MASTER THESIS MSc Accountancy University of Groningen
SN S2454750 Faculty of Economics and Business
January 21, 2019
Which elements of an integrated report are
most important to long-term investors?
Tara Kortman
University of Groningen
Supervisor: Dr. T.A. MarraABSTRACT: This study investigates the relationship between Integrated Reporting (IR) and the composition of a firm’s investor base of fifty Spanish companies listed on the Bolsa the Madrid. To investigate the adoption rate of IR in relation to the investor base, the eight content elements from the International Integrated Reporting Council (IIRC) are examined. This examination includes disclosure on organizational overview and external environment, governance, business model, risks and opportunities, strategy and resource allocation, performance, outlook, and other elements. This paper contributes to the emerging literature on IR as it provides evidence that among the eight content elements, two of them, namely business model and ‘other elements’ (conciseness and links, materiality determination process and board sign of), are most important to the information demands of long-term investors. Furthermore this study does not provide evidence that companies producing integrated reports more aligned with the IR framework have a more long-term investor base. Rather, this study provides suggestive evidence that companies producing integrated reports more aligned with the IR framework attract more long-term investors. The findings of this study could be useful for several parties, in particular investors, practitioners and regulators.
Keywords: Integrated Reporting, content elements, long-term investors, investment
horizon, agency theory, legitimacy theory.
Data Availability: Bureau van Dijk (Orbis) & Datastream Word Count: 7349
First of all I would like to thank my supervisor dr. T.A. Marra for all the help and support I received during the time I was writing my master thesis. Furthermore, I am very grateful to PwC, for providing me the opportunity to write my thesis during an internship. I am grateful for the comments and it was a nice opportunity to get acquainted with the colleagues and the audit profession. Lastly, I am grateful for the mental support I received from my family and friends.
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1. INTRODUCTION
According to Larry Page and Sergey Brin, the founders of Google, pressure from investors to meet short-term results often hamper corporate managers to take opportunities that are in the long-term interest of investors. In an ideal world, firms would have investors that do not pressurize firms to meet short-term performance (Francis, Philbrick and Schipper, 1994). For example, the short-term performance goals may ensure that managers abandon long-term investments in research and development, which are critical to the firm’s long-term performance (Hirshleifer ,Hsu and Li, 2013). Thus, if investors remain too focused on the firm’s short-term financial performance, this may disturb an organization’s ability to implement fundamental business model changes to achieve long-term value creation (Cheng, Green, Conradie, Konishi and Romi, 2014). According to the CEO of Unilever, Paul Polman, “driving shareholder wealth at the expense of everything else will not create a company that is built to last. You need to attract a shareholder base that supports your strategy, not the other way around. We actively seek one that is aligned with our longer term strategy”. Several corporate managers already try to attract investors with a more long-term horizon. Coca-Cola, for example, stopped issuing quarterly earnings forecasts to put more emphasize on the firm’s long-term strategy.
According to Dhaliwal, Zhen Li, Tsang and Yang (2011), Corporate Social Responsibility (CSR) initiating firms with superior CSR performance attract more dedicated institutional investors. Dedicated institutional investors are insensitive towards short-term performance of a firm (Bushee, 2004). In recent years, corporate information about environmental, social and governance (ESG) matters have become an important information source for investment decisions in the capital market (Arnold, Bassen and Frank, 2012). There are companies that voluntarily publish ESG reports. While these ESG reports provide useful information for investors to evaluate a firm’s long-term sustainability (Dhaliwal et al. 2011), IR might increase the usefulness of sustainability information to investors. The International Integrated Reporting Council (IIRC) proposed to create a single integrated report that provides a clear link between financial and non-financial information (Cheng et al., 2014). Integrated reporting (IR) provides ESG information in an integrated manner with the financial information, which does enhance the understanding of the firm to its shareholders (KPMG and Financial Executives Research Foundation, 2011; Zhou, Simnett and Green, 2017).
3 IR is a relatively new phenomenon and has become increasingly relevant the last ten years (Serafeim, 2015). Firms such as Coca Cola, Danone, Deutsche Bank, Marks and Spencer, Microsoft Corporation, Prudential Financial Tata Steel and Unilever voluntarily engaged in IR to test the principles and concepts of IR in their firm. Enagás SA, for example, stated that IR is already bringing significant external benefits, such as an improved understanding about how the firm creates value over time, a more forward-looking, long-term view of the firm’s performance and a stronger relationship with providers of financial capital. Furthermore, Enagás SA is convinced that investors have a better understanding of the firm’s strategy and have more confidence in the long-term future of the firm (IIRC, 2015).
While IR is gaining in popularity, there is lack of clear evidence of the benefits of IR (Zhou et al., 2017). The study of Serafeim (2015) provides evidence of the value of IR by examining the investor base of companies that practice IR. Serafeim notes a causal relationship between firms that compile integrated reports and shareholders that are interested in the long-term performance of firms. However, Serafeim used a comprehensive measure of IR, causing that Serafeim is not able to determine which elements of IR are most effective at attracting long-term investors. Therefore, this research focuses on the elements of IR and whether or not some elements are more important than others to long-term investors, vis a vis short-term investors. The following research question is central to this study:
“Which elements of an integrated report are most effective at meeting the information demands of long-term investors?”
This study contributes to the emerging research on IR in several ways. The main contribution of this paper is to isolate the impact of the different content elements. While Serafeim (2015) documented a relationship between companies practicing IR and long-term investors, it remains to be studied how these investors change their capital allocation decisions based on the specific kinds of IR information. Therefore, the findings of this study provide additional evidence to the growing literature on the benefits of IR.
Second, this study provides evidence whether firms with higher corporate IR have a more long-term investor base. Long-term investors are more interested in the long-run value of the firm and companies try to meet the information demand of these investors by adopting IR. These investors do not pressurize managers to achieve short-term results, but support the long-term strategy. However, the direction of causality might be reversed. Firms with higher corporate IR might not only have a more long-term investor base, but they might also attract
4 more long-term investors. Therefore, this study provides expectations about the ability of firms to attract more term shareholders. The change toward an investor base with more long-term shareholders will remove the external pressures for managers to achieve short-long-term results, reduce the risk that managers pursue their own interest and encourage managers to return their focus to a long-term strategy. Therefore, this study can help firms in their decision to adopt IR to attract more long-term investors.
Lastly, very little research has discussed the impact of IR on firms globally as most of the studies are done in South Africa. South Africa is the first country that mandated IR. However, due to the focus on a single country and the mandatory nature, these studies have limited generizability. Therefore, a research gap exists on the impact of IR globally. A worldwide sample is the major task for future research (Velte and Stawinoga, 2017; Arguelles, Balatbat and Green, 2015). This study aims to address this research gap by focusing on Spain. Spain is a member of the European Union (EU). Therefore, the results of this study are generalizable for Europe as the EU strives to create a single market. Hence, this paper could provide significant impetus for the adoption of IR among European listed companies.
The remainder of this paper is structured as follows. Chapter two describes the relevant theories concerning the abovementioned research question. The theoretical framework focuses on the agency theory and legitimacy theory. The development of the hypotheses are addressed in the third chapter. Chapter four explains the research method and describes the data collection. Chapter five provides the results. The last chapter contains the conclusion, a discussion of the results, possible limitations and suggestions for future research are given.
2. THEORETICAL FRAMEWORK
2.1. Integrated Reporting
Higher disclosure quality improves investors’ understanding of the performance and future outlook of companies (Hope, 2003; Lang and Lundholm, 1996). Higher disclosure quality is related to improved forecast accuracy and lower forecast dispersion (Hope, 2003; Lang and Lundholm, 1996). Prior literature reveals evidence that non-financial information is also taken into account by investors while forecasting firm performance. Ioannou and Serafeim (2015), for example, provide evidence that analysts issue more optimistic recommendations for firms with higher CSR ratings. Non-financial information is relevant to investors since it has
5 the ability to determine a company’s long-term financial performance (Eccles and Saltzman, 2011; Ghani and Said 2010).
However, investors have cognitive limitations in information processing (Zhou et al. 2017). When the information processing becomes too complex, it has an adverse effect on investors’ forecast accuracy and forecast dispersion (Bradshaw, Miller and Serafeim, 2009 and Lehavy and Merkley, 2011). According to Zhou et al. (2017), adding non-financial information might strengthen these adverse effects. Academic research has shown that standalone sustainability reports are still of little use to providers of financial capital, because of the great amount of non-financial information which is not connected to the financial report (Eccles and Krzus, 2010; Eccles and Serafeim, 2014). Simpson (2010) and Rajgopal, Shevlin and Venkatachalam (2003) found that investors tend to underreact to non-financial measures, despite their predictive ability for a firms’ long-term performance.
The IIRC came up with a framework to improve the linkage between a firm’s financial and non-financial information (IIRC, 2013). The IR framework enables firms to provide a “holistic view of a firm’s value creation by connecting previously disconnected pieces of information that refer to the combination, interrelatedness, and dependencies of a wide range of “capitals”, such as financial, human, and natural capital” (Baboukardos and Rimmel, 2016). In this way, IR increases the use of non-financial information, which users might have ignored if IR was not adopted (Agnew and Szykman, 2005; Hirshleifer and Teoh, 2003). The key guiding principles of the IR framework are, amongst others, materiality, conciseness and connectivity (IIRC, 2013). These principles help to mitigate the information overload problem faced by users of reports, which enables them to incorporate all applicable information (Zhou et al. 2017). Therefore, it helps investors in assessing the combined impact of the diverse factors that materially affect an organization’s long-term value (IIRC, 2011). In this way, IR addresses the potential short-termism of current reporting practices (Zhou et al., 2017).
2.2. IR and the agency theory
Agency theory describes the relationship between the shareholders (principals) and the management/company executives (agents) (Jensen and Meckling, 1976). According to Jensen and Meckling (1976), the shareholders delegate some decision-making authority to the manager to perform some services on their behalf. However, the manager will not always act in the best interest of the shareholders (Jensen and Meckling, 1976). The manager and the shareholder have their own interests and they tend to maximize their own wealth, which results in the
so-6 called agency problem (An, Davey & Eggleton, 2011). Information asymmetry, which is a key concept in the agency theory, occurs when the manager has an information advantage over the shareholder (An et al., 2011). This information advantage provides managers the opportunity to make decisions in their own interest (Jensen and Meckling, 1976).
Demand for financial reporting and disclosure derive from agency problems between managers and investors (Healy and Palepu, 2001). Corporate disclosure practices can resolve these agency conflicts by reducing information asymmetry (An et al. 2011; Verrecchia, 2001). IR is a mechanism to expand the information set of a company. IR includes financial, environmental, social and human value drivers into one report and connects these value drivers to explain the value creating activities of the company (Zhou et al. 2017). Because IR highlights the links between the value drivers, IR is able to reduce information asymmetry between managers and investors (Zhou et al. 2017). Furthermore, IR emphasizes the disclosure of corporate strategy, the company’s business model, and forward looking information to reduce the uncertainty of the outlook of firms (Zhou et al. 2017). The IR framework ensures that both managers and providers of financial capital take the long-term consequence of a broader set of capitals into account (De Villiers, Venter and Hsiao, 2017). Hence, the long-term focus of IR may strengthen the alignment of the interests between firms and their long-term investors (and thus lower agency cost), while it weakens the alignment of interests between firms and their short-term investors.
2.3. IR and the legitimacy theory
Legitimacy theory is concerned with an implicit social contract the organization has with the society in which it operates (Velte and Stawinoga, 2017) and it explains the importance of societal acceptance in ensuring a company’s survival (Mohd Ghazali, 2007). An organization is, due to the social contract (Shocker and Sethi, 1973), motivated to comply with the values, norms and boundaries of society by implementing adequate structures and processes (Dowling and Pfeffer, 1975). Failure to comply with community expectations can have implications for the ongoing survival of firms, since it will become more difficult to attract capital, customers, employees and so forth (Deegan, 2006). According to Gray, Owen and Adams (2009) “organisations can only continue to exist if the society in which they are based perceives the organization to be operating to a value system that is commensurate with the society’s own value system”. However, as community expectations change, firms constantly need to adapt their activities to legitimize their actions and ensure the firm’s survival (Deegan, 2006). Since
7 it is difficult to continually comply with expectations and norms of society a so called ‘legitimacy gap’ arises.
In contrast to investors with a term horizon who are only interested in the short-term investment profits, investors with a long-short-term horizon create more incentives to gather information relevant to the long-run value (Porter, 1992). Because legitimacy is essential to the firm’s survival and the ability to attract resources (Deegan, 2006), it is especially important to investors with a long-term horizon. A legitimacy gap could withhold long-term investors to invest in the company. A legitimacy gap should therefore be prevented. Lindblom (1994) suggests that this legitimacy gap could be mitigated by providing more transparency. Voluntary adoption of IR is an effective tool for firms to communicate their legitimization actions (Velte and Stawinoga, 2017). With IR, it is possible to enhance a firm’s image as a good corporate citizen (O’Donovan, 1999), since they try to show they comply with society’s expectations and norms (Lindblom, 1994). Hence, IR is able to mitigate the legitimacy gap between firms and investors with a long-term horizon, more than investors with a short-term horizon.
3. HYPOTHESIS DEVELOPMENT
3.1. IR and the attraction of long-term investors
According to Bushee and Noe (2000), the investment horizon of investors determines the importance of corporate disclosure practices to investors. Serafeim (2015) stated long-term investors are more likely to buy shares of companies which provide more information about the long-term prospects, because these companies are signaling their ability to practice long-term management. Bushee (2001) distinguished three types of institutional investors. The first are called “transient” institutions, which are institutions with high portfolio turnover and who own small stakes in portfolio companies. The second are called “dedicated” institutions, which have low portfolio turnover and who own large stakes in portfolio companies. The third is called “quasi-indexers”, which trade infrequently and who own small stakes in the firm (Bushee & Noe, 2000). The most important finding in this study is that companies with a more “transient” ownership structure are more likely to cut R&D spending to meet an earnings target than managers of companies with a more “dedicated” ownership structure. Dedicated institutional investors have a “relationship investing” role and are committed to provide long-term patient capital (Porter, 1992; Dobrzynski, 1993).
8 A study performed by Cox and Wicks (2011) provides suggestive evidence that corporate responsibility influences the demand for shares by dedicated institutions. As already noted, Dhaliwal et al. (2011) found a positive relation between CSR initiating firms with superior CSR performance and the attraction of more dedicated institutional investors. According to Zhou et al (2017), the long-term focus of IR corresponds well to the information demands of investors with a long-term earnings forecasting horizon. IR is expected to provide both new and value-relevant information to investors for their earnings forecasting tasks (Zhou et al., 2017). Baboukardos and Rimmel (2016) argue that IR helps investors in assessing firm performance and risks. Due to more accurate information investors are able to improve their investment decisions, because IR allows investors to better predict firms’ risks (García-Sánchez & Noguera-Gámez, 2017). Moreover, IR reduces the negative effects caused by information asymmetry, such as monitoring costs and the required cost of capital (Zhou et al. 2017; García-Sánchez & Noguera-Gámez, 2017; Serafeim, 2015).
These studies confirm the decision usefulness of IR to investors, since it helps them assessing firm performance and risks. The IIRC (2011) stated that IR highlights information about the future, which will assist investors in assessing a firm’s ability to generate future cash flows. Since long-term investors are more likely to buy shares of companies providing more information about the long-term prospects (Serafeim, 2015), it can be expected that there is a positive relation between IR adoption and an investor base that is interested in the long-run prospects and values of firms. However, the effectiveness of IR relies on the quality of the integrated report (Barth, Cahan, Chen and Venter., 2016; Bernardi and Stark, 2015; Lee and Yeo, 2016). Integrated reports that are more aligned with the IR framework are expected to be more useful to investors (Zhou et al., 2017). This leads to the following hypothesis:
H1: Companies compiling integrated reports more aligned with the IR framework are expected to have a more long-term investor base.
3.2. The content elements and the attraction of long-term investors
To isolate the impact of the different kinds of IR information, this study also focuses on the different content elements of the IR Framework. The content elements serve as a guideline for the adoption of IR, which are organizational overview and external environment, governance, risks and opportunities, strategy and resource allocation, business model, performance, future outlook, and basis of preparation and presentation (IIRC, 2013). It is an empirical question which information in integrated reports are most effective at meeting the
9 information demands of long-term investors. While long-term investors are interested in the firms long-term performance, the content element ‘future outlook’ might be more important compared to the other content elements. Further, IR places a firm’s sustainability activities in the context of its strategy and business model (Serafeim, 2015). IR emphasizes disclosure on corporate strategy and business model to reduce the uncertainty of a company’s future outlook (Zhou et al. 2017). Therefore, the content elements ‘strategy and resource allocation’ and ‘business model’, compared to the other content elements, might me more useful to long-term investors. Lastly, the ‘other elements’ reflect some of the guiding principles of IR and therefore might be relatively more important to long-term investors. Below, these four content elements are described in more detail.
3.2.1. Strategy and resource allocation
According to Grant (1991) and Mahoney & Pandian (1992) strategies are created by firms to obtain influence on the success and survival of their business. In doing so, firms optimize the allocation of scarce resources to improve the competitive position (Grant, 1991; Mahoney & Pandian, 1992). Hence, more disclosure on strategy and resource allocation might reveal more about the firm’s long-term value creation. This leads to the following hypothesis:
H2a: Firms disclosing more information on their strategy and recourse allocation are expected to have a more long-term investor base.
3.2.2. Business model
According to a research conducted by PwC (2016), business model reporting provides opportunities to drive future growth. PwC (2016) also stated that investors wish to get more detailed information on business models to make their investment decision. If companies do not articulate their business model clearly, investors are reluctant to invest in that firm (PwC, 2016). However, as business model reporting provides opportunities to drive future growth, business model reporting might be more important to investors that are interested in the long-term performance of firms and less important to investors that are only interested in the short-term performance of firms. Hence, more disclose on the company’s business model might reveal more about the firm’s long-term value creation and is therefore more important to investors with a more long-term horizon. This leads to the following hypothesis:
H2b: Firms disclosing more information on their business model are expected to have a more long-term investor base.
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3.2.3. Future outlook
The outlook element focuses on the anticipated variations over time. It provides a transparent and comprehensive analysis about the external environment the company confronts in the short, medium and long term (IIRC, 2013). Companies are required to respond to the changing environment that possibly has a negative effect on the ongoing survival of the firm (Wen and Heong, 2017). As more disclosure on the company’s outlook might reveal more about the firm’s long-term value creation, it might be more important to investors with a long-term horizon. This leads to the following hypothesis:
H2c: Firms disclosing more information on their future outlook are expected to have a more long-term investor base.
3.2.4. Other elements
This content element consists of conciseness and links, materiality determination process and the board sign-off. IR is viewed as the integration of a sustainability report and financial report into a single report (Churet and Eccles, 2014). Therefore, companies scoring higher on ‘conciseness and links’ are doing better at actually integrating the sustainability and financial information. Furthermore, the guiding principles of the IR framework are, amongst others, materiality and conciseness and connectivity (IIRC, 2013). These principles help investors in assessing the combined impact of the diverse factors that materially affect an organization’s long-term value (IIRC, 2011). Moreover, Serafeim (2015) provided suggestive evidence that materiality and connectivity are two key characteristics that drive the association between IR and a more long-term investor base. Therefore, more disclosure on ‘the other elements’ might reveal more about a firm’s long-term value creation. It therefore might be more important to investors with a long-term horizon. This leads to the following hypothesis:
H2d: Firms disclosing more information on the ‘other elements’ are expected to have a more long-term investor base.
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4. RESEARCH METHOD
4.1. Sample and data collection
The aim of this study is to find a relationship between IR and its elements and the presence of a more long-term investor base. Although there is no clear way to measure the number of companies that use IR, it is clear that a growing number of companies contain increasing amounts of ESG information in their financial reports (Serafeim, 2015). Although the EU did not consider the adoption of IR into their regulatory requirements yet, the number of firms that specifically label their reports as “Integrated” is growing slowly, but steadily (The KPMG Survey of Corporate Responsibility Reporting, 2017). According to the KPMG Survey of Corporate Responsibility Reporting (2017) there is a significant increase in the practice of IR in Spain the last few years. The number of companies issuing integrated reports increased from 27 to 36 between 2015 and 2017. After South Africa and Japan, Spain is ranked as the number three country worldwide to practice IR. Furthermore, Spain is one of the most committed European country to the presentation of non-financial information (Sierra-Garcia, Garcia-Benau, Bollas-Araya, 2018). Spanish companies achieve relatively high scores in sustainability indexes (KPMG, 2011). Therefore, Spain is an interesting country for this study.
The target sample selected in this paper focuses on the 57 largest Spanish companies listed on the Bolsa de Madrid based on market capitalization, resulting in 171 firm-year observations. However, nine firm-year observations were excluded in this paper as they did not provide an annual report during the research period. Further, sixteen firm-year observations were excluded as data on institutional holdings was missing in the Datastream database. The selected companies are observed for a for a three-year period from 2014 to 2016. This period is chosen since the IIRC published its International IR Framework in 2013. Until December 2013, there were no clear guidelines on what constituted an IR, except for a brief document prepared in early 2011 (Serafeim, 2015).
Data regarding institutional holdings can be conducted from Datastream. Datastream contains data on seven types of ownership and the percentage of shares each of these types own (at least 5 per cent). Data regarding IR will be hand-collected from the annual reports of the PLC’s. The initial sample consisted of 171 firm-years of which 25 are excluded due to missing data on institutional ownership in datastream or missing annual reports. The final sample consists of 146 firm-years (see table 1).
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Table 1: Sample selection criteria
Sample Initial firm-years between 2015-2017 171
Less:
Missing data concerning annual reports 9
Missing data concerning Institutional holdings in datastream 16
Missing data concerning control variables 0
25
Final sample 146
4.2. Dependent variable
To measure the proportion of long-term investors, this study focuses on different ownership types. Serafeim (2015) calculated the time horizon of a company’s investor base as the sum of the percentage held by banks, pension funds, insurance companies, and government investment funds. He subtracted this proportion from the sum of percentage of shares held by investment advisors and hedge funds. Van Essen et al. (2013) classified a relational investor as a blockholder that actively monitors the firm and as more committed to the long-term orientation of a company. He classified a bank, an insurance company, a family, or another corporation as relational blockholders.
However, datastream only identifies seven types of investors. Datastream identifies the percentage (for at least 5 per cent) of shares held by foreign investors, governments, investment funds, pension funds, employees, corporations and other holdings. Due to this data restriction, this study classified investment corporations as more short-term oriented, while government investment funds, pension funds, employees and corporations are classified as more long-term oriented. Foreign investors and other holdings cannot be classified as short-term or long-term oriented. Consequently, the time horizon of a firm’s investor base is calculated as the sum of the percentage of shares held by government investment funds, pension funds, employees and corporations and subtract it from the sum of the percentage of shares held by investment corporations. This variable is called LT-INVESTOR.
4.3. Independent variable
The explanatory variable in this study is IR quality and its different content elements. The quality of IR is not standardized in contrast to the casuistic guidelines of the GRI in CSR
13 reporting (Velte & Stawinoga, 2017). Despite the emerging nature of IR, there is no available external data provider supplying in depth information on integrated reports yet (Zhou et al., 2017). Moreover, the extent to which firms practice IR is a matter of degree and thus a subjective judgement.
In order to capture the heterogeneity between different integrated reports, Zhou et al. (2017) constructed a coding framework in line with the <IR> Prototype Framework issued by the IIRC in October 2012. Zhou et al. (2017) measured IR quality as the total disclosure score (IR_TOTAL). They constructed a coding framework consisting of 31 components across eight dimensions, which is in accordance with the IR prototype framework issued by the IIRC in 2012. The 31 components were scored either zero or one, so the maximum possible score of an integrated report was 31. This measure enables to determine the quality of IR, which is necessary due to the emerging nature of IR. To ensure the validity of the framework, Zhou et al. (2017) received input from key IIRC personnel who were involved in developing the IR framework. The coding framework was also validated through an investor survey. Fifteen large investor organizations commented on the completeness and appropriateness of the coding framework to measure IR quality. The respondents rated the ‘importance’ and ‘newness’ of the 31 components of the coding framework (Zhou et al. 2017). ‘Importance’ refers to the degree in which this component is important to investors for their decision making (Zhou et al. 2017). ‘Newness’ refers to the number of organizations for which the 31 components were currently not disclosed in the annual reports or CSR reports (Zhou et al. 2017). Furthermore, measurement of IR quality by the coding framework is correlated with the EY quality categories (EY, 2012), which adds further validity to the use of the framework of Zhou et al. (2017). This study follows the framework of Zhou et al (2017) to measure the alignment with the IR framework and to obtain insight in the different content elements. The coding framework can be found in the Appendix B.
4.4. Control variables
To ensure that the dependent variable is explained by the test variable, numerous control variables are included to capture previously documented determinants of corporate disclosure practices and institutional ownership.
14 4.4.1. Firm size
Firm size is an important control variable since larger companies receive more attention from the public and therefore they receive more public pressure to act social responsible (Cowen et al., 1987). According to Serafeim (2015) larger companies are more likely to engage in IR and have larger percentages of dedicated investors. Firm size can be measured with the natural logarithm of total assets (Mishina, Dykes, Block, & Pollock, 2010).
4.4.2. Leverage
Higher levels of leverage are associated with higher levels of institutional ownership (Badrinath, Gay and Kale, 1989; Skinner 1989). Leverage will be measured as total debt over assets (Serafeim, 2015).
4.4.3. ESG Score
While Dhaliwal et al. (2011) found evidence that CSR initiating firms with superior CSR performance attract more dedicated institutional investors, it is necessary to control for this effect as well. A score on ESG performance can be collected from the ASSET4 Database. 4.4.4. Industry
There is controlled for industry type using the BVD Major Sector from Orbis. Fifteen types of industries are identified in this study. Multiple dummies are created whereby the firm receives the value 1 if it falls within the range of the certain type of industry as shown below, and 0 otherwise.
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Table 2
Industry classification Frequency
Banks 18
Chemicals, rubber, plastics, non-metallic products 6
Construction 18
Food, beverages, tobacco 9
Gas, Water, Electricity 15
Hotels & restaurants 6
Insurance companies 6
Machinery, equipment, furniture, recycling 6
Metals & metal products 9
Other services 30
Post & telecommunications 9
Primary sector 6
Textiles, wearing apparel, leather 3
Transport 6
Wholesale & retail trade 3
Total 150
4.4.5. Other variables
According to Gompers and Metrick (1998), Bushee and Noe (2000) and Bushee (2001) there are several variables upon which institutions might base their trading decisions. These are dividend yield and sales growth. Further equity beta, earnings price ratio, price to book value, stock return volatility, and past one-year stock return are associated with the investor base of a firm (Bushee and Noe, 2000).
4.5. Data analysis
Hypothesis 1: To test the first hypothesis, a random effects regression is used. The regression model is specified as follows:
LT-INVESTOR = α + β1 * (IR)i,t + β2 * (CONTROLS)i,t + (Year Dummy + Industry
16 Where I compromises the firm and t the year
Hypotheses 2a-d: A random effects regression is used to test the other hypotheses too. The regression models are specified as follows:
LT-INVESTOR = α + β1 * (CE1)i,t + β2 * (CONTROLS)i,t + (Year Dummy + Industry
Dummy) + εi
LT-INVESTOR = α + β1 * (CE4)i,t + β2 * (CONTROLS)i,t + (Year Dummy + Industry
Dummy) + εi
LT-INVESTOR = α + β1 * (CE5)i,t + β2 * (CONTROLS)i,t + (Year Dummy + Industry
Dummy) + εi
LT-INVESTOR = α + β1 * (CE7)i,t + β2 * (CONTROLS)i,t + (Year Dummy + Industry
Dummy) + εi
5. RESULTS
5.1. Descriptive Statistics
In table 3, the descriptive statistics of this study are provided for each variable. To reduce the effect of outliers, all continuous variables are winsorised at the 1 and 99 percent levels. The descriptive statistics show that the mean (median) of the dependent variable is -29,592 (-31) per cent, while the standard deviation is 26,205. This indicates that in this sample, there are relatively more long-term investors than short term investors. The descriptive statistics further show that IR, on average, is relatively high mean (median) is 47,89247 (46,77419) with a standard deviation of 26,43407 which indicates a significant variation in the extent of IR within the sample. Further, it can be concluded that the first content element ‘Organizational overview and operating context’ has the highest store, namely 62,133 per cent. The last content element ‘other elements’ shows the lowest average sore, which is 32,444 per cent only. This represents that Spanish PLCs, on average, place less emphasis on the last content element.
The statistics for the year and industry dummies are not included in table 3. The observations are equally distributed over the year 2015 to 2017. Furthermore, the most common industries in the sample are banks (12 percent), construction (12 percent) and gas, water and electricity (10 percent). Twenty percent of the firms are attributed to the category ‘other services’. The remaining percentage is distributed among the 11 other industries.
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Table 3
Descriptive statistics
Variable N Mean Median Std. Dev. Min. Max.
Dependent variable
LT INVESTOR 147 -29,592 -31 26,205 -73 12
Independent variables
IR 150 47,892 46,774 26,434 6,452 93,548
CE1: Organizational overview and
operating context 150 62,133 60 32,781 0 100
CE2: Governance 150 47,167 50 26,944 0 100
CE3: Opportunities and risks 150 60,667 50 29,302 0 100
CE4: Strategy and resource allocation
plans 150 53,833 50 34,239 0 100
CE5: Business model 150 51,778 33,333 41,150 0 100
CE6: Performance and outcomes 150 40,286 42,857 31,406 0 100
CE7: Future outlook 150 38 33,333 33,452 0 100
CE8: Other elements 150 32,444 33,333 29,901 0 100
Control variables ESG score 150 68,437 70,53 12,468 35.69 92.34 Size 150 16,438 16,171 1,693 13,628 20,999 Leverage 150 225,267 145,215 404,898 0 2859.9 Dividend Yield 150 2,801 2,347 2,346 0 11.87 EP 150 7,291 5,884 9,115 0 76,923 PTB 150 2,807 2.21 2,248 0.35 10.68 Sales growth 150 3,904 2.915 11,500 -25.09 44.41 Beta 150 0.858 0.853 0.255 0.439 1,455 Volatility 150 5.02 4 3,288 2 18 Stock return 150 7,580 3.25 27,287 -57.12 111.3
This table presents the descriptive statistics for the variables employed in this study. All variables are defined in the appendix.
5.2. Multicollinearity
In order to rule out multicollinearity, a Pearson correlation test is performed. The correlation matrix is presented in table 4, which shows the correlation between the variables used in the primary analysis. I acknowledge that Size strongly correlates with ESG score (0,4533). However, this coefficient is not greater than |0,70|, and is similar to the research of Serafeim (2015). Furthermore, size is strongly correlated with beta (0,6102). As this coefficient is still not greater than |0,70|, which is acceptable within generally accepted norms, multicollinearity does not play a major role in this research.
However, between the different content elements is a collinearity problem. Although this makes sense, since the content elements are all part of an integrated report, an additional check is conducted. The variance inflation factor (VIF) of the content elements are provided in table 5. The control variables are also taken into account. None of the variables have a value
18 above 10, supporting the Pearson correlation matrix that multicollinaerity does not play a role in this sample (Hair et al., 2009; Gujarati & Porter, 2009).
Table 4
Collinearity statistics
Panel A: correlation variables LTINVESTOR to CE5: Business model
Variables 1 2 3 4 5 6 7
1 LT INVESTOR 1
2 IR -0.0923 1
3 CE1: Org. overview and operating context -0.1055 0.8652*** 1
4 CE2: Governance -0.001 0.7017*** 0.5464*** 1
5 CE3: Opportunities and risks 0.0829 0.584*** 0.4233*** 0.4954*** 1
6 CE4: Strategy and resource allocation -0.1363* 0.9021*** 0.785*** 0.4802*** 0.4105*** 1
7 CE5: Business model -0.2226*** 0.8304*** 0.7435*** 0.4762*** 0.4109*** 0.7593*** 1 8 CE6: Performance and outcomes -0.0032 0.9287*** 0.7336*** 0.6315*** 0.4988*** 0.8429*** 0.7071*** 9 CE7: Future outlook -0.0086 0.68*** 0.4642*** 0.4615*** 0.3939*** 0.5605*** 0.5059*** 10 CE8: Other elements -0.1678** 0.7728*** 0.6045*** 0.4342*** 0.4577*** 0.6972*** 0.5528*** 11 ESG score -0.0436 0.0672 -0.0828 0.0723 0.019 0.0067 0.0181 12 Size 0.1479* 0.2168*** 0.1112 0.1452* 0.0239 0.2503*** 0.1214 13 Leverage 0.0429 0.2308*** 0.1568* 0.1528* 0.1731** 0.2282*** 0.1715** 14 Dividend Yield 0.2638*** 0.0859 0.053 0.024 0.0123 0.0524 0.0415 15 EP 0.0511 -0.0894 -0.0626 -0.0191 -0.0836 -0.0904 -0.1509* 16 PTB 0.07 0.0299 -0.0002 0.0712 0.2199 -0.042 0.0218 17 Sales growth -0.0852 -0.0891 -0.0732 -0.0879 -0.0234 -0.1019 0.0278 18 Beta 0.0236 0.11 0.0208 0.0791 -0.0625 0.0887 0.0224 19 Volatility -0.0164 -0.1339 -0.1212 -0.1887** -0.1415* -0.1333 -0.0507 20 Stock return -0.0057 0.0737 0.0999 0.094 0.0065 0.1072 0.0406
Panel B: Correlation variables CE6: Performance and outcomes to Dividend Yield
Variables 8 9 10 11 12 13 14
8 CE6: Performance and outcomes 1
9 CE7: Future outlook 0.5651*** 1
10 CE8: Other elements 0.7156*** 0.4962*** 1
11 ESG score 0.1178 0.2411*** 0.0724 1 12 Size 0.27*** 0.2853*** 0.0574 0.4533*** 1 13 Leverage 0.2172*** 0.1572* 0.2325*** 0.035 0.1972** 1 14 Dividend Yield 0.0701 0.2408*** 0.0726 0.1696** 0.3529*** 0.0509 1 15 EP -0.0743 -0.0518 -0.0395 -0.0746 0.0337 0.015 -0.0112 16 PTB 0.052 -0.1597* 0.1326 -0.0963 -0.3505*** 0.2517*** -0.1573* 17 Sales growth -0.1136 -0.1218 -0.0271 -0.1485* -0.3193*** -0.222*** -0.2356*** 18 Beta 0.1768** 0.3124*** -0.0367 0.3402*** 0.602*** 0.0201 0.193** 19 Volatility -0.1081 -0.0354 -0.1045 -0.0218 -0.1319 0.1334 -0.0734 20 Stock return 0.0505 0.0071 0.0221 -0.0783 -0.0812 -0.253*** -0.2025**
Panel C: Correlation variables EP to Stock return
Variables 15 16 17 18 19 20 15 EP 1 16 PTB -0.132 1 17 Sales growth -0.2172** 0.2144*** 1 18 Beta -0.0699 -0.3803*** -0.1358* 1 19 Volatility -0.0231 0.1751** -0.0808 0.0225 1 20 Stock return 0.0914 0.0341 0.1106 -0.1116 -0.257*** 1 Signifance levels: *** p<0.01; **p<0.05; * p<0.1
19
Table 5
Variance Inflation Factor
Variable VIF
CE4: Strategy and resource allocation plans 6.1
CE6: Performance and outcomes 5.82
CE1: Organizational overview and operating context 3.49
CE5: Business model 3.13
Size 2.76
CE8: Other elements 2.65
CE7: Future outlook 2.22
CE2: Governance 2.04
BETA 2.02
PTB 1.8
CE3: Opportunities and risks 1.64
ESG Score 1.52 Leverage 1.48 Dividend Yield 1.39 Sales growth 1.38 Volatility 1.30 Stock return 1.30 EP 1.16 Mean VIF 2.4 5.3. Regression results.
Table 6 presents the regression results of this study. To decide whether a random- or fixed-effects model is appropriate for the regression, a Hausman test was performed. The Hausman test supported a random-effects model. Hence, a random-effects model is performed in this study.
The first model regresses LT-INVESTOR on several control variables. The direction of most control variables is in line with expectations, based on previous research, such as Serafeim (2015). However, only Leverage shows a significant relationship with LT-INVESTOR. The coefficient is positive, meaning that firms with higher leverage have relatively more short-term investors than long-term investors. Although the other control variables are not significant, they are still included, since other studies show the significant influence on the investment base of a firm (Bushee and Noe, 2000).
The second model tests hypothesis 1, which predicts a causal relationship between LT-INVESTOR and the practice of IR. Although the regression results show a negative relationship for IR, it is not statistically significant (β = -0,172 p > 0.1). Therefore, hypothesis 1 is not found to be supported.
20 To isolate the impact of the different content elements, this research uses different regression models to test possible causal relationships between the content elements and LT-INVESTOR. The sixth model tests hypothesis 2a, demonstrating a causal relationship between LT-INVESTOR and disclosure on ‘strategy and resource allocation’. The coefficient is negative, but not significant (β = -0.0525 p > 0.1). Therefore, hypothesis 2a is not supported. The seventh model tests hypothesis 2b, demonstrating a causal relationship between disclosure on business model and LT-INVESTOR. The coefficient on this content element is negative and significant (β = -0.0907 p < 0.05), which supports my hypothesis that companies providing more information on their business model have a more long-term investor base. The ninth model tests hypothesis 2c, which predicts a negative causal relationship between future outlook reporting and LT-INVESTOR. The coefficient on this content element is negative, but not significant (β = -0.0678 p > 0,1). The tenth model tests hypothesis 2d, which predicts a negative causal relationship between ‘other elements’ and LT-INVESTOR. The coefficient is negative and significant (β = -0.0902 p < 0.1), supporting my hypothesis that companies providing more information on the ‘other elements’ have a more long-term investor base.
In this study, the other content elements are also investigated. However, these content elements do not show a significant relationship with LT-INVESTOR.
21
Table 6
Model1 Model2 Model3 Model4 Model5 Model6 Model7 Model8 Model9 Model10 Model11 VARIABLES H1 H2a H2b H2c H2d Constant 21.08 30.17 19.52 26.50 28.06 23.70 16.94 25.42 21.82 29.21 -5.483 (62.63) (62.80) (63.58) (63.61) (64.27) (61.93) (59.72) (63.58) (62.73) (61.03) (59.55) IR -0.0962 (0.0756) CE1: Organizational overview and operating
context 0.0264 0.126
(0.0697) (0.0969)
CE2: Governance -0.0532 -0.00823
(0.0653) (0.0791)
CE3: Opportunities and risks -0.0219 -0.0155
(0.0440) (0.0536)
CE4: Strategy and resource allocation plans -0.0525 0.00550
(0.0581) (0.106)
CE5: Business model -0.0907**
-0.156*** (0.0416) (0.0588)
CE6: Performance and outcomes -0.0294 0.180
(0.0655) (0.119)
CE7: Future outlook -0.0678 -0.0527
(0.0466) (0.0619)
CE8: Other elements -0.0902* -0.112*
(0.0466) (0.0640) ESG score -0.0860 -0.113 -0.0815 -0.110 -0.0948 -0.0998 -0.0947 -0.0944 -0.103 -0.113 -0.0763 (0.168) (0.169) (0.169) (0.170) (0.168) (0.170) (0.166) (0.169) (0.167) (0.167) (0.168) Size 0.0307 -0.137 0.0565 -0.160 -0.296 0.151 0.714 -0.0516 -0.0521 -0.0537 1.438 (3.217) (3.208) (3.253) (3.258) (3.283) (3.170) (3.081) (3.234) (3.220) (3.130) (3.017) Leverage 0.00732* 0.00776* 0.00734* 0.00781* 0.00757* 0.00741* 0.00709* 0.00747* 0.00777* 0.00802* 0.00743* (0.00434) (0.00434) (0.00435) (0.00436) (0.00435) (0.00436) (0.00430) (0.00436) (0.00432) (0.00433) (0.00433) Dividend Yield 0.142 0.310 0.103 0.208 0.163 0.260 0.333 0.195 0.186 0.470 0.419 (0.571) (0.585) (0.580) (0.576) (0.573) (0.587) (0.575) (0.585) (0.568) (0.592) (0.601) EP 0.0321 0.0254 0.0339 0.0252 0.0266 0.0288 0.0397 0.0329 0.0229 0.0168 0.0203 (0.100) (0.1000) (0.100) (0.0999) (0.100) (0.101) (0.0999) (0.100) (0.0995) (0.100) (0.102) PTB -1.695 -1.818 -1.684 -1.749 -1.732 -1.719 -1.684 -1.744 -1.843 -1.909 -1.674
22 (1.294) (1.295) (1.300) (1.295) (1.297) (1.300) (1.278) (1.303) (1.291) (1.289) (1.278) Sales growth -0.145 -0.137 -0.145 -0.146 -0.142 -0.138 -0.0936 -0.145 -0.152 -0.133 -0.0425 (0.0951) (0.0952) (0.0953) (0.0948) (0.0951) (0.0963) (0.0979) (0.0954) (0.0946) (0.0950) (0.102) Beta 32.88 32.61 33.18 34.23 33.27 31.85 29.21 32.88 35.30 30.02 26.91 (23.06) (22.95) (23.30) (23.49) (23.50) (22.56) (21.83) (23.15) (23.18) (22.26) (21.26) Volatility -1.301 -1.380 -1.298 -1.337 -1.331 -1.375 -1.273 -1.357 -1.265 -1.382 -0.982 (1.470) (1.465) (1.486) (1.497) (1.500) (1.440) (1.388) (1.481) (1.476) (1.417) (1.348) Stock return 0.0110 0.0133 0.0106 0.0116 0.0123 0.0145 0.0119 0.0118 0.00827 0.0150 0.00882 (0.0306) (0.0306) (0.0306) (0.0305) (0.0306) (0.0311) (0.0306) (0.0307) (0.0304) (0.0306) (0.0317) Observations 146 146 146 146 146 146 146 146 146 146 146 Number of firms 50 50 50 50 50 50 50 50 50 50 50
Yeardummy Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Industrydummy Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
R-squared 0.3539 0.3701 0.3482 0.3512 0.3488 0.3788 0.4122 3571 0.3566 0.3838 0.4544
23
5.4. Additional analysis
To check the robustness of the regression results, five additional tests are conducted. The results can be found in the Appendix.
5.4.1. Lead lag analysis
Although the results of the regressions in table 6 show a robust relation between a long-term investor base and IR, the direction of causality could be reversed. Companies practicing IR might attract more long-term investors. Therefore, an additional analysis is conducted where the independent and control variables are lagged by one year. The results of the analysis without lagged variables, are shown in appendix III.
Model 1 shows a significant negative relationship between IR and LT-INVESTOR (β = -0.116 p < 0.1), suggesting that companies practicing IR attract more investors that find this information useful for their objectives.
The other models show a significant negative relationship between the content elements strategy and resource allocation, business model, performance and outcomes and future outlook and LT-INVESTOR. However, these significant relationships between the content elements and LT-INVESTOR are not supported by model 11. Therefore, the results are less reliable.
5.4.3. Alternative measure IR
Since IR is a subjective judgement, an alternative measure for IR is included. Following the study of Serafeim (2015), data from ASSET4 can be used to measure the degree of IR. ASSET4 provides a composite score for IR, ranging from zero to 100, reflecting a firm’s capacity to convincingly show and communicate that it integrates financial, social and environmental aspects into its day-to-day decision-making processes. The measurement of all other variables remains unchanged. The results of this additional analysis are shown in appendix IV. The coefficient is negative and significant (β = -0.116 p < 0.1). This measure is inconsistent with the primary analysis, as it supports my hypothesis that firms practicing IR have a more long-term investor base.
5.4.4. Alternative measure LT-INVESTOR
In the primary analysis the time horizon of the investor base is calculated as the percentage of shares held by short-term investors (investment corporations) less the percentage
24 of shares held by long-term investors (government investment funds, pension funds, employees and other corporations). As an additional check, short-term investors are excluded from LT-INVESTOR. Consequently, LT-Alternative measured as the sum of the percentage of shares held by government investment funds, pension funds, employees and other corporations. The results of this additional test are shown in appendix V. Consistent with the primary analysis, model 7 shows a significant negative relationship between business model reporting and LT-Alternative (β = -4.964 p < 0.01). Furthermore model 10 also shows a significant relationship between ‘other elements’ and LT-Alternative (β = -4.251) p < 0.01). Inconsistent with the primary analysis, the results show a significant relationship between IR and LT-Alternative (β = -0.116) p < 0.1), meaning that firms with higher alignment with the IR framework have a more long-term investor base.
5.4.4. Test for South African sample
As this study focuses on Spain, an additional test is conducted to examine the relationship between IR and the investor base in South Africa. The South African JSE was the first stock exchange to incorporate the move towards IR into its listing rules, under the King Code of Corporate Governance (JSE, 2015). Therefore, most studies on IR focused on South Africa (Serafeim, 2015). As this is a unique situation, this research performs an additional analysis with a South African sample, as this can be used as a benchmark. The results show a negative, but non-significant relationship between IR and LT-alternative, suggesting that due to the mandatory nature of IR, there is no relationship between IR and the investment horizon of a firm’s investor base. However, more alignment with the IR framework might be more important in South Africa and therefore a better measure.
6. DISCUSSION
6.1. Findings
This study examined the relationship between the practice of IR and the investor base of a firm. The findings of this study are based on 146 observations of 49 firms listed on the Bolsa de Madrid during the period 2014 to 2016. The eight content elements, which include organizational overview and operating context, governance, opportunities and risks, strategy and resource allocation plans, business model, performance and outcomes, future outlook and other elements, are examined to address the question which elements of IR are most important to long-term investors.
25 The findings first suggest a significant relationship between business model reporting and a more long-term investor base. This indicates that firms disclosing more information on their business model, which provides opportunities for future growth (PwC, 2016), have a more long-term investor base. Second, a significant relationship is found between ‘other elements’ and a more long-term investor base. This indicates that firms taking into account other elements, such materiality and conciseness and connectivity, have a more long-term investor base. Therefore, hypotheses 2b and 2d can be accepted. By investigating these relationships, this research builds on and confirms the agency theory and the legitimacy theory. No significant relationship is found between the strategy and outlook element and a more long-term investor base. Therefore, hypotheses 2a and 2c are rejected.
The results of this study suggest that firms producing integrated reports have a more long-term investor base. However, these results were only significant when using an alternative measure of IR, which is in accordance with the study of Serafeim (2015). Interestingly, there is no significant relationship found for the South African sample with this measure. One explanation for the non-significant results is that IR is mandatory in South Africa. According to Velte and Stawinoga (2017) voluntary adoption of IR might be an effective tool for organizations to communicate their legitimization actions. Another explanation is that in South Africa, the quality of IR (more alignment with the IR framework) might be more important. The results of this study do not provide conclusive evidence that Spanish companies compiling integrated reports that are more aligned with the IR framework have a more long-term investor base. However, when using a lead-lag analysis, this study provides evidence that suggests there is a causal relationship between the quality of IR and an investor base with more long-term shareholders.
In sum, based on the results of this research, the research question can be answered: “Which elements of an integrated report are most effective at meeting the information demands of long-term investors?” This study provides evidence that firms providing more disclosure on the content elements ‘business model’ and ‘other elements’, such as conciseness and links, and materiality, have a more long-term investor base, which suggests that these elements are more effective at meeting the information demands of long-term investors.
6.2. Theoretical and practical implications
The main theoretical implication of this paper is the examination of the importance of the different content elements to long-term investors. To the best of my knowledge, this is the
26 first study that tries to determine which elements are most important to long-term investors. Accordingly, the findings of this study contribute to the growing literature on IR.
Second, this study investigates the practice of IR in Spain. As most studies investigated IR in South Africa (Serafeim, 2015), a research gap exists on the impact of IR globally. This study aims to address this gap by providing evidence on the relationship between IR and the investor base of firms in Spain.
Third, the findings of this study can be practically relevant. As this study provides evidence which elements of an integrated report are relatively more important to long-term investors, the results can help companies in the adoption of IR. Furthermore, this study provides companies that consider the adoption of IR pragmatic expectations about their ability to attract more long-term investors.
6.4. Limitations and Future research
The results of this study should be considered in the light of some limitations. First, the sample employed for this paper focuses only on 50 Spanish companies listed on the Bolsa de Madrid. Hence, the findings of this small sample might not be generalizable to the entire population of Spain. Future research should extend the investigation to other countries and compare cross-country differences. Furthermore, despite the fact that the measurement of all variables are based on previous research, they suffer from some limitations. Firstly, the coding process involves a certain level of individual judgement. Therefore, the results of this study might be less reliable. Second, due to data restriction, this study uses a different combination of long-term and short-term investors to measure the investment horizon of the investor base. Hence, this measure might reduce the reliability of the findings.
Since this study focuses on the relationship between IR and a more long-term investor base, future research can examine the moderating effect of IR on the relationship between ESG performance and a more long-term investor base. Furthermore, it is important to note that IR is a costly activity and it is unclear whether the benefits exceeds the costs (Serafeim, 2015). Anecdotal evidence suggests that investments to improve information systems for sustainability data, acquiring skills and expertise to use and integrate data in financial reporting are the most important costs (Serafeim, 2015). Future research should investigate whether the benefits of IR exceed the costs. Lastly, future research could examine whether the practice of IR increases integrated thinking within the firm. Integrated thinking ensures the integrated report becomes
27 more than just the output of a process (IIRC, 2017). With integrated thinking, the integrated report becomes “a critical milestone in the continuous journey of improvement in decision-making, accountability and communication” (IIRC, 2017). Integrated thinking is embedded into a firm’s activities, which facilitates the natural connectivity of the information flow into management reporting, analysis and decision-making (IIRC, 2017).
28
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