Can social disclosure induce a better corporate social performance?

Abstract

Against the background of the debate on the social reporting-social performance link, this article aims to analyse the influence of social disclosures on social performance. Specifically, we analyse the effect of the voluntary disclosure of standardised indicators regarding labour practices and human rights on corporate social performance. A Tobit regression was used on data obtained through content analysis for a sample of 1,243 multinational enterprises for the period 2013–2017. The results show that both total and partial disclosure of the performance indicators are positively associated with higher social performance, confirming that the disclosure of such indicators is oriented towards the improvement of corporate sustainability as opposed to impression management strategies. We demonstrate that, even though companies may aim to satisfy stakeholder demands through the voluntary disclosure of labour practices, decent work and human rights indicators, these indicators can also act as catalysts for strengthening corporate social policies and practices. The findings provide a further motive to promote social reporting: its positive impact on corporate social performance favouring responsive labour management and greater social cohesion.

Keywords:

• Social reporting
• social performance
• labour practices and decent work
• human rights
• corporate social responsibility

JEL CODES:

• M14; M12; M49

1. Introduction

Society’s growing attention to companies’ working conditions and respect for human rights has led firms to voluntarily implement policies and practices aimed at both enhancing their employees’ working conditions and quality of life and at disclosing information about these issues (Parsa et al., 2018; Searcy et al., 2016). Prior research has stressed the relationship between employee-related disclosure and the significance firms place on human resources management practices (Vuontisjärvi, 2006; Fachada et al., 2022). Based on the premise that ‘where there is limited concern, there will be limited disclosure’ (Deegan et al., 2002, p. 335), the type and volume of employee-related information disclosed in corporate reports have been regarded as an indicator of a company’s efforts to improve its employees’ well-being (Wang et al., 2018; Gonçalves et al., 2021).

The relationship between corporate social disclosure and corporate social performance has been the subject of extensive research attention (García-Sánchez, 2021) with mixed findings (van der Laan, 2009; Koseoglu et al., 2021). However, most studies have focussed on the impact of social performance on social reporting whereas the reversed relationship (i.e., the effect of social reporting on social performance) has been less studied. This article aims to fill this gap in literature by analysing the influence of social disclosure on the reporting entity’s performance regarding labour practices, decent work, and human rights (LA&HR). Specifically, we seek to determine the effect of the disclosure of standardised non-financial information regarding LA&HR on corporate social performance.

As pointed out by Koseoglu et al. (2021), ‘the relationship between CSR performance and CSR reporting is controversial’, as companies can use disclosures for different objectives, from showing their good performance to stakeholders (i.e., signalling purposes) to using disclosure as an impression management strategy (i.e., greenwashing purposes). This study aims to contribute to the ongoing debate on the social reporting-performance link by analysing the less studied side of such a relationship and, thus, answer the following question: can social disclosure induce a better corporate social performance?

In order to answer this research question, a Tobit regression is used on data obtained through content analysis for a sample of 1,243 multinational enterprises for the period 2013–2017 (5,693 observations). The findings indicate that disclosure of all LA&HR performance indicators proposed by GRI + UN + SDG Compass is positively associated with higher LA&HR performance. Additionally, given that the most sustainable companies are those that disclose all LA&HR performance indicators proposed by GRI + UN + SDG Compass, we also analyse the impact of total versus partial disclosure of LA&HR indicators on social performance and whether this effect differs among more or less responsible companies. We find that 54.41% of the companies that fully disclose LA&HR indicators present an above-average performance in terms of LA&HR.

This research contributes to the literature by showing that disclosure of LA&HR indicators translates into actual improvements in a company’s social performance. Thus, we contribute to the open debate on whether and how corporate social responsibility (CSR) reporting affects CSR performance (Gray, 2006) by showing that both total and partial disclosure of LA&HR indicators yield tangible improvements in LA&HR performance. Furthermore, our findings provide support to the positive role played by social reporting in both improving employees’ well-being and enhancing social cohesion suggested by other researchers (Cahaya et al., 2015; Searcy et al., 2016), as opposed to its use in impression management strategies.

Furthermore, our focus on social reporting provides additional value to this study. Although human and labour rights have attracted increasing interest from researchers and policymakers over the last decades (Calabrese et al., 2018; Aibar-Guzmán et al., 2023), few studies have specifically focussed on social reporting (Monteiro et al., 2021) and, to the authors’ knowledge, no study has analysed the impact of LA&HR disclosure on social performance. Thus, this is the first empirical study that investigates the performance consequences of LA&HR reporting. Nevertheless, as Burns and Jollands (2020) contend, this kind of research ‘is required not because it is novel, but because of the large inequities within our societies, because the vulnerable exist, and because this has consequences for us all’ (p. 529).

This article contains five sections. The next section presents the theoretical background and the study’s main hypothesis. The third section sets out the study’s empirical framework, after which the findings are presented and discussed, along with some complementary analysis. In the fifth section, the main conclusions of the study are drawn, the implications of the findings are discussed, and some topics for future research are suggested.

2. Theoretical framework and hypothesis

The relationship between CSR disclosure and CSR performance has been extensively investigated (García-Sánchez, 2021), although most studies have focussed on the impact of CSR performance on CSR reporting. These studies have used a broad range of theories to explain the reasons behind the disclosure-performance link (Zyznarska-Dworczak, 2018), albeit they share a common idea: firms engage in voluntary non-financial reporting as ‘part of a calculated’ strategy (Thorne et al., 2017, p. 87), with an external focus. Thus, from the perspective of economics-based theories of disclosure (e.g., signalling theory, voluntary disclosure theory, proprietary costs theory, and theory of the expected utility), some authors contend that firms with superior performance are inclined to disclose more information to obtain competitive advantages in terms of enhanced reputation (Monteiro et al., 2022). Through reporting good social performers would look for signalling this fact to differentiate themselves from poor social performers, so that a positive association between social performance and social reporting is expected (Clarkson et al., 2008; Birjandi et al., 2015; Koseoglu et al., 2021). Conversely, based on socio-political theories of disclosure (e.g., legitimacy theory), other authors consider that voluntary social disclosure can be used as an impression management tool through which poor performers aim to influence stakeholders’ perceptions, resulting in a negative association between social performance and social reporting (Clarkson et al., 2011).

The effect of CSR reporting on CSR performance has been less studied, although several authors (e.g., Searcy et al., 2016; Orazalin & Baydauletov, 2020) have highlighted the positive effect that social disclosures may have on social performance, favouring respect for human rights and the implementation of human resource management practices that improve work environment and workers’ quality of life. From the stakeholder theory’s perspective, CSR disclosure is deemed as part of stakeholder dialogue through which firms seek to respond to their stakeholders’ requests and concerns (Freeman, 1984). Thus, stakeholder pressure would lead firms not only to enhance corporate transparency (García-Sánchez et al., 2019), but also to include social and environmental objectives in their planning processes and develop indicators to measure and control their achievement (Vurro & Perrini, 2011), as well as allocating additional resources to CSR activities (Thorne et al., 2017).

The influence of external reporting on managerial decision making was explained by Prakash and Rappaport (1977, p. 29) based on information inductance, defined as ‘the complex process through which the behaviour of an information sender is influenced by the information he is required to communicate’. Thus, anticipating the impact of corporate disclosures on stakeholders’ behaviour and its potential consequences to the firm, management may choose to modulate the disclosures with the aim of offering a desirable picture of the firm’s performance by engaging in impression management strategies or, alternatively, management may make decisions aimed at adjusting the firm’s performance to the desirable picture they want to offer, so that external reporting would induce changes in actual performance (Prakash & Rappaport, 1977; Covaleski et al., 1987; Collison et al., 2003).

This information inductance effect extends to any form of corporate reporting (Collison et al., 2003), including social and environmental reporting (Gray, 2006; van der Laan, 2009). Through information inductance effect, CSR disclosures would affect the importance placed by management on environmental and social issues (Dey, 2003), which in turn might lead to improved CSR performance (Gray, 2006). In other words, by giving visibility to social issues, social reporting may promote awareness among managers and the adoption of actions to improve performance in this regard (Burns & Jollands, 2020). Accordingly, quality reporting could lead to improved performance (Wang et al., 2018). As a result, besides being an external communication mechanism, CSR reports also play an important role in supporting management decision making (Vuontisjärvi, 2006), allowing firms to strengthen their in-house CSR capabilities (García-Sánchez et al., 2019), and leading to improved CSR performance (Vurro & Perrini, 2011).

Prior research has stressed the potential of social reporting in promoting the implementation of human resource policies and practices that foster employees’ physical and psychological well-being and respect for human rights (Jain et al., 2011). Vurro and Perrini (2011) found that CSR performance is positively associated with the breadth of disclosure, though they failed to find a significant relationship between CSR performance and the volume of disclosure. Similarly, Muslu et al. (2019) showed that good CSR performers issue more informative CSR reports. Searcy et al. (2016) explicitly referred to the information inductance effect as a potential reason behind the positive influence of social disclosures on corporate social performance.

However, Searcy et al. (2016) warm that the fact of companies not disclosing complete and comprehensive social indicators (Vuontisjärvi, 2006), along with the inconsistency and diversity of the disclosed indicators (Evangelinos et al., 2018), could hamper social disclosure comparability (Czaja-Cieszyńska et al., 2021) as well as the potential for social disclosures to transform into actual improvements in social performance. In this sense, the adoption of a disclosure strategy based on the indicators proposed by widely accepted reporting frameworks, such as the Global Reporting Initiative (GRI) guidelines, could not only enhance the comparability of the disclosed information, thus making it more useful to external stakeholders, but would also provide management with an improved informative basis for internal decision making (García-Sánchez et al., 2019).

Based on the above discussion, we posit that social disclosure can boost the implementation of more responsible business practices regarding issues related to LA&HR (Christensen et al., 2013; Searcy et al., 2016), leading to actual improvements in social performance. Therefore, the following hypothesis is stated:

Full disclosure of LA&HR indicators encourages more responsible business practices regarding LA&HR-related issues, leading to improved LA&HR performance.

3. Methodology

3.1. Population and sample

To test the hypothesis proposed in this study, the target population was selected as the largest listed multinationals whose information is available on the Thompson Reuters EIKON database. Subsequently, the companies that disclose non-financial information on the social and environmental impact of their activity in a sustainability report, integrated report or any other information format or statement were identified, removing those that did not present the information that we needed to estimate the proposed empirical model. As a result, the final sample corresponds to an unbalanced data panel consisting of 5,693 observations corresponding to 1,243 companies for the period 2013–2017. This period was determined by the availability of the companies’ corporate reports on their websites, because it is necessary to measure, using content analysis, the information disclosed in relation to labour practices and decent work (LA) and human rights (HR). We use an unbalanced data panel because, due to the availability of information in the database on the different variables included in the model, throughout the study period not all the companies included in the sample present the same number of observations.

Table 1 shows the frequencies that define the sample’s composition by sector, country, and period. In this respect, it can be seen that, although the distribution over time is rather homogeneous, there is a geographical bias towards countries such as the USA and Japan. At sectoral level, firms operating in Industry and Financial and Real Estate sectors stand out. These sample characteristics are like those of previous studies and are a consequence of its selection being based on criteria that are representative of the international business fabric (e.g., García-Sánchez et al., 2020a).

Table 1. Sample description.

Panel A: Geographical distribution
Country	%	Country	%	Country	%
Australia	3.57	India	2.02	Poland	0.49
Austria	0.21	Indonesia	0.63	Portugal	0.33
Belgium	0.74	Ireland	0.54	Qatar	0.11
Brazil	2.39	Israel	0.33	Russia	1.09
Canada	4.11	Italy	1.42	Saudi Arabia	0.07
Chile	0.40	Japan	13.84	Singapore	0.74
China	3.32	Jersey	0.05	South Africa	6.73
Colombia	0.40	Korea (South)	3.67	Spain	1.62
Czech Republic	0.11	Kuwait	0.07	Sweden	1.86
Denmark	1.26	Luxemburg	0.32	Switzerland	2.18
Finland	1.67	Malaysia	1.16	Taiwan	5.23
France	4.02	Mexico	0.88	Thailand	1.09
Germany	3.30	Netherlands	1.00	Turkey	0.51
Greece	0.46	New Zealand	0.21	United Kingdom	9.13
Hong Kong	2.32	Norway	0.83	United States	12.77
Hungary	0.16	Philippines	0.63
Panel B: Sectoral distribution				Panel C: Temporal distribution
Sector	%			Year	%
Oil and Gas	5.39			2013	18.62
Basic Materials	13.02			2014	20.97
Industry	21.52			2015	20.17
Consumer goods	13			2016	21.83
Health	4.06			2017	18.41
Consumer services	10.05
Telecommunications	2.97
Public services	5.66
Financial and Real State	19.09
Technology	5.25

Source: Authors’ calculations.

3.2. Empirical models, variables, and method

To test the proposed hypothesis, we designed the model set out in Equation (1)(1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1) . This equation was designed to identify the effect of the independent variable, LA&HR_Disclt-1, on the variable LA&HR_Perf, including the necessary control variables to avoid biased results and the one-period lagged endogenous variable, LA&HR_Perft-1. (1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1)

The dependent variable, LA&HR_Perf, is a score that takes values between 0 and 16, from the sum of the items related to labour practices and decent work (LA) and human rights (HR) depicted in Table 2 (Panel B). These items were selected considering both the usual CSR practices developed by companies and those related to the Sustainable Development Goals (SDG) set out in the United Nations’ 2030 Agenda that companies have begun to implement (García-Sánchez et al., 2020b; Monteiro et al., 2022). The creation of the score through the sum of different items is free of bias and presents the same effectiveness as other calculation approaches (Amor-Esteban et al., 2020).

Table 2. Variable description.

Panel A. Indicators of LA&HR_Discl
LA1. Total number and rates of new employee hires and employee turnover by age group, gender and region LA2. Benefits provided to full-time employees that are not provided to temporary or part-time employees LA3. Return to work and retention rates after parental leave, by gender LA4. Minimum notice periods regarding operational changes LA5. Representation on health and safety committees LA6. Injuries, occupational diseases, and work-related fatalities LA7. Workers with high incidence or high risk of diseases related to their occupation LA8. Health and safety topics covered in formal agreements with trade unions LA9. Average hours of training per employee by gender and by employee category LA10. Programs for skills management and lifelong learning that support the continued employability of employees and assist them in managing career endings LA11. Percentage of employees receiving a regular performance appraisal and career development review, by gender and by employee category LA12. Composition of governance bodies and breakdown of employees per employee category according to gender, age group, minority group membership, and other indicators of diversity LA13. Ratio of basic salary and remuneration of women to men by employee category, by significant locations of operation LA14. Percentage of new suppliers that were screened using labour practices criteria LA15. Significant actual and potential negative impacts for labour practices in the supply chain and actions taken by the firm
HR3. Total number of incidents of discrimination and actions taken by the firm
HR4. Operations and suppliers identified in which the right to exercise freedom of association and collective bargaining may be violated, and measures taken to support these rights
HR5. Operations and suppliers identified as having significant risk for incidents of child labour, and measures taken to contribute to the effective abolition of child labour
HR6. Operations and suppliers at significant risk for incidents of forced or compulsory labour, and measures to contribute to the elimination of all forms of forced or compulsory labour
HR7. Percentage of personnel trained in the organization’s human rights policies
HR8. Total number of incidents of violations involving indigenous people’s rights and actions taken by the firm
HR12. Number of grievances about human rights impacts filed, addressed, and resolved
Panel B. Items of LA&HR_Perf
KPIs1. The company claims to provide flexible working hours or programs that promote a work–life balance KPIs2. The company has a diversity and equal opportunity policy KPIs3. The company has a policy for maintaining a well-balanced membership of the board KPIs4. The company claims to favour promotion from within KPIs5. The company has a policy to support the skills training or career development of its employees KPIs6. The company has a competitive employee benefits policy or ensure good employee relations within its supply chain and the company has a policy for maintaining long-term employment growth and stability KPIs7. The company has a policy to improve employee health & safety within the company and its supply chain KPIs8. The company reports on policies or programs on HIV/AIDS for the workplace or beyond KPIs9. The company claims to provide its employees with a pension fund, health care, or other insurance KPIs10. The company claims to provide a bonus plan to most employees KPIs11. The company claims to provide day care services for its employees
KPIs12. The company reports or show to use human rights criteria in the selection or monitoring process of its suppliers or sourcing partners
KPIs13. The company has a policy to guarantee the freedom of association universally applied independent of local laws and the company has a policy for the exclusion of child, forced, or compulsory labour KPIs14. The company shows to be ready to end a partnership with a sourcing partner if human rights criteria are not met
KPIs15. The company has a policy to respect business ethics –ethics code, codes of conducts, compliance policies, etc.– or has signed the UN Global Compact or does it follow the OECD guidelines
KPIs16. The company has a commitment towards being a good citizen or endorse the Global Sullivan Principles
Panel C. Control variables
Female_Managers Size ROA Leverage Internatio	Cash Dloss Accruals Cov_Ana B_Indep	CSR_Comm B_Women DLawsuits NCSRPI	ICSRPI. Country Industry Year

Source: Authors’ calculations.

The independent variable, LA&HR_Discl, is a dummy variable which takes the value 1 if the firm discloses all LA&HR indicators proposed by the GRI + UN + SDG Compass, and 0 otherwise. A similar approach has been used by García-Sánchez et al. (2020a) for the analysis of the disclosure of information on gender issues. This variable has been lagged by one period because, as noted by Prakash and Rappaport (1977), sometimes the changes in performance derived from external reporting may need a long time to reach material dimensions. Vurro and Perrini (2011) followed a similar approach. Panel A in Table 2 summarises the LA&HR indicators that have been considered.

To avoid biased results, following previous literature (e.g., Koseoglu et al., 2021; Monteiro et al., 2022; García-Benau et al., 2022), several control variables were included (Table 2, Panel C), which identify the company’s size measured by the logarithm of assets (Size), its economic profitability (ROA), and the level of leverage with respect to total assets (Leverage). The level of internationalisation of a firm (Internatio) is identified by the percentage of investments in assets made in other countries. Cash refers to liquid money and other means that can be readily available for use; DLoss is a dummy variable that takes the value 1 if the business obtained losses in the financial year; and Accruals represents total accruals scaled by cash flow from operations. Cov_Ana identifies the number of analysts following the company; CSR_Comm corresponds to a dummy variable that takes value 1 if there is a CSR committee on the board of directors; B_Indep represents the independence of the board through the percentage of independent directors; B_Women reflects the percentage of female directors on the board; and Female_Managers represents the management team diversity through the percentage of female managers. DLawsuits is a dummy variable that takes value 1 if the company operates in hospitality, technology, and oil and gas as lawsuit-prone industries (Dadanlar & Abebe, 2020), and 0 otherwise. Institutional pressures at the country and sector level are controlled by using the indicators proposed by Amor-Esteban et al. (2018, 2019): NCSRPI and ICSRPI. Additionally, we control the effect of country, industry, and time using the Country, Industry and Year variables.

Finally, in Equation (1)(1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1) , η controls unobservable heterogeneity and ε denotes the disturbance. Given the censored nature of the dependent variable (LA&HR_Perf), a Tobit regression for panel data will be used. To correct for potential causality problems, the control variables are lagged by one period.

4. Results

4.1. Descriptives and correlations

Table 3 presents the descriptive statistics for the variables proposed for the empirical analysis. As can be seen, only 27% of the companies report all LA&HR indicators recommended by GRI + UN + SDG Compass, while 36% of the sample companies partially disclose such indicators. This result is in line with the findings obtained by prior studies on this subject, which also found a low level of disclosures regarding LA&HR indicators (Evangelinos et al., 2018; Parsa et al., 2018; Cahaya & Hervina, 2019; Monteiro et al., 2022).

Table 3. Descriptive statistics.

Variable	%
LA&HR—Full Disclosure	0.27
LA&HR—Partial Disclosure	0.36
DLoss	0.06
CSR_Comm	0.66
Dlawsuits	0.15
Variable	Mean	Std. Dev.
Female_Managers	0.24	0.15
LA&HR_Perf	9.28	2.77
Size	17.99	2.80
ROA	5.12	8.43
Leverage	0.25	0.17
International	0.19	0.24
Cash	11.80	0.66
Accruals	10.83	0.48
Cov_Ana	16.11	9.55
B_Indep	0.46	0.30
B_Women	0.14	0.12
NCSRPI	1.65	8.79
ICSRPI	0.57	3.03

Source: Authors’ calculations.

With regard to business practices in the areas of LA&HR, on average they reach a value of 9.28 out of 16 points. In this regard, prior studies (Vurro & Perrini, 2011; Wang et al., 2018), using data from different databases, document a medium-low value of social performance. Additionally, we observe that the firms’ management teams are unbalanced in terms of gender, as, on average, only 24% of their members are women. Furthermore, there is significant variability, with a standard deviation of 15%. This finding is consistent with prior evidence (Calabrese et al., 2018).

Table 4 shows the bivariate correlations. Based on the value of the coefficients and their significance, we verify that there are no multicollinearity problems between the variables considered in the empirical analysis.

Table 4. Bivariate correlations.

		1	2	3	4	5	6	7	8
1	LA&HR_Discl	1
2	Fema_Mang	−0.02	1
3	LA&HR_Perf	0.39***	0.13***	1
4	Size	0.13***	−0.15***	−0.09***	1
5	ROA	0.01	0.14***	0.06***	−0.11***	1
6	Leverage	0.05***	−0.03	−0.03***	0.02	−0.15***	1
7	Internatio	0.08***	−0.03	0.15***	−0.22***	−0.07***	−0.02	1
8	Cash	0.08***	−0.15***	0.01	0.41***	−0.01	−0.02	−0.09***	1
9	DLoss	0.00	−0.07***	−0.01	−0.04***	−0.30***	0.13***	0.11***	−0.01
10	Accruals	0.00	−0.02	0.00	−0.02	−0.01	−0.02	0.00	0.00
11	Cov_Ana	0.25***	0.07***	0.37***	0.22***	0.05***	−0.05***	0.07***	0.13***
12	B_Indep	−0.03***	0.12***	0.18***	−0.19***	0.05***	0.05***	0.07***	−0.03***
13	CSR_Comm	0.21***	0.02	0.35***	0.03***	0.00	0.03**	0.02	0.00
14	B_Women	0.04***	0.18***	0.27***	−0.22***	0.07***	−0.01	0.03**	−0.10***
15	DLawsuits	0.07***	−0.03*	0.11***	−0.03**	0.05***	−0.08***	0.07***	−0.01
16	NCSRPI	0.04***	0.05***	0.10***	−0.33***	0.00	−0.10***	0.25***	−0.09***
17	ICSRPI	0.06***	−0.48***	0.04***	−0.09***	−0.10***	0.11***	0.17***	0.01
		9	10	11	12	13	14	15	16
9	DLoss	1
10	Accruals	0.00	1
11	Cov_Ana	0.01	−0.02*	1
12	B_Indep	0.01	−0.02	0.13***	1
13	CSR_Comm	0.01	0.02	0.06***	0.04***	1
14	B_Women	−0.04***	0.00	0.05***	0.32***	0.13***	1
15	DLawsuits	0.04***	−0.03**	0.16***	0.08***	0.04***	0.00	1
16	NCSRPI	0.03**	0.02	−0.17***	−0.02	0.05***	0.15***	−0.02*	1
17	ICSRPI	0.10***	0.01	−0.05***	−0.01	0.01	−0.08***	0.05***	−0.07***

(*** p < 0.01, ** p < 0.05, * p < 0.1).

Source: Authors’ calculations.

4.2. Main results

Table 5 presents the results obtained by estimating Equation (1)(1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1) to empirically test the proposed research hypothesis. The first column shows the results of the Tobit estimations, demonstrating that the variable LA&HR_Discl (coeff. = 0.228; p < 0.05) has a positive and statistically significant impact on sustainability practices in terms of LA&HR, controlling for the lagged endogenous variable one period.

Table 5. Basic analysis models.

	LA&HR_Perft	LA_Perft	HR_Perft
	Equation 1(1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1)	Robust 1	Robust 2
	Coeff. (Std.error)	Coeff. (Std.error)	Coeff. (Std.error)
LA&HR_Perft-1	0.759***
	(0.0200)
LA_Perft-1		0.886***
		(0.0117)
HR_Perft-1			0.515***
			(0.0286)
LA&HR_Disclt-1	0.228**
	(0.113)
LA_Disclt-1		0.0497
		(0.0496)
HR_Disclt-1			0.250***
			(0.0853)
Size	0.0436*	0.00947	0.0484**
	(0.0261)	(0.0118)	(0.0199)
ROA	0.00675	0.00349	0.00667
	(0.00731)	(0.00328)	(0.00559)
Leverage	−0.00122	−0.00112	0.00138
	(0.00284)	(0.00128)	(0.00217)
Internatio	0.00191	−0.000400	0.00309**
	(0.00204)	(0.000914)	(0.00156)
Cash	0.000	−6.13e-11	0.000
	(2.04e-10)	(9.16e-11)	(1.56e-10)
DLoss	−0.0718	−0.00816	−0.00814
	(0.252)	(0.113)	(0.193)
Accruals	0.000680	0.000888	−6.54e-05
	(0.00121)	(0.000541)	(0.000921)
Cpv_Ana	0.0167***	0.00296	0.00950**
	(0.00625)	(0.00281)	(0.00461)
B_Indep	−0.000806	−0.000449	−0.000929
	(0.00172)	(0.000770)	(0.00131)
CSRCommittee	−0.625***	−0.146***	−0.160*
	(0.112)	(0.0483)	(0.0911)
B_Women	−0.00402	−0.00138	0.00102
	(0.00452)	(0.00200)	(0.00346)
Female_Manag	0.0121***	0.00408**	0.00479
	(0.00398)	(0.00180)	(0.00302)
Dlawsuits	0.124	0.0145	0.0910
	(0.128)	(0.0576)	(0.0980)
NCSRPI	−0.000522	0.00303	−0.00317
	(0.00614)	(0.00275)	(0.00468)
ICSRPI	0.0510**	0.00600	0.0415**
	(0.0235)	(0.0105)	(0.0178)
Constant	2.689***	1.030***	0.781*
	(0.568)	(0.260)	(0.402)
Industry, country and year controlled
Log Likelihood	−2505.8013	−1470.3176	−2157.2991
p-value	0.000	0.000	0.000

(*** p < 0.01, ** p < 0.05, * p < 0.1).

Source: Authors’ calculations.

The second and third columns in Table 5 present the results for the impact that the disclosure on all LA or HR indicators has on each of these practices, considered individually. In this regard, it can be observed that the previous results are only confirmed for commitments to HR issues (HR_Discl: coeff. = 0.250; p < 0.01), being statistically irrelevant for business practices related to LA (LA_Discl: coeff. = 0.0497; p > 0.10). These results seem to suggest that companies use other types of internal information regarding their responsibilities and actions made in favour of their employees.

4.3. Complementary analyses

According to the descriptive statistics in Table 2, 36% of companies partially disclose the LA&HR indicators proposed by GRI + UN + SDG Compass. Given that, as indicated earlier, according to Prakash and Rappaport (1977), a potential behavioural effect of external reporting on management’s behaviour is the manipulation of the information that is going to be disclosed to offer a desirable image of the firm’s performance, it seems relevant to analyse whether the indicators partially disclosed by companies were selected for their usefulness in internal decision-making processes or, on the contrary, were chosen for impression management purposes with the aim of manipulating stakeholders’ opinion by disclosing only information favourable to the company’s image (Wang et al., 2018).

Therefore, to carry out this complementary analysis, following Parsa et al. (2018), we use an ordinal variable, LA&HR_OrdDiscl, that takes values between 0 and 2, identifying whether the firm does not disclose the LA&HR indicators proposed by the GRI + UN + SDG Compass (0), does so partially (1), or discloses the totality of these indicators (2). In this respect, Panel A in Table 6 shows that the effects of the LA&HR_OrdDiscl variable (coeff.=0.185; p < 0.01) are highly similar to those obtained for the LA&HR_Discl variable in the basic analysis model. These results would lead us to confirm that both total and partial disclosure of LA&HR indicators are oriented towards the improvement of corporate sustainability. In this sense, the fact that partial disclosure of LA&HR indicators has a positive impact on LA&HR performance allows us to reject the possibility of managerial capture through the selective choice of the LA&HR indicators to be disclosed (Clarkson et al., 2008; Thorne et al., 2017).

Table 6. Complementary analyses.

Panel A. Estimates for Full and Partial disclosure (***p < 0.01, **p < 0.05, *p < 0.1)
	LA&HR_Perft	LA_Perft	HR_Perft
	Equation 1(1) $${\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}}={\mathrm{ß}}_0+{\mathrm{ß}}_1{\mathit{LA}\&\mathit{HR}\_\mathit{Perf}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_2{\mathit{LA}\&\mathit{HR}\_\mathit{Disc}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{ß}}_3{\mathit{Size}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_4{\mathit{ROA}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_5{\mathit{Leverage}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_6{\mathit{Internatio}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_7{\mathit{Cash}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_8{\mathit{DLoss}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_9{\mathit{Accruals}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{10}{\mathit{Cov}\_\mathit{Ana}}_{\mathrm{i},\mathrm{t}}{+\mathrm{ß}}_{11}{\mathit{B}\_\mathit{Indep}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{12}{\mathit{CSR}\_\mathit{Comm}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{13}{\mathit{B}\_\mathit{Women}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{14}{\mathit{Female}\_\mathit{Managers}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{15}{\mathit{DLawsuits}}_{\mathrm{i},\mathrm{t}}+{\mathrm{ß}}_{16}{\mathit{NCSRPI}}_{\mathrm{i}}++{\mathrm{ß}}_{17}{\mathit{ICSRPI}}_{\mathrm{t}}+{\mathrm{ß}}_{18}{\mathit{Country}}_{\mathrm{i}}+{\mathrm{ß}}_{19}{\mathit{Industry}}_{\mathrm{i}}+{\mathrm{ß}}_{20}{\mathit{Year}}_{\mathrm{t}}+{\epsilon }_{\mathrm{it}}+{\mathrm{\eta }}_{\mathrm{i}}\mathrm{ }$$(1)	Robust 1	Robust 2
	Coeff.	Coeff.	Coeff.
	(Std.error)	(Std.error)	(Std.error)
LA&HR_Perft-1	0.753***
	(0.0201)
LA_Perft-1		0.886***
		(0.0117)
HR_Perft-1			0.503***
			(0.0287)
LA&HR_OrdDiscl t-1	0.185***
	(0.0672)
LA_OrdDiscl t-1		0.0258
		(0.0294)
HR_OrdDiscl t-1			0.210***
			(0.0507)
Size	0.0367	0.00885	0.0411**
	(0.0263)	(0.0119)	(0.0200)
ROA	0.00701	0.00353	0.00709
	(0.00730)	(0.00328)	(0.00557)
Leverage	−0.00159	−0.00113	0.000986
	(0.00285)	(0.00128)	(0.00217)
Internatio	0.00197	−0.000372	0.00317**
	(0.00203)	(0.000913)	(0.00155)
Cash	0.000	−6.12e-11	0.000
	(2.04e-10)	(9.16e-11)	(1.55e-10)
DLoss	−0.0955	−0.0106	−0.0328
	(0.252)	(0.113)	(0.192)
Accruals	0.000736	0.000896*	1.88e-06
	(0.00120)	(0.000541)	(0.000918)
Cpv_Ana	0.0166***	0.00307	0.00895*
	(0.00622)	(0.00280)	(0.00458)
B_Indep	−0.000780	−0.000460	−0.000909
	(0.00171)	(0.000770)	(0.00131)
CSRCommittee	−0.639***	−0.146***	−0.170*
	(0.112)	(0.0486)	(0.0908)
B_Women	−0.00363	−0.00135	0.00148
	(0.00452)	(0.00200)	(0.00345)
Female_Manag	0.0113***	0.00397**	0.00369
	(0.00399)	(0.00180)	(0.00303)
Dlawsuits	0.119	0.0139	0.0845
	(0.128)	(0.0576)	(0.0977)
NCSRPI	−0.000311	0.00316	−0.00289
	(0.00611)	(0.00275)	(0.00465)
ICSRPI	0.0465**	0.00573	0.0355**
	(0.0236)	(0.0106)	(0.0179)
Constant	2.824***	1.031***	0.884**
	(0.572)	(0.262)	(0.402)
Industry, country and year controlled
Log Likelihood	−25.040.527	−14.704.362	−21.530.459
p-value	0.000	0.000	0.000
Panel B. Descriptive by performance category
	Higher Performance	Lower Performance
Full Disclosure (over total sample)	39.85%	9.92%
Full Disclosure (over its own subsample)	54.41%	45.59%
Panel C. Estimates for Full and Partial disclosure as a function of performance (*** p < 0.01, ** p < 0.05, * p < 0.1)
	LA&HR_Perft	LA_Perft	HR_Perft
	Equation 2.	Robust 3	Robust 4
	Coeff.	Coeff.	Coeff.
	(Std.error)	(Std.error)	(Std.error)
LA&HR_OrdDisclt-1	0.428**	0.245**	0.303**
	(0.190)	(0.107)	(0.129)
LA&HR_HigherPerf	2.343***
	(0.371)
LA_HigherPerf		0.977***
		(0.203)
HR_HigherPerf			0.654***
			(0.244)
OrdDiscl = 0*HigherPerf = 0	0.000	0.000	0.000
	(0.000)	(0.000)	(0.000)
OrdDiscl = 0*HigherPerf = 1	−0.0430	0.120	0.0556
	(0.412)	(0.228)	(0.280)
OrdDiscl = 1*HigherPerf = 0	0.549**	0.0687	0.417**
	(0.264)	(0.140)	(0.183)
OrdDiscl = 1*HigherPerf = 1	−0.0390	0.0551	0.0533
	(0.243)	(0.131)	(0.166)
OrdDiscl = 2*HigherPerf = 0	0.001***	0.000	0.001***
	(0.000)	(0.000)	(0.000)
OrdDiscl = 2*HigherPerf = 1	0.001***	0.000	0.001***
	(0.000)	(0.000)	(0.000)
Size	−0.00995	−0.0773**	0.0502*
	(0.0427)	(0.0325)	(0.0258)
ROA	0.0133	0.00247	0.0125*
	(0.0101)	(0.00622)	(0.00653)
Leverage	−0.00143	−0.00713**	0.00317
	(0.00452)	(0.00321)	(0.00278)
Internatio	0.00560*	−0.000844	0.00533***
	(0.00302)	(0.00197)	(0.00191)
Cash	2.21e-10	2.85e-10	8.32e-11
	(3.34e-10)	(2.40e-10)	(2.02e-10)
DLoss	−0.0404	0.111	−0.0315
	(0.304)	(0.161)	(0.210)
Accruals	0.000443	0.000100	0.000176
	(0.00127)	(0.000617)	(0.000926)
Cpv_Ana	0.0592***	0.0481***	0.0117**
	(0.00963)	(0.00677)	(0.00593)
B_Indep	−0.00273	−0.00204	−0.00155
	(0.00231)	(0.00132)	(0.00152)
CSRCommittee	−0.312**	−0.358***	0.245**
	(0.142)	(0.0801)	(0.0964)
B_Women	0.0163***	0.00507	0.0110***
	(0.00579)	(0.00324)	(0.00389)
Female_Manag	0.0174***	0.0123***	0.00173
	(0.00635)	(0.00453)	(0.00390)
Dlawsuits	0.276	0.192	0.119
	(0.219)	(0.179)	(0.130)
NCSRPI	−0.00488	0.000413	−0.00330
	(0.00994)	(0.00752)	(0.00601)
ICSRPI	0.131***	0.0924***	0.0503**
	(0.0392)	(0.0310)	(0.0234)
Constant	10.70***	9.742***	1.441***
	(0.841)	(0.634)	(0.512)
Industry, country and year controlled
Log Likelihood	−27.210.848	−2.062.080	−22.243.291
p-value	0.000	0.000	0.000

Source: Authors’ calculations.

Moreover, similar to the basic robust models, this effect is only confirmed for HR indicators (HR_OrdDiscl: coeff.= 0.210; p < 0.05), suggesting that decisions regarding human resource management would be supported by the information provided by other internal information systems of the human resource department. On the other hand, Panel B in Table 6 shows the relative frequencies for companies that disclose all LA&HR performance indicators proposed by the GRI + UN + SDG Compass. It can be seen that, with respect to 27% of companies that make a full disclosure of indicators, 54.41% present above-average sustainable performance in terms of labour and human rights. This percentage is approximately 40% of the total.

Ergo, it seems relevant to analyse whether the usefulness of these indicators differs between more or less sustainable companies. Panel C shows that the information provided by the LA&HR indicators is used by all companies (LA&HR_HigherPerf: coeff.= 2.343; p < 0. 01), where the effect is greater in the companies that disclose all indicators, regardless of their performance (OrdDiscl = 2*HigherPerf = 1/0: coeff.= 0.001; p < 0.01), and in less sustainable companies that make a partial disclosure of LA&HR indicators (OrdDiscl = 1*HigherPerf = 0: coeff.= 0.549; p < 0.05). These results confirm the evidence obtained in previous models, indicating the internal usefulness of this non-financial information, especially regarding HR.

5. Discussion

The results confirm our research hypothesis, showing that the disclosure of all LA&HR indicators proposed by GRI + UN + SDG Compass favours a more sustainable behaviour. Thus, as suggested by Dey (2003), Gray (2006), and Searcy et al. (2016), the disclosure of LA&HR indicators translates into actual improvements in the company’s social performance.

The act of disclosing LA&HR indicators implies a managerial effort to comprehend, measure, monitor, and interpret the firm’s social impacts, thereby acting as a catalyst for strengthening corporate social policies and practices (Burns & Jollands, 2020). This result confirms prior research findings and contentions regarding the positive impact of social reporting on social performance (Jain et al., 2011; Searcy et al., 2016). Furthermore, it is consistent with the positive association between the breadth of disclosure and CSR performance documented by Vurro and Perrini (2011), indicating that firms that disclose a broader range of CSR themes have better CSR performance.

As regards the effect on HR performance, a potential explanation could be that management tends to be more responsive to performance criteria that are more sensitive for stakeholders (Thompson, 1967). Thus, management would place more emphasis on issues with high reputational impact (e.g., human rights violations) and, consequently, would devote more resources to improve the company’s performance in that regard, whereas other issues with lower reputational impact (e.g., training) would receive less management attention (Aibar-Guzmán et al., 2023). This result supports Chetty’s (2011, p. 761) contention regarding the key role that information plays ‘in assisting business to internalise human rights norms and evolve their business models to ones which actively contribute to a ‘social and international order’ in which human rights can be realised’.

Additionally, it can be observed that larger companies that operate in sectors that are particularly committed to CSR and have a greater presence of women in their management teams show a greater commitment to labour and human rights. As regards firm size and activity sector, our findings are in line with most prior studies (Vurro & Perrini, 2011; Cahaya & Hervina, 2019). Regarding gender diversity, our finding also confirms the positive impact that the presence of women in management positions has on the company’s CSR performance documented by prior studies (Monteiro et al., 2022), as well as the positive influence of women managers on the firm’s social responsiveness (Ibrahim & Angelidis, 1994) and stakeholder orientation.

Conversely, the results suggest that the existence of a CSR committee on the board of directors has the opposite effect. Thus, although this type of committee is created with the aim of improving the company’s social and environmental performance, in the case of our sample the CSR committees seem to be more focussed on the environmental dimension of CSR than on the social one. Finally, Table 5 shows that LA&HR performance is also favoured by the monitoring work carried out by certain financial agents, such as analysts, thus confirming the positive influence of these financial agents on CSR (García-Sánchez et al., 2019). This result is also in line with the positive effect of analyst coverage on corporate philanthropy documented by Zhang et al. (2015).

6. Conclusions and implications

Social issues are a key component of a company’s CSR agenda (Searcy et al., 2016). In fact, they are deemed a ‘precondition for corporate social responsibility’ (Johnston, 2001), since any CSR strategy developed by a company cannot be considered viable if it does not consider the physical and psychological well-being of its employees and respect for human rights. In this sense, many policy documents and guidelines have addressed labour and human rights in the context of the CSR agenda and companies have engaged in social reporting practices.

This study intends to answer the following question: can social disclosure induce a better corporate social performance? Based on a sample of 1,243 multinational enterprises for the period 2013–2017 we show that the disclosure of all LA&HR performance indicators proposed by GRI + UN + SDG Compass is positively associated with higher LA&HR performance. The results confirm our research hypothesis regarding a positive effect of LA&HR disclosure on LA&HR performance, showing that both total and partial disclosure of LA&HR performance indicators are oriented towards the improvement of corporate sustainability as opposed to impression management strategies. These results confirm prior research findings and contentions regarding the positive impact of social reporting on social performance (Jain et al., 2011; Searcy et al., 2016) and support the double role that social reporting may play: as a vehicle of communication to external stakeholders that contributes to stakeholder dialogue and as a source of information for internal decision making (Vurro & Perrini, 2011; García-Sánchez et al., 2019) that favours the improvement of a company’s social performance.

From a theoretical viewpoint, our findings contribute to literature by adding to the current understanding of the performance consequences of external reporting and provide empirical support to the possibility that the information inductance effect extends to voluntary social reporting (Collison et al., 2003), acting as a catalyst for strengthening corporate social policies and practices. Thus, this study also contributes to instrumental stakeholder theory (Jones et al., 2018) by showing that responsiveness to stakeholders’ requests and concerns regarding labour and human rights through the disclosure of LA&HR performance indicators positively affects a firm’s social performance, favouring the adoption of ethical human resource management practices and respect for human rights.

The results also present various practical and policy implications. Firstly, they provide a further motive to promote social reporting: its positive impact on corporate social performance favouring responsive labour management and greater social cohesion. Indeed, our findings show that social reporting may be a driving force for real changes both at the firm and the society level, fostering the implementation of ethical human resource practices that not only benefit the firm’s employees and their families, but also society as a whole (Burns & Jollands, 2020).

Secondly, our findings may assist policymakers and standard setters in drafting regulations and standards that promote and/or regulate social disclosures (specifically those related to LA&HR indicators) to favour responsive labour management and respect for human rights. Thus, considering this study’s findings, it seems recommendable that policymakers and standard setters develop a regulatory framework that fosters a more complete and comparable disclosure of LA&HR indicators as a means to change business behaviour and advance to a fairer society. This is particularly pertinent at present as the economic crisis triggered by the COVID-19 has led companies to cut back labour rights (Aibar-Guzmán et al., 2023) and new reporting standards are being developed to promote corporate transparency in social information. Finally, stakeholders should be conscious that the reporting standards and guidelines not only normalise the information, thereby enhancing its comparability, but also have potential to influence social performance and, therefore, the fact that a firm follows a certain CSR reporting framework (e.g., the GRI guidelines) may affect its CSR performance, in line with the issues addressed in such a framework.

This research is subject to some limitations, which also suggest ideas for future research. Firstly, the fact that we focussed on listed multinational companies may have influenced the findings, because larger firms tend to be pioneers regarding the introduction of good business practices, as they are more visible and gather greater stakeholder attention (Vurro & Perrini, 2011). Thus, future studies could analyse small and medium companies as well as non-listed firms. Secondly, although we believe that our variables are reliable and accurate, the results may be affected by the way the main variables have been measured, so the study should be replicated using alternative measures of social performance and disclosure. Furthermore, the influence of other potential control variables (e.g., the existence of a CSR division) may be analysed.

Disclosure statement

No conflict of interest has been reported by the authors.

Additional information

Funding

Ministerio de Ciencia, Innovación y Universidades [Grant/Award Number: RTI2018- 093423- B- I00]; Consejería de Educación, Junta de Castilla y León [Grant/Award Number: SA069G18]; Universidad de Salamanca [Grant/Award Number: USAL2017- DISAQ]; Junta de Castilla y León y Fondo Europeo de Desarrollo Regional [Grant/Award No. CLU-2019-03 Unidad de Excelencia “Gestión Económica para la Sostenibilidad” (GECOS)]; and Xunta de Galicia [Grant/Award Number: 2020 GPC GI2016].