Public Service Motivation and Employee Participation in
Discretionary Pro-Environmental Behaviors
Justin Michael Stritch
The University of Georgia
Abstract
To what extent does Public Service Motivation (PSM) influence participation in pro-
environmental behaviors? A theoretical framework based on PSM and Organizational
Citizenship Behavior (OCB) is constructed to answer this question. The study uses data from
873 City of Charlotte employees to determine the relationship between PSM and participation in
pro-environmental behaviors. Results suggest a significant, positive relationship between PSM
and both exhibiting and encouraging pro-environmental behavior in the workplace even while
controlling for environmental attitudes.
Manuscript Prepared for
The 11th
Public Management Research Conference
The Maxwell School of Syracuse University, Syracuse, NY, June 2-4, 2011.
I would like to thank Robert K. Christensen, John Ronquillo, Derrick Andersen, Justin Bullock,
Michael Trivette, and Mary Milan for their helpful comments on previous drafts of this paper.
Additionally, I give special thanks to Gina Shell and Julie Burch at the City of Charlotte (NC) for
access to the data used in the analysis.
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Introduction
Everyday in the United States millions of public sector employees go to work. Once in
the office, some workers choose to recycle their disposable drink containers while others choose
to throw their recyclables in a waste basket next to the recycling bin. Some workers put their
lunch in the break-room refrigerator while others use a mini-fridge tucked away under their
desks. Some workers turn their printer setting to duplex and print on both sides, while others
take no steps to reduce the amount of paper they use. Why do only some employees act in an
environmentally friendly, or “green,” manner? The variations in employee behaviors occur at a
time of growing need for resource conservation and mainstream acknowledgement of a need for
humans to limit their negative impact on the environment for long-term sustainability.
Government has been thrust into the environmental policy arena in the last thirty years as
the institution responsible for administering collective policies as they relate to the environment
(Rabe, 2006). Public organizations, however, may also take less visible steps to act as stewards
of the environment. Eco-initiatives at the employee level can reduce the sector‟s environmental
impact. Additionally, conserving resources such as water, paper, and energy may result in
saving financial resources. To date, there has not been a comprehensive study of employee
participation in voluntary pro-environmental behaviors within public organizations. The aim of
this study is to fill that void.
Why do some employees working in the same office space, or work environment, take
small steps to reduce their negative environmental impact while others do not? What are the
motivating factors for participation in pro-environmental behaviors for employees in public
organizations? In this paper I will answer these questions by looking at a central tenet of the
public management literature over the past 20 years: Public Service Motivation (PSM). I will
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examine PSM‟s influence on employee participation in pro-environmental behaviors and the
likelihood of encouraging other employees to participate in discretionary pro-environmental
behaviors.
The study is divided into four sections. The first section is a literature review, which
starts by discussing the history and development of the literature on pro-environmental behavior.
I provide a brief description of the variables and theories associated with pro-environmental
behavior and a description of a theoretical framework for the study based on PSM. The second
section comprises the research methodology employed in the study and describes the data and
statistical techniques used to test the hypotheses. The third section reports the results and
findings of the analysis. Finally, the study concludes with a discussion of the findings, focusing
on the implications for public managers.
According to the U.S. Census Bureau (2007) there were approximately three million
federal civilian employees and 15 million state and local government employees in 2007. This,
of course, does not capture the total number of individuals working in the public sphere, and
given the increasingly nebulous nature of the term “public,” the definition may be expanded to
include the number of private sector contract employees that provide a range of government
services (Bozeman, 2007). At the macro-level, government is often responsible for
implementing environmental policies, but at the micro-level, environmental stewardship can
meaningfully begin within the public sector with public servants‟ decisions to participate in
discretionary pro-environmental behaviors, creating a large, aggregated reduction in negative
environmental impacts. Understanding public employees‟ motivations for participating in pro-
environmental behavior is an essential first step in achieving these reductions.
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Public Organizations, Social Values, and Environmental Initiatives
Scholars have long discussed the various differences between public and private
management and how public values influence the decisions of public managers (Dahl, 1947;
Wamsley & Zald, 1973; Denhardt, 1981; Kirlin, 1996; Rainey, 2009). There is a governmental
obligation to promote the public interest that distinguishes public management from the private
sector and that creates the moral sense of “higher purpose” (Rosenbloom, Kravchuk, & Clerkin,
2009, p. 7). The sense of higher purpose forces public organizations to carefully consider how to
implement managerial policies ranging from hiring practices to the accountability of resource
expenditures. The expectation of responsible government should extend to the environmental
impact of day-to-day operations.
The emphasis New Public Management places on economics and efficiency (Box et al.,
2001) may give us pause to consider whether or not it is good to use public resources to promote
environmentalism within an organization where the public benefit is not so clear. However,
economy and efficiency have not prevented private sector managers from taking environmental
impacts into account. In his normative evaluation of organizational sustainability in the private
sector, Shrivastava (1995) laid out seven reasons why organizations should actively promote
sustainability: 1) To drive down operating costs by reducing ecological inefficiencies; 2) to
create a competitive advantage among green consumers; 3) to distinguish themselves by
implementing duplicable strategies in their specific industry; 4) to enhance the corporate image;
5) to reduce the risks associated with resource depletion, shifting in energy costs, and pollution
management; 6) to reduce the health risks to the community in which they operate; and 7) to
position to the organization ahead of the regulatory curve. For some organizations, achieving
ecological sustainability may become integrated into the strategic goals of the organization (p.
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955). Reducing costs, reducing health risks, and presenting a strong corporate image to the
public are just a few reasons why public managers might also consider the environmental impact
of daily operations.
Bansal and Roth (2000) identified a conceptual model of the reasons an organization
should pursue environmental initiatives. The reasons include benefits from competitiveness,
legitimacy and social responsibility, and motivating factors for corporate environmental
responsiveness. Epstein and Roy (2001) concluded that organizations should look to local social
and environmental issues to serve as the external drivers of the “corporate strategy,” and can be
used to identify relevant stakeholders and incorporate environmental performance measures into
corporate strategies. Stringer (2009) set forth a method of incorporating ecological sustainability
into a Balanced Scorecard, creating measurable objectives for organizations. Given the focus on
objectives in the era of New Public Management and strategic performance of public
organizations, environmental objectives can easily be included as a measure of organizational
performance.
Eco-Initiatives and Organizational Citizenship Behaviors
When discussing employee participation in pro-environmental behaviors as supported,
but not mandated by their organization, it is important to develop a common language. The
terms “green,” “sustainable,” and “pro-environment” have all been used to describe a wide
variety of activities and behaviors designed to minimize environmental impacts. Ramus (2002)
defines eco-initiatives as “actions (or initiatives) taken by individuals and teams to improve the
environmental performance of companies” (p. 152). These actions may decrease the
environmental impact of the company, solve an environmental problem, or lead to the
development of a more eco-efficient product or service (Ramus, 2002).
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Throughout this paper, the terms “eco-initiative” and “pro-environment” will be used to
describe the discretionary employee behaviors examined. The behaviors range from carpooling
to recycling. These behaviors can also be categorized as Organization Citizenship Behaviors
(OCBs). According to Organ (as cited in Christensen & Whiting, 2009, p. 4), an OCB is an
“individual behavior that is discretionary, not directly or explicitly recognized by a formal
reward system, and that in aggregate promotes the effect functioning of the organization…the
behavior is not an enforcement requirement of the role or the job description…its omission is not
generally understood as punishable.”
This study of public sector employee participation in organization eco-initiatives will
look specifically at voluntary employee behaviors promoted by the organization and designed to
minimize the negative impact on the environment. Any behavior that minimizes environmental
impact will be referred to as “pro-environmental” (Karp, 1996; Dahlstrand & Biel, 1997;
Kollmuss & Agyeman, 2002; Nordlund & Garvill, 2002; Clark et al., 2003). To construct an
understanding of public employee participation in organizational eco-initiatives, I need to
understand the determinants of pro-environmental behavior. Understanding the determinants of
pro-environmental behavior, however, is difficult and to date there is not a generalizeable theory
that explains this behavior (Stern, 2000; Kollmuss & Agyeman, 2002; Clark et al., 2003;
Poortigna et al., 2004). The purpose of the following section is not to develop a general theory,
but rather to examine each of the variables that have been used in explanatory models, both
independently and in combination.
Social Bases of Pro-Environmental Behaviors
Van Liere and Dunlap (1980) evaluated common hypotheses about the social bases that
asserted a relationship with environmental behavior. The authors found that those who were
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younger, had higher educational attainment, and were more politically liberal, were more likely
to be concerned with environmental quality than those that were older, less-educated, and
conservative. The authors found empirical inconsistencies on the effect of a person‟s residence,
political party identification, and occupation on environmental concern. Evidence of income and
sex were not systemically related to environmental concern (Van Liere & Dunlap, 1980). Dietz,
Kalof and Stern (2002) found contradictory evidence that supports the “gender hypothesis,” but
the authors commented on the need to further examine the effect of gender on factor structures of
environmental concern. Clark et al. (2003) found a significant negative relationship between
participation in a premium green energy program and family size, and a positive relationship
between participation and household income. Poortinga et al. (2004) also found the same
relationship between pro-environmental behaviors and both family size and household income.
Values and Belief Bases of Pro-Environmental Behavior
A number of studies attempt to explain pro-environmental behavior with values (e.g.
Stern & Dietz, 1994; Karp, 1996; Nordlund & Garvill, 2002). Stern and Dietz (1994) found
“self-transcendence” and “ecocentrocism” are positively associated with “environmentalism,”
while “self-enhancement” and “anthrocentrisim” have a negative effect on ecological problem
awareness. Stern and Dietz (1994) concluded individuals with collective values and those who
value the environment for its own sake are more likely to be concerned about environmental
problems than those who do not value it for its own sake (cited in Garvill & Nordlund 2002, p.
753). Karp (1996) examined the effect of values on environmental behavior and found that
“self-transcendent/openness” and “univeralism/biospheric” have a positive influence on pro-
environmental behavior, while the values of “self-enhancement/conservation” have negative
influences on pro-environmental behavior. Nordlund and Garvill (2002) found support for a
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values-based approach using a “norm-activation” model where a personal norm of “a feeling of
moral obligation to protect the environment” predicted participation in pro-environmental
behaviors.
Identifying how values shape pro-environmental behaviors is complicated and might be
influenced by numerous external and internal drivers acting in a variety of ways. Kollmuss and
Agyeman (2002) observed the complexity: “Environmental knowledge, values and attitudes,
together with emotional involvement make up a complex called „environmental consciousness,‟”
and attitudes may change due to the life-stage of a person along with a variety of other
contextual factors (p. 256). Recently, there has been a turn toward behavioral economics to
explain the contextual factors that may influence the likelihood of a person‟s participation in
discretionary eco-initiatives or pro-environmental behaviors (Stern, 2006; Corraliza & Berenguer,
2000; Dieckman & Preisendorfer, 2003).
Contextual Factors Influencing Participation in Pro-Environmental Behaviors
In addition to individual social bases and values, contextual characteristics greatly
influence environmental behaviors. Stern (2000) suggested that causal factors of behavior may
interact with each other and noted that “attitudinal causes have the greatest predictive values for
behaviors that are not strongly constrained by the context of personal capabilities…behaviors
that are expensive and difficult, contextual factors and personal capabilities are likely to account
for the variance” (p. 422). Stern (2000) summarized the contextual factors he believes interact
with attitudes to formulate a more complete model explaining discretionary participation in pro-
environment behaviors. First, material costs and rewards may influence the types of behavior a
person chooses to perform. Second, laws and regulations may induce or prohibit certain
behaviors. Third, the technology available may influence a person‟s ability to participate in a
Stritch 8
pro-environmental behavior. Fourth, social norms and expectations may impact behavior. Fifth,
supportive policies may facilitate these behaviors. Finally, advertising and awareness might
introduce people to environmental behaviors, and thus induce participation.
Corraliza and Berenguer (2000) indicated the importance of the interaction among
personal determinants, values and beliefs, and situational determinants (physical-environmental)
on the predictive value of personal variables. The study made two major contributions. First,
environmental behavior does, in fact, rely on the interaction situational and personal variables.
Second, when a high conflict level is exhibited between situational and personal variables, the
predictive value of personal attributes is minimized. Dieckman and Preisendorfer (2003) found
evidence that environmental concerns will influence the behavior of individuals in situations that
pose a low cost to the individual. As the behavior begins to bear a higher cost, or larger
inconvenience, the likelihood of participation goes down.
Ramus and Steger (2000) found the presence of well-written and formulated
environmental policies were more likely to result in employees pursuing eco-initiatives. Ramus
and Steger (2000) and Ramus (2002) observed that at the employee level both organizational
policies and supportive supervisory behaviors can increase the likelihood of employee
participation in environmental initiatives. Stringer (2009) even discussed the need to
incorporate these behaviors and targets into the strategic management of an organization. We
know from the wealth of literature on goal setting that creating attainable goals can serve as a
motivating force that is likely to increase participation (see Locke & Latham 2002).
Public Service Motivation as a Theoretical Framework
When examining public employees‟ values and beliefs, one has to inquire about the
potential impact of the motivational bases of Public Service Motivation (PSM) and how that
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might influence participation in pro-environmental behaviors. Rainey (2009, p. 266) describes
PSM as the ethic that motivates people to serve the public, or the “service ethic.” Since the early
1980‟s, PSM has evolved into one of the central theories to public management scholarship (see
Perry & Porter, 1982; Perry & Wise, 1990; Perry, 1996; Brewer, Seldon, & Facer, 2000; Wright
& Pandey, 2005; Coursey & Pandey, 2007). Additionally, the definition of PSM itself has
evolved over the time. Perry and Wise‟s (1990) early conception was of public employees‟
predispositions to respond to motives grounded primarily in public institutions. Recently, the
definition of PSM has become more encompassing. Vandenebeele (2007) described PSM as the
“beliefs, values, and attitudes that go beyond self-interest and organizational interest that concern
the interest of a larger political entity and motivates individuals to act accordingly whenever
appropriate.”
Why do I expect PSM to be a predictor of participation in voluntary pro-environmental
behaviors? As discussed earlier, pro-environmental behaviors can be described as OCBs.
Recently, there has been a flurry of public sector research on the relationship between PSM and
OCBs (Kim, 2006; Pandey, Wright, & Moynihan, 2008; Christensen & Whiting 2009). Kim
(2006) found a positive relationship between PSM and participation in OCB in a study of the
Korean civil service. Pandey, Wright, and Moynihan (2008) found a positive relationship
between PSM and interpersonal citizenship behaviors (ICBs), a subcategory falling under the
OCB umbrella. As argued earlier, discretionary participation in eco-initiatives meet Organ‟s
definition of OCB. Building on the relationships found between PSM and OCB, I generate the
following hypothesis with respect to participation in voluntary pro-environmental behaviors:
H1: Employees with higher levels of Public Service Motivation (PSM) are more
likely to display pro-environmental behaviors than those with lower levels of PSM.
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Additionally, I am interested in determining how PSM affects the likelihood employees
encourage participation in pro-environmental behavior among their co-workers. Encouraging
pro-environmental behaviors also can be defined as an OCB. I expect PSM to explain
encouraging behavior given the external orientation and pro-social nature of the PSM construct.
Employees who see the benefit of the initiatives to both the organization and society are going to
be more likely to encourage others to participate. The second hypothesis based on the framework
integrating PSM and OCB is:
H2: Employees with higher levels of PSM will be more likely to encourage the
participation of others in pro-environmental behaviors.
There is little research that focuses on the pro-environmental actions in public
organizations‟ internal operations, and to date, no research has looked at public employees‟
discretionary participation in pro-environmental behaviors, or eco-initiatives. The following
analysis attempts to provide an understanding of environmental stewardship at the employee
level. Additionally, if a relationship between PSM and likelihood of participation and
encouraging pro-environmental behaviors is established, the research will add support to both
Kim‟s (2006) and Pandey, Wright, and Moynihan‟s (2008) work on the relationship between
PSM and OCB.
Data
I will use survey data from the City of Charlotte (NC) to test the study‟s two hypotheses.
The electronic survey was designed to help City managers understand the likelihood of employee
participation in discretionary pro-environmental behaviors and eco-initiatives. The data
collected in the survey were used to design programs encouraging participation in pro-
environmental behaviors among employees. The survey population included 3,120 City of
Charlotte employees in the following departments: Department of Engineering and Property
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Management, Neighborhood and Business Services, City Attorney‟s Office, Charlotte-
Mecklenburg Police Department Headquarters, Charlotte-Mecklenburg Planning Department,
Business Support Services and the City Manager‟s Office. The survey was distributed on the
list-serve for all City employees working at the Charlotte-Mecklenburg Government Center.
Additionally, internal communications representatives from the Police Department, the Fire
Department, Charlotte-Mecklenburg Utilities Department, and the Solid Waste Department were
asked to help distribute the survey within their own departments. Two reminders were sent to
those receiving the survey. The survey was open for approximately three weeks and yielded 843
responses for a response rate of approximately 27 percent.
Variables and Models
I will construct two models to test PSM‟s effect on the dependent variables stated in the
hypotheses. PSM is the key independent variable in both models and will be operationalized
using an index score based on survey responses for five PSM questions in the survey. The five
questions used are the same five used on the Merit Service Protection Board (MSPB) survey of
federal employees and can be found in Appendix I. Each question measures employee
responses on a seven-point Likert-scale (see Wright & Pandey, 2005, p. 7 for complete
discussion). The lowest possible PSM score for a respondent is five and the highest is 35 and the
scale reliability coefficient is .7941.
The likelihood of participation in a variety of discretionary pro-environmental behaviors
is the dependent variable in Model I. The variable is operationalized by constructing an index
score of the responses to ten survey questions that ask respondents the likelihood of their
participation in a specific pro-environmental behavior. The questions were evaluated and those
determined to be applicable to all workers in the City remained in the model. A seven-point
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Likert-scale is used to measure responses. The measure‟s possible composite scores range from
10 to 70. Appendix I contains the specific questions used to create the measure. The scale
reliability coefficient for the variable is .6861.
Model II assesses the impact of PSM on the likelihood that an individual encourages pro-
environmental behavior among their employees. The same PSM index score is used again. The
likelihood of encouraging participation is the dependent variable in Model II. This variable is
measured by creating a scale score for questions utilizing a seven-point Likert-scale to test the
likelihood of encouraging participation among other employees. Appendix I contains the
questions used to generate the measure. The composite score ranges from a low score of 3 to a
high score of 21. The scale reliability coefficient is .7793.
A key control variable in both models is a person‟s predisposition or attitude toward the
environment. Employees who feel more connected to environment should be more likely to
participate in pro-environmental behaviors than those who do not feel as deep a connection. The
connectedness to nature measure is a composite score based on 12 questions in Mayer and
Frantz‟s (2004) Connectedness to Nature Scale. I chose this scale because it taps attitudes, or
“connectedness,” toward the environment without asking questions with a simple “right” answer.
Simply asking employees if they think the environment is important may generate socially
desirable responses. The original scale has 14 questions, but two were omitted at the City‟s
request due to their politically sensitive nature. While this is not an ideal scenario, it is important
to use a tested mechanism to capture environmental attitudes in constructing the variable for the
analysis. These questions are worded in a way to tap “connectedness” to the environment, and
not simply opinions on the importance of environmental stewardship. Environmental
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connectedness is a composite score ranging from 12 to 60 and has a scale reliability coefficient
of .8539. Appendix I contains the questions used to generate the measure.
I control for race, educational attainment, age, tenure and workspace in the two models.
To control for race a dummy variable is constructed (minorities are coded with a “1” and those
who are white are coded with a “0”). Dummy variables are created to control for educational
attainment. Dummy variables are generated for employees whose highest level of educational
attainment is a bachelor‟s degree and those whose highest level of education is a graduate or
professional degree. The coefficients of these two dummy variables can be interpreted compared
to those achieving a high school education or less.
Age is measured in ten year increments (under 30, 30-39, 40-49, 50-59, and 60-69) and a
dummy variable is constructed for each group. The under 30 dummy variable is dropped from
the model and used as the comparison group to interpret coefficients produced by the other age
categories. Public sector tenure is measured in five year increments (5 or less, 6-10, 11-15, 16-
20, and more than 20 years) and dummy variable is constructed for each category. The dummy
variable for those with five or fewer years of experience is dropped from the analysis and serves
as the comparison group. A complete description of the collection and responses of the control
variables is available in Appendix III.
Methods Procedures
The first level analysis will be of the descriptive statistics of the key explanatory
variables. Second, the Pearson‟s correlation coefficient is used to analyze the bivariate
relationships between the independent and dependent variables. The final step in the analysis is
to run multivariate OLS regression to test both models. By examining the effect of controls, I
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am able to more accurately assess the true impact of PSM on the dependent variables in the
models by looking at the standardized beta-coefficients produced for each model.
Descriptive Analysis
Public Service Motivation (PSM) is a composite score on a scale from 5 to 35, with five
being the lowest possible level of PSM and 35 being the highest. The mean PSM score among
employees is 27.20. The survey measures an employee‟s likelihood of participation in eco-
initiatives on a composite scale of 10 to 70, with 10 being least likely and 70 being most likely to
participate in environmental initiatives. The mean score for employees on this scale is
50.33. The survey also measures the likelihood of encouraging pro-environmental behaviors on
a composite scale of 3 to 21, with 3 being least likely and 21 being the most likely to encourage
others to participate in pro-environmental behaviors. The mean score for City of Charlotte
employees is 11.92. The survey also measured environmental attitudes on a composite scale of
12 to 60. The mean score for this variable is 47.52. In Appendix II, Table I contains the
descriptive statistics of the independent variable (PSM), the two dependent variables
(participation pro-environmental behavior and encouraging pro-environmental behaviors) and
the environmental connectedness control variable examined in the study.
The number of non-responses, or “skips,” to survey questions measuring the control
variables is rather high, but not entirely unexpected. While the survey results are anonymous and
can not be tracked back to individual employees, these variables may have been viewed as
possible identifiers raising concerns about the anonymity of survey participants. Since the
information was collected by an employer (The City of Charlotte) this concern may have been
greater than if the survey had been implemented by an outside agent. Additionally, when the
instrument was designed, the City wanted employees to have the ability to opt-out of questions
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that may make them uncomfortable. The demographic questions were of secondary priority to
the City whose main interest in the data was to measure employee participation in pro-
environmental behaviors. As previously mentioned, the control variables are described in
Appendix III. The maximum number of cases with complete information is used in both the
bivariate and regression correlations that follow.
Bivariate Analysis
The first step in testing the hypotheses is to examine the bivariate associations between
the independent and dependent variables to determine whether the predicted relationships
exist. The results of these analyses are located in Table II of Appendix II. The Pearson
correlation coefficient between PSM and Likelihood of Pro-Environmental Behavior is 0.329,
significant at p<.000. The correlation coefficient between PSM and Likelihood of
Encouragement is 0.321 significant at p<.000. While this analysis generates preliminary support
for both hypotheses, it is necessary to test the variables further in more complex models that
control for environmental attitudes, age, race, educational background, work environment, and
the number of years a person is employed in the public sector.
Model I: PSM and Participation in Pro-Environmental Behaviors
The complete results for Model I are located in Appendix II. The first model tests
PSM‟s effect on participation in the pro-environmental behaviors while controlling for
environmental attitude, age, work environment, number of years in public employment, race and
education. The r-squared of the model is .265. In the model, PSM has a beta coefficient of .356,
significant at the p<.000 level. As expected, the largest predictor in the model was
environmental connectedness which has a beta coefficient of .455, significant at the p<.000 level.
The fact that the significant effect of PSM does not disappear when controlling for
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environmental attitudes confirms my hypothesis and provides evidence for the fact that PSM has
an independent effect on participation in eco-initiatives that can not be attributed to
environmental attitudes.
Model II: PSM and the Likelihood of Encouraging Pro-Environmental Behaviors
The complete results for Model II are located in Appendix II. The second model tests
the impact of an individuals‟ PSM on the likelihood of that individual encouraging pro-
environmental behaviors of their colleagues at work while controlling for age, work environment,
number of years in public employment, race and education. The r-squared of the second model
is .2856. In the model PSM, has a beta coefficient of .2124 and is significant at the p<.000 level.
The analysis also reveals environmental connectedness has a beta coefficient of .2089,
significant at the p<.000 level. The finding supports the hypotheses that higher PSM is
associated with a higher likelihood of encouraging discretionary pro-environmental behaviors in
others. This reiterates my earlier finding of the positive impact PSM on pro-environmental
behaviors.
Conclusion
This study provides support for the hypotheses that employees with high levels of PSM
will be both more likely to participate in pro-environment themselves and more likely to
encourage these behaviors among other employees in their organization. Employees that model
behaviors and encourage participation in an organization may have an impact on their coworkers
and help promote discretionary pro-environmental behaviors throughout the organization. These
conclusions are supported by both the bivariate analysis and the two OLS models used to test the
hypotheses that controlled for environmental attitudes, race, age, years of service in the public
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sector, education and workspace. The research builds support for the pro-social and outward
orientation of PSM, linking it to another type of OCB; pro-environmental behavior.
To tap the PSM of public sector employees, it is important public managers explain the
societal benefits of the discretionary behavior of their employees, whether in an informal
initiative among a few employees or in a branded campaign. Rather than just saying, “please
recycle,” it may be more fruitful to put particular initiatives in the context of the societal benefit
of that particular action. We know that employees with high levels of PSM have a pro-social
orientation, and maximizing this connection with an initiative may be the necessary step to
inciting participation. In addition to PSM, public managers can tap into other well known
theories of public management to inform the creation of organizational eco-initiatives and to
encourage participation in them. Drawing on both organizational commitment and goal setting
theories, public managers can design more effective programs. Additionally, public managers
need to emphasize the “service ethic” component of environmental stewardship when promoting
these initiatives within their organizations.
The study offers further evidence of the relationship between PSM and OCB, building on
earlier work (Kim, 2006; Pandey, Wright, & Moynihan, 2008). The study demonstrates the need
for additional understanding to be constructed around PSM and other OCBs beyond the scope
provided in this paper. Discretionary environmental initiatives are just one example of OCBs
influenced by PSM, and other areas such as employee giving, corporate volunteering, and
participation in voluntary social committees can be examined utilizing the framework put
forward in this paper. Studies such as these can help us understand more about PSM and why it
matters in the public organization.
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While the findings are indeed important, the study is a preliminary one, designed to serve
as a starting point for further studies on eco-initiatives within the public organization. This study,
while linking PSM to participation in pro-environmental behaviors, falls short of what may be
the most interesting question of all: How do we encourage those with low levels of PSM to
participate in these eco-initiatives? We need additional understanding on how incentives and
disincentives can be used to encourage or discourage behavior. Future research incorporating
behavioral economics can inform managers of programs that are likely to create behavioral
changes for the public employee. While this study was conducted based on existing data from the
City of Charlotte, more intensive studies that span multiple agencies, levels of government, and
economic sectors need to be conducted in order to more fully understand employee participation
in organizational eco-initiatives.
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Appendix I: Survey Questions Used in Scale Construction
Public Service Motivation Scale
Scale Scores
To what extent do you agree or disagree with the following?
Strongly Disagree Strongly Agree
Meaningful public service is very important to me 1 7
I am not afraid to go to bat for others, even if it means I will be ridiculed 1 7
I am often reminded by daily events about how dependent we are on one
another
1 7
I am prepared to make enormous sacrifices for the good of society 1 7
Making a difference in society means more to me than personal
achievement
1 7
Minimum and Maximum Totals (Range) 5 35
Scale reliability coefficient .7941
Participation in Pro-Environmental Behaviors Scale
How likely are you to do the following while at work? Very
Unlikely
Very
Likely
Recycle all paper waste 1 7
Recycle all aluminum cans or plastic bottles 1 7
Use reusable bottles or cups for beverages 1 7
Turn off your computer monitor 1 7
Use the back of old copies as scratch paper 1 7
Volunteer to have a smaller workspace or share your workspace 1 7
Print on both sides of the paper 1 7
Use common appliances as opposed to personal appliances 1 7
Turn off lights in empty rooms 1 7
Consider fuel efficiency of the work vehicles you use when appropriate 1 7
Minimum and Maximum Totals (Range) 10 70
Scale reliability coefficient= .6861
Encouragement Scale
How are likely are you to do the following while at work? Very
Unlikely
Very
Likely
Ask other employees to recycle 1 7
Join a team to encourage environmentally friendly behaviors at work 1 7
Participate in voluntary training on environmental awareness 1 7
Minimum and Maximum Totals (Range) 3 21
Scale reliability coefficient= .7793
Stritch 23
Connectedness to Nature Scale
To what extent do you agree or disagree with the following statements? Strongly
Disagree
Strongly
Agree
I often feel a sense of oneness with the natural world around me 1 5
I think of the natural world as a community to which I belong 1 5
I recognize and appreciate the intelligence of other living organisms 1 5
I often feel disconnected from nature 1 5
When I think of my life, I imagine myself as part of a larger process of living 1 5
I feel as though I belong to the earth as equally as it belongs to me 1 5
I have a deep understanding of home my actions affect the natural world 1 5
I often feel a part of the web of life 1 5
I feel that all inhabitants of earth share a common life-force 1 5
I consider myself to be a member of the top member of a hierarchy that exists in nature 1 5
I often feel like I am only a small part of the natural world around me 1 5
My personal welfare is independent of the welfare of the natural world 1 5
Minimum and Maximum Totals (Index Range) 12 70
Scale Reliability Coefficient=.8539
Stritch 24
Appendix II: Analysis and Results
Table I
Descriptive Statistics for Interval Level Variables
Variable N Range Min Max Mean
Std.
Dev.
Public Service Motivation 657 30 5 35 27.20 5.47
Likelihood of Encouragement 657 24 3 21 11.92 5.40
Likelihood of Pro-Environmental 657 59 11 70 50.34 10.29
Environmental Attitude 657 46 12 66 47.52 8.26
Table II
Bivariate Analysis of PSM and the Dependent Variables
Variable Pearson Correlation Sig. n
Likelihood of Pro-Environmental Behavior .3022 0.000 657
Likelihood of Encouragement .3405 0.000 657
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Model I: PSM and Participation in Pro-Environmental Behaviors
Independent Variable beta
std.
error t Sig.
PSM .356*** .078 4.58 .000
Controls
Environmental Attitudes .455*** 0.052 8.77 .000
Age (Relative to Employees Under 30)
30-39 -.979 1.401 -.70 .486
40-49 .864 1.5156 .57 .569
50-59 2.304 1.598 1.44 .150
60-69 1.627 2.036 .80 .424
Minimum Education (Relative to those selecting “Other”)
Bachelor's Degree 1.692 0.893 1.89 .059
Graduate/ Professional Degree .569 1.126 .51 .613
Race(Relative to Whites) .557 0.99 .56 .574
Years in Public Employment (Relative to those with less than 5 years)
6 to 10 .872 1.038 .84 .401
11 to 15 -2.196 1.392 -1.58 .115
16 to 20 -3.039* 1.509 -2.01 .045
More than 20 years. -3.410** 1.291 -2.64 .008
Private Work Environment (Relative to those who “Share an Office”) 2.465** .898 2.75 .006
Constant 17.296 2.760 6.260 .000
n 550
F 13.78
Prob>F .000
R-square .265
*p<.05
**p<.01
***P<.005
Stritch 26
Model II: PSM and Encouraging Pro-Environmental Behaviors
Independent Variable beta
std.
error t Sig.
PSM .212*** .040 5.32 .000
Controls
Environmental Attitudes .209*** .027 7.83 .000
Age (relative to those under 30 years old)
30-39 1.456* .722 2.02 .044
40-49 1.764* .779 2.26 .024
50-59 2.043*** .821 3.16 .002
60-69 2.99*** 1.046 2.86 .004
Education (Relative to those selecting “Other”)
Bachelor's Degree 1.691 .893 1.89 .059
Graduate/ Professional Degree .569 1.126 051 .613
Race (Relative to Other Minorities) 1.039* .509 2.04 .042
Years in Public Employment (Relative to those over 30 Years)
Less than 5
6 to 10 1.032 .533 1.93 .054
11 to 15 -.158 .715 -.22 .825
16 to 20 -2.169** .776 -2.8 .005
More than 20 years -1.731** .663 -2.61 .009
Private Office 1.201* .461 2.6 .010
Constant -6.061*** 1.419 -4.27 .000
n 550
F 15.28
Prob>F .000
R-square .2856
*p<.05
**p<.01
***P<.005
Stritch 27
Appendix III: Detailed Description of the Control Variables
Table VII
Race of Employees
Race Frequency Percent
American Indian or Alaskan Native 5 0.59%
Asian or East Indian 11 1.30%
Biracial or Multiracial 6 0.71%
Black (African American) 100 11.86%
Hispanic or Latino 7 0.83%
Native Hawaiian or Pacific Islander 4 0.47%
White 544 64.53%
No Response 166 19.69%
Total 843 100.00%
Work Environment Employees' Highest Educational Attainment
Description Frequency Percent Education Frequency Percent
Cubicle 190 22.54% Associate's Degree 119 14.12%
Field 46 5.46% Bachelor's Degree 282 33.45%
Other 77 9.13% Graduate/ Professional Degree 144 17.08%
Private Office 236 28.00% High School Graduate 35 4.15%
Reception Desk 6 0.71% Other 4 0.47%
Shared Office 132 15.66% Some College 118 14.00%
No Response 156 18.51% Some High School 1 0.12%
Totals 843 100.00% No Response 140 16.61%
Total 843 100.00%
Employees Ages Number of Years Working the Public Sector
Age Frequency Percent Years Frequency Percent
Under 30 75 8.90% Less than 5 219 25.98%
30-39 180 21.35% 6 to 10 187 22.18%
40-49 219 25.98% 11 to 15 82 9.73%
50-59 181 21.47% 16 to 20 71 8.42%
60 and Over 47 5.58% 21 to 25 92 10.91%
No Response 141 16.73% 26 to 30 34 4.03%
Total 843 100.00% More than 30 19 2.25%
No Response 139 16.49%
Total 843 100.00%