UNIVERSITY OF CINCINNATI
Date: 13-May-2010
I, Antony Seppi , hereby submit this original work as part of the requirements for the degree of: Master of Community Planning in Community Planning It is entitled: A Case for Avionics in Greene County and Southwestern Ohio
Student Signature: Antony Seppi
This work and its defense approved by: Committee Chair: Christopher Auffrey, PhD Christopher Auffrey, PhD
6/18/2010 251 A Case for Avionics in Greene County and Southwestern Ohio
A thesis submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of
Master of Community Planning
in the School of Planning of the College of Design, Art, Architecture and Planning
May 2010
Antony E. Seppi
B.A. Economics – Wake Forest University
Committee Chair: Christopher Auffrey, PhD Abstract
Industrial clustering as an economic development strategy can have very distinct advantages for a regional economy. Recent economic development efforts in the State of Ohio have focused on identifying key industrial clusters within specific regions of Ohio. With these initiatives,
Dayton, Ohio and its aerospace cluster became the first region to be tapped as part of the “Ohio
Hubs of Innovation and Opportunity” (OHIO) program sponsored by the Ohio Department of
Development in 2009. These “third-wave” economic development efforts are a combination of entrepreneurial ingenuity, buying-selling relationships, and a knowledge-based economy.
The following thesis project is a quantitative economic development study that looks at the prospects of a knowledge-based avionics industrial cluster in Greene County and Southwestern
Ohio. By using proven economic base analysis methods, I will identify the strong versus weak industries of the region. In addition, input-output models will be analyzed to determine what industries are buying and selling to and from each other in this region. From there, I will develop an avionics cluster from existing cluster templates based on the industrial analysis. This type of analysis will provide further basis to the concept of industrial clustering as a core foundation of sound economic development. In addition, the rationally based quantitative study allows officials to suggest recommendations and conclusions that will further enhance “Ohio’s
Hubs of Innovation and Opportunity” moving forward.
iii iv Acknowledgments
First off, I would like thank my wonderful wife, Katherine, and my three children, Sofia, Ethan, and Mira for allowing me to pursue this endeavor. I know that this has been difficult on all of them (and me) as it took away from our quality time together, but they stood behind me through thick and thin. Without their support and understanding none of this would have been possible, and I truly thank them for their patience and encouragement. I also want to thank my parents and Katherine's parents for their support and assistance throughout – they were always there to lend a helping hand – whether watching the kids, picking them up, or doing whatever.
Academically, I want to thank all who assisted me throughout this project. From Menelaos
Triantafallou and Professor vom Hofe in the Spring Studio of 2009 all the way to the end with my Committee Chair Christopher Auffrey – all of them were more than gracious in their time, guidance, and mentorship.
v Table of Contents Chapter 1 – Introduction...... 1 Chapter 2 – Literature Review...... 5 The Feser-Bergman Framework...... 16 The Kelton et al Framework...... 17 Entrepreneurs, Innovation, and Knowledge Networks...... 20 Geography and Supporting Institutions...... 22 The Cluster Initiative Greenbook...... 23 Chapter 3 – Case Studies of the Knowledge-Based Economy...... 28 The Research University...... 30 Entrepreneurial Culture and Financing...... 31 Leadership...... 33 Locational Aspects...... 33 The Event...... 34 Culture of Innovation...... 35 The Role of the University and the Educated Class...... 36 Chapter 4 – Avionics...... 37 Chapter 5 – Greene County and Southwestern Ohio...... 51 Greene County and Miami Valley Demographics...... 55 Physical Characteristics and Land Use...... 58 Transportation...... 59 Economic Characteristics...... 60 Higher Education...... 61 Demographics...... 64 Physical Characteristics and Land Use...... 66 Transportation...... 67 Economic Characteristics...... 67 Higher Education...... 69 Chapter 6 – Methodology...... 72 Employment Data for Greene County...... 76 IMPLAN Data ...... 76 Chapter 7 – Data Observations and Analysis...... 83 Economic Base Analysis – Employment ...... 84 Economic Base Analysis – Location Quotient...... 86 Economic Base Analysis – Shift-Share...... 87 Greene County Data and The McLean-Voytek Framework...... 89 Input-Output Analysis...... 91 Linkages...... 91 Multipliers ...... 95 Clustering in Greene County...... 96 Clustering in the Region...... 98 Chapter 8 – Recommendations...... 100 Chapter 9 – Conclusion...... 112 Bibliography...... 117 Appendix...... 120
vi Illustration Index Illustration 1: Porter's Competitive Diamond (Porter 1998)...... 12 Illustration 2: The Cluster Initiative Performance Model from The Cluster Initiative Greenbook (Solvell 2009)...... 24 Illustration 3: The Smilor Framework for High Tech Cluster Development (Smilor et al 2007). 29 Illustration 4: The Catalyst Organizations in San Diego (Smilor et al 2007)...... 31 Illustration 5: The Hybritech Tree (Walcott 2002)...... 32 Illustration 6: Employment Trends in Ohio Aerospace (Ohio Department of Development 2006) ...... 41 Illustration 7: Investment Trends in Ohio Aerospace (Ohio Department of Development 2006).42 Illustration 8: Aerospace Across Ohio (Ohio Department of Development 2006)...... 43 Illustration 9: The Wright Brothers Cycle Shop (Courtesy Aviation Trail Inc. 2009)...... 44 Illustration 10: Aviation Trail Map (Courtesy Aviation Trail Inc.2009)...... 45 Illustration 11: Ohio County DOD Contracts (Ohio Department of Development 2006)...... 47 Illustration 12: 38 County Study Region...... 52 Illustration 13: Greene County Ohio (Ohio Department of Development)...... 53 Illustration 14: Greene County Ohio (Ohio Department of Development)...... 54 Illustration 15: Miami Valley Region (Miami Valley Regional Planning Commission)...... 54 Illustration 16: Miami Valley Region (Miami Valley Regional Planning Commission)...... 55 Illustration 17: Montgomery County Population Trend (ODD 2008)...... 56 Illustration 18: Greene County Population Trend (ODD 2008)...... 57 Illustration 19: Miami Valley Population Trend (Miami Valley Regional Planning Commission 2008)...... 58 Illustration 20: Cincinnati-Middletown OH-KY-IN MSA – 15 County MSA (choosecincy.com 2010)...... 63 Illustration 21: Hamilton County Population Trend (ODD 2008)...... 65 Illustration 22: Four County (Hamilton, Warren, Butler, Clermont) Population Trend (ODD 2008)...... 65 Illustration 23: STEM Degrees Awarded - State of the Community Report 2008 (United Way of Greater Cincinnati 2008)...... 70 Illustration 24: 38 County Study Area and Greene County...... 74 Illustration 25: McLean and Voytek Decision Tree (Matthew Fischer and Assoc)...... 80 Illustration 26: Top 5 Industries by Location Quotient - Greene County...... 87 Illustration 27: Avionics Cluster Industry Assessment...... 89 Illustration 28: Greene County Buying-Selling Relationship - Avionics...... 92 Illustration 29: The Industrial Cluster Continuum - Greene County...... 97 Illustration 30: The Industrial Cluster Continuum - Greene County...... 114
vii Index of Tables Table 1: Feser-Bergman Cluster Template (Feser and Bergman 2000)...... 17 Table 2: Kelton et al Cluster Template (Kelton, Pasquale, and Rebelein 2008)...... 18 Table 3: Austin Texas Educational Attainment 2002 (Powers 2006)...... 37 Table 4: Avionics Components...... 39 Table 5: Manufacturing Employment in Miami Valley (Miami Valley Regional Planning Commission 2008)...... 60 Table 6: Higher Education - Dayton, Cincinnati (Dayton Development Coalition 2008)...... 62 Table 7: Hamilton County Land Use (ODD 2008)...... 66 Table 8: Four County (Hamilton, Butler, Warren, Clermont) Land Use (ODD 2008)...... 66 Table 9: Employment by Industry Sector - Cincinnati MSA (County Business Trends 2005)....68 Table 10: Enrollment in Area Colleges, Universities, and Vocational Schools (choosecincy.com 2010)...... 70 Table 11: Key Economic Indicators - State of the Community Report 2008 (United Way of Greater Cincinnati 2008)...... 72 Table 12: Avionics Specific Industries Employment Levels - Greene County...... 84 Table 13: Top 25 Industries Greene County - Employment/Employment Change 1992 - 2007..85 Table 14: Professional Services (NAICS 541) Industries...... 86 Table 15: Greene County Shift-Share Analysis...... 88 Table 16: Result of McLean-Voytek Decision Tree Analysis...... 90 Table 17: Backward and Forward Linkages - Greene County...... 93 Table 18: Backward and Forward Linkages - Greene County...... 93 Table 19: Backward and Forward Linkages - Greene County...... 94 Table 20: Backward and Forward Linkages - Greene County...... 94 Table 21: Avionic Multipliers for Greene County - IMPLAN 2006...... 96 Table 22: Draws for Businesses and Individuals(Kotler 2002)...... 110
viii Chapter 1 – Introduction
Background
As it relates to economic development, the concept of industrial clustering has been an area of intense scrutiny and debate over the past few decades. There is little consensus on the definition of a cluster, let alone what industries make up a particular cluster and what geographical regions and boundaries should be included in a cluster study. What does surface though, is the fact that there is an increasing importance placed on the concept of industrial clustering in economic development. Gone are the times of localities simply throwing money at companies to build a new factory in their community. The economic development process, including industrial cluster analysis, has evolved to become more of analytical, strategic, and long-term endeavor. Whether these federal, state, or regional organizations are going about these newly evolved initiatives in a prudent and rigorous manner is an entirely different matter though. There have been many “third wave” economic development initiatives characterized as targeted “clustering” or targeted economic development that have failed miserably. But, there have also been initiatives that have succeeded, and are still alive and well today.
Which brings us to the State of Ohio and its recent economic development initiatives. The State of Ohio Department of Development has consciously made a decision to identify strategic hubs to drive economic development and innovation. The goals of these hubs, as stated on the Ohio
Department of Development website, are threefold (Ohio Department of Development):
1 1. Propel innovation through cutting-edge, market-driven applied technology and knowledge spillover; 2. Foster the opportunity for job creation and retention; and 3. Catalyze the formation of new companies in the region, while at the same time helping to ensure that Ohio's existing industries retain their competitive advantage in the global marketplace.
As discussed above, Ohio has decided to embark on economic development efforts that are targeting key industries within specific regions of the state to drive innovation. This hub strategy was announced by Governor Ted Strickland in 2009 and has been a key component of Ohio's overall economic development efforts moving forward.
Moving forward to September of 2009, Governor Strickland announced the first hub of this economic development strategy – Dayton and its aerospace industry. Dayton is now the first spoke in the “Ohio Hub of Innovation and Opportunity” and with this appointment, there is now more of a sense of urgency to prove that this is a much deserved recognition. In addition,
Dayton and the surrounding region can expect to be the recipient of state grants and other resources to drive the aerospace and other ancillary industries over the course of the next few years. In fact, this past January, Dayton and the University of Dayton Research Institute received $250,000 in seed funds to propel this effort. According to a press release, the hub designation will enable the city and region and state to “leverage its resources to attract clusters of connected businesses, encourage new investments and an influx of talented workers, and create new opportunities to grow jobs and develop Ohio’s key industries” (Ohio Department of
Development).
2 There certainly is a rich tradition of aviation in the Dayton and the Miami Valley region .
Beginning with the Wright Brothers and their bicycle shop back in the early 1900’s to the contemporary Wright Patterson Air Force Base located in Greene County, aviation has always been a core competency of the Dayton and Miami Valley Region. Dayton is also heavily reliant on manufacturing, specifically as a supplier and original equipment provider to the automotive industry. The economy of Dayton and the Miami/Ohio Valley has taken a hit over the past several years due to a dramatic slowdown in automobile sales and other manufacturing, thus leading to a contraction in production of automobiles and other heavy materials. But, Dayton is also rich in professional services – specifically research and development – and with the presence of the Wright Patterson Air Force Base there is the opportunity to develop spin-off industries and businesses that fall into a category called the knowledge-based economy. As part of this knowledge-based economy is an avionics industry cluster that would fall into this category.
The need to explore industrial clustering is vital to furthering the economic development of the
Dayton and Miami Valley Region, including Greene County, home of the Wright Patterson Air
Force Base. In addition, identifying logical clusters that play off the strengths and weaknesses, the buying and the selling relationships amongst industries throughout this region is a strategy that the State of Ohio seems to have embraced. If an avionics cluster is identified, steps, strategies, and policies can be proposed that move this cluster into a position of strength throughout the region and provides long-term growth, opportunities, and vitality to a region that
3 appears to be on the cusp of entering into the knowledge-based economy. In an era of limited resources, this type of approach is imperative.
Research Question and Problem Statement
But how did our development leaders arrive at this selection of Dayton for aerospace and avionics? What is the basis of this designation? Have our state leaders jumped on the so-called cluster “fad” bandwagon that so many local, regional, state, and national leaders have embraced as part of their policy formation (Martin and Sunley 2003)? Has the policy come before the analysis? Or is it the fact that our leaders need to begin acting like entrepreneurs and jump on the
“third-wave” of economic development? These are some of the questions that this paper will attempt to address over the next several chapters. In summary:
• Why is industrial clustering important for the State of Ohio, specifically in Greene
County and Southwestern Ohio?
• How are potential industrial clusters identified and what are the characteristics of those
clusters in Greene County and Southwestern Ohio?
• What are the logical clusters of the region and where does it make sense to invest?
• What are some of recommendations and strategies that this region could implement to
take advantage of the potential clusters, particularly the avionics and aerospace cluster?
4 Structure of Thesis
To answer the preceding questions, the following paper will provide a quantitative approach to identifying industrial clusters, specifically the avionics cluster, in Greene County and
Southwestern Ohio region. To begin with, an understanding of industrial clustering and economic development will be presented in the form of a literature review. From there, several case studies will be reviewed to understand how specific circumstances, groups, and individuals are important in the development of an industrial cluster. Following the case study analysis, a background of avionics and where it has been successful will be discussed. From there, a demographic study of Greene County and the Southwestern Ohio Region will be summarized.
And finally, in the analysis phase of the paper, the data methodology will be outlined and performed. This methodology will provide the road-map to understanding how to perform an economic assessment of a local economy, with the intent of identifying logical industrial clusters. The data analysis will be followed by recommendations and conclusions for moving forward with industrial clustering, specifically as it relates to avionics.
Chapter 2 – Literature Review
The following literature review will introduce the reader to how economic development practices have evolved over the years from a single-minded, financially driven approach to a more holistic, long-term view. From that, the concept of industrial clustering is defined and discussed from several different positions. Finally, several frameworks are presented that will form the basis for the remainder of this economic development study. The review will conclude by offering a
5 summary of the various ways in which cluster development has been promoted throughout the world. Bringing all of these thoughts and ideas together in the final analysis will provide the springboard for the study of industrial clustering in Greene County and Southwestern Ohio.
Why Regional Economic Development?
It is imperative to understand why economic development is important. Proactive economic development by governments in the United States took a foothold after World War II (Goetz,
Deller, and Harris 2009). Goetz et. al cite several reasons for the increased interest by the state in impacting economic policy. These reasons include:
• The Great Depression and the doubt raised by this traumatic event
• Marshall Plan Success and Soviet Central Planning
• India and its plans for economic development after they became independent
• Japan and its success post WWII
• Success of state policies post WWII – for example Mississippi balancing agriculture
with industry
Other, more cynical views of economic development see government figures and policy makers as self-serving, and not necessarily market driven. Peter Eisinger cites the “Massachusetts
Miracle” as a prime example of how quickly things can turn, specifically for the political leaders involved in the planning (Eisinger 1995). In the Massachusetts example, some very proactive
6 economic development officials of the Dukakis administration claimed success as they turned the economy around. But then it quickly went back to bad, as the economy tanked. This is the reality of economic development, especially during a recession, and Eisinger points out that state programs consolidate during periods of sluggish growth (Eisinger 1995). They become defensive and are more concerned with political survival than effective development.
The importance of regional economic development lies in the fact that there is an opportunity to have an impact on the way a region grows economically. This impact does not necessarily have to be driven exclusively by government or private industry, but can be a healthy mix of both in most cases. This influence and competition among states, localities, and municipalities, plus the question of whether these initiatives are driven by government or private interests leads us to the three waves of economic development.
The Three Waves and Industrial Clusters
Regional economic development has gone through a series of phases over the past few decades.
Researchers have coined these phases: “First Wave”, “Second Wave”, and “Third Wave”
Economic Development practices (vom Hofe and Chen 2006). The “First Wave” is characterized primarily by programs that are designed to lure firms through financial incentives such as subsidies, tax incentives, and other direct payment programs. The lure of financial incentives is hardly justified for the economic development of a region, especially in early stage development as these incubator firms and industries are not even profitable (Feldman and
Francis 2004).
7 The “Second Wave” is more of an indirect approach that is characterized by an entrepreneurial strategy which includes business retention and expansion, investment programs, technical assistance programs, and other more creative components. This leads us to the “Third Wave” which is more of a holistic approach to economic development. Instead of throwing money after the next big firm, local and state authorities are taking a more comprehensive and long-term view of the local and regional economy. As Bradshaw and Blakely suggest, the “Third Wave”
“incorporates the first and second waves through systems of collaboration that facilitate the creation, location, or relocation of firms because of the general attractiveness of the region”
(Bradshaw and Blakely 1999).
“Third Wave” economic development is the concept of clustering. With regions relying more on “attractiveness” for a competitive advantage, the way that firms and industries interact with each other throughout these regions becomes increasingly important. Michael Porter shed some new light on this theory in an article in the Harvard business review in which he states: “Today’s economic map of the world is dominated by what I call clusters: critical masses – in one place – of unusual competitive success in particular fields” (Porter 1998). Porter’s complete definition of the industrial cluster is as follows:
“Clusters are geographic concentrations of inter-connected companies and institutions in a particular field. Clusters encompass an array of linked industries and other entities important to competition. They include, for example, suppliers of specialized inputs such as components, machinery, and services, and providers of specialized infrastructure. Clusters also often extend downstream to channels and customers and laterally to manufacturers of complementary products and to companies in industries related by skills, technologies or common inputs. Finally, many clusters include governmental and other institutions --- such as universities, standard-setting agencies, think tanks,
8 vocational training providers, and trade associations --- that provide specialized training, education, information, research, and technical support” (Porter 1998)
As we will see later on in this literature review, Porter’s definition is among a long list of definitions that characterize the concept of industrial clustering. Some of these definitions are very similar, while others have unique wording that distinguishes them from the others.
In addition, what are the benefits that can be gained by looking at local and regional economies through the cluster definition? In a 2002 report completed by Ecotec Research and Consulting for The Department of Trade and Industry in the United Kingdom, several clustering benefits are identified. The report entitled A Practical Guide to Cluster Development delineates the following benefits (Ecotec Research and Consulting 2002):
• Clusters increase levels of local expertise. This provides sourcing companies with a greater depth to their supply chain and allows for the potential of inter-firm learning and co-operation.
• Clusters give firms the ability to draw together complementary skills in order to bid for large contracts that as individual units they would be unable to successfully compete.
• Clusters allow for potential economies of scale to be realized by further specializing production within each firm, by joint purchasing of common raw materials to attract bulk discounts or by joint marketing.
• Clusters strengthen social and other informal links, leading to the creation of new ideas and new businesses.
9 • Clusters improve information flows within industries. For example, clusters may enable finance providers to judge who the good entrepreneurs are and business people to find who provides good support services.
• Clusters allow for the development of an infrastructure of professional, legal, financial and other specialist services.
But, as will be seen in the following paragraphs all have not bought into the concept of industrial clusters and the benefits that are documented above.
To Cluster or Not to Cluster?
In an era of scarce economic resources it would seem as if the practice of identifying logical industrial clusters in which to allocate those resources would be a certainty. Not so fast. There are several points of contention that some analysts and economists have identified with the industrial cluster. From too many broad, vague definitions to unreliable data, to unclear regional boundaries, to not enough emphasis on the spatial and geographical considerations – these are just a few of the objections. To understand where these faults are coming from is essential to understanding how the concept of industrial clustering has evolved over the years.
Going back to Porter’s work, vom Hofe and Chen critically analyzed clusters in their journal article entitled Whither or Not Industrial Cluster: Conclusions or Confusions? (vom Hofe and
Chen 2006) They identified three main bodies of work over the past 150 years as it relates to clusters. Obviously the one concept that they identify is that of Porter which is a more
“intuitive”, “business-friendly” approach (Martin and Sunley 2003). The other two that they identify are the Marshallian approach and the Inter-Industry approach.
10 The Marshallian approach that vom Hofe and Chen identify is based on regional specialization and looks at groups of establishments belonging to the same industry sector within a regional geographic boundary. This regional specialization approach is typically measured by a location quotient method.
The Inter-Industry model is based on inter-industry linkages and is typically measured using input-output tables. Input-output tables illustrate the upstream and downstream trading characteristics of each industry sector – for example what raw materials is the telecommunications industry using to produce their product and ultimately who is buying their end product – these are the linkages that make up the industry sectors within the regional economy.
Again, the Porter model as suggested by some experts does not seem to offer anything new in respect to the inter-industry linkages and regional agglomerations – it seems more an amalgam of the previous two concepts. The one area that Porter does seem to stress in regards to his cluster concept is the aspect of competitiveness (Illustration 1). These concepts have been viewed as vague and not based on logic. They have also been attacked for not having any clear geographical boundaries.
11 Illustration 1: Porter's Competitive Diamond (Porter 1998)
The vom Hofe and Chen analysis also gives mention to Gordon and McCann for their 2000 study and identification of three different cluster types. The cluster types that Gordon and McCann recognize align very well with the bodies of work that have been discussed earlier. The Gordon and McCann cluster types are: pure agglomeration (Marshallian), industrial complex (inter- industry), and the social network models. Their conclusion is that either one of these cluster models may be present in the area of economic study (Gordon and McCann 2000).
12 More current literature seems to suggest that the industrial cluster concept is not the panacea that it would seem to be. It seems that there is no clear definition or understanding of what clusters actually represent. In fact, Martin and Sunley in their article in the Journal of Economic
Geography identified a multitude of definitions throughout economic development literature.
Below is a catalog of the various definitions that Martin and Sunley identified in their research
(Martin and Sunley 2003):
Porter (1998) - ‘A cluster is a geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities.’
Crouch and Farrell (2001) - ‘The more general concept of ‘‘cluster’’ suggests something looser: a tendency for firms in similar types of business to locate close together, though without having a particularly important presence in an area.’
Rosenfeld (1997) - ‘A cluster is very simply used to represent concentrations of firms that are able to produce synergy because of their geographical proximity and interdependence, even though their scale of employment may not be pronounced or prominent.’
Feser (1998) - ‘Economic clusters are not just related and supporting industries and institutions, but rather related and supporting institutions that are more competitive by virtue of their relationships.’
Swann and Prevezer (1996) - ‘Clusters are here defined as groups of firms within one industry based in one geographical area.’
Swann and Prevezer (1998) - ‘A cluster means a large group of firms in related industries at a particular location.’
Simmie and Sennett (1999) - ‘We define an innovative cluster as a large number of interconnected industrial and/or service companies having a high degree of collaboration, typically through a supply chain, and operating under the same market conditions.’
Roelandt and den Hertag (1999) - ‘Clusters can be characterised as networks of producers of strongly interdependent firms (including specialised suppliers) linked each other in a value- adding production chain.’
Van den Berg et al. (2001) - ‘The popular term cluster is most closely related to this local or regional dimension of networks . . .Most definitions share the notion of clusters as localised networks of specialized organisations, whose production processes are closely linked through the exchange of goods, services and/or knowledge.’
Enright (1996) - ‘A regional cluster is an industrial cluster in which member firms are in close proximity to each other.’
13 So, all these definitions just seem to create additional noise and static around what clusters actually represent.
In a scathing attack against targeting, which goes hand in hand with industrial cluster development, Terry Buss discusses the shortcomings of governmental policy and programs devoted to “channeling scarce resources” into one particular industry or venture (Buss 1999).
Buss discusses the faulty, unscientific data and political motivations of the studies that encourage baseless financial incentives to be thrown at industries and firms as a result of these reports. One particular example that he cites is the city of Youngstown, where different studies encouraged investment in steel and high tech, while others suggested that they target the wooden toy industry. All of these ideas proved to be severely misguided.
It is important to keep in mind that local and regional agencies have come a long way from the smokestack chasing era (although it probably still happens) and have taken a more holistic approach towards economic development.
Moving forward, all of these views are timely in the face of Ohio’s efforts to identify areas of economic opportunity throughout the state. Through “Ohio’s Hub of Innovation and
Opportunity” (OHIO) program, the state is becoming proactive in identifying areas of economic opportunity throughout the state. For instance, Dayton has recently been designated as the first spoke in this program, with its focus on aerospace. The Ohio cluster initiative will be discussed
14 later on throughout this paper, especially as it relates to Dayton, Greene County, and
Southwestern Ohio.
No Magic Formula
There may not be a clear agreement on the definition of what a cluster is, but it seems that there are some common denominators in all of these definitions. “Group”, “network”, and “location” are common themes that run throughout. As Doeringer and Terkla put it: “There simply exists no single correct definition of an industrial cluster” (Doeringer and Terkla 1995). However, most (if not all) cluster concepts share a common denominator: industrial clusters refer to groups of firms, businesses, and institutions that co-locate geographically in a specific region and that enjoy economic advantages through this co-location (vom Hofe and Chen 2006). We can pick apart the concept of clustering to the nth degree, but moving forward that will not really help us with economic development.
Martin and Sunley’s contention that the cluster concept is completely “arbitrary”, “chaotic”, and devoid of any real boundaries is valid, but at some point quality analysis, along with intuition will help move the ball forward (Martin and Sunley 2003). In addition the breaking down of communication and transportation barriers is making these boundaries less important anyway
(Feldman and Francis 2004). The bottom line is that performing a sound quantitative and qualitative analysis will support the policy and development decisions going forward – all definitions aside. Also, in addition to local networks, it is important to achieve a balance that involves national and international network connections (McDonald et al. 2007). The case study
15 section of this paper will illustrate some sound qualitative and quantitative industrial clustering economic development studies, while the Greene County analysis will focus on the quantitative aspects.
Cluster Frameworks
Putting all of the debate in the background, how have industrial clusters been identified throughout the years? There are various quantitative and qualitative methods that economic researchers have used over the years to define clusters and what makes up a cluster for a particular region.
The Feser-Bergman Framework
There have been a few recent proposals delineated by Edward Feser and Edward Bergman based on SIC codes, followed by a more recent proposal conducted by Kelton, Pasquale, and Rebelein based on NAICS codes.
To begin with, the Feser/Bergman model relies on inter-industrial linkages at the national level – looking at the Standard Industrial Classification (SIC) codes and the buyer/seller relationships amongst industries. From this analysis, Feser and Bergman were able to identify 23 total industry clusters. These 23 clusters can be used as templates at the regional level to analyze what industries are interacting with each other throughout the economy. Feser and Bergman declare that these methods of cluster template analysis are a good baseline for formulating a
16 regional economic development plan, but other factors should also be considered (Feser and
Bergman 2000).
Table 1: Feser-Bergman Cluster Template (Feser and Bergman 2000)
The Kelton et al Framework
A number of years later Kelton, Pasquale, and Rebelein developed similar templates based on the
North American Industry Classification System (NAICS). One advantage of using this newer, more modern classification system is the fact that it accounts for more of the service sector industries that have developed over the past 30 to 40 years. The SIC system was more top heavy in manufacturing sectors, allowing for a more granular review of the those sectors – the
17 introduction of the NAICS system has accounted for the realignment to more of a service-based economy (Zeisset and Wallace 1998).
Table 2: Kelton et al Cluster Template (Kelton, Pasquale, and Rebelein 2008)
Cluster Identification Methods
Obviously, the two methods above can be used as a guide in determining what industries make up an industrial cluster on a general level, but what are some of the ways in which researchers can determine if any one of the clusters identified by Feser/Bergman or Kelton et al are viable in their local or regional economy.
18 First and foremost, to get a firm grasp on the existing regional economy various traditional methods are necessary. McLean and Voytek in their book Understanding Your Economy:
Using Analysis to Guide Local Strategic Planning have developed a decision tree to assess what industries of the economy are performing versus non-performing. A more detailed discussion of this methodology will be discussed later on in the methodology section of this paper.
Charles Colgan and Colin Baker in their assessment of the Maine economy analyzed industries and their potential for clustering. They stuck closely with a Porter model based on competitiveness and firm interactions. Using a quantitative and qualitative approach, they looked at the following eight cluster dimensions (Colgan and Baker 2003):
1. Innovation
2. Regional business functions
3. Entrepreneurship Objectives
4. Financing
5. Relationships
6. Locational Advantage
7. Market Potential
8. Lead Industry Group Growth
Then, by utilizing interviews and assessing employment growth they were able to award scores
(1-3) to the industry clusters that they were examining. By scoring the selected clusters
19 (information technology, biotechnology, advanced materials, forest products, agriculture, marine and aquaculture, environmental, and precision manufacturing) against each of the above dimensions, they were able to classify the clusters in terms of “stars”, “potential stars”, “base”, and “seeking direction” (Colgan and Baker 2003).
Sowing the Seeds of Cluster Development
This final portion of the literature review deals with the conditions that need to exist for industrial cluster formation. The range of ideas around this topic is varied. Some researchers insist that the formation of clusters is strictly geographical while others maintain that there are very specific economic, government, and industry conditions that need to be present. The bottom line seems to be that each regional situation is unique, and that replication is often difficult (Cortright and Mayer 2001).
Entrepreneurs, Innovation, and Knowledge Networks
Feldman and Francis discuss the role of the entrepreneur and innovation in the formation of clusters. They identify three stages: inert stage, formative stage, critical mass stage (Feldman and Francis 2004). The inert stage is marked by the presence of assets and resources, but no significant entrepreneurial work. The second stage begins the formation of the cluster, based on the significant activity of the entrepreneur. This activity, as noted by Feldman, is prompted by some “exogenous shock” to the local economy and success is enhanced by public and private investment in the overall infrastructure of the local economy – in conjunction with the
20 entrepreneur activity (Feldman and Francis 2004). The third stage is marked by a maturation of the initial entrepreneurial activity and the associated activity. These areas can now sustain themselves in that particular area of specialization – i.e. Silicon Valley, the Research Triangle, and the Boston Corridor all specializing and sustaining high-technology industrial clusters.
Peter Maskell discusses the evolution of the cluster in his journal article “Towards a Knowledge
Based Theory of Geographical Cluster”. His points seem to emphasize entrepreneurial activity and the need of the entrepreneur to be in close proximity to gain certain advantages – i.e., to gain better access to local knowledge base, suppliers, or customers (Maskell 2001). The entrepreneurs will want to be close to the action and eventually, they will be spinning off additional industries that contribute to the cluster.
But Edward Bee conducted a study that dismisses the idea of small firms (i.e. entrepreneurs) controlling the innovation process. Using patent records information, he was able to discern that it is actually the large, dominating firms that develop most of the new patents. It is usually one or two “prolific” firms in the region that tend to have the innovators, hence that region is looked upon as innovative (Bee 2003). Motorola, IBM, Hewlett Packard – these are the types of companies that tend to control most of the innovation. You see this in such places as
Raleigh/Durham, San Diego, and Austin where you have renowned learning institutions combined with some very notable companies. These are two traits that should propel regions into the high-tech arena (Smilor et al. 2007).
21 Reviewing Bee’s analysis against the Feldman and Francis model proves interesting. Bee’s analysis suggests that the patent data collected at the time (1990’s data) marked characteristics of the Feldman and Francis first stage in the formation of clusters – the inert stage. This stage is marked by large institutions and dominant companies driving the regional economy (Feldman and Francis 2004). The “exogenous shock” that propels cluster formation into the active, entrepreneurial stage could significantly alter Bee’s final analysis.
Geography and Supporting Institutions
Looking further at the conditions that are usually present for cluster formation, Ann Markusen identified four different types of “sticky” places. These “sticky” places
(industrial districts) have very distinct features and characteristics that enable them to evolve and interact in very specific ways. There is the traditional Marshallian district, the hub-and-spoke district, the satellite industrial platform, and the state-anchored district (Markusen 1996). Of particular interest, especially to this paper, is the state-anchored district. Markusen identifies the following traits as part of the state anchored district:
• Business structure dominated by one or several large, government institutions such as military bases, state or national capitals, large public universities, surrounded by suppliers and customers (including those regulated) • Scale economies relatively high in public-sector activities • Low rates of turnover of local business • Substantial intra-district trade among dominant institutions and suppliers, but not among others • Key investment decisions made at various levels of government, some internal, some external • Short-term contracts and commitments between dominant institutions and suppliers, customers • High degrees of cooperation, linkages with external firms for externally headquartered supplier organizations • Moderate incidence of exchanges of personnel between customers and suppliers • Low degree of cooperation among local private-sector firms to share risk, stabilize market, share innovation • Labor market internal if state capital, national if university or military facility or other federal offices for professional/technical and managerial workers
22 • Disproportionate shares of clerical and professional workers • Workers committed to large institutions first, then to district, then to small firms • High rates of labor in-migration, but less out-migration unless government is withdrawing or closing down • Evolution of unique local cultural identity, bonds • No specialized sources of finance, technical expertise, business services • No "patient capital" within district * Weak trade associations to share information about public-sector client • Weak local government role in regulating and promoting core activities • High degree of public involvement in providing infrastructure • Long-term prospects for growth dependent on prospects for government facilities at core
The above frameworks – the entrepreneurial approach and the institutional approach – seem to mesh well with the thoughts proposed by Martina Fromhold-Eisebith and Gunter Eisebith in their discussion of institutionalizing innovative clusters. They identified the need for “explicit top-down” and “implicit bottom-up” approaches in the formation of industrial clusters
(Fromhold-Eisebith and Eisebith 2005). The “explicit top-down” approach is the governmental policy directly promoting the formation of clusters, while the “implicit bottom-up” approach is almost a hands-off, market-driven approach by the firms themselves.
The Cluster Initiative Greenbook
More recently, there has been a push by a group from Europe to establish more concrete methods and processes for spearheading cluster initiatives. In 2003 Orjan Solvell, Goran Lindqvist, and
Christian Ketes undertook a survey of 500 (238 responded) cluster initiatives from around the world (Solvell, Lindqvist, and Ketels 2003). Their goal was to establish a methodology to assist policymakers and government agencies to move forward in a more systematic way. By looking at best practices across Europe and elsewhere, they hope to create a playbook for cluster economic development. Their outcome was the “Cluster Initiative Performance Model” (CIPM)
23 and a discussion of this model is helpful in understanding industrial clustering, especially as it relates to “sowing the seeds of cluster development”.
The Cluster Initiative Performance Model
In the CIPM there are four main points as noted in Illustration 2:
1. The Setting 2. The Objectives 3. The Process 4. The Performance
Illustration 2: The Cluster Initiative Performance Model from The Cluster Initiative Greenbook (Solvell 2009)
24 The Setting
The setting of a cluster initiative is important to its ultimate formation. The setting refers to the political, social, and economic factors that lead to how strong or how weak a cluster initiative performs (Sölvell 2009). These actors also have a determination in how policy is shaped and the corresponding business environment.
The Objectives
Solvell et al, as part of their model, identify five overriding objectives. These objectives include (Sölvell 2009):
1. Research and networking 2. Policy action 3. Commercial cooperation 4. Education and training 5. Innovation and technology 6. Cluster expansion
The Process
The process refers to how clusters are established and how they grow. In the Greenbook model, Solvell identifies six phases:
1. Initiation and planning 2. Governance and financing 3. Scope of membership 4. Resources and facilitator 5. Framework and consensus 6. Momentum
25 Performance
How does the Greenbook measure performance of cluster initiatives? The identify three
areas:
1. Innovation and international competitiveness 2. Cluster growth 3. Goal fulfillment
What of the Greenbook?
The whole point of this new and contemporary view of clusters in the Greenbook is to provide a model or framework for developing clusters moving forward. Further on in the case study section, one will visibly see a lot of these milestones, and the process and performance indicators that come along with it. The cluster movements of the past had no playbook or template or performance indicators to guide their development – they just happened by the interaction of various individuals and key events. There is not a whole lot that is earth shattering about the
Greenbook, but it is worth mentioning as another initiative that exemplifies the importance of industrial clustering.
What Does All of This Mean?
Bringing all of the following definitions, concepts, and frameworks together can be thoroughly confusing. What does any of this mean for economic development policy and industrial clustering going forward? There are three main takeaways from the above literature review:
26 1. There is no clear cut definition for the industrial cluster;
2. There are multiple ways to measure industrial clustering, but they must be measured
carefully. Also, once we have identified cluster, how do we measure success?
3. There is no one prescribed way for building a cluster.
The implications of these takeaways means that economic development planners need to be practical and use common sense when formulating their plans. Does it really matter that there is no accepted definition? Planners need to select a definition and stick to it throughout their research. They also need to use caution when formulating policy and programs that aim to promote specific industries or clusters over another. As Martin and Sunley would contend it does not make any sense to throw all of your eggs into one basket.
The preceding literature review leads us to the basis of the Greene County study. Using the national industry cluster templates proposed by Kelton, Pasquale, and Rebelein as a framework I will develop a template that resembles an avionics cluster. From there, using several economic analysis methods I will determine where Greene County and the surrounding region needs to focus their attention in developing their avionics cluster. Again quoting Porter, “to justify cluster development efforts, some seeds of a cluster should already have passed a market test”; and this is what I will attempt to do as part of this study as it relates to avionics (Porter 1998).
27 Chapter 3 – Case Studies of the Knowledge-Based Economy
We have reviewed the theoretical in the above section, now this section will assess several successful clusters and how they came to fruition. These case studies will delineate the traits, policies, and programs that have made the selected cities successful at developing their specific clusters. These components are important to Greene County and Southwestern Ohio due to the fact that they are easily replicable, or in some cases already prevalent in our study region. The cities that will be discussed below include San Diego for its biotech industry and Austin, Texas for its information technology cluster.
San Diego and Biotech
San Diego, California is usually more renown for its military presence rather than its biotechnology presence, but this city has vaulted itself forward in terms of medicine and technology. With an uncanny knack to attract venture capital and an employment growth rate of
97 percent from 1990 – 1996, the bioscience cluster in San Diego has proliferated.
There are several key traits that enabled San Diego to move to the forefront of the biotech scene.
Several traits were identified by Susan Walcott in her article “Analyzing an Innovate
Environment: San Diego as a Bioscience Beachhead” (Walcott 2002). These traits are outlined below and will be discussed further throughout this section.
• Research university with specialty • Entrepreneurial culture • Strong leadership • Risk financing
28 • Real estate
Raymond Smilor et al add onto this framework (Illustration 3) by saying that there is usually some outstanding event that propels the region to the forefront of its particular field or cluster
(Smilor et al. 2007). The following paragraphs will review the case of San Diego and the traits that are discussed above.
Illustration 3: The Smilor Framework for High Tech Cluster Development (Smilor et al 2007)
29 The Research University
The University of California, San Diego was the spark from which the biotech cluster took off in
San Diego. Established in 1959, the research university was an effort spearheaded by Roger
Revelle, who at the time was the director of the Scripps Institution of Oceanography. Other institutions that added to the brain swell included the Salk Institute and the Scripps Institute.
The culture of innovation and creativity that thrived at these academies cannot be understated.
With an interdisciplinary approach that fostered knowledge transfer and collaboration, Revelle actively encouraged his research personnel to share with other departments at the university.
Also helpful were the numerous military installations throughout San Diego that produced engineers and scientists at a rapid rate.
Entrepreneurial Culture and Financing
In the case of San Diego, the entrepreneurial culture has driven biotech. The one firm that had a huge impact on the development of this cluster was Hybritech (Walcott 2002). Susan Walcott identifies the number of employees that separated from Hybritech once Lilly bought them in
1986 and the number of direct or indirect spin-offs created by those executives. Whether it was managing venture capital firms or incubating their own biotech start-ups, the Hybritech family tree is startling as shown in illustration 5. This incendiary event – the purchase of Hybritech by
Lilly – catapulted many talented individuals into the marketplace who would rather venture out on their own than remain in the staid, corporate environment of Lilly. It also illustrates the
30 catalyst organization (illustration 4) that can have a huge impact on the development of talent and cluster industries.
Illustration 4: The Catalyst Organizations in San Diego (Smilor et al 2007)
Another key catalyst organization in the development of biotech in San Diego is UCSD
CONNECT. This organization was formed by a few very instrumental leaders (Mary Walshok and Richard Atkinson) in the San Diego community and today is one of the leading incubators linking up business entrepreneurs with science (Smilor et al. 2007). UCSD CONNECT assists close to fifty companies a year in start-up operations and financing assistance (Smilor et al.
2007).
31 Illustration 5: The Hybritech Tree (Walcott 2002)
Leadership
The leadership throughout the San Diego community and its impact on cluster formation over the years is readily apparent. From the initial founders of the Scripps Research Institute in 1955 to the leaders of UCSD Connect, the influential personalities were present throughout the development of San Diego’s high-technology cluster. Such names as Roger Revelle, Harold
Urey (Nobel Prize winner), David Bonner (geneticist), Richard Atkinson (from Silicon Valley),
Ivor Royston (founder of Hybritech), and many others led the way in terms of solidifying San
Diego as a biotech hub. In fact, in interviews conducted by Susan Walcott in her study of the
San Diego cluster, one respondent stated: “The number 1 reason for San Diego’s success is people. Success breeds success” (Walcott 2002).
32 Locational Aspects
Another component of the San Diego bioscience cluster is the locational aspect of the businesses and firms that made up this cluster. The firms that make up this cluster are located in close proximity to each other and the research universities that they collaborate with – not by accident, but out of necessity. It only makes sense from an information sharing and cost efficiency perspective to locate as close to each other as possible to take advantage of these natural relationships.
In looking at these firms on a map of San Diego, most of them are in close proximity to UCSD or the University Town Center. The reasons for this proximity are twofold: access to university infrastructure and knowledge transfer with the academic and research community. The firms that are located in this area usually are the headquarters and administrative staff who can afford the higher rents in this area, while production facilities are generally located in the less pricier properties that are further inland (Walcott 2002).
Austin, Texas and High Tech
Austin, Texas, like San Diego, California has a successful knowledge-based component as part of its overall economy. In the case of Austin, high technology is a sector that is thriving throughout the region. Austin is considered one of the forerunners in high technology development and manufacturing. There are several reasons for this development in Austin that need to be discussed and then related back to cluster-based initiatives.
33 The Event
In the cases of various cities it takes a unique event to spearhead their ascent towards success.
Smilor et al refer to this event as the “incendiary event” (Smilor et al. 2007) . Much like San
Diego, Austin's status as a high-technology innovation center was propelled by just such an event. The main event in Austin was the recruitment of the Microelectronics and Computer
Technology Corporation (MCC) back in 1983. MCC was the first private-sector high technology consortium in the United States.
The recruitment of MCC gave Austin instant credibility and demonstrated the effectiveness of combining efforts to achieve a common goal. The University of Texas worked together with government and private industry to formulate various incentives to attract MCC. These incentives ran the gambit from non-monetary to monetary and proved to be one of the driving forces behind MCC's decision to locate in Austin. These incentives included access to university facilities, teaching and fellowship positions, and subsidized home loans.
Other significant events in Austin business history include the recruitment of Texas Instruments,
Advanced Micro Devices, IBM, and many more. All of these industries are world renown and vaulted Austin to the top of the pack in terms of high-technology manufacturing and development. In the year 2000, almost two-thirds of all Austin employment was in the the high technology sector, or some sector associated with high technology (Smilor et al. 2007) .
34 Culture of Innovation
Austin was able to successfully brand itself as a leader in technology innovation. This culture was ingrained back in the 1960's by a leader named Vic Mathias who headed up the Austin
Chamber of Commerce. Smilor referred to Mathia as “one of the social architects, godfathers, or grandfathers” of modern Austin. He was among its first “captains of industrial recruitment” and he was able to champion Austin as a leader in high technology industries by bringing together leaders of business, government, and the university (Smilor et al. 2007).
Of course, there is Michael Dell, who while a freshman at the University of Texas sold computers out of his dorm room and later became the founder of Dell (Powers 2002). His success later spawned a huge influx of venture capital and investments that led to Austin becoming one of the leaders in venture capital firms with over 25 in the late 1990's (Smilor et al.
2007).
35 The Role of the University and the Educated Class
Obviously the University of Texas (UT) has had a profound impact on the high-technology initiatives in Austin, but it is not the only notable university in Austin. In the fall of 2002 there were approximately 113,655 students enrolled in Austin area universities and colleges (Powers
2002). UT led the way with over 50,000 students enrolled in that program (Powers 2002). This number speaks to the culture of innovation and education found throughout the city. Table 3 below illustrates how Austin compares to the rest of the United States in terms of college graduates and what high-technology sector employs them.
The impact of UT on the surrounding community and elsewhere is huge. In respect to research capabilities, UT is second in the nation in terms of federally funded research programs (Powers
2002). According to the University of Texas Bureau of Business Research, the economic impact of UT on the entire state of Texas is $7.4 billion, and UT employs 22,000 (Smilor et al.
2007).
The entrepreneurialism that spawned from UT is seen throughout the Austin business community. UT has served as an incubator for start-up companies and collaborated with the industry stalwarts of the area. The IC2 Institute (Innovation, Creativity, and Capital Institute), founded by Dr. George Kozmetsky of the UT College of Business, prided itself on its collaboration with the researchers, inventors, venture capitalists, and other key members of the
Austin business and university community.
36 Table 3: Austin Texas Educational Attainment 2002 (Powers 2006)
Chapter 4 – Avionics
This section will provide detail on what comprises the avionics industry and how aerospace and aviation-related industries (including avionics) have shaped the State of Ohio and the Dayton area. In addition, some case studies will be showcased that illustrate the circumstances and context for the development of successful avionics ventures throughout the world. This will then provide the springboard into the avionics cluster study of Greene County and Southwestern
Ohio.
37 What is Avionics?
In order to understand what would comprise an avionics cluster and the potential industries that are necessary to sustain an avionics cluster, avionics, sometimes referred to as “on-board” systems, must be defined. The American Institute of Aeronautics and Astronautics defined avionics as the following (American Institute of Aeronautics and Astronautics):
“Avionics are the aviation electronics systems that provide the functions and capabilities required for safe operation of aircraft throughout the world. Avionics encompass the ground, aircraft, and space assets required for control of flight of the aircraft, and its operation and movement while on the ground. Training systems incorporate avionics used in the aircraft.
The air traffic control system is a global network of national air traffic control systems that seamlessly pass the control of international flights as they travel between countries and continents. Air traffic control globally coordinates the use of airspace. Airspace capacity is influenced by weather conditions and bad weather at landing or takeoff airports creates backups, delays, and canceled flights.
The avionics on board an aircraft provides the crew the capability to manually or automatically control the flight of the aircraft in response to flight plans and air traffic control clearances. Avionics also provide passenger entertainment in airline operations. Avionics systems integrate the hardware and software that implement control of flight functions, navigation, guidance, control, communications, and systems operations and monitoring.
Technology advances rapidly and many avionics developments such as the Global Positioning System (GPS) have contributed to the economy by creating an industry that provides products with applications from the original navigation to surveying, construction, transportation, logistics, and recreational usage”.
Hence, the avionics of an aircraft is the hardware and software used to control the navigation, both in the air and on the ground, plus all of the other ancillary aspects of flight operations.
38 In summary, avionics can consist of the following:
Table 4: Avionics Components Weather Systems Aircraft Networks
Police and Air Communication from Aircraft to Ground
Ground navigation Monitoring GPS
Flight Controls Collision Avoidance Systems
Aircraft Management Mission and Tactical
Military Radar
Sonar Electronics
One concept that is of particular importance to the avionics industry is that of “flex tech” or flexible technology. The idea is that as technology grows and adapts, one small innovation can spur many other new developments, or continue working off each other. The idea that one product is the center and all other products fit in that mold is similar to the idea of circular causation. The avionics industry is constantly changing, new technology is invented everyday, and there is a need for the industry to do the same. The following sections will present a few successful avionics case studies and identify some of the key characteristics of these areas that are important to the growth of avionics.
39 The Importance of Avionics and Aerospace to Ohio
The importance of aerospace and aviation related industries cannot be underestimated in Ohio.
With a strong backing from research universities and government initiated programs there are numerous businesses and communities throughout the state that have benefited from the success of this industry. In fact, the Ohio Department of Development lists “aerospace and aviation” among one of its key industries (out of 10 key industries that are listed on its website) (Ohio
Department of Development - Office of Policy, Research and Strategic Planning 2010). The facts and figures of aerospace throughout Ohio are impressive as the following statistics from the
Ohio Department of Development will attest (Ohio Department of Development - Office of
Policy, Research and Strategic Planning 2010):
• 16,100 employed in this sector as of October 2007 – peak was in 2000 with 17,000 (Illustration 6 - below) • Ohio ranks 1st in terms of value produced per worker • Ohio ranks 8th in total industry employment for this sector • 72 industry establishments as 2005 paying an average wage of $69,286 versus statewide average of $45,033 for all manufacturing • $5.98 billion in 2006 DOD spending • Notable companies include: ◦ GE Aviation (Cincinnati) ◦ Goodrich (Cleveland) ◦ Aircraft Braking Systems (Akron) ◦ Honeywell, Boeing, Alcoa, RTI, Timken • Key Research Institutions: ◦ Wright-Patterson AFB ◦ NASA Glenn ◦ Ohio Aerospace Institute (OAI)
With the importance of the aerospace-and-aviation industries firmly entrenched in Ohio's economy, the opportunity for further investment and growth is questionable though. The trend
40 Illustration 6: Employment Trends in Ohio Aerospace (Ohio Department of Development 2006)
does not look good statewide as the infusion of capital and financing has actually been steadily going down. Illustration 7 (below) demonstrates the downward trend in investment dollars for this industry through 2006. There are several factors that could be driving this trend including the current recession, credit tightening, offshore investing, and a move back to reality after the venture capital bubble in 1999-2000. The Ohio trend is actually not that far off from the national capital investment for the years from 2001 through 2006, and according to Pricewaterhouse
41 Coopers, venture capital investing in 2009 was at its lowest level in more than a decade
(Pricewaterhouse Coopers 2010).
Illustration 7: Investment Trends in Ohio Aerospace (Ohio Department of Development 2006)
What does this mean going forward for the State of Ohio and the aerospace-and-aviation related industries? Obviously, the State of Ohio knows where its strengths lie as it continues to promote the importance of the aerospace-and-aviation industries. And with its clustering initiatives in place and Third Frontier Programs providing the necessary impetus to move forward with riskier ventures and research-backed initiatives, these core industries of Ohio will continue to provide the backbone and provide offshoot opportunities moving into the future. In addition, moving
42 further into this paper, there are some recommendations that the State, Counties, and other vested parties can implement to continue to drive these key industries.
Illustration 8: Aerospace Across Ohio (Ohio Department of Development 2006)
43 Brief History of Aviation/Avionics in Dayton and Greene County
As discussed in the previous section, the importance of aviation and aviation-related industries in the State of Ohio cannot be understated, but for the case of Greene County and the Dayton area it is even more important. The City of Dayton and the surrounding area is rich in aviation, and aviation-related history. The most important of these historical mentions is the home of Wilbur and Orville Wright, the founding fathers of aviation. It was in the west side of Dayton where the
Wright Brothers had a bicycle shop (Illustration 9) that eventually became their workshop for developing the first functional airplane. In addition to the Wright Brothers' bicycle shop and complex there are three other registered historical sites throughout the area that lend to the aviation heritage. These sites include Hoover Block Printing Shop, Huffman Prairie Flying
Field, and the Wright Flyer III, which is housed at the Wright Brothers Aviation Museum.
Illustration 9: The Wright Brothers Cycle Shop (Courtesy Aviation Trail Inc. 2009)
44 These aviation heritage sites are so numerous throughout the area that the “Dayton Aviation
Trail” was established in 1981 (Aviation Trail Inc 2009). This auto trail connects all of the aviation related artifacts throughout the area and condenses them into a trip back into history.
The list of attractions are noted below in Illustration 10 and display the importance of aviation to the history of Dayton.
Illustration 10: Aviation Trail Map (Courtesy Aviation Trail Inc.2009)
45 Today, Dayton and the surrounding area is home to a multitude of aviation-related industries and institutions that are of vital national and international importance. The most important of these is
Wright-Patterson Air Force Base (WPAFB). With Huffman Prairie (where the Wright Brothers conducted many test flights) right in the middle of the installation, Wright-Patterson Air Force
Base has a long history that goes all the way back to the Wright Brothers. The base is located primarily in Greene County.
Wright-Patterson Air Force Base originally established itself as a pilot training school right along the Huffman Field Prairie where the Wright Brothers conducted experimental flights. It was during World War I that the airfield really began to flourish with the training school and logistics coordination playing big roles at the base (88th Comptroller Squadron 2008).
In 1948, Wright Field merged with Patterson Field (named after Frank Patterson, who died in flight crash test in 1918) and Wright-Patterson AFB formally came to be. Today, it is home to approximately 25,000 employees making it the fifth largest employer in the State of Ohio
(Marcoa Publishing 2010). Contained at WPAFB are several divisions of the Air Force, including the Air Force Material Command (AFMC), the Aeronautical Systems Center (ASC), the Air Force Research Laboratory (AFRL), the Air Force Security Assistance Center (AFSAC), the Air Force Institute of Technology (AFIT), and the National Air and Space Intelligence
Center (NASIC) (88th Comptroller Squadron 2008). The level of research and development that comes out of WPAFB and the importance that it has to the Dayton area and Greene County is obvious – see Illustration 11 below. This will be readily apparent as we delve into the economic
46 analysis of the area. The next few sections will look at other areas of the country that have a heavy focus on aviation-related research and industry.
Illustration 11: Ohio County DOD Contracts (Ohio Department of Development 2006)
Albuquerque, New Mexico – Sandia Science and Technology Park
Sandia Science and Technology Park was founded in 1998 in Albuquerque, New Mexico, near
Kirtland Air Force Base. It is a 200-plus acre technology park that is affiliated with Sandia
National Laboratories, which is a U.S. Department of Energy research and development lab. The park boasts a strong public-private partnership and a wealth of support at the local, state, and federal levels.
47 Currently the park is home to 29 companies housed in 18 buildings in the campus-like setting.
Sandia Science and Technology Parks has produced 2,111 jobs and 5,441 indirect jobs. The park has also had a major impact on salaries and wages which have been attributed to park activities totaling $1,456,085, 248.
The park is developed using 67 acres of a 240 acre site which abuts the Kirtland Air Force Base.
The land use type is composed entirely of commercial and light industrial/manufacturing.
Tenant profiles range from engineering and research firms, light manufacturing, computer and technical support, modeling and simulation, and nanotechnology, to a credit union, childcare facility, and a museum.
Huntsville, Alabama – Cummings Research Park
Cummings Research Park was founded in 1962 in Huntsville, Alabama covering a mere 162 acres as a partnership between the University of Alabama and Milton K. Cummings, the former president of then Brown Engineering Company. Like Sandia Science and Technology Park,
Cummings also has strong ties to U.S. defense agencies. Over the next several decades, the park grew exponentially due to a wide base of support of local government agencies and public- private partnerships. It is now one of the premiere technology parks in the world.
There are 212 companies that are housed within Cummings Research Park, employing roughly
22,000 workers. The park is spread out in a campus-like setting over 3,800 acres. Company
48 profiles for Cummings Research Park range from engineering and design, computer programming and software, technology support, telecommunications, research and development to educational facilities. Cummings is also limited to commercial and light industrial/manufacturing usage.
Toulouse, France
Toulouse is located in southern France and is home to Airbus. What are some of the circumstances and characteristics that have vaulted it to be one of the world leaders in aerospace engineering, electronics, and software?
Jean-Mar Zuliani discusses the Marshall variables: local labor market, network of specialized producers, learning and innovation, and institutions (Zuliani 2008). As Zuliani states, “this trio particularly influences the crucial element of a Technopole system which consists of the interweaving of the aeronautical, space and electronics sectors with the field of companies specializing in scientific and technical computing” (Zuliani 2008). Ziulani specifically hones in on the skill sets that have been developed throughout the years in this particular region of France.
Ziulani conveys the importance of the “technical bridges” that existed between the aeronautical, space, and automobile electronics in terms of sharing knowledge and expertise, and how the skills needed to perform in one industry were readily transferable to other sectors, and this specifically gave rise to “on-board” systems.
49 Also important to this networking were the various private and public research organizations throughout Toulouse that brought a lot of these ideas and skill sets together. A key player in bringing the private industry and institutions together was the European Research Institute for
Electronic Systems for Transport (IERSET). The IERSET was a private project developed by
Siemens whose goal was to develop synergies amongst the electrical, aeronautical, and software firms throughout Europe. This organization succeeded in bringing a lot of the technical firms throughout Europe together to share knowledge and build up Toulouse as the aeronautical, aerospace, and electronic base of Europe.
Finally, the institutional support provided by the public sector was instrumental in bringing
Toulouse to where it is today. In 2006, there was formal recognition of an “aeronautics, space, and on-board systems” competitive cluster throughout the Toulouse region. Granted, most of the seeds had been sown by the time this formal recognition was levied, but it provided a formal framework on which to continue to grow. The competitive cluster concept, as established by the
Inter-ministerial Delegation for Town and Country Planning and Local Competitiveness
(DIACT), had the goal of mobilizing private firms, research institutions, and government entities to work together to increase the competitiveness of the region (Zuliani 2008).
50 Chapter 5 – Greene County and Southwestern Ohio
This section will detail Greene County, Ohio and the surrounding area of study. In order to produce a quality economic study, due diligence must be conducted on the area of study. This diligence will include an analysis of past and present day demographics, economics, physical and strategic importance, land use throughout the region, and growth opportunities. For this study the surrounding area will encompass the 39 counties throughout southwestern Ohio, southwestern Indiana, and northern Kentucky. The analysis below will contain facts and figures from different areas, but it will provide a general understanding of Greene County and more expansive Southwestern Ohio economy. For the sake of space and time, I will refer to this entire region as “Southwestern Ohio” – but in reality it comprises counties from two neighboring states, including southeastern Indiana and northern Kentucky.
One thing to keep in mind is the pending merge of the Cincinnati and Dayton Metropolitan
Statistical Area (MSA) into one consolidated MSA. This consolidation is anticipated to occur around 2013 and this could have huge financial and perception ramifications moving into the future. This consolidation will be discussed towards the end of this section.
To begin with, I will review Greene County at the micro-level and then zoom out for a larger macro-level review of the Southwestern Ohio region.
51 Illustration 12: 38 County Study Region
Greene County Background
Greene County is named after the Revolutionary War Hero General Nathaniel Greene. Its present day boundaries were established in 1819. Previous to that its boundaries extended all the way to the northern border of the State of Ohio (Greene County 2010). Xenia is the county seat of
Greene County, and ranks third population-wise in the county behind Beavercreek and Fairborn.
Other key jurisdictions in Greene County include Bellbrook, Sugarcreek, Cedarville, and Yellow
Springs.
52 Greene County, Ohio is located in the Miami Valley Region of Ohio as defined by the Miami
Valley Regional Planning Commission. This Miami Valley Region contains four other counties including Montgomery, Darke, Miami, and Preble. From a State of Ohio Department of
Development perspective, it is located in Region 4, along with the counties mentioned earlier, in addition to Shelby, Champaign, Clark, and Clinton. These counties are located in the western portion of the state of Ohio and a few of these counties actually border the state of Indiana.
Greene County does not border any other states.
Illustration 13: Greene County Ohio (Ohio Department of Development)
53 Illustration 14: Greene County Ohio (Ohio Department of Development)
Illustration 15: Miami Valley Region (Miami Valley Regional Planning Commission)
54 Illustration 16: Miami Valley Region (Miami Valley Regional Planning Commission)
In terms of the nucleus of this area, the City of Dayton is the main area of influence over the
Miami Valley Region and is located some eight miles from the Greene County line to the west.
To the southwest is the City of Cincinnati and it is located approximately forty-five miles going south on US Interstate 75.
Greene County and Miami Valley Demographics
With its proximity to Dayton, Greene County is a bedroom community for the City of Dayton and has steadily grown in population over the past few decades. The year 2000 population stood at 147,886 based on census data (Ohio Department of Development - Office of Policy, Research and Strategic Planning 2008a). The estimated population for 2007 was projected to be 154,656
(Ohio Department of Development - Office of Policy, Research and Strategic Planning 2008a).
55 Greene County seems to be the recipient of the population drain that is taking place within the
City of Dayton and Montgomery County.
While the population growth rate of Greene County trends upward slightly (Illustration 18), the same cannot be said for Montgomery County. From 1990 to 2000 the population of
Montgomery County decreased approximately -2.5%, while the Greene County population has increased 8.2% (Ohio Department of Development - Office of Policy, Research and Strategic
Planning 2008a). The downward population trend in Montgomery County has been ongoing since 1970 (Illustration 17).
Illustration 17: Montgomery County Population Trend (ODD 2008)
56 Illustration 18: Greene County Population Trend (ODD 2008)
In reviewing the population trends of the entire Miami Valley (area outlined in Illustration 16) there is a steady to flat trend in population. For the time period from 1990 to 2000 the Miami
Valley has seen a 3.9% increase in population, and population projections actually show the region losing population from 2010 to 2030 – Illustration 19 (Miami Valley Regional Valley
Planning Commission 2008).
57 Illustration 19: Miami Valley Population Trend (Miami Valley Regional Planning Commission 2008)
Physical Characteristics and Land Use
The land characteristics of Greene County and the surrounding area are generally flat. With rolling hills and two main tributaries of water that flow through the area – the Little Miami River and the Great Miami River – the area is awash in important watersheds that feed into the Ohio
River. The regional land use breakdown is as follows:
1. Residential – 65% 2. Public Facility – 19% 3. Commercial – 9% 4. Industrial – 4% 5. Schools – 2% 6. Water and Wastewater – 1%
58 In terms of the development potential of the region, 23.7% of regional land is developable, while
36.6% is undevelopable (Miami Valley Regional Valley Planning Commission 2008).
Transportation
Greene County and the Miami Valley Region are connected to surrounding counties via a robust interstate network. There are several national highways that run in close proximity to Greene
County and surrounding environs. Interstate 70 runs east/west, while interstate 75 runs north/south connecting with Cincinnati approximately 45 miles to the south. A connector interstate – interstate 675 – runs to the southeast of Dayton and connects I-75 to I-70. This connector runs right through Greene County. In fact, over 60% of the region’s industrial land is located within one mile of a major highway, and 49.5% is located within one mile of I-75
(Miami Valley Regional Valley Planning Commission 2008).
Mass transit options are available throughout the Greater Dayton metropolitan area and these are provided by Greater Dayton Regional Transit Authority. Service is provided into adjoining counties including Greene County.
In addition, alternative options of transit are available through an extensive bike path that extends throughout Dayton and the rest of the region, including Cincinnati. There is a local/regional bikeway plan that extends all the way down to the Ohio River from Yellow
Springs, Ohio in Greene County. This bike path is known as the Little Miami Scenic Trail and there are networks of this bike path that extend through the surrounding counties.
59 Physical connectivity is always important when discussing industrial clustering and the Greene
County area is well connected to Cincinnati and the surrounding counties. Whether it is auto, rail, or bike, the means are there for the transfer of knowledge and goods.
Economic Characteristics
This overview of the economy will touch on some of the high-level characteristics of the Greene
County economy. The Data Analysis section of this report will cover Greene County in much more detail.
The region has been primarily known as a manufacturing center but this has dramatically decreased over the past few decades. Table 5 below shows the decline in manufacturing for
Greene, Miami, Montgomery, and Warren Counties from 1980 to 2005 (Miami Valley Regional
Valley Planning Commission 2008).
Table 5: Manufacturing Employment in Miami Valley (Miami Valley Regional Planning Commission 2008)
1980 1990 2000 2005 Greene 3,852 4,248 5,343 5,384 Miami 14,390 13,700 15,323 14,727 Montgomery 65,461 59,865 59,165 52,454 Warren 3,287 3,271 Regional Total 83,703 77,813 79,831 72,565
60 Higher Education
The educational and research institutions throughout the area are important to moving forward as a progressive region. As discussed in the literature review, there are very distinct advantages for private and public corporations to team with these types institutions. Greene County and the surrounding counties are awash in educational opportunities, plus the research component that goes along with this. According to the 2008 Community Guide published by the Dayton
Development Coalition, there are a total of 23 nationally recognized educational institutions
(Table 6) located throughout both the Cincinnati and Dayton region (Dayton Development
Coalition 2008).
The impact of these institutions upon the Miami Valley and the surrounding region is well documented, both from an economic and competitive perspective. The Southwestern Ohio
Council for Higher Education (SOCHE) is a consortium of twenty-one colleges and universities that are found primarily in ten counties (Butler, Champaign, Clark, Clinton, Darke, Greene,
Miami, Montgomery, Preble, and Warren) of Southwestern Ohio. Together these universities and colleges of SOCHE accounted for $2.95 billion in economic impact on the economy of
Southwestern Ohio (Economics Center for Education and Research - University of Cincinnati
2007). While the economic impact alone is substantial, the human capital that comes out of these institutions cannot be understated, for it is the retention and growth of this human capital that will move Greene County and Southwestern Ohio forward as a community.
61 Table 6: Higher Education - Dayton, Cincinnati (Dayton Development Coalition 2008)
Background of Cincinnati, OH Region
Looking more broadly at the regional economy there are a few items worth noting. This regional overview will be discussed in the following sections and will include the demographic, physical characteristics, transportation, and economic characteristics of the region. The main areas of discussion will be around the Cincinnati MSA (officially the Cincinnati-Middletown OH-KY-IN
62 MSA – referred from this point forward as Cincinnati MSA) and its sphere of influence throughout the regional study area, especially as Cincinnati and Dayton converge to become a consolidated metropolis.
The Cincinnati Metropolitan Statistical Area (MSA) is made up of 15 counties throughout southwestern Ohio, southeastern Indiana, and northern Kentucky (City of Cincinnati Economic
Development 2010). The defined counties of the Cincinnati MSA are highlighted below in
Illustration 20.
Illustration 20: Cincinnati-Middletown OH-KY-IN MSA – 15 County MSA (choosecincy.com 2010)
63 Again, for the purposes of this regional study, I will be reviewing figures from the Cincinnati
MSA and beyond, in addition to counties in and around the Miami Valley Region. There are other counties that are not part of the defined MSA's of Cincinnati and Dayton that will be part of this regional study.
Demographics
The fifteen county Cincinnati MSA is home to approximately 2.1 million people according to
2008 United States census estimates. At the center of this MSA is the City of Cincinnati with a
2007 population estimate of approximately 332,458 people (Ohio Department of Development -
Office of Policy, Research and Strategic Planning 2008a). The City of Cincinnati is in Hamilton
County (which lies in the middle of this MSA) and contains an estimated 2007 population of approximately 842,369. The population trend for Hamilton County is steadily decreasing as more people are moving to outlying counties and beyond – see Illustration 21. For the larger region (four counties – Hamilton, Butler, Warren, and Clermont) the population is trending upward as shown in Illustration 22.
64 Illustration 21: Hamilton County Population Trend (ODD 2008)
Illustration 22: Four County (Hamilton, Warren, Butler, Clermont) Population Trend (ODD 2008)
65 Physical Characteristics and Land Use
The Cincinnati Region is marked by a varied degree of land use. The urban core of the City of
Cincinnati and Hamilton County is marked primarily by office buildings with residential throughout. The story is quite different for the outlying counties, especially if you add Butler,
Warren, and Clermont counties into the mix. Suburban sprawl seems to be the norm, with plenty of cropland and forest making up the land use. The land use figures are delineated below in
Table 7 and 8.
Table 7: Hamilton County Land Use (ODD 2008)
Table 8: Four County (Hamilton, Butler, Warren, Clermont) Land Use (ODD 2008)
66 Transportation
With its access to the Ohio River, in addition to major interstates, railroad networks, and an international airport, Cincinnati is well positioned to participate in the national and international economy. It is within 600 miles or 1 day driving distance of 30 major metropolitan markets
(City of Cincinnati Economic Development 2010) . This proximity to these major markets has allowed Cincinnati to establish itself as a major trading thoroughfare, particularly for the north- south routes from Canada all the way down to Mexico. In fact, Cincinnati is the fifth largest inland port in the United States according to the Cincinnati USA Partnership (City of Cincinnati
Economic Development 2010) .
Cincinnati's location is advantageous because it allows for multi-modal access to the rest of the country. By boat, rail, highway, or plane, there are various options throughout the Cincinnati region. In terms of the highway transportation network that connects Cincinnati to the rest of the country, Cincinnati is in a prime location. In Cincinnati there are three major interstates that converge in close proximity to downtown Cincinnati – interstates 71, 74, and 75. The Ohio
River allows for barge and river access upriver to Pittsburgh and downriver to St. Louis and the
Mississippi.
Economic Characteristics
The service economy seems to be driving the Cincinnati MSA region, with manufacturing on the decline. In order to be competitive, this transition to more of a service-oriented economy must
67 be realized and accommodated by the regional leaders. This mean transitioning displaced workers into educational programs that will help them become more marketable to this changing workforce. Reviewing Table 9 below one can see the preponderance of employees in the healthcare, retail trade, and accommodation/food services industries. From 2001 to 2006 this shift has represented a 19.4% decrease in manufacturing, while in professional services and healthcare there has been an increase of 0.8% and 10.3% respectively for Hamilton County
(Ohio Department of Development - Office of Policy, Research and Strategic Planning 2008b) .
Table 9: Employment by Industry Sector - Cincinnati MSA (County Business Trends 2005)
Industry Sector – Cincinnati MSA Employees Healthcare & Social Assistance 124,672 Manufacturing 120,508 Retail Trade 117,266 Accommodation & Food Services 88,902 Administration & Support 59,223 Professional, Scientific, Technical 55,708 Finance & Insurance 52,710 Wholesale Trade 54,784 Construction 49,689 Other Services 40,820 Transportation & Warehousing 37,349 Management of Companies 25,163 Information 17,092 Educational Services 16,074 Real Estate, Rental, Leasing 14,027 Art, Entertainment, Recreation 13,389 Mining 249 Utilities 217 Forestry, Fishing, Hunting 11
68 In terms of major employers in the area, Cincinnati has six Fortune 500 Corporations headquartered throughout the region (City of Cincinnati Economic Development 2010). These corporations include Kroger, Macy's, Fifth Third Bank, GE Aviation, Procter & Gamble.
Higher Education
Referring back to Illustration 16, one can see the multitude of higher education institutions throughout the region. With the University of Cincinnati as the premier research institution throughout the region, it is complemented by many other institutions including Xavier
University, Northern Kentucky University, Cincinnati State, Miami University, the College of
Mount St. Joseph, and many others. Table 10 shows the enrollment at various colleges and universities throughout the region.
Of particular educational importance going forward, especially to this study, are the fields of science, technology, engineering, and math (STEM). These fields of study are important to creating a region that is able to compete nationally and internationally, plus they offer a multitude of high paying, highly skilled jobs. Illustration 23 shows the number of STEM degrees awarded in the 2007-2008 academic year (United Way of Greater Cincinnati 2008) .
69 Table 10: Enrollment in Area Colleges, Universities, and Vocational Schools (choosecincy.com 2010)
Institution Students University of Cincinnati 39,000 Miami University 21,478 Northern Kentucky University 15,438 Cincinnati State 10,165 Xavier University 6,966 College of Mount St. Joseph 2,324 Thomas More College 1,858 Great Oaks (Secondary) 8,523 Great Oaks (Post-Secondary) 49,704
Illustration 23: STEM Degrees Awarded - State of the Community Report 2008 (United Way of Greater Cincinnati 2008)
70 Where Does the Region Stand?
After reviewing the preceding demographic and economic indicators, where does Greene County and Southwestern Ohio stand in comparison with the rest of the nation? Taking data from a recent 2008 United Way State of the Community Report and from the above observations, there are some key takeaways from an economic perspective. These takeaways include the following
(United Way of Greater Cincinnati 2008):
• Cincinnati's regional population is growing more slowly than the national average and is
marked by uneven growth;
• Regional unemployment is higher than the national average;
• Business starts are trending in the positive direction.
Table 11 below summarizes the Cincinnati region and some of the key indicators. Again this is provided courtesy of The United Way of Greater Cincinnati.
71 Table 11: Key Economic Indicators - State of the Community Report 2008 (United Way of Greater Cincinnati 2008)
Chapter 6 – Methodology
The main purpose of this study is to identify the potential industrial clusters throughout Greene
County, and then more largely, how they interrelate with the rest of the Cincinnati/Dayton
Metropolitan Region. More specifically, I would like to make a case for the avionics cluster within this region. Hence the title of my thesis is: A Case for Avionics in Greene County and
Southwestern Ohio. This study requires a thorough review of the economic data of Greene
County, as well as data that shows the interrelationships and linkages amongst Greene County industries and other industries throughout the thirty-eight county study area.
Relying primarily on secondary source data to drive this project, this data will be analyzed and run through a thorough process to determine what clusters are mature versus those that are still in
72 the developing phases. The following will cover each step in the data collection and analysis process that will eventually lead up to my identification of the industrial clusters that are present throughout Greene County and the surrounding counties. The following components regarding the data will be reviewed throughout this section, they include:
• Project Details and Study Area • Data Collection Methods and Sources • Analytical Techniques • Limitations of Data and Other Considerations • The Creation of the Avionics Cluster • Summary
Project Details and Study Area
Industrial clusters are an important consideration of economic development. There is a good deal of discussion as to how much consideration should be placed into the notion of economic development focusing on these industrial clusters. To begin with, Michael Porter defines industrial clusters as:
“Clusters are geographic concentrations of inter-connected companies and institutions in a particular field. Clusters encompass an array of linked industries and other entities important to competition. They include, for example, suppliers of specialized inputs such as components, machinery, and services, and providers of specialized infrastructure. Clusters also often extend downstream to channels and customers and laterally to manufacturers of complementary products and to companies in industries related by skills, technologies or common inputs. Finally, many clusters include governmental and other institutions --- such as universities, standard-setting agencies, think tanks, vocational training providers, and trade associations --- that provide specialized training, education, information, research, and technical support.”(Porter 1998)
73 Along with this conceptual definition comes the development of some actual templates that represent proposed clusters. Edward Feser and Edward Bergman identify 23 United States manufacturing cluster templates based on SIC codes that can be used as a guide in developing strategy and policy at the state and local levels (Feser and Bergman 2000). Taking this one step further to incorporate NAICS codes to identify cluster templates, a group from the University of
Cincinnati identified 61 national cluster templates that can be used to formulate regional industrial strategy and policy based on those templates (Kelton, Pasquale, and Rebelein 2008).
These templates will be used to analyze potential industry clusters in Greene County based on employment data. Linkages between these cluster industries and the surrounding counties will be shown using input/output data from IMPLAN.
Illustration 24: 38 County Study Area and Greene County
74 The study area consists of 38 counties (Illustration 24) throughout Southwestern Ohio,
Southeastern Indiana, and Northern Kentucky. Drilling down I will be looking specifically at employment and economic data from Greene County, Ohio. Greene County is a suburban/semi- rural county located approximately 15 miles from downtown Dayton, Ohio. The counties of study are illustrated above in Illustration 24, with a further drill down into Greene County.
Data Collection Methods and Sources
The majority of the data for this analysis comes from secondary source data. The data points that
I am using for this study range from 1992 – 2007. The two main points of data include employment by industry code for Greene County, and then IMPLAN data for Greene County alone, and IMPLAN data for the 38 county region. To obtain the employment data from the
Bureau of Labor and Statistics I simply had to download the 1992, 1997, 2002, and 2007 data from the Bureau of Labor and Statistics website. The data was then massaged and cleansed into a more relevant, readable format using Microsoft Excel. The 2006 IMPLAN data was provided to me by Professor vom Hofe as part of the Spring 2009 studio. IMPLAN data is developed by an organization called the Minnesota IMPLAN Group. The employment data for Greene
County and the IMPLAN data will be used to accomplish a variety of goals which are summarized below:
75 Employment Data for Greene County
The Bureau of Labor Statistics Quarterly Census of Employment and Wages Data (BLS) and IMPLAN data will be used to complete the analysis (Bureau of Labor Statistics
2009). Using average annual employment data for Greene County from the BLS for the years 1992, 1997, 2002, and 2007, I will calculate location quotients, track shift share analysis, and track employment trends. All of these methods can be used to analyze the economic base of a specific city, county, state, or region. Local industries were analyzed using the North American Industry Classification Systems (NAICS) at the three-digit level for most industries, with the exception of the scientific and research sector, which was analyzed at the four-digit level.
IMPLAN Data
IMPLAN data at the county level was obtained from Professor vom Hofe. This data is costly to obtain and requires commercial software, but as part of our collaboration and guidance from Professor vom Hofe he was able to run a county level data pull for 38 counties throughout the Cincinnati and Dayton Region (see figure 1 for counties included in this study). IMPLAN data provides buying and selling transactional data for up to 509 industries based on NAICS codes. This data captures those patterns at a certain point in time and is therefore static.
76 First, an analysis of Greene County IMPLAN data alone was performed to see what local
industries were interacting with each other. Secondly, an analysis of the IMPLAN
regional data was performed to determine inter-industry transactions. This data was then
used to calculate backward and forward linkages among local industries based on their
buying and selling patterns. In addition, multipliers will be calculated from this data as
well.
Analytical Techniques - Economic Base Analysis
Economic base analysis operates on the assumption that all economic activity within a region can be divided into two broad sectors: basic and non-basic. The basic sector is oriented toward export to markets outside the local economy. Non-basic industries rely on meeting the needs of local consumers. The basic sector is believed to drive economic growth by bringing new flows of revenue into the local economy, which is then circulated to support local businesses and create new jobs, which then re-circulates dollars further, creating a multiplier effect (Klosterman 1990).
Economic base analysis relies on location quotient analysis and shift-share analysis.
Location Quotient Analysis
In order to identify “basic” industries, local employment is compared to a larger reference
region such as the state or the nation. If five percent of the nation’s employment is in the
steel industry, for example, and the region’s steel employment is eight percent, then three
77 percent of the region’s steel employment is said to be basic. This is calculated using the formula for the location quotient, shown below.
When a region contains basic or export-oriented employment, it is said to be specialized in those industries. To determine the degree of industrial specialization in Greene
County, location quotients were calculated for as many as 76 separate industries for the years of 1992, 1997, 2002, and 2007. I initially compared local employment in each industry to two reference regions – Ohio and the United States – before settling on the nation as the basis for comparison.
Location Quotient Formula
ei = Local employment in industry i e = Total local employment Ei = Reference area employment in industry i E = Total reference area employment
Shift Share Analysis
Location quotients provide a way to understand a local economy's strengths and weaknesses, but they do not explain how changes occur over time or describe the way local economic performance differs from the nation. Using shift-share analysis, we are better able to explain changes in a local economy by breaking it down in terms of three
78 major elements: national share, industry share, and regional share. Shift-share analysis
can be written as:
share change + mix change + shift change.
Shift-Share Formula
ei = total regional employment in a given industry e = total regional employment Ei = total national employment in a given industry E = total national employment t = initial point in time t + n = later point in time
By calculating shift-share, industrial growth or decline can be examined and attributed to
a particular trend. Shift-share analysis is a dynamic measure of how the economy
changes over time. Changes in Greene County’s employment by industrial sector were
calculated comparing three five-year time periods: 1992-1997, 1997-2002, and 2002-
2007. In the analysis, I looked at the shift change in regional growth, which measures
local industry performance compared to the national average.
79 The resulting location quotients and shift-share numbers for each specific industry were
then run through the following McLean-Voytek decision tree (Illustration 25) to
determine where that specific industry falls in the scheme of the overall county business
trends (McLean and Voytek 1992).
Illustration 25: McLean and Voytek Decision Tree (Matthew Fischer and Assoc)
80 Limitations of the Data and Other Considerations
There are obviously limitations to using strictly quantitative data to support a specific project or analysis. The data that I am using to conduct my study does not consider the qualitative aspects of industries and firms within Greene County and surrounding counties. These qualitative aspects can have a significant consideration into how these firms do or do not interact with each other. Due to time and resource constraints the qualitative aspects of firm interaction were not included as part of this study, but they are worth mentioning and should be considered when formulating policy, programs, and strategies moving forward. A qualitative study of Greene
County and the surrounding region would be a logical next step.
Another limitation is the static nature of the data. Both BLS and IMPLAN data are static data collection methods that do not take into consideration the natural ebbs and tides of a local and regional economy. This does not mean that a study of this type is faulty, but this aspect also needs to be discussed when digesting the result of this analysis.
Besides the empirical analysis, there are examples in the literature review of how industrial cluster analysis has been used effectively and ineffectively in economic development. These examples need to be kept in mind when moving forward with the development and analysis of
Greene County and Southwestern Ohio.
81 The Clusters and Creation of an Avionics Cluster
Unfortunately, an “avionics cluster template” does not already exist, so it was created using existing templates. These templates were discussed in the literature review. The avionics cluster was built from a combination of existing national cluster templates, including “aircraft components,” “advanced electronic systems and components,” “information and technology services,” “telecommunications,” and “electrical equipment.” The following industries were determined to be relevant to avionics based on components of related clusters:
• Fabricated Metal Product Manufacturing • Primary Metal Manufacturing • Machinery Manufacturing • Computers and Electronic Components • Electrical Equipment • Transportation Equipment Manufacturing • Professional Services o Legal services o Accounting/Bookkeeping o Architectural/Engineering o Specialized design services o Computer design o Management and tech consulting o Scientific R&D o Advertising o Other Prof Services • Repair and Maintenance
The next section will provide the results of the data collection and analysis that are discussed in this section.
82 Chapter 7 – Data Observations and Analysis
This chapter will focus on the data analysis using the methodology that was described in Chapter
6. It will be presented in two parts: Part 1 will present the data analysis of Greene County – the results of running the data through the McLean and Voytek decision tree to determine the spectrum of the various industries in Greene County and the IMPLAN Input/Output Analysis;
Part 2 will present the regional input and output tables. All of the complete data and tables are available in the appendix of this document.
Again, going back to the methodology section the industries that make up the Avionics cluster include the following:
• Fabricated Metal Product Manufacturing • Primary Metal Manufacturing • Machinery Manufacturing • Computers and Electronic Components • Electrical Equipment • Transportation Equipment Manufacturing • Professional Services o Legal services o Accounting/Bookkeeping o Architectural/Engineering o Specialized design services o Computer design o Management and tech consulting o Scientific R&D o Advertising o Other Prof Services • Repair and Maintenance
83 Greene County
Economic Base Analysis – Employment
The base of the Greene County economy was analyzed in terms of employment for the time series 1992-1997, 1997 – 2002, and 2002 – 2007. The top 25 industries in terms of employment, and then their corresponding employment change is noted in Table 13. This is ranked from highest to lowest in terms of 2007 employment. There were a total of 107 industries that were included in the NAICS data pull; industries with fewer than 500 employees were not included in this employment analysis. In addition, Table 12 shows avionics-specific industries and their respective employment levels.
Table 12: Avionics Specific Industries Employment Levels - Greene County
84 Table 13: Top 25 Industries Greene County - Employment/Employment Change 1992 - 2007
85 Economic Base Analysis – Location Quotient
In order to properly populate the McClean/Voytek decision tree, the first component of this analysis will be a review of the location quotient of NAICS industries from 1992 – 2007, looking at three five-year increments, 1992 – 1997, 1997 – 2002, and 2002 – 2007.
This analysis was done at the three digit NAICs level, with a disaggregation at the 541 level.
This disaggregation was done to get a more granular look at the components that make up the
541 industries – or the professional, scientific, and technical industries level – as these appear on the surface to be industries that would make up an avionics cluster. There are a number of industries that comprise this level and they include the following (NAICS Association 2010):
Table 14: Professional Services (NAICS 541) Industries
Accounting and Bookkeeping Architectural and Engineering Specialized design services Computer Systems Design & Svcs Mgmt, Scientific, Tech Consulting Scientific R&D Advertising & Related Svcs Other Prof. Svcs
The graph in Illustration 26 displays the top five industries in terms of location quotient for the time series 1992 – 1997, 1997 – 2002, 2002 – 2007. NAICS Code 928 – National Security and
International Affairs – actually had the highest location quotient at over 40 for the time series
1997 – 2002, 2002 – 2007 (not sure why it did not register in 1992 – 1997). With this high of a location quotient, it made sense to completely remove it from this analysis, as it would skew the
86 entire analysis. In addition, due to the sensitive information of NAICS Code 928, there is no real understanding of what actually comprises this industry code, hence a deeper dive into this is not possible.
Illustration 26: Top 5 Industries by Location Quotient - Greene County
Economic Base Analysis – Shift-Share
The next economic base indicator for Greene County is shift-share. This analysis will provide a determination of where the growth is coming from – whether the growth can be attributed to actual county-wide growth, or if it is coming from state or national growth. In this case the shift share analysis was compared against national growth to obtain the results that are shown in Table
15 . An average shift-share number was obtained from the three time series to obtain the results
87 illustrated below. The top twenty-five industries in terms of shift-share analysis are illustrated below in Table 15.
Table 15: Greene County Shift-Share Analysis
88 Greene County Data and The McLean-Voytek Framework
After gathering the above data, it was run through the McLean-Voytek framework that was discussed in the methodologies section. The purpose of this is to determine which industries in
Greene County are strong, emerging, or weak. The results of that analysis are shown in Table 16 with avionics industries highlighted in yellow. Illustration 27 depicts graphically where each industry that makes up the avionics cluster falls in terms of strong versus weak.
Illustration 27: Avionics Cluster Industry Assessment
89 Table 16: Result of McLean-Voytek Decision Tree Analysis
90 Input-Output Analysis
The next component of a cluster analysis can include the inter-industry linkages amongst the industries in Greene County. Using IMPLAN data, detailed “input-output” tables were generated to identify inter-industrial buying and selling patterns in Greene County. This allowed for the identification of economically related industry clusters as well as “key” industries within clusters. These inter-industry relationships among Greene County industries are considered important, self-reinforcing engines of economic growth. The purpose of analyzing these inter- industry transactions is to determine what industries are buying and selling from each other.
This is important in terms of identifying how strong or how weak a cluster’s potential can be – these are the linkages. In addition, multipliers can be determined from an input/output analysis.
These will be discussed and analyzed below.
Linkages
Economic transactions between industries within the local and regional economy were
considered in order to determine how industries should be grouped into a particular
industrial cluster. Industrial linkages within the county were calculated by using the
input-output table, based on 2006 IMPLAN data from Greene County. These
calculations illustrate the extent that industries bought and sold from one another.
Financial flows create economic multipliers, which will be described in more detail in the
following section. Forward linkages indicate industries which sell or provide products or
services; backward linkages indicate industries which purchase services or products.
91 Of the 81 (there is some conversion that takes place between NAICS codes and IMPLAN data that reduces industries to 81 in the input/output table) industries that exist in Greene
County, the industries listed in Tables 17-20 have strong forward and backward linkages.
These linkages indicate the presence of robust buying and selling relationships with other local firms. Tables 17-20 show the backward and forward linkages for all the industries that are greater than the average backward and forward multipliers. Illustration 28 shows graphically the buying and selling relationships for the proposed avionics cluster.
Illustration 28: Greene County Buying-Selling Relationship - Avionics
92 Table 17: Backward and Forward Linkages - Greene County
Table 18: Backward and Forward Linkages - Greene County
93 Table 19: Backward and Forward Linkages - Greene County
Table 20: Backward and Forward Linkages - Greene County
94 Multipliers
The multiplier effect shows how much an initial stimulus in the economy will multiply the output of industries in that economy. For example, if an industry has a multiplier of
1.5, that will mean that if there is an investment of $100 in that industry, the multiplier effect will cause the output to be 1.5 times as much. Thus, the total output after the stimulus is $150. Multipliers allow for the identification of industries that have a major economic impact on the area’s economy.
With the model avionics cluster developed, it is possible to predict how stimulating one industry in the cluster would affect employment in the other related industries. Using the
2006 IMPLAN inter-industry transaction accounts data (i.e., all selling and buying that took place among industries) multipliers were calculated based on buying and selling relationships within Greene County’s emerging avionics cluster.
The eight industry sectors comprising the avionics cluster were emphasized in the analysis. They are as follows and the respective multipliers are displayed in Table 22:
• Primary Metal Manufacturing
• Fabricated Metal Production
• Machinery Manufacturing
• Computer and Other Electronics
• Electrical Equipment and Appliances
• Transportation Equipment
95 • Professional (Scientific and Technical Services)
• Repair and Maintenance
Several steps were taken to calculate the multipliers. First, the original IMPLAN inter-
industry transactions were entered. Industry columns show buying patterns, and rows
show selling patterns. The intersections show the fraction each industry is spending in all
other industries. Next, the matrix was inverted to create what is known as the alpha
matrix. The alpha matrix provides partial and total multipliers for all industries. Greene
County’s eight-industry avionics cluster multiplier matrix is shown in Table 21.
Table 21: Avionic Multipliers for Greene County - IMPLAN 2006
Clustering in Greene County
After the local analysis has been conducted, what does the data suggest in terms of clustering in
Greene County? The bottom line is that there are definitely strengths in terms of the industries
96 that would make up an avionics cluster. Based on the overall analysis, the avionics cluster could be placed into a middle tier to emerging cluster. Illustration 29 displays where the proposed avionics cluster would fall if compared against other clusters in Greene County.
Illustration 29: The Industrial Cluster Continuum - Greene County
Region-Wide Analysis
An input/output analysis was conducted to determine the strengths of certain industries within the entire region. This region wide analysis can then be compared with the Greene County input/output analysis to determine how strong or how weak the region plus Greene County performs in certain buying and selling relationships for numerous industries. If after conducting the input/output analysis for the region it can be identified that certain industries within the cluster templates are strong, weak, or emerging, then policy can be structured to enable cluster- based economic development throughout the region.
97 Clustering in the Region
The cluster analysis was expanded to incorporate the entire Cincinnati-Dayton corridor because economic boundaries do not necessarily correspond with political boundaries. Therefore,
IMPLAN data was gathered for the region. The Direct Requirements Matrix was used to help identify inter-industry buying and selling patterns. The Direct Requirements Matrix is composed of technical coefficients, which is the ratio of an inter-industry transaction and the total input. In this analysis a strong buying or selling pattern was considered to be above the average. Within the avionics cluster, some industries had above average technical coefficients with other industries in the cluster in terms of selling.
The following industries interacted most (selling) with other industries in the cluster:
811 – Repair and Maintenance 333 – Machinery Manufacturing 331 – Primary Metal Manufacturing
The industries that had strong forward interactions and already have a strong presence in the region are:
541 – Professional Services 334 – Computers and Electronic Components
And the following industries bought the most from other industries in the avionics cluster and are currently emerging in the region:
335 – Electrical Equipment 336 – Transportation
98 The regional conclusions were then compared to the local analysis in an attempt to analyze which industries are most needed in the area to create an avionics cluster, and which industries already have a strong presence in Greene County.
Locally, the following industries had the most above average technical coefficients in terms of selling:
811 – Repair and Maintenance 333 – Machinery Manufacturing 334 – Computers and Electronic Components
The industries that had strong forward interactions and already have a strong presence in the region are:
541 – Professional Services 332 – Fabricated Metal Products [strong in buying] 334 – Computers and Electronic Components
And the following industries are bought the most from other industries in the avionics cluster and are currently emerging in the region:
335 – Electrical Equipment 336 – Transportation
The Value of Qualitative Analysis
A qualitative analysis with Greene County officials would be a logical next step in this analytical process. Some questions that may be considered in terms of the overall workforce and development of the region include:
99 • Do Wright-Patterson military personnel remain in the region when they retire from
service?
• Do they tend to start second careers in the private sector related to aviation?
• Are there retention efforts to keep them in the area?
• How many and what kinds of civic and local business associations exist in the region
related to avionics?
• How large and active is the membership of these associations?
• How frequently do these associations meet, and are they more formal or informal?
Chapter 8 – Recommendations
Based on the preceding analysis, Greene County, the Miami Valley Region, and the entire
Southwest Ohio Region should move forward with their focus on an avionics cluster. There are, however, some caveats that should be considered. The following section will present some recommended policies and strategies that could propel the region toward this cluster in a more efficient manner. There are five main points that merit attention and these include:
1. Incentives
2. Collaboration
3. Industrial Synergies
4. Workforce Training and Retention
5. Place-Based Marketing Initiatives
100 Incentives
Incentives are economic development tools which are used to entice businesses and firms to locate in the local economy. Incentives can come in the form of improved infrastructure, buildings, tax credits, or workforce training. The usefulness of incentives is heavily debated in the literature, but nonetheless incentives can help create a ‘friendly business climate’ in the local economy. Secondly, it is important that the incentives used can be clearly differentiated from the packages offered by other local economies and states. Once a cluster is well developed, government incentives will not play the same role because the specialized labor market, the input supply, and the market itself will serve as business incentives.
Incentives which may prove useful in Greene County include tax increment financing (TIF's), tax abatements, technology investment tax credit, Edison Incubators, the business development
412 program, and workforce training. TIF's can work in a variety of ways, but are mostly commonly used to improve infrastructure. This is done by declaring an area a TIF district. Loans are used to build the new infrastructure, which ideally improves the value of the area. The current property values and tax rates are frozen for all other areas in the district. Any tax increase is assumed to be as a result of the improvements and thus is used to repay the loans.
Tax abatements are used to decrease the total costs of a firm. Tax abatements provide lower tax rates to companies for locating in the area. There are a variety of tax abatements, and discussion of the abatement that will best fit an avionics development should be carried on between the
101 stakeholder interests. For tax abatements, all upfront clawbacks can be used to insure that the corporation does not relocate after the abatements and funding is provided.
Technology investment tax credit, which includes tax credits at the state level, provides benefits to tax payers who invest in small technology-oriented businesses. Edison incubators provide business advice and skills training to start up programs. This program is organized by the Ohio
Department of Development. The business development 412 program provides funding for infrastructure development that is deemed to be environmentally sustainable or energy efficient.
Workforce training is another incentive which provides a skilled labor force and ultimately decreases labor training costs.
Careful consideration must be given to incentives as an economic development tool as the need to grow as a region must be kept in mind. Leaders need to consider that playing off one jurisdiction against another only hurts the region in the long run, thus collaborative agreements need to be structured to benefit the entire area. If industries and businesses are drawn to the region out of a need to get engaged in this avionics cluster development, then there needs to be a way to get all parties involved. The creation of joint economic development districts (JEDD) might be one way to encourage cooperation amongst neighboring jurisdictions. The JEDD tool allows partnering jurisdictions to share in the incremental tax revenues that are created by new business and development.
102 Collaboration
Collaborative efforts among government, universities, and industries are imperative to growing the avionics sector in Greene County and the surrounding region. The cooperation of these three entities is necessary to foster a relationship that benefits all parties. As seen in the case studies of
San Diego and Austin, it took a joint effort amongst the private and public sectors to drive those cluster economies.
Government
Local, state, and federal entities need to be proactive business partners with universities
and industries throughout the study area, both in terms of retaining and recruiting existing
and new employers to the region. Cluster-based development initiatives taken on by the
local government shows a sophisticated understanding of economic development.
Universities
Local and regional universities can play an active role in providing an incubator approach
to nurturing new firms and ideas, in addition to developing human capital. Developing
curricula and research programs that feed directly into these clusters will provide a talent
pool and improve the reputations of local institutions of higher learning.
Industry
Industries need to establish themselves as part of the community. By working
cooperatively with both the government and universities, they can gain legitimacy in the
region. Cooperative programs that engage Wright State, Sinclair Community College,
103 and other local colleges and universities will keep young graduates in the region and
provide talent from which to build companies. In addition, Wright Patterson Air Force
Base is a research institution that should be included in any avionics planning. Active
recruitment of early Air Force retirees could prove beneficial to avionics firms.
Industrial Synergies
Natural synergies need to be encouraged as well as the nurturing of growing or emerging cluster industries. This means that the identification of the strong performers, emerging performers, and weak performers from the data analysis is very important. Moving forward with policies and programs that take advantage of these natural synergies while assisting the weaker or emerging performers can be helpful. The following analysis looks at the strengths, weaknesses, opportunities, and threats that may impact these industrial synergies going forward. The analysis draws from the data observations that were presented in Chapter 7.
Strengths
The Professional and Computer Products Manufacturing sector is locally strong which
will benefit avionics formation. Locally, these industries have high employment and
return on investment. The Professional Services sector has a substantially high
employment in Greene County with 6,856 and has been increasing substantially since
2002 (see Table 12 and 13). Professional Services also has strong presence in the
104 economy as it is economically active in the Miami Valley. The buying and selling transactions among the industries in Greene County were used to determine the linkages.
As a service-oriented industry, the development of avionics would benefit from Greene
County’s strong Professional Services sector. The Computer and Electronic Product
Manufacturing sector also has a relatively high multiplier and strong buying presence.
This sector will provide the technological support needed for an avionics cluster development.
Weaknesses
The overall decline of the manufacturing industry in both the Dayton and Cincinnati region continues to be an area of concern. With the continued shutdown of automobile plants and the impact that this has on ancillary industries, the manufacturing component continues to decline. Until there are other secondary or tertiary industries that can back- fill the strong manufacturing component that is part of Southwestern Ohio's economy this will always be a weakness.
Opportunities
Repair and Maintenance and Transportation Equipment Manufacturing are industries that are not strong performers in Greene County, but they are economically strong regionally. Transportation Equipment Manufacturing has a multiplier of 1.14 with 897 employees. It is considered a constrained performer as a result of its growth patterns
105 analyzed in the shift-share analysis. This sector lost employment between 2002 and 2007; however, investment in this sector will yield a return 1.14 times the initial investment indicating that investment may help this sector grow. Regionally this sector is emerging.
Potential federal funding in transportation development may be beneficial to the formation of avionics cluster development. Repair and Maintenance has a higher multiplier than the Transportation Equipment Manufacturing sector (1.20) as well as a strong service-oriented presence in the economy. Avionics will require a substantial amount of support from Repair and Maintenance so this industry’s high economic potential in the county is an excellent indicator for the successful development of the avionics cluster.
These four industries (Professional Services, Computer and Electronic Manufacturing,
Repair and Maintenance, and Transportation Equipment Manufacturing) can collaborate for the benefit of the county and the development of an avionics sector. The collaboration of these industries will capitalize on the strengths of the industries locally in Greene
County as well as tap into the regional strengths of Southwestern Ohio.
Threats
The continued recession will be an ongoing threat. There are signs that the State and National economies are bouncing back, but fears of a double dip recession remain intact. Another direct impact of the recession has been the loss of thousands of manufacturing jobs in the Southwestern
Ohio Region. These jobs could be gone forever, and it is going to take a huge regional effort to bring them back in a way that could contribute to the future success of avionics and aerospace.
106 Workforce Training and Retention
A critical component of economic development is the skills and training of the workforce.
Avionics is a technical and research oriented field with a strong mechanical component. Many of the cutting edge innovations in avionics are emerging from the development of military applications. Greene County is exceptionally fortunate to be home to a number of well regarded universities and colleges, as well as the Wright-Patterson Air Force Base, where a considerable portion of the nation’s military aviation research is being conducted.
One of the major challenges in the region is the loss of manufacturing employment. The current economic crisis has only accelerated trends of industrial decline in the Unites States, hitting traditional manufacturing states like Ohio particularly hard. Considering these assets and challenges, it is recommended that the following workforce development and retention strategies to support a regional avionics industrial cluster are implemented.
Partner with Local Universities and Technical Colleges
• Strengthen current partnerships and seek out new links with regional colleges and
universities, not only with researchers in scientific and information technology, but also
in support and technical fields, such as electronics repair, mechanic training, and others.
In addition, promote internships in aviation and avionics-related companies.
• Explore ways to retain new graduates from regional schools to work and live in Greene
County through amenities that appeal to young people and those starting new families.
107 • Collaborate with local universities to develop programs geared toward younger students,
focusing on minority and low-income students to generate excitement in aviation,
science, and math.
Partnerships with Wright-Patterson Air Force Base
• Take advantage of the skills, leadership, and contacts of former military personnel by
providing incubation and start-up support for those retiring from service and looking to
begin second careers in the private sector.
• Support development of the kinds of amenities and quality of life priorities that would
convince military retirees to remain in Greene County after their service ends.
Integration of Displaced Manufacturing Workers
• Employment in Greene County’s struggling transportation manufacturing sector has been
declining, but still represented nearly 1000 local jobs in 2007 (BLS). For this reason, it is
important to integrate blue-collar workers into the avionics cluster.
• Consider ways to retrain blue collar workers for semi-skilled jobs in the avionics field, in
partnership with local community colleges and technical schools.
• Explore the possibility of retrofitting facilities and capital equipment to produce
specialized parts or prototypes.
108 Place-Based Marketing Initiatives – Conveying a Sense of Place
The Greene County and Southwestern Ohio area needs to accelerate its efforts to promote the region as an area friendly to business, families, students, and young professionals. This approach is often-times referred to as place-based marketing and involves developing a brand or product image to which these target audiences can relate.
Of course there are the efforts of the various chambers throughout the region, including the
Greater Cincinnati Chamber of Commerce and other organizations like it, but are they going about it in the right way? There are differing opinions on the role of the city in the international framework of today. There can be the approach that cities need to be self-sufficient and meet their demand locally, while there is the other end of the spectrum that espouses complete immersion in the competitive world economy while producing nothing of their own. Both of these views, and the way that the vested organizations approach them can determine a particular city's sense of place and overall success going forward. The important thing is that all of these organizations need to talk the same language and be consistent in the message they are trying to convey about the region.
The need for a balanced approach would seem to make the most sense – an approach that calls for creating and marketing a sense of place that locals are proud to call their home, while maintaining a cooperative and constructive place in the world economy. Some innovative ways to achieve this include:
109 • Social Infrastructure Development – A good example of this is in Vancouver where the
city requires that 5 percent of the value of development to be devoted to this concept,
which could be in many forms including better pedestrian access and public meeting
places (Newman 2009).
• Cooperative Marketing Agreements with Other Communities – Instead of competing
in a zero sum game, work with other communities to share knowledge and establish
“growth coalitions”(Doel and Hubbard 2002).
• Think Outside the Jobs Growth Box – Jobs are important, but long-term growth and
sustainability are vital as well; Table 22 below shows some other important factors
(Kotler and Gertner 2002). A good majority of these draws were identified and
discussed in the demographics section of this paper.
Table 22: Draws for Businesses and Individuals(Kotler 2002)
Local Labour Market Access to customer and supplier markets Availability of development site facilities and infrastructure Transportation Education and training opportunities Quality of life Business climate Access to R&D facilities Capital Availability Taxes and regulations
110 • Brand Consistency – all of the regional groups need to be talking and conveying the
same message, if not confusion could reign among customers and visitors. “Managing the
image” is a term that Kotler and Gertner use in their discussion of countries and their
approach to developing a brand. This approach could no doubt be applied to regions and
cities, and again Kotler states that “to be effective, the desired image must be close to
reality, believable, simple, appealing, and distinctive (Kotler and Gertner 2002).
Matt Haig in his book, “Brand Failures – The Truth About the 100 Biggest Branding
Mistakes of All Time”, identifies seven deadly sins of branding. These sins include
(Haig 2003):
• Brand Amnesia
• Brand Ego
• Brand Megalomania
• Brand Deception
• Brand Fatigue
• Brand Paranoia
• Brand Irrelevance
Obviously these pitfalls and other recommendations above could be applied to any marketing and branding effort, including the marketing and branding of cities and places. It is important to keep these thoughts and strategies in mind when moving forward with any type of marketing effort that promotes the Southwestern Ohio region.
111 Chapter 9 – Conclusion
In bringing this paper to a close there are several items that bear reviewing in terms of the State of Ohio's efforts to identify strategic hubs throughout the state, particularly the one that has been proposed in Dayton. First, I must go back to the few questions that were discussed in the introduction. These questions were the following:
• Why is industrial clustering important for the State of Ohio, specifically in Greene
County and Southwestern Ohio?
• How are potential industrial clusters identified and what are the characteristics of those
clusters in Greene County and Southwestern Ohio?
• What are the logical clusters of the region and where does it make sense to invest?
• What are some of recommendations and strategies that this region could implement to
take advantage of the potential clusters, particularly the avionics and aerospace cluster?
This final section will discuss the key points that were brought to light by the research and study of industrial clustering, as it relates to the questions above.
Why Clustering?
The importance of industrial clustering as a viable economic development strategy is ripe with debate. There are questions around what industries make up a cluster, the size of the study
112 region, the data that is used, among other issues. But let's start with the basic question – why is it important to understand and analyze potential industrial clusters in a region? In an era of scarce resources, particularly in today's competitive environment, there needs to be some understanding of the economy around us to determine where these limited resources will flow. In its economic development efforts, the State of Ohio has decided to embark on an effort to identify core strengths within certain regions of Ohio. While this effort is admirable and shows initiative, it is not quite clear how the state has arrived at some of its decisions. Reviewing the Ohio
Department of Development website simply reveals anecdotal evidence on why certain industries have been identified in certain regions throughout Ohio. There is no real transparency or hard data as to why these industries or regions have been selected (as of today one region has been identified – Dayton for aerospace-and-aviation). I do believe, though, that these types of efforts, regardless of all the infighting among researchers and academicians on definitions and parameters, are useful exercises as they provide focus and initiative going forward. But how do we identity potential industrial clusters? That brings us to our next question – how are these clusters identified?
How Are Potential Clusters Identified?
There are quantitative and qualitative methods in which to identify potential clusters in a region.
For the quantitative component you need to select your study region and the data associated with that region. Then, a simple economic base analysis can be calculated for your region and this should include location quotient and shift-share. Once those analyses are complete, you can run
113 the data through a McLean-Voytek filter to determine where certain industries lie in terms of strong versus weak. From there, the industries that you identify in the McLean-Voytek analysis are then placed into their respective cluster templates, as developed by Feser-Bergman or Kelton et. al. To conduct an even more precise analysis, one can use input-output data that can be obtained from IMPLAN. When used in conjunction with the economic base analysis, the input- output data can provide a strong case for determining which industries are buying and selling with each other in your study region. After completing this process it was determined that an avionics cluster is present in Greene County and Southwestern Ohio, among several other clusters including automotive, construction, and IT support services. The following illustration below (illustration 30) details some of the key clusters in Greene County on a weak to mature continuum.
Illustration 30: The Industrial Cluster Continuum - Greene County
114 Recommendations and Strategies Moving Forward
Finally, after performing the quantitative analysis to understand where the economy of Greene
County and Southwestern Ohio stands in terms of strengths and weaknesses, one can offer up policy recommendations, programs, and strategies to address certain areas of need. In summarizing the recommendations they can be grouped into the following areas (not necessarily in any order of importance):
1. Incentives
2. Collaboration
3. Industrial Synergies
4. Workforce Training and Retention
5. Place-Based Marketing Initiatives
Final Thoughts
With a comprehensive and detailed analysis, in addition to understanding the case studies of several other knowledge-based cluster cities (i.e. San Diego and Austin), economic developers can build strong cases for implementing policy-based economic development initiatives and strategies. Specifically for Greene County and Southwestern Ohio, I have proven that there is justification for moving forward with an avionics and aerospace industrial cluster in the region.
By utilizing this data and capturing some of the key characteristics of other knowledge-based, high technology cluster regions Greene County and Southwestern Ohio should move forward with confidence in attracting other industries and businesses that can contribute to this cluster. In
115 addition, there is the opportunity to build upon these quantitative efforts with a well thought out qualitative component. The next logical step would be to convene with public and private interests to determine how this data corresponds with their day to day operations and how cluster based initiatives like this can get off the ground. In this, I have presented a roadmap to do just that, and to lend more credibility to the State of Ohio's - “Ohio Hubs of Innovation and
Opportunity” (OHIO) efforts moving forward.
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119 Appendix
120 121 122 123 124 125 126 127 128 129 130 131 132 133 134