It's not easy building green

Academy of Management Journal

It's Not Easy Building Green: The Impact of Public Policy, Private Actors, and Regional Logics on Voluntary Standards Adoption

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Academy of Management Journal AMJ-2015-0769.R5 Special Research Forum: Grand Challenges Institutional theory < Theoretical Perspectives, Organizations and the Natural Environment < Topic Areas, Social issues in management (General) < Social Issues in Management < Topic Areas, Organization and management theory (General) < Organization and Management Theory < Topic Areas, Entrepreneurship (General) < Entrepreneurship < Topic Areas Human-induced climate change is one of the most daunting challenges of the early 21st century. Addressing climate change will require new sectors that create economically and ecologically sustainable products and services. Such sectors have received encouragement through voluntary certification standards. For example, the Leadership in Energy and Environmental Design (LEED) voluntary certification standard seeks to reduce the environmental impacts of buildings through stimulating growth of the â&#x20AC;&#x153;green buildingâ&#x20AC;? sector. Both public and private actors have subsequently attempted to promote such standards; however, we know little about the relative efficacy of these actors in encouraging adoption.

We know even less about how regional culture conditions the impact of such efforts. In this study, we theorize and test how regional institutional logics filter the efficacy of public and private efforts to promote adoption of standards. Our results demonstrate that in addition to policy, private actors such as social movement organizations, market intermediaries, and entrepreneurs play a role in bolstering adoption. Yet, the efficacy of such interventions is dependent upon variations in regional culture. Our findings advance understanding of how new markets are socially constructed and the conditions under which efforts to promote new sectors are more effective.

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Itâ&#x20AC;&#x2122;s Not Easy Building Green: The Impact of Public Policy, Private Actors, and Regional Logics on Voluntary Standards Adoption

Jeffrey G. York University of Colorado at Boulder Ph: 303-807-6027 jeffrey.york@colorado.edu

Siddharth Vedula Babson College svedula@babson.edu

Michael J. Lenox University of Virginia lenoxm@darden.virginia.edu

The authors gratefully acknowledge the outstanding guidance and feedback we received from Marc Gruber and three anonymous reviewers. We would like to thank Saras Sarasvathy, Dean Shepherd, Sankaran Venkatarman, Jerry Davis, Nils Kok, Rebecca Henn, Andrew Hoffman, Michael Lounsbury, Mike Russo, Eric Shade, and Stasi York for their helpful comments on earlier versions of this article.

This paper benefited from comments from attendees of the Alliance for Research on Corporate Sustainability (ARCS) annual conference, and seminars at Cornell University, Babson College, Indiana University, University of Florida, University of Michigan, University of Minnesota, University of Oregon, University of Virginia, and Syracuse University. We would also like to thank the USGBC and Building Green for their assistance in providing data for our analyses. Jeffrey York gratefully acknowledges the financial support of the Shane Faculty Scholar Gift through the Leeds School of Business Center for Education on Social Responsibility at University of Colorado Boulder.

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It’s Not Easy Building Green: The Impact of Public Policy, Private Actors, and Regional Logics on Voluntary Standards Adoption ABSTRACT Human-induced climate change is one of the most daunting challenges of the 21st century.

Addressing climate change will require new sectors that create economically and ecologically sustainable products and services, often supported through voluntary certification standards.

For example, the Leadership in Energy and Environmental Design (LEED) voluntary certification standard seeks to reduce the environmental impacts of buildings through stimulating growth of the “green building” sector. Both public and private actors have attempted to promote such standards; however, we know little about the relative efficacy of public and private efforts to encourage adoption. We know even less about how regional culture conditions the impact of such efforts. In this study, we theorize and test how regional institutional logics filter the efficacy of public and private efforts to promote adoption of standards. Our results demonstrate that in addition to policy, private actors such as social movement organizations, market intermediaries, and environmental entrepreneurs play a role in bolstering adoption. Yet, the efficacy of such interventions is dependent upon variations in regional culture. Our findings advance understanding of how new markets are socially constructed and the conditions under which efforts to promote new sectors are more effective.

Climate change is one of the most daunting and contentious challenges of the 21st century.

While scientists have determined that the climate is changing, humans are the cause, and negative consequences will be significant (IPCC, 2014), policy makers and businesses have struggled to take action, often disagreeing on the severity or even the existence of climate change (Ansari, Gray, & Wijen, 2011; Hiatt, Grandy, & Lee, 2015). Sectors such as “renewable energy” (Sine & Lee, 2009; York, Hargrave, & Pacheco, 2016a) and “green building” (York & Lenox, 2014) are controversial despite evidence showing their development could mitigate climate change (Asensio & Delmas, 2017; Hoffert et al., 2002). Recent work shows the climate change debate is embedded in cultural differences as we “relate to climate change through our prior ideological preferences…and gravitate towards opinions that fit with those of the people with which we identify” (Hoffman, 2015: 4; see also Schüssler, Rüling, & Wittneben, 2014).

The cultural roots of the climate change debate highlight shortcomings in our understanding of new practice adoption. Management scholars have long studied how standards (e.g. Delmas, 2002; Guler, Guillen, & Macpherson, 2002; Jiang & Bansal, 2003) impact adoption of new practices (e.g. Ansari, Fiss, & Zajac, 2010; Dobbin, 1994; Kennedy &

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Fiss, 2009; Tolbert & Zucker, 1983). Standards have fostered the emergence of sectors such as organic foods (Lee, Hiatt, & Lounsbury, 2017; Lee, 2009), renewable energy (Sine, David, & Mitsuhashi, 2007), and green building (Eichholtz, Kok, & Quigley, 2010; Simcoe & Toffel, 2014) that are critical to addressing climate change. Yet, we have a limited understanding of the forces that influence adoption of voluntary standards.

While it is well understood that regulation encourages adoption (Dobbin & Sutton, 1998) few studies have examined the role of broader cultural forces. Even when studies have included cultural-cognitive (Scott, 1995) institutions, they have done so through examining firm or industry-level variation (e.g. Delmas & Toffel, 2008) in centralized industries where the threat of regulation is pressing (King, Lenox, & Terlaak, 2005). The relative efficacy of public regulation versus private actors is relatively unexamined. We know even less of how regional culture may filter the efficacy of public and private efforts to promote voluntary standards. These are critical gaps in understanding adoption of nascent voluntary standards and practices linked to the climate change debate.

In this study, we develop a model of how policy, private actors, and regional culture may interactively encourage adoption of voluntary standards. We theorize that the impact of public regulation and private actions on standards adoption is conditioned by regional institutional logics (Friedland & Alford, 1991). Regional institutional logics embody culture as “rules of action, interaction, and interpretation that guide and constrain” actors within a geographic community (Lee & Lounsbury, 2015; Thornton & Ocasio, 1999: 804). As Marquis and Battilana point out, studies have neglected “the particularities associated with local communities” (2009: 297), specifically the role of culture (Marquis & Raynard, 2015). Our theory extends the insight that institutional logics act as cultural filters for how communities react to new practices (Thornton, Ocasio, & Lounsbury, 2012; Lee & Lounsbury, 2015).

Empirically, we examine the Leadership in Energy and Environmental Design (LEED) voluntary standard for construction in the U.S. The goal of LEED is to reduce buildings’ environmental impact through economically beneficial design (USGBC, 2004). Thus, LEED

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embodies two logics central to the climate change debate: 1) a market logic valorizing wealth creation, individualism, and economic prosperity and 2) a community logic advocating commitment to the community, collective benefit, and reciprocity (Hoffman, 2011b, 2011a; Hoffman & Henn, 2008; Schüssler et al., 2014). Using panel data over the period 2000-2014, we examine LEED adoption across 341 metropolitan statistical areas (MSAs). Our analysis suggests that private actors may have a greater direct impact than public policy on adoption of voluntary standards. In addition, incentive-based public policies and market-oriented actors more effectively drove adoption in regions with a strong market logic. However, we find environmental entrepreneurs were equally effective in regions with a strong market or community logic, indicating a potential bridging of logics. These findings extend our understanding of voluntary standards adoption, as well as the interactive relationship between public policy, private efforts, and regional culture in promoting standards.

RESEARCH CONTEXT: GREEN BUILDING IN THE UNITED STATES Buildings contribute approximately 30% of global greenhouse gas emissions and consume 40% of global energy (IPCC, 2014; Levine et al., 2007). Emissions from buildings are particularly acute in the U.S., totaling 2,318 million metric tons of carbon emissions (9% of global emissions) annually. If U.S. buildings were a country, it would rank as the third largest emitter of carbon dioxide, exceeding the combined total emissions of France, Japan, and the United Kingdom (US Department of Energy, 2008). Researchers have declared that “…each new building constructed in an energy-wasting manner potentially locks us into high climatefootprint buildings for decades... action now is important” (Urge-Vorsatz, 2007: 28).

Founded in 1993, the US Green Building Council (USGBC) focused on clarifying and legitimizing green building “…by creating energy-efficient, healthy, productive buildings that reduce or minimize the significant impacts of buildings on urban life and on the local, regional, and global environments” (Yudelson, 2007: xv). USGBC co-founder David Gottfried described his goal as not lobbying, but creating a new sector: The mere definition of lobbying meant trying to influence legislators in favor of special interests. Our vision, in contrast, was to build an organization of leaders who demonstrate constructive action through bricks-and-mortar

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methods: by constructing buildings that optimize environmental performance and are healthy for occupants and the planet (Gottfried, 2004: 108).

A unique result was the diversity of the USGBC’s membership. As of 2015, most USGBC’s 25,735 members were for-profit firms including construction firms (30%), professionals (45%), and product manufacturers (9.4%). Less than 6% of members were government or non-profit organizations. In 2000 the USGBC developed the LEED voluntary standard with the goal of fostering “…positive results for environment, occupant health and financial return” (USGBC, 2004). The LEED standard assigns points to a building based on six criteria areas (Table A1 of the Appendix available here: https://goo.gl/zDLSRo). By 2016, 45% of new construction was forecast to be LEED certified, indicating the potential for LEED to reduce overall carbon emissions (Allouhi et al., 2015; Asensio & Delmas, 2017).1 THEORY AND HYPOTHESES Management scholars have long utilized an institutional lens to examine how and why new practices, such as green building, are adopted (see Strang & Soule, 1998 for an overview).

Early work showed early adopters are motivated by technical gains, while later adoption is driven by contagion-like mechanisms (Tolbert & Zucker, 1983; Westphal, Gulati, & Shortell, 1997). These mechanisms include coercive, imitative, and normative pressures (DiMaggio & Powell, 1983; Dobbin & Sutton, 1998; Haveman, 1993). The literature has emphasized the interplay between economically motivated strategic action and the desire for legitimacy in driving adoption (Delmas & Toffel, 2008; Kennedy & Fiss, 2009).

Voluntary standards are one practice that has attracted growing interest. A voluntary standard verifies that an organization or product has met defined standards of performance (King et al., 2005). Delmas and colleagues (Delmas & Toffel, 2004; Delmas, 2002; Delmas & Montes-Sancho, 2011) have found that the legitimacy of emergent standards arises from regulative, normative and cultural-cognitive sources (Scott, 1995). Regulative sources include

1 The first author: a) volunteered at the 2008 USGBC Greenbuild Conference conducting 23 informal interviews with merchants, builders, consultants and USGBC employees, b) conducted formal interviews with consultants, USGBC employees, architects, and entrepreneurs, c) attended two LEED charrettes, d) became a LEED Green Associate, and e) engaged in careful reading and notation of multiple texts regarding LEED and green building. We utilized these data to ground our theorizing and provide illustrative examples.

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“rule-setting, monitoring and sanctioning activities” (Scott, 1995:52) of the state such as providing tax breaks for adopters (Sine, Haveman, & Tolbert, 2005). Normative sources include actors that present standards as morally “right” such as SMOs and trade associations (Russo, 2001). Cultural-cognitive sources create an environment where a standard is taken for granted as “normal”; sources of cognitive legitimacy are adoption by peers (Coleman, Katz, & Menzel, 1957) and marketing efforts (Van den Bulte & Lilien, 2001).

Despite voluntary standards permeating multiple, disaggregated industries (King, Prado, & Rivera, 2012; Wijen, 2014), extant studies have focused almost exclusively on highly centralized, regulated industries such as electric utilities (Delmas & Montes‐Sancho, 2010; Sine et al., 2007), traditional manufacturing (Delmas & Toffel, 2008; King et al., 2005), and chemical production (King & Lenox, 2000). This focus has led to an emphasis on regulation and isomorphism, neglecting the roles of private actors and cultural forces in driving adoption.

SMOs, intermediaries, entrepreneurs, and localized regional culture have all been shown to influence firm’s social and environmental practices (Marquis, Davis, & Glynn, 2013; Marquis, Glynn, & Davis, 2007), yet they are overlooked in the voluntary standards literature.

This is a critical oversight given that environmental issues, and particularly climate change, are of interest to a wide variety of stakeholders and infused with multiple institutional logics (henceforth logics) influencing organizations’ adoption decisions (Ansari, Wijen, & Gray, 2013). Regional differences in logics may have an impact on the receptiveness of organizations to promotion of environmental standards. Regional logics are social “rules of action, interaction, and interpretation that guide and constrain” (Thornton & Ocasio, 1999: 804) actors within a localized geographic community (Lee & Lounsbury, 2015). Such geographically bound “culture, norms, identity, and laws” (Marquis & Battilana, 2009: 284) likely influence the effectiveness of interventions to promote new standard adoption.

LEED provides a robust context to explore the impact of regional logics given the opportunity for multiple public and private actors to influence local adoption decisions. We develop our theory by first discussing the direct impact of both public and private actors in

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promoting LEED adoption. As the LEED standard sought to integrate the market logic of commercial real estate with a community logic of care, we propose that the regional strength of these logics moderated the efficacy of both public incentive policies and private interventions

by SMOs, market intermediaries, and entrepreneurs.

Direct Impacts of Public Policy and Private Actors on Adoption of Voluntary Standards Unlike public certification standards (e.g. Lee, 2009; Sine et al., 2007) private voluntary standards are created with limited government involvement. However, research suggests that regulation has an impact on the adoption of private voluntary standards (Delmas, 2002; Delmas & Montes-Sancho, 2011). Thus, we expect that policies such as tax refunds and rewarding of government contracts based on LEED were effective in promoting adoption. As of 2015, there were economic incentive policies supporting LEED in every state except Nebraska. Consistent with prior research, we anticipate that such policy interventions will have a direct and significant positive impact on regional adoption.

While prior studies have established the role of public policy, we private organizations such as SMOs, professionals, and entrepreneurs may also support standard adoption. Private actors may help to legitimize an emerging standard through: 1) justifying, framing, and advocating to foster normative legitimacy (Sine & Lee, 2009), 2) professionalizing the standard through linking it to current professions and providing infrastructure to support its adoption (Suddaby & Viale, 2011), and 3) the creation of new products and services to provide cognitive legitimacy for the standard (Tolbert, David, & Sine, 2011).

SMOs and Adoption. SMOs can foster normative legitimacy for voluntary standards that align with the goals embodied within a movement. Building from extant sociological work on technology and social movements (Hess, 2005), management scholars have recently examined technology-focused SMOs (TSMOs) as a form of â&#x20AC;&#x153;â&#x20AC;Śspecialized SMO that exclusively focuses on supporting the development and adoption of a specific technology to advance its social goalsâ&#x20AC;? (Pacheco, York, & Hargrave, 2014: 1610). In a pair of studies,

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Pacheco and her co-authors detailed how “clean energy” TSMOs supported the nascent wind energy industry (Pacheco et al., 2014; York et al., 2016a).

While TSMOs lack the coercive power of the state, they may convey normative legitimacy on a specific technology and serve as a powerful signal of its viability (Sine & David, 2010). Prior work has established that both professional associations (Hoffman, 1999; Sine et al., 2005) and SMOs (Sine & Lee, 2009) can galvanize collective action to legitimize emerging industries. Such organizations help to create a collective identity around emerging practices and sectors (Wry, Lounsbury, & Glynn, 2011). As such, TSMOs can be construed as actors who “expend effort to devise and promulgate principles specifying appropriate behavior” (Scott, 2010: 30) and generate normative legitimacy. We argue that the creation of a collective identity and normative legitimacy is crucial for adoption of new voluntary standards that break with established practice. Therefore, we anticipate that TSMO support for an emerging standard will have a direct and significant impact on adoption.

Market Intermediaries and Adoption. Market intermediaries -- economic agents that help buyers and sellers to transact (Spulber, 1996) -- may create legitimacy for a new practice through easing adoption and fostering legitimacy. For example, Khanna and Palepu (1999) found that the presence of financial service firms in Chile eased financial transactions, improving stock performance. Market intermediaries may impact standard adoption through educational efforts that link the emerging standard to extant practices (Scott, 1995; Suchman, 1995). Such efforts “create and warrant knowledge systems” (Scott, 2010: 30), increasing knowledge of the standard. Through educational efforts and promoting their services, intermediaries increase the comprehensibility of the new standard. Intermediaries offer knowledge about the standard and consult those seeking certification (Delmas, 2002).

In the case of green building, intermediaries are real estate professionals (e.g. architects, project managers, real estate agents) who become LEED Accredited Professionals (AP). The USGBC created the AP program to verify that an individual is knowledgeable on green building. By taking an exam, construction professionals can become APs and offer

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consultancy on LEED. When intermediaries themselves are certified, they become authorities and lend professional legitimacy to the standard through educating others and promoting their services. Because intermediaries can reduce the cost of standard adoption, we would generally expect a greater density of market intermediaries to have a positive direct impact on adoption.

Environmental Entrepreneurs and Adoption. Entrepreneurs can create means to align the voluntary standard with existing practices, increasing cognitive legitimacy for the standard.

New voluntary standards often require entrepreneurial entry of complementary product and service producers (Tolbert et al., 2011). For example, the advent of the USDA’s organic food standard necessitated the creation of a network of ingredient suppliers to facilitate adoption (Lee et al., 2017). By offering new services and products, entrepreneurs can increase culturalcognitive legitimacy for the standard by aligning it with current practice.

The creation of a new green building sector inherently required entrepreneurial entry of product and service providers to provide materials, products, and services. Because commercial builders do not vertically integrate, LEED fostered an entrepreneurial opportunity by awarding points for using local suppliers. In one LEED meeting, the project manager described the regional materials credit as, “It depends on what we specify…where our roof is coming from, where our precast is coming from…we need to draw the (geographic) circle.” By offering new services and products, we expect that entrepreneurs provide the resource base to increase adoption of LEED. Thus, we anticipate that regional density of such “environmental” entrepreneurs will have a direct and positive impact on LEED adoption.

Voluntary Standards Promotion Filtered through Regional Logics Up to this point we have argued public regulatory action and private advocacy will directly drive voluntary standards adoption. We now theorize that these efforts are also filtered through regional logics. The logics perspective “…focuses on explaining how organizational action is shaped by shared sets of beliefs—or cultural influences—that rationalize the value of particular interests and identities (Thornton et al., 2012)” (Cobb, Wry, & Zhao, 2016: 2106). A core assumption of this approach is that “…to understand individual and organizational behavior it

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must be located in a social and institutional context…” (Thornton & Ocasio, 2008: 102).

Logics permeate a geographic region when present both symbolically, in beliefs and norms, and materially, through practices and organizational instantiations. The logics approach addresses the “… need for a correction in organization theory towards taking into account local community influences to explain organizational behavior” (Thornton et al., 2012: 71).

Regional logics originate through the historic patterns of regulatory structure, social norms, and prevalence of organizational forms in a bounded geographic area (Marquis & Battilana, 2009). Thornton et al. (2012: 54) explain that logics can be empirically examined through the cultural symbols, material practices, and differing goals they embody. Logics may be aligned with a given ideology (e.g. a market logic is typically aligned with a politically conservative ideology (Thornton, Ocasio, & Lounsbury, 2012)) but they do not necessarily outline a specific set of goals for collective action (Zhao & Wry, 2016). Thus, logics provide a lens for organizational actors to view practice adoption (Lounsbury, 2007), industry consolidation (Marquis & Lounsbury, 2007), and engagement in corporate social responsibility (Lee & Lounsbury, 2015; Marquis et al., 2013).

In the climate change debate, a market logic that valorizes economic efficiency, profits, and self-interest has often conflicted with a community logic that advocates commitment to the community, collective benefit, and reciprocity (Hoffman, 2015; Hoffman, 2011b, 2011a).

Under a market logic, “profit-maximization is an appropriate goal or ‘basis for strategy’ [while] serving social need is only considered to the extent that it complements efficiency and control seeking behaviors” (Smets, Jarzabkowski, Burke, & Spee, 2015: 934). In contrast, a community logic embodies common norms, trust, and belief in reciprocity (Berrone, Gelabert, Massa-Saluzzo, & Rousseau, 2016; Pretty & Ward, 2001). These factors have been shown to influence belief in the urgency of addressing climate change regardless of the economic costs incurred (Leiserowitz, Maibach, Roser-Renouf, Feinburg, & Rosenthal, 2013).

While the logics perspective has long been grounded in family, religion, state, market, professions, and corporations (Thornton, 2004; Thornton & Ocasio, 1999), the concept of a

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community logic is a relatively recent addition. A community logic is not orthogonal to a market logic; rather, it offers a differentiated set of beliefs and normative assumptions. A community logic has norms of group membership, trust, and reciprocity rather than economic profitability and self-interest (Thornton et al., 2012). Those concerned about climate change tend to hold strongly collectivist values and to favor government intervention to deal with the threat, positions aligned with a community logic (Hoffman, 2011b; Leiserowitz et al., 2013).

The strength of a community logic, in the form of community social capital (Kwon, Heflin, & Ruef, 2013; Laursen, Masciarelli, & Prencipe, 2012), has been shown to foster recognition and resolution of environmental issues (Brondizio, Ostrom, & Young, 2009; Wolf, Adger, Lorenzoni, Abrahamson, & Raine, 2010). Within this literature, community social capital is defined as “the idea that social bonds and norms are important for people and communities” (Pretty, 2003: 1913) and “an attribute of individuals and their relationships that enhances their ability to resolve collective action problems” (Ostrom & Ahn, 2003: 4).

Beyond the climate change debate, research has shown the contrast between market versus community logics in settings ranging from symphonies (Glynn & Lounsbury, 2005), insurance (Smets et al., 2015), economic development (Cobb et al., 2016; Venkataraman, Vermeulen, Raaijmakers, & Mair, 2016; Zhao & Lounsbury, 2016; Zhao & Wry, 2016) and community banking (Marquis & Lounsbury, 2007). Similar conflict has been reported between these logics in the emergence of sectors seeking to address environmental degradation such as recycling (Lounsbury, Ventresca, & Hirsch, 2003), organic foods (Lee et al., 2017), wind energy (Pacheco & Dean, 2015; Pacheco et al., 2014; Russo, 2003), and solar energy (Kapoor & Furr, 2015; Meek, Pacheco, & York, 2010). In each of these sectors, actors experienced tensions between economic goals aligned with a market logic and conflicting ecological goals aligned with a community logic.

As noted above, market and community logics are not diametrically opposed; they simply support goals that often come into conflict. When and how actors are motivated to act on such issues depends upon their identification with varying logics. In the case of LEED,

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adoption may be motivated by an instrumental, strategic goal aligned with a market logic identity (e.g. shrewd real estate developer) or an altruistic, legitimizing identity aligned with a community logic (e.g. progressive employer) (Gauthier & Wooldridge, 2012; Hoffman & Henn, 2008). When framed with a market logic, LEED is associated with higher rates of occupancy, reduced costs, and employee retention; a community logic frames LEED as addressing environmental issues and reducing the negative health impacts of buildings.

Therefore, we do not argue that either logic will directly influence LEED adoption, but that the strength of each logic will filter how actors view efforts to promote LEED adoption.

This filtering effect results because individuals “…who are deeply embedded in a particular institutional logic through identification and socialization are more likely to invoke knowledge that is part of that institutional logic” (Thornton et al., 2012: 84) when assessing new opportunities and issues (Lee & Lounsbury, 2015). We extend this insight to posit that through attention and identification, the strength of regional market and/or community logics will filter potential adopters’ impression of public and private efforts to support LEED. Public Policy and Regional Logics. We argue that prevalent regional logics may moderate the effectiveness of policy interventions because “…logics will have a primary influence in fields or for issues where local geography is a pressing influence on decision making” (Lee & Lounsbury, 2015: 852). In the case of green building, local governments sought to persuade builders to adopt. Proponents often seek to align their arguments with those logics valued by important audiences (Jones, Maoret, Massa, & Svejenova, 2012). For example, Lee and Lounsbury (2015) showed that in regions dominated by a pro-conservative logic, facilities were less likely to comply with demands to reduce toxic emissions than facilities embedded in a pro-environment community.

We propose that the efficacy of economic incentive policies such as tax breaks and subsidies will be more effective in communities dominated by a market logic for three reasons.

First, the target audience for LEED adoption largely consisted of established real estate developers; building owners ultimately make the decision to adopt. Economic incentive

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policies are inherently aligned with a market logic of self-interest and profitability, and thus may tilt potential adopters towards viewing the voluntary standard as a market opportunity.

Second, incentive policies create the possibility for competitive advantage and differentiation through certification. Economic goals, such as increased revenues or reduced costs, can be aligned with the standard through incentives, fostering a perception that certification is economically desirable. For example, Pacheco et al. (2014) showed that incentive policies for wind energy adoption lead to separate and differentiated growth. One green building consultant described this motivation as follows: …if you’re in business and you wait until all the facts are in and commonly agreed upon, you’ve lost most of the potential rewards. Leaders act when others are sitting on the sidelines, and as we’ve seen, there are plenty of bold leaders in the world of commercial green building (Yudelson, 2007: 85).

Third, incentive policies for adoption advocate a market-based narrative through which to frame adoption. Proponents of new practices such as voluntary standards must create stories (Lounsbury & Glynn, 2001), meaning (Khaire & Wadhwani, 2010), and collective identities (Kennedy, 2008) which resonate with their target audiences. The earliest advocates of green building realized the need for such “market-based” framing: Building owners will only embrace green building when it is tied directly to their bottom line: rental rates, tenant leasing, lower expenses, higher occupancy rates, greater loan amounts at lower interest rates, higher building sales prices, and improved return on investment (Gottfried, 2014: 72).

While today there is evidence for the economic benefits of green building (Eichholtz et al., 2010) in the early days proof was absent (Yudelson, 2007). Incentive policies provided clear economic benefits, aligning LEED with a market logic. While early advocates sought to portray green building as aligned with a market logic, this was met with great skepticism.

Gottfried documented his struggles to reach building owners in the early days of the USGBC: Getting building owners to support us was a greater challenge. They were understandably, more immediately interested in the bottom-line than in saving the planet. In my early lectures, I made the mistake of focusing on the environmental degradation caused by buildings. The feeling in the room was dead (Gottfried, 2014: 71).

For actors embedded within a market logic, LEED was likely perceived as increasing construction costs and creating additional hurdles for building owners. Incentive policies can shift such views by encouraging action that contributes to their adopters’ economic interests,

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aligning with a market logic. This is a critical step for voluntary standards that invoke certain costs, but uncertain economic benefits.

In regions imbibed with a strong community logic, we would anticipate that economic incentive policies would have a lesser impact. Because such regions will perceive LEED as a communitarian -- rather than economic -- good, such policies are likely redundant. As such, we posit that policies in these regions may be perceived as helpful, but not necessary by building owners. Prior work (York and Lenox, 2014) has suggested that supplier entry into green building is more likely in regions steeped in environmentalism, which is highly associated with a community logic. These suppliers likely also reduce the transaction costs of LEED adoption in such regions, lessening the impact of economic incentives. Thus, we hypothesize that: Hypothesis 1: Government economic incentive policies will have a greater impact on LEED adoption when the market logic in a region is stronger, but they will have no difference in impact on LEED adoption when the community logic in a region is stronger.

SMOs and Regional Logics. In contrast to economic incentives, SMOs are more highly aligned with a community logic than with a market logic. For example, York and colleagues (2016a) detailed how SMO efforts to justify wind energy were rebuffed by audiences embedded within a strong market logic. As the sector evolved, more business-centric TSMOs focused on growing the renewable energy sector as ecologically and economically beneficial.

In the case of green building, the USGBC has clearly been the dominant TSMO. The USGBC sought commercial actors’ involvement from the beginning, but it focused largely on the reduction of negative environmental impacts through green building technology.

Thus, we anticipate that local USGBC membership would have a greater positive impact on adoption in regions embedded in a strong community logic. In regions with a strong community logic, environmental arguments from TSMOs will likely find greater support through aligning with belief in collective benefit, reciprocity, and working for the good of all.

One early LEED adopter described their motivation as: …community building purposes, social purposes. All these different reasons…We want them to leave here thinking, ‘Say, maybe I should rethink some of my values.’… To understand the connectedness for example… We’re all one, we’re all connected…It’s like trying to live simply. To work with less, to have gentle footprints on planet earth (Duckles, 2013: 273).

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Such motivations are aligned with social movement support, as well as a community logic.

In contrast, a market logic does not align with such motives and frames. Because a market logic emphasizes the pursuit of self-interest, and particularly economic interests, protecting the natural environment may be perceived as a constraint on freedom and profitability. While the strategic adoption of voluntary standards has often been utilized as a tactic to avoid mandatory regulations (Lenox, 2006), in the case of LEED, there was no threat of industry-wide regulation. Thus, we hypothesize: Hypothesis 2: TSMOs will have a greater impact on LEED adoption when the community logic in a region is stronger, but they will have no difference in impact on LEED adoption when the market logic in a region is stronger.

Market Intermediaries and Regional Logics. We argue that the impacts of market intermediaries on the adoption of LEED standards are also likely contingent upon regional logics. Because LEED APs are already members of the real estate industry, their influence is driven through personal expertise and status, aligned with the hierarchical tendencies of a market logic (Lounsbury, 2007; Scott, 2008). Therefore, such intermediaries may be less effective in regions dominated by a community logic, as the professionalization of green building could be looked upon as “green washing” through creating a false impression of environmental responsibility (Marquis, Toffel, & Zhou, 2016). This tension was highlighted during an early attempt to professionalize the USGBC: A scientist at the National Audubon Society had just begun his report on a grant application they had been working on for the pollution tax committee when Bill King (Armstrong World Industries) interrupted. “Why are we taking this on?” he asked. “We have many more ‘apple pie’ priorities.”

“This is chicken shit” the scientist declared. A new board member, he was responsible for Audubon’s pioneering green building in Manhattan…None of these folks here are environmentalists; they’re just a front for the industry” (Gottfried, 2014: 92).

In regions with a strong community logic, community members may view professionals who become APs as insincere supporters of the green building movement. Under a community logic, the concept of linking AP status to self-interest and economic gain may turn professional legitimacy into a liability, rather than an asset. Thus, we hypothesize: Hypothesis 3: Market intermediaries will have a greater impact on LEED adoption when the market logic in a region is stronger, but they will have no difference in impact on LEED adoption when the community logic in a region is stronger.

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Environmental Entrepreneurs and Regional Logics. Regional green building suppliers can be conceptualized as hybrid organizations that blend a community and market logic by producing ecological beneficial products through a for-profit firm (Battilana & Lee, 2014; Besharov & Smith, 2014). Prior work has referenced green building entrants as “environmental entrepreneurs” (York & Lenox, 2014: 1946), defined as “individuals who create new, often for-profit, ventures that help address environmental challenges” (Lenox & York, 2012: 70; York, O'Neil, & Sarasvathy, 2016b). The integration of community and market logics distinguished these start-ups from intermediaries, for whom green building was an extension of a profession, and from TSMOs that relied on philanthropic membership.

Because environmental entrepreneurs blended the market and community logics, we believe their impact will be positively moderated by both. Regions with a strong community will likely support such entrepreneurs both economically through patronage, but also psychologically by assessing what they are doing as normatively “right.” For example, in regions embedded in a community logic, potential customers often use local suppliers (Weber, Heinze, & DeSoucey, 2008). Recent work has shown that community identity drives the opportunities pursued, by entrepreneurs as well as the audiences they engage (Fauchart & Gruber, 2011). When regional logics are aligned with the ecological mission of environmental entrepreneurs, we would expect them to be more effective in promoting a nascent category.

We also expect that environmental entrepreneurs will be effective in regions dominated by a market logic, as for-profit entrepreneurship will be a highly-valued activity. By creating for-profit firms to support a nascent voluntary standard, entrepreneurs encourage the view that certification provides economic growth and employment in a community. For example, York and colleagues showed how views of the wind energy category evolved away from ecological impacts, and towards a “new energy economy” as entrepreneurs entered the field (York et al., 2016a). Environmental entrepreneurs help audiences embedded in either logic to see what they want to see in a voluntary standard, leading us to hypothesize: Hypothesis 4: Environmental entrepreneurs will have a greater impact on LEED adoption when the market logic in a region is stronger, and will also have a greater impact on

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LEED adoption when the community logic in a region is stronger.

METHODS To test our theory, we utilized a longitudinal dataset of LEED certification at the MSA level.

MSAs are geographical centers in the U.S. with a population of at least 50,000. Our window of observation begins in 2000 (the year LEED certification was made available) and runs through 2014 (the last full year data were available). During this time, there were 22,135 LEED certified projects in the U.S. We organized the data into an MSA-year panel, with 5,110 MSAyear observations in 341 MSAs for which we had complete data. Additional analyses and information about the dataset2 are available in the Appendix and online at http://itsnoteasybuildinggreen.strikingly.com.

LEED Certified Buildings As our dependent variable of LEED adoption, we utilized a count of new LEED certified buildings in an MSA-year. To construct this measure, we aggregated zip-code level information on building locations to the MSA level using a spatial concordance file3.

Regional Logics Community logics. To measure the regional strength of a community logic, we used an established measure of community social capital from the regional economics literature (Rupasingha, Goetz, & Freshwater, 2006) available at a county level from the North East Regional Center for Rural Development at Pennsylvania State University (http://aese.psu.edu/nercrd/community/social-capital-resources). As these data are available for the years 1990, 1997, 2005, and 2009, we interpolated data for missing years for each county and then aggregated to the MSA level.

2 Please note that two of the authors have utilized a subset of these data in a previous publication to compare the drivers of de novo and de alio entry into the green building sector (York & Lenox, 2014). Unlike this study, we used data dating from 20002007 at the state (not MSA) level to measure the adoption of LEED, USGBC membership, state-level policies, entrepreneurial entry, and commercial construction.

3 In sensitivity analyses, we also leveraged LEEDâ&#x20AC;&#x2122;s four levels of certification: Certified, Silver, Gold, or Platinum. Prior work has noted the possibility of symbolic versus substantive adoption of voluntary standards (e.g. Delmas & Mones-Sancho, 2010).

While we found building owners default to the minimum Certified level of LEED, some bear additional costs to achieve a higher level of certification. For each project, we coded the Level of Certification from 1 to 4 points: 1 signified Certified, 2 signified Silver, 3 signified Gold, and 4 signified Platinum. We aggregated these scores at the MSA-level. This weighted sum provides a measure of the extent adopters in a region pursued more substantive levels of certification versus symbolic, lower levels of certification. This model can be viewed in Table F1 of the Appendix here: https://goo.gl/KfCBkj. We also utilized an alternate ratio-based specification of the dependent variable, by normalizing these two count-based measures by the number of new real estate projects in an MSA with consistent results.

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Market logic. We could find no previous work that measured market logic prevalence within an MSA (but see Zhao & Lounsbury, 2016 for a country level measure). Since the state of the art in logics research is to construct variables using symbolic and material proxies (e.g.

Cobb et al., 2016) we created a factor composed of six items to capture the strength of the market logic in each MSA-year. Four of these items leverage the finding that political conservatism often aligns with a pro-market logic, particularly regarding environmental issues such as climate change (Hoffman, 2015; McCright & Dunlap, 2011). The additional two measures build from canonical work on market logics (Friedland & Alford, 1991).

The first item captures the ideology of each MSAâ&#x20AC;&#x2122;s political leaders on a liberalâ&#x20AC;&#x201C; conservative continuum (Berry, Ringquist, Fording, & Hanson, 1998). This item was constructed using the voting of state congressional delegations, the outcome of congressional elections, the division of state legislatures, and the party of the governor (Lee, 2009). Data for this measure is from the Citizen and Government Ideology database created by Berry and colleagues (1998) and maintained by Richard Fording at the University of Alabama (https://rcfording.wordpress.com/state-ideology-data/). For our analysis, we weighted this state-level measure to each MSA by population. The second item also derives from this database and captures the political ideology of citizens based on state-level election results for conservative versus liberal candidates (York & Lenox, 2014).

As our third item, we utilize the percentage of voters in an MSA that voted Republican in national elections. We obtained data at the congressional district level from DailyKos.com (http://www.dailykos.com/news/Pres-by-CD) and aggregated it to the MSA level. These data are widely used in political science research (e.g. Abramowitz & Saunders, 2006).

Fourth, we computed the ratio of contributions to Republican candidates relative to the total amount of donations in each MSA. We calculated this measure using county level data on contributions to federal candidates, parties, and PACs aggregated to the MSA level. These data are available on a biennial basis from the Center for Responsive Politics website (https://www.opensecrets.org) and have previously been used (Lee and Lounsbury, 2015).

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Fifth, to capture how tax policies may support a market logic, we used a measure of the local tax burden for businesses. We reverse coded this measure such that the lower the tax burden for businesses in an MSA, the stronger the market logic. We purchased this data from Moody’s Analytics (https://www.economy.com/regions/us-states-and-metro-areas).

The final item was a measure of the density of registered labor unions in a MSA. We reverse coded the item such that the lower the density of unions, the stronger the market logic.

The conflict between a market logic and labor unions goes back to the foundations of the logics perspective (Friedland & Alford, 1991: 257). Western and Rosenefeld (2011: 533) empirically observed that: “….unions offered an alternative to an unbridled market logic… As unions declined, not only did the logic of the market encroach on what had been the union sector, but the logic of the market deepened in the nonunion sector....” We obtained data on the annual number of registered labor unions (NAICS code 813930) at the county level from the Quarterly Census of Employment and Wages, then aggregated to the MSA level and normalized by population.

Using principal component factor analysis, these six items loaded into a single factor with an eigenvalue of 2.25 and an alpha value of 0.66. In sensitivity analyses, we explored the use of a reverse-coded liberalism measure using data from Americans for Democratic Action, rather than the Republican voting and donation data. In addition, we also checked the relationship of our market logic measure to related published metrics (Zhao & Lounsbury, 2016). A discussion of these verifications of the face validity of our measure, as well as visualizations and complete listing of the regional strength of each logic by MSA may be viewed in Appendices B (https://goo.gl/Lw3iZW) and C (https://goo.gl/1xE4vE).

Interventions Economic incentive policies. We measure economic incentive policies as the implementation of public policies that supported the adoption of LEED. We gathered data on policies from an online database provided by the USGBC, cross-validated with the Database of State Incentives for Renewables and Efficiency (http://www.dsireusa.org). We included

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policies enacted at a city or county level in our models, matched to appropriate MSAs. As we were interested in the effects of public policy on adoption rather than in the effects of any one policy, we constructed a count variable from the number of green building economic incentive policies by MSA-year. Because this variable is strongly right-skewed, we used its logged value in models. In sensitivity tests, we also computed the effects of state-level policies, available in Table F2 of Appendix F (https://goo.gl/KfCBkj).

Market intermediaries. We measure market intermediaries as the number of LEED APs in each MSA for a given year. To be clear, APs are not certifiers. Their role is purely advisory and is analogous to accounting advisors (as opposed to auditors). USGBC membership and APs should not be conflated. The USGBC cannot be joined by individuals, only by organizations; LEED AP certification is granted at an individual level. It is not a requirement that a LEED AP be involved to achieve LEED certification. So, while we expect that both USGBC membership and LEED AP certification levels will directly impact adoption, they are not endogenous to LEED projects. Data to construct this measure were provided by the Green Building Certification Institute (GBCI). We aggregated this zip code data to the MSA level, normalized by population, and scaled for interpretation of coefficients.

TSMOs. The USGBC has been the dominant TSMO in green building. Unlike trade association-sponsored programs, such the American Chemistry Councilâ&#x20AC;&#x2122;s Responsible Care Program (Lenox, 2006), LEED certification is decoupled from USGBC membership. One need not be a member of USGBC to receive LEED certification and the owners of LEED certified projects are not necessarily USGBC members. To create an annual measure of TSMO activity we obtained the addresses and joining dates of USGBC members. We normalized this count by MSA population and multiplied by 100,000 to scale appropriately for model coefficients.

Environmental entrepreneurs. To measure the degree of support by environmental entrepreneurs for LEED adoption, we utilized the GreenSpec Directory of green building product suppliers created by Building Green, an independent publishing company (BuildingGreen, 2007). Products are identified for inclusion by GreenSpec employees from

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press releases, trade shows, articles in green building publications, and general research.

GreenSpec is not advertising-based, and firms do not pay to be listed in the directory. The GreenSpec directory has been published annually every year since 1999 and identifies products that can help to obtain LEED certification. GreenSpec is neither associated with, nor supported by, the USGBC. We coded this measure as the number of new companies listed in the directory for each MSA-year in our panel. Following prior work in the green building context, we separated entrepreneurial entrants (founded no earlier than 1994) from incumbents and used a log-transformed count at the MSA level as an indicator of environmental entrepreneur entry into the green building sector (York & Lenox, 2014).

Control Variables We included a series of control variables to account for additional forces that may have impacted LEED adoption. All controls were time-varying, at the MSA level. Further details on our controls are available in Table D1 of Appendix D here: https://goo.gl/FC5xCt .

General regional level controls. We first controlled for a series of socioeconomic characteristics of MSAs that we expected to influence LEED adoption rates. First, we accounted for population density (obtained from the Census Bureau) as we expected that LEED certification levels should be higher in more densely populated regions. Second, we included a control for GDP Per Capita to control for the likelihood that affluent regions may more easily afford LEED certification. We obtained this measure from the Bureau of Economic Analysis. Third, we controlled for MSA size as we would expect to find more certifications in larger regions. To account for impacts of state-level elections on MSA-level policies and behavior, we included a variable that captured party legislative control obtained from the National Conference of State Legislatures (NCSL) website.

Context specific controls. We next included controls that were specific to the green building context. First, we controlled for the cost of energy and water usage. We purchased the energy data from Moodyâ&#x20AC;&#x2122;s, and obtained the water data at county-year level from the United

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States Geological Survey (https://water.usgs.gov/watuse/data/). We expected that both these factors could have an impact due to LEEDâ&#x20AC;&#x2122;s focus on reducing electricity and water usage.

Next, given the focus of the LEED standard on reducing environmental degradation, we included controls for regional environmentalism. First, we controlled for environmental activism by using the average revenue and assets per capita of environment, conservation, and wildlife organizations from the National Center for Charitable Statistics. Second, we controlled for pro-environmental attitudes in a region (Delmas, Russo, & Montes-Sancho, 2007; Kahn, 2007) using the League of Conservation Voters (LCV) Scorecard data that awards points based on how congressional members voted on environmental measures.

We also controlled for total commercial construction area as it could influence the supply of building projects and hence the demand for LEED construction. We purchased these data from Construct Connect, a private company that tracks commercial real estate. To account for prior adoptionâ&#x20AC;&#x2122;s influence we included a measure of mimetic isomorphism (logged prior LEED adoption) (Haveman, 1993). Last, we also included a full set of year dummy variables to account for unobserved differences across years, and general time trends driving adoption.

ANALYSIS AND RESULTS In Table 1, we present summary statistics and bivariate correlations. As expected, both incentive policies (r=0.45), as well as the private actors of interest (TSMOs, r=0.17; market intermediaries, r=0.27 and environmental entrepreneurs, r=0.39) are positively correlated with LEED certification. The mean Variance Inflation Factor (VIF) across all the variables was 1.58 and tests confirmed average VIF scores below 10 suggesting that multicollinearity is not a concern (Kennedy, 2003). Given the count nature of our dependent variable and that it exhibited over-dispersion, we utilized a negative binomial estimation model (Allison & Waterman, 2002; Greene, 2003). We lagged all independent variables by one year to enable causal interpretation (Wooldridge, 2010). In robustness tests discussed below, we utilized alternate model specifications.

---Insert Table 1 about here---

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In Table 2, we present our estimates from our main models. Model 1 presents estimates of the baseline model with control variables. We find that the level of LEED adoption in an MSA is significantly positively predicted by the population density (b=0.552, p<0.001), GDP per capita (b=8.782, p=0.003), MSA size (b=0.900, p<0.001), water usage (b=0.10, p=0.006), environmental activism (b=0.030, p=0.048), pro-environmental attitudes (b=0.017, p=0.013), and a larger commercial construction area (b=0.128, p=0.002). We also find that mimetic isomorphism plays an important role, with the level of cumulative prior adoption having a large and statistically significant positive impact on subsequent rates of LEED adoption (b=1.640, p<0.001). In economic terms, this coefficient means that a 1 standard deviation increase in the level of mimetic isomorphism (the logged number of cumulative prior adopters) in an MSA-year would increase the rate of LEED certification in an MSA-year by 170% relative to the current level of adoption.4 ---Insert Table 2 about here--Next, in models 2-6, we sequentially introduce the impacts of our independent variables of interest. In Model 2, we observe that both logics have statistically insignificant direct effects on LEED adoption (market logic: b=-0.038, p=0.166; community logic: b=-0.024, p=0.400). In Model 3, we observe that the impact of economic incentive policies on LEED certification is positive and statistically significant (b=0.255, p=0.015); a 1 standard deviation increase in the number of economic incentive policies would result in an incidence rate ratio (IRR) of 1.03 (=exp(0.255*0.1)), that is a 3% increase in the rate of LEED certifications. In Model 4, we observe that the TSMOs have a positive and significant impact on LEED certification (b=0.18, p<0.001); a 1 standard deviation increase in the number of TSMOs would result in an IRR of 1.16 (=exp(0.18*0.83)), a 16% increase in the rate of LEED certifications. In Model 5, we observe that the market intermediaries have a positive and 4 We compute effect sizes for our findings as follows: Since the negative binomial model is a log-linear model, the beta coefficient predicts the impact of a unit change in the covariate X on the difference in log values of the outcome variable Y (i.e. β = ∆ (ln Yx+1 - ln Yx)). Taking the exponent of both sides of this equation, we get exp (β)= exp (∆ (ln Yx+1 - ln Yx)) = exp (ln Yx+1 /ln Yx )= Yx+1 / Yx.. This ratio, also known as the incidence rate ratio (IRR), can therefore be interpreted as the relative increase (i.e. in relation to the existing level) of the outcome variable for a 1 unit change in the covariate (https://stats.idre.ucla.edu/stata/output/negative-binomial-regression/). Since the standard deviation of the mimetic isomorphism variable is 0.61 (see Table 1), and β=1.64, we compute the IRR for a 1 standard deviation increase in the covariate as exp (1.64*0.61) = 2.7. This corresponds to a 170% increase above the existing baseline IRR value of 1 (i.e. (2.71)/1=1.7/1=170%).

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significant impact on LEED certification (b=0.06, p<0.001); a 1 standard deviation increase in the number of market intermediaries would result in an IRR of 1.17 (=exp(0.06*2.56)), a 17% increase in the rate of LEED certifications in an MSA-year. In Model 6, we observe that the environmental entrepreneurs have a positive and significant impact on LEED certification (b=0.277, p=0.009); a 1 standard deviation increase in the number of environmental entrepreneurs would result in an IRR of 1.03 (=exp(0.277*0.12)), that is a 3% increase in the rate of LEED certification.

In Model 7, we include the effects of both logics, economic incentive policies, all three private actors, and all control variables. We observe that the effect of the market logic variable is negative and significant (b=-0.051, p=0.049). This means that a 1 standard deviation increase in the strength of the market logic leads to an IRR of 0.95 (=exp(-0.051*1)), a 5% decrease in the rate of LEED certification. The impact of the economic incentive policies is no longer statistically significant (b=0.048, p=0.607). In terms of the private actors, the TSMOs (TSMOs: b=0.11, p<0.001, IRR=1.10), market intermediaries: b=0.04, p<0.001, IRR=1.12), and the environmental entrepreneurs (b=0.17, p=0.07, IRR=1.02) each retain statistical significance. In terms of their cumulative effect, a 1 standard deviation increase in all four independent variables (i.e. policies, TSMOS, market intermediaries, and environmental entrepreneurs) combined would lead to a 25.9% (1.005*1.10*1.11*1.02=1.259) increase in the rate of LEED adoption5.

In Models 8-11 we test our hypotheses by interacting public and private engagement by the strength of the market and community logic in a region6. In Model 8 we test our first hypothesis, observing that the marginal impacts of economic incentive policies on LEED certification are positively moderated in regions with stronger market logics (b=0.412,

5

Since the nbreg model is a log-linear model, the β coefficients have an additive effect in the ln(Y) scale and the IRR has a multiplicative effect in the Y scale (https://stats.idre.ucla.edu/r/dae/negative-binomial-regression/).

6 Since the negative binomial model is a non-linear model, interpreting the coefficients of interactions is not straightforward as with a linear model (Wiersema & Bowen, 2009; Zelner, 2009) We therefore followed the approach recommended by Zelner (2009) and King and colleagues (King, Tomz, & Wittenberg, 2000) and use simulations to visualize the interaction effects at both strong (2 standard deviations above the mean value of 0) and weak (2 standard deviations below the mean value of 0) levels of each logic, with other model variables at mean values, and plot confidence intervals around each of our predicted point estimates. We used the Stata routine intgph provided by Zelner and Blanchette for this purpose.

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p=0.001). We also observe a positive, but insignificant, coefficient between the economic incentive policies and community logics variables (b=0.222, p=0.183). We visually plot these effects in Figure 1 and interpret them below.

---Insert Figure 1 about here--In Figure 1a, we plot the impacts of increases in the number of economic incentive policies implemented in an MSA (unlogged this variable for ease of illustration) on the predicted number of LEED certifications. In this panel, we plot the impact of economic incentive policies at both strong (dashed line) and weak (solid line) market logic levels along with the corresponding 90% confidence interval bands. In terms of effect sizes, we observe that as the number of policies increases to its maximum value in the sample (14), the difference in the level of adoption between strong and weak market logics increases by 1.33 LEED certifications, an approximately 35% increase over the average level of adoption in a MSAyear in the sample (average is 3.77 LEED certifications in a MSA-year, per Table 1). In Figure 1b we plot the difference in the predicted number of LEED certifications at both strong and weak market logics along with the associated 90% confidence interval (Figure 1b). We observe that the interaction effect between market logics and incentive policies is significant only after the number of policies in a region exceeds 1.03 as indicated by the arrow on the graph as the point at which the confidence interval does not cross 0.

We repeat these analyses and plots for the interaction effect between the community logic and economic incentive policy variables. As shown in Figure 1c, we observe that as the number of policies increases, regions with a strong community logic do not have significantly greater LEED adoption than regions with a weak community logic, as the confidence intervals overlap almost entirely. We again plot the difference in the predicted level of adoption Figure 1d. We observe that the confidence interval in this plot crosses 0 at all levels of economic incentive policies, confirming the lack of a significant interaction effect. Taken together, these results indicate that economic incentive policies are more effective at driving LEED adoption

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in regions with a strong (vs. a weak) market logic, and equally effective in regions with either strong or weak community logics. We therefore find support for Hypothesis 1.

In Model 9, we test our second hypothesis. Contrary to our prediction, we do not find evidence of a positive interaction effect between TSMO strength and community logics (b=0.009, p=0.704); we instead find that TSMOs are more effective at driving adoption as the strength of the market logic increases (b=0.055, p=0.003). We plot these effects in Figure 2.

---Insert Figure 2 about here--In Figure 2a, we observe that as the number of new TSMO members in a region increases, their marginal impact on adoption is greater under a strong market logic than a weak market logic condition. At the highest value of the TSMO variable, the difference in adoption level between strong and weak market logics is 3.56 more certifications per MSA-year, a 94% increase over the average level of adoption. In Figure 2b, we plot the difference between the strong and weak market logic conditions and observe that it is significant once the number of TSMO members exceeds 2.6.

We then repeat these analyses and plots for the corresponding interaction effect between the community logic and TMSOs. As shown in Figure 2c, we observe a negative interaction effect, but the pattern of overlap of confidence intervals suggests that this is not significant. To confirm these results, we plot the difference in the predicted level of adoption between strong and weak community logic levels in Figure 2d. The confidence interval in this plot crosses 0 at all levels of TSMOs, confirming the lack of a significant interaction effect.

Taken together, these results suggest that TSMOs are more effective at driving adoption in regions with a strong (vs. a weak) market logic, and equally effective in regions with either strong or weak community logics. We therefore do not find support for Hypothesis 2. We further investigated this unexpected result in a set of post-hoc analyses discussed below.

In Model 10, we test our third hypothesis and observe that the effectiveness of market intermediaries increases as the strength of the market logic increases (b=0.012, p=0.029). We

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find no significant interaction effect between the market intermediaries and community logic variable (b=-0.003, p=0.784). We plot these effects in Figure 3.

---Insert Figure 3 about here--In Figure 3a, we observe that as the number of market intermediaries in a region increases, their marginal impact on adoption is greater under a strong market logic condition than a weak market logic condition. At the highest count of market intermediaries (35 new market intermediaries) the difference in adoption level between strong and weak market logics is 4.8 more LEED certifications, a 127% increase. In figure 3b, we plot the difference between the strong and weak market logic conditions and observe that it is significant once the number of market intermediaries exceeds 19.

We then repeat these analyses and plots for the corresponding interaction effect between community logic and market intermediaries. As shown in Figure 3c, we observe a small negative interaction effect, but the pattern of overlap of confidence intervals suggests that this is not significant. We plot the difference in the predicted level of adoption between strong and weak community logic levels in Figure 3d. For all values of the market intermediary variable we observe that the confidence bands cross zero indicating no significant effects. Taken together, our results suggest that market intermediaries are more effective in regions with a strong (vs. a weak) market logic, and equally effective in regions with either strong or weak community logics. We therefore find support for Hypothesis 3.

In Model 11, we test our fourth hypothesis. Here we observe that the effectiveness of environmental entrepreneurs in driving LEED certification increases as the strength of the market logic increases (b=0.318, p=0.008) and as the strength of the community logic increases (b=0.469, p=0.001). We visually show these effects in Figure 4.

---Insert Figure 4 about here--In Figure 4a, we observe that as the number of environmental entrepreneurs in a region increases, their marginal impact on adoption is greater under a strong market logic condition than a weak market logic condition. At the highest value of the environmental entrepreneur

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variable (14 new environmental entrepreneurs), the difference in adoption level between strong and weak market logics is 0.90 LEED certifications, an approximately 24% increase over the average level of adoption. In figure 4b, we observe that this effect is significant when the count of environmental entrepreneurs exceeds 1.7.

We repeat these analyses and plots for the interaction effect between environmental entrepreneurs and the community logic. In Figure 4c, we observe that environmental entrepreneursâ&#x20AC;&#x2122; marginal impact on adoption is greater under a strong community logic than a weak community logic condition. The difference in adoption level between strong and weak community logics is 1.62 more LEED certifications, a 43% increase over the average level of adoption. We again plot the difference in the predicted level of adoption between strong and weak community logic levels in Figure 4d, and observe that it is significant once the value of the number of environmental entrepreneurs exceeds 1.03. Taken together, these results suggest that environmental entrepreneurs are more effective in regions with both a strong market logic and a strong community logic. We therefore find support for Hypothesis 4.

In Model 12, we included the control variables, logics, public policies, private actors and all 8 interaction terms (4 for the market logic and 4 for the community logic). Note that given the necessarily high pairwise correlations between the interaction terms (between 0.3 and 0.7), and the repeated appearance of the same covariates within multiple interaction terms, we expectedly observe that the β coefficients of the interaction terms are of similar economic magnitude to those in models 8-11, but have lower efficiency (i.e. with a larger confidence interval, and increase in the associated standard errors). Including all 8 inter-correlated interaction terms in a single model as we do here potentially increases the risk of type II errors (i.e. incorrectly rejecting an underlying interaction effect) due to incorrectly estimated wide confidence intervals. As anticipated, we observe a lower level of statistical significance in the β coefficients of the individual interaction terms, albeit with marginal effects of similar magnitude (Brambor, Clark, & Golder, 2005; Cortina, 1993; Ganzach, 1998). However, we include this model to explore the filtering impact of logics on the actions of all public and

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private actors as a whole. This approach allows us to assess the extent to which the filtering impacts of logics are relatively weaker or stronger for each of the actors, when viewed as a collective set of factors acting together to promote adoption.

We observe that the interaction term between economic incentive policies and market logics remains statistically significant (b=0.024, p=0.046). The interaction term between environmental entrepreneurs and market logics is significant at the 90% confidence level (b=0.19, p=0.077), and the interaction term between environmental entrepreneurs and community logics is significant (b=0.48, p<0.001). While directionally consistent with our previous models, we observe no statistically significant interaction effects between the logics and TSMOs or the logics and market intermediaries. We return to the implications of these results in the discussion section below.

Sensitivity Analyses We conducted a series of additional analyses to check the robustness of the findings presented in Table 2. These tests included changes to the dependent variables, independent variables, and different model specifications. First, we created an alternate dependent variable of LEED certification level weighting the level at which buildings were certified (i.e. Certified, Silver, Gold, or Platinum levels). Our findings were robust to this alternate specification suggesting our hypotheses hold for substantive versus symbolic adoption. Our results were also robust in models with a Tobit specification, utilizing a normalized count of LEED certified buildings by the number of new commercial building projects, 2 and 3 year lags on LEED certification, and using LEED registered, rather than certified, projects.

Our second series of tests focused on changes to the covariates in our model. First, we re-estimated our models including state dummy variables. Second, given the large number of zero values in some of our independent variables (e.g. incentives, mandates), we specified models utilizing dummy coded versions of these variables. Third, we re-estimated our models using dichotomized measures of both market and community logic variables.

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Our third series of sensitivity tests focused on alternate model specifications. First, we estimated all models using a population averaged negative binomial model specification.

Second, we estimated a zero-inflated negative binomial model specification. Third, given that MSAs are nested within states, we estimated our models using a mixed effects negative binomial specification allowing the fitted intercepts to vary by MSA and state. Our results were robust to each of these alternate specifications.

Co-evolution of adoption, policies, and private actors. There is clearly a potential coevolutionary relationship between public policies, private actors, and LEED adoption. For example, the strength of regional logics might influence public policy interventions as well as the entry of private actors. As adoption increases in a region, this might also in turn have impacts on the covariates in our main model. While using lagged covariates over a 15-year panel, as well as a lagged cumulative version of the dependent variable (mimetic isomorphism) should address most endogeneity concerns (Wooldridge, 2010), we used a series of simultaneous equational modeling approaches to test assumptions regarding endogeneity of the main model covariates. We present the results from two types of simultaneous equation approaches: 1) endogenous treatment effects (Greene, 2003) in Model 1 for economic incentive policies and 2) control functions (Blundell, Kristensen, & Matzkin, 2013; Blundell & Matzkin, 2014; Imbens & Wooldridge, 2017; Wooldridge, 2015) for all public and private actors in Models 2-5 of Table 3.

---Insert Table 3 here--Our main modeling approach treats the actions of the public actors (economic incentive policies) and private actors (TSMOs, market intermediaries and environmental entrepreneurs) as independent. However, it is possible that the presence and/or absence of an incentive policy might in turn impact the efficacy of private actors in promoting LEED adoption by influencing their behavior. To test for this possibility, we re-estimated Model 3, Table 2 using a simultaneous equation model approach (Stata command: etregress) to account for endogenous linear treatment effects (Greene, 2003). In this approach, we first estimate the likelihood of an

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incentive policy being put in place in an MSA-year by using all model covariates and the size of local government (US Census data on government payroll) as an exogenous variable. This binary treatment effect is then used in the second equation to observe the impact of this endogenous treatment on LEED certification. The impact of the treatment was consistent with our main results as shown in Model 1 of Table 3.

Next, to address the potential endogeneity of both public policies and private actors, we use a control functions approach (Blundell et al., 2013; Wooldridge, 2010). The control function approach is a simultaneous equation modeling method with similar assumptions to approaches in linear models such as 2SLS. However, this method is well suited to handling endogeneity in non-linear models, such as negative binomial regression (Blundell et al., 2013; Guo & Small, 2016)7. In the first equation, the endogenous variable is regressed on covariates and a variable that is exogenous to the study context. The reduced form residuals from this equation as well as the endogenous variable are then used in the second-stage, non-linear model (the negative binomial regression) with bootstrapped standard errors (Wooldridge, 2010). For the first stage equationsâ&#x20AC;&#x2122; exogenous variables, we used the size of local government (log of the local government payroll) to predict the number of economic incentives put in place. Following prior research that has shown a link between religiosity and social movement activity (Hannigan, 1991; Smith, 2014), we used the number of religious adherents in an MSA (data from Association of Religion Data Archives) as an exogenous predictor of TSMO activism. We used employment in business associations per capita (NAICS code 813910) from the Quarterly Census of Economics and Wages to predict market intermediaries and the number of clean energy startups (data from the i3 Cleantech Database) as a predictor of environmental entrepreneurship. We show the results from these specifications in Models 2 through 5 of Table 3, finding results consistent with our main analysis.

In Models 6-9 of Table 3, we use a dynamic panel specification to model the dependent variable as an autoregressive process. The dynamic panel specification differs from 7

Note that unlike the 2SLS approach where the predicted variables from a first stage equation with exogenous variables are used in the second stage, the control function approach uses the residuals from the first stage equation in the second stage. See Guo & Small (2016) for further details.

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conventional panels in that we explicitly include lagged versions of the dependent variable (in addition to our measure of isomorphism). All independent variables in this specification are treated as endogenous using the Arellano-Bond system GMM. Studies in strategic management have used this approach to handle endogeneity in non-linear count-based models (Fremeth & Shaver, 2014; Suarez, Cusumano, & Kahl, 2013; Uotila, Maula, Keil, & Zahra, 2009). These models are preferred when the dependent variable partly depends on its own history, the independent variables may not be strictly exogenous, and autocorrelation within regional level variables is possible (Roodman, 2006). The first difference of explanatory variables is instrumented with corresponding levels of lagged variables and the levels are simultaneously instrumented with lagged differences (Fremeth & Shaver, 2014). Because persistence in the dependent variable can cause weak instrument problems in GMM models, we used the system GMM estimator (Roodman, 2006)8. In Models 6-9 of Table 3, results with these specifications are consistent with our results.

DISCUSSION This study advances our understanding of the adoption of voluntary standards by focusing on: 1) the role that public and private actors in influencing adoption, and 2) the role that cultural context plays in determining the effectiveness of these interventions. Our findings confirm that government support can help encourage adoption of voluntary standards; however, private efforts also play an important role. We present evidence that government incentives, TSMOs, and market intermediaries were each more effective in promoting LEED adoption in regions embedded in a strong market logic. In addition, we demonstrate that environmental entrepreneurs were equally effective in promoting LEED in regions with strong market or community logics. Finally, our full model of interactions (Table 2, Model 12) in which interaction terms for both policy and environmental entrepreneurs remain significant raises an

8

We treated all explanatory variables in the system (i.e. at the regional level) as endogenous and the year dummies as exogenous. The instruments used in this specification are their own values for the exogenous variables, and the second and later lags of the endogenous variables since these are not correlated with the current error term. Following Fremeth & Shaver (2014) we also used a two-step robust estimator that corrects for panel specific autocorrelation and heteroskedasticity. We also checked the p values for the Hansenâ&#x20AC;&#x2122;s J statistic for overidentifying restrictions and the second-order autocorrelation term.

Both are insignificant, indicating the instrumental variables are uncorrelated to the error term and there is no second-order autocorrelation, consistent with the underlying assumptions of the model.

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interesting possibility. In this model, we indicate that the efficacy of private actors closer to the standard (TSMOs and market intermediaries) are marginally enhanced by logics, however, the efforts of both policy makers and environmental entrepreneurs are significantly moderated by the prevalence of regional logics. This finding implies that the further actors are from the focal industry they seek to influence, the greater the impact of regional logics. These findings suggest future research could examine actorsâ&#x20AC;&#x2122; position within an industry as a boundary condition of logicsâ&#x20AC;&#x2122; influence.

Taken together, our findings offer confirmation of prior studies that show voluntary standards adoption is driven through isomorphic pressure and governmental support. However, we extend this literature by highlighting the role of private actors in boosting adoption of voluntary standards; our analysis suggests that SMOs, market intermediaries and entrepreneurial entrants may all directly enhance adoption of standards. Our most significant extension of prior work is to highlight the moderating impact of regional culture on both public and private efforts to promote new voluntary standards. In sum, while much of the literature has focused on mimetic adoption processes within industries (Haveman, 1993), we show how practice diffusion is driven by multiple stakeholders operating within specific, local cultural settings (Marquis & Battilana, 2009). In addition, our study raises practical implications for the geographic diffusion of practices that can address environmental challenges, and specifically, climate change. We discuss these contributions in turn.

Public Policy, Private Actors and Voluntary Standards Adoption In contrast to prior studies, rather than focusing on the coercive power of the state, we highlight the role that government can play in actively promoting private voluntary standards.

Where the literature has emphasized that the threat of regulation may motivate the formation of private standards (e.g. Christmann & Taylor, 2006; King & Lenox, 2000), we considered the role of government in providing incentives to encourage adoption of a private voluntary standard. Our study provides evidence that incentive provision by the state can indeed play an important role in the adoption of private voluntary standards.

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Our findings help advance the literature further by providing evidence of the underexamined role of private actors in boosting adoption. Much of the previous work on voluntary standards has focused on the adopters of a new standard, rather than its diverse supporters. In most cases, the adopters are large firms who feel acute pressures by their customers to demonstrate environmentally friendly practices and are largely focused on industry-level, regulatory outcomes (see King et al., 2012 for an overview). In contrast, in this study we consider the interactive role of multiple stakeholders in standards adoption. In the case of green buildings, the adopters are building owners. The adoption pressures come from a variety of stakeholders including TSMOs, market intermediaries, and entrepreneurs. Further, our finding that economic incentive policies lose statistical significance in the presence of private actors (Table 2, Model 7) suggests that the role of private actors may be even greater than that of policy in promoting voluntary standards adoption. This study implies that future standards research should seriously incorporate the role of private actors.

This study provides several interesting insights into the effectiveness of these private actors. While the role of practitioners in encouraging adoption had been long understood, our findings expand understanding of how professionals from a variety of backgrounds can foster new markets (Scott, 2008). While traditional SMOs can carry with them the stigma of a logic that is incompatible with a marketâ&#x20AC;&#x2122;s prevailing belief system, TSMOs seek to hybridize community logic goals of societal benefit with market logics of economic viability. Contrary to our expectations based on the prior literature, TSMOs may be more aligned with, and effective under, a strong regional market logic than traditional SMOs. We also highlighted the unique role of market intermediaries. Because LEED APs lend the legitimacy of a variety of professions to the standard, our findings suggest a broader understanding of intermediaries outside of the focal sector (in our case green building) may lend legitimacy to new practices through their alignment. Our findings on entrepreneurial entrants bridge studies of voluntary standards and entrepreneurship by showing how adoption may be supported by private entrepreneurial actions. These entrepreneurs are different from institutional entrepreneurs

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(Battilana, Leca, & Boxenbaum, 2009; Pacheco, York, Dean, & Sarasvathy, 2010) and provide evidence of how the entry of new ventures facilitates standards adoption. This study is the first, to our knowledge, to show how entrepreneurial entrants can increase adoption of voluntary standards, suggesting a new path for future research.

The Filtering Impact of Regional Logics on Public and Private Efforts Our most important contribution in this paper is to illustrate how the effectiveness of public and private actors in influencing voluntary standard adoption is moderated by the underlying logics in the regions where adoption occurs. While scholars have suggested that logics â&#x20AC;&#x153;provide the framework for reasoning and justify why features are important and legitimateâ&#x20AC;? (Jones et al., 2012: 1524), this study finds that regional logics impart differing lenses on both public and private efforts to promote a nascent standard. By linking to the literature on regional logics (e.g. Lee & Lounsbury, 2015; Marquis & Battilana, 2009), our findings raise new questions for the examination of standards adoption.

Regional Logics as Policy Filters. For the broader literature on institutions and practice diffusion, our findings suggest that emergence may be best understood by not only examining endogenous technical advantages and isomorphism, but also the exogenous cultural context in which important audiences are embedded. Prior studies have shown the impact of public policy in promoting new, environmentally beneficial industries such as solar energy (Kapoor & Furr, 2015; Meek et al., 2010), wind energy (Sine et al., 2005; Sine & Lee, 2009), and even green building (Simcoe & Toffel, 2014; York & Lenox, 2014). However, these studies do not consider the filtering role of informal cultural forces such as regional logics. Even when policy and informal institutions are examined, they are considered as independent (Bansal, 2005).

Our study extends Lee and Lounsburyâ&#x20AC;&#x2122;s (2015) observations by showing how alignment between a market logic and incentive policies can drive acceptance of a new practice. Government incentives were more impactful under a market logic, but less effective in regions enmeshed in a community logic. In such regions, potential adopters are inclined to adopt environmental standards; government subsidies, while accepted, have little impact on

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adoption. These findings suggest that policy impacts on new practices and sectors should be considered within the context of the prevalent logics of the regions impacted.

Regional Logics as Private Actor Filters. The finding that TSMOs such as the USGBC also have a greater effect in the presence of a regional market logic was initially surprising to us. We believe that much of this effect is driven by the for-profit organizational membership of the USGBC. While the USGBC initiated with a more inclusive membership (in 2000, 12% of the membership was comprised of non-profits) it has evolved over time to more closely resemble a trade association in its membership, with less than 3% of the membership comprised of non-profit organizations by 2014. This finding, while counter to our hypothesis, provides support for our overarching theory that the perception of private actors, and the voluntary standards they advocate, may be moderated by regional logics. In this case, the USGBC has evolved away from a SMO-like identity as for-profit firms have dominated its membership. This finding suggests that beyond simply differentiating TSMOs from traditional SMOs, future studies should also consider the membership composition of such organizations.

Our findings on the increased efficacy of market intermediaries in regions with a strong market logic suggest that when intermediaries align with a new standard as an extension of, rather than a substitute for, their identity, they create greater acceptance amongst potential adopters. This is a critical consideration for the emergence of new voluntary standards seeking to address environmental issues, as markets are often skeptical of the economic viability of such efforts. Future research could also examine whether our finding that intermediaries and TSMOs are not more effective in the presence of a strong community logic holds across contexts. Studies suggest actors aligned with a community logic view the â&#x20AC;&#x153;professionalizationâ&#x20AC;? of addressing poverty through for-profit firms with great skepticism (Tracey, Phillips, & Jarvis, 2011), but these dynamics warrant further exploration.

Limitations. There are several limitations to this analysis. First, our study may extend only to practices embedded in institutional complexity. Yet, we do believe our theory would apply beyond environmentally relevant sectors, as complexity is a fact of life for contemporary

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organizations. For example, future studies could test the generalizability of our findings by examining how regional logics interact with policy changes to increase alternative health care practices, such as “natural” childbirth, or the legalization of medical marijuana.

Second, clearly co-evolutionary forces were at play in the emergence of LEED. Policy was likely influenced by the USGBC as well as regional APs at the MSA level. While we are confident that our use of numerous simultaneous equation modeling approaches, lagged dependent variables, and including measures of isomorphism has addressed this concern empirically, there is clearly opportunity to further develop understanding of these processes, perhaps through in-depth field work and process model development.

Third, one could argue that the marginal effects of both private actors and their interaction with policies were relatively small compared to more critical drivers such as isomorphism and environmental beliefs. We would agree; however, these effects were still important. For example, while the impact at the highest level of environmental entrepreneurship was 1.62 buildings under a strong regional community logic, based on the average adoption of LEED within an MSA (3.77), this represents a 42% increase. Further, the effect of such entrepreneurs becomes significant beyond 1.03 entrants in an MSA-year. These findings help illustrate that while the roles of private actors and the culture they are embedded within may be relatively small, they may still be a critical consideration for understanding the promotion of voluntary standards to address environmental problems.

Practical Implications: Regional Variation to Climate Change Solutions As discussed above, the conflict between market and community logics regarding both the causes of, and solutions to, climate change is well documented and solidly entrenched.

While the conflict is particularly acute in the United States, it has been noted on a global basis (Hoffman, 2015). As forecasts of climate scientists become more pessimistic, it is reasonable to ask what role actors beyond policy makers can play in finding solutions (Hiatt et al., 2015).

Hoffman argues that solutions to climate change: ...should be presented as an appeal to “ethical first principle,” in which proposals are placed in the context of our ideas and traditions by asking who we strive to be as a people and what kind of worlds we want to leave our children…To create such a vision, we must bridge the ideology of Left and Right. Solutions to climate

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change must fit the values of those who are more hierarchical and individualistic in their orientation (conservative) as well as those who are more egalitarian and communitarian (liberal) (2015 :64)

Our findings highlight the need for a greater understanding of regional cultural variation to foster such a vision. While an intuitive understanding might posit that â&#x20AC;&#x153;greenerâ&#x20AC;? regions would be more likely to adopt potential solutions to climate change, that policy is the essential key to encouraging such practices, and that a market logic is inherently oppositional to environmental standards. However, our study shows that regional adoption is driven by the complex interplay of policy, private action and culture. Our findings suggest that policies supporting voluntary standards should focus on aligning with market-based logics of economic advantage, particularly in more market-oriented regions. Also, the work of TSMOs and market intermediaries is more effective when a region is more highly attuned to a market logic. These findings point to the need for careful consideration of regional culture by both policy makers and activists seeking to create legitimacy for new voluntary standards.

We further suggest that private voluntary standards, and the sectors they initiate, offer one path towards such a vision, particularly when supported by for-profit entrepreneurial ventures. In the case of LEED, environmental entrepreneurs helped create new products and services to serve the nascent green building sector; these efforts increased adoption in regions embedded in either a market or community logic. We believe this is because there are at least two ways that such entrepreneurs may help find solutions to climate change. First, while large firms may find it difficult to take on the risky choice of supporting an unproven yet environmentally beneficial standard such as LEED, smaller firms may embrace the new technology, as they have little path dependency and no concern about cannibalization of existing profit streams. Second, by creating new ventures in which individuals who value economic goods can collaborate with individuals who value ecological goods, environmental entrepreneurs set the stage for new innovations and collaborative partnerships.

CONCLUSION The unique mechanisms explored in this study imply that supporting new ventures that create simultaneous economic and ecological benefits may be a compelling role for policy makers.

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Through doing so, policy could potentially escape the ideological quagmire that that has stymied progress in reducing carbon emissions. Future studies could examine this role of entrepreneurs in renewable energy, local and organic foods, and other environmentally beneficial and economically profitable sectors. While we have only scratched the surface of how public policy and private actors may leverage local culture in addressing critical environmental problems, our hope is that this study highlights the potential of this approach.

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TABLE 1 Descriptive Statistics and Correlation Matrix Mean S.D. VIF 1 2 Variables 1 LEED certified buildings 3.77 15.08 2.22 2 Population Density (in thousands) 0.27 0.31 1.95 0.462 3 GDP Per Capita (in millions) 0.04 0.01 1.35 0.261 0.333 4 MSA Size (logged) 0.48 0.24 1.44 0.255 -0.015 5 Party Legislative Control 1.83 0.73 1.11 -0.071 -0.056 6 Energy Cost 1.03 0.31 1.41 0.122 0.354 7 Water Usage (logged) 2.15 0.91 1.34 0.235 0.258 8 Environmental Activism (logged) -0.00 0.93 1.29 0.280 0.180 9 Pro-environmental Attitudes 3.82 3.30 1.49 0.139 0.298 10 Commercial Construction Area (logged) 5.10 2.23 1.18 0.194 0.100 11 Mimetic Isomorphism (cumulative prior adoption logged) 0.44 0.61 2.04 0.618 0.345 12 Economic Incentive Policies (logged) 0.02 0.10 1.52 0.452 0.421 13 TSMOs (per 100,000 people) 0.48 0.83 1.89 0.168 0.166 14 Market Intermediaries (per 100,000 people) 1.27 2.56 1.98 0.270 0.167 15 Environmental Entrepreneurs (logged) 0.04 0.12 1.42 0.388 0.423 16 Market Logic -0.00 1.00 1.65 -0.112 -0.258 17 Community Logic -0.00 1.00 1.61 -0.068 -0.040 Note: 5,110 observations. All |r|> 0.03 were significant at the 95% confidence level. 2 tailed t-tests.

3

4

5

6

7

8

9

10

11

12

0.116 -0.042 0.164 0.136 0.227 0.183 0.138 0.261 0.208 0.213 0.255 0.241 -0.153 0.256

-0.040 0.011 0.386 0.133 -0.046 0.127 0.265 0.202 0.073 0.105 0.233 0.125 -0.186

-0.235 -0.117 -0.066 -0.164 -0.060 -0.086 -0.070 -0.084 -0.075 -0.038 0.012 0.183

0.141 0.178 0.303 0.045 0.114 0.159 0.089 0.017 0.139 -0.155 -0.224

0.135 0.087 0.200 0.277 0.202 0.137 0.168 0.213 -0.100 -0.125

0.245 0.088 0.299 0.184 0.276 0.245 0.169 -0.186 0.163

0.068 0.156 0.164 0.216 0.210 0.145 -0.470 0.087

0.346 0.157 0.211 0.231 0.124 -0.064 -0.043

0.289 0.211 0.341 0.284 -0.139 -0.092

0.311 0.331 0.380 -0.133 -0.057

13

14

15

16

0.652 0.221 0.196 -0.183 -0.204 -0.093 0.080 0.103 -0.039 -0.353

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TABLE 2 Negative Binomial Models of Number of LEED Certified Buildings in an MSA-year Variables

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Population density

0.552*** (0.100)

0.539*** (0.100)

0.490*** (0.096)

0.520*** (0.092)

0.552*** (0.094)

0.492*** (0.096)

0.497*** (0.090)

0.530*** (0.082)

0.497*** (0.090)

0.499*** (0.089)

0.561*** (0.078)

0.569*** (0.079)

GDP per capita

8.782** (2.980)

9.332** (3.093)

9.142** (3.026)

8.308** (3.026)

5.372+ (3.144)

8.958** (3.084)

5.607+ (3.085)

5.997+ (3.217)

5.621+ (3.016)

5.625+ (3.064)

6.021+ (3.205)

5.899+ (3.187)

MSA Size

0.900*** (01 . 19 )

Party legislative control Democrat Controlled State Legislature

0.901*** (01 . 29 )

0.861*** 0 (1 . 28 )

0.944*** 0 (1 . 30)

0.946*** 0 (1 . 24 )

0.856*** 0 (1 . 26 )

0.923*** 0 (1 . 27 )

0.949*** 0 (1 . 26 )

0.911*** 0 (1 . 2 5)

0.921*** 0 (1 . 2 6)

0.969*** 0 (1 . 2 4)

0.967*** (01 . 2 7)

-0.085 (0.057)

-0.083 (0.056)

-0.084 (0.056)

-0.102* (0.052)

-0.103* (0.052)

-0.088 (0.057)

-0.113* (0.052)

-0.114* (0.050)

-0.105* (0.051)

-0.104* (0.051)

-0.113* (0.051)

-0.108* (0.049)

-0.027 (0.055)

-0.011 (0.055)

-0.011 (0.055)

-0.025 (0.052)

-0.023 (0.052)

-0.011 (0.056)

-0.029 (0.051)

-0.039 (0.050)

-0.033 (0.049)

-0.029 (0.049)

-0.030 (0.051)

-0.044 (0.049)

Energy cost

-0.059 (0.073)

-0.081 (0.076)

-0.079 (0.076)

-0.078 (0.075)

-0.032 (0.073)

-0.081 (0.076)

-0.043 (0.073)

-0.042 (0.071)

-0.037 (0.072)

-0.044 (0.072)

-0.036 (0.071)

-0.033 (0.070)

Water Usage

0.103** (0.037)

0.102** (0.037)

0.105** (0.037)

0.102** (0.036)

0.103** (0.036)

0.106** (0.037)

0.106** (0.036)

0.099** (0.036)

0.106** (0.036)

0.105** (0.036)

0.095** (0.035)

0.092* (0.036)

Enviromental Activism

0.030* (0.015)

0.034* (0.015)

0.031* (0.015)

0.002 (0.014)

0.016 (0.014)

0.032* (0.015)

-0.001 (0.014)

0.001 (0.014)

0.003 (0.014)

0.001 (0.014)

0.001 (0.015)

0.005 (0.014)

Pro-environmental Attitudes

0.017* (0.007)

0.014* (0.007)

0.014* (0.007)

0.012+ (0.007)

0.014+ (0.007)

0.014* (0.007)

0.012+ (0.007)

0.011+ (0.007)

0.013+ (0.007)

0.012+ (0.007)

0.011 (0.007)

0.011+ (0.007)

Commercial construction area

0.128** (0.042)

0.129** (0.042)

0.128** (0.043)

0.127** (0.042)

0.125** (0.041)

0.127** (0.042)

0.123** (0.041)

0.121** (0.041)

0.122** (0.041)

0.122** (0.041)

0.121** (0.041)

0.118** (0.040)

Mimetic Isomorphism (cumulative prior adoption) 1.640*** (0.060)

1.633*** (0.061)

1.630*** (0.061)

1.569*** (0.060)

1.518*** (0.060)

1.621*** (0.061)

1.505*** (0.059)

1.491*** (0.060)

1.502*** (0.060)

1.495*** (0.059)

1.485*** (0.060)

1.480*** (0.061)

Market Logic

-0.038 (0.027)

-0.035 (0.027)

-0.051+ (0.026)

-0.043 (0.026)

-0.041 (0.027)

-0.051* (0.026)

-0.066* (0.027)

-0.086** (0.030)

-0.079** (0.030)

-0.065* (0.028)

-0.092** (0.031)

Community Logic

-0.024 (0.028)

-0.019 (0.028)

-0.033 (0.027)

-0.045 (0.028)

-0.024 (0.028)

-0.043 (0.027)

-0.051+ (0.029)

-0.037 (0.033)

-0.039 (0.033)

-0.065* (0.029)

-0.050 (0.034)

0.048 (0.094)

0.401** (0.135)

0.072 (0.092)

0.064 (0.096)

0.110 (0.091)

0.282* (0.125)

0.114*** (0.026)

0.112*** (0.026)

0.135*** (0.027)

0.105*** (0.026)

0.110*** (0.026)

0.125*** (0.029)

0.043*** (0.011)

0.043*** (0.011)

0.044*** (0.010)

0.053*** (0.010)

0.041*** (0.011)

0.044*** (0.010)

0.174+ (0.097)

0.183+ (0.100)

0.173+ (0.097)

0.170+ (0.098)

0.416*** (0.125)

0.366** (0.119)

Republican Controlled State Legislature

Economic Incentive Policies

0.255* (0.105)

TSMOs

0.180*** (0.026)

Market Intermediaries

0.061*** (0.010)

Enviromental Entrepreneurs

0.277** (0.105)

Economic Incentive Policies * Market Logic

0.413*** (0.121)

0.242* (0.121)

Economic Incentive Policies * Community Logic

0.222 (0.167)

0.103 (0.154)

TSMOs * Market Logic

0.055** (0.019)

0.038 (0.026)

TSMOs * Community Logic

-0.009 (0.025)

-0.024 (0.032)

Market Intermediaries * Market Logic

0.012* (0.005)

0.001 (0.008)

Market Intermediaries * Community Logic

-0.003 (0.008)

-0.003 (0.010)

Environmental Entrepreneurs * Market Logic

0.318** (0.120)

0.191+ (0.108)

Environmental Entrepreneurs * Community Logic

0.469*** (0.142)

0.483*** (0.135)

Constant

-6.756*** -6.743*** -6.705*** -6.704*** -6.650*** -6.710*** -6.623*** -6.633*** -2.460*** -2.451*** -2.475*** -2.435*** (0.752) (0.751) (0.748) (0.751) (0.751) (0.749) (0.747) (0.746) (0.210) (0.210) (0.211) (0.212)

Year dummies Observations (MSA-Year) MSAs Ď&#x2021;2

Yes 5110 341 9046.947

2

Yes 5110 341 9063.313

Yes 5110 341 9409.305

Yes 5110 341 10028.949

Yes 5110 341 9094.896

Yes 5110 341 9027.430

Yes 5110 341 9878.145

Yes 5110 341 9759.101

Yes 5110 341 9849.648

Yes 5110 341 10081.269

Yes 5110 341 9416.707

Yes 5110 341 9351.429

McFadden's Pseudo R 0.351 0.351 0.352 0.356 0.356 0.352 0.358 0.359 0.359 0.358 0.359 0.360 Log-likelihood -5962.684 -5960.925 -5957.865 -5920.968 -5915.843 -5957.176 -5901.036 -5894.454 -5895.038 -5896.980 -5891.468 -5883.144 Standard errors in parentheses (+p<0.10, *p<0.05, **p<0.01, ***p<0.001). 2 tailed t-tests.

Academy of Management Journal

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

FIGURE 1 Impact of Economic Incentive Policies on LEED Certification at Strong and Weak Logic Levels

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Academy of Management Journal

FIGURE 2 Impact of TSMOs on LEED Certification at Strong and Weak Logic levels

Academy of Management Journal

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

FIGURE 3 Impact of Market Intermediaries on LEED Certification at Strong and Weak Logic Levels

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Academy of Management Journal

FIGURE 4 Impact of Environmental Entrepreneurs on LEED certification at Strong and Weak Logic Levels

Academy of Management Journal

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TABLE 3 Tests for Endogeneity (Treatment Effects Model, Control Functions, and Dynamic Panel Estimates)

Variables

Treatment Effects for Policies (1) (2)

Control Function Approach for Policies and Private Actors (3)

(4)

(5)

LEED certified buildings (lagged DV)

(6)

Dynamic Panel Arellano-Bond System GMM with lagged dependent variable (7) (8) (9)

0.945*** 0.946*** 0.945*** 0.916*** (0.032) (0.037) (0.040) (0.040)

Population Density

11.742*** -0.112 (2.506) (0.152)

1.343*** (0.187)

0.474+ (0.272)

-0.196 (0.196)

1.003 (1.443)

5.436*** 4.453** (1.489) (1.502)

6.225*** (1.723)

GDP Per Capita

8.364 (34.298)

8.432 (5.446)

-174.868*** 3.737 (49.852) (2.577)

4.178+ (2.442)

42.651+ (22.942)

13.718 (36.994)

46.501 (31.764)

39.400 (37.340)

MSA Size

4.642*** (1.101)

0.557** (0.201)

2.477*** (0.425)

0.969*** 0.397** (0.205) (0.143)

-1.867 (1.526)

-3.633 (2.521)

-3.842 (2.490)

-3.723 (2.714)

0.421 (0.517)

-0.106*** -0.661*** (0.030) (0.188)

-0.153+ (0.081)

-0.095 (0.068)

0.547* (0.276)

-0.069 (0.241)

0.091 (0.245)

0.308 (0.317)

-0.789+ (0.412)

-0.005 (0.049)

0.252* (0.108)

-0.051* (0.025)

-0.004 (0.040)

-0.032 (0.203)

0.109 (0.183)

-0.077 (0.207)

-0.163 (0.206)

Energy Cost

-0.966 (1.005)

-0.075 (0.128)

2.134*** (0.621)

-0.103 (0.094)

-0.067 (0.065)

-0.602 (0.590)

-1.142* (0.529)

-1.077* (0.544)

-0.872 (0.672)

Water Usage

-0.719+ (0.386)

0.125* (0.053)

0.035 (0.028)

0.130* (0.063)

0.117*** 0.001 (0.028) (0.121)

-0.109 (0.121)

-0.118 (0.133)

-0.248+ (0.139)

Environmental Activism

-0.475 (0.322)

0.005 (0.024)

-1.423*** (0.399)

-0.146* (0.060)

0.010* (0.004)

-0.263 (0.345)

-0.517+ (0.306)

-0.777** -0.522 (0.286) (0.353)

Pro-environmental Attitudes

-0.169* (0.076)

0.022** (0.007)

-0.079** (0.025)

0.006 (0.011)

0.013* (0.006)

-0.120+ (0.069)

-0.133+ (0.069)

-0.134* (0.064)

-0.180** (0.066)

Commerical Construction Area

0.004 (0.072)

0.121*** 0.072 (0.031) (0.065)

0.124*** 0.130*** 0.041+ (0.015) (0.036) (0.023)

0.019 (0.027)

-0.003 (0.030)

0.006 (0.031)

Cumulative Prior Leed Adoption

16.060*** 1.312*** -9.771** (1.884) (0.087) (3.064)

1.199*** 1.314*** 1.343* (0.154) (0.057) (0.574)

1.701* (0.676)

2.386*** 2.634*** (0.661) (0.728)

Market Logic

0.557* (0.265)

-0.021 (0.028)

-0.265*** (0.078)

-0.071*** -0.065* (0.017) (0.029)

0.176 (0.229)

0.171 (0.299)

0.091 (0.284)

0.284 (0.294)

Community Logic

-0.166 (0.202)

0.006 (0.043)

-1.038*** (0.255)

-0.082 (0.052)

-0.015 (0.256)

0.230 (0.277)

0.099 (0.282)

0.546+ (0.309)

Economic Incentive Policy Treatment(0/1)

6.378*** (1.549)

Party legislative control Democrat Controlled State Legislature

Republican Controlled State Legislature

Economic Incentive Policies

6.261*** (1.398)

Control function 1st stage residuals for Economic Incentive Policies

-6.082*** (1.479)

-0.012 (0.041)

23.473*** (5.948)

TSMOs

5.908*** (1.603)

Control function 1st stage residuals for TSMOs

-5.847*** (1.607)

0.488*** (0.113)

Market Intermediaries

1.115** (0.389)

Control function 1st stage residuals for Market Intermediaries

-0.952* (0.387)

0.982** (0.307)

Environmental Entrepreneurs

5.637*** (1.006)

Control function 1st stage residuals for Environmental Entrepreneurs

-5.509*** (0.980)

Constant

-2.635+ (1.451)

-6.430*** -2.891 (0.837) (6.890)

-6.569 (7.470)

-6.411*** (0.401)

Year dummies Observations (MSA-Year) MSAs McFadden's Pseudo R2

Yes 5110 341

Yes 5110 341

Yes 5110 341

Yes 5110 341

Yes 5110 341

0.35 0.36 Ď&#x2021;2 382.446 769.588 735.336 AR(1) AR(2) Instruments Hansen's J Note: Standard errors in parentheses (+p<0.10, *p<0.05, **p<0.01, ***p<0.001). 2 tailed t-tests.

5.048* (2.333)

-2.019 (1.369) Yes 4769 341

Yes 4769 341

Yes 4769 341

Yes 4769 341

0.36

0.36

-

-

-

-

716.534 -

775.322 -

7221.501 -5.672*** 1.120 134.000 102.965

7044.732 -5.318*** 1.266 134.000 101.298

5880.219 -5.374*** 1.108 134.000 99.831

4828.814 -5.259*** 1.311 134.000 106.170

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Academy of Management Journal

Jeffrey G. York (jeffrey.york@colorado.edu) is an associate professor of strategy and entrepreneurship and the Shane Faculty Scholar at the Leeds School of Business, the University of Colorado Boulder. He received his Ph.D. from the Darden School of Business at the University of Virginia. His research focuses on environmental entrepreneurship as the creation of simultaneous economic and ecological benefit through new ventures and the evolution of environmentally beneficial sectors.

Siddharth Vedula (svedula@babson.edu) is an Assistant Professor in the Entrepreneurship Division at Babson College, where he teaches the foundational course on new venture creation.

Sid holds a Ph.D. in Management and Entrepreneurship from the University of Colorado at Boulder, a Masters of Engineering from McGill University, and a Bachelors Degree in Physiology from the University of Toronto. His research focuses on how communities and regional institutions impact the behaviors and strategic decisions of entrepreneurs.

Michael J. Lenox (lenoxm@darden.virginia.edu) is the Tayloe Murphy Professor of Business at the University of Virginia’s Darden School of Business where he teaches the core MBA strategy course. He also serves as the school’s Senior Associate Dean and Chief Strategy Office. He received his Ph.D. in Technology Management and Policy from the Massachusetts Institute of Technology and the degrees of Bachelor and Master of Science in Systems Engineering from the University of Virginia. His research explores the business strategy and public policy drivers of the direction of innovative activity; his recent work examines strategies and non-traditional public policies that have the potential to drive “green” innovation and entrepreneurship.