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CLIMATE CHANGE, RESOURCE DEPENDENCE AND ENVIRONMENTAL PERFORMANCE: A LONGITUDINAL STUDY OF THE U.S. SKI RESORT INDUSTRY Pete Tashman Doctoral Candidate The George Washington University School of Business Department of Strategic Management and Public Policy Funger Hall 615, 2201 G Street, NW Washington, DC 20052 Phone: (202) 207-8571; Fax: (202) 994-8113

ABSTRACT

Research on corporate climate change adaptation has succeeded in classifying adaptation types,

identifying organizational characteristic that motivate adaptations, and describing processes of

organizational learning that underpin them. This empirical study seeks to improve our

understanding of the outcomes of climate change adaptation by examining relationships between

the corporate climate change vulnerability and environmental performance. In doing so, it

develops a logic of natural resource dependence, which recognizes that a firm’s vulnerability to

climate change and its propensity to adapt can be a function of the organization’s resource

dependence on its biophysical environment. Since climate change can disrupt the provisioning of

critical ecosystem services by the natural environment to the firm, adaptation is sometimes

required to manage the uncertainty created by the phenomenon. Using longitudinal data from 76

firms in the U.S. Ski Resort Industry from 2001 to 2009 (n=612), I find that vulnerability is

negatively related with environmental protection in firms’ biophysical environments, but

positively related to environmental protection of natural resources exchanged or embedded in

firms’ socioeconomic environments.

Keywords: climate change adaptation, climate change vulnerability, environmental

performance, resource dependence theory

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INTRODUCTION

Research on corporate climate change adaptations seeks to understand how firms respond

to the geophysical effects of climate change and the corporate vulnerability it creates (Hoffmann,

Sprengel, Ziegler, Kolb & Abegg, 2009). Early works have explored the determinants1, types2

and processes that underpin climate change adaptations3. To date, however, they have told us

little about the economic, environmental and social outcomes of climate-adaptation strategies.

Environmental impacts should merit particular attention, since climate change affects prospects

for sustainable development globally (Smit & Pilifosova, 2001). Specifically, it can contribute to

the global depletion of natural capital4 and ecosystem services5 (Vorosmarty, Green, Salisbury,

& Lammers, 2000), which puts added pressure on ecological systems, and the human systems

dependent upon them (IPCC, 2001; Prugh, Costanza, Cumberland, Daly, Goodland & Norgaard,

1999). Businesses that depend substantially on ecosystem services are particularly vulnerable to

climate change. If the phenomenon threatens access to these critical resources, the firm may alter

its consumption patterns of them. The result could improve prospects for corporate sustainability

or lead to greater environmental harm. The goal of this study is therefore to address the

following research questions: is there a relationship between corporate climate change

adaptations and environmental performance? If so, how are they related?

The conceptual framework guiding this study predicts that climate change can induce

adaptations that both positively and negatively affect environmental performance. More

specifically, it posits that it is possible that climate change adaptations can create negative

1 See for example Fankhauser, Smith and Tol (1999), Scott, McBoyle and Mills (2003), Smit et al. (2000). 2 See for example Scott and McBoyle (2007), Hertin, Berkhout, Gann and Barlow (2003) and Smit and Skinner (2002). 3 See Berkhout, Hertin and Gann (2006) and Hoffman et al. (2009) 4 Natural capital has been defined as stocks of natural assets, natural processes that link them, and the structural or network form in which they are embedded that keep them in a balanced system (Wackernagel and Rees, 1997). 5 Ecosystem services has been defined as the unique benefits provided to society from natural capital, such as air, air purification, water, water purification, soil formation, favorable climates, consumption of renewable resource, tourism, and a general feeling of appreciation for nature and the life it contains (Costanza, et al., 1997).

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impacts on firms’ biophysical environments, but have benevolent environmental effects in their

socioeconomic environments. The logic of resource dependence (Pfeffer & Salancik, 1978)

supports this assessment. Climate change adaptation can help a firm manage the uncertainty

associated with accessing critical ecosystem services by altering its use of its biophysical

environment in harmful ways. On the other hand, if the firm creates negative externalities in the

course of its adaptations, it might face problems maintaining its environmental legitimacy

(Bansal & Clelland, 2004). To protect its legitimacy in light of its declining environmental

protection of its biophysical environment, it could enact reactive environmental strategies that

improve its management of natural resources that are exchanged in its socioeconomic

environment. This can positively affect legitimacy by signaling to stakeholders that the firm is

committed to trying to protect the natural environment in other ways (Kotchen, 2009).

Climate change creates uncertainty for a firm associated with these types of resource

dependence when they are vulnerable to the phenomenon. Climate change vulnerability is a

function of climate-change exposure and sensitivity. Exposure refers to the geo-climatic

variability in the firm’s salient biophysical environment (Smit, Burton, Klein & Wandel, 2000;

Smit & Skinner, 2002). Sensitivity refers to the degree to which a firm’s business model can be

undermined by climate change (Hoffmann et al., 2009). Both conditions are necessary to induce

vulnerable, since climate change has to be actually present in the form of exposure to create

effects, and the firm needs to be sensitive to the phenomenon if effects are to happen.

The present study aims to make three contributions to the management discipline. First, it

gives attention to the unstudied relationship between geophysical expressions of climate change

and corporate environmental performance. Second, it examines the impacts of climate change on

multiple dimensions of environmental performance. Existing research on corporate

environmental performance has typically only considered one dimension of the construct

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(Rivera, De Leon & Koerber, 2006), which can lead to incomplete views of how firms really

manage the environment. For example, firms that perform well in some areas may be

“greenwashing” poor performance in other areas, rather than actually being environmentally

proactive (Lyon & Maxwell, 2008); this behavior can only be evaluated if the researcher knows

something about how well firms manage the environment more broadly. Lastly, it theorizes some

unique aspects of corporate resource dependence upon the natural environment. A central

premise of resource dependence theory is that corporate adaptations to resource dependence are a

function of the distribution of socially constructed power in a firm’s salient interorganizational

network (Cascario & Piskorski, 2005; Pfeffer & Salancik, 1978). Resource dependence on

ecosystem services is, however, a function of power that is both naturally and socially

constructed. When facing power involving events like climate change that are spatially and

temporally removed from the firm’s activities, the firm may have no option to prevent them from

happening (Pogutz & Winn, 2009).Conversely, the firm has a great deal of discretion if it

chooses to alter its use of its biophysical environment to help it address uncertainty created by

events it is powerless to change, because it typically has direct control of the resources embedded

in it. Thus, power associated with natural resource dependence tends to be distinct and unilateral,

rather than countervailing and a function of organizational interdependence.

The rest of the manuscript is organized as follows: the next section review the relevant

existing literature on corporate climate change adaptation. Next, it describes resource

dependence theory and some of the unique aspects of direct resource dependence on the natural

environment. Then, theory and hypotheses are presented. This is followed by a description of

methods and the presentation of results. Finally, the manuscript concludes with a discussion of

the implications, limitations and future research directions that could arise from the study.

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BACKGROUND

Climate change is at the top of the global-policy issue agenda, which is not surprising

given its potential to radically alter the terrestrial, hydrological, and, by definition, climatic

systems that support life (Intergovernmental Panel on Climate Change (IPCC), 2007), and there

is now scientific consensus that greenhouse gas emissions are a significant causal factor.

However, the destructive effects of climate change on our ecological, economic and social

systems are still nascent; as a result, most market activities and policy initiatives have focused on

mitigation efforts6 (Pinske & Kolk, 2009). Still, climate change adaptation7 is becoming more

urgent (IPCC, 2001; 2007) as we learn about melting glaciers and icecaps, flooding, rising ocean

levels, drought, declining winter snowpacks, changing soil compositions, and extreme weather.

The recent flooding in Pakistan, which has displaced millions of people and has been linked to

climate change by the United Nations, the IPCC and the World Meteorological Organization

(Gronewald, 2010), reflects the impacts that climate change can have on social systems broadly.

Businesses are certainly not immune (Hoffmann et al., 2009). Firms reliant on renewable

natural resources are particularly vulnerable (IPCC, 2001) because their business models depend

on ecological systems that climate change can undermine. Winter tourism is threatened by

changes in temperature and precipitation type and intensity (Scott, McBoyle & Mills, 2003);

agriculture is experiencing changing soil compositions and water availability (Schlenker,

Haneman and Fischer, 2005); commercial fishing face changing ocean temperatures that displace

fisheries (Lash & Wellington, 2007), and forestry’s commercial timber is vulnerable to various

spread of bark beetles, which are thriving because of warmer winters (Spittlehouse & Stewart,

6 Climate change mitigation refers to actions that are aimed at reducing greenhouse gas emissions into the atmosphere 7 The IPCC Third Assessment Report (2001) defines climate change adaptation as “…the adjustment in ecological, social, or economic systems in response to actual or expected climatic stimuli and their effects or impacts. This term refers to changes in processes, practices, or structures to moderate or offset potential damages or to take advantage of opportunities associated with changes in climate.

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2003). Even extractive industries in the arctic region are at risk as transportation routes using ice

roads are melting8 (Hoffman, 2006). In other industries, extreme weather events associated with

climate change threaten physical assets (Adger, 1999). For example, oil platforms in the Gulf of

Mexico are vulnerable to more frequent and more intense of hurricanes. Finally, firms in all

industries have indirect vulnerability to climate change as a result of their social and economic

interdependencies with climate-affected organizations. The insurance industry’s indirect

vulnerability is evidenced by the nearly $83 billion in claims in 2005 for the damages wrought

by extreme weather, such as Hurricane Katrina and the Indian Ocean Tsunami (Hoffman, 2006).

The interdependence between human, economic, political, and social systems on local and global

scales means that climate change effects can reverberate to all corners (IPCC, 2001; Smit &

Pilifosova, 2001). Thus, climate change adaptations have importance for many disciplines in the

natural and social sciences, including management (Hoffmann et al., 2009).

Currently, research has focused on descriptions and types of adaptations, why they

happen, and how they happen. Berkhout et al. (2006) identified several strategies that firms can

deploy, including risk assessment, risk spreading through insurance or strategic alliances, and

resource reallocation to reduce climate change exposure and vulnerability. The last category

includes increasing capacity to protect vulnerable resources (Hertin, Berkhout, Gann & Barlow,

2003) and diversifying revenue streams away from vulnerable businesses (Scott & McBoyle,

2007). Building on Adger, Arnell & Tomkin’s (2005) discussion of adaptation of social systems,

Hoffman et al. (2009) argue that the scope of adaptation is also an important variable, as firms

can deploy one or many adaptation strategies simultaneously and at different levels of intensity.

Some adaptations seek to buffer the firm from climate risk, while others seek to deliberately

8 While extractive industries are by definition dependent upon non-renewable natural resource, firms in this industry operating in arctic regions do depend upon ice, a renewable natural resource, for logistical access (Hoffman, 2006).

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transform the firm. The Hoffman team also found evidence that awareness of climate effects and

adaptation capacity correlate with protection of vulnerable resources and diversification into

less-exposed revenue streams. In addition, they found that vulnerability to climate change was

associated with measures to externalize climate risk.

With regard to the determinants of adaptations, Fankhauser at al. (1999) argued that

adaptation is prompted by three conditions: awareness of climate change, vulnerability to the

phenomenon, and the adaptation capacity. Hoffman et al. (1999) added uncertainty to this list,

arguing that a firm unsure about the likelihood of future climate change effects might choose to

“wait and see” (Berhout et al., 2006). Finally, with respect to organizational processes

facilitating adaptations, Berkhout et al. (2006) also studied the processes through which

adaptations occur, through the lens of evolutionary economics (Nelson & Winter, 1982) and the

dynamic capabilities view (Eisenhardt & Martin, 2000, Teece, et al., 1997). They suggest that

adaptations rely on the development of organizational learning capabilities, which modify

organizational routines as needed to respond to climate change stimuli. Specifically, adaptations

require initiating initiate “learning cycles” (Berhout et al, p. 138) that receive and interpret

climate signals, then search for, identify, codify and refine promising new approaches.

The extant literature does contain specific gaps relevant to the current study. First, we

know that firms tend to adapt when they are vulnerable to climate change, but we have not

framed the problem in within an organizational theory that accounts for the climate change’s

external linkages to vulnerability. Empirically, as mentioned above, there is some anecdotal

evidence that climate change vulnerability is associated with the phenomenon’s capacity to

undermine a firm’s relationship with its biophysical environment. It follows that adaptations to

address vulnerability somehow restore this relationship or reduce resource dependence on

resources that it provides. Both of these cases could involve changing consumption patterns of

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these resources, which can have implications for environmental performance. Since climate

change vulnerability appears to be a function of a firm’s resource dependence on its biophysical

environment, and since adaptation measures might have effects on the environmental

performance, it is necessary to frame the relationship through an organizational theory that

accounts for resource dependence and the firm-natural environment relationship. I argue below

that resource dependence theory (Pfeffer & Salancik, 1978) can satisfy both conditions.

THEORY AND HYPOTHESES

Resource Dependence and the Natural Environment

The central premise of resource dependence theory is that firm performance and survival

depend in part on its ability to access critical resources from its business environment, which

implies dependence upon other organizations which control these resources (Pfeffer & Salancik,

1978). The degree of resource dependence is a function of how critical the resource is for the day

to day functioning of the firm and the proportion of firm outputs that rely on it. Firms, however,

also require access to natural capital and ecosystem services that are directly provisioned by the

natural environment (Pogutz & Winn, 2009; Starik & Rand, 1995). This means that firms are not

only embedded in market and institutional systems, but also in ecological ones (Pogutz & Winn,

2009). Indeed, while most of the Earth’s natural resources are under some form of

socioeconomic control, many industries have direct relationships with the natural environment,

and this connection can provide leverage against institutional control. In natural resource

industries in particular, once a firm gains regulatory and social approval for its activities, it often

has direct control over its biophysical environment and the ecosystems that comprise it (Pugh et

al., 1999). Forestry firms have direct access to stocks of timber within their licensed area,

fisheries to local fish stocks, and hydroelectric facilities to water volume, to cite a few examples.

In addition, natural resource dependence is ultimately the root of all socioeconomic resource

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dependence involving physical capital. The beginning of every value-added chain for the

production of physical capital begins with raw materials that are natural resources (Costanza &

Daly, 1992). Thus, natural resource dependence also indirectly affects patterns of

interdependence and power in interorganizational fields (Pogutz & Winn, 2009).

When firms address the uncertainty associated with resource dependence, they can either

mitigate their resource dependence or adapt to their external environments, or use influence

strategies to induce other organizations to bend to their demands. According to Pfeffer and

Salancik (1978), the route of adaptation depends upon the distribution of power among

interdependent organizations. If a firm has power over other organizations derived from its

control of resources that are critical to them, its own uncertainty will induce it use its power to

secure access to its own critical resources. Conversely, if the balance of power resides with the

external organization, the focal firm will more likely be the one to acquiesce to external

influences, or restructure its internal demand for the resources in question.

Natural Versus Social Constructed Power

More powerful organizations are those that tend to have more control over critical

resources and/or less dependence upon resources controlled by other organizations (Pfeffer &

Salancik, 1978). Thus, power exists on a continuum, with organizations having more or less of it,

depending on the distribution of interdependencies among organizations in a field. Note that this

form of power is socially constructed through the economic and social interactions among

organizations within the field. In natural resource industries, power can be both naturally and

socially constructed. Firms can exercise control over the provision of ecosystem services when

the uncertainty surrounding their access is highly localized. Some do so through practices which

promote ecosystem health and resilience (Pogutz & Winn, 2009). But ecological processes, such

as climate change, involve natural power that is temporally or spatially removed from the firm’s

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local biophysical environment, which can still undermine the health and functioning of

ecosystems that comprise it (Pugh et al., 1999) and thus inhibit the firm’s ability to manage its

local natural resource dependence. For example, beyond collective action to reduce greenhouse

gas emissions, forestry firms or ski resorts can do nothing to reverse the climate change that is

resulting in the spread of bark beetles or reduction of winter snowpacks, respectively. This form

of natural power is therefore nearly absolute and beyond the scope of a firm’s socially

constructed power; a firm facing loss of natural resources due to global ecological processes like

climate change can only adapt to its resource dependence, rather use power and influence to

induce adaptations from its external environment.

At the same time, natural power occurring in global ecological events does not preclude

corporate adaptations to the firm’s biophysical environment (Wackernagel & Rees, 1997). If

firms’ access to critical sources of natural capital and ecosystem services is threatened by

globally dispersed ecological events like climate change, it can still alter its use of its biophysical

environment when it has direct control over it. This occurs when the ecosystems that comprise it

are not monetized or governed in a way that reflects their true value to society because they are

considered by policy regimes as freely available public goods (Costanza et al., 1997). Lacking

social governance institutions, firms may have extraordinary control over some ecosystems in

their biophysical environments (Pogutz & Winn, 2009; Wackernagel & Rees, 1997)

Climate Change Adaptations and Biophysical Environmental Performance

As mentioned earlier, there is some evidence that vulnerability is associated with the

firm’s dependence on locally embedded ecosystem services as key components of its business

model (Pogutz & Winn, 2009). Because firms that are threatened by climate change tend to

depend significantly on their biophysical environments for key resources, they have economic

incentives to deploy adaptations that are located there, since doing so leverages a valuable

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resource (its biophysical environment). If such a firm adapts to climate change in manner that

does not involve its biophysical environment, the adaptation may be based on resource of lesser

value, which is a more difficult means of remaining competitive (Prahalad & Hamel, 1990). For

example, forestry firms often adapt to climate-induced changes in soil compositions and the

spread of bark beetles by altering their forestry practices and harvesting patterns (Spittlehouse &

Stewart, 2003).9 Similarly, many ski resorts adapt to climate change by modifying their use of

the mountain environment (Scott & McBoyle, 2007). This is likely the case because the forest

and the mountain environment are the best resources that firms in these respective industries

have. In addition, natural resource dependence might limit the adaptation strategies available to

the firm to those that buffer the firm from its vulnerability or diversify its revenue streams away

from those that are dependent on vulnerable resources. Wait and see strategies apply when there

is uncertainty about whether climate effects are occurring, and strategies to share risk require the

cooperation of other organizations in an arena where insurance may be too expensive or mutually

beneficial alliances may be difficult to arrange. Buffering strategies, however, could help the

firm accumulate threatened ecosystem services that are substitutes for threatened ones, while

diversifying revenue streams could involve deploy new business activities into the firm’s

biophysical environment that are not vulnerable to climate change (Scott & McBoyle, 2007).

Unfortunately, buffering ecosystem services involves consuming them , and therefore can

lead to a loss of natural capital elsewhere in the biophysical environment, which can put pressure

on the continued function of the ecosystem in the aggregate (Marshall & Toffel, 2005). In

addition, diversifying business activities within a local ecosystem can disrupt ecosystem

functioning by perturbing that ecosystem (Costanza & Daly, 1992; Marshall & Toffel, 2005). As

9 There have been many attempts to mitigate the spread of bark beetle directly, through the application of cutting forest lines swaths to create a beetle diffusion barriers, and the use of beetle behavior modifying hormones, called tree-baiting; to date, these efforts have yielded little progress.

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an example, climate change adaptations in the ski resort industry include increasing use of

snowmaking, which consumes more water, expanding ski lifts access to areas with higher

elevation and/or more northerly facing areas, which can perturb those areas, and diversifying

business activities into real estate development and summer mountain recreation tourism, which

also can perturb those areas and increase demand for water use (Scott & McBoyle, 2007).

Adaptations to global ecological forces such as climate change therefore can affect

environmental performance, because they can involve altering consumption patterns of

ecosystem services that are embedded in the firm’s biophysical environment. Biophysical

environmental performance, which I define as the degree to which a firm protects or conserves

natural capital embedded in its biophysical environment, reflects environmental impacts in this

domain. In light of these considerations, I predict:

Hypothesis 1. Corporate climate change vulnerability is negatively associated with the

corporate biophysical environmental performance.

Climate Change Adaptations and Socioeconomic Environmental Performance

Pfeffer and Salancik (1978) describe how strategies designed to manage one source of

resource dependence can create new sources of them as an unintended consequence. For

example, diversification strategies reduce the resource dependence associated with the firm’s

original portfolio of businesses, but subject the corporate entity to industry dynamics in new

markets and can overextend the corporate office’s reach (Ramanujam & Varadarajan, 1989). One

possible unintended consequence of attempts to reduce resource dependence is the loss of

legitimacy (Oliver, 1991; Pfeffer & Salancik, 1978; Suchman, 1995). Suchman defines

legitimacy as “…a generalized perception or assumption that the actions of an entity are

desirable, proper, or appropriate within some socially constructed system of norms, values,

beliefs, and definitions” (Suchman,1995: 574). Legitimacy is the degree to which societal actors

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within an interorganizational field treat a firm’s actions as socially acceptable (Scott, 2008). As

such, legitimacy can be seen as a tacit resource that is conferred by societal actors and is

therefore externally controlled10 (Pfeffer & Salancik, 1978). Illegitimate corporate activity risks

alienating stakeholders who are critical to firm performance and survival (Clarkson, 1995).

Unhappy investors can divest, banks can withdraw credit, employees can quit, customers can

choose products and services from other businesses, and communities can withhold business

licenses, even if the firm’s market strategy is economically sound. Thus, legitimacy is essential

to the long-term survival of business organizations (Pfeffer & Salancik, 1978; Scott, 2008),

implying that firms need to manage the uncertainty associated with maintaining it.

As a firm’s biophysical environmental performance declines, external stakeholders that

are concerned about its corporate environmental performance are more likely to question its

legitimacy (Bansal, 2005; Bansal & Clelland, 2004; King & Berchicci, 2007), even if the decline

occurs in the context of climate change adaptations. Fearing this, a firm may decide to attempt

mitigate its environmental harm, since doing so can signal to legitimacy-conferring stakeholders

that it does care about the environment (Bansal & Clelland, 2004; Tashman & Rivera, 2010). In

some cases, firms can mitigate negative environmental externalities with offsetting practices,

such as purchasing carbon offsets in response to creating carbon emissions (Kotchen, 2009).

Such strategies would represent a form of acquiescence to institutional logics that define

legitimate behaviors, by complying with rules or following norms that are considered legitimate

business behavior by powerful stakeholders (Oliver, 1991; Bansall & Clelland, 2004).

In the case of climate change adaptations, the firm may be more likely to adopt a strategic

response to any legitimacy challenges that arise from practices that cause negative biophysical

10 Many scholars have described organizational legitimacy as a social constructed phenomenon that firm’s can play an active role in shaping (Scott, 2008), meaning that externally conferred legitimacy can be endogenous to firm-level influence.

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environmental impacts, because it is these practices that facilitate climate change adaptation.

Acquiescing to legitimacy demands in the manner described above could preclude the firm’s

ability to adapt to climate change. Oliver (1991) argues that firms facing institutional pressures

that are incongruent with their organizational goals are more likely to resists institutional

pressures with strategic responses. One such response is “avoidance” (Oliver, 1991: 10), where

the focal firm attempts to preclude the necessity for conformity to institutional pressures. One

method of avoidance is “concealment”, where the firm attempts to “disguise nonconformity

behind a façade of acquiescence” (Oliver, 1991: 10). In the case, a firm can conceal its declining

biophysical environmental performance by improving itself in other dimensions that are not

associated with adapting to climate change vulnerability. This includes developing or improving

practices associated with environmental performance in its socioeconomic environment.

Socioeconomic environmental performance involves the protection or conservation natural

resources that are exchanged in its socioeconomic system, rather than those that are embedded in

the biophysical environment. It is reflected in business practices that conserve energy and

reduce carbon emissions, involve green purchasing and sourcing, use better solid waste

management and recycling, and/or sponsors community sustainability initiatives, as examples.

Since these practices do not involve managing local ecosystems and ecosystem services,

implementing them does not interfere with climate change adaptations or require the firm to

change its use of its biophysical environment. Since climate change adaptations can lead to

negative impacts on the firm’s biophysical environment, which in turn can create legitimacy

problems for the firm, the firm is more likely to develop and implement a strategic response to its

legitimacy problems that allow it to continue to adapt to climate change. This includes strategies

that improve socioeconomic environmental performance. Therefore, I more formally predict:

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Hypothesis 2a: Corporate climate change vulnerability is positively associated with a firm’s

socioeconomic environmental performance.

Hypothesis 2b: Biophysical environmental performance mediates the relationship between

corporate climate change vulnerability and socioeconomic environmental performance.

POPULATION, SAMPLE AND DATA

The Ski Resort Industry

The ski resort industry provides a good test case for this study for several reasons. First, it

is a member of the global tourism sector, which accounts for approximately 10% of global trade,

is the top earner of foreign exchange in the global economy (Eilat & Einav, 2004), and is

substantially dependent upon climate. Sun and warmth are essential to beach-related

destinations, as is wind for sailing, waves for surfing, and snow for skiing. Thus, climate change

creates risks and opportunities for the industry by making some locations less or more desirable

over time (Hamilton, et al., 2005), and, as a result, induces tourism businesses to adapt. Winter

tourism has been repeatedly identified as vulnerable to the warmer weather (IPCC, 2001; Wall,

1992), and the ski resort industry’s vulnerability is particularly acute. Ski resorts have been

undertaking adaptations for decades, including snow-making, and diversifying into less

vulnerable businesses like real estate development, retail businesses, and summer recreation

operations (Hoffmann, et al., 2009; Scott et al., 2007; Scott et al., 2006; Scott, et al., 2003). Thus,

not only does the industry offer a track record of adaptation that can be examined, but it also

should provide insights for the tourism industry at large. In addition, it might generalize to other

resource dependent industries vulnerable to climate change, such as agriculture, forestry, or

renewable energy. Finally, U.S. ski resort environmental performance falls under a common

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regulatory framework of the U.S. Environmental Protection Agency (EPA)11. As a result, U.S.

federal environmental regulation provides an element of statistical control.

Sample and Data

The data for this study include firm-level environmental performance and climatic data,

and statistical controls for firm-, market-, and institutional-level factors that might have effects

on environmental performance. I initially identified 83 ski resorts in the U.S. for the period

between 2001 and 2009. This sampling restriction is due to the availability of environmental

performance data from the Ski Area Citizens Coalition (SACC), a non-profit corporate watchdog

that monitors ski resort development. The SACC has rated ski area environmental performance

of prominent U.S. ski resorts since 2001. Appendix A provides a description of these ratings.

The ratings are based on the occurrence of ski resort business practices that affect environmental

performance. For example, ski resorts that expand their operating area footprints in a given year

will receive a lower score in the category of Maintaining Ski Resort within Existing Footprint.

The SACC develops its rating from mixed sources and methods of data collection. Archival

sources include government documents from federal agencies such as the U.S. Forest Service

and the U.S. Fish and Wildlife Service, websites and corporate reports produced by ski resorts,

media reports, business press and trade journals. In addition, they administer a survey annually to

the ski resorts that they rate (Rivera & De Leon, 2004; Rivera, et al., 2006).12 The SACC sample

comprises only approximately 15% of the ski resorts in the U.S. (in 2009, there were 481 ski

resorts operating in the U.S.), and an even smaller fraction of global ski resorts. Nonetheless, its

ratings represent a unique data source for environmental performance of the industry at large.

Environmental performance measures for ski resorts elsewhere in the U.S. or for ski resorts in

11 See generally 42USC§4332 (1969), the National Environmental Protection Act, which requires the preparation of an environmental impact statement (EIS) for all federal actions that could significantly threaten social and/or environmental values. 12 Source: http://www.skiareacitizens.com/index.php?nav=how_we_grade. Access date: October 11, 2009.

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other countries are either not as comprehensive, lack the sampling history provided by the

SACC, or lack comparability with SACC ratings. The SACC data have been used in previous

studies involving ski resort environmental performance (e.g. Rivera & De Leon, 2004; Rivera,

De Leon & Koerber, 2006).

I collected climate data from the National Climatic Data Center (NCDC), a division of

the National Oceanographic and Atmospheric Association (NOAA) responsible for archiving

NOAA data sources, including longitudinal climatic data measured through the National

Weather Service (NWS) cooperative weather station network. This network contains 18,000

weather stations located within the United States.13 NWS cooperative weather station data were

available for 76 of the 83 ski resorts rated by the SACC in between the years 2000-2009.14 This

restriction yielded the final data set, which consists of an unbalanced panel of 76 ski resorts and

612 firm-year observations, for an average of 8.1 observations per ski resort.

Measures

Biophysical Environmental Performance. I developed a standardized score to measure

this construct from the sum of SACC ratings associated with environmental performance in a ski

resort’s biophysical environment. These ratings evaluate a ski resort’s: (i) maintenance of

existing areas within the existing footprint;(ii) preservation of undisturbed lands from

development; (iii) protection or maintenance of threatened and endangered species and their

habitats; (iv) preservation of environmentally sensitive areas; (v) conservation of water and

energy by avoiding new snowmaking; and, (vi) protection of water quality (See Appendix A).

First, I summed the ratings for each firm-year observation. Second, I standardized the summed

scores based on the average and standard deviation of the local environmental performance

13 Source: http://www.ncdc.noaa.gov/oa/climate/climatedata.html#monthly. Accessed February 25, 2010. 14 I matched weather stations to ski resorts if they were within 10 miles of the resort and if they were at least 500 vertical feet above the base of the ski resort.

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rating for that year. This procedure was necessary because the SACC ratings can contain

different scoring metrics from year to year.15

Socioeconomic Environmental Performance. I used the same procedure applied to

developing biophysical environmental performance scores to measure this construct. In this case,

I selected ratings that measure the degree to which a ski resort protects or conserves natural

resources in its socioeconomic environment: (i) use of renewable energy; (ii) water energy and

energy efficiency; (iii) employee and guest transportation programs; (iv) waste stream

management; (v) purchasing; and (vi) community sustainability (see Appendix A).

Corporate Climate Change Vulnerability. Since corporate climate change vulnerability

is a function of a firm’s exposure and sensitivity to the phenomenon, I develop this construct by

measuring both components independently and then creating an interaction term from them.

The first-order components were measured as follows:

Climate Change Exposure. Following several winter climate change studies in both the

natural16 and social sciences17, I measured climate change exposure at ski resorts as the annual

change in average depth of winter snowpack. This metric has the desirable property of being

functionally dependent on many other important climate indicators such as temperature,

humidity, precipitation type, precipitation intensity, exposure to sun, exposure to wind, and snow

water equivalent (McClung & Shaerer, 1993). The NWS weather stations used in this study

measure the snowpack depth at their locations each hour. I collected the hourly readings for each

day between October 1 and April 15 of the following year, the timeframe when mountain regions

typically build and maintain snowpack (Hauer et al., 1997; McClung & Shaerer, 1993). I then

15 This procedure was proposed and used by Berman and Mattingly (2006) in their treatment of multi-year corporate social performance data from Kinder, Lydenberg and Domani database, where ratings needed to be aggregated into categories and standardized within years because of intra-year variation in the ratings associated with those categories. 16 See for example Band, MacKay, Creed, Semkin and Jeffries (1996), Hauer, Baron, Campbell, Fausch, Hofstettler, Leavesly, Leavitt, Mcknight, and Stanford (1997) and Taylor (1995). 17 See for example Scott and McBoyle (2007) and Scott et al. (2003).

19

averaged these hourly measurements for each ski season to calculate the average annual depth of

winter snowpack for each firm-year. Finally, I calculated the annual change in average depths of

winter snowpack across years. This procedure yields a linear, time-invariant proxy measure of

climate change exposure for each firm. I then grand-mean centered the measure to improve the

interpretability of regression coefficients associated with it and reduce the potential for

multicollinearity with any interaction terms developed from it (Aiken & West, 1991). Finally, I

multiplied the grand-mean centered measure by -1 to reverse code the measure, since negative

annual growth rates in the average winter snowpack depth at ski resorts reflect increasing levels

of climate change exposure, while increasing annual growth rates reflect declining climate

change exposure.

Climate Change Sensitivity. I measured sensitivity first by calculating the average annual

depth of winter snowpack across the sampling history for each ski resort. The result of this

calculation reflects the degree to which a ski resort is buffered from its climate change exposure,

since average snowpack depth indicates the length of time a ski resort can withstand a given rate

of average annual decline in winter snowpack depth. Second, I took the inverse of this

calculation, since deeper snowpacks reflect lower levels of ski resort sensitivity to climate

change. The inverse-transformed measure can be interpreted as a percentage measure of

vulnerability. Finally, following Aiken and West (1991), I grand-mean centered the metric to

improve its interpretability and reduce the potential for multicollinearity with any interaction

terms of which it might be a part. As with exposure, sensitivity is time-invariant.

Control Variables. Several firm-level, industry and institutional characteristics might be

associated with ski resort environmental performance and are therefore modeled in the analysis

as statistical controls. At the firm level, Rivera et al. (2006) found Membership in the Sustainable

20

Slopes Program sponsored by the National Ski Area Association (NSAA)18 to be positively

associated with some natural resource conservation measures. A ski resort’s Baseline Size might

influence environmental performance (Rivera and De Leon, 2004), since larger ski resorts have

more extensive and potentially more complex environmental issues to manage (Clifford, 2002).

Baseline Size was measured in acres for each firm-year by reviewing current ski resort websites,

researching any ski area expansion reflected in Environmental Protection Agency (EPA)

Environmental Impact Statements (EIS) 19 in between 2001 and 2009, and subtracting the size in

acres of the expansion area from the ski area size in that year. Age (in years) might contribute to

a ski resort’s experience and skill for managing environmental issues. Ski resorts operating on

Public Land might receive stricter environmental oversight (Rivera, De Leon & Koerber, 2006;

Clifford, 2002; Briggs, 2000). To capture this effect, I include dummy variables to measure if the

ski resort’s terrain is located on Public Land, Private Land, or a combination of both in any

given year (the reference group includes ski resorts operating on both public and private land).

Some ski resorts are owned by horizontally integrated holding companies. Such companies

might experience fewer impacts from climate change since they have diversified their exposure

and vulnerability to the phenomenon across different ski resorts (Scott & McBoyle, 2007). On

the other hand, some civil organizations have argued that horizontally integrated ski resort

companies tend to engage in more terrain expansion and real estate development, which are both

practices that can have negative implications for biophysical environmental performance

(Clifford, 2002; SACC, 2008). To capture this effect, I include a dummy variable called Group,

which indicates whether or not the ski resort was part of one in any given year. Some ski resorts

are also Owned by a Public Company. Financial pressure from capital markets could affect the

18 The NSAA is the industry association for the U.S. ski resort industry. The Sustainable Slopes Program is a voluntary environmental program sponsored by the NSAA designed to improve the environmental performance of participating ski resorts. 19 U.S. ski resorts are regulated at the federal level by EPA (Clifford, 2002; National Forest Ski Area Permit Act, 1986). If they wish to expand their ski area footprints, they must receive approval from the EPA.

21

profit motive of public firms, which also could have a variety of effects on environmental

performance (Mattingly & Berman, 2006). Dummy variables capture whether a ski resort is

Public, Private, or Non-Profit (Non-Profit is the reference group). In a ski resort’s industry

environment, several characteristics could affect corporate strategy formulation and

implementation in ways that have implications for environmental performance. Distance to

Airports with Jet Service indicates ease of travel to the ski resort for destination travelers with

demand for lodging and real estate services. Population Density within a 75 Mile Radius

indicates the size of the local skiing market, which might be positively associated with local

environmental performance, since local skiers require less lodging and real estate development. I

took the logarithm of this measure since some resorts were located near densely populated urban

area. Ski Resorts within a 75 Mile Radius indicates both the competitive intensity of the regional

skiing market and a differentiating attribute for destination skiers who might prefer ski resort

variety. National Parks within a 75 Mile Radius indicates the desirability of a ski resort region as

a tourism destination for skiers who might value lodging and real estate services. Finally, in the

ski resort’s institutional environmental, social pressures for environmental protection could

moderate a ski resort’s decision to pursue strategies that have locally negative environmental

impacts. I capture this effect at the U.S. state level, using Sierra-Club membership per 1000

people in each state-year as a proxy for State Environmentalism. The Sierra Club is the largest

environmental NGO in the U.S, making its state-level membership concentration a suitable

proxy for the degree to which civil society is engaged in state-level environmental activism

(Fremeth and Holburn, 2010).

22

Estimation Methods20

Since the sample contains multiple yearly observations for each ski resort, it is effectively

a pooled-time series or panel data set (Johnson, 1995). Panel data are potentially problematic for

standard regression procedures such as ordinary least squares (OLS). The problem of serial

correlation will arise if within-firm observations are correlated over time, violating the OLS

assumption of independent errors. This problem is often called intra-panel serial correlation. In

addition, the error variances (standard errors) might not be homogeneous across firms, violating

the assumption of homoskedasticity. To test for intra-panel serial correlation, I followed

procedures outlined by Wooldridge (2002, which call for calculating a Wooldridge F-test (for

which I used Stata’s xtserial procedure), where the null hypothesis is within-panel independence.

In each of the models, the test statistic was highly significant, implying that intra-panel residuals

were serially correlated. To assess the potential for heteroskedasticity, I viewed scatterplots of

model residuals, which provided visual indications that the error variances were not constant.

Since the data violate two critical OLS assumptions, I implemented the Prais-Winsten procedure

for regression with panel-corrected standard errors (using Stata’s xtpcse procedure). Prais-

Winsten regression provides the option to perform a double transformation to the standard errors

produced in the OLS analysis, correcting both for intra-panel serial correlation and inter-panel

heteroskedasticity. Kmenta (1986) explained that the procedure adjusts the variance-covariance

matrix so that it is consistent across panels.

To test Hypothesis 2b, I implemented the procedure recommended by Baron and Kenny

(1986) to uncover mediation in regression analysis. They argue that the researcher must first

establish the proposed statistical relationship between the independent and mediator variables, in

this case a negative relationship between the corporate climate change vulnerability and

20 I conducted the statistical analysis using Stata 9.0 Intercooled.

23

biophysical environmental performance. Second, the researcher must establish the proposed

statistical relationship between the independent variable and the dependent variable, with the

mediator variable excluded from the model, in this case a negative relationship between

socioeconomic environmental performance and corporate climate change vulnerability. Finally,

to conclude that mediation is present, a model regressing the dependent variable on both the

independent and the mediator variables must show that the mediator variable is appropriately

related to the dependent variable and that the relationship between the independent variable and

the dependent variable has been suppressed when the mediator is entered into the model.

RESULTS

------------------------------------------- Insert Table One About Here

------------------------------------------- -------------------------------------------

Insert Table Two About Here -------------------------------------------

Table 1 reports descriptive statistics and correlations. The correlation matrix does not

indicate any apparent correlation between climate change exposure, sensitivity and vulnerability.

Table 2 reports the results of the Prais-Winsten regression analyses conducted to test Hypothesis

1, regarding the effect of climate change vulnerability on biophysical environmental

performance. Model 2 explicitly tests Hypothesis 1. Here, corporate climate change

vulnerability was negatively and significantly related to biophysical environmental performance

(b = -4.19, p<.01) lending support to the hypothesis. The salient effect size in Model 2 can be

interpreted as follows: a one unit increase in corporate climate change vulnerability leads to a

4.19 standard deviation decrease in biophysical environmental performance. Since corporate

climate change vulnerability is an interaction between corporate climate change exposure and

sensitivity, the coefficient can also be interpreted in moderating terms as follows: a one unit

24

change in climate change sensitivity us associated with a 4.19 standard deviation decrease in the

slope of climate change exposure on biophysical environmental performance. Figure 1 illustrates

the impact of average, moderately high (one standard deviation above the mean) and very high

(two standard deviations above the mean) levels of climate change sensitivity on the relationship

between climate change exposure and biophysical environmental performance. The decreasing

magnitude of slopes as vulnerability increases exacerbates the negative effect of climate change

exposure on the dependent variable.

------------------------------------------- Insert Figure One About Here

------------------------------------------- -------------------------------------------

Insert Table Three About Here -------------------------------------------

Table 3 reports the results of the Prais-Winsten regression analyses conducted to test

Hypothesis 2a and 2b, regarding the relationship between the corporate climate change

vulnerability and socioeconomic environmental performance, and the mediating role that

biophysical environmental performance might play in this relationship. Model 4 contains the

explicit test of Hypothesis 2a. These results indicate that the corporate climate change

vulnerability is positively and significantly related to socioeconomic environmental performance

(b = 6.55, p<.01) lending support to the hypothesis.

------------------------------------------- Insert Figure Two About Here

------------------------------------------- The salient effect size in Model 2 can be interpreted as follows: a 1 unit increase in

corporate climate change vulnerability is associated with a 6.55 standard deviation increase in

socioeconomic environmental performance. the positive relationship between climate change

exposure and non-local environmental performance. Alternatively, as an interaction between

25

corporate climate change exposure and sensitivity, the coefficient on corporate climate change

vulnerability can also be interpreted in moderating terms as follows: a one unit change in

climate change sensitivity is associated with a 6.55 standard deviation increase in the slope of

climate change exposure on socioeconomic environmental performance Figure 2 illustrates the

impact of average, moderately high (one standard deviation above the mean) and very high (two

standard deviations above the mean) levels of climate change sensitivity on the relationship

between climate change exposure and non-local environmental performance. The increasing

magnitude of slopes indicate that as vulnerability increases, so does the positive effect of climate

change exposure on the dependent variable.

Following the Baron and Kenny (1986) methodology, Models 2, 4 and 5 in conjunction

test Hypothesis 2b, that biophysical environmental performances mediates the positive

relationship between the corporate climate change vulnerability and socioeconomic

environmental performance. In Model 2, support for Hypothesis 1 satisfies the first test in the

mediation hypothesis, since biophysical environmental performance is not only the dependent

variable of Hypothesis 1, but also the mediator variable of Hypothesis 2b. In Model 4, support

for Hypothesis 2a satisfies the second test in the mediation hypothesis, since it shows evidence of

a positive relationship between the independent variable and the dependent variable. Finally,

Model 5 contains the fully specified model including both the independent variable and the

mediator included as explanatory variables. With the first two tests satisfied, I could conclude

that biophysical environmental performance mediates the relationship between the corporate

climate change vulnerability and socioeconomic environmental performance only if the

relationship between the independent and dependent variables becomes suppressed when the

mediator variable is entered into the model. However, there is little support for this test, as the

effect size on the corporate climate change vulnerability falls only .34 units, from 6.55 to 6.21

26

from Model 4 to Model 5. This means that the bulk of the effect of corporate climate change

vulnerability on socioeconomic environmental performance (6.21 out of 6.55 units) is unrelated

to biophysical environmental performance.

DISCUSSION AND CONCLUSIONS

Corporate climate change adaptation is a relatively new area of study that will likely

become increasingly important for both the practice and study of business (Hoffman et al.,

2009). Climate change is already degrading ecological systems and current predictions suggest

that global impacts on societal systems from rising oceans, water shortages, droughts and

extreme weather will be felt across the globe within the next few generations (IPCC, 2007).

Business is one of the societal systems affected by climate change and, as a result, the area of

corporate climate change adaptation has the potential to migrate towards the core of the

management discipline. Nonetheless, we still know very little about their economic,

environmental and social outcomes. This study opens the inquiry be examining the relationship

between climate change vulnerability and corporate environmental performance. It is based on a

theory that the nature of a firm’s adaptation is a function of its resource dependence on the

biophysical environment and the impact of climate change on the firm’s access to critical

ecosystems services. Hypothesis 1 received reasonably strong support, indicating that corporate

climate change vulnerability is associated with adaptations that harm their biophysical

environments. Hypothesis 2a and 2b predict that climate change adaptations that lead to lower

biophysical environmental performance can threaten firms’ legitimacy, inducing them to engage

in other environmental management strategies that upgrade their socioeconomic environmental

performance. The findings support Hypothesis 2a, indicating that corporate climate change

vulnerability is associated with higher levels of socioeconomic environmental performance.

However, Hypothesis 2b received weak support, leaving it unclear whether improvements in

27

socioeconomic environmental performance occur to atone for climate change adaptations that

lower biophysical environmental performance.

An alternative explanation is that corporate climate change vulnerability might raise the

strategic priority of the broader issue of climate change for individual firms, making them more

susceptible to industry norms that favor the adoption of business practices associated with

climate change mitigation. Further, climate change mitigation measures can occur in the context

of several dimensions of socioeconomic environmental performance, which implies a linkage

between corporate climate change vulnerability and socioeconomic environmental performance.

To explain, in the U.S. ski resort industry, there is a well-developed discourse about the threats

of climate change and the importance of developing mitigation strategies (Scott et al., 2006). In

2002, the NSAA, the Natural Resource Defense Council and Cliff Bar, Inc. launched the multi-

sectoral initiative “Keep Winter Cool,” which is designed to provide U.S. Ski Resorts with

guidelines and best practices for reducing carbon emissions.21 In addition, the NSAA has

repeatedly encouraged its membership to support regional and federal climate change

legislation22, a reflection of coalescing industry-wide norms that favor climate change mitigation

(Rivera et al., 2006). For managers of firms that are vulnerable to the phenomenon, these norms

might resonate, since climate change is not just a public issue for them, but also an external risk.

Managers that identify more with climate change issues may feel more compelled to address

them broadly (Dutton & Dukerich, 1991; Ocasio, 1997), making them more susceptible to

normative pressures emanating from the industry environment (King & Lennox, 2000). Finally,

conforming to these normative pressures can have positive effects on socioeconomic

environmental performance broadly, since climate mitigation can occur in many practices related

21 See http://www.keepwintercool.org. 22 See http://www.nsaa.org/nsaa/environment/climate_change.

28

to socioeconomic environmental performance, such as green purchasing, recycling, carpooling

and community-sustainability initiatives (Enkvist, Naucler & Oppenheim, 2008).

Theoretical Contributions

The study contributes to resource dependence theory by testing hypotheses associated

with some of the unique aspects of natural resource dependence. To date have scholars have

considered resource dependence to be a function of the distribution of power between

interdependent organizations (Cascario & Piskorski, 2005; Pfeffer & Salancik, 1978). With

regard to the natural capital and ecosystem services provisioned by the natural environment,

other organizations may not be involved, implying that different power dynamics are at play. In

particular, the natural environment, through expressions of geoclimatic and geophysical events

such as climate change and its associated phenomena, subjects natural resource-dependent firms

to forces that are exogenous of the firm’s institutional environment and outside of firms’ spheres

of influences. On the other hand, firms may be unconstrained be powerful social relationships in

their ability to alter their biophysical environments, because market and governance mechanisms

often consider the ecosystem services provided by them as public goods (Wackernagel & Rees,

1997). Thus, power in this case is not only a function of the distribution of organizational

dependencies in interorganizational fields, but also the unidirectional dependence that firms have

on their biophysical environments and the unilateral control they have over some of the

ecosystems that comprise them.

The study also contributes to a growing body of research that shows that firms can

perform well in some dimensions of environmental performance but poorly in others (e. g.

Kotchen, 2009; Mattingly and Berman, 2006; Rivera et al. 2006; Rivera and De Leon 2004). For

scholars who study corporate environmental performance, this finding highlights the importance

of assessing multiple dimensions of the construct if a goal is to be comprehensive in the

29

assessment. In addition, it also reflects that firms might do good and bad simultaneously with

regard to the natural environment for different reasons. The findings suggest that firms do create

more negative biophysical environmental impacts as they manage natural resource dependence,

but improve their socioeconomic environmental performance for other reasons, perhaps

including the interaction between firm issue attention and field level norms. In contrast, Kotchen

(2009) argues that this behavior can occur when firms try to off-set their negative externalities,

while Mattingly & Berman (2006) and Rivera et al. (2006) suggest that institutional or policy

weaknesses create incomplete incentives for firms, thereby inducing them to perform well in

some areas and poorly in others. Future research could develop a comprehensive model of the

antecedents of this behavior, which could help firms manage their legitimacy and help policy-

makers develop more sustainable prescriptions.

Implications

The findings suggest that climate change adaptations could simultaneously exacerbate the

negative environmental impacts associated with climate change and induce firms to improve

their socioeconomic environmental performance. In some cases, the latter effect could induce

other organizations in the firm’s value-added chain to improve their biophysical environmental

performance. However, since firms that are vulnerable to climate change are often suppliers that

operate in renewable natural resource industries, their ability to influence environmental

performance upstream might be constrained by their positions in value-added chains. Thus, to

break the linkage between the corporate climate change vulnerability and biophysical

environmental performance while preserving the relationship between vulnerability and

socioeconomic performance, policy-makers will need to develop creative prescriptions. They

could involve developing stronger coordinated biophysical environment performance

mechanisms, more incentives promoting socioeconomic environmental performance, and

30

incentives to develop innovations that help firms reduce their natural resource dependence as the

underlying cause of vulnerability. For this end, businesses could develop disruptive technologies

or more innovative business models. For example, in the agricultural industry, firms are now

dealing with droughts by using genetically-modified seed stocks, reducing their dependence on

irrigation.

Efforts to coordinate policy and innovation would be challenging since, irrespective of

the geophysical effects of climate change, policy regimes globally have not determined how to

protect the earth’s stocks of natural capital (Millenium Ecosystem Assessment, 2005). Moreover,

neither policymakers nor markets are properly accounting for their real value (Constanza et al.,

1997; Wackernagel and Rees, 1997). The Millenium Ecosystem Assessment, a 2005 report

sponsored by several United Nations Programs, attempted to take stock of the earth’s natural

capital, attempted to take stock of the earth’s natural capital, finding that most of the world’s

ecosystems were in decline. In addition, Constanza et al. (1997) found that the value of the

“free” ecosystem services provided to human society was likely between $16 trillion and $54

trillion annually in 1997. Yet, until we monetize them appropriately, it seems unlikely that we

can ensure that they will be managed sustainably (Costanza and Daly, 1992; Wackernagel and

Rees, 1997). A final complication stems from the integration of global markets, which make it

essential to harmonize global policy initiatives across countries, to prevent countries with good

policies from experiencing comparative disadvantages. Thus, the present study is intended to add

to the growing collection of research that has reaffirmed the importance of substantive and

collective recognition, multi-laterally, of the value and the fragility of natural capital and

ecosystem services.

Limitations and Future Research

31

The study is limited in several ways. First, the data I used to develop climatic measures

spanned 2000-2009, because of data availability. This is a potentially short sampling period for

capturing the attention span of managers to the geophysical effects of the climate change. A

longer history would have enabled assessment of trends from the more distant past that have

carried forward to influence recent ski resort strategies. Second, the sample is based on the use of

the SACC environmental performance database might not be representative of the U.S. ski resort

industry in the aggregate, since it comprises approximately 15% of the industry. The sample did

include many of the largest and most well-known U.S. ski resorts, but it excluded many small ski

resorts. Finally, the study did not test for the importance of several important moderating factors

emanating from community-level concerns. Even though U.S. ski resorts are governed under a

common federal-policy regime, community-level actions can affect the ability of firms to deploy

strategies that have biophysical environmental impacts (Gunningham, Kagan & Thornton, 2004).

This has been the case in the U.S ski resort industry where community opposition has played a

significant role in halting many ski area developments (Clifford, 2002).

Community dependence on the ski resort’s salient biophysical environment can also

affect the relationships modeled in this study. If the local community depends upon scarce

ecosystem services that a firm intends to perturb, it might challenge the firm over control of

those resources, impeding corporate climate change adaptations. For example, local communities

have successfully prevented ski resorts from deploying snow-making in regions with water

shortages (Clifford, 2002). Future research could analyze these moderating effects on the

relationship between climate change and environmental performance could lead to a more robust

understanding of the patterning of resource dependence and corporate attempts to adapt to it.

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South American farms. Ecological Economics, 67: 109–116 Spittlehouse, D. L. & R. B. Stewart. 2003. Adaptation to climate change in forest management.

British Columbia Journal of Ecosystems and Management, 4(1): 1-11. Starik, M. & G. Rands. 1995. Weaving an integrated web: Multilevel and multisystem perspect-

ives of ecological sustainable organizations. Academy of Management Review, 20: 908-934. Tashman, P. & J. Rivera. 2010. Are members of business for social responsibility more socially

responsible? Policy Studies Journal, 38: 487-514. Taylor, A. H. 1995. Forest expansion and climate change in the mountain hemlock (Tsuga

Mertensiana) zone, Lassen Volcanic National Park. Arctic and Alpine Research, 27: 207-216. Teece, D., G. Pisano & A. Shuen. 1997. Dynamic capabilities and strategic management.

Strategic Management Journal, 18: 509-533. Vorosmarty, C. J., P. Green, J. Salisbury & R. B. Lammers. 2000. Global water resources: Vul-

nerability from climate change and population growth. Science, 289: 284-288. Wackernagel, M. & W. Rees.1997. Perceptual and structural barriers to investing in natural

capital: Economics from an ecological footprint perspective. Ecological Economics, 20: 3-24.

Wooldridge, J. M. 2002. Econometric analysis of cross section and panel data. Cambridge, MA:

MIT Press.

36

APPENDIX A 2009 Ski Area Citizen Coalition Environmental Performance Rating Categories23

A. Habitat Protection (104 Points) 1. Maintaining ski terrain within the existing footprint (30 points) 2. Preserving undisturbed lands from development (31 points) 3. Protecting threatened, endangered, sensitive, or candidate species and their habitats (22 points) 4. Preserving environmentally sensitive areas (21 points) B. Protecting Watersheds (35 Points) 5. Protecting/preserving wetlands (9 points) 6. Protecting water quality (12 points) 7. Water conservation (14 points) C. Addressing Global Climate Change (50 Points) 8. Conserving energy (10pts) 9. Renewable energy (17 points) 10. Energy efficiency (14 points) 11. Transportation (9 points) D. Environmental policies and practices (41 points) 12. Environmental policy positions and advocacy (17 points) 13. Waste stream management (9 points) 14. Purchasing (8 points) 15. Environmental reporting and accountability (5 points) 16. Community sustainability (2 points)

23 Source: http://www.skiareacitizens.com/index.php?nav=how_we_grade. Access data February, 26, 2010

37

TA

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crip

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ile R

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***

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***

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0.0

00

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3-

0.3

6**

*-0

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***

1.0

0

39

TABLE 2

Results of Prais-Winsten OLS Regression of Biophysical Environmental Performance 2001-2009a

Variables Model 1 Model 2

Intercept 0.66

0.48

Membership in the Sustainable Slopes Program -0.18 ** -0.12

Baseline Size (Acres) 0.00 ** 0.00 **

Age 0.01 ** 0.01 **

Distance to Airport with Jet Service 0.00

0.00 *

Population within 75 Mile Radiusb -0.05

-0.04 ***

Number of Ski Areas within 75 Mile Radius -0.02 *** -0.02 ***

Number of National Parks with 75 Mile Radius -0.09 *** -0.11 ***

Public Land Dummyc 0.10

0.11

Private Land Dummyc 0.22 0.24 *

Ownership by Horizontally Integrated Firm 0.17 ** 0.16 **

Ownership by Public Companyd -0.35 -0.23

Ownership by Private Companyd 0.29

0.48 *

State Environmentalism 8.33 *** 9.11 ***

Exposure -0.01

-0.12 ***

Sensitivity 0.23 5.18 ***

Vulnerability (Exposure x Sensitivity)

-4.19 ***

Wald χ2 744.39 *** 845.30 ***

R2 0.32

0.34

∆ R2 0.02

a n=612 observations for 76 firms

b Logarithm

c The reference group is Mixed Public and Private Land

d The reference group is Ownership by Non-Profit Organization.

* p < .10

** p < .05

*** p < .01

40

TABLE 3

Results of Prais-Winsten OLS Regression of Socioeconomic Environmental Performance 2001-2009a

Variables Model 3 Model 4 Model 5

Intercept 0.82 1.58 * 1.58 **

Membership in the Sustainable Slopes Program 0.28 *** 0.20 * 0.19

Baseline Size (Acres) 0.00

0.00

0.00

Age 0.01 * 0.01 ** 0.01 ***

Distance to Airport with Jet Service 0.00 ** 0.00

0.00

Population within 75 Mile Radiusb -0.14 *** -0.19 ** -0.19 ***

Number of Ski Areas within 75 Mile Radius 0.01 0.01 0.01

Number of National Parks with 75 Mile Radius 0.08 *** 0.09 *** 0.08 ***

Public Land Dummyc -0.07

-0.07

-0.06

Private Land Dummyc 0.29 * 0.27

0.28

Ownership by Horizontally Integrated Firm 0.24

0.15

0.17

Ownership by Public Companyd 0.04

-0.15

-0.15

Ownership by Private Companyd 0.37 ** -0.06

-0.01

State Environmentalism 4.85 6.28 * 6.59 *

Exposure -0.01

0.16 *** 0.15 ***

Sensitivity -0.14

-7.80 *** -7.38 ***

Biophysical Environmental Performance

-0.08 *

Vulnerability (Exposure x Sensitivity)

6.55 *** 6.21 ***

Wald χ2 138.77 *** 344.43

*** 165.36 ***

R2 0.08

0.10

0.10

∆ R2 0.02 0.02

a n=612 observations for 76 firms

b Logarithm

c The reference group is Mixed Public and Private Land

d The reference group is Ownership by Non-Profit Organization.

* p < .10

** p < .05

*** p < .01

41

FIGURE 1 Effect of Climate Change Exposure on Biophysical Environmental Performance at Different Levels of Sensitivity

-10

-8

-6

-4

-2

0

2

4

1 2 3 4 5 6 7 8 9 10 11Local

Environmental Performance

Climate Change Exposure

Mean

+ 1 s.d.

+ 2 s.d.

FIGURE 2 Effect of Climate Change Exposure on Socioeconomic Environmental Performance at Different Levels of Sensitivity

-2

0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11

Non-Local Environmental Performance

Climate Change Exposure

Mean

+ 1 s.d.

+ 2 s.d.