Not all that glitters is green: empirical evidence from the Eurostoxx600 on stakeholders’ perception of greenwashing

Abstract

Greenwashing refers to the deceptive practice where a company exaggerates or misrepresents the sustainability of its actions or projects. Given the ambiguity surrounding the methodologies behind conventional ratings, we enquire their robustness through the implementation of an alternative comprehensive measure entailing both internally disclosed and externally generated data. We address a notorious critique in greenwashing research—that the entire voluntary CSR approach inadvertently facilitates the diffusion of greenwashing. We make a unique contribution to the statistical methodology by breaking down the difference between internal and external perception of sustainability through regression analysis. We claim that only when the presence of CSR Committees is coupled with tangible initiatives boosting sustainability, both external and internal stakeholders are found to positively evaluate the sustainable commitment of a company.

Full text

International Journal of Data Science and Analytics
https://doi.org/10.1007/s41060-024-00641-7
REGULAR PAPER
Not all that glitters is green: empirical evidence from the Eurostoxx600
on stakeholders’ perception of greenwashing
Costanza Bosone1,2 ·Paola Cerchiello1,2 ·Yana Kostiuk1,2
Received: 26 July 2024 / Accepted: 5 September 2024
© The Author(s) 2024
Abstract
Greenwashing refers to the deceptive practice where a company exaggerates or misrepresents the sustainability of its actions or
projects. Given the ambiguity surrounding the methodologies behind conventional ratings, we enquire their robustness through
the implementation of an alternative comprehensive measure entailing both internally disclosed and externally generated data.
We address a notorious critique in greenwashing research—that the entire voluntary CSR approach inadvertently facilitates
the diffusion of greenwashing. We make a unique contribution to the statistical methodology by breaking down the difference
between internal and external perception of sustainability through regression analysis. We claim that only when the presence
of CSR Committees is coupled with tangible initiatives boosting sustainability, both external and internal stakeholders are
found to positively evaluate the sustainable commitment of a company.
Keywords Sustainability ·Social responsibility ·CSR ·ESG ·Sustainable finance
1 Introduction
In investment decisions, integrating Environmental, Social,
and Governance (ESG) factors involves channelling capital
and savings towards companies and projects that priori-
tize sustainability. This entails supporting environmentally
friendly initiatives (Environment), ensuring the well-being
and inclusion of workers (Social) and promoting diversity
and gender equality in governance positions (Governance).
The moment when investments align with these principles is
referred to as sustainable finance [11].
In the aftermath of the Great Recession, sustainable
finance gained popularity as a way of combining social
responsibility with corporate governance. A growing number
of companies have been actively participating in sustainable
BCostanza Bosone
costanza.bosone@iusspavia.it
Paola Cerchiello
paola.cerchiello@unipv.it
Yana Kostiuk
yana.kostiuk@iusspavia.it
1Department of Economics and Management, University of
Pavia, Via San Felice 5, 27100 Pavia, Italy
2University School for Advanced Studies Pavia (IUSS),
Palazzo del Broletto, 27100 Pavia, Italy
initiatives, responding conscientiously to the call for action
from their stakeholders [15]. Notably, the Wall Street Journal
reports a significant uptick in the percentage of companies
disclosing ESG information, rising from 56% in 2022 to 63%
in 2023.1From investors and consumers to governments and
corporate customers, stakeholders are increasing the pressure
on companies to disclose information about their environ-
mental and social performance [32]. In line with the Nielsen
Media Research which reported that customers are willing to
pay more when they perceive firms as socially responsible2,
Grimmer and Bingham [28] show that customers are more
likely to buy at a higher price from socially responsible firms.
Despite the growth in interest in sustainable finance, a
comprehensive and systematic research on the evolution of
this phenomenon, specifically regarding its impacts on stake-
holders, is still needed [42]. Matter of factly, a major caveat
persists in the lack of standardization, which may lead to a
challenging, if not deceiving, interpretation of ESG ratings.
Barely a month goes by without a high-profile firm being
accused of misleading communications about its environ-
mental activities or sustainable performance [14].
Specifically, when scholars compare ESG ratings across
leading financial providers, they find a divergence in results
1See here the Wall Street Journal.
2See the Nielsen Media Research (2015) here.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
[12] or a low correlation between Refinitiv and S&P ESG
scores, despite these metrics purportedly assessing the same
aspects [3]. As companies lack defined targets and stan-
dards for presenting data [21], rating agencies are left free
to decide upon their own methodology.3The lack of trans-
parency stemming from this context heightens the risk for
investors to be potentially misinformed or misled, thus chan-
nelling their investments towards companies that only claim
to support green or social initiatives, without achieving any
tangible results. In summary, stakeholders face the risk of
greenwashing, a deceptive practice where a company exag-
gerates or misrepresents the sustainability of its actions or
projects [11].
Concerns about greenwashing practices have raised con-
currently with the rampant adoption of green practices. One
of the most notorious critiques is that the entire voluntary
Corporate Social Responsibility (CSR) approach inadver-
tently facilitates the diffusion of greenwashing [24]. While
the enhancement of CSR is supposed to boost the share of
green initiatives pursued by a company, the lack of standard-
ized rules or common guidelines is likely to pave the way to
misleading forms of green communication.
Drawing from a well-established literature, we enquire
the institutional complexity underlying the substantial ver-
sus symbolic adoption of environmental practices. First, we
assess the incentives and deterrents a company generally
faces when greenwashing. Next, we focus on the inter-
play between external and internal stakeholders, evaluating
the differences in the respective evaluations of a company
engagement in sustainability practices. Given the ambigu-
ity surrounding the methodologies behind conventional ESG
ratings, we test for the robustness of standardized black-box
scores offered by financial providers by implementing an
alternative measure entailing both internal and external stake-
holders’ perception of sustainability. Our main contribution
addresses the notorious critique that the entire voluntary CSR
approach inadvertently facilitates the diffusion of greenwash-
ing. We make a significant contribution by outlining how
internal versus external stakeholders’ perception of CSR dif-
fers.
The paper is organized as follows: in Sect.2we discuss
the relevant literature, in Sect.3we describe the data and
3When it comes to the methodology, two main aspects can be consid-
ered: (I) the indicators included in each pillar and (II) the weights given
to each indicator. By indicators, we refer to the aspects included by
providers in the evaluation of ESG final scores. For instance, Refinitiv
accounts for around 50 indicators in the evaluation of E such as "Tar-
gets Emissions" or "Biodiversity Impact Reduction". These indicators
are not easily knowable and must be manually derived by unboxing
each pillar from the provider site. By weights, we refer to the impor-
tance given to each indicator in the final ESG score. Since "Targets
Emissions" is available for many more companies than "Biodiversity
Impact Reduction", it is likely to weight more in the final computation
of the E score.
the relevant methodology, in Sect. 4we report our empirical
evidence, and finally, we draw our conclusions.
2 Literature review
Sustainable finance typically entails the integration of Envi-
ronmental, Social, and Governance (ESG) considerations
into corporate management, financial decision-making and
investors’ portfolio choices [37]. The correct integration of
the three ESG pillars into corporate practices involves chan-
nelling capital and savings towards companies and projects
prioritizing sustainability. This entails supporting initiatives
that are not "only" environmentally friendly (E), but also
ensure the well-being and inclusion of workers (S) and pro-
mote diversity and gender equality in governance positions
(G) [11].
In line with this perspective, out of the 17 Sustainable
Development Goals (SDGs) defined by the United Nations
(UN), three exclusively address environmental concerns,
while the remaining address socioeconomic concerns for the
promotion of future prosperity [50]. Similarly, Sheehy [44]
argues that sustainability should encompass environmental
as well as sociopolitical aspects, ultimately aiming at the
enhancement of labour conditions.
While there is evidence that the enhancement of sus-
tainable consumption and production not only benefits the
society as a whole, but also the economic performance
of those firms implementing it [36,40], companies might
be inclined to disseminate misleading information about
their ESG performance in the attempt to influence stake-
holders’ perceptions, a phenomenon commonly known as
greenwashing. We adopt the definition coined by [11] and
define greenwashing as the deceptive communication prac-
tice wherein a company exaggerates or misrepresents the
sustainability of its actions or projects.4
Numerous researchers have extensively investigated this
phenomenon. In their groundbreaking research, [18] develop
a comprehensive and well-known analysis of the exter-
nal, organizational, and individual drivers of greenwashing.
Being firms faced with "market external drivers" of green-
washing, they are demanded by both consumers and investors
to be environmentally friendly and to engage in sustainable
initiatives. As consumers and investors increasingly pressure
firms to be environmentally friendly, the likelihood of firms
enhancing their sustainable performance through misleading
4This definition is provided by the European Supervisory Authorities
(ESAs). The European Supervisory Authorities (ESAs) are represented
by three entities—i.e., European Banking Authority (EBA), European
Security and Market Authorities (ESMA), and European Insurance and
Occupational Pension Authorities (EIOPA)—responsible for oversee-
ing the financial sector of the European Union. The relative reports are
available here: EBA,ESMA,EIOPA.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
communication also rises. Moreover, the regulatory environ-
ment defines the availability and reliability of information
disseminated by companies about their environmental prac-
tices. At the same time, they argue that internal drivers, such
as firms’ characteristics, the effectiveness of intra-firm com-
munication, and incentive structure, can influence the way
that firms face external pressure. For instance, large and well-
known corporations, especially those operating in industries
with poor environmental performance, frequently find them-
selves under increased scrutiny from both activists and the
media. In line with this branch of research, our analysis
investigates differences in external and internal stakeholders’
perception by considering both self-disclosed and external
sources of data for the evaluation of the sustainability con-
duct of firms.
There is evidence that the ultimate impact of greenwash-
ing on a company performance is broad and even expands to
those companies authentically committed to their environ-
mental mission [23]. In a well-known article, Du [19] finds
evidence of a negative correlation between greenwashing and
corporate revenues, thus suggesting that companies are more
likely to resort to greenwashing behaviours during periods
of financial distress. Notably, other scholars assert that only
symbolic actions negatively impact a company’s financial
performance, while substantive actions neither harm nor ben-
efit firms [53]. Under the concept of green highlighting, they
differentiate between a firm’s environmental responsibility in
terms of past actions (substantive) and plans (symbolic), stat-
ing that only the difference between symbolic and substantive
actions gives rise to greenwashing. Ultimately, greenwashing
adversely affects financial outcomes.
Corporate governance plays a major role in deciding upon
the level of sustainability engagement of a company and the
actions undertaken. Accordingly, scholars have widened the
concept of corporate governance beyond the traditional focus
on economic and financial aspects. Hambrick and Mason [29]
state that organizational outcomes such as strategic choices
and performance levels can be partially predicted by man-
agerial background characteristics. Aguilera et al. [5] support
for a broader interpretation of governance encompassing the
intricate network of interdependencies between organiza-
tions and the diverse incentives that shape the effectiveness
of governance practices. Similarly, Aoki [7] argues that cor-
porate governance should consider the value systems of all
stakeholders involved in a firm, thus paving the way to the
inclusion of social, equality, and inclusive instances.
More recently, an innovative area of research has emerged,
shedding light on the distinct role of female stakeholders
within corporate governance. Specifically, scholars focus on
the influence exerted by the presence of women on boards
and its implications for a company’s performance across ESG
dimensions. Findings claim that higher levels of gender or
ethnic diversity make boards more responsive to sustainabil-
ity instances: a female CEO as well as a higher share of female
directors on the board Committees significantly increase cor-
porate environmental investments [10]. Moreover, gender
matters when it comes to the perception of ethical climate, as
women show a significantly more favourable attitude towards
ethical behaviours than men [38]. In comparison to male, the
environmental investment made by female executives sig-
nificantly reduces pollutant emissions, thus implying that
increasing representation of female executives in enterprises
can contribute to a significant improvement in environmental
quality [31]. An enhancement of female presence at corporate
level is bound to bring significant economic advancements
also at the global level, with an increase in global GDP by
26% [17].
Stemming from the literature on corporate governance,
a significant amount of research has concentrated on an
iconic element of a company sustainable engagement—
Corporate Social Responsibility (CSR). Despite its growing
relevance, CSR lacks of a universally accepted definition.
Sarkar and Searcy [43] delve into the evolution of CSR by
analysing 110 definitions spanning from 1953 to 2014. The
study identifies six recurring and enduring dimensions that
underpin the CSR concept: economic, social, ethical, stake-
holders, sustainability, and voluntary dimension. Despite
high levels of heterogeneity across definitions, these fea-
tures have persisted, providing key insights for the correct
definition of CSR. In line with [44], CSR can be defined
as a self-regulatory system that fosters a company’s social
accountability to itself, its stakeholders and the wider pub-
lic. To effectively implement CSR, companies establish CSR
Committees with the goal of conducting business in such a
way that actively contributes to societal and environmental
well-being, transcending mere profit-making objectives.
In reality, the mitigating role of CSR appears controver-
sial. CSR practices can sometimes act as a smokescreen,
concealing a company superficial engagement in sustainabil-
ity actions with the aim of winning or retaining investors’
trust [16]. Sometimes companies resort to CSR Commit-
tees in times when management becomes more intricate and
CSR Committees can function as a tool to reduce a company
exposure to responsibility failures [25]. Initiatives by social
stakeholders are found to potentially increase the likelihood
of future financial distress [20]. Similarly, there is a positive
correlation between a company’s probability of default and
the presence of CSR Committees [13]. Diverse perspectives
surround the impact of voluntary CSR disclosure. Supporters
argue that such disclosure mitigates problems of asymmet-
ric information among market agents [35] and is generally
linked to higher CSR performance scores [39]. However, con-
tenders argue that even companies with high CSR scores may
engage in various forms of greenwashing [1]. Furthermore,
[46] specifically focuses on the risk of greenwashing that
may arise when companies market high levels of commit-
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
ment to gender equality. Recent studies challenge the notion
that establishing CSR Committees alone can eliminate the
possibility of greenwashing [24]. In other words, the mere
existence of CSR Committees does not guarantee the absence
of deceptive environmental practices. Additionally, the pre-
vailing consumer and investor pressure for environmental
responsibility heighten the likelihood of firms resorting to
greenwashing [52], emphasizing the importance of scruti-
nizing relative claims.
To date, sustainable finance faces a notable weakness
attributed to the absence of standardized definitions or inter-
pretations [21]. A body of literature has highlighted how
the lack of clear policy frameworks paves the way to the
proliferation of greenwashing practices [34,49]. This void
creates a significant hurdle in interpreting ESG indicators,
thus reducing their credibility as reliable financial metrics.
Scholars have addressed this issue by mapping differences
in ESG rating methodologies among prominent providers
and categorizing them under a common taxonomy. Their
research reveals that divergent scores may arise from vary-
ing providers, prompting a call for a unified methodology
[3,12]. In response to this challenge, the European Commis-
sion, in collaboration with the Technical Expert Group on
Sustainable Finance, developed the "EU taxonomy" to pro-
vide a comprehensive list of economic activities considered
green [47]. However, it has not been made legally binding so
far.
To overcome the limitations of conventional ESG ratings,
we advocate for a departure from conventional black-box
scores offered by financial providers and we propose the
implementation of an innovative comprehensive measure
entailing both internally and externally disclosed data. This
approach allows us to investigate the differences in external
and internal stakeholders’ perception for the evaluation of the
sustainability conduct of firms, in line with [18]. By building
on both internal and external perception, we aim to shed new
light on the controversial role of CSR.
In sum, we draw from a well-established literature to
assess the consequences of misleading green communica-
tion on corporate performance. Our dataset and methodology,
alongside our results, will be presented in the next section.
3 Methodology and data
3.1 Data
Since the EU seems more sensible to sustainability problems
than other institutions, as proved by the number of initia-
tives and regulations promoted in this regard—e.g., Technical
Experts Group (TEG) on Sustainable Finance, we use the
Eurostoxx600 companies as a sample of data.
We advocate for a departure from standardized black-
box scores provided by financial institutions and propose
the implementation of an innovative measure entailing both
internal and external stakeholders’ perception of sustain-
ability. These data are sourced from FinScience and define
internal scores as those derived from self-reported and dis-
closed corporate data and external scores as those derived
from data generated by external stakeholders.5More specifi-
cally, internal scores encompass standard ESG metrics from
Refinitiv, S&P and Bloomberg, coupled with information
on sustainable initiatives derived from Sustainability/CSR
reports, corporate websites, sustainability memberships and
affiliations and certifications.6External data are sourced from
reputable entities, such as specialized websites, NGOs, ver-
tical websites and mainstream news sources, that provide
insights into the positive or negative sentiment surround-
ing news related to sustainability matters concerning the
company. The metrics include controversies and reviews,
crucial to capture instances where companies face sanctions
or fines due to environmental violations or their involve-
ment in highly polluting activities and, finally, information
sourced from social media. This way, external scores cap-
ture a dynamic information stream about a company’s
performance, providing a comprehensive overview of its
environmental reputation.
By combining internal and external scores, we can pro-
duce an indicator of greenwashing risk. More in detail, we
consider the difference between the internal and the external
scores—hereafter referred to as delta ()—and use it as a
proxy for the likelihood of a company to communicate mis-
leading information about its sustainability levels. In absolute
terms, a higher () implies a higher risk, as a company’s
external perception drifts away from its internal stakehold-
ers’ one. To compute () we keep only companies for which
both internal and external scores are available, obtaining a
dataset of 467 companies all belonging to the Eurostoxx600
index (see Appendix, Table 6for the complete list of com-
panies and 5for the definition of variables).
We enhance the scope of the dataset by incorporating
key variables to assess the different incentives faced by
stakeholders. To account for conventional models viewing
corporations as legal tools for stakeholders to maximize
their investment returns [45], we introduce traditional finan-
5FinScience is a tech company of the Datrix Group specialized in
applying AI to support investment decisions. See the official webpage
here.
6For memberships and affiliations to be considered trustworthy, com-
panies must meet stringent requirements related to environmental
performance or commitment. Specifically, it is requested the presence
of at least two reputable memberships associated with environmental
matters. For certifications to be considered trustworthy, it is requested
the presence of at least two certifications linked to environmental issues
(e.g., ISO 14001, ISO 50001).
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 1 Distribution of
companies across sectors GICS Sector Number of firms
Communication services & Information technology 52 (11,1%)
Consumer Discretionary 55 (11,8%)
Consumer Staples 43 (9,2%)
Energy 16 (3,4%)
Financials & Real Estate 93 (20%)
Healthcare 41 (8,8%)
Industrials 95 (20,3%)
Materials 45 (9,6%)
Utilities 27 (5,8%)
TOTAL 467
Sector classification based on the Global Industry Classification Standard (GICS)
cial performance indicators: Revenue Per Share, Return on
Assets (ROA), Return on Equity (ROE), Market Capitaliza-
tion, and Credit Rating. Simultaneously, we incorporate a
more modern perspective that sees corporations as respon-
sible for a broader range of stakeholders’ interests than
financial ones, thereby emphasizing the importance of fair
corporate governance mechanisms [5,9,48]. Specifically,
we include board size, the percentage of women on the
board, the percentage of women employees in a company
and the presence of a CSR Committee. The integration of
gender diversity metrics is vital for evaluating the commit-
ment of a company to equitable and inclusive practices,
foundational to sustainable business models. The presence of
women on the board is a critical indicator of gender diversity
at the highest decision-making level. Research has shown
that diverse boards are more likely to engage in responsi-
ble governance practices, thereby aligning more closely with
broader stakeholder interests, including sustainability [10,
31]. The proportion of women employees within a company
reflects gender diversity at the operational level. This metric
is essential for evaluating the inclusiveness of a company’s
workforce, which is a key component of its overall sustain-
ability. A balanced gender representation can indicate a more
equitable working environment, which is linked to better
social performance outcomes. In our study, the descriptive
statistics show that the average percentage of women employ-
ees is 37%, while the percentage of women on boards is
36%. This indicates that men occupy roughly two-thirds of
the remaining positions, both at the highest decision-making
level and at the operational level.
We source all variables from Refinitiv. We control for
the size of a company by dividing total assets into quartiles
and assigning a value ranging from 1 (smallest firms) to 4
(largest firms) to each quartile. We control for the operat-
ing sector of a company by relying on the Global Industry
Classification Standard (GICS) grouping companies into the
following sectors: communication services, consumer dis-
cretionary, consumer staples, energy, financial, healthcare,
industrial, materials and utilities.7The distribution across
sectors of the companies in our sample is reported in Table
1. Finally, Table 2reports descriptive statistics for continuous
variables and Table 3the correlation matrix.
3.2 Methodology
We use as our dependent variable, which is formally con-
structed as:
=internal score −external score
After standardizing the dataset, we perform the following
main equation:
=
n

i=1β0+β1RPS +β2ROA +β3ROE
+β4MarCap +β5CrRat
+β6CSR +β7BS +β8WOB +β9WE
+
n

k=1
ϕk+
n

j=1
ηj+i,
(1)
where all traditional financial indicators enter the equation
as regressors from β1to β5, namely Revenue per Share
(RPS), Return on Assets (ROA), Return on Equity (ROE),
Market Capitalization (MarCap) and Credit Rating (CrRar).
From β6to β9, we encompass all indicators assessing the
level of fairness at governance level, namely CSR Commit-
tee (CSR), Board size (BS), Women on Board (WB) and
7The GICS is an industry taxonomy developed in 1999 by MSCI and
S&P for the global financial community. The GICS structure consists
of 11 sectors, 25 industry groups, 74 industries and 163. See the report
here.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 2 Descriptive statistics Variable Mean Std.Dev. Min Max
Revenue Per Share 93.2 873 0.00 18648.275
Return on Assets 0.05 0.08 −0.193 0.87
Return on Equity 0.16 0.97 −2.14 20.5
Market Capitalization 2.899e+10 4.659e+10 2.649e+08 3.954e+11
Total Assets 1.203e+11 3.349e+11 2.194e+08 3.039e+12
Board Size 11.27 3.5 4 23
Women Employees 0.37 0.15 0.11 0.76
Female on Board 0.36 0.11 0.00 0.75
Delta −4.6 13.7 -48 38
Internal 66.44 11.5 29 88
External 71.02 9.5 41 84
Table 3 Correlation matrix
(1) (2) (3) (4) (5) (6) (7) (8)
(1) Revenue per Share 1.000
(2) ROA −0.010 1.000
(3) ROE −0.006 0.164 1.000
(4) Market Capitalization 0.006 0.076 0.013 1.000
(5) Total Assets −0.015 −0.179 −0.033 0.164 1.000
(6) Board Size −0.064 −0.281 −0.049 0.206 0.254 1.000
(7) Female on Board −0.100 −0.021 0.060 0.048 0.072 0.070 1.000
(8) Women Employees 0.064 −0.033 −0.027 0.088 0.214 −0.000 0.181 1.000
(9) Delta −0.065 0.006 0.023 0.082 0.016 0.119 −0.058 −0.232
(10) Internal −0.052 −0.076 0.043 0.171 0.126 0.290 0.050 −0.096
(11) External 0.031 −0.102 0.019 0.088 0.130 0.181 0.143 0.219
Women Employees (WE). Each specification runs for all
companies ifrom 1 to nincluded in the dataset. The error
term is indicated as i. To ensure the robustness and reliabil-
ity of our results, we first cluster standard errors at the sector
level to address potential correlations or heteroscedasticity
within sectors. Second, we incorporate fixed effects at size
level (ϕk) and sector level (ηj) to account for unobservable
factors that may systematically vary within the size of com-
panies or be unique to each economic sector.
The inclusion of CSR Committees in our analysis may
prompt questions about potential reverse causality concerns,
given that CSR-related variables are already a component
of the internal score. To address this concern, we break-
down how CSR enters our dependent variable. Specifically,
internal scores encompass information on I) the quality of
sustainability reports, by investigating whether a third party
ensures that the environmental/sustainability report under-
goes a verification process to conform to specific reporting
frameworks (e.g., GRI Sustainability Reporting Standards)
and II) the sustainability CSR section on official websites,
by examining whether a company official website dedicates
to environmental issues one or more sections. Furthermore,
it considers whether the company actively communicates its
sustainability efforts to the public through its online plat-
forms. Conversely, the variable CSR we use as a regressor in
our analysis is a dummy simply testing for the presence (1) or
absence (0) of CSR Committees. It does not provide informa-
tion about the writing of CSR reports nor about their quality.
While this approach allows us to differentiate between the
existence of CSR Committees and the nuanced qualities asso-
ciated with sustainability reporting, it is not likely to lead to
reverse causality.
In addition to Eq. 1, we run two further specifications
to test for internal and external stakeholders’ perception by
using internal and external score as dependent variables,
respectively:
Internal =
n

i=1β0+β1RPS +β2ROA +β3ROE
+β4MarCap +β5CrRat
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
+β6CSR +β7BS +β8WOB +β9WE+
+
n

k=1
ϕk+
n

j=1
ηj+i(2)
External =
n

i=1β0+β1RPS +β2ROA +β3ROE
+β4MarCap +β5CrRat
+β6CSR +β7BS +β8WOB +β9WE+
+
n

k=1
ϕk+
n

j=1
ηj+i(3)
4 Results
4.1 Delta scores
The first part of our research aims at analysing the different
drivers of greenwashing a company faces. We rely on Eq.
1and show results in Table 4from column (1) to (3). We
first run a standard OLS model without fixed effects (column
(1)). Next, we add fixed effects at size level (column (2)), and
finally, we include the set of fixed effects at the sector level
(column (3)).
The negative correlation between revenues per share and
() shown across all specifications suggests a compelling
signal that companies may be more inclined to convey mis-
leading messages on sustainability when faced with declining
profits. Our findings align with existing studies on the specific
connection between greenwashing, investor behaviour, and
market responses [14,19]. While the ROA shows a negative,
albeit non-significant correlation, the ROE shows a positive
and statistically significant correlation across all specifica-
tions. This result partially challenges our previous finding,
yet mixed evidence is found on the impact of the ROE on
the sustainable performance of a company [6,27] and on its
robustness as an indicator of financial performance [8].8
Neither Market Capitalization nor Credit Rating shows
a significant correlation with the dependent variable (),
except for a weak correlation between Market Capitalization
and greenwashing in column (2). The lack of significance
can be explained by little variations in terms of credit ratings
across the Eurostoxx600 companies. Beside, these results
align with the existing literature [30,33], where the weak
8Arditti [8] argues that elevated returns may signify inconsistent profits
or an over-reliance on excessive debt.
correlation between ESG scores and ratings is such that rat-
ings alone may not effectively capture the effect of ESG.
The presence of women seems to mitigate the risk of mis-
leading communication. We find that the share of female
employees is negatively and significantly correlated across
the three model specifications; thus, the risk of misleading
communication falls when the number of women employed
at different levels increases, in line with [10,31]. Similarly,
the share of women on the board shows a negative, albeit not
significant correlation across the model specifications. The
board size shows a positive and significant correlation; hence,
the larger the board, the higher the risk of greenwashing. This
is in line with those claiming that larger boards entail larger
agency costs due to a rise in inefficiencies [41].9
Corporate Social Responsibility (CSR) Committees, which
are supposed to mitigate greenwashing risks by accounting
for a company’s socially responsible actions and reputa-
tion [51], show a positive and significant correlation across
all three specifications. In reality, their mitigating role is
controversial; some claim that voluntary disclosure of CSR
information is generally associated with higher CSR perfor-
mance scores [39], others argue that companies are likely
to be involved in some forms of greenwashing even when
they show high CSR scores [1] or they may be guilty of
CSR-washing in an attempt of marketing higher levels of
commitment to gender equality initiatives than real ones [46].
Further studies deny the possibility of ruling out greenwash-
ing by simply setting up CSR Committees [24]. Our findings
confirm this last branch of literature. Ultimately, the presence
of such Committees is not enough to ensure an active corpo-
rate engagement in sustainability projects. Companies may
resort to CSR Committees in an attempt to green-market their
products or behaviours as “green” and to conquer or maintain
investors’ trust.
4.2 Internal versus external scores
We analyse the differences between internal and external
stakeholders’ perception of sustainability by relying on Eqs.
2and 3, respectively. Results are presented in Table 4from
column (4) to (9). As usual, we add sector-level fixed effects
(column (5) and (8), respectively) and size-level fixed effects
(column (6) and (9), respectively).
From column (4) to (6), we focus on the internal percep-
tion of sustainability. Revenues per share exhibit a negative
and statistically significant correlation across all three speci-
fications, which aligns with the previous negative correlation
found between revenues and (). Since greenwashing risks
9We remark that we only focus on companies belonging to the
Eurostoxx600 index, which are likely to share similarly sized boards
and hence to show little variation across our sample. Results may vary
if companies with larger differences are considered.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 4 Main estimates
Delta Internal External
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Revenue per Share −0.0566*** −0.049** −0.051** −0.0367** −0.047*−0.047** 0.037** 0.014 0.017
(0.011) (0.014) (0.02) (0.01) (0.014) (0.011) (0.014) (0.012) (0.012)
ROA 0.0278 −0.006 0.07 −0.005 0.04 0.033 −0.047 0.057 0.03
(0.06) (0.056) (0.044) (0.084) (0.094) (0.091) (0.048) (0.053) (0.06)
ROE 0.0183*0.0233*0.018*0.0487*** 0.045*** 0.044*** 0.033*0.021 0.027*
(0.009) (0.0086) (0.008) (0.004) (0.005) (0.006) (0.0014) (0.012) (0.009)
Market Capitalization 0.0591 0.081 0.021 0.1. 0.06 0.04 0.04 −0.04 0.02
(0.051) (0.047) (0.042) (0.065) (0.057) (0.051) (0.057) (0.025) (0.025)
Credit Rating −0.007 −0.004 0.0003 −0.005 −0.009 −0.007 0.0047 −0.005 −0.009
(0.007) (0.007) (0.07) (0.007) (0.006) (0.007) (0.01) (0.008) (0.007)
CSR Committee 0.67*** 0.7*** 0.576** 0.95*** 0.92*** 0.85*** 0.18*0.101 0.192*
(0.114) (0.114) (0.128) (0.154) (0.15) (0.16) (0.075) (0.061) (0.063)
Board size 0.0874*0.119. 0.124. 0.223*** 0.181*** 0.189** 0.145** 0.048 0.05
(0.044) (053) (0.057) (0.038) (0.038) (0.04) (0.053) (0.05) (0.05)
Womenonboard −0.0537 −0.043 0.024 0.118 −0.0022 0.0133 0.09 0.057 0.049
(0.041) (0.04) (0.04) (0.055) (0.051) (0.052) (0.056) (0.053) (0.058)
Women employees −0.2287** −0.231*−0.209*** −0.109*−0.11. −0.059 0.198*** 0.199*0.23**
(0.07) (0.075) (0.035) (0.05) (0.054) (0.032) (0.077) (0.065) (0.061)
Observations 467 467 467 467 467 467 467 467 467
Adj. R20.1 0.1 0.17 0.17 0.18 0.2 0.08 0.16 0.21
Size effects No Yes Yes No Yes Yes No Yes Yes
Sector effects No No Yes No No Yes No No Yes
Clustered Std.Err Yes Yes Yes Yes Yes Yes Yes Yes Yes
Clustered standard errors in parentheses: ***p<0.000; **p<0.001; *p<0.01; p<0.05
increase when revenues go down, it follows that internal
stakeholders are more likely to declare higher level of sustain-
ability performance when profits decrease. While the ROA
bears no significance, a positive and highly significant cor-
relation across all model specifications is found between the
ROE and the internal perception of sustainability. Signifi-
cance levels are higher than before, which we explain through
the intuition that corporate financial performance is likely to
weight more on internal perception [4].10
The board size shows a positive and significant correla-
tion; hence, larger boards seem to favour an improvement in
the internal perception of sustainability performance. Com-
pared to (), the significance level for the board size has
remarkably improved, in line with the importance played by
the board from tan internal stakeholder’s perspective.
The share of women on the board does not exhibit any sig-
nificant impact, while the share of female employees weakly
10 Weremark that ROE alone is neither an adequate measure of financial
performance [8] nor of sustainable performance [6]. Though our results
suggest that ROE has a positive and significant impact on a company’s
self-disclosed scores of sustainability, this intuition is limited to our
sample.
survives in the first two specifications (column (5) and (6),
respectively). The absence of a significant influence of this
variable from an internal perspective marks a structural dif-
ference from , as it infers that the overall level of women
employed is not decisive in shaping a company’s internal per-
ception of sustainability. Conversely, the presence of CSR
Committees shows a positive and highly significant corre-
lation across all specifications (from column (4) to (6)). It
follows that internal stakeholders greatly value the presence
of similar Committees when evaluating the sustainability
performance of the company. A similar robust correlation
implies that the mere presence of CSR Committees signals a
tangible commitment on the part of the company to address
sustainability concerns, yet the existing literature cautions
against over-interpreting the presence of these Committees
as a guarantee of active engagement in CSR investments
When we move to the external perception of sustainability,
the usual indicators of financial performance—i.e., Revenues
per Share and ROE—exhibit a diminished significance com-
pared to earlier results in both () and internal scores. The
significance level of Revenues survive only in the first model
specification (column (7) vis-à-vis column (1) and column
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
(4), respectively), while the ROE retains statistical relevance
only in the first and last models (column (9) vis-à-vis col-
umn (3) and (6)), with notably lower significance levels than
before, especially if compared with internal scores estimates.
A strong financial performance is viewed positively by exter-
nal stakeholders, but it does not seem to play a crucial role
in shaping their evaluation of the sustainable performance of
a company. Similarly, the significance of board size endures
only in the first model specification, indicating that the size of
the board may not be a consistent factor influencing external
stakeholders’ evaluations.
Notably, the level of women employed resurfaces with
a positive and strongly significant correlation across all
three model specifications, which seems to indicate that a
higher representation of women in the workforce corresponds
to a more favourable external perception of sustainability.
Finally, the loss of importance witnessed by the presence of
CSR comes as a validation of our results. Estimates are the
weakest out of all models and even lose their significance
in column (8), thus suggesting that external stakeholders are
not likely to accept the presence of CSR Committees as a
sufficient indicator of a firm’s commitment to sustainability.
5 Conclusions
We draw from a well-established literature to enquire the
institutional complexity underlying the substantial versus
symbolic adoption of environmental practices, namely green-
washing. We analyse the drivers of greenwashing through
regression analysis and break down the difference between
internal and external stakeholders’ perception of sustainabil-
ity.
We find a negative correlation between greenwashing and
corporate revenues, which suggests that firms facing financial
distress encounter heightened motivations for greenwashing
as a strategic move to secure investors’ trust. The absence
of stringent regulations in sustainable finance amplifies the
incentives for companies to present a positive image of their
sustainable practices. Conversely, a higher number of female
employees seem to mitigate the risk of greenwashing.
We uncover a disparity in external vis-à-vis internal stake-
holders’ evaluation of sustainability. The positive correlation
between the presence of CSR Committees and internal
perception is robust to the point that presence of CSR Com-
mittees may be enough to signal a tangible commitment on
the part of the company to address sustainability concerns,
yet results derived from the external perspective caution
against over-interpreting the presence of these Committees
as a guarantee of active engagement in CSR investments.
In the pursuit of sustainability, external stakeholders appear
to place greater emphasis on tangible, real-world achieve-
ments, such as the actual level of women employed at the
firm level, as opposed to internal stakeholders, who seem to
prioritize formal achievements, such as the mere presence of
CSR Committees and overall place greater emphasis on tra-
ditional indicators of financial performance. Crucially, this
contrast highlights a shift in priorities between internal and
external perception. After years of uncontrolled greenwash-
ing, consumers tend to become more cynical about green
claims, making it hard for companies to deceive them by the
mere establishment of CSR Committees.
Nevertheless, the need for a common methodology to
mitigate the risk of misleading communication is urgent. A
notable effort in this direction has been made by the “Techni-
cal Expert Group on Sustainable Finance” (TEG), established
in 2018 by the European Commission. The TEG developed
the EU taxonomy, a classification system that determines
whether an economic activity is environmentally sustainable,
and proposed disclosures for ESG factors. This framework
is one of the most significant achievements in sustainable
finance, though it primarily focuses on the Environmental
(E) dimension.
To improve sustainability assessments, ESG rating agen-
cies must integrate all three dimensions—Environmental (E),
Social (S), and Governance (G)—equally, considering both
current and future needs as well as specific risks over the
short and long term. In addition to standardizing methodolo-
gies, European authorities should develop a comprehensive
disclosure system for ESG indicators, providing clear and
consistent information to the monitored firms.
As further lines of research, valuable insights could be
gained by expanding the sample of companies analysed.
In particular, the inclusion of emerging internet companies,
which are rapidly gaining prominence, is likely to repre-
sent an innovative and valuable contribution to the literature.
Given the present of internal vis-à-vis external stakeholders’
perspective and in line with the innovative research developed
by [2][26] and [22], our methodology could be expanded
following their Bayesian approach with the aim of merging
the two stakeholders’ perspectives, eventually assessing the
impact on greenwashing.
Appendix
See Tables 5and 6.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 5 List of variables and their definition. Source: Authors’ elaboration
Type of variable Variable Description Source
Dependent variable Delta Difference in absolute term between internal and external scores Authors’ calculations
Internal score Measures the company’s ESG performance based on corporate self-
reported and disclosed data
FinScience
External score Measures the company’s ESG “perceived” performance based on alter-
native external stakeholder-generated data
FinScience
Explanatory variables Revenue per Share (RPS) Total Revenue for the fiscal year divided by Diluted Weighted Average
Shares Outstanding
Refinitiv
ROA Return on Assets Refinitiv
ROE Return on Equity Refinitiv
Market Capitalization (MarCap) Market value of the requested issue share type Refinitiv
Credit rating (CR) Agency-equivalent credit rating Refinitiv
CSR Committee (CSR) The presence of a CSR Committee or team in the company Refinitiv
Board size (BS) The total number of board members at the end of the fiscal year Refinitiv
Women on board (WOB) Percentage of female on the board Refinitiv
Women employees (WE) Percentage of women employees Refinitiv
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 List of companies. Source: Authors’ elaboration
Company Name Sector Company Name Sector
Ashmore Group PLC Financials & Real Estate Kesko Oyj Consumer Staples
Mercedes-Benz Group AG Consumer Discretionary Kingfisher PLC Consumer Discretionary
William Hill Ltd Consumer Discretionary Kingspan Group PLC Industrials
3i Group PLC Financials & Real Estate Kinnevik AB Financials & Real Estate
A2A SpA Utilities Klepierre SA Financials & Real Estate
AAK AB Consumer Staples Knorr Bremse AG Industrials
AB Skf Industrials Kone Oyj Industrials
Abb Ltd Industrials Koninklijke Ahold Delhaize NV Consumer Staples
ABN Amro Bank NV Financials & Real Estate Koninklijke DSM NV Materials
Acciona SA Utilities Koninklijke Philips NV Health Care
Accor SA Consumer Discretionary Koninklijke Vopak NV Energy
ACS Group Industrials LE Lundbergforetagen Financials & Real Estate
Adecco Group AG Industrials Air Liquide Materials
Adidas AG Consumer Discretionary L’Oreal SA Consumer Staples
Admiral Group PLC Financials & Real Estate Land Securities Group PLC Financials & Real Estate
Adyen NV Communication Services & IT Lanxess AG Materials
Aegon NV Financials & Real Estate LEG Immobilien SE Financials & Real Estate
Aena SME SA Industrials Legal & General Group PLC Financials & Real Estate
Aeroports de Paris SA Industrials Legrand SA Industrials
Airbus SE Industrials Leonardo SpA Industrials
Aker BP ASA Energy Linde PLC Materials
Akzo Nobel NV Materials Lloyds Banking Group PLC Financials & Real Estate
Alcon AG Health Care Logitech International Communication Services & IT
Allianz SE Financials & Real Estate LSEG PLC Financials & Real Estate
Alstom SA Industrials Lonza Group AG Health Care
Amadeus IT Group SA Communication Services & IT LVMH Moet Hennessy Louis Vuitton SE Consumer Discretionary
Amplifon SpA Health Care M&G PLC Financials & Real Estate
ams OSRAM AG Communication Services & IT Marks and Spencer Group PLC Consumer Staples
Amundi SA Financials & Real Estate Mediobanca Banca diCredito Finanziario SpA Financials & Real Estate
Andritz AG Industrials Meggitt PLC Industrials
Anglo American PLC Materials Melrose Industries PLC Industrials
Anheuser Busch Inbev SA Consumer Staples Merck KGaA Health Care
AP Moeller - Maersk A/S Industrials Metso Outotec Corp Industrials
ArcelorMittal SA Materials Moncler SpA Consumer Discretionary
Arkema SA Materials Mondi PLC Materials
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
ASM International NV Communication Services & IT Mowi ASA Consumer Staples
ASML Holding NV Communication Services & IT MTU Aero Engines AG Industrials
ASR Nederland NV Financials & Real Estate MunichRe Financials & Real Estate
Assa Abloy AB Industrials National Grid PLC Utilities
Assicurazioni Generali SpA Financials & Real Estate Natixis SA Financials & Real Estate
Associated British Foods PLC Consumer Staples Naturgy Energy Group SA Utilities
Assura PLC Financials & Real Estate Natwest Group PLC Financials & Real Estate
AstraZeneca PLC Health Care Nemetschek SE Communication Services & IT
Atlas Copco AB Industrials Neste Oyj Energy
Atos SE CommunicationServices & IT Nestle SA Consumer Staples
Avast PLC Communication Services & IT Next PLC Consumer Discretionary
AVEVA Group PLC Communication Services & IT NN Group NV Financials & Real Estate
Aviva PLC Financials & Real Estate Nokia Oyj Communication Services & IT
AXA SA Financials & Real Estate Nokian Tyres plc Consumer Discretionary
B&M European Value Retail SA Consumer Discretionary Nordea Bank Abp Financials & Real Estate
BAE Systems PLC Industrials Norsk Hydro ASA Materials
Banco Bilbao Vizcaya Argentaria SA Financials & Real Estate Novartis AG Health Care
Banco de Sabadell SA Financials & Real Estate Novozymes A/S Materials
Banco Santander SA Financials & Real Estate Ocado Group PLC Consumer Staples
Bank of Ireland Group PLC Financials & Real Estate OMV AG Energy
Bankinter SA Financials & Real Estate Orange SA Communication Services & IT
Barclays PLC Financials & Real Estate Orion Oyj Health Care
Barratt Developments PLC Consumer Discretionary Orkla ASA Consumer Staples
Barry Callebaut AG Consumer Staples Orsted A/S Utilities
Basf Se Materials Partners Group Holding AG Financials & Real Estate
BAWAG Group AG Financials & Real Estate Pearson PLC Communication Services & IT
Bayer AG Health Care Pernod Ricard SA Consumer Staples
Bayerische Motoren Werke AG Consumer Discretionary Persimmon PLC Consumer Discretionary
Bechtle AG Communication Services & IT Phoenix Group Holdings PLC Financials & Real Estate
Beiersdorf AG Consumer Staples Polski Koncern Naftowy Orlen SA Energy
Bellway PLC Consumer Discretionary Poste Italiane SpA Financials & Real Estate
Berkeley Group Holdings PLC Consumer Discretionary Prosiebensat 1 Media SE Communication Services & ITendtabular
BHP Group Ltd Materials Prudential PLC Financials & Real Estate
Biomerieux SA Health Care Prysmian SpA Industrials
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
BNP Paribas SA Financials & Real Estate Publicis Groupe SA Communication Services & IT
Boliden AB Materials Puma SE Consumer Discretionary
Bollore SE Communication Services & IT Qiagen NV Health Care
Bouygues SA Industrials Raiffeisen Bank International AG Financials & Real Estate
BP PLC Energy Randstad NV Industrials
Brenntag SE Industrials Rational AG Industrials
British American Tobacco PLC Consumer Staples Reckitt Benckiser Group PLC Consumer Staples
Britvic PLC Consumer Staples Red Electrica Corporacion SA Utilities
BT Group PLC Communication Services & IT Relx PLC Industrials
Bunzl plc Industrials Remy Cointreau SA Consumer Staples
Burberry Group PLC Consumer Discretionary Renault SA Consumer Discretionary
Bureau Veritas SA Industrials Rentokil Initial PLC Industrials
Caixabank SA Financials & Real Estate Repsol SA Energy
Capgemini SE Communication Services & IT Rexel SA Industrials
Carl Zeiss Meditec AG Health Care Rheinmetall AG Industrials
Carlsberg A/S Consumer Staples Rightmove PLC Communication Services & IT
Carnival PLC Consumer Discretionary Rio Tinto PLC Materials
Carrefour SA Consumer Staples Roche Holding AG Health Care
CD Projekt SA Communication Services & IT Rockwool International A/S Industrials
Cellnex Telecom SA Communication Services & IT Rolls-Royce Holdings PLC Industrials
Centrica PLC Utilities Rotork PLC Industrials
Chocoladefabriken Lindt & Spruengli AG Consumer Staples Royal Mail PLC Industrials
Chr Hansen Holding A/S Materials RSA Insurance Group Ltd Financials & Real Estate
Clariant AG Materials Rwe AG Utilities
Close Brothers Group PLC Financials & Real Estate Ryanair Holdings PLC Industrials
CNH Industrial NV Industrials Safran SA Industrials
CNP Assurances SA Financials & Real Estate Sage Group PLC Communication Services & IT
Coca-Cola Co Consumer Staples Sandvik AB Industrials
Coloplast A/S Health Care Sanofi SA Health Care
Commerzbank AG Financials & Real Estate SAP SE Communication Services & IT
Compagnie de Saint Gobain SA Industrials SBM Offshore NV Energy
Compagnie Financiere Richemont SA Consumer Discretionary Schibsted ASA Communication Services & IT
Michelin Consumer Discretionary Schindler Holding AG Industrials
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
Compass Group PLC Consumer Discretionary Schneider Electric SE Industrials
Continental AG Consumer Discretionary Schroders PLC Financials & Real Estate
ConvaTec Group PLC Health Care Scor SE Financials & Real Estate
Corbion NV Materials Securitas AB Industrials
Countryside Partnerships PLC Consumer Discretionary SEGRO PLC Financials & Real Estate
Covestro AG Materials SES SA Communication Services & IT
Credit Agricole SA Financials & Real Estate Severn Trent PLC Utilities
Credit Suisse Group AG Financials & Real Estate SGS SA Industrials
CRH PLC Materials Shell PLC Energy
Croda International PLC Materials Siemens AG Industrials
Danone SA Consumer Staples Siemens Energy AG Industrials
Danske Bank A/S Financials & Real Estate Siemens Gamesa Renewable Energy SA Industrials
Dassault Systemes SE Communication Services & IT Siemens Healthineers AG Health Care
Davide Campari Milano NV Consumer Staples SIG Combibloc Group AG Materials
DCC PLC Industrials Signature Aviation Ltd Industrials
Dechra Pharmaceuticals PLC Health Care Signify NV Industrials
Demant A/S Health Care Sika AG Materials
Deutsche Boerse AG Financials & Real Estate Skandinaviska Enskilda Banken AB Financials & Real Estate
Deutsche Lufthansa AG Industrials Skanska AB Industrials
Deutsche Post AG Industrials Smith & Nephew PLC Health Care
Deutsche Telekom AG Communication Services & IT Smiths Group PLC Industrials
Deutsche Wohnen SE Financials & Real Estate Smurfit Kappa Group PLC Materials
Diageo PLC Consumer Staples Snam SpA Utilities
DiaSorin SpA Health Care Societe Generale SA Financials & Real Estate
Direct Line Insurance Group PLC Financials & Real Estate Sodexo SA Consumer Discretionary
Dometic Group AB Consumer Discretionary Solvay SA Materials
DS Smith PLC Materials Sonova Holding AG Health Care
DSV A/S Industrials Spie SA Industrials
Dufry AG Consumer Discretionary Spirax-Sarco Engineering PLC Industrials
E.ON SE Utilities SSE PLC Utilities
Edenred SE Communication Services & IT St James’s Place PLC Financials & Real Estate
EDP Energias de Portugal SA Utilities Stadler Rail AG Industrials
EDP Renovaveis SA Utilities Standard Chartered PLC Financials & Real Estate
Eiffage SA Industrials Stellantis NV Consumer Discretionary
Electricite de France SA Utilities STMicroelectronics NV Communication Services & IT
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
Electrolux AB Consumer Discretionary Stora Enso Oyj Materials
Elekta AB Health Care Storebrand ASA Financials & Real Estate
Enagas SA Utilities Straumann Holding AG Health Care
Endesa SA Utilities Suez SA Utilities
Enel SpA Utilities Svenska Handelsbanken Financials & Real Estate
Engie SA Utilities Swatch Group AG Consumer Discretionary
Eni SpA Energy Swiss Life Holding AG Financials & Real Estate
Entain PLC Consumer Discretionary Swiss Re AG Financials & Real Estate
Epiroc AB Industrials Swisscom AG Communication Services & IT
Equinor ASA Energy Symrise AG Materials
Erste Group Bank AG Financials & Real Estate Tate & Lyle PLC Consumer Staples
EssilorLuxottica SA Consumer Discretionary Taylor Wimpey PLC Consumer Discretionary
Essity AB Consumer Staples TeamViewer AG Communication Services & IT
Etablissementen Franz Colruyt NV Consumer Staples Tecan Group AG Health Care
Eurazeo SE Financials & Real Estate TechnipFMC PLC Energy
Eurofins Scientific SE Health Care Tele2 AB Communication Services & IT
Euronext NV Financials & Real Estate Telecom Italia SpA Communication Services & IT
Evolution AB Consumer Discretionary Telefonaktiebolaget LM Ericsson Communication Services & IT
Evonik Industries AG Materials Telefonica SA Communication Services & IT
EVRAZ plc Materials Telenor ASA Communication Services & IT
Exor NV Financials & Real Estate Teleperformance SE Industrials
Experian PLC Industrials Telia Company AB Communication Services & IT
Faurecia SE Consumer Discretionary Temenos AG Communication Services & IT
Ferguson PLC Industrials Tenaris SA Energy
Ferrari NV Consumer Discretionary Terna Rete Elettrica Nazionale SpA Utilities
Ferrovial SA Industrials Tesco PLC Consumer Staples
Flutter Entertainment PLC Consumer Discretionary Thales SA Industrials
Fortum Oyj Utilities THG PLC Consumer Discretionary
Fresenius Medical Care AG & Co KGaA Health Care thyssenkrupp AG Materials
Fresenius SE & Co KGaA Health Care Tomra Systems ASA Industrials
Fuchs Petrolub SE Materials TotalEnergies SE Energy
G4S Ltd Financials & Real Estate Trainline PLC Consumer Discretionary
Galp Energia SGPS SA Energy Travis Perkins PLC Industrials
Games Workshop Group PLC Consumer Discretionary Trelleborg AB Industrials
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
GEA Group AG Industrials Tryg A/S Financials & Real Estate
Gecina SA Financials & Real Estate TUI AG Consumer Discretionary
Genmab A/S Health Care Ubisoft Entertainment SA Communication Services & IT
Genus PLC Health Care UBS Group AG Financials & Real Estate
Georg Fischer AG Industrials Ucb SA Health Care
Gerresheimer AG Health Care Umicore SA Materials
Getinge AB Health Care UniCredit SpA Financials & Real Estate
Givaudan SA Materials Unilever PLC Consumer Staples
Glanbia PLC Consumer Staples Uniper SE Utilities
GlaxoSmithKline PLC Health Care United Internet AG Communication Services & IT
Glencore PLC Materials United Utilities Group PLC Utilities
Grainger PLC Financials & Real Estate UPM-Kymmene Oyj Materials
Grifols SA Health Care Valmet Oyj Industrials
H & M Hennes & Mauritz AB Consumer Discretionary Veolia Environnement Utilities
Halma PLC Communication Services & IT Verbund AG Utilities
Hannover Rueck SE Financials & Real Estate Victrex PLC Materials
Hargreaves Lansdown PLC Financials & Real Estate Vifor Pharma AG Health Care
Hays PLC Industrials Vinci SA Industrials
HeidelbergCement AG Materials Virgin Money UK PLC Financials & Real Estate
Heineken Holding NV Consumer Staples Viscofan SA Consumer Staples
Hellofresh SE Consumer Staples Vivendi SE Communication Services & IT
Henkel AG & Co KGaA Consumer Staples Vodafone Group PLC Communication Services & IT
Hermes International SCA Consumer Discretionary voestalpine AG Materials
Hexagon AB Communication Services & IT Volkswagen AG Consumer Discretionary
Hikma Pharma PLC Health Care Volvo AB Industrials
Hiscox Ltd Financials & Real Estate Vonovia SE Financials & Real Estate
HomeServe PLC Industrials Wartsila Oyj Abp Industrials
Howden Joinery Group PLC Industrials Wendel SE Financials & Real Estate
HSBC Holdings PLC Financials & Real Estate WH Smith PLC Consumer Discretionary
Huhtamaki Oyj Materials Whitbread PLC Consumer Discretionary
Husqvarna AB Industrials Wienerberger AG Materials
Iberdrola SA Utilities Wizz Air Holdings PLC Industrials
ICA Gruppen AB Consumer Staples WM Morrison Supermarkets Ltd Consumer Staples
IG Group Holdings PLC Financials & Real Estate Wolters Kluwer NV Industrials
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Table 6 continued
Company Name Sector Company Name Sector
Iliad SA Communication Services & IT WPP PLC Communication Services & IT
IMCD NV Industrials Yara International ASA Materials
IMI PLC Industrials Zalando SE Consumer Discretionary
Imperial Brands PLC Consumer Staples Zurich Insurance Group AG Financials & Real Estate
Inchcape PLC Consumer Discretionary Novo Nordisk A/S Health Care
Industria de Diseno Textil SA Consumer Discretionary Alten SA Communication Services & IT
Infineon Technologies AG Communication Services & IT Pandora A/S Consumer Discretionary
Informa PLC Communication Services & IT Sartorius AG Health Care
ING Groep NV Financials & Real Estate Sartorius Stedim Biotech SA Health Care
Inmobiliaria Colonial SOCIMI SA Financials & Real Estate Swedbank AB Financials & Real Estate
InterContinental Hotels Group PLC Consumer Discretionary Swedish Match AB Consumer Staples
International Consolidated Airlines Group SA Industrials Unibail-Rodamco-Westfield SE Financials & Real Estate
Interpump Group SpA Industrials Valeo SE Consumer Discretionary
Intertek Group PLC Industrials VAT Group AG Industrials
Intesa Sanpaolo SpA Financials & Real Estate Vestas Wind Systems A/S Industrials
Investor AB Financials & Real Estate Alfa Laval AB Industrials
Ipsen SA Health Care Belimo Holding AG Industrials
Iss A/S Industrials British Land Company PLC Financials & Real Estate
ITV PLC Communication Services & IT Deutsche Bank AG Financials & Real Estate
J Sainsbury PLC Consumer Staples EQT AB Financials & Real Estate
JD Sports Fashion PLC Consumer Discretionary Geberit AG Industrials
JDE Peets NV Consumer Staples Getlink SE Industrials
Jeronimo Martins SGPS SA Consumer Staples Julius Baer Gruppe AG Financials & Real Estate
Johnson Matthey PLC Materials Koninklijke KPN NV Communication Services & IT
Just Eat Takeaway.com NV Consumer Discretionary Kuehne und Nagel International AG Industrials
Kaz Minerals Ltd Materials Lundin Energy AB Energy
KBC Groep NV Financials & Real Estate Lafarge SA Materials
Kering SA Consumer Discretionary Abrdn PLC Financials & Real Estate
Kerry Group PLC Consumer Staples
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
Author Contributions B.C. contributed to methodology, writing—
original draft preparation, and writing—reviewing and editing; K. Y.
contributed to conceptualization, data curation, software, and writing—
reviewing and editing; Cerchiello, P. contributed to methodology,
supervision, and writing—reviewing and editing.
Funding Open access funding provided by Università degli Studi di
Pavia within the CRUI-CARE Agreement.
Data availability Data are provided within the manuscript or supple-
mentary information files.
Declarations
Conflict of interest The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing, adap-
tation, 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 indi-
cate 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 copy-
right holder. To view a copy of this licence, visit http://creativecomm
ons.org/licenses/by/4.0/.
References
1. Aggarwal, P., Kadyan, A.: Greenwashing: the darker side of CSR.
Indian J. Appl. Res. 4(3), 61–66 (2014)
2. Agosto, A., Cerchiello, P., Giudici, P.: Bayesian learning models to
measure the relative impact of ESG factors on credit ratings . Int.
J. Data Sci. Anal. 1–12 (2023)
3. Agosto, A., Giudici, P., Tanda, A.: How to combine ESG scores?
A proposal based on credit rating prediction. Corporate Social
Responsibility and Environmental Management (2023)
4. Aguilera, R.V., Desender, K., Bednar, M.K., Lee, J.H.: Connecting
the dots: bringing external corporate governance into the corporate
governance puzzle. Acad. Manag. Ann. 91, 483–573 (2015)
5. Aguilera, R.V., Filatotchev, I., Gospel, H., Jackson, G.: An orga-
nizational approach to comparative corporate governance: costs,
contingencies, and complementarities. Organ. Sci. 19(3), 475–492
(2008)
6. Alareeni, B.A., Hamdan, A.: ESG impact on performance of US
S&P 500-listed firms. Corp. Gov.Int. J. Bus. Soc. 20(7), 1409–1428
(2020)
7. Aoki, M.: Toward a Comparative Institutional Analysis . MIT Press
(2001)
8. Arditti, F.D.: Risk and the required return on equity. J. Financ.
22(1), 19–36 (1967)
9. Ayuso, S., Rodríguez, M.A., García-Castro, R., Ariño, M.A.:
Maximizing stakeholders? interests: an empirical analysis of the
stakeholder approach to corporate governance. Bus. Soc. 53(3),
414–439 (2014)
10. Azmat, F., Rentschler, R.: Gender and ethnic diversity on boards
and corporate responsibility: the case of the arts sector. J. Bus.
Ethics 14(12), 317–336 (2017)
11. Bank of Italy. Cos’? il greenwashing e come ci inganna.
https://economiapertutti.bancaditalia.it/notizie/che-cos-il-
greenwashing-e-come-ci-inganna/?dotcache=refresh (2023)
12. Berg, F., Koelbel, J.F., Rigobon, R.: Aggregate Confusion: The
Divergence of ESG Ratings. MIT Sloan School of Management
Cambridge, MA, USA (2019)
13. Bosone, C., Bogliardi, S.M., Giudici, P.S.: Are ESG female? Con-
ference Paper. International Centre for Economic Analysis (ICEA).
“After the Pandemic” Conference series (2022)
14. Bowen, F., Aragon-Correa, J.A.: Greenwashing in Corporate Envi-
ronmentalism Research and Practice: The Importance of What We
Say and Do (Vol. 27) (No. 2). Sage Publications Sage CA, Los
Angeles, CA (2014)
15. Carroll, A.B.: Corporate social responsibility. Organ. Dyn. 44(2),
87–96 (2015)
16. Cherry, M.A., Sneirson, J.F.: Beyond profit: rethinking corporate
social responsibility and greenwashing after the BP oil disaster, p.
85983. Tul. L, Rev (2010)
17. de Bogotá, C.d.C. et al.: The power of parity: how advancing
women’s equality can add $12 trillion to global growth (2015)
18. Delmas, M.A., Burbano, V.C.: The drivers of greenwashing. Calif.
Manag. Rev. 54(1), 64–87 (2011)
19. Du, X.: How the market values greenwashing? Evidence from
China. J. Bus. Ethics 12(83), 547–574 (2015)
20. Dumitrescu, A., El Hefnawy, M., Zakriya, M.: Golden geese or
black sheep: Are stakeholders the saviors or saboteurs of financial
distress? Financ. Res. Lett. 37, 101371 (2020)
21. Escrig-Olmedo, E., Fernández-Izquierdo, M.Á., Ferrero-Ferrero,
I., Rivera-Lirio, J.M., Muñoz-Torres, M.J.: Rating the raters: eval-
uating how ESG rating agencies integrate sustainability principles.
Sustainability 11(3), 9–15 (2019)
22. Figini, S., Giudici, P.: Statistical merging of rating models. J. Oper.
Res. Soc. 62(6), 1067–1074 (2011)
23. Furlow, N.E.: Greenwashing in the new millennium. J. Appl. Bus.
Econ. 10, 6–22 (2010)
24. Gatti, L., Seele, P., Rademacher, L.: Grey zone in-greenwash
out. A review of greenwashing research and implications for the
voluntary-mandatory transition of CSR. Int. J. Corp. Soc. Respon-
sib. 4, 11–15 (2019)
25. Gennari, F., Salvioni, D.M.: CSR committees on boards: the impact
of the external country level factors. J. Manag. Gov. 23(3), 759–785
(2019)
26. Giudici, P., Mezzetti, M., Muliere, P.: Mixtures of products of
Dirichlet processes for variable selection in survival analysis. J.
Stat. Plan. Inference 111(1–2), 101–115 (2003)
27. Gregory, R.P.: Why ROE, ROA, and Tobin’s q in regressions aren’t
good measures of corporate financial performance for ESG criteria.
Available at SSRN 3775789 (2021)
28. Grimmer, M., Bingham, T.: Company environmental performance
and consumer purchase intentions. J. Bus. Res. 66(10), 1945–1953
(2013)
29. Hambrick, D.C., Mason, P.A.: Upper echelons: the organization as
a reflection of its top managers. Acad. Manag. Rev. 92, 193–206
(1984)
30. Jang, G.Y., Kang, H.G., Lee, J.Y., Bae, K.: ESG scores and the
credit market. Sustainability 12(8), 34–56 (2020)
31. Jiang, X., Akbar, A.: Does increased representation of female
executives improve corporate environmental investment? Evidence
from China. Sustainability 10(12), 47–50 (2018)
32. Kim, E.H., Lyon, T.: Greenwash vs. brownwash: exaggeration and
undue modesty in corporate sustainability disclosure. Organ. Sci.
26(3), 705–723 (2015)
33. Kim, S., Li, Z.: Understanding the impact of ESG practices in
corporate finance. Sustainability 13(7), 37–46 (2021)
34. Konietzko, J., Das, A., Bocken, N.: Towards regenerative business
models: A necessary shift? Sustain. Prod. Consum. 38, 372–388
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

International Journal of Data Science and Analytics
(2023). https://doi.org/10.1016/j.spc.2023.04.014.(https://www.
sciencedirect.com/science/article/pii/S2352550923000866)
35. La Rosa, F., Liberatore, G., Mazzi, F., Terzani, S.: The impact of
corporate social performance on the cost of debt and access to debt
financing for listed European non-financial firms. Eur. Manag. J.
36(4), 519–529 (2018)
36. Lee, H.J.: How do companies’ net zero efforts affect consumer
product evaluation through reciprocity and trust? A study in Korea.
Sustain. Prod. Consum. 38, 149–158 (2023). https://doi.org/10.
1016/j.spc.2023.03.021.(https://www.sciencedirect.com/science/
article/pii/S2352550923000659)
37. Liang, H., Renneboog, L.: Corporate social responsibility and sus-
tainable finance: a review of the literature. European Corporate
Governance Institute–Finance Working Paper 701 (2020)
38. Luthar, H.K., DiBattista, R.A., Gautschi, T.: Perception ofwhat the
ethical climate is and what it should be: the role of gender, academic
status, and ethical education. J. Bus. Ethics 16(2), 205–217 (1997)
39. Mahoney, L.S., Thorne, L., Cecil, L., LaGore, W.: A research note
on standalone corporate social responsibility reports: Signaling or
greenwashing? Crit. Perspect. Account. 244(5), 350–359 (2013)
40. Nishitani, K., Kokubu, K.: Can firms enhance economic perfor-
mance by contributing to sustainable consumption and production?
Analyzing the patterns of influence of environmental performance
in Japanese manufacturing firms. Sustain. Prod. Consum. 21, 156–
169 (2020). https://doi.org/10.1016/j.spc.2019.12.002
41. Raheja, C.G.: Determinants of board size and composition: a theory
of corporate boards. J. Financ. Quant. Anal. 40(2), 283–306 (2005)
42. Santos, C., Coelho, A., Marques, A.: A systematic literature review
on greenwashing and its relationship to stakeholders: state of art
and future research agenda. Manag. Rev. Q. 1–25 (2023)
43. Sarkar, S., Searcy, C.: Zeitgeist or chameleon? A quantitative anal-
ysis of CSR definitions. J. Clean. Prod. 13(5), 1423–1435 (2016)
44. Sheehy, B.: Defining CSR: problems and solutions. J. Bus. Ethics
131(3), 625–648 (2015)
45. Shleifer, A., Vishny, R.W.: A survey of corporate governance. J.
Financ. 52(2), 737–783 (1997)
46. Sterbenk, Y., Champlin, S., Windels, K., Shelton, S.: Is Femvertis-
ing the new greenwashing? Examining corporate commitment to
gender equality . J. Bus. Ethics 1–15 (2021)
47. TEG. TEG final report on the EU taxonomy. EU Techincal Experts
Group on Sustainable Finance. https://ec.europa.eu Accessed =
2022-25-05 (2020)
48. Tirole, J.: The Theory of Corporate Finance. Princeton University
Press (2010)
49. Turkcu, D., Tura, N.: The dark side of sustainable pack-
aging: battling with sustainability tensions. Sustain. Prod.
Consum. 40, 412–421 (2023). https://doi.org/10.1016/j.spc.
2023.07.007.(https://www.sciencedirect.com/science/article/pii/
S235255092300163X)
50. United Nations. THE 17 GOALS. https://sdgs.un.org/goals#
Accessed = 2022-23-05 (2022)
51. Velte, P., Stawinoga, M.: Do chief sustainability officers and CSR
committees influence CSR-related outcomes? A structured liter-
ature review based on empirical-quantitative research findings. J.
Manag. Control 31(4), 333–377 (2020)
52. Vos, J.: Actions speak louder than words: Greenwashing in corpo-
rate America . Notre Dame JL Ethics & Pub. Pol’y23673 (2009)
53. Walker, K., Wan, F.: The harm of symbolic actions and green-
washing: corporate actions and communications on environmental
performance and their financial implications. J. Bus. Ethics 109(2),
227–242 (2012)
Publisher’s Note Springer Nature remains neutral with regard to juris-
dictional claims in published maps and institutional affiliations.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com