What determines the transparency of Dutch companies?
Master Thesis, MSc, International Business and Management
,
University of Groningen, Faculty of Economics and Business
Abstract
This study investigates the determinants of the transparency of Dutch companies, defined as the content and quality of their corporate social responsibility (CSR) reports. Besides using firm characteristics, this study also assess to what extent the top management team (TMT) composition influences the degree of transparency. The TMT is responsible for the day-to-day managing of the firm and therefore determines the transparency of the firm. For the measurement of the degree of transparency the Transparency Benchmark will be used. The Transparency Benchmark annually analyzes the quality of corporate social responsibility reports of Dutch companies. This is a unique opportunity as this benchmark has never been used for this purpose before. A multiple regression analysis was used to determine what influences the transparency. The findings indicate that the TMT’s with a low proportion of foreigners are more transparent. In addition, the findings indicate that larger firms are more transparent.
Table of Contents
1. Introduction ... 1
2. Theory and hypotheses ... 3
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1. Introduction
The debate in society about the ethical and social aspects of business is a lively one. This debate has forced companies to react to the social and ethical pressure of the public and thus becoming more transparent (Graafland, Eijffinger and Smid, 2004). It is interesting to see which of the many factors influence the choice of companies to become transparent. This study is privileged to use the Transparency Benchmark (Transparentiebenchmark, 2014) to analyze the extent of transparency of companies. The Transparency Benchmark annually analyzes the content and quality of corporate social responsibility (CSR) reports of Dutch companies since 2004. The uniqueness of this benchmark is that it has never been used for this purpose before. Furthermore, the assessment is done by accountants (external parties) and not by the companies themselves and is therefore highly reliable. In addition data concerning the top management team (TMT) of big Dutch companies will be used. This combination provides us with a great opportunity to do research on what determines the transparency of Dutch companies. Which in this research is defined as the content and quality of CSR reporting.
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Another reason could be, it is not seen as interesting as they perceive it will not increase sales (Kolk, 2005b; Kolk, 2010). Research has shown that factors, such as size (Lee and Hutchison, 2005; Kolk, 2005a; Meznar and Nigh, 1995; Udayasankar, 2008), and industry (Dye and Sridhar, 1995; Patten, 2002; Cho and Patten, 2007; Haniffa and Cooke, 2005) influence the extent of CSR reporting. With varying levels of success, profitability has also been used on many occasions in order to see if there was a relation with CSR reporting (Jennifer Ho and Taylor, 2007; Tagesson, Blank, Broberg, Collin, 2009; Ragothaman and Carr, 2008).
Complementary to previous empirical studies, this study will, besides focusing on company characteristics, also focus on the influence of TMT composition on the degree of transparency. According to the upper echelon (UE) theory a TMT consists of the top decision makers of a firm. The UE theory focuses on these top decision makers in organizations and state that executive’s experiences, values and personalities greatly influence their interpretations of the situation they face and, in turn, affect their choices (Hambrick and Manson, 1984). Therefore, whether a company is transparent highly depends on the TMT (Egri and Herman, 2000). Despite the broad literature on transparency, few studies analyze the effect of TMT composition on the degree of transparency (Strand, 2012; Lau, Lu, Liang, 2014). This paper will contribute to the existing body of knowledge about transparency by investigating the relationship with TMT composition. Were the degree of transparency is measured by the content and quality of the CSR reports. This study will therefore add to the scarce research on transparency of Dutch companies (Van de Burgwal and Vieira, 2014; Chaudhri, and Ye, 2015) by providing new empirical data. The Netherlands provides a great opportunity to test the determinants of transparency as the majority of the companies are not forced to provide a CSR report. Secondly, the results of this study will contribute to the existing contradicting knowledge about the determinants of transparency. Thirdly, it will investigate to what extent TMT composition influences disclosure. Therefore, this paper will clarify the relationship between firm and TMT characteristics and disclosure. The purpose of this study is to expand the knowledge about the determinants of transparency. Furthermore, this study identifies whether TMT composition influences the degree of transparency. The research question is: What determines the transparency and to what extent does TMT composition influence the transparency of Dutch companies? In order to answer this question a multiple linear regression analysis will be used.
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and later on information concerning the data collection and data analysis. Finally, the implications of this study will be discussed and will end with a conclusion and the limitations of this study.
2. Theory and hypotheses
2.1. Literature review
Businesses have a big impact on the environment and therefore have a big responsibility in order to preserve the environment. The decision of a company to be transparent can therefore be seen as a strategic choice as the information can be used by investors, nongovernmental organizations (NGO’s), customers and regulators to act upon. The idea of being transparent started around four decades ago when the societal awareness and the concerns about the impact of businesses on the environment have risen (Van de Burgwal and Vieira, 2014). The attention for transparency gradually gains more attention as the years gone by and drew global attention during the 1990s (Gamble, Hsu, Jackson and Tollerson, 1996). Some big Dutch firms in the 1990s started reporting on CSR issues however this was not directly followed by other Dutch companies (KPMG, 2008). Maignan and Ralston (2002) found a similar result in their study about CSR in the business communication of companies in, among others the Netherlands in the year 1999. They found that companies from the Netherlands were lagging behind in respect to actively mention their CSR activities on their websites in comparison to other countries. In their sample, which consisted of roughly 400 big Dutch companies, only 24% of the companies mentioned their CSR activities on their website, in comparison to the other countries in the sample this is very low. Around 1999 the government made an amendment on a law (Stb, 1997) which required companies which cause serious impact on the environment to compile a report (Wetten overheid, 1998). The AMvB1 (Algemene Maatregel van Bestuur) decides which industries comply too the above criteria (Stb, 1998). Starting 2005 these reports were not made publicly anymore due to the high costs involved for the companies and the low interests of the public (Duurzaam ondernemen, 2004). However, the government does stimulate companies to provide a CSR report by use of the Transparency Benchmark (Transparantiebenchmark, 2014). DHV (2001) argues that corporate social responsibility will play a bigger role in the Netherlands since there has been an increasing amount of firms reporting. A survey of KPMG of 2008 revealed that around 2005 more and more firms started to report on corporate responsibility (some more than others) which places the Netherlands along the top corporate
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reporters. Furthermore KPMG (2008) mentions that there is an increasing amount of companies disclosing. Many companies publish a CSR report on a voluntarily basis, most of them which comply with the Global Reporting Initiative (GRI) guidelines (MAB, 2004; MAB, 2008). Especially, the companies in polluting industries often report on their activities (Cho and Patten, 2007).
Recently, the European Union (EU) has acknowledged the importance of CSR reporting and forces big companies in the EU which have more than 500 employees and have an environmental impact to compile a report (MVO Nederland, 2014). For the Netherlands this means that around 100 companies are required to compile a CSR report starting 2016 (MVO Nederland, 2015). In this report these companies need to provide information concerning the financial and non-financial developments, achievements and the impact of the companies they invest in. In the Netherlands the Transparency Benchmark (Transparantiebenchmark, 2014) will be used to make sure the companies comply (MVO Nederland, 2014).
As mentioned earlier, companies active in industries which have an impact on the environment are expected to compile reports about their activities concerning the environment. An example is the European Pollutant Release Transfer Register (EPRTR) which is a register where the public can see the polluting emission of companies (RVO, 2015). This information comes directly from the companies themselves which are obliged to provide data on this matter. Having to provide data like this can be useful when compiling the CSR report, since they already have this data. Companies active in other industries (like the service industry) do not have to provide this data and thus will probably feel less pressure to disclose information concerning their CSR activities.
Some of the benefits which could be derived from disclosing information are stronger corporate reputation (Aerts and Cormier, 2009), greater influence in the public policy process (Cho and Patten, 2007) and in the event of an environmental disaster or legal action it will function as an insurance-like protection (Godfrey, Merrill, and Hansen, 2009). Some of the potential costs of disclosure consist of greater legal exposure (Cormier and Magnan, 1997) and a greater chance of being perceived as a “greenwasher” or being targeted by activists (Lyon and Maxwell, 2011). The attention from researchers and professionals for corporate social and environmental reporting has thereby increased in the past decade (Jennifer Ho and Taylor, 2007; Haniffa and Cooke, 2005; Giannarakis, 2014). Also the amount of pages dedicated to corporate social and environmental disclosure has risen (Pinto, Villiers and Samkin, 2014).
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2.2. Hypotheses
In this section the hypotheses which are going to be used in this study will be introduced. In the end this will result in a conceptual model depicting all the relationships.
TMT gender diversity
A lot of literature is written about the differences between men and women in businesses (Biggins, 1999; Walt and Ingley, 2003; Rose, 2007). Schubert (2006) argues that women have better communicative skills and are better in risk management than their male counterparts, and thereby making them managing situations differently. Deschênes, Rojas, Boubacar, Prud’homme, and Ouedraogo (2015) state that the style of management of women improves the financial performance of companies. Having women in the TMT furthermore will bring benefits like (among others): expanding the content of discussions and providing different perspectives on the issues (Konrad, Kramer and Erkut, 2008). Both these attributes can affect the transparency of a company and therefore gender diversity within a TMT can influence the degree of transparency of a company. Several studies have found that women are positively oriented towards CSR (Williams, 2003; Webb, 2004; Fukukawa, Shafer and Lee 2007; Larrieta-Rubín de Celis, Velasco-Balmaseda, Fernández de Bobadilla, Alonso-Almeida, and Intxaurburu-Clemente, 2015). Therefore it is expected that the presence of women in a TMT positively influences the transparency. Soares et al. (2011) argues that women managers can provide different perspectives in discussions. Therefore, having a large proportion of women managers could lead to different approaches to CSR. Larrieta-Rubín de Celis et al. (2015) studied gender equality in top management in Spain with a sample consisting of 42 Spanish companies which voluntarily committed to gender equality. They found empirical evidence that having more woman in top management positions positively influences CSR activities. Thus the first hypothesis of this study is:
Hypothesis 1: TMT gender diversity has a positive effect on the degree of transparency
TMT age diversity
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negative significant effect of age diversity on corporate social performance. Thus the second hypothesis of this study is:
Hypothesis 2: TMT age diversity has a positive effect on the degree of transparency.
TMT educational background
Finkelstein, Hambrick and Cannella (2009) suggest that the educational background of executives influences the firm’s behavior and outcomes. Members of the TMT differ in their educational history and also to what extend they have been educated about CSR-related issues (Randy Evans and Davis, 2011). According to Dahlin, Weingart and Hinds (2005) “education
is one of several sources of knowledge that contributes to one’s expertise. Expertise can be used
to understand the importance of information and thereby evaluate it and incorporate into decisions (Bunderson and Sutcliffe, 2002; Cohen and Levinthal, 1990). Zalesny and Ford (1990) state that the depth of information processing is affected by the knowledge which resulted from education. Therefore when a TMT consists of individuals which have been educated about CSR this may increase the likelihood of the company being transparent. Slater and Dixon-Fowler (2010) on their turn found that CEO’s which have a MBA degree have a positive influence on the corporate environmental performance of the company. Since there is normally a long time span between receiving a college degree and becoming a member of the TMT Iqbal (2015) argues that there could be no relation at all. Therefore, the third hypothesis of this study is:
Hypothesis 3: A higher level of education of the TMT’s has a positive effect on the degree of transparency.
TMT nationality composition
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amount of foreigners in the board and CSR disclosure. However, the effect of foreigners on the TMT is country specific. In the case of the Netherlands the rate of CSR reporting is rather high in comparison to many other countries (KPMG, 2013). Therefore, it is expected that when a TMT consists of a large proportion of foreigners this will negatively influence the degree of transparency. Thus:
Hypothesis 4: The proportion of foreigners has a negative effect on the degree of transparency.
Profitability
The link between profitability and CSR disclosure have been studied on many occasions but with mixed results. Brammer and Pavlin (2006) argues that when a company makes profit, managers can use this to fund the costs of environmental disclosures. The results of the study of Al-Tuwaijri, Christensen and Hughes (2004) complies with this as they found a positive relationship between profitability and environmental disclosure. On the other hand Van de Burgwal and Vieira (2014) found in their Dutch sample of big firms no significant effect between the profitability of the firm and the level of environmental disclosure. Jennifer Ho and Taylor (2007) on their turn found a significant negative relationship between the profitability of the firm and the level of environmental disclosure. Stating that companies with lower profitability are more likely to disclose information. Jennifer Ho and Taylor (2007) state that it could be that when a firm experiences unfavorable profit performance, the company wants to emphasize the fact that they add social value and contribute to the society. Despite the results of the study of Jennifer Ho and Taylor (2007) it is expected that there is a positive relationship between profitability and transparency. This leads to the following hypothesis:
Hypothesis 5: Profitability has a positive effect on the degree of transparency.
Firm size
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that since smaller firms disclose less information as they face less pressure from the community and probably have less to gain from CSR. This leads to the following hypothesis:
Hypothesis 6: Firm size has a positive effect on the degree of transparency.
International listing
Firms which are listed on a variety of stock exchanges have more exposure and more stakeholders to comply to. This could result in different pressures on companies (Haniffa and Cooke, 2005). Firms which are listed on multiple stock exchanges will disclose more detailed information as it has to comply too different sets of disclosure rules (Cooke, 1989). Several studies found that international listings positively influences the extent of disclosure (Hossain, Tan and Adams, 1994; Robb, Single and Zarzeski, 2001; Haniffa and Cooke, 2005). However, Hossain and Reaz (2007) and Reverte (2009) found that there was no relationship between foreign stock market listings and CSR disclosure. Nevertheless, despite the latter results it is expected that there is a positive relationship between international listings and transparency. Thus:
Hypothesis 7: The amount of foreign listings has a positive effect on the degree of transparency.
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The conceptual model, depicted in figure 1, shows the research units and concepts presented in this paper and shows the relationship between them. The hypotheses formulated earlier are incorporated in the conceptual model and are depicted by the H1 to H7.
3. Methodology
The sample of this study consists of a number of big Dutch companies representing various industries. A secondary data set (source: dr. K. van Veen) is used for this study. This dataset contains general information about the biggest companies of the Netherlands and information concerning the TMT composition of 2013. This database will provide a group of companies which are comparatively stable, financially strong and have a relatively long history. Some of the companies were not taken into account in the Transparency Benchmark database and vice versa. This has resulted in a database consisting of 70 companies which are going to be used in this study. To test the hypotheses presented in this paper a multiple linear regression model is used.
Dependent variable
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companies which stimulates the companies to deliver a CSR report of better quality the next year (Transparantiebenchmark, 2014).
Independent variables
As mentioned in this research both firm characteristics as TMT characteristics are used as independent variables. Let us start with the firm characteristics which consists of profitability, firm size and international listings. For the independent variable profitability the return on equity (ROE) will be used which have been used by other studies in several occasions (Tagesson, Blank, Broberg and Collin, 2009; Ahmad, Osazuwa and Mgbame, 2015). The firm size is calculated, in line with the study of Brammer and Pavelin (2006), as the log of the firm’s total assets. International listings is accounted for as the number of foreign stock markets in which a firm is listed (Reverte, 2009). The data concerning these three variables are all derived from the Orbis database. If the data from Orbis was incomplete, the data was tried to be found in annual reports and corporate websites.
The TMT variables consist of TMT gender diversity, TMT age diversity, TMT nationality composition, and TMT education. The data concerning TMT gender and age diversity will be derived from the secondary database. To be able to calculate the gender diversity within the TMT the heterogeneity index (HI) will be used. This way of calculating gender diversity is used in the work of Wegge, Roth, Kanfer, Neubach and Schmidt (2008). Gender H1 is calculated by dividing the majority of persons in the TMT (women or men) by the total amount of persons of the TMT, subtracted from 1 (Formula 1).
Gender H1: 1 − 𝑛 (𝑜𝑓 𝑚𝑎𝑗𝑜𝑟𝑖𝑡𝑦 𝑔𝑒𝑛𝑑𝑒𝑟) 𝑛 (𝑡𝑜𝑡𝑎𝑙)
Formula 1
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𝐶𝑉 = √[ ∑(𝐷𝑖− 𝐷𝑚𝑒𝑎𝑛)2/𝑛] /𝐷 𝑚𝑒𝑎𝑛
Formula 2
As stated by Ali, Ng and Kulik (2014): “larger standard deviation (larger age differences
between TMT members) and lower mean age (higher representation of young TMT members) would generate higher age diversity values”. The independent variable TMT nationality
composition is also derived from the, earlier mentioned, secondary database. For each TMT the percentage of foreigners has been calculated to see which TMT had the highest concentration of foreigners in their TMT. The information concerning TMT education will be derived from the management scope database. In order to make sure the data provided by management scope is correct, Linkedin and Bloomberg are also used to verify the data. A distinction has been made between PhD, MSc, BSc (University or Higher Vocational Education), and other/lower education. This study used the following coding: 1 = other/lower education, 2 = BSc, 3 = MSc, and 4 = PhD. When an individual did multiple studies, the highest received degree was noted down. As it is expected that the higher educated the TMT the more transparent the firm will be, an average of each TMT has been calculated. Therefore, firms with an average closer to 4 have a higher educated TMT and therefore it is expected that they will be more transparent. A summary of all independent variables and how they are calculated is provided in table 1.
Control variables
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sensitive”. When a company is active in a more sensitive industry it will receive a one and when active in a less sensitive industry is will receive a zero.
The relationship between board size and disclosure has been tested on many occasions. Samaha, Khlif and Hussainey (2015) found a significant positive association between board size and voluntarily disclosure. Hildalgo, García-Meca and Martinez (2011) state that having a larger board comes with an increased pool of expertise and will increase the amount of available resources of the firm. They add to this that an increasing board size has also downsides as the communication will be less effective, the decision making time will probably increase. Allegrini and Greco (2013) and Abeysekera (2010) both found a positive relationship between board size and voluntarily disclosure. Allegrini and Greco (2013) state as reason that: “Larger boards could offer a wider ownership representation and be more open in disclosing information about the strategic objectives, as well as information useful to a broader range of stakeholders”. This control variable is operationalized as the total amount of people in the board.
Table 1
Independent variables Measurement
TMT variables TMT gender diversity TMT age diversity TMT education TMT nationality composition Firm variables Profitability Firm size International listings
1 – n (of majority gender) / n (total) The coefficient of variation of the TMT Average level of education of the TMT Percentage of foreigners on the TMT
ROE (Return on equity) Log of the firms total assets
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Table 2: Means, standard deviations and correlations (N = 70)
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4. Results
Tables 2 shows the mean, standard deviation and correlations for all variables tested in this study. The correlations between the variables for each year have been observed prior to undertaking the analysis in order to assess the level of multicollinearity. In the literature several cut-off points are used to seen when multicollinearity is present. Kim (2005) for instance advise .80 while Pallant (2001) proposes .90. When taking these two cut-off points in mind there is no multicollinearity in this dataset. The highest correlations found in this study comes down to 0.61 and 0.70. Which can be seen as a strong positive correlation. Therefore a variance inflation factor (VIF) analysis will be needed to be sure that the findings will not be biased by multicollinearity. Hair, Babin, Money and Samouel (2003) mention that a VIF of 5.0 is the maximum acceptable VIF value, in this model the highest value encountered was 2.20. Therefore, it can be concluded that the findings of this study were not biased by multicollinearity.
To test our hypotheses, a multiple regression analysis is used of which the results can be found in Table 3. In the first model, the dependent variable transparency and both control variables (industry and board size) were entered. In model 2 to model 8 the relationship between the dependent variable transparency has been tested with one of the independent variables and both control variables. In model 9, the dependent variable transparency and both control variables (industry and board size) and all the independent variables have been entered.
When looking at the results, presented in table 3, it shows that first of all only the control variable board size is positively significant (β = 0.48; p < 0.01; Model 1). However, board size was not to be found significant when taking all the variables into account. The effect of the control variable industry was not significant.
When considered individually, it can be seen that firms of which the TMT consists of more domestic people (Dutch people) and are not listed on international foreign stock markets are more transparent. Furthermore, firms which are bigger are more transparent. However, neither, TMT gender diversity, TMT age diversity, TMT education and profitability seemed to explain the differences in transparency. In terms of R2, the variable which was the most influential in explaining the variation in transparency was firm size (R2 = 0.35) followed by TMT nationality composition (R2 = 0.28) and international listings (R2 = 0.24). When looking at the total model (model 9) one can see that the model explains 37% of the variation of the transparency.
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Table 3: Regression analysis (N = 70)
Notes: Coefficients standardized.
* p < 0.05 ** p < 0.01
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
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In order to support the hypotheses the independent variables need to be significant in the full model and its sign needs to be in the predicted direction. H1 states that TMT gender diversity positively influences the degree of transparency. The coefficient of TMT gender diversity is not statistically significant (β = 0.14, n.s.). H1 is therefore not supported. The relationship between TMT age diversity the degree of transparency (H2) is also not statistically significant (β = -0.06, n.s.). H2 is therefore not supported. As is presented in table 3, there is also no relationship between a higher educated TMT and transparency (β = 0.05, n.s.). Therefore, H3 is not supported. However, the relationship between TMT nationality composition and transparency is negative and statistically significant. Suggesting that having a high proportion of foreigners in the TMT, rather than Dutch people, is negatively related to transparency (β = -0.25, p < 0.05). This finding supports H4. Hypothesis 5 which test the relationship between profitability and transparency also lacks empirical evidence (β = 0.06, n.s.). Therefore, H5 is not supported. However, the results provide evidence that the size of a firm positively influences the degree of transparency (β = 0.47, p < 0.01). Suggesting that bigger firms are more transparent. This finding supports H6. Lastly, no empirical evidence was found when testing the relationship between international listings and transparency (β = -0.02, n.s.). Therefore, H7 is not supported.
5. Discussion
This study intended to analyze what determinants the transparency of Dutch companies. In addition the effects of TMT composition have been analyzed to see what their effect is on the degree of transparency of companies. Our study illustrates that TMT’s consisting of a low proportion of foreigners are more transparent. This result is contradicting with the study of Lau et al. (2014) as they found no relationship between the proportion foreigners and the degree of CSR reporting. This can be legitimized by the fact that this study was based on an Asian context. Therefore, the term foreigners is perceived differently than in our study. Therefore this result is context based.
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The rest of the explanatory variables were not to be found statistically significant as determinant of transparency. Despite many argue that women are positively oriented towards CSR (Williams, 2003; Webb, 2004; Fukukawa, Shafer and Lee 2007; Konrad, Kramer and Erkut, 2008; Alonso-Almeida, and Intxaurburu-Clemente, 2015). This study found no significant effect of TMT gender and transparency. In contrary of Larrieta-Rubín de Celis et al. (2015) which found a positive effect. The reason why no significant effect is found is largely due to the lack of women in Dutch TMT’s. The full sample consisted of 272 people of these people only 17 were female, only 7% of the total sample. The study by Larrieta-Rubín de Celis et al. (2015) on the other hand used a sample consisting of 42 Spanish companies which voluntarily committed to gender equality. Therefore the amount of women in the TMT in this sample was much higher. TMT age diversity turned out to have no effect on the degree of transparency. Despite the beliefs that a combination of young and old managers would lead to more transparency. A reason for not finding a significant result could be the lack of younger people in the TMT. The average age of the TMT’s in our sample was 55, which is a rather mature age. In addition the education of a TMT seems not to be a factor which could explain the degree of transparency. This is probably due to the normally a long time span between receiving a college degree and becoming a member of the TMT (Iqbal, 2015).
There is no relationship found between the profitability of a firm and the degree of transparency. This can be rationalized by the argument made by Williams (1999) that CSR is rather influenced by “public” than “economic” pressure (Esa and Mohd Ghazali, 2012). Our result is consistent with Alsaeed (2006), Reverte (2009) and Giannarakis (2014) and inconsistent with Jennifer Ho and Taylor (2007) and Tagesson et al. (2009). The explanatory variable international listing is not associated with the degree of transparency. Despite Hossain et al. (1994) and Robb et al. (2001) found that international listings positively influences the extent of disclosure. A reason for not finding a significant result in this study is the lack of companies which are listed on stock exchanges outside Europe. The CSR standards are mostly equal in France, Germany and England (where the majority is listed). A small percentage is also listed in the United States, which is expected to have different CSR standards.
6. Conclusion
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in this study. In order to test the transparency of companies, the Transparency Benchmark is used. The Transparency Benchmark analyzes the CSR reporting among the largest Dutch companies and is annually performed. The uniqueness of this data is that it is performed by accountants which have no personal interest. Therefore, the data is highly reliable. Furthermore, this data is combined with TMT data of Dutch companies which led to a sample of 70 companies. Multiple linear regression analysis showed that the larger the company size the more transparent the company. While the extent of foreigners in a TMT is negatively related to the degree of transparency.
This study makes several potential practical and theoretical implications. This article is one of the few articles which analyzes the composition of the TMT on the degree of transparency (Lau, Lu, Liang, 2014). Furthermore, firms may increase CSR disclosure when being aware of the advantages of disclosure. Lastly, policy-regulators should focus more on smaller firms in the development of regulation concerning disclosure. As it are the smaller firms which are least likely to use CSR reporting.
This brings us by our first limitation. Our sample leads to a bias towards large and possibly internationally operating companies. Therefore the descriptive results probably show an overestimation of the expected effects. Second, by using the Transparency Benchmark this study purely focused on the annual report. Despite the fact that this medium is by far the most often used medium for CSR disclosure, it is possible that companies may have used other media. Lastly, the information provided by the companies in their annual report is not validated by an external party. The mere reason that it is in the annual report is no guarantee that it is actually done.
This study focused on the transparency of companies in 2013. Therefore the study doesn’t take the change in transparency into account. Future studies should take a longitudinal approach so they can reveal interesting results and trends. Prior studies have shown that disclosure practices do change over time (Gao, Heravi and Xiao, 2005). Furthermore, our results are based on a sample including the biggest companies of the Netherlands. Future studies could include smaller and medium sized firms in their samples to see whether the determinants of transparency differ (Udayasankar, 2008).
7. Acknowledgment
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