The factors affecting the application of integrated reports in listed enterprises on the Vietnamese stock market

enterprises in the stock market in particular. Therefore, it is necessary to have an in-depth study investigating the factors affecting the process of changing from using financial statements to the application of integrated reports. The reason is that provision of financial and non-financial information of businesses is a critical requirement in accordance with international practice and the information demand of users. Due to the above research gaps, it is necessary to have more in-depth, comprehensive and reliable research on the factors affecting the application of integrated reports in listed companies. The study examined the period from 2015 to 2017. Particularly, 2015 is an important milestone when Circular 155/2015/ TT-BTC on information disclosure on stock market was issued (replacing Circular No. 52/2012/TT-BTC). This Circular is a legally significant paper ensuring the transparency of the stock market to meet the increasing information requirements of investors in the market. CHAPTER 2: THEORETICAL FOUNDATION 2.1. Integrated reporting 2.1.1. Formation and development of the Integrated Reporting 2.1.2. Definition and nature of the Integrated Reporting 2.1.2.1. Definition of the Integrated Reporting Integrated reporting is an emerging concept which can be described as a comprehensive approach to financial and non-financial reporting for investors and other stakeholders, which describes the connection between strategies, management, risks, financial and non-financial information in the short, medium and long term. 8 2.1.2.2. Nature of the Integrated Reporting IIRC introduced an internationally accepted framework of integrated reporting on sustainable development accounting in 2013. This framework requires the compilation of all financial information, environment, society, and corporate governance must be clear, concise, relevant and comparable in an ‘integrated’ format. The report must express its purpose and help readers easily see the business performance, future vision as well as historical value of organizations towards sustainable development, global integration, and other arising requirements of related parties. Therefore, to prepare integrated reports, enterprises need to engage with stakeholders, especially investors in order to identify key issues concerned by parties and the degree of direct impact on enterprises. By preparing complete integrated reports, enterprises can enhance confidence in investors and thereby, positively affect the stock price of these companies. Therefore, integrated reports should provide information to help investors understand how enterprises create value over time through the use of input resources, including financial and non-financial resources. What all stakeholders want to know are issues affecting business activities now and in the future. 2.2. Principles and content of an Integrated Report 2.2.1. Principles of an Integrated Report under IIRF 2.2.2. Content of an Integrated Report under IIRF 2.2.3. Types of capitals and value creating process of the Integrated Report under IIRF 2.3. Fundamental theories 2.3.1. Legitimacy theory Legitimacy theory derives from the concept of organizational legitimacy. Suchman (1995) defined legitimacy as “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions”. Legitimacy theory is a mechanism supporting enterprises to make voluntary disclosure of social and environmental information to perform “social contracts” between an organization and the society in which it operates. In such an environment, companies try to legalize their actions by preparing CSR reports for the purpose of social approval. The organization shall demonstrate its existence through legally economic and social actions, without jeopardizing the existence of the society as well as the environment in which it operates. 2.3.2. Stakeholder theory Stakeholder theory (Freeman, 1984) addresses the expectations of specific groups in society (Smith et al., 2011). This theory considers the impact of expectations of stakeholders on information disclosure because some groups are more powerful than others. Stakeholders’ support is critical to the long-term existence of companies, and therefore companies must adjust activities to address stakeholders’ concerns. 2.3.3. Signal theory Signal theory was introduced in early 1970, based on the contributions of two main researchers Arrow (1971) and Spence (1973). Signal theory refers to information asymmetry between managers and stakeholders, in which the source of asymmetric information is primarily related to the quality of information that is publicly available. Therefore, a company that publishes information to the market sends signals to investors to 9 distinguish its operation from others’. The disclosure of voluntary information is more than legal regulations so that they can give better signals, optimize financial costs and increase the value of the company. 2.3.4. Agency Theory Jensen and Meckling (1976) defined the relationship between shareholders and managers as a social contract in which the role of the manager is to perform the management of the company, including power to make decisions about the company’s assets. In fact, a company’s top managers (executive directors or the Board of Directors) are chosen by the company’s shareholders. These people will be empowered by shareholders to make decisions on behalf of shareholders, aiming at the common goal of developing the company. 2.3.5. Theory of planned behavior The theory of planned behavior was developed from the theory of reasoned action (TRA). The TRA of Fishbein and Ajzen (1975) provided two attitude factors: behavior and subjective standards that show the pressure from society. 2.4. Factors affect the application of integrated reports in enterprises 2.4.1. Managerial ownership 2.4.2. Enterprise size 2.4.3. Profitability 2.4.4. Institutional ownership 2.4.5. Pressure from stakeholders 2.4.6. Audit quality 2.4.7. Foreign investment CHAPTER 3: METHODOLOGY 3.1. Qualitative research 3.1.1. Qualitative research process 3.1.1.1. Steps of qualitative research 3.1.1.2. Research sample 3.1.1.3. Data collection 3.1.1.4. Data analysis 3.1.2. Conceptual framework 10 Figure 3.1. Conceptual framework of factors affecting the application of integrated reports of enterprises 3.1.3. Research hypotheses 3.2. Quantitative research 3.2.1. Quantitative research process 3.2.2. Research models Frıas-Aceituno et. al (2012); Frias-Aceituno et. al (2014) Kurniawan (2018); Girella et. al (2019) applied multiple linear regression model to evaluate the factors affecting the application of integrated reports. As research data is panel data so regression equations are presented as follows: Regression equation (1) IR=
0 +
1 SIZE it+
2 ROA it +
3 MGO it +
4 QSH it +
5 FRO it +
6 PRE it +
7 BIG4 it + ɛit Regression equation (2) IR=
0 +
1 SIZE it+
2 ROA it +
3 MGO it +
4 QSH it +
5 FRO it +
6 PRE it +
7 BIG4 it + ωit 3.2.3. Measurement scales 3.2.3.1. Application of integrated reports Literature review showed that there are many different methods to measure application of integrated reports. Many researchers analyzed the content of enterprises’ reports, others measured application of integrated reports by building a checklist of the contents of the reports, then calculating indicators of information disclosures according to IIRF. Indicators of information disclosures were developed based on the 8 required contents 11 of the International framework of integrated reporting, including (1) organizational overview and external environment; (2) Corporate governance; (3) business model; (4) Risks and opportunities; (5) Strategy and resource allocation; (6) performance; (7) Outlook; (8) Basis of preparation and presentation of integrated reports. This research applied the set of indicators to measure the application of integrated reports of Stent and Dowler (2015); Herath and Gunarathne (2016); Gunarathne and Senaratne (2017). Furthermore, the contents of integrated reports were analyzed and evaluated according to IIRC’s guidance framework which consists of 40 criteria, with a maximum total score of 78. If an enterprise disclosed information equivalent to an indicator of the set of indicators developed in this research, that indicator is labeled “1”, otherwise it is labeled “0”. The total scores measure application of integrated reports of companies. The formula is presented as follows: DI =      In which, DI: Indicator of information disclosure of enterprise i di: score of information disclosure in which di = 1 if information indicator is disclosed ; di = 0 1 if information indicator is not disclosed) m: total number of indicators disclosed by enterprise DN i n: total number of indicators under IIRF (n= 78) 3.2.3.2. Measurement of independent variables (1) Enterprise size (SIZE) In this study, enterprise size is measured by natural logarithm of total assets Enterprise size = Ln (Total assets) (2) Profitability (ROA) ROA= Profits after taxes / Total average assets (3) Managerial ownership (MGO) Proportion of managerial ownership = Shares held by managers and the board of dirrectors x 100% Total shares outstanding (4) Institutional ownership (QSH) Proportion of institutional ownership = Shares held by institutions x 100% Total shares outstanding (5) Foreign investment (FRO) Proportion of foreign investment = Shares held by foreign investors x 100% Total shares outstanding 12 (6) Pressure from stakeholders (PRE) Pressure from stakeholders = Shares held by the government and large sharholders x 100% Total shares outstanding (7) Audit quality (BIG 4) To measure the quality of audit, the research used nominal variable with value of 1 if an enterprise is audited by 4 and value of 0 if an enterprise is not audited by Big 4. 3.2.4. Research sample The sample selected in this study consists of listed companies on Vietnam’s stock market. The research applied non-probability sampling method. Specifically, companies selected include listed companies competing for the Best Annual Reports, Sustainable Development Reports, organized by Ho Chi Minh Stock Exchange, Hanoi Stock Exchange, Investment Newspaper and Dragon Capital. The observation period in this study was 3 years, from 2015 to 2017. The reason for choosing 2015 is that it is an important milestone when Circular 155/2015/ TT-BTC on information disclosure on stock market was issued (replacing Circular No. 52/2012/TT-BTC). Due to large scale of the sample, research sample was selected based on clear criteria, namely (1) companies competing for the best annual reports, annual Sustainable Development Reports (at least 1 time) during the period from 2015 to 2017; (2) companies which have prepared Sustainable Development Reports or used the GRI standards in preparing the Sustainable Development Reports, Annual Reports, and Integrated Reports, (3) companies whose reports can be accessed on their official websites or website of Vietnam stock exchange (4) Managers of these companies have published their annual reports and sustainable development reports in the period of 2015-2017. Based on the purposive sampling method, 100 listed companies were selected (Appendix 1). The observation period was 3 years and the total number of observations was 300 observations. 3.2.5. Data collection Financial data was collected from annual reports of enterprises to calculate research indicators Non-financial data was collected directly from annual reports and sustainable development reports of enterprises on the website 3.2.6. Data analysis 3.2.6.1. Descriptive statistics 3.2.6.2. Correlation analysis 3.2.6.3. Regression analysis * Panel data regression (1) Pooled Ordinary least squares (Pooled OLS) (2) Fixed effects model (FEM) (3) Random effects model (REM) * Regression analysis 13 CHAPTER 4: RESEARCH RESULT 4.1. Overview of the Vietnam’s stock market and survey results on the publication of reports of listed enterprises 4.1.1. Overview of the Vietnam’s stock market 4.1.2. Survey results on the publication of reports of listed enterprises 4.2. Results of qualitative research 4.2.1. In-depth interviews with experts on the understanding of Integrated Reports 4.2.1. The survey results with experts 4.3. Results of quantitative research 4.3.1. Descriptive statistics and correlation between variables 4.3.1.1. Descriptive statistics Table 4.1. Descriptive statistics of independent variables Variable Obs Mean Std. Dev. Min Max SIZE 300 29.20303 1.97454 25.158815 34.723 ROA 300 0.0840977 0.076846 -0.055 0.7219 MGO 300 0.1784589 0.2273966 0 0.967 QSH 300 0.5941318 0.2701894 0 0.995342 PRE 300 0.5422883 0.2241256 0 0.967 FRO 300 0.2046867 0.1617687 0 0.66 Source: Output from Stata Table 4.2. Descriptive statistics of nominal variable Big4 Freq. Percent Cum. 0 35 35 35 1 65 65 100 Total 100 100 Stata Source: Output from Stata Table 4.3. Descrivetive statistics of dependent variables Variable Obs Mean Std. Dev. Min Max IR 300 0.6604167 0.1198602 0.5 1 Stata Source: Output from Stata 4.3.1.2. Correlation analysis 14 The IR variable has a relatively strong and positive correlation with SIZE (0.62); FRO (0.4187); BIG4 (0.5375). This shows that large-scale enterprises, large foreign investment and reports audited by Big4 with strategic visions are more likely to apply integrated reports to pursue sustainable development strategies for their businesses. The correlation coefficients of ROA, MGO, QSH, PRE are low which indicates that profitability, managerial ownership, institutional ownership, pressure from stakeholders are not associated with the application of integrated reports of enterprises 4.3.2. Ordinary least squares 4.3.2.1. Multicollinearity With VIF values less than 10, multicollinearity is not significant in the model. Therefore, it is appropriate to put independent variables into the same model for regression analysis. 4.3.2.2. Analysis of ordinary least squares Table 4.4. Output of OLS Number of obs = 300 F (7, 292) = 60.89 Prob > F = 0.0000 R-squared = 0.5935 Adj R-squared = 0.5837 IR Coef. Std. Err. t P>t [95% Conf. Interval] SIZE 0.0301893 0.002773 10.89 0.000 0.247309 0.0356477 ROA 0.106578 0.061859 1.72 0.086 -0.0151672 0.2283237 MGO 0.143727 0.020671 6.95 0.000 0.1030428 0.1844105 QSH -0.00019 0.023782 -0.01 0.994 -0.0469954 0.0466179 PRE -0.10148 0.029305 -3.46 0.001 -0.1591543 -0.0438016 FRO 0.174686 0.032116 5.44 0.000 0.1114787 0.2378932 Big4 0.060638 0.012062 5.03 0.000 0.0369273 0.0843477 _cons -0.27604 0.080561 -3.43 0.001 -0.4345981 -0.117491 Stata Source: Output from Stata For the analysis of panel data, the Pooled OLS method can distort the relationship between the independent and dependent variables of the observations in the sample. Therefore, Pooled OLS is not the optimal method. 15 4.3.3. Fixed Effects Model (FEM) Table 4.5. Output of FEM Number of obs = 300 F (7,191) = 1.39 Prob > F = 0.2107 R-squared = 0.4163 IR Coef. Std. Err. T P>t SIZE 0.0444301 0.0195101 2.28 0.024 ROA 0.0967849 0.0823981 1.17 0.242 MGO 0.0788998 0.0566711 1.39 0.165 QSH 0.0105654 0.0470169 0.22 0.822 PRE 0.0215358 0.0666830 0.32 0.747 FRO 0.0621287 0.0692580 0.9 0.371 Big4 -0.0258839 0.0692224 -0.37 0.709 _cons -0.6730580 0.5696972 -1.18 0.239 Source: Output from Stata REM was conducted and Hausman test was used to choose between FEM and REM. 4.3.4. Random Effects Model (REM), Table 4.6. Output of REM Number of obs = 300 Wald chi2(7) = 205.27 Prob > chi2 = 0.0000 R-squared = 0.5924 IR Coef. Std. Err. z P>z SIZE 0.0306848 0.0038857 7.90 0.0000 ROA 0.0997647 0.0643593 1.55 0.1210 MGO 0.1311937 0.0269384 4.87 0.0000 QSH -0.0063295 0.0281891 -0.22 0.8220 PRE -0.0837868 0.034773 -2.41 0.0160 FRO 0.1636586 0.0380974 4.30 0.0000 Big4 0.0585543 0.0166044 3.53 0.0000 _cons -0.290183 0.1121778 -2.59 0.0100 Source: Output from Stata Fixed effect models conceptualize the differences between studies as the result of random error, but random effects models regard such discrepancies as the result of the effect size being distributed according to some probability density function. Therefore, in order to 16 choose between FEM and REM, the Hausman test was used to select the best model for the research. 4.3.5. Hausman test and autocorrelation Table 4.7. Hausman test Chi2 Prob>chi2 Note 5.79 0.5641 Source: Output from Stata Table 4.11 shows that Chi2 = 5.79 and p-value = 0.5641 > 0.05, this indicates that H1 is rejected and H0 is accepted. Therefore, REM fits better in this study. After that, autocorrelation was tested for REM. The results are shown in the following table. Table 4.1. Test for autocorrelation F (1, 98) Prob > F 15.569 0.0001 Source: Output from Stata The test for autocorrelation shows that F (1.98) = 15,569, p-value = 0.0001 <0.05. It indicates that that autocorrelation still exists in the model; therefore, it is necessary to correct for the presence of autocorrelation in the model. 4.3.6. Random Effects Model with robust SE Table 4.9. Random Effects Model with robust SE Number of obs = 300 Wald chi2(7) = 332.30 Prob > chi2 = 0.0000 R-squared = 0.5883 IR Coef. Robust Std. Err. Z P>z SIZE 0.0294403 0.0037026 7.95 0.000 MGO 0.1345328 0.0289418 4.65 0.000 PRE -0.0862886 0.022304 -3.87 0.002 FRO 0.1682797 0.037931 4.44 0.000 Big4 0.0594343 0.0127451 4.66 0.000 _cons -0.2499969 0.0109081 -2.29 0.022 Source: Output from Stata Table 4.13 shows that Wald chi2(7) = 332.3, p-value = 0.0000< 0.05. This means that REM is an appropriate model for this study 17 CHAPTER 5: DISCUSSION, RECOMMENDATIONS, CONCLUSION 5.1. Discussion 5.1.1. Comparison of models After comparing three regression models OLS, FEM and REM as well as based on the REM (robust SE), the following regression model was used in this study IR= - 0.2499 + 0.02944 * SIZE it + 0.11345 * MGO it + 0.16823* FRO it - 0.08628* PRE it + 0.0594 * BIG4 it + ωit Based on the research hypotheses and results of REM (robust SE), a comparison was made between expectation and results of REM. It is shown in table 5.2 as follows: Table 5.1. Comparison between expectation and results of REM (robust SE) Hypothesis Factor Expectation Result REM (robust SE) p-value H1 Managerial ownership + + 0.1345328 0.000 H2 Enterprise size + + 0.0294403 0.000 H3 Profitability + H4 Institutional ownership + H5 Pressure from stakeholders + - - 0.0862886 0.002 H6 Foreign investment + + 0.1682797 0.000 H7 Audit quality + + 0.0594343 0.000 Source: Output from Stata 5.1.2. Discussion of research results 5.1.2.1. Managerial ownership (MGO) There is a positive relationship between managerial ownership with the application of integrated reports in enterprises, coefficient = 0.02944, p-value = 0.000. The results showed that the greater the ownership rate of managers, the higher probability of application of integrated reports. Hypothesis H1 is accepted. This result can be explained by agency theory. According to agency theory, the separation between managers and shareholders can lead to a conflict of interests. The conflict of interests might decrease as managers hold more of the company’s shares. Therefore, companies with members of the Board of Directors and managers holding a large proportion of stocks often want to minimize this conflict so they will publish more information. The role of senior managers in developing development strategies is very important. Their level of participation and support has a strong impact on the application of integrated reports. The research confirms the role of senior manager in developing economies like Vietnam. A good manager will make plans, 18 organize resources and make sure everyone understands what is going on, drives team members to succeed. 5.1.2.2. Enterprise size (SIZE) The enterprise size (SIZE) has a positive relationship with the application of integrated reports, coefficient = 0.13453, p-value = 0.000. The results show that the larger the scale of an enterprise, the higher the probability of applying integrated reports. In other words, hypothesis H2 is accepted. The reason is that large-scale enterprises are usually subject to supervisor from stakeholders. According to legitimacy theory and stakeholder theory, a large-scale enterprise requires develop strategies to minimize the impact from these monitoring activities. Firm size is an important factor motivating managers to develop the sustainable development. Large-sized enterprises have sufficient financial potential to develop and apply integrated reporting. This process requires the coordination of departments within the enterprise and the cost of application might be very high. According to the Article 54 of Decree 58/2012 / ND-CP dated July 20, 2012 of the Government, in order for companies to be listed on Vietnam’s stock market, they must be joint stock companies with the charter capital at the time of registration of at least VND 30 billion according to the book value. In the future, it is expected that Vietnamese enterprises will grow stronger and more businesses will participate in the stock market. According to the signal theory, large-scale enterprises applying integrated reporting might send good signals to related parties, improve the position of enterprises with foreign investors, facilitate the companies to attract foreign investors from developed countries. 5.1.2.3. Pressure from stakeholders (PRE) The pressure from stakeholders has a negative relationship with the application of integrated reports in enterprises, coefficient = -0.0863, p-value = 0.002. The results show that the greater the pressure from related parties, the less likely the enterprises want to publish information, or the lower the probability of applying integrated reports. In other words, as the pressure from stakeholders increase (in other words, the demand for information disclosure increases), senior managers of SMEs tend to reduce the level of information disclosure or lower the probability of applying integrated reports. In this study, the sample consisted of companies competing for the best annual reports. Therefore, these companies made comprehensive disclosure of financial and non-financial information, and committed to implementing the sustainable development strategies in their business activities. Enterprises in the sample were required to disclose information on business performance, social and environmental efficiency and the quality of information disclosure of such companies is increasing. In this study, the demand of information disclosure from stakeholders is relatively low because senior managers disclosed financial and non-financial information in a comprehensive manner. In other words, all SMEs must comply with the Ministry of Finance’s Circular No. 155/2015/TT-BTC on the information disclosure on the stock market. Furthermore, enterprises competing for annual reports improved the quality of their information. The main motivation for enterprises to apply integrated reports is based on internal factors such as the enterprise’s strategic vision and mission to establish sustainable development in their business activities, and not on based on the pressure from related parties. 5.1.2.4. Foreign investment (FRO) Foreign investment (FRO) has a positive relationship with the application of integrated reports in enterprises, coefficient = 0.1683, p-value = 0.000. The results showed 19 that the greater the foreign investment, the higher the probability of applying integrated reports. Hypothesis H6 is accepted. The research results showed the significant role of foreign investors in the application of integrated reports in enterprises. This means that in order to attract foreign investors, it is critical for enterprises to provide transparent, relevant reports on business activities and get audited according to international standards. Attracting foreign investors can both enhance capital and the reputation of enterprises, along