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Investigating Factors that Influence an Ecological
Attitude- Behavior Gap among Oregonians
by
Sayard Schultz
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Public Policy
Presented Defense Date June 9, 2016
Commencement June 11, 2016
Master of Public Policy thesis of Sayard Schultz presented on June 9, 2016
APPROVED:
Dr. Erika Allen Wolters (Chair); representing Political Science, Oregon State University
Dr. Alison Johnston; representing Political Science, Oregon State University
Dr. Brent S. Steel; representing Political Science, Oregon State University
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader upon
request.
AN ABSTRACT OF THE THESIS OF
Sayard Schultz for the degree of Master of Public Policy presented on June 9, 2016.
Title: Investigating Factors that Influence an Ecological Attitude- Behavior Gap among
Oregonians
Abstract approved:
Dr. Erika Allen Wolters
This study examines the determinants of food consumption behaviors, such as purchasing less
meat products, paying attention to how and where food is produced, and reducing food waste
within the household. Food consumption is particularly important given that it can often
comprise between 10% to 30% of the total household GHG emissions. To better understand
what situational and social-cognitive factors affect Oregon household ecological food
consumption behaviors beyond belief that climate change will cause dramatic and long-term
changes in the United States, a cross-sectional OLS regression analysis was employed within a
modified reasoned action approach framework. The four main factors of interest that were
hypothesized to impact ecological food consumption behavior were behavioral beliefs, means,
access, and information. Results from the regression show that behavioral beliefs are a
statistically significant factor that positively influences the engagement in ecological behavior. In
addition, work status, political ideology, revised-NEP, and gender also displayed a relationship
with food consumption behavior.
© Copyright by Sayard Schultz
June 9, 2016
All Rights Reserved
TABLE OF CONTENTS
Page
INTRODUCTION .............................................................................................................. 2
LITERATURE REVIEW ................................................................................................... 4
SOCIAL–PSYCHOLOGICAL FRAMEWORKS ....................................................................... 4
Schwartz's Moral Norm-Activation Theory ................................................................ 5
Value-Belief-Norm Theory ........................................................................................ 6
Theory of Planned Behavior ...................................................................................... 7
Reasoned Action Approach ......................................................................................... 8
Research examining the Reasoned Action Approach ............................................... 10
WHAT FACTORS INFLUENCE ECOLOGICAL BEHAVIORS .................................................. 11
Attitude-Behavior Gap ............................................................................................... 11
Behavioral Beliefs ...................................................................................................... 12
Means ......................................................................................................................... 14
Access......................................................................................................................... 15
Information ................................................................................................................. 16
Values and Social-Demographic Variables .............................................................. 17
Values .................................................................................................................. 17
Social-Demographic ............................................................................................ 19
HYPOTHESES .................................................................................................................. 21
DEFINITIONS ................................................................................................................. 21
VARIABLE SELECTION AND EMPIRICAL MODEL ................................................ 22
RESULTS ........................................................................................................................ 31
DISCUSSION AND CONCLUSION ............................................................................. 33
REFERRENCES .............................................................................................................. 36
APPENDICES ................................................................................................................. 46
Appendix A: 2013 rural-urban continuum codes ...................................................... 46
Appendix B: Construct of the Abbreviated 6-Question New Ecological
Paradigm Index Scale .......................................................................... 46
Appendix C: Summary Statistics for Subsample ...................................................... 47
Appendix D: Oregon Lifestyle Survey (C) ............................................................... 48
LIST OF FIGURES
Figure Page
Diagram 1: Reasoned Action Approach - Fishbein and Ajzen (2010) .............................. 9
Diagram 2: Modified Reasoned Action Approach .......................................................... 10
Graph 1: Frequency of Food Consumption Behavior Index ........................................... 25
LIST OF Tables
Table Page
Table 1: Description of Subsample and Variables ........................................................... 29
Table 2: Results of OLS Regression Analysis ................................................................. 31
2
INTRODUCTION:
Climate change is an existential global challenge that span multiple dimensions of
society, including issues related to human health, the economy, water and food supplies, politics,
and the environment (Crimmins et al., 2016; EPA, 2016). Because climate change is both local
and global in scope, engages many competing stakeholders and involves a multitude of
uncertainties, it may be the most intractable problem that the world has ever faced (Lazarus,
2010). In fact, a number of scholars have ominously labeled climate change a “wicked problem”
that presents a global social dilemma devoid of obvious solutions (see Levin, 2009 ; Turnpenny,
Lorenzoni, & Jones, 2009). Climate change is not only a wicked problem but can be expanded
to a global social dilemma (Chapstick, 2013).
According to Van Lange, Joireman, Parks, and Van Dijk (2013), Social dilemmas are
conflicts between immediate interest of individuals and the long-term interests of the collective
group. The relationship of climate change to transportation provides one example of how this
issue generates a social dilemma. An individual may choose to drive their gasoline-powered
vehicle to work every day because he or she considers it to be more convenient and comfortable
than public transit or biking. In the short run, driving a car may well be in the individual’s best
interest. Nevertheless, in the long run, emissions from driving gasoline vehicles adds to
greenhouse gases and exacerbates climate change, which is not in the world’s collective interest.
Moreover, even if the production of greenhouse gases is insignificant, the aggregation of
individual emissions can have a substantial impact on the Earth’s climate (Chapstick, 2013).
Unlike other actions, however, which have clear and visible environmental impacts, such as clear
cutting a forest, impacts of greenhouse gas emissions from other actions can be elusive and hard
for individuals to connect their actions to these climate consequences.
2
Basic research, conducted by physical scientists, is essential for devising effective
strategies to mitigate greenhouse gasses. But that’s only half the battle. Equally important is
research conducted by social scientists to uncover how individual and societal beliefs, attitudes,
and behaviors impact emission levels. In their research on why nations respond to climate
change differently, Tjernström and Tietenberg (2007) found that individual attitudes about
environmental protection not only directly impact greenhouse gas emissions on a daily basis but
also help to shape national environmental policies over the long-term. This is especially true in
democratic states since environmental policies are intimately linked to the functioning and well-
being of society. Individual lifestyles, as reflected through voting, thus become an important
issue to consider when addressing climate change.
When it comes to greenhouse gas emissions, personal attitudes and behavior are
particularly important factors in the United States. This is particularly salient regarding food
consumption behaviors; in which consumption often comprises between 10% to 30% of the
household emissions produced, depending on the household income (Jones & Kammen, 2011).
Within Oregon1, among the sixteen household commodity consumption categories
2 identified by
the Oregon Department of Environmental Quality (DEQ), food and beverage consumption yields
the third highest household GHG emissions (DEQ, 2016). Within this food commodity category,
red meat (which includes beef, pork, lamb, and other ruminant animals) and dairy and egg
products generate the largest amount of emissions (Stehfest et al., 2009; Stockholm Environment
Institute, 2011).3 In addition to meat consumption, wasting edible food also increases GHG
emissions because of the unnecessary consumption of fresh water and petroleum products.
1 The state of Oregon was specifically looked at because my study sample is made up of Oregonians households.
2The 16 categories of household consumption range from vehicle parts, water/wastewater, services, healthcare, to
any other goods/services consumed by the household. 3 The dietary needs and how ruminant animals stomachs are configured are the main reasons for these high GHG
emissions levels (Stockholm Environment Institute, 2011).
3
Research has found that food waste has steadily increased since 1974. In 2003, it totaled 1400
kcal per person per day4 (Hall, Guo, Dore, & Chow, 2009). In Oregon, GHG emissions produced
from the consumption of food is 30 times greater than emissions created from the disposal of
wasted uneaten food (primarily landfilled) (Stockholm Environment Institute, 2011). The reason
for such a difference is that energy and water used to produce food along with transportation to
retail markets are factored into the calculation of GHG emissions. Therefore, managing food
production at its source can have a significant impact in reducing emission and mitigating
climate change
The purpose of this thesis is to examine what situational and social-cognitive factors
affect Oregon household ecological food consumption behaviors beyond belief that climate
change will cause dramatic and long-term changes in the United States. Specifically, I examine
food consumption behaviors that are preformed in daily life, such as purchasing less meat
products, paying attention to how and where food is produced, and reducing food waste within
the household. These behaviors are important to consider when looking at climate change
because of their influence on greenhouse gases and community resilience. This study applies
Fishbein and Ajzen’s (2010) reasoned action approach as a theoretical framework. Based on the
reasoned action approach (RAA) and other relevant literature, I expect when holding attitudes
towards climate change constant, four primary factors involving efficacy, means, information,
and access will become important indicators in determining pro-ecological food consumption
behavior.
4 kcal reference to kilocalories- a unit of energy of 1,000 calories (equal to 1 large calorie). In the USA, kcal is
synonymous with Calories. Depending on gender and age, in general, adults should be consuming 1,600 - 2,800
calories per day (NIH, 2013).
4
Subsequent sections of this paper explore the social–psychological frameworks
commonly used to understand the relationship between individual cognitive factors and behavior.
I then survey the literature concerned with the key determinants of ecological behavior. The
section on methodology describes my data collection strategy and the analytical techniques. The
results sections explains the OLS outputs. The discussion and concluding section outlines the
validity of the hypotheses, study’s policy implications, study limitations and possible future
research directions.
LITERATURE REVIEW:
Social–Psychological Frameworks
Research into the relationship between individual cognitive forces and human behavior
has predominantly been conducted by social psychologists (Eagly & Chaiken, 1993). Since the
1920s, researchers have been working on the theoretical growth of attitude theory. In addition,
research on the relationship between attitudes and behavior can be seen far back as the 1930s
(see LaPiere, 1934; Allport, 1935). However, just as the theoretical frameworks and research into
this relationship were emerging, so were the disagreements on how much weight we can assign
attitudes in determining behavior. For instance, certain social situational variables may act as
obstacles that hinder attitudes-consistent behavior, thus clouding the true relationship (Eagly &
Chaiken, 1993). Campbell’s (1963) research on negative attitudes towards minorities found that
barriers such as norms of tolerance and politeness constrained individuals from expressing their
negative attitudes. Campbell (1963) concluded that social norms and other situational obstacles
could create thresholds for displaying attitudes. What follows is an examination of key social-
5
psychological frameworks that convey different concepts of how social-cognitive factors
influence pro-environmental behavior.
Schwartz's Moral Norm-Activation Theory
The Moral Norm-Activation Theory (MN-A) holds that the feeling of altruism is
motivated by one’s interval values, personal norms and the intention to assist others (Schwartz,
1977). The model contains three types of variables used to predict prosocial behavior. The first
are personal norms (PN) defined as the self-expectations constructed by an individual which
guides them on how to behave in certain circumstances (Schwartz, 1977). These personal norms
are influential when they are activated by two other variables, awareness of consequences (AC)
of events for others and ascription of responsibility (AR) where the belief that one’s own actions
could be responsible for the negative consequences of not acting pro-socially (Stern, Dietz, Abel,
Guagnano, & Kalof, 1999; Nolan & Schultz, 2015). With regards to environmentalism, others
could translate to the awareness of consequences to non-human species and the biosphere (Stern,
Dietz, & Kalof, 1993; Stern & Dietz, 1994). In employing this theory within an environmental
setting, two types of interpretations are commonly used: the model as a moderator and as a
mediator (De Groot & Steg, 2009).
In a study examining whether the respect of another’s health correlates with actions to not
burn yard or garden wastes, Van Liere and Dunlap (1978) indicated that AR was significantly
associated with burning behavior, whereas AC showed a weak association with burning. In a
meta-analysis examining how researchers employed the MN-A theory on a range of prosocial
intentions and behaviors, De Root and Steg (2009) found that the mediator model was supported
within research looking at social and environmental contexts. Their results are in line with other
research that showed awareness of consequences (AC) affects ascription of responsibility (AR)
6
and that responsibility indirectly affects intentions and behavior via personal norms (PN) (De
Ruyer & Wetzels, 2000; Steg, Dreijerink, & Abrahamse, 2005). Lastly, others have argued that
often the MN-A model neglects behavioral influences from an individual’s perceived belief
about others’ pro-environmental behavior ((Blamey,1998).
Value-Belief-Norm Theory
Stern et al. (1999), building on past theories and explanatory variables, developed the
Value-Belief-Norm (VBN) theory to explain non-activist environmental behavior. This theory
connects value theory, Schwartz’s norm-activation theory, and Dunlap and Van Liere’s Revised-
NEP perspective (Stern, Dietz, & Guagnano, 1995). In this model, the cognitive link moves
from more stable fundamentals of personality and belief structures to more focused beliefs about
the human-behavior connections (Stern, 2000b). In research applying the VBN theory, Steg,
Dreijerink, and Abrahamse (2005) were able to confirm this cognitive link. In addition,
Thøgersen and Grunert-Beckmann (1997) looking at waste minimizing behavior were able to
establish a value-attitude-behavior hierarchy.
Research utilizing the VBN model along with analyzing contextual factors to understand
pro-environmental behavior within business organizations found mixed results, in that only
perceived commitment to sustainability was significant in the VBN’s causal chain (Andersson,
Shivarajan, & Blau, 2005). Other studies have compared the VBN model to the theory of
planned behavior. These studies have found that the theory of planned behavior has a more
statistical significant fit statistics and a higher proportion of explained variance (Kaiser, Hübner,
& Bogner, 2005; López-Mosquera & Sánchez, 2012).
7
Theory of Planned Behavior
For over 45 years, Fishbein and Ajzen (2010) have been modifying their theoretical
frameworks in order to better understand and predict human social behavior within various
applied settings. The theory of planned behavior (TPB), in the late 1980s, was derived from the
theory of reasoned action in order to account for instances where people may lack complete free
will over their desired behavior (Fishbein & Ajzen, 2010). The TPB hypothesizes that the
intention to perform a behavior is determined by attitudes towards the behavior, subjective norms
towards the behavior, and perceived behavior control (the belief one can perform the behavior)
(Ajzen, 1991).
In the application of the theory of planned behavior, Han , Hsu, and Sheu (2009)
investigated customers’ intention to visit green hotels. Their results showed that the TPB
framework was robust and predicted attitudes, subjective norms, and perceived behavioral
controls, all of which positively affected the intention to stay at a green hotel. However, other
researcher have found mixed results when applying the TPB. In a study conducted by Cheung,
Chan, and & Wong (1999), they found that the TPB significantly predicted both behavioral
intentions and self-reported pro-environmental behavior, while perceived control had no
significant effect.
A criticism of the TPB is that it does not incorporate emotional factors such as threat,
fear, and mood within the framework (Dutta-Bergman, 2005) nor does it give an explanation of
how past behavior or habits influence future actions (Knussen, Yule, MacKenzie, & Wells,
2004). Furthermore, habits and past behavior are essential factors to take into account when
attempting to understand pro-environmental behavior (Reid, Sutton, & Hunter, 2010). Ajzen and
Manstead (2007) uphold the predictive power of the TPB and make a case that habitual and past
8
behavior factors are accounted for within the behavioral and normative aspects of the theory.
Regardless of possible limitations, the TPB continues to be one of the frameworks of choice
within the pro-environmental literature (Reid, Sutton, & Hunter, 2010).
Reason Action Approach
Recent theory has predicted and understood human social behavior via the reasoned
action approach (RAA) framework (Fishbein & Ajzen, 2010). This framework was built upon
their previous theories including the theory of planned behavior. The RAA purports that in order
to elicit a behavioral response several explanatory variables need to be activated. In addition, the
RAA does not assume rationality and it encompasses both deliberative and spontaneous decision
making. Fishbein and Ajzen, (2010) argue that individuals approach different kinds of behavior
in similar manners and that the same limited set of explanatory constructs can be applied to
predict and understand any behavior of interest. Fishbein and Ajzen (2010) have developed a
flow chart that illustrates their framework, which is shown below in diagram 1.
Within the diagram, the starting point in developing a behavior begins with an
individual’s background factors. These factors include, demographics, individual differences
(such as personality), knowledge, and social structure variables. These background factors
simultaneously influence a person’s behavioral beliefs (outcome expectancies about the action),
normative beliefs (how one believes he/she should be expected to act ), and control beliefs (self-
efficacy). Once these three attitudes have been activated, they interact with attitudes towards the
given behavior, perceived norms (social pressure that one would perceive to experience if she/he
acts or not), or perceived behavior control (perceptions of the ability to perform a given
behavior). When attitudes, perceived norms, and perceived behavioral controls are formed, the
9
combination of these three can lead to the development of behavioral intention or readiness to
perform the behavior. (Fishbein & Ajzen, 2010).
Diagram 1: Reasoned Action Approach - Fishbein and Ajzen (2010)
Within my study, I used a modified RAA as my theoretical foundation. Modifying the
RAA framework allowed for a better explanation of my data. Diagram 2 provides a schematic of
this modified version. Within this modified framework, I focus on a selected amount of
background factors that are found in the literature to influence behavior. These factors are held
constant throughout my study. Next, the attitudes towards behavior variable has been adapted to
measure the individual’s general belief about the impacts of climate change. These attitudes
towards climate change are held constant within my study. The social-situational and behavioral
beliefs factors are the factors of interest that my study aims to investigate. Because I want to test
if these factors have a more direct relationship to behavior, I have positioned them differently
than what would be found in the originally RAA model. The behavioral beliefs factor has been
10
operationalized to measure an individual’s general perceived self-efficacy towards their ability to
make a pro-environmental impact through their own actions. Once the social-situational and
behavioral belief factors have been activated, an individual has an intention to act and therefore
more than likely to engage in the behavior. The arrows in diagram 2 shows a causal link starting
with background factors and ending with food consumption behavior.
Diagram 2: Modified Reasoned Action Approach
Research examining the Reasoned Action Approach
In order to understand how these variables impact behavior, several studies have
reviewed the validity of these relationships. Webb and Sheeran (2006) investigated how changes
in behavioral intention related to behavior change. They found that medium to large changes in
intention correlated to a small to medium change in behavior. In addition, they also found that
intentions have a reduced impact on behavior if there is a lack of control over that behavior, if
the behavior is a habit, and on risky behaviors performed in social contexts Webb and Sheeran
(2006). As professed by Ajzen (2002), routinization of behavior aligns with a reasoned action
perspective. Other research has suggested that there is a gender-behavioral intention relationship
11
where females have stronger held beliefs towards environmental protection, thus are more
willing to perform pro-environmental behaviors (Stern and Dietz, 1994).
What Factors influence Ecological Behaviors
In addition to cognitive determinants, others have argued that situational, demographic,
and socioeconomic factors can also exert an influence on behavior (Corraliza & Berenguer,
2000). Others stress equal attention should be employed to both types of variables in order to
have the most complete analysis (Van Liere & Dunlap, 1980). In this section, to develop a more
comprehensive understanding of the factors that impact the decision to act, I will be looking at
both types of behavioral determinants.
Attitude-Behavior Gap
The Attitude-behavior gap refers to a discrepancy between evaluative views an individual
holds and a specific behavior the individual performs (Stern, 2000b). Research into the
relationship between attitudes and behavior has been investigated some time. For instance,
Wicker (1969) concluded that attitudes are not a strong gauge of ecological preservation
behavior, but have been considered significant predictors. Pro-environmental or environmentally
significant behavior can be defined as behavior that will bring about positive impacts on the
biosphere (Stern, 2000b). Academic research into the attitude-behavior relationship has primarily
split into two concentrations. One application evaluates how differences in measurement of
attitudes and behaviors affect the validity of the relationship. The other concentration examines
how other factors may be driving the attitudinal-behavioral gap.
In evaluating attitudinal and behavioral measurements, research by Sjöberg (1982) and
Werner (1978) found that relatively strong attitude-behavior relationships can be produced by
12
relating a general attitude (such as environmental sustainability) to a dependable behavioral
index, which is created by combining attitude-relevant behaviors. Tarrant and Cordell (1997)
have identified three reasons for an absence of correlation between attitude and behavior; (1)
lack of precise attitudinal and behavioral measurements; (2) lack of attitudinal measurement
quality; (3) and a failure to take into account the influence of external factors.
Wall (1995) concluded that context maybe the driving force influencing the disagreement
between one’s environmental concern and their behavior. For example, behavior may be nothing
more than a convenient way to act. Furthermore, Vermeir and Verbeke’s (2006) also highlight
that there is more to influencing behavior than attitudes. Their study looked at the potential gap
between positive attitudes towards ecological behavior and the behavioral intentions in
purchasing sustainable food products. They uncovered that the reason why there was a
disconnect between stated attitudes and corresponding stated behavioral intentions was due to the
perceived lack of available ecological products. This mediating variable, perceived lack of
availably, helped explain why intentions were low even when attitudes towards a behavior are
positive. More recent research has also confirmed that not only does environmental concern
influence water conservation behavior (which demonstrates an attitude-behavior consistency
relationship) but socio-demographic variables, age and income, also produce a statistically
significant impact on behavior, in the case of this study water consumption behavior (Wolters ,
2012).
Behavioral Beliefs
Within the literature that focuses on the attitude-behavior relationship, behavioral beliefs
have been identified as a key cognitive determinant. There are several different terms used to
understand this determinant; nonetheless, they all communicate the same meaning. Some
13
researchers simply use the term behavioral beliefs; which are ideas individuals hold about
negative or positive consequences they will experience from performing a behavior. These are
outcome expectancies and these expectancies form an individual’s attitude to performing a
behavior (Fishbein & Ajzen, 2010). In evaluating the impact of behavioral belief on behavior,
Tobler, Visschers, and Siegrist (2011) determined that consumers’ motivation to take up
ecological food consumption actions followed their belief that these behaviors would cause
environmental benefits. Similarly, increasing perceived consumer effectiveness, the extent that a
consumer believes their purchases make a difference, can elicit consumers to convey their
environmental concerns through pro-environmental behavior (Ellen, Wiener, & Cobb-
Walgren,1991).
Another way to understand how behavioral belief can influence action is by observing an
individual’s locus of control. The term locus of control is a measure of how an individual
perceives a reward or reinforcement that is conditional upon their behavior (Rotter, 1966). In
researching how ecological concern influences a consumer’s intention to purchase eco-friendly
packaged products, Schwepker Jr. and Cornwell (1991) concluded that individuals with a locus
of control, who were concerned about litter, and believed pollution was a pressing problem were
more likely to purchase ecologically packaged products.
In addition, others evaluate why an individual acts through the notion of perceived self-
efficacy. This term simply means that in order for an individual to act on their attitudes they must
perceive that they have the capacity to produce a desired effect (Bandura, 1994). Research
uncovering main antecedents of green purchase behavior found that individual’s positive beliefs
about self-efficacy mediated the relationship between the individual’s value orientation on
general ecology concern and their tendency to purchase green products (Kim & Choi, 2005). In
14
addition, Barr, Gilg, and Ford (2001) have shown that high levels of self-efficacy, specifically
the belief that a specific action will have an evident impact on the environment, has a significant
impact on environmental commitment.
Means
Means within this paper refers to the financial ability to purchase pro-environmental
produced food and the capability to invest time in ecological food consumption behaviors.
There are mixed results within the literature as to whether household income influences
environmental behavior. A study conducted by Wandel and Bugge (1997) showed that
purchasing ecologically produced food was not related to a customer’s social-economic situation.
Others found inconsistent results on how much income may influence behavior (Jones & Dunlap,
1992; Van Liere & Dunlap, 1980). In regards to the relationship between food consumption and
income, Gossard and York (2003) found that beef consumption was positively related to income
level; which may be due to the price of beef compared to other food products. Conversely, other
research has shown income to influence environmental behavior in part due to individuals having
more resources to carry out ecological efforts (Buttel, 1975; Clark, Kotchen, & Moore, 2003).
Time has also been shown to influence the engagement in ecological behavior. Within
this notion, ecological behaviors can be viewed as time investments in the environment (Reisch,
2001). For example, in order to purchase ecologically produced food it takes time to research and
be informed to make that decision. Blake (1999) has noted that individuals who have satisfied
their human needs are more likely to engage in ecological behavior because they have greater
resources such as time, money, and energy. Within this same vein of thought, other research has
examined the notion of “downshifting”, which illustrates the actions of working less and
increasing leisure time in an effort to reduce stress and improve one’s quality of life (Drake
15
2001). Other researchers have viewed “downshifting” as a means to bring about positive
environmental impacts (see Hayden, 2001; Thomas, 2008) through increased mindfulness
(Brown & Kasser, 2004) by having more leisure time and subsequently reducing consumption.
There have been other studies, however, that have demonstrated that work-status did not
influence the likelihood of purchasing ecologically produced food (Wandel,1997) nor
willingness to pay higher prices for ecologically safe products (Laroche, Bergeron, & Barbaro-
Forleo, 2001).
Access
Access defines the ability for individuals to obtain the desired goods and services that are
needed in order to complete an action. For example, if an individual believes that purchasing
ecologically produced food is good for the environment, however is only able to purchase non-
ecologically products, their attitudes and behavior will not be consistent. Evaluating access
frequently involves determining where an individual lives. For instance, living in a rural or urban
community can place different situational constrains on food availability (Morton, Bitto,
Oakland, & Sand, 2008). An example of situational constraint is food spatial disparity; which
entails long stretches of land where communities are without adequate nutritional food
selections. This phenomena has primarily been studied in low-income urban areas (Sharkey,
2009). However, other research has found spatial disparity among rural communities (Dean and
Sharkey (2011). These disparities are primarily a function of the great distances traveled and the
types of transportation available to rural communities (Wrigley, Warm, Margetts, & Whelan,
2002). The available food found in rural communities is mainly located in small stores that have
less available brands and alternatives than the food available in the larger grocery stores located
mainly in urban settings (Smith & Morton, 2009).
16
Another way to view food access is through the concept of redistribution and reciprocity.
These are two noneconomic methods used to help individuals who are not able to meet their food
resource needs in a market economy (Lomnitz, 2002). If low-income households are still not able
to meet their food needs via redistribution, which is largely employed by governments and
charities, they may turn to reciprocity (Morton et al., 2008). Research has found that reciprocal
nonmarket food exchange happens more often within rural low-income communities than in low-
income urban counterparts. For instance, rural households were able to obtain food such as meat,
fish, and vegetables from family, friends, and neighbors compared to urban households. In
addition, these low-income rural households were also able to acquire these food products from
local farms (Morton et al., 2008). Furthermore, comparing meat intake for rural and urban
communities, Gossard and York (2003) found that urban residents eat less beef than rural
residents; however, there was not a statistically significant difference among urban and rural
residences when measuring the consumption of total meat (which includes beef, pork, poultry,
seafood, and processed meats).
Information
Environmental knowledge is frequently considered a way to overcome misinformation
and ignorance and considered a precursor to ecological behavior (Gardner & Stern, 2002). An
indicator that has been used in the literature to measure how individuals retain and process
information and thus to gauge one’s knowledge on a subject is by surveying formal education
attainment . The judgment behind using education as a proxy to measure knowledge is that better
educated individuals are more practiced at learning and more skillful at organizing and gathering
key information (Price & Zaller,1993). Interesting enough, Jerit, Barabas, and Bolsen (2006)
research exploring the determinants of political knowledge found that the relationship between
17
education and knowledge varies according to how information is disseminated. They outline that
there is a positive relationship with increased newspaper coverage of a political topic and highly
educated individual’s knowledge, supporting the education-knowledge relationship. However,
they also discover a positive relationship among increased television converge on the political
topic and increase knowledge of the less educated, refuting the education-knowledge
relationship.
Some researchers have found that higher educated individuals convey stronger concerns
towards the environmental compared to less educated individuals (Howell & Laska, 1992; Jones
& Dunlap, 1992; Van Liere & Dunlap, 1980). Others have shown that education can have a
positive influence on concern and behavioral commitment (see Schultz, 2002; Johnson, Bowker,
& Cordell, 2004; Casey & Scott, 2006). Particularly looking at ecological impacts of meat
consumption, Gossard and York (2003) found that education is negatively related to beef and
total meat consumption. However, others have concluded that information does not influence
behavior (Stern, 2000a; Frick, Kaiser, & Wilson, 2004).
Values and Social-Demographic Variables
Values
Political ideology is another variable that has repeatedly been discussed in the literature
on environmental attitude formation and pro-environmental behavior. Recent decades have seen
strong polarization on environmental issues. Where liberals proclaim strong concern for the
environment, conservatives are generally opposed to introducing environmental protections
(Feygina, Jost, & Goldsmith, 2010; McCright & Dunlap, 2011). Environmental behaviors has
been shown to significantly differ along political ideological lines (Dunlap, Xiao, & McCright,
2001; McCright & Dunlap, 2011). Research in line with the above results illustrates that liberals
18
were significantly more likely than conservatives to indicate a committed to environmental
protection and to perform ecological behavior (Steel, 1996). However, there has been other
research that has indicated no significant differences between pro-environmental behaviors
across supporters of various political parties (Casey & Scott, 2006)
In addition to how political ideology values effect behavior, other research has sought to
develop a means to measure an individual’s ecological worldview, or primitive beliefs, in how
humans relate to nature. This measurement, called the new ecological paradigm scale (revised-
NEP) developed by Dunlap and Van Liere (1978, 1984) and Dunlap et al. (2000) is a 15-item
scale which ranges from a worldview holding anthropocentric values (viewing humans as
dominant over nature) to a worldview consisting of biocentric values (viewing humans and
nature as equal). Research has predominantly shown the revised-NEP as a reliable predictor of
pro-environmental concern and behavior. In Clark, Kotchen, and Moore’s (2003) study
examining factors that influence participation in a household renewable energy program, found
that both participants and non-participants indicated positive attitudes towards the
environmental; however, mean responses for the revised-NEP were higher among the
participants. Their analysis further pointed to a positive relationship among the revised-NEP
score and the probability of participating in renewable energy programs. The frequency an
individual engages in recycling, ecological consumption, or conservation behaviors has also been
shown to be positively associated with levels of biocentric values (Casey & Scott, 2006). The
revised-NEP has also been shown to be a significant predictor in determining ecological
behavior (Davis, Le, & Coy, 2011). Criticism towards the revised-NEP scale has primarily come
from how it’s administered. Studies that have used a 6-item version of the NEP scale showed
higher scores compared to studies using the 15-item NEP Scale. The authors warn that variations
19
in how the NEP scales are used could affect the accuracy in measuring environmental attitudes
(Hawcroft & Milfont, 2010).
Social-Demographics
Children in the household may also influence adult ecological attitudes and behaviors.
Xiao and McCright (2012) evaluated how parenthood could affect gender differences with regard
to concern about environmental issues within the United States. Their research determined that
parenthood did not have a significant effect on concern. Similarly, Wandel and Bugge (1997)
found that individual’s desire to consume ecologically produced food was not related to the
presence of children in the household. Other research was not able to determine whether children
impacted a parent’s pro-environmental beliefs (Torgler, Garcia-Valiñas, & Macintyre, 2008).
Lastly, other research has focused on how the number of individuals in a household influences
environmental behavior. Clark, Kotchen, and Moore’s (2003) find that more individuals in a
household decreases the amount of disposal income even after controlling for differences in
household income. As a result, the implication is that household size may impact pro-
environmental behavior, which is monetary-based.
Gender’s impact on environmental behavior has also been discussed in the literature. It
has been shown that women exhibit greater concern for the environment and engage in pro-
environmental behavior more than men; however, when examining specific behaviors this may
not be the case. For example, a number of studies have demonstrated a positive relationship
between gender and environmental concern (Jones & Dunlap, 1992; Steel, 1996; Tindall, Davies,
& Mauboules, 2003; Zelezny, Chua, & Aldrich, 2000). Casey and Scott ‘s (2006) found that
women are more concerned for the environment and indicate a higher engagement of pro-
environmental behaviors than men. Women are also found to engage in pro-environmental
20
behavior such as recycling more frequently than men (Johnson, Bowker, & Cordell, 2004). On
the other hand, Tobler, Visschers, & Siegrist (2011) found in regards to meat consumption that
men were more likely to reduce their meat consumption for environmental reasons where
females were more likely to reduce meat for health reasons. In addition, men are more likely to
eat meat (see Guenther, Jensen, Batres-Marquez, & Chen, 2005; Jensen & Holm, 1999) and have
a greater revealed preference for it than women (Kubberød, Ueland, Rødbotten, Westad, &
Risvik, 2002).
The impact of age on environmental concern or pro-environmental behavior, is more
disputed in the literature. Some have noted a negative relationship between age and
environmental concerns (Arcury, 1990; Dunlap et al., 2000; Jones & Dunlap,1992). However,
other research has found a positive correlation between age and environmental conservation
(Olli, Grenstad, & Wollebaek, 2001). Research examining the relationship between recycling
behavior and age found that age was not a significant predictor of behavior (Schultz, Oskamp, &
Mainieri, 1995). Contrary to the above findings, Casey and Scott ‘s (2006) analysis confirmed a
positive association between age and both increase levels of ecological concern and engagement
in ecological behaviors as recycling, consumption, and conversing. Wolters’ (2012) also
discovered a highly significant positive correlation between age and water conservation
practices. Other studies have focused on the theoretical explanation of how age may affect
ecological behavior. Otto and Kaiser (2014) found that learning rather than aging accounted for
the relationship between age and self-reported ecological behavior. Lastly, in viewing age as a
control variable for changes in dietary requirements, Gossard and York (2003) found that people
eat both less total meat and beef as they grow older.
21
Based on the above literature review concerning factors that have the potential to
influence ecological behavior, I pose the four below hypotheses.
Hypotheses
Recognizing an attitude-behavior gap related to attitudes towards climate change impacts
and pro-ecological food consumption behavior, I hypothesize that four primary factors influence
this gap.
H1: Behavioral Belief: If an individual believes that their behavior will bring about a positive
environmental change, they will be more likely to undertake pro-ecological food
consumption behaviors.
H2: Means: As an individual’s income increases, they will be more likely to undertake pro-
ecological food consumption behaviors. In addition, individuals who have more available
leisure time will be more likely to undertake pro-ecological food consumption behaviors.
H3: Information: As an individual’s level of education increases, they will be more likely to
undertake pro-ecological food consumption behaviors.
H4: Access: Individuals living in urban areas compared to rural areas are more likely to have
access to greater food variety and undertake pro-ecological food consumption behaviors.
Definitions
Within social-cognitive literature, the below terms have often been used interchangeably
which can create confusion (Rokeach, 1968; Schultz, Shriver,Tabanico, & Khazian, 2004). What
follows are the definition that I have employed in this study.
I use the term Belief to refer to inferences made by an individual about principal
conditions of expectation (Rokeach, 1968). For example, I believe commuting by bike will
22
reduce global warming. Beliefs are not necessarily based in fact. There are many types of beliefs
that make up one’s belief system (Rokeach, 1968). An environmental concern is the affect
related to a belief an individual has about an environmental problem (Schultz et al., 2004). In
continuing with the former example, I am concerned how the environment will be negatively
impacted by car emissions; therefore I will ride my bike.
Within our belief system are values, these are a set of beliefs which function as guiding
standards or moral principles (Dietz, Fitzgerald, & Shwom, 2005). These values go beyond
specific actions or situations one may find themselves in. Values are also ordered by their
importance; where this feature differentiates them from norms and attitudes (Schwartz, 2012).
Examples of values include equality, respect, and freedom. Moreover, environmental values
refer to values that specifically connect to nature (Schultz et al., 2004). For the term worldview, I
am referring to Dunlap and Van Liere’s (1978) environmental paradigm that is the portion of an
individual’s belief system encompassing beliefs about humanity’s relationship with nature.
Attitude refers to an evaluative view an individual holds about a certain object or
situation. Attitudes are frequently expressed in a negative or positive preference (Eagly &
Chaiken, 1993). For example, “I support an increase in my property tax to fund building more
bike paths.”
VARIABLE SELECTION AND EMPIRICAL MODEL:
Data used in this paper stems from the 2015-2016 Oregon Lifestyle Surveys. This
research project was fashioned from a partner project conducted by the Consensus Sustainability
Project, funded by the Environmental Protection Agency of Ireland (Consensus.ie, 2014). The
objective of the Consensus Project was “to gain an understanding of people’s attitudes and
23
behaviors towards sustainable household consumption and sustainable lifestyles” (Consensus.ie,
2014). The Oregon Lifestyle Survey Project concentrated on five major areas of study, four areas
based on the Irish Consensus Project and one unique to the Oregon project. These five areas of
study include: individuals’ energy behavior, mobility, food consumption, water consumption,
and consumerism.
Methods in gathering my data included the distribution of three waves of the Oregon
Lifestyle Survey by mail to a random sample of Oregon households. A modified version of
Dillman’s (2000) “Total Design Method” was employed for the survey design and
implementation. Names and addresses were provided by a national survey research company that
has comprehensive lists of public directories. In spring of 2015, two survey waves were sent to
2,200 randomly selected households. Two types of surveys (A & B) were sent out during both
wave one and wave two. Survey A focused on behaviors related to energy and consumerism.
Survey B focused on mobility, food, and water. From the 697 total surveys retuned, 374 were
survey A and 323 were survey B. The response rate for survey A and B combined was calculated
at 36%. This paper uses data from survey B. The primary reason for this is my interest in the
attitude-behavior relationship involving food consuming actions which was included in survey B.
Of the 323 (survey B) surveys returned, approximately 15% were from rural residents
and approximately 85% were from urban residents. Due to the rural sample size not being
representative of the rural population (according to the 2010 Oregon census population,
Oregon’s rural population is larger than 15% of the total population - Population Research
Center, 2014), an additional wave of survey B was administered in a similar manner mailed to
700 randomly selected rural Oregon residential households in spring of 2016. However, this third
wave of survey B was a condensed version; which this version will be called survey C.
24
Investigating my research question did not require all of the data that was in survey B; therefore
survey C was used. Survey C yielded a response rate of 18%. In order to produce a
representative sample of Oregon households for my research, I aggregated the results from the
questions that were present in both survey B and survey C5. This yielded a sample size of 440
households and a rural-urban split of 32% rural and 68% urban.
In order to use the above survey data to determine what factors influence an attitude-
behavior gap, I choose to hold attitudes towards climate change constant and examined whether
ecological food consumption behavior varied. If there is variation, this would indicate a gap.
This was accomplished by creating a subsample of all the respondents who indicated they
believe climate change will cause dramatic and long-term changes to the United States. This
group consisted of 258 respondents (59% of the total sample). Graph 1 highlights that there is
indeed variation of food consumption behavior amongst those that believe that climate change
will have long-term consequences; therefore, showing a gap. Referring to the x-axis in the graph
of Graph 1, ecological food consumption behavior was measured on a standardized index where
an index measure of 0 indicates an individual lies perfectly at the mean. As shown in Graph 1,
this variation in behavior ranges from index score -9 to index score +4. In sum, though all of the
individuals in my subsample believe climate change will cause dramatic and long-term changes
to the U.S., there is an inconsistency within the group in regards to the commitment to act.
5 A copy of Survey C is located in the Appendix D.
25
Graph 1: Frequency of Food Consumption Behavior Index
I then used the subsample to test my hypothesized factors that may influence an
ecological attitude-behavior gap. I conducted a cross-sectional study employing the ordinary
least squares (OLS) estimator to analyze how my primary explanatory factors influence food
consumption behavior amongst individuals who believe that climate change will have dramatic
long-term consequences. I selected ecological food consumption behavior as the primary
dependant variable of interest. Three lifestyle indicator survey questions were used to
operationalize respondent’s ecological food consumption behavior. This behavioral measurement
was developed by standardizing the respondent’s responses to the three questions initially
measured in a 5-point Likert scale. The questions include: “I pay attention to where and how the
food I buy is produced”; “ I try to avoid eating meat as much as possible”; and “I try to reduce
the amount of food waste that my household produces.” Looking particularly at question three,
food waste refers to food discarded at the end of the food line (from farm to table). The
standardized responses from each respondent were then added to develop a behavior index. An
0
.05
.1.1
5.2
.25
De
nsity
-10 -5 0 5FoodBxIndex
26
index measure of 0 indicates an individual lies perfectly at the mean . Individuals who have an
index value above zero are more likely to engage in ecological food consumption behavior
compared to the group average. Similarly, individuals who have an index value below zero are
less likely to engage in these behaviors compared to the group average.
I selected five explanatory variables of interest, which literature has shown to have an
impact on food consumption behaviors. The first indicator is a behavioral belief variable. This
variable measures the level of agreeability on a 5-point Likert scale as to whether a respondent
feels that their, “own personal behavior can bring about positive environmental change.”
Household income is the second indicator. The means to purchase ecologically friendly food
options tend to be more expensive. Therefore, I have included dummy variables that account for
household income. These variables represent three income groupings: income less than $25,000
(baseline dummy), income equal to $25,000 but less than $75,000, and income equal to and
greater than $75,000. Time an individual has in a day may also affect their ecological behavior.
Because a measure of leisure time was not in the survey, I used work status as a proxy for an
individual’s time that they can spend on ecological food consumption behavior. In this case, the
less someone works, the more time they may have to devote to ecological behavior. I created
four proxy categorical dummy variables for the time variable: employed full-time and self-
employed (baseline dummy), employed part-time, retired, and a dummy category that combines
unemployment, student, and other employment status such as not working outside home.
For the proxy variable of environmental knowledge I used level of education attainment.
This is measured as a categorical dummy where individuals were grouped according to attaining
a high school diploma (baseline dummy), undergraduate degree, or graduate degree. Lastly, the
27
explanatory variable food access6 was measured by means of a binary variable describing the
rural/urban location of a household. This variable was developed using the 2013 official Office
of Management and Budget (OMB) rural-urban continuum codes for determining rural and urban
locations (USDA-ERS, 2013). This rural-urban classification differentiates metropolitan counties
by the population size of their metro area, and nonmetropolitan counties by degree of
urbanization and adjacency to a metro area. The USDA-ERS (2013) continuum code range from
1 (most metropolitan) to 12 (least metropolitan). To create a more even distribution between
rural and urban residence, I combined counties who have a score between 3 to12 into the rural
category and scores 1 and 2 are considered urban (metropolitan). Once the sample was
aggregated into either rural or urban, I recoded the scores to reflect a binary distinction, where
0 = rural and 1 = urban. My empirical model can be summarized as follows:
FoodBxIndexi = βo + β1 Bx_beliefi + β2 Incomei + β3Work Statusi + β4 Educationi + β5Accessi
+ Ʃ βkXk,i + Ʃ βmYm,i + Ʃ βnZn,i + εi
Vector ƩβkXk,i includes all of the value variables: political ideology and revised-NEP.
Vector ƩβmYm,i includes the demographic variables: gender and age.
Vector ƩβnZn,i includes the situational variables: number of children in the household.
Variables that I controlled for in this study are as followed. The Revised-New Ecological
Paradigm (revised-NEP) scale is used to measure an individual’s world-view on the relationship
between humans and environment by evaluating an individual’s level of agreement concerning
6 Definitions of each score are located in Appendix A.
28
statements regarding equality between humans and nature and the environment’s sensitivity to
human actions Dunlap et al. (2000). Therefore, the more items an individual supports on the
revised-NEP scale, the more concerned they have for the environment. Within this research, I
employ an abbreviated 6-question version7 of the full 15-question scale (see other research that
has employed modified versions, i.e. Clark, 2002; Cordano, Welcomer, & Scherer, 2003;
Wolters, 2012). This abbreviated version allowed me to maintain a user-friendly survey length.
Scores range from a high of 30, indicating viewing the world with a pro-ecological stance, to a
low of 6, indicating viewing the world with weak ecological concern. The variable ideology is
measured on a scale from 1 to 5, where 1 indicates that someone is very liberal, 2 indicates that
they are liberal, 3 indicates they are moderate, 4 indicates they are conservative, and 5 indicates
they are very conservative. In addition, I include: gender; a binary variable, 1 = female and 0 =
male; age in years measured continuously; and number of kids still living at home as a
continuous variable. All of my variables and how they are measured are detailed in Table 1.
7 Description of constructing the abbreviated version is located in the Appendix B.
29
Table 1: Description of Subsample and Variables
Subsample:
I believe climate change…
1= Will cause dramatic and long-term changes to the United States.
Behavioral Dependant Variable:
Cumulative Standardized Index: -X (non-environmental) to +X (pro-environmental)
I pay attention to where and how the food I buy is produced.
I try to avoid eating meat as much as possible.
I try to reduce the amount of food waste that my household produces.
Explanatory Variables of Interest:
Behavioral Belief Factor:
Behavioral Belief: Likert scale from 1 (strongly disagree) to 5 (strongly agree) Means Factors:
Household Income Dummy: <25k (baseline) , 25k to <75k, ≥75k
Work Status Dummy: Full-Time (baseline), Part-Time, Retired, Other/Student/Unemployed
Information Factor:
Level of Education Dummy: ≤ HSdip (baseline), College Graduate, Graduate School
Access Factor:
ERS Urban/Rural Continuum: Urban = 1 , Rural = 0
Control Variables:
Value Variables:
Political Ideology: Scale from 1 (very liberal) to 5 (very conservative)
revised-NEP: Index from 6 (weak ecological concern) to 30 (strong ecological concern)
Demographic Variables:
Gender: Female=1, Male= 0
Age: Continuous Variable
Situational Variables:
Kids: Continuous Variable
Using the above variables, I ran six series of regressions. The outputs of these regressions
are found in the result’s section of this paper within table 1. The first five of these regressions
each specifically test a different stated hypothesis. The first regression, the Belief model,
examines the impact of behavioral belief on ecological food consumption behavior, while
incorporating values, demographic, and situational control variables. Model 2, Means1, looks at
how respondent’s household income influences ecological food consumption behavior, while
Likert scale
Range 1-5
30
incorporating values, demographic, and situational control variables. Model 3, Means2, analyzes
how work status influences ecological food consumption behavior, while incorporating values,
demographic, and situational control variables. Model 4, info, examines the impact using the
level of educational attainment as a proxy for ecological knowledge on ecological food
consumption behavior, while including values, demographic, and situational control variables.
Lastly, model 5, access, investigates how the level of access to food variety by means of a
rural/urban proxy variable impacts ecological food consumption behavior, while including
values, demographic, and situational control variables.
In order to reduce the impacts of omitted variable bias that each of the above five
regressions suffered from, model 6, the full model, was used for my principal analysis. Model 6
incorporates all explanatory independent variables of interest, belief, means, info, and access,
along with the values, demographic, and situational control variables. The inclusion of all
explanatory variables did cause model 6 to suffer from imperfect multicollinearity8. However, I
did not exclude any correlated independent variables because the collinearity did not
significantly alter the significance of the beta coefficients in model 6 nor did I want to
reintroduce omitted variable bias.
8 Multicollinearity: For model 6, running a pair-wise correlation showed 4 statistically significant negative
correlations between: 1) at most having a high school diploma and annual household income of more than $75,000;
2) full-time work status and retired work status; 3) having a undergraduate degree and at most having a high school
diploma; 4) having a graduate degree and at most having a high school diploma.
31
RESULTS: 9
Table 2: Results of OLS Regression Analysis
1 Baselines: >25k income Dummy; Full-Time Work Dummy; ≤ H.S. Diploma Dummy. Within Box: Control Variables. 2 Full Model (not shown in table 2): F-statistic = 0.000
Table 2, shows the beta coefficients for the individual OLS regressions preformed in
Stata for each independent variable of interest (behavioral belief, means, information, and
access). While controlling for ideology, revised-NEP score, gender, age, and children present in
household, the above regression outputs indicate that behavioral belief, income, and job status
have a statistically significant (at most p <.10) influence on ecological food consumption
behavior.
9 Summary statistics of all variables used in my analysis are contained in the Appendix C.
legend: * p<.1; ** p<.05; *** p<.01
F 10.327 7.119 8.326 7.275 9.200 5.548
r2_a 0.211 0.176 0.224 0.175 0.190 0.248
r2 0.234 0.204 0.255 0.203 0.213 0.303
N 210 202 204 208 211 194
_cons -2.896** -2.402* -2.291* -2.170 -2.249* -3.551**
ersurban_i~u 0.188 0.398
EDU_Graduate 0.206 0.063
EDU_CollGrad 0.033 -0.140
WK_OtherUn~p -1.698* -2.408**
WK_PT -0.689 -1.124**
WK_Retired -0.390 -0.464
INC_75kMore 0.090 -0.612
INC_25ku~75k -0.203 -0.669*
Kids -0.334** -0.293* -0.251 -0.303* -0.314* -0.233
Age 0.011 0.016 0.018 0.015 0.012 0.016
Female 0.715*** 0.745*** 0.860*** 0.704*** 0.791*** 0.705**
NEPindex 0.095** 0.111** 0.117*** 0.102** 0.111*** 0.099**
Ideology -0.544*** -0.464*** -0.563*** -0.491*** -0.519*** -0.488***
Bx_belief 0.338** 0.533***
Variable Belief Means1 Means2 Info Access Full
> F)
. estimate table Belief Means1 Means2 Info Access Full, b(%7.3f) star(.1 .05 .01) stats(N r2 r2_a
Y = FoodBxIndex
1 2
32
The reminder of the results section focuses on the full model and the model’s beta
coefficients that meet the statistically significant threshold of p < .05. Behavioral belief, which
represents a respondent’s level of agreement with the statement, “I feel that my own personal
behavior can bring about positive environmental change,” is statistically significant (p < .01).
This relationship shows that as an individual’s level of agreement with the above statement
increases by 1 Likert scale unit, they will increase their commitment to engage in ecological food
consumption behavior by .533 units holding ideology, revised-NEP, gender, age, and kids
constant.
The only additional factor that had a relationship with food consumption behavior was
the work status portion of the means factor. Within the full model, both dummy variables part-
time work and other (i.e. not working outside home) /student/unemployed work status were
statistically significant at 5%. Therefore, holding ideology, revised-NEP, gender, age, and kids
constant, an individual who works part-time is less likely to engage in ecological food
consumption behavior compared to an individual who works full-time. Similarly, compared to
full time workers, individuals who work from home, a student, or unemployed are less likely to
engage in ecological food consumption behavior
Concentrating on the control variables and interpreting the full model’s beta coefficients,
political ideology demonstrates a robust negative statistical significance (p < .01) throughout all
regressions. This implies that a more liberal political viewpoint is found to be associated with an
increase in partaking in ecological food consumption behavior. The revised-NEP score, which
measures a worldview concerning the human-nature relationship, also has a consistent
statistically significant impact on food consumption behavior. Although, its impact is weak,
individuals with a higher revised-NEP score (aligning with a pro-ecological world-view) also
33
display higher ecological food index. Lastly, the gender dummy shows a stable significance to at
least the 5% level among all the regressions. I found that women were more likely to take up
ecological food consumption behaviors than men.
DISCUSSION AND CONCLUSION:
Even among individuals who agreed that climate change will cause dramatic changes to
the U.S., I found a great deal of diversity among them when it comes to their commitment to
engage in ecological food consumption behavior. The key variables this study identified as
impacting the attitude-behavior gap are belief in one’s positive impact on the environment, work
status, values, and gender.
The first hypothesis was affirmed by the study’s results, where the notion that if an
individual believes that their behavior will bring about a positive environmental change, they
will be more likely to undertake that behavior. This finding is expected based on other relevant
studies, (see Mainieri, Barnett, Valdero, Unipan, & Oskamp, 1997; Lavelle, Rau, & Fahy, 2015)
and the behavioral belief concept within the reasoned action approach(Fishbein & Ajzen, 2010).
Income status did not impact food consumption behavior even though food is the second
largest household expense next to housing for both rural and urban Oregonians (EPI, 2015).
However, work status did impact food behavior although not in the study’s hypothesized
relationship direction. Consequently, this hypothesis was not able to be affirmed.
The work status results indicate that working less does not necessarily imply that there is
an automatic behavioral time trade between working and engaging in ecological food behaviors.
Furthermore, work status and household income have a complex relationship. For example,
someone who works part-time may not need to work full-time because their annual household
income is high enough not to warrant full-time work. On the other hand, a part-time worker may
34
have a low annual household income but cannot work full-time nor do they have the means
(financial or time) to engage in ecological food consumption behavior.
Similar to the means hypothesis, information (education-based) hypothesis and access
(rural/urban divide) hypothesis do not hold true due to statistically insignificant findings. This is
not surprising since previous literature showed mixed results.
What accounts for these outcomes? While previous studies have found a link between
education and higher rates of ecological behavior (Gossard &York, 2003), this link can vary
depending on how information is received (TV or Newspaper) (Jerit, Barabas, & Bolsen, 2006).
With regard to rural and urban differences in access to food variety, while research has
demonstrated that rural residents have less of a selection in food establishments in which to
purchase ecological products, this may be offset by rural residents having better access to harvest
their own food in a potential ecological manner (Morton et al., 2008). If this is the case, then
access would not impact food consumption behavior.
Several control variables were found to have a statistically significant relationship with
food consumption behavior. In line with much of the relevant literature (see Steel, 1996;
Dunlap, Xiao, & McCright, 2001), this study also found that more liberal political viewpoints
were associated with an increase in ecological behavior. Worldview values also had an impact on
food consumption behavior; however, unlike previous studies, my study does not support the
conclusion that the revised-NEP is a strong predictor of ecological behavior (Dunlap et al., 2000;
Teisl et al., 2010). Lastly, my findings parallel the conclusion of previous studies, which show
that females are more likely to engage in pro-ecological behavior (see Xiao & McCright, 2012;
Raudsepp, 2001; Stern & Dietz, 1994).
35
My analysis was limited in several respects. The results are correlational in nature and
should not be interpreted as causal evidence. The survey also suffered from response skewness
where the average age was 63 years of age. In addition, this study’s sample was concentrated in
Oregon; therefore, results may only be generalized to situations within that state. Study results
are also limited to ecological food consumption behaviors.
It is not entirely clear if people understand the role that food consumption plays with
regard to the production of GHG emissions and climate change impacts. However, with food
consumption being one of the top individual actions that Oregonians can take to reduce their
GHG emissions, increasing knowledge of the food consumption lifecycle (farm to fork) is
paramount. This research has demonstrated that there is a strong relationship between self-
efficacy and ecological behavior among Oregonians. Oregonians don’t need to be convinced that
they can help reduce GHG emissions but they can use help in translating their beliefs into
effective activities that will make a difference. Therefore, a public policy implementation which
connects the individual to a behavioral belief-action-outcome may help guide people’s food
decisions towards reducing climate change impacts.
Recommendations for future research could focus on critical case studies. For instance,
research aimed at understanding what factors are involved in eliciting one to believe that their
own behavior can bring about a positive environmental change may help researchers understand
how this belief is formed. Furthermore, since the consumption of food is linked not only to
ecological factors but also to other values, such as religious, cultural, taste, and nutrition,
(Tobler, Visschers, & Siegrist, 2011) future research would benefit from unpacking how these
other values interact with an individual’s readiness to take up ecological food consumption
behaviors. Lastly, because this study was limited to cross-sectional data, longitudinal research
36
analyzing how certain factors impact the engagement of ecological food consumption behavior
would be beneficial in providing a greater insight into the causal ordering of these factors and
how potential changes in these factors can impact an individual throughout their life course.
REFERENCES:
1. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human
decision processes, 50(2), 179-211.
2. Ajzen, I. (2002). Residual effects of past on later behavior: Habituation and reasoned action
perspectives. Personality and social psychology review, 6(2), 107-122.
3. Ajzen, I., & Manstead, A. (2007). Changing health-related behaviors: An approach based on
the theory of planned behavior. The scope of social psychology: Theory and applications, 43-
63.
4. Allport, G. (1935). Attitudes. In Handbook of social psychology. Edited by C. Murchison,
798–844. Worcester, MA: Clark Univ. Press.
5. Andersson, L., Shivarajan, S., & Blau, G. (2005). Enacting Ecological Sustainability in the
MNC: A Test of an Adapted Value-Belief-Norm Framework. Journal of Business Ethics,
59(3), 295-305.
6. Arcury, T. A. (1990). Environmental attitude and environmental knowledge. Human
Organization, 49(4), 300–304.
7. Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human
behavior (Vol. 4, pp. 71-81). New York: Academic Press.
8. Barr, S., Gilg, A.W., Ford, N.J. (2001). A conceptual framework for understanding and
analysing attitudes towards household waste management. Environment and Planning A 33,
2025–2048.
9. Blake, J. (1999). Overcoming the ‘value‐action gap’ in environmental policy: Tensions
between national policy and local experience. Local environment, 4(3), 257-278.
10. Blamey, R. (1998). The Activation of Environmental Norms: Extending Schwartz's Model.
Environment and Behavior, 30(5), 676.
37
11. Brown, K., & Kasser, W. (2004). Are Psychological and Ecological Well-being Compatible?
The Role of Values, Mindfulness, and Lifestyle. Social Indicators Research, 74(2), 349-368.
12. Buttel, F. H. (1975). The environmental movement: Consensus, conflict, and change. Journal
of Environmental Education, 7, 53–63.
13. Campbell, D. (1963). Social Attitudes and Other Acquired Behavioral Dispositions. In S.
Koch (Eds.). Psychology: A study of a science. Study II. Empirical substructure and relations
with other sciences. Volume 6. Investigations of man as socius: Their place in psychology
and the social sciences. , (pp. 94-172). New York, NY, US: McGraw-Hill.
14. Capstick, S. B. (2013). Public understanding of climate change as a social dilemma.
Sustainability, 5(8), 3484-3501.
15. Casey, P. J., & Scott, K. (2006). Environmental concern and behaviour in an Australian
sample within an ecocentric–anthropocentric framework. Australian Journal of Psychology,
58(2), 57-67.
16. Cheung, S. F., Chan, D. K. S., & Wong, Z. S. Y. (1999). Reexamining the theory of planned
behavior in understanding wastepaper recycling. Environment and behavior, 31(5), 587-612.
17. Clark, C., Kotchen, M., & Moore, M. (2003). Internal and external influences on pro-
environmental behavior: Participation in a green electricity program. Journal of
environmental psychology, 23(3), 237-246.
18. Consensus. ie: Consumption, Environment and Sustainability (2014). Environmental
Protection Agency, Ireland. Retrieved from http://www.consensus.ie/wp/wp-
content/uploads/2015/07/EPA-Research-138-final-for-web1.pdf
19. Cordano, M., Welcomer, S., & Scherer, R. (2003). An Analysis of the Predictive Validity of
the New Ecological Paradigm Scale. The Journal of Environmental Education, 34(3), 22-28.
20. Corraliza, J. A., & Berenguer, J. (2000). Environmental values, beliefs, and actions a
situational approach. Environment and behavior, 32(6), 832-848.
21. Crimmins, A., J. Balbus, J.L. Gamble, C.B. Beard, J.E. Bell, D. Dodgen, R.J,. … Ziska, L.
(2016). Executive Summary. The Impacts of Climate Change on Human Health in the United
States: A Scientific Assessment. U.S. Global Change Research Program, Washington, DC,
page 1–24. http://dx.doi.org/10.7930/J00P0WXS
22. Davis, J. L., Le, B., & Coy, A. E. (2011). Building a model of commitment to the natural
environment to predict ecological behavior and willingness to sacrifice. Journal of
Environmental Psychology, 31(3), 257-265.
38
23. De Groot, J., & Steg, L. (2009). Morality and prosocial behavior: The role of awareness,
responsibility, and norms in the norm activation model. The Journal of Social Psychology,
149(4), 425-449.
24. De Ruyter, K., & Wetzels, M. (2000). With a little help from my fans–Extending models of
pro-social behaviour to explain supporters’ intentions to buy soccer club shares. Journal of
Economic Psychology, 21(4), 387-409.
25. Dean, W. R., & Sharkey, J. R. (2011). Rural and urban differences in the associations
between characteristics of the community food environment and fruit and vegetable intake.
Journal of nutrition education and behavior, 43(6), 426-433.
26. DEQ. (2016). Oregon’s 2005 – 2014 Consumption-Based Greenhouse Gas Emissions.
Retrieved from. http://www.deq.state.or.us/lq/pubs/factsheets/GHGInvertory2014.pdf
27. Dietz, T., Fitzgerald, A., & Shwom, R. (2005). Environmental Values. Annual Review of
Environment and Resources, 30, 335.
28. Dillman, D. A. (2000). Mail and internet surveys: The tailored design method (Vol. 2). New
York, NY: Wiley.
29. Drake, J. (2001). Downshifting How to Work Less and Enjoy Life More (Ser. 0). San
Francisco: Berrett-Koehler.
30. Dunlap, R. E., & Van Liere, K. D. (1978). The “new environmental paradigm”. The journal
of environmental education, 9(4), 10-19.
31. Dunlap, R. E., & Van Liere, K. D. (1984). Commitment to the dominant social paradigm and
concern for environmental quality. Social Science Quarterly, 65(4), 1013.
32. Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Jones, R. E. (2000). New trends in
measuring environmental attitudes: measuring endorsement of the new ecological paradigm:
a revised NEP scale. Journal of social issues, 56(3), 425-442.
33. Dunlap, R., Xiao, C., & McCright, A. (2001). Politics and Environment in America: Partisan
and Ideological Cleavages in Public Support for Environmentalism. Environmental Politics,
10(1), 23.
34. Dutta-Bergman, M. J. (2005). Psychographic profiling of fruit and vegetable consumption:
the role of health orientation. Social Marketing Quarterly, 11(1), 19-35.
35. Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich
College Publishers.
39
36. Ellen, P. S., Wiener, J. L., & Cobb-Walgren, C. (1991). The role of perceived consumer
effectiveness in motivating environmentally conscious behaviors. Journal of Public Policy &
Marketing, 102-117.
37. EPA. (2016). Climate Change: Sources of Greenhouse Gas Emissions. Retrieved from.
https://www3.epa.gov/climatechange/ghgemissions/sources.html
38. EPI. (2015). Economic Policy Institute Family Budget Calculator. Retrieved from.
http://www.epi.org/resources/budget/
39. Feygina, I., Jost, J. T., & Goldsmith, R. E. (2010). System justification, the denial of global
warming, and the possibility of “system sanctioned change.” Personality and Social
Psychology Bulletin, 36, 326–338.
40. Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action
approach. New York: Psychology Press (Taylor & Francis).
41. Frick, J., Kaiser, F. G., & Wilson, M. (2004). Environmental knowledge and conservation
behavior: Exploring prevalence and structure in a representative sample. Personality and
Individual differences, 37(8), 1597-1613.
42. Gardner, G. T., & Stern, P. C. (2002). Environmental problems and human behavior (2nd
ed.). Boston, MA: Pearson.
43. Gossard, M. H., & York, R. (2003). Social structural influences on meat consumption.
Human Ecology Review, 10(1), 1-9.
44. Guenther, P., Jensen, H., Batres-Marquez, S., & Chen, C.. (2005). Socio-demographic,
knowledge, and attitudinal factors related to meat consumption in the United States. Journal
of the American Dietetic Association, 105(8), 1266–1274.
45. Hall, K., Guo, J., Dore, M., Chow, C. (2009) The Progressive Increase of Food Waste in
America and Its Environmental Impact. PLoS ONE 4(11): e7940.
doi:10.1371/journal.pone.0007940
46. Han, H., Hsu, L. T. J., & Sheu, C. (2010). Application of the theory of planned behavior to
green hotel choice: Testing the effect of environmental friendly activities. Tourism
management, 31(3), 325-334.
47. Hawcroft, L. & Milfont, T. (2010). The use (and abuse) of the new environmental paradigm
scale over the last 30 years: A meta-analysis. Journal of Environmental Psychology, 30(2),
143-158.
48. Hayden, A. (2001). Good Work, Less Toil. Alternatives Journal, 27(1), 12
40
49. Howell, S. E., & Laska, S. B. (1992). The changing face of the environmental coalition: a
research note. Environment and Behavior, 24(1), 134.
50. Jensen, K. O., & Holm, L. (1999). Preferences, quantities and concerns: Socio-cultural
perspectives on the gendered consumption of foods. European Journal of Clinical Nutrition,
53, 351–359.
51. Jerit, J., Barabas, J., & Bolsen, T. (2006). Citizens, knowledge, and the information
environment. American Journal of Political Science, 50(2), 266-282.
52. Johnson, C. Y., Bowker, J. M., & Cordell, H. K. (2004). Ethnic variation in environmental
belief and behavior an examination of the new ecological paradigm in a social psychological
context. Environment and behavior, 36(2), 157-186.
53. Jones, C., & Kammen, D. (2011). Quantifying carbon footprint reduction opportunities for
U.S. households and communities. Environmental Science & Technology, 45(9), 4088-95.
54. Jones, R. E., & Dunlap, R. E. (1992). The social bases of environmental concern: Have they
changed over time? Rural Sociology, 57(1), 28–47.
55. Kaiser, F., Hübner, G., & Bogner, F. (2005). Contrasting the Theory of Planned Behavior
With the Value‐Belief‐Norm Model in Explaining Conservation Behavior. Journal of
Applied Social Psychology, 35(10), 2150-2170.
56. Kim, Y., & Choi, S. M. (2005). Antecedents of green purchase behavior: An examination of
collectivism, environmental concern, and PCE. Advances in consumer research, 32, 592.
57. Knussen, C., Yule, F., MacKenzie, J., & Wells, M. (2004). An analysis of intentions to
recycle household waste: The roles of past behaviour, perceived habit, and perceived lack of
facilities. Journal of environmental psychology, 24(2), 237-246.
58. Kubberød, E., Ueland, Ø. , Rødbotten, M., Westad, F., & Risvik, E. (2002). Gender specific
preferences and attitudes towards meat. Food Quality and Preference, 13(5), 285–294.
59. LaPiere, R. T. (1934). Attitudes vs. actions. Social forces, 13(2), 230-237.
60. Laroche, M., Bergeron, J., & Barbaro-Forleo, G. (2001). Targeting consumers who are
willing to pay more for environmentally friendly products. Journal of consumer marketing,
18(6), 503-520.
61. Lavelle, M. J., Rau, H., & Fahy, F. (2015). Different shades of green? Unpacking habitual
and occasional pro-environmental behavior. Global Environmental Change, 35, 368-378.
62. Lazarus, Richard J. (2010). Super wicked problems and climate change: Restraining the
present to liberate the future. Environmental Law Reporter, 40(8), 10749-10756.
41
63. Levin, K. (2009). Playing it forward: Path dependency, progressive incrementalism, and the
"Super Wicked" problem of global climate change. IOP Conference Series: Earth and
Environmental Science, 6(50), 2.
64. Lomnitz, L. (2002). ‘‘Reciprocity, redistribution and market exchange in the informal
economy.’’ In F. Adaman and P. Devin (eds.), Economy and Society: Money, Capitalism and
Transition, (pp. 172–191). Montreal, Canada: Black Rose Books.
65. López-Mosquera, N., & Sánchez, M.. (2012). Theory of Planned Behavior and the Value-
Belief-Norm Theory explaining willingness to pay for a suburban park. Journal of
Environmental Management, 113, 251-262.
66. Mainieri, T., Barnett, E., Valdero, T., Unipan, J., & Oskamp, S. (1997). Green Buying: The
Influence of Environmental Concern on Consumer Behavior. The Journal of Social
Psychology, 137(2), 189-204.
67. McCright, A. M., & Dunlap, R. E. (2011). The politicization of climate change and
polarization in the American public's views of global warming, 2001–2010. The Sociological
Quarterly, 52(2), 155-194.
68. Morton, L., Bitto, W., Oakland, E., & Sand, A. (2008). Accessing food resources: Rural and
urban patterns of giving and getting food. Agriculture and Human Values, 25(1), 107-119.
69. NIH (National Institute of Health). (2013). Balance Food and Activity. Retrieved from.
http://www.nhlbi.nih.gov/health/educational/wecan/healthy-weight-basics/balance.htm
70. Nolan, J. & Schultz, P.W. (2015). Prosocial Behavior and Environmental Action. In D.A.
Schroeder & W.G. Graziano (Eds.). The Oxford Handbook of Prosocial Behavior. page 626.
Oxford University Press, USA.
71. Olli, E., Grenstad, G., & Wollebaek, D. (2001). Correlates of Environmental Behaviors:
Bringing Back Social Context. Environment & Behavior, 33(2), 181.
72. Otto, S., & Kaiser, F. G. (2014). Ecological behavior across the lifespan: Why
environmentalism increases as people grow older. Journal of Environmental Psychology, 40,
331-338.
73. Population Research Center. (2014). 2014 annual report tables Portland State University.
Retrieved from http://www.pdx.edu/prc/population-reports-estimates
74. Price, V., & Zaller, J. (1993). Who gets the news? Alternative measures of news reception
and their implications for research. Public opinion quarterly, 57(2), 133-164.
42
75. Raudsepp, M. (2001). Some socio-demographic and socio-psychological predictors of
environmentalism. Trames, 5(4), 355.
76. Reid, L., Sutton, P., & Hunter, C. (2010). Theorizing the meso level: The household as a
crucible of pro-environmental behaviour. Progress in Human Geography, 34(3), 309-327.
77. Reisch, L. A. (2001). Time and wealth: The role of time and temporalities for sustainable
patterns of consumption. Time & Society, 10(2-3), 367-385.
78. Rokeach, M. (1968). Beliefs, attitudes, and values : A theory of organization and change. (1st
ed.). Jossey-Bass behavioral science series. San Francisco, CA: Jossey-Bass.
79. Rotter, J. B. (1966). Generalized expectancies for internal versus external control of
reinforcement. Psychological monographs: General and applied, 80(1), 1.
80. Schultz, P. (1999). Changing Behavior With Normative Feedback Interventions: A Field
Experiment on Curbside Recycling. Basic and Applied Social Psychology, 21(1), 25-36.
81. Schultz, P. W., Oskamp, S., & Mainieri, T. (1995). Who recycles and when? A review of
personal and situational factors. Journal of environmental psychology, 15(2), 105-121.
82. Schultz, P.(2002). Knowledge, information, and household recycling: Examining the
knowledge-deficit model of behavior change. New tools for environmental protection:
Education, information, and voluntary measures, 67-82.
83. Schwartz, S. (1977). Advances in experimental social psychology. (Vol. 10, Advances in
Experimental Social Psychology Volume 10). New York: Academic Press.
84. Schwartz, S. H. (2012). An overview of the Schwartz theory of basic values. Online
Readings in Psychology and Culture, 2(1), 11.
85. Schwepker Jr., C., & Cornwell, T. (1991). An examination of ecologically concerned
consumers and their intention to purchase ecologically packaged products. Journal of Public
Policy & Marketing, 77-101.
86. Sharkey, J. R. (2009). Measuring potential access to food stores and food-service places in
rural areas in the US. American journal of preventive medicine, 36(4), S151-S155.
87. Sjöberg, L. (2000). Factors in Risk Perception. Risk Analysis, 20(1), 1-12.
88. Smith, C. and Morton, L. (2009). Rural Food Deserts: Low-income Perspectives on Food
Access in Minnesota and Iowa. Journal of Nutrition Education and Behavior, 41(3), 176-
187.
43
89. Steel, B. (1996). Thinking Globally and Acting Locally?: Environmental Attitudes,
Behaviour and Activism. Journal of Environmental Management, 47(1), 27-36.
90. Steg, L., Dreijerink, L., & Abrahamse, W. (2005). Factors influencing the acceptability of
energy policies: A test of VBN theory. Journal of environmental psychology, 25(4), 415-425.
91. Stehfest, E., Bouwman, L., Vuuren, D., Elzen, P., Eickhout, M., & Kabat, G. (2009). Climate
benefits of changing diet. Climatic Change, 95(1), 83-102.
92. Stern, P.(2000a). Psychology and the Science of Human–Environment Interactions.
American Psychologist, 55(5), 523-530.
93. Stern, P. (2000b). Toward a Coherent Theory of Environmentally Significant Behavior.
Journal of Social Issues, 56(3), 407.
94. Stern, P. C., Dietz, T., & Guagnano, G. A. (1995). The new ecological paradigm in social-
psychological context. Environment and behavior, 27(6), 723-743.
95. Stern, P., & Dietz, T. (1994). The value basis of environmental concern. Journal of Social
Issues 50(3), 65-84.
96. Stern, P., Dietz, T. & Kalof, L. (1993). Value orientations, gender, and environmental
concern. Environment & Behavior 25, 322-348.
97. Stern, P., Dietz, T., Abel, T., Guagnano, G., & Kalof, L. (1999). A value-belief-norm theory
of support for social movements: The case of environmentalism. Human ecology review,
6(2), 81.
98. Stockholm Environment Institute. (2011). Consumption-Based Greenhouse Gas Emissions
Inventory for Oregon 2005. Retrieved from.
http://www.deq.state.or.us/lq/pubs/docs/ConsumptionBasedGHGEmissionsInventoryORSum
maryReport.pdf
99. Tarrant, M., & Cordell, H. (1997). The effect of respondent characteristics on general
environmental attitude-behavior correspondence. Environment and behavior, 29(5), 618-637.
100. Teisl, M., Anderson, M., Noblet, C., Criner, G., Rubin, J., & Dalton, T. (2010). Are
Environmental Professors Unbalanced? Evidence From the Field. The Journal of
Environmental Education. 42(2), 67-83.
101. Thøgersen, J., & Grunert-Beckmann, S. C. (1997). Values and Attitude Formation Towards
Emerging Attitude Objects: From Recycling to General, Waste Minimizing Behavior.
Advances in consumer research, 24(1).
44
102. Thomas, L. (2008). Alternative Realities: Downshifting Narratives in Contemporary
Lifestyle Television. Cultural Studies, 22(5), 680-699.
103. Tindall, D. B., Davies, S., & Mauboules, C. (2003). Activism of conservation behavior in an
environmental movement: The contradictory effects of gender. Society and Natural
Resources, 16, 909–932.
104. Tjernström, E., & Tietenberg, T. (2007). Do differences in attitudes explain differences in
national climate change policies?. Ecological Economics, 65(2), 315-324.
105. Tobler, C., Visschers, V. H., & Siegrist, M. (2011). Eating green. Consumers’ willingness to
adopt ecological food consumption behaviors. Appetite, 57(3), 674-682.
106. Torgler, B., Garcia-Valiñas, M. A., & Macintyre, A. (2008). Differences in preferences
towards the environment: the Impact of a gender, age and parental effect. Social Science
Research Network Electronic Paper Collection. FEEM Working Paper No. 18.2008. SSRN:
http://ssrn.com/abstract=1105320
107. Turnpenny, J., Lorenzoni, I., & Jones, M.. (2009). Noisy and definitely not normal:
Responding to wicked issues in the environment, energy and health. Environmental Science
and Policy, 12(3), 347-358.
108. USDA-ERS. (2013). The 2013 Rural-Urban Continuum Codes. Retrieved from
http://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx
109. Van Lange, P. A., Joireman, J., Parks, C. D., & Van Dijk, E. (2013). The psychology of
social dilemmas: A review. Organizational Behavior and Human Decision Processes,
120(2), 125-141.
110. Van Liere, K. D. and Dunlap, R. E. (1978). Moral Norms and Environmental Behavior: An
Application of Schwartz's Norm-Activation Model to Yard Burning. Journal of Applied
Social Psychology, 8: 174–188.
111. Van Liere, K. D., & Dunlap, R. E. (1980). The social bases of environmental concern: A
review of hypotheses, explanations and empirical evidence. Public opinion quarterly, 44(2),
181-197.
112. Vermeir, I., & Verbeke, W. (2006). Sustainable food consumption: Exploring the consumer
“attitude–behavioral intention” gap. Journal of Agricultural and Environmental ethics, 19(2),
169-194.
113. Wall, G. (1995). General Versus Specific Environmental Concern A Western Canadian Case.
Environment and Behavior, 27(3), 294-316.
45
114. Wandel, M., & Bugge, A. (1997). Environmental concern in consumer evaluation of food
quality. Food Quality and Preference, 8(1), 19–26.
115. Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior
change? A meta-analysis of the experimental evidence. Psychological bulletin, 132(2), 249.
116. Werner, P. (1978). Personality and attitude-activism correspondence. Journal of Personality
and Social Psychology, 36(12), 1375-1390.
117. Wicker, A. W. (1969). Attitudes versus actions: The relationship of verbal and overt
behavioral responses to attitude objects. Journal of social issues, 25(4), 41-78.
118. Wolters, E. A. (2012). Attitude-behavior consistency in household water consumption. The
Social Science Journal, 51(3), 455.
119. Wrigley, N., Warm, D., Margetts, B., & Whelan, A. (2002). Assessing the impact of
improved retail access on diet in a 'food desert': a preliminary report. Urban Studies, 39(11),
2061-2082.
120. Xiao, C., & McCright, A. (2012). Explaining Gender Differences in Concern about
Environmental Problems in the United States. Society & Natural Resources, 25(11), 1067-
1084.
121. Zelezny, L. C., Chua, P., & Aldrich, C. (2000). Elaborating on gender differences in
environmentalism. Journal of Social Issues, 56(3),443–457.
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APPENDICES:
Appendix A: 2013 rural-urban continuum codes
Metropolitan Counties Codes
1 In large metro area of 1+ million residents
2 In small metro area of less than 1 million residents
Nonmetropolitan Counties Codes
3 Micropolitan area adjacent to large metro area
4 Noncore adjacent to large metro area
5 Micropolitan area adjacent to small metro area
6 Noncore adjacent to small metro area and contains a town of at least 2,500 residents
7 Noncore adjacent to small metro area and does not contain a town of at least 2,500
residents
8 Micropolitan area not adjacent to a metro area
9 Noncore adjacent to micro area and contains a town of at least 2,500
residents
10 Noncore adjacent to micro area and does not contain a town of at least 2,500
residents
11 Noncore not adjacent to metro or micro area and contains a town of at least 2,500
residents
12 Noncore not adjacent to metro or micro area and does not contain a town of at least 2,500
residents
Appendix B: Construct of the Abbreviated 6-Question New Ecological Paradigm Index
Scale
Within the survey, respondents were asked to indicate their level of agreement with each of
the below six questions. Responses ranged from 1 = Strongly Disagree to 5 = Strongly
Agree.
1. The balance of nature is very delicate and easily upset by human activities.
2. Humans have the right to modify the natural environment to suit their needs.
3. We are approaching the limit of people the earth can support.
4. The so-called "ecological crisis" facing humankind has been greatly exaggerated.
5. Plants and animals have as much right as humans to exist.
6. Humans were meant to rule over the rest of nature.
In order to develop the scale, question 2, 4, and 6, which are negatively worded, were reverse
coded so that high values indicated the same response meaning on every question. I then
added the responses to each of questions to create a cumulative index. Scores within this
index range from a high of 30, indicating a respondent views the world with a pro-ecological
stance, to a low of 6, indicating viewing the world with weak ecological concern.
47
Appendix C: Summary Statistics for Subsample
Kids 227 .3744493 .8014694 0 5
Age 256 62.44141 13.8061 30 92
Female 255 .5960784 .4916471 0 1
NEPindex 252 23.80159 3.394441 17 30
Ideology 245 2.444898 .8260764 1 4
ersurban_i~u 258 .6899225 .4634241 0 1
EDU_Graduate 253 .3359684 .4732641 0 1
EDU_CollGrad 253 .2213439 .4159744 0 1
EDU_HSdip 253 .4426877 .497689 0 1
WK_OtherUn~p 248 .016129 .1262265 0 1
WK_PT 248 .0846774 .2789641 0 1
WK_FT 248 .3387097 .4742281 0 1
WK_Retired 248 .5604839 .4973319 0 1
INC_75kMore 236 .3177966 .4666096 0 1
INC_25ku~75k 236 .5169492 .5007747 0 1
INC_under25k 236 .1652542 .3721992 0 1
Bx_belief 256 4 .9031535 1 5
FoodBxIndex 255 .3391617 2.018732 -6.316827 4.585572
Variable Obs Mean Std. Dev. Min Max
48
Appendix D: Oregon Lifestyle Survey ( C )
Lifestyle Survey
Please return surveys to:
Lifestyle Survey School of Public Policy
307 Gilkey Hall Oregon State University Corvallis, OR 97331-6206
541-737-2811
ID # _______________________________ [for mailing purposes only]
49
Lifestyle Survey 1:
Part A: General Attitudes Questions: Q1. In general, how concerned are you about your individual impact on resource use?
1. Very concerned 2. Somewhat concerned 3. Not concerned 4. No opinion/Don’t know
Q2. Would you be willing to do any of the following to reduce your household’s energy use? (Please circle all that apply)
1. Buy products with less packaging 2. Buy more energy-efficient appliances 3. Reduce your car use 4. Share your appliances with neighbors (e.g. washing machine, power tools, etc.) 5. Reduce use of home heating (e.g. turn down thermostat) 6. Reduce use of home air conditioner (e.g. use only on days above a certain temperature)
Q3. To what extent do you agree with the following statements? Please circle one.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
a. I feel that my own personal behavior
can bring about positive environmental change.
1 2 3 4 5
b. I would be willing to accept cuts in my standard of living, if it helped to protect the environment.
1 2 3 4 5
c. I would be willing to pay higher prices for goods and services, if it helped protect the environment.
1 2 3 4 5
d. I would be willing to support higher taxes, if it helped to protect the environment.
1 2 3 4 5
e. I would be willing to sacrifice some personal comforts in order to save energy.
1 2 3 4 5
Q4. I believe climate change…
1. Will cause dramatic and long-term changes to the United States. 2. Will cause changes but these will be small and easily dealt with. 3. Will make little difference to the United States. 4. Is exaggerated. 5. Is not real.
50
Part B: Transportation Questions: Q5. Which method of transport do you most frequently use to travel to work or school?
(Please circle one option)
1. Walk 2. Cycle 3. Bus/train 4. Car - gasoline (driver) 5. Car – hybrid or electric 6. Car (carpool or vanpool) 7. Car share (Uber, Zipcar, etc.) 8. Motorcycle 9. Light Rail 10. N/A
Q6. If you do not use public transportation, what is the primary reason for not using public transportation? (Please circle one option)
1. It’s too expensive 2. It’s unreliable 3. It’s very restrictive (can’t go when and where I want) 4. It’s unsafe 5. It’s unhygienic 6. I need to carry heavy/bulky things 7. I need to give rides to others 8. I need the car for work 9. Don’t know 10. Other (please specify)________________________________________________________
Q7. In your opinion, what is the biggest benefit of driving a car?
1. It’s very flexible (freedom to travel) 2. I can carry heavy/bulky things 3. I can give rides to others 4. I’m protected from bad weather 5. It’s safer (less risk of an accident) 6. Don’t know 7. Other (please specify)___________________________________________________________ 8. There are no benefits to driving a car
51
Q8. In your opinion, which one of the following would encourage people most to reduce their journeys by car? (Please circle one option)
1. An increase in the cost of fuel/parking/toll charges 2. Improved/more affordable public transportation 3. Improved bike lanes, footpaths and pedestrian crossings 4. More financial incentives to encourage people to walk/cycle 5. Easier online transactions such as banking, shopping, e-government 6. I don’t believe there is any encouragement that would make people leave their car at home 7. Don’t know 8. Other (please specify)________________________________________________________
Part C: Food Section: Q9. What is the most important issue for you when you buy food? (Please choose top three)
1. Price 2. Healthy benefits/Nutritional content 3. Where/how food is produced (i.e. fair-trade, organic) 4. Taste/Flavor 5. Brand 6. It’s easy to cook (i.e. convenience food/frozen meals) 7. Other (please specify)___________________________________________________________
Q10. If you buy fresh produce, where do you buy it? (Please choose top three)
1. Farmers market 2. Community Supported Agriculture (CSA) 3. Supermarket 4. Food Co-op 5. On-line 6. Other (please specify)__________________________________________________________ 7. Don’t know
Q11. Do you cultivate a garden or grow your own food?
1. Every year 2. Most years 3. Some years 4. Occasionally 5. I don’t cultivate a food garden
52
Q12. To what extent do you agree with the following statements? Please circle one.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
a. I pay attention to where and how the food I buy is produced.
1 2 3 4 5
b. I try to avoid eating meat as much as possible.
1 2 3 4 5
c. I trust eco-labels. 1 2 3 4 5
d. I try to reduce the amount of food waste that my household produces.
1 2 3 4 5
e. Food that is local, organic or fair-trade
is too expensive to buy.
1 2 3 4 5
Q13. Does your household compost? (please choose one option)
1. Yes (Go to Q15) 2. No (if no, please continue to Q14a) 3. Don’t know (Go to Q15)
Q14a. If no, what would encourage your household to start composting? (Please choose one option)
1. Better facilities 2. More space 3. Financial incentives (to reduce waste/start composting) 4. If friends and family were also composting 5. More information 6. None of the above would encourage me to start composting 7. Don’t know 8. Other (please specify)_______________________________________________________
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Part D: Water:
Q15. To what extent do you agree with the following statements? Please circle one.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
a. I pay attention to the amount of
water I use. 1 2 3 4 5
b. I have the right to use as much water as I want.
1 2 3 4 5
c. I don’t need to save water – there is plenty of it.
1 2 3 4 5
d. Using less water would be unhygienic. 1 2 3 4 5 Q16. Has your household cut down on water use over the last year for environmental reasons?
1. Yes 2. No 3. Don't know 4. No, but I intend to in the future
Part E: Attitudes Toward the Environment Q17. Listed below are statements about the relationship between humans and the environment. For each,
please indicate your level of agreement.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
a. The balance of nature is very delicate and easily upset by human activities.
1 2 3 4 5
b. Humans have the right to modify the natural environment to suit their needs.
1 2 3 4 5
c. We are approaching the limit of people the earth can support.
1 2 3 4 5
d. The so-called "ecological crisis" facing humankind has been greatly exaggerated.
1 2 3 4 5
e. Plants and animals have as much right as humans to exist.
1 2 3 4 5
f. Humans were meant to rule over the rest of nature.
1 2 3 4 5
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Part F: Conclusion
We now have a few concluding questions to check to see if our survey is representative of all types of people. We also have included a couple of questions concerning politics. Please remember that all answers are completely confidential. Q18. What is your current age in years?__________________________ Q19. Please indicate your gender. 1. Female 2. Male Q20. If you have children, how many still live at home?________ Q21. Do you own or rent your residence? 1. Own 2. Rent Q22. In which type of residence do you live? 1. Mobile home or trailer 2. One family house – detached 3. A building with apartments 4. A family house attached to one or more houses 5. Other________________________________________________________ Q23. What level of education have you completed? 1. Grade School 2. Middle or junior high school 3. High School 4. Vocational School 5. Some college 6. College graduate 7. Graduate school 8. Other________ Q24. Which of the following best describes your current work situation? 1. Employed full-time 2. Employed part-time 3. Not employed outside the home 4. Unemployed 5. Retired 6. Student 7. Self Employed 8. Other________________________________________________________ Q25. How would you describe your political ideology? 1. Very Liberal 2. Liberal 3. Moderate 4. Conservative 5. Very Conservative Q26. How would you describe your partisan affiliation? 1. Strong Democrat 2. Democrat 3. Independent 4. Republican 5. Strong Republican
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Q27. Which category best describes your household income (before taxes) in 2014? 1. Less than $10,000 2. $10,000-$14,999 3. $15,000-$24,999 4. $25,000-$34,999 5. $35,000-$49,999 6. $50,000-$74,999 7. $75,000-$99,999 8. $100,000-$149,999 9. $150,000-$199,999 10. $200,000 or more Q28. What is your zip code? _________________________________________ Those are all the questions we have. If you have any additional comments, please include those on a separate piece of paper. Thank you for your time.
