:: Biblioteca Digital de Ecopsicologia (BDE)

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically Forward‑Thinking Companies

Journal of Business Ethics (2022) 178:571–595

https://doi.org/10.1007/s10551-021-04800-9

ORIGINAL PAPER

Corporate Accountability Towards Species Extinction Protection:

Insights from Ecologically Forward‑Thinking Companies

Lee Roberts1 · Monomita Nandy1 · Abeer Hassan2 · Suman Lodh3 · Ahmed A. Elamer1

Received: 8 September 2020 / Accepted: 18 March 2021 / Published online: 10 April 2021

Abstract

This paper contributes to biodiversity and species extinction literature by examining the relationship between corporate

accountability in terms of species protection and factors affecting such accountability from forward-thinking companies.

We use triangulation of theories, namely deep ecology, legitimacy, and we introduce a new perspective to the stakeholder

theory that considers species as a ‘stakeholder’. Using Poisson pseudo-maximum likelihood (PPML) regression, we examine a

sample of 200 Fortune Global companies over 3 years. Our results indicate significant positive relations between ecologically

conscious companies that are accountable for the protection of biodiversity and species extinction and external assurance,

environmental performance, partnerships with socially responsible organizations and awards for sustainable activities. Our

empirical results appear to be robust in controlling for possible endogeneities. Our findings contribute to the discussion on

the concern of species loss and habitat destruction in the context of corporate accountability, especially in responding to

the sixth mass extinction event and COVID-19 crisis. Our results can also guide the policymakers and stakeholders of the

financial market in better decision making.

Keywords Biodiversity · Species extinction · Deep ecology · Legitimacy · Poisson pseudo-maximum likelihood ·

Stakeholders

Introduction

In recent years, policymakers, NGOs, academics, and com-

panies have devoted greater attention to the strategic impli-

cations of biodiversity loss and species extinction (hereafter

* Monomita Nandy

monomita.nandy@brunel.ac.uk

Lee Roberts

Lee.Roberts@brunel.ac.uk

Abeer Hassan

abeer.hassan@uws.ac.uk

Suman Lodh

s.lodh@mdx.ac.uk

Ahmed A. Elamer

ahmed.elamer@brunel.ac.uk

1 Brunel University London, Uxbridge UB8 3PH, UK

2 University of the West of Scotland, G226, Gardner Building,

Paisley PA1 2BE, UK

3 Middlesex University, The Burroughs, Hendon,

London NW4 4BT, UK

B/E). Yet, the relationship between corporate accountability1

in terms of species2 protection and factors affecting such

accountability (assurance, environmental performance,

country, partnerships, etc.) remains underexplored in

accounting and business literature (Atkins & Atkins, 2018;

Gaia & Jones, 2019; Reade et al., 2015). Biodiversity and

species extinction are part of wider global environmental

challenges facing humanity (Sobkowiak et al., 2020), with

the United Nations Sustainable Development Goals (SDGs),

specifically SDGs 14 and 153 the most recent call to action

1 In this paper, we refer to accountability as companies’ disclosure

on how to protect species to eliminate biodiversity loss in the future.

2 We identify species as the variety of plants (flora) and animals

(fauna) that provide balanced ecosystems essential for human survival

and welfare (Sandifer et al., 2015).

3 We refer to the United Nations Sustainable Development Goals

(SDGs) 14 ‘Life below water—Conserve and sustainably use the

oceans, seas and marine resources for sustainable development’ and

SDG 15 ‘Life on Land—Protect, restore and promote sustainable use

of terrestrial ecosystems, sustainably manage forests, combat desertifi-

cation and halt and reverse land degradation and halt biodiversity loss’.

1 3 Vol.:(0123456789)

572

L. Roberts et al.

to develop solutions and protect the planet from further bio-

diversity loss4 (UN, 2020a).

It is acknowledged that business activities are recognized

as one of the main drivers of biodiversity loss and species

extinction (Hassan et al., 2020a; Maroun & Atkins, 2018;

Roberts et al., 2020a). Thus, we contribute to the extant lit-

erature and examine how the accountability of ecologically

conscious/forward-thinking5 (hereafter EC/FT) companies

can prevent further species and biodiversity loss in the future

and align with SDGs 14 and 15. Our motivation for this

paper is to respond to the recent calls to contribute to devel-

oping solutions for the B/E crisis (Gibassier et al., 2020).

This research is significantly timely, as experts suggest that

pandemics such as COVID-19 are a result of habitat loss,

wildlife trafficking, and humanity’s destruction of biodiver-

sity (Ceballos et al., 2020; Johnson et al., 2020). Potentially,

COVID-19 may not be an isolated pandemic; therefore, there

must be a seismic shift from companies in valuing and pro-

tecting nature. In addition, biodiversity loss is now recog-

nized as one of the top five global risks (WEF, 2020)6 with

severe implications for society if transformational changes

are not made (WHO, 2020).

The above discussion motivates us to examine how EC/

FT companies that initiated efforts in conserving and pro-

tecting species before the current pandemic can influence

companies’ reporting in the post-COVID-19 era. Therefore,

we would expect corporates to consciously make tremen-

dous efforts in conserving biodiversity and protecting spe-

cies from extinction as companies realize their dependence

on nature. Thus, our findings can guide and encourage com-

panies to improve future reporting to achieve SDGs 14 and

15 targets by 2030, as “accounting academics can and should

play a substantial role helping embed policy and action at

an organizatinal level in a way that contributes towards the

4 We define biodiversity loss as the decline of the infrastructure of

ecosystems caused by the abuse from human and business overex-

ploitation (Hassan et al., 2020a; Roberts et al., 2020a).

5 We define ecologically conscious or forward-thinking companies as

those companies that realize the importance of biodiversity and spe-

cies extinction and have provided disclosure on how to protect both

biodiversity and species before the COVID-19 crisis. Therefore, we

use ecologically conscious and forward-thinking companies inter-

changeably.

6 The recent Intergovernmental Science-Policy Platform and Ecosys-

tem Services Global Assessment Report (IPBES, 2019) outlines one

million species which are under threat from extinction within dec-

ades if transformational changes are not made. Such species decline

challenges organizational viability as they are dependent on healthy

ecosystems providing natural assets for sustainable economic activity

(European Business and Biodiversity Campaign, 2020). Although no

monetary value can be placed on natural assets (Jones & Solomon,

2013), the value ecosystems provide in resources is estimated to be

between $125 to $145 trillion per year (Costanza et al., 2014), high-

lighting the intrinsic worth of natural resources to businesses.

achievement of the SDGs” (Bebbington & Unerman, 2018,

p. 2). The findings of this study will extend the existing

academic findings on emerging issues about B/E account-

ing (e.g., Adler et al., 2018; Atkins & Maroun, 2018; Has-

san et al., 2020a, b). The combination of the theoretical

framework along with robust empirical findings will assist

academics in advancing this stream of emerging literature,

and help companies to understand how to consider various

factors to be sustainable in the future. Additionally, this

will give a clear indication to regulators about the changes

required to motivate companies for preventing further B/E

loss.

Furthermore, extant B/E literature is limited. Specifically,

most studies employed one theoretical construct to explain

the companies’ accountability towards the extinction of spe-

cies, which contains several caveats. We respond to the pre-

vious call (Gaia & Jones, 2019) that a single theory is not

adequate in explaining B/E disclosure, by adopting a trian-

gulation of deep ecology, legitimacy, and stakeholder theo-

ries. By applying deep ecology and stakeholder concepts, we

support the argument of Roberts et al. (2020b), who suggest

that species are of fundamental value to business survival

and are main stakeholders in society; therefore, companies

should consider species as an important stakeholder of their

business. Legitimacy theory can explain how a company’s

legitimacy can be achieved by considering species as impor-

tant as other stakeholders in company operations. The com-

prehensive theoretical model allows us to contribute to the

limitation of the extant literature theoretically. To date, semi-

nal contributions in literature stimulate the development of

species protection by providing extinction accounting frame-

works (Atkins & Maroun, 2018; Hassan et al., 2020b) and

examination of organizational accountability for biodiversity

(Adler et al., 2018; Maroun et al., 2018). Emerging studies

(e.g., Raar et al., 2020) open a debate on how the incorpora-

tion of biodiversity accountability can assist in the preven-

tion of further species loss. Flowing from extant literature,

this paper builds on these bodies of work to empirically

examine company disclosure on species and what factors

motivate relationships for such disclosure. This research

responds to Roberts et al. (2020b) who identify the urgency

in B/E literature for the examination of species protection

disclosure to extend knowledge in the field and contribute

to advancing solutions.

Based on the above discussion, the objective of this paper

is to investigate factors affecting the relationship between cor-

porate accountability and species protection of EC/FT compa-

nies. We believe that providing disclosure on species protec-

tion enhances stakeholders’ trust and accountability (Hassan

et al., 2020b). To empirically test our idea, this study uses a

sample of the top 200 companies from Fortune Global in 2012,

2014, and 2016, to highlight how EC/FT companies reported

on the protection of species before the recent pandemic and

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

573

provide a springboard to develop solutions after the pandemic.

These companies directly or indirectly make significant use

of ecosystems, and therefore gain the most public attention

(Adler et al., 2018; Hassan et al., 2020b). Our justification is to

present how EC/FT companies report on conserving and pro-

tecting biodiversity and species, which could influence report-

ing in the recent and coming years. By applying advanced

empirical analysis, we find that companies that are disclosing

responsibly about species and are actively protecting against

extinction, for which these companies are recognized by

awards, have extended partnerships with species protection

organizations and are also getting favorable assurance for their

business.

The study makes several contributions to the extant B/E

literature. First, to the best of our knowledge, no studies have

examined the relationship between species disclosed by organ-

izations and its determinant factors. Therefore, this paper aims

to close this gap by contributing to the extant B/E literature

and demonstrate how EC/FT companies are displaying signifi-

cant efforts on species protection and restoring habitats. Sec-

ond, theoretically, we adopt a triangulation of theories; deep

ecology, legitimacy and stakeholder theories. We also suggest

that species should be considered as one of the main stake-

holders’ categories in addition to customers, employees, etc.,

as businesses have a two-way relationship with biodiversity

and species, including both the impact of companies on bio-

diversity and the impact of biodiversity on companies (Adler

et al., 2018). Third, our paper has an empirical contribution.

Instead of adopting OLS regression that is commonly used by

previous studies (Adler et al., 2018; Hassan et al., 2020b), we

test and create Poisson pseudo-maximum likelihood (PPML)

regression with a multi-way fixed effects model. We believe

the PPML model is more relevant to explore the relationship

between the species disclosed by companies and determinant

factors because our disclosure index includes positive count

values only. Fourth, our study has a number of implications for

policymakers. The proposed empirical model and theoretical

framework in this study will allow policymakers to process a

post-2020 framework to reshape the global relation with nature

(UN, 2020b) and support the United initiatives and achieve the

SDGs 14 and 15 objectives. The study will guide decision-

makers to understand how disclosure of species protection by

companies can assist society to mitigate further B/E loss in

the future. Finally, our paper responds to recent calls (Gaia

& Jones, 2019; Lambooy et al., 2018) to develop solutions by

showing how the potential for reporting for B/E can mitigate

the further risk of ecological collapse.

The rest of the paper is structured as follows: the next sec-

tion covers the literature review. Section three discusses the

theoretical literature. Section four discusses empirical litera-

ture and hypothesis development. Section five illustrates the

research design. Section six presents the empirical analysis.

Finally, a discussion of findings and limitations is exhibited

in the last section.

Corporate Accountability, Ecology,

and Species Extinction Protection Around

the World

Research on corporate accountability for B/E is in its

infancy (Addison et al., 2019; Adler et al., 2017) and is

an emerging strand of literature (Haque & Jones, 2020).

To date, academics have been relatively silent on examin-

ing the role of companies in conserving biodiversity and

species protection (Adler et al., 2018) and thus, there is

a huge call for company awareness from stakeholders of

businesses (Hassan et al., 2020b). To provide context,

B/E accounting emerges from biodiversity reporting and

this extends to include the ‘extinction’ element due to the

severity of the decline of nature (Atkins & Maroun, 2018).

The early seeds of biodiversity reporting were set by Jones

(1996) who suggested that organizations are stewards of

natural capital and have a moral duty to protect and to

publicly disclose their efforts (Atkins et al., 2014). Early

empirical studies began to explore reporting of compa-

nies on biodiversity issues at country level (Boiral, 2016;

Rimmel & Jonäll, 2013; van Liempd & Busch, 2013)

and industry level (Adler et al., 2017; Boiral & Heras-

Saizarbitoria, 2017). Prior studies are consistent in finding

that most companies provide poor disclosure, vague state-

ments, and are generally unimpressive with their efforts to

manage and protect biodiversity. Literature suggests that

companies fail to recognize the risk of biodiversity loss,

leaving them unconvinced that conservation warrants their

efforts (Skouloudis et al., 2019). It seems to be only when

endeavors provide rewards of stakeholder impressions or

reputational advantage that companies will pay attention

(Bhattacharya & Managi, 2013; Hassan et al., 2020b).

It is argued that biodiversity reporting on its own is

insufficient (Atkins & Maroun, 2018; King & Atkins,

2016). The widely adopted Global Reporting Initiative

(GRI) standards only make some reference to biodiversity

(Jones & Solomon, 2013), and therefore company account-

ability is limited. Companies following the GRI frame-

work are found to be indulging in impression management

(Gray & Milne, 2018; Solomon et al., 2013), with a lack of

consistent, transparent reporting. Atkins and Atkins (2018)

suggest that continuing to report in this method will lead

to a fossil record of species. Haque and Jones (2020) sup-

port the previous arguments and mention that companies

are using GRI standards as a mechanism to refer to bio-

diversity, providing symbolic statements and failing to

provide clarity on operational impact to natural capital.

574

L. Roberts et al.

In response to the limitation mentioned above, extinc-

tion accounting evolves from biodiversity reporting by

critically recognizing the need to address the current

extinction crisis (Atkins & Maroun, 2018). Incorporating

GRI biodiversity principles, extinction accounting aims

to promote change by companies and reverse species loss

(Atkins & Atkins, 2018; King & Atkins, 2016), providing

companies opportunity to disclose how they are acting to

prevent further extinctions (Hassan et al., 2020b).

The framework provides the opportunity to include nar-

rative detail and self-reflection, and to further articulate

extinction prevention measures with the hope that this

will lead to changes in company behavior (Hassan et al.,

2020b). Furthermore, companies should seek to consolidate

numerical data and narrative and pictorial evidence to com-

prehensively communicate conservation efforts (Atkins &

Maroun, 2020). Atkins (2020) argues that companies should

be integrating extinction accounting into annual reports to

trigger change and would have to “assess the populations

of threatened species living near their operations; work

out whether their business puts them at risk; come up with

plans to protect them; and explain them to investors”. Stud-

ies from extinction accounting give evidence of a genuine

concern for nature and represent the need for compassion

for species (Atkins et al., 2018; Buchling & Maroun, 2018);

they support the idea that companies begin to acknowledge

their dependence on natural capital. Motivated by extinction

concern, evidence of species names emerges in corporate

reports (Adler et al., 2018; Atkins et al., 2014). However,

an argument builds that certain alluring or desirable species

may attract more attention from companies than others, as

Weir (2018) observed that mammals and birds warranted

greater conservation efforts than insects and invertebrates.

Atkins et al. (2014) reinforce this theory, reporting that

favoritism may be shown towards certain species, especially

species which are beneficial to humans.

Smith et al. (2019) found that the corporate motiva-

tion to engage in conservation efforts is unclear. However,

the existing studies assist companies to recognize that the

threat of extinction is a material risk (Addison et al., 2019).

Global policymakers are also taking the initiative to encour-

age companies to be accountable towards the extinction of

species. For example, The Natural Capital Coalition (2020)

urges companies to realize that their success is driven by

ecosystems; the loss of any species to extinction is devas-

tating, but species which provide such intrinsic worth to

industries is frightening.7 Indeed, the global Aichi targets

7 For example, crop production which has an estimated annual

valuation of $577 billion, is under threat from pollination loss and

bee decline (The World Bank, 2020), threatening the food industry.

Approximately 70% of cancer drugs are derived from plant spe-

cies, consequently threatening the pharmaceutical industry (PWC &

WWF, 2020).

of the ‘Strategic Plan for Biodiversity 2011–2020’ have been

considered a failure as biodiversity decline is accelerating at

an unprecedented rate, with humanity’s legacy of biodiver-

sity at a crossroads for future generations (CBD, 2020). The

most recent call to action is the United Nations SDG targets

‘The 2030 Agenda for Sustainable Development’. Global

governments have agreed on a vision of ‘Living in harmony

with nature’ by 2050, and it is imperative lessons are learned

from the past decade if the SDGs are to be met. The UN

Biodiversity Conference in September 2020 emphasizes the

need for “Urgent action on biodiversity across all sectors

and from all actors” to meet the SDG target of 2030 (CBD,

2020). Furthermore, the post-2020 biodiversity initiatives

must be achieved, or humanity could potentially face future

pandemics.

The current COVID-19 crisis provides forewarning to

further encroachment between natural capital and humans

that can have detrimental impacts (Carrington, 2020). Cor-

porates must make transformational changes to restore their

relationship with nature and engage in sincere stewardship

of natural capital, as it is their moral duty to protect future

generations (Gaia & Jones, 2019). Turning a blind eye to

warning signs could be catastrophic for business prosper-

ity and survival. There is no extensive literature to explain

the accountability of companies towards species extinction.

Therefore, in this study, we discuss how the disclosure of

species by global companies can assist them in achieving

environmental awards, gain assurance from Big 4,8 and

allow companies to expand biodiversity partnerships lead-

ing to a financially sustainable company. The findings of

this study will be an example for stakeholders of companies

and will encourage academics to extend the studies on B/E

to assist companies to be more accountable towards B/E.

Furthermore, to meet SDGs 14 and 15, we offer a solution

that can assist in preventing further decline by advocating

that companies transform their reporting practice to include

information on their efforts to protect biodiversity and

species.

Theoretical Literature Review

Prior B/E research applies various theories to explain com-

pany viewpoints including impression management (Boiral,

2016), greenwashing (Hassan et al., 2020b), and legitimacy

(Adler et al., 2017; Bhattacharyya & Yang, 2019). However,

we observe that companies have not done enough to protect

species from extinction, and, as experts explain, it may be

that this is one of the reasons for zoonotic disease spillover

8 Big4—one of the big four accounting firms: Deloitte, Ernst &

Young, KPMG, PwC.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

575

such as COVID-19 (Ceballos et al., 2020). Lack of a com-

prehensive theoretical model cannot motivate companies

to identify a strategy for species protection. Therefore, we

introduce a triangulation of theories, namely deep ecology,

legitimacy, and stakeholder theories. Deep ecologists are of

the view that nature has intrinsic value, and all nonhuman

life should be preserved (Naess, 1989, 2008), thus rejecting

anthropocentric shallow ecology, which places humans of

most importance, believing nature has value because of what

it contributes to human satisfaction (Callicot, 1990, 1994;

Thompson & Barton, 1994). Deep-ecologists debate whether

environmental and extinction crises are human-induced

(Samkin et al., 2014) and support the suggestion that the

crisis is the result of dominating anthropocentric bias in cor-

porate behavior (Atkins et al., 2014). Absolute deep ecol-

ogy would reject business use of natural assets as a com-

modity. However, to mitigate corporate financial risk and

prevent societal collapse, a middle ground must be reached.

Companies must consider embedding an ecological culture

and stewardship (Jones, 1996) by protecting and investing

in nature. For example, Gaia and Jones (2019) found that

elements of deep ecology must be ethically rooted to enable

a sustainable society. Similarly, Samkin et al. (2014) found

deep ecology embedded in biodiversity disclosures and men-

tion that the approach requires a long-term commitment.

Embracing deep ecology is not to put a financial value on

species as this would be refuted by deep-ecologists; rather,

companies must evaluate their behavior and engage in a

balanced perspective to mitigate the risk of financial loss,

together with responsibly protecting species and habitats.

The relationship with nature must be realigned and eliminate

the arrogant profit-seeking objectives, which have driven us

to a planetary emergency (Gray & Milne, 2018).

Empirical evidence considers corporates to be rife in

legitimizing activities (Boiral & Heras-Saizarbitoria, 2017;

Cho & Patten, 2007; Milne & Gray, 2013; Patten, 2002).

Extant literature considers B/E accounting as a continua-

tion of corporate social responsibility (CSR) research into

corporate disclosure practices (Bebbington & Larrinaga,

2014; Hassan et al., 2020b). Legitimacy theory is one of the

most applied theories to explain the increasing CSR report-

ing over the past two decades (Hassan & Guo, 2017) and it

“involves the selective disclosure of positive actions result-

ing in misleading and biased reporting” (Mahoney et al.,

2013, p. 352). Extant literature uses legitimacy theory to

explain that dishonest companies misreport their CSR efforts

to capitalize on their face value to influence stakeholders’

perceptions and gain legitimacy (Lyon & Maxwell, 2011;

Zijl et al., 2017).

Adler et al. (2018) argue that biodiversity and threat-

ened species information is provided in order to fulfil the

desires and expectations of stakeholders. Bhattacharyya

and Yang (2019) specifically note that considering the

current planetary emergency, for businesses to gain soci-

etal legitimacy, they must increase biodiversity disclosure.

Lewis (2016) explains that legitimacy is a practice that is

deceivingly used to endorse that organizations’ policies

or practices are environmentally friendly, when arguably

they are not. Patten (2015), for example, explains that an

organization with specific environmental adversity intensi-

fies the extent of CSR reporting to signal to stakeholders

that the organization is addressing the concern. This con-

tinues a tradition of impression management-oriented lit-

erature in environmental accounting (Hassan et al., 2020a,

b). This research argues that companies provide disclosure

to legitimize companies’ concerns for B/E issues (Adler

et al., 2018; Cho et al., 2015a; Lyon & Maxwell, 2011).

As the species extinction crisis intensifies, it can be

expected that companies must meet external pressures

(Rimmel & Jonäll, 2013) and enhance reputation to main-

tain their “licence to operate” (Adler et al., 2017, p. 1714).

Research highlights that stakeholder and legitimacy theo-

ries overlap in social and environmental studies (Deegan,

2002; Gaia & Jones, 2017, 2019). Stakeholder theory has

been used to explain the needs and expectations of human

groups and individuals affected by the company (Boiral

& Heras-Saizarbitoria, 2017; Gaia & Jones, 2019). The-

oretically, we recognize a limitation within stakeholder

literature that prior studies have failed to recognize or

explain for the prevention of further species loss. Roberts

et al. (2020b) argue that species should be included as a

main stakeholder with the established groups of employ-

ees, NGOs, government agencies, environmental groups,

and customers (Jones, 1995; Schaltegger et al., 2017). We

believe that for deep ecology to be embedded in corporate

strategy, species of flora and fauna should be considered

as one of the main stakeholders’ categories, discarding

human hierarchy, for companies to protect and restore

species and their habitats. In this vein, we focus on a tri-

angulation of deep ecology, legitimacy, and stakeholder

theories, which can explain the relationship between spe-

cies numbers and determinant factors. We recognize that

corporates may be disclosing species-specific informa-

tion for legitimizing purposes, but we are also hopeful

that those companies who are disclosing species numbers

have started to realize the intrinsic worth of natural capital

and are consequently embedding ecological culture and

displaying a genuine concern for the extinction crisis by

identifying species as stakeholders. We hope that provid-

ing disclosure on species protection will be the new norm

for other companies to follow. Societal health is under-

pinned by nature (Roberts et al., 2020a); we expect that by

application of the triangulation of theories, we can assist

companies to explain the underlying motivation to reform

B/E impact, which will reduce potential future pandemics

(Ceballos et al., 2020).

576

L. Roberts et al.

Empirical Literature Review and Hypotheses

Development

B/E accounting is considered as an extension of CSR (Beb-

bington & Larrinaga, 2014; Bhattacharyya & Yang, 2019;

Hassan et al., 2020b). From the existing literature, we

identified that the assurance by leading assurance provid-

ers, presence of partnerships, environmental performance,

and environmental award are some important factors that

will assist the stakeholders to assess the accountability of

the companies towards nature. In the following section, we

discuss these factors in detail to develop the hypotheses

related to the research question, which is supported by the

comprehensive theoretical model explained previously.

Species and Assurance

Sustainability reporting is established in mainstream

practice to meet the needs of societal expectations (Junior

et al., 2014; Kolk & Perego, 2010). However, it is argued

in the literature that the reliability and quality of informa-

tion falls short (Cho et al., 2015a). Boiral et al. (2018)

imply that information can be biased and reporting by

companies is used as a window-dressing activity (Boiral,

2016), and thus, the credibility of information is ques-

tioned (Gray, 2010). To enhance the quality and credibility

of sustainable reporting in literature, we find that compa-

nies prefer to use third-party assurance from accounting

firms (Maroun, 2018). Involvement of third parties can

increase the confidence of the stakeholders in disclosure

(Simnettt et al., 2009). Human stakeholders perceive the

professionally audited reports from the external assurance

provider as a confident and legitimate report of the com-

pany performance (Cho et al., 2015a).

Because of the immense presence of independence in

the report prepared by the external assurance provider,

companies who are under public pressure due to poor per-

formance may prefer to seek external independent assur-

ance to indicate a better performance to the stakeholders

(Boiral et al., 2018; Maroun, 2018). But external assurance

is also required to identify which companies are better

in addressing the B/E risk, which is prominent (IPBES,

2019) and related to human behavior. The external assur-

ance report can help the stakeholders to understand how

the companies are following deep ecology principles by

engaging in the stewardship of natural capital (Bhattacha-

ryya & Yang, 2019). Legitimacy theory has been domi-

nant in the social and environmental accounting litera-

ture (Belal & Owen, 2015; Giordano-Spring et al., 2015).

Many studies (e.g., Ball & Craig, 2010; Cho, 2009; Cho &

Patten, 2007; Hassan & Guo, 2017; Patten, 2015; Tilling

& Tilt, 2010) empirically examine legitimacy theory and

support the argument that companies voluntarily provide

environmental information to gain legitimacy. The theory

also predicts that organizations who are more likely to

be subject to public pressure and legitimacy threats due

to negative CSR performance may hire third parties to

provide assurance to indicate favorable performance

(Boiral, 2016; Cho et al., 2014; Maroun, 2018). Conse-

quently, independent third-party assurance can help to

deflect attention from negative B/E performance, lessen

legitimacy risks, and install improved confidence among

stakeholders (Gürtürk & Hahn, 2016; Perego & Kolk,

2012). More specifically, these firms actively hire third

parties that provide limited assurance to portray that the

B/E information released in CSR reports is credible, in

order to improve stakeholders’ confidence and enhance

corporate reputation and perceived legitimacy (Cho et al.,

2014; Odriozola & Baraibar-Diez, 2017). Nevertheless,

as companies must comply with reporting standards, they

may prefer the ‘low-quality assurance’ with less scrutiny,

and thus they have opportunity to dissociate their revealed

from their actual performance.

However, it is also evident in the literature that assur-

ance providers deliver cautious rhetoric, failing to explic-

itly address issues around the report on biodiversity (Boiral

et al., 2019). Companies may prefer to buy less scrutinized

‘low-quality’ assurance options to deflect from their poor

performance (Hassan et al., 2020b), and are expected to

select limited assurance (Braam & Peeters, 2018) outside

of the accounting profession to focus on selected sec-

tions of the performance. In post-pandemic reporting, we

expect companies to engage in stewardship of protecting

species and habitats, embedding a deep-ecological culture

by regarding species as a main stakeholder. In the future,

assurance providers will scrutinize the company impact

on biodiversity. Our motivation for this hypothesis is to

extend existing literature which finds a positive relation

between B/E disclosure and external assurance (Hassan

et al., 2020b). Therefore, we examine whether external

assurance is an influencing factor in protecting species.

By applying deep ecology and stakeholder theory, compa-

nies are expected to commit to protecting species (Samkin

et al., 2014) and valuing them as stakeholders. The contra-

dictory findings of the importance of external assurance

motivated us to examine the influence of external assur-

ance on companies’ accountability towards the extinction

of species. Thus, we propose the following hypothesis:

Hypothesis 1 There is a positive relationship between the

number of species and buying assurance from an external

assurance provider.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

577

Species and Environmental Performance

Legitimacy theory helps to explain why companies with

poor environmental performance have higher environmental

scores (Mahoney et al., 2013). In the literature, we find that

the more extensive disclosure companies provide, the more

the firm’s reputation is enhanced (Cho & Patten, 2007; Cho

et al., 2012). Poor performers are anticipated to disclose in

order to gain legitimacy and enhance societal perception

(Clarkson et al., 2008). Hassan et al. (2020b) classify com-

panies into poor and better performers and find companies

with poor environmental performance disclose more and

offer justification to defend legitimacy. Based on this argu-

ment, we expect that poor performers will disclose more

species information to maintain legitimacy, and as a result,

the companies can be more accountable in mitigating the

extinction of species. If species are accepted as one of the

main stakeholders, we expect EC/FT companies to propose

long-term value creation and suppress demand on natural

capital, committing to achieving SDGs 14 and 15. Our moti-

vation is to extend B/E literature (Hassan et al., 2020b) and

contribute to it by empirically examining, in support with

legitimacy theory, the relationship between species and poor

environmental performers. Thus, we propose the following

hypothesis:

Hypothesis 2 There is a positive relationship between the

number of species and poor performers.

Species and Environmental Award

Gaining an environmental award is an excellent way of dis-

playing positive practices to stakeholders (Cho et al., 2015b;

Deegan, 2002), and motivates other companies to disclose

CSR practices (Hassan & Ibrahim, 2012). Acquiring awards

can show the true commitment of the company to natural

capital and confirm their deep ecological perspective (Clark-

son et al., 2008). Such awards influence investors to make a

positive decision about the company, which leads to favora-

ble future financial performance (Clarkson et al., 2011).

Prior B/E literature suggests that companies should report

on prizes and awards relating to conservation efforts (van

Liempd & Busch, 2013). Awards provide an opportunity to

signal genuine concern for nature (Adler et al., 2018; Atkins

et al., 2014) and showcase efforts. Hassan et al. (2020b)

exclusively find a positive association between B/E disclo-

sure and companies gaining environmental awards. Based on

this discussion, our motivation is to extend extant literature

and expect companies who disclose species to gain environ-

mental awards, and by doing so, deep ecology supports that

they have considered species as stakeholders (Roberts et al.,

2020b) in their reporting in order to address the extinction

crisis responsibly.

Hypothesis 3 There is a positive relationship between the

number of species and getting an environmental award.

Species and Partnerships

Prior literature finds a positive relationship between B/E

disclosure and partnership engagement (Adler et al., 2018;

Boiral & Heras-Saizarbitoria, 2017; Hassan et al., 2020b).

Here, partnership refers to when a company discloses a rela-

tionship with at least one conservation or wildlife organi-

zation. This can be viewed as a display of good corporate

practice (Adler et al., 2018) and a means of seeking pub-

lic trust (Deegan, 2002). Collaborating with organizations

such as WWF (World Wildlife Fund) or IUCN (International

Union for Conservation of Nature) can help companies to

engage in conservation efforts, and companies are therefore

more likely to minimize the extinction crisis (Adler et al.,

2018). Partnership engagement will motivate companies to

consider species as stakeholders (Atkins et al., 2018; Buch-

ling & Maroun, 2018; Zhao & Atkins, 2018). By supporting

this concept, EC/FT companies can commit to achieving

SDGs 14 and 15 and can align with long-term value crea-

tion. Thus, our motivation is to enhance B/E literature (Adler

et al., 2018; Boiral & Heras-Saizarbitoria, 2017) by empiri-

cally examining the relationship with species and partner-

ship engagement. Theoretically, deep ecology perspective

and regarding species as stakeholders, demonstrates that

companies are preserving nature (Atkins et al., 2018) and

showing genuine concern for the B/E crises. Thus, we expect

that companies which engage in partnerships will disclose

more species.

Hypothesis 4 There is a positive relationship between

the number of species and companies who engage in

partnerships.

Research Design

Sample Selection

The sample for this research consists of the top 200 compa-

nies from the Fortune Global list of 2016. Purposefully, we

considered these companies as they are typically leaders in

CSR (KPMG, 2017), make significant use of ecosystems,

and therefore gain the most public attention (Adler et al.,

2018; Hassan et al., 2020b). These companies represent a

variety of industries exposed to different levels of biodi-

versity risk (Addison et al., 2019; Bhattacharya & Managi,

2013) from diverse geographic locations (Hassan et al.,

2020b). The top 200 companies are selected from the For-

tune Global 500 list as literature supports that the remaining

companies rarely disclose biodiversity information (Adler

578

L. Roberts et al.

et al., 2018; Hassan et al., 2020b). The investigation period

is 3 years: namely, 2012, 2014, and 2016, as one of the vari-

ables, environmental performance, is calculated every 2

years. Corporate annual and sustainability reports are down-

loaded from company websites. Sustainability reports can

be referred to as environmental, corporate social responsi-

bility, citizenship, or such reports. Where these reports are

missing, we manually collected relevant information from

the annual reports. Following prior studies (Addison et al.,

2019; Adler et al., 2017), websites were not included in the

search. In total, 600 annual and sustainability reports were

downloaded (which are accessible on their corporate web

pages). After controlling for an outlier, our final sample

comprised of 599 companies. Following prior studies (Adler

et al., 2018), we used content analysis, and by searching key-

words,9 we counted for species information. Keyword search

and manual collection are followed in this paper to identify

companies from 22 countries10 and 19 sectors.11

Research Variables

Dependent Variable: Number of Species

The number of species count was comprised of species

numbers presented in quantitative terms or by naming in

qualitative terms. A manual count of all species disclosed on

reports were collected and recorded. The number of species

counted was protected or conserved or noted as threatened

with extinction by the company. Where companies disclosed

a group of species, for example, 10 birds, we counted these

as 10 species and so on. In the counting of species, duplicate

references were eliminated; in other words, species referred

to on more than one occasion were counted once.

9 The 28 keywords are "Extinct", "Extinction", "EN11", "EN12",

‘EN13", "EN14", "Wildlife", "Habitat", "Species", "Biodiversity",

"Biodiversity offset", "Forest", "Ecosystem", "Flora", "Fauna",

"Endangered", "Threatened", "Vulnerable", "Accident" (relating to

B/E), "Conservation", "Biological diversity", "Protected", "Floral/

Faunal wealth", "Rehabilitation", "Groundwater", "Marine", "Vegeta-

tion", "Wetlands" (Adler et al., 2018).

10 Countries are Australia (9), Brazil (12), China (120), France (45),

Germany (48), India (3), Italy (12), Japan (57), Luxembourg (3),

Malaysia (3), Mexico (6), Netherlands (12), Norway (3), Russia (12),

Singapore (3), South Korea (15), Spain (6), Switzerland (15), Taiwan

(3), Thailand (3), United Kingdom (24), and USA (186).

11 The 19 sectors are Aerospace (21), Apparel (3), Chemicals (6),

Energy (99), Construction (18), Financial (144), Food & Beverage

and Tobacco (15), Food & Drugs (33), Health care (30), Household

products (6), Industrial (18), Materials (12), Media (3), Motor Vehi-

cles and parts (48), Retails (21), Technology (42), Telecommunica-

tion (33), Transportation (15), and Wholesalers (33).

Independent Variables

We used assurance, environmental award, presence of part-

nerships, and environmental score as independent variables

(see Table 1). The environmental score was measured by the

environmental well-being score from the Sustainable Soci-

ety Foundations website (Adler et al., 2018; Hassan et al.,

2020b). The scores are available per country every 2 years

and following Hassan et al. (2020b), we classified the sample

into poor performers (score 0–2.9) and better performers

(score 3–5). The sample consisted of 290 poor performers

and 309 better performers.

Control Variables

For this research, we considered leverage, firm size, and rev-

enue as control variables. In addition, we used country-level

variables. Following Hassan et al. (2020b), we classified the

sample into developing and developed countries, according

to the United Nations classification. There are 177 develop-

ing and 422 developed firm-year observations in our sample.

The industry was controlled in the study and was classified

by risk exposure according to the three categories of the F

& C Asset Report (2004) risk level (red is high risk; amber

is medium risk and green is low risk).12 In accordance with

Hassan et al. (2020b), we grouped red and amber to “high

risk” classification, and green remained “low-risk” classifi-

cation. The total sample consisted of 219 high-risk firm-year

observations and 380 low-risk firm-year observations. Gov-

ernance indicators are widely used in multi-country studies

(Nguyen et al., 2015; Waldron et al., 2017) with empirical

evidence finding a positive correlation of company perfor-

mance with country-level governance (Luo et al., 2012).

Therefore, we added seven regularity governance level indi-

cators (see Table 1) developed by Kaufmann et al. (2011)

collected from the World Governance Indicator dataset. In

addition, we added World Development Indicators, like GDP

growth, inflation, the log of forest area, and C 02 emissions

(Spaiser et al., 2017; Stephan et al., 2015).

12 High-risk sectors (red zone) are Construction & Building Mate-

rials, Electricity, Food & Drug Retailers, Food Producers & Proces-

sors, Forestry & Paper, Leisure & Hotels, Mining, Oil & Gas, and

Utilities. Medium risk sectors (amber zone) are Beverages, Chemi-

cals, Financial Services, General Retailers, Household Goods &

Textiles, Personal Care & Household Products, Pharmaceuticals &

Biotech, Support Services, Tobacco, and Transport. Low risk sectors

(green zone) are Aerospace & Defence, Automobiles & Parts, Diver-

sified Industrials, Electronic & Electrical Equipment, Engineering

& Machinery, Health, Information Technology Hardware, Media &

Entertainment, Software & Computer Services, Steel & Other Metals,

and Telecom Services.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

579

Table 1 Research variables

Definition and coding

Dependent variable Number of species—Total count of number of species collected from published annual reports

Independent variable Assurance—has a value of “1” if the company has assurance and a value of “0” if not. Data collected from published

annual reports

Assurance by Big4—Company has a value of “1” if assured by one of the big four accounting firms (KPMG, E&Y, PwC,

or Deloitte), and a value of “0” if not. Data collected from published annual reports

Environmental Award—value of “1” if award is given, value of “0” if not. Data collected from published annual reports

Environmental Score—Company is given a value of “1” if classified a ‘poor performer’ and a value of “0” if classified

a better performer. Data collected from Sustainable Society Foundation (SSF). Score is calculated every 2 years and is

used in prior studies (Adler et al., 2018; Hassan et al., 2020a, b)

Presence of Partnerships—Presence of biodiversity/wildlife partnerships, value of “1” given if one or more present, value

of “0” if none. Data collected from published annual reports

Control variables

Country—Value of “1” given if the country is classified as developed and a value of “0” if developing. Data retrieved

from United Nations website

Industry—Company has a value of “1” if classified as red/amber-risk zone, and a value of “0” if classified as a green risk-

zone. Classification recommended by F & C Asset Report (2004)

Governance—Is the average score of voice & accountability, political stability, government effectiveness, regularity qual-

ity, rule of law, control of corruption and corruption index taken from Worldbank.org

GDP growth—(annual%)—World Development Indicator. Data collected from Worldbank.org

Inflation—GDP deflator (annual%) World Development Indicator. Data collected from Worldbank.org

Log (Forest area)—Forest areas (sq. km)—World development indicator. Data collected from Worldbank.org

CO2 emission—(metric tonnes per capita)—World Development Indicator. Data collected from Worldbank.org

Log (Revenue)—Data collected from published annual reports

Leverage—Total debt/total assets. Data collected from published annual reports

Firm size—Natural logarithm of total assets. Data collected from published annual reports

Empirical Results and Discussion

Summary Statistics

Our results show that 452 out of 599 reports (75%) failed

to disclose any species numbers (refer to Fig. 1). These

findings support prior literature (Adler et al., 2018; Bhat-

tacharya & Managi, 2013) and suggest a call for awareness

among companies (Rimmel & Jonäll, 2013; Hassan et al.,

2020b). However, the remaining EC/FT companies, 147

out of 599 (representing 25%), provided species numbers,

demonstrating ecological awareness by engaging in con-

servation efforts to protect and restore species and habi-

tats, valuing species as stakeholders. We found a slight

increase in species numbers over years which optimis-

tically displays a deep-ecological view with companies

being self-aware of the fundamental value of the planet

(Hassan et al., 2020b). The declaration of the SDGs in

2015 may also explain the increase. We acknowledge that

this is a small proportion of the sample. However, these

EC/FT companies provide seminal knowledge in establish-

ing relationships between species and developing solu-

tions to meet SDGs 14 and 15. These disclosures may be

a reporting exercise to manage impressions. However, we

expect post COVID-19 that there will be a seismic shift in

company reporting and committing to protecting nature,

and therefore justify the significance of our results.

Table 2 presents the descriptive statistics for all vari-

ables used in the study. The average number of species

disclosed by companies is about 3 species with a standard

deviation of 21. This implies that there is a significant

difference in the reported species among the companies.

We further nalysed by country and found developing coun-

tries have a higher mean score for the number of species

(i.e., 3.458) than developed countries (i.e., 2.614). This

supports the recent arguments, where experts believe that

developing countries are to blame for the COVID-19 pan-

demic due to illegal wildlife trade and wet markets and

call for enforcing the banning of such trades to prevent

further pandemics and extinctions and forcing companies

to become socially responsible (Ceballos et al., 2020; Ma

et al., 2020). Legitimacy theory explains that develop-

ing countries provide more species to maintain societal

legitimacy and reputation (Adler et al., 2018; Bhattacha-

ryya & Yang, 2019). We found developed countries have

a higher mean score for assurance, environmental award,

partnerships, Big4, leverage, governance, industry, and

CO2 emissions, which is similar to prior studies on CSR

(Bouten et al., 2011; Tagesson et al., 2009). Furthermore,

the developing countries had a higher mean score for

environmental score, firm size, GDP, and inflation which

580

DistribuƟon of Key InformaƟon

L. Roberts et al.

REPORTS

FIRMS

AWARD ASSURANCE

BIG4

POP

Series1

Series2

Fig. 1 This figures shows a distribution of key information of our

data from 599 annual reports of 200 firms. Series 1 represents the

reports where firms did not report any species and Series 2 docu-

ments the reports in which firms included the names of species (we

counted the number of species as explained in the data description).

REPORTS is the number of reports in our data. FIRMS is the num-

ber of firms (during 2012–2016) in each set of Series. AWARD is the

number of reports indicating the firms received environment award.

ASSURANCE is the number of reports which mention whether the

firms receive assurance. BIG 4 is a subset of ASSURANCE indicat-

ing whether the assurance received from BIG 4. POP represents the

number of reports which mentions the presence of biodiversity/wild-

life partnerships

Table 2 Summary statistics of the variables used in our models

Full sample

Obs Mean

Median St.Dev

Number of species

599

Buying assurance

599

Environment score

599

Green

599

Environment award

599

Presence of partnership 599

Big 4

599

Firm size

590

Log (revenue)

593

Leverage

596

Governance

599

CO2 emission

400

Log (forest area)

596

GDP growth

596

Inflation

596

2.863

0.679

0.065

0.658

0.199

0.237

0.391

12.494

11.346

6840.108

0.839

10.426

13.322

2.820

1.552

0.000

1.000

0.000

1.000

0.000

11.809

11.234

0.383

1.232

9.200

14.527

2.200

1.400

21.552

0.467

0.250

0.475

0.399

0.425

0.488

2.512

0.545

167,000

0.785

4.645

2.014

2.528

1.504

Developing country Developed country

Obs Mean

177

3.458 422

2.614

177

0.599 422

0.714

177

0.170 422

0.021

177

0.588 422

0.687

177

0.186 422

0.204

177

0.147 422

0.275

177

0.367 422

0.401

171 13.276 419

12.175

174 11.276 419

11.375

174 16.66

422 9653.568

177 − 0.246 422

1.294

116

7.545 284

11.602

174 14.100 422

13.002

174

5.681 422

1.641

174

2.344 422

1.226

Difference in means

t-test

0.844

− 0.115**

0.148***

− 0.100**

− 0.018

− 0.128***

− 0.033

1.101***

− 0.099**

− 9636.907

− 1.540***

− 4.058***

1.098***

4.040***

1.118***

supports the literature that finds a positive relation with

CSR disclosure (Chiu & Wang, 2014; Huang & Kung,

2010).

Table 3 provides the correlation matrix of all variables

included in the study. To identify any multicollinearity prob-

lems, we followed prior studies (Bhattacharyya & Yang,

2019; Haniffa & Cooke, 2005) and found a maximum of

0.161 as a correlation coefficient.

We tested the presence of multicollinearity by calculating

the variance inflation factor (VIF) and tolerance values for

each of the explanatory and control variables, as presented in

Appendix A. The VIF indicates how much the variance of a

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

581

582

L. Roberts et al.

coefficient is inflated because of the linear dependence with

other variables, and the tolerance is the extent of variability

of selected regressors not explained by the other regressors.

The threshold values for VIF and tolerance are less than 10

and more than 0.1, respectively (see Gujarati, 2003; Hair

et al., 2013). Appendix A shows that the VIFs are below 5

(except the Governance variable, which is 5.88). So, multi-

collinearity is not a problem for our estimations of models.

Empirical Models

To test our hypotheses, we started with OLS regression by

using the natural logarithm of the number of species as our

dependent variable. However, the coefficients of the regres-

sion led to inconsistent estimators of the parameters of our

model. Following Gourieroux et al. (1984), therefore, we

used the Poisson pseudo-maximum likelihood (PPML)

regression with multi-way fixed effects model, since our

dependent variable—the number of species—is a non-neg-

ative count variable. In other words, the number of species,

a Poisson random variable, has a discrete probability distri-

bution that indicates the probability of a given number of

species reported in a fixed interval of time. In related simu-

lation results by Santos Silva and Tenreyro (2011), it shows

that the PPML model provides better results even when the

dependent variable contains a large number of zeros. So, we

believe that the Poisson distribution model is appropriate for

our data. This is because 75% of our sample did not provide

disclosure on species protection. In general, we write our

empirical model as

unlikely to follow a negative binomial distribution. So, in

accordance with Cameron and Trivedi (1990), we tested for

over-dispersion. We failed to reject the null hypothesis of

mean–variance equality in all the estimations. This justifies

the use of Poisson for our sample.

Empirical Results

In Table 4, we report the results of the Poisson regression,

to explain the results for the likelihood of the number of

species disclosed by the companies. In addition to the coef-

ficients, we also show White’s heteroscedasticity robust

standard errors in parenthesis.13 In Model 1 of Table 4, the

model is estimated by traditional Poisson regression with

year and country fixed effects. In Model 2, we report the

Poisson pseudo-maximum likelihood (PPML) regression

with multi-way fixed effects.

Based on the deep ecology concept, in this paper, we

consider species as a stakeholder (Samkin et al., 2014), and

therefore, in Hypothesis 1, we propose that there is a posi-

tive relationship between the number of species and buy-

ing assurance. The proposition in Hypothesis 1 is proven

in Models 1 and 2, which show positive and statistically

significant coefficients (Model 1: β = 1.129, p < 0.05; Model

2: β = 1.131, p < 0.10, respectively) of buying assurance.

It implies that firms with assurance are likely to report a

greater number of species than those firms without assur-

ance. Hypothesis 1 reinforces empirical studies which have

found that assured information is viewed as more cred-

ible and reliable, narrowing the legitimacy gap (Cho et al.,

Yit = f (Buying Assurance, Environment Score, Environment Award, Green, Presence of Partnership,

(1)

Big 4, Firm- and Country-level control variables)

where, Y is the number of all species disclosed on financial

reports of sample firm i in year t.

In particular, for our Poisson model, the conditional mean

of Y in Eq. (1) is written as E(Y|X) = exp(X )

where X is the vector independent variable (shown in

Eq. 1) and a constant. The maximum likelihood estima-

tor of , the coefficients of relevant independent variables,

is calculated by maximizing the following log-likelihood

function:

∑

L( ) = Ytlog t − t − log(Yt)

(2)

where t = exp(xt� ) shows a model for the conditional

mean of the number of species. However, there may exist

a problem with the model as it imposes an assumption of

mean–variance equality in its empirical application. Thus, an

alternative model could be a negative binomial model. But

our outcome variable, i.e., the number of species, seemed

2015a; Maroun, 2018). Theoretically, our results support

deep ecology, legitimacy, and stakeholder theories as the

overall increase in disclosure optimistically displays a deep-

ecological view with companies being aware of the funda-

mental value of the planet. Our results support Hassan et al.

(2020b), which found a positive relationship between assur-

ance and biodiversity disclosures. Theoretically, our results

align with deep ecology, evidencing that companies are

committed to protecting species (Samkin et al., 2014), and

valuing them as stakeholders. Additionally, these findings

have implications for policymakers in developing solutions

with companies providing assurance on species information.

13 To adjust for the differences between variance and mean score,

we use a bootstrapping method in the Poisson regression using 500

replications (not reported). The resampling procedure with replace-

ment creates simulated datasets for the estimation. Our results remain

qualitatively similar.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

583

Table 4 Poisson regression results for the likelihood of number of

species disclosed

Dependent variable: number of species

Poisson regression with

year and country FE

PPML with

multi-way

(1)

(2)

Buying assurance

Presence of partnership

Environment Score

Environment award

Big 4

Green industry

Firm size

Log (revenue)

Leverage

Governance

CO2 emission

Log (forest area)

GDP growth

Inflation

Constant

Observations

Pseudo R2

Country fixed effects

Year fixed effects

1.129**

(0.498)

4.093***

(0.446)

1.533*

(0.800)

− 1.948***

(0.455)

− 1.675***

(0.552)

0.226

(0.454)

0.059

(0.069)

− 0.283

(0.366)

− 0.000***

(0.000)

3.991*

(2.193)

− 1.033*

(0.625)

0.727*

(0.384)

− 0.559*

(0.315)

0.546*

(0.285)

− 15.481

(9.832)

394

0.776

Yes

1.131*

(0.601)

4.111***

(0.477)

1.530**

(0.701)

− 1.937***

(0.454)

− 1.663***

(0.543)

0.233

(1.093)

0.062

(0.085)

− 0.313

(0.418)

0.020

(0.025)

3.912**

(1.865)

− 1.055

(0.822)

0.726**

(0.283)

− 0.561**

(0.274)

0.546*

(0.308)

1.021

(13.564)

373

0.773

Yes

The table reports the effects of assurance, environment award, pres-

ence of partnership and red Industry on the number of reported spe-

cies in firm’s annual report in each year. The data consists 599 firm-

year observations of top 200 firms listed in Global 500 firms for the

year 2012, 2014 and 2016. Green industry is a dummy equal to 1 if

the industry belongs to green industry and 1 if it is in red or amber

industry. Natural logarithm of total assets as a proxy for firm size is

used. Model 2 reports Poisson pseudo-maximum likelihood (PPL)

regression with multi-way fixed effects. Robust standard errors are

clustered at the industry level and reported in parenthesis

***Denotes 1%, **denotes 5% and *denotes 10% significance level

We expect that assurance will become an integral part of

companies committing to SDGs 14 and 15. This result is

in line with prior studies’ stream of literature that empiri-

cally examines the assurance of a company’s CSR report.

These studies note that stakeholders place more confidence

in CSR reports where the level of assurance provided is rea-

sonably high (Casey & Grenier, 2015; Kolk & Perego, 2010;

Mahoney et al., 2013; Peters & Romi, 2015; Pflugrath et al.,

2011; Simnett et al., 2009).

In addition, we consider the assurance provider as Big4.

Big4 is a binary variable equal to 1 if the sample company

has an auditor from one of the Big4 audit firms. The coef-

ficients in Models 1 and 2 show a negative and statistically

significant coefficient (Model 1: β = 1.675, p < 0.001; Model

2: β = 1.663, p < 0.001, respectively). This implies the num-

ber of species in reporting increases if the company is not

audited by one of the big four accounting firms. This addi-

tional result confirms that auditors from the Big4 account-

ing firms may be failing to address the B/E crisis or can-

not generate awareness in the company. A deep-ecological

concern would expect Big4 providers to relate to the need

for uniformed reporting guidelines on species and habitat

protection (Atkins & Atkins, 2018). Auditors from the Big4

must regard species as a main stakeholder post-pandemic.

To achieve SDGs 14 and 15, assurance providers like Big4

must encourage companies to develop long-term sustain-

ability and their consultancy must include advocating the

protection of species environmental recovery.

The coefficients of environment score in Models 1 and 2

are positive and statistically significant (Model 1: β = 1.533,

p < 0.10; Model 2: β = 1.530, p < 0.05, respectively). This

supports our Hypothesis 2, which states that poor environ-

mental performers are likely to report a greater number of

species compared to better environment performers. This

result is consistent with prior literature that these compa-

nies disclose more to defend legitimacy (Cho et al., 2012;

Clarkson et al., 2008). Our results support empirical studies

that have found a positive relationship between poor envi-

ronmental performers and biodiversity disclosure (Hassan

et al., 2020b). Theoretically, our results support legitimacy

theory, which explains that these poor performers may dis-

close more species as they negatively impact biodiversity

through illegal wildlife trade and lack robust regulations, and

therefore, our results may benefit regulators with assisting

in preventing further species loss. Deep ecology explains

that to achieve SDGs 14 and 15, these poor performers must

begin to consider species as a stakeholder to prevent further

extinctions. This implies that poor environmental perform-

ers are more likely to seek environmental legitimacy and

more stakeholders’ satisfaction by reporting useful B/E

information.

In Hypothesis 3, we predict that to get an award to nar-

row the legitimacy gap and prove a deep concern for nature,

584

L. Roberts et al.

firms report a higher number of species. But, in Table 4,

our empirical result shows an opposite sign in coefficients

(Model 1: β = − 1.948, p < 0.001; Model 2: β = − 1.937,

p < 0.001, respectively). These results are surprising as

empirical B/E studies have found a positive relationship

with companies gaining an award (Hassan et al., 2020b).

Our results do not support prior literature (Adler et al., 2018;

Atkins et al., 2014) that companies should showcase con-

servation efforts in protecting species and calls for further

academic examination. Theoretically, this evidence suggests

companies are disregarding species as stakeholders and

neglecting deep ecology. Such a lack of sensitivity towards

B/E will make it difficult in achieving the policymakers’

target of B/E prevention. Our justification for such results is

due to lack of awareness and so far, there is no mandatory

requirement to disclose on the number of species. This high-

lights that there is a huge call for awareness for species to

be regarded as stakeholders by companies. Furthermore, our

results suggest a shift in corporate governance consciousness

to embed deep-ecological concern by protecting species and

their habitats and to prevent future pandemics like COVID-

19. By viewing species as stakeholders post-pandemic, they

are responsibly committing to achieving SDGs 14 and 15.

Thus, if companies become ecologically conscious of the

biodiversity crisis, environmental awards will demonstrate

their commitment to sustainable development.

Further, we test the association between the presence

of wildlife conservation partnership and number of spe-

cies. Models 1 and 2 show positive and statistically signifi-

cant coefficients (Model 1: β = 4.093, p < 0.001; Model 2:

β = 4.111, p < 0.001, respectively). This implies that firms

which have a wildlife conservation partnership are likely

to disclose a greater number of species. This gives evi-

dence in favor of Hypothesis 4. Our results support prior

studies (Adler et al., 2018; Boiral & Heras-Saizarbitoria,

2017; Hassan et al., 2020b) and highlight that wildlife

partnerships are a key driver of companies protecting spe-

cies. This also implies additional empirical support for our

multi-theoretical perspective that integrates insights from

legitimacy, stakeholder, and deep ecology theories. Specifi-

cally, deep ecology explains how companies engaging in

partnerships are preserving nature (Atkins et al., 2018), and

confirms that companies view species as stakeholders by

protecting their habitats and realizing their intrinsic worth.

Our finding implies that companies respond to increased

stakeholder expectation by proactively engaging in compre-

hensive wildlife conservation partnerships, which leads to

better B/E-related activism and B/E reporting. Companies

may indeed be showcasing conservation efforts to protect

species and habitats to gain legitimacy (Adler et al., 2018).

However, partnership engagement increases knowledge and

can address the extinction crisis and prevent future pan-

demics. To meet SDGs 14 and 15, collaboration and shared

knowledge are encouraged (Jones & Solomon, 2013). Our

results imply that partnership association can help develop

solutions (Bebbington & Unerman, 2018; Gibassier et al.,

2020) and achieve a sustainable future. This evidence is also

in line with our multi-theoretical framework that implies

that companies use these mechanisms as public relationships

instruments to legitimize their existence (e.g., Adler et al.,

2018; Hassan et al., 2020b) and oversee the perceptions of

the pertinent stakeholders (Bhattacharyya & Yang, 2019).

Finally, regarding control variables, we find Governance,

Forest area, and Inflation are statistically significant and

positively related to the number of species, suggesting that

country-level variables are key determinants of disclosure on

the number of species. Overall, our hypotheses are mostly

supported by our empirical findings.

Robustness Tests

In the previous section, we use Poisson regression to inves-

tigate the relationship between company-level variables

(such as assurance, presence of partnerships, firm size) to

the number of species. In this section, we analyze our data

in three phases: (1) dividing the data into two sub-samples,

based on the firms headquarter, in developed and develop-

ing countries; (2) analyzing the full sample by taking care

of over-dispersion of the data by reclassifying the sample

into four groups based on the number of species disclosed,

and (3) dividing the sample into financial and non-financial

companies.

In our first test, we report the results of the variables that

influence companies to commit to a greater number of spe-

cies disclosure and how those variables work among firms

operating in developed and developing countries. The results

of Poisson regression at the firm-level data for developed

and developing countries are reported in Table 5.

Our findings in Table 5 mostly support our hypotheses.

Table 5 reveals that Environment Score and Environment

Award have a significant impact on disclosure of the number

of species protected in companies that operate in developing

environments compared with their counterparts that oper-

ate in developed countries. These findings are supported

by the legitimacy theory expectation that companies from

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

585

Table 5 Robustness tests:

Poisson regression

Dependent variables

Developed country

Poisson regression

Number of species

(1)

Developing country

(2)

Full sample (ZIP)

Zero-inflated

Poisson regres-

sion

nSpecies

(3)

Buying assurance

Presence of partnership

Environment score

Environment award

Big 4

Green industry

Firm size

Log (revenue)

Leverage

Governance

CO2 emission

Log (forest area)

GDP growth

Inflation

Constant

Observations

Pseudo R2

Country fixed effects

Year fixed effects

0.427

(0.541)

4.029***

(0.466)

− 0.486

(2.572)

− 2.110***

(0.685)

− 1.867***

(0.549)

n.a.

0.156**

(0.075)

− 0.871*

(0.489)

− 0.000***

(0.000)

− 6.800

(6.130)

− 0.588

(0.671)

0.399

(0.463)

− 0.193

(0.541)

1.268**

(0.565)

9.234

(11.970)

282

0.807

Yes

2.314***

(0.560)

2.765***

(0.431)

2914.660***

(630.495)

1.854***

(0.469)

− 1.951**

(0.821)

n.a.

− 0.743***

(0.169)

1.481***

(0.246)

− 0.057***

(0.015)

9.205***

(2.300)

2.534*

(1.317)

− 266.271***

(58.215)

− 1.078***

(0.334)

− 1.196***

(0.310)

3191.847***

(696.727)

112

0.924

Yes

0.100*

(0.059)

0.070**

(0.030)

− 0.109**

(0.046)

0.139**

(0.062)

− 0.066

(0.102)

0.054

(0.039)

− 0.004

(0.013)

− 0.029

(0.049)

− 0.001

(0.001)

0.001

(0.246)

n.a.

0.027

(0.030)

− 0.037**

(0.018)

− 0.019

(0.043)

0.005

(0.420)

587

n.a.

Yes

The table reports the effects of assurance, environment award, presence of partnership and green Industry

on the number of reported species in firm’s annual report in each year. The data consists 599 firm-year

observations of top 200 firms listed in Global 500 firms for the year 2012, 2014 and 2016. nSpecies-coded

from 0 to 4–0 if the number of species is 0, and 1–4 if the number of species is in the range of 1–99, 100–

199, 200–299, 300 and more respectively. Green industry is a dummy equal to 1 if the industry belongs to

green industry and 1 if it is in red or amber industry. Natural logarithm of total assets as a proxy for firm

size is used. Column 3 reports Zero-inflated Poisson (ZIP) regression. Robust standard errors are reported

in parenthesis

***Denotes 1%, **denotes 5% and *denotes 10% significance level

586

L. Roberts et al.

developing countries want to portray a positive corporate

image and influence stakeholder perception (Hassan et al.,

2020b; Tagesson et al., 2009). Similarly, we find that assur-

ance has a significant positive effect on disclosure of the

number of species protected in companies that operate in

developing environments, compared to their counterparts

operating in developed countries. Overall, the results support

our claim that institutional context has a moderating effect

on the relationship between Environment Score, Environ-

ment Award, Assurance, and disclosure of the number of

species.

In the second test, we reclassified our dependent variable

scores into a number of classifications. The first classifica-

tion includes all companies which scored zero; the second

classification contains companies which scored between 1

and 99. The third classification contains companies which

scored between 100 and 199, and the fourth classification

those which scored between 200 and 299 and more.

Let us consider Yi an observable variable having discrete

numbers 0, 1, 2, 3, and 4 based on the reported number of

species. Let yi∗ represent an unobservable variable that cap-

tures the level of concerns for biodiversity—proxied by the

number of species of ith firm. The outcome of diversity can

be represented as a function of a vector of explanatory vari-

ables (xi) and relevant control variables using the following

linear relationship:

yi∗ =

�

∑

controls + ui, whereui ∼ N(0, 1)

(3)

where is a vector of unknown parameters. Let us consider

mi and yi∗ are related to the observable variable Yi . Consider

mi as four levels of the reported number of species represent-

ing the extent of biodiversity by ith firm. mi determines five

observed values as below:

Yi = 0(‘unable to report any species’) if yi* = 0;

Table 6 Robustness tests: Poisson regression results

Non-financial firms

Model 1

Financial firms

Model 2

Dependent variable: num-

ber of species

Buying assurance

Presence of partnership

Environment score

Environment award

Big 4

Green industry

All control variables

Constant

Observations

Pseudo R2

Country fixed effects

Year fixed effects

2.312***

(0.851)

0.196

(1.052)

1.761**

(0.782)

− 1.628**

(0.774)

− 2.448**

(1.140)

4.216***

(1.609)

Included

7.091

(8.962)

394

0.568

Yes

0.660

(1.081)

− 1.542*

(0.838)

− 18.715***

(2.575)

− 0.987

(0.816)

− 0.371

(0.833)

n.a

Included

− 8.222

(9.830)

0.342

Yes

The table reports the effects of assurance, environment award, pres-

ence of partnership and red Industry on the number of reported spe-

cies in firm’s annual report in each year. The data consists 599 firm-

year observations of top 200 firms listed in Global 500 firms for the

year 2012, 2014 and 2016. Green industry is a dummy equal to 1 if

the industry belongs to green industry and 1 if it is in red or amber

industry. Natural logarithm of total assets as a proxy for firm size is

used. All control variables are included in both Models 1 and 2 but

not shown and Poisson regression is used. Robust standard errors are

clustered at the industry level and reported in parenthesis

***Denotes 1%, **denotes 5% and *denotes 10% significance level

Yi = 1(‘less than satisfactory level of reported species’) if 0 < yi∗ ≤ m1;

The probability of observed Y can be estimated by the

Yi = 2(}reasonably satisfactory level of reported species’) if m1 < y∗i ≤ m2;

Yi = 3(‘satisfactory level of reported species’) if m2 < y∗i ≤ m3;

Yi = 4(‘more than satisfactory level of reported species’) if y∗i ≥ m3

Let x denote the vector of explanatory variables that

influence the number of reported species y* and which are

denoted by the following model:

y∗

�

(4)

ordered Probit model. However, following Lambert (1992)

we use a zero-inflated Poisson (ZIP) model to measure the

relationship between disclosure on the number of species

protected and the rest of the research variables denoted as

y*, by each sample firm in the years 2012, 2014, and 2016.

The results show that buying assurance, presence of partner-

ship, environment score, and award are in line with the pre-

vious findings reported in Table 4. However, the coefficient

of Big4 is negative but not statistically significant. Overall,

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

587

we show that our results are robust with different specifica-

tions of estimations.

Further, we present the third test of robustness and divide

the sample into financial and non-financial companies (see

Table 6). The results show that buying assurance, environ-

mental score, and award from non-financial firms are in line

with previous findings.

Addressing Endogeneity

a negative binomial regression. The results are reported in

Columns 1–3 of Table 7.14 The likelihood ratio of Chi2 test

for the joint significance of independent variables is statis-

tically significant and therefore indicates a good model fit.

Overall, both the procedures qualitatively support our main

results and hypotheses.

Developing solutions and providing examples

from EC/FT companies

Our study uses a Poisson regression model to support the

hypotheses (see Table 4). However, the model is likely to

suffer from endogeneity. For instance, our sample firms

with stronger corporate governance tend to disproportion-

ally report the name of the species (source of selection bias).

In addition, the presence of stronger governance may lead

to a higher number of reported species. On the other hand,

it is also possible that firms with better awareness of B/E

tend to attract and hire more expert directors to the board

and improve their corporate governance (source of reverse

causality). The same argument is true for the environment

award variable. To deal with these issues, we use two dif-

ferent methods. Firstly, we follow Geraci et al. (2018) to

estimate our model by two-stage residual inclusion (2SRI).

Following Lin et al. (2017), we use an instrumental vari-

able, sindustry—a dummy variable equal to 1 if our sample

firms belong to environmentally sensitive industries, such

as energy, chemical, and materials, and 0 otherwise. We use

the endogenous variable environment award as a dependent

variable and sindustry and other exogenous variables (used

in Table 4) as independent variables of a logistic model (first

stage). We calculate the residual from this first stage and

include this residual in the second stage of the same Pois-

son model (as in Tables 4 and 5). The results are reported in

Column 4 of Table 7.

In the second approach, in accordance with Quigley et al.

(2019), we employ a propensity score matching (PSM) pro-

cedure to form matched sets of treated and control firms

which share a similar value on the propensity score (see

Heckman & Todd, 2009). This is also a two-step procedure.

We construct a dummy variable lgovernance equal to 1 if

a firm has a governance score less than the industry aver-

age governance score, and 0 otherwise. We run a logistic

model to estimate the probability that a firm would buy

an external assurance with weaker governance score. This

regression generates a propensity score. We follow Dehejia

and Wahba (2002) to match each treatment firm to a control

firm using the nearest neighbor algorithm with replacement

and setting the caliper to 0.25*standard error of the propen-

sity score. Appendix B shows each covariate (control vari-

ables reported) after the PSM procedure across treatment

and control firms. We re-estimate the matched sample with

From the empirical findings, we suggest how companies

can help to achieve SDGs 14 and 15 and lead future report-

ing in sustainable development. B/E accounting aligns with

wider disciplines in CSR research, such as global warming

and climate concerns. High on the economic agenda from

the COVID-19 recovery is the movement from a vulner-

able ‘business as usual’ to a sustainable ‘green recovery’,

rebalancing the human relationship with nature (Por-

ritt, 2020). Failure to provide sustainable solutions, and

if efforts to achieve the wider UN goals, including SDGs

14 and 15 are not met, the planet could be heading for an

apocalyptic crisis. We believe that due to the urgency of

the wider global environmental challenges facing humanity

(Sobkowiak et al., 2020), developing solutions is a matter

of urgency. We anticipate post COVID-19, biodiversity and

species accountability will be a core element of corporate

reporting. Companies must be responsible for committing to

achieving SDGs 14 and 15, as a failure to protect and con-

serve nature will have a catastrophic financial impact (WEF,

2020). Our results indicate that pre-COVID-19, only 25% of

companies embedded an in-depth ecological perspective and

valued species as stakeholders, which can explain positive

relations with species numbers and companies gaining assur-

ance and partnership engagement. Furthermore, our results

indicate there must be a seismic shift from poor environ-

mental performers and companies who wish to gain awards,

to consider species as stakeholders, and align with global

sustainability. Inspired by SDGs 14 and 15, we explain that

if companies collectively implement B/E reporting, this may

offer solutions for a sustainable society. As such, rethink-

ing accounting frameworks and guidelines is needed (SER,

2016), and accounting professionals need to know how they

can incorporate the B/E into their activities. For instance,

Royal Dutch Shell displays responsible disclosure:

“When we operate in critical habitats—those that are

rich in biodiversity and important to conservation—we

14 We use Pearson Chi2 test for observed and expected count frequen-

cies over time and we find that our results are statistically significant

at 5% level. This means, for instance, there is a significant relation-

ship between number of species and presence of partnership (or

environment award) Chi2 (20) = 165.014, obs-599, p < 0.00 (or C hi2

(20) = 61.72, obs-599, p < 0.00).

588

Table 7 Robustness tests:

addressing endogeneity

L. Roberts et al.

Dependent variable

Negative binomial regression

Number of species

(1)

(2)

(3)

2SRI

(4)

Buying assurance

Presence of partnership

Environment score

Environment award

Big 4

Green industry

Firm size

Log (revenue)

Leverage

Governance

CO2 emission

Log (forest area)

GDP growth

Inflation

Residual from 1st stage

Constant

LR C hi2

Observations

Pseudo R 2

Country fixed effects

Year fixed effects

1.694**

(0.855)

− 0.881

(0.757)

− 0.044

(0.642)

− 0.276***

(0.100)

0.945**

(0.457)

0.060

(0.047)

n.a.

− 0.155*

(0.084)

0.638***

(0.246)

− 0.575***

(0.162)

− 0.285

(0.234)

− 13.994**

(5.758)

44.90**

(0.016)

114

0.072

Yes

3.354***

(0.603)

1.056**

(0.522)

− 0.445

(0.424)

− 0.615***

(0.152)

0.757

(0.491)

− 0.043

(0.057)

n.a.

− 0.120*

(0.072)

0.182

(0.303)

− 0.168

(0.164)

− 0.420**

(0.200)

− 6.036

(6.391)

59.38***

(0.000)

114

0.151

Yes

1.488***

(0.526)

− 14.229**

(5.544)

0.277

(0.510)

− 0.398

(0.720)

− 0.309**

(0.131)

0.970*

(0.543)

0.610*

(0.360)

n.a.

− 0.310

(3.036)

3.436

(4.688)

0.081

(0.626)

0.115

(0.376)

− 45.575

(67.998)

46.38**

(0.017)

114

0.194

Yes

1.456***

(0.537)

5.004***

(0.533)

4.213***

(0.936)

− 8.838***

(1.654)

− 1.744***

(0.513)

− 0.037

(0.413)

− 0.114*

(0.064)

− 0.563*

(0.310)

− 0.001

(0.004)

7.028***

(1.723)

− 1.516***

(0.236)

1.796***

(0.342)

− 1.220***

(0.216)

0.736**

(0.305)

3.128***

(0.661)

− 28.562***

(7.855)

369

0.799

Yes

The table reports the effects of assurance, environment award, presence of partnership and green Industry

on the number of reported species in firm’s annual report in each year. The data consists 599 firm-year

observations of top 200 firms listed in Global 500 firms for the year 2012, 2014 and 2016. Green industry

is a dummy equal to 1 if the industry belongs to green industry and 1 if it is in red or amber industry. Natu-

ral logarithm of total assets as a proxy for firm size is used. Columns (1)–(3) reports Negative Binomial

regressions after using propensity score matching. Column (4) represents the 2-Stage Residual Inclusion

(2SRI) regression. Robust standard errors are reported in parenthesis

***Denotes 1%, **denotes 5% and *denotes 10% significance level

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

589

apply stringent mitigation standards. We were also the

first in the energy industry to introduce a biodiversity

standard.” (Royal Dutch Shell, company website).

This demonstrates how companies can regard species as

stakeholders by transparently disclosing their efforts for

nature to flourish. For example, Volkswagen has stated its

efforts in protecting and restoring biodiversity and species

as follows:

“In the grounds of the Volkswagen factory in Emden,

a colony of bees on the verge of extinction (Apis mil-

lifica) has been successfully established, growing from

5000 to 40,000 bees in just a short space of time. Plans

are underway to plant a further 1000 fruit trees to

ensure a plentiful supply of food for the bees.” (Volk-

swagen, CSR report, 2014).

Summary and Conclusion

The main aim of this paper is to explore the disclo-

sure of the number of species from the top 200 Fortune

Global companies to understand how EC/FT companies

are answering the collapse of biodiversity and threat of

further species extinction. We create and test with Pois-

son pseudo-maximum likelihood (PPML) regression, the

relationship between the number of species protected and

its determinant factors. Using a comprehensive sample

of Fortune Global companies from before the COVID-19

pandemic, from 2012, 2014, and 2016, our results reveal

that 75% of reports omit any species numbers, showing

that most companies are failing to address the B/E crisis.

However, the remaining 25% present how EC/FT compa-

nies have initiated efforts before the current pandemic,

which can influence companies’ reporting in the post

COVID-19 era. We contribute to developing solutions

with this empirical study by extending B/E literature and

encouraging companies to provide responsible reporting

and disclose B/E accountability to align with SDGs 14

and 15.

The empirical model is based on a comprehensive theo-

retical framework. These findings support prior B/E dis-

closure studies that have found that few companies provide

B/E information (Adler et al., 2018; Hassan et al., 2020b).

This evidences a huge call for companies to make trans-

formational changes from anthropocentrism, given the

urgency of the extinction crisis and existential threat to

civilization (Ceballos et al., 2020). The link to COVID-19

and human infringement with nature through illegal wild-

life markets and trade is inextricably linked to business

survival. Corporates are dependent on natural resources

and must cease to be disrespectful to nature and engage in

stewardship of natural assets (Jones, 1996). However, we

focus on the remaining EC/FT companies (25%) that are

responding to the extinction crisis and showing efforts to

conserve and protect habitats. Supporting deep ecology

theory and recognizing species as stakeholders, these com-

panies are displaying responsible corporate governance

by embedding deep ecological culture. Specifically, our

regression presents significant relationships between the

number of species disclosed and assurance, poor environ-

mental performers, presence of partnerships, and gaining

environmental awards (refer to Fig. 2). Our results imply

that there is a huge call for corporate consciousness and

opportunity for companies to display their responsible

efforts.

These findings make an important contribution to B/E

literature in at least four ways. First, our results suggest

assurance for B/E reporting as one important channel

through which corporate governance may influence B/E

outcomes, ascertaining a clear mechanism through which

external corporate governance may influence the firm’s

B/E reporting. Second, to our knowledge, this study is

the first to directly measure the number of species using a

comprehensive dataset. Thus, we can demonstrate a clear

positive relationship between environmental performance

(incentives for species protection) and species reporting,

contributing to the nascent but growing research investi-

gating how environmental performance and species report-

ing activities might be associated. Third, we contribute

more broadly to the literature by improving the under-

standing of the antecedents of species reporting of firms

using a cross-country sample. Fourth, this study extends

the extant B/E literature by taking species reporting into

consideration in a country-level institutional context. It has

been argued in the accounting literature that developing

economies suggest an interesting setting that explores both

regular questions in addition to a unique phenomenon (Lau

et al., 2016). Last, we suggest a reporting strategy for com-

panies to achieve wider global efforts of achieving SDGs

14 and 15 by advocating B/E accountability. Our evidence

shows that institutional context has a moderating effect on

the relationship between environment score, environment

award, assurance, and disclosure of the number of species.

These results have several implications. Our evidence

implies that businesses should begin to realize the intrin-

sic worth of natural capital and their reliance on balanced

ecosystems to survive. Embedding ecological culture and

aligning with societal and government expectation to prevent

further pandemics will be crucial for future organizational

survival. Additionally, our findings suggest that companies

590

L. Roberts et al.

Factors influencing B/E reporting

Assurance

Environmental

Award

Environmental

Score

Presence of

Partnerships

B/E reporting

Deep -Ecology

pressures

Fig. 2 Factors influencing B/E reporting

Legitimacy

pressures

Stakeholders

pressures

who engage with wildlife partnerships are leading in the

protection of species. These results imply that partnerships

are a key driver in preventing further species extinctions and

preventing pandemics. The collaboration between wildlife

and biodiversity experts and companies can achieve long-

term sustainability and contribute to developing solutions.

Our work can also guide policymakers in developed and

developing nations to the need to improve the surveillance

and capacity of the regulatory frameworks in the context

of B/E reporting, and to improve stakeholders’ pressures to

enhance B/E reporting adoption. Specifically, policymakers

and regulators need to make a generally agreed set of B/E

reporting guidelines and assurance standards. Collectively,

the visionary SDGs can be met by the targeted 2030, as fail-

ure to meet these targets will have severe consequences to

societal health and economic systems. This research aligns

with the United Nations initiatives and post 2020 biodiver-

sity frameworks and will guide decision-makers to under-

stand how disclosure of species protection by companies can

assist society to mitigate such risks in the future.

One of the caveats of this study is that our sample is a

qualitatively small representation of a larger population

to which it could apply. Our sample selection is limited to

the top 200 companies from the Fortune Global. There-

fore, future studies could extend the number of companies

or countries. Second, counting species numerically on its

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

591

own is not enough to advance solutions. Although this

research provides a seminal understanding of the relation-

ship between species and key determinants, additional

future research might qualitatively examine corporate

motivations and emotions for such disclosure, in order

to support our findings. Third, future studies might con-

sider case-studies and interviews with executives, boards,

shareholders, and stakeholders to investigate their views

on corporate initiatives to protect species and biodiversity,

and to align with the SDGs. There is a distinct lack of

primary data analysis in B/E literature; this would provide

invaluable insights into company motivations to protect

species. Also, there are undoubtedly other factors affecting

the number of species disclosed, such as ethnic identity,

religion, country-level or industry-specific factors, which

requires an expanded dataset to consider these additional

indicators. Research on why and how companies’ engage-

ment in biodiversity loss and species extinction report-

ing differs across nations is a promising avenue for future

work. In addition, exploring the influence of ethical deci-

sion making on biodiversity loss and species extinction

reporting across cultures would be a fruitful avenue for

further work. Furthermore, a potential avenue for future

research is to investigate the alignment of B/E, circular

economy model, and integrated reporting to enhance the

development of solutions for a sustainable society.

Appendix A

Variance inflation factor (VIF)

Variable

Number of species

Buying assurance

Environment score

Green

Environment award

Presence of partnership

Big 4

Firm size

Log (revenue)

Leverage

Governance

CO2 emission

Log (forest area)

GDP growth

Inflation

VIF Tolerance

1.04 0.9593

1.56 0.6396

1.29 0.7755

1.19 0.8397

1.14 0.8799

1.27 0.7853

1.51 0.6639

1.19 0.8402

1.20 0.8306

1.03 0.9668

5.88 0.1701

2.91 0.3442

2.96 0.3381

3.24 0.3083

1.79 0.5586

Appendix B

Covariate balance of control variables

Variables Unmatched (U)/ Treated

Matched (M)

Big 4 U

Green U

indus-

try

Firm size U

Log (rev- U

enue)

Leverage U

CO2

emis-

sion

Log

(forest

area)

GDP

growth

Inflation U

0.379

0.404

0.310

0.632

12.304

12.494

11.516

11.294

2.089

1.570

9.501

11.182

13.450

13.478

3.662

3.366

1.7603

1.3614

Control

0.395

0.421

0.800

0.596

12.569

12.728

11.277

11.376

9591.4

1.429

10.808

10.663

13.269

13.393

2.473

2.794

1.466

1.603

t-test

− 0.36

− 0.19

− 12.96***

0.38

− 1.16

− 0.51

4.95***

− 0.89

− 0.63

0.09

− 2.58**

0.58

0.99

0.21

5.33***

1.18

2.18

− 1.08

Firms with low governance and high governance score for unmatched

and matched samples.

***Denotes 1%, **denotes 5% and *denotes 10% significance level.

Open Access This article is licensed under a Creative Commons Attri-

bution 4.0 International License, which permits use, sharing, adapta-

tion, distribution and reproduction in any medium or format, as long

as you give appropriate credit to the original author(s) and the source,

provide a link to the Creative Commons licence, and indicate if changes

were made. The images or other third party material in this article are

included in the article’s Creative Commons licence, unless indicated

otherwise in a credit line to the material. If material is not included in

the article’s Creative Commons licence and your intended use is not

permitted by statutory regulation or exceeds the permitted use, you will

need to obtain permission directly from the copyright holder. To view a

copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

592

L. Roberts et al.

References

Addison, P. F. E., Bull, J. W., & Milner-Gulland, E. J. (2019).

Using conservation science to advance corporate biodiversity

accountability. Conservation Biology, 33(2), 307–318.

Adler, R., Mansi, M., & Pandey, R. (2018). Biodiversity and threat-

ened species reporting by the top Fortune Global companies.

Accounting, Auditing and Accountability Journal, 31(3),

787–825.

Adler, R., Mansi, M., Pandey, R., & Stringer, C. (2017). United

Nations Decade on Biodiversity: A study of the reporting prac-

tices of the Australian mining industry. Accounting, Auditing

and Accountability Journal, 30(8), 1711–1745.

Atkins, J. (2020). Push to put dollar value on ESG impact. The

Business Times, available at: Push to put dollar value on ESG

impact, Companies & Markets - THE BUSINESS TIMES.

Accessed 27 December 2020.

Atkins, J. F., & Atkins, B. C. (2018). Around the World in 80 Spe-

cies. . Routledge.

Atkins, J., Gräbsch, C., & Jones, M. J. (2014). Biodiversity report-

ing: Exploring its anthropocentric nature. In M. J. Jones (Ed.),

Accounting for biodiversity (pp. 213–215). Routledge.

Atkins, J., & Maroun, W. (2018). Integrated extinction accounting

and accountability: building an ark. Accounting, Auditing and

Accountability Journal, 31(3), 750–786.

Atkins, J. F., & Maroun, W. (2020). The Naturalist’s Journals of Gil-

bert White: Exploring the roots of accounting for biodiversity

and extinction accounting. Accounting, Auditing & Account-

ability Journal, 33(8), 1835–1870.

Atkins, J., Maroun, W., Atkins, B. C., & Barone, E. (2018). From

the Big Five to the Big Four? Exploring extinction accounting

for the rhinoceros. Accounting, Auditing and Accountability

Journal, 31(2), 674–702.

Ball, A., & Craig, R. (2010). Using neo-institutionalism to advance

social and environmental accounting. Critical Perspective on

Accounting, 21(2), 283–293.

Bebbington, J., & Larrinaga, C. (2014). Accounting and sustainable

development: An exploration. Accounting, Organizations and

Society, 39(6), 395–413.

Bebbington, J., & Unerman, J. (2018). Achieving the United Nations

sustainability goals: An enabling role for accounting research.

Accounting, Auditing and Accountability Journal, 31(1), 2–24.

Belal, A., & Owen, D. L. (2015). The rise and fall of stand-alone social

reporting in a multinational subsidiary in Bangladesh. Account-

ing, Auditing & Accountability Journal, 28(7), 1160–1192.

Bhattacharya, T. R., & Managi, S. (2013). Contributions of the pri-

vate sector to global biodiversity protection: Case study of the

Fortune 500 companies. International Journal of Biodiversity

Science, Ecosystem Services and Management, 9(1), 65–86.

Bhattacharyya, A., & Yang, H. (2019). Biodiversity disclosure in

Australia: Effect of GRI and institutional factors. Australasian

Journal of Environmental Management, 26(4), 347–369.

Boiral, O. (2016). Accounting for the unaccountable: Biodiversity

reporting and impression management. Journal of Business

Ethics, 135(4), 751–768.

Boiral, O., & Heras-Saizarbitoria, I. (2017). Managing biodiversity

through stakeholder involvement: Why, who, and for what ini-

tiatives? Journal of Business Ethics, 140(3), 403–421.

Boiral, O., Heras-Saizarbitoria, I., & Brotherton, M. C. (2019). Assess-

ing and improving the quality of sustainability reports: The audi-

tors’ perspective. Journal of Business Ethics, 155(3), 703–721.

Boiral, O., Heras-Saizarbitoria, I., Brotherton, M. C., & Bernard, J.

(2018). Ethical issues in the assurance of sustainability reports:

Perspectives from assurance providers. Journal of Business

Ethics, 159(4), 1–15.

Bouten, L., Everaert, P., Van Liedekerke, L., De Moor, L., & Chris-

tiaens, J. (2011). Corporate social responsibility reporting: A

comprehensive picture? Accounting Forum, 35(3), 187–204.

Braam, G., & Peeters, R. (2018). Corporate sustainability perfor-

mance and assurance on sustainability reports: Diffusion of

accounting practices in the realm of sustainable development.

Corporate Social Responsibility and Environmental Manage-

ment, 25(2), 164–181.

Buchling, M. & Maroun, W. (2018). Extinction accounting by the

public sector. In J. Atkins, & B. Atkins (Eds.), Around the

world in 80 species (pp. 201–218) Routledge.

Business and Biodiversity Campaign. (2020). Business and Biodiver-

sity. Retrieved May 7, 2020, from https://www.business-biodi

versity.eu/en/business

Callicott, J. B. (1990). Whither conservation ethics? Conservation

Biology, 4(1), 15–20.

Callicott, J. B. (1994). Conservation values and ethics. In G. K.

Meffe, & C. R. Carroll (Eds.), Principle of conservation biol-

ogy (pp. 29–42). Sinauer and Associates.

Cameron, A. C., & Trivedi, P. K. (1990). Regression-based tests for

overdispersion in the Poisson Model. Journal of Econmetrics,

46(3), 347–364.

Carrington, D. (2020). Halt destruction of nature or suffer even worse

pandemics, say world’s top scientists. The Guardian. Retrieved

May 7, 2020, from https://www.theguardian.com/world/2020/

apr/27/halt-destruction-nature-worse-pandemics-top-scientists

Casey, R. J., & Grenier, J. H. (2015). Understanding and contribut-

ing to the Enigma of Corporate Social Responsibility (CSR)

assurance in the United States. Auditing: A Journal of Practice,

34(1), 97–130.

Ceballos, G., Ehrlich, P. R., & Raven, P. H. (2020). Vertebrates on

the brink as indicators of biological annihilation and the sixth

mass extinction. In Proceedings of the National Academy of

Sciences of the United States of America, 1–7.

Chiu, T., & Wang, Y. (2014). Determinants of social disclosure qual-

ity in Taiwan: An application of stakeholder theory. Journal of

Business Ethics, 121(1), 1–20.

Cho, C. H. (2009). Legitimation strategies used in response to envi-

ronmental disaster: A French case study of Total SA’s Erika

and AZF incidents. European Accounting Review, 18(1),

33–62.

Cho, C. H., Guidry, R. P., Hageman, A. M., & Patten, D. M. (2012). Do

actions speak louder than words? An empirical investigation of

corporate environmental reputation. Accounting, Organizations

and Society, 37(1), 14–25.

Cho, C. H., Laine, M., Roberts, R. W., & Rodrigue, M. (2015a). Organ-

ized hypocrisy, organizational façades, and sustainability report-

ing. Accounting, Organizations and Society, 40, 78–94.

Cho, C. H., Michelon, G., Patten, D. M., & Roberts, R. W. (2015b).

CSR disclosure: The more things change…? Accounting, Audit-

ing and Accountability Journal, 28(1), 14–35.

Cho, C. H., & Patten, D. M. (2007). The role of environmental dis-

closures as tools of legitimacy: A research note. Accounting,

Organizations and Society, 32(7–8), 639–647.

Cho, C. H., Patten, D. M., & Roberts, R. W. (2014). Environmental

disclosures and impression management. In R. P. Hart (Ed.),

Communication and language analysis in the corporate world

(pp. 217–231). IGI-Global Publishers.

Clarkson, P. M., Li, Y., Richardson, G. D., & Vasvari, F. P. (2008).

Revisiting the relation between environmental performance and

environmental disclosure: An empirical analysis. Accounting,

Organizations and Society, 33(4–5), 303–327.

Clarkson, P. M., Li, Y., Richardson, G. D., & Vasvari, F. P. (2011).

Does it really pay to be green? Determinants and consequences

of proactive environmental strategies. Journal of Accounting and

Public Policy, 30(2), 122–144.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

593

Convention on Biological Diversity. (2020). Global Biodiversity

Outlook 5 Report. Retrieved December 7, 2020, from Global

Biodiversity Outlook 5, Convention on Biological Diversity

(cbd.int)

Costanza, R., De Groot, R., Sutton, P., Van Der Ploeg, S, Ander-

son, S. J., Kubiszewski, I., Farber, S., & Turner, R. K. (2014).

Changes in the global value of ecosystem services. Global

Environmental Change, 26, 152–158.

Deegan, C. (2002). Introduction: The legitimising effect of social and

environmental disclosures—A theoretical foundation. Account-

ing, Auditing & Accountability Journal, 15(3), 282–311.

Dehejia, R. H., & Wahba, S. (2002). Propensity score matching

methods for non-experimental causal studies. Review of Eco-

nomics and Statistics, 84(1), 151–161.

F&C Asset Report. (2004). Is biodiversity a material risk for com-

panies? Retrieved May 31, 2020, from http://www.businessan

dbiodiversity.org/pdf/FC%20Biodiversity%20Report%20FIN

AL.pdf

Gaia, S., & John Jones, M. (2017). UK local councils reporting of bio-

diversity values: A stakeholder perspective. Accounting, Auditing

and Accountability Journal, 30(7), 1614–1638.

Gaia, S., & Jones, M. J. (2019). Biodiversity reporting for governmen-

tal organisations: Evidence from English local councils. Account-

ing, Auditing and Accountability Journal, 33(1), 1–31.

Geraci, A., Daniele, F., & Chiara, M. (2018). Testing exogeneity of

multinomial regressors in count data model: Does two-stage

residual inclusion work? Journal of Econometric Methods, De

Gruyter, 7(1), 1–19.

Gibassier, D., Maas, K., & Schaltegger, S. (2020). Business, society,

biodiversity & natural capital. Business, strategy and the environ-

ment, Call for papers.

Giordano-Spring, S., Cho, C. H., & Patten, D. M. (2015). The norma-

tivity and legitimacy of CSR disclosure: Evidence from France.

Journal of Business Ethics, 130(4), 789–803.

Gourieroux, C., Monfort, A., & Trognon, A. (1984). Pseudo maximum

likelihood methods: Application to Poisson models. Economet-

rica, 52, 701–720.

Gray, R. (2010). Is accounting for sustainability accounting for sustain-

ability…and how would we know? An exploration of narratives

of organisations and the planet. Accounting, Organizations and

Society, 35(1), 47–62.

Gray, R., & Milne, M. J. (2018). Perhaps the Dodo should have

accounted for human beings? Accounts of humanity and (its)

extinction. Accounting, Auditing and Accountability Journal,

31(3), 826–848.

Gujarati, D. N. (2003). Student solutions manual for use with Basic

econometrics (4th ed.). McGraw-Hill.

Gürtürk, A., & Hahn, R. (2016). An empirical assessment of assurance

statements in sustainability reports: Smoke screens or enlighten-

ing information? Journal of Cleaner Production, 136(1), 30–41.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multi-

variate data analysis (7th ed.). Pearson Education Limited.

Haniffa, R. M., & Cooke, T. E. (2005). The impact of culture and

governance on corporate social reporting. Journal of Accounting

and Public Policy, 24, 391–430.

Haque, F., & Jones, M. J. (2020). European firms’ corporate biodiver-

sity disclosures and board gender diversity from 2002 to 2016.

British Accounting Review, 52(2), 100893.

Hassan, A., & Guo, X. (2017). The relationships between reporting for-

mat, environmental disclosure and environmental performance:

An empirical study. Journal of Applied Accounting Research,

18(4), 425–444.

Hassan, A., & Ibrahim, E. (2012). Corporate environmental informa-

tion disclosure: Factors influencing companies’ success in attain-

ing environmental awards. Corporate Social Responsibility and

Environmental Management, 19(1), 32–46.

Hassan, A., Nandy, M., & Roberts, L. (2020a). Does loss of biodiver-

sity by businesses cause Covid-19. Available at: https://www.

eauc.org.uk/does_loss_of_biodiversity_by_businesses_cause_c

Hassan, A. M., Roberts, L., & Atkins, J. (2020b). Exploring factors

relating to extinction disclosures: What motivates companies to

report on biodiversity and species protection? Business Strategy

and the Environment, 29(3), 1419–1436.

Heckman, J. J., & Todd, P. E. (2009). A note on adapting propensity

score matching and selection models to choose based samples.

The Econometrics Journal, 12(1), 230–234.

Huang, C., & Kung, F. (2010). Drivers of environmental disclosure

and stakeholder expectation: Evidence from Taiwan. Journal of

Business Ethics, 96(3), 435–451.

IPBES. (2019). Global assessment report on biodiversity and eco-

system services of the Intergovernmental Science-Policy Plat-

form on Biodiversity and Ecosystem Services. E. S. Brondizio,

J. Settele, S. Díaz, and H. T. Ngo (editors). IPBES secretariat,

Bonn, Germany. Available at: https://i pbes.n et/g lobal-a ssess ment

Johnson, C. K., Hitchens, P. L., Pandit, P. S., Rushmore, J., Evans, T.

S., Young, C. C. W., Doyle, M. M., & Johnson, C. K. (2020).

Global shifts in mammalian population trends reveal key predic-

tors of virus spillover risk. Proceedings of the Royal Society B.

https://doi.org/10.1098/rspb.2019.2736.

Jones, M. J. (1996). Accounting for biodiversity: A pilot study. British

Accounting Review, 28(4), 281–303.

Jones, M., & Solomon, J. (2013). Problematising accounting for biodi-

versity. Accounting, Auditing and Accountability Journal, 26(5),

668–687.

Jones, T. M. (1995). Instrumental stakeholder theory: A synthesis of

ethics and economics. Academy of Management Review, 20(2),

404–437.

Junior, R. M., Best, P. J., & Cotter, J. (2014). Sustainability reporting

and assurance: A historical analysis on a world-wide phenom-

enon. Journal of Business Ethics, 120(1), 1–11.

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2011). The worldwide gov-

ernance indicators: Methodology and analytical issues. Hague

Journal on the Rule of Law, 3(2), 220–246.

King, M. & Atkins, J. (2016). Chief Value Officer. Greenleaf

Publishing.

Kolk, A., & Perego, P. (2010). Determinants of the adoption of sus-

tainability assurance statements: An international investigation.

Business Strategy and the Environment, 19(3), 182–198.

KPMG. (2017). The road ahead—The KPMG survey of Corporate

Responsibility Reporting 2017, Retrieved April 28, 2020, from

https://assets.kpmg/content/dam/kpmg/xx/pdf/2017/10/execu

tive-summary-the-kpmg-survey-of-corporate-responsibility-

reporting-2017.pdf

Lambert, D. (1992). Zero-inflated Poisson regression, with an applica-

tion to defects in manufacturing. Technometrics, 34, 1–14.

Lambooy, T. E., Maas, K. E. H., van ‘t Foort, S., & van Tilburg, R.

(2018). Biodiversity and natural capital: Investor influence on

company reporting and performance. Journal of Sustainable

Finance & Investment, 8(2), 158–184.

Lau, C., Lu, Y., & Liang, Q. (2016). Corporate social responsibility in

China: A corporate governance approach. Journal of Business

Ethics, 136, 73–87.

Lewis, J. K. (2016). Corporate social responsibility/sustainability

reporting among the fortune global 250: Greenwashing or green

supply chain? Entrepreneurship, Business and Economics, 1(5),

347–362.

Lin, K. Z., Cheng, S., & Zhang, F. (2017). Corporate social responsibil-

ity, institutional environments, and tax avoidance: Evidence from

a subnational comparison in China. The International Journal of

Accounting, 52, 303–318.

Luo, L., Lan, Y. C., & Tang, Q. (2012). Corporate incentives to disclose

carbon information: Evidence from the CDP Global 500 Report.

594

L. Roberts et al.

Journal of International Financial Management and Accounting,

23(2), 93–120.

Lyon, T. P., & Maxwell, J. W. (2011). Greenwash: Corporate environ-

mental disclosure under threat of audit. Journal of Economics &

Management Strategy, 20(1), 3–41.

Ma, B., Xie, Y., Zhang, T., Zeng, W., & Hu, G. (2020). Identification

of conflict between wildlife living spaces and human activity

spaces and adjustments in/around protected areas under climate

change: A case study in the Three-River Source Region. Journal

of Environmental Management, 262, 110322.

Mahoney, L. S., Thorne, L., Cecil, L., & LaGore, W. (2013). A research

note on standalone corporate social responsibility reports: Sig-

nalling or greenwashing? Critical Perspectives on Accounting,

24(4–5), 350–359.

Maroun, W. (2018). A conceptual model for understanding corporate

social responsibility assurance practice. Journal of Business Eth-

ics, 161, 187–209.

Maroun, W., & Atkins, J. (2018). The emancipatory potential of extinc-

tion accounting: Exploring current practice in integrated reports.

Accounting Forum, 42(1), 102–118.

Maroun, W., Usher, K., & Mansoor, H. (2018). Biodiversity reporting

and organised hypocrisy, the case of the South African food and

retail industry. Qualitative Research in Accounting & Manage-

ment, 15(4), 437–464.

Milne, M. J., & Gray, R. (2013). W(h)ither ecology? The triple bottom

line, the global reporting initiative, and corporate sustainability

reporting. Journal of Business Ethics, 118(1), 13–29.

Næss, A. (1989). Ecology. . Cambridge University Press.

Næss, A. (2008). Ecology of wisdom. Publishers Group West.

Natural Capital Coalition. (2020). Natural Capital. Retrieved May 8,

2020, from https://naturalcapitalcoalition.org/natural-capital-2/

Nguyen, T., Locke, S., & Reddy, K. (2015). Ownership concentration

and corporate performance from a dynamic perspective: Does

national governance quality matter?. International Review of

Financial Analysis, 41, 148–161.

Odriozola, M., & Baraibar-Diez, E. (2017). Is corporate reputation

associated with quality of CSR reporting? Evidence from Spain.

Corporate Social Responsibility and Business Management,

24(2), 121–132.

Patten, D. (2002). The relation between environmental performance

and environmental disclosure: A research note. Accounting,

Organizations and Society, 27(8), 763–773.

Patten, D. M. (2015). An insider’s reflection on quantitative research

in the social and environmental disclosure domain. Critical Per-

spective on Accounting, 32(1), 45–50.

Perego, P., & Kolk, A. (2012). Multinationals’ accountability on sus-

tainability: The evolution of third-party assurance of sustainabil-

ity reports. Journal of Business Ethics, 110(2), 173–190.

Peters, G. F., & Romi, A. M. (2015). The association between sustain-

ability governance characteristics and he assurance of corporate

sustainability reports. Auditing: A journal of Practice, 34(1),

163–198.

Pflugrath, G., Roebuck, P., & Simnett, R. (2011). Impact of Assur-

ance and Assurer’s Professional Affiliation on Financial Ana-

lysts’ Assessment of credibility of corporate social responsibility

information. Auditing: A Journal of Practice, 30(3), 239–254.

Porritt, J. (2020). We must not miss this glorious chance to address

the biodiversity and climate crises. The Guardian. Retrieved

August 20, 2020, from https://www.theguardian.com/comme

ntisfree/2020/jun/24/climate-biodiversity-crises-government-

green-recovery-coronavirus

PWC, & WWF. (2020). Nature is too big to fail. Retrieved May 7,

2020, from https://www.pwc.ch/en/publications/2020/nature-is-

too-big-to-fail.pdf

Quigley, T. J., Hambrick, D. C., Misangyi, V. F., & Rizzi, G. A. (2019).

CEO selection as risk-taking: A new vantage on the debate about

the consequences of insiders versus outsiders. Strategic Manage-

ment Journal, 40, 1453–1470.

Raar, J., Barut, M., & Azim, M. I. (2020). The challenge: Re-steering

accountability concepts to incorporate biodiversity management

and reporting. Sustainability, Accounting, Management and Pol-

icy Journal, 11(1), 1–30.

Reade, C., Thorp, R., Goka, K., Wasbauer, M., & McKenna, M. (2015).

Invisible compromises: Global business, local ecosystems, and

the commercial bumble bee trade. Organization and Environment,

28(4), 436–457.

Rimmel, G., & Jonäll, K. (2013). Biodiversity reporting in Sweden:

Corporate disclosure and preparers’ views. Accounting, Auditing

and Accountability Journal, 26(5), 746–778.

Roberts, L., Hassan, A., Elamer, A., & Nandy, M. (2020). Biodiversity

and extinction accounting for sustainable development: A system-

atic literature review and future research developments. Business

Strategy and the Environment, 30(1), 705–720.

Roberts, L., Hassan, A., Nandy, M., & Elamer, A. (2020a). Nursing

both the Covid 19 and Biodiversity Crisis together. Available at:

https://w ww.e auc.o rg.u k/n ursin g_b oth_t he_c ovid_1 9_a nd_b iodi

versit y_cris

Samkin, G., Schneider, A., & Tappin, D. (2014). Developing a reporting

and evaluation framework for biodiversity. Accounting, Auditing

and Accountability Journal, 27(3), 527–562.

Sandifer, P. A., Sutton-Grier, A. E., & Ward, B. P. (2015). Exploring

connections among nature, biodiversity, ecosystem services, and

human health and well-being: Opportunities to enhance health

and biodiversity conservation. Ecosystem Services, 12, 1–15.

Santos Silva, J. M. C., & Tenreyro, S. (2011). Further simulation evi-

dence on the performance of the Poisson pseudo-maximum likeli-

hood estimator. Economics Letters, 112, 220–222.

Schaltegger, S., Hörisch, J., & Freeman, R. E. (2017). Business cases for

sustainability: A Stakeholder Theory Perspective. Organization

& Environment, 32(3), 191–212.

SER. (2016). Werken aan een circulaire economie: geen tijd te verliezen.

Sociaal-Economische Raad.

Simnett, R., Vanstraelen, A., & Chua, W. F. (2009). Assurance on sus-

tainability reports: An international comparison. The Accounting

Review, 84(3), 937–967.

Skouloudis, A., Malesios, C., & Dimitrakopoulos, P. G. (2019). Cor-

porate biodiversity accounting and reporting in mega-diverse

countries: An examination of indicators disclosed in sustainability

reports. Ecological Indicators, 98, 888–901.

Smith, T., Paavola, J., & Holmes, G. (2019). Corporate reporting and

conservation realities: Understanding differences in what busi-

nesses say and do regarding biodiversity. Environmental Policy

and Governance, 29(1), 3–13.

Sobkowiak, M., Cuckston, T., & Thomson, I. (2020). Framing sus-

tainable development challenges: Accounting for SDG-15 in

the UK. Accounting, Auditing & Accountability Journal, 33(7),

1671–1703.

Solomon, J. F., Solomon, A., Joseph, N. L., & Norton, S. D. (2013).

Impression management, myth creation and fabrication in private

social and environmental reporting: Insights from Erving Goff-

man. Accounting, Organizations and Society, 38(3), 195–213.

Spaiser, V., Ranganathan, S., Swain, R. B., & Sumpter, D. J. T. (2017).

The sustainable development oxymoron: Quantifying and model-

ling the incompatibility of sustainable development goals. Inter-

national Journal of Sustainable Development & World Ecology,

24(6), 457–470.

Stephan, U., Uhlaner, L. M., & Stride, C. (2015). Institutions and social

entrepreneurship: The role of institutional voids, institutional sup-

port, and institutional configurations. Journal of International

Business Studies, 46(3), 308–331.

Tagesson, T., Blank, V., Broberg, P., & Collin, S. (2009). What explains

the extent and content of social and environmental disclosures on

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically…

595

corporate websites: A study of social and environmentl reporting

in Swedish listed corporations. Corporate Social Responsibility

and Environmental Management, 1(6), 352–364.

The World Bank.. (2020). Biodiversity. Retrieved May 7, 2020, from

https://www.w orldbank.o rg/en/topic/b iodiversity#1

Thompson, S. C., & Barton, M. A. (1994). Ecocentric and anthropocen-

tric attitudes toward the environment. Journal of Environmental

Psychology, 14(2), 149–157.

Tilling, M. V., & Tilt, C. A. (2010). The edge of legitimacy: Voluntary

social and environmental reporting in Rothmans’ 1956–1999

annual reports. Accounting, Auditing & Accountability Journal,

23(1), 55–81.

United Nations. (2020a). Retrieved May 15, 2020, from https://www.

unenvironment.org/news-and-stories/story/2020-crunch-year-

biodiv ersit y-a nd-c limate-emergencies

United Nations. (2020b). Transforming our world: The 2030 agenda for

sustainable development. Retrieved August 14, 2020, from https://

sdgs.u n.o rg/2 030agenda

van Liempd, D., & Busch, J. (2013). Biodiversity reporting in Den-

mark. Accounting, Auditing and Accountability Journal, 26(5),

833–872.

Waldron, A., Miller, D. C., Redding, D., Mooers, A., Kuhn, T. S., Nib-

belink, N., Roberts, J. T., Tobias, J. A., & Gittleman, J. L. (2017).

Reductions in global biodiversity loss predicted from conserva-

tion spending. Nature, 551, 364–367.

WEF. (2020). The World Economic Forum. The Global Risk Report

2020. Retrieved May 4, 2020, from https://www.weforum.org/

reports/the-g lobal-risks-report-2 020

Weir, K. (2018). The purposes promises and compromises of extinction

accounting in the UK public sector. Accounting, Auditing and

Accountability Journal, 31(3), 875–899.

WHO. (2020). Climate change and human health. Retrieved August

14, 2020, from https://www.who.int/globalchange/ecosystems/

biodiv ersit y/en/

Zhao, L., & Atkins, J. (2018). Panda accounting and accountability.

In J. Atkins, & B. Atkins (Eds.), Around the world in 80 species

(pp. 359–388). Routledge.

Zijl, V. W., Wostmann, C., & Maroun, W. (2017). Strategy disclosures

by listed financial services companies: Signalling theory, legiti-

macy theory and. South African Integrated Reporting Practices,

48(3), 73–85.

Publisher’s Note Springer Nature remains neutral with regard to

jurisdictional claims in published maps and institutional affiliations.