Journal of Public Administration Research and Theory Advance Access published May 20, 2014
JPART
Explaining Coordination in Collaborative
Partnerships and Clarifying the Scope of the
Belief Homophily Hypothesis
John C. Calanni,* Saba N. Siddiki,† Christopher M. Weible,‡
William D. Leach§
*University of Colorado Denver; †Indiana University Purdue University Indiana;
‡
University of Colorado Denver; §University of Southern California
The move towards collaborative governance in environmental policy often takes the form
of collaborative partnerships involving multiple stakeholders with divergent beliefs and
interests. Within such partnerships, stakeholders selectively coordinate with one another
to varying degrees to achieve both individual and shared objectives. Using interview and
questionnaire data from 10 US marine aquaculture partnerships in 2009–2011, we test
three theoretical hypotheses regarding how individuals within collaborative partnerships
decide with whom to coordinate. These competing propositions include belief homophily
(individuals will coordinate with whom they share beliefs), trust (individuals will coordinate
with those whom they trust), and resources (individuals will coordinate with those who
hold critical resources). Results suggest that specific aspects of trust and resources are more
important than shared beliefs in driving coordination in marine aquaculture partnerships.
This finding qualifies previous studies that identified shared beliefs as a driving factor. This
study concludes with a theoretical discussion about the explanatory boundaries of belief
homophily.
INTRODUCTION
To cope with the intractability of modern social problems, public administration has
been trending towards governance strategies designed to be inclusive of a variety of interests and to employ flexible and adaptive processes that generate durable policy solutions
(Alter and Hage 1993; Bardach 2001; Feiock 2013; Hall and O’Toole 2000; Imperial 2005;
O’Toole 1997; Renn 2006). Collaboration is an example of such a governance strategy.
This article is a product of the Aquaculture Partnerships Project, conducted by the authors and graduate
student Scott Vince (Sacramento State). We thank members of our advisory committee and the many
stakeholders who graciously granted us an interview and/or survey response. We would also like to thank our
three anonymous reviewers whose comments and input were instrumental in the development of the ideas
advanced in this article. Any opinions, findings, and conclusions or recommendations expressed in this material
are those of the authors and do not necessarily reflect the views of the National Science Foundation. Address
correspondence to the author at [email protected].
doi:10.1093/jopart/mut080
© The Author 2014. Published by Oxford University Press on behalf of the Journal of Public Administration Research
and Theory, Inc. All rights reserved. For permissions, please e-mail: [email protected].
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
ABSTRACT
2
Journal of Public Administration Research and Theory
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Scholars and practitioners frequently prescribe collaboration for issues that exhibit technical, legal, and political complexity and that transect jurisdictional boundaries of multiple government agencies and multiple levels of government (Innes and Booher 2010;
Mullin and Daley 2009; O’Leary and Bingham 2009; Steelman 2010).
In complex and intractable environmental policy issues, manifestations of collaboration have been coined as watershed partnerships (Sabatier et al. 2005), collaborative
environmental management (Koontz 2004; Koontz and Thomas 2006), collaborative institutions (Lubell 2004), integrated environmental management (Margerum
and Born 1995), collaborative public management (Leach 2006; O’Leary, Gerard,
and Bingham 2006), ecosystem-based management (Layzer 2008), and collaborative
resource management institutions (Heikkila and Gerlak 2005). Very recently, stakeholders have used collaborative strategies to address natural resource dilemmas associated with development of the marine aquaculture industry in the United States,
which provides the policy context for the empirical focus of this article.
Collaboration comes in many forms with different purposes. Sometimes, collaboration brings together representatives from industry, government agencies, nongovernmental organizations, academia, and the interested general public to address
complex problems (Ansell and Gash 2008). Other times, collaboration is used to find
solutions to complex policy problems among government agencies (federal, state, and
local authorities), which has spurred research to evaluate the ensuing effects on public
policy (Agranoff 2004; Ansell and Gash 2008; Koontz and Thomas 2006; Mullin and
Daley 2009). When collaboration is used in policymaking, the overarching goal is
typically to generate durable solutions that represent the interests of the governed and
are based on deliberation and consensus building as opposed to a purely top-down
approach (Agranoff and McGuire 2001; Hall and O’Toole 2000, 2004; Imperial 2005;
Leach et al. 2002; Ostrom 2005; Schneider 2003). Collaborative efforts often attain a
degree of institutionalization, with elements such as a charter or bylaws, regular meetings, written agendas, a discernible organizational structure, a public Web site, and a
name that reifies the group as an entity unto itself (Leach et al. 2002). In this article,
we refer to these semiformalized groups as collaborative partnerships.
Within collaborative partnerships, actors display a selective behavior when deciding with whom to coordinate, such as coordinating with some and not with others, or
coordinating extensively with some and in a limited fashion with others (Wood 1991).
This behavior results in what scholars have referred to as coordination networks or,
specific to the realm of policymaking, policy networks (Lubell et al. 2012a; O’Toole
1997; Park and Rethemeyer 2012; Provan and Milward 1995; Weible and Sabatier
2005). Our focus in this study is the factors underlying the formation of coordination
networks, rather than the ensuing structure of those networks themselves. We base
our notion of coordination on the concepts put forth by Zafonte and Sabatier (1998,
480), who see it as “the spectrum of activity in which one party alters its own political strategies to accommodate the activity of others in pursuit of similar goals.” This
definition could include a variety of interactions including information exchange,
monitoring and aligning political behavior, as well as developing, communicating, and
implementing a common plan of action.
In the last few years there has been an increase in research focused on understanding the relationship drivers and behavior within collaborative partnerships. One of
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
THEORETICAL EXPLANATIONS OF COORDINATION NETWORKS
We test hypotheses generated from three theoretical lenses that each identify one key factor to explain how actors form coordination networks in collaborative partnerships. The
three factors and their affiliated theories are belief homophily in the ACF; interpersonal
trust in Social Capital Theory; and resource deficit in Resource Dependence Theory.
The Advocacy Coalition Framework
Developed by Sabatier and Jenkins-Smith in the 1980s, the ACF employs a model of
the individual that is based on Herbert Simon’s concept of bounded rationality, which
views individuals as fundamentally limited in cognitively processing the information
that they can encounter, consider, and subsequently use in policymaking (Simon 1955).
Given these limitations, individuals must use short cuts, or heuristics, to simplify and
process the information they encounter. They do this by filtering incoming information
based on how it lines up with their own beliefs and precognitions so as to reduce the
mental discomfort (also referred to as cognitive dissonance) new and often discordant
information creates (Festinger 1957; Lord et al. 1979). A part of the filtering process is
accepting information that confirms one’s pre-existing beliefs and tending to reject new
information that contradicts one’s pre-existing beliefs (causing uncomfortable psychological dissonance). The ACF cites this tendency of the individual as an impediment
to learning and belief change, and more relevant to the current study, relies on beliefs
as a causal driver for behavior and the primary heuristic on which individuals rely for
forming their networks of relationships and in political decision making.
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
the central questions explored within both the policy process and public management
literatures has been: what drives the formation of ties between participants in collaborative arrangements (Agranoff and McGuire 2001; Henry 2011; Imperial 2005;
Jones 1997; Kramer 1999; Lubell et al. 2012a, 2012b; Mullin and Daley 2009)? For
example, public management research has identified individual drivers of collaboration between agencies. These include the existence of strong professional incentives
(such as the ability to collaborate included as a criterion on performance evaluations
for public agency managers) as well as agency resource deficits (Mullin and Daley
2009). Likewise, policy process research can provide a context to further investigate
the formation of ties and ensuing networks among collaborative partnership participants (Lubell et al. 2012a). The Advocacy Coalition Framework (ACF) (Sabatier
and Jenkins-Smith 1993), for example, is one approach in policy process research that
posits shared beliefs are a primary causal driver in the formation of coordination networks, which is referred to as the belief homophily hypothesis.
This article seeks to contribute to public management and policy process literatures by advancing the understanding of the factors influencing coordination network
formation within collaborative partnerships by testing the ACF’s belief homophily
hypothesis alongside additional explanations based on Social Capital Theory (Coleman
1988; Putnam 1993) and Resource Dependence Theory (Pfeffer and Salancik 1978).
3
4
Journal of Public Administration Research and Theory
Hypothesis 1—Belief Homophily: In collaborative partnerships, members will
coordinate more closely with other members who share their views on major policy
issues.
Social Capital Theory
Social capital has been defined in many ways, including the facilitation of cooperation
due to trust, social norms, and expectations of reciprocity (Coleman 1988; Putnam
1993). We focus on the role of trust, mainly because the methods for its conceptualization and measurement are more highly developed in the existing literature (Agranoff
and McGuire 2001, Lubell 2007). Trust has been found to be an influential coordination determinant, particularly when considering microlevel relations (Cook, Hardin,
and Levi 2005). Levi and Stoker (2000) view trust as relational (between multiple individuals or groups), conditional (context specific), based on a transaction-cost model
(i.e., a reduction in transaction costs associated with monitoring and enforcement
activities), and reliant on beliefs about individuals and/or groups. In their definition of
trust, Levi and Stoker (2000) indicate that trust and trustworthiness have two dimensions: a commitment to act in the best interest of the truster on the basis of moral values (values that align incentives, a shared definition and value of promise keeping, and
a general concern for the welfare of the truster) and competence (trustworthy entities
have the aptitude to act in a trustworthy fashion). Ferguson and Stoutland (1999,
44) identify a similar set of trust dimensions: (1) participant motives, not exploiting or
betraying purposes; (2) competency, possessing the knowledge and skills to do what is
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
The most important type of beliefs in shaping political behavior in the ACF is
policy-core beliefs. Policy-core beliefs are subsystemwide in scope and are the foundation for forming coalitions, establishing alliances, and coordinating activities among
subsystem members. Policy-core beliefs can be particularly divisive or allying because
they reflect the policy-related values and perceptions about whose welfare counts, the
relative authority of governments and markets, the proper roles of the general public, elected officials, civil servants, experts, and the relative seriousness and causes of
policy problems in the subsystem as a whole (Sabatier and Jenkins-Smith 1999). Given
the nature of these beliefs, they are described as “the stickiest glue that binds coalitions together” and “help unite allies and divide opponents” (Sabatier 1993, 155).
Thus, one of the principal hypotheses in the ACF posits that when policy-core
beliefs are in dispute, coordination networks will be based on shared policy-core
beliefs. In fact, several studies have shown that there is an association between belief
congruence or shared ideology and network ties (Henry et al. 2012; McPherson et al.
2001; Weible 2005; Weible and Sabatier 2005). For example, Weare, Musso, and Jun
(2009) find clear evidence of belief homophily influencing the composition of neighborhood councils in Los Angeles, resulting in less diverse councils and fewer opportunities for discourse between members with differing political perspectives. Outside
of policy research, these findings have also been observed in studies of interorganizational collaboration where organizations that exhibit goal consensus are more likely to
work together (Provan and Kenis 2008). This leads us to our first testable hypothesis,
which emphasizes shared beliefs as the motivation for coordination.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Hypothesis 2—Trust: In collaborative partnerships, members will coordinate more
closely with other members whom they trust.
Resource Dependence Theory
Advanced by Jeffrey Pfeffer and Gerald Salancik (1978), Resource Dependence
Theory has its roots in sociology and is based on a power-maximization model of
organizations originated by Max Weber in 1947. Resource Dependence Theory has
been applied to both coalitions within organizations and coalitions among organizations (Park and Rethemeyer 2012; Ulrich 1984). These coalitions are viewed as continually changing their form and relationships primarily to decrease the organization’s
dependence on others and increase the reliance other organizations have on them.
Additionally, and critical to this theory, resources—defined as both material (ex.
financial) and social (ex. influence)—are seen as not only essential to organizational
power and survival, but also scarce and difficult to acquire (Park and Rethemeyer
2012; Ulrich 1984). Therefore, organizations will coordinate with other organizations
to reduce the uncertainty of obtaining critical resources. Organizations are expected
to strive to maximize their power by controlling resources and limiting their reliance
on other organizations for critical resources.
Just as Resource Dependence is scalable from the organizational level to the interand intraorganizational level, we have extended the scale to the individual level for
the purposes of this study. Conceptually, this should not pose a substantial problem
because, in Resource Dependence Theory, the organization is modeled after certain
attributes of rational choice actors (i.e., self-maximizing entities acting in a strategic manner). This model of motivation differs from those presented in our two previous theories, where trust and beliefs are the central behavioral impetus. Though
trust and behavior might be a component of Resource Dependence Theory (via the
1
Interests are different than beliefs. The term interest is used here to mean a pursuit toward which one is
directed.
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
expected; (3) dependability, holding the necessary resources; and (4) collegiality, showing respect and fairness. Alternatively, trust has also been defined more in line with
rational choice, where individuals act in a benefit-maximizing and cost-minimizing
fashion. For example, Hardin (1993) indicates that knowledge and incentives are central to trust. Therefore, if a group or individual has the knowledge of both their own
and another party’s interests,1 trust is engendered when those interests align or overlap
in such a way that living up to the expectations of the other group/individual is in
the best interest of both groups (self-maximizing behavior). In both cases presented
above, it is evident that interests play an essential role in the generation of trust.
A salient aspect of trust for this study is how trust translates to coordination
between individuals in collaborative partnerships. If we take the transaction cost
minimizing definition of trust, as well as the rational choice explanation of trust, it
would follow that in collaborative policy environments, the minimization of transaction costs or self-maximizing behavior would influence group coordination. Given this
idea of trust, we can generate the following hypothesis:
5
6
Journal of Public Administration Research and Theory
ease with which relationships are forged), controlling resource availability will dictate
with whom organizations collaborate. In the organizational literature, this translates
to firms forming coalitions and joint ventures, forging personal ties and/or contacts
with critical supply firms (Provan 1980), and nonprofit organizations forming collaboratives (Alter and Hage 1993). Speaking to the potential destabilizing effects of
Resource Dependence on collaboration, Park and Rethemeyer (2012, 1) found that
a decrease in “resource munificence” in the context of an adult basic education policy network may result in network segmentation and a re-ordering of relationships
among network members. With this power-based model of organization and coordination behavior, we can test a Resource Dependence hypothesis to juxtapose with the
ACF and Social Capital hypotheses.
The three factors that we use to understand what motivates coordination within collaborative arrangements are certainly not exhaustive. Other factors, for example,
include political leadership (Huxham and Vangen 2000; Raymond 2006) and institutional mechanisms that incentivize cooperation (Agrawal 2002; Raymond 2006;
Weber 1998). Our choice to focus on belief homophily, trust, and resource dependence
is based on the salience of these factors in recent research on policy networks.
BACKGROUND ON US MARINE AQUACULTURE
For the past decade, policy process scholars have studied watershed partnerships
(Lubell et al. 2009) and similar ecosystem-scale processes (Heikkila and Gerlak 2005).
This study investigates several partnerships engaged in a relatively new debate involving the development of marine aquaculture. The National Oceanic and Atmospheric
Administration (NOAA 2011, 1) defines marine aquaculture as “the propagation
and rearing of aquatic organisms for any commercial, recreational, or public purpose. This definition covers all production of finfish, shellfish, plants, algae, and other
marine organisms.” An interest in the development of marine aquaculture is led by
concerns that current fish supplies are inadequate for meeting the food needs of the
world’s population as well as by promise that aquaculture can “foster sustainable economic development and environmentally friendly technologies, create new employment opportunities, reduce the trade deficit in fish products, reduce fishing pressure on
living marine resources, and rebuild depleted stocks” (NOAA 1998, 1).
In the United States, domestic aquaculture supplies only about five percent of
the seafood consumed (NOAA 2011, 4). In 2009, domestic aquaculture production
reached 328,000 metric tons, with a wholesale value of $1.2 billion (National Marine
Fisheries Service [NMFS] 2011, 16). Although this may seem substantial, the United
States imports about 84% of the seafood it consumes, combining fishery and aquaculture production (NOAA 2011, 4). In 2010, the United States imported $14.8 billion of
seafood, and exported $4.4 billion, resulting in a seafood trade deficit of 10.4 billion
(NMFS 2011, 48). On a global scale, aquaculture accounts for about 39% of seafood
production (FAO 2010; NMFS 2011, 39).
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Hypothesis 3—Resource Deficit: In collaborative partnerships, members will
coordinate more closely with other members who have access to important resources.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Despite government support and societal needs, aquaculture development policy
in the United States has faced various policy and political barriers. One barrier is
that the overall regulatory landscape for marine aquaculture is quite complex and
somewhat piecemeal, including 18 applicable federal regulations that are housed
in a variety of federal agencies, as well as multiple state and local regulations that
may overlap or conflict with federal statutes (Firestone et al. 2004; Wirth 1999). The
piecemeal regulations often discourage new businesses from entering the industry, or
existing operations from expanding. An intimidating regulatory environment coupled
with stiff opposition to marine aquaculture from many environmental groups (concerned about natural resource degradation, impacts to native fish species, and visual
pollution), food safety advocates (concerned with mercury and other environmental
contaminants), fishermen (concerned about seafood market competition), homeowners (concerned about visual pollution), and coastal land developers (concerned about
coastal property values) has left the United States in the position of a laggard when it
comes to marine aquaculture development (Firestone 2003; Mazur and Curtis 2006;
McDaniels 2006; Wirth 1999). Given this backdrop, it is easy to see the challenge
confronting the NOAA when the agency was charged to “bring together its diverse
programs to develop a comprehensive aquaculture policy and strategy to provide a
context for agency activities for the next ten to twenty years” (NOAA 1998, 1). The
stage is thus set for a collaborative process that brings together a wide variety of individuals, groups, and interests, providing a prime opportunity to study collaborative
behavior in a socially relevant policy context.
The global debate over development of the aquaculture industry covers issues
rooted in economics, ecology, food safety, government jurisdiction, and regulatory
structure (Firestone et al. 2004). Advocates for rapid industry development, and those
demanding restraint to ensure sustainable industry development, see a role for aquaculture in helping to satisfy the global demand for seafood (which is currently outpacing supply) and also providing critical economic opportunities for remote and rural
communities worldwide (Katranidis 2003). Proponents for industry development also
take an ecological perspective, viewing aquaculture as a potential remedy for dwindling
populations of wild fish due to overfishing, pollution, habitat loss, and an entrenched
fisheries management process that cannot accommodate the rising global demand for
seafood (Firestone et al. 2004; Katranidis 2003). Specifically, marine aquaculture is
seen as a mechanism to help preserve threatened aquatic biodiversity in two ways: by
rebuilding endangered fish stocks and relieving the pressure placed on wild fish stocks
for food consumption (Frankic 2003).
Opponents have indicated that, from an ecological perspective, marine aquaculture is an unsustainable endeavor, at least in its current form. Specifically, they cite
the use of farmed and wild fish stocks (such as herring) for feeding larger farm-raised
species, often at a protein consumption rate that is higher than production (i.e., more
fish protein is consumed in the form of feed than is produced in the form of marketed
fish). Other arguments against industry development include the propagation of diseases (such as sea lice in salmon) from farmed fish to wild fish stocks; the biological and environmental accumulation of chemical and pharmaceutical products used
for disease control at aquaculture facilities; the potential for farmed fish to escape
and breed with wild fish stocks (referred to as genetic pollution of wild fish stocks);
7
8
Journal of Public Administration Research and Theory
CASE SELECTION: MARINE xUACULTURE PARTNERSHIPS
Marine aquaculture partnerships are defined as organizations that include governmental and nongovernmental groups that collaborate on policy or research (or both)
to support the development or regulation of the marine aquaculture industry. We
excluded international partnerships (e.g., the Aquaculture Dialogues) and domestic
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
competition between farmed fish escapees and wild stocks for habitat, food, and mating opportunities; and degradation of natural resources in the area of farming activities, including sedimentation, concentrated biological wastes emanating from farming
operations, as well as visual pollution (Black 2001; Frankic 2003; Mazur 2006; Naylor
2000; Treece 2002).
Conflicts regarding aquaculture development have been documented on a global
scale, ranging from degradation of mangroves and sensitive wetlands due to shrimp
farming in Asia (Kaiser and Stead 2002) to the relative cessation of salmon farming development in the Pacific Northwest of the United States due to environmental
and aesthetic opposition (Mazur 2006). Social science research has shown that much
of the conflict is based on risk perception disparity between experts and lay persons
in populations affected by aquaculture development (Mazur 2006) as well as public
uncertainty regarding the use of scientific information and the ability of technology to
solve industry challenges (Kaiser and Stead 2002; Petts and Leach 2000). To advance
the discussion on marine aquaculture, there has been a call globally to improve the
image of the industry by taking collaborative approaches to natural resource planning
in local communities (i.e., including a variety of stakeholders in planning) as well as
changing the way information is communicated to the public (Burbridge et al. 2001;
Mazur 2006).
Studies of public perception of aquaculture worldwide support this call, indicating that public risk perceptions and divergent expectations regarding management
and allocation of resources to maximize public benefit are substantial contributors
to community resistance to aquaculture development (Mazur 2006). European and
American scholars have suggested that there is a need to communicate accurate cost
and benefit information regarding sustainable aquaculture development to the public,
natural resource managers, and policymakers (Burbridge et al. 2001); establish proactive approaches to coastal resource management that is inclusive of a wide variety of
stakeholders and interests (Burbridge et al. 2001; Firestone et al. 2004; Mazur 2006);
and develop regulatory regimes that provide “for the sustainable use, conservation,
protection, and management of the marine environment in a transparent and equitable fashion” (Firestone et al. 2004, 111).
In the United States, several collaborative partnerships have emerged to grapple
with these issues. Similar to partnerships in watersheds and other complex socioecological systems, marine aquaculture partnerships feature government and nongovernment engaging in consensus-based deliberations with an emphasis on finding win-win
solutions. Like other collaborative processes, aquaculture partnerships are intended to
serve as a crucible for mitigating political disagreement and ensuring some coordination among stakeholders.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
DATA COLLECTION
We contacted the coordinator from each partnership to discuss the purpose of the
study, to solicit agreement to participate, and to obtain contact information for
partnership participants. No partnerships declined to participate in the study. We
then interviewed two to seven participants in each partnership (n = 43). After the
interviews, we administered an online survey to all current or former participants in
the partnership. In the survey, respondents were asked a series of questions relating
to their perceptions of problems associated with the expansion of the aquaculture
industry, views on aquaculture policy, coordination factors and networks, perceptions of the collaborative process and fellow partnership participants, and partnership impacts. The overall response rate for the survey was 68% (n = 129), with rates
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
partnerships that grapple exclusively with freshwater aquaculture issues but included
partnerships that address freshwater aquaculture along with marine.
To locate marine aquaculture partnerships in the United States, we scoured the
internet for likely candidates in the fall of 2009 and interviewed 21 individuals who
play leadership roles in aquaculture science and policy, including representatives from
industry, academia, government, and nongovernmental organizations. The interviewees were identified using a modified snowball sampling approach. From these interviews, we formed an eight-member advisory committee to help finalize the partnership
list and guide development of the interview protocol and survey instrument.
Our final study sample included 10 marine aquaculture partnerships that are or
have recently been active in the United States, excluding Hawaii and Alaska, which we
omitted to conserve our travel budget: the (1) California Aquaculture Development
Committee; (2) Florida Aquaculture Review Council; (3) Florida Net Pen Working
Group; (4) Maine Aquaculture Advisory Council; (5) Maine Fish Health Technical
Committee; (6) Maryland Aquaculture Coordinating Council; (7) New Jersey
Aquaculture Advisory Council; (8) Pacific Aquaculture Caucus; (9) Rhode Island
Aquaculture Working Group; and (10) Washington State Shellfish Aquaculture
Regulatory Committee.
Each of these partnerships was formed in the last 25 years. They range in size,
with the smallest partnership having four participants and the largest having over 50
participants. “Participants” were defined specifically as any current or former partnership members as well as any individuals who closely follow the work of the group.
Participants in over half of the partnerships reported minor participant turnover.
Nine of the partnerships studied focus on their respective state-level issues and one
(the Pacific Aquaculture Caucus) focuses on aquaculture issues relating to the entire
Pacific Northwest region. The majority of the partnerships were created through
legislative mandate with the purpose of addressing concerns regarding fish health,
public safety, and other issues relating to the expansion of the aquaculture industry
and act in an advisory capacity to the state regulatory authority (e.g., Department of
Agriculture) or to specific regulatory officials (e.g., Commissioner of Agriculture).
Finally, the groups vary in policy outputs; for example, in the number or policy recommendations or policy-related research projects they develop.
9
10
Journal of Public Administration Research and Theory
ranging from 59%–90% within each partnership. This article focuses on analysis of
the survey data.
Measuring the Perceived Importance of Belief Homophily, Trust, and Resources
•• They share my beliefs on major aquaculture policy issues.
The importance of trust was captured through the following three statements:
•• I trust them to keep their promises.
•• They are professionally competent.
•• I have worked with them in the past.
The importance of resources was operationalized using the following four statements:
•• They have influence outside the partnership.
•• They have influence inside the partnership.
•• They have access to financial resources.
•• They have access to expertise on major aquaculture policy issues.
Finally, respondents were asked to rate the following statement with regard to its
importance in coordination:
•• There is a legal requirement.
This was done to determine if there existed an overarching legal mandate for coordination due to operational rules, or legal prescription that would dominate coordination network formation over and above the behavioral attributes listed earlier.
The belief homophily statement was developed based on ACF surveys historically used in watershed and marine policy subsystem research where belief networks
are created by asking respondents to indicate which groups they tend to agree with on
specific policy issues (Weible 2005; Zafonte and Sabatier 1998). The attributes of trust
selected for inclusion in this study were informed by past studies of trust in collective
action settings (Lubell 2007) and evaluations of social and institutional trust (Lubell
2004). Resource attributes were developed based on a review of historical Resource
Dependence literature (Pfeffer and Salancik 1978) as well as more recent operationalizations of various resource attributes, including influence, access to funding, as
well as policy expertise (Casciaro and Piskorski 2005; Weible 2005). For the trust
and resources hypotheses, we conceptualize the multiple survey questions as discrete
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
To evaluate the relative importance of multiple factors influencing coordination network formation, respondents were asked, “In general, what factors are important
in choosing what group(s) you will coordinate with on aquaculture policy issues.”
Respondents rated the importance of each factor using a five-point scale (1 = “not
important at all” to 5 = “very important”).
The importance of belief homophily was operationalized using the following
statement:
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
11
reasons for coordination rather than complementary facets of a single underlying
concept. In other words, we are directly measuring each respondent’s stated reasons
for coordination, rather than measuring the respondent’s beliefs, trust, or resources.
Therefore we would not expect the various survey questions to form internally reliable
scales, as might be revealed by factor analysis.
Measuring Coordination Networks and Policy-Core Beliefs
RESULTS
Demographics
Following is a brief overview of respondent demographics. Survey respondents report
the following general affiliations: federal government (12), state government (38),
local government (3), university researchers/sea grant extension (22), industry (33),
environmental groups (5), consultants (5), commercial fisheries (2), and other nonuniversity research (1). Eight respondents did not indicate an affiliation. There are more
nongovernment (72) than government representatives (54) in the partnerships (3 did
not have a discernible affiliation), and males outnumber females almost 4 to 1 (84
males, 22 females, 23 did not respond). The majority of respondents (97) have a bachelor’s degree or higher, and the majority of these also have a master’s or professional
degree (43) or a JD, MD, or PhD (34); 22 did not respond. Most respondents are
50 years of age or older (81), and only 1 respondent is under 30 (22 did not respond).
Respondents were asked to report their level of competency over a variety of
business, engineering, and natural science subject areas (1 = no competency and
5 = complete competency). The highest reported competencies include ecology/
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
The survey measured coordination networks by asking respondents “Please indicate
which groups you tend to coordinate with on major aquaculture policy issues,” and
providing a checklist containing over 20 groups known to be involved with aquaculture policy (Appendix 1). Respondents were also provided an opportunity to manually
enter group names if needed. This network measurement approach is a combination
of the roster and name-generator approaches, each of which are biased in the data
they capture. Henry et al. (2012, 432) explain that the roster method measures many
linkages among a limited set of actors, whereas the name-generator method measures
fewer linkages among a broader set of actors. The hybrid approach helps to address
some of the limitations associated with applying either of these approaches alone.
Policy-core beliefs were measured by providing a battery of 12 statements regarding marine aquaculture policy in the United States (see Appendix 2 for exact wording)
and asking each respondent to indicate their level of agreement with the statement
(using a scale ranging from “strongly disagree” to “strongly agree”).
Using the data on respondents’ coordination networks and policy-core beliefs,
similarity matrices were developed using UCINET (Borgatti, Everett, and Freeman
2002) to determine the existence and degree of correlation between coordination citations and beliefs. Results of this evaluation are discussed in the following section.
12
Journal of Public Administration Research and Theory
Coordination Ties
To understand the factors underlying coordination networking decisions among the
participants, it is important to evaluate where coordination ties are being made on a
broad level. As mentioned above, coordination networks were developed by allowing
respondents to indicate (from a list) which groups they tend to coordinate with on
aquaculture issues. In table 1, the affiliations on the top row are the citing affiliations
and the affiliations on the left are the cited affiliations. All numbers are percentages
of all citations for each citing affiliation to each cited affiliation. For example, looking
down the first column in table 1, the 13 finfish industry representatives had a total of
68 citations for coordination, of which 19% went to finfish industry, 9% to shellfish
industry, 3% to other aquaculture industry, and so forth. As can be seen in table 1,
most of the coordination citations went to three main groups: industry (primarily
finfish and shellfish with an average of 12% and 16% of coordination citations, respectively), government (primarily state government with an average of 29% of citations),
and science/research entities including researchers and university extension (with an
average of 21% of citations). Based on this brief overview of coordination citations
within these partnerships, the question that next surfaces is: what factors are important when individuals are deciding with whom they will coordinate?
Perceived Importance of Belief Homophily, Trust, and Resources
Table 2 lists coordination factors, the mean score of importance (ranging from 1—
Not Important at All to 5—Very Important), and groupings based on significant
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
biology (mean reported competency of 3.7), as well as fish/shellfish culture (3.6), followed by policy, law, or planning (3.0). Oceanography and business/economics have
mean reported competencies of 2.6 and 2.4, respectively. The lowest reported competency is engineering (1.9).
The political leanings of the respondents are primarily moderate to liberal, with
the majority reporting moderate political beliefs (47), and 39 reporting either very
liberal (5) or liberal (34) leanings. Seventeen respondents report conservative political
beliefs and none indicate very conservative (26 did not respond). As a whole, the pool
of respondents hold somewhat proenvironmental beliefs, scoring 3.5 on a proenvironmental scale ranging from 1 (less environmentally oriented) to 5 (very environmentally
oriented).
Compared to sample populations reported in earlier watershed studies (Leach
2006), the population of this study appears relatively homogenous in several areas.
Participant affiliation is dominated by industry and government participants, with
limited representation from environmental groups or from organizations that might
be in opposition to marine aquaculture (such as homeowners, shoreline developers,
or marine fishermen). Similarly, the level of education of the participants is relatively
high, with the majority holding an advanced degree. Political leanings of respondents
are also generally at or to the left of center, with few respondents reporting either very
liberal or very conservative viewpoints.
1
6
33
1
20
3
12
26
0
1
21
4
3
1
100
Other aquaculture (%)
Federal government (%)
State goverment (%)
Local government (%)
Commercial/recreational
Science/research (%)
Consultants (%)
Environmental groups
Other (%)
Total (%)
100
2
3
2
0
100
3
3
3
22
0
0
34
9
100
2
2
3
23
1
0
25
13
1
16
13
263
10
Government
Federal
100
2
2
4
18
1
2
36
4
0
18
12
213
37
Government
State
100
2
6
4
19
2
6
26
2
0
19
13
47
3
Government
Local
100
3
2
1
22
3
0
33
7
0
18
10
89
100
1
3
3
24
1
1
31
8
0
18
9
172
25
Fishing
2
Science/
Research
Recreational
Commercial/
0
5
29
5
2
20
5
8
2
100
2
7
25
5
2
20
9
5
2
100
9
17
65
44
11
5
11
Groups
5
Environmental
Consultants
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
100
4
4
4
26
4
4
21
8
0
17
9
53
2
Other
NA
2
4
4
21
2
2
29
7
1
16
12
NA
NA
Average
Note: Percentages indicate the number of citations for each organizational affiliation by the total number of potential cites per organizational affiliation. Respondents were asked to indicate groups
with whom they tend to coordinate on marine aquaculture issues. All percentages greater than or equal to 10% have been placed in bold.
(%)
fishing (%)
9
9
3
16
8
20
19
Finfish (%)
Shellfish (%)
32
90
68
2
Number of cites
19
Aquaculture
13
Shellfish
Other
Number of Respondents
Finfish
Table 1
Coordination Citations
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
13
14
Journal of Public Administration Research and Theory
Table 2
Mean Scores for Importance of Coordination Factors
Coordination Factor
a.
b.
Significantly
Different than
Factors:
4.2
3.8
c–i
e–i
3.2
3.1
2.8
2.4
2.3
1.9
1.8
a, f–i
a, f–i
a–b, h–i
a–d, i
a–d
a–e
a–f
Note: Scale: 1 = not important at all; 5 = very important post hoc tests: Games-Howell, p < .01.
difference between means (discussed below). As table 2 shows, the most important
factors for respondents when deciding with whom to coordinate are associated with
trust (professional competence, mean score of 4.2; and trust to keep promises, mean
score of 3.2) as well as resources (access to expertise on major aquaculture issues, mean
score of 3.8; and influence outside the partnership, mean score of 3.1). The presence
of a legal requirement (included specifically to determine if there is an institutional
requirement that could be driving coordination) had a mean slightly below the scale
midpoint (2.8), followed by having worked with them in the past (2.4), influence in the
partnership (2.3), and access to financial resources (1.9). The least important factor for
respondents when deciding with whom to coordinate is belief homophily (i.e., shared
beliefs about major aquaculture issues; mean score of 1.8).
In order to determine if the differences in mean scores for coordination factors
are significant, a one-way analysis of variance (ANOVA) with post hoc testing was
performed. The results of a one-way ANOVA are considered reliable as long as the
following assumptions are met: independence of observations, normality (or approximate normality), and equality of variances. Each of these assumptions was evaluated,
with the following violations noted:
•• The assumption of normality was not met for four of the factors—shared beliefs
(normality factor of −5.1), professional competence (normality factor of −5.7),
access to expertise (normality factor of −3.8) and access to financial resources (normality factor of 4.0); and
•• The assumption of equality of variances was not met.
Normality was evaluated using the SPSS® software package by generating a normality factor. The normality factor was calculated by dividing the skewness value
by the standard error for each variable. When a normality factor is above |2.5|, the
distribution of a variable is considered significantly different from normal (p < .01).
However, ANOVA is especially robust against the assumption of normality (Leech
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
c.
d.
e.
f.
g.
h.
i.
They are professionally competent
They have access to expertise on major
aquaculture issues
I trust them to keep their promises
They have influence outside the Partnership
There is a legal requirement.
I have worked with them in the past
They have influence in the Partnership
They have access to financial resources
They share my beliefs about major
aquaculture issues
Mean Scale of
Importance
(N = 109–114)
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
2011). Therefore, the observed violation of normality is not expected to impact the
reliability of the results. The violation of the assumption of equality of variances can
be remedied by selection of the appropriate post hoc test (in this case using GamesHowell in lieu of Tukey’s Test—see below). Results of the ANOVA showed a statistically significant difference among the coordination factors, F(8, 990) = 51.1, p < .001
(assuming an alpha of .01 for significance).
Post hoc Games-Howell tests (used since equal variances cannot be assumed)
were performed in order to determine significant differences between mean scores for
coordination factors. The right column in table 2 presents the statistically significant
differences between coordination factors based on Games-Howell testing results. For
example, professional competence (coordination factor “a” in table 2) was significantly
more important than all other factors (factors “c” through “i” in table 2; p < .01), with
the exception of access to expertise on major aquaculture issues (coordination factor
“b” in table 2). Likewise, influence within the partnership, access to financial resources,
and shared beliefs about major aquaculture issues were significantly less important
than all other factors (p < .01).
Importantly, the coordination factors with the highest mean scores in the grouped
data were somewhat consistent within individual partnerships as well. For example,
the coordination factors with the highest mean scores for all groups combined (professional competence and access to expertise on major aquaculture issues) had the highest mean score for every individual partnership with the exception of two. In those
two partnerships, professional competence still had the highest mean score, followed
by trust to keep promises and a legal requirement. Similar to the data combined for all
groups, shared beliefs and access to financial resources had the lowest mean scores for
importance in six of the 10 partnerships, with shared beliefs scoring lowest in eight of
the 10 partnerships.
In order to determine the impact of organizational affiliation on the results
observed in the grouped data, respondents were grouped by reported affiliation
(based on five umbrella groups). Table 3 lists the general organizational affiliations across the top row and coordination factors along the far left row. The five
affiliations include the aquaculture industry (finfish, shellfish, and feed/other aquaculture), government (federal, state and local officials as well as elected officials),
scientists and consultants (university and nonuniversity researchers, university
extension representatives and consultants), environmental groups, and other (commercial/recreational fishermen and Native American Tribes). All reported numbers
are means, with coordination factors listed in order of decreasing importance when
considering the mean of all respondents (Grouped Data; included for reference and
comparison).
As indicated in table 3, the coordination factors that had the highest mean
scores in the grouped data were somewhat consistent for organizational affiliations.
For example, the factors that had the highest four mean scores for all groups combined also had the highest four mean scores for three out of five organizational
affiliations (aquaculture industry, scientists/consultants, and environmental groups).
Respondents who reported a government affiliation retained professional competence and access to expertise as the factors with the highest mean scores (similar to
the grouped data) but, not surprisingly, indicated the presence of a legal requirement
15
Government
4.1
3.7
2.8
2.5
3.3
2.2
2.0
1.7
1.5
Aquaculture
Industry
3.9
3.7
3.5
3.7
2.5
3.2
2.3
2.0
2.4
4.5
3.8
3.9
3.5
2.2
2.4
2.7
2.1
1.7
Scientists/
Consultants
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Note: Scale: 1 = not important at all; 5 = very important.
Means are cast in bold typeface to indicate the most important coordination factors for individual affiliations and for all data combined.
They are professionally competent
They have access to expertise on major aquaculture issues
I trust them to keep their promises
They have influence outside the Partnership
There is a legal requirement.
I have worked with them in the past
They have influence in the Partnership
They have access to financial resources
They share my beliefs about major aquaculture issues
Coordination Factors
Table 3
Coordination Factors by Organizational Affiliation
Other
4.5
4.5
4.0
2.3
2.3
1.8
3.0
2.0
2.0
Environmental
Groups
3.8
3.6
3.0
3.4
2.3
1.3
2.0
1.0
1.0
4.2
3.8
3.2
3.1
2.8
2.4
2.3
1.9
1.8
Grouped
Data
16
Journal of Public Administration Research and Theory
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Testing Belief Homophily by Associating Coordination Networks and Policy-Core
Beliefs
We applied a second approach to assess the influence of belief homophily on coordination. For this second approach we used surveyees’ responses to the battery of
statements regarding marine aquaculture policy in the United States. Even though
the respondents rated beliefs as relatively unimportant, we assumed that there is a
possibility that beliefs do in fact influence coordination choices unbeknownst to the
respondent. In other words, perhaps beliefs are subconsciously driving coordination
behavior, influencing who actors perceive as professionally competent or guiding who
they see as expert resources. To address this possibility, we employed a social-network-analysis tool called the quadratic assignment procedure (QAP), a technique for
calculating the association between two matrices (Dekker et al. 2008). QAP is one
of the three most often employed statistical methods used for conducting policy network analysis (Lubell et al. 2012b). It is particularly useful for the analysis of social
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
as the next most important factor. Similar to the grouped data, those designated
as “Other” retained professional competence, access to expertise and trust to keep
promises as the most important coordination factors, with influence in the partnership following. Equally as interesting is the fact that shared beliefs was the least
important coordination factor for three of the five organizational affiliations (government, scientists/consultants, and environmental groups) and was below the scale
midpoint for all groups.
These results provide little support for the belief homophily hypothesis (i.e.,
that agreement on aquaculture policy issues will drive the formation of coordination networks). In fact, shared beliefs appear to be one of the least important factors when individuals decide with whom they will coordinate. Alternatively, trust and
resources appear to play a more important role in forming coordination networks.
This is reflected in the scoring of professional competence, which is an attribute of
trust (Lubell 2004), as one of the most important coordination factor for respondents.
This was followed by the resource attribute of access to expertise, trust to keep promises, and finally the resource attribute of influence (outside the partnership). It is also
important to note that having worked with someone in the past (again, an attribute of
trust) scores above the scale midpoint. Thus, there appears to be some support for the
resources and trust hypotheses, and given which ones appear to be the most important, there may be an interaction between the two. For example, high importance is
placed on professional competence when deciding with whom to coordinate. Access
to expertise is a close second. Though each of these represent an attribute of a distinct
concept (i.e., trust versus resources), they share the idea of the expert; one relating
to access to expertise and the other relating to the competence of that expertise. It
is important to note that access to funding (a resource attribute) was also relatively
unimportant when compared to other resource and trust attributes. Additionally, the
presence of a legal requirement, though highest for government respondents (as might
be expected), was still significantly lower than professional competence and access to
expertise for those reporting a government affiliation.
17
18
Journal of Public Administration Research and Theory
2
A beliefs matrix was developed based on responses to 12 statements regarding marine aquaculture policy.
These beliefs represent policy-core beliefs as defined in the ACF framework.
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
networks since it is not based on an assumption of the independence of observations.
This is critical since other parametric statistical tests do require such an assumption.
With social network data (specifically the coordination data generated in this study),
one would reasonably assume that if an individual x reported some level of coordination with individual y, then individual y might report some coordination with individual x. Thus, the observations cannot be assumed to be independent. Since the QAP
is a nonparametric technique that does not rely on this assumption, it is a useful tool
for the analysis conducted in this study. In the context of this research, QAP provides
a means to determine if the policy-core beliefs held by a particular participant align
with those with whom he/she is coordinating. However, it gives no indication of extent
of coordination with the network as a whole.
Prior to running the QAP, it is necessary to first determine if there are significant differences in beliefs among the affiliations regarding marine aquaculture
policy issues. In other words, if there are no significant difference in beliefs, then
application of the QAP would be irrelevant. Thus, there would be no significant
variability in the data to measure. In order to address this, a one-way ANOVA was
conducted with post hoc Games-Howell testing. Table 4 lists organizational affiliations across the top row and marine aquaculture policy beliefs in the far left column.
All reported numbers are means. The results indicate that overall there are significant differences between affiliations regarding the level of agreement with 10 of the
12 policy statements F(4, 112) = 5.7–16.7, p < 0.01. The two exceptions were for the
following: “the best strategy for managing marine aquaculture involves sustained
dialogue among stakeholders” and “external verification and certification programs
provide the necessary incentives to develop a sustainable aquaculture industry.”
For example, respondents from aquaculture industry and scientists/consultants
indicated significantly higher levels of agreement with regard to expanding finfish
and shellfish aquaculture in US waters when compared to environmental groups
and government representatives. Similarly, scientists/consultants indicated a significantly higher level of agreement with the potential for marine aquaculture to diversify coastal economies when compared to government and environmental groups.
Government and environmental groups also indicated a significantly lower level of
agreement than industry with the statement that the aquaculture industry is already
too heavily regulated. Similar results (though opposite in direction) were observed
with regard to adverse risks to the natural environment posed by aquaculture facilities (i.e., government and environmental groups showed a significantly higher level
of agreement with the statement that adverse risks to the environment outweigh the
benefits of aquaculture).
Suffice it to say that since there appears to be variability in policy beliefs by affiliation, using the QAP will allow us to determine if there is a significant correlation
between actors with similar beliefs and those with similar coordination citations. In
our case we used QAP to determine if individuals that share common beliefs tend
to share similar coordination citation tendencies.2 Our belief homophily hypothesis
Government
3.8
3.6
4.0
3.5
4.1
3.0
2.1
2.8
3.6
4.0
2.1
4.0
Aquaculture
Industry
4.7
4.5
4.7
3.9
4.2
4.0
1.5
2.8
4.6
4.5
1.3
4.4
4.4
1.5
4.6
4.4
2.8
1.8
3.6
4.2
3.8
4.4
4.5
4.7
Science/
Consultants
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Marine shellfish aquaculture must be expanded
in US waters
Marine finfish aquaculture must be expanded in
US waters
Existing marine shellfish aquaculture facilities in
the United States are ecologically sustainable
Existing marine finfish aquaculture facilities in
the United States are ecologically sustainable
The best strategy for managing marine aquaculture involves sustained dialogue among all
stakeholders
The US marine aquaculture industry is already
too heavily regulated
Adverse risks to the natural environment outweigh the benefits of marine aquaculture
External verification and certification programs
provide the necessary incentives to develop a
sustainable marine aquaculture industry
The expansion of US marine aquaculture will
provide a significant supply of sustainable
and healthy seafood offsetting the trade
deficit
Marine aquaculture will diversify coastal
economies
Marine aquaculture threatens the livelihood of
commercial fishers
Marine aquaculture allows for the continuation
of maritime heritage
Policy Statements
Table 4
Marine Aquaculture Policy Beliefs by Organizational Affiliation
Other
4.7
4.3
4.3
3.7
4.0
3.0
1.3
4.0
4.7
4.7
1.7
4.7
Environmental
Groups
2.4
2.0
2.8
1.8
4.4
1.6
3.0
3.6
2.4
2.2
3.2
3.0
4.2
1.8
4.2
4.0
2.9
1.9
3.4
4.2
3.6
4.2
4.0
4.2
Total
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
19
20
Journal of Public Administration Research and Theory
Conclusions
In this study we have continued previous efforts at conducting theory-driven empirical research to evaluate the factors that influence how individuals form coordination
networks and have done so with the intent to bridge the relevant literatures from
public management and policy process theory. Recent work and conventional knowledge have suggested that beliefs are the primary heuristic guiding political coordination (Henry 2011). Conversely, research in public management has suggested that
collaboration between government institutions is strongly (and positively) related to
the existence of professional incentives (i.e., a structural factor in individual annual
performance evaluations) as well as a lack of resources to address specific public
policy problems (Mullin and Daley 2009). This article seeks to build upon those ideas
by evaluating alternative explanations for the formation of coordination networks in
collaborative policy environments. Specifically, we have evaluated the importance of
belief homophily, trust, and resources when individuals decide with whom they will
coordinate.
Data from this study do not support the belief homophily hypothesis. To the
contrary, individuals place more importance on attributes associated with trust and
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
would predict that there should be a strong, positive, and significant correlation across
belief and coordination networks. In order to conduct the QAP, two matrices were
created with 11 rows (one for each of the affiliations listed in table 1), and either 11
(citation matrix) or 12 (beliefs matrix) columns. Data in the citation matrix was normalized by dividing by the total number of respondents in a given affiliation. Each
matrix was then transformed by generating Pearson’s correlation coefficients between
each row to create two 11 by 11 similarity matrices (i.e., generating symmetrical matrices from nonsymmetrical matrices based on row similarities [using Pearson’s R]). The
two 11 by 11 matrices were then used as inputs for the QAP.
The QAP allows us to establish the existence, degree, and significance of a correlation between the belief and coordination networks mentioned above by generating thousands of random permutations of the independent matrix links (in this
case beliefs). Subsequently the procedure computes the proportion of coefficients
generated from the random permutations that appear as extreme as the coefficient between the matrices. For our purposes, significance is defined as the condition when a random permutation of links reveals a stronger correlation than that
observed between the two networks less than 5% of the time (i.e., 95% of the time
the randomly permuted correlation is weaker than the actual observed). There is
an inherent direction of causality using this approach. We have defined the beliefs
matrix as independent, leaving the coordination matrix as dependent. Thus, the
QAP will fix the structure of the beliefs network and randomly permute the coordination network. This approach tests whether beliefs explain coordination. Results
of the QAP show no significant correlation between the beliefs and coordination
networks (Pearson R = .02, p = .32), supporting previous results that suggest there
is no relationship between beliefs and coordination networks among respondents in
this study.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
resources (including professional competence, access to expertise, trust to keep promises, and external influence). Similarly, recent studies of policy network cohesion have
indicated that although shared ideology is a strong polarizing force in collaborative
environments, network cohesion is often better explained by power-seeking relationships (as defined by Resource Dependence Theory) that allow actors within a network
to increase their ability to influence policy outcomes (Henry et al. 2012). These results
indicate that rather than accepting long-standing assumptions about political behavior, we should probe the limits of those assumptions to further our understanding of
the policy process.
However, these findings do not disprove the role of ideology or shared beliefs
in political decision making documented in prior research. For example, Weible
(2005) and Weible and Sabatier (2005) have shown that in situations where policycore beliefs are contested, ally networks tend to correlate with beliefs. Similarly,
Henry et al. (2010) found that belief systems matter in forming collaboration networks, but more so to avoid actors with dissimilar beliefs than to link actors with
similar beliefs. The belief homophily was also supported in studies involving environmental conflicts by Matti (2011) and Ingold (2011). Placed alongside previous
studies that have demonstrated the importance of belief homophily, this study
illustrates a plausible contextual boundary of that importance. Namely, beliefs
may be a weaker driver of coordination networks in subsystems, and/or venues
within subsystems, where policy-core beliefs are not highly contested. Although
the participants in the aquaculture partnerships in this study differed in some of
their beliefs, they generally agreed that aquaculture should be developed at some
level. Hence, we conclude that Hypothesis 1, regarding belief homophily, should
be revised as follows: “In collaborative partnerships where policy-core beliefs are
threatened, members will coordinate more closely with other members who share
their views on major policy issues.”
It has long since been recognized that policymaking occurs within a variety
of venues within any given policy subsystem (Baumgartner and Jones 1993; Lubell
2013). These venues can be characteristically diverse with respect to size, composition,
influence, resources, among other ways. Assuming that policy actors will seek amiable
venues (Pralle 2003), collaborative partnerships will more likely attract policy actors
seeking pragmatic comprises and, thus, avoiding some of intransigent conflicts common in many applications of the ACF. The collaborative partnerships under consideration in this research represent just one of the many marine aquaculture policymaking
venues in the respective states. Our data show that these partnership venues, while still
involving some diversity of members as shown in table 3, are generally dominated by
aquaculture industry supporters. This is not to say that there is an absence of opposition to aquaculture in the United Sates, but rather that individuals who participate in
these partnerships tend to acknowledge the progression of aquaculture development.
Thus, in the absence of major disagreement of policy-core beliefs, they coordinate
with fellow participants who possess useful resources and/or those that are trustworthy to further their goals.
To further refine and clarify the scope of the belief homophily hypothesis, future
studies could directly compare two or more subsystems or venues with differing
degrees of policy-core belief conflict. Another improvement would be to ask survey
21
22
Journal of Public Administration Research and Theory
FUNDING
National Science Foundation (071067, 0913001).
APPENDIX 1
Respondents were provided the following coordination options:
Please indicate the groups that you regularly coordinate with on aquaculture policy
issues related to the [Partnership Name] (click all that apply).
Native American Tribe
US Department of Agriculture
National Oceanic and Atmospheric Administration
Army Corps of Engineers
US Fish and Wildlife Service
US Environmental Protection Agency
US Food and Drug Administration
State Environmental Protection Agency
State Department of Agriculture
State Department of Natural Resources/Division of Wildlife
Local Governments (city/county/districts)
Finfish Aquaculture
Shellfish Aquaculture
Other Aquaculture (e.g., aquatic plants)
Commercial Fisheries
Recreational Fishing
Shoreline Developers
Environmental Groups
Consultants
University Cooperative Extension
University Researchers
News Media
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
respondents to indicate the degree that they trust, share beliefs, or rely on resources
from the specific groups that they choose to coordinate with or not. Such data would
allow for a more rigorous application of network analysis to explore the interaction
of different variables affecting coordination but at the cost of taxing respondents with
a complex survey instrument.
This study contributes to the larger body of work related to the policy process
and public management literature and was intended to answer the multiple calls for
empirically based, theory-driven research to help build and refine the theories that
have been advanced in those fields. We have shown that alternative theory testing provides valuable insights into individual behavior in collaborative policy environments
and can help establish the limits of theoretical reach. And although our application
is specific to policy networks, the findings can also be translated to applications of
public management theories wherein the focus in on examining intra- and interorganizational patterns of coordination.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
23
APPENDIX 2
Respondents were asked to respond to the following policy-core beliefs statements:
The following statements express perceptions about US marine aquaculture issues.
Please indicate the response that best reflects your beliefs (1 = strongly disagree;
5 = strongly agree).
•• Marine shellfish aquaculture must be expanded in US waters.
•• Marine finfish aquaculture must be expanded in US waters.
•• Existing marine shellfish aquaculture facilities in the United States are ecologically
sustainable.
•• Existing marine finfish aquaculture facilities in the United States are ecologically
among all stakeholders.
•• The US marine aquaculture industry is already too heavily regulated.
•• Adverse risks to the natural environment outweigh the benefits of marine
aquaculture.
•• External verification and certification programs provide the necessary incentives to
develop a sustainable marine aquaculture industry.
•• The expansion of US marine aquaculture will provide a significant supply of sustainable and healthy seafood offsetting the trade deficit.
•• Marine aquaculture will diversify coastal economies.
•• Marine aquaculture threatens the livelihood of commercial fishers.
•• Marine aquaculture allows for the continuation of maritime heritage.
REFERENCES
Agranoff, Robert, and Michael McGuire. 2001. Big questions in public network management
research. Journal of Public Administration Research and Theory 11:295–326.
Agrawal, Arun. 2002. Common resources and institutional sustainability. In Drama of the commons,
eds. Elinor Ostrom, Thomas Dietz, Nives Dolsak, Paul C. Stern, Susan Stonich, and Elke U.
Weber, 41–85. Washington, DC: National Academy Press.
Alter, Catherine, and Jurrian Hage, eds. 1993. Organizations working together. Newbury Park, UK:
Sage.
Ansell, Chris, and Alison Gash. 2008. Collaborative governance in theory and practice. Journal of
Public Administration Research and Theory 18:543–71.
Bardach, Eugene. 2001. Developmental dynamics: Collaboration as an emergent phenomenon.
Journal of Public Administration Research and Theory 11:149–64.
Baumgartner, Frank R., and Bryan D. Jones. 1993. Agendas and instability in American politics.
Chicago: Univ. of Chicago Press.
Black, Kenneth D. 2001. Environmental impacts of aquaculture. Sheffield, UK: Sheffield Academic
Press.
Borgatti, Stephen P., Martin G. Everett, and Linton C. Freeman. 2002. Ucinet for windows: Software
for social network analysis. Harvard, MA: Analytic Technologies.
Burbridge, P., V. Hendrick, E. Roth, and H. Rosenthal. 2001. Social and economic policy issues
relevant to marine aquaculture. Journal of Applied Ichthyology 17:194–206.
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
sustainable.
•• The best strategy for managing marine aquaculture involves sustained dialogue
24
Journal of Public Administration Research and Theory
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Casciaro, Tiziana, and Mikolaj J. Piskorski. 2005. Power imbalance, mutual dependence, and
constraint absorption: A closer look at resource dependence theory. Administrative Science
Quarterly 50:167–99.
Coleman, James S. 1988. Social capital in the creation of human capital. American Journal of
Sociology 94:S95–S120.
Cook, Karen, Russell Hardin, and Margaret Levi, eds. 2005. Cooperation without trust? New York,
NY: Russell Sage.
Dekker, David J., David Krackhardt, and Thomas Snijders. 2008. Sensitivity of MRQAP tests to
collinearity and autocorrleation conditions. Psychometrika 72:563–81.
FAO (Food and Agriculture Organization of the United Nations). 2010. The state of world fisheries
and aquaculture 2010. Rome, Italy: FAO.
Ferguson, Ronald F. and Sara E. Stoutland. 1999. Reconceiving the community development field.
In Urban problems and community development, eds. R. F. Ferguson and W. T. Dickens, 33–76.
Washington, DC: Brookings Institution.
Feiock, Richard C. 2013. The institutional collective action framework. Policy Studies Journal
41:397–425.
Festinger, Leon. 1957. A theory of cognitive dissonance. Stanford, CA: Stanford Univ. Press.
Firestone, Jeremy. 2003. Fish as pollutants: Limitations of and crosscurrents in law, science, management, and policy. Washington Law Review 78:693–722.
Firestone, Jeremy, Willett Kempton, Andrew Krueger, and Christen Loper. 2004. Regulating offshore wind power and aquaculture: Messages from land and sea. Cornell Journal of Law and
Public Policy 14:71–111.
Frankic, Anamarija, and Carl Hershner. 2003. Sustainable aquaculture: Developing the promise of
aquaculture. Aquaculture International 11:517–30.
Hall, Thad E., and Laurence J. O’Toole. 2000. Structures for policy implementation: An analysis of
national legislation, 1965–1966 and 1993–1994. Administration and Society 31:667–86.
———. 2004. Shaping formal networks through the regulatory process. Administration and Society
36:186–207.
Hardin, Russel. 1993. The street level epistemology of trust. Politics and Society 21:505–29.
Heikkila, Tanya, and Andrea K. Gerlak. 2005. The formation of large-scale collaborative resource
management institutions: Clarifying the roles of stakeholders, science, and institutions. Policy
Studies Journal 33:583–612.
Henry, Adam. 2011. Ideology, power, and the structure of policy networks. Policy Studies Journal
39:361–83.
Henry, Adam, Mark Lubell, and Mike McCoy. 2011. Belief systems and social capital as drivers of policy network structure: The case of California regional planning. Journal of Public
Administration Research and Theory 21:419–44.
———. 2012. Survey-based measurement of public management and policy networks. Journal of
Policy Analysis and Management 31:432–52.
Huxham, Chris, and Siv Vangen. 2000. Leadership in the shaping and implementation of collaboration agendas: How things happen in a (no quite) joined-up world. The Academy of Management
Journal 43:1159–75.
Imperial, Mark T. 2005. Using collaboration as a governance strategy: Lessons from six watershed
management programs. Administration and Society 37:281–320.
Ingold, Karin. 2011. Network structures within policy processes: Coalitions, power, and brokerage
in Swiss climate policy. Policy Studies Journal 39:435–59.
Innes, Judith E., and David E. Booher. 2010. Planning with complexity: An introduction to collaborative rationality for public policy. New York, NY: Routledge.
Jones, Candace, William S. Hesterly, and Stephen P. Borgatti. 1997. A general theory of network governance: Exchange conditions and social mechanisms. Academy of Management Review 22:911–95.
Kaiser, M., and S. Stead. 2002. Uncertainties and values in European aquaculture: Communication,
management and policy issues in times of “changing public perceptions.” Aquaculture
International 10:469–90.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Katranidis, S., E. Nitsi, and A. Vakrou. 2003. Social acceptability of aquaculture development in
coastal areas: The case of two Greek islands. Coastal Management 31:37–53.
Koontz, Thomas M., and Elizabeth M. Johnson. 2004. One size does not fit all: Matching breadth of
citizen participation to watershed group accomplishments. Policy Sciences 37:185–204.
Koontz, Thomas M., and Craig W. Thomas. 2006. What do we know and need to know about
the environmental outcomes of collaborative management? Public Administration Review 66
(Suppl 1): 111–21
Kramer, Roderick M. 1999. Trust and distrust in organizations: Emerging perspectives, enduring
questions. Annual Review of Psychology 50:569–98.
Layzer, Judith A. 2008. Natural experiments: Ecosystem-based management and the environment.
Cambridge, MA: MIT Press.
Leach, William D. 2006. Collaborative public management and democracy: Evidence from western
watershed partnerships. Public Administration Review 66:100–10.
Leach, William D., Neil W. Pelkey, and Paul A. Sabatier. 2002. Stakeholder partnerships as collaborative policymaking: Evaluation criteria applied to watershed management in California and
Washington. Journal of Public Policy Analysis and Management 21:645–70.
Leech, Nancy, Karen Barrett, and George Morgan. 2011. IBM SPSS for intermediate statistics use
and interpretation, 4th ed. New York, NY: Routledge.
Levi, Margaret, and Laura Stoker. 2000. Political trust and trustworthiness. Annual Review of
Political Science 3:475–507.
Lord, Charles, Lee Ross, and Mark Lepper. 1979. Biased assimilation and attitude polarization: The
effects of prior theories on subsequently considered evidence. Journal of Personality and Social
Psychology 37:2098–109.
Lubell, Mark. 2004. Collaborative environmental institutions: All talk and no action? Journal of
Policy Analysis and Management 23:549–73.
———. 2007. Familiarity breeds trust: Collective action in a policy domain. Journal of Politics
69:237–50.
———. 2013. Governing institutional complexity: The ecology of games framework. Policy Studies
Journal 41:537–59.
Lubell, Mark, Adam. D. Henry, and Mike McCoy. 2012a. Collaborative institutions in an ecology
of games. American Journal of Political Science 54:287–300.
Lubell, Mark, William D. Leach, and Paul A. Sabatier. 2009. Collaborative watershed partnerships
in the epoch of sustainability. In Toward sustainable communities: Transitions and transformations in environmental policy, 2nd ed., eds Daniel A. Mazmanian and Michael E. Kraft, 255–
88. Cambridge, MA: MIT Press.
Lubell, Mark, John Scholz, Ramiro Berardo, and Gary Robins. 2012b. Testing policy theory with
statistical models of networks. Policy Studies Journal 40:351–74.
Margerum, Richard D., and Stephen M. Born. 1995. Integrated environmental management: Moving
from theory to practice. Journal of Environmental Planning and Management 38:371–92.
Matti, Simon, and Annica Sandström. 2011. The rationale determining advocacy coalitions:
Examining Coordination Networks and Corresponding Beliefs. Policy Studies Journal 39:
385–410.
Mazur, Nicole, and Allan Curtis. 2006. Risk perceptions, aquaculture, and issues of trust: Lessons
from Australia. Society and Natural Resources 19:791–808.
McDaniels, Timothy, Holly Longstaff, and Hadi Dowlatabadi. 2006. A value-based framework
for risk management decisions involving multiple scales: A salmon aquaculture example.
Environmental Science and Policy 9:423–38.
McPherson, Miller, Lynn Smith-Lovin, and J. M. Cook. 2001. Birds of a feather: Homophily in
social networks. Annual of Sociology 27:415–44.
Mullin, Megan, and Dorothy Daley. 2009. Working with the State: Exploring interagency collaboration within a federalist system. Journal of Public Administration Research and Theory 20: 757–778.
National Marine Fisheries Service. 2011. Fisheries of the United States 2010. Silver Spring, MD:
National Marine Fisheries Service.
25
26
Journal of Public Administration Research and Theory
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
National Oceanic and Atmospheric Administration. 1998. National oceanic and atmospheric administration aquaculture policy. http://www.nmfs.noaa.gov/aquaculture/docs/policy/noaa_aq_policy_1998.pdf
———. 2011. Marine aquaculture policy. Silver Spring, MD: National Oceanic and Atmospheric
Administration.
———. 2013. Aquaculture information homepage. http://www.nmfs.noaa.gov/aquaculture/ (accessed
September 2013).
Naylor, Rosamond, Rebecca Goldberg, Jurgenne Primavera, Nills Kautsky, Malcom Beveridge,
Jason Clay, Carl Folke, Jane Lubchenco, Harold Mooney, and Max Troell. 2000. Effect of
aquaculture on world fish supplies. Nature 405:1017–24.
O’Leary, Rosemary, and Lisa B. Bingham, eds. 2009. The collaborative public manager. Washington,
DC: Georgetown Univ. Press.
O’Leary, Rosemary, Catherine Gerard, and Lisa B. Bingham. 2006. Introduction to the symposium
on collaborative public management. Public Administration Review 66:6–9.
Ostrom, Elinor. 2005. Understanding institutional diversity. Princeton, NJ: Princeton Univ. Press.
O’Toole, Laurence J. 1997. Treating networks seriously: Practical and research-based agendas in
public administration. Public Administration Review 57:45–52.
Park, Hyun H., and Karl Rethemeyer. 2012. The politics of connections: Assessing the determinants
of social structure in policy networks. Journal of Public Administration Research and Theory
23:1–31.
Petts, Judith and Barbara Leach. 2000. Evaluating methods for public participation: Literature review.
R&D Technical Report E135. Bristol, UK: Environment Agency.
Pfeffer, Jeffrey, and Gerald R. Salancik. 1978. The external control of organizations: A resource
dependence perspective. Stanford, MA: Stanford Univ. Press.
Pralle, Sarah B. 2003. Venue shopping, political strategy, and policy change: The internationalization of Canadian forest advocacy. Journal of Public Policy 23:233–60.
Provan, Keith G., Janice B. Beyer, and Carlos Kruytbosch. 1980. Environmental linkages and power
in resource-dependence relations between organizations. Administrative Science Quarterly
25:200–25.
Provan, Keith G., and H. Brinton Milward. 1995. A preliminary theory of interorganizational
network effectiveness: A comparative study of four community mental health systems.
Administrative Science Quarterly 40:1–33.
Provan, Keith G., and Patrick Kenis. 2008. Modes of network governance: Structure, management,
and effectiveness. 18: 895–915.
Putnam, Robert, Robert Leonardi, and Raffealla Nanaetti. 1993. Making democracy work: Civic
traditions in modern Italy. Princeton, NJ: Princeton Univ. Press.
Raymond, Leigh. 2006. Cooperation without trust: Overcoming collective action barriers to endangered species protection. Policy Studies Journal 34:37–57.
Renn, Ortwin. 2006. Participatory processes for designing environmental policy. Land Use Policy
23:34–43.
Sabatier, Paul. A., and Hank C. Jenkins-Smith. 1993. Policy change and learning: An advocacy coalition approach. Boulder, CO: Westview.
———, eds. 1999. The advocacy coalition framework: An assessment. In Theories of the policy process, ed. Paul A. Sabatier, 117–66. Boulder, CO: Westview.
Sabatier, Paul A., Will Focht, Mark Lubell, Zev Trachtenberg, Arnold Vedlitz, and Marty Matlock,
eds. 2005. Swimming upstream: Collaborative approaches to watershed management. Cambridge,
MA: MIT Press.
Schneider, Mark, John Scholz, Mark Lubell, Denisa Mindruta, and Matthew Edwardsen. 2003.
Building consensual institutions: Networks and the national estuary program. American
Journal of Political Science 47:143–58.
Simon, Herbert A. 1955. A behavioral model of rational choice. The Quarterly Journal of Economics
69:99–118.
Calanni et al. Collaborative Partnerships and the Belief Homophily Hypothesis
Downloaded from http://jpart.oxfordjournals.org/ at Auraria Library on May 27, 2014
Steelman, Toddi A. 2010. Implementing innovation: Fostering enduring change in environmental and
natural resource governance. Washington, DC: Georgetown Univ. Press.
Treece, Granville D. 2002. Shrimp farm effluents. In Responsible marine aquaculture, eds Robert R.
Stickney and James P. McVey. Wallingford, UK.
Ulrich, David, and Jay B. Barney. 1984. Resource dependence, efficiency, and population. The
Academy of Management Review 9:471–81.
Weare, Christopher, Juliet Musso, and Kyu-Nahm Jun. 2009. Cross-talk: The role of homophily and
elite bias in civic associations. Social Forces 88:147–73.
Weber, Edward P. 1998. Pluralism by the rules: Conflict and cooperation in environmental regulation.
Washington, DC: US Department of Interior.
Weber, Max. 1947. Theory of social and economic organizations. New York, NY: Free Press.
Weible, Christopher, and Paul A. Sabatier. 2005. Comparing policy networks: Marine protected
areas in California. Policy Studies Journal 33:181–201.
Wirth, Ferdinand, and Jane E. Luzar. 1999. Environmental management of the U.S. aquaculture
industry: Insights from a national survey. Society and Natural Resources 12:659–72.
Wood, Donna J., and Barbara Gray. 1991. Toward a comprehensive theory of collaboration. Journal
of Applied Behavioral Science 27:139–62.
Zafonte, Matthew and Paul A. Sabatier. 1998. Shared beliefs and imposed interdependencies as
determinants of ally networks in overlapping subsystems. Journal of Theoretical Politics
10:473–505.
27