Linking social actors by linking social theories: toward improved GHG mitigation strategies

Abstract

Understanding how to alter people’s behavior to mitigate GHG emissions in cities is a challenge for both researchers and practitioners. The problem encompasses comprehending variation in behavior among thousands to millions of people living in cities, as well as their contributions to the cities’ GHG footprint. To help simplify this challenge, this article seeks to define and justify the partitioning of people into three categories of actors for understanding and mitigating GHGs at the city-scale. The three actor categories are policy actors, designers and operators of infrastructure and individual infrastructure users. By linking theories from across the social sciences, this article provides specific illustrations of the three actor categories and intertwines them with the goal of developing better GHG mitigation strategies. This paper concludes with a discussion of the need for meta-theoretical approaches toward describing and explaining the interactions among the social actor categories and GHG mitigation in cities.

While there is scientific consensus on the issue of climate change caused by human-action-generated GHGs [1–3], societies continue to struggle to reach a consensus on how to respond via policy change [4,5]. Today, the planet faces a situation where human-caused inputs of carbon-containing GHGs (e.g., CO₂ and methane [CH₄]) and noncarbon-containing GHGs (e.g., nitrous oxide [N₂0], choroflourocarbons, and choroflourocarbon-replacements) into the atmosphere greatly exceed the capacity of the natural environment to remove these gases from the atmosphere [1,2,6]. Given this situation, reducing GHG emissions entering the atmosphere becomes the lynchpin policy action for mitigating climate change.

The majority of people worldwide now live in cities. In the USA, for example, this urban majority is especially high with approximately 80% of Americans living in cities [101]. Cities represent a major sink in terms of resource utilization including, food, water, electricity and all other consumer products. Cities also represent a concentrated point of housing for the population as well as a hub of transportation. This concentration represents a significant demand for all kinds of infrastructure and a significant generation of GHGs. Owing to the current global trend toward increasing urbanization, the city-region will be the level of analysis throughout this paper.

Hillman and Ramaswami have developed a three-component method by which to measure the ‘footprint’ generated by this infrastructure demand in terms of carbon-equivalents. Their GHG footprint method aims to measure impacts from [7]:

	▪ Cross-scale transformative infrastructures;
	▪ Cross-scale transmission and distribution infrastructure that bring resources to a point of use (e.g., houses and businesses);
	▪ Point-of-use infrastructure (e.g., buildings).

The GHG footprint provides an important benchmark against which GHG mitigation strategies can be objectively measured. While having these measures available is critical, achieving real mitigation requires the participation of people. To this end, Ostrom, Bulkeley, Betsill and Flannery all argue that a focus on local- and individual-level interactions is an under-researched realm for GHG mitigation [4,5,8,9]. This article is an effort to begin the process of filling this important niche in the literature.

The effectiveness of any GHG mitigation strategy – from adopting a nationwide carbon tax to installing energy efficient lighting in a home – requires the participation of people. All people are actors with varied motives. Untangling these diverse motives, specifically in relation to GHG mitigation, is a challenging task in social science. Some actors have a predisposition that is favorable to GHG mitigation strategies (supportive of the underlying science, believing action is needed), while others actors have a predisposition against GHG mitigation strategies (suspicious of the underlying science, believing action is premature).However, this ‘two camp’ view is an oversimplification. This is because, within each of these two camps, there are individual actors who intentionally or unintentionally impede or support a particular GHG mitigation strategy. A ‘climate-change denier’ may install energy-efficient lighting and better insulation in their home simply for cost savings. A ‘climate-change activist’ may oppose a local wind farm because of the impact on their personal viewscape. This same pair may then alternately oppose or champion a GHG mitigation policy through the political process in a way ‘opposed’ to their individual-level decisions.

Thinking of the role of people in GHG mitigation strategies is a challenging endeavor for both researchers and practitioners. The problem is one of understanding variation in behavior among thousands to millions of people, with all these individual decisions culminating in what is ultimately a particular city’s GHG footprint. This paper contributes to the literature by providing a three-step line of reasoning for understanding how people relate to GHG mitigation in cities:

	▪ Step one: partitioning actors;
	▪ Step two: understanding context;
	▪ Step three: linking actor categories into chains of interdependent behavioral processes toward overall GHG mitigation outcomes at the city-scale subsystem.

For example, the factors affecting the decision by a city government to subsidize the development of a wind farm for energy generation is just as theoretically complex as the decision by designers and operators of infrastructure to build a wind farm and by a household to buy wind energy. The argument in this paper is that to develop effective strategies to mitigate GHG emissions in cities, understanding the interdependencies of behavior between the city government, wind farm developers, and the household is a necessity.

The first step to sucessfully link the interdependencies and variations among numerous factors is to find a way to simplify them. The following steps are an attempt to achieve this simplification. Step one partitions people, called social actors, into three categories:

	▪ Policy actors who are the political leaders attempting to influence GHG mitigation strategies;
	▪ Designers and operators of infrastructure, who are directly responsible for the city’s infrastructure;
	▪ Individual infrastructure users, including homeowners/renters and public and private entities, who are consumers of resources and in turn generators of GHGs.

The second step is to understand the specific context embedding the three actor categories. GHG mitigation requires changes in processes and outcomes. Processes and change involve the study of behavior of individuals and groups across different contexts and over time. When individual users (e.g., homeowners) decide to install energy-efficient lighting, important contextual factors might include: the extent to which individuals are favorably predisposed to energy-efficient lighting; perceptions of social pressures from neighbors and friends; their perceptions of self-efficacy; and their motivations to act [10]. Similarly, adopting a climate action plan requires overcoming numerous obstacles including attracting the attention of government officials, building a coalition of allies and supporters, framing the problem and solutions to minimize opposition and, perhaps, finding a champion to lead such an effort [11].

The third step is to link the three actor categories from their specific context into chains of interdependent behavioral processes and outcomes in a city-scale subsystem in relation to their impact on GHG mitigation in cities; for example, the success of a decision by policy actors (e.g., the adoption of a GHG action plan), might require the right incentives and constraints on the behavior of both designers and operators of infrastructure and homeowners. Similarly, the behavioral outcomes of the homeowner (perhaps strong opposition to stringent GHG mitigation policies, apathy toward voluntary programs, or rebound caused by increased usage of a more efficient resource) may influence revisions to the climate action plan among policy actors.

This paper aims to provide a more holistic understanding about GHG mitigation in cities and suggest actions that can develop from this understanding. The tasks are threefold:

	▪ To define and justify the three actor categories for simplifying city systems in the context of GHG mitigation;
	▪ To provide specific, contextual illustrations of the three actor categories;
	▪ To interrelate the three actor categories in a city-scale social subsystem.

The audience for this paper is students, researchers and practitioners who are interested in a simplified typology of people in the social system involved in GHG mitigation in cities. While this paper’s methods could be applied to a rural subsystem, the authors choose to focus on an urban subsystem for the examples throughout the paper since the city-level represents both the majority of the world’s population and the majority of human-caused global GHG emissions. The article is interdisciplinary from a social science perspective but does not incorporate approaches from engineering or the natural and physical sciences; that is, a city’s biophysical subsystem of natural resources and infrastructure. This article concludes with an argument for meta-theoretical approaches. This will contribute to the literatures analyzing social actors behaviors, and those analyzing climate mitigation, and will also contribute to the effectiveness of practitioners planning and decision making in relation to GHG mitigation in cities.

Defining the three social actor categories

The partitioning of people who affect a city’s GHG footprint into three social actor categories is built around the reality that mitigating GHGs involves interdependent behavior among partially distinct populations that differ both in roles and contexts. By using the three social actor categories we can establish strategies that are role- and context-appropriate, as well as recognize the strengths and limitations of strategies that target just one actor category but not the others. The goal should be to develop different strategies targeting the most appropriate audience. Thus, this section and Table 1 below define and discuss each of our three social actor categories: policy actors, designers and operators of infrastructure, and individual infrastructure users. Highlighting each social actor category is important to allow a better understanding of the complete social system. This allows for more appropriate application of GHG mitigation strategies, whether they are incentives or constraints.

The first category of social actors is policy actors. Policy actors constitute those people who directly or indirectly attempt to influence the processes and outcomes in the governance of a city’s infrastructures. Policy actors from government include elected, appointed and civil positions. Policy actors also involve nongovernmental actors, such as citizen groups, scientists, journalists and interest groups. These nongovernmental actors may involve leaders in a neighborhood association who are diffusing smart energy meters in a community to improve energy uses in individual households, scientists who calculate the GHG footprint in the form of policy advice for city leaders, interest groups and private associations advocating for and against GHG policy or carbon taxes, and government officials managing GHGs, carbon, and/or energy-related policies.

Designers and operators of infrastructure represent the second category of social actors. They are both private- and public-sector employees whose organizations have some authority in designing, constructing, managing/operating and dismantling/recycling/disposing of infrastructure over its life cycle. In this respect, they can alter how resources are used in the production process. This can influence both near- and long-term energy demands in three ways: designing for energy efficiency (so that the building itself uses less energy in its day-to-day operations than if energy efficiency were not a priority), the energy source (will electricity come from wind power, coal, natural gas, nuclear or solar), and the energy embedded in construction at point-of-construction (e.g., concrete production is very energy and resource-intensive). Voluntary adoption of green design and engineering principles among designers and operators of infrastructure can reduce input resource demand and reduce life cycle resource demand as well as stimulate cleaner production in energy outputs.

The third category of social actors is individual infrastructure users, with two subsets of note. The first subset is members of the city’s general public, who are best thought of as the typical citizen, such as the homeowner or renter. The second subset is public and private sector entities (i.e., nongovernment, government or private organizations) that are located within the city but do not directly attempt to influence climate mitigation policies or decision-making; for example, homeowners may have control over the energy efficiency of their homes and a renter can choose to buy a fuel-efficient vehicle or use alternate modes of transportation for commuting to work but neither attempt, as a homeowner or renter, to change city-scale policies or to alter the operation of city-scale infrastructure. Similarly for organizations in the public and private sector, a city-scale public or private organization geared toward providing shelter for the homeless is far removed from GHG mitigation policies, but they may install energy-efficient windows in the shelter or invest in energy-efficient appliances. The impact of these individual infrastructure users on climate mitigation is rooted in their demand and use of energy and resources as well as the source of the energy they utilize. An increase or a decrease in demand from this category (as an aggregate) can significantly increase or reduce energy consumption.

Providing the right incentives and constraints to motivate behavior that is sympathetic to climate mitigation in cities is further complicated by cross-scale policy actors and infrastructure designer-operators; who can sometimes live and work outside a city’s jurisdictional boundaries yet still influence a city’s metabolism; for example, policy actors, at national and subnational levels of government, may design and adopt a cap-and-trade policy, thereby altering the future energy flows in the city. Similarly, much of a city’s infrastructure lies beyond a city’s boundary requiring the long-distance transmission of resources and a GHG footprint that extends regionally and even globally. As a result, much of the effort in reducing a city’s GHG footprint must be focused both within and outside of a city’s boundary.

The three social actor categories are also not mutually exclusive. All social actors living in the city are themselves infrastructure users; that is, they live in homes, apartments or shelters. Some homeowners may participate on city-scale climate action committees and some infrastructure-designers may participate in climate mitigation policies as policy actors. Similarly, elected officials, who are involved in climate-related policies, will consciously or subconsciously make individual-level household energy efficiency decisions and choices about commuting to work. The main difference between policy actors and the other two actor categories is the time and effort devoted to influencing infrastructure-level decisions.

Contextualizing the three social actor categories

The three social actors operate within their own individual contexts and, therefore, have attracted the attention of the different disciplines and fields of study found in the social sciences. Given the context and different roles played by each category in a society, the social sciences have developed theoretical approaches for each. This section introduces sample theories and elaborates about the context of each. The point is to develop theoretical descriptions and explanations of each category to better understand how these social actors affect a city’s GHG footprint and GHG mitigation strategies.

Policy actors operate at one or two levels of analysis: subsystems and action situations. Policy subsystems are the topical and territorial unit involving policy actors attempting to influence subsystem affairs; for example, the city and county of Denver, CO, USA has a climate and energy subsystem. This city-level subsystem overlaps and is nested in a metropolitan-region subsystem, a state-level subsystem, and a national subsystem on the topic of climate and energy policy. Subsystems are appropriate contextual units of analysis when there are hundreds or more actors involved, the policies are numerous, and the pressing questions involve political behavior and policy change. The subsystem in a city may contain dozens or more policy-specific subsystems, which are best thought of as nested and overlapping, yet at the same time semi-independent from each other. ‘Nestedness’ can be in terms of vertical scale: local-, regional- and national-level. Overlapping jurisdictions can also be horizontal in scale [12]. Levels of government involved will be ‘equal’ in level, but their jurisdictions (within the same geographic area) will vary in terms of the forms of policy or the types of programs they implement. An example of this horizontal policy subsystem would be three governmental entities within the same geographic boundary, but each deals with a different program area, such as one focused on the homeless, one on education and one on health. Part of the ‘overlap’ is that these groups could very well be dealing with an identical group of individuals, but in different policy areas. An example of this overlap would be a homeless man with chronic health issues attempting to get his GED. Overlapping interactions can also be described as a ‘polycentric’ governance structure where multiple, independent decision-makers or jurisdictions have overlapping authority over the same people or issue [13]. The concept of federalism is firmly embedded in the polycentric approach. The key action in a federalist system is that these overlapping policy subsystems work together toward a particular end, but the individual entities involved still maintain their own identities, rights and authorities [14].

One of the major theories operating at the subsystem level is the advocacy coalition framework (ACF) [11] (for others see [15]). The advocacy coalition framework explains how policy actors seek to influence policy change by forming and maintaining coalitions based on similar policy-related beliefs (e.g., pro- and anti-GHG mitigation strategies). These coalitions have resources and deploy strategies to influence policy change within a given subsystem. As information enters the system, the coalition may engage in an analytical debate where the probability of learning may depend on the presence of an analytical forum or a broker, someone who helps opponents reach agreements. If the coalitions can compromise or if one coalition is sufficiently more powerful than the other coalition policy change may occur.

The second unit for studying policy actors is the ‘action situation.’ Every policy subsystem involves multiple ‘action situations’ where policy actors directly interact with each other, such as a committee on climate change policy in a city. The study of these action situations is best conducted by another theoretical framework called the Institutional Analysis and Development Framework (IAD). These are the collective action situations wherein people directly interact with one another, such as a committee on climate change in the city. Each action situation involves certain rules of participation, negotiation and scope. The importance of the IAD framework is the specification of rules and contextual factors (attributes of the community and attributes of the problem) that affect how people behave across different action situations. Where a policy subsystem could be interpreted as a broad-scale action situation, we find it more useful to restrict the definition of an IAD action situations to times and places where specific collective action decision-making occurs, such as a neighborhood association meeting, a public hearing, or a city council-level decision [16].

Designers/operators of infrastructure focus on the operation and maintenance of their facilities. Whereas policy actors operate in collectives at the subsystem or action situation level, infrastructure designers and operators operate at the firm level where the assumptions are effectiveness of service delivery, efficiency in operation, and in some cases profit [17]. Sample analytical approaches for understanding their behavior include club theory and the resource-based view of the firm.

Club theory is built around a group of private actors providing near-public goods. This collective, termed a ‘club’, is able to supply these near-public goods more successfully than the each actor individually. A common example in club theory literature is a voluntary environmental program (VEP) where the product is a positive environmental externality. Prakash and Potoski describe VEPs as voluntary collaborations that induce member-firms to reduce pollution above what government regulation alone would require [18]. Darnall et al. note the reasons for club membership by an industry actor are varied: industry-sponsored VEPs generally offer members ‘industry norms’ status; Government-sponsored VEPs generally offer members over-and-above distinctions, such as pollution-prevention leadership status or being distinguished as a user of fewer natural resources; third-party VEPs generally offer members independent legitimacy for their pollution reduction activities [19].

By contrast, the resource-based view of the firm is built around a focus on a firm’s resources (inputs) rather than a firm’s outputs. Resources include “all assets, capabilities, organizational processes, firm attributes, information and knowledge” [17]. Under this analytic approach, a firm will utilize its resource advantage to maximize efficiency, effectiveness and profit. By maximizing efficiency, the firm should in turn maximize social welfare via its deliverables to society [17].

Individual infrastructure users are people who use electricity and other utilities, and who travel on the city infrastructure. The study of individual infrastructure users has focused on the motivations shaping a particular choice context (recycling instead of trash disposal or taking a bus instead of driving a car). Drawing mostly from the social-psychology literature, two prominent analytical approaches include the theory of planned behavior [10] and value-belief-norm (VBN) theory [20,21]. These two theories explain specific behavior in specific situations.

The theory of planned behavior, for example, explains a specific type of conservation behavior (e.g., buying energy-efficient lighting) by three considerations surrounding the individual’s motivations to perform the act: their positive or negative evaluation of consequences of the act (individual behavioral beliefs), incentives and disincentives from social norms (normative societal beliefs), and their perception of control, which is often linked with external obstacles or incentives including laws and policies (control beliefs). The theory explicitly studies that although past behavior is often considered a strong measure of future behavior, the future behavior can indeed be altered if the above three considerations are of sufficient weight to tip the individuals motives with regard to a particular decision. This is particularly true when the past action was carried out with ‘a degree of ambivalence, indifference or uncertainty’ [10,22].

By contrast, VBN theory “evaluates the relationship between environmental concern and behavior” [21]. Stern notes that the same individual may act differently depending on the setting, perhaps displaying public environmental activism or nonactivist behavior in the public and then, by contrast, display private-sphere environmentalism. Actors are constantly weighing four primary factors: potential for adverse consequences, attitudinal factors, contextual capabilities, and habits/routines. Stern concludes that, “Different kinds of environmentally significant behavior have different causes. Because the important causal factors may vary greatly across behaviors and individuals, each target behavior should be theorized separately” [21].

The theories just highlighted describe and explain the behavior of the three social actor categories but are just samples of a larger number of applicable theories. Further examples include theoretical work on social norms [23] and the reasonable person model [24]. The purpose of theories is to focus the researcher toward a limited set of factors, inter-relate those factors in the form of hypotheses or propositions, and to provide explanations of the mechanisms linking the factors, such as the importance of beliefs or self-interest in motivating individuals to act in a particular way under a particular context. Every theory has its limitations with some espousing models of the individual who are motivating strongly by self-interest largely independent of context, as in the resource-based view of the firm to others supporting models of the individuals who may be goal-oriented but face nontrivial cognitive limitations a tendency to exaggerate their interpretations of stimuli as found in the advocacy coalition framework. Most importantly, researchers should recognize the strengths and limitations of their chosen theories. One of the major limitations of extant theories is that they focus on just one social actor category and do not link them – which is the intent of this paper.

Linking the three social actor categories

In some situations the behavior of the three actor categories can partly be viewed in isolation of the others. Examples of this from each of our actor categories would be:

	▪ For policy actors, understanding how a carbon tax got on the governing agenda via the advocacy coalition framework;
	▪ For designers and operators of infrastructure, understanding how new energy infrastructure decisions are made, particularly when they represent low-carbon energy options by applying the resource-based view of the firm;
	▪ For individual infrastructure users, how do they make energy efficiency decisions in their homes that entail up-front costs but long-term cost savings, as depicted by the theory of planned behavior.

Despite the value of these single-actor analyses, the real power of this framework comes to full fruition when it is used as an application to understand more complex GHG mitigation strategies that require linking the behavior of the three social actor categories in a cross-category manner. In this case, the typology of actors therefore provides a foundation for simultaneously applying multiple social science theories to understand the motivators and barriers for actors to mitigate GHGs at the city-scale.

Below we provide two examples of the theory of ‘linking’. The first application links in a top-down direction, beginning with policy actors. The second application links in a bottom-up direction, beginning with individual infrastructure users. In both applications, the links are the outputs of one theory or framework that, in turn, are used as inputs for another theory or framework.

An illustration linking the social actor categories might start with policy actors following a top-down approach. For example, one output of analytical debates of coalitions (consistent with the advocacy coalition framework) is changes in policy. Adopted policies may alter the formal rules that govern property rights of resources, making some more or less valuable to a particular firm (consistent with the resource-based view of the firm). The firm may respond with a different production processes that reduces its GHG footprint and products. The changes in prices of products and the activities of the policy actors may affect the behavior of infrastructure users who may reduce their demand for other products or seek substitutes with a smaller GHG footprint (as observed in the theory of planned behavior). In this simplified example, policy change adopted by policy actors indirectly impacts GHG mitigation by steering firms toward different production processes and infrastructure users toward different patterns of consumption. This example (Table 2) illustrates the linking of the three social actor categories via the interaction of their outputs and was structured by the logic found in the advocacy coalition framework, resource-based view of the firm, and the theory of planned behavior.

An additional example of linking social actor categories could instead begin with individual infrastructure users following a bottom-up approach. Perhaps an individual, or group of individuals, have decided to radically increase their personal energy efficiency. Such a decision and subsequent action could be seen as consistent within VBN theory. Initially, such decisions could be made completely on an individual level: installing energy-efficient lighting, devices and appliances. However, eventually the individual would become constrained by the infrastructure service their residence relies upon and would need to begin applying pressure to the designers and operators of infrastructure serving their residence and/or the policy actors elected to oversee their area of the city. Designers and operators could respond by forming a research consortium to expand their renewable energy alternatives available to their customers, consistent with a club theory approach. The individuals demanding a change from policy actors could be viewed as a new coalition via the advocacy coalition framework or they could be viewed as generating self-governing proposals consistent with the institutional analysis and development framework. Real examples of ‘bottom up’ pressures on these actors have included: consumer demand for renewable energy sources from their utilities, and the utilities adjusting their future development of their energy portfolio to reflect these individual demands; and consumers constrained by local regulations (such as local ordinances forbidding solar panels on a home for aesthetic reasons) seeking a change in laws to allow for the installation of these devices.

The choice of frameworks and theories applied herein was based partly on the prominence of each in their respective fields and disciplines. Similar logic can be applied to other analytical approaches to understand different kinds of linkages (or even the absence of linkages) among the three actor categories.

Conclusion

This article contributes to the literature by simplifying the analysis of people’s impact on GHG mitigation in cities by partitioning them into three categories for understanding and action. To date, most studies have dealt with just one actor category, from policy actors [8] to infrastructure designers and operators [17] to individual infrastructure users [20]. The argument is thus meta-theoretical and cross-disciplinary. Any single disciplinary approach in the social sciences will be insufficient for understanding the full puzzle of GHG mitigation in cities. Although stated in relation to his VBNs theory, Sterns comment is also valid for this broader analysis, ‘It is critical to underscore the need to draw on insights from across the behavioral and social sciences, because the important causal variables lie in the domains of various disciplines and because the variables interact. Thus, interdisciplinary research is necessary for full understanding’ [21]. For example, the advocacy coalition framework may help us understand the coalition politics and the resulting changes in policy but does not explain how policies translate into actual changes in behavior of homeowners decreasing their GHG footprint. The resource-based view of the firm may discuss how firms behave, but does not discuss the broader environment dominated by policy actors who determine the legal rights for resource acquisition and use. The theory of planned behavior helps explain individual behavior, such as recycling behavior in the household, but does not place these individuals into a broader context that explains the pricing of the product and the framing that shapes social norms.

The aspiration should be to think meta-theoretically. This article provides one approach for thinking meta-theoretically by showing how different theories can explain behavior of each of the three actor categories and by providing a general framework that links both the theories and actor categories to better understand GHG mitigation strategies. This requires articulation and comparison of social science theories in terms of their scope, assumptions, causal argument (independent variables, dependent variables and hypotheses) and overall lessons for action for researchers and practitioners. One of the benefits of meta-theoretical thinking is that it helps overcome threats from theory tenacity and confirmation bias [25]; that is, the tendency for people to seek confirmatory cases for their theory and obstinately believe a theory is true in the face of disconfirming evidence. One solution to confirmation bias and theory tenacity is to understand how theories serve as implicit and explicit lenses for describing and explaining stimuli and then to learn more than one theoretical approach to hedge descriptive and explanatory investments.

Future perspective

To date, global GHG mitigation strategies between nation-states have been either unsuccessful or have generated only modest gains, the Kyoto Protocol (and the lack of a follow-up treaty to replace Kyoto) being the most striking example. Parallel to this global-level lack-of-success have been numerous local-level initiatives, which by contrast have achieved much more significant GHG reduction gains. Examples at the state-level in the USA include Texas, Iowa and Colorado’s significant adoption of wind energy via renewable energy portfolio standards. An example at the regional-nation level would be the European Union’s success with carbon trading initiatives. There are also numerous city-level examples where GHG footprinting in combination with GHG mitigation strategies have proven successful. In the future, these local-level successes will lead to increasing emphasis on these polycentric local level initiatives versus singular, consolidated, global solutions. Having clearly delineated actor categories will help to further focus mitigation strategies by targeting them to the most appropriate actor-categories. The future study of GHG mitigation will continue to focus on single social actor categories (e.g., policy actors, designers and operators of infrastructure and individual infrastructure users) as well as focusing on linking the outputs of multiple social actor categories so that each becomes an input for the others. This paper contributes to the literature and policy initiatives by simplifying the analysis of people’s impact on GHG mitigation in cities. The use of a meta-theoretical approach will produce synergies across actor-categories and help to ensure that local-level initiative will continue to contribute significantly to the reduction of the size of GHG footprints via local- and city-level GHG mitigation strategies.

Table 1.  Defining the three actor categories.

	Three actor categories
	Policy actors	Infrastructure designers and operators	Individual infrastructure users
Definition	Actors attempt to influence policy processes and outcomes	Actors whose firms and organizations are directly responsible for designing, building, managing, dismantling and recycling infrastructures	Individual-level, household-level, and firm-level single-parties who do not attempt to influence broader city-wide policies but who make individual-level decisions that cumulatively have significant impacts
Examples	Government officials, scientists, journalists, interest group leaders, and private industry leaders within the city and outside the city	Professional infrastructure engineers, architects, and construction firms. Infrastructure operators such as energy, communication, water, wastewater, solid waste, and mass transit utilities	Homeowners and private and public sector entities located within the city

Table 2.  Illustrative example that contextualizes and links the social actor categories to GHG mitigation.

	Three actor categories
	Policy actors	Infrastructure designers and operators	Individual infrastructure users
Sample analytical approach	Advocacy coalition framework	Resource-based view of the firm	Theory of planned behavior
Sample dependent variables	Changes in policy Coalition formation and stability	Resource base of firm Product production of firm Pollution production of firm	Behavior (e.g., home energy conservation)
Sample independent variables	Beliefs, learning, strategies resources, events	Resource bundles Production techniques	Attitudes, social norms, self efficacy and intention
Sample links among actor categories and to GHG mitigation	Indirectly shapes GHG mitigation by: Establishing polices that determine property rights that govern infrastructure designers and operators Framing arguments that shape social norms Establishing policies that govern what is banned, required and permitted within the control of the individual infrastructure users and infrastructure designers and operators	Indirectly shapes GHG mitigation by: Providing incentives that shape the control, attitudes, and social norms among individual infrastructure users (e.g., information campaigns and changing the GHG footprint and/or price point of products produced) Directly influences GHG mitigation by Increasing efficiency of operation and design of infrastructure (e.g., specific products produced and pollution prevention or pollution mitigation related to this production)	Directly influences GHG mitigation by: – Energy usage and energy efficiency decisions – Product purchasing decisions – Personal transportation mode decisions – Personal diet and food-choice decisions – Personal career choice decisions

GHG footprint

A GHG footprint of a city is the cumulative total of its generation of GHG gases. The five most common GHGs are carbon dioxide, methane, nitrous oxide and CFCs/CFC-replacements. The GHG footprint is often standardized in terms of carbon dioxide equivalents.

GHG mitigation

Summation of all efforts by a city and its residents to reduce the size of the GHG footprint by reducing the total amount of GHGs they generate and release into the atmosphere.

Executive summary

	▪ Today, the planet faces a situation where human-caused inputs of carbon-containing and noncarbon-containing GHGs exceeds the capacity of the natural environment to remove these gases from the atmosphere.
	▪ The majority of people worldwide now live in cities and cities represent a major source of GHG emissions.
	▪ It is critical to have measures available that establish a GHG footprint (a GHG footprint of a city is the cumulative total of its generation of GHG gases).
	▪ To achieve real GHG mitigation (the summation of all efforts by a city and its residents to reduce the size of the GHG footprint) requires the participation of people.
	▪ Three social actor categories of people are defined as: - Policy actors, who are the people attempting to influence GHG mitigation strategies; - Infrastructure designers-operators, who are directly responsible for the city’s infrastructure; - Individual infrastructure users, including homeowners and public and private entities, who are consumers of resources and in turn generators of GHGs.
	▪ Social sciences theories have been developed over time to describe and explain behavior of each social actor category.
	▪ Developing effective GHG mitigation strategies requires linking the social actor categories by linking the theories explaining each category.
	▪ To mitigate GHG emissions, the aspiration should be to think meta-theoretically.

Acknowledgements

This paper was presented at the US–China Workshop on Pathways Toward Low Carbon Cities held in Hong Kong (December 2010), which was sponsored by the US National Science Foundation grant CMMI-1045411.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.