Content uploaded by Magali A. Delmas
Author content
All content in this area was uploaded by Magali A. Delmas on Jul 29, 2018
Content may be subject to copyright.
Environmental standards and labor productivity:
Understanding the mechanisms that
sustain sustainability
MAGALI A. DELMAS
1
*AND SANJA PEKOVIC
2
1
Anderson School of Management & Institute of the Environment and Sustainability, University of California, Los Angeles, U.S.A.
2
University Paris-Dauphine, Paris, France
Summary In the last decade, a rising number of firms have adopted voluntary international environmental management
and product standards, such as the international ISO 14001 management standard or organic certification.
Although emerging research analyzes the impact of these standards on environmental and financial perfor-
mance, there is to our knowledge no empirical research on how they affect the productivity of employees.
In this paper, we investigate the direct relationship between environmental standards and labor productivity,
as well as two mediating mechanisms through which environmental standards influence labor productivity:
employee training and enhanced interpersonal contacts within the firm. Our empirical results, based on a
French employer–employee survey from 5220 firms, reveal that firms that have adopted environmental
standards enjoy a one standard deviation higher labor productivity than firms that have not adopted such
standards. Copyright © 2012 John Wiley & Sons, Ltd.
Keywords: environmental standards; positive social identity; training; interpersonal contacts; labor
productivity
Introduction
Environmental management and product standards have been proposed as an innovative governance mechanism for
improving firms’environmental performance (Delmas & Young, 2009). These standards include the International
Environmental Management System Standard ISO 14001 and organic certification, both of which are increasingly
being adopted worldwide (Delmas & Grant, 2010; Delmas & Montes-Sancho, 2011). More than 150 000 ISO
14001 certificates have been issued around the world,
1
and as of 2007, organic certification reached a 3.9 per cent
market share in the EU.
2
Scholars have suggested that environmental standards could allow firms to profit from reducing their negative
environmental impact by improving their labor productivity (Ambec & Lanoie, 2008). Although an emerging body
of literature investigates the environmental and financial benefits derived from the adoption of environmental
standards (e.g., Aerts, Cormier, & Magnan, 2008; Barla, 2007; Christmann, 2000; Darnall, Gallagher, Andrews, &
Amaral, 2000; Delmas, 2001; Delmas & Montiel, 2009; King & Lenox, 2002; Nakamura, Takahashi, & Vertinsky,
2001), exactly how these standards impact organizational effectiveness and employee productivity remains unclear.
So far, only anecdotal evidence has been presented to support the argument of greater employee loyalty and
*Correspondence to: Magali A. Delmas, Anderson School of Management & Institute of the Environment and Sustainability, University of
California, Los Angeles, California, 90095, U.S.A. E-mail: delmas@ucla.edu
1
ISO website: www.iso.ch
2
http://epp.eurostat.ec.europa.eu
Special Issue Article
Copyright © 2012 John Wiley & Sons, Ltd.
Received 3 June 2011
Revised 15 June 2012, Accepted 7 August 2012
Journal of Organizational Behavior, J. Organiz. Behav. 34, 230–252 (2013)
Published online 11 September 2012 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/job.1827
productivity at environmentally or socially responsible firms (Brekke & Nyborg, 2008; Frank, 2003). For example,
the multinational corporation, Dole Food Co., Inc. reported that “key benefits [of the adoption of environmental
management systems] include strong employee motivation and loyalty that translate into reduced absenteeism and
improved productivity.”
3
Studying the effect of environmental standards on employees’productivity is important
because employees are widely recognized as a major source of competitive advantage (Grant, 1996; Pfeffer,
1994; Schuler & Jackson, 1987).
In this paper, we develop and test hypotheses on the relationship between the adoption of environmental standards
and labor productivity. First, we argue that the adoption of environmental standards might increase employee’s
social identification with their firm and result in enhanced labor productivity. Second, we make the case that the
adoption of environmental standards is associated with organizational changes, which may result in increased pro-
ductivity. These changes include implementation of employee training programs and higher levels of interpersonal
interactions, or greater employee engagement, in standard business operations. Training can lead to more effective
employees, and interpersonal contacts can help employees engage in knowledge transfer and lead to innovative
ideas that improve productivity. Interpersonal contacts can also promote employee job satisfaction and motivation,
which in turn lead to increased productivity. In other words, the adoption of environmental standards may also
improve organizational effectiveness through adjustments in the firm’s work systems.
We test our hypotheses with data obtained from a French survey, including responses with detailed employee
characteristics from 5220 firms. Our results show that the adoption of environmental standards is associated with
higher levels of labor productivity and that improved training and interpersonal contacts mediate this relationship.
This paper makes several contributions to the management literature as well as the business and the environment
literature. First, by unveiling organizational mechanisms that link the adoption of environmental standards to
corporate performance, our paper responds to the call made by some scholars to open the organizational black
box in order to understand the organizational changes associated with “greening”afirm (Delmas & Toffel, 2008;
Jackson, Renwick, Jabbour, & Muller-Camen, 2011). Second, we use data on employee and firm characteristics
from a large, representative sample of French firms, each of which employs more than 20 individuals. This allows
us to control for a very detailed set of workers and job characteristics in order to properly isolate the effect of envi-
ronmental standards on labor productivity. Third, using a French database brings a new and potentially enlightening
perspective to the debate on the relationship between corporate environmental performance and financial perfor-
mance, as empirical studies on the subject are typically based on U.S. data.
This paper is organized as follows. In the second section, we review the literature on environmental standards and
their impact on performance. In the third section, we develop hypotheses relating the adoption of environmental
standards to labor productivity. In the fourth section, we describe our empirical strategy based on a novel employee
database. In the fifth section, we describe our results. A concluding section follows.
Literature Review
Understanding the relationship between corporate environmental performance and financial performance has been
the focus of considerable research since the 1970s (Orlitsky, Schmidt, & Rynes, 2003). Within this wider context,
many scholars have focused on whether firms are financially rewarded for improving their environmental
performance. The contention of neoclassical microeconomics is that firms accrue little or no gain from investing
in environment performance, whereas “win–win”theorists claim that such investments can generate competitive
advantage and other profit opportunities (Orsato, 2006). Scholars attempting to empirically test these conflicting
3
Dole Reports Motivation, Health and Safety, and Productivity Benefits from ISO 14001. http://staratel.com/iso/ISO/ISO900014000/articles/pdf/
casestudy_2-01.pdf. Accessed on 27 May 2011.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 231
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
theories empirically have generated an extensive body of literature, with the balance of studies suggesting a
positive relationship between improved environmental and financial performance (Margolis & Walsh, 2003;
Orlitsky et al., 2003).
Environmental standards aim to improve environmental performance and firms’relationships with both market
and non-market actors (Delmas & Montiel, 2008). They require the adoption of management practices, which
are not legally mandated and which may promote organizational commitment to improving the natural environ-
ment (Darnall, Henriques, & Sadorsky, 2010; Delmas, 2002). These practices include the implementation of
environmental policies (Henriques & Sadorsky, 1996); the utilization of internal assessment tools, such as
benchmarking and accounting procedures (Nash & Ehrenfeld, 1997); the establishment of environmental
performance goals (Hart, 2005); internal and external environmental audits; the implementation of employee
environmental training; and the establishment of employee incentive compensation plans based on the firm’s
environmental performance (Welford, 1998). Hence, adopting these standards requires significant organizational
changes within the firm.
The literature has identified several mechanisms that can link the adoption of environmental management
standards to corporate performance. These include cost reduction, improved internal efficiency, enhanced firm
reputation, and access to green markets (Delmas & Montiel, 2009; Porter & Van Der Linde, 1995).
Environmental standards require the implementation of a set of environmental practices and procedures that
ensure that risks, liabilities, and impacts are properly identified, minimized, and managed (Darnall et al., 2000). Such
practices have the potential to reduce risks related to environmental compliance (Delmas, 2001; Grolleau, Mzoughi,
& Thomas, 2007) and decrease insurance costs (Barla, 2007).
Environmental standards can also help the firm improve efficiency, as the adoption of environmental practices
establishes new systems for gathering information and monitoring environmental performance (Khanna & Anton,
2002), which can induce the redesign of production processes (Christmann, 2000), trigger innovation, and improve
technologies that will positively affect a firm’sefficiency (Shrivastava, 1995).
Additionally, environmental standards can enhance corporate reputation (e.g., Konar & Cohen, 2001) and provide
access to environmentally oriented consumers (Anton, Deltas, & Khanna, 2004; Delmas & Montiel, 2009; Khanna
& Damon, 1999; Nakamura et al., 2001).
Research has also shown that employee involvement in the adoption and implementation of the environmental
management system ISO 14001 can lead to a competitive advantage (Delmas, 2001). However, there is very little
empirical evidence to support the hypothesis that environmental practices influence employee performance
outcomes. The goals of this paper are to develop and test hypotheses on the mechanisms that link environmental
certification to labor productivity. By identifying and testing such mechanisms, we hope to fill a void in the literature
and to enhance knowledge of the organizational changes associated with the adoption of green practices.
Hypotheses
Through the adoption of an environmental standard, a firm sends a signal to both its internal and external stake-
holders about its commitment to improve environmental performance (Delmas, 2002; Delmas & Montiel, 2009).
Hence, it would seem likely that an organization’s commitment to social and environmental issues would lead to
a positive organizational reputation and have a positive impact on employees’work attitudes. As Ambec and Lanoie
(2008, p. 57) noted:
people who feel proud of the company for which they work not only perform better on the job, but also become
ambassadors for the company with their friends and relatives, enhancing goodwill and leading to a virtuous circle
of good reputation.
232 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
One mechanism that we argue links the adoption of environmental standards to labor productivity is the positive
social identity that can be derived from working in a “greener”firm. Employees can identify more strongly with
ethical and responsible firms, and such identification may be translated into cooperative and citizenship-type
behaviors (Dutton, Dukerich, & Harquail, 1994; Frank, 2003; Jones & Hamilton Volpe, 2011) and increased
employee organizational commitment (Brammer, Millington, & Rayton, 2010; Peterson, 2004). Such positive
corporate social identity may create a stronger emotional association between employees and their firm, resulting
in enhanced labor productivity (Hess, Rogovsky, & Dunfee, 2002; Koh & Boo, 2001; Viswesvaran, Deshpande,
& Joseph, 1998).
Social and environmental responsibility may also make the firm more attractive to prospective employees
(Greening & Turban, 2000; Grolleau, Mzoughi, & Pekovic, 2012; Turban & Greening, 1997), and individuals
who choose to work for “greener firms”may work harder (Brekke & Nyborg, 2008).
As we will discuss in more details later, there are additional tangible organizational changes, such as training,
that result from the adoption of environmental standards that may also lead to high-performance work systems
and increased productivity. In other words, the implementation of environmental standards can create a virtuous
circle of reciprocal interactions between the firm structure and its workforce (Perez, Amichai-Hamburger, &
Shterental, 2009).
We therefore hypothesize that the adoption of environmental standards is associated with greater labor productivity.
Hypothesis 1: The adoption of environmental standards is associated with greater labor productivity.
We develop two additional hypotheses focusing on the main organizational changes associated with the
adoption of environmental standards—namely training and on interpersonal communication and contacts within
the organization—that we argue can lead to greater labor productivity. Such organizational changes have been
recognized as central to the adoption of environmental standards. Indeed, most environmental standards such as
ISO 14001 require the firm to implement an environmental management system in order to document and commu-
nicate environmental information more effectively and to allow continuous improvement (Delmas, 2000). A
substantial number of ISO 14001 requirements relate to the internal structure of the organization, record keeping
procedures, internal communication methods, definition of responsibilities, and training programs (Delmas, 2001).
As such, “training and communication are essential elements in the implementation of ISO 14001”(Sammalisto
& Brorson, 2008, p. 299).
Environmental standards, employee training, and labor productivity
The adoption of an environmental standard requires investment in employee training (Khanna & Anton, 2002).
For example, one of the basic requirements to become ISO 14000 certified is to provide job-appropriate employee
training (ISO, 1996), and several authors have shown that ISO certification is an important determinant of training
efforts within the organization (Blunch & Castro, 2007; Ramus & Steger, 2000). Training is typically provided to
over half of the firm’s employees, with some firms training over 95 per cent of their staff (Corbett & Luca, 2002).
For example, Honda’s environmental certification resulted in the development of a contractor-training program
(McManus & Sanders, 2001). This type of training enables employees to better identify pollution prevention
opportunities and empowers them to offer recommendations (Morrow & Rondinelli, 2002; Rondinelli & Vastag,
2000; Toffel, 2000).
Human capital stock, accumulated through training activities, is one of the main factors of production (e.g.,
Lynch, 1994). Investment in human resources has been recognized as a significant source of competitive advantage,
as such investments can lead to more effective employees (Porter, 1985), and one of the key tools for investing in
human resources is training (Jennings, Cyr, & Moore, 1995). Scholars have also argued that training is profitable
through an increase in the specificity of human capital, which is difficult to imitate (Koch & McGrath, 1996).
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 233
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Empirical evidence corroborates this conclusion and shows that training is positively associated with labor
productivity improvement (Conti, 2005; Dearden, Reed, & Van Reenen, 2006; Koch & McGrath, 1996; Rennison
& Turcotte, 2004; Zwick, 2004).
On the basis of this reasoning, we formulate the following hypothesis on the mediating role of employee training
on the relationship between environmental standards and labor productivity:
Hypothesis 2: Training mediates the relationship between the adoption of environmental standards and greater
labor productivity.
Environmental standards, interpersonal contacts, and labor productivity
Scholars have shown that the adoption of environmental standards alters the organization of the firm by requiring
changes in employee attitudes, roles, and responsibilities (Florida & Davidson, 2001; Hart, 1995) that might
indirectly influence employee performance outcomes (Lanfranchi & Pekovic, 2010). More specifically, we argue
that environmental standards are associated with improved interpersonal contacts within the firm, which may
increase labor productivity.
The majority of environmental management projects require a combination of different types of competencies that
can be obtained by establishing cross-functional teams (Denton, 1999; Rothenberg, 2003) and promoting collabora-
tive work from employees of different hierarchical levels and functions (Oh’Eocha, 2000). Environmental standards,
such as ISO 14001, have demonstrated the potential to transcend functional areas of the organization and integrate
environmental considerations throughout the entire organization (Delmas, 2001), and to additionally encourage
employees to work together in teams regardless of their placement within the organization (Arimura, Darnall, &
Katayama, 2011). Consequently, interpersonal contacts and teamwork are considered as a fundamental element of
environmental management standards.
There are two main reasons proposed in the literature to explain why increased interpersonal contacts in an
organization can lead to improved labor productivity. First, interpersonal contacts and communication among
workers with heterogeneous abilities can help employees engage in knowledge transfer and lead to innovative
ideas that improve productivity (Hamilton, Nickerson, & Hideo, 2003; Mohrman & Novelli, 1985). Second,
interpersonal contacts can promote employee job satisfaction and motivation, which in turn lead to increased
productivity. Work is a social activity that engages the same social needs and responses as any other part of life,
such as the need for connection, cooperation, support, and trust (Cohen & Prusak, 2001). Organizations that
facilitate interpersonal contacts among their employee provide an enhanced working environment that might lead
employees to give more to the firm and increase their productivity, which results in overall improved organiza-
tional productivity (Banker, Field, Schroeder, & Sinha, 1996; Batt, 2004; Huselid, 1995). We therefore hypoth-
esize the following:
Hypothesis 3: Interpersonal contacts mediate the relationship between the adoption of environmental standards
and greater labor productivity.
In summary, several mechanisms explain a positive relationship between environmental standards and labor
productivity. We argue that employees can derive a positive social identity from being associated with a firm adopt-
ing environmental standards and may be willing to work harder for such a firm. We also contend that the adoption of
environmental standards is associated with higher performance work systems, which we hypothesize lead to im-
proved employee productivity. These mediating mechanisms include employee training and improved interpersonal
contacts. We illustrate these relationships in Figure 1.
234 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Method
Data
To test our hypotheses, we used data from the French Organizational Changes and Computerization’s (COI) 2006
survey.
4
The COI survey is a matched employer–employee dataset on organizational change and computerization
from the National Institute for Statistics and Economic Studies (INSEE), the Ministry of Labor, and the Center
for Labor Studies (CEE). The survey contains 7700 firms, with at least 20 employees belonging to the private sector.
It is a representative population of French firms from all industries except agriculture, forestry, and fishing. Each
firm fills in a self-administered questionnaire concerning the utilization of information technologies and work
organizational practices in 2006, and changes that have occurred in those areas since 2003.
5
Firms were also
interviewed on the economic goals driving the decision to implement organizational changes and the economic
context in which those decisions were made.
Within each surveyed firm, employees were randomly selected and asked about their personal socio-economic
characteristics, as well as information about their job and position within the organization. The labor force
survey defines the employee’s job duties and responsibilities at the time of the survey and provides only a
few elements dealing with actual changes. In our sample, the respondents are associated with the following
departments: 46 per cent to general management; 32 per cent to finance and accounting; 7 per cent to human
resources; 2 per cent to manufacturing, logistics, and quality; 7 per cent to information technology; and 6 per cent
are classified as others.
The original dataset includes 14 369 employees. In order to obtain information on business export volumes,
employee value-added activities, and earnings and wage information, the COI survey was merged with two other
databases: the Annual Enterprise Survey (EAE) and the Annual Statement of Social Data (DADS). As a result of
these merges, our sample includes 10 663 employees from 5220 firms.
These databases offer a propitious opportunity to examine three relationships: (i) between the firm’s environmen-
tal orientation, employee training, and interpersonal contacts; (ii) between employee training and interpersonal
contacts and labor productivity; and (iii) between environmental standards and labor productivity. By controlling
for the organizational changes associated with the adoption of environmental standards, we sought to isolate the
4
More details about the design and scope of this survey are available on www.enquetecoi.net: Survey COI-TIC 2006-INSEE-CEE/Treatments
CEE.
5
We present information on questionnaire respondents in Appendix 1.
Figure 1. Environmental standards, training, interpersonal contacts, and labor productivity
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 235
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
positive social identity effect, which implementation of environmental standards may bring about and which might
lead to improved labor productivity.
Dependent and independent variables
Green
To test the main hypothesis of the paper, namely, that firms that have adopted environmental standards enjoy higher
labor productivity than firms that have not adopted such standards, we used the variable denoted Green, which is a
binary variable, coded 1 if the firm was registered according to one of the following standards in 2006: ISO 14001
standard, organic labeling, fair trade, and other types of environmental-related standards. Unfortunately, the database
does not distinguish between those standards; however, as these standards include similar components, it is expected
that their impact will be comparable. At the time of the survey, the majority of the adoption of environmental
standards consisted of the ISO 14001 standard with 3476 ISO 14000 certified firms in 2006.
6
Labor productivity
Drawing on prior research (e.g., Salis & Williams, 2010), we measured labor productivity as the logarithm of the
firm’s value added by the number of employees. We used the Annual Enterprise Survey (EAE) to obtain information
on the firm value added. We obtained number of employees from the Organizational Changes and Computerization
(COI) database.
Training
In order to estimate the mediating role of training on the relationship between environmental standards and labor
productivity, we constructed a training indicator that consists of the following five components: (i) general training
provided; (ii) employee received training in the last three years; (iii) duration of the last training received; (iv) training
led to a certificate; and (v) employee obtained training certificate. Because these variables were dummy or categorical
variables, we added them to construct the training variable. We tested the reliability of the training scale using
the mean standardized Cronbach’s alpha. We obtained a Cronbach’saof .77, which is considered satisfactory
(e.g., Churchill, 1979).
Interpersonal contacts
In order to analyze if improvement in employee’s interpersonal contacts could mediate the relationship between
environmental standards and labor productivity, we created an indicator for interpersonal contacts that includes
the following components: (i) employee works regularly with his or her subordinates; (ii) employee works regularly
with colleagues from the same or different departments; (iii) employee works regularly with people outside the firm;
(iv) employee shows his or her colleagues how to conduct specific tasks: often (at least two or three times a month),
sometimes (at least two or three times a year), never, or almost never; (v) employee shares work or takes part in work
distribution with his or her colleagues: often (at least two or three times a month), sometimes (at least two or three
times a year), never, or almost never; (vi) employee is consulted over difficulties with the team, clients, or other
persons: often (at least two or three times a month), sometimes (at least two or three times a year), never, or almost
never; (vii) employee is part of a work group, such as a project, problem-solving, pilot, or brainstorming group; (viii)
the employee works with: one colleague, two to five colleagues, six to 10 colleagues, or more than 10 colleagues;
and (ix) employee attends meetings. The interpersonal contact scale proved to be reliable with a mean standardized
Cronbach’sacoefficient of .72, which is considered satisfactory (e.g., Churchill, 1979).
6
The ISO Survey of Certifications 2007 (17th Cycle).
236 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Controls
In order to control for firm-level heterogeneity, our analysis includes variables representing firm characteristics
based on previous studies, specifically those relating environmental performance, training, interpersonal contacts,
and labor productivity (e.g., Delmas & Montes-Sancho, 2011; Delmas & Montiel, 2009; Grolleau, Mzoughi, &
Pekovic, 2007; Pfeffer & Langton, 1993; Zwick, 2004).
ISO 9000
Previous studies have shown that the adoption of the international quality management standard ISO 9000 can
facilitate the successful implementation of environmental standards through the utilization of related information,
resources, and skills (Delmas, 2002; Delmas & Montes-Sancho, 2011; Grolleau, Mzoughi, & Pekovic, 2007; King
& Lenox, 2002). Moreover, the adoption of management practices such as ISO 9000 is found to increase labor
productivity through improvement of employee skills (Huselid, 1995). We therefore included a binary variable
representing the adoption of ISO 9000 by the firm.
Export
Several empirical studies have confirmed the significant role played by exports in firms’decisions to adopt
environmental standards (Corbett & Kirsch, 2001; Delmas & Montiel, 2009; Grolleau, Mzoughi, & Pekovic,
2007). Furthermore, export-oriented firms tend to have higher labor productivity in order to compete internationally
(Zwick, 2004). We used a variable representing the firm’s volume of exports divided by the firm’s sales.
Earnings
The implementation of environmental standards requires the investment of significant financial and other resources;
hence, firms with more financial resources might be more likely to adopt an environmental standard (Grolleau,
Mzoughi, & Pekovic, 2007; Welch, Mori, & Aoyagi-Usui, 2002). In addition, the financial strength of the firm leads
to productivity improvement (Dearden et al., 2006). To control for this issue, we used information on firms’earnings
before interest, taxes, and depreciation.
Holding
Being part of a holding company could play a substantial role in the adoption of environmental management
standards (Abrahamson & Rosenkopf, 1997; Darnall et al., 2010). This might be because firms with holding
company associations have more financial resources available to them for investment in new practices (Pekovic,
2010; Zyglidopoulos, 2002). Additionally, being part of a holding company could improve labor productivity
through economies of scope (Eriksson & Jacoby, 2003). Hence, we included a dummy variable that takes a value
of 1 when the firm belongs to a holding company.
Size
Most empirical studies have found that the probability of implementing environmental standards increases with firm
size (e.g., Darnall et al., 2010; Delmas & Montiel, 2009; Grolleau, Mzoughi, & Pekovic, 2007). Firm size has also
been seen as a significant determinant of labor productivity (e.g., Pfeffer & Langton, 1993; Zwick, 2004). Firm size
is measured by the number of employees within the firm.
Sector of activity
In order to control for sector differences, we included sector dummy variables on the basis of the N36 sector
classification, created by the French National Institute for Statistics and Economic Studies: agri-food; consumption
goods; cars and equipment; intermediate goods; energy; construction; commercial; transport; financial and
real-estate activities; and business services and individual services.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 237
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
In addition, we control for employee characteristics that have been found to be related to green performance or
labor productivity in previous research (Burks, Carpenter, & Goette, 2009; Krueger & Schkade, 2008; Pfeffer &
Langton, 1993; Torgler & Garcia-Valinas, 2007; Zwick, 2004).
Gender
Gender has been identified as a predictor of environmental behavior. The findings show that women tend to have
greater environmental concerns than men (Torgler & Garcia-Valinas, 2007). There is also some evidence that
men are more likely to receive employer sponsored training (Veum, 1993). Research has also shown that women
are more likely to invest in interpersonal relationships than men (Liebler & Sandefur, 2002). Furthermore, it is
argued that women are less productive than men (Pfeffer & Langton, 1993). We therefore include a binary variable
that takes a value of 1 if the employee is a woman.
Age
Previous studies consider age to be negatively correlated with decisions to adopt environmental practices (Torgler &
Garcia-Valinas, 2007). As indicated by Frazis, Gittleman, and Joyce (2000), age decreases the probability of being
trained, as well. Moreover, interpersonal contacts at work tend to decrease with age (Krueger & Schkade, 2008). The
impact of employees’age on labor productivity depends on specific age groups (Conti, 2005). We therefore
introduce a variable that represent employees’age.
Education
It has been argued that employees with higher educational levels will be more interested in contributing environmen-
tal initiatives (e.g., Torgler & Garcia-Valinas, 2007) and in receiving training courses (Lynch & Black, 1998). The
productivity of highly educated employees should be greater than those of less educated employees. In order to
control for the level of education, we use 10 categories of education numbered from 1 to 10 from primary school
to Grande Ecole, PhD.
Wage
Wages offered by firms may have an impact on labor productivity. We therefore include a continuous variable
representing the firm average wage.
Seniority
Referencing previous literature, we may presume that seniority within the firm will positively influence labor
productivity (Medoff & Abraham, 1980; Pfeffer & Langton, 1993). Seniority is found to be negatively correlated
with training (Barth, 1997), as well as with employees’interpersonal contacts (Krueger & Schkade, 2008). Hence,
we include a variable that measures the number of years the employee has worked for the firm.
Occupation
Occupation has been shown to be closely related to employees’education and skills (Becker, 1964; Schultz, 1961).
The data comprise four categories: management, middle management, white-collar work, and blue-collar worker.
We include the management and blue-collar worker categories in the analysis, which are contrasted to the other
categories.
Working hours
Previous research has shown a positive correlation between productivity and working hours (Sousa-Poza & Ziegler,
2003). We included a variable that indicates employee working hours.
We present the variables used in estimation, their definitions, and sample statistics in Table 1. We detected no
problem of multi-colinearity (Appendix 1).
238 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Table 1. Definition of variables and sample statistics.
Variable Description Mean SD Min Max
Dependent and independent variables
Green* Registered for ISO 14001, organic labeling or
fair trade (=1 if registered in 2006)
0.22 0.42 0.00 1.00
Labor
productivity**
Logarithm of valued added per employee 3.90 0.64 1.16 7.92
Training* General training provided, employee received
training in the last 3 years, duration of the last
training, training lead to certificate, employee
obtained training certificate
4.84 3.82 0.00 13.00
Interpersonal
contacts*
Employee works with subordinates, colleagues
from the same or different departments;
employee works regularly with people outside
the firm; employee shows to his or her
colleagues how to conduct specific tasks: often
(at least 2 or 3 times a month), sometimes (at
least 2 or 3 times a year), never or almost never;
employee shares work or takes part in work
distribution with his or her colleagues: often (at
least 2 or 3 times a month), sometimes (at least 2
or 3 times a year), never or almost never;
employee is consulted over difficulties with the
team, clients, or other persons often (at least 2 or
3 times a month), sometimes (at least 2 or 3
times a year), never or almost never; employee
is part of a working group such as a project,
problem-solving, pilot, or brainstorming group;
employee works with 1 colleague, with 2 to 5
colleagues, with 6 to 10 colleagues, with more
than 10 colleagues; employee attends meetings
8.27 3.11 1.00 15.00
Control variables
Client supply
center*
Under customer policy firm uses contract to
assure delivery timeless in 2003
0.67 0.47 0.00 1.00
Dummy variable (=1 if yes)
Client call
center*
Under customer policy firm has contact or call
client center in 2003
0.35 0.48 0.00 1.00
Dummy variable (=1 if yes)
Informal
pronoun
usage*
The employee uses the between the informal
subject pronoun “tu”when speaking to his or
her superior (=1 if yes)
0.62 0.49 0.00 1.00
ISO 9000* Certified with ISO 9000 0.54 0.50 0.00 1.00
Dummy variable (=1 if certified in 2006)
Export** Share of exports of total sales (€) 0.12 0.23 0.00 1.01
Earnings** Earnings before interest, taxes, and
depreciation (€)
15 234.89 177 338.9 198 916 8 433 584
Size* Number of employees 655.26 3426.30 20.00 111 956.00
Holding* Belongs to a holding group (=1 if yes) 0.67 0.47 0 1.00
Sector* Agri-food, consumption goods, cars and
equipment, intermediate goods, energy,
construction, commercial, transport, financial
and real-estate activities, business services,
and individual services
(Continues)
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 239
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Estimation strategy
We hypothesize a direct effect of the adoption of environmental standards on labor productivity, as well as mediat-
ing effects of training and interpersonal contacts. Hence, in our model, employee training and interpersonal contacts
are determined by the adoption of environmental standards. We further argue that the adoption of environmental
standards and the degree of training and interpersonal contact within an organization determine labor productivity.
However, the adoption of environmental standards, training, interpersonal contacts, and labor productivity can be
influenced by the same variables (e.g., size, sector of activity, firm’s strategy), and this may cause a spurious rela-
tionship. Thus, an OLS regression is inappropriate because it considers environmental standards adoption, training,
and interpersonal contacts as exogenous.
In light of such endogeneity, we used a three-stage least square (3SLS) model (Aerts et al., 2008; Anton et al.,
2004) that considers environmental standards, training, and interpersonal contacts as endogenous variables. The
model relies on a simultaneous estimation approach (Pindyck & Rubinfeld, 1991), in which (i) the factors that
determine environmental standards are estimated simultaneously with (ii) the factors that explain employee training
or interpersonal contacts, and (iii) the factors that define labor productivity. We estimated jointly the three equations
for each explanatory variable using maximum likelihood.
Y
1,Y
2, and Y
3are latent variables influencing the probability that the firm implements environmental standards;
improves employee training or interpersonal contacts; and improves labor productivity, respectively. We consider
the following 3SLS model:
Table 1. (Continued)
Variable Description Mean SD Min Max
Wage*** Logarithm of average wage within a firm per
hour
12.35 8.06 1.26 68.03
Gender* The employee is a women (=1 if yes) 0.37 0.48 0.00 1.00
Age* Age 40.32 10.01 17.00 77.00
Education* Employee highest academic diploma is from:
(1) primary school; (2) middle school; (3)
short technical course: CAP (vocational
certificate), BEP (technical school certificate),
in apprenticeship; (4) short technical course:
CAP, BEP, etc. without apprenticeship; (5)
general secondary school (full 3 years); (6)
technological or professional secondary school
(full course); (7) 3-year university degree; (8)
4-year university degree; (9) 5-year university
degree; (10) grande école, engineering school,
business school
5.00 2.32 1.00 10.00
Seniority* Seniority 11.78 9.49 0.00 42.00
Occupation* Employee works as:
Management (included) 0.14 0.35 0.00 1.00
Middle management (not included) 0.23 0.42 0.00 1.00
White-collar worker (not included) 0.20 0.40 0.00 1.00
Blue-collar worker (included) 0.43 0.50 0.00 1.00
Working
hours*
Number of working hours per week 37.78 6.93 1.00 90.00
Because of the table’s length, we do not report sample statistics for these variables.
*Variables were retrieved from the COI.
**Variables retrieved from the EAE database.
***Variables retrieved from the DADS databases.
240 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Y
1¼a1þb1X1þd1Z1þm1
Y
2¼a2þb2X2þg1Y1þd2Z2þm2
Y
3¼a3þb3X3þg1Y1þg2Y2þm3
8
<
:
(1)
where X
1
are the vectors of exogenous variables including firm characteristics, such as export level, being a part of a
holding company, size, and sector activity. In addition, we control for employee characteristics, including gender,
age, education, and wage.
The vector of variable Z
1
represents the vectors of instrumental variables that guarantee the identification of the
model and help estimate correlation coefficients (Maddala, 1983). Hence, in order to identify the three-stage least
square model, we needed additional variables that explain the probability of adopting environmental standards,
but are not correlated to the error term of the labor productivity equation. In our case, Z
1
indicates that the firm
assured timely delivery to its customers and had a client call center in 2003.
Several rationales can explain why the client supply center and client call center variables affect environmental
practices. With environmental standards, it is essential to maintain close links with customers in order to identify
their needs, to receive feedback necessary for understanding if customer requirements are successfully met, and
to determine whether to initiate relevant improvement activities. Hence, firms that have a close link with their
customers also have strong incentives to demonstrate goodwill to their customers by implementing successful envi-
ronmental management systems (Nishitani, 2009). Moreover, the literature argues that a firm that wants to deliver
their products or services on time should adopt management practices, because the implementation of such practices
improves delivery performance, mainly through reduction in time spent on non-value-added activities (Pekovic, 2010).
We presumed that a firm’s relationships with clients would not positively influence labor productivity, because
scholars have identified potential tradeoffs between customer satisfaction and productivity (Anderson, Fornell, & Rust,
1997). It is worth noting that our proposed instrumental variables do not appear to be a significant determinant of
training, interpersonal contacts, and labor productivity in a single equation logit or probit model.
X
2
includes two sets of variables: (i) firm characteristics (export level, being a part of a holding, size, and sector
activity) and (ii) socio-demographic characteristics (gender, age, age square, education, wage, seniority, occupation,
and working hours).
As in the previous case, the vector of variable Z
2
represents the vector of the instrumental variable that explains
the probability of employee training improvement or interpersonal contacts, but is not correlated to the error term
of the labor productivity equation. For employee training and interpersonal contacts, the vector Z
2
includes
whether the employee uses the informal pronoun “tu”when speaking to his or her superior. The choice of this
variable as an instrument seems to be reasonable, because supervisors play a central role in employee work
empowerment and integration (Hopkins, 2005) and in developing opportunities for employees to practice their
skills (Noe, 1986).
X
3
also includes two sets of variables: (i) firm characteristics (export level, being a part of a holding, size, and
sector activity) and (ii) socio-demographic characteristics (gender, age, age square, education, wage, seniority,
occupation, and working hours).
b
1
,b
2
,b
3
,g
1
,g
2
,g
3
,d
1
,d
2
, and d
3
are slope coefficients to be estimated.
Finally, a
1
,a
2
,a
3
,m
1
,m
2
, and m
3
are the intercepts and the disturbance terms for the three equations, respectively.
Because our data provide information on multiple individuals within each organization, there is the potential
for correlation of errors across individuals within each organization. We therefore trimmed our sample and
used only a single individual respondent per firm in our estimations. As a robustness test, we conducted the
analysis with all the 10 663 observations. There is no significant difference in the results between the two
samples.
7
7
Results available from the authors.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 241
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Table 2. 3SLS estimates of the effect of environmental standards and training on labor productivity.
Variables Green (1) Training (2) Productivity (3)
Green 4.04* 0.61**
(1.56) (0.36)
Training 0.04 0.16*
(0.03) (0.05)
ISO 9000 0.27* 0.31 0.21*
(0.02) (0.42) (0.08)
Export 0.26* 0.19 0.15
(0.04) (0.47) (0.09)
Earnings 0.00 0.00 0.00*
(0.00) (0.00) (0.00)
Size 0.00* 0.00 0.00*
(0.00) (0.00) (0.00)
Holding 0.06* 0.58* 0.02
(0.03) (0.15) (0.04)
Wage 0.00** 0.01 0.01*
(0.00) (0.01) (0.00)
Gender 0.01 1.04* 0.13***
(0.03) (0.14) (0.06)
Age 0.00** 0.03* 0.00
(0.00) (0.01) (0.00)
Education 0.00 0.11* 0.01
(0.00) (0.04) (0.01)
Management position 0.06* 0.22 0.04
(0.03) (0.24) (0.05)
Blue-collar worker 0.00 0.10 0.03
(0.04) (0.15) (0.03)
Seniority 0.00* 0.05* 0.01**
(0.00) (0.001) (0.00)
Working hours 0.00 0.02** 0.00
(0.00) (0.01) (0.00)
Client supply center 0.03*
(0.01)
Client call center 0.08*
(0.02)
Informal 0.43*
(0.12)
Agri-food 0.01 0.72* 0.07
(0.03) (0.25) (0.06)
Consumption goods 0.09* 0.02 0.13*
(0.03) (0.28) (0.06)
Cars and equipment 0.00 0.23 0.08**
(0.02) (0.23) (0.05)
Energy 0.33* 0.17 0.15
(0.07) (0.82) (0.17)
Construction 0.02 0.21 0.03
(0.03) (0.25) (0.05)
Commercial 0.03 0.27 0.03
(0.02) (0.21) (0.04)
Transport 0.09* 0.84* 0.08
(0.03) (0.29) (0.07)
Financial and real estate 0.01 1.53* 0.84*
(0.06) (0.45) (0.12)
(Continues)
242 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Results
We present the results of the 3SLS estimation in Tables 2 and 3. In the first column, we present the model of the
determinants of environmental standards adoption; in the second column, the determinants of employee training
or interpersonal contacts; and in the third column, the determinants of labor productivity.
Adoption of environmental standards
We first present the estimation results regarding the factors that may influence firms to adopt environmental
standards (column 1 of Tables 2 and 3). As expected, the variables representing the adoption of ISO 9000—export
level,size and holding—are significant predictors for the adoption of environmental standards, and these results
confirm the findings of previous studies (e.g., Delmas & Montes-Sancho, 2011; Delmas & Montiel, 2009; Grolleau,
Mzoughi, & Pekovic, 2007).
The variables training and interpersonal contacts are not significant in this first stage. As expected, our
instrumental variables are positive and significant determinants of the adoption of environmental standards. Firms
in the energy and consumption goods sectors are also more likely to adopt environmental standards.
Regarding employee characteristics, as expected, wage is positively associated with the adoption of environmen-
tal standards.
Training and interpersonal contacts
We present the results of the determinants of training in the second column of Table 2 and of interpersonal contacts
in the second column of Table 3. Our results indicate that the adoption of environmental standards improves
employee training, because the coefficient of environmental standards on training is positive and significant
(p<.10). Similarly, the implementation of environmental standards is found to be positively and significantly
associated with interpersonal contacts improvement (p<.10).
Concerning the effect of the control variables on training, the variables holding,education,seniority, and working
hours have a positive and significant effect on training, whereas management position and age have a negative
association with training. Furthermore, women tend to obtain less training than men.
Table 2. (Continued)
Variables Green (1) Training (2) Productivity (3)
Business services 0.11* 0.62* 0.05
(0.02) (0.27) (0.06)
Individual services 0.03 0.74* 0.26*
(0.04) (0.31) (0.07)
Constant 0.11 2.94* 2.79***
(0.11) (0.54) (0.20)
Fstatistic 43.14 16.92 30.65
p0.00 0.00 0.00
Observations 4929 4929 4929
*Parameter significance at the 1 per cent level.
**Parameter significance at the 10 per cent level.
***Parameter significance at the 5 per cent level.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 243
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Table 3. 3SLS estimates of the effect of environmental standards and interpersonal contacts on labor productivity.
Variables Green (1) Interpersonal contacts (2) Productivity (3)
Green 1.98* 0.82**
(1.12) (0.37)
Interpersonal contacts 0.05 0.21**
(0.04) (0.09)
ISO 9000 0.25** 0.23 0.21**
(0.02) (0.30) (0.09)
Export 0.24** 0.24 0.17
(0.03) (0.33) (0.10)
Earnings 0.00 0.00 0.00**
(0.00) (0.00) (0.00)
Size 0.00** 0.00* 0.00**
(0.00) (0.00) (0.00)
Holding 0.05** 0.15 0.04
(0.02) (0.10) (0.04)
Wage 0.01* 0.06** 0.00
(0.00) (0.01) (0.01)
Gender 0.02 0.85** 0.15*
(0.04) (0.10) (0.08)
Age 0.00* 0.01** 0.00
(0.00) (0.01) (0.00)
Education 0.01 0.14** 0.00
(0.01) (0.02) (0.01)
Management 0.02 0.70** 0.14*
(0.03) (0.17) (0.08)
Blue-collar worker 0.05 1.13** 0.23**
(0.05) (0.11) (0.10)
Seniority 0.00** 0.02** 0.00
(0.00) (0.01) (0.00)
Working hours 0.00 0.06** 0.01
(0.00) (0.01) (0.00)
Client supply center 0.03**
(0.01)
Client call center 0.07**
(0.01)
Informal 0.31**
(0.08)
Agri-food 0.03 0.02 0.05
(0.02) (0.18) (0.05)
Consumption goods 0.08** 0.07 0.12*
(0.03) (0.20) (0.06)
Cars and equipment 0.00 0.14 0.08
(0.02) (0.16) (0.05)
Energy 0.30** 0.42 0.21
(0.07) (0.58) (0.18)
Construction 0.00 0.53** 0.11
(0.03) (0.18) (0.07)
Commercial 0.02 0.27* 0.04
(0.02) (0.15) (0.05)
Transport 0.11** 0.13 0.02
(0.03) (0.21) (0.06)
Financial and real estate 0.05 0.45 0.98**
(0.05) (0.32) (0.10)
(Continues)
244 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Regarding the impact of the control variables on interpersonal contacts, the variables education, wage,
management position, seniority, and working hours are positively and significantly associated with interpersonal
contacts, whereas size and age as well as blue-collar workers and women are associated with less interpersonal
contacts.
The results reveal that some sectors are more sensitive to training or interpersonal contacts. More precisely, being
a part of agri-food; transport; financial and real estate; and services sectors increases the probability of training.
Being a part of consumption goods; financial and real estate; and business service sectors increases the probability
of interpersonal contacts improvement. Finally, our instrumental variable informal has a positive and statistically
significant effect on training and interpersonal contacts.
Labor productivity
Third, we analyze the effect of the adoption of environmental standards on labor productivity (column 3 of Tables 2
and 3). The coefficient of the variable green on labor productivity is positive and statistically significant (p<.05
and p<.001, respectively) in Tables 2 and 3. The effect is quite large because the adoption of environmental standards
is associated with a change in almost one standard deviation of the labor productivity variable in Table 2 and 1.28
standard deviation in Table 3. This corresponds to a 16% increase above the average labor productivity in Table 2
and a 21% increase in Table 3. Hence, the main hypothesis of the paper—which is firms that have adopted
environmental standards are associated with higher labor productivity than firms that have not adopted environmental
standards—is confirmed by our results. Moreover, we obtained similar results concerning the effect of employee
training and interpersonal contacts on labor productivity.
The estimated coefficients of training and interpersonal contacts are positive and significant; we may conclude
that training and interpersonal contacts are positively associated to labor productivity improvement. As we also find
that environmental standards predict the adoption of training and interpersonal contacts, our results confirm
Hypotheses 2 and 3 on the mediating effect of training and interpersonal contacts on the relationship between
environmental standards and labor productivity.
Turning to the control variables, our findings are in line with those of the previous literature regarding earnings
and wages, which we found, generally, to have a positive influence on labor productivity, whereas size decreases
labor productivity (e.g., Conti, 2005; Pfeffer & Langton, 1993; Zwick, 2004). Interestingly, we find a negative
relationship between ISO 9000 standard and labor productivity. This is consistent with other studies that found
that ISO 9000 certification has no explanatory power on productivity and that this standard could potentially
reduce employees’flexibility and impede creativity because of its formal procedures (Levine & Toffel, 2010;
Martinez-Costa, Martinez-Lorente, & Choi, 2008).
Table 3. (Continued)
Variables Green (1) Interpersonal contacts (2) Productivity (3)
Business services 0.12** 0.19 0.11*
(0.02) (0.19) (0.06)
Individual services 0.03 0.63** 0.28**
(0.04) (0.22) (0.09)
Constant 0.23 4.80*** 2.24**
(0.22) (0.39) (0.45)
Fstatistic 44.53 64.34 26.09
p0.00 0.00 0.00
Observations 4929 4929 4929
*Parameter significance at the 10 per cent level.
**Parameter significance at the 1 per cent level.
***Parameter significance at the 5 per cent level.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 245
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
We conducted several robustness tests. As we mentioned earlier, the estimation was performed on the 10 663
observations and yielded similar results. We also ran a simpler model including only firm-level variables. The effect
of the variable green on labor productivity was also positive and significant (p<.01) but with a larger coefficient.
The results that we presented in this paper are therefore more conservative.
8
Discussion and Conclusion
Although the literature has focused on the impact of environmental practices on firm financial performance, little is
known about the impact of environmental practices on employees’outcomes, especially on labor productivity. The
subject is of great importance, especially if we consider that labor productivity is a crucial organizational outcome
that indicates the extent to which a firm’s labor force is efficiently creating output (Huselid, 1995).
The purpose of this study was to propose a richer conceptualization of the links between the firm’s commitment to
the environment—witnessed through the implementation of voluntary environmental standards—and employee
behavior. We propose several mechanisms that link the adoption of environmental standards to labor productivity.
We argue that employees may be more committed to firms that have adopted environmental standards, but that such
standards might also result in organizational changes, such as more training and better interpersonal contacts, that
may also contribute to labor productivity.
The main hypothesis of the paper, namely, that greener firms are associated with higher labor productivity, is
confirmed by our results. These findings are consistent with studies that have argued that a firm’s involvement in
social causes (such as improvement of environmental reputation) generally enhances a firm’s reputation, which leads
to a positive impact on employee work attitudes (e.g., Brekke & Nyborg, 2008; Hess et al., 2002; Peterson, 2004).
Furthermore, our study demonstrates that the adoption of environmental standards is associated with increased
employee training and interpersonal contacts, which in turn contribute to improved labor productivity. We argue that
increased communication among workers with diverse capabilities can lead to knowledge transfer and innovation.
This is consistent with the innovation literature, which shows that the integration of divergent thoughts and perspec-
tives enables teams to solve problems and leverage opportunities, and is a critical antecedent of innovation and
productivity (Barczak, Lassk, & Mulki, 2010; Hamilton et al., 2003). We also argued that enhanced interpersonal
contacts can lead to an improved work environment and increased productivity. This is also in line with the literature
showing how group characteristics, and social interactions impact organizational outcomes (Liden, Wayne, &
Sparrowe, 2000; Parker & Wall, 1998).
These results are also consistent with the literature on high-performance work systems, which have been shown to
increase labor productivity (Guthrie, 2001; Way, 2002). The adoption of environmental standards enhances work
practices and can create a virtuous circle of positive interactions between the organization and its employees.
Policymakers and supporters of voluntary standards can emphasize these benefits in order to encourage firms to
adopt environmental standards. Our findings suggest new ways of achieving the Porter hypothesis’promise of a
positive relationship between environmental practices and financial performance. They indicate that a firm’s social
orientation may not only lead to environmental improvements but can also act as an enhancement tool designed to
improve work systems.
This study makes several contributions. First, we tested the effect of environmental standards on labor productiv-
ity and provided a much-needed analysis in an area of inquiry where there is limited empirical work. We used a rich
and large database that allowed us to control for both firm and employee characteristics in order to provide a robust
test of our hypotheses. Second, we described and tested several mechanisms by which the adoption of environmental
8
Results available from the authors.
246 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
standards may be related to labor productivity. Third, we integrated concepts from both the organizational behavior
and the business and environment literatures, potentially enriching both areas of inquiry.
This paper is, or course, not without limitations. First, our analysis was limited to the French context, and future
research should explore similar questions in an international setting, because scholars have identified international
institutional differences regarding the implementation of environmental practices (Delmas & Montes-Sancho,
2011; Delmas & Montiel, 2008). Second, scholars should examine whether the effects identified in this study
persist over time. Although our database included a rich set of variables that allowed us to control for many or-
ganizational and individual characteristics, its cross-sectional nature hindered the completion of such an analysis.
Our database allowed us to identify important associations between variables, but a longitudinal analysis would be
better suited to tease out long-term causal effects. Third, because the survey instrument was not designed specif-
ically for our study, further research could add variables that more clearly isolate our constructs. For example, the
training variable included general training as well as environmental training, and further research could separate
both to test their relationship. We introduced a comprehensive indicator for interpersonal contact that includes
nine different items ranging from the amount of contact and number of colleagues involved to the type of
interactions. However, further research could include perceptions of conflicts between individuals or among teams
in such an indicator.
Fourth, whereas we focused primarily on training and interpersonal contacts, future research should test whether
additional mechanisms might affect employees’outcomes. The literature so far has focused mostly on the impact of
the adoption of corporate social responsibility practices at the macro-level, and our research opens the path to inves-
tigate the more micro-organizational impacts of the adoption of such practices. Scholars could, for example, test the
effect of environmental standards on safety, stress, or employee absenteeism. Future research could also better
evaluate organizational commitment such as organizational citizenship behavior and organizational identification
(Evans, Davis, & Frink, 2011). In our research, we hypothesized a positive relationship between interpersonal
contacts and organizational commitment. However, research has shown that an overload of interpersonal contacts
could lead to stress and lower organizational commitment (Leiter & Maslach, 1988). Additional research could test
the relationship between environmental standards, interpersonal contacts, and job burnout or stress in the organization.
Finally, the literature argues that corporate social performance consists of many dimensions, including environ-
mental impact, and also community investment and outreach, support for diversity in the workplace, employee
involvement, and benefits (Chen & Delmas, 2011). Hence, it would be interesting to examine the impact of various
environmental and social dimensions on these employee indicators.
Acknowledgement
Sanja Pekovic gratefully acknowledges the financial support for this work from the AFNOR “Performance des
Organisations”endowment in collaboration with the Paris-Dauphine Foundation.
Author biographies
Magali A. Delmas is a Professor of Management at the UCLA Anderson School of Management and the Institute of the
Environment and sustainability. She has written more than 50 articles, book chapters, and case studies in the area of busi-
ness and the natural environment.
Sanja Pekovic is a researcher at the University of Paris Dauphine (DRM-CNRS-UMR 7088). She is conducting
research on quality and environmental management, the economics of innovation, and applied econometrics.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 247
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
References
Abrahamson, E., & Rosenkopf, L. (1997). Social network effects on the extent of innovation diffusion: A computer simulation.
Organization Science,8(3), 289–309. DOI: 10.1287/orsc.8.3.289
Aerts, W., Cormier, D., & Magnan, M. (2008). Corporate environmental disclosure, financial markets and the media: An inter-
national perspective. Ecological Economics,64(3), 643–659. DOI: 10.1016/j.ecolecon.2007.04.012
Ambec, S., & Lanoie, P. (2008). When and why does it pay to be green. Academy of Management Perspective,23,45–62.
Anderson, E. W., Fornell, C., & Rust, R. (1997). Customer satisfaction, productivity, and profitability: Differences between good
and services. Marketing Science,16(2), 129–145.
Anton, W. R. Q., Deltas, G., & Khanna, M. (2004). Incentives for environmental self-regulation and implications for environmen-
tal performance. Journal of Environmental Economics and Management,48, 632–654. DOI: 10.1016/j.jeem.2003.06.003
Arimura, T. H., Darnall, D., & Katayama, H. (2011). Is ISO 14001 a gateway to more advanced voluntary action? The case of
green supply chain management. Journal of Environmental Economics and Management,61(2), 170–182. DOI:
10.1016/j.jeem.2010.11.003
Banker, R. E., Field, J. M., Schroeder, R. G., & Sinha, K. K. (1996). Impact of work teams on manufacturing performance:
A longitudinal field study. Academy of Management Journal,39(4), 867–890.
Barczak, G., Lassk, F., & Mulki, J. (2010). Antecedents of team creativity: An examination of team emotional intelligence, team
trust and collaborative culture. Creativity & Innovation Management,19(4), 332–345.
Barla, P. (2007). ISO 14001 certification and environmental performance in Quebec’s pulp and paper industry. Journal of
Environmental Economics and Management,53(3), 291–306. DOI: 10.1016/j.jeem.2006.10.004
Barth, E. (1997). Firm-specific seniority and wages. Journal of Labor Economics,15(1), 459–506.
Batt, R. (2004). Who benefits from teams? Comparing workers, supervisors and managers. Industrial Relations,43(1), 183–212.
Becker, G. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. New York, NY:
Columbia University Press.
Blunch, N.-H., & Castro, P. (2007). Enterprise-level training in developing countries: do international standards matter?
International Journal of Training and Development,11(4), 314–324.
Brammer, S., Millington, A., & Rayton, B. (2010). The contribution of corporate social responsibility to organizational commitment.
International Journal of Human Resource Management,18(10), 701–1719. DOI: 10.1080/09585190701570866
Brekke, K. A., & Nyborg, K. (2008). Attracting responsible employees: Green production as labor market screening. Resource
and Energy Economics,30(4), 509–526. DOI: 10.1016/j.reseneeco.2008.05.001
Burks, S., Carpenter, J., & Goette, L. (2009). Performance pay and the erosion of worker cooperation: Field experimental
evidence. Journal of Economics and Behavior Organization,70, 458–469. DOI: 10.1016/j.jebo.2008.02.012
Chen, C.-M., & Delmas, M. (2011). Measuring corporate social responsibility: An efficiency perspective. Production and
Operations Management,20(6), 789–804.
Christmann, P. (2000). Effects of “best practices”of environmental management on cost advantage: The role of complementary
assets. Academy of Management Journal,43(4), 663–680.
Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research,
16,64–73.
Cohen, D., & Prusak, L. (2001). In good company: How social capital makes Organizations Work. Cambridge, MA: Harvard
Business Press.
Conti, G. (2005). Training, productivity and wages in Italy. Labor Economics,12, 557–576. DOI: 10.1016/j.labeco.2005.05.007
Corbett, C. J., & Kirsch, D. A. (2001). International diffusion of ISO 14000 certification. Production and Operations Management,
10, 327–342. DOI: 10.1111/j.1937-5956.2001.tb00378.x
Corbett, C. J., & Luca, A. (2002). Global survey on ISO 9000 and ISO 14000: Summary of findings. Unpublished manuscript,
The Anderson School, University of California at Los Angeles, Los Angeles, California.
Darnall, N., Gallagher, D. R., Andrews, R. N. L., & Amaral, D. (2000). Environmental management systems: Opportunities for
improved environmental and business strategy? Environmental Quality Management,9(3), 1–9. DOI: 10.1002/1520-6483(200021)
Darnall, N., Henriques, I., & Sadorsky, P. (2010). Adopting proactive environmental practices: The influence of stakeholders and
firm size. Journal of Management Studies,47(6), 1072–1094. DOI: 10.1111/j.1467-6486.2009.00873.x
Dearden, L., Reed, H., & Van Reenen, J. (2006). The impact of training on productivity and wages: Evidence from British panel
data. Oxford Bulletin of Economics and Statistics,68(4), 397–421. DOI: 10.1111/j.1468-0084.2006.00170
Delmas, M. (2000). Barriers and incentives to the adoption of ISO 14001 in the United States. Duke Environmental Law and
Policy Forum,Fall:1–38.
Delmas, M. (2001). Stakeholders and competitive advantage: The case of ISO 14001. Production and Operation Management,
10(3), 343–358. DOI: 10.1111/j.1937-5956.2001.tb00379.x
Delmas, M. (2002). The diffusion of environmental management standards in Europe and in the United States: An institutional
perspective. Policy Sciences,35(1), 91–119. DOI: 10.1023/A:1016108804453
248 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Delmas, M., & Grant, L. (2010). Eco-labeling strategies and price-premium: The wine industry puzzle. Business & Society.
http://bas.sagepub.com/content/early/2010/03/04/0007650310362254.full.pdf+html. DOI: 10.1177/0007650310362254
Delmas, M., & Montes-Sancho, M. (2011). An institutional perspective on the diffusion of international management
system standards: The case of the environmental management standard ISO 14001. Business Ethics Quarterly,21(1), 103–132.
Delmas, M., & Montiel, I. (2008). The diffusion of voluntary international management standards: Responsible care, ISO 9000
and ISO 14001 in the chemical industry. Policy Studies Journal,36(1), 65–93. DOI: 10.1111/j.1541-0072.2007.00254.x
Delmas, M., & Montiel, I. (2009). Greening the supply chain: When is customer pressure effective? Journal of Economics and
Management Strategy,18(1), 171–201. DOI: 10.1111/j.1530-9134.2009.00211.x
Delmas, M., & Toffel, M. (2008). Organizational responses to environmental demands: Opening the Black Box. Strategic
Management Journal,29(10), 1027–1055.
Delmas, M., & Young, O. 2009. Governance for the environment: New perspectives. Edited volume. Cambridge, MA:
Cambridge University Press.
Denton, K. D. (1999). Employee involvement, pollution control and pieces to the puzzle. Environmental Management and
Health,10(2), 105–111.
Dutton, J. E., Dukerich, J. M., & Harquail, C. V. (1994). Organizational images and member identification. Administrative
Science Quarterly,39, 239–263.
Eriksson, C., & Jacoby, S. (2003). The effects of employer networks on workplace innovation and training. Industrial & Labor
Relations Review,56(2), 203–223.
Evans, W. R., Davis, W. D., & Frink, D. D. (2011). An examination of employee reactions to perceived corporate citizenship.
Journal of Applied Social Psychology,41(4), 938–964.
Florida, R., & Davidson, D. (2001). Gaining from green management: Environmental management systems inside and outside the
factory. California Management Review,43(3), 64–84.
Frank, R. H. (2003). What price the moral high ground? Ethical dilemmas in competitive environments. Princeton, NJ: Princeton
University Press.
Frazis, H., Gittleman, M., & Joyce, M. (2000). Correlates of training: An analysis using both employer and employee character-
istics. Industrial & Labor Relations Review,53, 443–462.
Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal,17(Special Issue), 109–122.
Greening, D. W., & Turban, D. B. (2000). Corporate social performance as a competitive advantage in attracting a quality work-
force. Business & Society,39, 254–280. DOI: 10.1177/000765030003900302
Grolleau, G., Mzoughi, N., & Pekovic, S. (2007). Chemical firms’registration for the responsible care program and the ISO
14001 standard: A comparative approach. Economics Bulletin,12,1–13.
Grolleau, G., Mzoughi, N., & Pekovic, S. (2012). Green not (only) for profit: An empirical examination of the effect of environ-
mental-related standards on employees’recruitment. Resource and Energy Economics,34(1), 74–92.
Grolleau, G., Mzoughi, N., & Thomas, A. (2007). What drives agrifood firms to register for an environmental management
system? European Review of Agriculture Economic,34,1–23. DOI: 10.1093/erae/jbm012
Guthrie, J. (2001). High-involvement work practices, turnover, and productivity: Evidence from New Zealand. Academy of
Management Journal,44(1), 180–190.
Hamilton, B. H., Nickerson, J. A., & Hideo, O. (2003). Team incentives and worker heterogeneity: An empirical analysis of the
impact of teams on productivity and participation. Journal of Political Economy,111(3), 465–97.
Hart, S. L. (1995). A natural-resource-based view of the firm. Academy of Management Review,20(4), 986–1014.
Hart, S. L. (2005). Capitalism at the crossroads: The unlimited business opportunities in solving the world’s most difficult
problems. Upper Saddle River, NJ: Wharton School Publishing.
Henriques, I., & Sadorsky, P. (1996). The determinants of an environmentally responsive firm: An empirical approach. Journal of
Environmental Economics and Management,30, 381–395. DOI: 10.1006/jeem.1996.0026
Hess, D., Rogovsky, N., & Dunfee, T. (2002). The next wave of corporate community involvement: Corporate social initiatives.
California Management Review,44(2), 110–125.
Hopkins, K. (2005). Supervisor support and work–life integration: A social identity perspective. In E. E. Kossek, & S. J. Lambert
(Eds.), Work and life integration: Organizational, cultural and individual perspectives (pp. 445–468). Mahwah, NJ: Erbaum.
Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial
performance. Academy of Management Journal,38, 635–672.
ISO. (1996). Retrieved from www.iso.org
Jackson, S. E., Renwick, D. W. S., Jabbour, C. J. C., & Muller-Camen, M. (2011). State-of-the-art and future directions for green
human resource management: Introduction to the special issue. Zeitschrift für Personalforschung (German Journal of
Research in Human Resource Management),25(2), 99–116.
Jennings, P. D., Cyr, D., & Moore, L. F. (1995). Human resource management on the Pacific Rim: An integration. In L. F. Moore,
& P. D. Jennings (Eds.), Human resource management on the Pacific Rim: Institutions, practices, and attitudes (pp. 351–379).
Berlin: de Gruyter.
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 249
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Jones, C., & Hamilton Volpe, E. (2011). Organizational identification: Extending our understanding of social identities through
social networks. Journal of Organizational Behavior,32, 413–434. DOI: 10.1002/job.694
Khanna, M., & Anton, W. R. (2002). Corporate environmental management: Regulatory and market-based incentives. Land
Economics,78(4), 539–558.
Khanna, M., & Damon, L. A. (1999). EPA’s voluntary 33/50 program: Impact on toxic releases and economic performance of
firms. Journal of Environmental Economics and Management,37(1), 1–25. DOI: 10.1006/jeem.1998.1057
King, A., & Lenox, M. (2002). Exploring the locus of profitable pollution reduction. Management Science,48(2), 289–299.
doi: 10.1287/mnsc.48.2.289.258
Koch, M. J., & McGrath, R. G. (1996). Improving labor productivity: Human resource management policies do matter. Strategic
Management Journal,17(5), 335–354. DOI: 10.1002/(SICI)1097-0266(199605)17:5<335::AID-SMJ814>3.0.CO;2-R
Koh, H. C., & Boo, E. H. Y. (2001). The link between organizational ethics and job satisfaction: A study of managers in
Singapore. Journal of Business Ethics,29, 309–324. DOI: 10.1023/A:1010741519818
Konar, S., & Cohen, M. A. (2001). Does the market value environmental performance? The Review of Economics and Statistics,
83(2), 281–289. DOI: 10.1162/00346530151143815
Krueger, A., & Schkade, D. (2008). Sorting in the labor market: Do gregarious workers flock to interactive jobs? Journal of
Human Resources,43, 859–883.
Lanfranchi, J., & Pekovic, S. (2010). How green is my firm? Worker well-being and job involvement in environmentally related
certified firms. Working paper. Noisy-le-Grand, France: CEE.
Leiter, M. P., & Maslach, C. (1988). The impact of interpersonal environment on burnout and organizational commitment.
Journal of Organizational Behavior,9, 297–308.
Levine, D. I., & Toffel, M. W. (2010). Quality management and job quality: How the ISO 9001 standard for quality management
systems affects employees and employers. Management Science,56(6), 978–996. DOI: 10.1287/mnsc.1100.1159
Liden, R. C., Wayne, S. J., & Sparrowe, R. T. (2000). The examination of the mediating role of psychological empowerment on
the relations between the job, interpersonal relationships, and work outcomes. Journal of Applied Psychology,85, 407–416.
Liebler, C. A., & Sandefur, G. D. (2002). Gender differences in the exchange of social support with friends, neighbors, and
co-workers at midlife. Social Science Research,31, 364–391. DOI: 10.1016/S0049-089X (02)00006-6
Lynch, L. M. (1994). Training and the Private Sector, NBER Comparative Labor Market Series. Chicago, IL: University of
Chicago Press.
Lynch, L. M., & Black, S. E. (1998). Beyond the incidence of employer-provided training. Industrial & Labor Relations Review,
52,64–81.
Maddala, G. S. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge, MA: Cambridge University
Press.
Margolis, J., & Walsh, J. (2003). Misery loves companies: Rethinking social initiatives by business. Administrative Science
Quarterly,48(2), 268–305.
Martinez-Costa, M., Martinez-Lorente, A. R., & Choi, T. Y. (2008). Simultaneous consideration of TQM and ISO 9000 on
performance and motivation: An empirical study of Spanish companies. International Journal of Production Economics,
113(1), 23–39.
McManus, M., & Sanders, L. (2001). Integrating an environmental management system into a business and operating culture:
The real value of an EMS. Pollution Engineering,33(5), 24–27.
Medoff, J., & Abraham, K. (1980). Experience, performance and earnings. Quarterly Journal of Economics,95, 703–736.
Mohrman, S. A., & Novelli, Jr. L. (1985). Beyond testimonials: Learning from a quality circles programme. Journal of
Occupational Behavior,6(2), 93–110.
Morrow, D., & Rondinelli, D. A. (2002). Adopting environmental management systems: Motivations and results of ISO 14001
and EMAS certification. European Management Journal,20(2), 159–171. DOI: 10.1016/S0263-2373(02)00026-9
Nakamura, M., Takahashi, T., & Vertinsky, I. (2001). Why Japanese firms choose to certify: A study of managerial responses to
environmental issues. Journal of Environmental Economics and Management,42,23–52. DOI: 10.1006/jeem.2000.1148
Nash, J., & Ehrenfeld, J. (1997). Codes of environmental management practice: Assessing their potential as tools for change.
Annual Review of Energy and Environment,22, 487–535. DOI: 10.1146/annurev.energy.22.1.487
Nishitani, K. (2009). An empirical study of the initial adoption of ISO 14001 in Japanese manufacturing firms. Ecological
Economics,68(3), 669–679. DOI: 10.1016/j.ecolecon.2008.05.023
Noe, R. A. (1986). Trainee attributes and attitudes: Neglected influences of training effectiveness. Academy of Management
Review,11, 736–749.
Oh’Eocha, M. (2000). A study of the influence of company culture, communications and employee attitudes on the use of 5S for
environmental management at Cooke Brothers Ltd. The TQM Magazine,12(5), 321–330.
Orlitsky, M., Schmidt, F., & Rynes, S. (2003). Corporate social and financial performance: A metaanalysis. Organization Studies,
24, 403–441.
Orsato, R. J. (2006). Competitive environmental strategies: When does it pay to be green? California Management Review,48(2), 127–143.
250 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
Parker, S. K., & Wall, T. D. (1998). Job and work design: Organizing work to promote well-being and effectiveness.SanFrancisco,
CA: Sage.
Pekovic, S. (2010). The determinants of ISO 9000 certification: A comparison of the manufacturing and service sectors. Journal
of Economic Issues,44(4), 895–914. DOI: 10.2753/JEI0021-3624440403
Perez, O., Amichai-Hamburger, Y., & Shterental, T. (2009). The dynamic of corporate self-regulation: ISO 14001, environmental
commitment, and organizational citizenship behavior. Law & Society Review,43(3), 593–630.
Peterson, D. K. (2004). The relationship between perceptions of corporate citizenship and organizational commitment. Business
& Society,43, 296–319. DOI: 10.1177/0007650304268065
Pfeffer, J. (1994). Competitive advantage though people. Boston, MA: Harvard Business School.
Pfeffer, J., & Langton, N. (1993). The effect of wage dispersion on satisfaction, productivity, and working collaboratively:
Evidence from College and University Faculty. Administrative Science Quarterly,38(3), 382–407.
Pindyck, S. R., & Rubinfeld, D. L. (1991). Econometric models and economic forecasts. New York, NY: McGraw-Hill.
Porter, M. E. (1985). Competitive advantage. New York, NY: The Free Press.
Porter, M. E., & Van Der Linde, C. (1995). Toward a new conception of the environment–competitiveness relationship. Journal
of Economic Perspectives,9(4), 97–118.
Ramus, C. A., & Steger, U. (2000). The roles of supervisory behaviors and environmental policy in employee ‘ecoinitiatives’at
leading edge European companies. Academy of Management Journal,43, 605–626.
Rennison, L. W., & Turcotte, J. (2004). Productivity and wages: Measuring the effect of human capital and technology use from
linked employer–employee data. Working paper. Department of Finance, Economic and Fiscal Policy Branch. Canada, No.
2004-01.
Rondinelli, D., & Vastag, G. (2000). Panacea, common sense, or just a label? The value of ISO 14001 environmental manage-
ment systems. European Management Journal,18(5), 499–510. DOI: 10.1016/S0263-2373(00)00039-6
Rothenberg, S. (2003). Knowledge content and worker participation in environmental management at NUMMI. Journal of
Management Studies,40(7), 1783–1802.
Salis, S., & Williams, A. M. (2010). Knowledge sharing through face-to-face communication and labor productivity: Evidence
from British workplaces. British Journal of Industrial Relations,48(2), 436–459. DOI: 10.1111/j.1467-8543.2009.00762.x
Sammalisto, K., & Brorson, T. (2008). Training and communication in the implementation of environmental management
systems (ISO 14001). A case study at the University of Gävle, Sweden. Journal of Cleaner Production,16, 299–309.
doi: 10.1016/j.jclepro.2006.07.029
Schuler, R. S., & Jackson, S. E. (1987). Linking competitive strategies with human resource management practices. The Academy
of Management Executive,1(3), 207–219.
Schultz, T. (1961). Investment in human capital. American Economic Review,51,1–17.
Shrivastava, P. (1995). Environmental technologies and competitive advantage. Strategic Management Journal,16, 183–200.
DOI: 10.1002/smj.4250160923
Sousa-Poza, A., & Ziegler, A. (2003). Asymmetric information about workers’productivity as a cause for inefficient long
working hours. Labour Economics,10(6), 727–747.
Toffel, M. (2000). Anticipating greener supply chain demands: One Singapore company’s journey to ISO 14001. In R. Hillary
(Ed.), ISO 14001: Case studies and practical experiences. Sheffield: Greenleaf Publishing.
Torgler, B., & Garcia-Valinas, M. A. (2007). The determinants of individuals’attitudes towards preventing environmental
damage. Ecological Economics,63, 536–552. DOI: 10.1016/j.ecolecon.2006.12.013
Turban, D. B., & Greening, D. W. (1997). Corporate social performance and organizational attractiveness to prospective
employees. Academy of Management Journal,40, 658–672.
Veum, J. R. (1993). Training among young adults: Who, what kind, and for how long? Monthly Labor Review,116(8), 27–32.
Viswesvaran, C., Deshpande, S. P., & Joseph, J. (1998). Job satisfaction as a function of top management support for ethical
behaviour. Journal of Business Ethics,17, 365–371. DOI: 10.1023/A:1017956516324
Way, S. A. (2002). High performance work systems and intermediate indicators of firm performance within the US small business
sector. Journal of Management,28(6), 765–785.
Welch, E. W., Mori, Y., & Aoyagi-Usui, M. (2002). Voluntary adoption of ISO 14001 in Japan: Mechanisms, stages and effects.
Business Strategy and the Environment,11,43–62.
Welford, R. (1998). Corporate environmental management 1. London: Earthscan Publications.
Zwick, T. (2004). Employee participation and productivity. Labor Economics,11, 715–740. DOI: 10.1016/j.labeco.2004.02.001
Zyglidopoulos, S. C. (2002). The social and environmental responsibilities of multinationals: Evidence from the Brent Spar.
Journal of Business Ethics,36(1/2), 141–151. DOI: 10.1023/A:1014262025188
ENVIRONMENTAL STANDARDS AND LABOR PRODUCTIVITY 251
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job
APPENDIX 1
PEARSON CORRELATION COEFFICIENTS
Labor
productivity Green Training
Interpersonal
contacts
Client
call
center
Client
supply
center Informal
ISO
9000 Export Earnings Size Holding Gender Age Education Wage Seniority Management
Blue-
collar
worker
Working
hours
Labor
productivity
1.00 —— — —— ———————— — — — — — —
Green 0.10* 1.00 — — —— ———— ———— — — — — — —
Training 0.12* 0.12* 1.00 — —— ———————— — —— — — —
Interpersonal
contacts
0.13* 0.03 0.23* 1.00 —— —————————— — — — — —
Client call
center
0.09* 0.17* 0.07* 0.06* 1.00 ————————— — —— — — —
Client supply
center
0.12* 0.13* 0.08* 0.08* 0.21* 1.00 ———————— — —— — — —
Informal 0.09* 0.04 0.11* 0.10* 0.08* 0.05* 1.00 ——————— — —— — — —
ISO 9000 0.11* 0.38* 0.16* 0.07* 0.30* 0.11* 0.08* 1.00 —————— — —— — — —
Export 0.20* 0.24* 0.11* 0.05* 0.16* 0.04* 0.08* 0.24* 1.00 ———————— — ——
Earnings 0.15* 0.09* 0.03 0.05* 0.03 0.07 0.02 0.04* 0.03 1.00 ——————— — ——
Size 0.04* 0.13* 0.05* 0.04* 0.05* 0.09* 0.03 0.08* 0.05* 0.75* 1.00 —————— — ——
Holding 0.17* 0.17* 0.15* 0.11* 0.18* 0.17* 0.11* 0.24* 0.20* 0.04* 0.08* 1.00 ————— — ——
Gender 0.04* 0.03* 0.15* 0.14* 0.08* 0.04* 0.20* 0.13* 0.05* 0.00 0.01 0.02 1.00 ———— — ——
Age 0.02 0.05* 0.00 0.02 0.03 0.02 0.00 0.07* 0.07* 0.01 0.01 0.04 0.03 1.00 ——— — ——
Education 0.22* 0.00 0.07* 0.32 0.02 0.10* 0.08* 0.01 0.04* 0.07* 0.05 0.09* 0.07* 0.32* 1.00 —— — — —
Wage 0.30* 0.08* 0.11* 0.41* 0.07* 0.11* 0.09* 0.08* 0.13* 0.07* 0.06* 0.15* 0.14* 0.22* 0.41* 1.00 ————
Seniority 0.06* 0.12* 0.09* 0.04* 0.05* 0.01 0.05* 0.11* 0.14* 0.00 0.01 0.08* 0.03 0.63* 0.28* 0.14* 1.00 ———
Management 0.20* 0.00 0.06* 0.36* 0.05* 0.07* 0.08* 0.02 0.05* 0.08* 0.08* 0.11* 0.09* 0.09* 0.47* 0.66* 0.01 1.00 ——
Blue-collar
worker
0.12* 0.04* 0.02 0.29* 0.09* 0.11* 0.05* 0.13* 0.08* 0.04* 0.04* 0.04* 0.30* 0.04 0.50* 0.33* 0.06* 0.35* 1.00 —
Working
hours
0.16* 0.02 0.08* 0.30* 0.07* 0.02 0.06* 0.03 0.02 0.04 0.03 0.04* 0.24* 0.09* 0.19* 0.40* 0.01 0.38* 0.12* 1.00
*p<.01.
252 M. A. DELMAS AND S. PEKOVIC
Copyright © 2012 John Wiley & Sons, Ltd. J. Organiz. Behav. 34, 230–252 (2013)
DOI: 10.1002/job