IMPORTANCE OF SOCIOPOLITICAL CONTROL, SENSE OF COMMUNITY AND
CITIZEN PARTICIPATION IN TOURISM PROMOTION AND POLICY
By
Eunseong Jeong

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Community, Agriculture, Recreation and Resource Studies
2012

ABSTRACT
IMPORTANCE OF SOCIOPOLITICAL CONTROL, SENSE OF COMMUNITY AND
CITIZEN PARTICIPATION IN TOURISM PROMOTION AND POLICY
By
Eunseong Jeong
Since the rise in importance of community-based and sustainable tourism, the
concepts of citizen participation, empowerment, and sense of community have emerged
as significant areas of study. Active citizen participation has been recognized as a
cornerstone of contemporary policies and programs in diverse fields including the
tourism domain. Active citizen participation enhances policy control and leadership
competence, which are two key ingredients of empowerment. Empowered citizens can
contribute to the development of creative solutions and influence policy-making
processes in tourism. Citizen participation and empowerment are derived from
awareness of citizens’ community which they belong. The sociopolitical control scales
has been used to test the association between empowerment and citizen participation
while sense of community is a key construct for contributing to find the association three
notions in influencing policy-making. This study is one of few studies that empirically
examine the relationship between citizen participation, sociopolitical control, and sense
of community. The empirical results demonstrate: 1) sociopolitical control and sense of
community as valid construct in the tourism context; 2) group differences in
psychological empowerment and sense of community; 3) relationship among
socioeconomic status, sense of community, sociopolitical control, tourism participatory
behavior, familiarity of tourism campaign, and perceived impact of tourism policy; and 4)
partial mediation effects between variables and sociopolitical control. These results can

contribute to the tourism field by providing policymakers and analysts a valid and
reliable quantitative tool for evaluating successful policy outcomes. Furthermore, the
study provides empirical evidence to tourism policymakers and agencies for evaluating
the social outcomes of their programs with focus on community-based programs and
initiatives. This approach can be used in concert to pursue sustainable tourism policies
and promotion by obtaining strong support and consensus from local communities.

Dedicated to My Parents, Hyungbong Jeong and Youngmi Cho
&
My Wife, Yonghwa Park and My Daughter, Soring Jeong

iv

ACKNOWLEDGEMENTS
I have just arrived at a destination in my life travel. During this travel, my people
have encouraged and given me their sincere and thoughtful advice for the travel.
I would first like to gratefully and sincerely thank Dr. Dennis B. Propst, my major
professor and committee chair, for his guidance, patience, and most importantly, his
mentorship during my doctoral studies at Michigan State University. He has been
invaluable on both an academic and a personal level for which I am extremely grateful.
He has always been supportive whenever I asked something of him.
My sincere thanks also go to my committee members, Dr. Maureen H.
McDonough, Dr. Mark I. Wilson, and Dr. Daniel T. McCole for guiding my research for
the past several years and helping me to develop my academic background. Dr.
McDonough has led me to build my knowledge in citizen participation. Dr. Wilson has
always listened to my academic and professional plans during my graduate studies at
MSU. Special thanks go to Dr. McCole, who was willing to participate in my final
committee at the last moment. I also would like to thank the Michigan Applied Public
Policy Research (MAPPR) Grant and the Institute for Public Policy and Social Research
at Michigan State University. My research was initiated under their support.
I wish to express my deepest gratitude to Ms. Kyungsik Irene Shim, Director of
Global Programs at the School of Planning, Design and Construction at MSU. I can do
everything through her endless support for my academic and outreach activities.
Furthermore, her family, Ms. Youngsik Joanna Shim and Mr. James Seong, are my
American family and their love have encouraged during my time in the United States.

v

My heartfelt appreciation is also extended to Dr. Seung Hyun Kim, Dr. Jaemin
Cha, Dr. Muwoong Kim, Hoejin Hong, Hyunwoo Park, and Soyoung Ahn. Their
friendship and brotherhood always makes me happy and helps me to know God’s love.
Additionally, I would like to express my deep appreciation to my academic family, Dori
Pynnonen and Leanna Popp. They are always willing to discuss and work to help me in
my research and personal matters.
I would like to thank Dr. Chanbok Woo, my academic advisor in South Korea,
who encouraged and inspired my professional passion for tourism. I also thank Dr.
Heechan Lee who gave his broad methodological insight to me when I first conducted
data analyses. Special thanks go to Dr. Hansoo Kim, without his financial support and
encouragement my doctoral studies would not have been successful.
I acknowledge, appreciate, and return the love and support of my family in Korea,
without whom I would be lost. My parents Hyungbong Jeong and Youngmi Cho have
been anchors in my life. Without their support and patience, my dissertation would not
be done. I also indebt my sister Dr. Eun Jeong and my brother-in-law Mr. Kicheol Shin
because they are always showing their love to me and my family. I truly miss my
nephew, Hojin Shin whom I have yet to meet.
My utmost appreciation must go to my wife, Yonghwa Park. Since my senior
year at college, Yonghwa has always supported everything in my life. Her patience and
love are beyond description. Finally, I not only greatly thank, but express regret to my
lovely daughter, Sorin. I did not have enough time to play with her; however, she
always expressed her love to me. Thank you and I love you, Sorin.

vi

Table of Contents
LIST OF TABLES ............................................................................................................ix
LIST OF FIGURES ..........................................................................................................xi
Chapter 1 ........................................................................................................................ 1
Introduction .................................................................................................................. 1
Study Purpose .......................................................................................................... 7
Study Objectives ....................................................................................................... 7
Delimitations ............................................................................................................. 8
Chapter 2 ........................................................................................................................ 9
Literature Review ......................................................................................................... 9
Tourism Promotion ................................................................................................... 9
Citizen Participation and Community Involvement .................................................. 12
Psychological Empowerment and Sociopolitical Control ........................................ 16
Sense of Community .............................................................................................. 21
Problem Statement ................................................................................................. 26
Definitions of Major Variables ................................................................................. 26
Conceptual Model and Hypotheses ........................................................................ 27
Chapter 3 ...................................................................................................................... 30
Methods ..................................................................................................................... 30
Study Authorization................................................................................................. 30
Sample Design ....................................................................................................... 30
Data Collection Procedure ...................................................................................... 32
Survey Measurement .............................................................................................. 33
Data Analysis .......................................................................................................... 36
Chapter 4 ...................................................................................................................... 41
Results ....................................................................................................................... 41
Socio-demographic Characteristics of Survey Respondents .................................. 41
Familiarity with the Pure Michigan Campaign ......................................................... 44
Perceived Impact of the Pure Michigan Campaign ................................................. 46
Citizens’ Tourism Participatory Behavior ................................................................ 49
vii

Reliability and Normality of Major Constructs ......................................................... 50
Confirmatory Factor Analysis of Major Constructs .................................................. 52
Assessment of Reliability and Validity .................................................................... 58
Level of Psychological Empowerment and Sense of Community ........................... 60
Construct Validity of the Measurement ................................................................... 65
Testing Hypotheses ................................................................................................ 68
Chapter 5 ...................................................................................................................... 83
Discussion and Conclusion ........................................................................................ 83
Summary of Key Findings ....................................................................................... 83
Theoretical Implications .......................................................................................... 87
Practical Implications .............................................................................................. 90
Limitations .............................................................................................................. 92
Directions of Future Study ...................................................................................... 94
APPENDICES ............................................................................................................... 97
APPENDIX A. Subset of SOSS that Generated the Data Used in this Study ............ 98
APPENDIX B. Operational Definition of Major Variables ......................................... 104
References .................................................................................................................. 105

viii

LIST OF TABLES
Table 1.

The Margins of Error for Each Region and the Total Statewide Sample ..... 33

Table 2.

Steps in Establishing Mediation effects through the OLS Regression ........ 39

Table 3.

Socio-demographic Characteristics of Survey Participants ........................ 43

Table 4.

Familiarity with Pure Michigan Campaign ................................................... 44

Table 5.

Mean Differences in Familiarity with the Pure Michigan .............................. 46

Table 6.

Respondents’ Perceived Impacts of the Pure Michigan Campaign ............. 47

Table 7.

Mean Differences in Perceived Statewide Impact of Pure Michigan ........... 48

Table 8.

Mean Differences in Perceived Local Impact of Pure Michigan................... 49

Table 9.

Respondents’ Participatory Activities in Tourism Policy and Planning ........ 50

Table 10. The Results of Reliability of TPC, LC, and SOC.......................................... 51
Table 11. Normality Test Results of Observed Variables ............................................ 52
Table 12. Respondents’ General Perspectives of TPC, LC, and SOC ........................ 54
Table 13. The Recommended Goodness-of-Fit Indices for CFA ................................. 57
Table 14. Comparison of the Proposed and Modified Full Measurement Models ....... 58
Table 15. The Results of CFA for the Modified Measurement Model .......................... 59
Table 16. Mean Differences in Tourism Policy Control................................................ 61
Table 17. Mean Differences in Leadership Competence............................................. 63
Table 18. Mean Differences in Sense of Community ................................................. 65
Table 19. Multivariate Analysis of Covariance Comparing SPC Profile Group with
Familiarity of Tourism Campaign, Tourism Participatory Behavior, Perceived
Impact of Tourism Policy, and Sense of Community .................................... 67
Table 20. Regression Analysis for H1 ......................................................................... 68
Table 21. Regression Analysis for Modified H1 ......................................................... 70
Table 22. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Tourism Participatory Behavior ......................................... 71
Table 23. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Socioeconomic Status ...................................................... 73
Table 24. Measuring Mediation Effect between Tourism Participatory Behavior and
Socioeconomic Status through Socioeconomic Status ................................ 74
ix

Table 25. Measuring Mediation Effect between Tourism Participatory Behavior and
Socioeconomic Status through Familiarity of Tourism Campaign ............... 76
Table 26. Measuring Mediation Effect between Tourism Participatory Behavior and
Sociopolitical Control Scale through Perceived Impact of Tourism Policy ... 77
Table 27. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Familiarity of Tourism Campaign ...................................... 79
Table 28. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Perceived Impact of Tourism Policy ................................. 80

x

LIST OF FIGURES
Figure 1.

IAPS Spectrum of Public Participation ....................................................... 13

Figure 2.

Three Interrelated Components of Psychological Empowerment ............... 19

Figure 3.

Four Elements of Sense of Community ...................................................... 24

Figure 4.

Conceptual Model of Path Analysis of This Study ...................................... 29

Figure 5.

Six Regions in the State of the State Survey, Spring 2011 ........................ 31

Figure 6.

Mediation Regression Model ...................................................................... 40

Figure 7.

Proposed Measurement Model for Confirmatory Factor Analysis .............. 56

Figure 8.

Classification of SPC Profile Group ............................................................ 66

Figure 9.

The Relationship between SPC and the Predictors (Initial Model) ............ 69

Figure 10. The Relationship between SPC and the Predictors (Modified Model) ....... 70
Figure 11. Testing H2 for Measuring Indirect Effect ................................................... 72
Figure 12. Testing H3 for Measuring Indirect Effect ................................................... 73
Figure 13. Testing H4 for Measuring Indirect Effect ................................................... 75
Figure 14. Testing H5 for Measuring Indirect Effect ................................................... 76
Figure 15. Testing H6 for Measuring Indirect Effect ................................................... 78
Figure 16. Testing H7 for Measuring Indirect Effect ................................................... 79
Figure 17. Testing H8 for Measuring Indirect Effect ................................................... 81
Figure 18. The Results of Testing Mediation Hypotheses .......................................... 82

xi

Chapter 1
Introduction
The advancement of technology and expansion of the dissemination of
knowledge contribute to individuals taking more interest in their sociopolitical
environments and increase opportunities to participate in policy-making processes. In
the last few decades, there has been an increase in individual attention to values of
locality and community, which are beneficial in establishing long term and sustainable
policies and programs.
Citizen participation and empowerment are critical elements of democratic policymaking and a subject of citizens’ everyday life (Fung & Wright, 2003). To date, most
policies and programs as well as regulations emphasize the significance of these two
topics. President Obama (2009) stressed that government should be transparent,
participatory, and collaborative which highlighted the importance of citizen participation
and empowerment as significant feature of contemporary policy-making in the United
States.
Contemporary governmental policies and programs often include procedures for
collecting and reflecting upon citizens’ opinions as well as achieving citizens’ consensus
for the policies and programs. A variety of democratic participation approaches have
been introduced and implemented in order to enhance consensus through voting, public
hearings, and citizen committees. These forms of citizen participation have been widely
adopted in policy-making processes; however, they are sometimes criticized as forms of
indirect democracy.

1

Under the indirect democracy system, citizen participation plays a limited role in
democratic process (Parry, Moyser, & Day, 1999). Most societies utilize representative
democracy systems as indirect democracy, in which citizens elect representatives.
Citizens believe that the representatives advocate their need and opinions to policymaking bodies. These features of indirect democratic systems cause citizens to rely on
public officials and administrators as well as their representatives (Roberts, 2004).
The skeptical view of indirect democracy has led citizens and researchers to
search for more active and direct participatory mechanisms to gain more direct
involvement in policy-making. It is evident that there has been a resurgence of interest
in policy-making through diverse forms of citizen participation and empowerment in
policy-making since the late 20th century (Chamber, 2003; Fung & Wright, 2003; Manzo
& Perkins, 2006; Reddel & Woolcock, 2004; Simpson, 2008; Umbach & Wishnoff,
2008).
In the United States, citizen participation and empowerment are rooted in two
different philosophies. Thomas Jefferson argued for direct democracy, while James
Madison advocated for representative democracy that relies on elected officials who
make decisions for citizens (Clarke & Cortner, 2002). Even though their philosophies
were different, both emphasized active citizen participation and empowerment as a
cornerstone of American society.
In the 20th century, American society witnessed the evolution of citizen
participation in fields such as land use policy, urban housing, public education,
conservation of natural resources, public health, and tourism (Pennington, 2004;

2

Roberts, 2004; Smith & Propst, 2001). As a result, governments from federal to local
levels recognize citizen participation as a key strategy to enhance healthy communities.
As an essential tool to promote a more democratic perspective in the policymaking processes, citizen participation experts have emphasized the importance of
public input in diverse contexts of planning and development. As a result, many
contemporary policy and planning organizations have proposed strategies, programs
and regulations to respect the need for citizen participation and empowerment. Citizen
participation and empowerment require evaluation through proven evaluation tools
because there is a need for finding whether mechanisms of citizen participation and
empowerment are successful (Rowe & Frewer, 2000).
Citizen participation has been a growing topic in tourism as business,
development, and policy-making success are often dependent upon it (Keogh, 1990;
Ruiz-Ballesteros, 2011; Timothy, 2007). Tourism is a system of which tourist
destinations and host communities are an integral part. Citizen’s active and voluntary
participation is important because without access to natural and cultural resources and
local level tourism infrastructure, enthusiasm and hospitality, tourists hardly experience
what tourism attractions promise.
The success of tourism promotion also relies on a close relationship with host
communities. Influence on host communities has been widely recognized as an
element if the tourism promotion aims to be sustainable in the long term (Pérez &
Nadal, 2005). Active citizen participation plays an important role to minimize the conflict
between host communities and tourism development for pursuing long-term capacity
while satisfying the demand of tourists (Liu, 2003).
3

It is necessary for tourism policy-making and promotion to simultaneously pursue
economic enhancement, environmental protection and socio-cultural preservation in
host communities (Lansing & De Vries, 2007). Citizen participation plays an important
role in sustaining socioeconomic, cultural, and natural environments of tourism host
communities. Members of host communities can articulate the shared values that
should be sustained for protecting their communities under tourism development,
planning, and policies. They also possess the means by which these values are
expressed.
Citizen support and motivation to participate in tourism policy-making and
promotion come from a variety of sources, beginning with awareness of policies and
programs. Hence, it is important to evaluate community assets, which create
momentum to carry forward policy and program goals. Two correlates of momentum
are individuals’ sense of community and active participation in the implementation of
tourism policy and promotion (Peterson, Speer, & McMillan, 2008). Active participation,
in turn, enhances policy control and leadership competence, which are two key
ingredients of empowerment (Ohmer, 2007). Empowered citizens can contribute to the
development of creative solutions and influence policy-making processes in tourism.
The sociopolitical control scale (SPCS) has been used to examine the
association between empowerment and citizen participation since the 1990s. The
SPCS measures three primary dimensions of empowerment: a citizen’s sense of
leadership efficacy (Leadership Competence), the belief that one can influence the
political world (Policy Control), and participatory behaviors. Empowerment-related
outcomes of community-based programs and projects have been assessed by adapting
the SPCS to various contexts and applications in the last few decades.
4

Sense of community (SOC) is a key construct in community psychology which
contributes to find the association between participatory behavior and sociopolitical
control in influencing policy-making that impacts tourism outcomes. SOC refers to the
connections between humans and other social groups. Research has found that SOC
explains significant variation in citizen participation and empowerment in community
groups and activities (Peterson & Reid, 2003; Peterson, Speer, & Hughey, 2006). Since
the rise in importance of community-based and sustainable tourism, the concepts of
citizen participation, empowerment, and sense of community have emerged as
significant areas of study. Tourism research has emphasized that citizens feel tied to
their communities and empowered to engage in policy-making relevant to tourism
promotion and development (Akama & Kieti, 2007; Blackstock, 2005; Cole, 2006).
Community-based programs and projects generally try to achieve healthy and
sustainable communities through economic enhancement. In order to rejuvenate
national, regional, and local economies, many governmental agencies have proposed a
range of policies. The tourism industry has been recognized as a leading economic
force and has the potential to play a significant role in rejuvenating the economy of
nations and local communities. Mass tourism, however, is associated with some
negative effects such as destruction of natural, ecological, and socio-cultural
environments of tourism destinations (Chapman & Speake, 2011). In order to address
the tension between economic growth and protection of tourism destinations, citizen
participation and empowerment are critical factors.
Many governments have proposed a variety of policies to promote their tourism
industries and revitalize their economies (Pearce, Filep, & Ross, 2011; Wang & Pfister,
2008). In the United States, most governmental entities from local to federal have
5

established tourism promotion campaigns in order to stimulate their economies.
Tourism campaigns, as part of an overall tourism promotion strategy, are mechanisms
for advertising tourism destinations to other places and differentiating themselves in the
tourism market (Pike, 2005).
The state of Michigan has recently experienced an economic downturn that has
caused an increase in the unemployment rate and population decline. Many policies
and programs have been established and implemented to regenerate the state’s
economy. One of the more well-known state economic growth programs is Pure
Michigan, an advertising and branding campaign designed to stimulate the state of
Michigan’s economic growth through tourism.
Since the Pure Michigan campaign launched in 2006, the campaign has had a
positive effect on the state’s tourism industry and contributed to promoting the state’s
image brand. Due to the campaign’s success, its budget has, with the exception of
2010, continuously increased since 2006. In 2011, the state legislature authorized, and
Michigan Governor Snyder signed, a bill transferring $25 million to the Pure Michigan
campaign from the 21st Century Jobs Trust Fund. The continuous investment in the
campaign has improved the state’s image as a tourism destination, which in turn has
increased travel, visitor spending, and state tax revenue (Propst & Jeong, 2011).
Travel Michigan, the official agent of the Pure Michigan campaign, announced
that the campaign has had a ripple effect on the state’s tourism and economy. As of
2011, the Longwood International (2012) released data showing that the campaign has
motivated 10.4 million trips to the state with visitors spending approximately 2,937
million dollars. Further, visitors have paid 208.1 million dollars in Michigan sales tax
6

since 2006. For generating a sustainably positive impact to both the state and local
communities through a tourism campaign like Pure Michigan, sociopolitical indicators of
success--such as local level sentiments of empowerment and participation--should be
addressed.
Study Purpose
The primary purpose of this study is to examine how a sense of community and
citizen participation in tourism policy-making affect a topic-specific measure of
sociopolitical control. Additionally, finding the association between these constructs and
differences based on citizen characteristics provides recommended strategies to
tourism policymakers for enhancing policy success and increasing support and
consensus from the host communities of tourism destinations.
The results of this study will contribute to the tourism field by providing
policymakers and analysts a valid and reliable quantitative tool for evaluating successful
policy outcomes. Knowing how empowered citizens feel, whether or not they see
themselves as leaders and current actions they are taking to be active participants
should be of broad interest to policymakers. This study will demonstrate how
sociopolitical control and sense of community maintain their psychometric properties in
the tourism domain. In addition, host and destination communities are vital to the
overall tourism system. Community psychologists attempt to improve overall health of
communities by studying behaviors. Likewise, it is necessary to study individual
behaviors and outcomes in tourism policy-making for this reason.
Study Objectives

7

In the tourism context, this study is one of few studies empirically examining the
relationship between sense of community, citizen participation, and sociopolitical
control. The first objective of this study, therefore, is to examine whether the SPC can
be modified for use in the tourism domain while maintaining psychological rigor. The
second objective of this study is to assess group differences in psychological
empowerment and sense of community. The third objective is to explore the
relationship among socioeconomic status (SES), sense of community (SOC),
sociopolitical control (SPC), tourism participatory behavior, familiarity with a tourism
campaign, and perceived impact of a tourism policy. The fourth objective of the present
study is to examine partial mediation effects between independent variables and SPC.
Delimitations
There are two delimitations in this study. First, it is not feasible to evaluate the
entirety of tourism policies and promotional campaigns in one study. Hence, the subject
of this study was the Pure Michigan campaign which began in 2006. This campaign is a
representation of Michigan’s tourism policy to attract out-of-state visitors. Second, the
focus and variables of this study pertain to psychological, as opposed to actual or
behavioral empowerment. This is because there has been much research on
psychological empowerment in the community psychology literature in recent years. In
this literature, psychological empowerment has been found to be associated with
benefits of numerous community interventions such as public health programs,
substance abuse prevention program, and so forth.

8

Chapter 2
Literature Review
The literature relevant to this study is presented in this chapter. In order to follow
a logical composition, the literature is reported under the following topics: (1) tourism
promotion; (2) citizen participation and community involvement; (3) psychological
empowerment and sociopolitical control; (4) sense of community. The chapter
concludes with problem statement, definitions of major variables, and conceptual model
and hypotheses.
Tourism Promotion
Marketing is an essential component of success in public and private sectors
(Hutt & Speh, 2010; Irwin, 2002). The tourism industry is not only comprised of a
variety of sectors, but also is a dynamic and complex system (Rodolfo, 2008; S.
Williams, 2004). As such, public policy makers and private businesses devote
substantial resources to appropriate and efficient marketing strategies for promoting
their tourism products.
Promotion is a cornerstone of successful tourism-related activities (A. Williams,
2006). As an instrument for promoting tourism, a tourism campaign attempts to
increase the spread of tourism in destination communities, build opportunities to have
more destination publicity to attract tourists, and enhance destination images (Cano &
Prentice, 1998; Dore & Crouch, 2003). Organizations, businesses, and governmental
authorities of the tourism industry have emphasized tourism campaigns for advertizing
their tourism attractions and products through a variety of media such as radio,
television, film and the Internet (Butler, 1990; Connell, 2005).
9

Locations that are featured on television shows, documentaries, or movies, for
instance, have grown to be attractive tourism destinations (Hudson & Miller, 2005).
Tourist behaviors are significantly influenced by Internet blogs that include visual
information (Lin & Huang, 2006). The positive impacts of media-based tourism
campaigns have led tourism promotional campaigns to emphasize images of tourism
destinations (Avraham & Ketter, 2008; Chaudhary, 2000).
In the United States, most state and local governments have established tourism
promotion related policies and strategies in order to stimulate or regenerate their
economies. As part of the tourism promotion, campaigns are a mechanism for
advertising tourism destinations to other places and tourists, while differentiating
themselves in the tourism market by creating brands (Pike, 2005). Brand-based tourism
promotion, for example, has attracted significant numbers of out-of-state tourists to Iowa
(Mak, 2011).
In the United States, scholars prefer to use “destination branding” rather than
“place branding.” According to Cai (2002, p. 722), “destination branding can be defined
as selecting a consistent element mix to identify and distinguish it through positive
image branding.” Destination branding is a strategic attempt by tourism destinations to
make their identities and characteristics unique and distinguishable (Wright, 2007).
Hosany and his colleagues (2006) asserted that destination branding has been
essential for making competitive tourism products in the tourism market. A recent study
revealed that some state’s tourism promotion campaigns have evolved into destination
branding such as “Explore Minnesota,” “Ohio, Too Much Fun for Just One Day,” “Pure
Michigan,” and “Awaken Florida” (Propst & Jeong, 2011).

10

For a leading tourism promotion campaign to evolve into destination branding,
sustained funding is critical. In fewer than half of the states in the United States, the
financial source for tourism promotion is the general tax fund (Bonham & Mak, 1996;
Deskins & Seevers, 2011; Shield, 2006). Additionally, some states tourism promotion
funds come from other sources such as tourism industry-related taxes, membership
fees, and lottery ticket sales (Shield, 2006). For instance, the total budget of Alaska’s
core marketing program is $11.7 million with $9 million coming from state government
and the rest provided by the state’s tourism industry through the Alaska Travel Industry
Association (Alaska Travel Industry Association, 2010).
Many states have invested heavily in tourism promotion to recover from
economic slumps. In the Midwest states for fiscal year 2010, Illinois spent $48.9 million;
Michigan contributed $18.7 million; Wisconsin paid $13.1; Minnesota expended $15.4
million; Ohio paid $5.4 million; and Indiana disbursed $2.8 million (Steinke, 2010). To
sustain continuous funding sources, states need to show the positive impacts of their
investments. The impact indicator of choice tends to be return on investment (ROI),
which is used to demonstrate positive economic impacts from tourism promotion
spending (Longwoods International, 2010; Strategic Marketing & Research Inc., 2007).
Since tourism is a system, of which destinations and host communities are
integral parts, sociopolitical indicators of success, such as local level sentiment of
empowerment and participation in tourism planning efforts, are as relevant as return on
investment (Bornhorst, Ritchie, & Sheehan, 2010; Propst & Jeong, 2011). Several
studies argued that citizen participation and community involvement are significant
aspects of long-term oriented tourism promotion (Fallon & Kriwoken, 2003; Li, 2006;
Mitchell & Reid, 2001).
11

In order to achieve sustainable tourism, promotional strategies are part of the mix
and social impacts on host communities are as relevant as economic impacts (Hardy &
Beeton, 2001; Saarinen, 2006). Active citizen participation is a key element of
maximizing positive social impacts and minimizing negative ones (Byrd, Bosley, &
Dronberger, 2009; Dredge, 2006; Haley, Snaith, & Miller, 2005).
Tourism psychological studies have highlighted citizen participation and
community involvement by examing such diverse constructs as place attachment
(Gross & Brown, 2008), community identity (Wang, Yu, & Fesenmaier, 2002),
community attachment (Anderreck, Valentine, Knopf, & Vogt, 2005), and sense of place
(Derrett, 2003). Citizen participation and community involvement serve as tools to
promote integration of tourism development and local communities, minimizing existing
conflicts and negative impacts on tourism destinations (Mannigel, 2008).
Citizen Participation and Community Involvement
Citizen participation has been used as an integral part of democratic decision
making since the latter part of the 20th century (Laurain & Shaw, 2009). According to
the International Association for Public Participation (IAP2), public participation occurs
along a spectrum ranging from informing to consulting, involving, collaborating, and
empowering. The IAP2’s spectrum classifies public participation according to types of
engagement with stakeholders. The level of public impact increases as citizens’
progress from ‘informing’ through to ‘empowering’ types of participatory behaviors
(International Association for Public Participation, 2007).

12

Figure 1. IAP2 Spectrum of Public Participation (Adapted from the IAP2)

Public Participation

Increasing Level of Public Impact

Inform

Consult

Involve

Collaborat
e

Empower

Wellman and Propst (2004) indicated that citizen participation can result in
improved public understanding and support for policy-making. Citizen participation can
also address diverse stakeholders’ needs and preferences by cultivating better dialogue
and broadening consistencies involved in decision-making (Thompson, Elmendorf,
McDonough, & Burban, 2005). There are two distinct goals for participatory
approaches: participation as a means to increase efficiency, and participation as an end
for empowerment and equity (Clever, 1999; Diamond, 2002). Mannigel (2008) found
participation as an end empowers local stakeholders.
Empowerment is indispensable in order for citizens to address the social and
political changes in their lives (Laverack & Wallerstein, 2001). The degree of citizen
empowerment is one way to consider the effectiveness of citizen participation in policymaking processes. If the goal of citizen participation is to empower citizens and
communities, policymakers need to provide: 1) education for citizens about the realities
of policy-making processes; 2) a means of informing civic officials about the processes;
and 3) more chances for dialogue between community residents and other stakeholders
13

(Thompson, et al., 2005). These three provisions can empower individuals to become
leaders and activists, who can, in turn, facilitate the involvement of entire communities.
Community involvement is described as specific roles that community members
play in supporting community activities that can occur within or transcend local
boundaries (Nettles, 1991). Community involvement refers to individual engagement in
organized community group activities while citizen participation is community-action
behavior which focuses on individual civic participation (Speer, Jackson, & Peterson,
2001). Community involvement has long been advocated as an integral part for
addressing sustainable community development. Both public and private policies and
development, for instance, have implemented community involvement by organizing
citizens’ advisory committees, community partnerships, deliberative polling, and so
forth.
Both citizen participation and community involvement have been identified as
prerequisites to engagement in policy-making in a variety of fields such as
environmental decision making (Konisky & Beierle, 2001), urban planning (Matsuoka &
Kaplan, 2008), and natural resource management (Parkins & Mitchell, 2005;
McDonough, Russell, Nancarrow, & Burban, 2002). Likewise, tourism studies have
pointed out the importance of citizen participation and community involvement. Citizen
participation in tourism creates networks between businesses and local communities in
locales with booming tourism economies (Bahaire & Elliot-White, 1999; Byrd, 2007;
Lynn, 1992; Mbaiwa, 2005). Some studies have argued that community-based tourism
is derived from active citizen participation from host communities (Choi & Sirakaya,
2006; Reed, 1997; Sebele, 2010; Simmons, 1994). Research has also claimed that

14

citizen participation plays a significant role in achieving sustainable tourism (Bahaire &
Elliot-White, 1999; Byrd, et al., 2009; Cole, 2006; Joppe, 1996; Tosun, 2001).
It is considered important for local communities to take responsibility for their
engagement and participation in the tourism policy-making process (Jackson &
Morpeth, 1999). Furthermore, even though geographical boundaries significantly affect
policy-making in regard to tourism, uniformity in attitudes in local communities should
not be expected (Strickland-Munro, Allison, & Moore, 2010). Hence, it is necessary to
consider the diverse voices of local stakeholders for involving host communities of
tourism destinations.
Community involvement is an important element of collaborative policy-making
processes in the tourism context (Buckley, Pickering, & Weaver, 2003). To achieve
active community involvement, government and development authorities have the
responsibility to encourage stakeholders to take action toward policy-making processes
(d'Angella & Go, 2009; Keogh, 1990; Lewis & Newsome, 2003). This requires
organizers and planners to efficiently and openly communicate with the public
(Yankelovich, 1991).
Jamal and Getz (1995) claimed that community involvement allows government
and development authorities to understand local norms and values that need to be
addressed through collaborative planning. Yates and his colleagues (2010) proposed
three factors that enhance community involvement and collaboration among
stakeholders as follows: 1) community ownership; 2) accessibility of planning or
management resources; and, 3) maintaining a broad stakeholder base by involving local
NGOs.
15

As can be seen thus far, tourism research in the last few decades has indicated
the strong role of citizen participation and community involvement in tourism
policymaking and planning (Aas, Ladkin, & Fletcher, 2005; Anderreck, et al., 2005;
Bahaire & Elliot-White, 1999; Charlton & Essex, 1996). Parallel to tourism findings,
community psychological research has argued that psychologically empowered
communities and citizens influence their external sociopolitical environments and also
act to improve their circumstances (Ohmer, 2007; Peterson & Zimmerman, 2004;
Rapport, 1984; Zimmerman, Israel, Schulz, & Checkoway, 1992).
Many studies have adapted the sociopolitical control scale (SPCS) for evaluating
empowerment-related outcomes of community-based programs and projects (Peterson,
Lowe, Hughey, Reich, et al., 2006). Psychological empowerment of citizens is an
indicator of the success of community participation in policymaking processes, including
tourism promotion.
Psychological Empowerment and Sociopolitical Control
During the past several decades, empowerment has been of academic and
practical interest. Empowerment is defined as a mechanism that links an individual’s
mastery over their sociopolitical environments and their strengths and competencies
(Perkins & Zimmerman, 1995; Rappaport, 1981; Rapport, 1984; Speer, 2000).
Similarly, empowerment represents the motivational perspective of self-efficacy
(Conger & Kanungo, 1988) and is defined as “increased intrinsic task motivation
manifested in a set of four cognitions, which are meaning, competence, selfdetermination, and impact, reflecting an individual’s orientation to his or her work role”
(Speitzer, 1995, p. 1143; Thomas & Velthouse, 1990b).
16

Power is at the heart of the concept of empowerment (Page & Czuba, 1999).
Empowerment is the act of individuals embracing the opportunity to make their
sociopolitical decisions by expanding their autonomy in decision making (Chiang &
Jang, 2008; Vogt, 1997). According to Wilkinson (1998, pp. 45-46) empowerment can
be classified by five types: “information sharing; upward problem solving; task
autonomy, attitudinal shaping; and self-management.” Conceptual involvement of
empowerment consists of two factors: The internal-psychological factor embodies a
competence, responsibility, sense of control, and future orientation, whereas the
situational-social factor of empowerment includes interpersonal skills, organizational
skills, and control over resources (Kosciulek, 2005; Schalock, 2001; Stein, 1997;
Zimmerman, 1995).
Empowerment is a process by which individuals gain greater control over their
own lives and participate in the lives of their primary and purposive groups (Perkins &
Zimmerman, 1995; Speer, et al., 2001; Tremblay & Gutberlet, 2010; Zimmerman, et al.,
1992; Zimmerman & Rapport, 1988). The notion, therefore, includes two aspects:
individual and organizational empowerment. Zimmerman (1990b) argued that the
former focuses on individuals’ abilities to have efficacy and control in decision-making,
while the latter emphasizes a collaborative atmosphere between different members
within an organization. Hence, he highlighted that empowerment substantiates an
interactional relationship between individuals and their sociopolitical environment.
Speer (2000, p. 52) provided the distinction between empowerment and
psychological empowerment (PE) as follows: “empowerment at an individual level of
analysis is focused solely on the individual without considering contextual influences
whereas psychological empowerment embraces the reciprocal influences and
17

confluence of macro and micro level forces that impact the emotional, cognitive, and
behavioral aspects of individuals.” Empowerment refers to the act of empowering
others while psychological empowerment denotes the internal state of the individual
being empowered (Menon, 2001).
The term PE as a self-perception of competence is not merely individualism
because it includes not only active involvement in an individual’s community but also a
direct understanding of one’s sociopolitical circumstances (Zimmerman, 1995, 2000;
Zimmerman, et al., 1992). Research has discovered that the degree of PE varies
according to the sociopolitical situation that one encounters (Foster-Fishman, Salem,
Chibnall, Legler, & Yapchai, 1998; Speer, 2000; Zimmerman, 1990b, 1995).
According to Zimmerman’s (1995) framework, PE is composed of three
interrelated parts: intrapersonal, interactional and behavioral. The intrapersonal
component of PE involves self-perceptions of competence, efficacy and mastery
(Ohmer, 2007; Perkins & Zimmerman, 1995; Speer, et al., 2001). The interactional
component of PE refers to awareness and comprehension of the political situation; and
the behavioral piece refers to actions taken purposefully to affect outcomes (Peterson,
Lowe, Hughey, Reich, et al., 2006).

18

Figure 2. Three Interrelated Components of Psychological Empowerment.
Intrapersonal

Psychological
Empowerment

Interpersonal

Behavioral

Data Source: Zimmerman (1995) and Speer (2001).
For representing the intrapersonal component of PE, sociopolitical control (SPC)
is a construct that represents how strongly individuals believe in their abilities and
efficacy in social and political contexts (Itzhaky & York, 2003; Peterson, Lowe, Aquilino,
& Schneider, 2005; Peterson, Lowe, Hughey, Reich, et al., 2006; Peterson & Reid,
2003; Peterson, Speer, & Peterson, 2011; Smith & Propst, 2001; Zimmerman, Ramí
rezValles, & Maton, 1999; Zimmerman & Zahniser, 1991b). Empirically, sociopolitical
control has been found to consist of two dimensions: an individuals’ sense of leadership
efficacy (Leadership Competence: LC) and the belief that one can influence the political
world (Policy Control: PC) (Peterson, Speer, et al., 2006; Zimmerman, 1990a). It is
considered to be a ‘sphere-specific’ measure of perceived control. Sphere-specific
measures were found to be efficient and theoretically relevant in the psychology
literature as they helped reduce contradictory results of early investigations of more
global measures of perceived control (Zimmerman & Zahniser, 1991b). In order to
19

develop specific-sphere measure of perceived control that integrates personality,
cognitive, and motivational domain because it can differ across life sphere and
psychological domain (Zimmerman & Zahniser, 1991).
The SPC has been recognized as a public policy assessment tool in diverse
areas such as natural resource decision-making (Smith & Propst, 2001) and
community-based programs and projects (Peterson, Lowe, Hughey, Reid, et al., 2006).
Additionally, research has revealed the relationship between the SPC and citizen
participation behaviors (Smith & Propst, 2001; Zimmerman & Zahniser, 1991a). For
example, Smith and Propst (2001) found that those who reported high levels of
participation in natural resource-related political behaviors had significant higher scores
on the SPCS (Sociopolitical Control Scale) than those who did not. Studies have
adapted the SPCS to diverse settings in the last few years. Peterson’s recent research
(2011), for instance, demonstrated the validation of the SPCS which was designed to
represent the two dimensions of LC and PC by studying urban youth.
In order to improve the internal consistency of the SPCS, Peterson and his
colleagues (2006) rephrased the two negatively worded items so that all statements
were positively worded. Further tests of the modified SPCS supported the scale’s
hypothesized two-factor structure: leadership competence (LC) and policy control (PC)
(Peterson, Lowe, Hughey, Reich, et al., 2006; Zimmerman, 1995; Zimmerman &
Zahniser, 1991a).
In the past decade, researchers have demonstrated that the association between
community participation and psychological empowerment incorporates individuals’
socio-demographic characteristics as moderating variables (Itzhaky & York, 2000;
20

Peterson, Hamme, & Speer, 2002; Peterson & Hughey, 2002). Christen and his
colleagues (Christens, Speer, & Peterson, 2011) asserted that socio- economic status
(SES) moderated the relationship between the intrapersonal and interactional
component of psychological empowerment. They found that there was a positive
relationship between SES and the intrapersonal component of psychological
empowerment.
Tourism studies have also focused on empowerment in a variety of contexts,
including customer or tourist empowerment (Hjalager, 2001; Niininen, Buhalis, & March,
2007; Stockdale, 2007); employee empowerment (Erstad, 1997; H. J. Kim, Tavitiyaman,
& Kim, 2009; Klidas, van den Berg, & Wilderom, 2007; Lashley, 1999; Ross, 2005); and
the relationship between community empowerment and sustainable tourism (Hughes,
1995; Manyara & Johnes, 2007; Okazaki, 2008; Scheyvens, 1999; Timur & Getz, 2009).
While the tourism and hospitality domains have been interested in the
interpersonal component of PE within the wider agenda of the professional workplace
level, community psychologists have approached PE at the level of community-based
organizations. Thus, community psychologists have further extended their attention to
the relationship between PE and a sense of community.
Sense of Community
Tourism is “essentially place-based and involves the product of destination
identity” (Dredge & Jenkins, 2003, p. 383), which indicates that geographical boundaries
seem to play a significant role in communities for tourism planning and policymaking.
Sociopolitical environments and technical advancement have caused the definition of
community to be expanded (Iriye, 2002). Community, however, still highlights a
21

geographical place where personal relationships, face-to-face interaction, and
attachment to place occur (DeFilippis & Saegert, 2008).
The recognition of community has also been a popular research topic for tourism
scholars. Investigators have found that a key component of achieving sustainable
tourism is the appreciation of local communities’ needs and preferences as well as
socio-cultural and physical values (Blackstock, 2005; Joppe, 1996; Murphy, 1988;
Simpson, 2008). Community attachment plays an important role in assessing the
impacts of tourism development, as a significant positive relationship between tourism
development and community attachment has been found (Gursoy & Rutherford, 2004;
Látková & Vogt, 2012; Mason & Cheyne, 2000; McCool & Martin, 1994).
While these tourism studies have focused on the relationship between the tenure
of residency of community members and their attitudes toward tourism development,
community psychologists have focused their attention more on the psychological
features of community including feeling and belonging. In particular, sense of
community has been found to be a key variable related to empowerment and
participatory behaviors related to public health (Goodman, et al., 1998; Peterson &
Reid, 2003).
Sarason (1974) introduced Sense of Community (SOC) as a significant principle
of community psychology. However, there was no consensus regarding the definition,
model, or method of investigating sense of community before McMillan and Chavis
developed a theory in 1986. This is because “researchers’ constructions of their own
community experience oriented their hypotheses, methods, and interpretations of a
community’s response” (Chavis & Pretty, 1999, p. 636). McMillan (1976) initially
22

defined sense of community as “a feeling that members have of belonging, a feeling
that members matter to one another and to the group, and a shared faith that members’
needs will be met through their commitment to be together” (McMillan & Chavis, 1986,
p. 9).
Based on this definition, McMillan and Chavis (1986) proposed four elements of
sense of community: membership, influence, integration and fulfillment of needs, and
shared emotional connection. McMillan and Chavis defined these four elements
accordingly: “1) membership is the feeling of belonging or of sharing a sense of
personal relatedness; 2) influence is sense of mattering, of making a difference to a
group and of the group mattering to its members; 3) integration and fulfillment of needs
is the feeling that members’ needs will be met by the resources received through their
membership in the group; and 4) shared emotional connection is the commitment and
belief that members have shared and will share history, common places, time together,
and similar experiences” (McMillan & Chavis, 1986, p. 9).

23

Figure 3. Four Elements of Sense of Community.

Sense of Community

Integration
and
Fulfillment of
Needs

Shared
emotional
connection

Membership

Influence

Data Source: McMillan and Chavis (1986).
Much of the published literature has examined the variables related to a strong
sense of community, but there are few robust findings (Colombo, Mosso, & DePiccoli,
2001; Hill, 1996; Peterson, et al., 2008). One reason for this lack of consistent findings
is that certain aspects of a sense of community differ from setting to setting (Hill, 1996;
Peterson, Speer, et al., 2006). Regardless of the debate on the causes of inconsistent
findings, the four elements of sense of community by McMillan and Chavis have been
widely studied in a variety of contexts such as neighborhood solidarity (Brodsky & Marx,
2001; Colombo, et al., 2001), psychological rehabilitation (Herman, Onaga, PerniceDuca, Oh, & Ferguson, 2005), community organizations (Hughey, Speer, & Peterson,
1999), and international communities of interest (Obst, Zinkiewicz, & Smith, 2002).
Studies find that a sense of community affects local action (Chavis & Wandersman,
1990) and psychological empowerment (Peterson & Reid, 2003).
24

There have been ongoing debates on the factor-structure of the SOC since it was
introduced to the community psychology context in 1974. Some research has asserted
that the SC is validated only as unidimensional construct (Lounsbury, Loveland, &
Gibson, 2003; Okun & Michel, 2006; Proescholdbell, Roosa, & Nemeroff, 2006;
Rosenbaum, Ostrom, & Kuntze, 2005) while other studies claimed that the SC is a
multifactor construct (Obst & White, 2004; Peterson, Speer, et al., 2006; Peterson, et
al., 2008). This controversy may reflect, as mentioned above, the variety of
sociopolitical settings among communities and different life situations of community
members (Chavis & Wandersman, 1990; Maton & Salem, 1995; Tu & McIsaac, 2002).
Long and Perkins (2003) conducted confirmatory factor analysis (CFA) of the
SOC. Their analysis revealed a poor model fit for the original items from McMilan and
Chavis’s theoretical formulation. Therefore, they prompted the development of the brief
sense of community (BSC) scale, which yielded a three-factor solution when combining
the five original items from McMilan and Chavis, plus three additional items. Obst and
White (2004) conducted CFA utilizing Long and Perkins’s BSC scale; however, they
found that the hypothesized factor structure of the BSC scale did not have a good fit for
their data. Hence, they proposed that it is more appropriate to preserve the four-factor
structure for the sense of community scale. Peterson and his colleagues (2008)
supported the finding that the four-factor structure is valid for the BSC scale.
In the past decade, community psychologists have attempted to find the
relationship between SOC and SPC. Peterson and Reid (2003) found that a sense of
community predicted psychological empowerment, which was measured using the
Zimmerman and Zahniser’s (1991) SPC scale (SPCS). They found that citizens with a
greater sense of community participated more and were more psychological
25

empowered and concluded that SOC predicted PE both directly and indirectly through
its positive effect on participatory behavior. Hughey and his associates (2008) found
that the intrapersonal component of psychological empowerment was significantly
predicted by SOC in community organizations by measuring the SPCS. Their main
finding also indicated that SOC of community organizations can contribute to
intrapersonal empowerment by utilizing SPCS.
Peterson, Speer, and Peterson (2011) explained the relationship between
environment-related features, perception of community utilizing SC, citizen participation
related to community-based substance abuse prevention, and psychological
empowerment which was measured by SPC. Some findings of the study revealed that
individuals who greatly participated in the prevention activities tend to experience higher
level of psychological empowerment. Additionally, awareness of community programs
had a direct positive influence on citizen participation and citizen participation had a
direct positive influence on psychological empowerment.
Problem Statement
Little attention has been given to the association between sociopolitical control,
sense of community, and citizen participation in the context of tourism policy and
promotion. Without identifying these relationships, it is difficult to assess how well local
communities will be able to achieve certain positive outcomes, like empowerment, and
thereby continue on a path to sustainable tourism. Furthermore, a valid tourism-specific
measure of sociopolitical control is required but does not exist.
Definitions of Major Variables
The major variables of this study are defined as:
26

Sociopolitical Control: Individuals’ belief about their abilities and efficacy in social and
political context (Itzhaky & York, 2000; Zimmerman & Zahniser, 1991a).
Tourism Policy Control: A sense of control over one’s own life toward tourism policymaking processes (Holden, Evans, Hinnant, & Messeri, 2005; Smith & Propst, 2001;
Zimmerman & Zahniser, 1991a).
Leadership Competence: Individuals’ skills that may include organizing others for
achieving common goals and speaking in front of a large group (Peterson, Lowe,
Hughey, Reich, et al., 2006; Smith & Propst, 2001; Zimmerman & Zahniser, 1991a).
Sense of Community: A feeling that members matter to one another and to the group
(McMillan, 1976; McMillan & Chavis, 1986; Peterson & Reid, 2003).
Tourism Participatory Behavior : Behavior is classified whether a citizen participates in a
voluntary activity by each citizen intended to affect, either directly or indirectly, political
choices at various levels of the tourism policy-making processes (Conge, 1988; Smith &
Propst, 2001; Zimmerman & Zahniser, 1991a).
Sociopolitical Control Profile Group: A group of adults based on their sociopolitical
control score by cross-tab analysis such as higher scores on both dimensions, lower
scores on both dimensions, and higher scores on only one of the two dimensions
(Peterson, Peterson, et al., 2011; Speer, 2000).
Socioeconomic Status: It is calculated by combining a measure of household income
and level of educational attainment into a single score (Christens, Speer, et al., 2011).
Conceptual Model and Hypotheses
Studies have demonstrated the pathways to empowerment through sense of
community (SOC) and citizen participation. The conceptual model of this study
proposes that there are direct positive associations between SOC, tourism participatory
27

behavior (TPB), and sociopolitical control. Citizens with a greater level of SOC tend to
participate in TPB more and are more psychologically empowered. In addition, SOC
predicts psychological empowerment both directly and indirectly through its positive
effect on TPB, and there are positive relationship between SPC and familiarity with
tourism campaign (FTC) and perceived impact of tourism policy. The model also
predicts that socioeconomic status (SES) and SOC between TPB and SPC. Based on
the suggested conceptual model (See Figure 5), the following hypotheses are
proposed:
H1: SOC, FTP, PITP, TPB, and SES will have a direct positive influence on SPC.
H2: The relationship between SOC and SPC is partially mediated by TPB.
H3: The relationship between SOC and SPC is partially mediated by SES.
H4: The relationship between TPB and SPC is partially mediated by SES.
H5: The relationship between TPB and SPC is partially mediated by FTC.
H6: The relationship between TPB and SPC is partially mediated by PITP.
H7: The relationship between SOC and SPC is partially mediated by FTC.
H8: The relationship between SOC and SPC is partially mediated by PITP.

28

Figure 4. Conceptual Model for Path Analysis of This Study.
SES

SPC
FTC
TPC

TPB

PITP

LC

SOC

Note: SPC (sociopolitical control); TPC (tourism policy control); LC (leadership
competence); SOC (sense of community); TPB (tourism participatory behavior); FTC
(familiarity of tourism campaign); and PITP (perceived impact of tourism policy).

29

Chapter 3
Methods
Study Authorization
This study was initiated under the 2010-2011 Michigan Applied Public Policy
Research (MAPPR) Grant, entitled “Policy Implications of the Pure Michigan Campaign”
with data collection and analysis provided under the Institute for Public Policy and
Social Research (IPPSR) at Michigan State University (MSU). The MAPPR grant is
intended to support research that is related to economic development in the state of
Michigan (Institute for Public Policy and Social Research, 2012).
The IPPSR’s Office of Survey Research (OSR) at MSU utilized its computerassisted telephone interview (CATI) system to conduct a telephone survey of a random
sample of Michigan residents. Instruments were developed using research related to
the objectives of this study and the OSR added demographic and other variables for its
“State of the State Survey (SOSS).”
Sample Design
The population of the SOSS is comprised of non-institutionalized Michigan
residents. Since the Office of Survey Research conducted the SOSS by telephone,
only individuals who lived in households that had landline telephones could be
interviewed (Hembroff, 2011). The SOSS used a stratified random sample of Michigan
residents who were more than 18 years old and English-speaking adults (IPPSR, 2011).
Data sets were weighted based on the MSU Extension Office’s regional categories (See
Appendix C.) in order to ensure they were representative of the adult population of
30

Michigan (Hembroff, 2011). Each survey participant’s county of residence was also
coded in the data set in order to allow reclassification into alternative regional groupings
(Hembroff, 2011).
Figure 5. Six Regions in the State of the State Survey, Spring 2011.

31

A stratified sampling design assured sufficient minimum number of respondents
from each of the strata to permit detailed analysis (Hembroff, 2011). The sample size
recommended by the SOSS is approximately 1,000 respondents and calls for: (1) 150
telephone interviews from the East Central, the Southwest, and the combined Upper
Peninsula and Northern Lower Peninsula regions; (2) 200 telephone interviews from the
West Central and the Southeast regions; and (3) 150 telephone interviews from the City
of Detroit (Hembroff, 2011).
Data Collection Procedure
Data for this study were collected as part of the SOSS Round 59 which provides
information about citizen opinion on critical issues in Michigan (Institute for Public Policy
and Social Research, 2012). The section of the SOSS that this research utilizes
assesses the familiarity and satisfaction of the Pure Michigan campaign by Michigan
residents. The spring 2011 version of the SOSS also collected responses of residents
to four itemized scales that measure tourism policy control (TPC), leadership
competence (LC), sense of community (SOC), and tourism participatory behaviors
(TPC) related to tourism planning and policy at the local level (Appendix A).
The careful development of survey questions is critical because measurement
error is derived from poor questionnaire wording and construction (Dillman, Smyth, &
Christian, 2009). To reduce measurement error, survey questions should use words
that are consistent and valid measures of phenomena the study wants to examine
(Flower, 1995). The study should conduct an appropriate literature review, consult with
experts, and conduct pre- or pilot tests in order to minimize measurement error even
further.
32

Before conducting the SOSS, two pilot studies were conducted. The first pilot
study (n=36) was conducted in January 2011 with graduate students at MSU to test the
initial instrument. The scales for TPC, LC, and SOC demonstrated acceptable reliability
ranging from α=.87 to α=.94. After conducting the first pilot study, a second pilot study
(n=34) was conducted by the OSR for all SOSS items in order to develop clearer
wording for the final telephone survey instrument. Michigan residents were randomly
selected by telephone number from a telephone directory and were sent an
informational letter about the SOSS approximately one week prior to their interview
(Hembroff, 2011). The telephone interview for the SOSS study survey was completed
between May 13, 2011 and July 7, 2011. A total of 40,562 calls were made; 23.7% of
calls were refused. In total, 947 Michigan residents completed the SOSS. The
statewide sampling error was plus or minus 3.2%; regional sampling errors ranged from
a low of plus or minus 7.2% for the West Central region to a high of plus or minus
13.1% for the Upper Peninsula (Hembroff, 2011).
Table 1. The Margins of Error for Each Region and the Total Statewide Sample.
Region
Number of Cases
Margin of Sampling Error
Upper Peninsula
57
± 13.1%
Northern Lower Peninsula
98
± 10.0%
West Central
187
± 7.2%
East Central
150
± 8.0%
Southwest
155
± 7.9%
Southeast
181
± 7.3%
Detroit
119
± 9.0%
Statewide Total
947
± 3.2%
Data Source: Hembroff, L.A. (2011).
Survey Measurement
The reduced survey items for this study were developed based on previous
studies (Appendix B). The reason for the need to reduce the number of scale item was
33

because the questions of the study were in a larger survey so it needed to keep the part
of the study as brief as possible. The operational definitions of major constructs are
below.
Sociopolitical Control
The SOSS survey included 11 out of 17 items used by Zimmerman and Zahiser
(1991), Smith and Propst (2001), and Peterson and his colleagues (2006) to measure
the two dimensions of sociopolitical control: TPC and LC. TPC items were reworded
slightly to reflect tourism content from the original items of policy control.
The response format for the six TPC items was a five-point Likert scale from 1=
strongly disagree to 5=strongly agree with the following statements: “I feel like I have a
pretty good understanding of the important issues surrounding the Pure Michigan
campaign,” “I enjoy political participation because I want to have as much say as
possible in influencing a state government agency like Travel Michigan,” “People like
me are generally qualified to participate in decisions affecting state programs like the
Pure Michigan campaign,” “There are plenty of ways for people like me to have a say in
how Pure Michigan funds are spent,” “It is important to me that I actively participate in
influencing state government,” and “It is important to vote in state elections that might
affect the outcome of the Pure Michigan campaign.”
The five selected items for the LC scale were previously used by Zimmerman
and Zahniser (1991), Smith and Propst (2001), and Peterson and his colleagues (2006).
The response format for the LC items was a five-point Likert scale from 1= strongly
disagree to 5=strongly agree with the following statements: “I am often a leader in
groups,” “I would prefer to be a leader rather than follower,” “I would rather have a
34

leadership role when I am involved in a group project,” “I can usually organize people to
get things done,” and “Other people usually follow my idea.”
Sense of Community
This study used a reduced, four-item version of the original eight-item sense of
community scale developed by Peterson and Reid (2008). One item represented each
of the four dimensions of SOC: integration and fulfillment of needs, influence,
membership, and shared emotional connection. The four items selected had the
highest Cronbach alpha reliability scores based on pilot test data. The response format
for the SOC scale was a five-point Likert scale from 1= strongly disagree to 5=strongly
agree with the following statements: “My neighborhood or community helps me fulfill my
needs,” “I feel like a member of my neighborhood or community,” “I have a say about
what goes on in my neighborhood or community,” and “I have a good bond with others
in my neighborhood or community.”
Tourism Participatory Behavior
The SOSS employed Smith and Propst’s (2001) participatory behavior scale
modified to reflect tourism content. The responses to the five TPB item were given on
a categorical scale from 0= no to 1=yes with the following questions: “I attended a public
hearing or meeting that addressed statewide or local tourism issues,” “I communicated
with Travel Michigan or state government about some matter related to the Pure
Michigan campaign,” “I served on a committee or advisory board that addresses tourism
issues such as the Visitor and Convention Bureau, or a similar body,” “I wrote a letter to
an editor of a newspaper about the Pure Michigan campaign,” and “I posted a comment
on Facebook, Twitter, or a blog about the Pure Michigan campaign.”
35

Familiarity with Tourism Campaign
Survey participants were asked their degree of familiarity with Michigan’s recent
tourism promotion, Pure Michigan. The response to the one FTC item was given on a
five-Likert scale from 1=strongly disagree to 5=strongly agree with the following
statement: “How familiar are you with the Pure Michigan campaign?”
Perceived Impact of Tourism Policy
Two items related to the perceived impact of Pure Michigan were asked. The
responses to the two items were given on a five-Likert scale from 1=strongly disagree to
5=strongly agree with the following questions: “The Pure Michigan campaign has
positively affected tourism in Michigan”; and “The Pure Michigan campaign has
positively affected tourism in my local community.”
Data Analysis
Survey data were analyzed in several steps. Preliminary statistics were
calculated using the Statistical Package for the Social Sciences (SPSS) version 19.
Descriptive statistics were calculated to determine the distributional characteristics of
each variable including the means, standard deviation, skewness and kurtosis.
Skewness and kurtosis statistics assess the normality of each variable (Babbie, 2001).
In addition, all observed variables were standardized by transforming them into zscores. The standard score allows calculation of the probability of a score fitting the
standard normal distribution with a mean of 0 and standard deviation of 1(Field, 2005).
Standardization into z-scores also permits the identification of univariate outliers
(Hepper & Hepper, 2004).
36

Reliability is the extent to which a particular measure applied repeatedly to the
same population will yield the same or relevant result each time (Babbie, 2001). One
measure of reliability, internal consistency, is the degree of consistency within
responses to a set of questions (Vaske, 2008). Cronbach’s alpha test was conducted in
order to estimate internal consistency. This technique measures the extent to which
answers to survey questions correlate with each other (Cronbach, 2004). This tool can
be used to estimate if survey participants consistently answer the items within a given
scale.
Confirmatory factor analysis (CFA) was used for evaluating the psychometric
properties of the various scales in this study. CFA can be used to examine construct
validity and whether a measure is invariant or unchanging across groups, populations,
or time (Harrington, 2009). Therefore, CFA can be used to confirm the factor structure
of this study as a step to assess whether the same structure can be identified in a new
sample (Harrington, 2009). In other words, exploratory factor analysis may be used as
an exploratory first step during the development of a measure. However, SPC has
been developed with a strong theoretical framework in community psychology so it can
be possible to skip the initial exploratory factor analysis and go directly to the CFA.
For examing the mean difference of the levels of independent variables on
dependent variables, one-way analysis of variance (ANOVA) was conducted. In
addition, the present study used multivariate analysis of covariance (MANCOVA) to
support construct validity of the scales of this study. The MANCOVA was used to test if
there was covariation between variables. There should be significant covariation
between variables and the SPC profile groups that were created on the basis of their
SPC scale scores.
37

To determine overall model fit and direction as well as significance of
relationships, path analysis was performed by ordinary least squares (OLS) regression.
Path analysis enables the proposed model to simultaneously evaluate variables in a
causal process (Baloglu, 2000). In addition, path analysis allows this study to analyze
direct and indirect relationships by examining path coefficients (beta weight) between
variables in the model (de Vaus, 2002). A path coefficient as a standardized partial
regression coefficient expresses the importance of a direct association between two
variables (Yu & Littrell, 2003).
Most research studied moderation effects between observed variables by
utilizing hierarchical regression tests. However, the moderation effect hardly explains a
causal step approach because “a moderator is independently a third variable that
affects the direction and/or strength of the relationship between a predictor and a
criterion variable” (Vaske, 2008, p. 593). To demonstrate the indirect flow of the
variables in the present study, mediation hypotheses were employed and tested through
a causal step approach. Hence, this study explains several mediation effects toward
SPC between observed variables in the tourism context by using ordinary squares
regression.
For testing indirect (or mediation) effects between independent and dependent
variables, a causal step approach using OLS (Table 2 and Figure 7.) was followed
(Hoyle & Robinson, 2004; Vaske, 2008) to determine the existence of mediation effects,
a series of criteria (Table 2) should be satisfied (Vaske, 2008). The mediation analysis
is derived from its capacity to go beyond descriptive to a more operative understanding
of the association among variables (Preacher & Hayes, 2004). In other words,
mediation hypotheses are conducted to assess the indirect effect that an independent
38

variable affects a dependent variable through at least one mediator (Preacher & Hayes,
2008). Additionally, this study conducted the Sobel test for assessing statistical
significance of mediated relationships. The Sobel test has been recognized as one of
common statistics for assessing mediation effects (Vaske, 2008). Partial mediation is
satisfied when the Sobel’s z-value is significant.
Table 2. Steps in Establishing Mediation Effects through the OLS Regression a.
Step
Description
Regression Model Equation
Demonstrates that the:
1
Independent variable affects the dependent
1
Y=1(X)
variable. This step estimates path c1 in Figure
7.
2
Independent variable affects the mediator. This
2
M=1(X)
step estimates path a in Figure 7.
3
Independent variable and mediator affects the
3
Y=1(X)+ 2(M)
dependent variable. This step estimates path
c2 and b in Figure 7.
4
If M fully mediates the XY relationship, path
c2=0.
If M partially mediates the XY relationship,
path c2<path c1.
5
Conduct Sobel Test (Z-score):

If the value of z is significant, M partially mediates between
independent and dependent variable
Note: X= independent variable, Y=dependent variable, and M=moderator
a
Adapted from Vaske (2008), p.578.

39

Figure 6. Mediation Regression Model.
Mediator
a

Independent
Variable

b

c1
c2

Note: Adapted from Vaske (2008), pp.576-578.

40

Dependent
Variable

Chapter 4
Results
Study results are presented in this chapter. First, descriptive statistics are
reported to include: socio-demographic characteristics of survey respondents, familiarity
with Pure Michigan, perceived impacts of Pure Michigan, respondents’ participatory
activities in tourism policy and planning, and group differences in familiarity and
perceived impacts. Second, confirmatory factor analysis (CFA) results are presented:
descriptive statistics of the constructs, reliability and normality tests, and then overall
CFA results. Analysis of variance (ANOVA) test results are also presented in order to
evaluate the mean differences of the major constructs by some of socio-demographic
variables. Third, multiple analysis of covariance (MANCOVA) results are reported as
another way to provide evidence for scale validity. Finally, path analysis results are
discussed to assess the quality of the proposed model, hypotheses and mediation
effects.
Socio-demographic Characteristics of Survey Respondents
Table 3 contains the survey respondents’ socio-demographic characteristics.
The majority of participants (56.6%) were female. The greatest proportion of
participants, 36.4%, were 65 years or older; around 22.5% were in their 50s; 15.3%
were between 60 to 64 years old; 14.0% were in their 40s; 7.8% were in their 30s; and
4.0% were in their 20s or less than 20 years old.
As for race, 84.8% were white while 12.1% were black/African Americans and
2.7% were other racial groups. As to employment, 44.0% of the respondents had at
least part time jobs. Retirees comprised 37.4% of the participants, and 18.7% were
41

unemployed, laid off, looking for a job, full time students, disabled, homemakers, or
unable to classify. The preponderance of survey respondents came from the West
Central (19.7%) and Southeast (19.1%) regions of Michigan; 16.4% were from the
Southwest; 15.8% were from East Central regions of the state; 12.6% were from the city
of Detroit; and 10.3% and 6.0% of the participants resided in the Northern Lower and
Upper Peninsulas, respectively. In terms of educational background of the
respondents, 65.9% of the respondents enrolled or were enrolling at least
technical/junior colleges or 1-4 year colleges.
As to the survey participants’ marital status, 54.4% of the respondents were
married or remarried while 17.2% and 13.5% were widowed and divorced, respectively.
The survey participants’ level of household income was also calculated. Among the
survey respondents, 17.7% of them earned less than 20,000 dollars in their household
in 2010 whereas 14.7% of the respondents earned more than 100,000 dollars in the
year.

42

Table 3. Socio-Demographic Characteristics of Survey Respondents.
Variable Name
Value
Frequency
Gender
Male
411
Female
536
Total
947
Age
Less than 30 years
37
30-39 years
72
40-49 years
130
50-59 years
209
60-64 years
142
65 or older
337
Total
927
Race
White
803
Black/African American
120
Other
24
Total
947
Employment
Work full time
295
Work part time
104
Work and go to school
4
Have a job, but not at work last week
9
Unemployed/Laid off/Look for work
27
Retired
350
School full time
8
Homemaker
89
Disabled
48
Other: Unable to classify
3
Total
937
Region
Upper Peninsula
57
Northern Lower Peninsula
98
West Central
187
East Central
150
Southwest
155
Southeast
181
Detroit
119
Total
947
Education
Lower than high school
25
High school graduate
274
Technical/Junior college
23
College (1-4 year graduate)
472
Some post graduate
24
Graduate degree
125
Total
945
Note: The value of “frequency” varies, due to questions not answered.

43

%
43.4
56.6
100.0
4.0
7.8
14.0
22.5
15.3
36.4
100.0
84.8
12.7
2.5
100.0
31.5
11.1
0.4
1.0
2.9
37.4
0.9
9.5
5.1
0.3
100.0
6.0
10.3
19.7
15.8
16.4
19.1
12.6
100.0
2.8
29.0
2.4
50.1
2.6
13.2
100.0

Table 3. Socio-Demographic Characteristics of Survey Respondents (Cont’d).
Variable Name
Value
Frequency
%
Marital Status
Married/Remarried
509
54.4
Divorced
126
13.5
Separated
7
0.7
Widowed
161
17.2
Member of an unmarried couple
15
1.6
Single/Never been married
117
12.5
Total
935
100.0
Household Income <$20,000
153
17.7
$20,000<$30,000
93
10.8
$30,000<$40,000
102
11.8
$40,000<$50,000
108
12.5
$50,000<$60,000
91
10.5
$60,000<$70,000
71
8.2
$70,000<$90,000
84
9.7
$70,000<$100,000
34
3.9
>$100,000
127
14.7
Total
863
100.0
Note: The value of “frequency” varies, due to questions not answered.
Familiarity with the Pure Michigan Campaign
Respondents’ overall familiarity level of the Pure Michigan campaign is presented
in Table 4. Approximately 87% of the survey participants were at least a little familiar
with the campaign: very familiar (25.4%); somewhat familiar (47.0%); and not very
familiar (15.2%) whereas 12.5% of the respondents were not familiar at all with the
campaign.
Table 4. Familiarity with the Pure Michigan Campaign.
Variable Name
Value
Frequency
FTC
Not familiar at all
118
Not very familiar
143
Somewhat familiar
444
Very familiar
240
Total
946
Note: FTC (Familiarity with Tourism Campaign).

44

%
12.5
15.2
47.0
25.4
100

This study considered whether citizens’ familiarity with the Pure Michigan
campaign differed according to age, region, education, and household income. The
question was analyzed utilizing one-way ANOVA with an F-test in order to assess the
statistical significance of the resulting difference among the four groups of data (Table
5).
The study found statistically significant differences according to age [F (4, 920) =
5.174, p=0.000], region [F (6, 938) = 4.162, p=0.000], education [F (3, 938) = 21.312,
p=0.000], and household income [F (8, 852) = 11.178, p=0.000]. The 30s age group
(M=3.04) was most familiar with the Pure Michigan campaign while those less than 30
years old (M=2.46) were least familiar with the campaign. The respondents who
resided in the Southeast region of Michigan were most familiar with campaign whereas
the survey participants in the Upper Peninsula (M =2.47) were least familiar. The
survey participants who had more than a college education (M=3.01) were most familiar
with the campaign while the respondents who had less than a high school education
(M=2.39) were least familiar. The respondents who earned more than 100,000 dollars
were most familiar with the campaign whereas those who earned less than 20,000
dollars were least familiar.

45

Table 5. Mean Differences in Familiarity with the Pure Michigan.
Variable
Value
Mean
S.D.
Age
Less than 30 years
2.46
1.07
30s
3.04
0.84
40s
2.98
0.94
50s
2.83
0.96
More than 60 years
2.68
0.98
Total
2.77
0.97
Region
Upper Peninsula
2.47
1.12
Northern Lower Peninsula
2.73
1.02
West Central
2.82
0.96
East Central
2.64
0.99
Southwest
2.88
0.91
Southeast
2.96
0.87
Detroit
2.53
1.00
Total
2.76
0.97
Education
Less than High School
2.39
0.92
High School
2.42
0.98
Some College
2.82
0.97
More than College
3.01
0.89
Total
2.76
0.97
Household <$20,000
2.36
1.04
$20,000<$30,000
2.54
0.94
Income
$30,000<$40,000
2.71
0.90
$40,000<$50,000
2.70
0.98
$50,000<$60,000
2.98
0.87
$60,000<$70,000
2.87
0.86
$70,000<$90,000
3.15
0.75
$70,000<$100,000
3.09
0.87
>$100,000
3.19
0.82
Total
2.80
0.95
Note: Legend: 1. Not familiar all to 4. Very Familiar
***P<0.001, **P<0.01, *P<0.05

df
4

F-Value
5.174***

6

4.162***

3

21.312***

8

11.178***

Perceived Impact of the Pure Michigan Campaign
Citizens’ opinions on statewide and local impacts of the Pure Michigan campaign
was evaluated (Table 6). As for statewide impact, approximately 87% of the survey
participants expressed that the campaign positively affected Michigan’s tourism; the
remainder did not. As for local impact, the response was evenly split with 49.0%
agreeing that the campaign had a positive impact on their local communities and 48.8%
disagreeing.
46

Table 6. Respondents’ Perceived Impacts of the Pure Michigan Campaign.
Variable
Value
Frequency
%
Mean
Name
Statewide
Strongly Disagree (1)
11
1.4
4.03
Somewhat Disagree (2)
75
10.2
Neither (3)
5
0.6
Somewhat Agree (4)
437
58.7
Strongly Agree (5)
209
28.1
Total
737a
100.0
Local
Strongly Disagree (1)
90
12.3
3.02
Somewhat Disagree (2)
268
36.5
Neither (3)
16
2.2
Somewhat Agree (4)
259
35.3
Strongly Agree (5)
100
13.7
a
Total
733
100.0
Note: The value of “frequency” varies, due to questions not answered.

S.D.
.910

1.327

The present study assumed whether citizens’ perceived impact of the Pure
Michigan campaign differed according to age, region, education, and household
income. The assumption was assessed using one-way ANOVA with an F-test for
evaluating the statistical significance of the resulting differences among the four groups
of data (Table 7). The study found that there were statistically significant differences
between citizens’ perceived statewide impact of the campaign and the four socioeconomic variables: age [F (4, 746) = 2.967, p=0.05]; region [F (6, 757) = 3.567,
p=0.01]; education [F (3, 757) = 3.855, p=0.01]; and household income [F (8, 700) =
2.336, p=0.01]. The respondents, who were in their 30s (M=4.11) and 40s (M=4.11),
were most positive about the statewide impact of the campaign while the 20s (M=3.54)
were least positive. Survey participants who resided in the Southwest region of
Michigan were most positive about the statewide impact of the campaign whereas
residents of Detroit (M=3.55) were least positive. Survey participants who possessed
more than a college education (M=4.05) were most positive about the statewide impact
of the campaign while those who had less than a high school education (M=3.71) were
47

least positive. Respondents who earned more than 100,000 dollars (M=4.24) were
most positive about the statewide impact of the campaign while those who earned less
than 20,000 dollars (M=3.69) were least positive.
Table 7. Mean Differences in Perceived Statewide Impact of Pure Michigan.
Variable
Value
Mean
S.D.
df
Age
Less than 30 years
3.54
1.04
4
30s
4.11
0.92
40s
4.11
0.82
50s
3.95
1.06
More than 60 years
3.84
1.11
Total
3.92
1.04
Region
Upper Peninsula
3.75
1.10
6
Northern Lower Peninsula
3.91
1.22
West Central
3.83
1.01
East Central
3.88
1.10
Southwest
4.11
0.83
Southeast
4.08
0.98
Detroit
3.55
1.21
Total
3.91
1.05
Education
Less than High School
3.71
1.42
3
High School
3.73
1.11
Some College
3.90
1.08
More than College
4.05
0.95
Total
3.91
1.05
Household <$20,000
3.69
1.20
8
Income
$20,000<$30,000
3.79
1.23
$30,000<$40,000
3.92
0.98
$40,000<$50,000
3.83
1.01
$50,000<$60,000
3.98
0.98
$60,000<$70,000
3.90
1.21
$70,000<$90,000
3.93
1.04
$70,000<$100,000
4.03
0.96
>$100,000
4.24
0.77
Total
3.93
1.04
Legend: 1. Strongly Disagree to 5. Strongly Agree
***P<0.001, **P<0.01, *P<0.05

F-Value
2.967*

3.567**

3.855**

2.336**

As for citizens’ perceived local impact of the campaign, age group [F (4, 762) =
7.850, p=0.000] and educational level of the respondents [F (3, 775) = 2.763, p=0.05]
were significantly different (Table 8). On the other hand, there were no statistically
48

significant differences between perceived local impact, region and household income.
Survey participants who were in their 40s (M= 3.90) were most positive about their
perceived local impact of the campaign while those less than 30 years old (M=2.68)
were least positive. Respondents who had less than a high school education (M=3.95)
were most positive about local impact of the campaign.
Table 8. Mean Differences in Perceived Local Impact of Pure Michigan.
Variable
Value
Mean
S.D.
df
Age
Less than 30 years
2.68
1.39
4
30s
3.52
1.28
40s
3.90
1.11
50s
3.88
1.08
More than 60 years
3.77
1.14
Total
3.75
1.16
Region
Upper Peninsula
3.66
1.18
6
Northern Lower Peninsula
3.96
1.09
West Central
3.76
1.05
East Central
3.67
1.20
Southwest
3.65
1.19
Southeast
3.87
1.16
Detroit
3.51
1.36
Total
3.74
1.17
Education
Less than High School
3.95
1.24
3
High School
3.54
1.18
Some College
3.82
1.15
More than College
3.79
1.17
Total
3.74
1.17
Household <$20,000
3.67
1.21
8
Income
$20,000<$30,000
3.55
1.12
$30,000<$40,000
3.66
1.12
$40,000<$50,000
3.60
1.27
$50,000<$60,000
3.76
1.16
$60,000<$70,000
3.92
1.13
$70,000<$90,000
3.73
1.17
$70,000<$100,000
4.13
0.97
>$100,000
3.86
1.17
Total
3.74
1.17
Legend: 1. Strongly Disagree to 5. Strongly Agree
***P<0.001, **P<0.01, *P<0.05
Citizens’ Tourism Participatory Behavior
49

F-Value
7.850***

1.620

2.763*

1.277

The descriptive statistics for citizens’ tourism participatory behaviors are
presented in Table 9. A multiple responses analysis created two groups. Group 1
contains individuals who did not participate in any kind of tourism participatory activity in
the last five years while Group 2 is comprised of individuals who participated in at least
one tourism participatory activity in the last five years. Depending on the activity 3.6 to
11.7 percent of the survey participants expressed that they once participated in
activities in tourism policy and planning in the last five years. Approximately 21% of the
survey respondents expressed that they once participated in policy-making activities
related to the tourism context while approximately 79% of the respondents did not.
Table 9. Respondents’ Participatory Activities in Tourism Policy and Planning.
Variable
Statement
Frequency
Percentage
Name
TPB1
Have attended a public hearing or
64
11.7
meeting that addressed statewide or
local tourism issues in the past five
years.
TPB2
Have communicated with Travel
60
9.8
Michigan or state government about
some matter related to the Pure
Michigan campaign in the past five
years.
TPB3
Have served on a committee or advisory
28
4.4
board that addresses tourism issues
such as the Visitor and Convention
Bureau, or a similar body in the past five
years.
TPB4
Have written a letter to an editor of a
15
3.6
newspaper about the Pure Michigan
campaign in the past five years.
TPB5
Have posted a comment on Facebook,
51
6.7
Twitter or a blog about the Pure
Michigan campaign in the past five
years.
Note: Legend: 0. No 1: Yes
Reliability and Normality of Major Constructs

50

Perceived level of psychological empowerment was measured by the 11-item
SPC scale (SPCS). The SPCS consists of two subscales, one assessing TPC and the
second measuring LC. The SOC was assessed by 4-items derived from the 8-item
SOC scale developed by Peterson, Speer and McMillan (2008). Generally, an alpha of
more than 0.70 is recognized as acceptable in tourism and recreation studies (Vaske,
2008). Even though this study reduced the number of items from the original version of
the scales, the reliability or internal consistency exceeded the recommended standard
(Table 10).
Table 10. The Results of Reliability of TPC, LC, and SOC.
Construct
Variable Name
Cronbach’s Alpha if Item
Deleted
TPC
TPC1
0.819
TPC2
0.804
TPC3
0.808
TPC4
0.816
TPC5
0.815
TPC6
0.813
LC
LC1
0.813
LC2
0.814
LC3
0.819
LC4
0.814
LC5
0.821
SOC
SOC1
0.803
SOC2
0.804
SOC3
0.803
SOC4
0.811
Note: Overall Cronabach’s Alpha for 15 items was 0.822.
This study also conducted normality tests for skewness and kurtosis. Skewness
is the symmetry of a frequency distribution while kurtosis is the degree to which scores
cluster in the tails (Field, 2005). The multivariate normality and maximum likelihood
assumptions of confirmatory factor analysis require that all observed variables are
univariate normally distributed (Harrington, 2009). Table 11 shows that the value for
univariate skewness and kurtosis ranged from -1.899 to 0.205 and from -1.529 to 2.759
51

respectively. Values of all variables for univariate skewness and kurtosis thus fell
within conventional criteria which is that absolute values must be less than 3.0 for
skewness while absolutes value must be less than 10.0 for kurtosis (Harrington, 2009;
Kline, 2005).
Table 11. Normality Test Results of Observed Variables.
Construct
Variable Name
Skewnessa
Kurtosisa
TPC
TPC1
-0.519
-1.109
TPC2
-0.718
-0.871
TPC3
-0.664
-1.030
TPC4
0.205
-1.529
TPC5
-1.147
0.072
TPC6
-1.899
2.399
LC
LC1
-0.885
-0.492
LC2
-0.858
-0.647
LC3
-0.830
-0.723
LC4
-1.748
2.759
LC5
-1.295
1.194
SOC
SOC1
-0.813
-0.622
SOC2
-1.223
0.229
SOC3
-0.404
-1.413
SOC4
-1.707
2.336
Note: Skewness >|3|=extremely skewed while kurtosis >|10|=extremely peaked.
Confirmatory Factor Analysis of Major Constructs
Before conducting CFA, this study assessed the survey participants’ general
perspectives of the major constructs (Table 12). The mean for the overall TPC scale
was 3.75 on a 5-point Likert scale, reflecting agreement with the statements and
relatively high level of tourism policy control. The mean for the overall LC scale was
3.70 on a 5-point Likert scale, indicating agreement with the statements and high
degree of leadership competence. Respondents perceived themselves to have
relatively high level of both TPC (i.e. positive attitudes regarding their potential to
influence decisions regarding Pure Michigan) and leadership competence (i.e. ability to
take charge when the situation warrants). The only item scoring below the midpoint
52

(3.0) was “TPC4” (M=2.67), which reflects respondents’ sense of their ability to
influence how Pure Michigan funds are spent. The mean for the overall SOC was 3.92
on a 5-point Likert scale, revealing agreement with the statements and strong sense of
community. The survey participants were slightly more positive about their
connectedness (SC2) with their neighborhood and communities (SC4) than they were
about having their needs met (SC1) or influencing decisions (SC3), respectively.

53

Table 12. Respondents’ General Perspectives of TPC, LC and SOC.
Variable Name
Statement
TPC

TPC1
TPC2
TPC3
TPC4
TPC5
TPC6

I feel like I have a pretty good understanding of the
Important issues surrounding the Pure Michigan
campaign.
I enjoy political participation because I want to have
as much as possible in influencing a state
government agency like Travel Michigan.
People like me are generally qualified to participate in
decisions affecting state programs like the Pure
Michigan campaign.
There are plenty of ways for people like me to have a
say in how Pure Michigan funds are spent.
It is important to me that I actively participate in
influencing state government.
It is important to vote in state elections that might
affect the outcome of the Pure Michigan campaign.

Total
LC

N
782
777

3.76
(1.28)

770

3.62
(1.40)

757

2.67
(1.47)
4.09
(1.22)
4.60
(0.90)
3.75
(0.78)
3.55
(1.34)
3.56
(1.43)
3.41
(1.45)
4.03
(1.21)
3.87
(1.11)
3.70
(1.04)
3.65
(1.32)
4.15
(1.17)
3.56
(1.39)
4.33
(0.99)
3.92
(0.98)

792
792
716

LC1

I am often a leader in groups.

795

LC2

I would prefer to be a leader rather than follower.

789

LC3

795

LC4

I would rather have a leadership role when I am
involved in a group project.
I would rather organize people to get things done.

LC5

Other people usually follow my ideas.

789

Total
SOC

SOC1
SOC2
SOC3
SOC4

798

771
My neighborhood or community helps me fulfill my
needs.
I feel like a member of my neighborhood or
community.
I have a say about what goes on in my neighborhood
or community.
I have a good bond with others in my neighborhood
or community.

Total

791
799
798
799
790

Note: Legend: 1. Strongly Disagree to 5. Strongly Agree.
The value of “frequency” varies, due to questions no answered.

54

Mean
(S.D.)
3.74
(1.17)

Figure 7 depicts the proposed measurement model for conducting CFA which
consists of three factors and 15 observed variables. The observed variables were
tested based on the measurement by employing the factor loadings of the observed
variables and their error term (S. H. Kim, 2007). All constructs and observed variables
were specified based on previous research. TPC was specified by six observed
variables. LC was specified by five observed variables. SOC was specified by four
observed variables. A CFA with robust maximum likelihood estimation was conducted
on the 15 items of the TPC, LC, and SOC, utilizing the AMOS 19.0.

55

Figure 7. Proposed Measurement Model for Confirmatory Factor Analysis.

TPC1

e1

TPC6

e6

LC1

e7

LC5

e11

SOC1

e12

SOC4

e15

Tourism
Policy
Control

Leadership
Competence

Sense of
Community

Note: All observed variables were transformed to z-score.
The recommended CFA goodness-of-fit indices and their ranges are displayed in
Table 13. The value of Chi-square reveals the amount of difference between observed
and expected covariance matrices (Suhr, 2006). Comparative fit index (CFI) examines
56

the proportionate improvement in fit by comparing the target model with the
independence model (Schilling, 2002). The Tucker-Lewis Index (TLI) is known as the
non- normed fit Index which measures parsimony by evaluating the degrees of freedom
from the proposed model to the null model (Hoe, 2008). Root Mean Square Error of
Approximation (RMSEA) measures the degree to which the analyzed data
approximates the population covariance matrix (Raykov, 2008).
Table 13. The Recommended Goodness-of-Fit Indices for Confirmatory Factor Analysis.
Goodness-of-Fit Indices Used for this
Recommended Range of Good Model Fit
Study
Significant p-value (p,0.01)
Chi-square Statistics (2)
Comparative Fit Index (CFI)
Tucker-Lewis Index (TLI)
Root Mean Square Error of
Approximation (RMSEA)
Date Source: Kline (2005).

>0.90
>0.90
<0.08

In step one, CFA for the proposed measurement model with the major constructs
was tested. According to the Table 13 criteria, the proposal model did not produce a
clearly good fit with the data, 2(87) = 402.941, p<0.001 (CFI = 0.908, TLI =0.873,
RMSEA = 0.072).

As evidenced by the significant chi square and fit indices close to

the standards, the data fit the model marginally well. Therefore, the model was modified
and retested.
The proposed model was modified not only because it did not fit the data
extremely well, but also because some observed variables had low standardized factor
loadings and large residuals. Kline (2005) suggests that standardized factor loadings
from CFA should be greater than 0.50. Based on Kline’s criterion, three observed
variables (TPC1, TPC4, and TPC6) with low factor loadings for the expected constructs
were eliminated from the initial model. After removing these three observed variables
57

which standardized factor loadings were less than 0.50, the recommended goodness of
fit indices were met in the modified model: 2(51) = 274.041, p<0.001 (CFI = 0.927, TLI
=0.902, RMSEA = 0.079) in the modified model.
Table 14. Comparison of the Proposed and Modified Full Measurement Models (n=694).
Model
df
CFI
TLI
RMSEA
2
2
Initial
402.941
87
0.908
0.873
0.072
Model
Modified
274.041
51
0.927
0.902
0.079
128.9
Model
Note: 2=2 difference between two models.
Studies propose that the 2 statistic is not a strong test of model fit and should be
de-emphasized. This is because it is affected by sample size and distribution of
variables (Jöreskog & Sörbom, 1993; M. R. Kim, 2010); as a result, it typically rejects
the model if large samples are utilized. Therefore, this study excluded 2 as an index to
assess goodness of fit. As such, the modified model was acceptable for testing the
hypotheses of this study.
Assessment of Reliability and Validity
Both validity and reliability of the modified measurement model were assessed.
The reliability test was performed by calculating Cronbach’s alpha and composite
reliability, which assess the internal consistency of the observed variables measuring
each factor. In the modified model, the values of Cronbach’s alpha and composite
reliability of three constructs exceeded the recommended standard 0.70 (Kline, 2005).
Both Cronbach’s alpha and composite reliability are generally used to test the reliability
of scales. Cronbach’s alpha test was conducted in this study in order to estimate
internal consistency by measuring the extent to which answers to survey questions
correlate with each other (Cronbach, 2004). The composite reliability test provides an
58

estimate of the variance shared by the respected indicators, through utilizing the item
loadings obtained within a nomological network (Hair, Anderson, Tatham, & Black,
2006; Karim, 2009). A nomological network refers to the basic features of a construct
by providing evidence of their observable manifestations and the interrelationship
among constructs (Peterson and Zimmerman, 2004).
Average variance extracted (AVE) was used to test discriminant validity, which
exceeded the recommended standard 0.50 (Fazlollahi, 2002). Discriminant validity
means that measurement do not only have method variance, but they are also pure
measures of discrete traits (Throndike & Throndike-Christ, 2010). The AVE for each of
the constructs is greater than the squares of the correlations between all constructs
(Fornell & Larker, 1981).
Table 15. The Results of Confirmatory Factor Analysis for the Modified Measurement
Model.
Variable Standardized
Cronbach’s
Composite
Construct
AVE
Name
Loading
Alpha
Reliability
TPC
TPC2
0.758***
0.727
0.71
0.51
TPC3
0.506***
TPC5
0.691***
LC
LC1
0.635***
0.850
0.82
0.54
LC2
0.825***
LC3
0.838***
LC4
0.702***
LC5
0.631***
SOC
SOC1
0.728***
0.855
0.85
0.59
SOC2
0.865***
SOC3
0.701***
SOC4
0.681***
Note: Standardized loadings refer to relationship between observed variables and their
associated factors for examing convergent validity.
Composite Reliability=(Standardized Loading)2/[(Standardized Loading)2+Indicator
Measurement Error].
Average Variance Extracted=(Standardized Loading2)/[ Standardized Loading2)+
Indicator Measurement Error].
***Factor loadings are all significant at the level of 0.001.
59

Level of Psychological Empowerment and Sense of Community
This study analyzed the survey participants’ perceived level of psychological
empowerment by socio-demographic variables using the eight item SPCS in the
modified model.
Group Differences in Tourism Policy Control
The study conducted one-way ANOVA to test for statistically significant
differences between TPC and the socio-demographic variables, age, region, education,
and household income. First, there was a statistically significant difference between
age and overall TPC [F (4, 646) = 8.821, p<0.001]. The 40s age group (M=4.02) had
the greatest sense of control over their ability to influence tourism policy-making
decisions via the political processes while the 30s group (M=3.35) had the least sense
of TPC. Second, there was a statistically significant difference between region and
overall TPC [F (6, 647) = 5.055, p=0.000]. Residents of the Southwest region of
Michigan (M=4.03) had the greatest sense of TPC whereas residents of the East
Central region (M=3.29) had the least sense of TPC. Third, there was a statistically
significant difference between education and TPC [F (3, 648) = 15.033, p<0.001].
Those with at least some college education had a greater sense of TPC than those with
high school and less education. Finally, there was a statistically significant difference
with household income [F (8, 638) = 8.735, p<0.001]. Respondents who annually
earned between $70,000 and $100,000 (M= 4.32) had the greatest sense of TPC
whereas the survey participants whose annual household income was between $40,000
and $50,000 had the least sense of TPC.

60

Table 16. Mean Differences in Tourism Policy Control.
Variable
Value
Mean
S.D.
df
F-Value
Age
Less than 30 years
3.35
1.03
4
8.821***
30s
3.73
1.15
40s
4.02
0.92
50s
3.70
0.99
More than 60 years
3.90
0.97
Total
3.73
1.05
Region
Upper Peninsula
4.01
1.18
6
5.055***
Northern Lower Peninsula
3.63
1.02
West Central
3.47
0.98
East Central
3.29
1.34
Southwest
4.03
0.89
Southeast
3.75
1.03
Detroit
3.98
0.87
Total
3.74
1.04
Education
Less than High School
3.55
1.67
3
15.033***
High School
3.35
1.15
Some College
4.01
0.86
More than College
3.80
1.02
Total
3.74
1.05
Household <$20,000
3.41
1.22
8
8.785***
Income
$20,000<$30,000
3.62
0.94
$30,000<$40,000
3.63
1.08
$40,000<$50,000
3.09
1.01
$50,000<$60,000
3.95
0.90
$60,000<$70,000
3.46
0.92
$70,000<$90,000
3.89
0.80
$70,000<$100,000
4.32
0.75
>$100,000
4.04
1.05
Total
3.74
1.04
Legend: 1. Strongly Disagree to 5. Strongly Agree. TPC included TPC2, 3, and 5.
***P<0.001, **P<0.01, *P<0.05
Group Differences in Leadership Competence
The statistical differences between LC and socio-demographic characteristics
were assessed by one-way ANOVA. First, there was a statistically significant difference
between age and overall LC [F (4, 646) = 11.317, p<0.001]. The 30s age group (M=
4.21) had the greatest perceived level of LC whereas the 60s-plus age group had the
lowest perceived level Second, there was a statistically significant difference between
61

region and LC [F (6, 647) = 2.675, p<0.05]. Residents of the Southeast region of
Michigan (M=4.13) had the greatest sense of LC while the respondents of the
Southwest (M=3.78) had the least sense LC. Third, there was a statistically significant
difference between household income and LC [F (8, 638) = 5.959, p<0.001]. The
survey participants who annually earned between $70,000 and $100,000 (M=4.39) had
the greatest sense of LC whereas the respondents who annually obtained between
$20,000 and $30,000 (M=3.33) had the least sense of LC. There was no statistically
significant difference between education and LC.

62

Table 17. Mean Differences in Leadership Competence.
Variable
Value
Mean
Age
Less than 30 years
4.11
30s
4.21
40s
4.13
50s
3.79
More than 60 years
3.57
Total
3.99
Region
Upper Peninsula
3.96
Northern Lower Peninsula
4.04
West Central
3.87
East Central
3.88
Southwest
3.78
Southeast
4.13
Detroit
4.01
Total
4.00
Education
Less than High School
3.39
High School
4.07
Some College
3.97
More than College
3.97
Total
3.99
Household <$20,000
4.20
$20,000<$30,000
3.33
Income
$30,000<$40,000
3.77
$40,000<$50,000
3.84
$50,000<$60,000
4.02
$60,000<$70,000
3.84
$70,000<$90,000
4.05
$70,000<$100,000
4.39
>$100,000
4.14
Total
3.99
Legend: 1. Strongly Disagree to 5. Strongly Agree
***P<0.001, **P<0.01, *P<0.05

S.D.
0.81
0.78
0.83
0.96
1.09
0.91
0.87
0.75
0.91
0.92
0.75
0.93
1.11
0.91
1.40
1.03
0.84
0.86
0.91
0.81
0.91
1.23
1.01
1.03
0.90
0.73
0.73
0.72
0.91

df
4

F-Value
11.371***

6

2.675*

3

1.586

8

5.959***

Different Level toward Sense of Community
The study assessed the respondents’ different perspective toward SOC by sociodemographic characteristics using one-way ANOVA. First, there was a statistically
significant difference between age and SOC [F (4, 646) = 31.897, p<0.001]. The 40s
age group (M=4.04) had the greatest SOC while the 30s age group (M=2.88) had the
lowest SOC. Second, there was a statistically significant difference between region and
SOC [F (6, 647) = 5.336, p<0.001]. Residents of the Northern Lower Peninsula
63

(M=4.17) had the highest SOC whereas the respondents of the East Central (M=3.52)
had the lowest SOC. Third, there was a statistically significant difference between
education and SOC [F (3, 648) = 18.288, p<0.001]. The group with more than a college
education (M=4.08) had the greatest SOC while the respondents who obtained a high
school diploma (M=3.30) had the lowest SOC. Finally, there was a statistically
significant difference between household income and SOC. Respondents who annually
earned between $70,000 and $100,000 (M=4.53) had the greatest SOC whereas those
who annually earned less than $20,000 (M=2.96) had the lowest SOC.

64

Table 18. Mean Differences in Sense of Community.
Variable
Value
Mean
Age
Less than 30 years
2.88
30s
3.91
40s
3.95
50s
4.04
More than 60 years
3.99
Total
3.72
Region
Upper Peninsula
3.96
Northern Lower Peninsula
4.17
West Central
3.73
East Central
3.52
Southwest
4.05
Southeast
3.67
Detroit
3.19
Total
3.73
Education
Less than High School
3.84
High School
3.30
Some College
3.72
More than College
4.08
Total
3.72
Household <$20,000
2.96
$20,000<$30,000
3.27
Income
$30,000<$40,000
3.37
$40,000<$50,000
3.69
$50,000<$60,000
3.50
$60,000<$70,000
4.08
$70,000<$90,000
4.09
$70,000<$100,000
4.53
>$100,000
4.06
Total
3.72
Legend: 1. Strongly Disagree to 5. Strongly Agree
***P<0.001, **P<0.01, *P<0.05

S.D.
1.25
0.97
0.97
0.76
1.01
1.11
0.96
0.70
0.97
1.11
0.91
1.19
1.27
1.11
1.20
1.38
1.01
0.80
1.11
1.50
0.92
1.04
0.78
1.17
0.87
0.77
0.57
0.90
1.11

df
4

F-Value
31.897***

6

5.336***

3

18.288***

8

16.314***

Construct Validity of the Measurement
Construct validity is a basic issue in creating and/or testing a valid measure of an
underlying construct (Clark & Watson, 1995). Generally, empirical studies establish the
construct validity of a measure by demonstrating its correlation it with a number of other
measures (Westen & Rosenthal, 2003). This study evaluated the construct validity of
the tourism-specific SPC scale by conducting multivariate analysis of covariance
65

(MANCOVA), the multivariate version of analysis of covariance (ANCOVA). Both
ANCOVA and MANCOVA are generally used to evaluate the reliability and validity of
scales (Jones, Fernyhough, de-Wit, & Meins, 2008; Smith & Propst, 2001).
Following the procedure of Peterson et al. (2011), four SPC profile groups
(Figure 8.) were created on the basis of their SPC scale scores. Next, the differences
among the groups and levels of familiarity, tourism participatory behavior, perceived
impact of tourism policy, and sense of community were examined while allowing income
and education to covary.
Figure 8 Classification of SPC Profile Group.
Tourism Policy Control
High
Group 1

Group 2

Leadership Competence
High

Low
Group 3

Group 4
Low

The MANCOVA results demonstrated that, after controlling for education and
income, statistical differences were found between SPC profile groups for all four of the
conceptually relevant measurements. The results are not only consistent with other
employment studies that had education and income as independent variables (Leung,
66

2008; Speer, Jackson, & Peterson, 2001), but also support the construct validity of the
scales used to measure LC and PC. In addition, Post hoc pairwise comparisons
revealed that individuals in Group 1 had significantly higher scores on familiarity than
Group 4. Additionally, post hoc analysis revealed that Group 2 had significantly higher
scores on tourism participatory behavior than Group 1. The third post hoc analysis
indicated that Group 2 had significant higher scores on sense of community than Group
3 and 4. Finally, individuals in Group1 were found to have significantly higher scores on
perceived impact of tourism policy than individuals in Group 4. The results
demonstrated significant differences between SPC profile groups on measures of
familiarity with tourism campaign, tourism participatory behavior, sense of community,
and perceived impact of tourism policy. Specifically, higher levels of tourism policy
control seemed as important for stronger familiarity with tourism campaign and
perceived impact of tourism policy. In sum, the MANCOVA testing provides empirical
support for validity of SPC, and has necessary implications for psychological
empowerment studies in the tourism context.
Table 19. Multivariate Analysis of Covariance Comparing SPC Profile Groups with
Familiarity, Tourism Participatory Behavior, Perceived Impact of Tourism Policy, and
Sense of Community.
SPC Profile Group
Mean
Univariate Different
Variable
Group1 Group2 Group3 Group4 F(3, 588)
P<0.05
Familiarity with
3.17
3.15
3.11
2.97
2.710*
1>4
Tourism Campaign
Tourism Participatory
1.30
1.34
1.09
1.15
10.367***
1<2
Behavior
Sense of Community
3.91
4.10
3.41
3.35
18.813***
2>3.4
Perceived Impact of
3.67
3.54
3.53
3.19
7.859***
1>4
Tourism Policy
Note: Overall SPC multivariate: Wilks Lambda = 0.842; F (12, 1548.056) = 8.686,
p<0.001
Covariate: Income and Education ***P<0.001, **P<0.01, *P<0.05
67

Testing Hypotheses
Hypothesis 1: SOC, FTP, PITP, TPB, and SES will have a direct positive influence on
SPC.
The Independent variables (i.e. predictor variables), SOC, FTP, PITP, TPB, and
SES were entered into a simultaneous regression model predicting SPC. The result,
shown in Table 17, indicated that the model was significant, F (5, 644) = 31.003,
p<0.001, and accounted for 19.4% of the variance in SPC scores. The value of R2
indicated that 19.4% of the variance in SPC can be predicted from the independent
variables. F-test reveals whether the proposed relationship between SPC and the set
of independent variables (SOC, Familiarity, PITP, TPB, and SES) is was statistically
significant. SOC (=0.274, t=7.033, p<0.001), PITP (=0.212, t=5.730, p<0.001), and
TPB (=0.150, t=4.182, p<0.001) were each found to be positive and significant unique
predictors of SPC while FTP and SES were not significant. As a result, Hypothesis 1
was only marginally supported so these two variables were dropped and a second
regression analysis was conducted.
Table 20. Regression Analysis for H1.
Variable
B
Std. Error
t-value

Sense of Community
0.274
0.039
0.274
7.033***
Familiarity of Tourism Campaign
0.011
0.039
0.011
0.291
Perceived Impact of Tourism Policy
0.223
0.039
0.212
5.730***
Tourism Participatory Behavior
0.155
0.037
0.150
4.182***
Socioeconomic Status1
0.019
0.024
0.032
0.792
2
F=31.003*** R =0.194
Note: Dependent variable: Sociopolitical Control. ***P<0.001, **P<0.01, *P<0.05.
1
Socioeconomic status (SES) was calculated by combining a measure of household
income and level of formal educational attainment into a single score. Both scales were
standardized to means of zero and standard deviation of one, and then they were
summated to generate the measure for SES.

68

Figure 9. The relationship between Sociopolitical Control and the Predictors (Initial
Model).

Tourism
Participatory
Behavior
0.274
Familiarity
of Tourism
Campaign

Socioeconomic
Status

0.011

R2=0.194
F=31.033,
p<0.001
Sociopolitical
Control
Tourism
Policy
Control

0.032

Leadership
Competence

0.212
Perceived
Impact of
Tourism
Policy
0.150

Sense of
Community

Note: 1. Solid line indicated the supported hypothesis.
2. Dotted line indicated that hypothesis was not supported.
SOC, PITP, and TPB were entered into a simultaneous regression model
predicting SPC. The modified model was significant F (3, 651) = 51.858, p<0.001, and
19.8% of the variance in SPC was predicted from SOC, PITP, and TPB (Table 18).
SOC (=0.288, t=7.928, p<0.001), PITP (=0.217, t=6.018, p<0.001), and TPB
69

(=0.151, t=4.260, p<0.001) were found to be positive and significantly unique
predictors of SPC. The relationship between SPC and the independent variables is
depicted in Figure 12.
Table 21. Regression Analysis for Modified H1.
Variable
B
Std. Error
Sense of Community
0.287
0.035
Perceived Impact of Tourism Policy
0.228
0.038
Tourism Participatory Behavior
0.155
0.036
2
F=51.858*** R =0.198
Note: Dependent variable: Sociopolitical Control
***P<0.001, **P<0.01, *P<0.05


0.288
0.217
0.151

t-value
7.928***
6.018***
4.260***

Figure 10. The relationship between Sociopolitical Control and the Predictors (Modified
Model).

TPB
0.288

PITP

SOC

0.217

R2=0.194
F=51.858,
p<0.001
SPC

0.151

Hypothesis 2: The relationship between SOC and SPC is partially mediated by TPB.
For testing Hypothesis 2, several steps utilizing the OLS regression were
conducted (Table 25 and Figure 18). The first step satisfied the condition to build
mediation effect which indicated that the independent variable (SOC) influenced the
70

dependent variable (SPC), =0.354, p<0.001. The second step performed for
establishing mediation implies that the SOC requires affecting the mediator (TPB). The
result of the second step was that between these two measure was =0.113, p<0.01.
The third step regressed that the SPC on both the predictor (SOC: =0.337, p<0.001)
and the mediator (TPC: =0.152, p<0.001).
The fourth step indicated that the path c1 (=0.354) was greater than path c2
(=0.337), which demonstrated that partial mediation effect satisfied. The result
informed that there was a mediation effect between SOC and SPC through TPB. In
addition, the Sobel test revealed that TPB (z=2.366, p<0.05) was a significant mediator
of the influence of the SPC on SOC. Taken together, Hypotheses 8 was supported.
Table 22. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Tourism Participatory Behavior.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
SOC
0.354 0.036 0.354 9.670***
SOCSPC (Path c1)
Dependent : SPC
2

SOCTPB (Path a)

3

SOCTPBSPC
(Path b and c2)

SOC
0.110
Dependent: TPB
TPB
0.156

0.038

0.113

2.912**

0.037

0.152

4.170***

SOC
0.335
Dependent: SPC

0.036

0.337

9.255***

4
Path c1 (0.354)>Path c2 (0.337): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05

71

Figure 11. Testing Hypothesis 2 for Measuring Indirect Effect.

TPB
Path a=0.113

SOC

Path b=0.152

Path c1=0.354

SPC

Path c2=0.337
Sobel test: Z=2.366, p<0.05

Hypothesis 3: The relationship between SOC and SPC is partially mediated by SES.
In order to test mediation Hypothesis 3, the path analytical steps described in
Table 2 for demonstrating mediation effects (Vaske, 2008) were followed (Table 23 and
Figure 14). The first step satisfied the condition that the independent variable (SOC)
should influence the dependent variable (SPC), =0.354, p<0.001. The second step is
to show that SOC affects the mediator (SES). Step two was satisfied: =0.377,
p<0.001. The third step regressed the SPC on both independent variable (SOC:
=0.330, p<0.001) and the mediator (SES: =0.156, p<0.05) simultaneously.
The fourth step indicated that the path c1 (=0.354) in the first step was greater
than the path c2 (=0.330), which demonstrated that partial mediation occurred. The
result is that there was a mediation effect between SOC and SPC through SES.
Furthermore, the Sobel test indicated that the SES (z=3.684, p<0.01) was a significant

72

mediator of the influence of SPC on SOC. Taken together, the relationship between
SOC and SPC was partially mediated by SES so Hypothesis 2 was supported.
Table 23. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Socioeconomic Status.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
SOC
0.352 0.036 0.354 9.670***
SOCSPC (Path c1)
Dependent : SPC
2

SOCSES (Path a)

3

SOCSESSPC
(Path b and c2)

SOC
0.627
Dependent: SES
SES
0.152

0.061

0.377 10.350***

0.034

0.156

2.534*

SOC
0.330
Dependent: SPC

0.040

0.330

8.331***

4
Path c1 (0.354)>Path c2 (0.330): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05
Figure 12. Testing Hypothesis 3 for Measuring Indirect Effect.

SES
Path a=0.377

SOC

Path b=0.156

Path c1=0.354
Path c2=0.330

Sobel test: Z= 3.684, p<0.01

73

SPC

Hypothesis 4: The relationship between TPB and SPC is partially mediated by SES.
For testing mediation Hypothesis 3, the OLS regression steps were performed
based on the suggested method (Table 24 and Figure 13). The first step satisfied the
condition for establishing mediation which indicated that the independent variable (TPB)
influenced the dependent variable (SPC), =0.190, p<0.001. The second step
conducted for building mediation indicated that the TPB required affecting the mediator
(SES). The result of the second step reported that between TPB and SES measure
was =0.120, p<0.01. The third step positively regressed the SPC both independent
variable (TPB: =0.174, p<0.001) and the mediator (SES: =0.164, p<0.001).
In the fourth step, the result revealed that path c1 (=0.190) was greater than
path c2 (=0.174), which demonstrated that partial mediation occurred. The result
indicated that there was a mediation effect between TPB and SPC by SES. However, a
significant Sobel test (z=1.737, p>0.05) did not provide evidence that TPB underlies
SPC by SES. Therefore, the relationship between TPB and SPC was not partially
mediated by SES so Hypothesis 3 was not supported.
Table 24. Measuring Mediation Effect between Tourism Participatory Behavior and
Sociopolitical Control through Socioeconomic Status
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
TPB
0.195 0.040 0.190 4.941***
TPBSPC (Path c1)
Dependent : SPC
2

TPBSES (Path a)

3

TPBSESSPC
(Path b and c2)

TPB
0.208
Dependent: SES
SES
0.098

0.067

0.120

3.088**

0.023

0.164

4.286***

TPB
0.180
Dependent: SPC

0.040

0.174

4.538***

4
Path c1 (0.185)>Path c2 (0.061): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05
74

Figure 13. Testing Hypothesis 4 for Measuring Indirect Effect.

SES
Path a=0.120

TPB

Path b=0.164

Path c1=0.190

SPC

Path c2=0.174
Sobel test: Z=1.737, p=0.082

Hypothesis 5: The relationship between TPB and SPC is partially mediated by FTC.
The steps using the OLS regressions provided to test mediation Hypothesis 5
(Table 25 and Figure 16). The first step satisfied the condition to build mediation which
indicated that the independent variable (TPB) influenced the dependent variable (SPC),
=0.190, p<0.001. The second step performed for establishing mediation implies that
SES needs to affect the mediator (FTC). The result revealed that between these two
variables was =0.138, p<0.01. The third step regressed the SPC on both independent
variable (TPB: =0.172, p<0.001) and the mediator (FTC: =0.138, p<0.001)
simultaneously.
Finally, the path c1 (=0.190) was greater than c2 (=0.172), which
demonstrated that partial mediation occurred. The result revealed that there was a
mediation relationship between TPB and SPC by FTC. Additionally, the Sobel test
indicated that Familiarity (z=2.432, p<0.05) was a significant mediator of influence of the
75

SPC on Familiarity. In sum, the association between TPB and SPC was partially
mediated by FTC; hence, Hypothesis 4 was supported.
Table 25. Measuring Mediation Effect between Tourism Participatory Behavior and
Sociopolitical Control through Familiarity with Tourism Policy.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
TPB
0.195 0.040 0.190 4.941***
TPBSPC (Path c1)
Dependent : SPC
2

TPBFTC (Path a)

3

TPBFTCSPC
(Path b and c2)

TPB
0.135
Dependent: FTP
FTC
0.139

0.040

0.131

3.373**

0.038

0.138

3.603***

TPB
0.177
Dependent: SPC

0.040

0.172

4.472***

4
Path c1 (0.190)>Path c2 (0.172): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05
Figure 14. Testing Hypothesis 5 for Measuring Indirect Effect between TPB and SPC
through FTC.

FTC
Path a=0.131

TPB

Path b=0.138

Path c1=0.190
Path c2=0.172

Sobel test: Z=3.432, p<0.05

76

SPC

Hypothesis 6: The relationship between TPB and SPC is partially mediated by PITP.
For testing mediation Hypothesis 6, several steps using the OLS regression were
conducted (Table 26 and Figure 17). The first step met the condition to establish
mediation which indicated that the predictor (TPB) influenced the criterion (SPC),
=0.190, p<0.001. The second criterion for establishing mediation is that TPB required
should affect the mediator (PITP). There was no statistical significance between TPB
and PITP (=0.029). The result revealed that this condition for mediation effect was not
satisfied. The third step positively regressed the SPC both the predictor (TPB: =0.182,
p<0.001) and the criterion (SPC: =0.281, p<0.001). In the fourth step, the result
indicated that path c1 (=0.190) was greater than path c2 (=0.182), which revealed
that partial mediation was demonstrated. However, the Sobel test was not significant
(z=0.759, p>0.05). Therefore, Hypothesis 5 was not supported.
Table 26. Measuring Mediation Effect between Tourism Participatory Behavior and
Sociopolitical Control through Perceived Impact of Tourism Policy.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
TPB
0.195 0.040 0.190 4.941***
TPBSPC (Path c1)
Dependent : SPC
2

TPBPITP (Path a)

3

TPBPITPSPC
(Path b and c2)

TPB
0.028
Dependent: PITP
PITP
0.295

0.038

0.029

0.734

0.039

0.281

7.625***

TPB
0.187
Dependent: SPC

0.038

0.182

4.932***

4
Path c1 (0.190)>Path c2 (0.182): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05

77

Figure 15. Testing Hypothesis 6 for Measuring Indirect Effect.

PITP
Path a=0.029

TPB

Path b=0.281

Path c1=0.190

SPC

Path c2=0.182
Sobel test: Z=0.759, p>0.05

Hypothesis 7: The relationship between SOC and SPC is partially mediated by FTC.
To test mediation Hypothesis 7, the study conducted several steps using the
OLS regression (Table 27 and Figure 18). The first step satisfied the condition to build
mediation which indicated that the independent variable (SOC) influenced the
dependent variable (SPC), =0.354, p<0.001. The second step performed for building
mediation implies that the SOC requires affecting the mediator (FTC). The result of the
second step was that between these two measure was =0.252, p<0.001. The third
step regressed that the SPC on both the predictor (SOC; =0.335, p<0.001) and the
mediator (Familiarity: =0.077, p<0.05) simultaneously.
The fourth step indicated that the path c1 (=0.354) was greater than path c2
(=0.335), which demonstrated that partial mediation effect satisfied. The result
informed that there was a mediation effect between SOC and SPC through FTC.
78

Furthermore, the Sobel test indicated that F (z=2.024, p<0.05) was a significant
mediator of the influence of the SPC on SOC. Taken together, the relationship between
SPC and SOC was partially mediated by FTC so Hypothesis 7 was supported.
Table 27. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Familiarity of Tourism Campaign.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
SOC
0.354 0.036 0.354 9.670***
SOCSPC (Path c1)
Dependent : SPC
2

SOCFTC (Path a)

3

SOCFTCSPC
(Path b and c2)

SOC
0.250
Dependent: FTP
FTC
0.077

0.038

0.252

6.640***

0.038

0.077

2.032*

SOC
0.333
Dependent: SPC

0.038

0.335

8.870***

4
Path c1 (0.354)>Path c2 (0.335): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05
Figure 16. Testing Hypothesis 7 for Measuring Indirect Effect between SOC and SPC
through FTC.

FTC
Path a=0.252

SOC

Path b=0.077

Path c1=0.354
Path c2=0.335

Sobel test: Z=2.024, p<0.05

79

SPC

Hypothesis 8: The relationship between SOC and SPC is partially mediated by PITP.
For assessing mediation Hypothesis 8, the OLS regression steps were
performed based on the suggested method (Table 24 and Figure16). The first step met
the criterion in order to establish mediation which indicated that the independent
variable (SOC) influenced the dependent variable (SPC), =0.354, p<0.001. The
second step conducted for establishing mediation indicated that the SOC required
affecting the mediator (PITP). The result of this step reported that between SOC and
PITP measure was =0.224, p<0.001. The third step positively regressed the SPC both
independent variable (=0.305, p<0.001) and the mediator (=0.218, p<0.001).
In the final step, the result revealed that path c1 (=0.354) was greater than path
c2 (=0.305), which demonstrated that partial mediation occurred. The result indicated
that there was a mediation effect between SOC and SPC through PITP. In addition, a
significant Sobel test (z=4.218, p<0.001) provided evidence that SOC underlies the
SPC by the PITP. Therefore, the association between SOC and SPC was partially
mediated so Hypothesis 8 was supported.
Table 28. Measuring Mediation Effect between Sense of Community and Sociopolitical
Control through Perceived Impact of Tourism Policy.
Step
Description
Variable
B
Std.
t-value

(Path)
Error
1
SOC
0.354 0.036 0.354 9.670***
SOCSPC (Path c1)
Dependent : SPC
2

SOCPITP (Path a)

3

SOCPITPSPC
(Path b and c2)

SOC
0.212
Dependent: PITP
PITP
0.229

0.036

0.224

5.869***

0.038

0.218

5.955***

SOC
0.305
Dependent: SPC

0.036

0.305

8.337***

4
Path c1 (0.354)>Path c2 (0.305): Partial Mediation
Note: ***P<0.001, **P<0.01, *P<0.05
80

Figure 17. Testing Hypothesis 8 for Measuring Indirect Effect between SOC and SPC
through PITP.

PITP
Path a=0.224

SOC

Path b=0.218

Path c1=0.354

SPC

Path c2=0.305
Sobel test: Z=4.218, p<0.001

Summary of Hypothesis Testing
The eight hypotheses of this study were tested by path analyses utilizing
simultaneous multiple regression. Additionally, several steps using the OLS regression
was used to demonstrate the partial mediation effects of a set of variables.
Hypothesis 1 was supported after removing two predictors (Familiarity of Tourism
Campaign). The result indicated that SOC, PITP, and TPB had a direct positive
influence on SPC (See Figure 10.). Figure 20 depicted the result of testing mediation
hypotheses. Hypothesis 2 was supported, indicating that the relationship between SOC
and SPC was partially mediated by TPB. Hypothesis 3 was supported in that the
relationship between SES and SPC was partially mediated by SOC. Hypothesis 4 was
not supported because the Sobel test showed no statistical significance at the level of
0.05 even though the steps of the OLS regression satisfied the condition of the
81

mediation effect. Hypothesis 5 was supported in that the relationship between TPB and
SPC was partially mediated by FTC. Hypothesis 6 was not supported because the
Sobel test showed no statistical significance at the confidence at the Alpha level of 0.05.
Hypothesis 7 was supported that the association between SOC and SPC was partially
mediated by FTC. Finally, Hypothesis 8 was supported that the association between
SOC and SPC was partially mediated by PITP.
Figure 18. The Result of Testing Mediation Hypotheses.

SES

SPC
FTC
TPC
TPB

LC
PITP

SOC

Note: 1. Solid line indicated the supported hypothesis.
2. Dotted line indicated that hypothesis was not supported.

82

Chapter 5
Discussion and Conclusion
This chapter is comprised of four sections. The first section presents key findings
of this study. The second section discusses theoretical and practical implications and
contributions. The limitations of the present study and directions of future study are
addressed in the final two sections.
Summary of Key Findings
Objective 1: Psychometric Rigor for Sociopolitical Control and Sense of
Community
This study empirically examined sociopolitical control (SPC) and sense of
community as valid constructs in the tourism context. Confirmatory factor analysis
(CFA) was conducted to test construct validity. The full proposed model did not
adequately fit the data set. Three items in the tourism policy control subscale (TPC:
TPC1, TPC4, and TPC6) were deleted from the full measurement model. The value of
standardized factor loadings and model fit indices were used in selecting the variables
that were deleted. The modified model fits the data well.
The results of CFA established evidence of reliability which refers to precision
and accuracy of a measurement instrument in the modified model. Additionally, the
result demonstrated discriminant validity which shows how much variance is in the
indicators that are able to explain variance in the construct (Said, Badru, & Shahid,
2011, p. 1099). Even though this study employed reduced sets of items for SPC and
SOC like previous research in other domain (Christens, Speer, & Peterson, 2011;
83

Hughey, Peterson, Lowe, & Oprescu, 2008; Peterson & Reid, 2003), the slightly
modified tourism-specific model is consistent with the model of psychological
empowerment found in other domains. Furthermore, the result of the multivariate
analysis of covariance (MANCOVA) revealed evidence of construct validity of scales
used to measure LC and TPC. This was through demonstration of correlation between a
number of other measures such as tourism participatory behavior, familiarity of tourism
campaign, socioeconomic status, and perceived impact of tourism policy.
Hence, psychological empowerment of citizens is an indicator of the success of
community participation in the policy-making process, including tourism planning.
Sense of community is significant as studies have shown it to be a precursor of citizen
participation in activities and organizations. Therefore, these two indicators can
contribute to assess residents’ sense of community and empowerment in influencing
decisions that impact local tourism outcomes. They also can make recommendations to
tourism promotion and policy makers for ways to enhance the success of the tourism
promotion and policy for increasing support from local communities.
Objective 2: Group Differences in Psychological Empowerment and Sense of
Community
After examining the validity of the SPC and SOC scales, the study conducted
one-way analysis of variance (ANOVA) tests to find citizens’ different perspectives
toward SPC and SOC by socio-demographic characteristics. The results indicated that
there were statistically significant differences between TPC and a set of independent
variables (age, region, education, and household income) at the significance level of
0.001. Additionally, statistically significant differences were found between leadership
84

competence and a set of independent variables (age, region, and household income) at
the significance level of 0.05. Finally, sense of community varied by age, region,
education, and household income at the level of 0.001.
These results indicated that empowerment and sense of community were
relatively high overall, but certain groups (those less than 30 years old, those more than
60 years old, and residents of Detroit) felt less empowered and less attached to their
communities. The results indicated that the survey participants felt knowledgeable and
qualified to make decisions regarding Pure Michigan. They are also motivated to
exercise their voice in state politics, through voting and other means. However,
Michigan residents felt that the mechanism available to them for influencing decisions
regarding Pure Michigan is limited. In other words, their actual political behaviors are
limited, not by desire but by lack of knowledge of the means available to them for
exercising their voice.
In addition, the results suggested that an important barrier to a younger person’s
sense of empowerment is their lack of understanding of the important issues related to
Pure Michigan. On the other hands, older persons expressed less confidence in their
ability to lead and organize others than younger persons. Even so, the means are
relatively high (close to 4 and above 4 on a 5-point scale) for all age groups for
sociopolitical control as an indicator of psychological empowerment. This is a good sign
as competent leaders and policy controllers for all ages are needed in state tourism
planning and policy development. The results also revealed that older persons felt
more attachment to their communities than younger persons. Furthermore, residents of
all regions, except Detroit, were more likely to feel that their communities met their
needs.
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In sum, Michigan residents felt empowered to participate in political actions
regarding the campaign with one important exception: knowing how to participate. Lack
of knowledge of the various means by which citizens can exercise their voice with
regard to Pure Michigan is a major factor that needs to be addressed by the state.
Objective 3: Relationship among Socioeconomic Status, Sense of Community,
Sociopolitical Control, Tourism Participatory Behavior, Familiarity of Tourism
Campaign and Perceived Impact of Tourism Policy
This study conducted a path analysis with a simultaneous regression test to find
the relationship between SPC and SOC, familiarity, perceived impact of tourism policy
(PITP), tourism participatory behaviors (TPB), and socioeconomic status (SES). Even
though the proposed model explained 19.4% with significance at the level of 0.001, it
was not wholly supported because familiarity and SES were not found to be significant
unique predictors of SPC. Hence, the modified model was re-tested after removing
these two predictors. The modified model was significant, and accounted for 19.8% of
the variance in SPC scores. SOC, PITP, and tourism participatory behavior (TPB) were
each found to be significant unique predictors of SPC.
The modified model explained 20% of the variance in SPC, which may be
considered as weak evidence that the three predictors affect SPC. The results can be
derived from several reasons like measurement error which may come from systematic
error by sampling bias. The predictor variables generally have small effects on
dependent variables in social science (Cohen, 1990; Stevens, 2007), but it does not
mean that the results are not significant. The present study firstly tested that the
predictor variables can affect sociopolitical control in the tourism domain. In the early
86

stages, there is not enough research that has been provided to identify all the variables
that would explain for the variance (Pearce, Kramer, & Robbins, 1999).
The relationship among the variables revealed that sense of community, citizen
participation and perception of citizens’ perception of their efficacy in tourism policymaking can affect a topic-specific measure of sociopolitical control. These results
indicate that engaged citizens can contribute to create their high perspectives of
psychological empowerment.
Objective 4: Partial Mediation Effect toward Sociopolitical Control
Path analysis utilizing a set of OLS regression equations was conducted to find
partial mediation effects between the variables and SPC. The results confirmed most
hypothesized relationships, except for Hypothesis 4 (TPBSESSPC) and Hypothesis
6 (TPBPITPSPC). To summarize: 1) SOC was found to partially act on SPC via
SES; 2) TPB was found to partially act on SPC via FTC; 3) SOC was found to partially
act on SPC via FTC and PITP.
The mediating analyses demonstrated the indirect effect between a set of
predictors and sociopolitical control via mediators. The mediating relationship can
explain relationships between sociopolitical control and a set of independent variables
through the mediators. The results indicated that FTC and PITP are environmental
variables that have been found to mediate the effects of SOC and participatory
behaviors in other studies.
Theoretical Implications

87

The present study has several theoretical implications for citizens’ participation
and community involvement in the tourism domain. First, this study is the only empirical
study examining whether the SPC can be modified for use in the tourism domain. The
SPC scale has been widely used to assess citizens’ level of psychological
empowerment in policy-making in community programs and policies (Peterson, Lowe, et
al., 2006; Zimmerman, 1995, 2000; Zimmerman, Ramí
rez-Valles, & Maton, 1999).
Sense of community has been recognized as an important situation-related variable that
is empirically related to citizens’ empowerment (Colombo, Mosso, & DePiccoli, 2001;
Herman, Onaga, Pernice-Duca, Oh, & Ferguson, 2005; McMillan, 1996: Peterson &
Reid, 2003).
This study provides empirical evidence that SPC and SOC can be applied to
future tourism studies to use as a valid measurement tool. In addition, several studies
have demonstrated reliability and validity of reduced item versions of these two scales
(B. D. Christens, N. A. Peterson, & P. W. Speer, 2011; Peterson, et al., 2008). The
present study also provided evidence of valid measurement properties, while utilizing
the reduced items of the constructs with modified wording appropriate to the tourism
context.
Second, this study provides a foundation for researchers in the understanding of
the association among SPC, SOC, and participatory behavior in the realm of tourism
policy-making. Previous studies conclude that SOC and participatory behaviors predict
SPC (Peterson & Reid, 2003; Peterson, Speer, & Peterson, 2011). The present study
confirms the same set of relationships among these dimensions in tourism policymaking. In particular, SOC and participatory behaviors related to tourism directly
predicted SPC. Furthermore, SOC influences SPC indirectly through participatory
88

behaviors. The results provide evidence that citizens with a greater sense of
community participated more and are more psychologically empowered. The study also
demonstrates that citizens who participate in policy-making processes often feel more
psychologically empowered.
The third implication expands upon the previous two implications. Several
studies have examined the association among SPC, SOC, and a set of predictors such
as socio-demographic characteristics, awareness, alienation, and other situational
variables (B. D. Christens, P. W. Speer, et al., 2011; Hughey, et al., 2008; Itzhaky &
York, 2000; Peterson & Hughey, 2002; Peterson, et al., 2011). Most research relevant
to the association among SPC, SOC, and other variables has studied the direct effect
between observed variables by utilizing hierarchical regression tests with moderators.
The mediator effect is the indirect effect between independent and dependent variables
via mediator variables. The moderator effect tests for an interaction effect that the
effect of independent variable on the dependent variable on the level of a third variable
(Kramer, Kiernan, & Essex, 2008). Tourism studies have tested the indirect (i.e.
mediator) effect of certain predictors and outcomes. These were several mediation
effects discovered via analysis recommended by Vaske (2008). The mediation
hypotheses of the present study explained the relationships between predictors and
sociopolitical control in the tourism domain through a causal step approach. For
instance, SOC has a causal influence on SPC directly and through the indirect effect of
PITP. Hence, this study explains several mediation effects toward SPC between
observed variables in the tourism context by using ordinary least squares regression.
An advantage of ordinary least square regression is to easily check measurement error
and the model assumption of outliers.
89

In sum, the present study indicates that the scales used to measure SPC and
SOC exhibit acceptable psychometric properties. The present study demonstrated that
SPC and SOC can be validly measured utilizing reduced item versions. Furthermore,
the relationships found in other contexts hold when examined in the tourism domain.
Practical Implications
The results of this study can provide several practical implications to
policymakers and tourism planners. First, the present study stresses the importance of
sociopolitical indicators of success such as citizens’ psychological empowerment and
participation in tourism policy and planning efforts. Tourism is a system, of which
destination and host communities are integral parts, but most impacts of tourism
policies and promotions are mainly evaluated with economically-oriented indices like the
return on investment (ROI). Social impacts including the level of citizen participation,
community involvement, and empowerment need to be addressed as important
measures of success of tourism policies and promotions. There is a need to address
sociopolitical indicators of success, such as the local level sentiments about the
usefulness of various tourism promotions or level of local participation in tourism
planning efforts. Tourism is a system, of which destinations and host communities are
integral parts so tourism promotion and policy require citizens’ active participation for
achieving their purposes.
Second, it is recommended that more information is provided about ways citizens
can engage with tourism policy-making and planning. With one important exception, the
empirical results of the present study revealed that Michigan citizens have a good sense
of tourism policy control when it comes to Pure Michigan (i.e. they understand the
90

issues and feel it is important to participate in state politics). That one exception is the
relative lack of knowledge of ways to influence how Pure Michigan funds are spent.
Combined, these two results indicated that Travel Michigan should provide clear and
easily understandable information about the process by which Pure Michigan funds are
allocated and how citizens may have a voice in that process. Combined with more
efforts at the level to leverage interest in Pure Michigan, more channels for
communicating with citizens will increase empowerment and participation in the policy
making process regarding the state’s tourism industry.
Third, there were mean differences on both statewide and local impacts of the
Pure Michigan campaign between regions. In particular, residents of Detroit and the
East Central region were least positive about local impacts than other regions. It is not
clear why these residents feel this way. However, the study recommends that state
tourism representatives identify reasons for these results and then set up the campaign
resources and efforts, including partnerships, in these regions. Studies have
recognized local tourism partnerships as key ingredients for improving tourism
attractions and destinations for local communities and visitors simultaneously (Wang &
Krakover, 2008; Watkins & Bell, 2002). Moreover, the partnerships can play a role to
reduce different perceived impacts of Pure Michigan both local and statewide by having
more opportunities to participate in the campaign.
Fourth, voluntary citizen participation and active community involvement have
been accepted as a critical components sustainable tourism development and planning
(Buckley, Pickering, & Weaver, 2003; Dredge, 2006). The tourism specific SPC scale
provides practitioners a valid and reliable quantitative tool for assessing policy

91

outcomes. The empirical tool can contribute to bridging the gap between agencies and
local communities.
Fifth, studies have demonstrated that the intrapersonal component of
psychological empowerment is an indicator of the effectiveness of programs and other
initiatives in public health and other fields. Likewise, increases in psychological
empowerment can result from tourism policies and planning that produce enhancement
in citizen participation. In the context of tourism, it is significant for citizens to feel
empowered because tourists can experience what tourism attractions promise when
citizens of local communities are empowered for the tourism policies and programs.
Therefore, this association is governed by a socialization mechanism, which indicates
that tourism representatives need to be more intentional about improving socialization
processes such as a sense of community and tourism participatory behaviors. This can
be achieved through developing efficient media including email, websites, blogs, and
social media for enhancing citizen participation (B. Christens, et al., 2011).
In summary, this study provides empirical evidence to tourism policymakers and
agencies for evaluating the social outcomes of their programs with focus on communitybased programs and initiatives. This approach can be used in concert to pursue
sustainable tourism policies and promotion by obtaining strong support and consensus
from local communities and building capacity
Limitations
Several limitations were found through the research process of this study. The
present study employed a CATI telephone survey with random sampling of Michigan
residents.
92

The first limitation includes demographic bias. In comparing the US Census
2010 data to the demographic data of the participants, there was the disparity of age
distribution of more than 60 years old between the Census data (18.9%) and the survey
data (51.7%) (U.S. Census, 2011). The disparity of the age distribution may be due to
the timing of the survey because the telephone survey selected the survey participants
who had landline phones. Under the Telephone Consumer Protection Act of 1996, the
interviewees of the telephone survey are only allowed to interview the survey
participants of the telephone survey between 8:00 and 21:00 (Marketing Research
Association, 2012). This limitation of interview timing produces demographic bias such
as overrepresentation of the respondents who were more than 60 years old because
the elderly age group has a higher possibility of being at home during the timing of the
telephone survey rather than the younger age group (Frarquhar, 1995; Hilderbrand,
2003). In addition, research revealed that as of 2005, approximately 63% of American
adults whose ages are between 18 and 34 years old do not have landline phone in their
household (Blumberg, Luke, Cynamon, & Frankel, 2006). Therefore, the disparity of
age distribution is one of the sampling limitations in this study.
The second limitation of this study is also related to the telephone survey. In the
last decade, there has been an increase of the proportion of the American adult
population with a cell phone as their primary contact, instead of having a landline phone
(Link, Battaglia, Frankel, Osborn, & Mokdad, 2007). As of 2010, over 20% of American
households have cut landline telephones and only use cell phones (Foreman, 2010). In
Michigan, as of 2010, approximately 29% of Michigan households only have cell phones
for their voice communication (Tavernise, 2011). These aspects produce the limitation
of sample coverage for the household survey of this study by utilizing landline telephone
93

surveys. The issue of sample coverage is closely correlated to the overrepresentation
of the proportion of the elderly aging group in this study.
The third limitation concerns the survey instrument scales. The items of the
major construct of this study were reworded to be appropriate to the tourism domain.
The reduced items of this study are valid and reliable measurement in the tourism
domain, but as the number of items in a scale increase, the reliability of the scale can
improve.(Thorndike & Thorndike-Christ, 2010). The rephrased items of tourism policy
control scale were found to be problematic in terms of testing citizens’ involvement in
tourism policies and promotion. Three items of tourism policy control were removed
based on low factor loadings. Moreover, the items of SOC in this study were reliable
and related to the proposed model, but the study did not clearly define what community
is in the context of this study. The unclear definition and the combination of
“neighborhood and community” may have confused some survey participants.
The fourth limitation is relevant to the context of survey and the fact that
questions of this study were embedded in a larger survey that asked a variety
questions, including global climate change, transportation related issues, the purchase
of medications via the Internet, and so forth. Combining various topics in a large survey
instrument have been shown to impact the results (Fowler, 2009).
Directions of Future Study
The limitations suggest several directions for future study. First, it is
recommended that future research tests the full number of items of SPC and SOC for
more valid and reliable measurement properties in the tourism domain. Even though
several studies yielded appropriate validity and reliability from the reduced items of this
94

construct, a future study requires testing the items with rephrasing questions for the
tourism domain. This recommendation should result in stronger association among
citizens’ sense of PE, SOC, and participatory behavior in tourism policy and promotion.
Second, there are three components of PE such as intrapersonal, interpersonal,
and behavioral components. Future research is recommended to test citizens’ different
perspectives of the three different components of PE. This recommendation will
contribute to find the theoretical connections among the three components of PE, which
helps improve the assessment and design of community intervention and the overall
predictive ability of the model (Zimmerman, Israel, Schulz, & Checkoway, 1992).
Third, citizens’ socioeconomic statuses have utilized a variable to find
association among citizen participation, sense of community, and psychological
empowerment. Demographic variables, however, are generally weak and complicated
predictors so valid and reliable sampling design and methods of data collection are
necessary. Studies related to the topic of this study have criticized the fact that landline
telephone surveys are biased with respect to complicated or sensitive issues like
community (Hughey, et al., 2008; Peterson & Reid, 2003). As mentioned in the
limitation section, landline telephone surveys have a high risk of fair distribution of
demographic variables. In particular, there has been an increase of households and
adult populations with only a cell phone in the United States during the last decade.
This aspect suggests a future study to consider how to cover households without
landline phones in the telephone survey. The present study recommends a future study
to appropriately select a telephone survey between landline phones and cell phones
depending on characteristics of survey population. Hence, telephone surveys of

95

landline only samples are biased and need to be replaced by other methods, including
telephone surveys that include mobile phones, mail and Internet surveys.

96

APPENDICES

97

APPENDIX A. Subset of SOSS that Generated the Data Used in this Study
Before we begin, let me tell you that this interview is completely voluntary. You may
choose not to participate and you may end your participation at any time without penalty.
Should we come to any question that makes you feel too uncomfortable or you do not
want to answer, just let me know and we can go on to the next question. Information
collected for this study will be kept confidential to the extent allowed by local, state and
federal law, and no reference will be made in any oral or written report that would link
you individually to this study. While there is no direct benefit to you personally for
participating in this research, results from this research may produce benefits to the
people of the State of Michigan. There are also no known risks to you personally for
participating in this research. For quality control purposes, this interview may be
monitored by my supervisor. The supervisor has the ability to listen to the interview at
anytime.
I would like to ask you some questions about the Pure Michigan Advertising campaign.
Pure Michigan is a nation-wide campaign that was launching in 2006 as a way of
promoting tourism in Michigan, a branch of the Michigan Economic Development
Corporation, manages the Pure Michigan campaign.
<pure1> How familiar are you with the Pure Michigan campaign?
(4) very familiar (3) somewhat familiar (2) not very familiar (1) not familiar at all
(8) do not know (9) refused
To what extent do you agree or disagree with each of the following statements
about the Pure Michigan campaign?
<pure2a> The Pure Michigan campaign has positively affected tourism in Michigan
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2b> The Pure Michigan campaign has positively affected tourism in my local
community.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2c> I feel like I have a pretty good understanding of the important issues
surrounding the Pure Michigan campaign.
98

(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2d> I enjoy political participation because I want to have as much say as possible
in influencing a state government agency like Travel Michigan.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2e> People like me are generally qualified to participate in decisions affecting
state programs like the Pure Michigan campaign.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2f> There are plenty of ways for people like me to have a say in how Pure
Michigan funds are spent.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2g> It is important to me that I actively participate in influencing state government.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure2h> It is important to vote in state elections that might affect the outcome of the
Pure Michigan campaign.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
In the past five years, please tell me if you personally participated in any of the
following activities related to the Pure Michigan campaign or tourism planning in
general.
<pure3a> I attended a public hearing or meeting that addressed statewide or local
tourism issues?
(1) yes (2) no (8) do not know (9) refused
99

<pure3b> I communicated with Travel Michigan or state government about some matter
related to the Pure Michigan campaign.
(1) yes (2) no (8) do not know (9) refused
<pure3c> I served on a committee or advisory board that addresses tourism issues
such as the Visitor and Convention Bureau, or a similar body.
(1) yes (2) no (8) do not know (9) refused
<pure3d> I wrote a letter to an editor of a newspaper about the Pure Michigan
campaign.
(1) yes (2) no (8) do not know (9) refused
<pure3e> I posted a comment on Facebook, Twitter or a blog about the Pure Michigan
campaign.
(1) yes (2) no (8) do not know (9) refused
I would like to read you some statements related to working with others to
achieve a goal. For each, please tell me to what extent you agree or disagree with
each.
<pure4a> I am often a leader in groups.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure4b> I would prefer to be a leader rather than follower.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure4c> I would rather have a leadership role when I am involved in a group project.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure4d> I can usually organize people to get things done.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
100

<pure4e> Other people usually follow my ideas.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
Now, thinking about your neighborhood or your community, please tell me to
what extent you agree or disagree with each statement.
<pure5a> My neighborhood or community helps me fulfill my needs.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure5b> I feel like a member of my neighborhood or community.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure5c> I have a say about what goes on in my neighborhood or community.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
<pure5d> I have a good bond with others in my neighborhood or community.
(1) strongly agree (2) somewhat agree (3) neither (4) somewhat disagree
(5) strongly agree (8) do not know (9) refused
Finally, I have some background questions for you.
<CD1> I need to verify that I am speaking with a male/female adult?
(1) male (2) female (8) do not know (9) refused
<CD2> In what year were you born?
<CD3> What is the highest level of education you have completed?
(0) did not go to school (1) 1st grade (2) 2nd grade (3) 3rd grade (4) 4th grade
(5) 5th grade (6) 6th grade (7) 7th grade (8) 8th grade (9) 9th grade (10) 10th grade
(11) 11th grade (12) 12th grade (13) 1st year college (14) 2nd year college
101

(20) technical/junior college graduate (15) 3rd year college
(16) college graduate (four year) (17) some post graduate (18) graduate degree
(98) do not know (99) refused this question
To get a picture of people’s financial situations, we’d like to know the general
range of incomes of all households we interview. This is for statistical analysis
purposes and your answers will be kept strictly confidential.
<inca> Did your household receive $40,000 or more 2010?
(1) yes (go to incd) (2) no (go to incb) (8) do not know (9) refused
<incb> Was it less than $20,000?
(1) yes (go to incc) (2) no (go to incca) (8) do not know (9) refused
<incca> What is less than $30,000?
(1) yes (2) no (8) do not know (9) refused
<incc> Was it less than $10,000
(1) yes (2) no (8) do not know (9) refused
<incd> Was it $60,000 or more?
(1) yes (go to incg) (2) no (go to incf) (8) do not know (9) refused
<incf> Was it $50,000 or more?
(1) yes (2) no (8) do not know (9) refused
<incg> Was it more than $100,000?
(1) yes (go to inci) (2) no (8) do not know (9) refused
<inch> Was it more than $70,000?
(1) yes (2) no (8) do not know (9) refused
<incha> Was it more than $90,000?
(1) yes (2) no (8) do not know (9) refused
<inci> Was it more than $150,000?
102

(1) yes (2) no (8) do not know (9) refused
<zipcode> What is your zip code?

103

APPENDIX B. Operational Definition of Major Variables

Category

Latent
Variable

Policy
Control

Definition
(Source)

Item

A sense of control
over one’s own life
toward tourism
policy making
processes
(Zimmerman &
Zahniser, 1991;
Smith & Propst,
2001; Holden et al.,
2005).

SPCS

Individuals’ skills
that may include
organizing others in
order to achieve
common goals and
speaking in front of
Leadership large group
Competence (Zimmerman &
Zahniser, 1991;
Smith & Propst,
2001; Peterson et
al., 2006).
104

Scale

I feel like I have a pretty
good understanding of
the important issues
surrounding the Pure
Michigan campaign.
I enjoy political
participation because I
want to have as much say
as possible in influencing
a state government
agency like Travel
Michigan.
People like me are
generally qualified to
participate in decisions
affecting state programs
like the Pure Michigan
1. Strongly
campaign.
Disagree
There are plenty of ways
for people like me to have 2. Somewhat
Disagree
a say in how Pure
Michigan funds are spent.
3. Neither
It is important to me that I 4. Somewhat
actively participate in
Agree
influencing state
5. Strongly
government.
Agree
It is important to vote in
state elections that might
affect the outcome of the
Pure Michigan campaign.
I am often a leader in
groups.
I would prefer to be a
leader rather than
follower.
I would rather have a
leadership role when I am
involved in a group
project.
I can usually organize
people to get things done.
Other people usually
follow my ideas.

References

105

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