter 5: Solutions and policy recommendations 4 CHAPTER 1 OVERVIEW OF THE RESEARCH SITUATION 1.1. Studies on the linear relationship between financial structure and business efficiency of enterprises 1.1.1. Financial structure has a positive impact on business efficiency of enterprises 1 .1.2. Financial structure has a negative impact on business efficiency of the enterprises 1.1.3. Financial structure does not affect business efficiency of the enterprises Table 1.1. Summary of empirical evidence on the impact of financial structure on business efficiency of enterprises Independent variables Result Author Debt ratio + Abor (2005); Zeitun and Gang Tian (2007); El-Sayed Ebaid (2009); Gill et al. (2011); Chowdhury and Chowdhury (2010); Sudiyatno et al (2012); Antwi et al. (2012); Asiri and Hameed (2014); Hoque et al. (2014); Khan (2012) - Le Thi Phuong Vy and Phung Duc Nam (2013) N/A Carpentier (2006); Karaca and Savsar (2012); Rajhans 2013); Asiri and Hameed (2014) Short-term debt ratio N/A Karaca and Savsar (2012) Long-term debt ratio + Chowdhury and Chowdhury (2010); Antwi et al. (2012) N/A Karaca and Savsar (2012) Asset structure + Robert M Hull and Varun Dawar (2014) - Zeitun and Gang Tian (2007); Muritala (2012); Onaolapo and Kajola (2010); Doan Vinh Thang (2016) N/A Zeitun and Gang Tian (2007); Muritala (2012); Onaolapo and Kajola (2010) Receivables structure - Le Thi Nhu (2017) N/A Le Thi Nhu (2017) Inventories structure - Le Thi Nhu (2017) N/A Le Thi Nhu (2017) Source: Summary of the author Note: (+): Positive impact; (-): Negative impact; N/A: No impact or impact with no statistical significance 1.2. Studies on the non-linear relationship between financial structure and business efficiency of enterprises Table 1.2. Table of empirical evidence on the impact of financial structure on business efficiency in a non-linear relationship Independent variable Result Author Capital structure Impact Nieh et al. (2008); Cheng et al. (2010); Lin and Chang (2011); Vo Xuan Vinh and Nguyen Thanh Phu (2014); Nguyen Thanh Cuong (2014); Berzkalne (2015) No impact Nguyen Huu Huan and Le Nguyen Quynh Huong (2014) Source: Summary of the author 1.3. Studies using quantile regression method to evaluate business efficiency of enterprises These empirical studies also provide: Commonly used methods: Descriptive statistics, correlation coefficient analysis, multivariate linear regression analysis with table data, then perform appropriate tests. Based on the empirical evidence and methods used in these studies, the thesis will inherit some ideas from previous studies, as well as supplement and adjust to better fit the research content. The proposed model along with research hypotheses to clarify research objectives will be presented in detail in the following chapter. 1.4. Research gaps Although there have been many studies on the impact of financial structure on business efficiency of enterprises in Vietnam, there are still some gaps as follows: (i) There have been some studies analyzing the influence of financial structure on business efficiency, however the sample is limited to listed enterprises but not all enterprises in the economy. (ii) There have not many studies assessing the impact of financial structure on business efficiency of a specific economic sector, especially construction industry. (iii) The use of quantile regression method to analyze the impact of financial structure on business efficiency of enterprises at different quantiles has not been applied much in research. 5 CHAPTER 2 BASIC THEORETICAL ISSUES ON FINANCIAL STRUCTURE AND BUSINESS EFFICIENCY OF CONSTRUCTION ENTERPRISES 2.1. Business operation characteristics of construction enterprises 2.1.1. Product characteristics 2.1.2. Characteristics of financial structure 2.2. Rationale for financial structure in the business 2.2.1. Concept of financial structure Financial structure is a combination of asset structure and capital structure consistent with business characteristics of enterprises in order to improve results and business efficiency of the enterprise. 2.2.2. Asset structure of enterprises Asset structure is a combination of short-term assets and long-term assets of an enterprise as measured by the proportion of each asset component in the total assets of the enterprise. 2.2.3. Capital structure of enterprises Capital structure which is a combination between liabilities and shareholder equity in enterprises is measured by one of the financial ratios such as debt ratio, shareholder equity ratio, debt to equity ratio and leverage ratio. These indicators represent the level of contribution of various components in total investment, indicating the level of debt use and the ability to ensure self-financing of enterprises. 2.3. Business efficiency of construction enterprises 2.3.1. Concept of business efficiency The business efficiency of an enterprise is an economic category, reflecting the level of using production factors to ensure the highest results in the condition of lowest costs to achieve the set goals. 2.3.2. Indicators measure the business efficiency of enterprises - Profitability indicator group: + According to book value: ROA; ROE; ROS; GM + According to market value: P/E, Tobin'Q - Indicator group reflect income, expense 2.3.3. Factors affecting business efficiency of enterprises - Capital structure - Enterprise age - Enterprise size - Growth rate - Asset structure 2.4. The role of financial structure to business efficiency of enterprises 2.5. Theoretical basis 2.5.1. The theory of optimal financial structure 2.5.2. The capital structure theory of Modigliani and Miller (M&M) 2.5.3. Trade off theory of capital structure (TOT) 2.5.4. Pecking Order theory (POT) 2.5.5. Timing Market theory 2.5.6. Optimum Asset Structure theory 2.5.7. Theories discussion CHAPTER 3 RESEARCH METHOD 3.1. Research design 3.2. Methods of data collection and processing 3.2.1. Methods of data collection 3.2.2. Methods of data processing 3.3. Research model 3.3.1. Dependent variables 3.3.2. Independent variables 6 Figure 3.2. Research model Source: Summary of the author Control variables - Enterprise size (SIZE) - Enterprise age (AGE) - Growth rate (GRO) Capital structure - Capital structure (CTNV) Business efficiency - ROA - ROE FINANCIAL STRUCTURE Asset structure - Property structure (CCTS) - Inventories structure (CCTK) - Receivables structure (CCPT) 7 Table 3.1. Abbreviations, explanations and expected impact direction of variables in the model Abbreviations Variable name Expected Measure Research Dependent variable ROE Return on Equity Net Income/ Shareholder Equity Zeitun and Gang Tian (2007); Le Thi Phuong Vy (2015); Nguyen Thanh Cuong (2014); Nguyen Thi Tuyet Lan (2019) ROA Return on Assets Net income/ Total Assets Variable explained CTNV Capital structure + Total debts/ Total assets Zeitun and Gang Tian (2007); Tran Hung Son (2008); Lin and Su (2008); Jiraporn and Tong (2010); Le Thi Phuong Vy (2015) CCTS Property structure + Fixed assets/ Total assets Zeitun and Gang Tian (2007); San and Heng (2011); Choi et al. (2014); Hoque et al. (2014) CCTK Proportion of inventories - Inventories/ Total assets Le Thi Nhu (2017) CCPT Proportion of receivables in total assets - Short-term receivables/ Total assets Le Thi Nhu (2017) Variable control SIZE Enterprise size + Ln (Total assets) Carpentier (2006); Choi et al. (2014); Le Thi Phuong Vy (2015) GRO Growth rate + (Revenue year t – Revenue year (t-1)) / Revenue year (t-1) Carpentier (2006); Chowdhury and Chowdhury (2010); Ahmad et al. (2012); Hasan et al. (2014); Le Thi Phuong Vy (2015) AGE Enterprise age + Year t - Year of establishment Hoque et al. (2014) Source: Author’s synthesis 3.3.3. Methods of estimating models a. OLS, FEM, REM methods b. GMM method c. Quantile regression method CHAPTER 4 RESEARCH RESULTS ON THE EFFECT OF FINANCIAL STRUCTURE ON BUSINESS EFFICIENCY OF CONSTRUCTION ENTERPRISES IN VIETNAM 4.1. Overview of Vietnamese construction enterprises in the period of 2012-2017 Table 4.1. Number and size of construction enterprises by enterprise size in the period of 2012-2017 Enterprise size Year Total 2012 2013 2014 2015 2016 2017 Micro enterprises 21,007 25,781 28,795 32,847 37,004 38,517 183,951 Small enterprises 21,467 21,075 21,017 21,238 22,856 23,902 131,555 Medium enterprises 644 640 597 585 593 572 3,631 Large enterprises 765 795 732 728 742 723 4.485 Total 43,883 48,291 51,141 55,398 61,195 63,714 323,622 Source: Authors' calculations Table 4.2. Number and structure of construction enterprises by the enterprise type in the period of 2012-2017 Enterprise type Year 2012 2013 2014 2015 2016 2017 Total 1. State enterprises 811 745 748 729 682 629 4,344 8 2. Private enterprises 42,585 47,114 49,924 54,138 59,966 62,489 316,216 3. FDI 487 432 469 531 547 596 3,062 Total 43,883 48,291 51,141 55,398 61,195 63,714 323,622 Source: Author’s' calculations 4.1.3. Situation of production and business activities of Vietnamese construction enterprises in period of 2012-2017 The size of construction enterprises in this period tended to increase with the average annual growth rate of 15.76% per year. In the period of 2012-2016, enterprises achieved a very high growth rate of total assets in YOY comparison. The growth rate of total assets is likely to decrease sharply in 2017. Figure 4.4. Size and growth rate of total assets of construction enterprises in the period of 2012-2017 Looking at the total assets of enterprises by their size, it can be seen that large enterprises have strong levels of business expansion with the average total assets increased from VND 400,028 million in 2012 to VND 531,409 million in 2017. 4.2. Current situation of financial structure of construction enterprises in Vietnam in the period of 2012-2017 4.2.1. Situation of asset structure of construction enterprises in Vietnam in the period of 2012-2017 a. Asset structure The proportion of short-term assets and long-term assets did not change much during the study period, short-term assets still accounted for the majority of the total assets of the construction enterprises (accounting for over 70%), which indicates that most of the construction machinery and equipment were hired and the enterprises did not pay much attention to invest in machinery and equipment. The proportion of short-term assets tended to increase in the period of 2012-2015 and tended to decrease in the period of 2016-2017. Figure 4.7. Asset structure of construction enterprises in the period of 2012-2017 Source: Author's calculations b. Proportion of inventories and receivables - Regarding the proportion of inventories: Generally, in construction enterprises, most of inventories are unfinished products. - Regarding the proportion of receivables: Figure 4.8 shows that the proportion of receivables of 2012, 2013, 2014 has not changed much until 2015 this proportion increased to 28.68% and in 2016 it decreased to 15,03%, and in 2017 this rate was very high at about 29.32%. Figure 4.9. The proportion of inventories and receivables in the total assets of construction enterprises during 2012- 2017 Source: Author’s calculations 0.00% 50.00% 100.00% 150.00% 2012 2013 2014 2015 2016 2017 71.29% 70.51% 71.79% 73.49% 72.63% 71.17% 28.71% 29.49% 28.21% 26.51% 27.37% 28.83% The proportion of Long-term Assets The proportion of Short-term Assets 0.00% 10.00% 20.00% 30.00% 2012 2013 2014 2015 2016 2017 25.71% 25.68%25.48% 28.68% 15.03% 29.32% The Proportion of Inventories in Total Assets The Proportion of Receivables in Total Assets 9 4.2.2. Situation of capital structure of Vietnamese construction enterprises in the period of 2012-2017 Due to the characteristics of the industry, the common construction enterprises will use loans to implement projects. Therefore, the construction enterprises will often have a large debt in the total capital. Figure 4.10. Capital structure of construction enterprises during 2012-2017 Source: Authors' calculations Considering the level of loan use of construction enterprises by the enterprise size, we can see some of the following characteristics: (i) The average capital structure of the entire construction enterprises was studied at a high level, with little variation and maintained at 60% to 65%; (ii) The capital structure of the micro enterprises is at the lowest range from 35% to 53%, showing that it is very difficult for these enterprises to access loans; (iii) Large enterprises have the highest capital structures due to taking advantage of the size and their capital structures even higher than the industry average and often maintain the debt ratio above 71%, (iv) Although the capital structure of the whole industry has been on a downward trend from 2013 until now, this index has shown some considerable fluctuations over years when measured by size. Figure 4.12. Structured sources of capital according to the size of the construction enterprises during 2012-2017 Source: Author's calculations 4.3. Situation of business efficiency of Vietnam construction enterprises in the period of 2012-2017 4.3.1. Business results of construction enterprises in the period of 2012-2017 - Regarding revenue: The revenue of the construction enterprises all increased over the years, on average each year in the period of 2012-2017, the revenue increase reached 10.68%. Figure 4.14. Total revenue by the enterprise type and average revenue of construction enterprises during 2012-2017 - 1,000,000 2,000,000 3,000,000 4,000,000 2012 2013 2014 2015 2016 2017 604,952 769,702 828,581 864,695 1,205,566 1,099,105 394,449 424,180 464,585 499,547 737,997 676,782 999,401 1,193,882 1,293,165 1,364,242 1,943,563 1,775,887 B il li o n V N D Liabilities Equity Total Capital 2012 2013 2014 2015 2016 2017 Micro enterprises 35.80% 51.26% 53.55% 50.42% 42.74% 40.30% Small enterprises 60.18% 62.38% 62.05% 62.37% 66.32% 64.23% Medium enterprises 66.75% 72.88% 71.75% 68.69% 69.07% 70.48% Large enterprises 72.06% 73.37% 71.82% 71.68% 72.28% 72.77% Average 60.53% 64.47% 64.07% 63.38% 62.03% 61.89% 60.53% 64.47% 64.07% 63.38% 62.03% 61.89% 58.00% 59.00% 60.00% 61.00% 62.00% 63.00% 64.00% 65.00% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Micro enterprises Small enterprises Medium enterprises Large enterprises Average 14,832 13,692 14,076 15,159 15,996 17,493 0 5,000 10,000 15,000 20,000 - 200,000 400,000 600,000 800,000 1,000,000 2012 2013 2014 2015 2016 2017 M il li o n V N D B il li o n V N D Total Revenue of State Enterprises Total Revenue of Private Enterprises Total Revenue of FDI Enterprises Average Revenue 10 Source: Author's calculations - Regarding profit before tax: Although the revenue of the construction enterprises increased steadily over the years, the profit before tax of the construction enterprises fluctuated significantly. Profit before tax of enterprises tends to increase, besides, profit before tax of private enterprises is larger than that of state enterprises and FDI enterprises. In regards of contribution to the profit of the whole construction industry, profit of private enterprises account for a large proportion, usually accounting for about 60% of the profits of the whole industry. Figure 4.15. Profit before tax by ownership type and profit of construction enterprises during 2012-2017 Source: Author's calculations However, there is a fact that in this period, there is a huge number of enterprises with loss of business results, especially from 2014-2017, the number of enterprises reporting losses accounted for over 35%, especially in 2017, the number enterprises with negative profits accounted for 39.66%. 4.3.2. Business efficiency of construction enterprises in the period of 2012-2017 In general, business efficiency of construction enterprises calculated based on ROA and ROE of enterprises in the industry is low and tends to decrease sharply in the research period. Table 4.9. ROA by the size of construction enterprises in the period of 2012-2017 Unit: % Enterprise size Year General 2012 2013 2014 2015 2.016 2.017 Micro enterprises -5.119 0.181 -1.128 -1.339 -1.315 -2.703 -1.792 Small enterprises -0.188 0.357 0.466 0.563 0.437 0.594 0.377 Medium enterprises 2.466 0.636 1.438 1.429 1.228 1.062 1.383 Large enterprises 1.618 1.222 1.297 0.781 1.813 1.870 1.433 General -2.414 0.282 -0.402 -0.527 -0.596 -1.367 -0.817 Source: Author's calculations Table 4.10. ROE by the size of construction enterprises in the period of 2012-2017 Unit: % Enterprise size Year General 2012 2013 2014 2015 2.016 2.017 Micro enterprises -13.355 -0.502 -2.943 -2.507 -2.842 -9.734 -5.086 Small enterprises -4.300 -6.008 -1.611 1.796 0.50 -4.620 -2.379 Medium enterprises 7.907 0.841 5.498 4.406 3.669 4.632 4.490 Large enterprises 4.311 4.690 7.252 2.437 6.863 7.998 16.194 General -8.179 -2.817 -1.203 -0,661 -1.406 -7.462 -3.563 Source: Author's calculations 4.4. Quantitative research results 4.4.1. Descriptive statistics 4.4.2. Tests For model 1: Research uses Chi Square test and comes to conclusion that model 1 has endogenous factors. To overcome the endogenous phenomena, the thesis uses the Generalized Method of Moments (GMM) method. For model 2: Similar to model 1, the conclusion is that model 2 has no endogenous factors. 225 77 154 192 244 336 0 100 200 300 400 - 10,000 20,000 30,000 2012 2013 2014 2015 2016 2017 M il li o n V N D B il li o n V N D Profit Before Tax of State Enterprises Profit Before Tax of State Enterprises Profit Before Tax of FDI Enterprises Average Profit 11 4.4.3. The regression results Table 4.12. Estimated results with ROA as the dependent variable Variable Dependent variable ROA (Model 1) OLS FEM REM GMM Capital structure 0.235 *** 0.342 *** 0.235 *** 0.080 *** (0.047) (0.060) (0.047) (0.010) Property structure 0.175 *** 0.175 *** 0.175 *** 0.080 *** (0.042) (0.042) (0.042) (0.006) Receivables structure -0.227 *** -0.303 *** -0.227 *** -0.131 *** (0.025) (0.032) (0.025) (0.005) Inventories structure -0,022 *** -0.038 *** -0,022 *** -0.010 *** (0.007) (0.007) (0.007) (0.001) Enterprise size 0.002 ** 0.002 ** 0.002 ** 0.001 *** (0.001) (0.001) (0.001) (0.000) Growth rate 0.000 0.000 0.000 -0,000 (0.000) (0.000) (0.000) (0.000) Enterprise age 0.000 * 0.000 0.000 * 0.000 *** (0.000) (0.000) (0.000) (0.000) Constant -0.021 -0.004 -0.021 0.003 (0.015) (0.015) (0.015) (0.002) Number of observations 83,472 83,472 83,472 83,472 Prob> F 0.000 Hausman Prob> Chi2 0.000 *, **, *** represent estimated coefficients with statistical significance, respectively, 10%, 5% and 1%. Source: Author's calculations Table 4.13. Estimated results with ROE as the dependent variable Variable Dependent variable ROE (Model 2) OLS FEM REM Capital structure 0.443 ** 0.717 *** 0.443 ** (0.215) (0.274) (0.215) Property structure 0.449 ** 0.449 ** 0.449 ** (0.190) (0.190) (0.190) Receivables structure -0.567 *** -0.776 *** -0.567 *** (0.112) (0.143) (0.112) Inventories structure -0.127 *** -0.181 *** -0.127 *** (0.030) (0.031) (0.030) Enterprise size 0.017 *** 0.016 *** 0.017 *** (0.005) (0.005) (0.005) Growth rate 0.000 0.000 0.000 (0.000) (0.000) (0.000) Enterprise age 0.001 0.000 0.001 (0.001) (0.001) (0.001) Constant -0.098 -0.038 -0.098 (0.068) (0.068) (0.068) Number of observations 83,472 83,472 83,472 Prob> F 0.000 Hausman Prob> Chi2 0.000 *, **, *** represent estimated coefficients with statistical significance, respectively, 10%, 5% and 1%. Source: Authors' calculations Table 4.14. Summary of the impact results of variables on the business efficiency of construction enterprises Independent variable Dependent variable ROA Expectation Result ROA ROE Capital structure + + + In accordance with TOT theory Property structure + + + In accordance with TOT, POT theory Receivables structure - - - Correct Inventories structure - - - Correct Enterprise size + + + In accordance with TOT theory, agency cost theory Growth rate N/A N/A + Wrong Enterprise age + N/A + Exactly a complaint Note: "-": Negative impact with statistical significance; "+": Positive impact with statistical significance; "N/A": Impact with no statistical significance Source: Author’s synthesis The average regression analysis have the following results: (i) No relationship between revenue growth rate and business efficiency of construction enterprises was found; (ii) The more the enterprises loan, the higher the business efficiency is; (iii) The greater the proportion of fixed assets is, the more effectively the enterprises operate; (iv) The higher the inventories structure is, the lower the business efficiency is for both ROA and ROE variables; (v) A negative relationship between receivables structure and business efficiency of enterprises was found; (vi) Enterprises with more business operation time will operate more effectively than newly established enterprises. 12 4.4.4. Quantile regression results In general, the results of quantile regression research show that there is a strong differentiation of the impact level of the factors on each group of enterprises at each quantile of the business efficiency. It means that this signal will be different when considered at different quantiles. Therefore, to achieve the highest efficiency level, the business manager should focus on factors affecting business efficiency in correspondence with the quantile of their own enterprise. For enterprises with business efficiency at the 0.1 quantile and 0.25 quantile, it is recommended to increase the use of debt rather than the use of equity. Table 4.15. Quantile regression results with ROA as the dependent variable Variable Dependent variable ROA Quantile regression 0.1 0.25 0.5 0.75 0.9 Capital structure 0.297*** 0.041*** -0.032*** -0.033*** -0.133*** (0.005) (0.003) (0.001) (0.003) (0.009) Property structure 0.003 0.005* 0.001 0.001 -0.001 (0.005) (0.002) (0.001) (0.002) (0.008) Receivables structure -0.215*** -0.061*** -0.022*** -0.028*** 0.001 (0.003) (0.001) (0.001) (0.001) (0.004) Inventories structure 0.014*** 0.012*** 0.008*** 0.006*** 0.004*** (0.001) (0.000) (0.000) (0.000) (0.001) Enterprise size -0.000 0.000*** 0.000*** 0.000*** 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) Growth rate -0.000*** -0.000 0.000* 0.000 -0.000 (0.000) (0.000) (0.000) (0.000) (0.000) Enterprise age 0.000 -0.000*** 0.000*** 0.000*** 0.000*** (0.000) (0.000) (0.000) (0.000) (0.000) Constant -0.007*** 0.002*** 0.012*** 0.018*** 0.046*** (0.002) (0.001) (0.000) (0.001) (0.003) Number of observations 83,472 83,472 83,472 83,472 83,472

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