Innovation, Corporate Social Responsibility and Financial. Performance. A Thesis. Presented to the. Faculty of Economics and Business Administration

Transcription

1 Innovation, Corporate Social Responsibility and Financial Performance A Thesis Presented to the Faculty of Economics and Business Administration in partial fulfillment of the requirements for the degree of M.Sc. in Economics by Monica M. Montoya ANR: Advisor: Dr. J.J. Graafland Tilburg University 2011

2 Acknowledgements I would like to express gratitude towards Professor J.J. Graafland for his invaluable support and guidance. Thanks to Professor J.A. Smulders for his comments on this thesis. I would also like to thank Drs. H. Smid for making the data available for this study and his collaboration. Special thanks to my family and friends for their encouragement, support and inspiration. i

3 Abstract The link between Corporate social performance (CSP) and corporate finance performance (CFP) have been the focus of a large number of studies. However, there is few research on the role of innovation in this linkage. This study is conducted to examine the effect of innovation on the CSP-FP relationship. CSR firm data from Sustainalytics (for 2008 and 2009) and the financial data from Capital IQ (2007 and 2009) were used to carry out a regression analysis with lagged independent variables. This analysis suggests no role of innovation on the CSR-FP, and shows no statistical significance or ambiguity on relationships between CSP, FP and innovation identified previously in the literature as positive. The obtained models are robust other time range specifications. ii

4 Table of Contents Abstract ii Introduction 1 1 Theoretical Background Concepts Literature Review and Hypothesis Development Innovation, CSR and Economic Performance CSR and Financial Performance CSR and Innovation Innovation and Financial Performance Research Analysis Conceptual Framework Methods The data Specification and Data Issues Treatment Definition of Variables Analysis Bi-variate Analysis: Pearson correlation coefficients Multi-variate Analysis: linear regression Checking Models Robustness Results and Conclusions Summary of Results Conclusion A Appendix A 40 Bibliography 43 iii

5 List of Figures 1.1 The five dimensions of competitiveness Conceptual Framework Results A.1 Measurements of Financial Performance in CSR literature iv

6 List of Tables 2.1 Variables of the study Descriptive Statistics Regions and economic sectors in the sample Firm Size Regression analysis, Hypothesis 1 and Regression analysis, Hypothesis 4 and Regression analysis, Hypotheses 2 and 6. Disaggregated growth variables Regression analysis, Hypotheses 2 and 6. Disaggregated return variables 32 A.1 Hypothesis 1 and 3. Regression analysis including Profit Growth A.2 Hypothesis 2 and 6. Regression analysis including desagregated growth and CSR variables v

7 Introduction Corporate Social Responsibility (CSR) has become of greater practical significance to increase competitiveness for firms and governments alike. Firms engage on CSR practices aiming to improve corporate social performance and financial performance. Governments want to implement policies that support firms environmentally and socially responsible behavior (Wagner, 2010) looking to increase international competitiveness, sustainable development and economic growth. For example, the European Commission sees CSR as an important part of the European strategy for increasing growth, competitiveness, quality of jobs (Lisbon Strategy) and sustainable development (Gothenburg strategy). In sum, greater involvement in CSR by governments and companies contributes to increase EU competitiveness and sustainable development. Company s competitiveness and success is increasingly being linked to CSR. Managers are expressing interest for approaches to corporate sustainability linked to innovation (Wagner, 2010) as a way to increase competitiveness. While innovation has been recognized as one of the key elements to increase competitiveness, it may be also one of the most effective ways to increase corporate social performance. There is case-based evidence showing this type of approach may produce the highest potential benefit for both the firm and the society (Halme and Laurila, 2009). The objective of this study is to describe the links between CSR and financial performance (FP) and, most importantly, identify the role of innovation on this relationship. The relationship between CSR and FP has been extensively analyzed but the discussion on the key role of innovation just started in the last decade with the work of 1

8 Introduction 2 McWilliams and Siegel (2000), which shows that misspecification in previous models cause estimators to be upwardly biased. McWilliams and Siegel (2000) revealed a flaw in previous econometric studies about the link between CSR and FP as these studies do not control for R&D. Some studies state that it remains unclear whether factors such as R&D might influence the relationship between CSP and FP as a whole or through CSP or CFP (van Beurden and Gössling, 2008). Further analysis in this direction is needed as it is a way to approach CSR s complexity (Padgett and Galan, 2009) and find empirical evidence for potential moderators or possibly confounding variables (Orlitzky, 2001). We aim to analyze the effect that R&D has on the link between CSR and FP providing a broader understanding of this effect and contributing to the literature in this area by using environmental, social and governance data from Susainalytics 1. The present analysis is framed in the following questions: what is the relationship between CSR and economic performance/competitiveness? What is the role of innovation in this relation? Which other factors have an influence upon it? Are there differences for large and small companies and for different sectors and countries? What about the reverse effects? Is a company with CSR practices more open to create new products and processes? This work is divided in three sessions as follows. In Section one an overview of the theory and previous studies on CSR and its relationship with competitiveness and innovation is provided. In Section two the research analysis is presented. In Section three the results are discussed and the conclusion is presented. 1 One common database used by recent studies is the KLD database

9 Chapter 1 Theoretical Background The link and consequences of CSR, across economic, social and environmental dimensions, have been the subject of numerous studies and debates. The literature in this area is characterized by: (1) a large number of studies focusing on the link between CSR and company s economic or financial performance (FP), (2) a smaller number of studies on the relationship between CSR and societal or environmental outcomes, and (3) few studies on the role of innovation on the link between CSR and economic performance. In this section we discuss the existing literature on the links between CSR, innovation and financial performance, and introduce our hypotheses. We will use literature published after 1990 following Gössling and van Beurden s (2008) argument that the Brundtland Report (The World Commission on Environment and Development, 1987) was a turning point in the attention toward CSR and after 1990 the role of business was discussed in a new light. These changes are not likely to enter academic research and be published before Concepts Corporate Social Responsibility. There is not consensus in a clear way to define the concept of Corporate Social Responsibility (CSR), not exactly on which elements should be included in its definition. This is a common problem already identified on CSR literature (van Beurden and Gössling, 2008; Orlitzky, 2001; Orlitzky, Schmidt, 3

10 Chapter 1. Theoretical Background 4 and Rynes, 2003). Despite the lack of consensus as to how CSR should be defined, Dahlsrud (2008) argues that the confusion is not so much about how CSR is defined, as about how CSR is socially constructed in a specific context. Based on an extensive study of CSR definitions, Dahlrud (2008) identifies five dimensions often involved in existing CSR definitions: economic, environmental and social value creation, stakeholder relations and voluntariness. The economic dimension refers to socio-economic or financial aspects of CSR that contribute to firm s economic development and business operations. The environmental dimension of CSR includes firm s environmental stewardship and environmental concerns in business operations. The social element touches on the relationship between business and society and looks into how the company integrates social concerns in their business operations and considers the full scope of their impact on communities. The fourth element of CSR, stakeholder relations, refers to how organizations interact with their employees, suppliers, customers and communities community as a large. The fifth element of voluntariness implies actions beyond legal obligations and based on ethical values. In this study we base our definition of CSR on The European Commission s CSR definition (2001), that is, CSR is a concept whereby companies integrate social and environmental concerns in their business operations and in their interaction with their stakeholders on a voluntary basis. This definition encompasses the five CSR elements identified by Dahlrud (2008). However, for our study we note that CSR constitutes more than simply voluntary actions. For instance, there are incentives designed by governments (e.g. regulations or economic instruments) to encourage CSR. Also, companies may engage in strategic CSR practices as a way to differentiate themselves and increase their competitiveness (Hull and Rothenberg, 2008). CSR is difficult to measure mainly due to its broad scope. For instance, it covers factors inside and outside of the company and also aspects of implementation and

11 1.1. Concepts 5 performance. Scholars and practitioners use other variables as proxies for CSR such as Corporate Social Performance (CSP) and Environmental Management Systems (EMS) that reflect the implementation of CSR practices. Three CSR types are identified by Halme and Laurila (2009): (1) Philanthropy. Emphasizing on charity, sponsorships, employee voluntarism, etc. (2) Corporate responsibility Integration, looking into conducting existing business responsibly. (3) Corporate responsibility Innovation, focusing on developing new business models aimed at reducing social and environmental problems. According to the authors, the CR Integration type is more prominent in terms of financial outcomes than philanthropy, but there are no studies on the relation between corporate responsibility innovation and FP. Innovation. The innovation of a firm is reflected in the introduction of or effort to implement new products, processes or organizational systems. Companies want to adopt innovation that will allow them to produce with less inputs, improve or develop new goods or introduce new forms of management, contributing to the firm s profit maximization and competitiveness. As pointed out by Wagner (2010), among chief executive officers of global companies, there is an increasing awareness of the need for strategic approaches to corporate sustainability and corporate social performance that are linked with related innovation activities (Wagner, 2010:581) There are different indicators utilized to measure innovation. They can be classified in output indicators (e.g. product and process innovation), intermediate indicators (e.g. number of patent applications) and input indicator (e.g. total innovation and R&D expenditures). The literature does not offer a consensus on which type of indicator is better, and it is not expected to do so given that these innovation indicators reflect different components of innovation. R&D and patents application - two commonly used indicators for innovation - are not perfect indicators and some researchers argue they have drawbacks. For instance,

12 Chapter 1. Theoretical Background 6 Kleinknecht, Van Montfort, and Brouwer (2002) state that patent applications are not necessarily representative of innovation because not all firms that innovate apply for patents; the patent application is costly and time consuming, so firms may not have the resources and structure to apply and obtain patents approved. In addition, this indicator refers mostly to innovations that are completely new to the sector, excluding incremental ones. On the other hand, the sole use of R&D as an innovation indicator will underestimate innovation efforts in sectors like services. Financial Performance. There are mainly two kind of instruments to measure the economic performance of a company, market-based (e.g. stock performance, market return, price per share, share price appreciation) and accounting-based instruments (e.g. returns on assets, returns on equity, profit). Financial performance measurements used in CSR studies are diverse (see Figure A.1 in Appendix A). There is a difference in the prediction of financial performance between market-based and accounting-based measures of corporate financial performance (van Beurden and Gössling, 2008). Wu (2006) concludes that studies using market measurements report a smaller relationship between corporate social performance and FP than studies using other measurements, such as profitability and growth. Competitiveness. In broad terms competitiveness is described as the strength of an organization in comparison with the competitors in the market (Vilanova, Lozano, and Arenas, 2008). There are many definitions and measurements. Vilanova et al. (2008) identify five key dimensions of competitiveness (see Figure.1.1) representing a comprehensive characterization of it: (1) Performance ( e.g. earnings, growth or profitability); (2) Quality of products, services and capacity to satisfy customer expectations; (3) Productivity, related to higher production and lower use of resources; (4) Innovation of products, services and management and (5) Image, including corporate branding in terms of building trust and reputation with stakeholders.

13 1.2. Literature Review and Hypothesis Development 7 In this conceptual context, in this study we are analyzing three key variables that drive competitiveness of companies. We look into dimensions (1), (4) and (5) that is financial performance (accounting measurements), general innovation (R&D expenditure) and CSR variables, respectively. Figure 1.1: The five dimensions of competitiveness Source: Vilanova et al Literature Review and Hypothesis Development Innovation, CSR and Economic Performance Many studies mention the importance of the role of innovation on the link between CSR and Economic performance, but there are few studies analyzing this role in detail. The discussion on the key role of innovation started with the work of McWilliams and Siegel (2000) who revealed a flaw in previous econometric studies about the link between CSP and FP, as they did not control for innovation. McWilliams and Siegel (2000) demonstrate that innovation is a significant driver of firm performance, and when innovation is included among the independent variables the significance of the CSP-FP relationship could disappear. Researchers offer different reasons to explain why innovation is an important mechanism in the CSR-FP relationship. Wagner (2010:583) argues that CSR activities

14 Chapter 1. Theoretical Background 8 can lead to innovation that, for example, enable environmental product differentiation. Product differentiation can lead to higher prices and hence improve firms economic performance [...] If this holds true, then innovation would be one important mechanism through which CSP can positively influence economic performance. Likewise, once the adoption of environmental innovations takes place and the competition among firms is more environmentally conscious, there will be an urgency for firms to focus on social demand and try environmentally friendly alternatives (Lee, Gemba, and Kodama, 2006). Innovation seems to be an element through which comparative advantage can be obtained, and it may be even stronger than CSR in this respect. As stated by McWilliams and Siegel (2001) using a differentiating strategy in order to obtain a competitive advantage through the use of CSR resources may also include investment in R&D. Innovation, besides being a strong predictor of financial performance, may moderate other variables that affect financial performance (Hull and Rothenberg, 2008). As previously mentioned, the literature reviewed suggests the need for further analysis taking into consideration the role of innovation on the CSR-FP link. While innovation has been recognized as a possible moderator on the relation between CSR and FP, the literature identifies bi-directional relationships between FP and Innovation (see Section 1.2.4), and CSR and Innovation (see Section 1.2.3). These links suggest that innovation can be a mediator between CSR and FP. In this study we aim to provide answers to the following questions: Which is the role of innovation on the link between CSR and FP? Is there empirical evidence for innovation as a potential moderator or mediator for the relationship between CSR and FP?

15 1.2. Literature Review and Hypothesis Development CSR and Financial Performance Studies on the relation between CSR and economic performance do not offer a single conclusion, indicating negative, positive and neutral linkages. Yet there are literature reviews showing that most of the studies find a positive relationship (van Beurden and Gössling, 2008; Wu, 2006; Allouche and Laroche, 2005; Goll and Rasheed, 2004; Orlitzky et al., 2003) and rigorous empirical studies supporting this positive relation (Waddock and Graves, 1997). A literature study to analyze the relation between CSP and financial performance (FP) was performed by van Beurden and Gössling (2008), finding empirical evidence for a positive correlation. Of the included studies 68% found a significant positive relationship, 26% found no significant relationship, and 6% found a significant negative relationship. The authors admit CSP and FP are measured in different ways and take into account these differences to be able to compare the studies. Orlitzky et al. (2003) also find empirical evidence, through a meta-analysis of 52 studies, to conclude that there is a positive relationship between CSP and FP, and that this relationship tends to be bidirectional and simultaneous (Orlitzky et al., 2003:427). Waddock and Graves (1997) and Scholtens (2008) also find a bidirectional relationship between CSR and FP, which makes it difficult to analyze the causality between corporate financial performance and corporate social performance. Scholtens (2008) identifies causation, suggesting that financial performance in general terms precedes social performance much more often than the other way around. Both studies suggest a virtuous cycle between CSP and financial performance. That is, CSP is found to be positively associated with prior financial performance, supporting the theory of slack resource availability (Waddock and Graves, 1997). This theory states that good financial performance makes available funds and resources necessary for the company to spend on CSP activities that improve social or environmental performance. On the other

16 Chapter 1. Theoretical Background 10 hand, CSR also adds financial value to the firm (Padgett and Galan, 2009; Schnietz and Epstein, 2005; McWilliams and Siegel, 2000; Konar and Cohen, 2001; Scholtens, 2008). Attention to CSP domains and efficient use of resources improves relationship with stakeholders, which could result in an increase of company value, and reduction of taxes and regulations. For instance, Konar and Cohen (2001) found that major corporations voluntarily over-comply with environmental regulations and externally portray an image of being environmentally concerned; and these firms are rewarded in the marketplace with a market value increase. Based on the findings on previous studies on the CSR-FP relationship, we predict that the bidirectional relationship is positive, and propose the following hyphotheses. Hypothesis 1: Financial Performance has a positive effect on CSR Hypothesis 2: CSR increases financial performance of firms CSR and Innovation The relationship between CSR and innovation could be bidirectional, CSR affecting innovation or innovation affecting CSR outcomes. On the link between CSR and innovation, the literature is divided in two main groups. The first group of researchers focus on general innovation and CSR; the second group of studies look into environmental innovation and CSR. Several studies argue CSR is positively correlated with innovation (Hull and Rothenberg,2008; McWilliams and Siegel, 2000; and Padgett and Galan,2009). Those studies point out that the positive effect of R&D intensity on CSR is not the same across industries. For instance, it seems that the effect of R&D in CSR more intense in manufacturing industries than in non-manufacturing ones (Padgett and Galan, 2009). There are some particular elements of CSR that have been focus of numerous studies, in its relation with innovation; those include environmental management systems

17 1.2. Literature Review and Hypothesis Development 11 (EMS), Voluntary Environmental Agreements (VEA) and in general CSR initiatives or policies implemented by firms aiming to improve their environmental performance. In this subgroup of studies there are also bi-directional causal links (Carrión-Floresa and Innesb, 2010). EMS systems enable the development of strategic resources which can have a positive impact on innovation capabilities in general and thus also on technological environmental innovations (Wagner, 2007; Frondel, Horbach, and Rennings, 2007). Similarly, specific management tools such as EMS tend to favor the adoption of cleaner production technologies instead of end-of-pipe technologies (Frondel et al., 2007) On the other hand, EMS could also reversely be affected by environmental innovations (Ziegler and Nogareda, 2009). Ziegler and Nogareda (2009:891) argue that technological environmental innovations are likely to be influenced by organizational routines, capabilities, and tacit knowledge related to environmental issues. These factors are probably also determinants of the adoption of EMS, challenging the positive correlation between EMS and technological environmental innovations, and concluding that the causal relationship as well as the partial correlation between those elements is ambiguous. Former empirical evidence suggest that general innovation can have a positive impact on the adoption of voluntary environmental programs (VEP). Those studies argue that Innovative firms are already engaged in improving production processes and products and therefore have overcome management barriers such as the lack of finance or know-how such that they are more likely to be capable of undertaking organizational changes and absorbing new costs (Ziegler and Nogareda, 2009:887). There are a number of other factors besides CSR practices, identified by scholars, that stimulates innovation and/or environmental innovation. Among those are Demand Articulation (Lee et al., 2006), and knowledge capital (Horbach, 2008). Lee et al. (2006) explain that Demand Articulation is an effective process by which knowledge

18 Chapter 1. Theoretical Background 12 and information flows raise the technological capability and awareness levels of firms and consumers for environmental improvement, inducing the adoption of new technologies and the development of new products. This development of technologies has been shown to trigger environmental innovations (Horbach, 2008). Hence, after this review it is reasonable to expect that: Hypothesis 3: Advancements on innovations increase CSR Hypothesis 4: CSR has a positive effect on innovations Innovation and Financial Performance The literature on innovation has identified several determinants of firm s R&D expenditures. Becker and Pain (2003) identify five main types of determinants in the existing literature: firm/industry characteristics (e.g. size, sector, country), product market competition, public policies, endowment and location, and spillovers from other sectors and support by foreign funds. Given that in this study we are interested in the impact of financial performance on innovation, we categorize the determinants of firm s R&D expenditures as financial and non-financial ones. Empirical studies have found that non-financial determinants having a positive impact on R&D include: tax incentives and public sector R&D (Falk, 2006); patent protection and strategic alliances (Cumming and MacIntosh, 2000). The financial factors that favor higher R&D expenditures are: low debt-equity ratios (Cumming and MacIntosh, 2000); sales and profitability (Becker and Pain, 2003); cash flows and expected returns (Mulkay, Hall, and Mairesse, 2001; Fazzari and Athey, 1989). In general, the economic rationale behind the impact of these financial variables in R&D is related to sources of financing. For companies to finance R&D projects, they need to have access to funds, and those funding resources are closely related to firm s profitability. Thus, the financial status of a firm or profitability may determine how flexible the company is to use its resources and thus, the degree of R&D investment.

19 1.2. Literature Review and Hypothesis Development 13 Innovation is a variable long argued to be an important driver of firm s FP 1. Innovation activities in general are found to have a positive and significant impact on business performance (Porter, 2010; Porter and Kramer, 2006; Lee et al., 2006; Rennings, Ziegler, Ankele, and Hoffmann, 2006). For instance, R&D is considered to be a form of investment in technical capital, resulting in knowledge enhancement, which leads to product and process innovation. This innovative activity allows firms to enhance their productivity (McWilliams and Siegel, 2000:604), increase market share and enter new markets. Similar discussions take place on studies about the relationship between environmental innovation and financial performance, the conclusions about the total effect are not always clear. Government regulation is one of the most debated topics in this relationship. Ideas like the Porter hypothesis which suggests that strict environmental policy spurs innovation, increases in resource efficiency and lead to higher economic efficiency (Ambec, Cohen, Elgie, and Lanoie, 2011), are still - and after 20 years - being debated with still blurry conclusions. Porter (2010) explains that companies with strategies to reduce the cost of the regulations and the risks - imposed by environmental, economic and social issues- can increase their competitive advantage, market position and foster innovation. Under this logic environmental innovation is a tool driving innovation as well as competitiveness. On the other hand, there are studies concluding that the impact of environmental innovation on firm performance is ambiguous. Rennings and Rammer (2010) explore the impact of innovations stimulated by environmental regulation on firm performance, compared with the effect of innovations triggered by market demand or by new tech- 1 Hull and Rothenberg (2008) mention some studies, inluding: Abernathy and Clark, 1985; Abernathy and Utterback, 1978; Burns and Stalker, 1961; Christensen and Bower, 1996; Hamel and Prahalad, 1994; Schumpeter, McWilliams and Siegel (2000) also point out several studies linking investment in R&D to long term economic performance, with robust studies: Lichtenber and Siegel (1991), Clark and Griliches(1984), Ben-Zion(1984), Guerard, Bean and Andrews(1988)) and Hall (1999).

20 Chapter 1. Theoretical Background 14 nological developments. The authors explain that there are two opposing effects that make the total effect ambiguous, On the one hand, regulatory-driven environmental innovation may impose additional costs to firms and lower their profits. On the other hand, eco-innovators could profit from lower uncertainty in innovation due to regulatory standards and demand-generating effects (Rennings and Rammer, 2010:3). In this study we predict that: Hypothesis 5: Financial performance has a positive effect on innovation Hypothesis 6: Innovation has a positive effect on financial performance

21 Chapter 2 Research Analysis 2.1 Conceptual Framework Based on the literature review and description of the concepts outlined above, we construct a system of hypotheses to analyze the relationship between CSR, innovation (R&D) and FP, where each of these elements influences each other (See Figure 2.1). The hypotheses of our study take into consideration the bidirectional nature of CSR-FP relationship and our central research question, about the role of innovation on this link. In sum, we propose the following hypotheses: Hypothesis 1: Financial Performance has a positive effect on CSR Hypothesis 2: CSR increases financial performance of firms Hypothesis 3: Advancements on innovations increase CSR Hypothesis 4: CSR has a positive effect on innovation Hypothesis 5: Financial performance has a positive effect on innovation Hypothesis 6: Innovation has a positive effect on financial performance Furthermore, these hypotheses capture the idea that CSR has an effect on FP, directly and through general innovations. For these reasons we follow the steps to check mediation and moderation effects of R&D over the CSR-FP relationship 1. Mediation (Baron, 1986) is a hypothesized causal chain between three variables, in 1 Researchers who have suggested that R&D should be included as a moderator in theoretical models that have received mixed or ambiguous empirical support include Han et al.(1998), and Hull and Rothenberg (2008) 15

22 Chapter 2. Research Analysis 16 Figure 2.1: Conceptual Framework which the relation between two variables decomposes through a third call the mediator. The first variable affects the mediator and the mediator affects the second. In this case R&D, hypothesized to be the mediator, mediates the relationship between (CSR) and (FP). In other words, we propose that CSR is correlated with FP not only because it has a direct effect upon FP, but because it changes in an R&D, and then this mediating variable causes changes in FP. In statistics, moderation (Baron, 1986) occurs when the relationship between two variables depends on a third variable called the moderator which affects the direction and/or strength of the relation between dependent and independent variables. The moderator affects the zero-order correlation between the two variables. According to Hull and Rothenberg (2008), innovation should be included as a moderator between FP and CSR. In order to structure better our analysis, we separate our hypotheses in two sets: the first group H1, H3 and H5 testing the effect of FP on CSR and the role of R&D in this link (see inner box of diagram 2.1); and the second group of hypothesis H2, H4 and H6 testing the effect of CSR on FP and again checking the role of R&D on it (see outer box of diagram 2.1). Innovation as a core value, creating capabilities driving the CSR-FP relationship.

23 2.2. Methods 17 This proposition that innovation is a mediatior role 2.2 Methods The data We use the linkage of two databases to be able to associate CSR, innovation and financial performance. The CSR data is from Sustainalytics and the financial and innovation data is taken from Capital IQ. Combining the two databases we obtained a sample size of 241 companies with innovation, and financial performance data for 2007 and 2009, and CSR data for 2008 and The data sample is composed by companies from 25 different countries of the world. Sustainalytics develops detailed Environmental, Social and Governance (ESG) information for over of the largest companies worldwide. Companies are analysed by local research partners using one consistent, sound methodology that consists of over 110 (including sector specific) indicators per company. For the analysis of a company Sustainalytics applies strict criteria and has adopted a stringent quality management system to ensure consistency and quality. A large variety of sources are consulted, such as public reporting of a company in addition to information from non-governmental organisations (NGOs), international institutions, press, governments etcetera. In order to further improve quality Sustainalytics enters into an active dialogue with the company as well as experts. Company profiles are continuously updated to include the latest information, such as occurring controversies. The research methodology is based on an analysis of the companies performance on several themes, such as business ethics, community, corporate governance, customers, employees, environment and suppliers (supply chain). For each of the themes the companies performance is analyzed on the topics transparency, policies, management systems and performance. Based on these

24 Chapter 2. Research Analysis 18 parameters Sustainalytics develops a company rating Specification and Data Issues Treatment In this study we use Pearson correlation coefficients and multiple regression for our analysis. Pearson correlation coefficients technique was used to examine the strength and the direction of the relationship between the dependent and independent variables. Regression analysis was used to test our hypotheses. This study used SPSS software package for both the bi-variate and the regression analysis. Endogeneity. Endogeneity arises when one of the independent variables is determined simultaneously along with the dependent one. From the literature review we observe this is the case for CSR and FP, which are jointly determined. If this source of endogeneity is not considered the estimators are likely to be biased. We consider the bi-directional linkage between CSR and FP, and use lagged independent variables to avoid endogeneity in our models. Outliers and Influential Observations. We pay special attention to unusual observations that could greatly affect our regression estimates. For the results reported we have removed just the ones that were evident mistakes, such as rates of NetIncGrowth> 1,000%, GrowthMean >4,000. In a second stage we analyzed the dependent and independent variables searching for outliers; we found that in particular the financial return and growth variables, risk and innovation had few observations that could be considered outliers, we performed the regressions dropping those observations from the analysis but the estimators did not change significantly. Multicollinearity. We tested for multi-collinearity by examining the Variance Inflation Factor (VIF). For each variable we checked that the variance inflation factor was smaller than ten. Independent variables that failed to meet this condition were

25 2.2. Methods 19 excluded from the regression model. High collinearity was observed when all three growth variables, and sometimes with even just two, were included in our regression models. In those cases we removed net income growth and/or revenue growth and used only growth in gross profit as it was the variable from this group presenting higher significance level and lower collinearity. In most of the cases we include only one growth variable since including any of the other two will increase the collinearity. Unfortunately, we had to remove almost all the interaction effects due to high collinearity with other independent variables Definition of Variables We use several variables from our data base, separating them into independent/dependent and control variables. Table 2.1 presents all the dependent, independent and control variables and table 2.2 provides the descriptive statistics (mean and standard deviation) of all variables used in the study; including the different measurements for CSR and FP we use in our analysis. It shows the variables in year t (2009) and in year t-1 (2007 or 2008 according to data availability). Table 2.1: Variables of the study CSR Company Score Score Governance Score Social Score Environmental Financial Performance Innovation Control Variables Returns Mean Growth Mean R&D (R&D expenditure / revenues) Return on Assets % Return on Capital % Return on Equity % Gross Profit, 1 Yr Growth % Total Revenues, 1 Year Growth % Gross Profit, 1 Year Growth % Risk (Long Term debt / assets) Size (by revenues: small, medium, large, giant) Sector (6 economic sectors) Regions (6 geographical regions)

26 Chapter 2. Research Analysis 20 Dependent and Independent variables We test bidirectional relationships, hence a dependent variable in one hypothesis becomes the independent one in another. These variables are grouped in three groups: CSR, innovation, and financial performance. Corporate Social Performance (CSR). In this study, we use a data set with governance, social and environmental indicators. Those indicators measure company performance of each of these three CSR domains. For each company we use the composite total CSR based on governance, social and environmental scores constructed by Sustainalytics as total CSR score (CompScore). Innovation: Research and Development (R&D). We use the ratio of R&D expenditures to revenues (rdexp/rev) to measure innovation. Similar measurements such as R&D expenditures to sales have been used in CSR and innovation research, some of these studies include McWilliams and Siegel (2000). Hull and Rothenberg (2008) measured R&D using a 3-year average of R&D expenditures. In the original database there are a large number of R&D observations with zero values, we were not able to determine if those were in fact zeros or missing values (there was only one missing value reported). We select the cases for which this variable was different than zero in at least one year (2008 or 2009), obtaining 249 cases. Financial Performance (FP). Financial performance was measured using two types of accounting variables: growth and returns. These accounting-based measures reflect an organization s internal efficiency. The growth variables include one year growth rate of: gross profit (ProfitGrowth), total revenues (TotRevGrowth) and net income (NetIncGrowth). We also utilize the average of returns (Returns Mean), that is the average of return on capital (ROC ), return on equity (ROE) and return on assets (ROA), these measurements are very often used in CSR literature (see Figure A.1.).

27 2.2. Methods 21 In our regressions we use first the average level and then the individual values of those variables. Among financial accounting variables used to measure financial performance in CSR literature, ROA is a common one; it provides direct information about a chosen allocation of resources (Hull and Rothenberg, 2008; Padgett and Galan, 2009). ROA is also used by the investment community to assess corporate financial performance (Waddock and Graves, 1997). Table 2.2: Descriptive Statistics RISK R&D FP CSR Variable N Mean Std. Deviation CompScore GOV SOC ENV CompScore GOV SOC ENV Valid N (listwise) 241 ReturnsMean ROA ROC ROE ReturnsMean ROA ROC ROE GrowthMean TotRevGrowth ProfitGrowth NetIncGrowth GrowthMean TotRevGrowth ProfitGrowth NetIncGrowth Valid N (listwise) 149 R&D R&D Valid N (listwise) 245 Risk Risk Valid N (listwise) 245

28 Chapter 2. Research Analysis 22 Control variables Several studies point out the importance to identify confounding factors that influence the relationship of CSR and economic, social and environmental dimensions and to control for them (van Beurden and Gössling, 2008). Among this kind of variables Ziegler and Nogareda (2009) and Pavelin and Porter (2008)) identify: R&D, size, environmental dynamics, industry, investment intensity, risk, exporting, market, age, and industry growth. The most important confounding factor is size, followed by industry type (van Beurden and Gössling, 2008). For our study dummy variables were recorded for the size of the firms, economic sectors and region of the world. We also include risk as a control variable. Next, the control variables used in this study are described. Risk. We include risk as a control variable in our analysis. In CSR literature firm risk has typically been considered as an adjustment factor for return measures of financial performance (Orlitzky and Benjamin, 2001) and management s risk tolerance (Waddock and Graves, 1997). In our study risk is measured as the percentage of a firm s long-term debt relative to assets (LTDebt/assets). This measurement is used by Graves and Waddock (1994 and 1997), Hull and Rothenberg (2008) and Padgett and Galan (2009). It is one of the most commonly used in CSR literature among the accounting risk measurements 2. Based on the review of literature on risk and CSR we can assume that firms facing high debt/asset ratios will have fewer resources to spare for innovation and for pursuing CSR. Regions. There are firms from 25 different countries in our database. These countries were assigned to one of the following regions, namely: AngloSax excludenorthameri, 2 Other examples of measures of accounting risk, typically used in CSR studies, are the ratio debt to equity, the ratio of the standard deviation to the mean of ROC, and the standard deviation of a firms longterm ROA or ROE. See Orlitzky and Benjamin (2001) for a list of risk measurements used in the studies included in their metaanalysis.

29 2.2. Methods 23 North America, Western Europe, Scandinavian, Mediterranean and Asia. To enter the different regions into the regression model, the six regions were recoded into dummy variables. Around half (50.2%) of the companies in our sample are from North America (USA and Canada), the second region by number of companies is Western Europe (see Table 2.3). Table 2.3: Regions and economic sectors in the sample Region Sector Variable Frequency Percent AngloSax excludnorthamer Asia Western Europe Mediterranean Scandinavian NorthAmerica Total Utilities&energy HealthCare Industrials InfoTech&telecomm Materials ConsumerDiscret&Stap Total Economic Sectors. It has been showed that there are clear differences on CSR performance among industries (Waddock and Graves, 1997). For instance, the content of innovation tends to be greater for those firms in industrial sectors most closely associated with relevant, high profile social and environmental issues such as wood and paper, oil, consumer chemicals and recycling sectors (Pavelin and Porter, 2008). Six economic sectors are identified and included in this study (see Table 2.3). This sector classification is based on the Global Industry Classification Standard (GICS) which is a commonly used industry classification among investment researchers and by investment management professionals. MSCI and Standard & Poor s, the developers of GICS, mention (in their web site) some advantages of using this classification which are also relevant for our study: this classification reflects company s financial performance, which is one of the factors we want to measure, provides global coverage and allows for

30 Chapter 2. Research Analysis 24 cross country comparisons. Furthermore, GICS is a market-oriented industry classification, instead of production-oriented which reflects the emergence of the service era. To enter the sector categories into the regression model, the six categories were recoded into dummy variables. Size. In the link between CSR and FP, there has been some theoretical and empirical research arguing that the positive relationship between CSR and FP is caused by large firm size. Orlitzky (2001) does not confirm size as a confounding factor while Wu (2006) and Waddock and Graves (1997) find a significant effect of size on CSR and FP link. We utilize the revenue of the firm to calculate its size, a similar and commonly used measurement is sales (Padgett and Galan, 2009). For this we calculated the average revenue for the years 2007 and 2009, and then computed the log of the average. Then we clustered this variable into four groups (small, medium, large and giant) using the k-means algorithm. The k-means clustering method attempts to find the centers of actual clusters in the data and assign the observation to the cluster with the nearest mean. Table 2.4 summarizes the center of each cluster (the mean of Log revenue for each group) and the number of companies in each of the four clusters. Most of the companies in our sample ( 42.2%) are medium size. Table 2.4: Firm Size Small Medium Large XLarge Total Frequency Percent Cluster Centers (Log(rev))

31 2.3. Analysis Analysis Bi-variate Analysis: Pearson correlation coefficients Pearson Correlation Coefficients were used to check the strength of the association between the independent and dependent variables. The conclusion about the significance of the variable is based on a significance level smaller than 0.1. We point out only the observed significant correlations 3. FP-CSR The results of Pearson Correlation Coefficients suggest that there is a linear correlation between the financial growth variables for year 2009 and some of the CSR variables for years 2008; the correlations are as follows. Negative between: TotRevGrowth09 and CompScore for both years 2008 and 2009; and TotRevGrowth09 and SOC for 2008 and Also for ProfitGrowth09 and both SOC08 and ENV09. Positive between: NetIncGrowth09 and SOC08; and ProfitGrowth09 and SOC09 In sum, in the relationship between the FP and CSR variables, we find that not all our variables present a CSR-FP relation. Furthermore, the relationship is negative for some variables and positive for others. The CSR variable that seems to be most significant is SOC. We did not observed a relation between 2008 growth variables and CSR variables, or between financial return variables (2008 or 2009) and CSR measurements. The strength of association between the variables is rather small ( with Pearson Correlation coefficients <0.028 in all cases). 3 The Matrix of correlations is available upon request but is not included here for sake of space

32 Chapter 2. Research Analysis 26 R&D-CSR The correlation results indicate that there is a low but negative relationship between R&D07 and SOC09. There is not enough evidence to conclude a linear relationship between R&D and any other CSR variable. It is worth to mention that, again the only CSR variable that appear to be significant is SOC. R&D-FP We find linear relationships between R&D and FP variables; the correlations are as follows. Positive between R&D09 and all 2007 growth variables (GrowthMean07, NetInc- Growth07, ProfitGrowth07 and TotRevGrowth07). R&D07 is positively related with two growth variables for both years 2007 and 2009 (TotRevGrowth07 and 09; and ProfitGrowth07 and 09). Negative between between R&D07 and all returns variables from the same year (ReturnsMean07, ROA07, ROC07, ROE07) Multi-variate Analysis: linear regression Multi-variate linear regression technique is used to produce a more efficient and precise explanation of how the independent variables are related to each dependent one. From the literature review we observe that CSR and FP are in principle jointly determined, to avoid endogeneity in our models we use lagged independent variables. To generate the regression models, first we include only the control variables and the independent variables, in a second step we included R&D if applicable, and lastly we included the interaction variables. The model we report here is the last model of the

33 2.3. Analysis 27 regression because of space restrictions, but if a dependent variable presented a change compared with previous models, the change is reported. The models are constructed in two levels, we include first the variables at the aggregate level and then a subgroup of variables (e.g. first we include ReturnsMean and in a second model we include ROA, ROE and ROC) to check if including the variables individually makes any difference for the results. Regression Results First Group of Hypotheses With the first group of hypotheses (H1, H3 and H5) we test the effect of FP on CSR and the role of R&D on this link (see inner box of diagram 2.1), the results from the regression models are as follows. Hypothesis 1: Financial Performance has a positive effect on CSR. Table 2.5 presents the results of the data analysis using the four measurements of CSR (TotalScore, GOV, SOC and ENV) as our dependent variable and FP and R&D as explanatory variables. We use 1-period lag between CSR and all independent variables. As it can be observed in Table 2.5, FP variables (ReturnsMean07 and Growth- Mean07) do not appear to have a significant impact on any CSR variable (its level of significance was larger than the set threshold 0.1.). These results do not support our first hypothesis. The interaction variable is not significant in any of our models, so R&D has no moderating effect. It is of interest that even though the financial performance variables are not significative, ReturnsMean07 has a negative but insignificant impact on TatalScore09, SOC09 and Env09 while GrowthMean07 has a positive but insignificant impact in almost all CSR variables. Hypothesis 3: Advancements on innovations increase CSR Our regression results, (see Table 2.5) fail to confirm Hypothesis 3. R&D does

34 Chapter 2. Research Analysis 28 Table 2.5: Regression analysis, Hypothesis 1 and 3 CSR09 Variable Total Score GOV09 SOC09 ENV09 (Constant) (.000) (.000) (.000) (.000) SIZE Small (.000) (.005) (.000) (.000) Large (.000) (.344) (.000) (.000) XLarge (.000) (.043) (.001) (.005) RISK Risk (.771) (.556) (.793) (.405) REGION SECTOR FP AnglSax nona (.460) (.212) (.820) (.339) Asia (.001) (.000) (.001) (.521) WEurope (.012) (.988) (.002) (.039) Mediterr (.000).570 (.774) (.000) (.000) Scandin (.094) (.234) (.462) (.064) Utilities&Energy (.039) (.259) (.144) (.068) HealthCare (.009) (.045) (.002) (.597) Industrials (.007) (.018) (.006) (.236) Materials (.675) (.805) (.390) (.190) Discret&Stap (.008) (.208) (.102) (.011) ReturnsMean (.549).017 (.732) (.682) (.275) GrowthMean (.995).002 (.220).000 (.999) (.509) R&D R&D (.805) (.638) (.554) (.311) R&D07*ReturnsMean (.930) (.730).002 (.998).061 (.914) R R Note - Unstandardized coefficients are shown, with p-values listed in parentheses. Statistical significance: 1% level ( ); 5% level ( ); and 10% level ( ). not appear to have a significant impact on any CSR variables (CompScore09, Gov09, SOC09 or ENV09). The level of significance for the coefficient of R&D was larger than the set threshold 0.1. in all cases. We further checked models including the three growth variables independently as well as three returns variables, but similar results were found and there was not enough evidence to confirm our first hypothesis (See Table A.1 in Appendix A for an example). The variables that best predict the changes in the CSR are control variables. For instance small firms are estimated to have a lower CSR scores than Medium size firms, while large and XLarge firms are estimated to present a higher CSR scores across the different measurements of CSR, compared with medium size firms. Also, all regions but Asia and AngloSax.noNA are expected to have a higher CompScore compared with North America region. Regarding the economic sectors, all industries but Materials

35 2.3. Analysis 29 are estimated to have a lower CompScore compared with InfoTech&TeleComm sector. Similar results were obtained when checking the effect of FP in GOV, SOC and ENV scores, see Table 2.5. Hypothesis 5: Financial performance has a positive effect on innovation Table 2.6 shows the regression results of FP variables on R&D, these results contradict Hypothesis 5. FP has a negative effect on innovation but the significance of this effect depends on the financial variables entered to the model. ReturnsMean07 (Model 1 and 4 Table 2.6) is significant with a negative effect on R&D, while GrowthMean07 has a positive but insignificant effect on innovation. We explore further this issue by including different FP measurements, as independent variables. In Model 2 and 3, Table 2.6, we observe that ROA and ROC affect R&D in a negative way at a p < 0.10 and p < 0.01 level respectively. None of the growth variables is significative. In Table 2.6 we can also observe that there are differences on R&D investment across firm s industrial sectors. In the other hand, there are no much differences among regions and size. Regression Results Second Group of Hypotheses We test the effect of CSR on FP and check the role of R&D on this link with our second group of hypothesis H2, H4 and H6 (see outer box of diagram 2.1). Hypothesis 2: CSR increases financial performance of firms, and Hypothesis 6: Innovation has a positive effect on FP of firms Table 2.7 and 2.8 present the results of testing hypotheses two and six. In a first level of analysis, we observe that changes on CompScore neither affect GrowthMean09 nor ReturnsMean09, checking at a disaggregated level of variables, we find that SOC08 has a positive impact on NetIncGrowth09 and a negative impact on ProfitGrowth09;

36 Chapter 2. Research Analysis 30 R R Note - Unstandardized coefficients are shown, with p-values listed in parentheses. Statistical significance: 1% level ( ); 5% level ( ); and 10% level ( ). CSR CompScore.000 (.621) GOV (.420) SOC (.978) ENV (.146) ROA (.052) ROE (.750) ROC (.009) FP NetIncGrowth (.396) TotRevGrowth (.729) ReturnsMean (.006) (.304) (.015) (.009) GrowthMean (.542).000 (.528).000 (.387).000 (.500) SECTOR Utilities&Energy (.000) (.000) (.000) (.000) (.000) (.000) HealthCare (.328) (.157) (.093) (.593) (.121) (.211) Industrials (.000) (.000) (.000) (.000) (.000) (.000) Materials (.000) (.000) (.000) (.000) (.000) (.000) Discret&Stap (.000) (.000) (.000) (.000) (.000) (.000) REGION AnglSax nona.013 (.536).008 (.674).006 (.776) (.587).015 (.461).012 (.569) Asia (.075) (.081) (.060) (.045) (.070) (.050) WEurope (.436) (.681) (.690) (.549) (.646) (.457) Mediterr (.923).001 (.955) (.913) (.609).001 (.937) (.699) Scandin (.591) (.640) (.871) (.624) (.643) (.545) RISK Risk (.091) (.198) (.017) (.017) (.181) (.084) SIZE Small.014 (.295).004 (.739).002 (.893).009 (.493).007 (.571).015 (.247) Large (.406) (.373) (.471) (.746) (.472) (.268) XLarge.009 (.748).012 (.673).008 (.765).018 (.491).012 (.651).006 (.829) (Constant).139 (.000).158 (.000).172 (.000).143 (.000).155 (.000).149 (.000) R&D09 Variable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Table 2.6: Regression analysis, Hypothesis 4 and 5

37 2.3. Analysis 31 and GOV08 has a positive impact on ProfitGrowth09 (see Table A.2). Table 2.7: Regression analysis, Hypotheses 2 and 6. Disaggregated growth variables FP09 Variable GrowthMean09 TotRevGrowth09 NetIncGrowth09 ProfitGrowth09 (Constant) (.894) (.624) (.520) (.373) Small (.874) (.597).978 (.974) (.342) Large (.781).237 (.939) (.805) (.745) XLarge (.034) (.378) (.197) (.113) RISK Risk (.588).627 (.934) (.531) (.712) SIZE REGION SECTOR AnglSax nona (.456) (.922) (.406) (.807) Asia (.362) (.711) (.019) (.575) WEurope (.494) (.215) (.662) (.164) Mediterr (.061) (.834) (.199) (.279) Scandin (.789) (.745) (.860) (.129) Utilities&Energy (.916) (.584) (.859) (.540) HealthCare (.781) (.000) (.006) (.000) Industrials (.177) (.827) (.221) (.673) Materials (.708) (.307) (.770) (.483) Discret&Stap (.576) (.013) (.078) (.013) CSR CompScore (.449) (.472) (.085) (.785) R&D R&D (.784) (.949) (.098) (.866) R R Note - Unstandardized coefficients are shown, with p-values listed in parentheses. Statistical significance: 1% level ( ); 5% level ( ); and 10% level ( ). Similar mixed results are observed for R&D, its coefficients suggests that an increase on R&D will reduce returnsmean09 (see Table 2.8) but will increase NetIncGrowth09 (Table 2.7). R&D affects returns variables (ReturnsMean) in a negative way at a p < 0.05 level. Exploring further at a disaggregated level of CSR and returns variables we find that R&D have a negative effect on return variables, namely ROA and ROC (see Table 2.8). Finding NetIncGrowth09 as the only growth variable positively affected by R&D and CSR (CompScore) was puzzling, so when we run the set of regressions drooping outliers we payed particular attention to these relationships. We found that when removing outliers the effect of R&D and CompScore on income disappears. Hence, it seems that the effect of R&D and CompScore on NetIncGrowth09 is not robust. Results regarding control variables show that companies in the HealthCare sector

38 Chapter 2. Research Analysis 32 Table 2.8: Regression analysis, Hypotheses 2 and 6. Disaggregated return variables FP09 Variable ReturnsMean09 ROA09 ROE09 ROC09 (Constant) (.505) (.016) (.910) (.007) Small (.131) (.109) (.154) (.110) Large (.381).111 (.899) (.469) (.249) XLarge (.105) (.060) (.213) (.072) RISK Risk (.152) (.700) (.030) (.336) SIZE REGION SECTOR AnglSax nona (.725) (.491) (.619) (.471) Asia (.635).091 (.965) (.575) (.769) WEurope (.167) (.529) (.198) (.293) Mediterr (.025) (.072) (.055) (.044) Scandin (.845) (.223) (.646).871 (.675) Utilities&Energy (.933) (.732) (.902) (.514) HealthCare (.002) (.000) (.011) (.003) Industrials (.494) (.054) (.094) (.076) Materials (.704) (.068) (.621) (.033) Discret&Stap (.507) (.206) (.817) (.104) CSR CompScore (.289).002 (.974).379 (.207).004 (.960) R&D R&D (.044) (.028) (.153) (.003) R R Note - Unstandardized coefficients are shown, with p-values listed in parentheses. Statistical significance: 1% level ( ); 5% level ( ); and 10% level ( ). are estimated to have a better financial performance compared with firms in the InfoTech&Telecomm sector (Tables 2.7 and 2.8 ). Hypothesis 4: CSR has a positive effect on innovations Our results do not support our hypothesis that CSR has a positive effect on innovations. Table 2.6 shows that the coefficients of CompScore, GOV, SOC and ENV are not significant Checking Models Robustness Four robustness checks were conducted: (1)Removal of outliers; (2) Including data for one more year, namely 2010; (3) Running the models for a subgroup of companies, namely manufacturing sector, based on studies that have found that the effect of R&D on CSR is more intense in manufacturing industries than in non-manufacturing ones (Padgett and Galan, 2009); (4) redefining the sectors into three main sectors: service

39 2.3. Analysis 33 sector, manufacturing related to consumers and industries We did not find significant changes on the results on the robustness test. The only changes worth mentioning were found for test number (4), were GrowthMean07 has a significant (10% level) negative effect on SOC09 and R&D07 has a significant (5% level) positive effect on ENV09.

40 Chapter 3 Results and Conclusions 3.1 Summary of Results The results of this study are summarized in Figure 3.1. Next we will point out and discuss our main findings. Figure 3.1: Results In sum, the results of this study do not confirm an effect of FP on CSR directly (Hypothesis 1) nor through innovation (Hypotheses 5 and 3); we find ambiguous effects of FP on innovation, and no impact of innovation on CSR. Under these circumstances we are not able to identify the role of innovation in the FP CSR link (i.e. moderation or mediation effect). Likewise, our results suggest the effect of CSR on FP (Hypothesis 2) is ambiguous and the role of innovation in this relationship is hard to identify given the lack of effect of CSR on general innovation (Hypothesis 4), and the ambiguous impact of innovation on FP (Hypothesis 6). 34

41 3.1. Summary of Results 35 These findings are surprising, considering most empirical studies (as suggested by the literature review) predict a positive effect FP CSR or from CSR FP; or even more a virtuous cycle between CSP and financial performance (Waddock and Graves, 1997; Scholtens, 2008). The current financial crisis may be a source of explanation for our uncommon results, in particular because of its effects on FP and innovation. The effect of the financial crisis in the levels of R&D is confirmed by the 2011 Innovation Union Competitiveness Report by the EU. According to this report in the EU s business sector R&D expenditure decreased by -3.1% in nominal terms in In a similar trend, the report states that despite large decreases in sales and profits, nominal R&D investment by the world s top 1400 R&D investing companies, decreased by only 1.9% in The decrease in R&D investment was sharper in US companies than in EU companies. In general, it may be that firms with financial resources have more flexibility and capacity to invest in CSR, but during periods of crises this freedom can be truncated by the urgency of solving short term concerns (such as difficulties facing shorter term payments and credit constraints) in contrast to investments in long term strategic programs such as CSR. On the other hand, the mixed and ambiguous effects of CSR on FP could reflect a broader and unstable economic context; during an economic crisis there may be external forces affecting firm s capacity to maintain programs that contribute to the society such as philanthropy or donations and employee turnover rate. The effects of the crisis can be reflected even more in the FP-Innovation relationship. In this study we found two kind of impacts on innovation: a negative impact from financial returns and a positive impact from firm s economic growth.similar mixed results were found on the impact of R&D on FP; we found that financial performance has an effect on R&D, but the direction of this relationship (negative or positive) depends on the variable used to measure FP. There are internal and external, as well as

42 Chapter 3. Results and Conclusions 36 long and short term circumstances that could contribute to this situation. A possible explanation for this result is that in times of economic crisis, companies find it difficult to decide between cutting R&D investment to focus resources on solving short term and urgent problems, or to keep expanding R&D as a way to gain efficiency, productivity and competitiveness in the long run. To test for a possible effect of the crisis on the relationship between FP, CSR and R&D, the multivariate regression presented in Section was repeated using data only for the so called year t 1 (2007 or 2008). The obtained results were very similar to those found in the lagged models. Therefore, it is not clear what is the effect of the crisis on the Hypotheses studied. Our results do not support the hypothesis that R&D has a positive effect on CSR. This effect is interesting since the literature reviewed points out that companies that give great deal to innovation, pay particular attention to comply with environmental and social standards, as in the case for manufacturing industries (Padgett and Galan, 2009). But on the other hand those sectors can be forced to change investment practices on CSR and innovation. For instance, in the current crisis the decrease of R&D investment is more accentuated in automobiles and IT hardware sectors compared with other sector like the pharmaceutical (European Commision - Research and Innovation, 2011). The analysis of the first group of hypotheses also give us information about the CSR performance across company differences such as size, region and sector. We found that there are significant differences in those areas. For instance, it calls our attention that Asian companies consistently have lower CSR performance,compared with North American ones. The companies from other regions in general perform better (in CSR) than North American ones but there is no a single region that perform better across all CSR aspects. As our results suggest, there are differences on R&D investment across economic sec-

43 3.1. Summary of Results 37 tors, in particular the InfoTech&Telecomm sector invest more in innovation compared with the other sectors. This result is interesting since it has been proven by empirical studies that sectors such as pharmaceutical and manufacturing, usually score high on R&D investment. On the other hand during the current economic crisis the manufacturing sector is among the most affected, and has been forced to reduce investment in R&D. Likewise, we found that the CSR performance depends on company size, as suggested by some researchers analyzed in the literature review section. Small companies seem to have lower scores than medium size ones while large and giant companies seem to have better performance across all CSR pillars. These results support the findings by Wu (2006) and Waddock and Graves (1997) who find significant effect of size in CSR and FP link. Pavelin and Porter (2008) argue that large firms are subject to greater pressure to demonstrate their social performance and have more money to invest in CSR, even when the returns to their activity happen in the long run. In contrast, smaller firms may not exhibit as many socially responsible behavior as do larger firms because as they mature and grow, they attract more attention and then need to be more open with stakeholders (Waddock and Graves, 1997). As can be seen in our models there are considerable differences in the CSR ratings, but also in the level of R&D among industries. These results indicate the importance of controlling for sector in the analysis of the relationship between CSR, FP and innovation. The InfoTech&telecomm sector seems to perform better, consistently across all CRS indicators, compared with other industrial sectors, supporting the argument by Waddock and Graves (1997) and Pavelin and Porter (2008) on the existence of clear differences on CSR performance among industries. Risk does not seem to have any effect on CSR indicators. This finding does not refute the argument that firms facing high risk will have fewer resources to allocate on

44 Chapter 3. Results and Conclusions 38 CSR or CSR related innovation. It might be that CSR also helps to reduce risk, as explained by Orlitzky and Benjamin (2001), and thus companies facing high levels of risk may be motivated to invest in CSR. These two contravening effects may explain why risk seems to have a neutral effect on CSR. In our regressions we did not find a significant effect of interaction terms. This leads us to conclude that R&D does not moderate the relationship between CSR and FP. A positive value for the effect of the interaction term would imply that the higher the R&D the greater the effect of FP on CSR, or the greater the effect of CSR on FP. In our regressions it was not possible to include several interaction terms because of the high collinearity among them and with the other variables in the model. 3.2 Conclusion This study addresses the role of innovation on the link between CSR and FP. The existing CSR literature suggests innovation plays a key role in the relationship between CSP and FP. We did not find empirical evidence supporting R&D as a potential moderator or possibly confounding variable in the CSR-FP relationship. Our study reflects the importance to consider more complex possibilities when examining the CSR-FP relationship, as suggested by McWilliams and Siegel (2000). We found evidence showing than even if CSR performance is not significative at the aggregated level, individual components of CSR (governance, environmental, social) can have a significant effect on particular measurements of financial performance. By analyzing those CSR dimensions and different measurements of financial performance, our study points out that one has to be careful when assuming a general positive relation between CSR and financial performance. We found evidence to support the argument of CSR performance, FP and innovation

45 3.2. Conclusion 39 being influenced by firm s characteristics (McWilliams and Siegel, 2000) and context: size, geographical region and economic sector. Even though we were not able to confirm a moderation or mediation role of innovation in the CSR-FP link, this study provides important insights in the CSR-FP analysis. It also generates interesting questions for further research. Is the pattern seen here a consequence of the financial crisis? How will the dependence between firms characteristics (size, sector, etc), and the relation between the studied variables (CSR, FP, Innovation) evolve as a response to economic crisis? Studies in CSR field commonly use CSR indicators based on the CSP attributes ratings of the firm Kinder, Lydenberg, and Domini (KLD). Our empirical study presents results based on CSR data drawn from Sustainalytics, a recognized data quality source. This study accounts for the endogeneity (a common and ignored problem in CSR literature) due to simultaneous causality between CSR performance and financial performance of firms by using lagged independent variables for our regression models.

46 Appendix A Appendix A Figure A.1: Measurements of Financial Performance in CSR literature Source: Literature Review by van Beurden and Gössling (2008) 40