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CSR Structures: Evidence, Drivers, and Firm Value Implications

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Abstract

This paper investigates the corporate social responsibility (CSR) structures of U.S. listed firms. We find evidence of a general tendency towards CSR specialization with almost three-quarters (73.91%) of these firms focusing on a single CSR dimension. The degree of specialization varies across industries and the single CSR dimension focused on also varies for industries with similar degrees of specialization. We find that firms with higher exposures to CSR concerns, international activities, larger size, and higher financial slack tend to diversify across multiple CSR dimensions. More importantly, we find evidence that diversified CSR structures positively affect a firm’s value relative to a control group before and during the 2008 financial crisis. Our findings have important implications for corporate and portfolio managers, investors, and policy makers.

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Notes

  1. Also, a 2014 report in the Financial Times shows that the Fortune Global 500 companies devote more than $15.2 billion a year on CSR activities (The Financial Times Limited, 2020).

  2. A similar methodology is used by Colla et al. (2013) and John et al. (2021) who studied firm debt structures in the U.S. and internationally.

  3. According to Lin-Hi and Müller (2013), corporate social “irresponsibility” (CSI) can be defined as “corporate actions that result in (potential) disadvantages and/or harm to other actors.”

  4. In the same vein, policy makers design regulations for specific industries or sectors.

  5. The materiality of CSR activities also depends on the industry where a firm is operating (Ioannou & Serafeim, 2019; Khan et al., 2016).

  6. We compute the adjusted Entropy so that it yields the same directional interpretation as the HHI index so that high (low) values indicate specialization (diversification).

  7. As another alternative measure of CSR specialization, we follow Colla et al. (2013) and John et al. (2021) and compute a dummy variable Sup90 which equals one if a firm obtains at least 90% of its CSR from one CSR dimension and zero otherwise. A value of one indicates that the firm is highly concentrated in its CSR structure. All the obtained results are qualitatively similar to those with HHI and Entropy measures.

  8. We compute the percentage of the firms which rely on each CSR dimension for their CSR engagement and find that 54.52% and 42.37% use, respectively, the diversity and employee relations dimensions. Also, an important share of the firms, which is 27.87%, 23.04%, 20.55%, and 16.11%, use, respectively, the environment, governance, community, and product dimensions to structure their CSR actions. Finally, few (almost 2%) of the firms in the sample rely on the human rights dimension for their CSR. The inclusion of this dimension tends to understate the measures of specialization. Overall, firms are different in their usage of the seven CSR dimensions and thereby present various CSR structures.

  9. For the identification of clusters, we use the Stata command cluster kmeans with clusters defined over all seven CSR dimensions simultaneously and run kmeans for up to 15 clusters. We then apply a stopping rule based on the Calinski/Harabasz index.

  10. These results are robust to different specifications of the conditioning threshold. In appendix 4, we provide the findings when the conditioning threshold is 40% and 50%.

  11. The detailed definition of the 17 industries is available at: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.

  12. We also run probit regressions using the clusters that we have already defined. Our dichotomic-dependent variables are computed based on firm membership in the six specialized clusters of CSR dimensions (Product, Diversity, Governance, Employees, Community, and Environment). We also define the baseline comparison group using the set of our three diversified CSR clusters already computed. The findings are provided in Appendix 3. Except for the community CSR dimension, Size negatively, and significantly drives CSR specialization which is consistent with our Hypothesis H5 [Larger (smaller) firms are expected to have more diversified (specialized) CSR structures]. International operations are found to negatively and significantly drive CSR specialization in Diversity and Employee relations in support of our Hypothesis H3 [Firms with international (domestic) activities are expected to have more diversified (specialized) CSR actions].

  13. Our testing strategy is similar to that of Bushanan, Cao and Chen (2018) who examine how Corporate Social Responsibility, jointly with influential institutional ownership, affects firm value around the 2008 financial crisis.

  14. Additional tests show that the CSR ratings of firms in the extractive industries changed following the BP Deepwater disaster shock. As expected, the ratios in the parentheses of Eq. (1) decreased for these firms' Environment and Product dimensions, and increased mechanically for these firms' Governance and Human rights dimensions.

  15. Results for an Euclidian distance clustering analysis based on CSR dimensions ratios (CSR specialization measure) are reported in Appendix 1 (2).

  16. This lagged modeling specification should further alleviate somewhat the concerns associated with endogeneity biases. A similar argument is used in the corporate governance literature (e.g., Adams et al., 2009; Jiraporn et al., 2009; Kryzanowski & Mohebshahedin, 2016).

  17. (β1 + β2) = 0.2727 − 0.1921 = 0.0806.

  18. We also use our subsample of diversified CSR structures and integrate two interactions of CSR dimensions indicators (Employee-Product and Product-Environment) to capture their effects on Tobin’s Q. The findings are reported in Appendix 5 (Firm value and CSR structures: CSR dimensions combinations). They are supportive of the finding of Cavaco and Crifo (2014) that environment and business behaviors towards customers and suppliers are substitutable.

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Acknowledgements

The authors would like to thank two anonymous referees and the participants to the Administrative Sciences Association of Canada (ASAC) 2022 conference in particular Amos Sodjahin (discussant), and Hyeonjoon Park for their valuable comments and suggestions. Kryzanowski thanks the Senior Concordia University Research Chair in Finance and the Social Sciences and Humanities Research Council of Canada (SSHRC, Grant #435-2018-048) for providing financial support for this project. We thank Jamal Ouenniche for his help with Matlab programming. An earlier version of this article won the best paper award for the finance division at the Administrative Sciences Association of Canada (ASAC) 2022 conference.

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Appendices

Appendix 1

Cluster analysis on CSR dimensions ratios.

Cluster

Governance

Community

Diversity

Environment

Product

Human Rights

Employee

HHI

Cluster 1

0.999

0.000

0.000

0.000

0.000

0.000

0.001

0.999

Cluster 2

0.001

0.001

0.002

0.002

0.002

0.000

0.992

0.985

Cluster 3

0.002

0.006

0.980

0.002

0.005

0.000

0.005

0.965

Cluster 4

0.010

0.007

0.015

0.934

0.007

0.005

0.022

0.897

Cluster 5

0.040

0.006

0.073

0.069

0.806

0.001

0.006

0.766

Cluster 6

0.020

0.664

0.156

0.079

0.049

0.004

0.029

0.573

Cluster 7

0.419

0.015

0.408

0.088

0.024

0.010

0.036

0.360

Cluster 8

0.060

0.082

0.060

0.190

0.107

0.029

0.472

0.347

Cluster 9

0.027

0.096

0.450

0.138

0.044

0.005

0.241

0.290

All

0.138

0.075

0.356

0.133

0.064

0.006

0.228

0.689

Appendix 2

Cluster analysis on CSR dimensions ratios and CSR specialization (HHI).

Cluster

Governance

Community

Diversity

Environment

Product

Hum Rights

Employee

HHI

2

0.000

0.000

0.999

0.000

0.000

0.000

0.001

0.998

3

0.003

0.001

0.002

0.991

0.001

0.000

0.002

0.984

5

0.999

0.000

0.000

0.000

0.000

0.000

0.001

0.999

6

0.018

0.834

0.024

0.011

0.045

0.062

0.006

0.859

7

0.001

0.007

0.000

0.008

0.976

0.000

0.008

0.962

8

0.000

0.000

0.000

0.002

0.001

0.000

0.996

0.993

1

0.115

0.127

0.561

0.036

0.058

0.003

0.098

0.391

4

0.051

0.078

0.232

0.048

0.090

0.005

0.496

0.361

9

0.077

0.110

0.185

0.356

0.079

0.015

0.177

0.255

All

0.138

0.075

0.356

0.133

0.064

0.006

0.228

0.689

Appendix 3

Firm characteristics and CSR specialization: logistic regressions on CSR dimensions specialized clusters.

Dimension of specialization

PRO

DIV

GOV

EMP

COM

ENV

(1)

(2)

(3)

(4)

(5)

(6)

CSR concerns

 − 0.016

 − 0.054***

0.059*

 − 0.020

 − 0.036

0.011

(0.513)

(0.001)

(0.054)

(0.266)

(0.103)

(0.577)

International

0.075

 − 0.354***

 − 0.327*

 − 0.456***

0.045

 − 0.095

(0.604)

(0.000)

(0.069)

(0.000)

(0.694)

(0.457)

Size

 − 0.226***

 − 0.107***

 − 0.578***

 − 0.211***

 − 0.007

 − 0.216***

(0.000)

(0.000)

(0.000)

(0.000)

(0.834)

(0.000)

Cash-flows

 − 0.593*

 − 0.246

 − 0.111

 − 0.134

 − 0.294

0.086

(0.095)

(0.422)

(0.806)

(0.624)

(0.439)

(0.842)

Leverage

0.346

0.572***

0.051

0.473***

0.546***

0.530**

(0.174)

(0.001)

(0.848)

(0.005)

(0.009)

(0.014)

Profitability

0.321

 − 0.406

 − 0.182

0.171

0.496

 − 1.317***

(0.563)

(0.236)

(0.711)

(0.583)

(0.308)

(0.008)

R&D intensity

 − 1.692**

 − 2.028***

 − 1.824***

 − 0.191

 − 3.884***

 − 4.532***

(0.043)

(0.000)

(0.002)

(0.599)

(0.000)

(0.000)

Constant

 − 0.060

 − 0.706**

1.821***

0.826***

 − 1.941***

0.653**

(0.868)

(0.017)

(0.000)

(0.003)

(0.000)

(0.039)

Observations

4 798

6 656

5 094

5 536

5 113

5 096

Pseud R2

0.126

0.216

0.403

0.116

0.122

0.183

Industry FE

Yes

Yes

Yes

Yes

Yes

Yes

Year FE

Yes

Yes

Yes

Yes

Yes

Yes

  1. This table presents the regression results for the relation between firm characteristics and CSR specialization using CSR dimension specialized subsamples. All variables are defined in the legend of Table 1. In all regression models, control variables are one-year lagged. All regressions control for firm industry membership. All continuous variables are winsorized at the 1st and 99th percentile. P values are reported in the parentheses. Heteroskedasticity-consistent standard errors are clustered at the firm level. ***, **, * denote statistical significance at 1%, 5%, and 10% levels, respectively

Appendix 4

CSR structures and specialization: additional tests.

Condition

GOV

COM

DIV

ENV

PRO

HUM

EMP

Panel A: Conditional CSR structures (40%)

 Governance > 40%

0.855

0.005

0.081

0.017

0.013

0.002

0.028

 Community > 40%

0.014

0.661

0.152

0.063

0.027

0.001

0.082

 Diversity > 40%

0.039

0.043

0.775

0.035

0.019

0.001

0.088

 Environment > 40 %

0.028

0.032

0.077

0.733

0.031

0.003

0.095

 Product > 40%

0.030

0.027

0.057

0.053

0.731

0.001

0.101

 Hum Rights > 40%

0.065

0.006

0.035

0.103

0.007

0.720

0.063

 Employee > 40%

0.019

0.026

0.109

0.064

0.039

0.002

0.741

Panel B: Conditional CSR structures (50%)

 Governance > 50%

0.998

0.000

0.001

0.000

0.000

0.000

0.001

 Community > 50%

0.001

0.931

0.038

0.014

0.006

0.000

0.010

 Diversity > 50%

0.010

0.019

0.924

0.008

0.007

0.001

0.032

 Environment > 50%

0.008

0.005

0.015

0.941

0.006

0.001

0.024

 Product > 50%

0.001

0.007

0.000

0.008

0.976

0.000

0.008

 Hum Rights > 50%

0.000

0.000

0.000

0.000

0.000

0.980

0.020

 Employee > 50%

0.004

0.007

0.022

0.028

0.015

0.001

0.923

  1. This table presents the results of conditional CSR structures. We impose the condition that a firm’s involvement in a particular CSR dimension must exceed 40% (50%) of total CSR actions in Panel A (B). For the set of observations that satisfy this condition, we then compute the mean ratios of each CSR dimension

Appendix 5

Firm value and CSR structures: CSR dimensions combinations.

 

Diversified structures

Based on HHI

Based on Entropy

EMP*PRO

0.1096

0.2565

(0.713)

(0.370)

PRO*ENV

 − 0.6655*

 − 0.5704*

(0.065)

(0.084)

PRO

0.6366**

0.3801

(0.029)

(0.159)

ENV

0.0290

0.0271

(0.773)

(0.801)

EMP

0.1222

0.0874

(0.257)

(0.473)

Size

 − 0.0822**

 − 0.0947**

(0.031)

(0.022)

Leverage

 − 0.9973**

 − 1.0280***

(0.011)

(0.008)

Cash holdings

0.7889**

0.8339*

(0.032)

(0.076)

R&D intensity

4.5289***

4.7736***

(0.000)

(0.000)

Capital expenditure/book asset

0.9800

0.6850

(0.256)

(0.476)

Advertising intensity

2.1034

2.6572

(0.150)

(0.118)

Sales growth rate

0.6852*

0.6572*

(0.053)

(0.075)

Fixed assets/book assets

0.1616

0.2011

(0.596)

(0.489)

Profitability

3.4034***

3.3718***

(0.002)

(0.002)

Constant

2.2983***

2.4330***

(0.000)

(0.000)

Observations

625

625

Adj. R-squared

0.419

0.428

Industry FE

Yes

Yes

  1. This table presents regression results for the relation between combinations of Tobin’s Q and CSR dimensions. EMP, PRO, and ENV are indicators of firm engagement in Employee relations, Product, and Environment CSR dimensions, respectively. FF17_2 is the dummy variable indicating that mining and minerals industry, and FF17_3 is the dummy variable indicating the oil and petroleum products industry. The definitions of the remaining industries are provided in the first two columns of Table 9. All the other variables are defined in the legend of Table 1. In all regression models, control variables are one-year lagged. All regressions control for firm industry membership. All continuous variables are winsorized at the 1st and 99th percentile. P values are reported in the parentheses. Heteroskedasticity-consistent standard errors are clustered at the firm level. ***, **, * denote statistical significance at 1%, 5%, and 10% levels, respectively

Appendix 6

Firm characteristics and CSR specialization: industry dummies.

 

HHI

Entropy

CSR concerns

 − 0.011***

 − 0.011***

(0.000)

(0.000)

International

 − 0.080***

 − 0.069***

(0.000)

(0.000)

Size

 − 0.069***

 − 0.057***

(0.000)

(0.000)

Cash-flows

 − 0.088*

 − 0.079**

(0.092)

(0.037)

Leverage

0.103***

0.087***

(0.000)

(0.000)

Profitability

 − 0.054

 − 0.034

(0.339)

(0.404)

R&D intensity

 − 0.410***

 − 0.323***

(0.000)

(0.000)

FF17_2

0.156***

0.134***

(0.003)

(0.001)

FF17_3

0.161***

0.142***

(0.000)

(0.000)

FF17_4

0.056

0.043

(0.295)

(0.335)

FF17_5

0.065

0.049

(0.205)

(0.258)

FF17_6

0.051

0.053

(0.254)

(0.138)

FF17_7

0.107**

0.077**

(0.011)

(0.027)

FF17_8

0.050

0.051

(0.259)

(0.146)

FF17_9

0.141**

0.107**

(0.030)

(0.046)

FF17_10

0.053

0.054

(0.328)

(0.179)

FF17_11

0.050

0.049*

(0.138)

(0.080)

FF17_12

0.155***

0.131***

(0.001)

(0.000)

FF17_13

0.110***

0.099***

(0.004)

(0.002)

FF17_15

0.094**

0.077**

(0.011)

(0.012)

FF17_17

0.107***

0.090***

(0.001)

(0.001)

Constant

1.123***

1.155***

(0.000)

(0.000)

Observations

10,144

10,144

Adj. R-squared

0.227

0.266

Industry FE

Yes

Yes

Year FE

Yes

Yes

  1. This table presents regression results for model 3 and 4 of Table 6 on the relation between firm characteristics and CSR specialization. In this Table, we provide the estimates of industry dummies coefficients. All variables are as defined in the notes to Table 6. All right-hand side variables are lagged one-year. All specifications control for industry fixed effects and year fixed effects. Heteroskedasticity-consistent standard errors are clustered at the firm level. All the continuous variables are winsorized at the first and the 99th percentile. P values are reported in the parentheses. ***, **, * denote statistical significance at 1%, 5%, and 10% levels, respectively

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Bouslah, K., Hmaittane, A., Kryzanowski, L. et al. CSR Structures: Evidence, Drivers, and Firm Value Implications. J Bus Ethics 185, 115–145 (2023). https://doi.org/10.1007/s10551-022-05219-6

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