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An empirical exploration of the role of strategic and responsive corporate social responsibility in the adoption of different Green IT strategies

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There are few studies of the impact of firms’ voluntary measures in terms of the determinants of environmental change. This paper aims to address this gap by examining the role played by corporate social responsibility in the adoption of Green IT. We consider two different corporate social responsibility policies and different typologies of Green IT. We believe that CSR plays a role in the adoption of Green IT and different CSR strategies induce the implementation of different types of Green IT in the firms. We utilise a survey carried out in Luxembourg on firms’ CSR practices together with a community survey on information and communication technology usage by enterprises. Our estimations show that corporate social responsibility is a driver of Green IT adoption. We also show that strategic and responsive CSR induce the adoption of different types of Green IT based on the intensity of changes but all CSR strategies have the same effect on Green IT typology based on the moment when Green IT is adopted.
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An empirical exploration of the role of strategic and responsive
corporate social responsibility in the adoption of different Green IT
strategies
Amélie BOHASa, Nicolas POUSSINGb
a Université Lyon 3, Centre de recherche Magellan, 6 Cours Albert Thomas, BP8242, 69355 LYON CEDEX 08,
France, email: amelie.bohas@univ-lyon3.fr
b LISER, CREM, 11, Porte des Sciences, Campus Esch/Belval, 4366 ESCH-SUR-ALZETTE, Luxembourg
email: nicolas.poussing@liser.lu, (corresponding author)
Abstract:
There are few studies of the impact of firms’ voluntary measures in terms of the
determinants of environmental change. This paper aims to address this gap by examining the
role played by corporate social responsibility in the adoption of Green IT. We consider two
different corporate social responsibility policies and different typologies of Green IT. We
believe that CSR plays a role in the adoption of Green IT and different CSR strategies induce
the implementation of different types of Green IT in the firms. We utilise a survey carried out in
Luxembourg on firms’ CSR practices together with a community survey on information and
communication technology usage by enterprises. Our estimations show that corporate social
responsibility is a driver of Green IT adoption. We also show that strategic and responsive CSR
induce the adoption of different types of Green IT based on the intensity of changes but all CSR
strategies have the same effect on Green IT typology based on the moment when Green IT is
adopted.
Keywords:
Green IT, Adoption, Strategic Corporate Social Responsibility, Responsive Corporate Social
Responsibility, Survey, Empirical Analysis
1. Introduction
With the global warming context, environmental concerns present a crucial topic for
researchers. To meet the challenges raised by this issue, three main instruments have been
developed to change the behaviour of economic agents: taxes, regulations and investment aids
for sustainable projects (Acemoglu et al., 2009; Aghion et al., 2009; Bosetti et al., 2009;
Veugelers, 2012). To these external policy tools can be added internal firm-specific factors
which are voluntary processes implemented by organisations (Demirel and Kesidou, 2011).
Indeed, due to the growing awareness of their environmental impacts, an increasing number of
organisations are intensifying their actions in favour of the environment (Melville, 2010; Porter
and Reinhardt, 2007). Firms introduce social and environmental concerns in their business
operations and in their interaction with their stakeholders on a voluntary basis (Commission of
the European Communities, 2001, 6). These practices tie in with the definition provided by the
European Commission of the concept of corporate social responsibility (CSR).
In this context, information and communication technologies (ICT) have a central role to
play due to their ability to have several impacts on firms such as on strategies, business
processes, organisational structures and skills. In particular, some IT strategies, called Green IT,
“reduce negative IT impacts on the environment (Jenkin et al., 2011, 2). Green IT has
emerged as one of the top issues of concern for IT and business managers(Molla et al., 2009,
3). Scholars underline the environmental gain of using ICT but, as noticed by Arnfalk et al
(2015), few policy measures and concrete initiatives have been implemented. The question of
the adoption of Green IT remains relevant.
When we look at the literature relative to eco-innovation, research have increasingly focused
on the determinants of eco-innovations but few studies (Ait-Daoud, 2012; Bansal and Roth,
2000; Campbell, 2007; Hasnaoui and Freeman, 2010; Molla et al., 2009; Pensel, 2010) have
taken into account the impact of firms’ voluntary programmes in favour of green technologies;
while the firms adopt “programs, codes, agreements and commitments that encourage
organizations to voluntarily reduce their environmental impact” (Darnall and Sides, 2008, 96).
For example, with the ISO 14001 environmental management systems and the Eco-
Management and Audit Scheme (EMAS), firms have the possibility to assess, report and
improve their environmental performance. In addition, as Demirel and Kedisou (2011) argue,
the impact and effectiveness of environmental CSR policies on eco-innovation remain
unresolved, begging for further research(Demirel and Kedisou, 2011, 1549). This paper aims
to fill this gap by examining the role of CSR in the adoption of Green IT.
By combining different conceptual typologies of strategic management from a CSR
perspective and from information systems (IS) about Green IT we consider the role of two types
of CSR policies in the adoption of different types of Green IT strategies. The two types of CSR
policies taken into account come from Porter and Kramer (2006). Porter and Kramer (2006)
consider that CSR creates a competitive advantage when firms integrate CSR into their strategic
visions. In consequence, they distinguish strategic CSR, which is part of the business strategy
and ties in with the highest level of commitment, to responsive CSR, which is a limited level of
commitment in the firms. The typologies of Green IT taken into account come from research
conduct by, on the one hand, Faucheux and Nicolaï (2011), and on the other hand, Berkhout and
Hertin (2001) and Jenkin et al., (2011). These typologies describe Green IT depending on their
integrations within the organisation. The key question of this article concerns the impacts of
strategic and responsive CSR on different Green IT strategies and we hypothesise that different
CSR strategies induce the implementation of different types of Green IT in the firms.
The paper is structured as follows. Section two presents the conceptual framework and our
hypothesis. Section three presents the data and methodology used for the empirical analysis, the
results of which are discussed in Section four. Finally, we derive some conclusions and policy
recommendations from our empirical findings.
2. Conceptual Framework and hypothesis
2.1 Green IT vs Green IS
Information Communication Technologies have a negative impact on the environment if we
consider their life cycle; indeed, they consume resources in their production and in the energy
they use and they generate waste at the end of their life (Berkhout and Hertin, 2001; Hilty,
2008; Kuehr et al., 2003; Murugesan, 2008). However, although ICTs contribute to worsening
environmental problems, they can also solve or at least minimise them (Fuchs, 2008; Mingay,
2006). As a consequence, there are two sides to Green IT ICTs as one of the causes of
environmental problems and ICTs as part of the solution to solving environmental problems
(Molla et al., 2009, 4). For instance, according to Molla et al. (2009, 5), Green IT is an
organization’s ability to systematically apply environmental sustainability criteria (such as
pollution prevention, product stewardship, use of clean technologies) to the design, production,
sourcing, use and disposal of the IT technical infrastructure as well as within the human and
managerial components of the IT infrastructure.
Furthermore, a clear distinction can be made between IT and IS components of Green IT
[…] based on their focus and impact on the environment (Jenkin et al., 2011, 2). We thus
identify two main approaches: ‘Green IT’ and ‘Green IS’ (Boudreau et al., 2008; Faucheux and
Nicolaï, 2011; Jenkin et al., 2011). In the first case, Green IT’, which ties in with a Green for
IT strategy, seeks to have a direct effect by reducing negative IT impacts on the environment
(Jenkin et al., 2011, 2). In the second case, Green IS’, which corresponds to an IT for Green
strategy, tends to have an indirect effect by using IS to support other business initiatives in
reducing their negative environmental impacts(Jenkin et al., 2011, 2).
This paper retains the general term Green IT to include the two perspectives above in
order to avoid the possibility of definitional confusion and to maintain congruency with
practitioners’ use of the term(Daly and Butler, 2009, 2).
2.2. Green IT typologies
In practice, the description of Green IT varies depending on their integration within the
organisation; it may be instantiated as technologies or systems, practices, policies or even
governance (Molla et al., 2009). Given this diversity of strategies, some typologies of Green IT
strategies have been established. Two major typologies emerge: 1) the typology suggested by
Berkhout and Hertin (2001) and Jenkin et al. (2011) focuses on the changes made within the
firms when companies adopt Green IT; 2) for their part, Faucheux and Nicolaï (2011) give a
central role to the moment when the firm implement the Green IT.
Green IT typology based on the intensity of changes
Berkhout and Hertin (2001) and Jenkin et al. (2011) focus on the degree of novelty
associated to the green IT practices. In other words, they differentiate strategies according to the
changes resulting from the implementation of Green IT. They identify various types of
strategies on a continuum from lower to higher strategic and environmental impacts, resulting
in a strategy hierarchy(Jenkin et al., 2011, 7).
The typology suggested by Berkhout and Hertin (2001) distinguishes strategies that have a
direct impact from those that have an indirect impact and identifies three types of strategies
depending on the nature of their impacts: first-order impacts, second-order impacts and third-
order impacts. The first-order environmental effects of ICT concern direct environmental
effects of the production and use of ICT, second-order effects represent efficiency gains
through ICT use, and third-order effects correspond to structural change, the rebound effect
and life style changes (Berkhout and Hertin, 2001, 12).
For their part, Jenkin et al. (2011), combining insights from strategic management (Dyllick
and Hockerts, 2002; Hart, 1995) and from IS (Chen et al., 2008), identify four types of
strategies on a continuum from lower to higher strategies. The first type of strategy (Type 0) is
characterised by discourses on the environmental concerns of the firm but no implementation in
terms of practices or policies (only intentions). This absence of action in terms of environmental
concerns can be seen as greenwashing’ intentions or it may result from a lack of organisational
capacity. Type 1 strategies consist of resorting to Green IT in line with motivations that include
an economic expectation of enhancing efficiency, a regulatory response of ensuring
compliance and a normative objective of attaining legitimacy(Molla et al., 2009, 1920). The
IT and IS strategies that are then implemented aim, essentially, at making efficient use of
natural and firm resourcesas well as preventing and controlling pollution (Jenkin et al., 2011,
8). In the third type of strategy (Type 2), the firm uses ICT to help reduce the environmental
impact of an organisation’s product(s)’ taking into account considerations of product
stewardship and eco-equity (Jenkin et al., 2011, 7). Finally, Type 3 strategies, which go beyond
the considerations of the previous ones whilst subsuming the other strategies, embed the eco-
effectiveness goal into all of the firms activities and interactions and seek to combine
environmental protection with economic growth.
From the typology of Berkhout and Hertin (2001) and Jenkin et al. (2011), three main types
of Green IT strategies emerge based on the changes due to the implementation of Green IT:
(1) those dedicated to reducing the direct environmental effects of ICT (first-order
effects in Berkhout and Hertin’s typology and Type 1 strategies in Jenkin et al.’s
typology);
(2) those dedicated to substitutingthe inputs with more environmentally friendly
alternatives (second-order effects in Berkhout and Hertin’s typology and Type 2
strategies in Jenkin et al.’s typology);
(3) those designed to transformthe way in which firms conduct business and, more
widely, lifestyles (third-order effects in Berkhout and Hertin’s typology and Type 3
strategies in Jenkin et al.’s typology).
Green IT typology based on the moment when the Green IT is adopted
According to Faucheux and Nicolaï (2011), the characteristics of eco-innovations could be
applied to Green IT strategies. The eco-innovation theory commonly subdivides eco-
innovations into two types of environmental innovations. The first type of eco-innovation is
composed of ‘integrated’ or ‘cleaner’ eco-innovations. This type of eco-innovation intervenes in
a preventive manner and often consist of incremental innovations but can also represent radical
innovations (Demirel and Kesidou, 2011; Rennings et al., 2006). The second type of eco-
innovation, called ‘added’ or ‘end-of-pipe’ eco-innovations, aims to minimise an existing
environmental impact and, therefore, have an ‘add-on’ or ‘curative’ effect. In line with this
typology, Faucheux and Nicolaï (2011) proposed a typology of green IT with a time-based
criterion. They suggested two categories of Green IT:
(1) the green IT strategies adopted at the end of the production process which are
integrated innovations operated in a preventive’ manner through incremental or
radical changes and;
(2) the green IT strategies which intervened at the beginning of the production process
to avoid environmental degradation. These Green IT strategies correspond to eco-
innovations implemented in a curative manner mainly through incremental
changes.
The researchers which investigate the effect of environmental practices on firms’ performance
show the relevance of this distinction (preventive vs curative practices). Without taking into
account this distinction, the effect of pro-environmental practices on firms’ performance is not
clear cut. Numerous authors found that pro-environmental practices are profitable (Bosworth
and Clemens, 2011; Clemens (2006); Orlitzky et al., 2003); but others authors didn’t find any
effect (Telle, 2006; Wilcox et al., 2014). In line with the Porter Hypothesis, Aragon-Correa et
al. (2008) or Burgos-Jimenez et al. (2013) argue that only preventive measures in favour of the
environment create a competitive advantage. For Rivera-Torres et al. (2015), these preventive
measures are often complemented with the implementation of certain organisational strategies;
like stakeholder management (Plaza-Ubeda et al., 2000; Wagner, 2015).
2.3 Drivers of Green IT Strategies
Rennings (2000) points to three types of determinants of eco-innovation: technology push
(e.g. product quality, energy efficiency), ‘regulatory push’ (e.g. existing environmental law) and
market pull (e.g. customer demand, image). For Faucheux and Nicolaï (1998), the regulatory
framework is the primary driver of eco-innovation. Horbach et al. (2012) find another main
determinant of eco-innovation: firm-specific factors, such as knowledge transfer mechanisms
and involvement in networks. In addition, the drivers of eco-innovation are not the same for
every type of eco-innovation (Demirel and Kesidou, 2011; Triguero et al., 2013).
In the context of Green IT, given the nascent nature of this phenomenon and its
heterogeneity within organisations, a growing amount of theoretical and empirical research is
dedicated to identifying the determinants of Green IT adoption and diffusion. It emerges that the
major factors driving the adoption of Green IT are: ‘economical (‘pursuing internal efficiency
and market performance’), ‘regulatory (‘adherence to green or environmentally responsible
behaviours or initiatives’) and normative (‘pursuit of legitimacy within the wider social
context’) (Molla et al., 2009, 6). These motivating forces are either factors internal to the firm
(‘organisational forces’) or external variables (‘regulatory-market, socio-cultural, ecological and
technologicalforces) (Jenkin et al., 2011, 6).
Most of the studies of factors internal to the firm ignore the impact of the firm’s existing
environmental practices on the adoption of Green IT. Indeed, according to Poussing and Le Bas
(2013), few studies address firms’ voluntary programmes for environmental changes. In
addition, more broadly, the effect of CSR practices on eco-innovation remains undetermined
(Demirel and Kesidou, 2011). Despite Poussing and Le Bas (2013) finding a positive impact of
CSR on eco-innovation, Aggeri (1999) argues that environmental actions are more affected by
external policy tools than by voluntary agreements. For Wagner (2010), the effect of CSR is
linked to the size of the firms. This is the reason why, using an empirical approach, the research
of Cuerva et al. (2014) shows that CSR has no impact for small firms.
In respect of Green IT adoption, the literature review also reveals contradictory results. On
the one hand, the development of CSR (…) and environmental policies might not always be
associated with the development of policies intended to Green IT (Molla et al., 2009, 13),
whereas, on the other hand, Green IT may appear as part of the CSR policy (Daly and Butler,
2009). Furthermore, other studies show that IS could make a contribution to proactive
environmental strategies and to a firm’s environmental performance through the development of
an appropriate organisational capability (Bengtsson and Ãgerfalk, 2011; Benitez-Amado and
Walczuch, 2012). This IS-enabled environmental sustainability (Elliot, 2011; Melville, 2010)
confirms the existence of a link between IS and Sustainable Development. If we consider as
Matten and Moon (2004) that SD is the generic term of CSR, there is a link between IS and
CSR.
To assess the effect of CSR policy on eco-innovation adoption, most previous studies
measure CSR policy only through the decision to invest in such a programme, whereas this
concept can take many forms (Brammer et al., 2007). For instance, Demirel and Kesidou (2011,
1551) introduce CSR into their empirical model with a dummy variable: CSR=1 if the firm
invested in environmental protection. As a consequence, from our point of view, the effect of
CSR has not been clearly assessed due to the poor measure used to identify it.
A brief conceptualisation is required to identify the variety of CSR practices. Some
researchers propose distinguishing two types of CSR practices: environmental practices and
social practices (Baden et al., 2009; Fernando, 2010). Carroll (1979) takes into account four
dimensions of a firm’s responsibilities: economic, legal, ethical and discretionary. This
conceptualisation is widely accepted(Acar et al., 2001, 30). Economic responsibilities are
related to the obligation for businesses to make profits and produce services and goods. Legal
responsibilities refer to respect for the law. Ethical responsibilities expect organisations to adopt
moral rules. Discretionary responsibilities refer to voluntary and charitable activities. Maignan
and Ferrell (2000) have developed measures for each dimension of Carroll’s conception.
In recent years, CSR has been directly associated with firms’ performance (Porter and
Kramer, 2006; Vilanova et al., 2009). Porter and Kramer (2006) argue that CSR creates a
competitive advantage for firms if they integrate CSR into their business practices. When CSR
provides business gains, CSR is called strategic CSR (Lantos, 2001; Porter and Kramer, 2006;
Crawford and Scaletta, 2005; Salzmann et al., 2005). In consequence, two opposite views of
CSR emerge. Baron (2001) and Hillman and Keim (2001) make the distinction between
altruistic CSR and strategic CSR. Porter and Kramer (2006) oppose strategic CSR to
responsive CSR. Whilst strategic CSR is part of the business strategy and ties in with the
highest level of commitment, responsive CSR corresponds to the lowest level of commitment.
In other words, strategic CSR implies a more comprehensive implementation of CSR within a
firm, as opposed to limited implementation in the case of a responsive CSR strategy. Different
papers describe CSR activities which are strategic (Bhattacharyya et al., 2007, 2008; Burke and
Logsdon, 1996; McAlister and Ferrell, 2002). For Husted and Allen (2007), the approach
suggested by Burke and Logsdon (1996) is promising and appears to be useful in understanding
value creation via CSR projects. Burke and Logsdon (1996, 497) propose differentiating
strategic CSR from responsive CSR through five strategy dimensions: (1) centrality (the
closeness of fit to the firm’s mission and objectives); (2) proactivity (the ‘degree to which the
programme is planned in anticipation of emerging social trends and in the absence of crisis);
(3) voluntarism (‘the scope for discretionary decision-making and the lack of externally
imposed compliance requirements’); (4) visibility (‘observable, recognizable credit by internal
and/or external stakeholders for the firm’); (5) specificity (the ‘ability to capture private benefits
by the firm).
Bocquet et al. (2013) used the approach suggested by Burke and Logsdon (1996) and
showed that firms with strategic CSR profiles do not innovate in the same way than firms with
responsive CSR profiles. In line with this result, we expect that strategic CSR and responsive
CSR may have different impacts on Green IT adoption. Overall, the review of the literature
suggests that there exist heterogeneous Green IT strategies. As a consequence of this, our paper
aims to contribute to the existing literature on the drivers of eco-innovation by targeting
different types of Green IT that correspond to this diversity of strategies. Given that a
conceptual gap exists regarding the impact of voluntary measures on environmental change
(Bansal and Roth, 2000), we investigate the effectiveness of voluntary processes, such as CSR,
in stimulating eco-innovation (Antonioli and Mazzanti, 2009).
To resume, in line with the literature, our main hypothesis is related to the fact that
Corporate Social Responsibility has a positive effect on the adoption of Green IT. Moreover, we
think that different strategies of CSR (strategic CSR vs responsive CSR) have different effects
on the adoption of different Green IT strategies.
First, we adopt the strategic CSR framework (Bocquet et al., 2013; 2014; Burke and
Logsdon, 1996; McWilliams and Siegel, 2000; Porter and Kramer, 2006) which underlines a
strong relationship between strategic CSR and innovation. We particularly focus on the research
conducted by Bocquet et al. (2013) who showed that firms with strategic CSR profiles do not
innovate in the same way than firms with responsive CSR profiles. With respect to these
previous studies, we take into account the two CSR strategies (strategic vs responsive) and
different types of Green IT strategies and we formulate our first hypothesis:
H1: Strategic CSR and responsive CSR induce the adoption of different types of Green IT
Second, we have seen that it is important for a firm to adopt preventive measures in favour
of the environment (Bosworth and Clemens, 2011; Clemens (2006); Orlitzky et al., 2003) and
these preventive measures are often complemented with the implementation of certain
organisational strategies (Rivera-Torres et al. (2015); like stakeholder management (Plaza-
Ubeda et al., 2000; Wagner, 2015). From these research findings and in line with the Porter
Hypothesis, we therefore present our second hypothesis:
H2: The firms which implement Strategic CSR have a biggest probability to implement
proactive Green IT than the firms which implement Responsive CSR.
3. Data and Methodology
3.1 Description of the Data
In this research we use data drawn from two surveys carried out in 2008 and 2011 by the
Luxembourg Institute of Socio-Economic Research (LISER)1 in Luxembourg. The firms
covered by the sampling process are located in Luxembourg, have more than 10 employees and
are representative of almost all sectors of activity.
The first survey, conducted in 2008 by Luxembourg Institute of Socio-Economic Research
(LISER), revealed firms’ commitment to CSR. Among other information, firms indicated the
field(s) that their CSR policy covers: environmental, social and/or economic (which represent
the common ‘three pillars’ of CSR). They also provided information about the way in which
they implement their CSR policy: the existence in the firms of a CSR department, allocation of
a CSR budget, definition of measurable objectives, creation of a reporting system, training of
staff, etc.2
The second survey is the Community survey on Information and Communication
Technologies Usages by Enterprises. LISER conducted the survey in 2011 on behalf of
STATEC (the National Statistics Institute of Luxembourg), with financial support from the
European Commission (EUROSTAT, 2011). The aim was to describe how firms adopted and
used ICT in 2011. Regarding the issue of Green IT, the Community survey considers the
adoption of eight Green IT policies (see Table 1): policies aimed at reducing the volume of
paper used for printing or copying, policies dedicated to reducing the energy consumption of
ICT, IT applications dedicated to reducing the energy consumption of business processes,
policies implemented for using ICT instead of travelling, policies designed to acquire less
energy-consuming ICT, policies designed to make the firm’s employees aware of the
1 http://www.liser.lu
2 Appendix A gives an overview of the questionnaire items from the Corporate Social Responsibility Survey used in the
econometric model.
environmental impact of their use of ICT, policies aiming to carefully manage electronic waste
and, finally, IT applications adopted to ease employees remote access to the firm’s mail
system, documents and software. In addition to the types of Green IT policies adopted, the
survey questions explored the motivations for the adoption of Green IT.3
These two surveys followed exactly the same methodology for the sampling process and for
data collection: a stratified random sample of firms from the national database of companies
located in Luxembourg (available from STATEC) was selected and the administration of the
survey was conducted by mail. A total of 2,700 responses were received for the Community
survey in 2011 and 1,144 responses were collected in 2008 from the CSR survey. Using the
identification number of the companies, it is possible to merge the two data sets, providing 815
usable responses for our analysis (firms that participated in both surveys). With the aim of
making our results representative of the population studied, we use a weighting system based on
the sampling probability and the rate of response.
Among the 815 firms in the data set (see Table 1), 79% have fewer than 50 employees
(SMALL), 18% have between 50 and 249 employees (MEDIUM) and 3% have 250 employees
or more (LARGE); 87% of the companies are from the services sector and almost one firm in
four (23%) is part of a group (GROUP).
With regard to Green IT, the analysis shows that a large proportion of companies (84%)
have adopted at least one Green IT policy (GREEN). Among the Green IT policies considered
by the Community survey (as discussed above), the most widespread is the policy seeking to
reduce the energy consumed by ICT (56% of the companies in the data set). Conversely, using
ICT instead of travelling is the least adopted action (27%).
In respect of their motivation, in most cases, companies state that they adopted Green IT,
firstly, to reduce their operating costs (59% of companies) and, secondly, in order to improve
their image (42%).
The statistics in Table 1 report that 15% of firms in the data set are committed to CSR (85%
without any CSR policy NO_CSR).
3 Appendix B gives an overview of the questionnaire items from the survey on ‘Information and Communication Technologies
Usages by Enterprises’ Survey used in the econometric model.
Table 1. Description of the variables and descriptive statistics for the population and the sample
of companies committed to CSR (means, standard deviation in brackets)
Variables
Definition (binary, 1 = yes/0 = no)
Population
Responsible firms
CSR variables
CSR
= 1 if the firm implemented a CSR policy
0.14971
(0.74269)
1
(0)
Strategic_CSR
= 1 if the firm implemented a strategic CSR
policy
0.08138
(0.569153)
0.54358
(0.99249)
Responsive_CSR
= 1 if the firm implemented a responsive
CSR policy
0.06833
(0.52521)
0.45641
(0.99249)
NO_CSR
= 1 if the firm did not implement any CSR
policy
0.85028
(0.74269)
0
(0)
Green IT variables
GREEN
= 1 if the firm adopted at least one Green IT
policy
0.84197
(0.75927)
0.94568
(0.45160)
GREEN_A
= 1 if the firm implemented policies designed
to reduce the volume of paper used for
printing or copying
0.52557
(1.03942)
0.62059
(0.96687)
GREEN_B
= 1 if the firm implemented policies designed
to reduce the energy consumption of ICT
0.56571
(1.03175)
0.67597
(0.93254)
GREEN_C
= 1 if the firm implemented policies for using
telephone, web or video conferences instead
of travelling
0.26724
(0.92113)
0.33916
(0.94333)
GREEN_D
= 1 if the firm implemented policies designed
to acquire less energy-consuming ICT
0.44543
(1.03456)
0.58411
(0.98208)
GREEN_E
= 1 if the firm implemented policies designed
to make its employees aware of the
environmental impact of their use of ICT
0.35982
(0.99904)
0.53333
(0.99407)
GREEN_F
= 1 if the firm implemented policies designed
to manage electronic waste (e-waste)
0.54901
(1.03577)
0.74159
(0.87226)
GREEN_G
= 1 if the firm adopted IT applications
dedicated to reducing the energy
consumption of business processes
0.12881
(0.69732)
0.18490
(0.77356)
GREEN_H
= 1 if the firm adopted IT applications to ease
employees remote access to the firm’s mail
system, documents and software
0.46583
(1.03835)
0.73667
(0.8776068122)
Types of Green IT strategies
REDUCE
Green IT policies corresponding to the
‘reduction’ type of Green IT strategies
0.75190
(0.89904)
0.88187
(0.64311)
SUBSTITUTE
Green IT policies corresponding to the
‘substitution’ type of Green IT strategies
0.54904
(1.03576)
0.68759
(0.92350)
TRANSFORM
Green IT policies corresponding to the
‘transformation’ type of Green IT strategies
0.61586
(1.01245)
0.80273
(0.79290)
CURATIVE
Green IT policies corresponding to the
‘curative’ type of Green IT strategies
0.69953
(0.95431)
0.79506
(0.80431)
PREVENTIVE
Green IT policies corresponding to the
‘preventive’ type of Green IT strategies
0.68736
(0.96494)
0.83580
(0.73814)
Control variables
COST
= 1 if the firm adopted Green IT to reduce its
operating costs
0.59669
(1.02113)
0.73463
(0.87977)
IMAGE
= 1 if the firm adopted Green IT to improve
its corporate image
0.42119
(1.02777)
0.55152
(0.99098)
SMALL
= 1 if the firm is small (from 10 to 49
employees)
0.78976
(0.84819)
0.67584
(0.93264)
MEDIUM
= 1 if the firm is medium-sized (from 50 to
249 employees)
0.18498
(0.80823)
0.27577
(0.89049)
Variables
Definition (binary, 1 = yes/0 = no)
Population
Responsible firms
LARGE
= 1 if the firm is large (250 or more
employees)
0.02525
(0.32659)
0.04838
(0.42754)
INDUS
= 1 if the firm is from the industrial sector
0.12735
(0.69393)
0.11444
(0.63434)
GROUP
= 1 if the firm belongs to a group (parent
company or subsidiary)
0.23443
(0.88184)
0.32584
(0.93390)
IT2
Intensity of use of IT (number of ITs used)
2.53038
(2.969898)
3.18956
(2.43627)
3.2 Methodology
3.2.1 Dependent Variables
The Community survey, Information Communication Technologies Usages by Enterprises,
enables us to explore the determinants of eight different Green IT policies (see Table 1). Firstly,
we aggregate the different Green IT policies into three groups according to the typologies
proposed by Berkhout and Hertin (2001) and Jenkin et al. (2011), as mentioned at the beginning
of this paper:
policies aiming to reduce the volume of paper (GREEN_A), the energy consumption of
ICT (GREEN_B) and that of the business processes (GREEN_G), as well as managing
waste (GREEN_F), make up the strategy type REDUCE’;
policies aiming to substitute the use of telephone, web and video conferences for travel
(GREEN_C), as well as those dedicated to acquiring less energy-consuming ICT
(GREEN_D), are part of the strategy type SUBSTITUTE’;
policies concerning the awareness of employees of the environmental impact of their use
of ICT (GREEN_E) and those related to the use of IT applications to give employees
remote access to the application systems of the firm (GREEN_H), constitute the strategy
type, namely TRANSFORM’.
Moreover, we create a second typology in accordance with Faucheux and Nicolaï (2011).
This typology leads us to aggregate Green IT policies according to the nature of the underlying
eco-innovation. This results in two groups:
policies aiming to reduce the volume of paper (GREEN_A), the energy consumption of
ICT (GREEN_B) and that of the business processes (GREEN_G), as well as substituting
the use of telephone, web and video conference for travel (GREEN_C) and those related
to the use of IT applications to give employees remote access to the application systems
of the firm (GREEN_H), constitute the type of Green IT namely CURATIVE’;
policies aiming to acquire less energy-consuming equipment (GREEN_D), as well as
those dedicated to managing waste (GREEN_F) and those concerning the awareness of
employees of the environmental impact of their use of ICT (GREEN_E), constitute the
type of eco-innovation, namely PREVENTIVE’. These strategies are integrated
throughout the life cycle of the product (Faucheux and Nicolaï, 2011).
3.2.2 Independent Variables
Main Independent Variables
To identify strategic and responsive CSR (Porter and Kramer, 2006), which are our main
independent variables, we use the results of Bocquet et al. (2013). They performed a cluster
analysis to differentiate firms according to their CSR policy (strategic versus responsive). In
line with Husted and Allen (2007) who propose measures for each dimension of Burke and
Logsdon’s conceptual framework (1996), they used questions related to the implementation of
CSR practices according to the five strategic dimensions noted by Burke and Logsdon (1996).
To take into account centrality’, they examine whether a document exists that describes the
firm’s values and whether the firm communicates information about its CSR commitment on
the web or in a report. Two items measure ‘proactivity’: the existence of a CSR action plan and
the existence of an agenda. ‘Voluntarism’ is captured through the identification by the firm of
the firm's business stakeholders. ‘Visibility is assessed through the existence of a
communication plan. ‘Specificity’ is measured through three dimensions linked to value
creation for the firm: the capacity to attract clients, the capacity to improve the firm’s image and
the level of differentiation from the competition.
With the nine variables discussed above, Bocquet et al. (2013) conducted a principal
component analysis (PCA) to distinguish firms that implement strategic CSR from firms that
adopt responsive CSR. The PCA identifies the uncorrelated factors, referred to as the principal
components, which best summarise the information contained in the theoretical dimensions. A
non-hierarchical cluster analysis then determines the final number of clusters.
The cluster analysis results reveal that among the 134 firms that are committed to CSR, 55%
are committed to a strategic CSR policy, whereas 45% have a responsive one (see Table 2). The
proportion of firms which adopt Green IT is high (82%) among the firms without CSR policy
(see Table 2). But, the confidence intervals show that this proportion is significantly higher
among the firms committed to CSR (95%). A breakdown of the CSR commitment into strategic
CSR and responsive CSR suggests that the adoption of Green IT does not appear to be
significantly different. As indicated, the proportion of companies that have adopted at least one
Green IT policy is almost the same in these two sub-populations, with 96% and 94% (chi-
square = 1.0473, p = 0.3061) respectively.
Table 2. Contingency table linking CSR commitment with Green IT adoption (number,
percentage in brackets, confidence interval in square brackets)
Firms without a
CSR policy
Firms with a CSR policy
Total
Strategic CSR
Responsive CSR
Total
Firms without a
Green IT policy
529
(17.64)
[16.24 19.03]
10
(4.15)
[1.58 6.71]
18
(6.36)
[3.47 - 9.24]
28
(5.30)
[3.35 7.24]
557
(15.80)
[14.57 17.02]
Firms with a
Green IT policy
2470
(82.36)
[80.96 83.75]
231
(95.67)
[93.37 98.54]
269
(93.64)
[90.75 96.52]
500
(94.70)
[92.75 96.64]
2970
(84.20)
[82.97 85.42]
Total
2999
(100.00)
241
(100.00)
287
(100.00)
528
(100.00)
3527
(100.00)
Source: Community survey on ICT usage by enterprises and CSR survey (Luxembourg)
Other Independent Variables
The firm size, business sector, membership (whether the firm belongs to a group or not), IT
intensity and expected benefits, in particular cost savings and desire for social acceptance, are
proposed as control variables. The size of the firm can influence the adoption of Green IT in
respect of the organisation’s concerns (Molla et al., 2009) and its capabilities (Dick and Burns,
2011; Elliot, 2009). This variable is measured using three dummy variables that summarise the
total number of the firm’s employees: SMALL (from 10 to 49 employees), MEDIUM (from 50
to 249 employees) and LARGE (250 or more employees). The business sector and membership
have been used as control variables for the analysis of the adoption of eco-innovations (Bocquet
et al., 2013; Molla et al., 2009; Poussing and Le Bas, 2013). The dummy variable INDUS
enables us to identify companies from the industrial sector. If the company belongs to a group,
this is indicated via the variable GROUP. IT intensity is suggested as an enabler of the adoption
of Green IT (Molla et al., 2009). This variable (IT2) is modelled through the evaluation of the
number of ICTs used within the firm. Five technologies are taken into account: possessing a
website, communicating data between firms electronically, sending/receiving electronic
invoices, sharing information electronically and automatically between different functions
within the company, and conducting business online. Finally, cost savings are identified as an
important driver for cleaner production technologies (Frondel et al., 2007) and for Green IT
adoption (Molla et al., 2009) as well as corporate image improvement, also labelled as ‘Green
corporate image’ (Amores-Salvado et al., 2014).
The appendix C gives the correlation matrix of the variables.
3.2.3 Econometric Specification
Our objective is to ascertain whether CSR strategies stimulate different types of Green IT
strategies. In order to achieve this, we use multivariate models. Simple dichotomous models,
such as logit and probit, are particularly appropriate when the dependent variables of the models
are binary (they equal 1 if the firm adopted the Green IT strategy and 0 if not). In Greene
(2007), the general framework of the probability models is
Prob (event j occurs) = Prob (Y = j) = F [relevant effects, parameters]
Due to the normality assumption, the probit model is more popular than logit in
econometrics (Wooldridge, 2003). But given that the probit and logit models usually produce
similar results (Davidson and MacKinnon, 1984; Morimune, 1979), we choose to resort to the
latter. In the logit model, the decision on whether to implement a Green IT strategy is defined
by yi, where yi = 1 when the company adopted this strategy and yi = 0 when it did not. The
probability of adoption of Green IT strategies is conditional upon a series of exogenous
variables:
Prob(yi = 1|x) = F(x, β)
Prob(yi = 0|x) = 1 - F(x, β)
where F( ) indicates a cumulative distribution function, xi the explanatory variables and β the
vector of the parameters to be estimated.
For the logit model (Greene, 2007, p. 773), the logistic distribution is:
Prob (Y = 1 | x) = (ex’ β) / (1 - ex’ β) = Λ (x’β)
4. Results and Discussion
Table 3 identifies the determinants of the adoption of our different types of Green IT
strategies.
The models 1, 2 and 3 highlight the determinants of the adoption of the three types of Green
IT proposed by Berkhout and Hertin (2001) and Jenkin et al. (2011). We note that, in
comparison with responsive CSR, strategic CSR has a positive effect on the probability to adopt
REDUCE green IT (model 1), a negative effect on the probability to adopt TRANSFORM
green IT (model 3) and no impact on the probability to adopt SUBSTITUTE green IT (model
2). In other words, there does not seem to be any significant difference between Strategic and
responsive CSR on the probability to adopt SUBSTITUTE green IT. The latter is negatively
impacted when the firms don’t implement CSR.
The models 4 and 5 show the determinants of the two types of Green IT according to the
typology of Faucheux and Nicolaï (2011). The results show that both strategic and responsive
CSR strategies have no effect on the probability of adopting the ‘CURATIVE’ strategy type.
CSR doesn’t play a role in the adoption of CURATIVE green IT. Model 5 shows that don’t
adopt any CSR strategy have a negative effect on the probability to adopt PREVENTIVE green
IT. In other words, we can say that all CSR strategies have a positive effect on the probability to
adopt PREVENTIVE green IT.
To resume, in comparison with responsive CSR, strategic CSR has not the same effect on
REDUCE and TRANSFORM green IT. In consequence, we could validate our first hypothesis:
Strategic CSR and responsive CSR induce the adoption of different types of Green IT
But, because there is no significant difference between strategic and responsive CSR on the
probability to adopt PREVENTIVE and CURATIVE green IT we reject our second hypothesis:
The firms which implement Strategic CSR don’t have a biggest probability to implement
proactive Green IT than the firms which implement Responsive CSR.
As far as the control variables are concerned (COST, IMAGE, SMALL, INDUS, GROUP,
IT2), the results are the same for every types of Green IT. Our results indicate that the
probability of adopting Green IT is positively affected by cost savings (COST) and corporate
image (IMAGE). This is consistent with the literature review (Frondel et al., 2007; Molla et al.,
2009).
In keeping with the findings of Dick and Burns (2011) and Elliot (2009), we found that
being a small firm (SMALL) has a negative effect on the adoption of Green IT as compared
with a medium-size company (MEDIUM). Conversely, belonging to a group (GROUP) and
making intensive use of ICT (IT2) have a positive effect on the adoption of Green IT. As far as
the industrial sector is concerned, our results indicate that this factor has no impact on the
adoption of Green IT. These results are in line with those of Molla et al. (2009, 20) who indicate
that there is no significant difference across industries either for green policies or for Green IT
infrastructure technologies: the drivers appear to be more or less the same across the different
industries.
As compared with a medium-size company (MEDIUM), being a large firm (LARGE) has a
positive effect on the adoption of SUBSITUTE, TRANSFORM and curative Green IT.
Table 3. Determinants of the adoption of different types of Green IT strategies (logit)
Intensity change based criteria
Time-based criteria
REDUCE
SUBSTITUTE
TRANSFORM
CURATIVE
PREVENTIVE
Model 1
Model 2
Model 3
Model 4
Model 5
Strategic_CSR
0.8142***
(0.2957)
-0.3437
(0.2172)
-0.6815**
(0.2669)
0.1527
(0.2530)
0.1431
(0.2623)
Responsive_CSR
REF.
REF.
REF.
REF.
REF.
NO_CSR
-0.1032
(0.2238)
-0.4745***
(0.1769)
-1.0862***
(0.2669)
0.0037
(0.2057)
-0.4414**
(0.2103)
COST
1.2098***
(0.1014)
0.9389***
(0.0876)
1.1088***
(0.0938)
1.6641***
(0.0993)
1.0867***
(0.0933)
IMAGE
0.9699***
(0.1184)
0.7622***
(0.0887)
0.1763*
(0.0960)
0.4535***
(0.1078)
0.6890***
(0.1018)
SMALL
-0.3707***
(0.1274)
-0.3861***
(0.1037)
-0.3426***
(0.1118)
-0.2096*
(0.1169)
-0.3749***
(0.1159)
MEDIUM
REF.
REF.
REF.
REF.
REF.
LARGE
0.6452
(0.5367)
0.7530**
(0.3533)
0.7222*
(0.4102)
1.0119**
(0.4975)
0.0323
(0.3632)
INDUS
0.2074
(0.1340)
0.1027
(0.1166)
-0.0189
(0.1245)
0.0625
(0.1281)
0.2318*
(0.1254)
GROUP
0.4666***
(0.11934)
0.5130***
(0.0962)
1.1834***
(0.1116)
0.6965***
(0.1142)
0.3395***
(0.1067)
IT2
0.2737***
(0.0324)
0.2339***
(0.0278)
0.4118***
(0.0296)
0.2496***
(0.0309)
0.3188***
(0.0300)
Intercept
-0.2140
(0.2650)
-0.6361***
(0.2183)
-0.1734
(0.2615)
-0.7641***
(0.2477)
-0.2110
(0.2494)
Observations
815
815
815
815
815
-2 Log L
3234.47
4160.14
3836.12
3491.29
3697.97
Percentage Concordant
77.4
73.3
77.9
76.7
74.3
Standard error in parentheses. * Coef. significant at the threshold of 10%, ** 5%, *** 1%.
Source: Community survey on ICT usage by enterprises and CSR survey (Luxembourg)
5. Conclusions
The aim of this article is to investigate the links between different CSR strategies and Green
IT strategies. This paper originates from the premise that an increasing number of firms are
committed to CSR strategies, seeking, among other things, to reduce their impact on the
environment. Considering that eco-innovations are often presented as central in easing the
unambiguous trade-offs between environmental protection and economic growth(Demirel and
Kesidou, 2011, 1546), our study contributes to the growing literature on the assessment of the
relationship between CSR and eco-innovation by focusing on the adoption of Green IT
strategies. More precisely, we determine the effects of two iconic CSR strategies, strategic CSR
and responsive CSR (Porter and Kramer, 2006), on the adoption of different types of Green IT
strategies: (1) the three types inspired by Berkhout and Hertin’s (2001) and Jenkin et al.’s
(2011) typologies, labelled in our study ‘REDUCE’, ‘SUBSTITUTE’ and ‘TRANSFORM’; and
(2) the two types stressed by Faucheux and Nicolaï (2010), entitled ‘CURATIVE’ and
‘PREVENTIVE’.
This paper provides three mains results. First, our findings indicate that CSR plays a role in
the adoption of Green IT. This result is in line with the findings of Veugelers (2012) or
Poussing and Le Bas (2013) who show the importance of firms voluntary measures as a driver
of environmental innovations. Second, we show that different CSR strategies are linked to
different types of Green IT. The firms which adopt strategic CSR have a biggest probability to
adopt ‘REDUCE’ and ‘TRANSFORM’ types of Green IT. The firms which adopt responsive
CSR have a biggest probability to adopt Green IT strategies, such as ‘SUBSTITUTE’ or
‘TRANSFORM’. These results are comparable to Bocquet et al. (2013) when they find that
strategic and responsive CSR are linked to different technological innovations (process and
product innovation). They are also in line with the findings of Bocquet et al. (2014) and
McWilliams and Siegel (2000). Third, when we adopt a typology depending on the ways in
which Green IT is integrated throughout the life cycle of a product, the effect of both strategic
and responsive CSR is the same on the PREVENTIVE’ strategy type. All types of CSR
strategies have a positive effect on the probability to adopt ‘PREVENTIVE’ Green IT.
In addition to our key findings described above, the novelties of this work are the use of
different strategies of CSR and green IT to analyse the link between these two issues and the
use of two original data sets at the firms level (the community survey on ICT usage by
enterprises and a survey relative to CSR practices).
For public authorities seeking to encourage the adoption of green or virtuous behaviours on
behalf of economic agents, these results show that firms’ commitment is influenced by
economic factors (cost savings) and by the desire for social acceptance (corporate image) but
also by their core values (which we consider to be an important element of their CSR policy).
Consequently, the diffusion of Green IT should not be stimulated exclusively by means of direct
or indirect taxes or grants but also by policies aiming to increase corporate awareness and,
hence, voluntary agreements by firms (Demirel and Kesidou, 2011). Our findings also provide
empirical evidence showing that it is necessary to consider firms’ level of maturity with regard
to their CSR policy in order to determine its impact on different types of Green IT.
From a managerial point of view, considering the existence of a positive link between CSR
policy and Green IT adoption and knowing that these two approaches are traditionally led by
distinct services within organisations, IT and strategic departments; our results underline the
necessity for greater cooperation between these departments in order for IT/S strategies to be
aligned with organisational strategies and for these espoused strategies to be instantiated,
implemented and “realized” as Green IT/S(Jenkin et al., 2011, 7). This recommendation is in
line with that of Uhlman (2008, 2) who shows that greater cooperation between IT and facilities
departments and an integrated, holistic, collaborative approach to their respective missions can
greatly […] maximize resources and provide the levels of service needed by IT.
One limitation of our paper lies in the data used. Our data are cross-sectional and limited to
one country. Further research needs to address this limitation by using time-series and cross-
country data to obtain a more robust measure of the effects of CSR on Green IT adoption.
Moreover, to strengthen our results by dealing with the concept of greenwashing, which is a
widespread practice across industry (Laufer, 2003), further research should measure CSR
commitment with questionnaires but also with direct measures.
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Appendix A: Questionnaire items from the Corporate Social Responsibility Survey used in the
econometric model
Is your company active in the field of Corporate Social Responsibility (CSR)?
Yes No, but it is scheduled No
within less than 2 years End of questionnaire
End of questionnaire
Glossary: corporate social responsibility is the voluntary integration of companies' social and
ecological considerations into their business operations and relations with their stakeholders.
Being socially responsible means not only fully meeting the legal obligations applicable, but
going still further, and investing "even more" in the human capital, the environment and
relations with stakeholders (employees, customers, suppliers, non-governmental organisations,
local authorities and shareholders).
Where is your CSR policy described? (several replies possible)
In your activity report
In a report dedicated to CSR
On your website
Nowhere
Other (give details): ______________________________
Do you have a document describing the values and priority concerns and/or motivations
of your company in social and environmental terms?
Yes No
Have you identified the stakeholders targeted by your CSR policy?
Yes No
Before initiating your CSR policy, did you enter into contact with your stakeholders?
Yes No
What are the three main effects you wish to achieve with your CSR policy?
Attracting new employees |__|
Attracting investors |__|
Attracting new customers |__|
Improving the company's image |__|
Standing out from the competition |__|
Anticipating changes in legislation |__|
Reducing your costs |__|
Satisfying your stakeholders |__|
Reducing your impact on the environment |__|
Increasing the well-being of your employees |__|
Other (give details): _______________________________
Before initiating your CSR policy, did you:
(several replies possible)
Yes No
Make a list of the actions already carried out within your company
Make a list of the actions that could be envisaged within your company
Study the actions carried out by other companies
Collect information from specialised bodies
Collect information from the public authorities
Find out about existing CSR standards and labels
Assess the costs of implementing CSR
Have you drawn up a schedule for the CSR actions you wish to carry out?
Yes No
Have you drawn up any communication plans on your CSR commitments?
In-house Yes No
External Yes No
Appendix B: Questionnaire items from the ‘Information and Communication Technologies
Usages by Enterprises’ survey used in the econometric model.
In January 2011, did your enterprise have in place any of the following policies?
Yes
No
a)
Policies designed to reduce the amount of paper used in
printing or copying …………………………….……...
b)
Policies designed to reduce the energy consumption of your
ICT equipment.
e.g. Computers and screens to be turned off, use of automated
power down devices for the ICT equipment, use of multi-
function peripheral imaging devices (printers, scanners,
photocopiers) etc. …………………………………………
c)
Policies for using telephone, web or video conferencing instead
of physical travel…………………………………….
d)
Policies designed to acquire equipment which consumes less
energy
e.g., materials with eco-label …………………….………..
e)
Policies designed to make your employees aware of the
environmental impact of their behaviour in the use of ICT
equipment……………………..
f)
Policies designed to manage electronic waste
e.g. recycling, recovery, resale of electrical and electronic
equipments………..
In January 2011, did your enterprise have in place any dedicated IT applications to
reduce the energy consumption of business processes? (including the optimisation of work
routines, production processes, transport or logistics)
Yes No
In January 2011, did your enterprise provide to the persons employed remote access to
the enterprise's e-mail system, documents and applications?
Yes No
In 2010, did your enterprise assess the energy consumption of its computer equipments?
Yes No
H1. In January 2011, what were the objectives sought by your enterprise in the use of
"Green IT"?
Yes
No
a)
Reduce the environmental footprint ………………………
b)
Reduce operating costs ………………………………………
c)
Improve the corporate image of the enterprise ..……………..
d)
Respond to a demand from employees, customers, suppliers,
shareholders, etc…………………………...
e)
Align the IT policy with the enterprise’s environmental policy
Appendix C: Correlation matrix of the variables.
Pearson Correlation Coefficients, N = 815
Prob > |r| under H0: Rho=0
Strategic
CSR
Responsive
CSR
NO_CSR
COST
IMAGE
SMALL
MEDIUM
LARGE
Strategic
CSR
100.0
-0.088
-0.4927
0.0110
0.0074
-0.0875
0.0821
0.0207
0.0111
<.0001
0.7530
0.8319
0.0124
0.0190
0.5543
Responsive
CSR
100.0
-0.4324
0.1429
0.1043
-0.1059
0.0610
0.1107
<.0001
<.0001
0.0029
0.0024
0.0817
0.0015
NO_CSR
100.0
-0.0761
-0.0704
0.1517
-0.1139
-0.0994
0.0297
0.0445
<.0001
0.0011
0.0045
COST
100.0
0.5656
-0.0376
-0.0080
0.1055
<.0001
0.2831
0.8176
0.0025
IMAGE
100.0
-0.1065
0.0470
0.1432
0.0023
0.1795
<.0001
SMALL
100.0
-0.9044
-0.3133
<.0001
<.0001
MEDIUM
100.0
-0.1218
0.0005
LARGE
100.0
Pearson Correlation Coefficients, N = 815
Prob > |r| under H0: Rho=0
INDUS
GROUP
IT2
Strategic_CSR
-0.0069
-0.0050
0.1297
0.8421
0.8865
0.000
Responsive_CSR
0.0638
0.1262
0.1684
0.0683
0.0003
<.0001
NO_CSR
-0.0290
-0.1314
-0.2325
0.4082
0.000
<.0001
COST
-0.0493
0.0744
0.2206
0.1591
0.0337
<.0001
IMAGE
-0.0454
0.0744
0.2061
0.1945
0.0335
<.0001
SMALL
-0.0897
-0.2700
-0.2167
0.0104
<.0001
<.0001
MEDIUM
0.0636
0.2233
0.1550
0.0694
<.0001
<.0001
LARGE
0.0671
0.1310
0.1591
0.0554
0.0002
<.0001
INDUS
100.0
0.0887
0.0186
0.0113
0.5946
GROUP
100.0
0.2315
<.0001
IT2
100.0
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Offered here is a conceptual model that comprehensively describes essential aspects of corporate social performance (CSP). The three dimensional model address major questions of concern: (1) What is included in the definition of CSR? (2) What are the social/stakeholder issues the firm must address? and (3) What is the organization's strategy/mode/philosophy of social responsiveness. The first dimension is the source of the original four-part definition of CSR originated: economic, legal, ethical, and discretionary (later termed philanthropic). It was later presented at the CSR Pyramid (1991).
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We test the relationship between shareholder value, stakeholder management, and social issue participation. Building better relations with primary stakeholders like employees, customers, suppliers, and communities could lead to increased shareholder wealth by helping firms develop intangible, valuable assets which can be sources of competitive advantage. On the other hand, using corporate resources for social issues not related to primary stakeholders may not create value for shareholders. We test these propositions with data from S&P 500 firms and find evidence that stakeholder management leads to improved shareholder value, while social issue participation is negatively associated with shareholder value. Copyright © 2001 John Wiley & Sons, Ltd.
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Researchers have reported a positive, negative, and neutral impact of corporate social responsibility (CSR) on financial performance. This inconsistency may be due to flawed empirical analysis. In this paper, we demonstrate a particular flaw in existing econometric studies of the relationship between social and financial performance. These studies estimate the effect of CSR by regressing firm performance on corporate social performance, and several control variables. This model is misspecified because it does not control for investment in R&D, which has been shown to be an important determinant of firm performance. This misspecification results in upwardly biased estimates of the financial impact of CSR. When the model is properly specified, we find that CSR has a neutral impact on financial performance. Copyright © 2000 John Wiley & Sons, Ltd.
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Those promoting the corporate social responsibility agenda to small and medium-sized enterprises (SMEs) are interested in the potential of supply chain drivers as an incentive. This paper presents results from an empirical study into the attitudes and behaviours of 103 UK SME owner/managers in response to buyer pressure to demonstrate CSR activities. Most said that the inclusion of social and environmental requirements as preconditions to supply would increase their motivation to engage in CSR (82% for environmental criteria and 55% for social criteria). However, a quarter would be put off tendering and 12% thought that such criteria would be counter productive.
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We test the relationship between shareholder value, stakeholder management, and social issue participation. Building better relations with primary stakeholders like employees, customers, suppliers, and communities could lead to increased shareholder wealth by helping firms develop intangible, valuable assets which can be sources of competitive advantage. On the other hand, using corporate resources for social issues not related to primary stakeholders may not create value far shareholders. We test these propositions with data from S&P 500 firms and find evidence that stakeholder management leads to improved shareholder value, while social issue participation is negatively associated with shareholder value. Copyright (C) 2001 John Wiley & Sons, Ltd.