the role of location in the marketing strategy of performing arts organizations

The Role of Location in the
Marketing Strategy of Performing Arts Organizations

By
Christine A. Lai
October, 2006

A dissertation submitted to the Faculty of the Graduate School of the
State University of New York at Buffalo in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy

Department of Geography

UMI Number: 3244223
3244223
2007
Copyright 2007 by
Lai, Christine A.
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ii
Acknowledgements
This dissertation is the result of the contributions of many extremely creative and
valued professionals. The number of individuals who have contributed to this
dissertation study, both intellectually and emotionally, are numerous, and it would be
impossible to thank them all. However, I would like to especially thank Dr. Jessie Poon,
who agreed to act as my dissertation advisor, and whose patience, enthusiastic support,
and expertise inspired me to persevere. She was integral to the development of this
study from its inception, and her efforts constitute the primary reason that I received
funding for this research. The exceedingly generous amount of time and work she
contributed to guiding me along every step of my degree program is a testament to her
superior professionalism. I am forever grateful.

My thanks to my committee members, Dr. James McConnell and Dr. Alan
MacPherson who contributed insight to my research by offering useful comments at the
preliminary stage of my research and for the knowledge they imparted during the
coursework stage of my studies.

The following professionals provided invaluable guidance. The insight and
knowledge of the performance arts industry of Randall Kramer played a key role in the
development of my survey instrument, the foundation of my study. Dr. Peter Rogerson’s
assistance with statistical testing subject matter is significantly valued. I would also like
to thank my friend and colleague Dr. William DiPietro for his support and for serving as
my sounding board as I verbally organized ideas.

On the personal level, I would like to express my sincere gratitude to my family
for their patience and support throughout this entire process. I dedicate this work to
them: to my children Daniel, Kimberly, and William, whose drive for academic
excellence inspired me to continue with my studies, and my supportive husband Sek

Hong for his love and encouragement.

iii
Table of Contents

Page
Abstract x
1 Introduction 1
1.1 Introduction and Motivation 1
1.2 Purpose of Dissertation Research 4
1.3 Overview of Dissertation 9
2 Theoretical Background 11
2.1 Traditional Regional Development Theories 11
2.2 More Recent Development Theories 19
2.2.1 Agglomeration economies and clusters 19
2.2.2 Localization and urbanization economies 22
2.2.3 Creative economies and human capital theory 28
2.3 Summary 32
3 Marketing and Nonprofit Performance Arts Organizations:
Some Background 34
3.1 Marketing Defined 34
3.2 Marketing Nonprofit Organizations 36

iv
3.3 Background of Nonprofit Performance Arts Organizations 37
3.4 Location Preferences of Nonprofit Organizations 39
3.5 Summary 48
4 Data Collection Technique and Respondents Profile 50
4.1 Research Questions 50
4.2 Data 51

4.3 Variables and Constructs 59
4.4 Summary 65
5 Respondents’ Profile, Analysis, and Discussion 66
5.1 Characteristics of Nonprofit Performing Arts 66
5.2 Locational Factors 79
5.2.1 Summary of Results from Research Question #1 95
5.3 The Marketing Mix 97
5.3.1 Regression Variables 97
5.3.1.1 Dependent Variable: Revenue Concentration Index (REVCON) 97
5.3.1.2 Independent Variables 99
5.3.1.3 Variable Summary 110
5.3.2 Statistical Analysis 110
5.3.3 Summary of Regression Analysis 115

v
5.4 The Arts and Regional Development 116
5.4.1 Summary of Results from Research Question #3 128

6 Conclusion 130
6.1 Summary of Dissertation 131
6.2 Policy Implications 137
6.3 Limitations of Study and Future Directions 139
References 141
Appendix I Survey Instrument 152

vi
List of Tables
Title Page
Table 1.1: Industrial Employment Statistics among cities in
Northeastern and Midwestern United States 7

Table 1.2: Occupational Employment Statistics among cities in
Northeastern and Midwestern United States 8
Table 4.1: Population Size of Performance Arts Organizations 52
Table 4.2: Survey Response Results 56
Table 4.3: Pearson Chi-square Test for Non-response Bias 57
Table 4.4: Independent Samples Test for Non-response Bias 57
Table 5.1: Response rate distributed over 63 Organizations 67
Table 5.2: Response Rate by SMA Location 68
Table 5.3: Years Organization had been established 69
Table 5.4: Description of Types of Organizations 70
Table 5.5: Organization’s Activities 71
Table 5.6: Distribution of Organization’s Mission 72
Table 5.7: Distribution of Ranked Organizational Activities 74
Table 5.8: Distribution of Annual Attendance 75
Table 5.9: Total Annual Subscribers 76
Table 5.10: Full-Time paid Organization Staff 77

vii
Table 5.11: Part-Time paid Organization Staff 77
Table 5.12: Volunteer Staff in Organization 78
Table 5.13: Importance of Metropolitan Area Location Factors 81
Table 5.14: Factor Analysis: Component 1 (Localization Economies) 83
Table 5.15: Factor Analysis: Component 2 (Urbanization Economies) 85
Table 5.16: Factor Analysis: Component 3 (Institutional Support) 86
Table 5.17: Factor Analysis: Component 4 (Local Talent) 88
Table 5.18: Factor Analysis: Component 5 (Market Conditions) 89
Table 5.19: Location of Organization Performance Facility 93
Table 5.20: Types of Facilities 94
Table 5.21: Accessibility to Organization 95
Table 5.22: Cronbach’s Alpha for Locational Factor Analysis Components 101

Table 5.23: Location Variables and Revenue Concentration Index 102
Table 5.24: Organization Single Performance Ticket Price 103
Table 5.25: Organization Season Performance Ticket Price 104
Table 5.26: Organization Purchasing Options Offered 104
Table 5.27: Factor Analysis on Product 106
Table 5.28: Product Variables and Revenue Concentration Index 107
Table 5.29: Most Effective Adverting Media for Organizations 107

viii
Table 5.30: Source of Reputation 109
Table 5.31: Advertising & Promotion and Revenue Concentration Index 110
Table 5.32: Summary of Variables 111
Table 5.33: Regression Results 113
Table 5.34: Regression Results of Reduced Model 115
Table 5.35: Share of Inter-organizational Relationships Among PAOs 117
Table 5.36: Organization Patrons that are Residents of SMA 121
Table 5.37: Organization Performers that are Residents of SMA 122
Table 5.38: Organization Technical Staff that are Residents of SMA 123
Table 5.39: Organization Administrative Staff that are Residents of SMA 124
Table 5.40: Percentage of Organizations Hiring/Receiving Producer Services 125
Table 5.41: Total Local Donated Services versus Total Local Paid Services 127
Table 5.42: Total Local Paid Services versus Non-local Paid Services 127

ix
List of Figures

Figure 5.1 Location Variable Factor Analysis Scree Plot 83

x
ABSTRACT

This dissertation seeks to determine the relative importance of location in the
marketing strategy of non-profit performing arts organizations (PAOs). Recent marketing
and arts organizational research has shown that PAOs' marketing practices are shifting
from product development to audience development. While product development and
promotional strategies are important marketing variables, location selection has become
an important strategic factor for the arts industry. Yet very little research has been done
on the locational dimensions of this industry. Based on a mail survey of PAOs in six
second tier U.S. statistical metropolitan areas (SMAs), this paper will investigate: (i) the
attributes that explain the location of PAOs in the SMAs (that is, Buffalo, Pittsburgh,
Cleveland, Columbus, Cincinnati, and Milwaukee) and (ii) the extent to which location
influences the success of PAOs. All six SMAs have a population range of 1 million to 2.5
million. While they are located in a region that has witnessed a decline in manufacturing
activities, the cities however are relatively rich in cultural and arts activities.

To test the relative strength of location attributes influencing the success of the
PAO, a revenue concentration index was created and used as the dependent variable in a
multiple regression analysis. This model reveals that location does indeed play a
significant role in the success of PAOs particularly with regards to affordability and
abundance of arts industry specific labor.

In addition to benefiting from arts industry specific labor, PAOs have access to
and support surrounding producer services such as accounting, law, advertising, and web
page creation, indicating the PAOs gain from urbanization economies. Collaboration
with peer PAOs and other institutions such as universities, foundations, and corporations
appear to be essential to building audience support and acquiring additional sources of
revenue suggesting that localization economies and local institutional support also play a
role in the success of the organization.

1

Chapter 1
Introduction and Purpose
“Creativity means business…Creativity has become the ultimate economic
resource, adding a new dimension to the competitive potential of cities around the
world.” (Meric Gertler, Canadian Architect, 7/25/2006) “Economic development and
creativity are not separate entities…” (Canadian Architect, 7/25/2006)

1.1 Introduction and Motivation of Research
Both economic geography and marketing disciplines are concerned with the
locational dimensions of economic activities, including those associated with firms and
industries. Industrial geography, for example is traditionally concerned with firm
location embeddedness and inter-organizational relationships (Yeung, 1998). Similarly,
the marketing discipline has focused on optimal location primarily as a function of
product distribution to the end consumer. This may be seen for example in the real estate
industry where location plays a critical role in the positioning of retail outlets to best
serve target markets (Armstrong and Kotler, 2005).
Recently, the arts industry has become an interest in both disciplines. From the
economic geography perspective, it is being examined for its potential contribution to
regional economic development (Beyers, 2002; Scott, 1997; Scott 1999; and Markusen

2
and King, 2003). William Beyers (2002) proposes that more economic geographic
research is needed as cultural industries become increasingly important to local
economies. He suggests a greater attention to cultural industry income leakages from
local economies and the injection of “new” money from outside the community. Other
economic geography studies of cultural industries focus on their effect on regional
employment (Scott, 1997), regional knowledge spill-overs forming agglomerations of
creative talents (Scott 1999), and the economic impact of the “artistic dividend”
(Markusen and King, 2003).
In 2000, the Americans for the Arts (2002) updated its first economic impact

study which was performed in 1994. It is estimated that in 2000 the US nonprofit arts
industry generated $134 billion in economic activity $53.2 billion in spending by arts
organizations and an additional $80.8 billion in event-related spending by arts audiences.
This spending supports 4.9 million full-time jobs and generates $24.4 billion in federal,
state, and local government revenues annually. By comparison, federal, state, and local
governments collectively spend less than $3 billion on support for the arts each year.
The US Conference of Mayors (Americans for the Arts, 2002) urges cities across the
country to invest in nonprofit arts organizations through their local arts agencies as a
catalyst to generate economic impact, stimulate business development, spur urban

3
renewal, attract tourists and area residents to community activities, and to improve the
overall quality of life.
Marketing is also playing an important role in the arts industry as a result of
financial cutbacks from traditional revenue sources such as government agencies,
corporate donors, and foundations. These cut-backs have forced the arts industry to
examine its marketing practices in order to survive. According to Hardy (1981), UK
theaters have been slow to adopt professional marketing practices. In the US in 1987,
while ticket sales to nonprofit arts organizations exceeded ticket sales to sporting events,
the performing arts industry was experiencing declining financial support from
foundations, government agencies and corporate sources (Scheff and Kotler, 1996).
Corporations that continued to contribute did so out of commercial and not philanthropic
reasons. Compounding this shift in corporate motivation to support the arts is the belief
that most patrons of the arts are unable to recall the sponsor of an event (LePla, 2004).
Seventy-five percent of the respondents in a study conducted by LePla (2004) indicated
that their purchasing behavior is not swayed by corporate sponsorship of the arts, with
people in higher income brackets being less likely to be influenced than those in lower
income brackets. This is not good news for sponsors of arts events as the majority of arts
patrons are members of the high income bracket (DiMaggio, Useem and Brown, 1978;
Garbarino and Johnson, 1999; Americans for the Arts, 2002). These events have led to

4
increased studies in the marketing of the arts in the areas of audience development
(Samuels and Tonsic, 1996; and Rentschler, Radbourne, Carr, and Rickard 2002)
including target marketing to increase the diversity of patron demographics both
ethnically and by age (Zoll, 1997; Galvin, 1998; Stooksbury-Guier, 2001; and Dezell,
2002), and relationship marketing and audience retention (Rentschler, Radbourne, Carr,
and Rickard, 2002; and Garbarino and Johnson, 1999).
The Performing Arts Research Coalition conducted research to provide a detailed
picture of the value of the performing arts to individuals and their communities, and to
obtain a greater understanding of the perceived obstacles to greater attendance
(Kopczynski and Hager, 2002). The findings revealed that the arts audience was
comparable in size to audiences for movies and sporting events, and more diverse in
demographic characteristics than initially believed. Such information should be useful to
a variety of stakeholders, including policymakers evaluating the role of government in
supporting the arts; funders who need hard data on which to base their financial support
of the arts; and managers of arts organization attempting to increase and diversify their
audiences.
1.2 Purpose of Dissertation
Academic research on the marketing and organizational dimensions of the arts
reflects the industry’s shift in focus from product development to audience development

5
in their marketing practices. While product development and promotional strategies are
important marketing variables, organization location selection is also an important
strategic factor for the arts industry organizations in terms of access to market demand
conditions and necessary resources. However, little research has been done on the
locational dimensions of arts organizations. The purpose of this dissertation is to
compare the marketing activities of non-profit performance arts organizations (henceforth
abbreviated to PAOs) to understand locational motivations of the industry and to

determine the relative importance of location in the marketing strategy. More
specifically the research seeks to investigate the following themes: (i) the attributes that
explain the location of theaters in second tier metropolitan areas, namely, Buffalo,
Cincinnati, Cleveland, Columbus, Milwaukee, and Pittsburgh, and (ii) the extent to which
location influences the success of the organization. Market demand, along with
congestion effects in traditional arts reputed cities such New York and Los Angeles result
in theater clustering in second tier cities. (Sweeney and Feser, 1998; Markusen and King,
2003) Second tier cities in this study are defined as cities with a population range of 1
million to 2.5 million. Specifically, the study will focus on the above six second tier cities
in the rust belt region of the Northeastern and Midwestern US. This region stretches
from the western end of Southern Wisconsin and St. Louis, Missouri, to the East Coast,
and as far south as the Baltimore, Maryland -Washington D.C. area.
To understand why second tier cities are becoming important hosts of the arts
industry, the employment distribution of various industries is presented in Table 1.1. The
table traces the change in manufacturing and service employment in first and second tier
cities in the Northeastern and Midwestern United States from 1990 to 2000. Table 1.1

6
reports the change in employment of US manufacturing industry from 1990 to 2000
among cities in the Northeast and Northern Midwest of the United States (US). It reveals
negative percentage changes in persons employed in the manufacturing industry in all of
the six selected cities, while Cincinnati, Cleveland, Columbus, Milwaukee, and
Pittsburgh experienced positive percentage changes in total employment. Table 1.2
further reports the change in employment in terms of occupations from 1999 to 2003
based on US Department of Labor statistics. All six selected SMAs experienced positive
percentage changes in the Arts, design, entertainment, sports, and media occupations.
Both Tables 1.1 and 1.2 suggest that the arts industry is becoming more and more
important as a source of employment in the six cities. Markusen and King (2003) suggest
that more research in regional economic development should be focused on occupations
rather than industries, which would result in placing human capital at the center of the

economic development process. To identify cities with a high concentration of arts and
culture, this study utilizes Sperling’s and Sander’s work on Cities ranked and rated:
More than 400 metropolitan areas evaluated in the U.S. and Canada (2004). Sperling
and Sander (2004) divided arts and culture into three areas: Media & libraries,
performing arts, and museums. This study will focus on the performance arts sector of
cultural industries. Sperling and Sander (2004) define performing arts as: i) classical
music which includes traditional symphony and opera companies, ii) ballet/dance
companies, iii) professional theater companies, but not dinner theater or traveling shows,
and iv) university arts programs that include classical music, dance, theater, and
international programs. The rust belt US cities included for investigation in the proposed
research are ranked within the top 30 cities on arts and cultural attributes.

7
Table 1.1 Industrial Employment Statistics among cities in Northeastern and Midwestern United States

SMAs Total employment of persons 16
years and over
Persons 16 and over employed in
Manufacturing Industry
Percentage of labor force
employed in
Manufacturing Industry
Persons 16 and over employed in
Service Industry
Percentage of labor force
employed in
Service Industry
1990 2000 % change 1990 2000 % change 1990 2000 % change 1990 2000 %
change
1990 2000 %

change

New York


8,716,770

9,520,481

9.22%
1,249,091 918,238 -26.49% 14.3 9.6 -32.87% 4,494,772 6,174,605 37.37% 51.6 65.0 25.97%

Chicago

3,896,930

4,287,747

10.03%
775,237 681,863 -12.04% 19.9 15.9 -20.10% 1,722,461 2,442,498 41.80% 44.2 56.9 28.73%

Philadelphia

2,830,741

2,865,306

1.22%
483,768 339,580 -29.81% 17.1 11.9 -30.41% 1,368,653 1,769,144 29.26% 48.3 61.8 27.95%

DC

2,184,661

*3,843,329

75.92%
126,821

*221,038 74.29% 5.8 *5.8 0.00% 1,370,140 *2,708,237 97.66% 62.7 *70.5 12.44%

Detroit

2,124,748

2,538,924

19.49%
517,267 579,553 12.04% 24.3 22.8 -6.17% 903,675 1,321,385 46.22% 42.5 52.1 22.59%

Boston

2,173,765

2,952,632

35.83%
379,206 397,441 4.81% 17.4 13.5 -22.41% 1,091,959 1,829,602 67.55% 50.2 62.0 23.51%

Minneapolis

1,329,371

1,619,473

21.82% 260,067 257,567 -0.96% 19.6 15.9 -18.88% 599,656 920,866 53.57% 45.1 56.8 25.94%

St Louis

1,154,922

1,252,570

8.45%
219,038 178,594 -18.46% 19.0 14.3 -24.74% 506,579 723,640 42.85% 43.9 57.8 31.66%

Baltimore

1,192,182
*

*
147,150 * * 12.3 * * 616,663 * * 51.7 * *

Pittsburgh

972,290
1,074,663
10.53% 141,719 132,180 -6.73% 14.6 12.3 -15.75% 447,748 623,861 39.33% 46.1 58.1 26.03%

Cleveland

1,266,993
1,401,208
10.59%
292,728 272,444 -6.93% 23.1 19.4 -16.02% 535,200 762,768 42.52% 42.2 54.5 29.15%
Cincinnati 828,333 968,170
16.88% 170,085 167,913 -1.28% 20.5 17.3 -15.61% 345,025 525,857 52.41% 41.7 54.4 30.46%
Columbus 690,205 792,093
14.76% 101,539 87,896 -13.44% 14.7 11.1 -24.49% 335,280 476,985 42.26% 48.6 60.2 23.87%
Providence 558,603 569,397
1.93% 136,255 100,960 -25.90% 24.4 17.7 -27.46% 236,377 321,438 35.99% 42.3 56.5 33.57%
Indianapolis 633,277 810,610
28.00% 111,736 127,965 14.52% 17.6 15.8 -10.23% 279,644 440,056 57.36% 44.2 54.2 22.62%
Milwaukee 784,796 832,079
6.02%
195,975 177,910 -9.22% 25.0 21.4 -14.40% 328,268 448,013 36.48% 41.8 53.8 28.71%
Buffalo 542,686 531,984
-1.97% 101,947 83,296 -18.29% 18.8 15.7 -16.49% 248,126 308,457 24.31% 45.7 58.1 27.13%
Hartford 572,120 583,072
1.91% 109,478 83,940 -23.33% 19.1 14.4 -24.61% 286,414 358,581 25.20% 50.1 61.4 22.55%
Rochester

491,589 526,930
7.19% 132,954 111,271 -16.31% 27.0 21.1 -21.85% 206,294 289,673 40.42% 42.0 55.0 30.95%
Source: US Census 1990 – 2000
Note: Not all industries are reported here; *2000 Washington D.C. SMA includes data from Baltimore as a result of 1997 census re-definitions.


8

Table 1.2 Occupational Employment Statistics among cities in Northeastern and North Midwestern United States
MSA’s Service related occupations Goods related Occupations
Health care & social services All Occupations Business &
finance
Practitioners &
technical
Healthcare
support
Community &
social services
Sales & related Arts, Design,
entertainment,
sports, and
media
occupations
Production Transportation
& material
moving
1999 2003 1999 2003 1999 2003 1999 2003 1999 2003 1999 2003 1999 2003 1999 2003 1999 2003
New York

3,485,035

3,976,070 191,940

194,230 203,030

207,880 147,190

137,410 54,620

77,420 364,580

395,170 120,620

112,790 239,460

151,110 198,290

193,300
Chicago

3,707,600

3,973,440 209,330

191,740 186,170

183,140 63,310

78,170 49,690

41,470 395,320

405,710 46,900

50,270 439,980

334,710 322,920

330,470
Philadelphia
2,229,945

2,318,870
94,770 103,410 135,650 138,040 58,990 61,980 31,070 42,440 244,910 254,190 22,560 23,560 193,040 138,750 155,820 153,110
DC

2,431,875

2,694,130 161,890

185,220 110,780

108,130 38,340

40,880 24,290

26,980 240,140

244,640 45,290

50,690 80,310

70,570 132,360

123,990
Detroit

1,879,275

2,015,850 96,850

105,520 97,240

95,960 53,110

50,590 20,760

16,210 209,810

213,370 25,310

26,160 296,540

225,010 154,200

143,180
Boston

1,885,050

1,920,950 93,430

93,680 115,270

112,510 51,170

46,240 28,060

30,310 199,800

189,820 27,370

29,200 127,750

95,050 98,020

90,060
Minneapolis

16,111,220

1,686,210 90,060

104,750 81,360

76,840 41,430

35,960 23,970

25,190 186,730

193,760 27,920

23,830 173,710

135,230 124,970

99,160

St Louis

1,237,635

1,274,720 42,720

52,780 65,890

67,920 32,020

34,500 14,350

12,030 138,870

134,020 14,440

15,790 118,130

98,970 102,470

89,530
Baltimore

1,047,310

1,223,090
52,200

54,920
73,250

64,290
25,530

27,610
21,500

24,360
118,350

120,840
14,100

14,160
70,370

55,460
80,340

75,670
Pittsburgh
992,070 1,070,840 34,080 36,590 60,530 65,740 33,440 32,020 14,110 17,080 112,740 110,580 9,390 10,390 84,330 75,130 99,170 72,900
Cleveland
1,047,980

1,083,810 41,920

52,560 64,440

60,890 28,270

32,490 11,290

14,100 123,910

116,940 10,510

12,550 150,440

109,880 84,650

77,790
Cincinnati
829,420

845,240 26,390

38,330 46,910

43,490 24,690

22,190 8,990

8,630 89,230

91,610 8,880

9,210 88,810

69,030 73,950

68,540
Columbus
768,410

845,420 30,010

43,220 41,160

43,420 19,400

20,190 9,710

9,140 77,360

84,050 8,150

11,490 71,410

58,060 73,830

71,960
Providence

466,800

520,890 16,560

18,410 31,290

32,060 14,450

17,620 10,310

11,050 53,700

52,670 4,670

5,860 62,230

55,080 36,450

30,760
Indianapolis

818,020

854,710
39,270

37,320
48,080

45,070
14,870

17,910
8,210

7,060

100,500

89,480
11,420

9,920
100,800

73,900
75,780

74,400
Milwaukee

878,085

817,420 31,840

32,600 42,650

41,560 23,760

23,970 8,230

11,310 85,510

81,780 10,220

12,510 139,860

97,970 64,970

57,460
Buffalo
526,370 527,240 16,700 18,090 33,270 28,360 15,950 15,680 10,410 7,860 55,910 54,370 4,640 4,750 58,270 49,620 35,130 32,170
Hartford
567770

597,390 32,300

37,340 25,900

31,720 16,600

17,530 9,090

11,520 60,800

55,310 7,070

7,610 58,170

43,400 37,870

32,420
Rochester
502,570

508,290 18,860

15,760 30,280

26,000 15,890

15,840 8,950

8,680 47,680

53,890 4,940

5,910 68,000

51,070 36,750

26,980
Source: US Department of Labor—Bureau of Labor Statistics 1999 2003 Note: Not all occupations are reported here

9
Incidence of failure in the sense of mortality rates of nonprofit arts organizations
was found to be higher than other forms of nonprofit organizations in a study by Bowen,
Nygren, Turner, and Duffy (1994). The authors examined the nonprofit organization
failure rates from 1984 to 1992 and found that on the average nonprofit organizations
failed at a rate of 2.2 percent annually. In contrast, they observed that arts organizations
had a substantially higher annual failure rate with the performing arts of ballet at 25.1
percent, opera at 22.7 percent, dance at 22.3 percent, and theater at 20.3 percent. The
only type of nonprofit organization with a higher failure rate than those mentioned above
is job training organizations with a failure rate of 26.5 percent (Bowen, Nygren, Turner,
and Duffy, 1994). Given this observed high failure rate of ballet, opera, dance and
theater, this dissertation will attempt to determine the variables contributing to the
success of independently operated nonprofit ballet, opera, dance, and theater companies.

1.3 Overview of Dissertation
The research will be undertaken using multiple methods that employ a
combination of mail and telephone interview surveys of non-profit performance arts
organizations in six cities located in the traditional manufacturing belt of the US. Chapter
2 provides the theoretical basis for the research by reviewing two strands of the regional
development literature. The first section of Chapter 2 reviews classical location theory
which focuses on a firm’s location decision based on access to transportation. In addition
this section examines staple and export based theories and their implications for regional

10
economic growth. The second section of Chapter 2 provides the theoretical framework
from the perspectives of firm-centered and human capital-centered theories and their
movement from the manufacturing sector and application to the service sector.
Chapter 3 provides an overview of the marketing process, and the marketing and
locational motivations of non-profit organizations. The first and second sections of
Chapter three focus on the generalities of marketing and nonprofit marketing. The third
section of presents the background of nonprofit performance arts organizations (PAOs).
The fourth and final section of Chapter 3 reviews the literature on the locational
preferences of nonprofit organizations.
Chapters 4 and 5 present the methodology as well as the results of the mail and
telephone interview surveys. Chapter 4 describes the sample selection and the data
collection methods. Chapter 5 describes the characteristics of the sample data, analyses
the quantitative data obtained from the mail survey and the qualitative data obtained from
the interview survey, and provides a profile of the characteristics and perceptions of the
performance arts organizations that are located in the six cities selected for this study.
Chapter 6 summarizes the results of the research questions, discusses policy
implications of the study’s results, as well as the shortcomings of the research, and
suggests possible directions for future research.

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Chapter 2
Theoretical Background

In this chapter, both classical and more recent strands of regional development
theories will be reviewed. Classical theories on regional development are far more
relevant to industrial economies where agricultural and manufacturing activities
dominate. In contemporary regional economies and cities where producer services form
an important share of economic output (Sassen, 2001), it is the creative industries that
have gained considerable attention among geographers recently. The nature of creative
industries suggests that agglomeration economies and their emphasis on creative human
capital linkages are more relevant to the research themes in this dissertation.

2.1 Traditional Regional Development Theories
Regional development theories harkens back to the 1930s when the optimum
location of manufacturing industries became a popular theme.
From the perspective of classical location theory, access to transportation is one
of the key variables determining a firm’s locational choice (Sassen, 2001). The early
location theories of Weber (1909) and Losch (1940) focused on the movement of goods
and the availability of labor and markets. Alfred Weber was a German economist and
pioneer in industrial location theory. Weber (1909) formulated a theory of industrial

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location in which an industry is located where the transportation costs of raw materials
and final product is a minimum. The point for locating an industry that minimizes costs
of transportation and labor requires analysis of three factors: i) the weight of the raw
materials or final products, ii) availability and cost of unskilled or skilled labor, and iii)
the concentration of firms allowing individual firms to enjoy external and internal
economies of scale.

In addition to the Weberian model, other more traditional theories focus on the
role of resources and exports in local development, that is, export-led growth theories,
such as the staple theory and export base theory. Thomas (1964) defines economic
growth as “a rise in output per head of population”. Economic growth is a function of
availability, cost, and allocation of natural resources and human behavior and occurs
when increases in efficiency of the use of inputs result in an increase in supply of outputs.
Thomas (1964) suggests that the human behavior factors that inhibit or promote
economic growth may include society’s system of values, religion, institutions, changes
in the society’s demographic characteristics, and the society’s ability to create and adapt
to technological change. Economic growth may occur as a result in increased internal
market demand for a region’s output if it results in an increase in real income, and an
increase in external market demand for regional output.

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Staple theory assumes that staple export production is the leading sector of a
regional economy and therefore is the catalyst of economic growth (Watkins, 1963;
Altman, 2003; North, 1955; and Hayter and Barnes, 1990). North (1955) was one of the
first researchers to apply location theory in his analysis of the historical economic growth
of American regions. North (1955) suggests that regional growth occurs in five stages.
Stage one is characterized by a self-sufficient subsistence economy. In stage two, some
local specialization and trade will take place as improvements in transportation occur.
Stage three is marked by a progression of agricultural crops while early industrialization
underscores stage four. The final stage five will see a specialization and exportation of
staples from the region to less developed regions. North’s (1955) Location Theory and
Regional Economic Growth is concerned with the fourth stage, early industrialization, in
which staple products are produced and exported. Staple products are predominantly raw
materials (Altman, 2003) and may be defined as the leading export product(s) in a given
sector (Watkins, 1963). The basic objective of the staple theory of economic growth is
to produce goods by using a region’s natural resources, resulting in an increase of income
to the region. As staple production continues, staple producers become more efficient in

producing the staple; this process leads to more investment and hence the subsequent
growth of the staple industry (Altman, 2003). Federal and state aid, in the form of
transportation improvements, increases the competitive position of the region (North,

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1955; Hayter and Barnes, 1990). The growth of the staple industry generates linked
industries that are dependent on the staple production, residentiary industries then
develop to meet the consumption needs of the staple producing population, and footloose
industries that develop by chance may become additional staple industries (North, 1955).
North suggests that while the staple industry may not be the most dominant producer in
terms of employment and output in an area, its existence creates staple-related linkages
that generate a higher level of income than would be produced in its absence.
The export base theory emphasizes the value of export industries in explaining
regional economic growth (Thomas, 1964). Regional economic growth is determined by
the success of the export sector and the characteristics of the export sector. Economic
growth will exist when export activities create an economic base from which other
industries or residentiary economic activities are derived. This diversification of
industrial structure creates new levels of economic activity. Hence, the export sector
growth is the means by which resulting dependent residentiary industries develop and
grow. North (1955) suggests that regional economic growth is a function of the growth
rate of the export sector, and its export sector growth facilitates the growth of the
supporting, non-export residentiary sectors. The arguments for a positive export–
economic growth relationship include: first, an increase in demand for a country’s
products increases the production of such products. Second, as production increases in