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Rules and decision making

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Title:
Rules and decision making understanding the factors that shape regulatory compliance
Creator:
Siddiki, Saba Naseem
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Language:
English
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ix, 243 leaves : ; 28 cm

Subjects

Subjects / Keywords:
Aquaculture industry -- Law and legislation -- Virginia ( lcsh )
Aquaculture industry -- Law and legislation -- Florida ( lcsh )
Aquaculture -- Government policy -- Florida ( lcsh )
Aquaculture -- Government policy -- Virginia ( lcsh )
Aquaculture -- Government policy ( fast )
Aquaculture industry -- Law and legislation ( fast )
Florida ( fast )
Virginia ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Bibliography:
Includes bibliographical references (leaves 229-243).
General Note:
School of Public Affairs
Statement of Responsibility:
by Saba Naseem Siddiki.

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|University of Colorado Denver
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|Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
779857098 ( OCLC )
ocn779857098
Classification:
LD1193.P86 2011D S53 ( lcc )

Full Text
RULES AND DECISION MAKING: UNDERSTANDING THE FACTORS THAT
SHAPE REGULATORY COMPLIANCE
by
Saba Naseem Siddiki
B.A, University of Puget Sound, 2005
M.A., University of Denver, 2007
A thesis submitted
to the University of Colorado Denver
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
School of Public Affairs
2011


2011 by Saba Naseem Siddiki
All rights reserved.


This thesis for the Doctor of Philosophy
degree by
Saba Naseem Siddiki
has been approved
Chris Weible
,1
Tanya Heikkila
Christine Martell
Elinor Ostrom
Ckit-W ( //
Date


Siddiki, Saba Naseem (Ph.D., Public Affairs)
Rules and Decision Making: Understanding the Factors that Shape Regulatory
Compliance
Thesis directed by Associate Professors Chris Weible and Tanya Heikkila
This dissertation presents findings from a study to assess compliance motivations
within the context of aquaculture in two states, Virginia and Florida. This analysis is
based upon scholarship relating to policy design, regulatory compliance, and the
institutional analysis and development (IAD) framework. Data for this study were
collected in four stages toward a comparative case study analysis of compliance
motivations in the two study states: (1) a preliminary study involving interviews
(n=10) and a questionnaire of members of the National Association of State
Aquaculture Coordinators (0=32; response rate = 57%); (2) a comprehensive coding
of all state level regulations governing aquaculture in each study state; (3) formal
semi-structured interviews with 30 members of the aquaculture communities of
Virginia and Florida; and (4) a questionnaire of aquaculture producers in Florida
(n=78; response rate = 19%). Primary findings from this study indicate that
individuals are more likely to comply with regulations (1) when regulatory
enforcement personnel are perceived as being knowledgeable; (2) when farmers have
a desire to maintain a good reputation with other members of the industry; (3) when
farmers have a strong sense of guilt associated with not complying with regulatory
directives; and (4) that the expression of compliance motivations, such as reputational
concerns and feelings of guilt, is contingent upon a variety of factors, including the
desire to protect the natural environment, prevent consumers from becoming ill as a
result of eating a contaminated product, and prevent conflict with neighbors and other
resource users.
This abstract accurately represents the content of the candidates thesis. I recommend
its publication.
ABSTRACT
Signed
Tanya Heikkila
Chris Weible


DEDICATION
I dedicate this dissertation to my parents, Muhammad and Maryam Shaukat, who
gave me an appreciation for learning, always encouraged me in my goals, and taught
me the value of perseverance and hard work. I also dedicate this to my husband, Oran
Day, for his unwavering support and encouragement.


ACKNOWLEDGEMENTS
I want to express my sincere gratitude to the chairs of my dissertation committee,
Chris Weible and Tanya Heikkila for sharing their knowledge with me and for so
generously offering their time and support. I also wish to thank Christine Martell,
John Brett, and Elinor Ostrom for their valuable participation and insights. Finally, I
wish to thank Anu Ramaswami and the UCD IGERT program (Grant #: DGE-
0654378).
Support for this research was provided by the National Science Foundation (Grant #:
0721067)


TABLE OF CONTENTS
List of Tables...............................viii
CHAPTER
1. INTRODUCTION................................1
2. BUNDLING REGULATORY INSTRUMENTS: AN ANALYSIS
OF THE U.S. AQUACULTURE INDUSTRY...........43
3. DIAGNOSING REGULATORY STRINGENCY USING THE
INSTITUTIONAL GRAMMAR TOOL: A COMPARATIVE
ANALYSIS OF U.S. AQUACULTURE POLICIES......76
4. THE CULTURE OF COMPLIANCE: CONTEXTUALIZING
GUILT, SOCIAL DISAPPROVAL, AND FEAR OF MONETARY
SANCTIONS.................................110
5. RULES AND DECISION MAKING: UNDERSTANDING THE
FACTORS THAT SHAPE REGULATORY COMPLIANCE..151
6. CONCLUSION................................190
APPENDIX
A: SUMMARIZING INSTITUTIONAL GRAMMAR
CHARACTERISTICS...........................201
B. NAS AC STUDY INTERVIEW QUESTIONS..........204
C. NASAC STUDY QUESTIONNAIRE.................208
D. BROADER STUDY INTERVIEW QUESTIONS.........215
E. BROADER STUDY QUESTIONNAIRE...............218
F. SUPPLEMENTARY ORDERED LOGISTIC REGRESSION
ANALYSES..................................224
G. ORDINARY LEAST SQUARES REGRESSION RESULTS.227
BIBLIOGRAPHY.........................................229
vii


LIST OF TABLES
Table 1.1: Primary independent variables................................... 19
Table 1.2: Additional analytical variables relating to compliance.......... 20
Table 1.3: Concept measurement: primary independent and dependent
variables....................................................... 22
Table 1.4: Most-similar case study design: case selection variables........ 30
Table 1.5: Summary of data collection steps................................ 37
Table 2.1: Summary of Interview Findings................................... 64
Table 2.2: Descriptive Results Per Regulatory Factor....................... 67
Table 2.3: Correlations between regulatory factors and compliance.......... 69
Table 3.1 Types of data generated for each IGT syntactic component....... 94
Table 3.2: Summary of coded Deontic and Or else data...................... 97
Table 3.3: Summary of coded Attribute and Deontic data...................... 103
Table 4.1: Sampling of Q-Sort statements Florida aquaculture producers.. 132
Table 4.2: Comparative summary of interview findings....................... 138
Table 4.3: Summary of q-sort results: agreement between prescribed and
actual behavior................................................... 140
Table 4.4: Contingent compliance motivations................................. 142
Table 5.1: Propositions for testing compliance motivations................... 162
Table 5.2: Analytical variables and related operationalizations in
questionnaire..................................................... 170
viii


Table 5.3: Breakdown of interview responses regarding compliance
motivations........................................................ 175
Table 5.4: Kendalls Tau bivariate correlations between regulatory based
compliance motivations and individual and community based
motivations and compliance.................................................... 177
Table 5.5: Model 1: Ordered logistic regression for regulatory based
compliance motivations and compliance.............................. 179
Table 5.6: Model 2: Ordered logistic regression for individual and community
based motivations and compliance................................... 180
Table 5.7: Model 3: Ordered logistic regression for significant predictors from
table 5.5 and table 5.6 and compliance............................. 182
IX


CHAPTER 1: INTRODUCTION
Establishing effective governance necessitates understanding the relationship
between human behavior and institutions, such as policies, laws, and regulations. This
dynamic relationship is informed primarily by three factors: (1) the design of
institutions; (2) the mechanisms established to enforce these institutions; and (3) the
internal and externally based motivations that influence how individuals interpret and
choose to respond to institutional directives. Institutions structure the behavioral
opportunities and constraints available to individuals according to the objectives of
their designers in an effort to achieve desired outcomes (Ostrom 2005; Pierson, 1993,
598; Kiser and Ostrom, 2000, 66-67; March and Olsen, 2006). Enforcement of these
institutions is context dependent and can be conducted via governmental or
community based mechanisms. Ultimately, whether individuals choose to comply
with institutions is dependent upon their internal valuations regarding the costs and
benefits of compliance considering motivations emerging from institutional,
individual, and community contexts. An examination of compliance thus requires a
concerted analysis of motivations emerging from each of these realms. This
dissertation presents findings from a study to assess compliance motivations within
the context of aquaculture in two states, Virginia and Florida.


Three scholarly lenses are relevant for this study: (1) Policy Design to
examine the structure of policies; (2) Regulatory compliance to understand
discrepancies between regulatory policies and the behavior actually exhibited by
individuals; and (3) the Institutional Analysis and Development (IAD) Framework to
identify behavioral motivations that may affect institutional compliance. The IAD
framework also houses the Institutional Grammar Tool (IGT). The IGT is an
approach to policy analysis that offers the ability to systematically parse the
constitutive elements of institutions and illuminate institutional design characteristics.
Each of the three lenses identified above was jointly applied to provide analytical
guidance as well as a model of the individual from which research questions and
propositions were derived. By coupling the IAD framework with the regulatory
compliance literatures, the researcher was able to draw upon a broader stock of
empirical research that points to analytical variables that have been demonstrated to
influence compliance behavior. Also identified through the pairing of these two
literatures is a model of the individual that characterizes specific tendencies of actors
in relation to the variables chosen for analysis (Ostrom, 2007, 26).
This dissertation involved a comparative most-similar case study design of
aquaculture communities in two states: Virginia and Florida. Aquaculture is an
expanding and increasingly regulated industry in which community members are
asked to adapt their behaviors to meet the criteria of various state and federally
2


initiated regulations (Ackefors et al., 1994). Data were collected using a mixed-
method approach in four stages:
Stage 1: A preliminary study involving interviews (n=l 0) and a questionnaire (n=32;
response rate = 57%) of members of the National Association of State
Aquaculture Coordinators;
Stage 2: A comprehensive coding of all state level regulations governing aquaculture
in each study state;
Stage 3: Formal semi-structured interviews with 30 members of the aquaculture
communities of the two states; and
Stage 4: A questionnaire of aquaculture producers in Florida (n=78; response rate =
19%).
In the following sections of this introduction, a literature review will be
presented which discusses key aspects of policy design, regulatory compliance, and
the IAD framework as they relate to one another for the proposed study, followed by
a presentation of the research questions and propositions guiding this study, a detailed
discussion of the data collection and sampling methods employed, a discussion of the
theoretical, methodological, and practical significance of the study, and finally, a
brief overview of the organization of the dissertation. The body of this dissertation
consists of four stand alone chapters that address the research questions posited in this
introduction through an analysis of collected data.
3


Literature Review
Policy Design
In democratic societies, policies reflect the collective output of multiple actors
as represented in policy debates, voting, and other community engagement
mechanisms through which constituents are asked to express their political values and
goals (Bobrow and Dryzek, 1987, 18-19; Pressman and Wildavsky, 1973). The
collective output is articulated in a set of prescribed actions, the performance of
which, serve as a means to achieve desired outcomes. Policies are dynamic through
periodic adjustment and revision in response to the variable demands from
constituencies (Peters and Pierre, 1998) and other actors involved in the policy
process (Bobrow and Dryzek, 1987, Schneider and Ingram 1997; Schneider and
Sidney, 2009). Bobrow and Dryzek (1987) articulate these points: Policy designs,
like any type of design, involves the pursuit of valued outcomes through activities
sensitive to the context of time and place.. .Policy design faces a messier world of
multiple unclear and conflicting values, complex problems, dispersed control, and the
surprises that human agents are capable of springing. (Bobrow and Dryzek, 1987,
18-19)
Scholars have studied policy design from a variety of angles to explore the
ways in which policies respond to, and affect, political, social, and bio-physical
contexts. Initially led by Dahl and Lindblom (1953), the discussion centered on how
various forms of policies were being used by governments to reach political goals
4


(Dahl and Lindblom, 1953; Schneider and Ingram, 1997, 69). Others have sought to
identify the different policy instruments applied by policy makers in different policy
contexts (Bardach, 1980; Salamon, 1989; May, 1991, 187; Sidney, 2007).
Lowi (1964; 1972) characterized policies as consisting of one of the following
four types based on the content of the policy and the political organization of actors
involved with its development: Distributive, Regulatory, Redistributive, and
Constituent (Lowi, 1964). Lowis policy typography has been criticized for
characterizing policy types as being mutually exclusive and also for focusing on the
ways that politics determine policies without also considering how institutions and
political culture shape policies (Heinelt, 2007, 111-112). However, despite criticisms,
Lowis typology offers a generally useful categorization. Of particular interest for this
study is regulatory policy. Regulatory policies are generally those that seek to
regulate behavior by stipulating limits or controls on acceptable behavior and/or
activities. Speaking to the foundational aspects of regulatory policy design, Meier
(2000) writes: Regulatory policies affect policy through normal mechanisms of
policy implementation. Another policymaker, in this case usually Congress, sets
general guidelines on regulatory policy and agencies expand these general guidelines
into specific policy actions (Meier, 2001, 72).
Regulatory policies are supported by a regulatory system, including law
enforcement personnel and courts, meant to ensure that policy directives are carried
out and responded to in the manner prescribed that is, that compliance with policies
5


is achieved. The underlying assumption is that law abiding citizens are expected to
follow the prescriptions embodied within these documents. It is further expected that
disagreement with them be voiced in accordance with formal governmental
procedures that engage policy makers and other citizens of the community. Bardach
and Kagan (1982) summarize this point:
The basic techniques of these regulatory programs have been the legislation of rules
of law specifying protective measures to be instituted by regulated enterprises and the
enforcement of those rules by government inspectors and investigators, who are
instructed to act in accordance with the terms of these regulations, not on the basis of
their own potentially arbitrary judgment. But uniform regulations, even those that are
justifiable in the general run of cases, inevitably appear to be unreasonable in many
particular cases (Bardach and Kagan, 1982, 3).
As is expressed by Bardach and Kagan, numerous empirical examples exist to
demonstrate that the ideal situation they describe is very rarely achieved (March and
Olsen, 2006; Schneider and Sidney, 2009; Linder and Peters, 1992) and many policy
design scholars have sought to explore the connection between policies and the
contexts in which they are derived from, and for, in instances in which individuals or
the policies themselves fail to meet ideal expectations (Sidney, 2007; May, 1991;
Linder and Peters, 1989; Bobrow and Dryzek, 1987). For example, Steinberger
(1980) argued that manifested in individuals behavior is their interpretation and the
meaning they assign to a particular policy (Steinberger, 1980; Schneider and Ingram,
1997). Other scholars look to motivations such as enforcement practices (Burby and
Paterson, 1993; Gray and Scholz, 1993; Helland, 1998; May, 2005), the perceived
technical competence of regulatory agents (Bardach and Kagan, 1982), and the
6


presence of trust between enforcement personnel and those they are regulating
(Scholz and Lubell, 1998).
This discussion of policy design is meant to display the various ways that
policy design scholars have examined how policies structure, and are structured by,
the behavior of constituents interacting in relation to particular policy area. For the
purposes of this study, policy designs are characterized as the institutions that policy
designers use as a vehicle to achieve desired outcomes by prescribing within them a
set of opportunities and constraints available to different community actors. The
degree of congruency between prescribed behavior articulated within policies and
actual behavior exhibited by individuals is assessed in light of the ways in which is it
informed by various internally and externally derived factors. Such compliance
motivations will be discussed more thoroughly in the following section on regulatory
compliance.
Regulatory Compliance
As previously asserted, compliance is one of the primary goals associated with
regulatory policies. As May writes, The typical policy is a package of policy
instruments aimed at some combination of gaining compliance through the use of
mandates, improving short-term performance through the use of incentives,
enhancing longer term performance through various capacity building measures, or
altering the system for providing goods and services by introducing system changes
(May, 1991, 199). When significant efforts are made by policy designers to ensure
7


that compliance is achieved, cases on non-compliance incite inquiry as to what
motivates individuals to not comply with policy directives. Three types of
motivations identified by regulatory scholars as being particularly influential in
shaping compliance that were explored in this study are: a fear of monetary sanctions,
personal guilt or shame, and social disapproval.
The classic regulatory deterrence model is premised upon the assumption that
legal sanctions suffice to thwart the desire for non-compliance on the part of
regulated agents. Consistent with the rational actor model of the individual (Hatcher,
2000), regulated actors from this perspective are considered self utility maximizing
agents in which the incentive to maximize benefits, or conversely, to not bear
excessive costs, is the sole motivator guiding individuals decision making processes.
As such, sanctions administered through a regulatory entity are viewed as the primary
coercive mechanism for fostering regulatory compliance (Zimring and Hawkins,
1973; Bentham, 1789; Becker, 1968).
Increasingly, empirical research in the regulatory field that draws upon
scholarship from Sociology and Social Psychology (Elster, 1989; Coleman, 1990;
Ajzen, 1988) has shown that a variety of other factors contribute to regulatees cost-
benefit estimations regarding when to comply with regulatory directives (Hatcher et
al., 2000). Additional factors include social sanctions and influence, or social
disapproval (Sutinen and Kueperan, 1999; Braithwaite and Makkai, 1991), and
feelings of personal shame or guilt (Grasmick and Bursik, 1990). Hatcher et al.
8


(2000), for example, found that social pressures served as an effective deterrent to
non-compliance relating to catch quotas, or individual fishing quotas, in the United
Kingdom. Similarly, Kuperan and Sutinen (1995) have explored the relationship
between compliance and feelings of moral obligation among regulatees regarding
fishery zoning regulations in Malaysia. Research focusing on individual or
community based factors in the regulatory scholarship has been limited to date,
however, and many areas remain to be explored regarding socially based compliance
motivations.
Regulatory scholars have also studied a number of political/regulatory
variables in understanding factors that influence compliance, including: enforcement
practices, specifically, frequency of inspections (Burby and Paterson, 1993; Gray and
Scholz, 1993; Helland, 1998; May, 2005), belief congruency between regulators and
regulates regarding the way an industry should be managed (May, 2005; Bardach and
Kagan, 1992), technical competence of the regulatory agency as perceived by
members of the industry (Bardach and Kagan, 1982), and the presence of trust
between the two types of actors (Scholz and Lubell, 1998).
Presented within this brief overview of regulatory literature is a distinction
between regulatory based compliance motivators, such as sanctions administered by
an outside agency, and individual and community based motivators, such as guilt and
social disapproval that, together, inform the behavior exhibited by individuals. The
latter emerge from the experiences and interactions between actors in a given
9


regulatory domain. These individual and community-derived motivations are a
product of the bio-physical and social context in which actors are housed. An
institutional approach is best suited to understand the institutions that structure the
behavior of various actors, and individuals responses to them, as a result of these
bio-physical and social contexts (Ostrom, 2005). The institutional lens used in this
study was the institutional analysis and development (1AD) framework.
Institutional Analysis and Development (IAD) Framework
The institutional analysis and development (IAD) framework provides a
structured approach for mapping out the institutions that govern actions and outcomes
within collective action arrangements (Ostrom, 2007). The structure of the action
space in which individuals interact is presumed to be a product of three inter-related
variables, including the rules [institutions] used by participants to order their
relationships, attributes of the biophysical world, and the structure of the more
general community within which any particular arena is placed (Ostrom, 2005, 15).
Within this context, individuals actions are presumed to be influenced by the types of
participants involved, their relative positions within a community, potential
behavioral outcomes, perceived action-outcome linkages, the amount of control that
participants can exercise in affecting these linkages, information flows, and the costs
and benefits assigned to actions and outcomes (Ostrom, 2005, 14).
Within the IAD framework, individual behavior is examined in relation to the
institutions by which it is informed. Institutions are understood to be contextual in
10


nature and interactive with the various cultural and biophysical attributes of the
arenas in which they are applied (Ostrom, 1994). Further, institutions are generated
by actors to structure their behaviors and participant roles and responsibilities.
Ostrom (1994) writes that, Rules [institutions] are the result of implicit or explicit
efforts to achieve order and predictability among humans by creating classes of
persons (positions) who are then required, permitted, or forbidden to take classes of
actions in relation to required, permitted, or forbidden states of the world (Ostrom et
al., 1994, 38). Sometimes these institutions are formalized into policies. Consistent
with the policy design and regulatory literatures it is through this process that
constraints and opportunities are formally structured and supported by state imposed
enforcement and judicial mechanisms.
The IAD framework offers a distinction between rules-in-form and rules-
in-use, which are also referred to as institutions-in-form and institutions-in-use
in this dissertation. This is because institutions can exist in the form of rules, norms,
and strategies. Thus, the terms institutions-in-form and institutions-in-use are
more encompassing of different types of institutional directives. Institutions-in-form
are those which have been codified in formal documents such as policies, laws, and
regulations. Comparatively, institutions-in-use are articulated in social patterns of
behavior (Ostrom, 2007). Over time, these institutions-in-use are recognized by
individuals so as to structure their interactions with another in daily life to foster
reciprocity, expected action-outcome linkages, and resource management techniques.
11


A variety of internal and externally based motivations are presumed to animate
individuals decision making behavior in relation to institutional directives (Crawford
and Ostrom, 1995).
Decision making can occur at multiple nested levels, where decisions and
institutions designed at one level structure the opportunities and constraints available
to actors at other levels (Ostrom, 2005, 57). Levels of decision making are
categorized as metaconstitutional, constitutional, collective choice, and operational.
According to Ostrom (2005):
Operational rules directly affect day-to-day decisions made by the participants in
any setting. These can change relatively rapidlyfrom day to day. Collective choice
rules affect operational activities and results through their effects in determining who
is eligible to be a participant and the specific rules to be used in changing operational
rules. These change at a much slower pace. Constitutional choice rules first affect
collective-choice activities by determining who is eligible to be a participant and the
rules to be used in crafting the set of collective choice rules that, in turn, affect the set
of operational rules (Ostrom, 2005, 58).
Relevant for this study is understanding how institutions-in-form developed at the
collective choice level are interpreted and responded to by individuals at the
operational choice level and how internally and externally derived motivations shape
this relationship. In other words, how do individuals interpret and respond in their
daily behaviors to institutions designed at the state level by regulatory bodies?
Internal and External Motivations and Related Model of the Individual
The discussion of internal and external motivations as it pertains to this study
is centered on their ability to explain the behavior exhibited by individuals.
12


Specifically, the internal motivations that were studied herein include (1) the personal
shame or guilt that actors may feel from not complying with institutions-in-form, and
the external motivations include (2) social disapproval, which arises from actors
desires to establish a positive reputation with other actors (Ostrom, 2005, 146-147)
and (3) fear of incurring monetary sanctions.
The internal and external motivations regarding compliance studied herein are
consistent between the IAD and regulatory literatures in that both consider the
influence of the fear of monetary sanctions, peer pressure, and feelings of personal
guilt or shame in influencing compliance outcomes (Frey, 1994; Bendor and
Mookherjee, 1990; Crawford and Ostrom, 1995). This list of factors is certainly not
exhaustive in either of these literatures. The researcher has chosen to focus on these
factors in particular as they are explicitly stated in the IAD literature as being
influential in shaping individuals response to institutions (Crawford and Ostrom,
1995; Ostrom, 2005; Speer, 2010).
The discussion of these particular motivators in relation to one another from
the perspective of each is cast around a model of the individual that assumes
individuals are boundedly rational and that the individuals who calculate benefits
and costs are fallible learners who vary in terms of the number of other persons
whose perceived benefits and costs are important to them and in terms of their
personal commitment to keeping promises and honoring forms of reciprocity
extended to them (Ostrom et al., 1993, 45). From a regulatory perspective this model
13


of the individual contrasts with the rational actor model upon which the classical
regulatory deterrence approach is premised. From an institutional perspective, this
view of the individual contrasts with rational choice institutional models that view
actors as having static preferences and behavior solely as a product of externally
provided constraints, information, and outcome possibilities, while neglecting
socially, or community, derived motivations (McCay, 2002; Shepsle, 2006, 24-25).
It is assumed, thus, that social pressure and material and non-material rewards
all factor into community members decision making processes. Additionally, the
types of enforcement and sanctioning mechanisms chosen by an authoritative body
may also influence how individual actors rationalize decisions regarding actions and
outcomes. In other words, this choice may impact the influence of internal and
external motivations at the individual level regarding compliance. Ostrom explains
that internal and external motivations are added to an individuals payoff to
represent the perceived costs and rewards of obeying or breaking a prescription
(Ostrom, 2005, 146). As such, the decision to rely on external or internal sanctions is
largely driven by the costliness associated with each (Ostrom et al., 1994, 48). As in
any traditional cost-benefit analysis estimation, the rewards of sanctioning must be
greater than the costs of their imposition and enforcement. Crawford and Ostrom
(1995) explain:
If it is costly to monitor the actions of others and/or to impose sanctions on them,
those assigned these tasks may not be motivated to undertake these assignments
unless (1) the monitor or sanctioner face a probability of an Or else [a sanction
14


associated with not complying with an institution-in-form], (2) social pressure to
monitor and sanction is large and is salient to the monitor and sanctioner (3) The
monitor and sanctioner hold some strong moral commitment to their responsibilities,
and/or (4) The payment schemes for the monitor and sanctioner create prudent
rewards high enough to offset the costs. (Crawford and Ostrom, 1995, 589)
Thus, in order to gain a comprehensive understanding of the behavior exhibited by
actors within a community, one needs to understand the array of incentives presented
to the individual externally, as with monetary and social sanctions, as well as the
internal incentives which may manifest in personal shame or guilt associated with
non-compliance.
It is important to note that measuring the cost-benefit estimations of
individuals considering internal and external motivations is a challenging endeavor in
non-laboratory settings; that is, in a simplified social setting where the researcher may
introduce a quantifiable measure to reflect individuals cost-benefit estimations in
relation to particular activity. In field settings, the measurement of such variables is
necessarily less quantifiable and less precise.
Compliance from an IAD Perspective
Compliance within the setting of the IAD framework as it relates to this study
is characterized as conformance with institutions-in-form, e.g., state level regulations,
and is shaped by both individuals normative and material considerations emerging
from biophysical, community, and individual contexts (Ostrom, 2005, 167). In
addition to the three motivations, monetary sanctions, social disapproval, and
personal guilt or shame, other scholars studying compliance in relation to them have
15


found the following biophysical, community, and individual factors to be influential:
(1) Change in resource availability with use (Olson, 1991; Hirschman, 1985;
Mansbridge, 1994); (2) Involvement of community members in labor unions (Offe
and Wisenthal, 1980); (3) Involvement of community members in rule development
(Frey, 1994); and (4) Perceived legitimacy of rules (Ostrom, 2005). For the purposes
of this study, such variables are characterized as contingent variables, meaning that
the extent to which internal and external motivations (fear of social disapproval,
feelings of guilt, and fear of monetary sanctioning) will be expressed in individuals
decision making is contingent upon a variety of community-based, bio-physical, and
political variables, as well as individual situational and endogenous factors. For
example, interviewees in this study expressed that their primary compliance
motivation was guilt associated with non-compliance and that this guilt is rooted in a
desire to protect the natural environment. In other words, these individuals would feel
guilty from not complying with regulations as this could result in negative impact to
the environment. In this case, a desire to protect the environment would be
characterized as a contingent motivation.
The purpose of this discussion of the IAD framework is to demonstrate that it
is an appropriate lens to support an analysis of the relationship between policy
designs, regulatory compliance, and internal and external compliance motivations.
Research questions and propositions arising from the joint application of these the
16


three literatures policy design, regulatory compliance, and the IAD framework -
will be discussed in the following section.
Research Questions and Propositions
Research Questions
The following discussion provides a synopsis of how the analytical concepts
explored in this study relate to one another. Behavior exhibited by individuals is
reflective of their decision making considering institutional directives and internal
and external motivations. Contextual bio-physical and community attributes are
assumed to shape the extent to which such motivations may influence individuals
decision making, along with a variety of individual situational characteristics and
endogenous variables such as principles of justice, feelings of responsibility, and a
desire to act appropriately. These factors are characterized as contingent motivations
and are presumed to shape the expression of internal and external motivations.
Finally, the outcome of interest is the extent to which the behavior exhibited by
individuals is in compliance, or conformance, with institutions-in-form.
In line with this conceptual logic, the following research questions are
explored in this study as part of the overarching question: what motivates regulatory
compliance? The first of these is the primary research questions. The second and third
are secondary research questions.
RQp Which internal and external motivators are most influential in guiding the
behavior of community actors in relation to institutions-in-form?
17


RQi- Which contingent motivations are most influential in shaping the expression of
internal and external compliance motivations?
RQ3: How can the constitutive elements of institutions be assessed and compared?
Propositions
No explicit theory exists to inform the formulation of specific hypotheses that
can articulate directionality of the influence of the independent variables upon the
dependent variables of interest. As such, one generic proposition was offered in this
study to explain the ways and extent to which individuals behavior is influenced by
internal and external compliance motivations; specifically, a fear of monetary
sanctioning, reputational concerns, and feelings of guilt associated with non-
compliance: Social disapproval andfeelings of personal guilt or shame are more
likely to influence individuals' decision making regarding compliance than is the fear
of monetary sanctions.
Table 1.1 shows the primary independent variables considered for this study
(internal and external motivations) and the perceived influence the presence/absence
of each was expected to have on the dependent variable compliance.
18


Table 1.1 Primary independent variables
Effect on Compliance (where,
Variable Type Variable + = compliance increases with presence and = compliance decreases with
presence
Internal Motivations Personal guilt or shame +
External Motivations Monetary Sanctions +
Social Disapproval +
In addition to these variables, Table 1.2 provides a list of additional variables
that have been demonstrated to influence compliance and that were assessed in
relation to compliance in this study through interviews and questionnaires. The list
presented in Table 1.2 was collated from various applications spanning the policy
design, regulatory compliance, and IAD literatures.
19


Table 1.2 Additional analytical variables relating to compliance
Variable
Enforcement practices of regulatory enforcement personnel
Perceived technical capacity of regulatory enforcement personnel
Trust of enforcement personnel
Regular communication between regulatee and regulator regarding regulations
Perceived regulatory appropriateness
Extent to which regulations are perceived as being consistent with industry
level best management practices
Knowledge sharing among industry members regarding the
regulatory/administrative aspects of the industry
Knowledge sharing among industry members regarding the scientific/technical
aspects of the industry
Moral obligation to produce a good product
Finally, the analysis of compliance motivations in this study also examined
the types of contingent motivations that influence the expression of primary
compliance motivations. Contingent motivations were identified in an exploratory
matter and thus no variables were identified prior to data collection. A
complementary examination of these primary and contingent variables allows the
researcher to capture more analytical dimensions; the former set of variables
informing when compliance is expected to occur (Ex. When an individual fears
20


monetary sanctioning, she/he is more likely to comply with institutions-in-form), and
the latter offering an explanation as to how or why certain fixed factors interact with
the internal psychological variables of interest (external and internal compliance
motivations) as they do to produce a particular outcome (compliance) (Baron and
Kenny, 1986). In this way, the contingent variables represent the causal mechanisms
that inform the relationship between behavioral motivations and compliance. George
and Bennett (2005) describe causal mechanisms consistent with this logic: Causal
mechanisms are the independent stable factors that under certain conditions link
causes to effects [and] are central to causal explanation (George and Bennett, 2005,
8).
Concept Measurement
Table 1.3 provides a list of the primary independent and dependent variables
relevant for the proposed study. Data for each of the independent variables and the
dependent variable were collected through the preliminary National Association of
State Aquaculture Coordinators (NASAC) study, coding, interviews, and/or the
online questionnaire.
21


Table 1.3 Concept measurement: primary independent and dependent variables
Variable Research Question1 Data Collection Method Variable Measurement
IV,: Social disapproval 1,2 Interviews and Questionnaire Self-reporting of study participants in interviews and questionnaire regarding the extent to which social disapproval influences their decision making regarding compliance with institutions-in-form in relation to monetary sanctions and feelings guilt or shame.
IV2: Monetary Sanctions 1,2,3 Interviews, Questionnaire, and Coding Self-reporting of study participants in interviews and questionnaire regarding the extent to which the fear of monetary sanctions influences their decision making regarding compliance with institutions-in-form in relation to social disapproval and feelings of guilt or shame. The presence of monetary sanctions within institutions-in-form was also identified via coding.
1V3: Personal Guilt or Shame 1,2 Interviews and Questionnaire Self-reporting of study participants in interviews and questionnaire regarding the extent to which feelings of guilt or shame influences their decision making regarding compliance with institutions-in-form in relation to social disapproval and monetary sanctions.
DV,: Compliance 1,2 Interviews and Questionnaire Agreement between prescribed and actual behavior. Measurement around coding using Institutional Grammar. Ex. Percent agreement between prescribed and actual Deontics as indicated by study participants in interviews.
1 Research Questions: RQi: Which internal and external motivators are most influential in guiding the
behavior of community actors in relation to institutions-in-form? RQ2: Which contingent motivations
are most influential in shaping the expression of internal and external compliance motivations? RQ3:
How can the constitutive elements of institutions be assessed and compared?
22


Research question 3, regarding how the constitutive elements of institutions can be
assessed and compared, was addressed entirely through coding. Activities exhibited
by individuals that diverge from what is prescribed in institutions-in-form was
characterized as non-compliance; in other words, compliance was equated with
conformance with institutions-in-form, and vice-versa (Ostrom, 2005, 167). The
justification for pursuing compliance data through a questionnaire and interviews
rather than on state records is that there may be types of compliance exhibited by
aquaculturists that are not registered or detected by enforcement officials, and also
because some forms of non-compliance may appear subtle from the states
perspective but may represent important messages and/or meaning from the
perspective of aquaculturists.
Case Study
The United States currently produces approximately 20% of its seafood
consumed while importing 80%, resulting in a seafood trade deficit that exceeds nine
billion dollars (NOAA 2009). This deficit has prompted federal and state policy
makers to encourage the development of a domestic aquaculture industry. The
production of aquaculture involves consideration of complex interdependencies
among ecological, economic, technical, and social factors (Firestone, Kempton,
Krueger, and Loper 2004), resistance from the public regarding farmed seafood
(Amberg and Hall 2010; Mazur 2006), and numerous concerns about the industry
23


from disease control to degradation of marine ecosystems (Black 2001; Francik 2003;
Naylor et al., 2000; Mazur 2006; Treece 2002).
As the U.S. aquaculture industry grows, so too is the number of state level
regulations designed to govern it, taking into account all of the above factors. Similar
to regulations designed for other natural resource based industries, aquaculture
regulations tend to be fairly technical and decentralization of regulatory governance is
commonly observed (May, 2005). Such decentralization has meant that the types of
regulations and supporting regulatory mechanisms vary widely from state to state.
The receptivity of recent regulatory efforts in different state aquaculture industry
contexts also varies. When new regulations are applied in states that have well
established industries, receptivity to them depends, in part, on how consistent they are
with industry level best management practices and norms. It also depends on how
contextually appropriate regulations are perceived as being.
Given the changing nature of the regulatory environment relating to U.S.
aquaculture, it provides a theoretically interesting context within which to examine
compliance motivations as it is one that is characterized by increasing levels of state
level regulations while simultaneously representing an environment in which industry
members have demonstrated a proclivity to develop community level best practices
and norms. As such, it provides the appropriate setting for analyzing diverse
compliance motivations, including those stemming from features of the regulatory
environment as well as those that are individual and community based.
24


Research Methodology
Case Study Selection
A comparative case study design was used to address the research questions
posed for this research study in which two cases of aquaculture communities in the
United States were examined to understand cross-case and within-case variation
(Gerring, 2007, 28; Miles and Huberman, 1994; Pierson, 1993). The population of
relevance was any U.S. state which houses an aquaculture community, which
currently includes all fifty states. The selection of study cases was conducted based
on data collected through a preliminary study of state aquaculture coordinators. The
study involved a questionnaire of 56 and interviews with 10 members of the National
Association of State Aquaculture Coordinators (NASAC). The questionnaire was
administered in March 2010. Of the 56 individuals to whom the questionnaire was
sent, 32 responded, yielding a 57% response rate. In the questionnaire, NASAC
members were asked to respond to a series of questions regarding the structure of
regulatory mechanisms within their state, levels of compliance with regulatory
policies, perceived contributors to compliance, and aquaculture community
characteristics. The overall purpose of this study was to glean an understanding of the
regulatory landscape within each U.S. state in order to provide a basis upon which to
compare them on the independent and dependent variable dimensions relevant for the
broader dissertation study.
25


George and Bennett (2005) state that one of the requirements for conducting
sound case study research is ensuring that the variables chosen for inclusion in the
analysis be of theoretical interest for purposes of explanation (George and Bennett,
2005, 69). Currently, no single causal theory of institutional compliance exists to
specify key variables and case parameters with which to guide an analysis. Ostrom
(2005) states, The development and use of theories enable the analyst to specify
which components of a framework are relevant for certain kinds of questions and to
make broad working assumptions about these elements. Thus, theories focus on parts
of a framework and make specific assumptions that are necessary for an analyst to
diagnose a phenomenon, explain its process, and predict outcomes (Ostrom, 2005,
28). To remind, the primary independent variables in this study (fear of monetary
sanctions, fear of social disapproval, and feelings of personal guilt or shame) are
identified by Sue Crawford and Elinor Ostrom (1995; 2005) in relation to the
Institutional Grammar Tool and related discussion of internal and external
compliance motivations. Additionally, many of the additional variables examined in
this study are also are identified in the IAD framework as being key variables
supporting an institutional analysis, including: institutional and/or social/community
attributes. The remaining variables were identified based on a review of the
regulatory compliance literature, and include: political/regulatory characteristics,
individual situational characteristics, and endogenous factors.
26


The type of behavior that was singled out for examination in this study was
compliance with state-level aquaculture regulations. Of central interest was
understanding a lack of variation in compliance outcomes factoring variation on one
independent variable. This type of design is characterized as a most-similar case
study design. In such a design, the cases chosen for comparison share similar qualities
on all variables, except one identified as being of theoretical interest (Gerring, 2007,
131). Typically, variation is sought on the dependent variable, though it is also
possible to have variation on the independent variable (Gerring, 2007). A most-
similar research design allows the analyst to hold multiple variables constant to allow
for the ability to consider additional intervening factors that influence the relationship
between independent and dependent variables.
For the study, similarity was sought on all variables except state level
regulations, specifically considering regulatory stringency. That is, those cases were
selected that exhibit varying degrees of regulatory stringency while sharing similar
characteristics in all other relevant respects, including compliance outcomes.
Regulatory stringency, characterized as a measure relating to institutions-in-form,
was central to the analysis and thus selected as the varying factor. For example, two
of the primary independent variables (feelings of shame or guilt associated with non-
compliance with institutions-in-form and monetary sanctioning) as well the primary
dependent variable (compliance with institutions-in-form) are all anchored on this
27


factor. In other words, each of these variables has a direct analytical and operational
linkage to institutions-in-form.
Additionally, due to the nature of the data being used for case selection,
regulatory stringency was deemed an appropriate choice for the varying factor as this
information is easily conveyed by state aquaculture coordinators describing state level
characteristics. This contrasts, for example, with individual situational characteristics
and endogenous factors for which aquaculture coordinators may be able to provide a
general sense but not individual level data. Since this type of data was not obtainable
through the questionnaire, these factors were not an appropriate choice upon which to
select cases. However, it was possible to obtain information from the questionnaire
responses that represent characteristics of the bio-physical setting, general views
regarding the political/administrative aspects of the state regulatory system, as well as
industry dynamics.
A first step in the selection of cases involved identifying how the states
represented in the preliminary NASAC study compared. Data were sorted and
analyzed to allow for a comparison on the variables of interest. For each of the
variable categories (e.g. biophysical attributes, political/regulatory characteristics,
etc.), the two cases were compared on at least one dimension. These dimensions were
captured in one of the questionnaire items posed to respondents from the NASAC
study, with each dimension corresponding with one item. Internal and external
28


motivations were not included as case selection variables as this information must be
obtained from individuals in communities.
The selection of cases was conducted in a stratified manner. From the full
sample of 30 cases, those cases were first selected that exhibited the maximum
amount of variation in terms of regulatory stringency; for example, those cases in
which regulations were either reportedly very stringent or very non-stringent. Next,
the states were compared in relation to regulatory compliance. The sample of cases
was then further narrowed by selecting those cases which were reported to have high
to very high compliance with aquaculture regulations. The remaining cases were then
compared across other dimensions such as political regulatory characteristics,
biophysical characteristics, and social, community, and industry characteristics. Two
sets of two states exhibited opposing levels of regulatory stringency, very high
compliance with aquaculture regulations, and similar characteristics on several other
dimensions: Hawaii and Pennsylvania and Virginia and Florida. From these two
options, Virginia and Florida were chosen as the two cases for the proposed study. In
addition to comparability on theoretical variables, these states are comparable in
additional ways, including, the types of aquaculture produced, the presence of both
marine and inland aquaculture, and the relative establishment of the aquaculture
industry. Virginia and Florida were also considered to be comparable due to their
geographic proximity and shared regional characteristics as compared to
29


Pennsylvania and Hawaii, Table 1.4 displays how the two states compare across the
variables of interest.
Table 1.4 Most-similar case study design: case selection variables
Case One: Virginia Case Two: Florida
Institutions-in-Form
Regulatory Stringency Non-Stringent Regulations Very Stringent
Political and Regulatory Factors
Regulatory Clarity Very Clear Regulations Very Clear Regulations
Permitting Costs Inexpensive Permits Inexpensive Permits
Industry involvement in Reporting Non-Compliance Moderate Involvement Moderate Involvement
Regulatory Clarity as a Contributor to Compliance Significant Contributor Significant Contributor
Strong Penalties as a Contributor to Compliance Mild Contributor Mild Contributor
Industry Trust of Monitoring and Enforcement Officials as a Contributor to Compliance Moderate Contributor Moderate Contributor
Social, Community, and Industry Factors
Start Up Costs as a Barrier to Aquaculture Development Significant Barrier Significant Barrier
Stringent Environmental Protection Regulations and Safeguards as a Barrier to Aquaculture Development Moderate Barrier Moderate Barrier
30


Table 1.4 (Cont.)
Case One: Virginia Case Two: Florida
Social, Community, and Industry Factors
Complicated Regulatory Process Associated with Obtaining Permits, Licenses, Etc. as Barrier to Aquaculture Development Minor Barrier Minor Barrier
Domestic Competition as a Barrier to Aquaculture Development Moderate Barrier Moderate Barrier
Local User Conflicts as a Barrier to Aquaculture Development Minor Barrier Minor Barrier
Bio-physical Attributes
Resource Constraints as a Barrier to Aquaculture Development Significant Barrier Moderate Barrier
Compliance
Compliance with Aquaculture Regulations Very High Compliance with Aquaculture Regulations Very High Compliance with Aquaculture Regulations
31


As stated by George and Bennett, selecting cases that are identical in all
characteristics, especially at the state level, is challenging and is rarely possible. As
such, many researchers must choose cases that are identical on some variables and
similar on others. This is the method chosen in the case selection procedure for this
study. As may be noted in Table 1.4, all of the variables, except that relating to bio-
physical attributes, are reportedly identical. For the latter, the criterion was that the
variables be characteristically similar. Resource constraints are a barrier to
aquaculture development in both cases, but more so in Virginia than Florida.
To corroborate findings from the NASAC data, informal interviews with three
NASAC members were conducted to ensure that the cases were appropriate
selections given the researchers analytical objectives. In these interviews, the
research objectives of this study were described, including explaining the desire to
compare two U.S. states that share similar characteristics but differ with regard to
regulatory stringency. Discussions with these individuals revealed that these cases
were well suited for the proposed analysis.
Methods of Data Acquisition and Sampling
Once the case study states were selected, data for the study were collected in
the following steps and for the following purposes. First, all state level aquaculture
regulations for each of the selected study states, Virginia and Florida, were coded in
their entirety in accordance with the IADs Institutional Grammar Tool (IGT). In
addition to providing a systematic means through which to understand the content of
32


these regulations, the IGT was applied in this study to demonstrate the Tool's
applicability in conducting comparative institutional analyses and to see if it may be
applied as a diagnostic tool to discern the regulatory stringency of institutions.
The IADs Institutional Grammar Tool was first proposed by Crawford and
Ostrom (1995) as a tool with which individuals conducting analysis using the I AD
framework can systematically identify and code institutions. The Tool is applied to
examine institutional documents, such as policies and laws, by dividing phrases from
the document into individual statements and dissecting these statements in accordance
with six syntactic elements (please see Appendix A for a summary on institutional
grammar characteristics):
Attribute [A], the actor to whom the statement applies;
oBjectx[B], the animate or inanimate receiver of action within the statement;
Deontic [D], the prescriptive operator that indicates whether the focal action
of the statement may, must, or must not be performed;
aim [I], the action of the statement;
Condition [C], the temporal, spatial, or procedural boundaries in which the
action of the statement is or is not to be performed; and
Or else [OJ, the punitive sanction associated with not carrying out the
statement directive as prescribed.
In the Grammar, there are three necessary conditions for a phrase to constitute an
institutional statement. Each institutional statement must contain at minimum an
Attribute, an Aim, and a Condition. The Deontic and Or else component may be
1 The original grammar did not include the Object as an institutional statement component. The Object
was introduced by Siddiki et al. (2011) in an effort to clarify coding guidelines and enhance the
applicability of the institutional grammar tool.
33


present but are not necessary to qualify a phrase as an institutional statement. Those
statements which contain each of the aforementioned components are characterized as
rules (ABDICO), while statements containing the first five components (ABDIC) are
characterized as norms, and statements only containing an Attribute, Aim, Condition,
and/or oBject (A1C/ABIC) are considered to be shared strategies.
Once an analyst has coded all of the institutional statements within a given
document, data for each syntactic element can be aggregated so as to portray a
complete depiction of the target audiences of the institution, the actions associated
with them, conditions specifying the performance of these actions, and sanctions
associated with non-compliance. Doing so gives a more general illustration of how
institutional statements are configured within an institution to reflect the roles and
responsibilities of various actors as intended by the institutional designer(s).
Next, formal semi-structured interviews were conducted with members of the
aquaculture communities of Virginia and Florida (n= 30 or 15 per state). Crawford
and Ostrom (2005) argue that qualitative methods such as in-depth interviews are
required to undercover the institutional bases that inform behavior (Crawford and
Ostrom, 2005, 171). Interviews for this study consisted of two parts: In the first part,
interview participants were asked to respond to a series of questions included in a pre-
designed interview protocol meant primarily to capture their compliance motivations.
In the second part, participants were asked to participate in a Q-Sort exercise. The Q-
34


Sort exercise was designed to capture data pertaining to compliance behavior and
compliance motivations.
Twenty-two of the 30 interviews were conducted in-person and 8 were
conducted via telephone. In Florida, a regulatory official provided a list of 50 names
of aquaculture producers to the researcher to contact for participation in the study,
from which 15 were randomly selected and agreed to participate. In contacting
individuals from this list it was evident that the regulator randomly selected these
individuals from a list of Florida aquaculture producers as those contacted expressed
varying degrees of familiarity with the state regulators. For Virginia, the researcher
randomly selected participants from a directory of Virginia aquaculture producers.
The final sample of interview participants across the two states consisted of 18
shellfish producers, seven regulatory officials, two ornamental fish producers, two
aquaculture processor/handler and ornamental fish producers, and one shellfish and
finfish producer. In Virginia, two of the 15 individuals interviewed were regulators
while the rest were aquaculture producers or processors/handlers. In Florida, four of
the 15 individuals interviewed were regulators while the rest were aquaculture
producers or processors/handlers.
Finally, an online questionnaire was administered to aquaculture producers in
Florida (n=78; response rate = 19%)2. Aside from offering an additional data
2 An online questionnaire was also administered to aquaculture producers in Virginia. However, very
few individuals responded, precluding the inclusion of findings from the questionnaire in this study.
35


collection technique, the observed value and limitations of using a questionnaire to
capture data regarding behavior was examined. Questionnaires are a useful
methodological strategy for testing causal relationships identified in three-variable
hypotheses (Shoemaker et al., 2004, 70, 83) and may be used to support analytic
generalizability across the selected cases (Yin, 2003, 32-33). However, questionnaires
alone are not sufficient to comprehensively capture the information desired. As such,
the questionnaire in this case was used primarily to triangulate data collected through
interviews.
The online questionnaire was administered in the spring and summer of 2011
to 415 aquaculture producers in Florida State. These 415 producers represent the
entire population of aquaculture farmers in Florida registered and licensed with
current email addresses under the Florida Department of Agriculture and Consumer
Services (FDACS) to practice aquaculture. The email addresses of these individuals
were provided to the author by a regulatory official at the agency. Of the 415
aquaculture producers to whom the questionnaire was sent, 78 responded yielding a
19% response rate. The respondent sample included 23 finfish producers, 17
ornamental fish producers, 12 aquaculture processor or handlers, 10 shellfish
aquaculture producers, 3 individuals who are both aquaculture processor or handlers
The researcher contacted the State Aquaculture Coordinator of Virginia to inquire about possible
reasons for the low response rate. She was informed that multiple surveys were administered to VA
aquaculture producers around the same time, and asking similar types of questions, possibly leading to
confusion or fatigue among the producers.
36


and shellfish producers, 2 individuals who are both aquaculture processor or handlers
and finfish producers, 1 ornamental and finfish producer, 1 aquaculture processor or
handler and alligator producer, and 9 individuals involved in miscellaneous aspects of
aquaculture (e.g. live rock, experimental aquaculture, etc.). Though the sample was
limited, the respondents appropriately reflect the range of aquaculture participants in
the Florida industry which is comprised predominantly of shellfish, finfish, and
ornamental fish producers (UDSA, 2006).
Table 1.5 provides a summary of the data collection steps employed in this
study.
Table l .5 Summary of data collection steps
Data Collection Step Procedural Detail Schedule
Step 1: Preliminary study to provide a broad depiction of the regulatory landscape for U.S. aquaculture and to identify an appropriate sample of cases for the broader dissertation study. Interviews with 10 and questionnaire of all 56 coordinator members of the National Association of State Aquaculture Coordinators (NASAC) (questionnaire response rate = 57%). Fall 2009 and Winter 2010
Step 2: Coding of regulatory documents to dissect and compare institutions of stringent and non- stringent states. Coding of all state level aquaculture regulations in Virginia and Florida in accordance with IAD Institutional Grammar Tool. Summer 2010
Step 3: Formal semi-structured interviews with members of the aquaculture community to understand motivations of compliance. Interviews with 30 members of the aquaculture communities of Virginia and Floirda. Fall 2010
Step 4: Administration of online questionnaire to aquaculture producers in Florida to understand motivations for compliance from a larger population. Administered survey to 415 aquaculture producers in Florida (response rate = 19%). Spring and Summer 2011
37


Theoretical, Methodological, and Practical Significance of Study
This research brings together a macro and microscopic lens for understanding
the institutions and motivations that govern the behavior of individuals in aquaculture
communities. At the microscopic level, IGT was used to understand the constitutive
elements that comprise institutional statements presented within policies and compare
institutional design characteristics across the two study states. The IGT was coupled
with other data collection techniques, including interviews and a questionnaire, to
understand behavior at a macroscopic level, including the ways in which participants
interact with one another, and how the roles and relationships between them lead to
certain actions and outcomes. Theoretically, by complementarily drawing upon
research relating to policy design, regulatory compliance, and the IAD framework,
the research shows how regulatory, individual, and community based factors
complementarily influence the behavior of community members.
Methodologically, the analytical capacity of the IGT toward comparative
institutional analysis was examined. This was done by demonstrating its utility as a
diagnostic tool for assessing regulatory stringency across institutional contexts.
Further, the study combined data collection methods that have rarely been used in
similar applications of the IGT. Typically, the IGT is used exclusively to identify
institutional statements present in formal documents, such as policies and laws, upon
which qualitative cluster analyses are subsequently conducted to summarize coding
results (Basurto et al, 2010). For example, Basurto et al. (2010) used this method to
38


code and analyze U.S. transportation policy and abortion policy in the State of
Georgia. In this dissertation, the IGT was applied alongside other data collection
forms, such as a questionnaire and interviews, to understand compliance behavior.
Such an application builds off the work of Speer (2009), in which she used a similar
approach to study participatory governance legislation in Guatemalan municipalities.
Practically, the study offers insights regarding how aquaculture community
members are responding to aquaculture directives. Such insights are useful for local
and non-local policy makers who are designing policies that meet the needs of
aquaculture constituencies in a way that is appropriate and effective. For example,
they provide an indication of the extent to which different types of regulatory
mechanisms will be effective in promoting compliance based on an assessment of the
compliance factors found to be most influential to aquaculture producers.
Organization of Dissertation
Four analytical chapters are included herein in which different sets of data
collected throughout this study are examined. Each of these chapters is presented as a
stand-alone chapter that relates to the overarching research objectives and questions
of the study. In Chapter 2, interview and questionnaire data collected through the
NASAC study are analyzed to assess the perceived effectiveness of aquaculture
regulations in fostering compliance and to identify factors correlating with
compliance. In Chapter 3, data coded using the IGT is analyzed to gain a
comprehensive understanding of the state regulations governing the practice of
39


aquaculture in Virginia and Florida and to explore the Tool's utility in a comparative
examination of institutional designs. In Chapter 4, interview data is analyzed to
examine the compliance motivations of members of the aquaculture communities of
Virginia and Florida. In Chapter 5, questionnaire data collected among aquaculture
producers in Florida is analyzed, along with interview data, to assess their compliance
motivations. Abstracts for each of these analytical chapters are provided below.
Following the analytical chapters, a concluding chapter is offered which summarizes
the key findings from each of these, discusses the broader implications of this
research, identifies limitations of this study, and provides a future research agenda
that extends the research conducted herein.
Chapter 2: Bundling Regulatory Instruments: An Analysis of the U.S. Aquaculture
Industry
This chapter reports original mixed-method data from a national study to assess the
perceived effectiveness of aquaculture regulations in fostering compliance. Data were
collected through interviews and a survey of state aquaculture coordinators.
Qualitative data obtained through interviews provide insight on the inter-
dependencies between regulatory factors, including perceptions of peer pressure,
trust, and knowledge sharing and regulatory compliance. Analysis of survey data
showed that perceptions of compliance correlates with five factors: (1) Fair and
consistent enforcement of regulations; (2) Belief of regulated persons that regulations
are scientifically and technically appropriate; (3) Trust of regulatory agents; (4) Trust
between industry members; and (5) Knowledge sharing between industry members on
scientific/technical and regulatory/administrative issues. The paper concludes with a
discussion for policy makers for designing effective policy instruments to govern the
aquaculture industry.
Chapter 3: Diagnosing Regulatory Stringency Using the Institutional Grammar Tool:
A Comparative Analysis of U.S. Aquaculture Policies
40


Advances in comparative institutional analysis necessitate the development of tools
that allow analysts the ability to understand systematically the constitutive elements
that comprise institutions, such as policies, laws, and regulations. One such tool is the
institutional grammar tool (IGT). Housed within the institutional analysis and
development (IAD) framework, the IGT offers the ability to systematically dissect
institutions to gain a comprehensive understanding of the actors being governed by
them, activities that they are allowed, forbidden, and required to perform, the spatial,
temporal, and procedural boundaries of these activities, and gradations of sanctions
for non-compliance. The objectives of this chapter are two-fold: First, to apply the
IGT to understand systematically the content of regulatory policies governing the
practice of aquaculture in Florida and Virginia, United States. Second, to demonstrate
how regulatory stringency may be operationalized using the IGT as a diagnostic tool
to assess any discernable differences between policies that are reportedly stringent
and non-stringent. In pursuing these objectives, this discussion demonstrates the
IGT's applicability toward comparative institutional analysis.
Chapter 4: The Culture of Compliance: Contextualizing Guilt, Social Disapproval,
and Fear of Monetary Sanctions
What motivates regulatory compliance? Drawing from regulatory and institutional
scholarship, this question is explored in this chapter in the context of aquaculture
communities. Findings come from a comparative case study analysis of two U.S.
states, involving a systematic coding of regulatory documents and interviews with
thirty members of the study states aquaculture communities. The findings indicate:
(i) varying levels of compliance among individual farmers depending on the type of
institutional directive; (ii) feelings of personal guilt or shame and fear of social
disapproval, together, are more influential in shaping individuals decision making
regarding compliance than fear of monetary sanctioning; and (iii) the expression of
compliance motivations is contingent upon a variety of factors, including the desire to
protect the natural environment, prevent consumers from becoming ill as a result of
eating a contaminated product, and to prevent conflict with neighbors and other
resource users.
Chapter 5: Rules and Decision Making: Understanding the Factors that Shape
Regulatory Compliance
What motivates regulatory compliance? This question is examined through the logic
of regulatory scholarship and the Institutional Analysis and Development (IAD)
framework using questionnaire and interview data collected among members of the
aquaculture community in Florida State. The findings indicate that individuals are
more likely to comply with regulations (1) when regulatory enforcement personnel
41


are perceived as being knowledgeable about aquaculture; (2) when farmers have a
desire to maintain a good reputation with other members of the industry; and (3)
when farmers have a strong sense of guilt associated with not complying with
regulatory directives. In demonstrating the influence of such factors on compliance,
this paper supports past IAD research that emphasizes the influence of community
based factors in shaping compliance while drawing attention to individual behavioral
motivations, such as feelings of guilt. The findings add to the regulatory scholarship
by validating past studies that posit that individuals are more likely to comply with
regulations when they perceive enforcement personnel as being knowledgeable.
42


CHAPTER 2:
BUNDLING REGULATORY INSTRUMENTS: AN ANALYSIS OF THE U.S.
AQUACULTURE INDUSTRY
Chapter Abstract
This chapter reports original mixed-method data from a national study to
assess the perceived effectiveness of aquaculture regulations in fostering compliance.
Data were collected through interviews and a survey of state aquaculture
coordinators. Qualitative data obtained through interviews provide insight on the
inter-dependencies between regulatory factors, including perceptions of peer pressure,
trust, and knowledge sharing and regulatory compliance. Analysis of survey data
showed that perceptions of compliance correlates with five factors: (I) Fair and
consistent enforcement of regulations; (2) Belief of regulated persons that regulations
are scientifically and technically appropriate; (3) Trust of regulatory agents; (4) Trust
between industry members; and (5) Knowledge sharing between industry members on
scientific/technical and regulatory/administrative issues. The paper concludes with a
discussion for policy makers for designing effective policy instruments to govern the
aquaculture industry.
Introduction
One of the central pursuits of regulatory scholars has been exploring the
factors that most influence regulatory compliance in order to gain insight for crafting
43


effective regulatory instruments. Some scholars direct their attention at understanding
how characteristics of the regulatory context, or regulators, affect compliance
outcomes (Gunningham et al. 2005; May and Wood 2003, Burby and Patterson 1993;
Braithwaite and Makkai 1991), while others have sought to examine the affect of
characteristics of regulated communities (Grafton 2005; Berkes 1987; Sutinen and
Kueperan 1999). What this research makes abundantly clear is that crafting and
implementing regulatory instruments that appropriately reflect the complexities of
distinct industries, as well as the contexts in which they are applied, remains a
challenging task. Not surprisingly, varying factors have been found to affect
compliance across cases leaving questions regarding the most appropriate choice of
regulatory instruments. Identifying the correct bundle of regulatory instruments to
ensure high levels of compliance is particularly challenging in emerging industries in
which knowledge of broader scale impacts associated with development remain
uncertain, including the effects of development on environmental and health
outcomes (May 2005). U.S. aquaculture represents one such industry. In this paper,
the aquaculture regulatory contexts of thirty states are examined, including factors
reported as being related to compliance, to decipher the types of regulatory
instruments that would be effective for governing this industry. Data come from
interviews with 10 and a survey of 56 members of the National Association of State
Aquaculture Coordinators (NASAC).
44


Aquaculture, defined as the propagation and rearing of aquatic species in
controlled or selected environments" (NOAA 1980), provides one example of an
emerging natural resource based industry that is an increasingly important state and
national level policy issue. Aquaculture has the potential to pose significant
economic, environmental, and health impacts to local communities. The United States
currently produces approximately 20% of its seafood consumed while importing
80%, resulting in a seafood trade deficit that exceeds nine billion dollars (NOAA
2009). Aquaculture development in the United States faces a number of barriers,
including: an uncertain regulatory landscape (Firestone 2004; Wirth 1999), complex
interdependencies among ecological, economic, technical, and social factors
(Firestone 2004), resistance from the general public regarding farmed seafood (Mazur
2006; Amberg and Hall 2010), conflict about aquaculture development (Kaiser and
Stead 2002), and numerous concerns about the industry from disease control to
degradation of marine ecosystems (Black 2001; Francik 2003; Treece 2002; Naylor
2000; Mazur 2006). The challenges faced by the U.S. aquaculture industry resemble
those faced by other natural resource based industries where regulations tend to be
fairly technical and where decentralization of regulatory governance is commonly
observed (May 2005). The aquaculture industry has been vastly understudied from a
social science perspective. Given, however, the growing importance of the industry in
a national context, more attention must be devoted to analyzing the policy and
regulatory considerations of the industry.
45


Regulatory scholars have studied compliance in similarly characterized policy
environments, including the agro-environmental industry in Denmark (May 2005),
boatyard industries in the states of Washington and California (May 2005), and the
concentrated animal feeding operation (CAFO) industry (Koski 2007). Like these
industries, aquaculture is an example of a private good that is both maintained and
constrained by the availability of natural resources, is governed by environmental
regulations targeted at reducing negative externalities, and is immersed in socio-
economic considerations, including the need to respond to consumer preferences and
resource user conflicts.
As of yet, no single theory exists to explain why individuals comply with
regulations. Increasingly, empirical research in the regulatory field has demonstrated
that a variety of factors contribute to regultees decisions to comply with regulatory
directives. Some of these factors relate to characteristics of regulating entities or
relationships between regulators and industry members, including, the enforcement
practices of regulatory agents (E. Ostrom 1994) and the presence of trust between
regulatory and regulated actors (Gunnignham et al. 2003; 2005; Bardach and Kagan
1982; May 2005; Murphy 2004). Others relate to characteristics of industry members.
For example, industry members confidence in the regulating agency and its
personnels technical capacity in administering regulatory policies (Gunningham et
al. 2005; Bardach and Kagan 1982), the presence of trust between a regulated
industrys members (Ostrom 2005), and social sanctions and influence (Berkes 1987;
46


Sutinen and Kueperan 1999; Braithwaite and Makkai 1991; May 2005a).
Additionally, knowledge sharing among regulatees regarding scientific/technical and
regulatory/administrative issues may also influence compliance (Grafton 2005).
In examining such factors, this study adds to a body of knowledge that
challenges presumptions posed within classical models of regulatory deterrence. The
classic regulatory deterrence model is premised upon the assumption that legal
sanctions will sufficiently thwart the desire for non-compliance on the part of
regulated actors. In this view, regulatees are considered self utility maximizing agents
and, thus, costly sanctions administered through regulatory agencies are viewed as the
primary coercive mechanism in fostering regulatory compliance (Zimring and
Hawkins 1973; Bentham 1789; Becker 1968).
As the aquaculture industry continues to develop in the United States, the
regulatory instruments used to govern the industry are also likely to become
commensurately more comprehensive and complex. As such, it is timely and
important to identify the varying types of regulatory instruments currently in place
across aquaculture producing states as well as gain a nationwide understanding of the
factors perceived as being most important in influencing compliance with regulatory
directives. In doing so, one can begin to discern how they may be crafted to most
effectively foster regulatory compliance in the aquaculture industry, in addition to
other similarly characterized natural resource based industries.
47


Factors Shaping Regulatory Compliance
Compliance is one of the primary goals associated with regulatory policies. As
May (1991) writes, The typical policy is a package of policy instruments aimed at
some combination of gaining compliance through the use of mandates, improving
short-term performance through the use of incentives, enhancing longer-term
performance through various capacity building measures, or altering the system for
providing goods and services by introducing system changes (May 1991, 199;
Elmore 1987). Within this discussion, instruments are broadly synonymous with
factors that relate to the ways in which regulations are implemented and enforced; for
example, factors relating to regulatory enforcement personnel. Included within this
broad definition of instruments are factors emerging from regulating entities as well
as those emerging from the community Where significant efforts are made by policy
designers to ensure that compliance is achieved, cases of non-compliance incite
inquiry as to what motivates individuals to comply, or not comply.
Enforcement Practices
Regulatory scholars have found that the enforcement practices of regulatory
agents may be a key motivating factor in fostering regulatory compliance. For
example, where inspections are conducted more frequently, higher compliance has
been observed (Gunningham et al. 2005; May and Wood 2003, Burby and Patterson
1993). However, while regular inspections have been found to increase the capacity
of regulators to detect non-compliant behavior, findings remain unclear as to how
48


reliably or consistently sanctions are administered when a violation is found
(Braithwaite and Makkai 1991). Reinforcing the notion that regulatory agents are
somewhat autonomous legal decision makers, Kagan (1989) and May and Wood
(2003, 117) posit that regulatory personnel possess a great deal of discretion when it
comes to monitoring and enforcing regulatory directives and the ways in which they
interact with regulatees. Regulatory enforcement relating to the environment, in
particular, Zinn (2002, 1) argues, has been demonstrably more favorable to alternative
enforcement techniques, including informal negotiation and compromise with
regulatees. Irrespective of the particular enforcement techniques employed by
regulatory personnel, research has shown that perceived fairness and consistency of
regulatory enforcement can have positive compliance effects (Levi 1998; Ostrom
2005). Thus, more explicit attention must be paid to capturing the reliability with
which sanctions are administered, particularly because this may relate to additional
regulatory factors to influence compliance outcomes. The expectation is that
compliance with regulatory directives will be higher when it is perceived that
industry members view regulations as being fairly and consistently enforced.
Trust and Knowledge Sharing
The concept of trust has been defined variably by scholars to represent
different dimensions that relate to regulatory processes and compliance (Braithwaite
and Makkai 1994; May 2004; Levi 1988). Levi (1998) defines trust generally as a
holding word for a variety of phenomena that enable individuals to take risks in
49


dealing with others, solve collective action problems, and/or act in ways that seem
contrary to standard definitions of self-interest (Levi 1998, 78). More specifically,
trust may be defined in terms of the expectation by regulated agents that regulatory
commitments will be dependably fulfilled by regulatory agents (May 2004; Levi
1988; Murphy 2004). By this definition, trust is thus a by-product of positively
viewed enforcement practices that can result in favorable compliance outcomes.
Presumably, where monitoring and enforcement is reliably conducted, trust may be
established between regulatory and regulated agents, which in turn can foster cession
by the latter of self-interest in favor of compliance with regulatory directives (Levi
1998; Scholz and Lubell 1998). In a similar vein, it has been demonstrated that
regulated actors may be more willing to forfeit self-interest for a collective good, in
this case being collective compliance, where they exhibit a high level of trust and
cooperation amongst each other (Putnam 1993). Thus, it is expected that compliance
with regulatory directives will be higher when it is perceived that industry members
trust those monitoring and enforcing regulations as well amongst each other.
An additional possible outcome of trust is a decrease in attempted deceit by
either party as trusting actors are more likely to share information and resources
regarding industry and management matters (Grafton 2005). In the context of
fisheries, Grafton (2005) asserts that where regulatory actors harbor feelings of trust,
they are more likely to share information with one another thus fostering positive
compliance outcomes (Grafton 2005, 755). While Grafton was referring specifically
50


to the relationship between fishermen and the management authority, it is further
plausible that the presence of trust among industry members themselves may foster
intra-industry knowledge sharing that could similarly result in positive compliance
outcomes. Pomeroy and Berkes (1997) find this to be true in their study of co-
management systems relating to common-pool resources. As such, these findings
suggest that compliance with regulatory directives will be higher when industry
members are perceived to share knowledge with one another regarding
scientific/technical and regulatory/administrative aspects of the industry.
Rule Appropriateness
The perceived appropriateness of regulations is another important quality
characterizing the relationship between regulating and regulated agents in influencing
compliance with regulatory directives. Appropriateness of regulations in this case
refers to the applicability of regulations in relation to local resource, political, and
social conditions (Ostrom 1990; 2005). Where regulating and regulated actors possess
disparate beliefs regarding how an industry should be managed, scholars argue that
regulated agents may question the legitimacy of regulatory agents as well as the
legitimacy and fairness of the directives themselves (May 2005; Ostrom 1990). This
in turn, may negatively impact compliance levels (May 2005, 321; Bardach and
Kagan 1982; Levi 1988). Referring to governance rules of common pool resources
more broadly, Ostrom (1990) proffers that rules, or regulations, well tailored to the
context in which they are being applied contribute to the long-term sustainability of
51


such resources (Ostrom 1990, 92). In exploring this issue within a fisheries context,
Jentoft (2004) asserts that when fishers lose the ability to feel morally committed to
values such as honesty and respect for rules (Jentoft 2004, 144), the ascendancy of
regulatory over regulated agents begins to diminish, thereby increasing chances of
non-compliance by the latter. It is thus expected that compliance with regulatory
directives will be higher when it is perceived that industry members feel they are
contextually appropriate.
Technical Capacity
Confidence in a regulatory agency and its personnels technical capacity, or
competence, as perceived by regulated agents is yet an additional factor that may
influence compliance outcomes. When this quality of the relationship between the
former and the latter is lacking, regulated actors may feel that regulatory agents are
unfairly or incompetently administering regulatory directives (Gunningham et al.
2005). Regulatees may also view those whom they feel are technically incapable as
being overly stringent in their administration of directives due to an overly strict
interpretation of regulatory policies stemming from an inability to reason in varying
regulatory situations from an experiential and knowledge deficiency (Bardach and
Kagan 1982). Based on empirical findings, it is expected that compliance with
regulatory directives will be higher when it is perceived that industry members feel
those enforcing regulations are competent.
52


Peer Monitoring and Enforcement
Increasingly, empirical research in the regulatory field that draws upon
scholarship from sociology and social psychology (Elster 1989; Coleman 1990; Ajzen
1988) has shown that a variety of other factors contribute to regulatees decisions
regarding when to comply with regulatory directives (Hatcher et al. 2000). Additional
factors include social sanctions and influence, or social disapproval (Berkes 1987;
Sutinen and Kueperan 1999; Braithwaite and Makkai 1991), and personal shame or
guilt (Grasmick and Bursik 1990). Hatcher et al. (2000), for example, found that
social pressures served as an effective deterrent to non-compliance relating to catch
quotas, or individual fishing quotas, in the United Kingdom. Similarly, Kuperan and
Sutinen (1995) have explored the relationship between compliance and feelings of
moral obligation among regulatees regarding fishery zoning regulations in Malaysia.
However, because regulatory scholars have traditionally focused on top-down
influences on compliance, research focusing on community based or bottom-up
factors has been limited to date and many areas remain to be explored regarding
socially based compliance motivations. Based on the research that has been
conducted to date, it is expected that compliance with regulatory directives will be
higher when it is perceived that industry members engage in peer monitoring and
enforcement.
The expectations highlighted throughout this discussion in relation to the
different regulatory factors showcased will be assessed in this paper using data
53


obtained through an online survey of members of the NASAC. In addition, each of
these factors was explored in interviews with NASAC members toward
understanding the regulatory context surrounding aquaculture in their respective
states.
Methods of Data Acquisition
Data collection for the discussed study consisted of two parts: In the first part,
interviews were conducted with 10 members of the National Association of State
Aquaculture Coordinators (NASAC). In the second part, an online survey was
administered to the 56 individuals listed as members of the NASAC in 2009. Through
the interviews and survey, NASAC members were asked to comment on their
perceptions regarding a variety of regulatory factors in their respective states as well
as the relationship between these factors and perceived levels of compliance. NASAC
members are highly knowledgeable about the aquaculture industry, particularly with
respect to regulatory/management and/or technical matters. In many cases, these
individuals are the State Aquaculture Coordinators from the different States. Where
there is no official State Coordinator, these individuals are selected to serve as
representatives to NASAC either due to their professional position or influence in the
respective aquaculture communities. Most states have one representative, though
some states have more.
Given their specialized knowledge regarding various aspects pertaining to
their respective state aquaculture industries, NASAC members were selected as an
54


appropriate study population in place of industry members whose knowledge may be
limited to issues relevant to their operation. Further, as the intention of this study was
to glean insight into the national context relating to the regulation of the aquaculture
industry, the researcher was interested in a data collection design that would allow her
to select one knowledgeable representative of the industry from each state in the
interest of breadth, rather than interviewing and surveying multiple industry members
within a few select states for a more in-depth understanding of the aquaculture
regulatory landscape.3
Data Collection Instrument: Interviews
Ten telephone interviews were conducted with NASAC members.
Interviewees were asked a series of questions regarding regulatory characteristics
pertaining to aquaculture in their respective state. The interview protocol included
questions that relate specifically to the regulatory factors being examined in this
study, including, enforcement practices, perceived technical capacity of monitoring
and enforcement personnel, peer monitoring and enforcement, knowledge sharing,
and compliance. Questions relating to rule appropriateness and trust, both of
regulatory agents and between industry members, were only posed in the online
3 Follow-up studies to the one discussed here will involve the latter, wherein the researcher will be able
to gather data representing farmers perceptions of various regulatory instruments and how they
influence and are influenced by the contexts in which they are embedded.
55


survey. The following questions were posed to interviewees for each remaining
relevant regulatory factor.
[Enforcement practices] How reliably do you feel sanctions are imposed?
[Technical capacity] What do you feel is the level of understanding among
those enforcing permit requirements regarding activities that are allowed and
forbidden?
[Peer monitoring and enforcement] Do you think peer pressure among
aquaculturists helps to enforce compliance with regulations?
[Knowledge sharing] On whom do members of the aquaculture community
tend to rely to obtain information and/or resources on various aquaculture
related issues?
[Compliance] What is the level of regulatory compliance in your state?
Data Collection Instrument: Online Survey
An online survey was crafted to supplement findings from the interview. As
the survey was designed subsequent to the interviews, these questions were more
sharply crafted in accordance with the analytical objectives of this paper. For the
online survey, several questions from the interview protocol were modified and/or
expanded to capture more dimensions on the issues of interest. For example, an
additional dimension of peer monitoring and enforcement was included in the survey:
peer reporting of non-compliance to governmental agencies. In addition, questions
relating to rule appropriateness and trust were added (please refer to Appendix C for a
list of relevant survey questions).
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In the survey, respondents were asked to indicate their general perceptions
regarding the regulatory factors under consideration. For this set of questions,
respondents were asked about (for complete questions, please refer to Appendix C):
The extent to which (i) enforcement practices; (ii) rule appropriateness; and
(iii) trust of regulatory personnel and of fellow industry members were
contributors to compliance (Scale: 0 to 4, where 0 = Not a Contributor; 1 =
Mild Contributor; 2 = Moderate Contributor; 3 = Significant Contributor; and
4 = Biggest Contributor).
The extent to which community members conduct monitoring and
enforcement in their respective state (Scale: 0 to 4, where 0 = None; 1 =
Little; 2 = Moderate; 3 = Significant; and 4 = Heavy);
The extent to which they disagree/agree with the statement most non-
compliance is reported to government agencies by other members of the
industry (Scale: -2 to 2, where -2 = Strongly Disagree; -1 = Mildly Disagree;
0 = Neutral; 1 = Mildly Agree; and 2 = Strongly Agree);
The extent to which they disagree/agree with the statement industry members
often share knowledge of the scientific/technical aspects of aquaculture with
one another (Scale: -2 to 2, where -2 = Strongly Disagree; -1 = Mildly
Disagree; 0 = Neutral; 1 = Mildly Agree; and 2 = Strongly Agree);
The extent to which they disagree/agree with the statement industry members
often share knowledge of the regulatory/administrative aspects of aquaculture
with one another (Scale: -2 to 2, where -2 = Strongly Disagree; -1 = Mildly
Disagree; 0 = Neutral; 1 = Mildly Agree; and 2 = Strongly Agree); and
The extent to which they disagree/agree with the statement compliance with
aquaculture regulations is very high (Scale: -2 to 2, where -2 = Strongly
Disagree; -1 = Mildly Disagree; 0 = Neutral; 1 = Mildly Agree; and 2 =
Strongly Agree).
Survey participants included those individuals listed as state aquaculture
representatives in the NASAC database in 2009 (n=56). Prior to receiving the survey,
potential respondents were sent an invitation to participate explaining the purpose and
57


procedures of the study, possible risks and benefits associated with participation, and
details relating to the confidentiality of respondents answers. Following the
administration of the survey, three reminders were sent to non- respondents
requesting their participation in the survey. Two of these reminders were sent by the
author and one was sent by an administrative representative of the NASAC.
Survey Responses
Of the 56 individuals to whom the survey was sent, 32 individuals responded,
yielding a 57% response rate. The states represented in the respondent sample were
grouped according to the U.S. Census Bureaus regional distinctions to determine the
percentage of states from each region that were represented. In accordance with this
regional categorization, 46% of states from the West, 75% from the Midwest, 56% of
states from the northeast, and 59% of southern states were represented in the
respondent sample. Each state had one respondent except for two states which had
two respondents. So that these states were not overrepresented in the analysis, the
mean was calculated between each of these states two respondents responses to
produce a combined response. This mean calculation was conducted for
questions/responses that represent state level variables, versus individual level
variables. For example, the responses of the two respondents from Alaska and Ohio
were not combined for questions such as those asking survey respondents to indicate
their gender, years employed in each professional position listed, and educational
background. They were combined for questions such as those asking survey
58


respondents to provide details about the level of compliance and characteristics of the
regulatory processes in their respective states.
To determine the response bias associated with the sample of respondents,
one-way ANOVA tests were conducted to determine if statistically significant
differences were present between respondent and non-respondent states with respect
to a variety of industry demographics; namely, industry size and type of aquaculture
produced. Industry demographics for all states were obtained from the United States
Department of Agriculture (USDA) 2005 Census of Aquaculture (USDA, 2006).
Respondent and non-respondent states were compared on (1) total number of farms;
(2) total farm sales; (3) number of food fish farms; (4) number of sport
fish/recreational farms; (5) number of baitfish farms; (6) number of ornamental fish
farms; (7) number of crustacean farms; and (8) number of mollusk farms. ANOVA
results indicate that respondent and non-respondent states differed statistically only in
terms of the number of sport fish/recreational aquaculture farms (p < .05), with
respondent states having more than non-respondent states.
Data Analyses
Data from the interviews and survey were analyzed separately as the data
collection obtained through these different means speak to different analytical
objectives. Surveys were used to determine if there was a relationship between the
perceived presence of various regulatory characteristics and compliance. Interviews,
59


on the other hand, were used to gain a contextual understanding of regulatory
characteristics in ten study states.
Data from the interviews were summarized by collating all of the responses
across the ten interviewees around the regulatory factors under consideration.
Interview data were analyzed in this manner to display trends in the responses across
the different factors to supplement findings from the online survey. Analysis of
survey data was conducted using SPSS analytical software. First, descriptive statistics
were performed on the data aggregated across the thirty respondent states to assess
the survey participants responses for each regulatory factor. Specifically, the
descriptive analyses were applied to determine the breakdown of survey participants
responses for each of the regulatory compliance factors under consideration. Next, to
identify relationships between each regulatory factor and compliance, correlation
analyses were conducted.
Results
Results: Interviews
A review of interview data provides useful insight relating to the regulatory
context of aquaculture in ten U.S. States, which, together with survey data, offers a
more illustrative depiction of the national aquaculture regulatory landscape. While the
interview findings did provide evidence for the relationship between regulatory
factors and compliance, they were particularly useful in revealing important
interdependencies between regulatory factors and compliance.
60


Enforcement Practices (n=7 out of 10)
Of the seven individuals that responded to this question, five indicated that
sanctions were reliably enforced. Interviewees provided varying responses as to why
they felt this was the case, including, small industry size (Interviewee ID: 004), strict
legislative mandates that require monitoring and enforcement personnel to reliably
administer sanctions (Interviewee ID: 002), and the types of activities that are being
enforced; for example, reliable enforcement regarding compliance with paperwork
requirements is relatively easy (Interviewee ID: 003). Another interviewee stated that
enforcement is more reliable when the activity under consideration is hot at the
time (Interviewee ID: 001). Finally, consistent with the literature (Kagan, 1989; May
and Wood, 2003), the one interviewee who responded negatively stated that,
Enforcers have a lot of flexibility in enforcing regulations and so there can be some
variability in how sanctions are administered (Interviewee ID: 005).
Technical Capacity (n=9 out of 10)
Of the nine interviewees that responded to this question, six stated that those
enforcing regulatory requirements do not possess a good level of understanding
regarding activities that are allowed and forbidden, while three stated that they do.
Two individuals stated that oft changing regulatory requirements is the primary
reason for lack of knowledge among enforcement personnel (Interwiewee IDs: 005
and 006). Another interviewee stated that the regulatory agency tasked with
regulating aquaculture activities lacks a sound knowledge regarding how to manage
61


the industry, saying, Their regulations are not based on sound management, but
based on interpretations and whims of employees [enforcement personnel] that dont
know what they are doing (Interviewee ID: 009). Other reasons cited as contributing
factors, include personnel turnover (010), lack of state-level monitoring and
enforcement capacity (Interviewee ID: 004), and enforcement personnel who are
motivated by their private motives (Interviewee ID: 001).
Peer Monitoring and Enforcement (n=10 out of 10)
Of the ten individuals that responded to this question, six responded that peer
pressure among aquaculturists helps to enforce compliance with permits and
regulations, two responded that peer pressure is becoming increasingly common as
state aquaculture industries continue to grow and develop, and two responded that
peer pressure regarding compliance with aquaculture regulations does not exist. Of
those who responded that peer pressure does play a role, three stated that industry
members applied positive peer pressure on one another to comply with aquaculture
regulations out of a mutual trust of one another that manifests in the sharing of
information and resources. For example, one interviewee stated, Growers do help to
keep each other accountable trust and reciprocity in the community not a cutthroat
industry very respectful of one another and so they dont want to not comply with
regulations and risk losing the trust of other industry members (Interviewee ID:
006). Another interviewee stated, They share information about what they know -
friends helping friends and monitoring each other (Interviewee ID: 009). One of the
62


interviewees who indicated that peer pressure among industry members is growing
linked this trend with changing environmental conditions, stating, ...this will
probably increase as time goes on. The state is entering a new era of dealing with
water issues and as water shortages continue, the community will start applying more
peer pressure to make sure that people are complying with the regulations
(Interviewee ID: 001)
Knowledge Sharing (n=10 out of 10)
Of the ten individuals that responded to this question, nine responded that they
obtain information from other industry members via their respective state aquaculture
association or industry trade publications. A number of these interviewees indicated
that information sharing and coordination was most frequently observed between
farmers conducting similar types of aquaculture (Interviewee IDs: 001, 002, 010).
Compliance (n=8 out of 10)
Six of the eight individuals that responded to this question indicated that
compliance with aquaculture regulations in their state was high to very high, with one
individual stating that compliance was pretty decent (Interviewee ID: 006) and one
individual providing a compliance rate at around 70% (Interviewee ID: 007). A
variety of factors were cited as contributors to high levels of regulatory compliance,
including non-stringent regulations (Interviewee ID: 001), fear of social disapproval
(Interviewee ID: 001), and adherence to best management practices articulated within
regulatory directives (Interviewee ID: 010). In describing instances of non-
63


compliance, one interviewee stated that sometimes the monetary costs associated with
meeting regulatory requirements can thwart compliance (Interviewee ID: 007).
Another interviewee stated that, most of the time, cases of non-compliance are
attributable to oversight on the part of the regulatees as opposed to malicious intent
(Interviewee ID: 006).
Table 2.1 provides a summary of interview results, including general trends
and specific findings in responses for each regulatory factor under consideration.
Table 2.1 Summary of interview findings
Regulatory Factor General Results Reasons Explaining General Trends
Enforcement Five out of seven interviewees Small industry size and strict
Practices indicated that sanctions are mandates, and easy to monitor
(n=7/10) reliably enforced. activities.
Technical Six out of nine interviewees Personnel turnover, oft
Capacity (n=9/10) indicated that they do not feel those enforcing regulations possess a good level of understanding of regulations. changing regulatory requirements, lack of state level monitoring and enforcement capacity.
Peer Monitoring Eight out of ten interviewees Desire to look after one
and Enforcement (n= 10/10) indicated that peer monitoring and enforcement is or is becoming increasingly prevalent in maintaining compliance with regulatory directives. another, industry competition, increasing resource constraints.
Knowledge Sharing (n=10/10) Nine out of ten interviewees stated that they share information with one another. Information sharing through state aquaculture association and/or through industry trade publications.
Compliance (n=8/10) Six out of eight interviewees reported high compliance. Non-stringent regulations, fear of social disapproval, adherence to best management practices in regulations.
64


The responses obtained through the interviews illuminate interdependencies
between regulatory factors. In particular, several interviewees described peer
monitoring and sanctioning and knowledge sharing in relation to the presence of trust
between members of the aquaculture industry. Interestingly, the presence or lack of
trust reported within a community tended to shape how interviewees interpreted the
notion of peer monitoring and enforcement and peer pressure. Where interviewees
felt that trust between industry members is a prominent feature of the aquaculture
industry, they tended to speak about peer involvement in regulatory affairs in a
positive light industry members trust each other and so they want to look after one
another (Interviewee IDs: 006 and 009). In contrast, where there was an apparent lack
of trust among industry members, interviewees tended to interpret peer monitoring
and enforcement and peer pressure more negatively industry members distrust of
one another leads them to engage in policing of one anothers activities
(Interviewee ID: 007).
Responses from the interviews also provide qualitative elaborations as to why
compliance is reported as being relatively high across the majority of aquaculture
producing states, a finding reflected in the responses to both interview and survey
questions. Higher levels of compliance were attributed to non-stringent regulations,
fear of social disapproval, and adherence to best management practices articulated in
regulatory directives. Two of the interviewees also commented that non-compliance
65


is not grounded in malicious intent, but rather has more often to do with other factors,
such as mere oversight or the costliness of compliance (Interviewee IDs: 006 and
007). Such insight is useful as it addresses another dimension of compliance not
addressed in the online survey. Non-compliance has varying degrees; one end of the
spectrum representing that which is unintentional and the other end of the spectrum
representing non-compliance that is intentional. In future studies, both data collection
instruments should be modified to capture this dimension of compliance/non-
compliance.
Results: Online Survey
Descriptive Analysis Results
Findings from the descriptive analyses presented in Table 2.2 indicate that,
overall, respondents had mixed perceptions regarding enforcement practices (mean
response = 1.68), rule appropriateness (mean response = 1.88), technical capacity
(mean response = 1.63), and trust of regulatory personnel (mean response = 1.54) and
fellow industry members (mean response = 2.18) as contributors to compliance,
nearly all of the respondents indicated that peer monitoring and enforcement was
minimal to moderate in their respective state (mean response = 1.07), only 11% of
respondents indicated that most non-compliance in their state is reported by peers
(mean response = -.54), more than 60% perceived frequent sharing of information
(scientific/technical issues mean response = .80; regulatory/administrative issues
66


mean response = .86), and 75% reported high compliance with regulatory directives
(mean response = .98).
Table 2.2 Descriptive results per regulatory factor
Regulatory Factor Mean Mode Standard Deviation
Enforcement Practices 1.68 1 1.26
Rule Appropriateness 1.88 1 1.37
Technical Capacity 1.63 1 1.28
Trust 1: Enforcement Personnel 1.54 1 1.23
Trust 2: Industry Members 2.18 3 1.29
Peer Monitoring and Enforcement 1: Peer Monitoring and Enforcement 1.07 1 .90
Peer Monitoring and Enforcement 2: Peer Reporting -.54 0 1.11
Knowledge Sharing 1: Scientific/Technical .80 l 1.11
Knowledge Sharing 2: Regulatory/ Administrative .86 1 1.01
Compliance .98 2 .99
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The variability between states on regulatory factors, evidenced by mixed overall
perceptions on several factors, indicates that a variety of contextual factors are
responsible for determining how regulatory instruments are crafted, implemented, and
perceived by regulatees in individual states. Contextual nuances are not made evident
through basic descriptive analyses.
Bivariate Analysis Results
Responses to the above questions were then analyzed using correlation
analyses to see if there is a relationship between perceptions of regulatory factors and
compliance. The results from the correlation analysis are provided in Table 2.3.
Largely consistent with the literature, the following factors were found to be
significantly correlated with compliance with regulatory directives: (1) Fair and
consistent enforcement of regulations by regulatory agents; (2) belief of regulated
persons that regulations are scientifically and technically appropriate; (3) trust of
regulatory agents; (4) trust between members of industry; and (5) sharing of
knowledge between industry members regarding the scientific/technical and
regulatory/administrative aspects of aquaculture. Conversely, the following factors
were not found to be significantly correlated with regulatory directives: (1) Perceived
technical capacity of regulatory agents; and (2) peer monitoring and enforcement.
Evident from these findings is that both types of factors, those relating to
characteristics of regulatory entities as well as those relating to characteristics of the
industry are related to compliance with regulatory directives.
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Table 2.3 Correlations between regulatory factors and compliance (n=28)
Regulatory Factor Pearson Correlation
Enforcement Practices .39*
Rule Appropriateness .55**
Technical Capacity .35
Trust 1: Enforcement Personnel .47*
Trust 2: Industry Members .59**
Peer Monitoring and Enforcement 1: Peer Monitoring and Enforcement -.23
Peer Monitoring and Enforcement 2: Peer Reporting .033
Knowledge Sharing 1: Scientific/Technical .56**
Knowledge Sharing 2: Regulatory/Administrative .56**
* = Correlation is significant at the .05 level (2-tailed)
** = Correlation is significant at the .01 level
The findings from the survey provide only a first step in unpacking how
various characteristics of state regulatory instruments impact levels of compliance,
particularly in this study given the small survey sample size. The descriptive results
presented show that there is a fair amount of variability between the states regarding
the different regulatory factors under consideration. For example, the respondents
indicated mixed perceptions regarding the extent to which they feel that enforcement
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practices, rule appropriateness, trust of regulatory agents, and perceived technical
capacity are contributors to compliance in their respective states.
As there has been little federal legislation governing aquaculture in past years,
states have had a great deal of discretion in how they choose to manage their
respective aquaculture industries. As such, the regulatory landscapes concerning
aquaculture differ markedly across states reinforcing the need to heed distinct
regulatory contexts when exploring factors such as those studied herein. The results
from the interviews, while not showing direct relationships between regulatory
factors and compliance, provide further contextual elaborations regarding the
regulatory factors under consideration in ten states.
Discussion and Conclusions
One of the challenges in governing natural resource based industries remains
crafting bundles of regulatory instruments that appropriately reflect the complexities
of the industries themselves, considering the dynamic relationship between
environmental, social, and political factors. In designing regulatory instruments in
such arenas, policy designers should heed the contexts in which they will be applied
so that they speak to the motivations that expressly influence compliance among
industry members. This study contributes to such an endeavor by articulating factors
that influence compliance in the context of an increasingly salient natural resource
based industry, U.S. aquaculture. In doing so, the findings and discussion offer
answers to the following questions:
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What factors relate to compliance with regulations in the aquaculture industry?
Of the factors considered in the online survey, those found to be significantly
correlated to compliance include: enforcement practices of regulatory personnel, rule
appropriateness, trust between regulating and regulated agents, trust between industry
members, and knowledge sharing between industry members regarding the
scientific/technical and regulatory/administrative aspects of aquaculture. Factors that
were found not to be significantly related to compliance include: the perceived
technical capacity of regulatory agents and the presence of peer monitoring and
enforcement.
Interviews were used to complement findings from the online survey. From
the interviews, additional insight was garnered to depict contextual differences with
respect to the regulatory factors under consideration in ten states. In general,
interviewees believe that sanctions are reliably enforced, express skepticism
regarding the technical capacity of monitoring and enforcement personnel, tend to
engage in peer monitoring and enforcement, frequently share knowledge with one
another regarding scientific/technical and regulatory/administrative aspects of the
industry, and are largely compliant with aquaculture regulations.
Findings from this study validate previous research that contest the classical
regulatory deterrence model and provide further evidence of the role of an alternative
set of factors in affecting compliance, including those that pertain to characteristics of
the interactions between regulating and regulated actors and characteristics and/or
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dynamics of the regulated industry. Should regulatory scholars attempt to construct a
theory of regulatory compliance, this study makes clear that incorporation of both sets
of factors is fundamental. The next research step associated with this study is to
explore how compliance motivations differ across the study states considering
contextual factors, including such factors as industry demographics and regulatory
histories.
How should policy makers bundle regulatory instruments to promote compliance?
The extent to which policy designers and other administrators involved in the
governance of aquaculture can influence community based factors, such as the
establishment of trust between industry members, may be limited. However, they do
possess the capacity to influence other critical factors demonstrated to positively
influence levels of compliance in past regulatory scholarship. For example, they can
foster consistent enforcement of regulations, which in turn can promote trust of
regulatory agents (Scholz and Lubell 1998), develop or maintain collaborative
processes that encourage industry members to provide input on aquaculture
regulations and policies to ensure that they are viewed as being as appropriate
(Ostrom 1990; 2005), and support venues in which industry members can exchange
knowledge regarding the scientific/technical and regulatory/administrative matters of
the industry (Grafton 2005; Pomeroy and Berkes 1997). As several interviewees
stated that they lacked confidence in the technical capacity of regulatory entities to
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enforce directives, administrative officials should pay careful attention to properly
training agency personnel in such matters.
How does the regulatory governance of aquaculture relate to other natural resource
based industries?
The findings presented in relation to aquaculture may also be useful to
scholars studying factors contributing to regulatory compliance in other natural
resource based industries. The complex regulatory governance systems developed to
manage such industries must mimic the complexity of the industries themselves that
are entangled with ecological, economic, technical, and social concerns. The question
then arises: How can regulatory instruments be both crafted and implemented to deal
with the inherent complexities of the industries they are intended to manage? Any
research that contributes to describing how such industries are managed as well as the
critical factors that contribute to the effectiveness of regulatory instruments is both
useful and necessary. The findings from this study punctuate the need to develop
policy instruments that are geared toward enhancing the efficacy of regulatory
personnel and processes toward achieving compliance in addition to instruments that
foster norms of reciprocity between industry members (Ostrom 2005).
This study is not without limitations. Some contradiction was observed
between findings from the online survey and interviews. For example, peer
monitoring and enforcement was not reported as being prevalent by survey
respondents, nor was it found to be significantly correlated with compliance. In
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contrast, interviewees indicated that peer monitoring and enforcement was observed
and that it does contribute to compliance with regulatory directives. This discrepancy
remains curious to the researcher, though there are reasons that may help to explain
these contradictory findings. A foremost reason lies in differences in data collection
instruments and the types of information they are suited to capture. The wording of
the question in the online survey as opposed to in the interviews may have shaped the
responses received. Further, interviews provided the researcher with the opportunity
to probe for further elaboration regarding the question.
Another notable limitation concerning the study sample is that those
interviewed and surveyed are primarily representatives from the administrative and/or
regulatory agencies dealing with aquaculture in the respective states. This may have
influenced the results to more positively reflect levels of compliance. Leach (2002)
found in his study of multi-stakeholder resource management groups that surveying
only a single stakeholder category can result in a more favorable depiction of the
processes in which these actors are involved (Leach 2002, 641). Additionally,
regulatory and administrative agents may not be privy to the full extent of non-
compliance with directives. They also may lack knowledge about peer monitoring
and enforcement. It is difficult to ascertain the level of bias associated with these
results as aquaculture farmers were less represented in the study sample. However,
while there may be limitations associated with the selected study sample, state
aquaculture coordinators are some of the most knowledgeable individuals in the
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aquaculture community with respect to the regulatory aspects of aquaculture and thus
are poised to offer an informed assessment of the current state of aquaculture
development and associated issues.
Understanding the factors that influence compliance is central to crafting
effective regulatory instruments. In this study, a variety of regulatory factors are
examined in an effort to discern the relative influence of those that relate to
characteristics of regulatory agents as well as those that relate to regulatees as
contributing to compliance. The findings show that an effective bundle of regulatory
instruments will recognize the influence of both types of factors.
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CHAPTER 3: DIAGNOSING REGULATORY STRINGENCY USING THE
INSTITUTIONAL GRAMMAR TOOL: A COMPARATIVE ANALYSIS OF U.S.
AQUACULTURE POLICIES
Chapter Abstract
Advances in comparative institutional analysis necessitate the development of
tools that allow analysts the ability to understand systematically the constitutive
elements that comprise institutions, such as policies, laws, and regulations. One such
tool is the institutional grammar tool (IGT). Housed within the institutional analysis
and development (IAD) framework, the IGT offers the ability to systematically
dissect institutions to gain a comprehensive understanding of the actors being
governed by them, activities that they are allowed, forbidden, and required to
perform, the spatial, temporal, and procedural boundaries of these activities, and
gradations of sanctions for non-compliance. The objectives of this chapter are two-
fold: First, to apply the IGT to understand systematically the content of regulatory
policies governing the practice of aquaculture in Florida and Virginia, United States.
Second, to demonstrate how regulatory stringency may be operationalized using the
IGT as a diagnostic tool to assess any discernable differences between policies that
are reportedly stringent and non-stringent. In pursuing these objectives, this
discussion demonstrates the IGT's applicability toward comparative institutional
analysis.
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Introduction
The crux of comparative institutional analysis is better understanding of the
formation and design of institutions to govern social behavior across contexts such as
different political jurisdictions (Majone, 1999). Institutions are the prescriptions, or
rules, that humans use to structure their interactions (Ostrom, 2005, 3). A
comparative understanding of institutions is an important endeavor for, as Cyr and
deLeon state, comparative policy analysis raises the possibility of much richer
insights concerning the influence of cultural milieu, political competition, and
governmental structures themselves on the characteristics of public policy (Cyr and
deLeon, 1975, 378). For descriptive exercises, comparative institutional analysis can
elucidate differences in institutional design characteristics. For explanatory exercises,
comparative institutional analysis aids in an examination of the factors that influence
alternative choices of institutional design within seemingly similar political and social
settings (Vining and Weimer, 1999, 39). As a first step in comparatively examining
institutions, however, it is first necessary to gain a thorough understanding of their
design and content. Such a task requires the aid of tools that allow for the systematic
dissection of institutions to decipher their various constitutive elements.
Institutions may be embodied in the form of policies, laws, or regulations or in
the form of cultural and social habits and/or patterns of behavior. Those who study
the former have demonstrated how the design of policies, regulations, and laws
provides insight into the intended objectives of policymakers within a particular
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policy domain. Either implicitly or explicitly, institutions reflect the provisions of
power in society and distributions of benefits and burdens (Schneider and Ingram,
1997). Institutions can also outline opportunities and constraints for target audiences
(Ostrom, 2005) and identify the combination of tools or instruments available to
policy makers to achieve policy objectives (Bardach, 1980; Salamon, 1989; May,
1991, 187; Sidney, 2007).
Policy scholars have developed several typologies for understanding
institutional or policy design to identify ways in which policies shape, and are shaped
by political, social, and behavioral environments (Lowi, 1964; 1972; Ostrom, 1993;
2005; Schneider and Ingram, 1997; Wilson, 1995). Some of these typologies focus on
how the participation of different types of actors involved in the policy process
affects policy design (Lowi, 1964; 1972, Wilson, 1995). Others shed light on
normative implications of policy designs (Schneider and Ingram, 1997). For example,
in their discussion of the theory of social construction and policy design, Ingram et al.
(2007) posit that "policy designs structure opportunities and send varying messages to
differently constructed target groups about how government behaves and how they
are likely to be treated by government" (Ingram et al., 2007, 98).
Policy typologies have a number of strengths and weaknesses. For example,
while highlighting important factors that affect policy design, they offer little
guidance for gaining a systematic understanding of the elements of policy design that
profoundly shape individual behavior within a policy context. Needed is an approach
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that provides meticulous analysis of the constitutive elements of policy designs: Who
exactly are the target audiences of policies? How do policies structure the behavioral
opportunities and constraints available to these different audiences by delineating
policy activities as being allowed, prescribed and forbidden? What types of sanctions
are identified for cases of non-compliance? Understanding these kinds of constitutive
elements is fundamental to gaining a comprehensive understanding of policy design
and, thus, is necessary for a comparative examination of them.
To organize diagnostic and prescriptive inquiry regarding institutional design
(Ostrom, 2011), the Institutional Analysis and Development (IAD) framework offers
policy scholars the ability to systematically understand the substantive elements that
constitute institutions. Indeed, Polski and Ostrom (1999) state that one of the
appropriate applications of the framework is as a diagnostic tool to understand the
information and incentive structure of a policy (Polski and Ostrom, 1999, 7). This
systematic approach is captured in the Institutional Grammar Tool (IGT) (Crawford
and Ostrom, 1995; Basurto et al., 2010, Siddiki et al., 2011). The IGT allows for a
comprehensive and methodical dissection of institutions and their constitutive
elements. Using the IGT to analyze institutions, one can gain a more complete
understanding of their target audiences, the activities these individuals are required,
allowed, and forbidden to perform, the conditions under which activities are/are not to
occur, and sanctions associated with non-compliance. By conceptualizing institutions
79


as placing boundaries on acceptable behavior, institutions are viewed as structuring
interactions between actors in relation to specified activities.
In this paper, the IGT is applied to compare state level regulations governing
the practice of aquaculture in Virginia and Florida, United States. Aquaculture is
defined as "the propagation and rearing of aquatic species in controlled or selected
environments" (NOAA, 1980). In the U.S., aquaculture has become an increasingly
important policy issue as the federal and state governments seek to expand the
industry to compensate for depleting wild fish stocks and the associated degradation
of marine ecosystems (Naylor et al., 2000) and reduce a seafood trade deficit that
exceeds nine billion dollars (NOAA, 2009). As the industry in the U.S. continues to
expand, so too has the number of regulatory policies designed to govern it.
Regulatory concerns relating to aquaculture include water pollution from farm
effluent, competitive feed pricing, and siting issues in public waters (Ackefors et al.,
1994). The development of aquaculture regulations has been largely decentralized
with individual states being given the autonomy to develop rules for governing the
industry. As such, regulations from state to state differ considerably to account for
differences in the local contexts surrounding the aquaculture industry.
One approach to comparing institutional designs in the study of aquaculture is
to find cases with similar industry and biophysical characteristics but whose
regulations are markedly different. Virginia and Florida represent an example of two
such cases. These two states are notably similar in their industry and biophysical
80


characteristics. Florida, however, has developed relatively more stringent regulations
to govern its industry. The aim of this paper is two-fold: First, to apply the IGT to
systematically understand the content of the aquaculture regulatory policies of
Virginia and Florida. Second, to demonstrate how regulatory stringency may be
operationalized using the IGT to assess whether there are discernable differences
between policies that are reportedly stringent and non-stringent. In pursuing this
analysis, this paper demonstrates the IGT's applicability toward comparatively
examining institutional designs.
The Institutional Analysis and Development Framework, the Institutional Grammar
Tool, and Regulatory Stringency
Institutional Analysis and Development Framework and the Institutional Grammar
Tool
The Institutional Analysis and Development (IAD) framework has been
applied extensively by scholars to study institutions that individuals use to structure
their behavior within collective action settings. Institutions within the framework are
the result of implicit or explicit efforts to achieve order and predictability among
humans by creating classes of persons (positions) who are then required, permitted, or
forbidden to take classes of actions in relation to required, permitted, or forbidden
outcomes or face the likelihood of being monitored and sanctioned in a predictable
fashion (Ostrom, 2005, 18). In other words, institutions are the rules, norms, and
strategies that govern human interaction. Institutions can be codified into formal
documents such as policies, laws, or regulations, or may be reflected in social
81


behavior and cultural practices. Sometimes institutions as formal documents are
congruent with social behavior and cultural practices and sometimes there is no
congruence at all. In other situations, there might be a mix of congruence and
incongruence. The focus of this paper is on these formal documents or institutions-
in-form.
The 1AD framework offers a foundation to guide scholars in conducting
institutional analyses for unpacking the different working parts that comprise
institutions, such as, the actors being governed by institutions, how their activities are
to be conducted, and gradations of sanctions for reprimanding behavior agreed upon
to be socially unacceptable (Ostrom, 2005). These guidelines are captured within the
Institutional Grammar Tool, originally developed by Sue Crawford and Elinor
Ostrom (1995; 2005). The purpose of the IGT is to (1) differentiate between different
types of institutional statements (i.e. rules vs. norms vs. strategies)4, where
institutional statements are the individual clauses within institutions that outline
specific actions and outcomes relating to different actors (Crawford and Ostrom,
1995); and (2) to allow analysts the ability to study how the inclusion of different
linguistic elements within institutional statements affects how individuals interpret
regulations and resultant behavioral choices.
4 The Institutional Grammar Tool can be applied to understand institutional statements that are written
down in documents such as policies, laws, and regulations, as well as those that are reflected in social
patterns of behavior. However, to date, it has only been applied to code institutions captured within
policies and regulations (Basurto et al., 2010; Siddiki et al., 2011).
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Coding institutions, such as regulations, using the IGT involves a two-step
process. First, the institution under examination (e.g. law, statute, regulation, policy,
etc.) is divided into individual institutional statements, and second, those statements
are further dissected into syntactic categories reflecting different grammatical or
syntactic elements. According to the IGT, institutional statements are
compartmentalized along the following six syntactic elements:
Attribute [A], the actor to whom the statement applies;
oBjectfB], the animate or inanimate receiver of action within the statement;
Deontic [D], the prescriptive operator that indicates whether the focal action
of the statement may, must, or must not be performed;
aim [I], the action of the statement;
Condition [C], the temporal, spatial, or procedural boundaries in which the
action of the statement is or is not to be performed; and
Or else [O], the punitive sanction associated with not carrying out the
statement directive as prescribed.
At a minimum, institutional statements must contain an Attribute, aim, and Condition.
That is, at a minimum, a statement must identify an activity, an actor associated with
it, and its temporal and/or spatial boundaries. One statement ends and another begins
when a new configuration of syntactic elements is observed; when the same or a new
actor is described in relation to the same or different activity within certain temporal,
spatial, and/or procedural boundaries. Many times institutional statements will
correspond to individual sentences within an institution, though it is also commonly 5
5 The original grammar did not include the Object as an institutional statement component. The Object
was introduced by Siddiki et al. (2011) in an effort to clarify coding guidelines and enhance the
applicability of the institutional grammar tool.
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observed that multiple institutional statements may be present within sentences. Thus,
the analyst must take great care to appropriately dissect the institution in accordance
the rules of the Tool. Below is an example of a statement from the Florida Best
Management Practices Rule containing an Attribute, oBject, Deontic, aim, and
Condition.
Example statement: Farmers must conduct systematic reviews of their operations
annually.
Attribute: farmers
oBject: systematic reviews of their operations
Deontic: must
aim:conduct
Condition: annually
Or else: N/A
When applying the IGT it is sometimes necessary to imply information
corresponding to different syntactic elements to satisfy the minimum requirements for
a phrase to constitute an institutional statement or to provide additional information
beyond just the required information. For example, sometimes statements are written
passively so that there is no explicitly stated Attribute but it is clear who the actor is
that is required to carry out a particular action based on the other passages in the
document and the situation described. For instance, a passively written version of the
aforementioned example would be: Systematic reviews of operations must be
conducted annually. There is no clearly stated Attribute in this statement, however, it
may be clear to the coder based on the context of the statement within the regulation
that farmers are those required to perform this activity. Thus, the Attribute, farmers,
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would be implied for this particular statement. As another example, where there is no
explicit Condition given within a statement, the default Condition is at all times
(Basurto et al., 2010; Crawford and Ostrom, 2005, 149). All syntactic elements can
be implied in certain cases based on the structure and arrangement of institutional
statements within a particular institution. In many cases, information from preceding
statements is carried over to subsequent statements. While a coder using the IGT will
frequently find her/himself implying information for different syntactic elements, it is
important to stress that this be done carefully with strict adherence to the institutional
context so as to not introduce innovations to the institution.
Once an analyst has coded all of the institutional statements within a given
document, data for each syntactic element can be aggregated to represent a complete
depiction of the target audiences of the institution, the actions associated with them,
conditions specifying the performance of these actions, and sanctions associated with
non-compliance. Doing so provides a general illustration of how statements are
configured within an institution to reflect the roles and responsibilities of various
actors as intended by institutional designers.
In addition to just providing a descriptive summarization, however,
aggregating coded data across syntactic elements can also reflect additional design
characteristics of institutions. For example, aggregating Deontic data from an
institution not only tells one descriptively the types and frequency of prescriptive
operators associated with the activities outlined therein, it also gives some indication
85


of the level of stringency of the institution. As Bucciarelli and Johnson-Laird note,
Deontic principles vary in the rigor that they are enforced, and in their
consequences, both for abiding by them and for violating them (Bucciarelli and
Johnson-Laird, 2005, 160). Within a shared linguistic context, individuals share some
understanding of the relative meaning and stringency of different types of Deontics.
The most often seen Deontics are must, must not, may, may not, and
should. Must and must not Deontics imply a greater sense of stringency than
may, may not, and should Deontics, as the word must implies that one is
required or forbidden to perform a particular activity, while the word may implies a
degree of allowance. As such, an institution that contains a relatively higher portion
of Deontics containing the word must may be characterized as being more stringent
than an institution in which the majority of statements are associated with Deontics
containing the word may.
Similarly, an aggregation of data in the Or else coding category does not only
tell one how many activities are linked to a sanction and/or the types of sanctions
included within a particular institution. An analysis of Or else data can also reflect the
degree of stringency of a particular institution. Institutions contain various types of
sanctions for non-compliance. Common examples of sanctions found in regulations
include the revocation of privileges, monetary penalties, and incarceration. Numerous
studies within the regulatory scholarship have demonstrated that these types of
sanctions are effective in promoting institutional compliance (Becker, 1968; Zimring
86


and Hawkins, 1973). Designers of policies, regulations, and laws appear to share an
understanding of this fact and, thus, the inclusion of sanctions within such documents
may indeed be thought of as a tool used by them to indicate a higher level of
institutional stringency.
To date, the IGT has been applied by few scholars (Basurto et al., 2010;
Siddiki et al., 2011; Speer, 2011; Schluter and Theesfeld, 2010). As such, its
analytical and empirical utility is underdeveloped. Those who have applied it have
either demonstrated or foreshadowed its capacity as a tool for analyzing institutions
cross-sectionally (Basurto et al., 2010; Siddiki et al., 2011) or over-time, as well as its
applicability in relation to policy processes theories and framework outside of the
I AD framework (Basurto et al., 2010). This paper seeks to test its usefulness in
comparative institutional analysis by offering an additional application of the Tool
within the context of U.S. aquaculture in two states and demonstrates how it can be
applied as a diagnostic tool in operationalizing the concept of regulatory stringency.
In other words, can the regulatory stringency of a particular institution, in this case
regulatory policy, be deciphered using the IGT?
Measuring Regulatory Stringency
The concept of regulatory stringency has been operationalized variably by
those studying it. For example, in their examination of the relationship between
housing prices and stringency of state level regulations, Quigley and Raphael (2005)
measured stringency of state regulations based on the number of growth control
87


measures adopted and included therein. In their international study of the relationship
between housing prices and stringency of country level land use policies, Mayo and
Shepard (1996) measured stringency in terms of the number of development controls
included within a countrys land use policies. As another example, in their study of
the relationship between foreign direct investment and stringency of environmental
regulations, List and Co (2000) measured stringency in terms of the actual amount of
monies paid by state agencies and firms as part of pollution control, prevention, and
abatement and a states ranking based on the Environmental Protection Index, which
produces a dollar ranking for each state based on a calculation of a combination of
local, state, and federal government pollution abatement efforts with firm-level
abatement expenditures (List and Co, 2000, 6).
One lesson gleaned from this sample of the literature is that measurement of
the stringency concept is largely context dependent. The study of regulatory
stringency would benefit from the ability to assess generically the stringency of a
given institution. By focusing on a comparison of syntactic elements within a given
institution as directed by the IGT, rather than case specific measures, the analyst is
better situated to conduct comparative assessments around regulatory stringency.
Based on the syntactic elements highlighted in the IGT, stringency may be thought of
as containing two operational dimensions; the first relates to the types of prescriptive
operators, or Deontics, present within an institution. The second relates to the
frequency and severity of sanctions, or Or elses, relating to non-compliance specified
88


within an institution. Because the IGT focuses on syntactic elements, in accordance
with which institutions may be more objectively coded, it has the potential for being a
useful comparative institutional analysis tool.
Below is a list of four indicators drawn from the IGT that will be examined in
this paper for comparing one stringent and one non-stringent state to see if there
are discernable differences between the two states regulations:
Diagnostic Indicator p The regulations of stringent states will contain a greater
number of total institutional statements than regulations of non-stringent states.
Diagnostic Indicator2. The regulations of stringent states will have proportionally
more must/must not Deontics and less may/may not/should Deontics than regulations
of non-stringent states.
Diagnostic Indicators: The regulations of stringent states will contain similarly
stringent Deontics across all types of Attributes.
Diagnostic Indicator4. The regulations of stringent states will contain more
statements with Or else codes that are greater in severity than regulations of non-
stringent states.
It is also important to note that the concept of stringency in this case is not
dichotomized so as to represent two opposite dimensions (i.e. stringency vs. non-
stringency). Rather, these two dimensions of the concept are treated as two varying
points on a continuum of stringency, assuming that there will be cases that will have
more or less stringent regulations than those of the two selected study states. The IGT
is applied as a diagnostic tool to ascertain the presence of certain institutional
characteristics. And, as with any diagnostic procedure, it is presumed that different
89


cases will present varying degrees of these characteristics (i.e. extreme non-
stringency vs. mild non-stringency or moderate vs. extreme stringency).
Methods of Data Acquisition
Case Selection
Two states were chosen for this study based on a comparison of national level
data obtained though an online survey of the National Association of State
Aquaculture Coordinators (NASAC) administered in 2010. The NASAC membership
is comprised of state aquaculture coordinators and knowledgeable members of the
aquaculture industry6. Thirty states were represented in the final survey respondent
sample (n=32 out of 56 NASAC members or 57% response rate). In the survey,
NASAC members were asked to provide information regarding the regulatory context
relating to aquaculture in their respective states, including levels of regulatory
compliance and factors perceived as being most influential in affecting compliance as
well as characteristics of state level aquaculture regulations. In questions pertaining to
the latter, survey respondents were asked to indicate the level of stringency of
regulations in their respective states by expressing their level of agreement with the
following statement: State regulations are very stringent in requirement and control.
6 These individuals are typically employed by a state agency charged with the regulation and/or
development of the aquaculture industry or are prominent members of the aquaculture community.
They are highly knowledgeable about the regulatory, administrative, and/or scientific aspects of
aquaculture production. Most states have one aquaculture coordinator or representative, though there a
few states that have more than one. At the time the survey was administered, there were 56 individuals
included in the NASAC membership database, each representing one U.S. aquaculture producing state.
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Using data collected through the survey of NASAC members, Virginia and
Florida were chosen for comparison because their regulations were reported to vary in
terms of regulatory stringency. But the two states were reportedly similar on a variety
of regulatory and industry characteristics including levels of levels of compliance.
Table 1.4 provides a list of characteristics upon which the two states were compared
demonstrating similarity between the two cases on all variables except for regulatory
stringency in which Florida was reported as being having more stringent regulations
than Virginia. For example, pertaining to political and regulatory characteristics, both
states were reported as having very clear regulations, inexpensive aquaculture
permits, and moderate involvement of the industry in reporting non-compliance. With
respect to social, community, and industry characteristics, both sates were reported to
have significant start-up costs associated with entering the aquaculture industry,
moderate amounts of domestic competition, and low levels of user conflicts (i.e.
between aquaculture producers, commercial fishermen, recreational fishermen, etc.).
In addition to data provided in the NASAC survey, background research
conducted on the two states indicated that they were comparable on several other
dimensions that may serve as control measures. For example, both states were
reported as being supportive of aquaculture development. As such, the design of
aquaculture regulations would not be expected to be influenced by varying levels of
state support of the industry. Second, in terms of aquaculture product, Virginia and
Florida were both regarded as leading shellfish producers in the U.S. Finally, these
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