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Citation: Susanto, Hendra, Nyoman
Adhi Suryadnyana, Rusmin Rusmin,
and Emita Astami. 2024. The Impact
of Family Firms and Supervisory
Boards on Corporate Environmental
Quality. Journal of Risk and Financial
Management 17: 263. https://
doi.org/10.3390/jrfm17070263
Academic Editor: Ming-Lang Tseng
Received: 2 May 2024
Revised: 23 May 2024
Accepted: 7 June 2024
Published: 26 June 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Journal of
Risk and Financial
Management
Article
The Impact of Family Firms and Supervisory Boards on
Corporate Environmental Quality
Hendra Susanto 1, *, Nyoman Adhi Suryadnyana 2, Rusmin Rusmin 3and Emita Astami 3
1Fakultas Ekonomi, Universitas Sriwijaya, Palembang 30662, Indonesia
2Badan Pemeriksa Keuangan Republik Indonesia, Jakarta 10043, Indonesia; nyomyman@yahoo.com
3Fakultas Bisnis dan Humaniora, Universitas Teknologi Yogyakarta, Yogyakarta 55285, Indonesia;
rusmin@uty.ac.id (R.R.); eastami@uty.ac.id (E.A.)
*Correspondence: hendra.susanto@fe.unsri.ac.id
Abstract: This paper examines the impact of family ownership and supervisory board characteristics
on carbon emission disclosure. It uses balanced panel data and a matched-pair design of 124 non-
financial firms listed on the Indonesia Stock Exchange from 2017 to 2019. This study finds that family
firms and larger boards improve, while female board members harm carbon emission performance.
Further analyses reveal non-linear relationships between family ownership and carbon performance.
When control rights are limited, family firms prioritize controlling managers and improving carbon
quality. Conversely, they prioritize personal objectives over environmental concerns when there
are high control rights, resulting in decreased carbon emission performance. Additionally, family
board members generate more carbon information, indicating the family owners effectively utilize
their position on the supervisory boards to influence the company’s carbon emission performance.
Finally, the study reports that more faculty member boards seem to hurt carbon emission reduction
efforts. This result suggests that the diversity of their professional experiences does not affect
the environmental effectiveness of supervisory boards. Our findings highlight the importance
of understanding SEW principles and their connection to families in comprehending Indonesian
corporate carbon emissions disclosures. The findings of this study enrich the worldwide literature
by exploring the potential benefits of family business environmental performance. This study also
adds to the literature on corporate governance, especially the role played by supervisory boards. Our
findings align with the resource dependence theory, emphasizing the central function of supervisory
boards as a monitoring tool. This study is constrained by its reliance on carbon emission data
extracted from the annual reports of public firms, with a particular emphasis on pre-COVID-19 data.
Future research should focus on sustainability reports and explore the time frame encompassing
COVID-19 (2020–2022 datasets) to determine any differences in the findings.
Keywords: family firms; supervisory boards; carbon emission; Indonesia stock exchange
1. Introduction
Numerous countries are witnessing a growing public concern regarding a range of
environmental problems. Carbon emissions are widely recognized as the primary factor
behind environmental issues such as climate change, rising sea levels, and more frequent
extreme weather events (Jia et al. 2024;Liu et al. 2022;Ramanathan and Feng 2009;Wang
et al. 2022). According to Lin and Zhang (2024), the BP Statistical Review of World Energy
2023 highlights a 0.8% increase in carbon dioxide emissions in 2022 compared to 2021.
There is a concerning forecast that global CO
2
emissions could potentially result in a rise in
Earth’s temperature by 1.5 to 2 degrees Celsius, which poses a severe threat to the survival
and development of humanity (Du et al. 2023;Li et al. 2023). In 2016, a historic global
climate change agreement, known as the Paris Agreement, was signed by 178 countries
worldwide (Liu and Yang 2021). This agreement aims to decelerate climate warming and
J. Risk Financial Manag. 2024,17, 263. https://doi.org/10.3390/jrfm17070263 https://www.mdpi.com/journal/jrfm
J. Risk Financial Manag. 2024,17, 263 2 of 24
enhance the capacity to combat climate change by limiting global warming to 1.5 degrees
Celsius. However, this topic holds particular significance for the BRICS countries due to
their rapid economic growth and substantial contribution to global economic expansion
(Gyamfi et al. 2022;Khattak and Ahmad 2022).
The carbon management practices of Indonesian-listed companies have been sub-
ject to rigorous scrutiny, mainly attributed to Indonesia’s massive population, surpassing
270 million, resulting in substantial carbon emissions (Chariri et al. 2019). Business entities
in Indonesia are under tremendous pressure to reduce their carbon emissions, both from
domestic and international communities (Rokhmawati 2020). The Indonesian government,
via Kementerian Energi dan Sumber Daya Mineral Republik Indonesia, has mandated
that the manufacturing sector reduce its carbon emissions in response to internal pressure
through Regulation No. 70/2009. In light of global carbon emission concerns, the govern-
ment has committed to lowering greenhouse gas emissions by 29% by the year 2030. In
addition to government regulations, Indonesian companies are also facing pressure from
consumers and investors, who are increasingly concerned about the environmental impact of
their products and services. To meet these market demands, enterprises must adopt sustainable
approaches, assess their carbon emissions, set targets for reducing emissions, promote energy
efficiency, and utilize renewable energy sources. The increasing demand to comply with regula-
tions and appeal to environmentally responsible customers and stakeholders drives companies
to shift towards greater transparency in sustainable practices (Rahmaniati and Ekawati 2024).
Numerous studies have been conducted to analyze the carbon emission disclosures
(CED) provided by companies, with a specific focus on identifying the factors that impact
the level of CED. Still, the majority of studies, such as those by Gray et al. (1995), Iyer and
Lulseged (2013), and Baalouch et al. (2019), have focused on the UK, the US, and European
countries. The type and scope of corporate disclosure in Asia, notably Indonesia, have not
been thoroughly studied. Chau and Gray (2002) claim that Asian companies are less willing
to disclose information publicly than their Anglo-American counterparts. In addition,
Lam et al. (1994) found that the management and ownership structures of Asian firms
significantly impacted the information they provided. Several research studies have been
conducted on the voluntary disclosure of carbon emissions within the Indonesian context.
For instance, Faisal et al. (2018), Hermawan et al. (2018), Pratiwi et al. (2021), as well
as Wahyuningrum et al. (2024), analyze the company’s specific characteristics to predict
the disclosure of greenhouse gas emissions. Qosasi et al. (2022) study the relationship
between ownership structure and carbon performance. Meanwhile, Andrian (2021) places
significant importance on investigating the impact of the board of directors, institutional
ownership, and firm performance on the disclosure of carbon emissions. Most prior empir-
ical studies have focused on a specific predictor in isolation rather than combined. This
paper investigates the effect of family-controlled firms and supervisory board mechanisms
on CED. As Vafeas and Theodorou (1998) remark, studying key related firm or corporate
governance characteristics in isolation may hide meaningful inferences, leading to mislead-
ing findings. This study is essential because research on the relationship between family
ownership and carbon performance in developing countries is limited. For several reasons,
understanding the relationship between family ownership and carbon performance in
Indonesia is essential. First, Indonesia is one of the world’s largest emitters of greenhouse
gases, primarily due to its reliance on fossil fuels for energy production (Wijaya et al. 2017).
Second, Joni et al. (2020) report that family business groups control most of Indonesia’s
listed companies, with about 95% being family-owned. Family-owned companies gen-
erate millions of jobs and play an essential role in developing the Indonesian economy
(PriceWaterhouseCoopers 2018). As such, their environmental practices directly impact
the overall sustainability of the economy and the population’s well-being. This research
can give us insights into family-owned businesses’ decisions regarding environmental and
social governance (ESG). This information can be used to develop targeted policies and
initiatives that encourage these businesses to adopt more sustainable practices and reduce
their carbon footprint. Overall, understanding the association between family ownership
J. Risk Financial Manag. 2024,17, 263 3 of 24
and carbon performance in Indonesia is crucial for promoting environmental sustainability,
mitigating climate change, and ensuring the long-term prosperity of the country.
Good corporate governance practices are essential to promoting investments and
boosting the economy in Indonesia (Deloitte 2020). Some regulations, such as Law No.
40/2007 on Limited Liability Companies and Law No. 25/2007 on Investment, have
been released to ensure the professional, accountable, and transparent business practices of
companies listed on the IDX. According to Jain and Jamali (2016), the literature on corporate
governance notes a robust theoretical link between better corporate governance practices
and a firm’s corporate social responsibility performance (CSR). The link between corporate
governance and CSR can be understood through various mechanisms. Firstly, improved
corporate governance practices, such as the presence of independent directors, effective
board oversight, and transparent reporting, can enhance accountability and transparency
within an organization. Consequently, this can lead to better management of social and
environmental risks and improved stakeholder engagement. Secondly, effective corporate
governance mechanisms can facilitate the adoption of CSR-related policies and practices
throughout the organization. For instance, an effective board of directors is crucial in
guiding management in implementing CSR initiatives, establishing goals, and tracking
progress. Through this, CSR can be integrated into the organizational culture and day-to-
day activities, fostering the adoption of sustainable and ethical business practices. In light
of this, this study explores How family ownership and supervisory board
1
characteristics
impact carbon emission disclosure in Indonesian non-financial listed firms.
The remainder of this paper is organized as follows: The next section provides a
literature review and research hypotheses. The third section describes the study’s sample,
data, and model. The fourth section presents the results, tests, and analysis. The final
section concludes the study.
2. Literature Review and Hypotheses Development
Most of the past research regarding family businesses argues that family management
uses their concentrated ownership to confiscate the earnings of minority shareholders.
This problem is commonly called principal–principal conflict (Miller and Le Breton-Miller
2006). Nevertheless, Anderson and Reeb (2003) note that concentrated ownership in listed
family-controlled businesses minimizes the traditional issues of managerial expropriation
because the family’s wealth is closely associated with business welfare. Moreover, Andres
(2008) provides evidence that families prioritize non-monetary goals and are worried about
the firm’s reputation and existence.
This study uses the socio-emotional wealth (SEW) concept to explain the behavior
of family-controlled firms regarding corporate social responsibility activities. The SEW
approach argues that the primary goal of the family owners is to preserve the family’s SEW
(Berrone et al. 2012;Gómez-Mejía et al. 2007). Specifically, Berrone et al. (2012) and Brune
et al. (2019) indicate that a critical aspect of SEW is that the decision-making processes in
family firms are driven not only by economic goals but also by non-economic objectives.
Thus, SEW refers to the non-financial aspects that support the family’s needs. These
elements include family control and influence, family members’ identification with the
business, tying up social ties, emotional attachment, and upholding the family’s reputation
and status in the community (Berrone et al. 2012). The desire to protect SEW may lead
family firms to positive outcomes by actively participating in social initiatives such as
preserving environmental quality (Cennamo et al. 2012).
This study also refers to the corporate governance philosophy, as it is designed to
enhance efficiency and ensure management accountability in the utilization of resources.
In the literature, effective corporate governance is frequently associated with high-quality
financial reporting and companies’ disclosure performance (Arora and Dharwadkar 2011;
Martinez-Ferrero et al. 2020;Peasnell et al. 2005). The resource dependence theory offers
justifications for the distinctive traits of corporate governance, especially the board of super-
visors or board of commissioners. According to resource dependence theory, supervisory
J. Risk Financial Manag. 2024,17, 263 4 of 24
boards are essential for allocating external resources (including image, expertise, back-
ground, reputation, and capabilities) and connecting with external organizations. When
supervisory boards offer expertise, experience, knowledge, or skills, they are supplying
human capital to the board. Likewise, supervisory boards contribute social capital by
accessing outside resources and connecting with other organizations (Haynes and Hillman
2010). Thus, supervisory boards are expected to bring different resources to the company.
The boards provided with social and human capital might perform their duties and re-
sponsibilities more effectively (Ramon-Llorens et al. 2020), which could have a favorable
effect on firms’ strategic decisions, like supporting corporate social responsibility (CSR)
disclosure (Wang and Dewhirst 1992).
In conclusion, Ramon-Llorens et al. (2020) argue that companies with diverse boards
will improve information flow by better-influencing decision-making. These firms prefer to
share CSR-related information, which could strengthen their connections and relationships
with outside stakeholders and organizations. As a result, resource dependence theory adds
another viewpoint to governance research by emphasizing the notion that supervisory
boards are a company’s most important resource (Chalu 2021;Pfeffer and Salancik 1978)
and provide stakeholders with better CSR information (Allegrini and Greco 2013).
2.1. Family Ownership and Carbon Emission Disclosure
Aligned with the socio-emotional perspective, families that prioritize self-actualization
and the well-being of others may create an atmosphere that is more conducive to meeting
higher-level needs, such as increased carbon emission disclosure. Berrone et al. (2012)
and Brune et al. (2019) have conducted a study highlighting an essential aspect of socio-
emotional wealth in family-run businesses. According to their findings, the decision-
making processes in these businesses are not solely driven by economic objectives but also
influenced by non-economic goals. In preserving the family’s socio-emotional wealth, fam-
ily owners are willing to take on a higher risk of experiencing poor economic performance
(Chua et al. 2015;Stockmans et al. 2010).
Indeed, Cruz et al. (2014) note that different socio-emotional wealth reference points
may justify family owners’ varied responses to the various strategic outcomes. When
family owners prioritize family control, they focus on retaining control over their company
to protect their socio-emotional endowment (Anderson and Reeb 2004). Consequently,
they may refrain from engaging in corporate social responsibility endeavors that could
potentially jeopardize their control (Ashiq Ali and Radhakrishnan 2007). On the other hand,
if family owners prioritize family identity, they may place greater importance on acting
socially responsibly to uphold a positive family image and protect the family’s reputation
(Healy and Palepu 2001;Martin et al. 2016).
Research gaps exist regarding the impact of socio-emotional wealth reference points
on family firms’ involvement in corporate social responsibility. Family businesses often
hesitate to disclose their corporate governance practices to maintain control over top man-
agement positions without interference from non-family shareholders (Rees and Rodionova
2015). This reluctance to share information is driven by a desire to avoid setting a prece-
dent (Graham et al. 2005). Once information is disclosed, the firm becomes committed to
ongoing voluntary disclosures, which may be challenging to stop in the future (Diamond
and Verrecchia 1991;Verrecchia 2001). There is some evidence suggesting that non-family
businesses tend to prioritize self-interested and self-serving goals rather than focusing on
generating CED (Corbetta and Salvato 2004;Le Breton-Miller and Miller 2009). By contrast,
family-owned firms have a higher awareness of maintaining a firm’s sustainability and
increasing the activity of CSR (Dyer and Whetten 2006;Iyer and Lulseged 2013;Zellweger
et al. 2011), thus pursuing family-centered non-financial objectives (Andres 2008;Chrisman
et al. 2012) that generate SEW (Berrone et al. 2012;Gómez-Mejía et al. 2007;Iyer and
Lulseged 2013). Accordingly, our first hypothesis is:
H1:Family-controlled firms disclose more carbon emission information.
J. Risk Financial Manag. 2024,17, 263 5 of 24
2.2. Supervisory Boards Characteristics and Carbon Emission Disclosure
The resource dependence theory suggests that the board of commissioners is central
to a company’s internal governance (Pfeffer and Salancik 1978). They play a fundamental
role in ensuring the company’s social and environmental commitment (García-Sánchez and
Martínez-Ferrero 2017). Gray et al. (1995) argue that firms with more effective boards will
encourage engagement in and facilitate the disclosure of CSR issues. Nam and Nam (2004)
claim that a board’s size is an essential determinant of a board’s effectiveness. Arguably,
limited members of the board of commissioners benefit from good communication and
coordination, which might lead to better monitoring and control of management (Dey 2008).
However, small members might suffer from high workloads and responsibilities, hindering
their monitoring role (Beiner et al. 2004). Beiner et al. (2004) claim that more members
sitting on the board of commissioners reflect more resources to monitor and evaluate
management decisions. Jizi (2017) and Ramon-Llorens et al. (2020) argue that larger boards
will be more effective in setting firms’ CSR agendas and encouraging the communication of
CSR information because they bring various perspectives and backgrounds to the boards.
Moreover, previous studies (e.g., Cancela et al. 2020;Mallin and Michelon 2011;Walls et al.
2012) report that the number of board members has a significant and positive impact on
the extent of disclosure regarding corporate environmental sustainability. Overall, the
research suggests that having a larger board of directors can lead to more comprehensive
and transparent reporting on environmental sustainability practices within a company.
Furthermore, the diverse perspectives and experiences brought by a larger board can
also contribute to more effective decision-making processes when it comes to setting CSR
priorities and strategies.
Dechow et al. (1996) suggest that the ability of the supervisory boards to act as an
effective monitoring mechanism depends on their independence from management. From
a resource-dependence point of view, independent boards are considered resources less
allied with the management and family owners (Napitupulu et al. 2020). Greater board
independence is associated with more effective monitoring of managerial opportunism;
thus, companies can be expected to have more corporate disclosure (Fama and Jensen
1983;Jizi 2017). Previous studies (Adams and Hossain 1998;García-Meca and Sánchez-
Ballesta 2010;Patelli and Prencipe 2007) document a positive and significant relationship
between the larger proportion of independent members on the board of commissioners
and corporate environment disclosure. Independent boards of commissioners are more
likely to push for greater transparency and disclosure of corporate information, as they
are not directly tied to the management team and are focused on protecting the interests
of shareholders.
Prior studies have identified diligence as one of the most critical measures in quan-
tifying the board of commissioners’ effectiveness. Although greater time spent by board
members does not always translate into more monitoring activities (Menon and Williams
1994), Davidson et al. (2005) contend that frequent board meetings often improve the
board’s oversight function. Such time must be used for various governance tasks to en-
hance organizational performance and monitor corporate actions or strategies (Wijethilake
et al. 2015). In other words, supervisory boards that meet frequently will likely perform
monitoring and advisory duties effectively (Davidson et al. 2005;Lipton and Lorch 1992;
Vafeas 1999). Several studies (Allegrini and Greco 2013;Davidson et al. 2005;Kent and
Stewart 2008;Lipton and Lorch 1992) note that companies with more frequent board meet-
ings tend to have better disclosure performance. In summary, regular board meetings create
a culture of transparency and accountability within the company, providing a platform
for open discussions and information sharing. Consequently, this cultivates improved
disclosure practices, as companies are inclined to offer precise and timely information to
their stakeholders.
J. Risk Financial Manag. 2024,17, 263 6 of 24
One specific goal of the board of commissioners is to promote diversity within the
organization’s governance structures (Millet-Reyes and Zhao 2010). However, Mahadeo
et al. (2012) highlight how board diversity might be conceptualized. Board gender diversity
forms a new corporate governance dimension. Numerous initiatives have been imple-
mented worldwide, particularly in Indonesia, to increase gender diversity on the board
of commissioners. The Financial Service Authority in Indonesia encourages companies
to develop a policy on gender diversity in their executive teams and supervisory boards.
The observance of this policy should be noted in the companies’ yearly reports (OJK 2014).
Huse and Solberg (2006) claim that, compared to males, females are likelier to have bet-
ter communication skills, personality, commitment, and diligence. Thus, the presence of
women on corporate boards will provide more charitable contributions and have higher
environmental involvement and social welfare activities (Post et al. 2011;Williams 2003).
Previous research (Barako and Brown 2008;Liao et al. 2015;Mallin and Michelon 2011)
reports that higher female participation on boards positively influences the effectiveness
of a firm’s social and environmental profile. These studies highlight the positive impact
that gender diversity on corporate boards can have on a company’s social responsibility
initiatives. Having women on boards can bring different perspectives and priorities to
decision-making, leading to a greater focus on sustainability, community engagement, and
ethical business practices. Based on the corporate governance and resource dependence
theories, we pose the following hypotheses:
H2:Firms with a larger board of commissioners disclose more carbon emission information.
H
3
:Firms with a higher proportion of independent members on the board of commissioners disclose
more carbon emission information.
H
4
:Firms with more frequent board of commissioner meetings disclose more carbon emission information.
H
5
:Firms with a higher proportion of female members on the board of commissioners disclose more
carbon emission information.
3. Data and Methodology
3.1. Data Collection
This research utilizes balanced panel data and a matched-pair design to examine
the environmental performance of both family-owned and non-family-owned companies.
Initially, we identified family-controlled companies by referring to the Globe Asia Business
Magazine (GlobeAsia 2019). We proceeded to track down the websites of every company
group and discovered 62 non-financial family firms that consistently released their annual
reports from 2017 to 2019. A matched-control sample of non-family enterprises was
carefully selected to ensure a comparison between the two groups was accurate and
unbiased. This selection process was based on three specific criteria: fiscal year, industry
classification, and the closest total asset amount. The independent-sample t-test (results not
included for brevity) indicates that the means of total assets of family and non-family firms
are not significantly different. Hence, the dataset consists of 124 non-financial companies
listed on the IDX that consistently published their annual reports from 2017 to 2019. The
analysis was conducted on a balanced panel of 124 firms, resulting in 372 observations over
the three years (see Table 1).
The data in Table 1shows that companies in the property, real estate, and building
construction sectors comprise the largest sample size, with 114 observations (30.65%). The
second largest is the basic industry and chemical firms, with 30 observations (16.13%). In
contrast, the smallest group of firms is in the agriculture and infrastructure, utilities, and
transportation sectors, with 24 observations (6.45%), respectively.
J. Risk Financial Manag. 2024,17, 263 7 of 24
Table 1. Sample by the IDX industry classification.
Sector Industry Classification 2017–2019
N%
1 Agriculture 24 6.45%
2 Mining 36 9.68%
3 Basic industry & chemicals 60 16.13%
4 Miscellaneous industry 24 6.45%
5 Consumer goods industry 54 14.52%
6 Property, real estate & building construction 114 30.65%
7 Infrastructure, utilities & transportation 24 6.45%
9 Trade, services & investment 36 9.68%
Total 372 100.00%
Note: This study excludes industry sector number 8 for finance firms.
3.2. Dependent Variable
The study employs the CED level as the dependent variable and implements a carbon
emissions checklist developed by Choi et al. (2013). The measurement of the dependent
variable follows the unweighted approach, which assigns equal weight to each disclosure
item. This method is more objective than a weighted index approach (Cooke 1993). The
indicator variable is assigned a score of 1 if company jdiscloses information based on the
checklist items and 0 if not.
3.3. Independent Variables
We employ family ownership and four dimensions of supervisory board characteristics
(board size, board independence, board meeting frequency, female board) as explanatory
variables in the model. Family firms are identified by the percentage of equity ownership
and the presence of family members in executive or supervisory positions (Anderson and
Reeb 2003).
3.4. Control Variables
In line with prior studies into environmental disclosure, we controlled for variables
that might impact the level of carbon emission disclosure. The agency conflicts that arise
when firm ownership is dispersed might differ from those when it is concentrated (Jensen
and Meckling 1976). To control the effect of ownership characteristics, we include concen-
trated ownership as a percentage of outstanding shares owned by the largest shareholder
(Pindado et al. 2008;Yin et al. 2012). The audit committee size is incorporated to address
agency issues and minimize information asymmetry between internal and external stake-
holders (Al-Shaer and Salama 2015;Collier 1993). Firm size, leverage, and profitability
are included to control for the effect of a firm’s visibility, risk, and financial performance
(Al-Tuwaijri et al. 2004;Clarkson et al. 2011;Martinez-Ferrero et al. 2020;Pucheta-Martinez
and Gallego-Alvarez 2020). Big4 auditors are incorporated to control the impact of audit
quality on disclosure performance. It is a commonly held belief that companies audited by
Big4 accounting firms tend to disclose a greater amount of information compared to those
audited by non-Big4 firms. (Craswell and Taylor 1992;Rover et al. 2016). Additionally,
we control for price-to-book ratio, cash flow from operations, and firm age due to their
documented effects on environmental quality (Madden et al. 2020;Ramon-Llorens et al.
2020;Tran and Adomako 2020). Table 2provides a detailed description of the variables.
J. Risk Financial Manag. 2024,17, 263 8 of 24
Table 2. Description of variables.
Title Description Source
Dependent variable
CED
Carbon emission disclosure index. The indicator
variable scored 1 if the company discloses
information as determined in the checklist items
and 0 otherwise.
Faisal et al. (2018); Kalu et al. (2016)
Independent variables
FAM The percentage of outstanding shares owned by
family members Anderson and Reeb (2003)
BOARD
The total number of board members as reported by
the company
Martinez-Ferrero et al. (2020); Ramon-Llorens et al.
(2020)
BOIND The proportion of independent members on the
boards
Patelli and Prencipe (2007); García-Meca and
Sánchez-Ballesta (2010)
BOMEET The number of board meetings held yearly in the
company
Martinez-Ferrero et al. (2020); Ramon-Llorens et al.
(2020)
FEMALE The percentage of female board members at the
end of the fiscal year
Patelli and Prencipe (2007); García-Meca and
Sánchez-Ballesta (2010)
Control variables
TOP The percentage of outstanding shares owned by
the largest shareholder. Pindado et al. (2008); Yin et al. (2012)
AC The total number of audit committees Collier (1993); Al-Shaer and Salama (2015)
Size The natural log of total assets Martinez-Ferrero et al. (2020); Pucheta-Martinez
and Gallego-Alvarez (2020)
Leverage Total debt to total assets ratio Martinez-Ferrero et al. (2020); Pucheta-Martinez
and Gallego-Alvarez (2020)
ROA Net income to total assets ratio Martinez-Ferrero et al. (2020); Pucheta-Martinez
and Gallego-Alvarez (2020)
Big4
Take a value of 1 if the company’s auditor is a Big4
audit firm and 0 otherwise Craswell and Taylor (1992); Rover et al. (2016)
Age
The natural logarithm of the number of years since
the company was established
Ramon-Llorens et al. (2020); Tran and Adomako
(2020)
P/B Ratio
The company’s stock price per share divided by its
book value per share Madden et al. (2020); Ramon-Llorens et al. (2020)
CFO Cash flow from operations to total assets ratio Ramon-Llorens et al. (2020); Tran and Adomako
(2020)
3.5. Empirical Model Equations
The primary statistical technique to test the hypotheses is ordinary least squares
(OLS) multiple regression. The OLS multiple regression is a highly utilized and adaptable
statistical technique that plays a crucial role in analyzing hypotheses and facilitating well-
informed decisions through empirical data. The regression models are defined in the
following equation:
CEDi= ai+αi1FAMit +αi2BOARDit +αi3BOINDPit +αi4BOMEETit +αi5FEMALEit +αi6Topit +αi7ACit +αi8SIZEeit +
αi9LEVit +αi10ROAit +αi11 BIGit +αi12AGEit +αi13 P/BRATIOit +αi14CFOit +IndustryFEit +YearFEit εi
J. Risk Financial Manag. 2024,17, 263 9 of 24
4. Findings and Discussions
4.1. Descriptive Statistics
The descriptive statistics and early indications of the relationships between the key
variables of interest are shown in Tables 3–5. As exhibited in Table 3, AC-1 was the most
published item (96.77%, 100%, and 100%, respectively). Following that is RC-1 (81.45%,
81.45%, and 83.87%, respectively), and the least disclosed item is RC-4 (0.81%, 1.61%,
and 0.81%, respectively). Table 3also demonstrates an upward trend in carbon emission
disclosure, which increased from 33.69% in 2017 to 34.95% in 2018 and 36.92% in 2019.
These numbers reflect a rise in companies’ spending on environmental initiatives. The
carbon emission items revealed by family and non-family businesses varied significantly.
Family firms provide much more information on the CC-2, EC-3, RC-1, and AC-1. In
contrast, non-family companies disclose more information about CE-3, CE-4, CE-7, EC-1,
RC-3, and RC-4.
Table 3. Percentage firm disclosed per item by years and family versus non-family.
Code Carbon Emission Details
Full Sample Sub-Sample
2017 2018 2019 Mean
Family
Non-Family t-Value
CC1
1. Assessment/description of the risks (regulatory,
physical, or general) relating to climate change and
actions taken or to be taken to manage the risks
57.26 56.45 61.29 58.33 62.9 53.76 1.791
CC2
2. Assessment/description of current and future
financial implications, business implications, and
opportunities of climate change
24.19 23.39 23.39 23.66 32.26 15.05 3.976 *
CE1 3. Description of the methods used in calculating
GHG emissions (e.g., GHG protocol or ISO) 16.94 18.55 19.35 18.28 18.82 17.74 0.268
CE2 4. Existence of external verification of quantity of
GHG emission- if so, by whom and on what basis 13.71 15.32 16.13 15.05 13.98 16.13 −0.579
CE3 5. Amount of GHG Emissions – metric tones
CO2-emitted 11.29 11.29 13.71 12.1 5.38 18.82 −4.051 *
CE4 6. Disclosure of scopes 1 and 2 or related to the
direct GHG emissions 4.03 3.23 5.65 4.3 1.61 6.99 −2.571 *
CE5 7. Disclosure of GHG emissions based on the
sources (e.g., coal, electricity, etc.) 31.45 39.52 42.74 37.9 34.41 41.4 −1.389
CE6 8. Disclosure of GHG emissions based on the
facility or level of segment 34.68 35.48 36.29 35.48 33.87 37.1 −0.649
CE7 9. Comparison of the amount of GHG emissions
with last year 9.68 11.29 11.29 10.75 1.61 19.89 −5.940 *
EC1 10. Total amount of energy consumption (e.g.,
tera-joules or petajoules) 23.39 29.84 33.87 29.03 16.67 41.4 −5.446 *
EC2 11. Total amount of energy used from renewable
sources 35.48 34.68 38.71 36.29 34.95 37.63 −0.538
EC3 12. Disclosure based on types, facilities, or
segments 69.35 67.74 72.58 69.89 76.88 62.9 2.965 *
RC1 13. Detail of plans or strategies to reduce GHG
emissions 81.45 81.45 83.87 82.26 87.63 76.88 2.734 *
RC2 14. Specification of GHG emissions reduction
target and target year 10.48 6.45 8.87 8.6 6.45 10.75 −1.48
RC3 15. Emissions reductions and associated costs or
savings 12.9 13.71 12.9 13.17 7.53 18.82 −3.257 *
RC4 16. Cost of future emissions factored into capital
expenditure planning 0.81 1.61 0.81 1.08 0 2.15 −2.016 **
AC1
17. Indication of which board committee (or other
executive body) has overall responsibility for
actions related to climate change
96.77 100 100 98.92 100 97.85 2.016 **
AC2
18. Description of the mechanism by which the
board (other executive body) reviews the
company’s progress regarding climate change
72.58 79.03 83.06 78.23 77.42 79.03 −0.376
Mean 33.69 34.95 36.92 35.19 34.02 36.35 −1.414
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests). CC = Climate change:
risks and opportunities; CE = Carbon emissions; EC = Energy consumption; RC = Carbon emission reduction and
cost; AC = Carbon emission accountability.
J. Risk Financial Manag. 2024,17, 263 10 of 24
Table 4. Number of items disclosed per theme by industry.
Industry Sector Classification Percentage of Items Disclosed Per Theme Mean
CC CE EC RC AC
1-Agriculture 60.42 35.12 47.22 31.25 89.58 45.14
2-Mining 61.11 22.22 60.19 25.69 94.44 41.67
3-Basic industry & chemicals 53.33 28.81 55.00 28.75 99.17 43.70
4-Miscellaneous industry 18.75 12.50 30.56 36.46 81.25 29.17
5-Consumer goods industry 36.11 18.78 50.00 25.46 87.96 35.08
6-Property, real estate & building construction 37.72 8.27 33.04 23.03 85.96 27.58
7-Infrastructure, utilities & transportation 35.42 38.10 68.06 32.29 95.83 47.92
9-Trade, services & investment 23.61 15.87 37.04 20.14 73.61 27.62
The mean of disclosure per the theme 40.99 19.12 45.07 26.28 88.58 35.19
Legend: CC = Climate change: risks and opportunities; CE = Carbon emissions; EC = Energy consumption;
RC = Carbon emission reduction and cost; AC = Carbon emission accountability.
Table 5. Descriptive statistics.
Mean Median Std Dev Min Max
Panel A—Continuous Variables
Independent Variable:
FAM 54.44 52.72 15.78 24.05 92.4
BOARD 4.92 5 1.84 2 11
BOIND 41.21 40 11.08 20 100
BOMEET 7.53 6 3.85 2 31
FEMALE 0.11 0 1.27 0 0.67
Control Variables:
AC 3.15 3 0.49 2 5
TOP 58.98 57.27 17.43 23.32 96.31
SIZE (Total Sales in million IDR) 12,614,178 3,917,768 25,172,610 24,569 239,205,000
LEV 46.47 48.11 19.46 4.15 97.26
ROA 4.84 3.76 8.17 −40.14 50.67
AC 37.5 37.08 17.2 3.17 98.92
TOP 2.53 1.13 5.57 0.09 46.5
SIZE (Total Sales in million IDR) 5.73 4.89 9.72 −27.69
Panel B—Categorical Variables Freq. %tage
Control Variables:
NON-BIG4 208 55.91
BIG4 164 44.09
Table 4presents the percentage of items disclosed per theme by each industry. The
firms that disclose the greatest (47.92%) carbon emission information are those in the
infrastructure, utilities, and transportation sectors. Firms in the agriculture sector (45.14%)
come in second, while companies in property, real estate, and building construction (27.58%)
have the lowest disclosure levels. Table 4shows that the theme for the AC category has
received the highest disclosures (88.58%) by the sample firms, followed by the themes for
the EC (45.07%) and the CC categories (40.99%). Interestingly, the CE is the lowest disclosed
by the sample firms. With a mean of 35.19%, the CED score varies between 27.58% (in the
property, real estate, and building construction sectors) and 47.92% (in the infrastructure,
utilities, and transportation sectors). This score is significantly less than the results of 52.8%
by Faisal et al. (2018). The reason could be that most companies in our sample are from the
property, real estate, and building construction industries, with the least disclosed carbon
J. Risk Financial Manag. 2024,17, 263 11 of 24
emission items. The mining, basic industry, and chemicals, infrastructure, utilities, and
transportation sectors have been designed as sensitive industries under Government Law
No. 32/2009 on environmental protection and management. In line with Law No. 32/2009,
our findings imply that companies in these industry sectors take the lead in providing
information on carbon emissions.
Table 5exhibits the univariate descriptive statistics of the independent and control
variables in the study. Panel A displays the statistical summary for continuous variables,
while Panel B demonstrates the dummy regression variables.
According to Table 5, Panel A, on average, family members own about 54.44% of the
stock in the sample company. The board size ranges from two to 11 members, with a mean
of five. The percentage of independent members on the board of commissioners is 41.21%,
somewhat more than the 33.33% mandated by Financial Services Authority Regulation
(POJK) No. 33/2014. The board meeting frequency ranges from two to 31, with an average
of eight. According to POJK 33/2014, the board of commissioners must meet at least once
every two months. Of the total number of board members, women make up 11%. This
lower percentage of female board members reflects the corporate governance practices in
Indonesia. The average number of members of audit committees is three. This number
complies with POJK No. 55 of 2015, which calls for at least three audit committee members.
More than half (58.98%) of the outstanding shares of the firms are held by the top ten
stockholders, with a median shareholding of 57.27% and a standard deviation of 17.43%.
The mean of companies’ total sales in the sample years is IDR12,614,178 million,
with a median of IDR3,917,768 million. The median value is much lower than the mean
figure, suggesting a small number of substantially capitalized companies in the sample
firms. The sample’s total sales likewise have a wide range of minimum and maximum
values, and the data indicate that total sales are skewed to the left. Consistent with the
methodology applied in other studies, this study converts total sales into the natural
logarithm to determine a firm’s size. The average total debt-to-assets ratio (LEV) is 46.47%,
with a median of 48.11%. The low mean ROA (4.84%) indicates that firms experienced
financial hardship during the sample year periods. The AGE variable averages 37.50 years
and has a median of 37.08 years. The mean market-to-book value is 2.53%. In addition,
our sample firms generate small amounts (5.73% of the total assets) of cash flow from
operations. Finally, Panel B shows that the Big 4 firms audited around 44.09% of the sample
observations, suggesting they are a prominent source of audit services for the Indonesian
capital market.
4.2. Correlations
Table 6illustrates the Spearman correlation matrix to assess for multicollinearity
among the variables employed in this study. Correlation results support the study’s hy-
potheses, except for independent boards (BOIND). The results reveal that family ownership
(FAM), board size (BOARD), and board meeting frequency (BOMEET) are significantly
positively correlated (at p< 0.01) with CED. Additionally, there is a negative and significant
(at p< 0.01) relationship between women’s boards of directors (FEMALE) and CED. The
correlation coefficients of all variables are lower than the critical threshold of 0.80 (Cooper
and Schindler 2003). Hence, we assert that there is no indication of multicollinearity among
the variables in the regression models.
Table 6. Correlation matrix.
CED FAM BOARD BOIND BOMEET FEMALE AC TOP SIZE LEV ROA BIG4 AGE P/B
RATIO
FAM 0.139*
BOARD 0.392 * −0.052
BOIND −0.053 −0.048 −0.018 *
BOMEET 0.208 * −0.123 ** 0.134 * −0.077
FEMALE −0.159 * −0.002 0.096 0.009 0.121 **
AC 0.250 * −0.170 * 0.264 * −0.139 * 0.229 * −0.043
J. Risk Financial Manag. 2024,17, 263 12 of 24
Table 6. Cont.
CED FAM BOARD BOIND BOMEET FEMALE AC TOP SIZE LEV ROA BIG4 AGE P/B
RATIO
TOP 0.008 −0.002 −0.084 −0.022 0.046 −0.101 * 0.082
SIZE 0.465 * 0.035 0.425 * 0.049 0.132 * 0.028 0.288 * −0.099
LEV 0.199 * −0.124** 0.099 −0.012 0.164 * 0.148 * 0.160 * −0.179 * 0.246 *
ROA 0.238 * 0.176 * 0.175 * 0.082 −0.085 −0.126 ** 0.079 −0.003 0.342 ** −0.234 *
BIG4 0.296 * 0.060 0.343 * −0.064 0.048 −0.140 * 0.234 * 0.05 0.440 * −0.026 0.207 *
AGE 0.222 * −0.076 0.259 * −0.033 0.284 * 0.054 0.180 * 0.061 0.310 * 0.092 −0.030 0.175 *
P/B
RATIO 0.230 * 0.111 ** 0.102 0.083 0.065 −0.008 0.124 ** −0.022 0.271 * −0.020 0.513 * 0.184 * 0.071
CFO 0.288 * 0.142 * 0.192 * 0.068 −0.066 −0.024 0.068 0.042 0.346 * −0.147 * 0.553 * 0.302 * −0.006 0.464 *
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests).
4.3. Multivariate Regression Results
Table 7provides the outcome of multiple regression for testing our main hypothesis.
Panels A to E present results from regressions with only one independent variable. Panel
F shows the results of all independent variables in one multiple regression. The highest
reported VIF is 2.694 (not included in the table), thus confirming that multicollinearity is
not a concern. The results of regression analyses support the hypotheses that family firms
(H
1
) and firms with larger board sizes (H
2
) disclose more carbon emission information.
However, our research findings do not provide evidence supporting the notion that having
independent supervisory board members (H
3
) and board meeting frequency (H
4
) is linked
to better carbon performance. Finally, our research reveals that, contrary to H
5
, the pres-
ence of women on corporate boards has a negative impact on the carbon performance of
Indonesian firms.
Table 7. Main regression results.
Panel A Panel B Panel C Panel D Panel E Panel F
Beta t-Stat Beta t-Stat Beta t-Stat Beta t-Stat Beta t-Stat Beta t-Stat
(Constant) −3.161 * −
2.325 **
−2.436 * −
2.611 **
−2.763 * −2.461 *
FAM 0.052 2.772 * 0.057 3.118 *
BOARD 1.121 3.333 * 1.265 3.756 *
BOIND −0.054 −1.096 −0.035 −0.713
BOMEET 0.193 1.296 0.257 1.761
FEMALE −7.240 −
2.203 **
−1.566 −
2.244 **
AC 2.772 2.337 ** 1.779 1.524 2.070 1.751 1.825 1.511 2.067 1.762 1.764 1.472
TOP 0.056 1.733 0.064 1.994 ** 0.053 1.638 0.051 1.564 0.049 1.518 0.059 1.872
SIZE 1.659 3.907 * 1.431 3.306 * 1.764 4.135 * 1.787 4.191 * 1.738 4.095 * 1.366 3.192 *
LEV 2.415 0.718 1.720 0.517 1.608 0.476 1.005 0.297 2.455 0.724 3.116 0.938
ROA −0.776 −0.075 0.817 0.079 0.772 0.074 −0.336 −0.032 −1.808 −0.173 −2.286 −0.223
BIG4 0.424 0.333 0.043 0.034 0.576 0.448 0.683 0.530 0.311 0.242 −0.226 −0.179
AGE 1.474 1.423 0.889 0.857 1.331 1.275 1.043 0.979 1.557 1.491 0.878 0.841
P/B RATIO 0.364 2.869 * 0.337 2.679 * 0.334 2.619 * 0.330 2.591 * 0.303 2.380 ** 0.341 2.736 *
CFO −0.562 −0.066 −1.890 −0.222 −0.443 −0.051 1.706 0.197 2.631 0.306 0.040 0.005
YEAR FE Yes Yes Yes Yes Yes Yes
INDUSTRY FE Yes Yes Yes Yes Yes Yes
Adj. R-Sq. 0.385 0.391 0.374 0.375 0.380 0.412
F-Statistic 13.239 * 13.542 * 12.667 * 12.709 * 12.989 * 12.307 *
Sample 372 372 372 372 372 372
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests).
Panels A and F report that the coefficients on the FAM are positive and significant
at p< 0.01 related to the level of CED, suggesting that family members control a large
proportion of companies’ shares associated with an increasing level of CED. Thus, the result
supports H
1
. Our findings demonstrate the advantages of family-controlled businesses over
non-family firms, most likely due to decreased agency costs in publicly traded companies
in Indonesia (Anderson and Reeb 2003). Our findings confirm the SEW hypothesis that
family businesses are more likely to uphold an outstanding image for the company, which
results in increased awareness and orientation toward sustainability and CSR initiatives
(Dyer and Whetten 2006;Iyer and Lulseged 2013;Zellweger et al. 2011). Therefore, the
results are consistent with previous studies, which show that family owners prioritize
J. Risk Financial Manag. 2024,17, 263 13 of 24
social rights and non-economic goals by maintaining better environmental quality (Andres
2008;Berrone et al. 2012;Chrisman et al. 2012;Gómez-Mejía et al. 2007;Iyer and Lulseged
2013). However, our finding contradicts prior studies (Akrout and Othman 2013;Chen and
Jaggi 2001;Muttakin and Khan 2014;Vural 2018) that document family firms tend to be
less socially responsible. This inconsistency might exist due to Indonesia’s unique legal,
political, and cultural values, as examined in past studies.
The regression coefficients for BOARD are positive and statistically significant at
p< 0.01 (Panels B and F); thus, they support the board size hypothesis H
2
: Firms with a
larger board of commissioners disclose more carbon emission information. This finding sug-
gests that boards with a larger number of members can bring a variety of perspectives and
skills. They are better equipped to understand the needs and expectations of various stake-
holders, including employees, customers, communities, and investors. This understanding
can facilitate the development and implementation of CSR initiatives (Beiner et al. 2004;
Gray et al. 1995) and the effective communication of CED information to meet societal needs
(Jizi 2017;Ramon-Llorens et al. 2020). By promoting inclusivity, equity, and comprehensive
understanding, large boards can effectively set CED agendas, make informed decisions,
and contribute to the sustainable development of organizations and society. In addition,
empirical evidence from previous studies (Cancela et al. 2020;Mallin and Michelon 2011;
Walls et al. 2012) supports the notion that the size of the supervisory board has a positive
and significant impact on the disclosure level of corporate environmental sustainability.
The findings reported in Panels C and F do not support H
3
regarding the positive
effect of board independence on CED. Our results fail to support prior studies (e.g., Adams
and Hossain 1998;García-Meca and Sánchez-Ballesta 2010;Patelli and Prencipe 2007) that
claim that independent members on the board positively impact corporate social disclosure.
According to our results, the fact that independent members sit on the boards does
not lead to a higher disclosure of carbon emission information. Yet, independent board
members presume to have a broader outlook beyond companies’ financial performance and
to be more inclined toward social responsibility and disclosure (Arora and Dharwadkar
2011). However, our findings note that this does not guarantee that their attitude toward
CED will differ from that of the other members. The relationship between independent
board members and carbon emission disclosure is more complex than previously thought.
While independent commissioners are expected to act in the best interest of shareholders
and hold management accountable, they may not always prioritize environmental concerns
or have the expertise to evaluate and push for increased disclosure of carbon emissions. A
possible explanation is that our sample’s proportion of independent boards is slightly larger
(Table 5) than the minimum number required by PJOK No. 3/2014. Thus, an independent
board of commissioners seems to comply with regulations and has not significantly im-
pacted carbon emission performance. Despite the common belief in mainstream corporate
governance practices and the requirement for Indonesian listed companies to have at least
33,33% independent commissioners, there is no clear indication that these independent
commissioners significantly enhance environmental sustainability.
The coefficients on BOMEET (Panel D and F) are positive but statistically insignificant,
suggesting no direct link between the diligence or overall activity of the board and carbon
emission performance for our study sample. Our results are consistent with a study by
Haji (2013) in Malaysia. Although previous literature (e.g., Davidson et al. 2005;Kent and
Stewart 2008;Lipton and Lorch 1992;Vafeas 1999) argues that meeting frequency has been
associated with better firm performance and higher reporting quality, it can turn out to
have a less significant impact when the meeting is filled with less crucial agendas (Menon
and Williams 1994). Further, Menon and Williams (1994) argue that the higher frequency of
board meetings is seen as only a rough estimation of board activities as it does not indicate
the quality and work accomplished during the meeting. In summary, the frequency of
board meetings is often viewed as an indicator of the level of activity and engagement of
supervisory boards in carrying out their duties; however, it is important to note that the
J. Risk Financial Manag. 2024,17, 263 14 of 24
number of meetings does not always reflect their effectiveness or productivity or enhance
monitoring quality.
Opposite to our H
5
, the coefficients on FEMALE are negative and statistically signifi-
cant at p< 0.05 (Panels E and F), suggesting that the participation of women on corporate
boards has a negative influence on Indonesian firms’ carbon emission reporting. This
finding raises questions about the effectiveness of gender diversity in corporate governance
in promoting environmental responsibility. Our results align with a study by Cucari et al.
(2018) and Qosasi et al. (2022), who report a negative and significant relationship be-
tween female boards of directors and environmental, social, and governance performances.
Including women in commissioner roles does not seem to result in increased oversight.
Despite common arguments suggesting that diversity in board composition could bring
unique perspectives and enhance monitoring effectiveness, our findings do not support
this notion. The limited presence of female directors included in our sample (as indicated in
Table 5) might be a contributing factor to their minimal influence on board decisions, as the
majority vote often sways them. Culture could be another potential factor that may be asso-
ciated with this phenomenon. Lindawati and Smark (2015) asserted that within Indonesian
culture, particularly Javanese culture, a belief exists that women should not place the same
level of importance on their careers as men. Women are traditionally seen as followers
and expected to adhere to men’s leads. Past literature argues that women’s representation
appears to have minimal impact unless a critical mass of at least three members is present
on a board (Post et al. 2011). Our findings fail to verify a study by Barako and Brown
(2008), Mallin and Michelon (2011), and Liao et al. (2015), who highlighted that a high
proportion of females on boards is positively associated with companies’ CSR performance.
Those authors imply that the presence of a woman on the boards of directors promotes the
establishment, implementation, and reporting of social and environmental-related policies.
Thus, a women’s board of directors enhances shareholders’ social welfare and boosts the
firm’s reputation.
4.4. Additional Analyses
To boost the credibility of the main findings, we carried out a variety of extra anal-
yses. First, it is suggested that family-owned businesses can have both advantages and
disadvantages when running the company (Anderson and Reeb 2003). When ownership
within the family is less concentrated, it has a favorable effect on business performance,
supporting the monitoring hypothesis. However, as the level of family share ownership
increases, the relationship between the two variables becomes negative. Combining these
two assumptions leads to the prediction of a non-linear relationship between concentrated
family ownership and the disclosure of carbon emissions. Similarly, Boone et al. (2007)
contend that the size of a board reflects a trade-off between the specific advantages and
disadvantages of monitoring within a firm. Consequently, numerous empirical studies
have endeavored to determine the ideal size for a company’s board of directors. Lipton
and Lorch (1992) provide evidence that a board size of less than ten is optimal, as a smaller
board functions more effectively and is less susceptible to manipulation by delegated
directors. Conversely, Jensen (1993) proposes that supervisory board sizes in the US tend to
be excessively large and recommends that boards consist of no more than eight members.
Table 8examines the nonlinearities between family ownership, board of commissioner size,
and carbon emission performance.
The coefficients for family ownership and its square in Panels A and C are positive
and negative (p< 0.01 and p< 0.05), showing a non-linear link between family businesses
and carbon performance. The results infer that carbon performance improves as family
ownership rises to a certain amount (the inflection point is 42.34%, but omitted in the
table for conciseness), providing evidence for the monitoring hypothesis. Once family
equity exceeds this threshold, carbon performance decreases, leading to the dominance
of the expropriation hypothesis. The majority family shareholders may take advantage of
their control over the company to the detriment of the minority shareholders. Our results
J. Risk Financial Manag. 2024,17, 263 15 of 24
suggest that while family ownership can initially lead to better carbon performance due
to the family’s long-term perspective and commitment to sustainability, there is a tipping
point where the interests of the majority family shareholders may diverge from those of the
minority shareholders and the broader stakeholder community. This deterioration can be
attributed to several factors. Firstly, as family ownership increases, there is often a lack of
external oversight and accountability, leading to a decrease in implementing sustainable
practices. Additionally, as family ownership becomes more concentrated, decision-making
power becomes centralized within a smaller group of individuals. This phenomenon can
lead to a lack of diversity in perspectives and ideas, hindering innovation and the adoption
of environmentally friendly technologies and practices.
Table 8. Nonlinearities relationship.
Variables
Panel A Panel B Panel C
Beta t-Stat Beta t-Stat Beta t-Stat
(Constant) −3.598 ** −3.522 * −2.943 *
FAM 1.235 2.500 * 1.055 2.774 * 1.244 2.590 *
FAM -Square −1.401 −1.958 ** −1.469 −2.052 **
BOARD 1.639 4.705 * 3.251 2.353 ** 3.486 2.526 *
BOARD-Square −4.133 −1.238 −4.608 −1.383
BOIND −0.059 −1.133 −0.065 −1.261 −0.057 −1.102
BOMEET 0.339 2.132 ** 0.406 2.568 * 0.357 2.242 **
FEMALE −2.687 −3.667 * −2.705 −3.681 * −2.640 −3.605 *
AC 2.254 1.772 2.292 1.797 2.250 1.771
TOP −0.041 −0.875 0.022 0.650 −0.044 −0.942
SIZE 1.799 4.382 * 1.3827 4.406 * 1.872 4.528 *
LEV 5.440 1.621 5.905 1.758 5.435 1.621
ROA −22.493 −2.145 ** −20.863 −1.980 ** −21.565 −2.055 **
BIG4 1.314 0.992 1.168 0.882 1.472 1.108
AGE 0.993 0.918 0.918 0.845 0.937 0.867
P/B RATIO 0.134 1.056 0.159 1.262 0.130 1.030
CFO 21.527 2.522 * 21.329 2.490 * 21.232 2.490 *
YEAR FE Yes Yes Yes
INDUSTRY FE Yes Yes Yes
SUMMARY
Adj. R-Squared 0.303 0.301 0.307
F-Statistic 11.885 * 12.657 * 11.290 *
Sample Size 372 372 372
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests).
The coefficients for BOARD and BOARD-Square (Panels B and C) are positive and
negative, which may indicate a non-linear relationship between board of commissioner
size and carbon performance. However, the coefficients for BOARD-Square are statistically
not significant and thus do not confirm a non-linear relationship between board size and
carbon emission disclosure.
Second, this study examines the impact of family involvement in the firm. Family
members in key management roles can better align the company’s interests, enhancing
firm performance and reputation (Anderson and Reeb 2003). We use two active family
controls, considering the family member’s participation in the CEO (FAMCEO) and the
board of commissioners (FAMBOC). The value of FAMCEO is denoted as 1 if the family
controls the company and a family member serves as the chief executive officer; otherwise,
it is set to 0. FAMBOC is the total number of family members on the commissioners’ board.
Table 9provides a summary of the outcomes of this extra examination. Panels A and C
indicate a positive but statistically insignificant effect of the family CEO on the level of
CED, implying that the presence of a family member in the CEO position has no significant
impact on carbon emission performance. One explanation might be that a family CEO
prioritizes and considers environmental performance using different frames of reference.
The coefficients on FAMBOC are positive and significant at p< 0.01 (Panels B and C). These
results are consistent with a study by Ibrahim and Angelidis (1995) and Garcia-Sanchez
et al. (2014) suggesting that family members who serve on the board of commissioners
J. Risk Financial Manag. 2024,17, 263 16 of 24
often demonstrate a greater interest in social and environmental issues while also being
conscious of the public’s expectations for improving the company’s reputation. This finding
also suggests that the family utilizes their position on the board to influence the company’s
carbon emission performance.
Table 9. Active family control and carbon emission disclosure.
Variables
Panel A-Family CEO Panel B-Family BOC Panel C-Active Family
Control
Beta t-Stat Beta t-Stat Beta t-Stat
(Constant) −2.429 ** −2.605 * −2.597 *
FAM 0.053 2.608 * 0.038 2.282 ** 0.038 2.263 **
FAMCEO 0.669 0.429 0.062 0.039
FAMBOC 1.250 2.017 ** 1.256 1.968 **
BOARD 1.283 3.776 * 1.209 3.592 * 1.207 3.544 *
BOIND −0.034 −0.693 −0.027 −0.550 −0.027 −0.583
BOMEET 0.521 1.709 0.247 1.695 0.247 1.689
FEMALE −1.640 −2.279 ** −2.014 −2.761 * −2.009 −2.712 *
AC 1.798 1.496 2.272 1.863 2.271 1.860
TOP 0.062 1.913 0.074 1.855 0.074 1.768
SIZE 1.355 3.158 * 1.338 3.138 * 1.339 3.132 *
LEV 3.158 0.949 3.974 1.192 3.974 1.190
ROA −2.468 −0.240 −2.546 −0.250 −2.530 −0.248
BIG4 −0.245 −0.194 −0.730 −0.569 −0.730 −0.569
AGE 0.836 0.795 0.749 0.719 0.753 0.719
P/B RATIO 0.339 2.717 * 0.327 2.633 * 0.327 2.629 *
CFO −0.099 −0.012 0.917 0.108 0.934 0.110
YEAR FE Yes Yes Yes
INDUSTRY FE Yes Yes Yes
SUMMARY
Adj. R-Squared 0.411 0.417 0.416
F-Statistic 11.774 * 12.068 * 11.552 *
Sample Size 372 372 372
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests).
The third test explores how boards’ social and human capital affect carbon emission
disclosure. We also examine the influence of the power of boards as moderators on the
association between the supervisory board categories and CED. Haynes and Hillman
(2010) argue that when board members deliver expertise, background, knowledge, or
skills, they are supplying human capital to the board. The boards provide social capital
when they have external resources and maintain connections with external organizations.
Thus, the board of commissioners should not be considered homogeneous. Following
Ramon-Llorens et al. (2020) and Armano and Scagnelli (2012), we classify members of
the board of commissioners into four categories: industry experts (BOINDUS), advisors
(BOADV), community leaders (BOLEAD), and academic (BOACAD) backgrounds. This
category is based on the taxonomy of directors’ resource dependence roles proposed by
Hillman et al. (2000). Board members with industry experts (BOINDUS) when they have
expertise, capabilities, and a professional background as an executive or top management.
BOADV is when these boards have developed their role as insiders in auditing, accounting,
financial, marketing, or other consulting companies. BOLEAD is when the members can
be classified as politicians, heads of non-profit organizations, or other significant public
positions. Finally, BOACAD is when they are currently or formerly a faculty member2.
Panel A of Table 10 presents the effect of board members classified as industry ex-
perts, advisors, community leaders, and academic backgrounds on CED. Interestingly, the
coefficients on those four categories of boards are all negative but statistically insignif-
icant, suggesting that the attitude toward CED will not differ from those categories of
boards. In addition, we investigate the moderating effect of boards under the proposition
that boards expose substantial influence on CED when they have a large member size.
We generate a moderator variable (board power) to test this hypothesis. Board power
(POWERBO) is a dummy variable equal to 1 if the total number of board members is higher
J. Risk Financial Manag. 2024,17, 263 17 of 24
than its median value and 0 otherwise. Panel B of Tabel 10 exhibits results from regressions
with the moderating effect of board power (BOPOWER) for all board of commissioner
backgrounds. The coefficients on POWERBO*BOINDUS and POWERBO*BOADV are
negative but statistically insignificant, implying that the interaction effect between a board
of commissioners and both specific knowledge (industry expertise and advisor) does not
have a significant influence on carbon emission quality. Additionally, the positive asso-
ciation between POWERBO*BOLEAD and CED suggests that a more significant board
member with a community leader background might make companies more sensitive to
environmental issues. However, this coefficient is statistically not significant. Concerning
board members with academic backgrounds, Panel B exhibits a negative and statistically
significant (at p< 0.01) impact of boards with educational backgrounds on CED for firms
with high-powered boards. This result suggests that the adverse effects of boards on CED
(Panel A) are more robust for companies with a high presence of academic members on the
board of commissioners. Our finding indicates that the dominance of faculty staff on the
supervisory board tends to lower carbon emission performance. The possible explanation
for these results is the faculty staff’s lack of managerial skills and entrepreneurial expe-
rience (Cyert and Goodman 1997;Litan et al. 2007). Another argument is because of the
lack of time caused by their academic commitments or the conflicts between the university
and business cultures (Armano and Scagnelli 2012). Similarly, Yin et al. (2012) argue that
those board members have exclusively an academic background and little practical and
industrial experience, which limits their role.
Table 10. Board characteristics and carbon emission disclosure.
Variables Panel A Panel B
Beta t-Stat Beta t-Stat
(Constant) −2.604 * −3.119 *
FAM 0.060 3.038 * 0.067 3.365 *
BOARD 1.395 4.058 * 1.423 2.783 *
BOINDUS −1.090 −0.284 5.263 1.121
BOADV −0.727 −0.298 1.889 0.642
BOLEAD −3.995 −1.660 −6.624 −2.270 **
BOACAD −4.064 −0.906 8.398 1.368
POWERBO 14.410 1.557
POWERBO*BOINDUS −14.023 −1.582
POWERBO*BOADV −2.587 −0.469
POWERBO*BOLEAD 5.357 1.135
POWERBO*BOACAD −5.448 −2.751 *
BOIND −0.007 −0.137 0.008 0.153
BOMEET 0.319 2.065 ** 0.250 1.597
FEMALE −1.700 −2.419 * −1.474 −2.040 **
AC 2.705 2.089 ** 2.871 2.207 **
TOP 0.058 1.761 0.079 2.379 **
SIZE 1.496 3.418 * 1.413 3.227 *
LEV 1.812 0.530 2.947 0.859
ROA −2.717 −0.265 −4.404 −0.430
BIG4 −0.770 −0.592 −0.745 −0.572
AGE 1.107 1.004 0.771 0.684
P/B RATIO 0.338 2.700 * 0.323 2.586 *
CFO −0.579 −0.068 −0.590 −0.069
YEAR EFFECT Yes Yes
INDUSTRY EFFECT Yes Yes
SUMMARY
Adj.R-Sq 0.410 0.420
F-Statistic 10.658 * 9.397 *
Sample 372 372
Legend: * and ** indicate significance at p< 0.01 and p< 0.05 (based on two-tailed tests).
J. Risk Financial Manag. 2024,17, 263 18 of 24
5. Conclusions
5.1. Discussion of Results
This study investigates the impact of family ownership and supervisory board charac-
teristics on carbon emission disclosure. This study proposes five hypotheses (H
1
to H
5
):
Family ownership, larger supervisory board sizes, more independent board members, fre-
quent board meetings, and more female board members disclosing more carbon emission
information. The regression analysis findings confirm that family firms (H
1
) and firms with
larger board sizes (H
2
) tend to disclose a greater amount of carbon emission information.
Nevertheless, our research results do not support the notion that having independent
supervisory board members (H
3
) and frequent board meetings (H
4
) are associated with
improved carbon performance. Lastly, our research indicates that, contrary to hypothesis
H
5
, the participation of women on corporate boards has a detrimental effect on the carbon
performance of Indonesian companies.
The study reveals a significant positive association between family firms and carbon
emission performance. The results support the SEW theory, which argues that family-
controlled firms are more likely to be driven by non-financial goals than exclusively fi-
nancial objectives (e.g., Berrone et al. 2012;Chrisman et al. 2012;Gómez-Mejía et al. 2007).
Specifically, family firms tend to maintain the firm’s excellent reputation, leading to higher
awareness and orientation towards sustainability and corporate social responsibility activi-
ties. Consistent with prior research (Cancela et al. 2020;Mallin and Michelon 2011;Walls
et al. 2012), this study also finds that supervisory board size is positively associated with car-
bon performance. Our results align with the resource dependency theory, which contends
that firms with larger and more diverse boards will be more successful in establishing their
CSR agendas and promoting the dissemination of CSR information because these boards
represent a more comprehensive range of perspectives and backgrounds (Jizi 2017;Ramon-
Llorens et al. 2020). Contrary to our expectations, the OLS model reports that independent
members on the boards and board meeting frequencies do not influence the carbon emis-
sion performance of Indonesian non-financial firms. These findings negate the belief that a
resource-rich board of commissioners contributes to better reporting practices. Although
resource dependence theory notes that those board characteristics are assumed to be the
platform to protect shareholders’ interests, they have not been well demonstrated in the
Indonesian context. Additionally, our result suggests that female boards of commissioners
have a negative impact on Indonesian firms’ carbon emission reporting.
The additional analyses confirm a non-linear relationship between concentrated family
ownership and the disclosure of carbon emissions. Family firms initially improve carbon
performance due to the family’s long-term perspective and dedication to sustainability.
However, once family equity exceeds a specific threshold, the performance of carbon emis-
sions starts to decline. Furthermore, family board members are positively and significantly
associated with carbon emission disclosure. Our findings suggest that family-controlled
firms are more likely to use their indirect influence through substantial ownership and
a seat on the board, corresponding to their commitment to the greater good of the envi-
ronment and, thus, SEW objectives. In other words, the family remains attached to their
business despite giving up executive positions. Finally, we find a negative and significant
impact of boards with academic backgrounds on carbon emission disclosure for companies
with high-powered boards. Our results indicate that the dominance of faculty staff on the
board of commissioners tends to lower carbon performance. Faculty members, renowned
for their expertise in various academic disciplines, bring a unique perspective to the super-
visory board. Their presence is often sought after due to their extensive knowledge and
research in environmental science, sustainability, and corporate social responsibility. While
their inclusion may seem beneficial in promoting environmentally conscious practices, our
findings suggest otherwise.
J. Risk Financial Manag. 2024,17, 263 19 of 24
5.2. Theoretical Implications
This study’s results infer that understanding SEW precepts and how they relate to
families is crucial to comprehending Indonesian corporate carbon emissions disclosures.
Family-controlled entities tend to disclose more information about their carbon emissions
than non-family firms. This finding implies that the SEW agenda of family businesses
may be better aligned with efforts to minimize emissions and promote transparency and
accountability for their environment. Specifically, family involvement in the board of com-
missioners is linked to higher levels of carbon emission disclosure. The results of this research
contribute to the global body of knowledge by investigating the possible advantages of family
business environmental practices. Additionally, this study expands on the existing literature
regarding corporate governance, mainly focusing on the significance of supervisory boards, and
supports the resource dependence theory by highlighting the critical role of supervisory boards
in monitoring functions. The study supports the view that board commissioners are a com-
pany’s most valuable resource in improving the quality of corporate environmental disclosure
(Allegrini and Greco 2013;Chalu 2021;Pfeffer and Salancik 1978).
5.3. Practical Implications
This study highlights the importance of understanding familial motivations and fam-
ily board memberships when formulating policies to improve information transparency
on Indonesian carbon emissions. A deeper understanding of familial SEW leanings may
benefit corporate Indonesia in managing carbon emission reduction or understanding the
carbon cycle. By comprehending these motivations, policymakers can tailor their strategies
and initiatives to align with the values and priorities of families. The non-linear relationship
between family ownership and carbon performance highlights the importance of monitor-
ing and governance mechanisms to prevent the potential negative impacts of excessive
family ownership on environmental performance. Firms with significant family ownership
should consider implementing transparent reporting, independent board oversight, and
stakeholder engagement to prioritize the interests of all shareholders and maintain a strong
commitment to sustainability. The implications of our findings extend beyond the specific
context of our study. They hold importance for other developing economies that share
similar economic and cultural contexts. These economies can learn from our research and
apply the insights to their family businesses and corporate governance practices.
5.4. Research Limitations
There are certain constraints associated with this study. The carbon emission data
were gathered from the annual reports of publicly listed firms between 2017 and 2019. It
is recommended that future research concentrate exclusively on sustainability or social
responsibility reports as a data source for capturing and analyzing carbon emission in-
formation. These reports are expected to analyze event firms’ communication regarding
carbon emission disclosure comprehensively. Furthermore, our research thoroughly exam-
ines data before the emergence of COVID-19. Future studies may explore the time frame
encompassing COVID-19 (including datasets from 2020 to 2022) to determine if there are
any discrepancies in the results.
Author Contributions: Conceptualization, H.S., N.A.S. and R.R.; methodology, H.S., N.A.S., R.R. and
E.A.; writing-original draft preparation, R.R. and E.A.; formal analysis, R.R. and E.A.; resources, E.A.;
writing-review and editing, H.S., N.A.S. and R.R.; supervision, H.S. and E.A.; validation, H.S. and
N.A.S. All authors have read and agreed to the published version of the manuscript.
Funding: The APC is funded by the author.
Data Availability Statement: The data that support the findings of this study are available on request.
Conflicts of Interest: The authors declare no conflict of interest.
J. Risk Financial Manag. 2024,17, 263 20 of 24
Notes
1
Indonesia has a two-tier board structure, the management team is responsible for governance, while the supervisory board is in
charge of oversight. The board of commissioners has been given the formal name by the supervisory board. For this reason,
throughout the paper, the terms ‘supervisory board’ and ‘board of commissioners’ will be used interchangeably.
2
In Indonesia, the board of commissioners is not a full-time position. Thus, it is very common, for example, a professor of a
university is also a member of the board of commissioners in a publicly listed company.
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