Journal of Tourism Research & Hospitality

Joo, et al., J Tourism Res Hospitality 2015, 4:1
http://dx.doi.org/10.4172/2324-8807.1000145
Case Report
Journal of Tourism
Research & Hospitality
A SCITECHNOL JOURNAL
Revitalizing Cities: Amenities,
Economic Development, and the
Attraction of Human Capital
productive and skilled labor. What can cities and regions suffering
from decline as a result of macroeconomic changes do to attract and
retain a highly educated workforce and the individuals that drive
innovation? These are the questions that have been at the forefront of
urban policy debates for decades.
Mijin Joo1* and Mark S. Rosentraub2
Even regions that were former manufacturing centers must attract
far more educated workers to meet the demands of the highly
mechanized factories that are less dependent on unskilled labor and
more invested in robots and computers. In the past these areas relied
on a series of comparative advantages often related to transportation
efficiencies and a labor force appropriate for assembly line work.
Those transportation advantages have dissipated. Robots and
computerized systems have led to new levels of productivity and the
need for workers with skills different from that in-demand for decades
ago. That change in skill types and increasing levels of efficiency and
the reliance on automation has reduced the overall demand for labor.
These changes and the rise to prominence of other industries with
demands for highly educated and creative workers have focused every
region on enhancements to the “quality of life.” Quality of life
amenities are code words for the lifestyles desired by the most
educated workers. Exactly what constitutes a high quality of life
remains highly subjective.
1Chung-Ang
2University
University, Dongjak-Gu, Seoul, Korea
of Michigan, Ann Arbor, Michigan, Korea
Corresponding author: Mijin Joo Ph.D., Chung-Ang University, Dongjak-Gu,
Seoul, Republic of Korea, E-mail: abraxa2009@gmail.com
Rec date: Aug 06, 2014 Acc date: Dec 01, 2014 Pub date: Jan 10, 2015
Abstract
The focus on knowledge, innovation, and a highly educated
workforce as the agents of economic transformation has reemphasized Marshall’s “ideas in the air” as the keys to
successful long-term growth strategies. He was among the first
to suggest that wealth occurs where creative, skilled labor
concentrates. It is these individuals who generate the ideas
that create new products, processes, innovations, and, most
importantly, jobs. Recent empirical work has validated the
importance of a well-educated labor for development. As a
result, areas that seek to reverse periods of economic
contraction are driven to policies and practices that help attract
and retain highly productive and skilled labor.
Some regions have capitalized on warm weather, mountains,
or Bohemian life-style neighborhoods to attract well-educated
labor. Other regions lacking those assets have turned to
investments in sports facilities or other entertainment-oriented
amenities to compete with areas with milder winters. Do those
investments often funded by higher taxes have the potential to
change labor migration patterns? That is the focus of the
research reported to help community leaders design new public
policies for redevelopment strategies.
Two analyses are provided. The first focuses on the
relationship between different sets of amenities and the
movement of highly educated workers. The second looks for
differences in migration patterns and the presence of different
amenities related to the age of educated workers. The findings
suggest some entertainment amenities are indeed useful for
attracting workers, but additional research is needed.
Introduction
The focus on knowledge, innovation, and a highly educated
workforce as the agents of economic transformation has reemphasized Marshall’s “ideas in the air” as the keys to successful longterm growth strategies [1]. Marshall’s ideas suggest that wealth occurs
where creative, skilled labor is concentrated. It is these individuals who
generate the ideas that create new products, processes, innovations,
and, most importantly, jobs. Recent empirical work has validated the
importance of a well-educated labor for development and wealth [2,
3]. As a result, areas that seek to reverse periods of economic
contraction are driven to policies and practices that lead to the
production or creation of environments that attract and retain highly
Some regions, for example, have capitalized on environmental
amenities (warm weather and year-round access to beaches,
mountains, or Bohemian life-style neighborhoods). Other regions
lacking those assets have turned to investments in large-scale changes
to their built-environment to offer spectator-based amenities to attract
and retain highly educated and skilled workers. Do those investments
often funded by higher taxes have the potential to change labor
migration patterns? That is the focus of the research reported here in
an effort to increase the information available to community leaders
who must frame and design new public policies to guide and support
redevelopment strategies and efforts.
The rising prominence of the quality of life in economic
development
Business locations are still dependent on production costs (labor,
capital, transportation, energy, communication, etc.). Increasingly,
however, efficiencies with regard to certain inputs have increased the
geographic options that exist with regard to the areas in which
companies can locate. The increasing dependency of new businesses
and those focused on new levels of productivity, and those
concentrated in the fastest growing segments of the economy, are
dependent on highly skilled/educated labor. This has elevated the
financial returns to firms from locating in areas that offer the most
coveted workers the quality of life they desire or demand. As a result,
businesses in the post-industrial age can maximize their profit
potential by locating in areas that offer access to a large pool of skilled
and well-educated workers [4].
Areas or regions that rose to economic prominence as a result of the
access they provided to transportation networks or raw materials and
other factor inputs must now compete with the available mix of
amenities that appeal to the labor needed by the growing
predominance of finance, management, media, information
technology, and advanced engineering firms. A failure to build an
environment capable of attracting and retaining educated and skilled
workers will lead to economic stagnation and decline [5]. With
All articles published in Journal of Tourism Research & Hospitality are the property of SciTechnol and is protected by
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Citation:
Mijin J, Mark SR (2015) Revitalizing Cities: Amenities, Economic Development, and the Attraction of Human Capital. J Tourism Res Hospitality 4:1.
doi:http://dx.doi.org/10.4172/2324-8807.1000145
numerous North American and Western European formermanufacturing centers mired in various stages of economic
contraction community leaders in those areas are focused on ways to
attract and retain human capital. Ironically, in many of these areas
there is no shortage of institutions producing well-educated workers.
Several highly ranked universities are located in some of America’s
slowest growing states (e.g., The University of Michigan, Indiana
University, the Ohio State University, the University of Illinois, the
University of Chicago, etc.). The problem is not producing a large pool
of talent; the challenge is to attract and retain this educated workforce
after they finish their education.
The quality of life and economic development
Straubhaar [6], Florida [7] and Clark [8] point out that in the
modern knowledge-based economy what affects the residential choices
of skilled and educated workers has changed. Entertainment and other
activities associated with enjoyment of arts, culture, and recreation
influence the locations valued by well-educated workers. Clark [8]
explains that human capital aggregations and amenities jointly create a
location that is a desirable place to live and work. The extraordinary
growth in America’s southern and western states also attests to the
value workers place on areas with mild winters. What quality of life
amenities can areas with less temperate climates offer to compete for
skilled labor? Can improvements in the built-environment or what is
often described as entertainment amenities offset the advantage of
mild winters?
This study was designed to offer some insight into the linkage
between the presence of certain amenities and the concentration of a
well-educated workforce. Many communities struggling to attract
well-educated workers have made large investments in sports facilities,
entertainment complexes, cultural centers, and other entertainmentrelated amenities despite the absence of data suggesting the value of
these assets in changing the distribution of human capital. The
research reported here is designed to help officials understand if
investments in entertainment or other amenities have any impact on
the migration of educated workers. Two analyses are provided in an
effort to offer insight into the relationship between amenities and the
distribution of well-educated human capital. The first focuses on the
relationship between entertainment amenities and the movement of
highly educated workers. The second analysis looks for differences in
location choices and entertainment amenities related to the age of
educated workers. These analyses are preceded by a brief review of
recent research into the factors that attract skilled labor to particular
areas and the concluding section looks at the implications of the
findings for public policies and investments while also offering
suggestions for future work.
What Attracts Skilled Labor to an Area? From the Pull
of Jobs to the Rising Importance of the Quality of Life
Numerous early studies of labor migration identified the
importance of employment opportunities and higher wage
expectations as the factors that explained the attraction and retention
of workers to specific areas [9]. The importance or primacy of
employment opportunities and wages were sometimes described as the
“pull factors” that predicted labor migration patterns. Jobs and higher
wages were usually found in areas where transportation assets reduced
the costs of acquiring raw materials and transporting them to
production facilities and finished products to markets. Workers
followed businesses to those areas.
Volume 4 • Issue 1 • 145
As noted, once similar transportation and other factor input costs
could be found in multiple areas firms had more flexibility in the
choices that could be made regarding locations. That flexibility has
contributed to a focus on the quality of life for labor as a factor of
production that can ensure a firm would always have access to the
talent needed for profitability. Increasingly the quality of life that a
region offers to its residents has become a primary factor in selecting a
location for a business. Florida [7] and Clark [8] have suggested that in
the modern knowledge-based economy highly skilled workers are as
focused on preferences for entertainment or other lifestyle amenities
as they are on wages. Business leaders understand this changing
environment and choose to locate in areas that have a reputation for
offering skilled labor a desirable quality of life. Depending on the
researcher (or pundit) the relative importance of pecuniary gains or
amenities could be seen to be at parity or one set of benefits could be
more valuable than another. Regardless of the relative weight workers
played on amenities or wages it is clear that the quality of life available
to highly regarded employees is now part of the portfolio of factor
inputs that predict the locations preferred by employers. The
importance of quality of life amenities has convinced community
leaders in areas with longer winters, colder average temperatures, and
a lack of access to mountain areas or other highly regarded physical
amenities to invest in entertainment amenities. The goal of these
public investments has been to create a built environment that
achieves a level of competitive balance relative with the quality of life
available in other areas.
The role of amenities could assume in attracting talent was initially
discussed by [10,11] decades ago. They also found that a more
temperate climate helped to create a pool of talented workers and that
could mean that communities in more severe climates might be
encouraged to consider enhancements to their built-environments.
Other researchers also offered early evidence of the role of amenities in
the choice of locations preferred by educated workers [12] Graves, et.
al. There was also growing evidence that those areas with warmer
climates seemed to prosper for than other regions. Areas in colder
climates became “rust belts” of decline and this ushered in a frenzy of
activity to enhance the supply of built-environment amenities to offset
a perceived lower quality of life.
Numerous cities, for example, built sports facilities for professional
sports teams as well as centers for the performing arts to highlight a
commitment to the quality of life [13]. The focus on the quality of life
as a tool for economic development raises several important questions.
For example, what are the components of the quality of life that firms
and workers value in their choice of a location in which to live and
work? Which particular amenity is the most valued, and how much
more valuable is any amenity relative to another in terms of the
attraction of more highly-educated workers? In which amenity should
a government invest relative to magnitude of the shift in migration
patterns that would be engendered? While these research questions
were being discussed others challenged the view that the quality of life
was a new magnet for human capital, Herzog, Schlottmann, and
Johnson [14] concluded earnings were still the principal factor
directing the migration decisions of talented human capital. Florida
[7] and Clark [8], however, continued to stress the importance of
amenities and their research illustrated that the distribution of
educated and skilled workers was related to what it takes to makes an
area a desirable place to live.
Figure 1 depicts the different perspectives researchers have debated
regarding the relationship between the factors that effect the migration
• Page 2 of 7 •
Citation:
Mijin J, Mark SR (2015) Revitalizing Cities: Amenities, Economic Development, and the Attraction of Human Capital. J Tourism Res Hospitality 4:1.
doi:http://dx.doi.org/10.4172/2324-8807.1000145
of labor. In the traditional view underscored by those who deemphasize the role of amenities, classical factors of production and not
the quality of life predict local choices and the presence of jobs in a
region’s economy. The concentration of jobs is also related to higher
wage packages. A different approach, labeled human capital theory
elevates amenities but suggests the simple presence of firms and the
salaries offered to employees are more important than amenities.
Amenity theory elevates the quality of life factors to a superior
position relative to pecuniary elements changing the areas where firms
choose to locate (Figure 1).
to the building of amenities be given to public officials. Community
leaders need information that describes the relative value of any factor
or amenity. Simply put what amenity or set of amenities should local
governments foster in an effort to attract and retain an educated work
force? Or, is it best to simply induce the firms likely to offer the highest
wages to locate in their communities?
In this study, amenities that create entertainment options for
residents and visitors were analyzed to understand their importance
for the attraction of human capital. These amenities can clearly
contribute to the quality of life by producing numerous and varied
entertainment options [16]. What constitutes entertainment, for this
analysis, was separated into those large facilities built by numerous
communities for professional sports teams and centers for the
performing arts. What was also included were measures of
entertainment that are more neighborhood-based or far smaller in
scale to assess some of the insights made by Clark [8] and others who
askew the focus on large-scale (sometimes called “big ticket” amenities
because of their cost) and instead recommend the building of
Bohemian-style neighborhoods (and thus more in line with theories
advanced by Jane Jacobs [15]).
Conceptual Model
Figure 1: The relationships between firms, human capital, and
amenities
The amenities studied here were those classified as part of the builtenvironment designed to offer entertainment options to residents.
They included neighborhood-scale attractions and larger regional
assets (sports facilities, museums, etc.). The larger-scale amenities were
classified into three areas or types: (1) sports-related, (2) cultural, and
(3) amusements (including casinos).
Those proponents of the overarching (or leading) value of amenities
should actually categorize the relationship as hypothetical since the
level of empirical research already performed is too small to sustain
the paramount role of quality of life factors in labor migration.
Reflecting that observation, the research reported here is designed to
add to the understanding of the value of amenities in the migration of
highly educated labor. The work is undertaken in an effort to provide
additional empirical tests of the ideas suggested by several and
underscored by Florida and Clark’s work.
There is evidence that businesses are interested in having
convenient access to large pools of educated workers. What constitutes
an amenity that appeals to this to this labor pool, however, is far less
certain or precise. For example, built-environment amenities can
mean sports facilities for major league teams, or it can also mean high
quality schools, subjective evaluations of public safety, or
neighborhoods that offer easy access to music, restaurants, or pubs.
Precision in definitions of each of the components or elements that
contribute to the quality of life is necessary. In addition, attention
must be directed to the quantification of amenities. How many
amenities are needed to attract more highly educated workers?
Without precision of this nature the quality of life can be seen to mean
anything that improves an environment or makes people happy. If the
quality of life is everything then it runs the risk of being nothing that
can be quantified and translated into specific policy targets. As a result
what needs to be a part of any study is the inclusion of numerous
different sets of amenities to see which ones seem to be associated with
the migration of labor while also controlling for numerous other
factors. Only when that is done can policy recommendations relative
Volume 4 • Issue 1 • 145
Figure 2: The Conceptual Model
Human capital was measured by years of education and migration
decisions were analyzed for entry-level or younger workers, for
middle-aged workers, and for older workers. These different segments
were considered since it is possible entry-level workers focused on
their first job may place less emphasis on entertainment options.
Slightly older workers might be more influenced by amenities related
• Page 3 of 7 •
Citation:
Mijin J, Mark SR (2015) Revitalizing Cities: Amenities, Economic Development, and the Attraction of Human Capital. J Tourism Res Hospitality 4:1.
doi:http://dx.doi.org/10.4172/2324-8807.1000145
to their emerging families (education), and older workers with less
family-formation responsibilities might be more focused on
entertainment options [3,17,18]. Migration was defined as a move
from one place to another place for a period of at least one year. The
conceptual model that guided the research to understand the influence
of built tourist amenities is described in Figure 2.
Variables and Data
Dependent variable
Human capital was the dependent variable measured by educational
attainment. It is recognized that educational attainment is but one
measure of human capital and does not capture training and
experience. Florida R [19] too has argued that education is not the best
measure of human capital and suggests a focus on what people do as
an index of talent. Educational attainment was used in this analysis as
it less controversial, far easier to measure, is readily available from
secondary data sets, and is commonly used as a derived shadow
measure of skills or a better educated workforce. A review of
Index
numerous studies of human capital found that 11 relied on
educational attainments as the best available proxy (Table 1) for skill
level.
Independent variables
Amenities were defined by with three groups or categories of
activities: (1) sports, (2) culture (museums) and (3) amusement. These
amenities were classified using the numbering system developed by
the United States Department of Commerce (North American
Industry Classification System or NACIS). Sports-related amenities
were defined by spectator sports (NAICS codes 7112 and 7113).
Museums, historical sites, and performing arts companies were a
second type of built amenities and were defined by NAICS codes 7121
and 7111. The third type of amenities included cinemas, big box retail
stores, themed restaurants, record and video superstores, simulation
theatres, virtual reality arcades, gaming establishments, and other
amusement (NAICS codes 7131, 7132, and 7139). Care was taken to
divide by total establishments to reduce problems with
multicollinearity and heteroskedasticity.
Occupation
High
Factor
Technology
Education
Professional
Scientists
Engineers
High
School
Or above
25
or
above
Male
White
10
3
1
1
X
X
1986
X
Gottlib
1995
X
Arora,
Florida,
Gates and Kamlet
2000
X
Kordrzychi
2001
X
Florida
2002
Florida
2002
X
Clark
2003
X
Glaeser and Saiz
2004
X
Hansen, Ban and
Huggins
2003
X
Heuer
2010
X
Shapiro
2006
Gottlieb
Joseph
and
Artnz
Mellender
Florida
2006
2007
X
X
X
2006
and
1
College or
above
Herzog,
Scholottmann,
Johnson
X
2
Race
4
X
2
Sex
Total number of Studies
X
1
Age
X
X
X
X
X
X
X
X
Table 1: Measuring human capital: a survey from earlier studies
Volume 4 • Issue 1 • 145
• Page 4 of 7 •
Citation:
Mijin J, Mark SR (2015) Revitalizing Cities: Amenities, Economic Development, and the Attraction of Human Capital. J Tourism Res Hospitality 4:1.
doi:http://dx.doi.org/10.4172/2324-8807.1000145
Control variables
The control variables used were divided into four categories: (1)
weather-related factors (2) local public services, and (3) regional
economic condition. Average daily temperatures in January and mean
precipitation levels measured weather. There are a number of variables
to measure local public services. Based on a review of several studies
[20-22] crime, education and house value variables were selected as
measures of the value of local public services. The level of crime was
Variable
measured by local violent crime rates (a measure of the performance of
the police and other civic institutions to advance civil behavior). The
ratio of students per teacher in public schools was a measure of the
quality of schools (another important amenity). Median value of
owner-occupied-housing units was used to measure the house values.
Employment levels and median income controlled regional economic
conditions. A “regions variable” controlled for the faster growth levels
in the southern and western parts of the United States.
Category
Detail
Date Source
Educated Migrants Rate
The Number of Migrants over college degree/
Total Population
IPUMS (http://usa.ipums.org/)
Young Migrants Rate
The Number of Migrants between age 25 and
45/Total Population
Middle Migrants Rate
The Number of Migrants between age 45 and
55/Total Population
Older Migrants Rate
The Number of Migrants between over age 55/
Total Population
Income
Median household income
American Community survey 2005,
2008
Log (Employment)
Total employment
County Business Patterns, 2005,
2008
House Value
Median value of owner-occupied-housing units
American
2005,2008
Crime
Violent crime
Crime in the United States, FBI,
2005, 2008
Pupil ratio
Teacher per pupil
IES (National Center for Educational
Statics) 2005, 2008
Annual precipitation
Annual precipitation (inches)
Average January temperature
Average daily temperature (degrees Fahrenheit)
Dependent Variable
Age
Economic Factor
Social Factor
Weather
Independent Variable
County and
2000,2008
community
City
Data
survey
Book
(Amusement Parks and Arcades (7131)/Total
Establishments
Amusement Rate
(Gambling Industries
Establishments
(7132)
)/
Total
(Other Amusement and Recreation Industries
(7139) )/Total Establishments
(Performing Arts Companies (7111) )/Total
Establishments
Amenities
County Business Patterns 2005, 2008
Cultural Rate
(Museums, Historical Sites, and Similar
Institutions (7121) )/ Total Establishments
(Spectator
Sports
Establishments
(7112)
)/
Total
Sports Rate
(Promoters of Performing Arts, Sports, and
Similar Events (7113) )/Total Establishments
Table 2: Variables and sources
Data
Panel data from 2005 and 2008 were used. Income and employment
data came from American Community Survey and County Business
Patterns produced by the US Bureau of the Census. The enumeration
of students per public school teachers was from the National Center
Volume 4 • Issue 1 • 145
for Education Statics (NCES) and local crime rates came from the
Federal Bureau of Investigation’s national crime database. Housing
values were from the US Bureau of the Census’ American Community
Survey. The built amenities data were obtained from County Business
Patterns. Small amenities included restaurants, bookshops, and food
• Page 5 of 7 •
Citation:
Mijin J, Mark SR (2015) Revitalizing Cities: Amenities, Economic Development, and the Attraction of Human Capital. J Tourism Res Hospitality 4:1.
doi:http://dx.doi.org/10.4172/2324-8807.1000145
service businesses while big amenities were placed into one of three
broad categories: amusements, art, or sports.
Migration information was obtained from the Integrated Public Use
Micro Data Series (IPUMS) maintained by the Minnesota Population
Center at the University of Minnesota. The American Community
Survey samples in 2005 and 2008 from IPUMS were selected to
compare the two different years. IPUMS data do not provide any
detailed migration category; immigration and non-movement was
analyzed based on metropolitan area of residence data from a previous
year provided by respondents.
The focus on 2005 and 2008 permitted a look at recent changes.
Assessments of other years and time periods were considered. A focus
on changes between 1980, 1990, and 2000 could not be done; the
required data could not be properly aligned for those years making it
impossible to properly assess changes. Focusing only on 2005 and 2008
raises the possibility that an insufficient time period was used to
identify changes. This limitation will be addressed but suffice to note
at this point that the data used still included a large number of people
who moved from one location or area to another. Further, the time
period selected is a number of years after numerous cities had made
substantial investments in sport facilities and cultural centers. If
migration was influenced by these “big ticket” investments it should be
evident. All of the data were realigned to conform to the definitions of
MSAs specified on the IPUMS web site using the 1990 definitions or
specifications. Economic, social and natural/built amenities data
between 2005 and 2008 were collected at the county level and were
aligned to the migration data from IPUMS. When conflicts emerged
counties were excluded from the analysis.
Research model
A research model using panel analysis was constructed to measure
the relationship between the movement of educated workers and
amenities. First, several basic appropriate tests for autocorrelation,
multi-correlation, and heteroskedasticity issues were performed. The
Durbin–Watson statistic confirmed that there is no serious
autocorrelation problem. To detect multi-correlation, a variance
inflation factor (VIF) that measures how much multicollinearity has
increased was used. After the test, variables with multi-collinearity
issues such as population were removed from the model. Because
employment was correlated with the amenity variables the measure of
employment was transformed by using its log to resolve the multicorrelation issue. Residual plots and Levene‘s test determined that
there was a heteroscedastic issue. After several transformation tests,
the dependent variable was transformed (natural log) to eliminate any
heteroscedasticity issues.
Second, to construct the appropriate model for panel data, some
statistical tests were needed. Panel data refers to any database of
individuals for whom there are repeated observations across a
sequence of time periods [23]. Park HM [24] explained that a fixed
effect model assumes differences in intercepts across groups or time
periods, whereas a random effect model explores differences in error
variances. He explained that a one-way model should include one
dummy variable such as a cross-sectional variable (e.g., firm, city, and
county) or time-series variable (e.g., month and year) while a two way
model may have two sets of dummy variables (e.g., firm and year). By
using the SAS statistical program, the group and time effect in the data
were tested and it turns out that there was no serious time effect but
the group effect existed. The Hausman test was also used to identify
whether the fixed or random effects model should be used. After the
Volume 4 • Issue 1 • 145
Hausman test, a one-way fixed effect model was finally chosen to
analyze the relationship between amenities and the movement of
human capital.
There are several one-way fixed group effect models (e.g., the least
squares dummy variable model (LSDV), the within effect model, and
the between effect model). In this study, LSDV model was chosen
because the LSDV model is relatively easy to estimate. This LSDV,
however, becomes problematic when there are many groups or
subjects in the panel data (Park, 2009). To minimize degrees of
freedom the various Metropolitan Statistical Areas (MSAs) were
placed into four geographic zones - South, West, Northeast, and
Midwest.
The model used involved migration rates in MSAs in the United
States and enumerated amenity levels:
Ln (M)=o + β1 C + β2 A +ε ,
Where,
Ln (M)=Log of migrant rate in MSAs;
C=Control variables in MSAs;
A=Built tourist amenities rate variables in MSAs
and ε=error t.
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doi:http://dx.doi.org/10.4172/2324-8807.1000145
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