The influence of CSR on CFP in different industries: a competitive position perspective

(1)

The influence of CSR on CFP in different industries: a

competitive position perspective

Brenden B.J. Vorenkamp

S2570602

MSc. Finance University of Groningen Faculty of Economics and Business

Submitted: 10 January 2019

(2)

2

ABSTRACT

(3)

3

1. INTRODUCTION

Over the last decades, a lot of research has been done in the field of corporate social responsibility (CSR) (Dam and Scholtens, 2015; Mackey, Mackey, and Barney, 2007; McWilliams and Siegel, 2001). CSR is generally defined in the literature as the extent to which a corporation does business in a social responsible way, by taking into account different stakeholder demands grounded on environmentally, socially and governmental issues (Moir, 2001). Researchers in the literature field of CSR reached a consensus that in the current era, CSR has become an inevitable aspect of doing business, due to voluntary actions and/or governmental pressures (Eichholtz, Kok, and Quigley, 2009; Liang and Renneboog, 2017; Van Beurden and Gössling, 2008). For instance, in terms of governmental pressures, the recent Paris Agreement to combat climate change, has consequences on the way corporations do business in the participating countries (The Paris Agreement, 2016). In these countries, companies have to obey certain requirements of the governments regarding the carbon emissions. This encourages companies to make use of sustainable alternatives to non-renewable resources and to innovate products and production processes. Apart from the governmental pressures to do business socially responsible, in the current era companies have to deal with an increasing importance to account for other external stakeholders in their decision making process. That is because external stakeholders more often hold companies accountable for social issues resulting in possible financial risks for the companies that do not comply (McWilliams and Siegel, 2001; Van Beurden and Gössling, 2008). Whether complying to such pressures and voluntary investments in CSR will be beneficial for firms (in the long run), is still a topic of debate in the CSR literature field. Many researchers studied the implications of CSR on corporate financial performance (CFP), but the exact effect between the two is inconclusive (Saeidi, Sofian, Saeidi, Saeidi, and Saaeidi, 2014). Given the increasing pressures from external stakeholders to do business socially responsible, the topic is still worth investigating and has great practical relevance.

(5)

5

effect on a firm’s competitive position and eventually higher sales can be expected (in the long run). However, whether this relationship withstands in practice might depend on the strategies of a firm’s competitors with respect to CSR. When competitors follow a similar strategy, CSR might have a less strong impact on CFP as in cases when a firm can create a unique sustainable competitive position. Therefore, the influence of competition on the CSR-CFP nexus might explain the inconclusive results. By introducing the measure of competition in the framework, this study will also try to further extend the existing relationship. Furthermore, this study will not solely focus on firms and their competitors in the same industry. Different industries will be examined and compared to get more insight into the effect of the salient stakeholder demands and sustainable competitive position on the CSR-CFP nexus.

Apart from research frameworks in the CSR literature field that should be reworked, a possible reason why previous researchers find no or even a negative correlation can be attributed to the research methods in place. As Dam and Scholtens (2015) notice, some studies use event studies to prove the effects of CSR on stock market returns. They often find no or negative significant results which makes a direct effect between CSR and CFP questionable. The problem with these event studies in this context is that it focuses on the short term and it is hard to determine when a particular CSR event occurs. Also Lu et al. (2014), who did a critical review of empirical research of the CSR-CFP nexus, argue that implementing CSR in a strategy takes time to result in CFP. They state that future researchers should take into account this time effect, which this study will do.

(6)

6

RQ: What is the impact of a firm’s sustainable competitive position on the link between a firm’s CSR performance and CFP?

In order to give an answer to this research question, three hypotheses were developed. The first hypothesis examines the relationship between CSR and CFP. The second hypothesis proposes that sustainable competitive position has a moderating effect on the link between CSR and CFP, implying that their relationship is curvilinear. The results point out there is some evidence of a negative relationship between CSR and CFP, which contradicts the proposed hypotheses. Also no evidence is found for a curvilinear relationship in the total sample. However, in the energy industry, some evidence is found that proves competition positively moderates the CSR-CFP relationship. The third hypothesis examines several industries separately in order to assess the importance of salient stakeholder groups (the customer in particular) on the CSR-CFP nexus. The results show that the CSR-CFP relationship behaves differently in each industry, but no conclusive support is found for hypothesis 3.

The remainder of this study is structured as follows. In chapter 2, the concept of CSR and competitive position will be discussed in depth and relevant theories and literature will be reviewed for the development of the hypotheses. Chapter 3 will discuss the methodology used in this study, including the data collection method, measurements, and plan of analysis. In chapter 4 the test results will be presented. Chapter 5 will answer the research question by relating the findings to the existing literature. Also the theoretical and managerial implications, limitations, and suggestions for future research will be discussed.

2. LITERATURE REVIEW

(7)

7 2.1 The link between CSR and CFP

Many researchers have a diverse view on what CSR incorporates and hence an exact definition of CSR is still up to debate. For instance, Mackey, Mackey, and Barney (2007) define CSR as voluntary actions that are performed to improve social conditions that go beyond the transactional interests of a firm. Others state that such actions are not driven by regulations, but are voluntary in nature, all in an attempt to improve society (McWilliams and Siegel, 2000). In line with these definitions, Moir (2001) states that CSR deals with a wide range of issues such as: the environment, labour conditions, employee relations, customer/supplier relations, corporate ethics, and community relations. This last definition grasps the key point of CSR. Although many researchers define CSR differently, in general most definitions emphasize that acting socially responsible means taking into account different stakeholder groups in the decision making process of managers. The growing importance of CSR in practice (Van Beurden and Gössling, 2008) is in accordance with the changing view firms have on their primary objective. This objective to maximize shareholder value shifted towards a focus on stakeholder value, where making trade-offs between the different interests of all stakeholder groups became more important. This perspective, embodied in stakeholder theory, describes that apart from shareholders of a firm, customers, employees, suppliers, and governments can affect or are affected by the achievement of the firm’s objectives (Freeman, 1984; Sen, Bhattacharya, and Korschun, 2006). According to Jensen (2001), stakeholder theory does not contain information on how to make trade-offs between stakeholders. He suggests that the theory should include directions on how to make managers accountable for their actions, otherwise they will continue pursuing their own interests to maximize short-term value at the expense of the long-term value of the firm. Jensen (2001) further argues that a combination of pursuing value maximization and stakeholder theory results in so-called enlightened stakeholder theory. This implies that managers will strive to act in favour of the firm’s stakeholders as long as this reduces financial damage or increases financial performance. Based on this aspect of enlightened stakeholder theory, companies will only behave socially responsible when they expect the costs to be offset by the benefits. This statement explains the increasing interests of businesses in the current era to behave socially responsible, as Porter and Kramer (2006) notice that social responsible actions are used to be viewed by firms as costs and constrains rather than opportunities.

(8)

8

and Kramer (2006) argue that these costs are accompanied with the duty of doing the right thing and being a good citizen. On the other hand, strategic CSR is seen as an opportunity and stems from both the risks (Godfrey, 2004) and opportunities (McWilliams and Siegel, 2001) associated with CSR. In terms of risks, pressures from various stakeholders to do business socially responsible can be very costly when it is expressed in financial performance. Complying to these demands can result in less financial damage, since potential conflicts are prevented (Freeman, 1984). CSR can be seen as an opportunity when companies try to include intangible assets such as identities, reputations and goodwill into their marketing strategies in order to improve their sustainable competitive position. This has an effect not only on the customers, but on other stakeholders as well because of their multidimensional relationships with a firm (i.e. by being an employee, customer and capital investor at the same time) (Sen, Bhattacharya, and Korschun, 2006). Porter and Kramer (2002) and McWilliams and Siegel (2001) also state that investments in CSR benefits a firm’s competitive position through better managing of risks and reputation and better access to capital. Moreover, it leads to better marketing of products and services, because CSR will function in similar ways as advertising, by increasing demand for products, which in turn is crucial for maximizing long term value (Becchetti, Ciciretti, and Hasan, 2007). Also other researchers that examined the link between CSR and CFP did find promising results towards a positive relationship (Barnett and Salomon, 2006; Saeidi et al., 2014; Waddock and Graves, 1997). On the other hand, some studies did prove the two to be not or even negatively correlated (Crisótomo, Freire, and Vasconcellos, 2011; Freedman and Jaggi, 1986). For instance, Vance (1975) studied the effect of CSR on stock market returns and found a negative relationship. Lu et al, (2014), who did a meta-analysis on the empirical research of the CSR-CFP nexus, argue that the mixed results found in this literature field can be mainly attributed to the research methods in place. They state that event studies, which measure the short-term effect of CSR, predominantly find no or negative results. Implementing social responsible activities in a strategy takes time to result in CFP (Jensen, 2001; Lu et al., 2014), so by including stock market returns as the financial performance measure, a time effect will disregarded. Therefore, this study will include only financial performance measures that measure long-term financial performance. This will be explained in detail in chapter 3.

(9)

9

seek to satisfy stakeholder demands at minimum costs. So, even if the social responsible actions are based on altruistic grounds, the theory suggests managers will seek to do so at minimum costs. Some academics even state that although CSR might be presented as a gift, it leads to unspecified reciprocity which builds respect towards the giver (Kennett, 1980; Tonkiss and Passey, 1999). Also Godfrey, Merrill and Hansen (2009) argue that social responsible actions are not a signal of complete altruism, but show that a firm is aware it impacts others in their decisions, which leads to firms accruing appreciation and consequently a better sustainable competitive position. Based on this discussion, it is proposed that CSR will positively affect CFP in the long run through increased reputation, better access to capital and overall an increased demand for products. The following hypothesis comprises the proposed relationship between CSR and CFP:

H1: A firm’s CSR level is positively related to its corporate financial performance.

2.2 The influence of a sustainable competitive position on the relation between CSR and CFP

(10)

10

The formal model constructed by McWilliams and Siegel (2001a) shows how competition in CSR could affect the link between CSR and CFP. By using resource based theory, the model describes how to profit-maximize CSR. McWilliams and Siegel (2001a) propose two companies producing identical products of which one adds a social feature to its product, which is valued by customers and potentially other stakeholders. Managers decide based on a cost-benefit analysis how much to invest in CSR by assessing the demand for CSR which eventually increases returns of the firm. Some researchers assume in the CSR literature that investing in CSR will lead to a sustainable competitive position and eventually to CFP (Becchetti et al., 2007). However, less research is done on the effect of the sustainable competitive position of competitors on this relationship. When the model constructed by McWilliams and Siegel (2001a) is taken into account, a better sustainable competitive position can be expected when a company adds a social feature when its competitors do not. In practice, when competitors have comparable resources or investments in CSR, the effect of socially responsible actions on CFP may be small to negligible. That is because it becomes harder for a company to differentiate from their competitors and socially responsible products can become less unique. So, it is proposed that socially responsible activities will increase reputation, but the intensity of their correlation is expected to be affected by the CSR performance of competitors. A firm with a higher CSR performance relative to the industry standard (i.e. the average CSR performance of the industry) will be able to accrue more appreciation from stakeholders due to its relatively better sustainable competitive position. Firms that perform similar to the industry standard are expected to benefit less from reputation building. These companies might meet certain pressures from external stakeholders to prevent potential conflicts that cause financial damage (Freeman, 1984). However, their sustainable behaviour/reputation will not stand out and/or their products are less unique compared to better socially performing companies in the same industry. In other words, their strategic investments deal with the risks associated with CSR, but they seize less to the opportunities such as building a sustainable competitive position. Consequently, companies that do not excel with respect to their sustainable competitive position might expect a less strong influence of their CSR investments on CFP. Hence, it seems that the link between CSR and CFP is not just a linear relationship as previous literature often suggests, but their association is moderated by the relative sustainable competitive position of a firm. This association translates into a curvilinear relationship. When a firm’s CSR level is lower relative to the industry standard, investments in CSR will improve CFP by decreasing marginal returns until the CSR level reaches the industry standard, after which the impact of CSR on CFP will enhance by increasing marginal returns. The following hypothesis is developed in order to examine the proposed moderating effect of sustainable competitive position on the link between CSR and CFP:

H2: The association between a firm’s CSR level and CFP is positively moderated by its

(11)

11 2.3 Stakeholder demands and industry focus

(12)

12

(e.g. food products, personal products, and beverages), and energy (e.g. oil, gas and consumable fuels and energy equipment and services) industry. These particular industries are chosen because CSR is expected to be important in these industries and/or the composition of the salient stakeholder groups are expected to be dissimilar. As has been noted before, in the food industry, customers will be the salient stakeholder and therefore a stronger relationship between CSR and CFP is expected. Similar to the food industry, in the consumer cyclical and consumer non-cyclical industries, customers are expected to be a salient stakeholder group. In case of energy sector, the composition of salient stakeholder groups will differ with less focus on the customer (Miles, 1987). Hence, different pressures and reactions of the salient stakeholders will determine whether the link between CSR and CFP will maintain in an industry. The following hypothesis is constructed that takes the importance of customers as the salient stakeholder group into account when predicting the extent to which CSR-CFP holds in an industry:

H3: The relationship between CSR and CFP will be stronger in industries where the

customer is the salient stakeholder group.

3. METHODOLOGY

In this section, the data collection method, measurements, and plan of analysis will be discussed. In this study, a quantitative research design is the most appropriate method to use, because the hypotheses that will be tested are grounded with well-developed literature and more empirical evidence is needed in this literature field. Although some contradictory results can be found in previous literature regarding the CSR-CFP relation, this study will again examine this widely tested relation by taking into consideration the time effect with use of new insights on the measurement of CFP and the moderation effect of competition. Furthermore, different industries will be compared and contrasted.

3.1. Data collection

(13)

13

designed to objectively measure a company’s environmental, social and governance (ESG)1 performance based on company-reported data. The data goes back to 2002 and is available on over 7000 public companies that are measured across more than 400 ESG metrics that cover a couple of themes, such as emissions, environmental product innovation and human rights (Thomson Reuters ESG Scores, 2018). Orbis also provides comprehensive and reliable company data on around 300 million companies worldwide and is used to collect the financial data for this study (bvdinfo.com). If possible, any missing financial data is complemented with data collected from Eikon.

This study only takes companies located in Europe or North America into consideration, because these companies all operate mainly in the same economically developed markets. By including companies that operate either in Europe or North America, the dataset becomes a fair representation of the developed western world. Including companies outside these locations might create noise in the dataset due to cultural and political differences between countries and the associated expectations regarding the social responsibility of firms (Ho, Wang, and Vitell, 2011; Peng, Dashdeleg, and Chih, 2012). Besides that, all firms are publically owned commercial companies with an annual revenue exceeding 1 million euros.

The CSR and financial data used in this study are collected in the period October-December 2018 for companies tracked in the period 2013-2017. Although the ESG data available in Eikon goes back to 2002 for some companies, a smaller period is used in order to create a dataset that covers companies with data available throughout the entire timespan. Any companies having more than two years of missing data were excluded from the dataset. In case a firm misses data in one year, the mean of the company’s time series data replaces the missing data point in that year. In this way, no valuable data is lost. The initial sample size covered 426 companies. After comparing the ESG score with all three individual pillar scores (that should contribute equally to the ESGscore) for each company, some inconsistent data points were discovered. To make sure the dataset would be reliable, companies with conflicting scores we left out. The final dataset consists of 402 companies in various industries with headquarters located in Europe and North America. Table 1 provides a more detailed representation of the final dataset.

3.2. Measurement

This study contains two dependent variables (that measure corporate financial performance), several control variables and two independent variables in order to test the hypotheses. Next, the measurement of these variables will be explained in detail.

1_{In this study, the terms CSR (level) and ESG (score) are used interchangeably. ESG score is adopted from the}

(14)

14

Table 1. Final sample distribution, number of firms by industry and location of HQ

Industry Number of firms Percentage

Total Europe North America

Cyclical Consumer Products 107 56 51 26.6%

Non-Cyclical Consumer Products 107 59 48 26.6%

Energy 188 72 116 46.8%

Total 402 187 215 100%

3.2.1. Financial performance

(15)

15

3.2.2. CSR level

As has been discussed before, the data used to measure a company’s CSR level is based on Thomson Reuters’ ESG scores. These ESG scores are based on over 400 ESG measures that are standardized for each company, which makes comparing between a range of companies possible. In line with a company’s ESG disclosure, the data is updated at least once a year. The 400 ESG measures are translated into 10 categories, which are equally weighted and grouped into three pillar scores: environmental, social and corporate governance (see table 2). These three pillar scores then formulate – with proportionally equal importance - the final ESG score. Both pillar and ESG scores are weighted on a scale from zero (worst) to 100 (best).

In order to measure whether the CSR-CFP relationship behaves differently when firms out- or underperform in an industry with respect to their sustainable competitive position, an additional CSR variable is introduced as a polynomial term. This will be explained in detail in paragraph 3.3.

3.2.3. Control variables

This study includes several control variables in order to account for sources of heterogeneity:

firm size, capital expenditure, research and development (R&D), leverage, and growth. Also time, industry and law dummies are included. First of all, firm size was considered. This variable is widely recognized as an important predictor of financial performance (Ullman, 1985). Larger firms have less growth opportunities and consequently lower CFP (Fama and French, 1992). In order to make size comparable between companies, the logarithm of a firm’s total market capitalization was taken.

The second control variable capital expenditure is included, because higher relative capital expenditures are proven to enhance stock returns, which is positively related to CFP (McConnell and Muscarella, 1985). This variable is measured by calculating capital expenditures divided by the total assets in a company.

The third control variable R&D controls for the amount of investments a company makes in research and development. This results in more intangible assets, which leads to unique products and a better competitive position. This has a positive influence on CFP (McWilliams

Table 2. ESG score construction

ESG pillars

Environmental Governance Social

Resource Use Management Workforce

Emissions Shareholders Human Rights

Innovation CSR Strategy Community

(16)

16

and Siegel, 2001; Surroca et al., 2010). In line with Chan, Lakonishok, and Sougiannis (2002), this study measures R&D by dividing intangible assets by total assets.

The fourth variable leverage controls for the extent to which a firm is financed with debt. Firms with high levels of leverage have a higher risk of default, so they can suffer from underinvestment (Lang, Ofek, and Stulz, 1996; Lioui and Sharma, 2012; Myers, 1977). Therefore, underinvestment is predicted to be negatively associated with CFP. This variable is measured by dividing total debt by total assets.

The fifth variable growth controls for sales growth. Higher growth is positively related to CFP and therefore included in this study (Cai et al. 2012). This variable is measured by dividing each year’s total revenue by the value in the previous year.

Also, all control variables are winsorized at the 2.5th and 97.5th percentiles in order to reduce the effect of outliers (Tukey, 1962).

Due to the various geographical locations covered in this study, political differences might be present, which could distort the test results. For instance, Liang and Renneboog (2017) state that countries have different value maximizing levels of CSR due to different legal regimes resulting in different expectations of external stakeholders towards the social responsibility of firms. Their results suggest that in countries that originate their legal regime from civil law, firms have higher levels of CSR than countries with a legal regime that is based on common or socialist law. Also Campbell (2007) proposes that firms are more likely to act in sustainable ways when the regulations encourage such behaviour. Therefore, in order to account for possible differences in expectations of external stakeholders in each country, this study incorporates law fixed effects. Table A1 provides a detailed representations of the countries and their legal origin used in this study. In addition, this study considers both time, industry and country fixed effects.

3.3 Analysis

3.3.1. Regressions

The empirical model consists of multiple regressions. In the first model, all control variables are regressed on Tobin’s Q. The objective in the first hypothesis is to estimate the effect of CSR on CFP. This is achieved in the second model where the control variables and CSR level are regressed on Tobin’s Q:

Tobin′_{s Q}

𝑖,𝑡 = 𝑏0+ 𝑏1(CSR𝑖,𝑡−1) + 𝑏𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠(Controls𝑖,𝑡−1) + Year𝑖,𝑡+ Industry𝑖,𝑡+ Country𝑖,𝑡

+ Law𝑖,𝑡+ e𝑖,𝑡

(17)

17

well-known problem addressed in previous literature, called endogeneity, where the sign of the regression coefficients can be biased if not corrected for (Bascle, 2008). The control variables are lagged by one period as well to account for endogeneity.

In model three, a quadratic term of the CSR level is added to the previous model. This term functions as a constitutive term and is necessary for the interaction term that is added in model 4 (Brambor, Clark and Golder, 2006). The cubic term of the CSR level is added in model 4 to the previous model in order to test the second hypothesis: sustainable competitive position has a positive moderating effect on the CSR-CFP relationship. This method is in line with work done by Barnett and Salomon (2006), who also investigate an inflection point in this literature field. The associated regression is:

Tobin′s Q𝑖,𝑡 = 𝑏0+ 𝑏1(CSR𝑖,𝑡−1) + 𝑏2(CSR𝑖,𝑡−12) + 𝑏3(CSR𝑖,𝑡−13) + 𝑏𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠(Controls𝑖,𝑡−1)

+ Year𝑖,𝑡+ Industry𝑖,𝑡+ Country𝑖,𝑡+ Law𝑖,𝑡+ e𝑖,𝑡 for firm i at time t.

In order to test the third hypothesis, the same set of regressions were performed for each industry separately. The test results will be compared and contrasted in order to give answer to this hypothesis.

Furthermore, all previous steps were performed for the dependent variable ROA, which is the second variable used in this study to measure CFP. Furthermore, additional tests were conducted that exclude the governance pillar which is one of the three pillars that measure a firm’s CSR level. This is necessary since some researchers state that the governance pillar has no direct relationship with CFP (Dalton and Dalton, 2011). Including the governance pillar in the CSR variable could therefore lead to biased results.

3.3.2. Panel data model

(18)

18

A model that can include these time invariant dummies is the RE model. In a RE model, the cross-sectional effects are assumed to be random and uncorrelated with the independent variables in the model. A Hausman test is conducted to decide whether a FE or RE model should be used, by testing if the unobserved random effects are correlated. The test is significant at p < 0.01, so the effects are correlated and a fixed effects model is preferred.

The RE model did show insignificant results regarding the country and law fixed effects. However, the industry fixed effects were found to be significant, implying that industry effects should be considered when constructing the model. Since the Hausman test proves that the FE model is preferred over the RE model, industry fixed effects will not be included in the final model. In order to account for the industry fixed effects regardless, separate regressions for each industry are performed. These results will be discussed in chapter 4.

4. RESULTS

In this section, the descriptive statistics, correlation matrix and results of the multiple regressions that test the hypotheses are presented. Also additional regression analyses are discussed for robustness and to explore the differences between industries. Before the correlation matrix can be generated, the data is tested for normality by conducting a Jarque-Bera test. The result (p < 0.01) indicates that the data has a non-normal distribution. Due to violations of normality, a Pearson’s correlation cannot be run. Therefore, the Spearman rank-order correlation (which can deal with nonparametric data) is used to create the correlation matrix. In table 3, the descriptive statistics and correlation matrix of the variables are presented.

(19)

19

Table 3. Descriptive statistics and correlation matrix of variables (Spearman correlation)

1 2 3 4 5 6 7 8 9 1 TobinsQ 1.00 2 ROA 0.37** 1.00 3 Firm size*** 0.26** -0.04 1.00 4 R&D 0.35** 0.15** 0.14** 1.00 5 Capex -0.23** -0.20** -0.08** -0.35** 1.00 6 Leverage 0.11** 0.16** 0.11** 0.12** -0.14** 1.00 7 Growth 0.19** 0.16** 0.13** 0.04 -0.06* -0.04 1.00 8 ESGscore 0.08** 0.05 0.48** 0.06* -0.08** 0.27** -0.13** 1.00 9 ESscore 0.08** 0.11** 0.50** 0.07** -0.12** 0.25** -0.10** 0.93** 1.00 N 1939 1971 1554 1352 1593 1589 1564 1582 1581 Mean 1.66 0.86 15.57 0.19 0.07 0.57 0.97 55.84 57.69 S.D. 0.90 0.63 1.54 0.18 0.06 0.19 0.20 16.76 20.14 Minimum 0.62 0.12 12.20 0.00 0.00 0.18 0.50 7.89 8.57 Maximum 4.85 2.74 18.66 0.62 0.27 1.02 1.46 93.92 95.40

All independent variables and control variables are lagged with one period. See section 3.2 for explanation and calculation of the variables. Dummies for industry, year and law are not included in the table.

* p < 0.05 (two-tailed) ** p < 0.01 (two-tailed)

(20)

20

p < 0.01; r = 0.16, p < 0.01; r = 0.16, p < 0.01). Also here, the coefficients of capital expenditures

and leverage are the opposite of what is expected. Furthermore, the table shows a high correlation coefficient between the two CSR measures. This is plausible, because they have to measure a similar fact. Also these variables are not regressed simultaneously, so no multicollinearity will occur. Looking at the parameters related to the more general hypotheses that will be tested, three significant correlation coefficients are found. The correlation coefficient between Tobin’s Q and ESGscore/ESscore is statistically significant (r = 0.08, p < 0.01, for both variables). Also the correlation coefficient between ROA and ESscore is positive and statistically significant, which is in line with the predictions. More surprisingly is the significant correlation between the control variables and the independent variables. This might be a sing of multicollinearity.According to Dormann (2013), when a correlation coefficient is lower than -0.7 or higher than 0.7, multicollinearity may be present. In this case, these variables do not exceed these thresholds. Nonetheless, to make sure no multicollinearity exists, a variance inflation factor (VIF) method is conducted. In case a variable has a VIF above 10, the data suffers from multicollinearity (Menard, 1995). The highest VIF score was 1.46 for ESscore, so the data does not suffer from multicollinearity. After the variables were proved to be satisfactory, a multivariate analysis can be performed that tests the hypotheses presented in chapter 2.

4.1. Multivariate analysis

The test results of the multivariate analysis are summarized in table 4. For each CFP measure, the table presents three models. In model 1, the endogenous variable is regressed against the control variables. Model 2 adds the independent variable ESG score, model 3 adds the quadratic term and model 4 adds the cubic term. In model 1, the control variables capital expenditures and growth are found to be negatively related to Tobin’s Q and firm size is positively related, which is not in line with previous literature. For the other financial measure ROA, almost all control variables are statistically significant. Also here, unlike predicted, firm size, capital expenditures, and leverage are found to be negatively related to ROA. Only growth is positive and statistically significant correlated to ROA, which is expected.

As can be seen in the table, all models have significant F-values. However, under Tobin’s Q all models have a low adjusted R-squared, implying that the models do not fit the data well. Hence, interpretations should be made with caution. Furthermore, in the models under Tobin’s Q no year dummies were included. The test results point out that the hypothesis that all coefficients for all years are equal to zero is not rejected.

(21)

21

Table 4. Regression analysis

Tobin’s Q Return on Assets

Model 1 Model 2 Model 3 Model 4 Model 1 Model 2 Model 3 Model 4 Independent variables B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E)

Control variables Firm size(-1) 0.14*** (0.04) 0.14*** (0.04) 0.14*** (0.04) 0.14*** (0.04) 0.04* (0.03) 0.04* (0.03) 0.04* (0.03) 0.04* (0.03) R&D(-1) -0.21 (0.22) -0.21 (0.22) -0.20 (0.22) -0.20 (0.22) -0.13 (0.10) -0.09 (0.12) -0.09 (0.12) -0.09 (0.12) Capex(-1) -0.78* (0.51) -0.97** (0.52) -0.97** (0.51) -0.97** (0.51) -0.49*** (0.19) -0.57*** (0.19) -0.57*** (0.19) -0.56*** (0.19) Leverage(-1) 0.17 (0.25) 0.15 (0.26) 0.14 (0.26) 0.14 (0.26) 0.21** (0.13) 0.21* (0.13) 0.21* (0.13) 0.21* (0.13) Growth(-1) -0.28*** (0.08) -0.29*** (0.08) -0.29*** (0.08) -0.29*** (0.08) 0.19*** (0.04) 0.19*** (0.04) 0.19*** (0.04) 0.19*** (0.04) Direct effects ESG score(-1) -0.00** (0.00) -0.00 (0.00) -0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) ESG score^2(-1) -0.00 (0.00) -0.00 (0.00) 0.00 (0.00) 0.00 (0.00) ESG score^3(-1) -0.00 (0.00) 0.00 (0.00) Model fit Observations 1305 1279 1279 1279 1305 1279 1279 1279 R-squared 0.03 0.04 0.04 0.04 0.14 0.15 0.15 0.15 Adjusted R-squared 0.03 0.04 0.04 0.04 0.14 0.14 0.14 0.14

Year dummy NO NO NO NO YES YES YES YES

Fixed/random effect: Fixed Fixed Fixed Fixed Fixed Fixed Fixed Fixed F-value 4.52*** 4.11*** 3.59*** 3.52*** 15.10*** 13.32*** 12.28*** 11.17*** All independent variables and control variables are lagged with one period. Robust standard errors are used to

account for heteroscedasticity. * p < 0.10 (one-tailed)

(22)

22

Hypothesis 2 predicts that the relationship between CSR and CFP is not linear, but positively influenced by the moderation effect of sustainable competitive position. The variable ESGscore was centered before the polynomial term was made, because a product term can result in collinearity (Aiken and West, 1991; Barnett and Salomon, 2006). Model 4 shows that the cubic term that represents the curvilinear relationship is insignificant under both CFP measures and therefore no support is found for hypothesis 2.

After the regressions were performed, a Modified Wald statistic was conducted which tests the model for joint heteroscedasticity in the residuals (Greene, 2000). The null hypothesis of homoscedasticity was rejected and therefore robust standard errors were used to overcome potential issues with heteroscedasticity. These robust standard errors are included in the regression outputs presented.

(23)

23

Table 5. Regression analysis per industry

Panel A: Energy Panel B: Consumer

Cyclicals

Panel C: Consumer Non-Cyclicals

Tobin’s Q ROA Tobin’s Q ROA Tobin’s Q ROA

Model 4 Model 4 Model 4 Model 4 Model 4 Model 4 Independent variables B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E)

Control variables Firm size(-1) 0.06** (0.04) 0.03* (0.04) 0.35*** (0.13) 0.01 (0.04) 0.21*** (0.05) -0.09** (0.05) R&D(-1) 0.23 (0.26) -0.18 (0.16) -1.97** (1.18) 0.01 (0.26) 0.09 (0.21) -0.13 (0.17) Capex(-1) 0.22 (0.35) -0.61*** (0.21) -6.13* (3.97) 0.10 (0.42) -0.07 (1.44) -2.02* (1.25) Leverage(-1) 0.36** (0.25) 0.42*** (0.12) 0.15 (0.69) -0.00 (0.19) 0.29 (0.26) -0.04 (0.20) Growth(-1) -0.19*** (0.06) 0.12*** (0.03) 0.49** (0.22) 0.08 (0.07) -0.06 (0.17) 0.33** (0.15) Direct effects ESG score(-1) 0.00 (0.00) -0.00 (0.00) -0.01** (0.01) -0.00* (0.00) -0.00 (0.00) 0.00 (0.00) ESG score^2(-1) 0.00 (0.00) -0.00 (0.00) -0.00 (0.00) -0.00 (0.00) -0.00 (0.00) 0.00 (0.00) ESG score^3(-1) 0.00 (0.00) 0.00** (0.00) 0.00 (0.00) -0.00 (0.00) -0.00 (0.00) -0.00 (0.00) Model fit Observations 505 505 395 395 379 379 R-squared 0.17 0.40 0.12 0.03 0.05 0.09 Adjusted R-squared 0.15 0.39 0.11 0.01 0.05 0.07

Year dummy YES YES NO NO YES YES

Fixed/random effect: Fixed Fixed Fixed Fixed Random Fixed F-value 9.85*** 23.95*** 2.37** 1.31 33.10*** 3.60*** This table presents the regression analyses for each industry separately. Only model 4 is

presented. All independent variables and control variables are lagged with one period. Robust standard errors are used to account for heteroscedasticity.

* p < 0.10 (one -tailed) ** p < 0.05 (one -tailed)

(24)

24

Table 6. Regression analysis for robustness check Panel A: All

industries

Panel B: Energy Panel C: Consumer

Cyclicals

Panel D: Consumer Non-Cyclicals

Tobin’s Q ROA Tobin’s Q ROA Tobin’s Q ROA Tobin’s Q ROA

Model 4 Model 4 Model 4 Model 4 Model 4 Model 4 Model 4 Model 4 Independent variables B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E) B (S.E)

Control variables Firm size(-1) 0.17*** (0.04) 0.04* (0.03) 0.08** (0.04) 0.03 (0.04) 0.32*** (0.12) 0.00 (0.04) 0.11** (0.07) -0.08* (0.05) R&D(-1) -0.21 (0.23) -0.12 (0.11) 0.25 (0.26) -0.14 (0.17) -2.17** (1.14) -0.04 (0.26) 0.21 (0.23) -0.22* (0.16) Capex(-1) -0.92** (0.51) -0.52** (0.19) 0.27 (0.35) -0.57*** (0.20) -5.67* (3.93) 0.18 (0.41) -0.59 (1.50) -1.14 (1.16) Leverage(-1) 0.20 (0.25) 0.22** (0.13) 0.43** (0.25) 0.40** (0.19) 0.43 (0.65) 0.04 (0.20) -0.02 (0.29) -0.01 (0.21) Growth(-1) -0.27*** (0.08) 0.19 (0.04) -0.24 (0.06) 0.13*** (0.04) 0.50** (0.23) 0.09 (0.07) 0.07 (0.14) 0.39*** (0.13) Direct effects ES score(-1) -0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) -0.01** (0.01) -0.00* (0.00) -0.00 (0.00) -0.00 (0.00) ES score^2(-1) -0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) -0.00 (0.00) -0.00 (0.00) ES score^3(-1) 0.00 (0.00) 0.00 (0.00) -0.00 (0.00) 0.00 (0.00) 0.00*** (0.00) 0.00* (0.00) -0.00 (0.00) 0.00 (0.00) Model fit Observations 1280 1280 505 505 395 395 380 380 R-squared 0.04 0.15 0.18 0.40 0.15 0.03 0.05 0.06 Adjusted R-squared 0.03 0.14 0.16 0.39 0.13 0.01 0.02 0.05

Year dummy NO YES YES YES NO NO YES NO

Fixed/random effect: Fixed Fixed Fixed Fixed Fixed Fixed Fixed Fixed F-value 3.33*** 12.58*** 10.10*** 16.19*** 2.95*** 1.20 2.19** 4.63*** This table presents the test results of the robustness check for the whole sample and each industry separately. Only model 4 is presented with ESscores as independent variables, which excludes the governance pillar. All independent variables and control variables are lagged with one period. Robust standard errors are used to account for

heteroscedasticity. * p < 0.10 (one -tailed) ** p < 0.05 (one -tailed)

(25)

25 4.2. Robustness test

As a robustness test, additional regressions will be examined that exclude the governance pillar from the regressions performed in table 4 and 5. The test results are presented in table 6. The results indicate that ESscore is only negatively related to Tobin’s Q (b = -0.00, p < 0.05) in the consumer cyclicals industry (panel C), so hypothesis 1 is not supported. Furthermore, in the same industry, the cubic term is found to be statistically significant related to Tobin’s Q (b = 0.00, p < 0.01). This result implies that the prediction of an inflection point is present and the relationship between ESscore and CFP is curvilinear. However, a similar relationship between ROA and the cubic term is not proven, since the model is insignificant. So, some minor evidence of a curvilinear relationship exists when the governance pillar is excluded. However, since only one of the CFP measures is found to be significant, no conclusive answer can be given regarding the prediction of a non-linear relationship. Furthermore, when the test results of the energy sector are compared with table 5, it can be noticed that the cubic term has become insignificant when the governance pillar is excluded.

5. DISCUSSION AND CONCLUSION

In this section, the test results will be related to existing literature. Since the main hypotheses were found to be insignificant, no conclusive answer can be given to the main research question. Plausible reasons will be presented as to why these results were insignificant. Some of the test results, however, do confirm there is a difference in the way the CSR-CFP nexus is present in industries, but the results are not in line with the predictions. Furthermore, the theoretical and managerial implications of this study will be discussed. At the end of this section, the limitations of this study will be presented which steers the suggestions for future research.

5.1 Discussion

This study investigates the relevance of sustainable competitive position in explaining the relationship between CSR and CFP. Three hypotheses were developed in order to give an answer to the research question. The data used to test the hypotheses comes from secondary data sources and covers companies in several industries located in countries in Europe or North America.

(26)

26

CSR is mostly not significantly related to CFP. In some cases, even a negative association was found, suggesting that higher levels of CSR will damage CFP. Therefore, no support was found for this hypothesis, which is not in line with the current literature on the CSR-CFP debate and the enlightened stakeholder theory. A plausible reason for the insignificant and negative results found regarding the CSR-CFP nexus, could be attributed to the ambiguity and complexity of the concept of CSR and the effect is has on CFP. It may be too hard for managers to keep track of the indirect effect one dollar investment in CSR has on CFP, since CSR is often suggested to improve a wide range of business aspects that eventually lead to a better sustainable competitive position. Together with the increasing pressures from external stakeholders and attention in academic papers to act socially responsible, companies in the current era might overestimate the turnover of their CSR investments, which may distort the test results or even lead to a negative association between CSR and CFP.

Second, it was suggested that the strength of the association between CSR and CFP ultimately depends on a firm’s sustainable competitive position relative to the industry standard. The CSR-CFP nexus is proposed to be moderated by the sustainable competitive position of a firm, which translates into a curvilinear relationship between CSR and CFP. The results do not provide any evidence of a curvilinear relation in the total sample. Only in the energy sector a curvilinear relationship between CSR and ROA is present. Furthermore, in the robustness test, which excludes the governance pillar in calculating CSR, a curvilinear relationship exists in the consumer cyclical industry. This insinuates that excluding the governance pillar makes sense when establishing the link between CSR and CFP in this industry. The differences in results found between industries do suggest that the link between CSR and CFP is affected by the characteristics of an industry. Whether this is due to the type of salient stakeholder present in an industry is examined in the last hypothesis.

(27)

27

was proposed that the consumer was the salient stakeholder group in both the consumer cyclicals and consumer non-cyclicals industry. However, the results show insignificant results for the consumer non-cyclicals industry, implying that the proposed relationship is inconsistent between the two.

Altogether, the results provide no conclusive answer to the research question, so limited managerial and theoretical implications can be made. The only valuable inferences that can be made regarding the test results, is that acting socially responsible is often negatively related to CFP and their association is not consistent between industries. Whether these differences can be attributed to the salient stakeholder groups in place, stays inconclusive. More research is needed in order to assess the possible effect of stakeholder demands on the CSR-CFP nexus.

5.2 Limitations and future research

Next, a couple of limitations will be discussed which might be the reason that insignificant results were found in this study. Based on these limitations and the findings in this study, suggestions for future research will be provided.

First of all, the sample size (402 companies) was moderate to small. Especially because the dataset is split to test for each industry separately, the sample size could affect significant results. Redoing this research with a larger sample size and longer time period might lead to more reliable results.

Second, although this study takes the importance of the salient stakeholder group into account, which is based on the general assumptions made in previous literature, the exact composition of the salient stakeholders in an industry and the importance of each and every pressure and reaction to CSR cannot be specified. Since stakeholder reactions to CSR can change over time and between industries (Buysse and Verbeke, 2003), results implying that a certain relationship between CSR and CFP exists, might also change with time. Future researchers should take this into account by examining a single industry over time and keep track of the most salient stakeholders and their evolving pressures and demands. By doing this, more insights in the role of salient stakeholders on the CSR-CFP nexus can be provided.

(28)

28

REFERENCES

Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions

Barnett, M. L., & Salomon, R. M. (2006). Beyond dichotomy: The curvilinear relationship between social responsibility and financial performance. Strategic Management Journal, 27(11), 1101-1122.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.

Bascle, G. (2008). Controlling for endogeneity with instrumental variables in strategic management research. Strategic Organization, 6(3), 285-327.

Becchetti, L., Ciciretti, R., & Hasan, I. (2007). Corporate social responsibility and sharholder's value: An event study analysis. Unpublished working paper.

Becker-Olsen, K. L., Cudmore, B. A., & Hill, R. P. (2006). The impact of perceived corporate social responsibility on consumer behavior. Journal of Business Research, 59(1), 46-53. Berman, S. L., Wicks, A. C., Kotha, S., & Jones, T. M. (1999). Does stakeholder orientation

matter? the relationship between stakeholder management models and firm financial performance. Amj, 42(5), 488-506.

Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political Analysis, 14(1), 63-82.

BSR. (2016). The Paris agreement. Retrieved from

https://www.bsr.org/reports/BSR_WeMeanBusiness_Business_Climate_Paris_Agreemen t_Implications.pdf

Bureau van Dijk. Bvdinfo. Retrieved from bvdinfo.com

Buysse, K., & Verbeke, A. (2003). Proactive environmental strategies: A stakeholder management perspective. Strategic Management Journal, 24(5), 453-470.

Cai, Y., Jo, H., & Pan, C. (2012). Doing well while doing bad? CSR in controversial industry sectors.108(4), 467-480.

Campbell, J. L. (2007). Why would corporations behave in socially responsible ways? an institutional theory of corporate social responsibility. Amr, 32(3), 946-967.

Chan, L. K. C., Lakonishok, J., & Sougiannis, T. (2001). The stock market valuation of research and development expenditures. The Journal of Finance, 56(6), 2431-2456. Dam, L., & Scholtens, B. (2015). Toward a theory of responsible investing: On the economic

foundations of corporate social responsibility. Resource and Energy Economics, 41, 103-121.

(29)

29

Dhaliwal, D., Li, O. Z., Tsang, A., & Yang, Y. G. (2014a). Corporate social responsibility disclosure and the cost of equity capital: The roles of stakeholder orientation and financial transparency. Journal of Accounting and Public Policy, 33(4), 328-355. Dhaliwal, D., Li, O. Z., Tsang, A., & Yang, Y. G. (2014b). Corporate social responsibility

disclosure and the cost of equity capital: The roles of stakeholder orientation and financial transparency. Journal of Accounting and Public Policy, 33(4), 328-355. Dormann. (2013). Collinearity: A review of methods to deal with it and a simulation study

evaluating their performance.

Ducassy, I. (2013). Does corporate social responsibility pay off in times of crisis? an alternate perspective on the relationship between financial and corporate social performance. Corporate Social Responsibility and Environmental Management, 20(3), 157-167. Eccles, R. G., Ioannou, I., & Serafeim, G. (2014). The impact of corporate sustainability on

organizational processes and performance.

Eicholtz, P., Kok, N., & Quigley, J. M.Doing well by doing good? green office buildings.100(5), 2492-2509.

El Ghoul, S., Guedhami, O., & Kim., Y. (2017). Country-level institutions, firm value, and the role of corporate social responsibility initiatives.48(3), 360-385.

Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427-465.

Freedman, M., & Bikki, J. (1986). An analysis of the impact of corporate pollution disclosures included in annual financial statements on investors’ decisions. In M. Neimark (Ed.), Advances in Public Interest Accounting, 1, 193-212.

Freeman, R. (1984). Strategic management: A stakeholder perspective. Englewood Cliffs, NJ: Prentice-Hall.

Godfrey, P. C. (2005). The relationship between corporate philanthropy and shareholder wealth: A risk management perspective. Amr, 30(4), 777-798.

Godfrey, P. C., Merrill, C. B., & Hansen, J. M. (2009). The relationship between corporate social responsibility and shareholder value: An empirical test of the risk management hypothesis. Strategic Management Journal, 30(4), 425-445.

Greene, W. (2012). Econometric analysis Upper Saddle River, NJ: Prentice–Hall.

Gregory, A., Tharyan, R., & Whittaker, J. (2014). Corporate social responsibility and firm value: Disaggregating the effects on cash flow, risk and growth.124(4), 633-657. Ho, F. N., Wang, H. D., & Vitell, S. J. (2012). A global analysis of corporate social

performance: The effects of cultural and geographic environments.107(4), 423-433. Jensen, M. C. (2010). Value maximization, stakeholder theory, and the corporate objective

function. Journal of Applied Corporate Finance, 22(1), 32-42.

(30)

30

Lang, L., Ofek, E., & Stulz, R. (1996). Leverage, investment, and firm growth. Journal of Financial Economics, 40(1), 3-29.

Liang, H., & Renneboog, L. (2017). On the foundations of corporate social responsibility. The Journal of Finance, 72(2), 853-910.

Lin, X., Zhang, Y., & Zhu, N. (2009). Does bank ownership increase firm value? evidence from china. Journal of International Money and Finance, 28(4), 720-737.

Lioui, A., & Sharma, Z. (2012). Environmental corporate social responsibility and financial performance: Disentangling direct and indirect effects. Ecological Economics, 78, 100-111.

Lu, W., Chau, K. W., Wang, H., & Pan, W. (2014). A decade's debate on the nexus between corporate social and corporate financial performance: A critical review of empirical studies 2002–2011. Journal of Cleaner Production, 79, 195-206.

Mackey, A., Mackey, T. B., & Barney, J. B. (2007). Corporate social responsibility and firm performance: Investor preferences and corporate strategies. Amr, 32(3), 817-835.

McConnell, J. J., & Muscarella, C. J. (1985). Corporate capital expenditure decisions and the market value of the firm. Journal of Financial Economics, 14(3), 399-422.

McWilliams, A., & Siegel, D. (2000). Corporate social responsibility and financial performance: Correlation or misspecification? Strategic Management Journal, 21(5), 603-609.

McWilliams, A., & Siegel, D. (2001). Corporate social responsibility: A theory of the firm perspective. Amr, 26(1), 117-127.

Miles, R. A. (1987). Managing the corporate social environment. Englewood Cliffs, NJ: Prentice-Hall.

Moir, L. (2001). What do we mean by corporate social responsibility? Corporate Governance, 1(2), 16-22.

Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economics, 5(2), 147-175.

Peloza, J., & Papania, L. (2008). The missing link between corporate social responsibility and financial performance: Stakeholder salience and identification.11(2), 169-181.

Peng, Y., Dashdeleg, A., & Chih, H. L. (2012). Does national culture influence firm’s CSR engagement: A cross country study. International Proceedings of Economics

Development and Research, 58(9), 40-44.

Porter, M. E., & Kramer, M. R. (2006). Strategy and society: The link between competitive advantage and corporate social responsibility. Harvard Business Review, 84(12), 78-92. Refinitiv. (2018). Thomson reuters ESG scores. Retrieved from

(31)

31

Russo, M. V., & Fouts, P. A. (1997). A resource-based perspective on corporate

environmental performance and profitability. Academy of Management Journal, 40(3), 534-559.

Saeidi, S. P., Sofian, S., Saeidi, P., Saeidi, S. P., & Saaeidi, S. A. (2015). How does corporate social responsibility contribute to firm financial performance? the mediating role of competitive advantage, reputation, and customer satisfaction. Journal of Business Research, 68(2), 341-350.

Sen, S., Bhattacharya, C. B., & Korschun, D. (2006). The role of corporate social responsibility in strengthening multiple stakeholder relationships: A field experiment. Journal of the Academy of Marketing Science, 34(2), 158-166. Surroca, J., Tribó, J. A., & Waddock, S. (2010). Corporate responsibility and financial

performance: The role of intangible resources. Strategic Management Journal, 31(5), 463-490.

Tonkiss, F., & Passey, A. (1999). Trust, confidence and voluntary organisations: Between values and institutions. Sociology, 33(2), 257-274.

Tukey, J. W. (1962). The future of data analysis. The Annals of Mathematical Statistics, 33(1), 1-67.

Ullman, A. (1985). Data in search of a theory: A critical examination of the relationships among social performance, social disclosure, and economic performance of U.S. firms.10, 540-557.

Van Beurden, P., & Gössling, T. The worth of values – A literature review on the relation between corporate social and financial performance.82(407)

Vance, S. (1975). Are socially responsible corporations good investment risks? 64(8), 18-24. Waddock, S. A., & Graves, S. B. (1997). The corporate social performance–financial

performance link. Strategic Management Journal, 18(4), 303-319.

Walsh, G., & Beatty, S. E. (2007). Customer-based corporate reputation of a service firm: Scale development and validation.35(1), 127-143.

(32)

32

APPENDIX

Table A1. Representation of countries and their legal origin

ISO Country Number of

observations

Legal origin Law High/Low

expected CSR

AT Austria 1 German Civil High

BE Belgium 3 French Civil High

BM Bermuda 4 English Common Low

CA Canada 67 English Common Low

CH Switzerland 14 German Civil High

CY Cyprus 1 English Common Low

DE Germany 14 German Civil High

DK Denmark 3 Scandinavian Civil High

ES Spain 4 French Civil High

FI Finland 5 Scandinavian Civil High

FR France 22 French Civil High

GB United Kingdom 49 English Common Low

GR Greece 4 French Civil High

HU Hungary 1 Socialist Socialist Low

IE Ireland 6 English Common Low

IT Italy 6 French Civil High

JE Jersey 1 English Common Low

LU Luxembourg 1 French Civil High

NL Netherlands 10 French Civil High

NO Norway 7 Scandinavian Civil High

PL Poland 4 Socialist Socialist Low

PT Portugal 3 French Civil High

RU Russian Federation 12 Socialist Socialist Low

SE Sweden 11 Scandinavian Civil High

UA Ukraine 1 French Civil High

The influence of CSR on CFP in different industries: a competitive position perspective