Promoting Sustainable Consumption Behaviors: The Impacts of Environmental Attitudes and Governance in a Cross-National Context

Abstract

This article assesses the impacts of individual-level environmental attitudes and national-level environmental governance on individual sustainable consumption. Multilevel analysis based on data from 31 countries shows that three key environmental attitudes, environmental concern, environmental efficacy, and perceived environmental impact, are all positively associated with sustainable consumption behavior. Environmental governance is found to have different impacts in high-income compared with other countries analyzed. In high-income countries, effective environmental governance encourages people to participate in sustainable consumption, whereas it discourages people’s participation in other countries. In addition, in high-income countries, people with strong proenvironmental attitudes are more likely to consume sustainably in the face of weak environmental governance; in other countries, however, the attitude–behavior association is strengthened in the face of effective governance. The results highlight the importance of individual attitudes and the broader context in influencing proenvironmental behaviors, and suggest that sustainable consumption should be understood as a social process accomplished through collaboration between individual consumers and institutions.

Keywords

sustainable consumption environmental governance attitude–behavior gap multilevel analysis cross-national research crowding out effect

Introduction

Consumption is an important economic and social activity. It has grown at an unprecedented pace, reaching $43 trillion US dollars in 2013, accounting for more than 60% of GDP worldwide (World Bank, 2015). Behind this large-scale consumption, massive natural resources are being depleted, local and global environments are being polluted, and biodiversity of many habitats is in danger. Sustainable consumption is thus proposed as a replacement for traditional consumption patterns that are unequally distributed and result in significant environmental damage (United Nations, 1998). In recent years, a growing emphasis has been placed on individual attitudes and intentions toward sustainable consumption and their impacts on actual consumption behaviors; however, many previous studies have failed to find the link between environmental motivation and sustainable consumption behaviors (SCBs; Davies, Foxall, & Pallister, 2002; Moisander, 2007).

Some argue that the individualist perspective, to a large extent, may overshadow the importance of institutional driving forces and barriers; as such, there has been a call for research on broader institutional contexts that construct expectation, social norms, and material infrastructure for successful implementation of sustainable consumption (Peattie, 2010; Spaargaren, 2011). Empirical studies provide strong evidence of the effect of context on SCBs and other environmentally friendly practices. Macias and Williams (2016) found that after accounting for environmental concern and background characteristics, individuals living in closely connected neighborhoods are more likely to purchase chemical-free produce, use less water and household energy, and drive less due to exposure to a variety of perspectives. Based on a survey in the United States, Schultz, Bator, Large, Bruni, and Tabanico (2013) revealed that litter rates significantly dropped in locations where trash receptacles were available and sufficient, and less litter was present in the site. Recent community-based social marketing programs also illustrate the effectiveness of sustainable behavior change within communities (McKenzie-Mohr, 2011). Most research concerning the contextual effect primarily focuses on the community level, yet only a few studies take a further step and examine a broader geographical scale. This is surprising, given that the environmental context within neighborhoods or communities is largely constructed and influenced by institutional forces such as government policy, market strategies, and civic participation at the societal level.

The aim of this study is to address these gaps in the literature and examine how individual attitudes and institutional context work together to affect individuals’ engagement in sustainable consumption. More specifically, multilevel modeling techniques and data from 31 countries were used to investigate the relationship between environmental attitudes and SCBs, and to explicitly explore the role of environmental governance—one of the fundamental institutional driving forces that affect human–environment relationships involving a wide range of actors—in influencing individual SCB. Although many previous studies have been conducted concerning the attitude–behavior gap within sustainable consumption, no definitive answers have been found. This may be partly due to the fact that much research is based on experimental and ethnographic data from one specific country. The use of a cross-national data set in this study provides an opportunity to quantitatively assess this relationship across countries and mitigate potential bias within particular economic and cultural backgrounds. In addition, by focusing on the extent to which national-level environmental governance shapes individual consumption decision making and is involved in the attitude–behavior transition, the current research responds to the current lack of incorporating contextual influence into the analysis. Thus, this study contributes to current scholarship by increasing the understanding of sustainable consumption as a social process, suggesting integrating top-down and bottom-up strategies constructed systematically by agents at multiple levels, and pointing the way to more balanced social and environmental development through collaboration between institutional practices and individual efforts.

Individual Environmental Attitudes

Environmental social psychologists and sociologists have examined a wide range of factors internal to the individual that may stimulate SCBs, such as environmental knowledge, awareness, experience, efficacy, and values. Numerous studies have shown that some of these factors (e.g., environmental knowledge) are not necessarily prerequisites for environmentally friendly behavior (Kollmuss & Agyeman, 2002; McKenzie-Mohr, 2011). Therefore, this study focuses on three environmental attitudes that are likely to be more relevant to SCB: environmental concern, environmental efficacy, and perceived environmental impact.

The impact of environmental concern on SCB is one of the most widely studied topics in environmental studies, with some research concluding that environmental concern is positively associated with SCBs (Minton & Rose, 1997; Roberts & Bacon, 1997), and others suggesting that high environmental concern alone does not always result in engagement in sustainable consumption (Bang, Ellinger, Hadjimarcou, & Traichal, 2000; Kollmuss & Agyeman, 2002; Poortinga, Steg, & Vlek, 2004). In a qualitative study of sustainable consumers in Ireland, Connolly and Prothero (2008) found that consumers often fail to maintain a “green” lifestyle even with strong concern for the environment due to everyday dilemmas and situational choice. Recent studies also report that the relationship between environmental concern and SCBs is mediated through other mechanisms such as environmental efficacy and social norms (Oreg & Katz-Gerro, 2006; Straughan & Roberts, 1999; Vermeir & Verbeke, 2006).

According to Ajzen’s (1991, 2005) theory of planned behavior and Stern’s (2000) value-belief-norm theory, in addition to environmental concern, environmental efficacy (or perceived consumer effectiveness) is also critical in determining actual environmental behavior. Environmental efficacy is based on the evaluation of individual capability and the opportunities and resources embedded in the individual’s social context. It captures the extent to which individuals believe their efforts can make a difference in environmental improvement (Ellen, Wiener, & Cobb-Walgren, 1991), thus making it a necessary belief that directs consumers toward actual SCBs. Previous studies from different countries demonstrate that high perceived consumer effectiveness promotes the purchase of environmentally safe products as well as recycling behaviors (Ellen etal., 1991; Vermeir & Verbeke, 2008; Vicente-Molina, Fernández-Sáinz, & Izagirre-Olaizola, 2013). In fact, some studies found that perceived environmental efficacy is the strongest predictor of SCBs compared with other demographic characteristics and psychological attributes (Roberts, 1996; Straughan & Roberts, 1999).

Perceived environmental impact on everyday life is another important predictor of SCBs at the individual level, as it evokes emotional reactions toward environmental degradation and increases individual commitment to environmental protection (Chawla, 1999). Many people engage in sustainable consumption, such as purchasing organic food and using efficient means of energy, not because they are concerned about the environment in a broader sense, but rather that a polluted environment may pose threats to their well-being (Baldassare & Katz, 1992; Fransson & GäRling, 1999).

Environmental Governance

Lemos and Agrawal (2006) defined environmental governance as “the set of regulatory processes, mechanisms and organizations through which political actors influence environmental actions and outcomes,” involving state, businesses, communities, mass media, nongovernmental organizations (NGOs), and other stakeholders (p. 298). Built upon the alliance of multiple agents, environmental governance is designed to address the externalities associated with the consumption of natural resources and formulates environmental discourse and material infrastructure that mobilize individual incentives in favor of responsible environmental outcomes (Lemos & Agrawal, 2006; United Nations Environmental Programme, 2016).

Previous studies have found that environmental governance is important in solving and mitigating environmental problems such as resource waste, ecosystem degradation, climate change, and ozone depletion (Betsill & Bulkeley, 2004; Dauvergne, 2011; Prakash & Potoski, 2006; Robertson, 2004). Similarly, environmental governance may also have a positive influence on individual sustainable consumption. World polity, or world society, scholars emphasize a global cultural model of universalism, individualism, cosmopolitanism, and rational progress as well as the transnational penetrating influence of international organizations in modern society (Boli & Thomas, 1997; Meyer, Boli, Thomas, & Ramirez, 1997). They apply this neoinstitutional approach to the study of nature–society interaction and note that the proliferation of a global environmental regime characterized by highly interconnected international nongovernmental associations, intergovernmental organizations, and treaties calling for balanced social development significantly contributes to sustainable development at multiple levels (Frank, Hironaka, & Schofer, 2000b; Meyer, Frank, Hironaka, Schofer, & Tuma, 1997).

Researchers identify two ways through which world polity boosts environmental practices: the transnational diffusion of cultural principles and codes of ethics, and the global mobilization of associational resources (Frank etal., 2000b; Longhofer & Schofer, 2010). The world environmental regime constructs and spreads environmental culture globally, increases people’s awareness and concern for the environment, and legitimizes an international value system on environmental protection (Boli & Thomas, 1997; Frank, Hironaka, & Schofer, 2000a; Wapner, 1996). Givens and Jorgenson (2013) assessed the impact of world polity on individual environmental concern in 37 countries and conclude that the presence of environmental international NGOs (EINGOs) and environmental ministries reinforces environmental attitudes at the individual level. The global environmental regime also directly funds and organizes local environmental activities and movements; lobbies and monitors governments, businesses, and other social actors on environmental issues; promotes sustainable production–consumption systems; and fosters networks among organizations (Longhofer & Schofer, 2010; Shandra, 2007; Shandra, Leckband, McKinney, & London, 2009). Different from assumptions of the old institutionalism, world polity is built upon autonomous and purposive collective as well as individual agents, who are willing and able to transcend their personal interests for the common good and take agentic responsibility (Meyer, 2010). Accordingly, world polity theory predicts that under the influence of a world environmental regime, environmental governance increases individuals’ participation in sustainable consumption, especially those who already embrace environmental values and norms.

In addition to the institutional effect penetrating down to individuals, Gardner and Stern (1996) reviewed four specific intervention approaches that facilitate individuals’ proenvironmental behavior: (a) institutional efforts to improve the material incentive structure through rewards and penalties, (b) education to change attitudes and deliver knowledge and information, (c) small group or community management to establish shared norms and expectations, and (d) moral, religious, and/or ethical appeals that strengthen environmental values and beliefs. Combing the world polity theory and the four approaches, environmental governance may affect individual SCBs in various ways. To begin with, by shaping environmentally friendly discourse and offering organizational support, effective environmental governance encourages green production and imposes environmental taxes on industries and products that have, historically, been heavy polluters. For example, taxes account for between 40% and 60% of the sales price of motor fuels in European nations, which is substantially higher than their equivalent in the United States. This has changed both producer and consumer behavior toward environmentally friendly innovation and purchasing decisions, resulting in emissions of carbon dioxide from transport in Europe that are 2 to 3 times lower than in the United States (European Environment Agency, 2006). The use of market incentives has been found to stimulate the invention, application, and spread of sustainable technology and utilities, a process that gradually discards inefficient energy and environmentally unfriendly commodities and provides opportunities to incorporate sustainable consumption into individuals’ everyday routines (Van Vliet, Chappells, & Shove, 2005).

In addition to the fiscal approach, environmental governance reforms consumption habits by enhancing “soft” instruments such as educational programs and community norm cultivation (Macias & Williams, 2016) and internalizing environmental preferences. Based on a study of a local organic food network in the United Kingdom, Seyfang (2006) found that sustainable food consumption is possible through the promotion of ecological citizenship and the development of informed, educated communities about food through education, farm visits, outreach, and websites. Liu, Wang, Shishime, and Fujitsuka (2012) revealed that urban residents in China participate more in sustainable consumption when provided with accurate and sufficient product-related environmental information. It is not uncommon to observe that environmental governance works through a hybrid of these approaches. For instance, the media coverage of sustainable resource use may increase individuals’ environmental literacy and contribute to the development of social norms and expectations on relevant issues.

Some research suggests that environmental governance may decrease individuals’ involvement in sustainable consumption. The crowding out effect, first discovered by economists (Titmuss, 1972) and applied later in environmental studies (e.g., Frey & Oberholzer-Gee, 1997), implies that institutional intervention designed to motivate prosocial behavior sometimes actually leads to the crowding out of an individual’s sense of public spiritedness and decreased participation. It takes place through two mechanisms: financial compensation and responsibility shift. First, by using monetary rewards to compensate for people’s time and effort devoted to public good, external incentives turn voluntary goodwill into economic calculation and reduce individuals’ willingness to proactively behave sustainably (Deci, 1971; Frey & Jegen, 2001). In a survey study based on a community in central Switzerland, Frey and colleagues (Frey & Oberholzer-Gee, 1997; Frey, Oberholzer-Gee, & Eichenberger, 1996) find that in the reward-free scenario, around half of the respondents agree to accept nuclear waste disposal in their community, hoping to promote public good; however, when provided with financial compensation, the level of acceptance dropped by half (from 51% to 25%).

Second, in the study of common pool resources, researchers find that institutional intervention shifts responsibility from individuals to institutions and generates self-interested behaviors (Ostmann, 1998). If environmental governance is perceived to be well-functioning, consumers will increasingly ascribe the responsibility of environmental protection to formal organizations such as governments, corporations, and NGOs rather than individuals. These organizations, as opposed to autonomous individuals, are perceived to have more power and resources with which to address environmental problems. Through coordination and cooperation, these institutional actors are also perceived to be more effective and efficient in reducing consumption-related resource depletion and pollution (Fahlquist, 2009). If these institutional actors recognize the significance of sustainability, take environmentally friendly actions, and make progress toward a cleaner environment and well-maintained ecosystem, it may disqualify individual efficacy and even exempt individuals from moral obligations regarding the environment. Cardenas, Stranlund, and Willis (2000) performed a series of experiments in rural Colombia, and reveal that institutional regulation encourages residents to pursue self-interests that often lead to environmental degradation and abandon group-oriented strategies.

Whether external intervention affects individual behavior positively or negatively depends on two conditions: (a) whether the external intervention is perceived to be supportive or controlling, and (b) whether the individuals affected have high or low degree of self-determination, self-esteem, and possibility for expression (Frey, 2012; Frey & Jegen, 2001). Empirical evidence supports the argument. For example, drawing on common pool resource games conducted in four villages in Cambodia, Travers, Clements, Keane, and Milner-Gulland (2011) found that treatments that create opportunities for self-organization and local decision making among resource users promote cooperation and reduce individual extraction. A field experiment in Mexico reveals that a history of institutional corruption leads to low trust in community leaders and low participation rate in collecting litter from village streets (Kerr, Vardhan, & Jindal, 2012). In their study of modernization and values across the world, Inglehart and his collaborators (Inglehart, 2003; Inglehart & Baker, 2000; Inglehart & Welzel, 2003) suggest that compared with lower income countries, high-income countries are more likely to have democratic institutions, and citizens in general show higher levels of self-expression and political activism. Therefore, the impact of external intervention such as environmental governance on individual SCBs may be divergent in countries with different income levels depending on the smoothness of interactions between institutions and individuals as well as citizens’ levels of self-determination and self-expression. In high-income countries where negotiations between institutions and individuals are thorough and democratic and the level of expression and self-determination is high, environmental governance is likely to encourage individual engagement, whereas the opposite is true in other countries.

Like other contextual factors, the impact of environmental governance on SCBs is also likely to be contingent on individuals’ attitudes or beliefs. If environmental governance facilitates SCBs, then this may have a stronger influence on individuals with proenvironmental attitudes than those without due to increased convenience and affordability in a supportive context. In fact, using data from three areas in Canada, Derksen and Gartrell (1993) supported this existence of an interaction effect of context between attitude and recycling behavior. In their study, an environmentally friendly attitude translates into recycling behavior only among residents with easy access to a structured recycling program. Similarly, if environmental governance discourages individual engagement in sustainable consumption, then this suppressing effect may be more obvious among people who are less concerned for the environment because they are not internally motivated enough to overcome the contextual barriers.

Taken together, previous studies have identified important predictors of SCBs and discussed underlying influential mechanisms. Most research focused on the individualist explanation and ignored, to a large extent, the impact of the institutional context. The practices of sustainable consumption are deeply embedded in the social sphere (rather than being isolated individual behaviors); therefore, it is critical to examine how macrolevel factors such as environmental governance either facilitate or mitigate sustainable consumption. In addition, even though acknowledging the importance of environmental governance, the existing, limited relevant studies have not attained consensus about how it influences individual sustainable consumption. To address these gaps in existing literature, this study empirically examines three research questions based on cross-national data in the following sections:

Research Question 1: How do environmental attitudes influence SCBs in a cross-national context?

Research Question 2: How does national-level environmental governance influence individual SCBs in countries of different income levels?

Research Question 3: To what extent does environmental governance encourage or inhibit the transition from environmental attitudes to SCBs?

Data and Method

Three data sets are combined for this analysis. The individual-level data are from the most recent wave of three surveys on the environment module launched by the International Social Survey Programme 2010 on Environment III (ISSP2010). The ISSP2010 survey investigates a series of environmental attitudes and behaviors in 32 societies. The national-level variable, environmental governance, was obtained from the Environmental Sustainability Index (ESI; Yale Center for Environmental Law and Policy, Center for International Earth Science Information Network at Columbia University, World Economic Forum, & Joint Research Centre of European Commission, 2005), one of the most acknowledged global environmental indices and widely used in environmental studies (Parris & Kates, 2003). All national-level control variables are from the World Development Indicators (World Bank, 2015). Taiwan is excluded from the analysis due to missing data on national-level variables. The final analytical sample includes 39,496 respondents from 31 countries. It is important to note that despite the large sample size at the individual level, there are only 31 observations at the national level. Therefore, findings from the current research should be used with caution when analyzing similar phenomena in countries outside of the current sample. Online Appendix Table S1 reports all countries in the analysis.

Six items evaluate SCBs in ISSP2010; however, the frequency of respondents’ reduction in driving a car for environmental reasons was excluded from the index because around one-quarter of the respondents do not own or cannot drive a car. The remaining five items ask about the frequency of respondents’ special efforts to do the following for environmental reasons: (a) sort glass or tins or plastic or newspapers, and so on, for recycling; (2) buy fruits and vegetables grown without pesticides or chemicals; (c) reduce the energy or fuel used at home; (d) choose to save or reuse water; and (e) avoid buying certain products. Answers were given along a 4-point scale, ranging from 1 (always) to 4 (never). The second and fifth items measure purchase behavior, the third and fourth items measure resource use behavior, and the first item measures postuse behavior (Peattie, 2010). Together, these items evaluate important aspects of the sustainable consumption process. The Cronbach’s alpha value of the five items is .74, indicating an acceptable level of internal consistency. The dependent variable, the SCB index, is derived from these five items by reversing the values and taking their average, with higher values indicating a higher level of SCB.

The following three variables were used to measure environmental attitudes: environmental concern, environmental efficacy, and perceived environmental impact. The corresponding question in the survey for environmental concern is “Generally speaking, how concerned are you about environmental issues,” which is measured on a 5-point rating scale varying from 1 (not at all concerned) to 5 (very concerned). The variable of environmental efficacy is a constructed index from respondents’ agreement on six statements: (a) It is too difficult for someone like me to do much about the environment; (b) I do what is right for the environment, even when it costs more money or takes more time; (c) there are more important things to do in life than protect the environment; (d) there is no point in doing what I can for the environment unless others do the same; (e) many of the claims about environmental threats are exaggerated; and (f) I find it hard to know whether the way I live is helpful or harmful to the environment. The Cronbach’s alpha value of the six items is .67, which is not optimal but sometimes used in the literature focused on similar contexts (e.g., Bland & Altman, 1997; Howell, Shaw, & Alvarez, 2015; Poortinga etal., 2016). A further factor analysis shows that there is one factor underlying the items on the efficacy scale (eigenvalue = 2.29, percentage variance = 38.11). The second item is reverse-coded, and then the average values are calculated. The third variable, perceived environmental impact, is derived from respondents’ agreement on the statement, “Environmental problems have a direct effect on my everyday life,” with its 5-point Likert-type scale ranging from 1 (disagree strongly) to 5 (agree strongly). For all three variables, higher values indicate stronger proenvironmental attitudes.

As mentioned, environmental governance is a multidimensional concept, making it difficult to capture its complex nature using a single variable. Therefore, the key national-level predictor, environmental governance, is an indicator built upon 12 carefully selected variables constructed by the ESI research team (see Table 1; Yale Center for Environmental Law and Policy etal., 2005). By incorporating variables such as level of environmental protection, innovation in environmental studies, EINGO participation, and institutional effectiveness, this indicator provides a comprehensive evaluation of the level of environmental governance in a given country. One common critique against the use of a composite measure is that the application of nontransparent or unsound methods may affect its validity. Fortunately, to ensure reliability and validity of the indicators, the ESI team provides in-depth descriptions of the statistical techniques used to calculate the indicators and has carried out a series of uncertainty and sensitivity analyses (see Appendix A in the ESI report). More importantly, the data are standardized and transformed to facilitate cross-national comparison, making them suitable for the current analysis. The most recent version is available for the year 2005; regardless, this variable is used in this study to predict behavior in 2010, considering the potential lagged impact of governance on individual behavior.

Table 1.

Variables Constructing the Environmental Governance Indicator.

Variable description	Source
Percentage of total land area under protected status	United Nations Environment Program—World Conservation Monitoring Centre (UNEP-WCMC), plus country data.
Ratio of gasoline price to world average	World Bank.
Percentage of variables missing from the CGSDI “Rio to Joburg Dashboard”	Consultative Group on Sustainable Development Indicators (CGSDI).
Knowledge creation in environmental science, technology, and policy	Yale Center for Environmental Law and Policy (YCELP) Knowledge Divide Project, plus country data.
IUCN member organizations per million population	Internatioanl Union for Conservation of Nature (IUCN)-The World Conservation Union.
Local Agenda 21 initiatives per million people	International Council for Local Environmental Initiatives (ICLEI).
Corruption measure	World Bank.
Rule of law	World Bank.
Civil and political liberties	Freedom House.
WEF Survey on environmental governance	World Economic Forum (WEF).
Government effectiveness	World Bank.
Democracy measure	Polity IV Project, University of Maryland.

Source. Environmental Sustainability Index 2005 Data Dictionary.

To further differentiate the impact of environmental governance in nations of varying stages of economic development, a dummy variable is used to indicate whether the country is a high-income country or not, defined by the World Bank (2016). Depending on the fiscal-year gross national income (GNI) per capita, there is a change in the classification of some countries. More specifically, five countries, Argentina, Chile, Latvia, Lithuania, and the Russian Federation, are affected in the sample. For instance, Latvia was classified as high income in 2009, upper middle income in 2010 and 2011, and then again high income since 2012. Because the environmental culture is not likely to change as quickly, only countries that have never been classified as high-income countries are considered as non-high-income countries to ensure analytical rigidity. In addition, a robustness test was conducted later by including the country classification using the income group threshold specifically in 2010.

This study controls for both individual- and national-level variables that may influence focused relationships. The individual-level control variables include gender, age, and education level. Previous studies, in general, found that individuals who are female, younger, and highly educated are more likely to be sustainable consumers (Straughan & Roberts, 1999; Wang, Liu, & Qi, 2014). In this study, gender is measured as a dummy variable (female = 1). Age is a continuous variable based on the self-reported age of respondents. In a preliminary analysis, age is also included in the models as seven categorical variables (15-19, 20-29, 30-39, 40-49, 50-59, 60-69, and 70 and above) to examine the presence of curvilinear relationships. Results are essentially the same. Education level is measured by four dichotomous variables: less-than-secondary qualification, intermediate secondary completed, higher secondary completed, and university degree (incomplete or completed).

Two variables are controlled at the country level and transformed into a natural logarithm to correct for excessive skewness: GDP per capita and population density. Prior literature found that GDP per capita has a substantial yet varied impact on environmental outcomes, with some studies suggesting that national affluence increases people’s awareness and ability to afford choices that enable a cleaner environment (e.g., Ewers, 2006), whereas others argue the opposite—that it weakens people’s environmental attitudes and leads to environmental degradation (Givens & Jorgenson, 2011; Parikh & Shukla, 1995; York, Rosa, & Dietz, 2003). Despite the controversial effects, this variable is included considering the complex and important interaction between economy and environment. Based on the neo-Malthusian perspective, many previous studies emphasize the importance of population density to explain environmental impacts (Vasi, 2007; York etal., 2003), so it is also controlled at the national level.

Multilevel modeling techniques are used to adjust for correlated errors and unequal error variance associated with the nesting data structure (Raudenbush & Bryk, 2002). As the dependent variable is a continuous variable and there are no theoretical reasons to assume that each country has a separate regression model with its own intercept and slope, hierarchical linear models with random intercepts are estimated. To better identify cross-level interactions, the three variables of substantial interest that measure environmental attitudes at the individual level are group-mean centered. All national-level predictors and the nondichotomous control variables at the individual level are grand mean centered (Enders & Tofighi, 2007). Table 2 summarizes all variables used in the analysis.

Table 2.

Descriptive Statistics.

Variables	M	SD	Range
Outcome variable
Sustainable consumption behavior index	2.38	0.72	1-4
National-level predictors
Environmental governance	0.76	0.57	−0.40-1.59
GDP per capita (logged)	9.82	0.92	7.25-11.10
Population density (logged)	4.25	1.23	1.32-6.23
High-income countries	0.84	—	0/1
Individual-level predictors
Environmental concern	3.62	1.12	1-5
Environmental efficacy	3.15	0.69	1-5
Perceived environmental impact	3.21	1.08	1-5
Gender (female = 1)	0.54	—	0/1
Age	47.06	17.37	15-98
Education level
Less-than-secondary qualification	0.19	—	0/1
Intermediate secondary completed	0.22	—	0/1
Higher secondary completed	0.27	—	0/1
University degree (incomplete or completed)	0.32	—	0/1

Note. n = 39,496 (respondents), n = 31 (countries).

Results

Table 3 presents regression results from the multilevel models. First, the null model is estimated without predictors (see Online Appendix Table S2). The variance at the national level is .077 and the intraclass correlation is .18 (p < .001), indicating that 18% of the variance in SCBs is between countries. Therefore, it is important to include national-level predictors for a better understanding of individual SCBs.

Table 3.

Multilevel Linear Models Predicting Sustainable Consumption Behavior Index.

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Intercept	2.212***	2.316***	1.589***	1.589***	1.592***	1.589***
Intercept	(0.051)	(0.050)	(0.265)	(0.265)	(0.264)	(0.265)
Individual-level variables
EC		0.114***	0.114***	0.176***	0.112***	0.114***
EC		(0.003)	(0.003)	(0.016)	(0.003)	(0.003)
EF		0.203***	0.203***	0.202***	0.502***	0.202***
EF		(0.005)	(0.005)	(0.005)	(0.030)	(0.005)
PEI		0.073***	0.073***	0.072***	0.069***	0.063***
PEI		(0.003)	(0.003)	(0.003)	(0.003)	(0.019)
National-level variables
High-income countries			0.707**	0.707**	0.707**	0.707**
High-income countries			(0.269)	(0.269)	(0.269)	(0.269)
EG			−1.105**	−1.105**	−1.105**	−1.105**
EG			(0.396)	(0.396)	(0.395)	(0.396)
EG × High-Income Countries			1.255**	1.255**	1.255**	1.255**
EG × High-Income Countries			(0.401)	(0.401)	(0.400)	(0.401)
Cross-level interactions
EC × High-Income Countries				−0.052**
EC × High-Income Countries				(0.017)
EC × EG				0.143***
EC × EG				(0.026)
EC × EG × High-Income Countries				−0.162***
EC × EG × High-Income Countries				(0.027)
EF × High-Income Countries					−0.275***
EF × High-Income Countries					(0.031)
EF × EG					0.611***
EF × EG					(0.048)
EF × EG × High-Income Countries					−0.643***
EF × EG × High-Income Countries					(0.049)
PEI × High-Income Countries						0.011
PEI × High-Income Countries						(0.019)
PEI × EG						−0.011
PEI × EG						(0.029)
PEI × EG × High-Income Countries						0.011
PEI × EG × High-Income Countries						(0.030)
National-level control
GDP per capita (logged)			0.110	0.110	0.110	0.110
GDP per capita (logged)			(0.087)	(0.087)	(0.087)	(0.087)
Population density (logged)			0.036	0.036	0.036	0.036
Population density (logged)			(0.032)	(0.032)	(0.032)	(0.032)
Individual-level control
Gender (female = 1)	0.110***	0.076***	0.076***	0.076***	0.075***	0.076***
Gender (female = 1)	(0.007)	(0.006)	(0.006)	(0.006)	(0.006)	(0.006)
Age	0.005***	0.005***	0.005***	0.005***	0.005***	0.005***
Age	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Intermediate secondary completed	0.083***	0.029**	0.029**	0.029**	0.028**	0.029**
Intermediate secondary completed	(0.011)	(0.010)	(0.010)	(0.010)	(0.010)	(0.010)
Higher secondary completed	0.135***	0.045***	0.044***	0.044***	0.042***	0.045***
Higher secondary completed	(0.010)	(0.010)	(0.010)	(0.010)	(0.010)	(0.010)
University degree (incomplete or completed)	0.205***	0.057***	0.056***	0.056***	0.052***	0.057***
University degree (incomplete or completed)	(0.010)	(0.010)	(0.010)	(0.010)	(0.010)	(0.010)
(Reference: less-than-secondary qualification)
Variance component
National level	0.077***	0.075***	0.037***	0.037***	0.037***	0.037***
Log likelihood	−38,566.526	−35,714.282	−35,703.152	−35,699.541	−35,699.541	−35,699.541

Note. n = 39,496 (respondents), n = 31 (countries); standard errors in parentheses. EC = environmental concern; EF = environmental efficacy; PEI = perceived environmental impact; EG = environmental governance.

p < .05. **p < .01. ***p < .001 (two-tailed tests).

Model 1 estimates the impact of individual-level control variables on the SCB index. The results are generally consistent with previous studies except the effect of age, and indicate that women, older people, and those with higher education levels are more likely to be green consumers. Model 2 adds the three environmental attitudes. Unlike past research, which identified an attitude–behavior gap, after accounting for individual-level characteristics, this study found that the three environmental attitudes are all positively associated with the SCB index in the cross-national context. In other words, on average, individuals who are more concerned about the environment, more aware of environmental impacts, and find their environmental behavior worthy and effective tend to actively engage in sustainable consumption. As for the control variables, the coefficients of gender and education substantially decrease in magnitude, suggesting that their impacts on SCBs are mediated by environmental attitudes. The effects of individual-level variables are essentially the same in the following models.

Model 3 consists of both individual-level and national-level predictors. The decrease in the variance component reveals that the cross-national variation in sustainable consumption is mainly due to contextual differences. After including national-level variables, the model explains about 51% (=[.075 − .037] / .075) of the cross-national variance in sustainable consumption. On average, residents in the sampled high-income countries participate more in SCBs compared with their counterparts in other countries with lower average income. It is interesting to see that the impact of environment governance on SCBs diverges in high-income and other countries. In high-income countries, environmental governance has a significantly positive impact on sustainable consumption (b = −1.105 + 1.255 = 0.150, p < .01), suggesting that effective environmental governance at the national level can facilitate individual sustainable consumption, net of other variables. In other countries, however, effective environmental governance holds back individuals’ engagement (b = −1.105, p < .01), revealing the crowding out effect. Unlike previous studies that predict environmental outcomes (such as carbon emissions and deforestation), the two national-level control variables are not significantly related to individual behavioral outcomes.

Models 4 through 6 examine the extent to which environmental governance at the national level influences the transition from environmental attitudes to sustainable behaviors by including cross-level three-way interaction terms between environmental governance, high-income countries, and each environmental attitude. In Models 4 and 5, all interaction terms are statistically significant. Although environmental concern and efficacy are positively associated with SCBs in both types of countries, the significant negative interaction terms between these two environmental attitudes and high-income countries mean that individual attitudes matter more in lower income countries from the sample. A closer look shows that the interaction effects between environmental attitude and environmental governance are negative (b = 0.143 − 0.162 = −0.019 in Model 4 and b = 0.611 − 0.643 = −0.032 in Model 5) in high-income countries and positive in other countries (b = 0.143 in Model 4 and b = 0.611 in Model 5). These results suggest that in high-income countries, improvement in environmental governance slightly weakens the impact of environmental concern and efficacy on SCBs, whereas in lower income countries, effective environmental governance promotes individuals with higher concern and efficacy to consume more sustainably.

Figures 1 and 2 illustrate the impacts of environmental concern and efficacy on SCBs in two types of countries under different levels of environmental governance. The solid and dash lines represent high (1 standard deviation above the mean) and low (1 standard deviation below the mean) environmental governance, respectively. The SCB index is estimated for college-educated women holding all else at the mean, based on Models 4 and 5. It is clear that, despite varying magnitudes, all slopes are positive, indicating that the two environmental attitudes are important impetuses of SCBs under all estimated scenarios. The first panels in both figures show that in high-income countries, the SCB index is higher where environmental governance is more effective, but the slopes in countries with low environmental governance are slightly steeper (dash lines). Turning to the second panels, they show that a high level of environmental governance substantially suppresses individuals’ participation in other countries, but the slopes are steeper in countries with a high level of environmental governance (solid lines). Taken together, the results indicate that the average frequency of sustainable consumption is higher among residents in high-income countries. More importantly, the effect of environmental governance differs in high-income and other countries. In high-income countries, people consume more sustainably in a supportive environment, and the attitude–behavior association is slightly stronger when the level of environmental governance is lower. In countries with lower levels of development, institutional environmental governance crowds out individual engagement in sustainable consumption, but people whose intrinsic environmental motivation is not suppressed by external forces are particularly inspired by contextual efforts in environmental improvement.

Figure 1.

Estimated effects of environmental concern on sustainable consumption behavior index.

Figure 2.

Estimated effects of environmental efficacy on sustainable consumption behavior index.

In Model 6, the national-level interaction term between environmental governance and high-income countries remains significant, but the three-way cross-level interactions are not. A further examination shows that the effect of perceived environmental impact on SCBs is contingent on the level of environmental governance. The association is positive and the pattern is similar in high-income and other countries (see Online Appendix Table S3). Therefore, the results imply that environmental governance facilitates the transition between perceived environmental impact and SCBs in both types of countries.

A number of sensitivity tests were conducted to evaluate the robustness of the findings reported here. First, considering that under the study’s rigorous definition there are only five non-high-income countries in the sample, restrictions were loosened and the models were estimated using a dummy variable indicating high-income countries (21 countries) versus other countries (10 countries) based on the income group threshold, specifically in 2010 (refer to Online Appendix Table S1 for countries included in each category), to see if similar patterns could be found. Results show that though the magnitudes of corresponding coefficients change to some extent, the directions remain the same (see Online Appendix Table S4). Second, two important individual-level control variables, class and marital status, were included in the models. Previous studies show that these two individual characteristics are also important predictors of environmental attitudes and behaviors (Diamantopoulos, Schlegelmilch, Sinkovics, & Bohlen, 2003; Givens & Jorgenson, 2013; Welsch & Kühling, 2009). However, their effects were not estimated earlier, because information on socioeconomic class was not collected in New Zealand and Great Britain, and information on marital status was not collected in Japan. In the sensitivity test, class is added to the model as a continuous variable derived from a survey question where respondents placed themselves on a scale, ranging from 1 (low) to 10 (high). Marital status is measured by three dichotomous variables: never married; married; and separated, divorced, or widowed. After including these control variables, results show that despite smaller sample size, the original results are not affected (see Online Appendix Table S5). Third, to address the issue of multicollinearity (which is common with three-way interactions), the author estimated two-way interaction models separately for high-income and other countries. The results are consistent (results available upon request).

Discussion

Sustainable consumption has become an important and necessary path toward a greener future due to the global increase in general consumption and its resulting destruction of resources and environmental capacity around the world. Many previous studies have discussed predictors of sustainable consumption and potential ways to promote individuals’ participation. This prior research, however, focuses on construction of psychological models and overlooks, to a large extent, the institutional context that provides sustainable products and services and constitutes an environmentally friendly social environment. On one hand, the overwhelming emphasis of individualist explanation and lack of a comparative perspective lead to mixed empirical findings on the relationship between environmental attitudes and behaviors. On the other hand, among the limited studies that delve into environmental governance—a fundamental institutional factor influencing individual environmental outcomes—researchers propose two contrary arguments with respect to its actual impact on SCBs. This study addresses the above limitations in an effort to advance general understanding of sustainable consumption by examining how environmental attitudes influence SCBs in a cross-national context, and more importantly, to what extent institutional settings affect this attitude–behavior link at the individual level.

Drawing on multilevel data from 31 countries, the results show that proenvironmental attitudes in general promote SCBs after controlling for demographics and other individual and contextual characteristics. Therefore, this study supports the environmental attitude–behavior connection, rather than the attitude–behavior gap, net of control variables in the comparative context.

Regarding the extent to which environmental governance affects individual SCBs, the findings suggest that, as expected, institutional efforts exert divergent influences on individual environmental activities depending on the level of national development. Different traditions, cultures, value systems, and environmental governance practices may contribute to the observed varying effects. As only 31 countries were analyzed, the following discussion should be considered within the context of the sample size and not broadly generalized to countries outside of the current sample. In high-income countries, environmental governance may be implemented in a supportive manner, and the individuals affected tend to have a high level of self-determination and autonomy as well as more opportunities to express their concerns. As a result, environmental governance enhances individual involvement in sustainable consumption. In countries with lower income, however, external intervention on the environment may be carried out in a more controlling way without sufficient communication between different interest groups, and residents in these countries may focus more on survival values and have lower self-esteem and fewer chances to express themselves. Consequently, the implementation of environmental governance in this context triggers the crowding out effect, meaning that institutional involvement dissolves personal environmental obligation to a large extent and suppresses individual proenvironmental participation.

In addition, the results suggest that the impact of environmental governance on the transition from environmental concern and efficacy to SCBs also differs between high-income and other countries, at least in the countries analyzed. In high-income countries, environmental protection may be a priority social issue, and proenvironmental norms, values, and lifestyles are widely shared. If individuals perceive a low level of institutional effort, the attitude–behavior association is strengthened and people with proenvironmental attitudes are more willing to step up and take more responsibility. In other countries, economic development may trump the need for environmental protection and restoration for many people, and individuals are eager to attribute the responsibility to more powerful and connected institutions. Despite these factors, there are still people who are concerned for the environment and believe their efforts can make a difference. Effective environmental governance mobilizes these agentic actors, especially those with high levels of environmental efficacy, to transit their attitudes into green consumption behaviors, compared with those who are less intrinsically motivated. Unlike the other two environmental attitudes, environmental governance strengthens the effects of perceived environmental impact in both types of countries. This is perhaps due to the fact that worries about the harmful influence of environmental pollution and degradation on health, ecosystem, biodiversity, and so on are more universal compared with environmental concern and efficacy, which are more contingent on the local social context.

The ramified effects of environmental governance highlight the delicacy of carrying out relevant policies, regulations, activities, and movements aimed at motivating individuals’ participation in the pursuit of common good. Individuals constantly evaluate the benefits and costs associated with their behavioral choices, but at the same time, they are also embedded in the social context and systematically influenced by the culture, values, and activities of both institutions and their peers. Prior literature shows that environmental governance promotes individuals’ participation in sustainable consumption through objectively expanding sustainable products and services, and altering consumers’ subjective willingness and intention. Despite these benefits, inadequate implementation without considering local context may lead to ineffective or even adverse consequences. Therefore, it is important to consider the history, culture, values, and norms of the region and its residents as a key factor in both the design and enforcement of any external intervention. In other words, as the theories of practice would propose, the institutional efforts from the top should be in concert with people’s everyday practices.

Field experiments on the crowding out effect highlight another effective way to overcome such environmental dilemmas. Such experiments suggest that one could foster social capital at the local level by building trust and social ties within the community, cultivating local grass roots organizations, and encouraging communication and collaboration horizontally as well as hierarchically. Through these processes, individuals learn to recognize and maintain the balance between self- and public interests and are empowered to actively organize themselves and cooperate with other institutional stakeholders. Once positive interaction is formed between individuals and institutions, the beneficial effects of environmental governance can be observed in countries with lower income as well.

This study has several limitations. First, due to the use of cross-sectional data, the longitudinal trend of the findings cannot be measured. Second, to the best of the author’s knowledge, ISSP2010 is the only cross-national data set available that examines SCBs. Unfortunately, it does not include countries with GNI per capita less than US$995, also known as low-income countries such as Afghanistan, Haiti, and Kenya. Future studies should examine if the crowding out effect can also be found in these countries. Regardless of these limitations, the findings of this study highlight the importance of institutional driving forces in influencing individual environmental behaviors. In addition to addressing these limitations, future studies should also investigate other contextual factors that may influence the attitude–behavior transition to gain a deeper understanding of the impact of contextual variables on individual patterns of SCB.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Social Science Fund of China (16CSH023), Tianjin Philosophy and Social Science Fund (TJSR15-005), Fundamental Research Funds for the Central Universities (NKZXB1481), and Research Initiation Funds for the Returned Overseas Chinese Scholars (ZX20150018).

Author Biography

Yan Wang is an assistant professor at the Department of Sociology, Zhou Enlai School of Government, Nankai University, China. Her current research interests include environmental sociology, social inequality, and cross-national studies.

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