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Mapping the Geospatial Community


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MAPPING THE GEOSPATIAL COMMUNITY By MATIAS SEBASTIAN CAMPINS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2004

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Copyright 2004 by Matias S. Campins

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To my best friend and partner Heather Campins.

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iv ACKNOWLEDGMENTS There are many people during this long jour ney through my education that I would like to thank; those people who were the bi ggest influences during my studies for my Master of Arts degree are recognized below. I would like to thank my wife, Heather, whom I love with all my heart, for all of her support and help throughout my education and my life. Heather is the person who helped me with the long nights of study and the times that I did not feel like continuing with my education. Her constant support with my decisions and love helped me achieve my goals and dreams. I cannot forget to menti on all her help with ed iting my thesis and all my papers for school. I would also like to thank my parents, Gabriel and Raquel, who have taught me the social aspects of life. Specifically, I would like to thank my mother, Raquel, whose voice always reminds me that I can accomplish anything I decide in life. I cannot forget my brother and sister, Leona rdo and Cynthia, on whom I can always count. Grant Ian Thrall is the person most respons ible for the completion of my Master of Science degree. He gave me the knowledge n ecessary to achieve my goals as a business geographer. Also, it was his en thusiasm for the study of bus iness geography attracted me to the field. I would also like to thank Sc ottie Barnes for all of her assistance with arranging for Dr. Thrall and me to have access to the GeoSpatial Solutions’ database.

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v Finally, to the rest of my graduate committee--Joshua Comenetz, and Rhonda Phillips--I would like to express my gratit ude for their support and enthusiasm. Their support allowed my thesis and my gra duate program to be more enjoyable

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vi TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES...........................................................................................................viii LIST OF FIGURES.............................................................................................................x ABSTRACT.....................................................................................................................xi v CHAPTER 1 INTRODUCTION........................................................................................................1 Geographic Informati on Systems Industry...................................................................1 The Magazine Industry.................................................................................................2 Business Geography.....................................................................................................3 ACORN lifestyle segmentation indices........................................................................8 2 LITERATURE REVIEW...........................................................................................14 3 DATA METHODOLOGY.........................................................................................22 Data Acquisition.........................................................................................................22 Geocoding Results......................................................................................................23 Final Dataset...............................................................................................................24 4 MAPPING THE GEOSPATIAL COMMUNITY......................................................26 Geographic Regions in the US...................................................................................28 Primary Submarket..............................................................................................29 Secondary Submarket..........................................................................................33 Tertiary Submarket..............................................................................................33 GIS Producers.............................................................................................................38 Business Codes....................................................................................................43 Organizational affiliation.............................................................................44 Title codes....................................................................................................44 Corporate Management:......................................................................................48 Operations............................................................................................................50 GIS Firms....................................................................................................................59

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vii 5 SOCIAL-ECONOMIC CORRELATIONS................................................................70 High Concentration Regions.......................................................................................70 Primary Sub Market............................................................................................75 Secondary Sub Market........................................................................................75 Education....................................................................................................................80 Buffer at 10 Miles........................................................................................80 Buffer at 12 Miles........................................................................................83 Buffer at 15 Miles........................................................................................83 Buffer at 18 Miles........................................................................................83 Market Attraction................................................................................................83 Market Attraction at 10 Miles......................................................................88 Market Attraction at 12 Miles......................................................................88 Market Attraction at 15 Miles......................................................................88 Market Attraction at 18 Miles......................................................................89 Firms.........................................................................................................................1 00 Buffer at 7 Miles........................................................................................103 Buffer at 20 Miles......................................................................................103 LSPs at 7 Miles..........................................................................................104 6 CORRELATION OF ANALYSIS WITH INTERNATIONAL GEOGRAPHIC REGIONS.................................................................................................................111 Global Analysis........................................................................................................111 Global Market....................................................................................................111 Europe........................................................................................................112 Asia & Australia.........................................................................................112 Africa..........................................................................................................112 South America............................................................................................115 Canada........................................................................................................115 7 CHARACTERISTICS OF GIS PRODUCERS........................................................120 APPENDIX A GEOGRAPHIC MATCH LEVEL FOR SUBSCRIBERS.......................................124 B GEOGRAPHIC MATCH LEVEL FOR FIRMS......................................................131 C 2000 US CENSUS DATA........................................................................................138 LIST OF REFERENCES.................................................................................................148 BIOGRAPHICAL SKETCH...........................................................................................151

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viii LIST OF TABLES Table page 1. Geocoding match level summary of 27,050 s ubscribers’ first address field from CACI Coder/Plus......................................................................................................24 2. Geocoding match level summary of 27,050 subscribers’ second address field from CACI Coder/Plus.............................................................................................24 3. Geocoding match level summary of 26,024 s ubscribers’ final address field from CACI Coder/Plus......................................................................................................25 4. Geocoding match level summary of top 20 states by number of subscribers from CACI Coder/Plus.............................................................................................28 5. GeoSpatial Solutions’ tertiary s ubmarket counts processed using CACI Coder/Plus (ESRI).........................................................................................33 6. GeoSpatial Solutions ’ percentage of subscribers by state using data from the US Census Bureau..........................................................................................................37 7. GeoSpatial Solutions ’ business code categories using their data set.......................39 8. GeoSpatial Solutions ’ ten business codes groups....................................................43 9. GeoSpatial Solutions ’ title code categories using their data set...............................48 10. GeoSpatial Solution’ corporate management codes.................................................49 11. GeoSpatial Solutions’ information technology (MIS/IS).........................................49 12. GeoSpatial Solutions’ operations codes...................................................................59 13. GeoSpatial Solutions ’ percentage of companies by st ate using data from the US Census Bureau..........................................................................................................64 14. Geocoding match level summary of top 20 metropolitan areas by percentage of subscribers from CACI Coder/Plus..........................................................................70 15. Identification of metropolitan area s by count of subscribers from CACI Coder/Plus......................................................................................................73

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ix 16. GIS market attracted to the education market..........................................................88 17. University ranking of companies market by count based on MSAs........................96 18. GeoSpatial Solutions ’ subscribers LSP’s...............................................................100 19. GeoSpatial Solutions’ firms LSP’s........................................................................101 20. GeoSpatial Solutions’subscribers at 7 and 20 miles radius from companies.........104 21. GeoSpatial Solutions’subscribers LSP’s at 7 miles radius from companies..........107 22. Percent of total companies in each mark et as defined in in ternational maps.........112

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x LIST OF FIGURES Figure page 1. 2001 Worldwide GIS Revenue (Software Only). The figure was compiled in 2002 by Daratech, Inc................................................................................................2 2. Magazine Revenue Sources. This figure was assembled in 1998 by Compaine.......3 3. Timeline for business geographic market an alysis of retail location decisions after 1996 and 1997 by Thrall and del Valle..............................................................5 4. Timeline of location-based mark et analysis by Thrall (2002)...................................6 5. ACORN lifestyle segmentation indices by CACI/Coder Plus...................................8 6. The four types of consumer information. This figure presented in The Insider’s Guide to Demographic Know-How in 1990.............................................................12 7. The advantages of mapping demographi cs and the further analysis possible by Piccilli 1999..............................................................................................................15 8. Survey response statisti cs conducted by Hartung 1997...........................................17 9. GeoSpatial Solutions ’ US market subscribers pro cessed using ArcMap (ESRI)....27 10. GeoSpatial Solutions individual state subscriber s color-coded by state counts processed using ArcMap (ESRI)..............................................................................30 11. GeoSpatial Solutions ’ US market subscribers pe rcent by State using ArcMap (ESRI). ....................................................................................................................31 12. GeoSpatial Solutions ’ three US GIS submarkets processed using ArcMap (ESRI).......................................................................................................................32 13. GeoSpatial Solutions ’ primary submarket processed using ArcMap (ESRI)..........34 14. GeoSpatial Solutions ’ secondary submarket proce ssed using ArcMap (ESRI).......35 15. GeoSpatial Solutions ’ tertiary submarket processed using ArcMap (ESRI)...........36 16. GeoSpatial Solutions ’ percentage rate of subscriber s by state using data from the US Census Bureau....................................................................................................41

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xi 17. GeoSpatial Solutions ’ subscription card..................................................................42 18. GeoSpatial Solutions ’ subscription card..................................................................42 19. GeoSpatial Solutions ’ combined business codes processed with ArcMap..............45 20. GeoSpatial Solutions ’ combined business codes percent by state processed with ArcMap. ....................................................................................................................46 21. GeoSpatial Solutions ’ individual business codes processed with ArcMap..............47 22. GeoSpatial Solutions ’ combined organizational affiliation codes processed with ArcMap. ....................................................................................................................51 23. GeoSpatial Solutions ’ combined organizational affiliation codes percent by state processed with ArcMap............................................................................................52 24. GeoSpatial Solutions ’ individual organizational affiliation codes processed with ArcMap. ....................................................................................................................53 25. GeoSpatial Solutions ’ combined corporate management codes processed with ArcMap. ....................................................................................................................54 26. GeoSpatial Solutions ’ combined corporate management codes percent by state processed with ArcMap............................................................................................55 27. GeoSpatial Solutions ’ individual corporate manage ment codes processed with ArcMap. ....................................................................................................................56 28. GeoSpatial Solutions ’ combined information technology codes processed with ArcMap. ....................................................................................................................57 29. GeoSpatial Solutions ’ combined information technology codes percent by state processed with ArcMap............................................................................................58 30. GeoSpatial Solutions ’ individual information tec hnology codes processed with ArcMap ....................................................................................................................60 31. GeoSpatial Solutions ’ combined operations codes processed with ArcMap...........61 32. GeoSpatial Solutions ’ combined operations codes percent by state processed with ArcMap............................................................................................................62 33. GeoSpatial Solutions ’ individual operations codes processed with ArcMap..........63 34. GeoSpatial Solutions ’ US companies data set processed with ArcMap..................66 35. GeoSpatial Solutions ’ US companies data set percent by state processed with ArcMap. ....................................................................................................................67

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xii 36. GeoSpatial Solutions ’ percentage of companies by st ate using data from the US Census Bureau..........................................................................................................68 37. GeoSpatial Solutions ’ percentage rate of companies by state using data from the US Census Bureau....................................................................................................69 38. GeoSpatial Solutions ’ top metropolitan areas by s ubscribers processed with ArcMap ....................................................................................................................72 39. GeoSpatial Solutions ’ top metropolitan areas by count processed with ArcMap....74 40. GeoSpatial Solutions ’ high concentration areas in Maryland/Virginia processed with ArcMap............................................................................................................76 41. GeoSpatial Solutions ’ high concentration areas in California processed with ArcMap. ....................................................................................................................77 42. GeoSpatial Solutions ’ high concentration areas in Massachusetts/New Hampshire processed with ArcMap.........................................................................78 43. GeoSpatial Solutions ’ high concentration areas in Illinois processed with ArcMap.....................................................................................................................79 44. GeoSpatial Solutions ’ education business code US market processed with ArcMap.....................................................................................................................81 45. GeoSpatial Solutions ’ US education market with a buffer at 10 miles processed with ArcMap............................................................................................................82 46. GeoSpatial Solutions ’ US education market with a buffer at 12 miles processed with ArcMap............................................................................................................84 47. GeoSpatial Solutions ’ US education market with a buffer at 15 miles processed with ArcMap............................................................................................................85 48. GeoSpatial Solutions ’ US education market with a buffer at 18 miles processed with ArcMap............................................................................................................86 49. GeoSpatial Solutions ’ US companies dataset processed with ArcMap...................87 50. GeoSpatial Solutions ’ US education market attr action at 10 miles radius processed with ArcMap............................................................................................90 51. GeoSpatial Solutions ’ US education market attrac tion percentage at 10 miles radius processed with ArcMap.................................................................................91 52. GeoSpatial Solutions ’ US education market attr action at 12 miles radius processed with ArcMap............................................................................................92

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xiii 53. GeoSpatial Solutions ’ US education market attrac tion percentage at 12 miles radius processed with ArcMap.................................................................................93 54. GeoSpatial Solutions ’ US education market attr action at 15 miles radius processed with ArcMap............................................................................................94 55. GeoSpatial Solutions ’ US education market attrac tion percentage at 15 miles radius processed with ArcMap.................................................................................95 56. GeoSpatial Solutions ’ US education market attr action at 18 miles radius processed with ArcMap............................................................................................98 57. GeoSpatial Solutions ’ US education market attrac tion percentage at 18 miles radius processed with ArcMap.................................................................................99 58. GeoSpatial Solutions ’ US firms dataset processed with ArcMap..........................105 59. GeoSpatial Solutions ’ subscriber percentage at 7 miles from companies processed with ArcMap..........................................................................................106 60. GeoSpatial Solutions ’ subscriber percentage at 20 miles from companies processed with ArcMap..........................................................................................108 61. GeoSpatial Solutions ’ subscriber Lifestyle Segmen tation Profiles at 7 miles from companies processed with ArcMap...............................................................110 62. GeoSpatial Solutions global market subscribers’ processed with ArcMap...........113 63. GeoSpatial Solutions global market subscribers’ Europe processed with ArcMap...................................................................................................................114 64. GeoSpatial Solutions global market subscribers’ As ia and Australia processed with ArcMap..........................................................................................................116 65. GeoSpatial Solutions global market subscribers’ Africa processed with ArcMap...................................................................................................................117 66. GeoSpatial Solutions global market subscribers’ South America processed with ArcMap..........................................................................................................118 67. GeoSpatial Solutions global market subscribers’ Canada processed with ArcMap...................................................................................................................119

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xiv Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MAPPING THE GEOSPATIAL COMMUNITY By Matias Sebastian Campins December 2004 Chair: Grant Ian Thrall Major Department: Geography The deployment of Geographic Informa tion Systems (GIS) technology has become virtually spatially ubiquitous within the US during the past decade. However, the GIS production industry is highly concentrated with in a few submarkets of the nation. This has national and even global implications as GIS is estimated today to be a multibilliondollar industry to the US, and even more when global figures are considered. Where is GIS? Where are the submarkets (geographical region s) of GIS production within the US? What are the major socialeconomic correlates between those submarkets with high concentrations of GIS firms? What are the characteristics of GIS firms? Can this information be used to guide other submarkets, including submarkets in other nations, to economic opportunities by focusing on the GIS industry? One of the leading professional pub lications in the GIS industry is GeoSpatial Solutions That publication has made available to Dr. Grant Thrall its entire 30,000 record subscriber database. This database is used as one source of information to answer the

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xv questions posed above. Every December, GeoSpatial Solutions publishes a list of almost every GIS business firm in the US. Thes e databases are used to document and corroborate concentrations of GIS business within a few submarkets. Lastly, socialeconomic data are drawn from the 2000 census and private data vendors, as well as lifestyle segmentation profiles for those GeoSpatial Solutions readers whose publications are delivered to their home addresses. Included among the beneficiaries of this study are Advanstar Inc., owner of GeoSpatial Solutions ; the GIS industry, as the results of this work are co-authored with Dr. Grant Thrall and published in GeoSpatial Solutions and other GIS publications; and, economic development officers at the local, national, and international scale. The National Chamber of Commerce of Sweden, wo rking with the Swedish Embassy to the US, contacted Dr. Thrall, looking for answers to assist with locati ng its subscribers and why they locate in specific areas. With this informati on, it can better understand the characteristics of the market and any corre lation that may exist among the European and US markets. Some of the questions which ar e addressed in this analysis include: where are the submarkets (geographical regions) of GIS production within the US? What are the major social-economic correlates between thos e submarkets with hi gh concentrations of GIS firms? What are the charac teristics of GIS firms? Can this information be used to guide other submarkets, includ ing submarkets in other na tions, to economic opportunities by focusing on the GIS industry? The Chambe r, along with the editorial staff of GeoSpatial Solutions, serve as unofficial outside readers of this thesis.

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1 CHAPTER 1 INTRODUCTION This thesis incorporates Geographic In formation Systems (GIS) principles and business geography Market Analysis practices. This analysis performed on one of the leading professional publications in the GIS industry. The GI S industry is estimated to exceed one billion dollars annua l revenue within the US and even more internationally. Cambridge, MA, November 12, 2002 Worl dwide GIS software revenue reached $1.1 billion in 2001, an outstanding growth of 14.3% over the previous year, according to a just-published market st udy by Daratech, Inc., a Cambridge, MAbased market research and technology asse ssment firm. The largest market for GIS software was the utilities industry, which accounted for 21% of all software revenue, followed closely by state and lo cal governments, the telecommunications industry, and organizations involved in earth resources management. Moreover, GIS software sales drove more than $7.7 billion in total user spending on software and related hardware and se rvices. Indeed, serv ices contributed a whopping $5.4 billion, including $5 billi on from non-core-business vendorscompanies that do not develop GIS applic ations software products. (Daratech, 2002) Geographic Information Systems Industry Clearly, this industry has a national and gl obal impact. Beneficiaries of this study include the magazine industry, such as GeoSpatial Solutions and economic development offices at the local, national, and international scales, such as the National Chamber of Commerce of Sweden. This thesis incorporat es the advances of business geography and GIS to create a study of the GeoSpatial Solutions market. Two industries merged using the technology of Geographic Information Systems (GIS) and the ideas of business geography; “business geography integrates geographic analysis, reasoning and technology for the improvement of the bus iness judgmental decision. Without the

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2 demonstrated ability to improve the busin ess decision, there is no business geography. This differentiates business geography from the traditional descriptive of explanatory objective of economic and urban geography” (Thrall, 2003). Figure 1. 2001 Worldwide GIS Revenue (Softw are Only). The figure was compiled in 2002 by Daratech, Inc. The GIS industry’s net worth is estimated today to be a multibillion-dollar industry to the United States, and more when gl obal figures are considered (Figure 1). The Magazine Industry The magazine industry has approximate re venue of more than $22 billion (cf: newspapers) (Compaine, 1998). This graph re presents where the revenues come for the magazine industry (Figure 2).

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3 Figure 2. Magazine Revenue Sources. This figure was assembled in 1998 by Compaine. Business Geography Business geography is the study and research of a geographic market for various industries, including the retail industry, the ho tel industry, the real estate industry, the publishing industry, the developm ent industry, and the government. The Market Analyst or Business Geographer relies on data availa bility, timeliness, accuracy, and choice of procedures. Business Geographers analyze markets to determine where clients locate and the characteristics of those clie nts in the market or new mark et area. Market analysis can

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4 be used for both small and larger market areas. business geography has steadily evolved from the eras of Johann Heinrich Von Thunen and William Applebaum, to the present era of Business Geographer Dr. Grant Thrall. The theories and ideals th at make up the study of business geography are constantly changi ng. One process that was introduced to the field in 1993 was “a four-stage compartm entalization of GIS activity” (Thrall and Elshaw-Thrall 1993). The original f our-stage process is as follows: Stage One: Description Stage Two: Explanation Stage Three: Prediction Stage Four: Judgment A fifth stage was implicitly added to the earlier stages of evolution (Thrall and Ruiz 1994; Thrall, Bates, and Ruiz 1994): Stage Five: Implementation and Management Stage Six: likely to be holistic appli cation of geographic reasoning and technology throughout the enterprise (personal corre spondence with Dr. Grant Thrall, 2004) The evolution of these six stages can be represented chronologically, as shown for the business geography field in Figure 3. The graph represents the evolution of the GIS stages conceding the longevity of the theories and ideals of business geography. Geography theories and ideals have been ar ound since the 1900s, and their stages and principles will continue to evolve well into the future. An issue of all stage theories is that th ey do not address "what next" after the last referenced stage. A stage seven added to the time line for business geographic market

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5 analysis would likely, according to Thrall, be an adoption of his stage five and 6 of his general stages of GIS reasoning. Figure 3. Timeline for business geographic mark et analysis of reta il location decisions after 1996 and 1997 by Thrall and del Valle. Market analysis is not new, however the evolution of this field has changed with the induction of new technologies (Figure 4) Changes in technology, like the automobile, which changed the shape of cities, and the evolution of the business industry, create a need to understand and analyze traffic flow, so cial characteristics, social behavior, and people’s lifestyle preferences. Also, the adva nces of computers a nd the introduction of GIS (Geographic Information Systems) redirected the study and analysis of the market to a more complete and profound understa nding of consumers and neighborhood characteristics, which ultimately improves the analysis and data for business geography. For the analysis of the magazine industry’s market, the Lifestyle Segmentation Profile (LSP) is used because the magazine i ndustry also classifies their subscribers by LSP; further, programs like CACI Coder/Plus that are co mmonly used to geocode the data assigns a specific Lifestyle Segmen tation Profile (LSP) to each address.

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6 Being able to classify subscribers in th is way can improve understanding of which their customer is, in terms of salary, e ducation level, and occupation, which improves their judgment in decision making for marketi ng, distribution, and development. Further, these LSPs can be used to evaluate a single market and the LSP of two or more markets (Figure 5). The table listed below outlines th e indices used for classifying people into nine categories based on similar characteristics. TIMELINE OF LOCATION-BASED MARKET ANALYSIS Stage Description 1. Pedestrian and sign posting era The c ity center offered the best location for marketing high-order retail goods. Other sites may have been chosen, but on a trialerror basis. Some parallels to this approach exist today: for example, some national retail chains consider only a location near the regional mall adjacent to the freeway exit (Thrall et al. 1996) 2. Mapping and cartography The cu mulative body of knowledge about locational analysis goes back at least to the 1920s and the use of gravity models back to the 1850s. Early applied business geography originates with contract work by retail chains to determine the relative value of a site, compared with the relative advantages of other sites. Most important in the development of this stage was the work of Applebaum. The methodologies used in the era before contemporary geographic technologies were mainly subjective in nature (Goldstucker et al. 1978). 3. Sales potential predictive models Be gan in the mid-1960s and contributed a number of methodological advancements, particularly in us ing and manipulating statistical data to arrive at sales potentials Figure 4. Timeline of location-based market analysis by Thrall (2002).

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7 Stage Description for a total complex of stores in a shopping center (Craig et al. 1984). Most important in the development of this stage of marketing geography were the contributions of Huff (1959, 1963) to the advancement of gravity and spatial interaction models. For discussion, see Haynes and Fotheringham (1984) 4. The rise of the holistic vi ew Began around 1966 and saw the development of more sophisticated models of retail potential that considered the influence of store size, distance, image factors, merchandise quality, and services of all competitors within the same trade area. During this stage, academic research largely had the objective of measuring retail image and the dimension that underline these perceptions; seldom were these considerations deal with in the professional and academic locational analysis literature prior to the 1960s (Goldstucker et al. 1978). This stage differs from the third stage by the inclusion of nongeographic factors as having equal or even greater importance than location. 5. GIS as an exotic technology The 1970s and 1980s were the beginning of the use of geographic information systems in retail location analysis. However, the software in this era was very complex, often having been adopted from natural resource applications or written from scratch by programmers at the retail firm. Data were either very expensive. GIS had a deserved reputation in this era of being an exotic technology that was very expensive and difficult to use. The GIS of this era was dependent on mainframe computers or large workstations. Figure 4. Continued

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8 Stage Description 6. GIS as common desktop computer technology, integrati on of geographic analysis into routine strategic management Noted for significant advances in desktop computer hardware, including CD-ROMs for the distribution of data: the widespread use of Microsoft Windows operating system that allowed for the standardization of the software user interface: declining computer software programming cost; and the emergence of a business geography technology industry offe ring a wide array of low-cost data a nd specialized, highly productive software applications. The future of this stage will include the integration of GIS and management practices, a greater s ophistication of the modeling behind the analysis, automation, improved qualitative analysis, and real time information delivered via the Internet. Figure 4. Continued ACORN lifestyle segmentation indices ACORN Category Description 1. Affluent families 1A Top one percent 1B Wealth seaboard suburbs 1C Upper income empty nesters 1D Successful suburbanites 1E Prosperous baby boomers 1F Semirural Lifestyle 2. Upscale households 2A Urban professional couples 2B Baby boomers with children 2C Thriving immigrants 2D Pacific Heights 2E Older settled married couples 3. Up & coming singles 3A High rise renters 3B Enterprising young singles 4. Retirement styles 4A Retirement communities 4B Active senior singles 4C Prosperous older couples 4D Wealthiest seniors 4E Rural resort dwellers 4F Senior sun seekers Figure 5. ACORN lifestyle segmen tation indices by CACI/Coder Plus.

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9 ACORN Category Description 5. Young mobile adults 5A Twenty something 5B College campuses 5C Military proximity 6. City dwellers 6A East Cost immigrants 6B Working class families 6C Newly formed households 6D Southwestern families 6E West Cost immigrants 6F Low income young and old 7. Factory and farm communities 7A Middle America 7B Young frequent movers 7C Rural industrial workers 7D Prairie farmers 7E Small town working families 7F Rustbelt neighborhoods 7G Heartland communities 8. Downtown residents 8A Young immigrant families 8B Social security dependents 8C Distressed neighborhoods 8D Hard times 8E Urban working families 9 Nonresidential neighborhoods 9A Business district neighborhoods 9B Institutional populations 9C Unpopulated areas Figure 5. Continued This LSP and market analysis improves th e judgment (Stage Four) of the company for which the market analysis is done by giving the company a more complete understanding of their market; this also give s the company more insi ght for better target marketing and creating a more proficient ta rget strategy to increase their audience. Likewise, this enables them to identify specifi c target markets or increase the subscribers of less saturated markets. This analysis al so helps to identify where the strongest and weakest markets are located and what th e LSPs are for the specific markets. This analysis provides companies with a co mposite of the likes and wants of their markets. This form of analysis, which most companies in the industry do, represents only

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10 one of the four types of consumers’ inform ation (Figure 6). However, to get a better understanding of their market s the use of Lifestyle Segm entation Profiles (LSPs) can increase the assessment of each individual (consumer) and, at the same time, better characterize markets and consumers of the publishing company. Of course psycho demographics are important, but Lifest yle Segmentation Profiles (demographics, psychographics, purchase behavior s, and media preferences) with the incorporation of business geography and GIS, shows a more comp lete analysis and representation of the market characteristics, their subscrib ers’ spatial location, and consumption characteristics. This can be understood also as the cognitive measures that the marketing industry use adding the geographical analysis. Consumer researchers who desire to know about their market more than just demographic characteristics may attempt to collect cognitive information; that is, information about consumers’ knowledge, attitudes, motivations, and perceptions. Merely observing consumers cannot fully e xplain why they behave as they do, and questioning often does not provide reliable an swers because of consumers’ inability or reluctance to reveal true feelings to an interviewer. Thus, researchers attempt to explore intervening variables potentially us eful in explaining c onsumer behavior by utilizing other techniques. (Loudon, Della Bitta, 1979) This analysis explains and demonstrates the necessity of the publishing companies to incorporate the new technology and ideas of GIS and business geography. Applying the four types of consumers’ information from the following Figure 1-6 to the publishing industry helps determine valuable informati on about their subscribers’ demographics (age, income, occupation, location), psychograp hics (what they think), media preferences (print or broadcast), and purch ased behavior (how they spend their money). Using this information, the magazine could decide what ki nd of advertisements are best suited for inclusion in the magazine, type of advertising to market th eir magazine, what cost to charge for the magazine, and where to distri bute the magazine. These types of decisions

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11 are crucial for the growth and success of a ny organization. And, any organization can use these business geography ideals to ma ke Better Business Decisions (BBDs). Chapter 2 presents a literature review of the industry involved in this thesis. Relevant articles have been chosen accordi ng to their importance to the GIS, magazine, and business geography industries. Chapter 3 details how the data acquisition pr ocess and steps applied to the data set in order to analyze it. GeoSpatial Solutions made this data set available for these analyses. Chapter 4, using data provided by GeoSpatial Solutions describes where the Geographic Information Systems Market, compos ed of companies using GIS, is located and who uses GIS in the US. This chapter is broken into three main areas. The analysis then proceeds to explain why the industry is located where it is. First, the geographic regions in the United States is analyzed to identify the primary, s econdary, and tertiary submarket regions of GeoSpatial Solutions’ subscribers in each individual submarket. Second, the location of the GIS producers and th eir submarkets in the US is identified. And, third, this chapter identif ies geographic locations of GI S firms and their submarkets in the US. Chapter 5 identifies the social-economic influences of submarkets with a high concentration of GIS users for the different markets of the US. This chapter is divided into four sub areas. First, the analysis s hows geographic areas w ith high concentration regions of GIS. Second, the analysis shows the influences of high edu cation to attract the GIS market to the region. Thir d, the analysis shows the influe nces of the submarkets to

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12 attract firms to the region. F ourth, this analysis shows the influences of the area for GIS producers to locate in a specific region. Chapter 7 addresses the relevant questi ons for use in a global perspective for international market analysis. This analysis assists international markets to increase economic opportunities by focusing on the GI S industry and its characteristics. Chapter 8 concludes this analysis by e xplaining where and why GIS locates in particular geographic markets. Figure 6. The four types of consumer information. This figure presented in The Insider’s Guide to Demographic Know-How in 1990.

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14 CHAPTER 2 LITERATURE REVIEW Business geography literature dates to the early part of the la st century however for the purpose of this analysis the focal poi nt of this thesis is on the “New business geography, according to Thrall (2002) is “…the assembly of information on trade areas, demand, and competitive supply for the purpose of improving the judgmental decision.” The goal of a business geographer is to create analysis for a client that enables more informed business decisions to be made. Thra ll (2002) has presented the stages that GIS analysts and business geographers in partic ular, go through in their reasoning. These stages are: 1. Description 2. Explanation 3. Prediction 4. Judgment 5. Management and Implementation The most important stage to the busine ss geographer is judgment. Judgment is necessary in the final analysis to justify the business geographic analysis. The geographic analysis is expedited using geographic technol ogy, including data and GIS software. This GIS software has great applications of th e business geography fiel d. Bill Pinkovitz, N.R. Sumathi and Bill Ryan noted the importance of the data, demography, lifestyle, etc for the Business Geographer. Also, the GIS techno logy has opened a field in which the data can be represented by mapping demographics Business geographers use GIS technology to create comprehensive pictures of the subs cribers’ markets. Piccilli (1999) explains the advantages of mapping demographics and the further analysis possible with the current

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15 technology. The chart in Figure 7 shows six unique characteri stics of the advances of technology on the business geography and GIS An alysis field. These methods help the companies to utilize data sets and consum er characteristics to make better decisions. Media buys: Once the precise location of your custom er base is known, you can make costeffective media buys that get the right me ssage to the right target. For example, by using the knowledge gained from m apping their customer base, a marketer who wants to place inserts in a loca l newspaper can target the neighborhoods with the highest level of customers. Competitive analysis: Plotting the location of the competition (direct and indirect) on a map is much easier to understand than a list of locati ons on a report. You can adjust your marketing strategy to fit the number of competitors in the immediate geographic area. Drive-time analysis: Mapping your customer drive times is us eful for analyzing c annibalization issues, new store placement and competition. By plotting the drive-time area on a map, you clearly see any overlap among vari ous business locations and competitive sites. Barriers such as military bases airports, parks or college campuses all influence your customer's drive time, but those barriers are not apparent on reports. Market-entry planning: Using demographic mapping for market-ent ry planning clearly identifies sales potential in a region. For market entry, be sure to look at retail sales potential, lifestyle segments, propensity to use or purchase products and services, population, income, age, number of bu sinesses and competition. Using a thematic map, your market ing strategy can be tailored to fit the new market's unique characteristics. Budgeting: For comparisons, demographic mapping is in valuable. Analyzing maps for each geographic area enables marketers to deter mine where to allocate their budgets. Areas with high growth potential or hi gh sales potential are quickly spotted and marketing strategies can be adjusted accordingly. Lifestyle segmentation: Used in conjunction with dem ographic mapping, segmentati on is a great tool for identifying quality prospect s. Lifestyle segmentati on systems use demographic and aggregated consumer demand data to cl assify every household in the United States into a unique market segment. Each segment consists of households that share similar interests, purchasing pa tterns, financial behavior and demand for specific products and services. Figure 7. The advantages of mapping demogr aphics and the furthe r analysis possible by Piccilli 1999. However, one of the principal problem s that the GIS industry encounters is distinguishing itself from other industries. GIS is part of many applications, users, and disciplines. And the GIS industry is comprised of hardware, software, and data (users and

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16 creators). Purvi Rajani (2002) expresses the c onfusion of this field to identify itself by showing the questions that can separate the industry “Which products and companies should consider GIS and, perhaps more impor tantly which one shouldn’t? Is it fair to compare MapInfo Corp., Troy, N.Y., with Ge nasys II Inc., Fort Collins? Are these companies really in the same industry?” Th is is a continuous dilemma that the GIS industry must consider and analyze itself Valerie L. Hartung (1997) analyze the GIS industry, although the fast growi ng characteristics of this in dustry make it difficult to research. Hartung attempts to ev aluate the role of the GIS i ndustry and she describes the nature of the industry as a pyramid of func tionality, which each layer has to support the previous one. THE GOAL (Top of the pyramid) Is the goal clearly defined, with measurable objectives and time frame? Is the goal, as defined, truly of benefit to the organization? Is the budget available to accomplish the goal? USER Do the users have enough time available to implement the new system? Do the users have adequate training? Are the users motivated to make the system work? DATA Is all of the data that is needed available? Is the data free from errors? Does the data require conversion from another format or medium? APPLICATION SOFTWARE Does the application software truly accomplish the goal or goals desired? Is the application software available from a reliable company? Does the application softwa re require customization?

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17 NETWORK Is the network reliable? Does the network have adequate storage and space? Is the network security being used? OPERATING SYSTEM Do the operating systems be st support the application software? Do the operating systems best support the users’ needs? HARDWARE (foundation of the pyramid) Is the hardware reliable? Does the hardware have all the components to support the layers above? The dataset that was collected through a surv ey that Hartung created gave a small, but reliable dataset. However, for a complete sta tistical analysis of the GIS industry or related firms this is a very small sample size (Figure 8). Figure 8. Survey response sta tistics conducted by Hartung 1997. Through her study, Hartung then analyses the characteristics of the industry growth. Moreover, Hartung shows statistica lly that the revenue for this industry is increasing. The United States Canada Total Sampling Frame Population2 874 345 1219 Number of Firms that agreed to participate 504 194 698 Number of Responses 300 84 384 Response Rate 59.5% 43.3% 55.0%

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18 results of her survey revealed many charac teristics about the GI S industry, which are listed below: GIS firms are young (median year founde d 1983, first year GIS revenue 1989), small (median labor force is eleven) a nd earn on average $1 Million per annum. Approximately one-half of the resp ondents earned export revenues. One third of known GIS firms are located in the Colorado Corridor, Washington Beltway, and Los Angeles and its Environs. Firms located in one of the three tier one clusters are apt to be more specialized then those firms located elsewhere. GIS firms appear to be vertically inte grating, offering customers a full-service solution or one-stop shop. The largest demand market for GIS technologi es is utility companies and all levels of governmental agencies. Hartung maps the firms to provide a ge ographic view of the GIS industry. Thrall (1998) demonstrated the important uses of geocoding software to identify the geographic location of subscribers and thei r LSP characteristics. CACI Coder/Plus is software that gives the analyst the advant age of analyzing a data set and obtain a comprehensive assignment of geographic in formation, which includes, latitudes, longitudes, and lifestyle segmentation info rmation. The magazine industry understands

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19 the importance of reaching the right market so lifestyle segmentation is a way to understand who your market is. Cathy Bond ( 1997) documents customer magazines are using segmentation (lifestyle) as a marketi ng tool to reach the right people the right message. Some magazine titles are promoting services for the right lifestyle customer, age, or social economic profile. This lifesty le segmentation is important to assess the lifestyle of the US subscribers and de pendent upon business geography because to survive it must be oriented to its global market. So in a general way the magazine industry has become more scientific than before and has also become more market oriented. As Sharpf (1989) explains these advances have attrac ted both advertising market and advertisers that are willing to pa y to "fine tune their advertising expenditures to keep waste to a minimum.” The market re search industry organiza tions are using their knowledge of lifestyle to increase their an alysis proficiency. Sh arpf (1989) argues: For the publisher, the cost of subscriber’s analysis, the trade down risk, and the economic feasibility of segmentation can make for a complex marketing package. It can also mean developing editorials to go with the segmentations; but that again should help the sell. Further, Dickenson (1998) explains that the magazine industry has advanced to a point in which magazines and brochures can be produced for specific segmentation groups (lifestyles) that the publishing compa ny or magazine wants to target. An example of this is Goldfish, which is a United Kingdom credit card company that produces a guided index of their members’ lifestyle segm entation that helps the magazine industry in targeting specific lifestyle segmentations. The publishing industry is a very compet itive industry. As Chepesieuk (1994) explains that specialization and the use of se gmentation is essential for magazine in the industry to survive and grow. A good example of this is Winston-Salem Journal (N.C.)

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20 had to specialize to the lifestyle of his market to survive the competition of two new local real estate publications. Ni che publishing can be form by the analysis of segmentations like women, men, ethic group, the elderly, tourist, children, prof essors, etc. Even a high regarded publication lik e the Chicago Tribune had to targ et a specific lifestyle segment (elementary and high school) during the 80’s to increase their market readership. Thrall (2001) presents a case for (Thrall, 2002) th at Lifestyle Segmentation Profile for a good market analysis is today a require d part of the analyst's report. The lifestyle segmentation profile is derived by the combination of census databases and private databases. LSP (lifestyle segmentation profile) is the main characteristic that the magazine industry s hould take in consider ation for use in their market analysis. Pinkovitz (1997) denotes th e differences of consumers’ lifestyles (psychography), where they live, (geography) and age, income, etc. (demography). On the other hand, the LSP (lifes tyle segmentation profile is a more complete way of segmenting the market and the Business Geogr apher is the person that puts these small groups together and creates a more profound analysis. Hucker-Brown (2003) joins these ideas by combining demographic data or se gmentation data with the likely market a better understanding can be done. The following analysis brings together all of these ideas to create a clear and unique analysis of GeoSpatial Solutions magazine and with this data try to understand the social and locational makeup of the GIS industry.

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22 CHAPTER 3 DATA METHODOLOGY The data used for the analysis was ma de available by Advanstar Communications for their GIS magazine GeoSpatial Solutions The database includes their entire subscribers list (approximatel y), a list of GIS business fi rms in the US, and a list of international GIS companies also from GeoSpatial Solutions which are used to document and corroborate GIS business c oncentrations within submar kets. Social-economic data from the 2000 US Census, private data vendors and CACI Coder/Plus (ESRI) are used to understand the social influences of submarkets to attract GIS firms and GIS producers to specific submarkets in the US Analysis is produced using leading GIS technology including CACI Coder/Plus (ESRI), ArcGIS (ESRI), ArcView Business Analyst (ESRI), and Microsoft Excel. Data Acquisition To acquire the data from GeoSpatial Solutions a constant communication link was made by Dr. Grant Ian Thrall (University of Florida Professor of business geography), Scottie Barnes (Editor fo r Advanstar Communications, GeoSpatial Solutions ) and me. After a few weeks, Advanstar Comm unications, the publishing company for GeoSpatial Solutions released their subscribers’ data lists to Dr. Grant Ian Thrall and me. These data lists included 27,050 subscribers, 647 firms, a nd 161 international firms. Because of the competitive nature of this market, all the pa rties involved signed a disclosure agreement to keep their subscribers lists confidential. Also, due to competitive nature of the

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23 magazine publishing industry, any preliminar y results of this research were kept confidential until the publication of articles in GeoSpatial Solutions The 27,050 subscribers’ data pr ovided by the GIS magazine GeoSpatial Solutions was processed using ESRI’s geocoder progr am CACI Coder/Plus Executing the CACI program on the list, using data from address fields one and two, a ssigned a latitude and longitude to each address. The original data set had two different address fields. To have a more complete data set, using Microsof t Excel, the data was analyzed and the twoaddress fields were consolidated into a singl e, more complete address field. Afterward, using this complete address field the program CACI Coder/Plus (ESRI) was again used to give each completed address geographical latitude and longitude, and an individual Lifestyle Segmentation Profile (LSP). The re sults of the CACI Coder/Plus geocoding process were included in the analysis of the program in a Geocoding Match Level Summary at the completion of this analysis. Because the subscribers’ data list has multiple address lists, the process of geoc oding was processed three separate times. Geocoding Results The first address gave only a 4.9% accur acy level. All the addr esses from the first address list were kept and the rest of the subscribers were deleted. Then using Microsoft Excel, the addresses that did not have a latitude and/or a longitude were checked for data entry errors, such as extra spacing within the address, or a misspelling in the street name; were edited and the addresses that could not be edited because of data entry errors or nondistinguishable addresses were removed from the list.

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24 Table 1. Geocoding match level summary of 27,050 subscribers’ first address field from CACI Coder/Plus. Number of Records: 27,050 Match Description Match Code Number Percent Street Match S 1,330 4.9% Dominant Tract in ZIP Code Z 22,809 84.3% One Tract in ZIP Code T 1,263 4.7% No Geocode X 1,648 6.1% 27,050 100.0% The second address field (column) ga ve a 66.2 % accuracy level. The same process as was used for the first address fi eld, using Microsoft Excel, was followed to get a more accurate data set of the address lists. Table 2. Geocoding match level summary of 27,050 subscribers’ second address field from CACI Coder/Plus. Number of Records: 27,050 Match Description Match Code Number Percent Street Match S 17,916 66.2% Dominant Tract in ZIP Code Z 6,691 24.7% One Tract in ZIP Code T 901 3.3% No Geocode X 1,542 5.7% 27,050 100.0% Final Dataset After, editing the two address fields, the two data sets were merged together. The final list was also geoprocessed using CACI Coder/Plus by Dr. Grant Thrall. The final result of CACI Coder/Plus was a geocode d match of 73.4%, which is 26,024 subscribers from the original data set. These 26,024 subscribers of GeoSpatial Solutions were used to proceed with the analysis.

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25 Table 3. Geocoding match level summary of 26,024 subscribers’ final address field from CACI Coder/Plus. Number of Records: 26,024 Match Description Match Code Number Percent Street Match S 19,101 73.4% Dominant Tract in ZIP Code Z 5,537 21.3% One Tract in ZIP Code T 850 3.3% No Geocode X 536 2.1% 26,024 100.0% The same three-step geocoding process was performed with the firm’s data list. Due to a lack of international GIS software, the international firm’s data set was geocoded using geospatial proximities to obtain a general overview of GeoSpatial Solutions ’ global market.

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26 CHAPTER 4 MAPPING THE GEOSPATIAL COMMUNITY This chapter provides a business geographic analysis of GeoSpatial Solutions ’ subscriptions. Using the final data list, Bu siness Analyst (ESRI) and ArcGIS (ESRI), a map of the total subscribers was created. This subscriber’s map shows a complete presentation of Geospatial Solutions ’ subscribers nationally. The map corresponds to high concentrations of subscribers located in metropolitan areas. Th e northeast US shows the largest concentration of GeoSpatial Solutions subscribers in the US. These states include New Hampshire, New York, Virginia, and the District of Columbia. From this map, other high concentration geographical mark et regions can be distinguished (Figure 9). The map represents a general su bscribers’ representation of GeoSpatial Solutions The subscribers of each state are represented wi th colored dots, with each state having its own color. The total count of subscribers by state is located in the legend at the bottom left of the map. To create this map the data set for total subscribers was utilized. After selecting the geoprocessing wizar d from the tool icon, the attribute selected was to do a count (dissolve) on each st ate based on subscribers. Th e input layer used was the subscriber. After, the specific output (save as) archive was selected; an additional field for ACORN LSP categories was activated. The new layer created also included the total count of subscribers by state. The subscribe r’s layer and the new s ubscribers count layer were merged according to their state field. Ne xt, using the properties of subscribers the

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27 Figure 9. GeoSpatial Solutions ’ US market subscribers pro cessed using ArcMap (ESRI).

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28 symbology tab was selected to activate. Fr om these new windows, the unique valuesmany fields category was selected. Then, the st ates and count-states were selected and all the values were added. The legend symbols we re edited for better pr esentation and fit and they were integrated with the new map (F igure 10). The following map represents the percentage rate of the total subscribers for GeoSpatial Solutions ’ data set by state (Figure 11). Geographic Regions in the US The market analysis identifies primary, s econdary, and tertiary submarket regions of GIS (Subscriber and Companies) in the US. To create this map, the subscribers’ data set was separated into three submarkets to show the states with high, middle, and low representation of the US market. To create these three submarkets, the geocoding ma tch level summary from CACI Coder/Plus (ESRI) was used. The following table outline s the top 20 states by highest number of subscribers per state (Table 4). The co rresponding percentage demonstrates the percentage of all subscribers in each state. Table 4. Geocoding match level summary of top 20 states by number of subscribers from CACI Coder/Plus. Record Count Percent Top 20 States California 3,286 12.6% Texas 1,564 6.0% Florida 1,429 5.5% New York 1,271 4.9% Virginia 1,179 4.5% Pennsylvania 955 3.7% Illinois 872 3.4% Colorado 869 3.3% Ohio 832 3.2% Maryland 772 3.0% Washington 677 2.6% New Jersey 661 2.5% North Carolina 630 2.4%

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29 Michigan 627 2.4% Georgia 609 2.3% Massachusetts 599 2.3% Minnesota 520 2.0% Wisconsin 512 2.0% Missouri 504 1.9% Oregon 487 1.9% Other States 6,633 25.5% Non-geocoded Records 536 2.1% The top 20 states list was used to further di vide the data set into the top 3 markets, in terms of percentage of subscribers, for GeoSpatial Solutions A state being classified as primary means that the state contains over 4% of all GeoSpatial Solutions subscribers. A state being classified as s econdary submarket means that th e state contains 2% to 3.9% of all GeoSpatial Solutions subscribers. And the tertiary submarket means that the state contains 1.9% and below of all GeoSpatial Solu tions subscribers. These three submarkets were separated into three indi vidual maps for a more in de pth look at the three primary submarkets. These layers show a ll three leading submarkets for GeoSpatial Solutions and by implication the GIS industry in the US. Mo reover, it represents the strongest and weakest market saturation areas for GeoSpatial Solutions (Figure 12). Primary Submarket Figure 13 shows the states that represent the primary submarket of subscribers in the US and their total count. These states were selected based on their percentage classification. The primary submarket is made up of those states with 4% and above subscriber representations by state. The stat es that comprise the primary submarket are CA with 3,309 subscribers, TX with 1,587 subscribers, FL with 1,473 subscribers, NY with 1,279 subscribers, and VA with a tota l subscriber list of 1,207 (Figure 13).

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30 30 Figure 10. GeoSpatial Solutions individual state subs cribers color-coded by state counts processed using ArcMap (ESRI).

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31 Figure 11. GeoSpatial Solutions ’ US market subscribers percen t by State using ArcMap (ESRI).

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32 32 Figure 12. GeoSpatial Solutions ’ three US GIS submarkets processed using ArcMap (ESRI).

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33 Secondary Submarket Figure 4-6 is a representation of GeoSpatial Solutions subscribers by state that fit the secondary market, which was created, base d on the percentage of subscribers by state that CACI Coder/Plus (ESRI) summary rel eased. The secondary submarket represents 2% to 3.9% of subscribers by st ate. The states that form th is submarket include: PA with 959, CO with 937, IL with 876, OH with 835, MD with 772, WA with 678, NJ with 666, NC with 636, MI with 630, GA with 617, MA with 599, MN with 522, and WI with 512 (Figure 14). Tertiary Submarket Figure 15 shows the tertiary submarket of subscribers, formed by using the percentage of the top 20 states on the CACI Coder/Plus (ESRI) summary list. All the states that have 1.9% of subscribers or belo w are included. The states and their individual subscribers counts follow (Figure 15). The st ate counts for the tertiary submarket were also included in the analysis (T able 5). (Human data entry er rors should be considered.) Table 5. GeoSpatial Solutions ’ tertiary submarket coun ts processed using CACI Coder/Plus (ESRI).

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34 Figure 13. GeoSpatial Solutions ’ primary submarket processed using ArcMap (ESRI).

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35 Figure 14. GeoSpatial Solutions ’ secondary submarket pro cessed using ArcMap (ESRI).

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36 Figure 15. GeoSpatial Solutions ’ tertiary submarket processed using ArcMap (ESRI)

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37 Table 6. GeoSpatial Solutions ’ percentage of subscribers by state using data from the US Census Bureau. Percentage Rate of Subscriber by State State Population 18 years and Over SubscribersSubscribers per capita 100000 Colorado 3,200,466 937 29.28 Wyoming 364,909 103 28.23 North Dakota 481,351 121 25.14 Montana 672,133 160 23.80 Virginia 5,340,253 1207 22.60 South Dakota 552,195 116 21.01 Idaho 924,923 186 20.11 Maryland 3,940,314 772 19.59 Oregon 2,574,873 487 18.91 New Mexico 1,310,472 247 18.85 Utah 1,514,471 275 18.16 New Hampshire 926,224 160 17.27 Maine 973,685 161 16.54 Nebraska 1,261,021 205 16.26 Washington 4,380,278 678 15.48 Nevada 1,486,458 223 15.00 Minnesota 3,632,585 522 14.37 California 24,621,819 3309 13.44 Wisconsin 3,994,919 512 12.82 Kansas 1,975,425 249 12.60 Missouri 4,167,519 517 12.41 Arizona 3,763,685 466 12.38 Massachusetts 4,849,033 599 12.35 Vermont 461,304 56 12.14 Iowa 2,192,686 262 11.95 Florida 12,336,038 1473 11.94 Connecticut 2,563,877 302 11.78 Rhode Island 800,497 92 11.49 Alabama 3,323,678 373 11.22 Mississippi 2,069,471 230 11.11 Texas 14,965,061 1587 10.60 New Jersey 6,326,792 666 10.53 North Carolina 6,085,266 636 10.45 Georgia 6,017,219 617 10.25 Pennsylvania 9,358,833 959 10.25 Delaware 589,013 60 10.19 Ohio 8,464,801 836 9.88 South Carolina 3,002,371 296 9.86 West Virginia 1,405,951 137 9.74 Louisiana 3,249,177 312 9.60 Illinois 9,173,842 876 9.55 Oklahoma 2,558,294 238 9.30 Tennessee 4,290,762 390 9.09

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38 Table 4-3. Continued State Population 18 years and OverS ubscribersSubscribers per capita 100000 Kentucky 3,046,951 273 8.96 New York 14,286,350 1279 8.95 Indiana 4,506,089 398 8.83 Arkansas 1,993,031 176 8.83 Michigan 7,342,677 630 8.58 District of Columbia 4,570,678 208 4.55 Source: U.S. Census Bureau Public Information Office Table 6 is the rate of GeoSpatial Solutions subscribers by state (Table 6). To create this chart, data from the 2000 US Census of popul ation 18 years of age and over was used. The formula used to get the percentage rate is: (Subscriber) / (population) (100,000) The chart shows a descending percentage rate of the states with the higher percentage rates to the lowe r percentage rates. The publishing industry would generally view tables like this as evidence of which st ates have the greatest potential for expansion. That interpretation might carry over here as well. Florida and California both have large GIS subscriber bases, but not as large as th e total population of the state would indicate. The lower-rated states should be considered for as opportunities for market growth in subscriptions for these states (Figure 16). GIS Producers Within the GeoSpatial Solutions database, subscribers are required to select which industry best represents their use of GIS. This is known as the "Business Code" database. The business codes map represents a genera l spatial location of the business codes. The business codes map was created using the da ta list of subscribers. The list below has a field for Business Codes, Function Codes, and Title Codes (Table 7).

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39 Table 7. GeoSpatial Solutions ’ business code categories using their data set. Business Codes Card Code Description 10 Surveying / Mapping 20 Government Operations 30 Construction / Mining / Civil Engineering 40 Utilities / AM / FM 50 Natural Resources / Environmental Planning 55 Telco (including Cellular / Wireless) 60 Business Services 70 Software Development / Systems Integration 160 Education / Research 85 Healthcare 90 Other Organizational Affiliation Codes (Function Codes) Card Code Description 15 Government/Public Sector 25 Private Business 35 University/College 45 Other Title Codes (Code 31) Card Code Description Corporate Management 1 Owner, President, CEO 2 Senior Manager (incl. VP, Ge neral Division Manager, etc.) 3 VP/Director/Manager Sales & Marketing 4 Other Corporate Management Information Technology (MIS/IS) 5 Senior Manager (incl. CIO, VP, etc.) 6 Manager-Information Technol ogy/Systems (incl. MIT/MIS) 7 Applications Developer 8 In-house User Support Representative 9 Internet/Web Designer/Developer L Other IS or IT Staff Operations M Senior Manager (including COO, VP, etc.) N Manager (incl. Coordinator/supervisor /administrator/data processing systems) O Engineer P GIS Technician

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40 Table 4-4. Continued Business Codes Card Code Description Q Geospatial Professional (incl. Biologis t/ geologist/ professo r/ cartographer/ surveyor/ mapmaker and all others) R Systems Integrator S Technician/Analyst/Administrator T Other Operations Other Job Title U Other These data codes are collected from the subscr ibers’ card codes that are selected when people subscribe to the magazine (Figure 17) and (Figure 18). To perform this analysis, the three codes were analyzed individually a nd also the Title Codes were separated into three categories (Corporate Management, Information Technology, and Operations). The map shows all the ten classificati ons together as a general group. Each individual subscriber selects his or her in dividual classification on the card codes when they fill out their subscription card.

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41 Subscribers per capita (Penetration Rate) 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00C olorado W y o ming N orth Dakota M on a tan a V irginia S outh Da k o t a I dah o M ar yl a n d Or eg o n N ew Me x ico U ta h N ew H am pshir e M aine N eb r a s ka W ashingt o n N eva d a M i n ne s o ta C alifor n i a W i s con s in K ansas M i s so u ri A riz o na M assachu s e tt s Ver m ont I ow a F lor i d a C on n ectic u t R ho d e I s lan d A la b am a M i s sis si p pi T e x a s N ew Jer s e y N orth Car o l i n a Ge or g i a P enn s ylavan i a D elawar e Oh i o S outh Ca r oli n a W est Virg i n i a L ou i si a na I l l inois Ok lah o ma T e nnessee K entu ck y N ew York I ndian a A rkan s a s M i c h i g a nStatespercent by 100,000 Figure 16. GeoSpatial Solutions ’ percentage rate of subscribers by state using data from the US Census Bureau.

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42 Figure 17. GeoSpatial Solutions ’ subscription card. Figure 18. GeoSpatial Solutions ’ subscription card.

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43 Business Codes Figure 19 is the general spatial location of subscribers by business codes. The Business Codes map was also created using the data list of subscribers. The list has a field for Business Codes. This business codes data is collected from the card codes that the subscribers check when subscribing to th e magazine (Figure 19). This map represents the percentage of total subscriber s in the business codes category of GeoSpatial Solutions ’ database by state (Figure 20). This map shows each of the ten business c odes groups in a different color and lists their individual counts by categor y. The legend of this map shows: Table 8. GeoSpatial Solutions ’ ten business codes groups. Code Description Total Subscribers Percentage 10 Surveying/Mapping 3,57413.7% 20 Government Operations 5,68921.9% 30 Construction/Mining Civil Engineering 2,93611.4% 40 Utilities/AM, FM 1,4315.5% 50 Natural Resources Environmental Planning 2,2458.6% 55 Telco 8663.3% 60 Business Services 3,38313% 70 Software/Development System Integration 2,5569.8%

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44 Table 4-5. Continued Code Description Total Subscribers Percentage 85 Healthcare 6442.5% 90 Other 60.2% 160 Education/Research 2,61410.1% Total 2,5998 100% This map gives an idea of which mark et groups have high and low subscriber representation by GeoSpatial Solutions (Figure 21). Organizational affiliation The Organizational Affiliation codes (Function codes) were created to distinguish a geographic perspective where these codes we re located in the US The organizational affiliation is formed by four unique categor y codes: 15, Government/Public Sector; 25, Private Business; 35, Univers ity/College; 45, other. This map represents the total Organizational Affiliation market (Figur e 22). The proceeding map illustrates the organizational affiliation code of GeoSpatial Solutions ’ subscribers by state (Figure 23). The second map represents the function code s and respective count s for each category (Figure 24). Title codes The Title Codes (Code 31) were too la rge to analyze as one group, so the group was separated into its three main categorie s (Table 8). Each category was analyzed independently to better unders tand its markets. Maps for these categories were created and maps of individual counts for each category were also created.

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45 Figure 19. GeoSpatial Solutions ’ combined business codes processed with ArcMap.

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46 Figure 20. GeoSpatial Solutions ’ combined business codes percent by state processed with ArcMap.

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47 Figure 21. GeoSpatial Solutions ’ individual business codes processed with ArcMap.

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48 Table 9. GeoSpatial Solutions ’ title code categories using their data set. Title Codes (Code 31) Card Code Corporate Management 1 Owner, President, CEO 2 Senior Manager (incl. VP, General Division Manager, etc.) 3 VP/Director/Manager Sales & Marketing 4 Other Corporate Management Information Technology (MIS/IS) 5 Senior Manager (incl. CIO, VP, etc.) 6 Manager-Information Technology /Systems (incl. MIT/MIS) 7 Applications Developer 8 In-house User Support Representative 9 Internet/Web Designer/Developer L Other IS or IT Staff Operations M Senior Manager (including COO, VP, etc.) N Manager (incl. Coordinator/supervisor/ administrator/data processing systems) O Engineer P GIS Technician Q Geospatial Professional (incl. Biologist/ geologist/ professor/ cartographer/ surveyor/ mapmaker and all others) R Systems Integrator S Technician/Analyst/Administrator T Other Operations Corporate Management: This map shows the general geographic loca tion of all of the s ubscribers that fit the category of corporate management from th e title code list (Code 31). The data set of subscribers that fit this co rporate management category and a new layer was created (Figure 25). The next map s hows the percent of total cor porate management subscribers of GeoSpatial Solutions ’ dataset by state (Figure 26). This map shows the corporate management category query builder from th e subscribers’ data set. The corporate management code is divided by GeoSpatial Solutions into four different groups. The map shows each of these four groups in a different color and it shows the count of subscribers that fit the categories (Figure 27).

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49 Table 10. GeoSpatial Solution’ corporate management codes. Categories Total Subscribers Percent of Total Owner/President/CEO 4,39844.8% Senior Manager 2,52425.7% VP/Director/Manager Sales and Marketing 1,45614.8% Other Corporate Management 1,43814.7% Total 9,816 100% Information Technology : This map shows a general representation of all the subscribers that fit on the Title Code (Code 31) list (the category of inform ation technology). This category is selected from the general subscribers list and an indi vidual layer of these subscribers was created to show their representation in the US (Figure 28). This ma p represents the percent of information technology subscribers of GeoSpatial Solutions ’ dataset by state (Figure 29). This map shows a deeper analysis of the Information Technology code. The information technology code is broken into six categories, which were selected by the subscribers when they filled out the card for their subscription. Also, the total count for each of these six categories was pr oduced. The six categories are: Table 11. GeoSpatial Solutions’ information technology (MIS/IS). Code Description Total Subscribers Percent of Total 5 Senior Manager 46914.1%

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50 Table 11. Continued Code Description Total Subscribers Percent of Total 6 Manager-Information Technology/Systems 1,21636.7% 7 Applications Developer 66420% 8 In-House User Support Representative 38611.6% 9 Internet/Web Designer/Developer 2758.3% L Other IS or IT Staff 3079.3% Total 3,317 100% The map shows these categor ies and their respective total counts (Figure 30). Operations This map shows the geographic location of subscribers and their distribution in the United States. The Operations Code is a broad category. This category encompasses many departments and firms. These codes ar e primarily formed by seven subcategories (Figure 31). The following map represents the percent of total count of operations codes of GeoSpatial Solutions ’ database by state (Figure 32). In addition the map shows the operations title codes and each individual category count. The operations code is divide d into eight individual categories.

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51 Figure 22. GeoSpatial Solutions ’ combined organizational affiliation codes processed with ArcMap.

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52 Figure 23. GeoSpatial Solutions ’ combined organizational affiliation codes percent by state processed with ArcMap.

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53 Figure 24. GeoSpatial Solutions ’ individual organizational affiliation codes processed with ArcMap.

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54 Figure 25. GeoSpatial Solutions ’ combined corporate management codes processed with ArcMap.

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55 Figure 26. GeoSpatial Solutions ’ combined corporate management codes percent by state processed with ArcMap.

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56 Figure 27. GeoSpatial Solutions ’ individual corporate management codes processed with ArcMap.

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57 Figure 28. GeoSpatial Solutions ’ combined information technology codes processed with ArcMap.

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58 Figure 29. GeoSpatial Solutions ’ combined information technology codes pe rcent by state processed with ArcMap.

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59 These categories and their counts ar e represented on map (Figure 4-25): Table 12. GeoSpatial Solutions’ operations codes. Code Description Total Subscribers Percent of Total M Senior Manager 634 5.7% N Manager 2,432 22% O Engineer 1,892 17% P GIS Technician 1,249 11.2% Q Geospatial Professionals 2,962 26.6% R Systems Integrator 236 2.1% S Technician/Analyst/Administrator1,453 13.1% T Other Operations 260 2.3% Total 11,118 100% GIS Firms This analysis identifies geographic locatio ns of GIS firms and their submarkets in the US GeoSpatial Solutions made available a data set of companies that receive their magazine. Using this ‘companies’ data set a geographic analysis was done to locate each company by their corresponding latitude and longitude. This map shows the general representation of the GeoSpatial Solutions companies data set and their geographic location. The companies’ list was formed of 647 records (Figure 36). This map shows the submarket for these 647 companies. The three submarkets were created using the summary from the CACI Coder/Plus (ESRI) after geocoding the companies list.

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60 Figure 30. GeoSpatial Solutions ’ individual information technology codes processed with ArcMap

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61 Figure 31. GeoSpatial Solutions ’ combined operations codes processed with ArcMap.

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62 Figure 32. GeoSpatial Solutions ’ combined operations codes percent by state processed with ArcMap.

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63 Figure 33. GeoSpatial Solutions ’ individual operations code s processed with ArcMap.

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64 The submarkets were categorized usi ng the top 20 metro areas; the primary submarket ranging from the 4% and above, th e secondary submarket from 2% to 3.9%, and the tertiary submarket from 1.9% and be low. Also, figure 33 shows the companies’ counts for each market. The tertiary market has the highest count with 321 companies, the secondary submarket has a count of 170 co mpanies, and the primary submarket has a count of 156 companies (Figure 33). The next map illustrates GeoSpatial Solutions ’ companies dataset percent of total by state (Figure 34). To get a better understanding of the influences of GeoSpatial Solutions in each state a percentage rate of firms by state was analyzed. To analyze this data set further, data of Establishments (firms) from US Census Bureau from 2000 was acquired. This new data and the data made available by GeoSpatial Solutions was processed through the following formula: (Firms / Establishment) 1000 = Rate of Companies The analysis was executed using Microsof t Excel and a graph of the rates of companies by state was created (Table 9). The result was a high concentration of companies located in Colorado, and a lower concentration in New Mexico, Virginia, Maryland, and lower concen trations in the othe r states (Figure 35). Table 13. GeoSpatial Solutions ’ percentage of companies by state using data from the US Census Bureau. Percentage Rate of Companies by State Estates GeoSpatial Solutions Companies EstablishmentRate of Companies by 1000 Colorado 77115,8930.66 New Mexico 1038,3200.26 Virginia 36155,9850.23 Maryland 23113,4810.20 Georgia 34175,2500.19

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65 Table 4-10. Continued Estates GeoSpatial Solutions CompaniesE stablishmentRate of Companies by 1000 New Hampshire 633,1460.18 California 123693,9870.18 Massachusetts 27154,3850.17 Alabama 1491,4720.15 Utah 746,4730.15 Montana 427,1400.15 Oregon 1088,2920.11 District of Columbia 217,8170.11 Washington 15142,6530.11 Vermont 219,0970.10 Connecticut 883,1450.10 Texas 40420,1390.10 Idaho 331,9910.09 Florida 34372,1320.09 Minnesota 11120,6680.09 Arizona 998,8340.09 Maine 333,7210.09 Kentucky 781,9350.09 Missouri 9130,2690.07 Nebraska 344,0290.07 Wisconsin 8125,6000.06 Wyoming 115,7130.06 Pennsylvania 16267,5460.06 Ohio 14246,2100.06 Mississippi 354,3680.06 Iowa 473,4360.05 Louisiana 592,0920.05 New Jersey 11205,0430.05 West Virginia 237,8000.05 Nevada 240,2110.05 Delaware 120,4780.05 South Dakota 121,0370.05 South Carolina 486,7700.05 Kansas 367,1390.04 New York 19429,3970.04 North Carolina 8181,3060.04 Illinois 11273,4210.04 Rhode Island 125,1390.04 Oklahoma 376,5660.04 Tennessee 4119,3620.03 Michigan 4210,5080.02 Arkansas 156,2350.02 Indiana 2133,2260.02 North Dakota 018,3080.00 Source: U.S. Census Bureau Public Information Office

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66 Figure 34. GeoSpatial Solutions ’ US companies data set processed with ArcMap.

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67 Figure 35. GeoSpatial Solutions ’ US companies data set percent by state processed with ArcMap.

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68 Figure 36. GeoSpatial Solutions ’ percentage of companies by state usin g data from the US Census Bureau.

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69 GeoSpatial Solutions Percent Companies by State 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70C o lor a do N e w Me x ico Virg in ia Mary l and Georgia N e w Hampshire C a lif o rn ia Massac h usett s Alabama U t a h Monatana Oregon D is trict o f C o lumbia W a s h ington Ver m ont C o nn e c t icut Te x as Idah o Florida Minnes o t a Arizon a Maine Ken t ucky Misso u ri N e bras k a W is consin W y o min g Pen n sylavan ia Ohi o Mississ ip pi Iow a Louis ia na N e w Jer s e y W e s t Virgini a N e v a da D e lawar e Sou t h Dak o t a Sou t h Caroli n a Kan s as N e w York N o rth C a rol in a Ill in ois R h od e I sland Oklah o ma Te n ness e e Michiga n Arkan s as India n aStatesPercent by 1,000 Figure 37. GeoSpatial Solutions ’ percentage rate of companies by state using data from the US Census Bureau.

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70 CHAPTER 5 SOCIAL-ECONOMIC CORRELATIONS This analysis identifies social-economic (LSP) influences of sub markets with a high concentration of GIS fo r their location in the US. The social-economic correlation directly an d/or indirectly affe cts the location of GIS industries in a specific area, city, or state. High Concentration Regions The market analysis identifies geographi c location areas with high concentration regions of GIS. A further analysis of GeoSpatial Solutions ’ subscribers was performed to better understand and graphically see which metr opolitan areas have high concentrations of subscribers in the United States. To analyze GeoSpatial Solutions ’ market more in depth, the top metropolitan areas were created. Using the summary created by CACI Coder/Plus (ESRI), three sub markets were selected from the Top 20 Metropolitan Statistical Areas (Table 14). Then, based on a percentage count, a map of t op metropolitan areas was created. Table 14. Geocoding match level summary of top 20 metropolitan areas by percentage of subscribers from CACI Coder/Plus. Record Count Percent of Total Subscribers Top 20 Metropolitan Areas Washington, DC (8840) 1,372 5.3% Los Angeles-L.Beach (4480) 657 2.5% Boston-Wor-Law-Lw-Br (1123) 576 2.2% Chicago, IL (1600) 566 2.2%

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71 Table 5-1. Continued Top 20 Metropolitan Areas New York, NY (5600) 486 1.9% Atlanta, GA (0520) 421 1.6% Denver, CO (2080) 421 1.6% San Diego, CA (7320) 387 1.5% Houston, TX (3360) 383 1.5% Philadelphia, PA-NJ (6160) 359 1.4% Minneapolis-St. Paul (5120) 326 1.3% Seattle-Bellev-Ev’tt (7600) 321 1.2% Dallas, TX (1920) 304 1.2% Orange County, CA (5945) 298 1.1% Baltimore, MD (0720) 295 1.1% St. Louis, MO-IL (7040) 279 1.1% Oakland, CA (5775) 259 1.0% Phoenix-Mesa, AZ (6200) 255 1.0% Sacramento, CA (6920) 255 1.0% Riverside-San Bern. (6780) 247 0.9% Other MAs 13,219 50.8% Records not in an MA 4,338 16.7% These submarkets were divided into prim ary, secondary, and tertiary markets based on the percentage count of subscribers in each metropolitan area (Table 15). This map also shows the three sub mark ets and their specif ic counts for each metropolitan area (Figure 38). These three sub markets were divided according to their percentage levels. The primary market is fo rmed by subscriber count percentages of 4% or higher. The secondary sub market is made up of percentages between 2% and 3.9% of subscribers. The tertiary s ubmarket is comprised of per centages between 1.1% and 1.9% of total subscribers. To create this map fr om the subscribers’ data set, the MSA was

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72 Figure 38. GeoSpatial Solutions ’ top metropolitan areas by subscr ibers processed with ArcMap.

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73 selected. Metropolitan Statistical Area code s were produced using CACI Coder/Plus (ESRI) produced. The primary sub market is formed by the MSA code 8840, which corresponds with the Washington, DC area. The secondary sub market is formed by the MSA codes: 4480, the Los Angeles-L Beach area; 1123, the Boston-Wor-Law-Lw-Br area; 1600, and the Chicago, IL area. The tertiary sub market is formed by the MSA codes: 5600, the New York area; 0520, the Atlanta area; 2080, th e Denver area; 7320, the San Diego area; 3360, the Houston area; 6160, the Philadelphia, PA-NJ area; 5120, the Minneapolis-St. Paul area; 7600, the Seattle-Bellev-Ev’tt ar ea; 1920, the Dallas area; 5945, the Orange County area; 0720, the Baltimore, MD area; and 7040, the St. Lois, MO-IL area (Figure 39). Table 15. Identification of metropolitan areas by count of subscribers from CACI Coder/Plus

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74 Figure 39. GeoSpatial Solutions ’ top metropolitan areas by count processed with ArcMap.

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75 Also, a geographic representa tion of the data set of GeoSpatial Solutions companies was created to show their ge ographic location in the United States. To take the analysis of the metropolitan areas one step further, the primary and secondary MSAs (Metropolitan Statistical Ar eas) were analyzed individually, and maps for each of the high concentration areas of the metropolitan areas were also included. Primary Sub Market Figure 40 shows the metropolitan areas of Maryland, Virginia, and Washington DC. This is the strongest sub market in the US for GeoSpatial Solutions subscribers. There is a concentration of subscribers in th e Washington, DC area; this could be because of the uses of GIS in the government environment. Also, it may be due to an increase in companies and subscribers in this area because of the recent budget al locations granted to the home land defense agency. Secondary Sub Market Figure 41 shows the secondary metropolitan area, Los Angeles, which is a sub market area containing a high c oncentration of subscribers in the US. This might be because Los Angeles is a high technology i ndustry, which brings a high market for GIS products. This map shows the secondary sub mark et that locates in the Massachusetts and New Hampshire area. The highest concentra tion locates in the Suffolk and Middlesex areas (Figure 42). This map shows the secondary sub market that locates in the Illinois area. The highest concentration is in Cook County (Figure 43). The tertiary sub market was also created using the MSA; however the representation of the first two markets show s a more important characteristic for this analysis. Further analys is of the tertiary sub market can show new and interesting sub

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76 Figure 40. GeoSpatial Solutions ’ high concentration areas in Maryla nd/Virginia proce ssed with ArcMap.

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77 Figure 41. GeoSpatial Solutions ’ high concentration areas in Ca lifornia processed with ArcMap.

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78 Figure 42. GeoSpatial Solutions ’ high concentration areas in Massachusetts /New Hampshire processed with ArcMap.

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79 Figure 43. GeoSpatial Solutions ’ high concentration areas in Il linois processed with ArcMap.

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80 markets where GeoSpatial Solutions could increase their subs criptions and market area. So further analysis may be an increasing a dvantage and an important judgment (category 4 of geographic reasoning) for the company. Education The following analysis documents the influe nces of education to attract the GIS market to the region. To do this analysis th e map for business code University/College, code 35, was overlain with the GIS business ma ps. This overlay creates a new layer or map of education and this show s the correlations between the GeoSpatial Solutions companies list and the University/Education codes. Figure 44 shows the total education market in the United States. The data set for this map was extracted from the subscribers list using the organizational affiliate code for University/College, code 35. Using this data a new layer was created which shows the geographic location of universities and colleges in the US. The result of these layers were buffered ( buffering creates a circular area selected within a specified radius of the University/Col lege code data set. Four buffers at varying mile radiuses were formed. These four buffers were established for 10, 12, 15, and 18 miles and applied to the subscriber data to s ee its characteristics. These buffers show the influence of the educational sect or to attract the GIS market to its area. These buffers, of 10, 12, 15, and 18 miles, were selected in or der to find the business geography standard of 80% (where 80% of the va lues locate near a target). Buffer at 10 Miles Figure 5-8 shows the geographic location of all the universities and colleges, from GeoSpatial Solutions ’ data code 35, in the US. These locations where buffered to a 10 miles radius. The buffer and the locati ons were added to the same layer.

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81 Figure 44. GeoSpatial Solutions ’ education business code US market processed with ArcMap.

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82 Figure 45. GeoSpatial Solutions ’ US education market with a buffer at 10 miles processed with ArcMap.

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83 Buffer at 12 Miles Figure 46 shows all the market for th e universities and colleges, from GeoSpatial Solutions ’ data code 35, with a geographic locati on within the 12 miles radius. Then the two layers were overlapped to shows the educational market and the correspondent 12 miles buffer. Buffer at 15 Miles Figure 47 shows the geographic location of all the universities and college in the US. Also, it shows a buffer of 15 miles radius from each location. Buffer at 18 Miles Figure 48 shows the geographic location of universities and colle ges based on their latitude and longitude. The layer of this location was buffered to an 18 miles radius. Market Attraction Also, to analyze the influen ces of the education from the GeoSpatial Solutions companies’ data set, the company map was us ed to identify the location of the companies inside the four buffers and indicate the pe rcentages of companies that locate near a university or college for each area. This map represents the 647 company locations provided by GeoSpatial Solutions in the US (Figure 49). The company and the buffer maps were overlapped to form new data and layers. These new layers were creat ed to show the Education Market Attraction for GIS companies to locate near universities and colleges. Table 16 represents the percentage of total companies from the GI S market that fit the 10, 12, 15, and 18 miles buffers from an educational institution.

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84 Figure 46. GeoSpatial Solutions ’ US education market with a buffe r at 12 miles processed with ArcMap

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85 Figure 47. GeoSpatial Solutions ’ US education market with a buffer at 15 miles processed with ArcMap.

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86 Figure 48. GeoSpatial Solutions ’ US education market with a buffer at 18 miles processed with ArcMap.

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87 Figure 49. GeoSpatial Solutions ’ US companies dataset processed with ArcMap.

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88 Table 16. GIS market attracted to the education market. Market Attraction at 10 Miles To create this map two layers were overlaid together. The map for the 647 companies in the US and the university/college map that was buffered to a 10 miles radius were overlaid. This map shows the relationship between th e education and the company sectors. An analysis of the da ta set showed 466 companies of 647 total companies located inside this 10 miles ra dius (Figure 50). Correspondingly, this is 72.02% of the total companies in the US subscribed to GeoSpatial Solutions (Figure 51). Market Attraction at 12 Miles Overlapping the companies layer with th e universities/colleges layer that was previously buffered to a 12 miles radius created this map. The map shows all the companies that locate within a 12 miles radi us from the educational market. There are 488 companies that locate inside this 12 miles radius (Figure 52). This represents 75.43% of the total companies in the US (Figure 53). Market Attraction at 15 Miles This map shows the companies layer and th e university/college buffer at a 15 miles radius (Figure 54). After overlaying these two layers the data set shows that there are 504 Buffer (miles) Total Companies Companies in Buffer Percent of Total Companies 10 647 466 72.02% 12 647 488 75.43% 15 647 504 77.9% 18 647 520 80.37%

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89 companies located inside this radius. Th ese 504 companies represent 77.9% of the 647 companies in the US (Figure 55). Market Attraction at 18 Miles This map was created using the data set extr acted from the subscribers list using the Organizational Affiliation code for the University/College Code 35. Also, the data set that GeoSpatial Solutions made available with a total count of 647 companies. The two

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90 Figure 50. GeoSpatial Solutions ’ US education market attraction at 10 miles radius processed with ArcMap.

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91 Figure 51. GeoSpatial Solutions ’ US education market attraction percentage at 10 miles radius processed with ArcMap.

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92 Figure 52. GeoSpatial Solutions ’ US education market attraction at 12 miles radius processed with ArcMap.

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93 Figure 53. GeoSpatial Solutions ’ US education market attraction percentage at 12 miles radius processed with ArcMap.

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94 Figure 54. GeoSpatial Solutions ’ US education market attraction at 15 miles radius processed with ArcMap.

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95 Figure 55. GeoSpatial Solutions ’ US education market attraction percentage at 15 miles radius processed with ArcMap.

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96 layers created with this data were overlappe d to understand the attr action of the education industry on the companies subscribed to the magazine. The univers ity/college layer was buffered to an 18 miles radius, which it is no t an uncommon distance for a student or an employee to commute to and from their working or studying environment. When buffering was processed and all the companies that located at 18 miles from and college or university a surprising resu lt. The data set shows that 520 companies out of 647 locate at this distance from any uni versity/college categ ory (Figure 56). This is an outstanding 80.37% of the total company list (Figure 57). Th is is a very important discovery for the GIS and education industries. This finding show s that 8 out of 10 GIS firms locate within 18 miles of a college or university. So, ther e is a social or economic influence causing companies to locate near the education i ndustry. Maybe these companies located near their market suppliers in order to attract and recruit new grad uates from these institutions. Does a spatial attraction for these companies’ locations exist? If a spatial attraction is present, who is the beneficiary? Using the data that the buffer for 18 miles gave, a count of MSAs of the companies that fit this buffer was created. This count was linked to all the ma in universities and a ranking of these universities was determined. This ranking represents which universities influence the GIS market to lo cate in their area (Table 17) Further analysis should be done to understand each university’s in fluence to their individual market. Table 17. University ranking of comp anies market by count based on MSAs. University Ranking of Companies Market Universities City State Companies Count CU-Denver Denver CO 41 Colorado School of Mines Golden CO 41 Univ of Denver Denver CO 41

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97 Table 5-4. Continued Universities City State Companies Count American Univ Washington DC 38 George Mason Univ Fairfax VA 38 George Washington Univ Fairfax VA 38 Univ of DC Washington DC 38 Univ of Maryland Alexandria VA 38 Emory Decatur GA 29 GeorgiaTech Atlanta GA 29 Georgia State Univ Atlanta GA 29 Spelman College Atlanta GA 29 Univ of West Georgia Carrollton GA 29 Babson College Babson Park MA 26 Boston Univ Boston MA 26 Bridgewater State Coll ege Bridgewater MA 26 Clark Univ Worcester MA 26 MIT Cambridge MA 26 Salem State College Salem MA 26 Univ New Hampshire Durham NH 26 Univ of Massachusetts Boston MA 26 Worchester State College Worcester MA 26 San Jose State Univ San Jose CA 22 Stanford Univ Stanford CA 22 Sam Houston State Univ Spring TX 21 Univ of Houston Houston TX 21 California Poly Pomona Pomona CA 17 California State Northridge West Hills CA 17 California State Univ Los Angeles CA 17 California State Univ Northridge CA 17 Univ of California Los Angeles CA 17 Univ of California Valencia CA 17 Univ of Southern California Los Angeles CA 17 San Diego State Univ San Diego CA 16 Univ California/San Diego La Jolla CA 16 Univ of Colorado Boulder CO 16 Univ of California at Berkeley Berkeley CA 15 San Francisco State Univ San Francisco CA 14 Sonoma State Univ Belvedere-Tiburo CA 14 Univ of California San Francisco CA 14 California State Univ Long Beach Westminster CA 13 Univ of California at Irvine Irvine CA 13

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98 Figure 56. GeoSpatial Solutions ’ US education market attraction at 18 miles radius processed with ArcMap.

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99 Figure 57. GeoSpatial Solutions ’ US education market attraction percentage at 18 miles radius processed with ArcMap.

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100 Firms The analysis shows the influences of the sub markets to attract GIS firms to the region. The market was then analyzed by their LSP’s (Lifestyle Segmentation Profiles) to see which categories have a higher influence and attraction to the specific geographic areas. CACI Coder plus produced a table with the specific char acteristics of the subscribers Lifestyle Segmentation Profile a nd their percentage (Table 17) and also CACI Coder plus produced a tabl e for the charac teristics of GeoSpatial Solutions subscriber firms, represents the percentage of subscribers in each LSP (Table 18). Table 18. GeoSpatial Solutions ’ subscribers LSP’s. Subscriptions GeoSpatial Solutions Customer Penetration U.S. ACORN Description Number % Per 1000 Number % Index 1 Affluent 1A Top One Percent 3831.50.31 1,248,8611.2125 Families 1B Wealthy Seaboard Suburbs 7142.80.32 2,220,1262.1131 1C Upper Income Empty Nesters 7102.70.31 2,319,0622.2125 1D Succes sful Suburbanites 9833 .80.38 2,555,2302.4157 1E Prosperous Baby Boomers 1,55960.31 5,000,2634.7127 1F Semirural Lifestyle 1,3925.40.24 5,681,6925.4100 2 Upscale 2A Urban Professional Couples 1,29350.31 4,212,2264125 Households 2B Baby Boomers With Children 9593.70.23 4,177,326494 2C Thriving Immigrants 3121.20.19 1,654,8791.677 2D Pacific Heights 2841.10.35 807,9610.8143 2E Older Settled Married Couples7352.80.16 4,467,4314.267 3 Up & Coming 3A High Rise Renters 1,1244.30.47 2,395,6822.3191 Singles 3B Enterprising Young Singles 1,3685.30.34 4,082,7113.9137 4 Retirement 4A Retirement Communities 4761.80.35 1,365,1721.3142 Styles 4B Active Senior Singles 7042.70.25 2,866,3292.7100 4C Prosperous Older Couples 7152.80.21 3,463,7783.384 4D Wealthiest Seniors 2310.90.18 1,295,8161.273 4E Rural Resort Dwellers 1600.60.16 997,6390.965 4F Senior Sun Seekers 2280.90.15 1,474,5141.463 5 Young Mobile 5A Twenty-somethings 1,2304.80.59 2,089,3632240 Adults 5B College Campuses 1,1034.31.35 819,0800.8550 5C Military Proximity 3431.30.5 687,2840.7204 6 City Dwellers 6A East Coast Immigrants 3891.50.15 2,594,1442.561

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101 Table 5-5. Continued ACORN Description Number % Per 1000 Number % Index 6B Working Class Families 1320.50.11 1,210,6081.145 Number % Per 100 0 Number % Ind ex 6C Newly Formed Households 1,1974.60.23 5,180,7604.994 6D Southwestern Families 2911.10.14 2,010,3291.959 6E West Coast Immigrants 1680.70.14 1,218,9451.256 6F Low Income: Young & Old 4741.80.2 2,319,3802.283 7 Factory 7A Middle America 1,1614.50.13 8,615,4438.255 & Farm 7B Young Frequent Movers 7172.80.19 3,787,7253.677 Communities 7C Rural Industrial Workers 5021.90.09 5,898,4505.635 7D Prairie Farmers 1140.40.11 1,055,112144 7E Small Town Working Families26810.15 1,787,8631.761 7F Rustbelt Neighborhoods 4901.90.13 3,829,0343.652 7G Heartland Communities 6912.70.19 3,730,4623.576 Total 25,843 100 0.25 105,480,101 100 100 Table 19. GeoSpatial Solutions’ firms LSP’s. Firms GeoSpatial Solutions Customer Penetration U.S. ACORN Description Number% Per 1000 Number % Index 1 Affluent 1A Top One Percent 182.80.01 1,248,8611.2235 Families 1B Wealthy Seaboard Suburbs 213.20.01 2,220,1262.1154 1C Upper Income Empty Nesters 172.60.01 2,319,0622.2120 1D Succes sful Suburbanites 335. 10.01 2,555,2302.4211 1E Prosperous Baby Boomers 538.20.01 5,000,2634.7173 1F Semirural Lifestyle 345.30.01 5,681,6925.498 2 Upscale 2A Urban Professional Couples 385.90.01 4,212,2264147 Households 2B Baby Boomers With Children 253.90.01 4,177,326498 2C Thriving Immigrants 152.30.01 1,654,8791.6148 2D Pacific Heights 50.80.01 807,9610.8101 2E Older Settled Married Couples 121.90 4,467,4314.244 3 Up & Coming 3A High Rise Renters 4570.02 2,395,6822.3306 Singles 3B Enterprising Young Singles 7311.30.02 4,082,7113.9292 4 Retirement 4A Retirement Communities 162.50.01 1,365,1721.3191 Styles 4B Active Senior Singles 172.60.01 2,866,3292.797 4C Prosperous Older Couples 192.90.01 3,463,7783.389 4D Wealthiest Seniors 20.30 1,295,8161.225 4E Rural Resort Dwellers 30.50 997,6390.949 4F Senior Sun Seekers 71.10 1,474,5141.477 5 Young Mobile 5A Twenty-somethings 3960.02 2,089,3632304 Adults 5B College Campuses 152.30.02 819,0800.8299 5C Military Proximity 10.20 687,2840.724

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102 Table 5-6. Continued 6 City Dwellers 6A East Coast Immigrants 81.20 2,594,1442.550 ACORN Description Number% Per 1000 Number % Index 6B Working Class Families 60.90 1,210,6081.181 6C Newly Formed Households 182.80 5,180,7604.957 6D Southwestern Families 60.90 2,010,3291.949 6E West Coast Immigrants 91.40.01 1,218,9451.2120 6F Low Income: Young & Old 60.90 2,319,3802.242 7 Factory 7A Middle America 111.70 8,615,4438.221 & Farm 7B Young Frequent Movers 1320 3,787,7253.656 Communities 7C Rural Industrial Workers 40.60 5,898,4505.611 7D Prairie Farmers 10.20 1,055,112115 7E Small Town Working Families 40.60 1,787,8631.736 7F Rustbelt Neighborhoods 40.60 3,829,0343.617 7G Heartland Communities 50.80 3,730,4623.522 8 Downtown 8A Young Immigrant Families 20.30 1,050,710131 Residents 8B Social Security Dependents 142.20.02 881,7700.8259 8C Distressed Neighborhoods 10.20 949,0940.917 8D Hard Times 30.50 1,592,2871.531 8E Urban Working Families 30.50 1,635,5161.630 9 Nonresidential 9A Business Districts 71.10.27 26,24304349 Neighborhoods 9B Institutional Populations 101.50.04 223,8010.2728 9C Unpopulated Areas 40.60 000 Total 647 100 0.01 105,480,101 100 100 To see the characteristics of the areas where the companies locate (Figure 58), the total amount of subscribers that locate ar ound the companies was analyzed to understand the companies’ market decisions better. Using a 7 miles and a 20 miles buffer from the companies (these buffers were selected to show different perc entage rates, the total amount of subscribers that fit inside of each of these markets were extracted and analyzed. These analyses created two individual maps one for the 7 miles radius and one for the 20 miles radius. These two distances where decided to give a general re presentation and show th e characteristics of the LSP’s of subscribers in the proximities of the companies. These buffers of 7 and 20 miles were specifically chosen for the firms code because of the characteristic driving flows within large cities and the proximities to suburban areas. The analysis also gave the

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103 percentage rate of the subscribers of GeoSpatial Solutions that located inside of the previous buffers mentioned. Buffer at 7 Miles This map was created to s how what percentage of GeoSpatial Solutions subscribers locate at 7 miles from a company. First, a buffer of 7 miles was created around the companies to find the percentage rate of subscribers. The new buffer layer was overlapped with the layer of total subscribers. Afterward, the subscribers that intersected inside the buffer layer were selected and extracted to create a new layer. The total subscribers remaining that received their subscription in a 7 miles radius from a company, is a total of 8,881, which is equivalent to 34.12% of the total GeoSpatial Solutions subscribers in the United States (Figure 59). Buffer at 20 Miles This map shows how many subscribers re ceived their magazine subscription around the companies. To create this ma p, a 20 miles buffer from the companies layer was created. Then, this new layer was overlapped with the total GeoSpatial Solutions subscribers layer. A selection of subscribers that intersec ted inside the 20 miles buffer was done and a new layer with these subscr ibers was created. The total amount of subscribers that receive d their subscription for GeoSpatial Solutions magazine in the 20 miles radius from a company is 52.43%, an 18.31% increase from the percent of subscribers in the 7 miles radius (see Table 20). This shows that 50% of GeoSpatial Solutions market locates within a 20 miles radi us from the companies (Figures 60). To further understand social-economic char acteristics of the GIS firms to locate in a specific market, the Lifestyle Segmentation Profile of the subscr ibers at the 7 miles radius was analyzed. The analyses were done to see the primary categor ies that locate in

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104 the area. Where the categorie s of LSPs are high, firm are located in prosperous communities or neighborhoods. If the LSP of this area is low, it shows that the firms are not marketing to a high market. This can demonstrate what kind of market the GIS industry prefers to locate. Table 20. GeoSpatial Solutions ’ subscribers at 7 and 20 miles radius from companies. Buffer (miles) Total Subscribers Percent subscribers 7 8,88134.12% 20 13,64452.43% Total 14,525 86.55% LSPs at 7 Miles This map shows the Lifestyle Segmentation Pr ofile of the subscribers that locate at a 7 miles radius from companies. It also s hows the corresponding count for each kind of LSPs in the area. The categories of LSP we re summarized into 9 different groups. These groups correspond to the nine ACORN descriptio ns presented in the Introduction to this thesis (Table 19).

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105 Figure 58. GeoSpatial Solutions ’ US firms dataset processed with ArcMap.

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106 Figure 59. GeoSpatial Solutions ’ subscriber percentage at 7 miles from companies processed with ArcMap

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107 Table 21. GeoSpatial Solutions ’ subscribers LSP’s at 7 miles radius from companies. ACORN Description Count 1 Affluent Families 2,398 2 Upscale Households 1,356 3 Up and Coming Singles 1,391 4 Retirement Styles 834 5 Young Mobile Adults 868 6 City Dwellers 811 7 Factory and Farm 309 8 Downtown Residents 463 9 Non Residential Neighborhoods 448 There is a high amount of subscribers that fit into the Affluent Families, Upscale Households, and Up and Coming Singles ACOR N descriptions and locate in a 7 miles radius from the companies (Figure 61). This analysis highlights the reasons that some GIS groups locate near the education market. Maybe these locations are chosen for these

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108 Figure 60. GeoSpatial Solutions ’ subscriber percentage at 20 miles from companies processed with ArcMap.

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109 companies to select graduates with higher education or maybe these companies can use students to do internships. The decision to lo cate near education also enables employers to select a fresh group of graduates that can bring innovation to the company. As most of the technology market is easy to see bases in the three highe st categories of LSPs that surround these companies that the GIS firms lik e to locate in high-level markets. To understand the reasons for companies to locate in a more economically prosperous area, such as the top 3 ACORN categories previous ly mentioned, further and more complete analyses should be completed.

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110 Figure 61. GeoSpatial Solutions ’ subscriber Lifestyle Segmentation Profiles at 7 miles from companies processed with ArcMap.

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111 CHAPTER 6 CORRELATION OF ANALYSIS WITH INTERNATIONAL GEOGRAPHIC REGIONS Global Analysis The analysis addresses the relevant questi ons for use in a glob al perspective for international market analysis. This assists international markets and increase economic opportunities by focusing on the GIS i ndustry and its ch aracteristics. GeoSpatial Solutions made their global market data set availa ble for this analysis This data set was formed of 167 companies located in different countries. The majority of these companies, however, were located in Canada. This da ta set shows a general idea of where GeoSpatial Solutions ’ international market is located, and how many subscribers are in each location. This is not a representation of where the GIS market locates in a global perspective, and this analysis should not be used to demonstr ate the GIS market for ces in other countries as the data set is specifically for the GIS global market of GeoSpatial Solutions subscribers. Global Market Figure 62 shows the global location of all the companies that are part of GeoSpatial Solutions’ data set. This global data set includes: Europe, Asia, Austra lia, Africa, South America, Canada, and the United States. Th e following table summarizes the number of international companies in the GeoSpatial Solutions’ firms dataset in addition to the percentage of total companies liste d by geographical ar ea (see Table 20).

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112 Table 22. Percent of total companies in each market as defined in international maps. Global Market International CompaniesPercent Africa 20.3% Asia 131.6% Australia 50.6% Canada 8510.5% Europe 546.7% South America 20.3% United States 64880% Total 809 100% Europe Figure 63 of Europe shows part of the data set of GeoSpatial Solutions The map shows companies that are located in the European market and Russia. Asia & Australia Figure 64 shows the international markets of Asia and Australia that locates in India, Australia, Japan, Korea, and Paki stan. These companies are part of the GeoSpatial Solutions international data set. Africa Figure 65 shows the international data for those companies located in Africa. This map was created using the data set provided by GeoSpatial Solutions

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113 Figure 62. GeoSpatial Solutions global market subscribers’ processed with ArcMap.

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114 Figure 63. GeoSpatial Solutions global market subscribers’ Eu rope processed with ArcMap.

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115 South America Figure 66 shows the internati onal companies in South America. The international data set of GeoSpatial Solutions was used to locate these companies. Canada Figure 67 shows the Canadian market. This map was created with the data set of international companies provided by GeoSpatial Solutions The data shows a concentration of companies in major metropolitan areas of Canada. The data shows an even distribution of companies located in the east and west of Canada.

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116 Figure 64. GeoSpatial Solutions global market subscribers’ Asia a nd Australia processed with ArcMap.

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117 Figure 65. GeoSpatial Solutions global market subscribers’ Africa processed with ArcMap.

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118 Figure 66. GeoSpatial Solutions global market subscribers’ Sout h America processed with ArcMap.

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119 Figure 67. GeoSpatial Solutions global market subscribers’ Ca nada processed with ArcMap.

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120 CHAPTER 7 CHARACTERISTICS OF GIS PRODUCERS This analysis summarizes ge neral characteristics of GeoSpatial Solutions’ dataset (representative of the GIS industry) for their location in the US and their general reasons for locating in a specific submarket. To expl ain these characteristics, consideration was taken for the social-economic influences. These social-economic influences were analyzed in Chapter 5 and include high concen tration regions, educat ion, firms, and LSP characteristics. All of these characteristics came together to create a thorough and telling analysis of the market for the GIS industry to locate and open new markets based on the GeoSpatial Solutions subscribers. Also, the adva nces of technology, more userfriendliness, and faster Inte rnet access have affected a nd improved these markets. The increases in the market have encouraged the use of consulting firms to do similar analyses, and the improvements in the indus try have provided individuals with the education and knowledge of the industry, gi ving them more employment options. Also the industry’s high growth has created new su bmarkets for the GIS industry in the US and globally. While analyzing the data that GeoSpatial Solutions made available to use, distinguishable characteristics of geographi c locations were made clear. Some of the geographic decisions influenci ng the GIS industry to locate their enterprises in the US could be explained in the overview of Chapter 5. Chapter 4 shows the main characteristics of the high concentrations of subscribers in the top metropolitan areas. Th ese high concentrations are not surprising since the areas

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121 correspond to areas of high populat ion are high concentration. In this case, there is a continued correlation between the high me tropolitan areas in the US and the high concentration of subscribers of GeoSpatial Solutions Chapter 5 demonstrates a deeper analysis of the GIS industry characteristics or attraction to specific market areas. The analysis for this part of Chapter 5 was done to see if there were any correlations between th e GIS industry and high education areas. During this analysis an outstanding statistic was revealed. The GI S industry has a location bias based on higher education areas. The analysis showed that 72.02% of GeoSpatial Solutions GIS firms data set located within a 10 miles buffer from any university or college and 80.37% of the total firms loca ted within an 18 miles radius from any university or college location. This may show that the GIS market is attracted to higher educational areas where they can obtain recent graduates. A chart of the rank of universities that attract mo st of the GIS market is included in Chapter 5. The latter part of Chapter 5 was analyzed in a different way; this part of the chapter shows where the subscribers locate from the GIS market and their Lifestyle Segmentation Profiles (LSPs). Knowing the LSPs of their subscribers may show GeoSpatial Solutions what kind of market these firms have pref erences toward. The analysis showed that 34.12% of the total subscribers locate within 7 miles of any firm, and 52.43% of the total locate within a 20 miles radius from any fi rm. This analysis shows that half of GeoSpatial Solutions ’ subscribers market localizes within a 20 miles radius fr om the GIS market. While analyzing the Lifestyle Segmentation Prof iles of the subscribers within 7 miles of the firms a surprising 60% of these total subs cribers fit on the three higher categories of LSPs. This represents that the GIS markets lo cates in more expensive markets. This could

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122 be because most of the GIS market is a hi gh technology market. Also, it may be because the GIS market takes advantage of the know ledge spillover from the universities and colleges, and even from other high technology companies; or maybe it is because of the labor market pooling effect in which mo st high tech companies participate. These localization characteristics could be further proved with more analysis of each individual market is performed and furt her characteristics of why the GIS market locates in specific areas could be revealed. Also, these same characteristics of the GIS market may influence the international market to locate where they locate. However, the international market may also be affected by other social-economic influences for each country. To understand the global market analysis, statistical figures should be used and compared to the global picture. The GeoSpatial Solutions market, being one of the leading professional publications in the GIS industry, represents a general and complete characteristic of the GIS market in the United States. To conclude, this analysis has identif ied the 3 primary market areas of GIS production within the US for GeoSpatial Solutions. The primary US submarket includes: California, Texas, Florida, New York, and Virginia. The secondary US submarket includes: Pennsylvania, Colorado, Illinois, Ohio, Maryland, Washington, New Jersey, North Carolina, Michigan, Georgia, Massac husetts, Minnesota, and Wisconsin. And the tertiary submarket includes the remaining US states (see Chapter 4, Table 5 for complete listing). The tertiary market provides the greatest potenti al of growth for GeoSpatial Solutions Due to the dense population in these geogr aphic areas, it is not surprising that they have been identified as the top 3 markets of GIS production. Further, the major social-economic correlates between these hi gh concentration submarkets have been

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123 pinpointed. Included in these social-economic correlates are: education, firms, and Lifestyle Segmentation Profiles (LSPs) (review Chapter 5, Table 16-17). Moreover, this thesis outlines the characteristics of GIS fi rms as locating near e ducational institutions and in high LSP areas (refer to Chapter 5, Ta ble 21). In addition, it has been determined that this information can be used as a gui de for other submarkets, including foreign markets, to capitalize on econom ic opportunities with the use of GIS. As seen in Chapter 6, Table 22 the opportunities for international growth abound. This thesis has provided an analysis of the subscriber base of GeoSpatial Solutions to locate GIS users in the US and abroad, the research can be adapted by ot her publishing companies as well as other industries to determine where their clients ar e and gain insight on how to better serve the market.

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124 APPENDIX A GEOGRAPHIC MATCH LEVEL FOR SUBSCRIBERS In this appendix, a geocoding summar y, created with the process of GeoSpatial Solutions subscribers’ data set and the use of CACI Coder/Plus (ESRI), is outlined. This section supplements the analysis of subscribers found in Chapter 4 and the analysis of Lifestyle Segmenta tion Profiles found in Chapter 5. During the analysis of the dataset the t op 20 zip codes a correlation between these zip codes and the subscribers was found. A re view of specific zip codes reveals a relation between the top zip codes and leadi ng organizations in the geospatial industry. For example, zip code 92373 is located in Redlands, CA—the home of Environmental Systems Research Institute (E SRI); zip 20910 is in Silver Springs, MD the home of the National Oceanic and Atmospheric Ad ministration (NOAA); and zip 21401 in Annapolis, MD is the location of the Envir onmental Protection Agency (EPA). Further research of the top 20 zip codes can be done to find additional correlations between zips and industry leaders.

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125 Geocoding Match Level Summary File: C:\Text\Grant\GeoSpatial_Solutions\subscr iptions\geocode\New_add\new_geocode\ge omap3_c_xy.dbf Subscriptions GeoSpatial Solutions Number of Records: 26,024 Match Description Match Code Number Percent Street Match S 19,101 73.4% Dominant Tract in ZIP CodeZ 5,537 21.3% One Tract in ZIP CodeT 850 3.3% No Geocode X 536 2.1% 26,024 100.0% Match Description ESRI BIS assigns your customer record s to one of four match levels. The best match level is Street Addre ss or ZIP+4. If a record cannot be matched at the Street Address or ZIP+4 levels, the Geo-Fix option can assign a census tract thr ough a ZIP Code to census tract correspondence. The census tract with the largest popul ation in the ZIP Code is appended to the record. This match is referred to as a Dominant Tract in ZIP Code (Z) match. If the ZIP Code is buil t from only one census tract, then the match code (T) denotes only one tract in the ZIP Code. If an address is assigned a “No Ge ocode”, no match was possible below the county level. Post office boxes, rural routes or drops, or incomplete addresses can preclude a match. Addr esses outside the U.S. cannot be matched either. ZIP Code to Census Tract Correspondence Summary Census tracts, and in nontracted ar eas, block numbering areas (BNAs), are assigned to residential ZIP Code s by overlaying the centroids of the component blocks on ZIP Code boundaries. Expressed as latitude/longitude coordinates, cen troids approximate the geographic centers of blocks. If the centroid of a block falls within the ZIP Code, it is included. Blocks are then aggregat ed, and the ratio of the block totals to tracts/BNAs is used to create the ZIP Code to census tract correspondence. Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 6/3/2003 West: (800) 394-3690 FAX: (858) 677-5420

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126 Customer Geographic Summary File: C:\Text\Grant\GeoSpatial_Solutions\subscrip tions\geocode\New_add\new_geocode\geomap3_c_xy.dbf Subscriptions GeoSpatial Solutions Number of Records: 26,024 Record Count Percent Top 20 States California (06) 3,286 12.6% Texas (48) 1,564 6.0% Florida (12) 1,429 5.5% New York (36) 1,271 4.9% Virginia (51) 1,179 4.5% Pennsylvania (42) 955 3.7% Illinois (17) 872 3.4% Colorado (08) 869 3.3% Ohio (39) 832 3.2% Maryland (24) 772 3.0% Washington (53) 677 2.6% New Jersey (34) 661 2.5% North Carolina (37) 630 2.4% Michigan (26) 627 2.4% Georgia (13) 609 2.3% Massachusetts (25) 599 2.3% Minnesota (27) 520 2.0% Wisconsin (55) 512 2.0% Missouri (29) 504 1.9% Oregon (41) 487 1.9% Other States 6,633 25.5% Non-geocoded Records 536 2.1% Top 20 Counties Los Angeles, CA (06037) 657 2.5% Fairfax, VA (51059) 430 1.7% San Diego, CA (06073) 387 1.5% Cook, IL (17031) 317 1.2% Harris, TX (48201) 310 1.2% Orange, CA (06059) 298 1.1% King, WA (53033) 263 1.0% Maricopa, AZ (04013) 249 1.0% Santa Clara, CA (06085) 233 0.9% Montgomery, MD (24031) 231 0.9% Dallas, TX (48113) 199 0.8% Sacramento, CA (06067) 197 0.8% New York, NY (36061) 195 0.7% District of Columbia, DC (11001) 187 0.7% Middlesex, MA (25017) 184 0.7% Alameda, CA (06001) 173 0.7% Miami-Dade, FL (12086) 159 0.6% Travis, TX (48453) 156 0.6% Franklin, OH (39049) 149 0.6% San Bernardino, CA (06071) 142 0.5% Other Counties 20,372 78.3% Non-geocoded Records 536 2.1% Record Count Percent Top 20 ZIP Codes 80225 Denver, CO 62 0.2% 92373 Redlands, CA 55 0.2% 95814 Sacramento, CA 39 0.1% 22030 Fairfax, VA 36 0.1% 63010 Arnold, MO 35 0.1% 65401 Rolla, MO 35 0.1% 20192 Herndon, VA 33 0.1% 20910 Silver Spring, MD 32 0.1% 94025 Menlo Park, CA 32 0.1% 80112 Englewood, CO 31 0.1% 80202 Denver, CO 31 0.1% 21401 Annapolis, MD 30 0.1% 40601 Frankfort, KY 30 0.1% 87109 Albuquerque, NM 29 0.1% 20191 Reston, VA 28 0.1% 22315 Alexandria, VA 27 0.1% 95616 Davis, CA 26 0.1% 20171 Herndon, VA 25 0.1% 20190 Reston, VA 24 0.1% 57198 Garretson, SD 24 0.1% Other ZIP Codes 25,360 97.4% Records with no ZIP Code 0 0.0% Top 20 Metropolitan Areas Washington, DC (8840) 1,372 5.3% Los Angeles-L.Beach (4480) 657 2.5% Boston-Wor-Law-Lw-Br (1123) 576 2.2% Chicago, IL (1600) 566 2.2% New York, NY (5600) 486 1.9% Atlanta, GA (0520) 421 1.6% Denver, CO (2080) 421 1.6% San Diego, CA (7320) 387 1.5% Houston, TX (3360) 383 1.5% Philadelphia, PA-NJ (6160) 359 1.4% Minneapolis-St. Paul (5120) 326 1.3% Seattle-Bellev-Ev’tt (7600) 321 1.2% Dallas, TX (1920) 304 1.2% Orange County, CA (5945) 298 1.1% Baltimore, MD (0720) 295 1.1% St. Louis, MO-IL (7040) 279 1.1% Oakland, CA (5775) 259 1.0% Phoenix-Mesa, AZ (6200) 255 1.0% Sacramento, CA (6920) 255 1.0% Riverside-San Bern. (6780) 247 0.9% Other MAs 13,219 50.8% Records not in an MA 4,338 16.7%

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127 Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 6/3/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com Customer ACORN Profile File: C:\Text\Grant\GeoSpatial_Solutions\subscr iptions\geocode\New_add\new_geocode\ge omap3_c_xy.dbf Subscriptions GeoSpatial Solutions Customers Penetration U.S. ACORN Description Number % Per 1000 Number % Index 1 Affluent Families 5,741 22.2 0.30 19,025,234 18.0123 2 Upscale Households 3,583 13.9 0.23 15,319,823 14.595 3 Up & Coming Singles 2,492 9.6 0.38 6,478,393 6.1157 4 Retirement Styles 2,514 9.7 0.22 11,463,248 10.990 5 Young Mobile Adults 2,676 10.4 0.74 3,595,727 3.4304 6 City Dwellers 2,651 10.3 0.18 14,534,166 13.874 7 Factory & Farm Communities 3,943 15.3 0.14 28,704,089 27.256 8 Downtown Residents 1,383 5.4 0.23 6,109,377 5.8 92 9 Nonresidential Neighborhoods 860 3.3 3.44 250,044 0.21404 Total 25,843100.0 0.25 105,480,101 100.0100 Copyright 2003 ESRI BIS East: (800) 2922224 FAX: (703) 243-6272 6/3/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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128 Customer ACORN Profile File: C:\Text\Grant\GeoSpatial_Solutions\subscr iptions\geocode\New_add\new_geocode\ge omap3_c_xy.dbf Subscriptions GeoSpatial Solutions Customers Penetration U.S. ACORN Description Number % Per 1000Number % Index 1 Affluent 1A Top One Percent 383 1.50.31 1,248,861 1.2 125 Families 1B Wealthy Seaboard Suburbs 714 2.80.32 2,220,126 2.1 131 1C Upper Income Empty Nesters 710 2.70.31 2,319,062 2.2 125 1D Successf ul Suburbanites 983 3.80 .38 2,555,230 2.4 157 1E Prosperous Baby Boomers 1,559 6.00.31 5,000,263 4.7 127 1F Semirural Lifestyle 1,392 5.40.24 5,681,692 5.4 100 2 Upscale 2A Urban Professional Couples 1,293 5.00.31 4,212,226 4.0 125 Households 2B Baby Boomers With Children 959 3.70.23 4,177,326 4.0 94 2C Thriving Immigrants 312 1.20.19 1,654,879 1.6 77 2D Pacific Heights 284 1.10.35 807,961 0.8 143 2E Older Settled Married Couples 735 2.80.16 4,467,431 4.2 67 3 Up & Coming 3A High Rise Renters 1,124 4.30.47 2,395,682 2.3 191 Singles 3B Enterprising Young Singles 1,368 5.30.34 4,082,711 3.9 137 4 Retirement 4A Retirement Communities 476 1.80.35 1,365,172 1.3 142 Styles 4B Active Senior Singles 704 2.70.25 2,866,329 2.7 100 4C Prosperous Older Couples 715 2.80.21 3,463,778 3.3 84 4D Wealthiest Seniors 231 0.90.18 1,295,816 1.2 73 4E Rural Resort Dwellers 160 0.60.16 997,639 0.9 65 4F Senior Sun Seekers 228 0.90.15 1,474,514 1.4 63 5 Young Mobile 5A Twenty-somethings 1,230 4.80.59 2,089,363 2.0 240 Adults 5B College Campuses 1,103 4.31.35 819,080 0.8 550 5C Military Proximity 343 1.30.50 687,284 0.7 204 6 City Dwellers 6A East Coast Immigrants 389 1.50.15 2,594,144 2.5 61 6B Working Class Families 132 0.50.11 1,210,608 1.1 45 6C Newly Formed Households 1,197 4.60.23 5,180,760 4.9 94 6D Southwestern Families 291 1.10.14 2,010,329 1.9 59 6E West Coast Immigrants 168 0.70.14 1,218,945 1.2 56 6F Low Income: Young & Old 474 1.80.20 2,319,380 2.2 83 7 Factory 7A Middle America 1,161 4.50.13 8,615,443 8.2 55 & Farm 7B Young Frequent Movers 717 2.80.19 3,787,725 3.6 77 Communities 7C Rural Industrial Workers 502 1.90.09 5,898,450 5.6 35 7D Prairie Farmers 114 0.40.11 1,055,112 1.0 44 7E Small Town Working Families 268 1.00.15 1,787,863 1.7 61 7F Rustbelt Neighborhoods 490 1.90.13 3,829,034 3.6 52 7G Heartland Communities 691 2.70.19 3,730,462 3.5 76 8 Downtown 8A Young Immigrant Families 129 0.5 0.12 1,050,710 1.0 50 Residents 8B Social Security Dependents 746 2.9 0.85 881,770 0.8 345 8C Distressed Neighborhoods 149 0.6 0.16 949,094 0.9 64 8D Hard Times 180 0.7 0.11 1,592,287 1.5 46 8E Urban Working Families 179 0.7 0.11 1,635,516 1.6 45 9 Nonresidential 9A Business Districts 144 0.6 5.49 26,243 0.0 2240 Neighborhoods 9B Institutional Populations 474 1.8 2.12 223,801 0.2 864 9C Unpopulated Areas 242 0.9 0.00 0 0.0 0

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129 Total 25,843 100.0 0.25 105,480,101 100.0 100 Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 6/3/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com Customer ACORN Profile File: C:\Text\Grant\GeoSpatial_Solutions\subscr iptions\geocode\New_add\new_geocode\ge omap3_c_xy.dbf Subscriptions GeoSpatial Solutions Rank ACORN Description Customers U.S. Index 1 1E Prosperous Baby Boomers 6.0% 4.7% 127 2 3B Enterprising Young Singles 5.3% 3.9% 137 3 2A Urban Professional Couples 5.0% 4.0% 125 4 5A Twenty-somethings 4.8% 2.0% 240 5 3A High Rise Renters 4.3% 2.3% 191 Subtotal 25.4% 16.9% 151 6 5B College Campuses 4.3% 0.8% 550 7 1D Successful Suburbanites 3.8% 2.4% 157 8 8B Social Security Dependents 2.9% 0.8% 345 9 1B Wealthy Seaboard Suburbs 2.8% 2.1% 131 10 1C Upper Income Empty Nesters 2.7% 2.2% 125 Subtotal 16.5% 8.3% 198 11 4A Retirement Communities 1.8% 1.3% 142 12 9B Institutional Populations 1.8% 0.2% 864 13 1A Top One Percent 1.5% 1.2% 125 14 5C Military Proximity 1.3% 0.7% 204 15 2D Pacific Heights 1.1% 0.8% 143 Subtotal 7.6% 4.1% 185 16 9A Business Districts 0.6% 0.0% 2240 Subtotal 0.6% 0.0% 2240 Total 50.0% 29.3% 171

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130 Note: Only classifications with an index higher than 100 are reported. Subtotals are shown for every 5 classifications. Output File Layout File: C:\Text\Grant\GeoSpatial_Solutions\subscr iptions\geocode\New_add\new_geocode\ge omap3_c_xy.dbf Subscriptions GeoSpatial Solutions Field COMPANY ADDRESS_LI ADDRESS_L1 CITY STATE F9DIGIT_ZI COUNTRY BUSINESS_C FUNCTION_C CODE_31 GEOCODE GEOLEVEL MSA_CODE LATITUDE LONGITUDE LOC_CODE ZIP4 ACORN ACORN_DESC ACORNLEVEL GEOCODE GEOLEVEL MSA_CODE LATITUDE LONGITUDE ZIP4 ACORN ACORN_DESC ACORNLEVEL Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 6/3/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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131 APPENDIX B GEOGRAPHIC MATCH LEVEL FOR FIRMS In this appendix, a geocoding summar y, created with the process of GeoSpatial Solutions firms’ data set and the use of CACI Coder/Plus (ESRI), is outlined. This section supplements the an alysis of firms found in Chapter 4 and Chapter 5.

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132 Geocoding Match Level Summary File: F:\GrantThrall_Private\Text_C\Gran t\GeoSpatial_Solut ions\Companies\geocod ed\COMPANIESUS2.dbf GIS Companies CONFIDENTIAL Number of Records: 647 Match Description Match Code Number Percent Street Match S 555 85.8% Dominant Tract in ZIP Code Z 83 12.8% One Tract in ZIP Code T 8 1.2% No Geocode X 1 0.2% 647 100.0% Match Description ESRI BIS assigns your customer records to one of four match levels. The best match level is Street Address or ZIP+4. If a reco rd cannot be matched at the Street Address or ZIP+4 levels, the Geo-Fix option can as sign a census tract through a ZIP Code to census tract correspondence. The census tract with the largest population in the ZIP Code is appended to the record. This match is referred to as a Dominant Tract in ZIP Code (Z) match. If the ZIP Code is built from only one census tract, then the match code (T) denotes only one tract in the ZIP Code. If an address is assigned a “No Geocode”, no match was possible below the county level. Post office boxes, rural routes or drops, or incomplete addresses can preclude a match. Addresses outside the U.S. cannot be matched either. ZIP Code to Census Tract Correspondence Summary Census tracts, and in nontracted areas, block numbering areas (BNAs), are assigned to residential ZIP Codes by overlaying the cent roids of the component blocks on ZIP Code boundaries. Expressed as latitude/longitu de coordinates, centroids approximate the geographic centers of blocks. If the centroid of a block falls within the ZIP Code, it is included. Blocks are then aggregated, and the ratio of the block totals to tracts/BNAs is used to create the ZIP Code to census tract correspondence. Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 7/10/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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133 Customer Geographic Summary File: F:\GrantThrall_Private\Text_C\Grant\Geo Spatial_Solutions\Companies\geocoded\CO MPANIESUS2.dbf GIS Companies CONFIDENTIAL Number of Records: 647 Record Count Top 20 States California (06) 123 Colorado (08) 77 Texas (48) 40 Virginia (51) 36 Florida (12) 34 Georgia (13) 34 Massachusetts (25) 27 Maryland (24) 23 New York (36) 19 Pennsylvania (42) 16 Washington (53) 15 Alabama (01) 14 Ohio (39) 14 Illinois (17) 11 Minnesota (27) 11 New Jersey (34) 11 New Mexico (35) 10 Oregon (41) 10 Arizona (04) 9 Missouri (29) 9 Other States 103 Non-geocoded Records 1 Top 20 Counties Santa Clara, CA (06085) 25 Fairfax, VA (51059) 19 Los Angeles, CA (06037) 17 Boulder, CO (08013) 17 Harris, TX (48201) 17 San Diego, CA (06073) 16 Alameda, CA (06001) 15 Jefferson, CO (08059) 15 Fulton, GA (13121) 15 Middlesex, MA (25017) 15 Denver, CO (08031) 14 Orange, CA (06059) 13 Arapahoe, CO (08005) 11 Madison, AL (01089) 9 Hillsborough, FL (12057) 9 Montgomery, MD (24031) 9 King, WA (53033) 9 San Francisco, CA (06075) 8 Suffolk, MA (25025) 8 Maricopa, AZ (04013) 7 Other Counties 378 Record Count Percent Top 20 ZIP Codes 80202 Denver, CO 6 0.9% 92121 San Diego, CA 6 0.9% 20166 Sterling, VA 5 0.8% 77042 Houston, TX 5 0.8% 80112 Englewood, CO 5 0.8% 80301 Boulder, CO 5 0.8% 95050 Santa Clara, CA 5 0.8% 20170 Herndon, VA 4 0.6% 30004 Alpharetta, GA 4 0.6% 80021 Broomfield, CO 4 0.6% 80111 Englewood, CO 4 0.6% 80302 Boulder, CO 4 0.6% 94043 Mountain View, CA 4 0.6% 94612 Oakland, CA 4 0.6% 20151 Chantilly, VA 3 0.5% 30328 Atlanta, GA 3 0.5% 33760 Clearwater, FL 3 0.5% 35758 Madison, AL 3 0.5% 35824 Huntsville, AL 3 0.5% 80026 Lafayette, CO 3 0.5% Other ZIP Codes 564 87.2% Records with no ZIP Code 0 0.0% Top 20 Metropolitan Areas Denver, CO (2080) 48 7.4% Washington, DC (8840) 46 7.1% Atlanta, GA (0520) 32 4.9% Boston-Wor-Law-Lw-Br (1123) 30 4.6% San Jose, CA (7400) 25 3.9% Houston, TX (3360) 23 3.6% Boulder-Longmont, CO (1125) 17 2.6% Los Angeles-L.Beach (4480) 17 2.6% Oakland, CA (5775) 17 2.6% San Diego, CA (7320) 16 2.5% Tampa-St.Pete-Clearw (8280) 15 2.3% San Francisco, CA (7360) 14 2.2% Orange County, CA (5945) 13 2.0% Philadelphia, PA-NJ (6160) 13 2.0% Chicago, IL (1600) 11 1.7% Baltimore, MD (0720) 10 1.5% Minneapolis-St. Paul (5120) 10 1.5% Seattle-Bellev-Ev’tt (7600) 10 1.5% Huntsville, AL (3440) 9 1.4% Kansas City, MO-KS (3760) 7 1.1% Other MAs 227 35.1% Records not in an MA 37 5.7% Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272

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134 7/10/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com Customer ACORN Profile File: F:\GrantThrall_Private\Text_C\Gran t\GeoSpatial_Solut ions\Companies\geocod ed\COMPANIESUS2.dbf GIS Companies CONFIDENTIAL Customers Penetration U.S. ACORN Description Number % Per 1000 Number % Index 1 Affluent Families 176 27.2 0.0119,025,234 18.0 151 2 Upscale Households 95 14.7 0.0115,319,823 14.5 101 3 Up & Coming Singles 118 18.2 0.026,478,393 6.1 297 4 Retirement Styles 64 9.9 0.0111,463,248 10.9 91 5 Young Mobile Adults 55 8.5 0.023,595,727 3.4 249 6 City Dwellers 53 8. 2 0.0014,534,166 13.8 59 7 Factory & Farm Communitie s 42 6.5 0.0028,704,089 27.2 24 8 Downtown Residents 23 3.6 0.006,109,377 5.8 61 9 Nonresidential Neighborhoods 21 3.2 0.08250,044 0.2 1369 Total 647 100.0 0.01 105,480,101 100.0 100 Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 7/10/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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135 Customer ACORN Profile File: F:\GrantThrall_Private\Text_C\Gran t\GeoSpatial_Solut ions\Companies\geocod ed\COMPANIESUS2.dbf GIS Companies CONFIDENTIAL Customers Penetration U.S. ACORN Description Number % Per 1000 Number % index 1 Affluent 1A Top One Percent 18 2.8 0.01 1,248,861 1.2235 Families 1B Wealthy Seaboard Suburbs 21 3.2 0.01 2,220,126 2.1154 1C Upper Income Empty Nesters 17 2.6 0.01 2,319,062 2.2120 1D Successful Suburbanites 33 5.1 0. 01 2,555,230 2.4211 1E Prosperous Baby Boomers 53 8.2 0.01 5,000,263 4.7173 1F Semirural Lifestyle 34 5.3 0.01 5,681,692 5.498 2 Upscale 2A Urban Professional Couples 38 5.9 0.01 4,212,226 4.0147 Households 2B Baby Boomers With Children 25 3.9 0.01 4,177,326 4.098 2C Thriving Immigrants 15 2.3 0.01 1,654,879 1.6148 2D Pacific Heights 5 0.8 0.01 807,961 0.8101 2E Older Settled Married Couples 12 1.9 0.00 4,467,431 4.244 3 Up & Coming 3A High Rise Renters 45 7.0 0.02 2,395,682 2.3306 Singles 3B Enterprising Young Singles 73 11.3 0.02 4,082,711 3.9292 4 Retirement 4A Retirement Communities 16 2.5 0.01 1,365,172 1.3191 Styles 4B Active Senior Singles 17 2.6 0.01 2,866,329 2.797 4C Prosperous Older Couples 19 2.9 0.01 3,463,778 3.389 4D Wealthiest Seniors 2 0.3 0.00 1,295,816 1.225 4E Rural Resort Dwellers 3 0.5 0.00 997,639 0.949 4F Senior Sun Seekers 7 1.1 0.00 1,474,514 1.477 5 Young Mobile 5A Twenty-somethings 39 6.0 0.02 2,089,363 2.0304 Adults 5B College Campuses 15 2.3 0.02 819,080 0.8299 5C Military Proximity 1 0.2 0.00 687,284 0.724 6 City Dwellers 6A East Coast Immigrants 8 1.2 0.00 2,594,144 2.550 6B Working Class Families 6 0.9 0.00 1,210,608 1.181 6C Newly Formed Households 18 2.8 0.00 5,180,760 4.957 6D Southwestern Families 6 0.9 0.00 2,010,329 1.949 6E West Coast Immigrants 9 1.4 0.01 1,218,945 1.2120 6F Low Income: Young & Old 6 0.9 0.00 2,319,380 2.242 7 Factory 7A Middle America 11 1.7 0.00 8,615,443 8.221 & Farm 7B Young Frequent Movers 13 2.0 0.00 3,787,725 3.656 Communities 7C Rural Industrial Workers 4 0.6 0.00 5,898,450 5.611 7D Prairie Farmers 1 0.2 0.00 1,055,112 1.015 7E Small Town Working Families 4 0.6 0.00 1,787,863 1.736 7F Rustbelt Neighborhoods 4 0.6 0.00 3,829,034 3.617 7G Heartland Communities 5 0.8 0.00 3,730,462 3.522 8 Downtown 8A Young Immigrant Families 2 0.3 0.00 1,050,710 1.031 Residents 8B Social Security Dependents 14 2.2 0.02 881,770 0.8259 8C Distressed Neighborhoods 1 0.2 0.00 949,094 0.917 8D Hard Times 3 0.5 0.00 1,592,287 1.531 8E Urban Working Families 3 0.5 0.00 1,635,516 1.630 9 Nonresidential 9A Business Districts 7 1.1 0.27 26,243 0.04349 Neighborhoods 9B Institutional Populations 10 1.5 0.04 223,801 0.2728 9C Unpopulated Areas 4 0.6 0.00 0 0.0 0 Total 647 100.0 0.01105,480,101 100.0100

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136 Customer ACORN Profile File: F:\GrantThrall_Private\Text_C\Gran t\GeoSpatial_Solut ions\Companies\geocod ed\COMPANIESUS2.dbf GIS Companies CONFIDENTIAL Rank ACORN Description Customers U.S. Index 1 3B Enterprising Young Singles 11.3% 3.9% 292 2 1E Prosperous Baby Boomers 8.2% 4.7% 173 3 3A High Rise Renters 7.0% 2.3% 306 4 5A Twenty-somethings 6.0% 2.0% 304 5 2A Urban Professional Couples 5.9% 4.0% 147 Subtotal 38.3% 16.9% 227 6 1D Successful Suburbanites 5.1% 2.4% 211 7 1B Wealthy Seaboard Suburbs 3.2% 2.1% 154 8 1A Top One Percent 2.8% 1.2% 235 9 1C Upper Income Empty Nesters 2.6% 2.2% 120 10 4A Retirement Communities 2.5% 1.3% 191 Subtotal 16.2% 9.2% 176 11 5B College Campuses 2.3% 0.8% 299 12 2C Thriving Immigrants 2.3% 1.6% 148 13 8B Social Security Dependents 2.2% 0.8% 259 14 9B Institutional Populations 1.5% 0.2% 728 15 6E West Coast Immigrants 1.4% 1.2% 120 Subtotal 9.7% 4.5% 214 16 9A Business Districts 1.1% 0.0% 4349 17 2D Pacific Heights 0.8% 0.8% 101 Subtotal 1.9% 0.8% 235 Total 66.2% 31.4% 211 Note: Only classifications with an index higher than 100 are reported. Subtotals are shown for every 5 classifications. Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 7/10/2 003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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137 Output File Layout File: F:\GrantThrall_Private\Text_C\Gran t\GeoSpatial_Solut ions\Companies\geocod ed\COMPANIESUS2.dbf GIS Companies CONFIDENTIAL Field COMPANY ADDRESS ADDRESS_IN CITY STATE ZIP GEOCODE GEOLEVEL MSA_CODE LATITUDE LONGITUDE ZIP4 ACORN ACORN_DESC ACORNLEVEL Copyright 2003 ESRI BIS East: (800) 292-2224 FAX: (703) 243-6272 7/10/2003 West: (800) 394-3690 FAX: (858) 677-5420 Internet: http://www.esribis.com

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138 APPENDIX C 2000 US CENSUS DATA In this appendix US States demographic data from the 2000 US. Census was used to supplement the analysis of the percentage rate of subscribers by state in Chapter 4. The data set for Establishment and Employment Changes from Births, Deaths, Expansions, and Contractions from the 2000 US. Census supplements the analysis of the firms’ concentration rate by state in Chapter 4.

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139 U.S. States Demographic Data Geographic area: Alabama [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,447,100 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,323,678 Bachelor’s degree . . . . . . . . . . . . . . 351,772 Graduate or professional degree . . . . . . . 197,836 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Arizona [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 5,130,632 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,763,685 Bachelor’s degree . . . . . . . . . . . . . . 493,419 Graduate or professional degree . . . . . . . 272,793 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Arkansas [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 2,673,400 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,993,031 Bachelor’s degree . . . . . . . . . . . . . . 190,427 Graduate or professional degree . . . . . . . 98,001 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: California [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 33,871,648 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 24,621,819 Bachelor’s degree . . . . . . . . . . . . . . 3,640,157 Graduate or professional degree . . . . . . . 2,029,809 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Colorado [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,301,261 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,200,466 Bachelor’s degree . . . . . . . . . . . . . . 599,028 Graduate or professional degree . . . . . . . 308,727 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Connecticut [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 3,405,565 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 2,563,877 Bachelor’s degree . . . . . . . . . . . . . . 416,751 Graduate or professional degree . . . . . . . 304,243 Table DP-1. Profile of General Demographic Characteristics: 2000

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140 Geographic area: Delaware [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 783,600 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 589,013 Bachelor’s degree . . . . . . . . . . . . . . 80,376 Graduate or professional degree . . . . . . . 48,541 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: District of Columbia [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 572,059 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 457,067 Bachelor’s degree . . . . . . . . . . . . . . 69,496 Graduate or professional degree . . . . . . . 80,741 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Florida [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 15,982,378 100.0 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 12,336,038 Bachelor’s degree . . . . . . . . . . . . . . 1,573,121 Graduate or professional degree . . . . . . . 889,207 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Georgia [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 8,186,453 100.0 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 6,017,219 Bachelor’s degree . . . . . . . . . . . . . . 829,873 Graduate or professional degree . . . . . . . 430,305 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Idaho [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,293,953 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 924,923 Bachelor’s degree . . . . . . . . . . . . . . 116,901 Graduate or professional degree . . . . . . . 53,714 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Illinois [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 12,419,293 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 9,173,842 Bachelor’s degree . . . . . . . . . . . . . . 1,317,182 Graduate or professional degree . . . . . . . 760,867 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Indiana [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 6,080,485 Subject Number Percent

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141 18 years and over . . . . . . . . . . . . . . 4,506,089 Bachelor’s degree . . . . . . . . . . . . . . 475,247 Graduate or professional degree . . . . . . . 280,366 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Iowa [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 2,926,324 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 2,192,686 Bachelor’s degree . . . . . . . . . . . . . . 278,350 Graduate or professional degree . . . . . . . 123,740 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Kansas [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 2,688,418 Subject Number Percent Bachelor’s degree . . . . . . . . . . . . . . 290,271 Graduate or professional degree . . . . . . . 148,707 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Kentucky [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,041,769 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,046,951 Bachelor’s degree . . . . . . . . . . . . . . 271,418 Graduate or professional degree . . . . . . . 182,051 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Louisiana [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,468,976 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,249,177 Bachelor’s degree . . . . . . . . . . . . . . 339,711 Graduate or professional degree . . . . . . . 180,067 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Maine [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,274,923 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 973,685 Bachelor’s degree . . . . . . . . . . . . . . 129,992 Graduate or professional degree . . . . . . . 68,968 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Maryland [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 5,296,486 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,940,314 Bachelor’s degree . . . . . . . . . . . . . . 629,304 Graduate or professional degree . . . . . . . 470,056 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Massachusetts

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142 [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 6,349,097 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 4,849,033 Bachelor’s degree . . . . . . . . . . . . . . 834,554 Graduate or professional degree . . . . . . . 583,741 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Michigan [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 9,938,444 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 7,342,677 Bachelor’s degree . . . . . . . . . . . . . . 878,680 Graduate or professional degree . . . . . . . 517,579 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Minnesota [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,919,479 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,632,585 Bachelor’s degree . . . . . . . . . . . . . . 605,210 Graduate or professional degree . . . . . . . 262,872 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Mississippi [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 2,844,658 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 2,069,471 Bachelor’s degree . . . . . . . . . . . . . . 194,325 Graduate or professional degree . . . . . . . 102,766 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Missouri [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 5,595,211 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 4,167,519 Bachelor’s degree . . . . . . . . . . . . . . 507,892 Graduate or professional degree . . . . . . . 276,584 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Montana [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 902,195 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 672,133 Bachelor’s degree . . . . . . . . . . . . . . 100,758 Graduate or professional degree . . . . . . . 42,203 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Nebraska [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,711,263 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,261,021 Bachelor’s degree . . . . . . . . . . . . . . 179,181

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143 Graduate or professional degree . . . . . . . 78,959 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Nevada [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,998,257 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,486,458 Bachelor’s degree . . . . . . . . . . . . . . 158,078 Graduate or professional degree . . . . . . . 79,797 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: New Hampshire [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,235,786 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 926,224 Bachelor’s degree . . . . . . . . . . . . . . 153,874 Graduate or professional degree . . . . . . . 82,230 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: New Jersey [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 8,414,350 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 6,326,792 Bachelor’s degree . . . . . . . . . . . . . . 1,063,665 Graduate or professional degree . . . . . . . 621,196 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: New Mexico [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,819,046 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,310,472 Bachelor’s degree . . . . . . . . . . . . . . 154,372 Graduate or professional degree . . . . . . . 111,777 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: New York [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 18,976,457 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 14,286,350 Bachelor’s degree . . . . . . . . . . . . . . 1,954,242 Graduate or professional degree . . . . . . . 1,478,970 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: North Carolina [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 8,049,313 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 6,085,266 Bachelor’s degree . . . . . . . . . . . . . . 808,070 Graduate or professional degree . . . . . . . 378,643 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: North Dakota [For information on confidentiality protection, nonsampling error, and definitions, see text]

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144 Subject Number Percent Total population. . . . . . . . . . . . . 642,200 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 481,351 Bachelor’s degree . . . . . . . . . . . . . . 67,551 Graduate or professional degree . . . . . . . 22,292 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Ohio [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 11,353,140 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 8,464,801 Bachelor’s degree . . . . . . . . . . . . . . 1,016,256 Graduate or professional degree . . . . . . . 547,276 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Oklahoma [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 3,450,654 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 2,558,294 Bachelor’s degree . . . . . . . . . . . . . . 297,082 Graduate or professional degree . . . . . . . 149,689 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Oregon [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 3,421,399 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 2,574,873 Bachelor’s degree . . . . . . . . . . . . . . 369,252 Graduate or professional degree . . . . . . . 195,314 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Pennsylvania [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 12,281,054 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 9,358,833 Bachelor’s degree . . . . . . . . . . . . . . 1,153,383 Graduate or professional degree . . . . . . . 694,248 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Rhode Island [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,048,319 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 800,497 Bachelor’s degree . . . . . . . . . . . . . . 110,175 Graduate or professional degree . . . . . . . 67,642 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: South Carolina [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 4,012,012 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,002,371 Bachelor’s degree . . . . . . . . . . . . . . 351,526 Graduate or professional degree . . . . . . . 178,529

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145 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: South Dakota [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 754,844 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 552,195 Bachelor’s degree . . . . . . . . . . . . . . 73,563 Graduate or professional degree . . . . . . . 28,449 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Tennessee [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 5,689,283 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 4,290,762 Bachelor’s degree . . . . . . . . . . . . . . 478,463 Graduate or professional degree . . . . . . . 254,225 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Texas [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 20,851,820 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 14,965,061 Bachelor’s degree . . . . . . . . . . . . . . 1,996,250 Graduate or professional degree . . . . . . . 976,043 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic Area: Utah [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 2,233,169 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,514,471 Bachelor’s degree . . . . . . . . . . . . . . 213,959 Graduate or professional degree . . . . . . . 99,004 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Vermont [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 608,827 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 461,304 Bachelor’s degree . . . . . . . . . . . . . . 74,124 Graduate or professional degree . . . . . . . 44,901 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Virginia [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 7,078,515 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 5,340,253 Bachelor’s degree . . . . . . . . . . . . . . 835,011 Graduate or professional degree . . . . . . . 539,977 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Washington [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent

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146 Total population. . . . . . . . . . . . . 5,894,121 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 4,380,278 Bachelor’s degree . . . . . . . . . . . . . . 704,826 Graduate or professional degree . . . . . . . 356,599 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: West Virginia [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 1,808,344 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 1,405,951 Bachelor’s degree . . . . . . . . . . . . . . 109,651 Graduate or professional degree . . . . . . . 73,309 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Wisconsin [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 5,363,675 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 3,994,919 Bachelor’s degree . . . . . . . . . . . . . . 530,268 Graduate or professional degree . . . . . . . 249,005 Table DP-1. Profile of General Demographic Characteristics: 2000 Geographic area: Wyoming [For information on confidentiality protection, nonsampling error, and definitions, see text] Subject Number Percent Total population. . . . . . . . . . . . . 493,782 Subject Number Percent 18 years and over . . . . . . . . . . . . . . 364,909 Bachelor’s degree . . . . . . . . . . . . . . 47,066 Graduate or professional degree . . . . . . . 22,096 Establishment a nd Employment Changes from Births, Deaths, Expansions, and Contractions by Employment Size of the Enterprise for the United States and All States, Totals: 1999 – 2000 AREA CODE DATA TYPE Employment Size of the Enterprise United States 01 Initial year establishments6,248,411 Alabama 01 Initial year establishments91,472 Arizona 01 Initial year establishments98,834 Arkansas 01 Initial year establishments56,235 California 01 Initial year establishments692,987 Colorado 01 Initial year establishments115,893 AREA CODE DATA TYPE Employment Size of the Enterprise Connecticut 01 Initial year establishments83,145 Delaware 01 Initial year establishments20,478 District of Columbia 01 Initial year establishments17,817

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147 Florida 01 Initial year establishments372,132 Georgia 01 Initial year establishments175,250 Idaho 01 Initial year establishments31,991 Illinois 01 Initial year establishments273,421 Indiana 01 Initial year establishments133,226 Iowa 01 Initial year establishments73,436 Kansas 01 Initial year establishments67,139 Kentucky 01 Initial year establishments81,935 Louisiana 01 Initial year establishments92,092 Maine 01 Initial year establishments33,721 Maryland 01 Initial year establishments113,481 Massachusetts 01 Initial year establishments154,385 Michigan 01 Initial year establishments210,508 Minnesota 01 Initial year establishments120,668 Mississippi 01 Initial y ear establishments54,368 Missouri 01 Initial year establishments130,269 Montana 01 Initial year establishments27,140 Nebraska 01 Initial year establishments44,029 Nevada 01 Initial year establishments40,211 New Hampshire 01 Initial year establishments33,146 New Jersey 01 Initial year establishments205,043 New Mexico 01 Initial year establishments38,320 New York 01 Initial year establishments429,397 North Carolina 01 Initial year establishments181,306 North Dakota 01 Initial year establishments18,308 Ohio 01 Initial year establishments246,210 Oklahoma 01 Initial year establishments76,566 Oregon 01 Initial year establishments88,292 Pennsylvania 01 Initial year establishments267,546 Rhode Island 01 Initial year establishments25,139 South Carolina 01 Initial year establishments86,770 South Dakota 01 Initial year establishments21,037 Tennessee 01 Initial year establishments119,362 Texas 01 Initial year establishments420,139 Utah 01 Initial year establishments46,473 Vermont 01 Initial year establishments19,097 Virginia 01 Initial year establishments155,985 Washington 01 Initial year establishments142,653 AREA CODE DATA TYPE Employment Size of the Enterprise West Virginia 01 Initial year establishments37,800 Wisconsin 01 Initial year establishments125,600 Wyoming 01 Initial year establishments15,713 United States Census 2000 Data

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148 LIST OF REFERENCES Bond C., April 1997, “Divide and Conquer, ” Haymarket Publishing Ltd, London,.pp. 29. Campbell R., Martin C., Fabos B., Media and Culture an Introduction to Mass Communication Bedford, New York. Chepesiuk R., February 1994, “Finding the Righ t Niche,” Editor & Publisher, 127: 14-16. Cissna K., Applied Communication in the 21st Century Lawrence Erblbam Associate Publishers, Hillsdale, New Jersey 1995. Craig C., Ghosh A., McLafferty S., 1984, “M odels of Retail Location Process: A Review,” Journal of Retailing, 49(3): 51-63. Daratech. Geographic Information Systems: Markets and Opportunities 2003 Cambridge, MA: Daratech, 2002. Davud L, Della Bita A., 1979, Consumer Behavior: C oncepts and Applications McGraw-Hill, New York 1979, pp. 50-54. Dickenson N., “The Brave New World of Segmentation,” Campaign, (University of Florida) InfoTrac OneFile, pp. 36, February 6, 1998. Geller L., “Blazing New Trails Takes Nerv e,” Philadelphia, September 2003, 26: 9 pp. 20. Goldstucker J., Bellenger D., Stanley T., Otte R., New Developments in Retail Trading Area Analysis and Site Selection 1978, Atlanta: College of Business Administration, Georgia State University. Granatstein L., “Talkin’ Shop,” Mediaw eek, New York, September 2003, 13: 33 pp. 37. Hartung V ., “An Economic Perspective of the GIS Industry,” NCGIA, Buffalo, pp. 1-12. Haynes K., Fotheringham A., “Gravity and Spatial Interaction Models,” Scientific Geography Series, 1984, vol. 2, Thousand Oa ks, California: Sage Publications. Hucker-Brown K., “Estimating the Potential of Your Chosen Market,” Direct Response, London, March 2003, pp. 33. Huff D., “Geographical Aspects of Cons umer Behavior,” 1959, University of Washington Business Review, 18: 27-37.

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149 Katz M., “You Do the Math: Measure for Meas ure, Site Selection Process Has Big-Time Sales Potential,” Nation’s Restaurant News, New York, December 2002, 36: 48 pp. 27-28. Liebeskind K., “Unleashing Data’s Selling Powe r,” Editor & Publisher, New York, July 1996, 129: 29 pp. 27C. Maguire D., Goodchild, M., Rhind D., 1991. Geographical Information Systems: Principles and Applications Longman Group, Cambridge, UK. Martin M., “Man Behind Maxim’s Success Stil l Isn’t Ready to Take It Easy,” Campaign, August 21, 1998, pp. 19. Merrick A., “The 2000 Count: Counting on the Census---New Data Will Let Starbucks Plan Store Openings, Help Blockbuster St ock Its Videos,” Wall Street Journal, New York, February 2001, pp. B1. Mummert H., “Best Practices,” Target Mark eting, Philadelphia, September 2003, 26: 9 pp. 34. Piccillo S., “How Marketers Benefit From Mapping Demos,” Marketing News, June 1999, 33: 13 pp. 15-16. Piirto R., Capturing Consumers Ithaca, NY: American Demographic Press, 1990. Saolik M., “Print Media: Placement Strategies for the New Segmentation,” November 1989, Public Relation Jo urnal, 45: 15-16. Scharpf N., “Target Marketing: Publishers Must Lead,” Folio, February 1989, pp. 168. Strout E., “The Segmentation Game,” Sa les and Marketing Management, New York, August 2003, 155: 8 pp. 11. Swann M., “Mass Magazine Circulation Patterns in the United States: Regional Variations in Urban and Rural Tastes,” Dept. of Geography, Discussion Paper, Syracuse University, Syracuse, New York, Number 6, June 1975. Thrall G., “CACI Coder/Plus Version 1,” Ge o Info Systems, June 1998, Cleveland, 8: 6 pp. 43-45. Thrall G., Albury J., Business Geography and New Real Estate Market Analysis Oxford University Press, Inc., New York, NY, 2002. Thrall G., Casey J., Quintana A., “Mosaic, ” GeoSpatial Solutions, Duluth, April 2001, 11: 4 pp. 40-43. Thrall G., Del Valle J., Amos P., McGurn K ., “Measuring the Development Potential of an Historic Downtown”. Geo Info Sy stems, 1996, 6(4), Cleveland, pp. 44-49.

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150 Van Zuiles A., The Life Cycle of Magazines Graduate Press, Uithoorn 1997.

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151 BIOGRAPHICAL SKETCH Matias Sebastian Campins is the son of Gabriel Miguel Campins and Raquel Beatriz Campins. Born on October 25, 1975, in Buenos Aires, Argentina, he lived with his family until the age of 21, when the fam ily moved to Orlando, Florida. There, he attended Valencia Community College and rece ived his Associate of Arts degree in 2000. He then moved to Gainesville, Florida, to begi n his studies at the University of Florida. In December 2002, he received his Bachelor of Arts degree in geography from the University of Florida. Currently, he is wo rking toward his Master or Arts degree in geography with a specialization in real estate market analys is and a minor in urban and regional planning.


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Permanent Link: http://ufdc.ufl.edu/UFE0008100/00001

Material Information

Title: Mapping the Geospatial Community
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0008100:00001

Permanent Link: http://ufdc.ufl.edu/UFE0008100/00001

Material Information

Title: Mapping the Geospatial Community
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0008100:00001


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Full Text












MAPPING THE GEOSPATIAL COMMUNITY


By

MATIAS SEBASTIAN CAMPINS













A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2004

































Copyright 2004

by

Matias S. Campins
































To my best friend and partner Heather Campins.















ACKNOWLEDGMENTS

There are many people during this long journey through my education that I would

like to thank; those people who were the biggest influences during my studies for my

Master of Arts degree are recognized below.

I would like to thank my wife, Heather, whom I love with all my heart, for all of

her support and help throughout my education and my life. Heather is the person who

helped me with the long nights of study and the times that I did not feel like continuing

with my education. Her constant support with my decisions and love helped me achieve

my goals and dreams. I cannot forget to mention all her help with editing my thesis and

all my papers for school.

I would also like to thank my parents, Gabriel and Raquel, who have taught me the

social aspects of life. Specifically, I would like to thank my mother, Raquel, whose voice

always reminds me that I can accomplish anything I decide in life. I cannot forget my

brother and sister, Leonardo and Cynthia, on whom I can always count.

Grant Ian Thrall is the person most responsible for the completion of my Master of

Science degree. He gave me the knowledge necessary to achieve my goals as a business

geographer. Also, it was his enthusiasm for the study of business geography attracted me

to the field.

I would also like to thank Scottie Barnes for all of her assistance with arranging for

Dr. Thrall and me to have access to the GeoSpatial Solutions' database.









Finally, to the rest of my graduate committee--Joshua Comenetz, and Rhonda

Phillips--I would like to express my gratitude for their support and enthusiasm. Their

support allowed my thesis and my graduate program to be more enjoyable.
















TABLE OF CONTENTS
page

A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES .................................................... ....... .. .............. viii

LIST OF FIGURES ............................... ... ...... ... ................. .x

ABSTRACT ........ .............. ............. ...... ...................... xiv

CHAPTER

1 IN T R O D U C T IO N ............................................................................. .....................

Geographic Information Systems Industry ..... .......... ..................... .................
The M magazine Industry ....................................................... ................. .2
Business Geography ....................... ..................................
ACORN lifestyle segmentation indices............................................... .................. 8

2 LITERATURE REVIEW ........................................................................... 14

3 DATA M ETHODOLOGY ............................................................ ............... 22

Data Acquisition ................................. ................................ ....... 22
Geocoding Results .................. ................................... ................. 23
F in a l D a ta set ......................................................................................................2 4

4 MAPPING THE GEOSPATIAL COMMUNITY.................................................26

Geographic Regions in the U S ............................................................................28
Prim ary Subm arket..............................................................................29
Secondary Subm arket.......................................................... ............... 33
Tertiary Subm market .................. ............................ .. ........ .. ............ 33
GIS Producers ................ ......... ...................... ............. ........... 38
Business Codes ................................... ........ ...............43
O organizational affiliation ........................................ ......... ............... 44
T title co d e s ..............................................................4 4
C corporate M anagem ent: ................................................................ ................48
Operations ............... ...............................50
G IS F irm s........................................................5 9









5 SOCIAL-ECONOMIC CORRELATIONS .............................................................70

H igh C concentration R egions.............................................................. ....................70
Prim ary Sub M market ................................................... ............................... 75
Secondary Sub M market ............................................................... ....................75
E d u c atio n ...........................................................................................8 0
Buffer at 10 M iles ............................ ..... ... ............ .............. 80
Buffer at 12 M iles ............................ ..... ... ............ .............. 83
Buffer at 15 M iles ............................ ..... ... ............ .............. 83
Buffer at 18 M iles ............................ ..... ... ............ .............. 83
M market A attraction .......................... .. .... ................ ... ........... .............. 83
M market A attraction at 10 M iles ............................................. ............... 88
M market A attraction at 12 M iles ............................................. ............... 88
M market A attraction at 15 M iles ............................................. ............... 88
Market Attraction at 18 Miles .......................................... ............... 89
F irm s ..............................................................................................1 0 0
B u ffer at 7 M iles ................................ .... .......... .................. ............ 103
B uffer at 20 M iles ............................ ................ .................... .............. 103
L SP s at 7 M iles ........................ .. .. .......................... .. .... ............104

6 CORRELATION OF ANALYSIS WITH INTERNATIONAL GEOGRAPHIC
R E G IO N S .............................................................. .................................... 1 1 1

G global A analysis ........................................................................................... 111
G global M market .............................................................. .. ... ............... 111
E urope ..................................... ..........................112
A sia & A u stralia .................................................................................... 1 12
A frica.................................................. 112
S o u th A m erica ....................................................................................... 1 15
C a n a d a ................................................................................................... 1 1 5

7 CHARACTERISTICS OF GIS PRODUCERS ....... ........ ..... ................ 120

APPENDIX

A GEOGRAPHIC MATCH LEVEL FOR SUBSCRIBERS .................................. 124

B GEOGRAPHIC MATCH LEVEL FOR FIRMS .................................................131

C 2000 U S C E N SU S D A T A ................................................................................... 138

L IST O F R E F E R E N C E S ............................................................................................ 148

BIOGRAPHICAL SKETCH .............................................................. ...............151
















LIST OF TABLES


Table page

1. Geocoding match level summary of 27,050 subscribers' first address field from
C A C I C oder/P lu s........... ... ............................................................ ......... ....... 24

2. Geocoding match level summary of 27,050 subscribers' second address field
from CA CI Coder/Plus ...................... ....... .................................... ............... 24

3. Geocoding match level summary of 26,024 subscribers' final address field from
C A C I C oder/P lu s........... ... ............................................................ ......... ....... 25

4. Geocoding match level summary of top 20 states by number of subscribers
from CA CI Coder/Plus ...................... ....... .................................... ............... 28

5. GeoSpatial Solutions' tertiary submarket counts processed using
CACI Coder/Plus (ESRI). .................................................................. 33

6. GeoSpatial Solutions' percentage of subscribers by state using data from the US
C en su s B bureau ......... ........... ................ ................. .............................37

7. GeoSpatial Solutions' business code categories using their data set .....................39

8. GeoSpatial Solutions' ten business codes groups. ................................................43

9. GeoSpatial Solutions' title code categories using their data set ............ .............48

10. GeoSpatial Solution' corporate management codes................. .............49

11. GeoSpatial Solutions' information technology (MIS/IS)............... ............... 49

12. GeoSpatial Solutions' operations codes ....................................... ............... 59

13. GeoSpatial Solutions' percentage of companies by state using data from the US
C en su s B bureau ......... ........... ................ ................. .............................64

14. Geocoding match level summary of top 20 metropolitan areas by percentage of
subscribers from CACI Coder/Plus. ............................ ............................. 70

15. Identification of metropolitan areas by count of subscribers from
C A C I C oder/P lu s........... ... ............................................................ ......... ....... 73









16. GIS m market attracted to the education m market ............... .............. .....................88

17. University ranking of companies market by count based on MSAs .......................96

18. GeoSpatial Solutions' subscribers LSP's. ....................................................... 100

19. GeoSpatial Solutions' firms LSP's. ............................................ ............... 101

20. GeoSpatial Solutions'subscribers at 7 and 20 miles radius from companies......... 104

21. GeoSpatial Solutions'subscribers LSP's at 7 miles radius from companies ..........107

22. Percent of total companies in each market as defined in international maps.........112
















LIST OF FIGURES


Figure p

1. 2001 Worldwide GIS Revenue (Software Only). The figure was compiled in
2002 by D aratech, Inc. ..................... ................ ............ .............. .2

2. Magazine Revenue Sources. This figure was assembled in 1998 by Compaine.......3

3. Timeline for business geographic market analysis of retail location decisions
after 1996 and 1997 by Thrall and del V alle................................... .....................5

4. Timeline of location-based market analysis by Thrall (2002). .................................6

5. ACORN lifestyle segmentation indices by CACI/Coder Plus................................8

6. The four types of consumer information. This figure presented in The Insider's
Guide to Demographic Know-How in 1990........................................ ...............12

7. The advantages of mapping demographics and the further analysis possible by
Piccilli 1999 ................................ ........................... ... .... ........ 15

8. Survey response statistics conducted by Hartung 1997. ....................... ....... 17

9. GeoSpatial Solutions' US market subscribers processed using ArcMap (ESRI). ...27

10. GeoSpatial Solutions individual state subscribers color-coded by state counts
processed using ArcM ap (ESRI) ................................................................. ....... 30

11. GeoSpatial Solutions' US market subscribers percent by State using ArcMap
(E SR I). ............................................................................ 3 1

12. GeoSpatial Solutions' three US GIS submarkets processed using ArcMap
(E S R I) ........................................................................... ............... 3 2

13. GeoSpatial Solutions' primary submarket processed using ArcMap (ESRI) .........34

14. GeoSpatial Solutions' secondary submarket processed using ArcMap (ESRI).......35

15. GeoSpatial Solutions' tertiary submarket processed using ArcMap (ESRI) ...........36

16. GeoSpatial Solutions' percentage rate of subscribers by state using data from the
U S Census Bureau ......... ....... ...... ....................... ...... ...... ... .............. 41









17. GeoSpatial Solutions' subscription card. ..................................... ............... 42

18. GeoSpatial Solutions' subscription card. ..................................... ............... 42

19. GeoSpatial Solutions' combined business codes processed with ArcMap .............45

20. GeoSpatial Solutions' combined business codes percent by state processed with
ArcM ap..................................... ................................... ......... 46

21. GeoSpatial Solutions' individual business codes processed with ArcMap..............47

22. GeoSpatial Solutions' combined organizational affiliation codes processed with
ArcM ap..................................... ................................... ......... 51

23. GeoSpatial Solutions' combined organizational affiliation codes percent by state
processed w ith A rcM ap ............................................. ......................................... 52

24. GeoSpatial Solutions' individual organizational affiliation codes processed with
ArcM ap..................................... ................................... ......... 53

25. GeoSpatial Solutions' combined corporate management codes processed with
ArcM ap..................................... ................................... .......... 54

26. GeoSpatial Solutions' combined corporate management codes percent by state
processed w ith A rcM ap ......................................... .............................................55

27. GeoSpatial Solutions' individual corporate management codes processed with
ArcM ap..................................... ................................... .......... 56

28. GeoSpatial Solutions' combined information technology codes processed with
ArcM ap..................................... ................................... ......... 57

29. GeoSpatial Solutions' combined information technology codes percent by state
processed w ith A rcM ap ............................................. ......................................... 58

30. GeoSpatial Solutions' individual information technology codes processed with
A rcM ap ............................................................................. 6 0

31. GeoSpatial Solutions' combined operations codes processed with ArcMap...........61

32. GeoSpatial Solutions' combined operations codes percent by state processed
w ith A rcM ap ...................................................... ................. 62

33. GeoSpatial Solutions' individual operations codes processed with ArcMap. .........63

34. GeoSpatial Solutions' US companies data set processed with ArcMap ................66

35. GeoSpatial Solutions' US companies data set percent by state processed with
ArcM ap..................................... ................................... .......... 67









36. GeoSpatial Solutions' percentage of companies by state using data from the US
C en su s B bureau ......... ........... ................ ................. .............................68

37. GeoSpatial Solutions' percentage rate of companies by state using data from the
U S C ensu s B bureau ............... .. ..... ......................................................... 69

38. GeoSpatial Solutions' top metropolitan areas by subscribers processed with
A rcM ap ............................................................................. 7 2

39. GeoSpatial Solutions' top metropolitan areas by count processed with ArcMap....74

40. GeoSpatial Solutions' high concentration areas in Maryland/Virginia processed
w ith A rcM ap ...................................................... ................. 76

41. GeoSpatial Solutions' high concentration areas in California processed with
ArcM ap..................................... ................................... .......... 77

42. GeoSpatial Solutions' high concentration areas in Massachusetts/New
Hampshire processed with ArcM ap. ............................................. ............... 78

43. GeoSpatial Solutions' high concentration areas in Illinois processed with
ArcM ap..................................... ................................... .......... 79

44. GeoSpatial Solutions' education business code US market processed with
ArcM ap..................................... ................................... ......... 81

45. GeoSpatial Solutions' US education market with a buffer at 10 miles processed
w ith A rcM ap ...................................................... ................. 82

46. GeoSpatial Solutions' US education market with a buffer at 12 miles processed
w ith A rcM ap .........................................................................84

47. GeoSpatial Solutions' US education market with a buffer at 15 miles processed
w ith A rcM ap ...................................................... ................. 85

48. GeoSpatial Solutions' US education market with a buffer at 18 miles processed
w ith A rcM ap ...................................................... ................. 86

49. GeoSpatial Solutions' US companies dataset processed with ArcMap ..................87

50. GeoSpatial Solutions' US education market attraction at 10 miles radius
processed w ith A rcM ap ......................................... .............................................90

51. GeoSpatial Solutions' US education market attraction percentage at 10 miles
radius processed with ArcM ap. ........................................ ........................... 91

52. GeoSpatial Solutions' US education market attraction at 12 miles radius
processed w ith A rcM ap ......................................... .............................................92









53. GeoSpatial Solutions' US education market attraction percentage at 12 miles
radius processed with ArcM ap. ........................................ ........................... 93

54. GeoSpatial Solutions' US education market attraction at 15 miles radius
processed w ith A rcM ap ......................................... .............................................94

55. GeoSpatial Solutions' US education market attraction percentage at 15 miles
radius processed with ArcM ap. ........................................ ........................... 95

56. GeoSpatial Solutions' US education market attraction at 18 miles radius
processed w ith A rcM ap ......................................... .............................................98

57. GeoSpatial Solutions' US education market attraction percentage at 18 miles
radius processed with ArcM ap. ........................................ ........................... 99

58. GeoSpatial Solutions' US firms dataset processed with ArcMap..........................105

59. GeoSpatial Solutions' subscriber percentage at 7 miles from companies
processed w ith A rcM ap .......................................................... ............... 106

60. GeoSpatial Solutions' subscriber percentage at 20 miles from companies
processed w ith A rcM ap................................................. ............................. 108

61. GeoSpatial Solutions' subscriber Lifestyle Segmentation Profiles at 7 miles
from companies processed with ArcMap ......................................................110

62. GeoSpatial Solutions global market subscribers' processed with ArcMap. ..........113

63. GeoSpatial Solutions global market subscribers' Europe processed with
A rcM ap ............................................................... .... ...... ......... 114

64. GeoSpatial Solutions global market subscribers' Asia and Australia processed
w ith A rcM ap. .................................................................... ..........116

65. GeoSpatial Solutions global market subscribers' Africa processed with
A rcM ap ............................................................... .... ...... ......... 117

66. GeoSpatial Solutions global market subscribers' South America processed
w ith A rcM ap. .................................................................... ..........118

67. GeoSpatial Solutions global market subscribers' Canada processed with
A rcM ap ............................................................... .... ...... ......... 119















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

MAPPING THE GEOSPATIAL COMMUNITY


By

Matias Sebastian Campins

December 2004

Chair: Grant Ian Thrall
Major Department: Geography

The deployment of Geographic Information Systems (GIS) technology has become

virtually spatially ubiquitous within the US during the past decade. However, the GIS

production industry is highly concentrated within a few submarkets of the nation. This

has national and even global implications as GIS is estimated today to be a multibillion-

dollar industry to the US, and even more when global figures are considered.

Where is GIS? Where are the submarkets (geographical regions) of GIS production

within the US? What are the major social-economic correlates between those submarkets

with high concentrations of GIS firms? What are the characteristics of GIS firms? Can

this information be used to guide other submarkets, including submarkets in other

nations, to economic opportunities by focusing on the GIS industry?

One of the leading professional publications in the GIS industry is GeoSpatial

Solutions. That publication has made available to Dr. Grant Thrall its entire 30,000 record

subscriber database. This database is used as one source of information to answer the









questions posed above. Every December, GeoSpatial Solutions publishes a list of almost

every GIS business firm in the US. These databases are used to document and

corroborate concentrations of GIS business within a few submarkets. Lastly, social-

economic data are drawn from the 2000 census and private data vendors, as well as

lifestyle segmentation profiles for those GeoSpatial Solutions readers whose publications

are delivered to their home addresses.

Included among the beneficiaries of this study are Advanstar Inc., owner of

GeoSpatial Solutions; the GIS industry, as the results of this work are co-authored with

Dr. Grant Thrall and published in GeoSpatial Solutions and other GIS publications; and,

economic development officers at the local, national, and international scale. The

National Chamber of Commerce of Sweden, working with the Swedish Embassy to the

US, contacted Dr. Thrall, looking for answers to assist with locating its subscribers and

why they locate in specific areas. With this information, it can better understand the

characteristics of the market and any correlation that may exist among the European and

US markets. Some of the questions which are addressed in this analysis include: where

are the submarkets (geographical regions) of GIS production within the US? What are the

major social-economic correlates between those submarkets with high concentrations of

GIS firms? What are the characteristics of GIS firms? Can this information be used to

guide other submarkets, including submarkets in other nations, to economic opportunities

by focusing on the GIS industry? The Chamber, along with the editorial staff of

GeoSpatial Solutions, serve as unofficial outside readers of this thesis.














CHAPTER 1
INTRODUCTION

This thesis incorporates Geographic Information Systems (GIS) principles and

business geography Market Analysis practices. This analysis performed on one of the

leading professional publications in the GIS industry. The GIS industry is estimated to

exceed one billion dollars annual revenue within the US and even more internationally.

Cambridge, MA, November 12, 2002 Worldwide GIS software revenue reached
$1.1 billion in 2001, an outstanding growth of 14.3% over the previous year,
according to a just-published market study by Daratech, Inc., a Cambridge, MA-
based market research and technology assessment firm. The largest market for GIS
software was the utilities industry, which accounted for 21% of all software
revenue, followed closely by state and local governments, the telecommunications
industry, and organizations involved in earth resources management.

Moreover, GIS software sales drove more than $7.7 billion in total user spending
on software and related hardware and services. Indeed, services contributed a
whopping $5.4 billion, including $5 billion from non-core-business vendors-
companies that do not develop GIS applications software products. (Daratech,
2002)

Geographic Information Systems Industry

Clearly, this industry has a national and global impact. Beneficiaries of this study

include the magazine industry, such as GeoSpatial Solutions, and economic development

offices at the local, national, and international scales, such as the National Chamber of

Commerce of Sweden. This thesis incorporates the advances of business geography and

GIS to create a study of the GeoSpatial Solutions market. Two industries merged using

the technology of Geographic Information Systems (GIS) and the ideas of business

geography; "business geography integrates geographic analysis, reasoning and

technology for the improvement of the business judgmental decision. Without the









demonstrated ability to improve the business decision, there is no business geography.

This differentiates business geography from the traditional descriptive of explanatory

objective of economic and urban geography" (Thrall, 2003).


2001 Worldwide GIS Revenue

(Software Only)

1e~~:4%~


SM.AD 1
5%



MUaplirio
5%


$SITM MllIko

EMRI
L :-............. -


G.A7%


riAnIMN'2awc1


Figure 1. 2001 Worldwide GIS Revenue (Software Only). The figure was compiled in
2002 by Daratech, Inc.

The GIS industry's net worth is estimated today to be a multibillion-dollar industry

to the United States, and more when global figures are considered (Figure 1).

The Magazine Industry

The magazine industry has approximate revenue of more than $22 billion (cf:

newspapers) (Compaine, 1998). This graph represents where the revenues come for the

magazine industry (Figure 2).


O^Flt kh3 U.ta.


\










Magazine Revenue Sources


I I I I I
1989 1990 1991 1992 1993

Legend
Advertising Subscriptions
SSingle-copy sales List-rental revenue


Figure 2. Magazine Revenue Sources. This figure was assembled in 1998 by Compaine.

Business Geography

Business geography is the study and research of a geographic market for various

industries, including the retail industry, the hotel industry, the real estate industry, the

publishing industry, the development industry, and the government. The Market Analyst

or Business Geographer relies on data availability, timeliness, accuracy, and choice of

procedures. Business Geographers analyze markets to determine where clients locate and

the characteristics of those clients in the market or new market area. Market analysis can









be used for both small and larger market areas. business geography has steadily evolved

from the eras of Johann Heinrich Von Thunen and William Applebaum, to the present era

of Business Geographer Dr. Grant Thrall. The theories and ideals that make up the study

of business geography are constantly changing. One process that was introduced to the

field in 1993 was "a four-stage compartmentalization of GIS activity" (Thrall and

Elshaw-Thrall 1993). The original four-stage process is as follows:

Stage One: Description

Stage Two: Explanation

Stage Three: Prediction

Stage Four: Judgment

A fifth stage was implicitly added to the earlier stages of evolution (Thrall and

Ruiz 1994; Thrall, Bates, and Ruiz 1994):

Stage Five: Implementation and Management

Stage Six: likely to be holistic application of geographic reasoning and technology

throughout the enterprise (personal correspondence with Dr. Grant Thrall, 2004)

The evolution of these six stages can be represented chronologically, as shown for

the business geography field in Figure 3. The graph represents the evolution of the GIS

stages conceding the longevity of the theories and ideals of business geography.

Geography theories and ideals have been around since the 1900s, and their stages and

principles will continue to evolve well into the future.

An issue of all stage theories is that they do not address "what next" after the last

referenced stage. A stage seven added to the time line for business geographic market









analysis would likely, according to Thrall, be an adoption of his stage five and 6 of his

general stages of GIS reasoning.

1900 1920 1940 1960 1980 1990 2000



Stage 1

Stage 2

Stage 3

Stage 4

Stage 5

Stage 6


Figure 3. Timeline for business geographic market analysis of retail location decisions
after 1996 and 1997 by Thrall and del Valle.

Market analysis is not new, however the evolution of this field has changed with

the induction of new technologies (Figure 4). Changes in technology, like the automobile,

which changed the shape of cities, and the evolution of the business industry, create a

need to understand and analyze traffic flow, social characteristics, social behavior, and

people's lifestyle preferences. Also, the advances of computers and the introduction of

GIS (Geographic Information Systems) redirected the study and analysis of the market to

a more complete and profound understanding of consumers and neighborhood

characteristics, which ultimately improves the analysis and data for business geography.

For the analysis of the magazine industry's market, the Lifestyle Segmentation

Profile (LSP) is used because the magazine industry also classifies their subscribers by

LSP; further, programs like CACI Coder/Plus that are commonly used to geocode the

data assigns a specific Lifestyle Segmentation Profile (LSP) to each address.









Being able to classify subscribers in this way can improve understanding of which

their customer is, in terms of salary, education level, and occupation, which improves

their judgment in decision making for marketing, distribution, and development. Further,

these LSPs can be used to evaluate a single market and the LSP of two or more markets

(Figure 5). The table listed below outlines the indices used for classifying people into

nine categories based on similar characteristics.

TIMELINE OF LOCATION-BASED MARKET ANALYSIS


Stage


1. Pedestrian and sign posting era


2. Mapping and cartography


3. Sales potential predictive models


Description


The city center offered the best location for
marketing high-order retail goods. Other
sites may have been chosen, but on a trial-
error basis. Some parallels to this approach
exist today: for example, some national
retail chains consider only a location near
the regional mall adjacent to the freeway
exit (Thrall et al. 1996)

The cumulative body of knowledge about
locational analysis goes back at least to the
1920s and the use of gravity models back
to the 1850s. Early applied business
geography originates with contract work by
retail chains to determine the relative value
of a site, compared with the relative
advantages of other sites. Most important
in the development of this stage was the
work of Applebaum. The methodologies
used in the era before contemporary
geographic technologies were mainly
subjective in nature (Goldstucker et al.
1978).
Began in the mid-1960s and contributed a
number of methodological advancements,
particularly in using and manipulating
statistical data to arrive at sales potentials


Figure 4. Timeline of location-based market analysis by Thrall (2002).











Stage Description

for a total complex of stores in a shopping
center (Craig et al. 1984). Most important
in the development of this stage of
marketing geography were the
contributions of Huff (1959, 1963) to the
advancement of gravity and spatial
interaction models. For discussion, see
Haynes and Fotheringham (1984)
4. The rise of the holistic view Began around 1966 and saw the
development of more sophisticated models
of retail potential that considered the
influence of store size, distance, image
factors, merchandise quality, and services
of all competitors within the same trade
area. During this stage, academic research
largely had the objective of measuring
retail image and the dimension that
underline these perceptions; seldom were
these considerations deal with in the
professional and academic locational
analysis literature prior to the 1960s
(Goldstucker et al. 1978). This stage differs
from the third stage by the inclusion of
nongeographic factors as having equal or
even greater importance than location.

5. GIS as an exotic technology The 1970s and 1980s were the beginning of
the use of geographic information systems
in retail location analysis. However, the
software in this era was very complex,
often having been adopted from natural
resource applications, or written from
scratch by programmers at the retail firm.
Data were either very expensive. GIS had a
deserved reputation in this era of being an
exotic technology that was very expensive
and difficult to use. The GIS of this era was
dependent on mainframe computers or
large workstations.

Figure 4. Continued









Description


6. GIS as common desktop computer
technology, integration of geographic
analysis into routine strategic
management


Noted for significant advances in desktop
computer hardware, including CD-ROMs
for the distribution of data: the widespread
use of Microsoft Windows operating
system that allowed for the standardization
of the software user interface: declining
computer software programming cost; and
the emergence of a business geography
technology industry offering a wide array
of low-cost data and specialized, highly
productive software applications. The
future of this stage will include the
integration of GIS and management
practices, a greater sophistication of the
modeling behind the analysis, automation,
improved qualitative analysis, and real time
information delivered via the Internet.


Figure 4. Continued

ACORN lifestyle segmentation indices

ACORN Category Description

1. Affluent families 1A Top one percent
1B Wealth seaboard suburbs
1C Upper income empty nesters
ID Successful suburbanites
1E Prosperous baby boomers
1F Semirural Lifestyle
2. Upscale households 2A Urban professional couples
2B Baby boomers with children
2C Thriving immigrants
2D Pacific Heights
2E Older settled married couples
3. Up & coming singles 3A High rise renters
3B Enterprising young singles
4. Retirement styles 4A Retirement communities
4B Active senior singles
4C Prosperous older couples
4D Wealthiest seniors
4E Rural resort dwellers
4F Senior sun seekers


Figure 5. ACORN lifestyle segmentation indices by CACI/Coder Plus.


Stage










ACORN Category Description

5. Young mobile adults 5A Twenty something
5B College campuses
5C Military proximity
6. City dwellers 6A East Cost immigrants
6B Working class families
6C Newly formed households
6D Southwestern families
6E West Cost immigrants
6F Low income young and old
7. Factory and farm communities 7A Middle America
7B Young frequent movers
7C Rural industrial workers
7D Prairie farmers
7E Small town working families
7F Rustbelt neighborhoods
7G Heartland communities
8. Downtown residents 8A Young immigrant families
8B Social security dependents
8C Distressed neighborhoods
8D Hard times
8E Urban working families
9 Nonresidential neighborhoods 9A Business district neighborhoods
9B Institutional populations
9C Unpopulated areas
Figure 5. Continued

This LSP and market analysis improves the judgment (Stage Four) of the company

for which the market analysis is done by giving the company a more complete

understanding of their market; this also gives the company more insight for better target

marketing and creating a more proficient target strategy to increase their audience.

Likewise, this enables them to identify specific target markets or increase the subscribers

of less saturated markets. This analysis also helps to identify where the strongest and

weakest markets are located and what the LSPs are for the specific markets.

This analysis provides companies with a composite of the likes and wants of their

markets. This form of analysis, which most companies in the industry do, represents only









one of the four types of consumers' information (Figure 6). However, to get a better

understanding of their markets the use of Lifestyle Segmentation Profiles (LSPs) can

increase the assessment of each individual (consumer) and, at the same time, better

characterize markets and consumers of the publishing company. Of course psycho

demographics are important, but Lifestyle Segmentation Profiles (demographics,

psychographics, purchase behaviors, and media preferences) with the incorporation of

business geography and GIS, shows a more complete analysis and representation of the

market characteristics, their subscribers' spatial location, and consumption

characteristics. This can be understood also as the cognitive measures that the marketing

industry use adding the geographical analysis.

Consumer researchers who desire to know about their market more than just
demographic characteristics may attempt to collect cognitive information; that is,
information about consumers' knowledge, attitudes, motivations, and perceptions.
Merely observing consumers cannot fully explain why they behave as they do, and
questioning often does not provide reliable answers because of consumers' inability
or reluctance to reveal true feelings to an interviewer. Thus, researchers attempt to
explore intervening variables potentially useful in explaining consumer behavior by
utilizing other techniques. (Loudon, Della Bitta, 1979)

This analysis explains and demonstrates the necessity of the publishing companies

to incorporate the new technology and ideas of GIS and business geography. Applying

the four types of consumers' information from the following Figure 1-6 to the publishing

industry helps determine valuable information about their subscribers' demographics

(age, income, occupation, location), psychographics (what they think), media preferences

(print or broadcast), and purchased behavior (how they spend their money). Using this

information, the magazine could decide what kind of advertisements are best suited for

inclusion in the magazine, type of advertising to market their magazine, what cost to

charge for the magazine, and where to distribute the magazine. These types of decisions









are crucial for the growth and success of any organization. And, any organization can use

these business geography ideals to make Better Business Decisions (BBDs).

Chapter 2 presents a literature review of the industry involved in this thesis.

Relevant articles have been chosen according to their importance to the GIS, magazine,

and business geography industries.

Chapter 3 details how the data acquisition process and steps applied to the data set

in order to analyze it. GeoSpatial Solutions made this data set available for these

analyses.

Chapter 4, using data provided by GeoSpatial Solutions, describes where the

Geographic Information Systems Market, composed of companies using GIS, is located

and who uses GIS in the US. This chapter is broken into three main areas. The analysis

then proceeds to explain why the industry is located where it is. First, the geographic

regions in the United States is analyzed to identify the primary, secondary, and tertiary

submarket regions of GeoSpatial Solutions' subscribers in each individual submarket.

Second, the location of the GIS producers and their submarkets in the US is identified.

And, third, this chapter identifies geographic locations of GIS firms and their submarkets

in the US.

Chapter 5 identifies the social-economic influences of submarkets with a high

concentration of GIS users for the different markets of the US. This chapter is divided

into four sub areas. First, the analysis shows geographic areas with high concentration

regions of GIS. Second, the analysis shows the influences of high education to attract the

GIS market to the region. Third, the analysis shows the influences of the submarkets to









attract firms to the region. Fourth, this analysis shows the influences of the area for GIS

producers to locate in a specific region.

Chapter 7 addresses the relevant questions for use in a global perspective for

international market analysis. This analysis assists international markets to increase

economic opportunities by focusing on the GIS industry and its characteristics.

Chapter 8 concludes this analysis by explaining where and why GIS locates in

particular geographic markets.


CONSUMERS


Figure 6. The four types of consumer information. This figure presented in The
Insider's Guide to Demographic Know-How in 1990.














CHAPTER 2
LITERATURE REVIEW

Business geography literature dates to the early part of the last century however

for the purpose of this analysis the focal point of this thesis is on the "New business

geography, according to Thrall (2002) is "...the assembly of information on trade areas,

demand, and competitive supply for the purpose of improving the judgmental decision."

The goal of a business geographer is to create analysis for a client that enables more

informed business decisions to be made. Thrall (2002) has presented the stages that GIS

analysts and business geographers in particular, go through in their reasoning. These

stages are:

1. Description
2. Explanation
3. Prediction
4. Judgment
5. Management and Implementation

The most important stage to the business geographer is judgment. Judgment is

necessary in the final analysis to justify the business geographic analysis. The geographic

analysis is expedited using geographic technology, including data and GIS software. This

GIS software has great applications of the business geography field. Bill Pinkovitz, N.R.

Sumathi and Bill Ryan noted the importance of the data, demography, lifestyle, etc for

the Business Geographer. Also, the GIS technology has opened a field in which the data

can be represented by mapping demographics. Business geographers use GIS technology

to create comprehensive pictures of the subscribers' markets. Piccilli (1999) explains the

advantages of mapping demographics and the further analysis possible with the current










technology. The chart in Figure 7 shows six unique characteristics of the advances of

technology on the business geography and GIS Analysis field. These methods help the

companies to utilize data sets and consumer characteristics to make better decisions.

Media buys:
Once the precise location of your customer base is known, you can make cost-
effective media buys that get the right message to the right target. For example,
by using the knowledge gained from mapping their customer base, a marketer
who wants to place inserts in a local newspaper can target the neighborhoods
with the highest level of customers.
Competitive analysis:
Plotting the location of the competition (direct and indirect) on a map is much
easier to understand than a list of locations on a report. You can adjust your
marketing strategy to fit the number of competitors in the immediate geographic
area.
Drive-time analysis:
Mapping your customer drive times is useful for analyzing cannibalization issues,
new store placement and competition. By plotting the drive-time area on a map,
you clearly see any overlap among various business locations and competitive
sites. Barriers such as military bases, airports, parks or college campuses all
influence your customer's drive time, but those barriers are not apparent on
reports.
Market-entry planning:
Using demographic mapping for market-entry planning clearly identifies sales
potential in a region. For market entry, be sure to look at retail sales potential,
lifestyle segments, propensity to use or purchase products and services,
population, income, age, number of businesses and competition. Using a
thematic map, your marketing strategy can be tailored to fit the new market's
unique characteristics.
Budgeting:
For comparisons, demographic mapping is invaluable. Analyzing maps for each
geographic area enables marketers to determine where to allocate their budgets.
Areas with high growth potential or high sales potential are quickly spotted and
marketing strategies can be adjusted accordingly.
Lifestyle segmentation:
Used in conjunction with demographic mapping, segmentation is a great tool for
identifying quality prospects. Lifestyle segmentation systems use demographic
and aggregated consumer demand data to classify every household in the United
States into a unique market segment. Each segment consists of households that
share similar interests, purchasing patterns, financial behavior and demand for
specific products and services.
Figure 7. The advantages of mapping demographics and the further analysis possible by
Piccilli 1999.

However, one of the principal problems that the GIS industry encounters is

distinguishing itself from other industries. GIS is part of many applications, users, and

disciplines. And the GIS industry is comprised of hardware, software, and data (users and










creators). Purvi Rajani (2002) expresses the confusion of this field to identify itself by

showing the questions that can separate the industry "Which products and companies

should consider GIS and, perhaps more importantly which one shouldn't? Is it fair to

compare MapInfo Corp., Troy, N.Y., with Genasys II Inc., Fort Collins? Are these

companies really in the same industry?" This is a continuous dilemma that the GIS

industry must consider and analyze itself. Valerie L. Hartung (1997) analyze the GIS

industry, although the fast growing characteristics of this industry make it difficult to

research. Hartung attempts to evaluate the role of the GIS industry and she describes the

nature of the industry as a pyramid of functionality, which each layer has to support the

previous one.

THE GOAL (Top of the pyramid)

Is the goal clearly defined, with measurable
objectives and time frame?
Is the goal, as defined, truly of benefit to the
organization?
Is the budget available to accomplish the goal?

USER

Do the users have enough time available to
implement the new system?
Do the users have adequate training?
Are the users motivated to make the system work?

DATA

Is all of the data that is needed available?
Is the data free from errors?
Does the data require conversion from another format
or medium?

APPLICATION SOFTWARE

Does the application software truly accomplish the
goal or goals desired?
Is the application software available from a reliable
company?
Does the application software require customization?










NETWORK

Is the network reliable?
Does the network have adequate storage and space?
Is the network security being used?

OPERATING SYSTEM

Do the operating systems best support the application
software?
Do the operating systems best support the users'
needs?

HARDWARE (foundation of the pyramid)

Is the hardware reliable?
Does the hardware have all the components to support the layers
above?

The dataset that was collected through a survey that Hartung created gave a small, but

reliable dataset. However, for a complete statistical analysis of the GIS industry or related

firms this is a very small sample size (Figure 8).


United
States Canada Total


Sampling Frame 874 345 1219
Population2


Number of Firms 504 194 698
that agreed to
participate


Number of 300 84 384
Responses

Response Rate 59.5% 43.3% 55.0%


Figure 8. Survey response statistics conducted by Hartung 1997.

Through her study, Hartung then analyses the characteristics of the industry growth.

Moreover, Hartung shows statistically that the revenue for this industry is increasing. The









results of her survey revealed many characteristics about the GIS industry, which are

listed below:

* GIS firms are young (median year founded 1983, first year GIS revenue 1989),
small (median labor force is eleven) and earn on average $1 Million per annum.

* Approximately one-half of the respondents earned export revenues.

* One third of known GIS firms are located in the Colorado Corridor, Washington
Beltway, and Los Angeles and its Environs.

* Firms located in one of the three tier one clusters are apt to be more specialized
then those firms located elsewhere.

* GIS firms appear to be vertically integrating, offering customers a full-service
solution or one-stop shop.

* The largest demand market for GIS technologies is utility companies and all levels
of governmental agencies.

Hartung maps the firms to provide a geographic view of the GIS industry.





comprehensive assignment of geographic information, which includes, latitudes,
it a lify sio in io. T m in i y


.

I ,1






Thrall (1998) demonstrated the important uses of geocoding software to identify

the geographic location of subscribers and their LSP characteristics. CACI Coder/Plus is

software that gives the analyst the advantage of analyzing a data set and obtain a

comprehensive assignment of geographic information, which includes, latitudes,

longitudes, and lifestyle segmentation information. The magazine industry understands









the importance of reaching the right market so lifestyle segmentation is a way to

understand who your market is. Cathy Bond (1997) documents customer magazines are

using segmentation (lifestyle) as a marketing tool to reach the right people the right

message. Some magazine titles are promoting services for the right lifestyle customer,

age, or social economic profile. This lifestyle segmentation is important to assess the

lifestyle of the US subscribers and dependent upon business geography because to

survive it must be oriented to its global market. So in a general way the magazine

industry has become more scientific than before and has also become more market

oriented. As Sharpf (1989) explains these advances have attracted both advertising

market and advertisers that are willing to pay to "fine tune their advertising expenditures

to keep waste to a minimum." The market research industry organizations are using their

knowledge of lifestyle to increase their analysis proficiency. Sharpf (1989) argues:

For the publisher, the cost of subscriber's analysis, the trade down risk, and the
economic feasibility of segmentation can make for a complex marketing package. It
can also mean developing editorials to go with the segmentations; but that again
should help the sell.

Further, Dickenson (1998) explains that the magazine industry has advanced to a

point in which magazines and brochures can be produced for specific segmentation

groups (lifestyles) that the publishing company or magazine wants to target. An example

of this is Goldfish, which is a United Kingdom credit card company that produces a

guided index of their members' lifestyle segmentation that helps the magazine industry in

targeting specific lifestyle segmentations.

The publishing industry is a very competitive industry. As Chepesieuk (1994)

explains that specialization and the use of segmentation is essential for magazine in the

industry to survive and grow. A good example of this is Winston-Salem Journal (N.C.)









had to specialize to the lifestyle of his market to survive the competition of two new local

real estate publications. Niche publishing can be form by the analysis of segmentations

like women, men, ethic group, the elderly, tourist, children, professors, etc. Even a high

regarded publication like the Chicago Tribune had to target a specific lifestyle segment

(elementary and high school) during the 80's to increase their market readership. Thrall

(2001) presents a case for (Thrall, 2002) that Lifestyle Segmentation Profile for a good

market analysis is today a required part of the analyst's report.

The lifestyle segmentation profile is derived by the combination of census

databases and private databases. LSP (lifestyle segmentation profile) is the main

characteristic that the magazine industry should take in consideration for use in their

market analysis. Pinkovitz (1997) denotes the differences of consumers' lifestyles

(psychography), where they live, (geography), and age, income, etc. (demography). On

the other hand, the LSP (lifestyle segmentation profile is a more complete way of

segmenting the market and the Business Geographer is the person that puts these small

groups together and creates a more profound analysis. Hucker-Brown (2003) joins these

ideas by combining demographic data or segmentation data with the likely market a

better understanding can be done.

The following analysis brings together all of these ideas to create a clear and unique

analysis of GeoSpatial Solutions magazine and with this data try to understand the social

and locational makeup of the GIS industry.














CHAPTER 3
DATA METHODOLOGY

The data used for the analysis was made available by Advanstar Communications

for their GIS magazine GeoSpatial Solutions. The database includes their entire

subscribers list (approximately), a list of GIS business firms in the US, and a list of

international GIS companies also from GeoSpatial Solutions, which are used to document

and corroborate GIS business concentrations within submarkets. Social-economic data

from the 2000 US Census, private data vendors, and CACI Coder/Plus (ESRI) are used to

understand the social influences of submarkets to attract GIS firms and GIS producers to

specific submarkets in the US Analysis is produced using leading GIS technology

including CACI Coder/Plus (ESRI), ArcGIS (ESRI), ArcView Business Analyst (ESRI),

and Microsoft Excel.

Data Acquisition

To acquire the data from GeoSpatial Solutions, a constant communication link was

made by Dr. Grant Ian Thrall (University of Florida Professor of business geography),

Scottie Barnes (Editor for Advanstar Communications, GeoSpatial Solutions) and me.

After a few weeks, Advanstar Communications, the publishing company for GeoSpatial

Solutions, released their subscribers' data lists to Dr. Grant Ian Thrall and me. These data

lists included 27,050 subscribers, 647 firms, and 161 international firms. Because of the

competitive nature of this market, all the parties involved signed a disclosure agreement

to keep their subscribers lists confidential. Also, due to competitive nature of the









magazine publishing industry, any preliminary results of this research were kept

confidential until the publication of articles in GeoSpatial Solutions.

The 27,050 subscribers' data provided by the GIS magazine GeoSpatial Solutions

was processed using ESRI's geocoder program CACI Coder/Plus. Executing the CACI

program on the list, using data from address fields one and two, assigned a latitude and

longitude to each address. The original data set had two different address fields. To have

a more complete data set, using Microsoft Excel, the data was analyzed and the two-

address fields were consolidated into a single, more complete address field. Afterward,

using this complete address field the program CACI Coder/Plus (ESRI) was again used to

give each completed address geographical latitude and longitude, and an individual

Lifestyle Segmentation Profile (LSP). The results of the CACI Coder/Plus geocoding

process were included in the analysis of the program in a Geocoding Match Level

Summary at the completion of this analysis. Because the subscribers' data list has

multiple address lists, the process of geocoding was processed three separate times.

Geocoding Results

The first address gave only a 4.9% accuracy level. All the addresses from the first

address list were kept and the rest of the subscribers were deleted. Then using Microsoft

Excel, the addresses that did not have a latitude and/or a longitude were checked for data

entry errors, such as extra spacing within the address, or a misspelling in the street name;

were edited and the addresses that could not be edited because of data entry errors or non-

distinguishable addresses were removed from the list.










Table 1. Geocoding match level summary of 27,050 subscribers' first address field
from CACI Coder/Plus.
Number of Records: 27,050

Match Description Match Code Number Percent



Dominant Tract in ZIP Code Z 22,809 84.3%

One Tract in ZIP Code T 1,263 4.7%

No Geocode X 1,648 6.1%

27,050 100.0%



The second address field (column) gave a 66.2 % accuracy level. The same

process as was used for the first address field, using Microsoft Excel, was followed to get

a more accurate data set of the address lists.

Table 2. Geocoding match level summary of 27,050 subscribers' second address field
from CACI Coder/Plus.
Number of Records: 27,050

Match Description Match Code Number Percent


Dominant Tract in ZIP Code Z 6,691 24.7%

One Tract in ZIP Code T 901 3.3%

No Geocode X 1,542 5.7%

27,050 100.0%



Final Dataset

After, editing the two address fields, the two data sets were merged together. The

final list was also geoprocessed using CACI Coder/Plus by Dr. Grant Thrall. The final

result of CACI Coder/Plus was a geocoded match of 73.4%, which is 26,024 subscribers

from the original data set. These 26,024 subscribers of GeoSpatial Solutions were used to

proceed with the analysis.










Table 3. Geocoding match level summary of 26,024 subscribers' final address field
from CACI Coder/Plus.
Number of Records: 26,024

Match Description Match Code Number Percent

Street Match S 19,101 73.4%

Dominant Tract in ZIP Code Z 5,537 21.3%

One Tract in ZIP Code T 850 3.3%

No Geocode X 536 2.1%

26,024 100.0%

The same three-step geocoding process was performed with the firm's data list.

Due to a lack of international GIS software, the international firm's data set was

geocoded using geospatial proximities to obtain a general overview of GeoSpatial

Solutions' global market.














CHAPTER 4
MAPPING THE GEOSPATIAL COMMUNITY

This chapter provides a business geographic analysis of GeoSpatial Solutions'

subscriptions. Using the final data list, Business Analyst (ESRI) and ArcGIS (ESRI), a

map of the total subscribers was created. This subscriber's map shows a complete

presentation of Geospatial Solutions' subscribers nationally. The map corresponds to

high concentrations of subscribers located in metropolitan areas. The northeast US shows

the largest concentration of GeoSpatial Solutions subscribers in the US. These states

include New Hampshire, New York, Virginia, and the District of Columbia. From this

map, other high concentration geographical market regions can be distinguished (Figure

9).

The map represents a general subscribers' representation of GeoSpatial Solutions.

The subscribers of each state are represented with colored dots, with each state having its

own color. The total count of subscribers by state is located in the legend at the bottom

left of the map. To create this map the data set for total subscribers was utilized. After

selecting the geoprocessing wizard from the tool icon, the attribute selected was to do a

count (dissolve) on each state based on subscribers. The input layer used was the

subscriber. After, the specific output (save as) archive was selected; an additional field

for ACORN LSP categories was activated. The new layer created also included the total

count of subscribers by state. The subscriber's layer and the new subscribers count layer

were merged according to their state field. Next, using the properties of subscribers the












































Figure 9. GeoSpatial Solutions' US market subscribers processed using ArcMap (ESRI).









symbology tab was selected to activate. From these new windows, the unique values-

many fields category was selected. Then, the states and count-states were selected and all

the values were added. The legend symbols were edited for better presentation and fit and

they were integrated with the new map (Figure 10). The following map represents the

percentage rate of the total subscribers for GeoSpatial Solutions' data set by state (Figure

11).

Geographic Regions in the US

The market analysis identifies primary, secondary, and tertiary submarket regions

of GIS (Subscriber and Companies) in the US.

To create this map, the subscribers' data set was separated into three submarkets to

show the states with high, middle, and low representation of the US market. To create

these three submarkets, the geocoding match level summary from CACI Coder/Plus

(ESRI) was used. The following table outlines the top 20 states by highest number of

subscribers per state (Table 4). The corresponding percentage demonstrates the

percentage of all subscribers in each state.

Table 4. Geocoding match level summary of top 20 states by number of subscribers
from CACI Coder/Plus.
Record Count Percent
Top 20 States
California 3,286 12.6%
Texas 1,564 6.0%
Florida 1,429 5.5%
New York 1,271 4.9%
Virginia 1,179 4.5%
Pennsylvania 955 3.7%
Illinois 872 3.4%
Colorado 869 3.3%
Ohio 832 3.2%
Maryland 772 3.0%
Washington 677 2.6%
New Jersey 661 2.5%
North Carolina 630 2.4%









Michigan 627 2.4%
Georgia 609 2.3%
Massachusetts 599 2.3%
Minnesota 520 2.0%
Wisconsin 512 2.0%
Missouri 504 1.9%
Oregon 487 1.9%
Other States 6,633 25.5%
Non-geocoded Records 536 2.1%

The top 20 states list was used to further divide the data set into the top 3 markets,

in terms of percentage of subscribers, for GeoSpatial Solutions. A state being classified

as primary means that the state contains over 4% of all GeoSpatial Solutions subscribers.

A state being classified as secondary submarket means that the state contains 2% to 3.9%

of all GeoSpatial Solutions subscribers. And the tertiary submarket means that the state

contains 1.9% and below of all GeoSpatial Solutions subscribers. These three submarkets

were separated into three individual maps for a more in depth look at the three primary

submarkets. These layers show all three leading submarkets for GeoSpatial Solutions and

by implication the GIS industry in the US. Moreover, it represents the strongest and

weakest market saturation areas for GeoSpatial Solutions (Figure 12).

Primary Submarket

Figure 13 shows the states that represent the primary submarket of subscribers in

the US and their total count. These states were selected based on their percentage

classification. The primary submarket is made up of those states with 4% and above

subscriber representations by state. The states that comprise the primary submarket are

CA with 3,309 subscribers, TX with 1,587 subscribers, FL with 1,473 subscribers, NY

with 1,279 subscribers, and VA with a total subscriber list of 1,207 (Figure 13).












































Figure 10. GeoSpatial Solutions individual state subscribers color-coded by state counts processed using ArcMap (ESRI).












































Figure 11. GeoSpatial Solutions' US market subscribers percent by State using ArcMap (ESRI).











































Figure 12. GeoSpatial Solutions' three US GIS submarkets processed using ArcMap (ESRI).










Secondary Submarket

Figure 4-6 is a representation of GeoSpatial Solutions subscribers by state that fit

the secondary market, which was created, based on the percentage of subscribers by state

that CACI Coder/Plus (ESRI) summary released. The secondary submarket represents

2% to 3.9% of subscribers by state. The states that form this submarket include: PA with

959, CO with 937, IL with 876, OH with 835, MD with 772, WA with 678, NJ with 666,

NC with 636, MI with 630, GA with 617, MA with 599, MN with 522, and WI with 512

(Figure 14).

Tertiary Submarket

Figure 15 shows the tertiary submarket of subscribers, formed by using the

percentage of the top 20 states on the CACI Coder/Plus (ESRI) summary list. All the

states that have 1.9% of subscribers or below are included. The states and their individual

subscribers counts follow (Figure 15). The state counts for the tertiary submarket were

also included in the analysis (Table 5). (Human data entry errors should be considered.)

Table 5. GeoSpatial Solutions' tertiary submarket counts processed using CACI
Coder/Plus (ESRI).
Subscribers
STATE, CountSTATE DE, 60 MO, 517 PR, 135
AA, 1 GU, 6 MS, 230 PW, 2
AE, 5 HI, 159 MT, 160 RI, 92
AK, 133 IA, 262 ND, 121 SC, 296
AL, 373 ID, 186 NE, 205 SD, 116
AP, 8 IN, 398 NH, 160 TN, 390
AR, 176 KS, 249 NM,247 UT, 275
AZ, 466 KY, 273 0 NV, 223 VI, 1
CT, 302 LA, 312 OK, 238 VT, 56
DC, 208 ME, 161 OR, 487 WV, 137
WY, 103










































Figure 13. GeoSpatial Solutions' primary submarket processed using ArcMap (ESRI).











































Figure 14. GeoSpatial Solutions' secondary submarket processed using ArcMap (ESRI).
































































A ,1 GU.6 N* ,230 PlU.2
AE., HI, 159 PET, 1I R1,92
AK, 133 L. 2 ND,121 SC 296
AL.373 ID,186 NE,. 5 SD, 116
AP, IN,398 NH, 16U TN,3.
AR, 16 S,249 NI.2? UT,2 7
Z* A 4 K Y .2T3 N .223 VI,1.
CT,3,2 LA,312 OK 23 VT, 56
D, 2WD ME, 161 OR,48T7 At,13?
i103 0 800
Figure 15. GeoSpatial Solut Milessubm




Figure 15. GeoSpatial Solutions' tertiary submarket processed using ArcMap (ESRI)












Table 6. GeoSpatial Solutions' percentage of subscribers by state using data from the
US Census Bureau.

Percentage Rate of Subscriber by State

State Population 18 years and Over Subscribers Subscribers per capital 100000
Colorado 3,200,466 937 29.28
Wyoming 364,909 103 28.23
North Dakota 481,351 121 25.14
Montana 672,133 160 23.80
Virginia 5,340,253 1207 22.60
South Dakota 552,195 116 21.01
Idaho 924,923 186 20.11
Maryland 3,940,314 772 19.59
Oregon 2,574,873 487 18.91
New Mexico 1,310,472 247 18.85
Utah 1,514,471 275 18.16
New Hampshire 926,224 160 17.27
Maine 973,685 161 16.54
Nebraska 1,261,021 205 16.26
Washington 4,380,278 678 15.48
Nevada 1,486,458 223 15.00
Minnesota 3,632,585 522 14.37
California 24,621,819 3309 13.44
Wisconsin 3,994,919 512 12.82
Kansas 1,975,425 249 12.60
Missouri 4,167,519 517 12.41
Arizona 3,763,685 466 12.38
Massachusetts 4,849,033 599 12.35
Vermont 461,304 56 12.14
Iowa 2,192,686 262 11.95
Florida 12,336,038 1473 11.94
Connecticut 2,563,877 302 11.78
Rhode Island 800,497 92 11.49
Alabama 3,323,678 373 11.22
Mississippi 2,069,471 230 11.11
Texas 14,965,061 1587 10.60
New Jersey 6,326,792 666 10.53
North Carolina 6,085,266 636 10.45
Georgia 6,017,219 617 10.25
Pennsylvania 9,358,833 959 10.25
Delaware 589,013 60 10.19
Ohio 8,464,801 836 9.88
South Carolina 3,002,371 296 9.86
West Virginia 1,405,951 137 9.74
Louisiana 3,249,177 312 9.60
Illinois 9,173,842 876 9.55
Oklahoma 2,558,294 238 9.30
Tennessee 4,290,762 390 9.09










Table 4-3. Continued
State Population 18 years and Over Subscribers Subscribers per capital 100000
Kentucky 3,046,951 273 8.96
New York 14,286,350 1279 8.95
Indiana 4,506,089 398 8.83
Arkansas 1,993,031 176 8.83
Michigan 7,342,677 630 8.58
District of Columbia 4,570,678 208 4.55
Source: U.S. Census Bureau Public Information Office


Table 6 is the rate of GeoSpatial Solutions subscribers by state (Table 6). To create this

chart, data from the 2000 US Census of population 18 years of age and over was used.

The formula used to get the percentage rate is:

(Subscriber) / (population) (100,000)




The chart shows a descending percentage rate of the states with the higher

percentage rates to the lower percentage rates. The publishing industry would generally

view tables like this as evidence of which states have the greatest potential for expansion.

That interpretation might carry over here as well. Florida and California both have large

GIS subscriber bases, but not as large as the total population of the state would indicate.

The lower-rated states should be considered for as opportunities for market growth in

subscriptions for these states (Figure 16).

GIS Producers

Within the GeoSpatial Solutions database, subscribers are required to select which

industry best represents their use of GIS. This is known as the "Business Code" database.

The business codes map represents a general spatial location of the business codes.

The business codes map was created using the data list of subscribers. The list below has

a field for Business Codes, Function Codes, and Title Codes (Table 7).









Table 7. GeoSpatial Solutions' business code categories using their data set.

Business Codes
Card Code Description
10 Surveying / Mapping
20 Government Operations
30 Construction / Mining / Civil Engineering
40 Utilities / AM / FM
50 Natural Resources / Environmental Planning
55 Telco (including Cellular / Wireless)
60 Business Services
70 Software Development / Systems Integration
160 Education / Research
85 Healthcare
90 Other

Organizational Affiliation Codes (Function Codes)
Card Code Description
15 Government/Public Sector
25 Private Business
35 University/College
45 Other

Title Codes (Code 31)
Card Code Description
Corporate Management
1 Owner, President, CEO
2 Senior Manager (incl. VP, General Division Manager, etc.)
3 VP/Director/Manager Sales & Marketing
4 Other Corporate Management
Information Technology (MIS/IS)
5 Senior Manager (incl. CIO, VP, etc.)
6 Manager-Information Technology/Systems (incl. MIT/MIS)
7 Applications Developer
8 In-house User Support Representative
9 Internet/Web Designer/Developer
L Other IS or IT Staff


Operations
M
N
0
P


Senior Manager (including COO, VP, etc.)
Manager (incl. Coordinator/supervisor/administrator/data processing systems)
Engineer
GIS Technician









Table 4-4. Continued
Business Codes
Card Code Description
Q Geospatial Professional (incl. Biologist/ geologist/ professor/ cartographer/
surveyor/ mapmaker and all others)
R Systems Integrator
S Technician/Analyst/Administrator
T Other Operations
Other Job Title
U Other


These data codes are collected from the subscribers' card codes that are selected when

people subscribe to the magazine (Figure 17) and (Figure 18). To perform this analysis,

the three codes were analyzed individually and also the Title Codes were separated into

three categories (Corporate Management, Information Technology, and Operations).

The map shows all the ten classifications together as a general group. Each

individual subscriber selects his or her individual classification on the card codes when

they fill out their subscription card.

















Subscribers per capital (Penetration Rate)


35.00



30.00



25.00

0
0
o 20.00



15.00



10.00



5.00



0.00



Q e I c ll

States



Figure 16. GeoSpatial Solutions' percentage rate of subscribers by state using data from the US Census Bureau.











42

















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Business Codes

Figure 19 is the general spatial location of subscribers by business codes. The

Business Codes map was also created using the data list of subscribers. The list has a

field for Business Codes. This business codes data is collected from the card codes that

the subscribers check when subscribing to the magazine (Figure 19). This map represents

the percentage of total subscribers in the business codes category of GeoSpatial

Solutions' database by state (Figure 20).

This map shows each of the ten business codes groups in a different color and lists

their individual counts by category. The legend of this map shows:


Table 8


GeoSpatial Solutions' s


Code Description Total Subscribers Percentage

10 Surveying/Mapping 3,574 13.7%

20 Government Operations 5,689 21.9%

30 Construction/Mining 2,936 11.4%

Civil Engineering

40 Utilities/AM, FM 1,431 5.5%

50 Natural Resources 2,245 8.6%

Environmental Planning

55 Telco 866 3.3%

60 Business Services 3,383 13%

70 Software/Development 2,556 9.8%

System Integration









Table 4-5. Continued
Code Description Total Subscribers Percentage

85 Healthcare 644 2.5%

90 Other 60 .2%

160 Education/Research 2,614 10.1%





This map gives an idea of which market groups have high and low subscriber

representation by GeoSpatial Solutions (Figure 21).

Organizational affiliation

The Organizational Affiliation codes (Function codes) were created to distinguish a

geographic perspective where these codes were located in the US. The organizational

affiliation is formed by four unique category codes: 15, Government/Public Sector; 25,

Private Business; 35, University/College; 45, other. This map represents the total

Organizational Affiliation market (Figure 22). The proceeding map illustrates the

organizational affiliation code of GeoSpatial Solutions' subscribers by state (Figure 23).

The second map represents the function codes and respective counts for each category

(Figure 24).

Title codes

The Title Codes (Code 31) were too large to analyze as one group, so the group

was separated into its three main categories (Table 8). Each category was analyzed

independently to better understand its markets. Maps for these categories were created

and maps of individual counts for each category were also created.












































Figure 19. GeoSpatial Solutions' combined business codes processed with ArcMap.












































Figure 20. GeoSpatial Solutions' combined business codes percent by state processed with ArcMap.











































Figure 21. GeoSpatial Solutions' individual business codes processed with ArcMap.










Table 9. GeoSpatial Solutions' title code categories using their data set.
Title Codes (Code 31)
Card Code
Corporate Management
1 Owner, President, CEO
2 Senior Manager (incl. VP, General Division Manager, etc.)
3 VP/Director/Manager Sales & Marketing
4 Other Corporate Management
Information Technology (MIS/IS)
5 Senior Manager (incl. CIO, VP, etc.)
6 Manager-Information Technology/Systems (incl. MIT/MIS)
7 Applications Developer
8 In-house User Support Representative
9 Internet/Web Designer/Developer
L Other IS or IT Staff
Operations
M Senior Manager (including COO, VP, etc.)
N Manager (incl. Coordinator/supervisor/administrator/data processing systems)
O Engineer
P GIS Technician
Q Geospatial Professional (incl. Biologist/ geologist/ professor/ cartographer/ surveyor/
mapmaker and all others)
R Systems Integrator
S Technician/Analyst/Administrator
T Other Operations

Corporate Management:

This map shows the general geographic location of all of the subscribers that fit

the category of corporate management from the title code list (Code 31). The data set of

subscribers that fit this corporate management category and a new layer was created

(Figure 25). The next map shows the percent of total corporate management subscribers

of GeoSpatial Solutions' dataset by state (Figure 26). This map shows the corporate

management category query builder from the subscribers' data set. The corporate

management code is divided by GeoSpatial Solutions into four different groups. The map

shows each of these four groups in a different color and it shows the count of subscribers

that fit the categories (Figure 27).









Table 10. GeoSpatial Solution' corporate management codes.
Categories Total Subscribers Percent of Total

Owner/President/CEO 4,398 44.8%

Senior Manager 2,524 25.7%

VP/Director/Manager Sales and 1,456 14.8%

Marketing

Other Corporate Management 1,438 14.7%





Information Technology:

This map shows a general representation of all the subscribers that fit on the Title

Code (Code 31) list (the category of information technology). This category is selected

from the general subscribers list and an individual layer of these subscribers was created

to show their representation in the US (Figure 28). This map represents the percent of

information technology subscribers of GeoSpatial Solutions' dataset by state (Figure 29).

This map shows a deeper analysis of the Information Technology code. The

information technology code is broken into six categories, which were selected by the

subscribers when they filled out the card for their subscription. Also, the total count for

each of these six categories was produced. The six categories are:

Table 11. GeoSpatial Solutions' information technology (MIS/IS).
Code Description Total Subscribers Percent of

Total

5 Senior Manager 469 14.1%









Table 11. Continued
Code Description Total Subscribers Percent of

Total

6 Manager-Information 1,216 36.7%

Technology/Systems

7 Applications Developer 664 20%

8 In-House User Support 386 11.6%

Representative

9 Internet/Web Designer/Developer 275 8.3%


Other IS or IT Staff


9.3%


The map shows these categories and their respective total counts (Figure 30).

Operations

This map shows the geographic location of subscribers and their distribution in the

United States. The Operations Code is a broad category. This category encompasses

many departments and firms. These codes are primarily formed by seven subcategories

(Figure 31). The following map represents the percent of total count of operations codes

of GeoSpatial Solutions' database by state (Figure 32).

In addition the map shows the operations title codes and each individual category

count. The operations code is divided into eight individual categories.












































Figure 22. GeoSpatial Solutions' combined organizational affiliation codes processed with ArcMap.

























II,.


Figure 23. GeoSpatial Solutions' combined organizational affiliation codes percent by state processed with ArcMap.


Function Codes
Function Code as Percent of Total
S0% -2%
S3% -5%
M 5%-


] I M/iles






















































Other
0045,194
IW us ses 0 800

Figure 24. GeoSpatial Solutions' individual organizational affiliation codes processed with ArcMap.
Figure 24. GeoSpatial Solutions' individual organizational affiliation codes processed with ArcMap.












































Figure 25. GeoSpatial Solutions' combined corporate management codes processed with ArcMap.











































Figure 26. GeoSpatial Solutions' combined corporate management codes percent by state processed with ArcMap.























































Corporate Management e. "
O er, President, CEO
4398
Senior Manager
2524
Director, Manager Sales & Marketing
1456
Other Corporate Management







Figure 27. GeoSpatial Solutions' individual corporate management codes processed with ArcMap.












































Figure 28. GeoSpatial Solutions' combined information technology codes processed with ArcMap.














































Information Technology
Information Technology as Percent of Total
S0% 2%

S5%+ o0 800







Figure 29. GeoSpatial Solutions' combined information technology codes percent by state processed with ArcMap.









These categories and their counts are represented on map (Figure 4-25):

Table 12. GeoS atial Solutions' operations codes.
Code Description Total Percent of

Subscribers Total

M Senior Manager 634 5.7%

N Manager 2,432 22%

O Engineer 1,892 17%

P GIS Technician 1,249 11.2%

Q Geospatial Professionals 2,962 26.6%

R Systems Integrator 236 2.1%

S Technician/Analyst/Administrator 1,453 13.1%

T Other Operations 260 2.3%




GIS Firms

This analysis identifies geographic locations of GIS firms and their submarkets in

the US GeoSpatial Solutions made available a data set of companies that receive their

magazine. Using this 'companies' data set a geographic analysis was done to locate each

company by their corresponding latitude and longitude.

This map shows the general representation of the GeoSpatial Solutions companies

data set and their geographic location. The companies' list was formed of 647 records

(Figure 36). This map shows the submarket for these 647 companies.

The three submarkets were created using the summary from the CACI Coder/Plus

(ESRI) after geocoding the companies list.












































Figure 30. GeoSpatial Solutions' individual information technology codes processed with ArcMap












































Figure 31. GeoSpatial Solutions' combined operations codes processed with ArcMap.











































Figure 32. GeoSpatial Solutions' combined operations codes percent by state processed with ArcMap.












































Figure 33. GeoSpatial Solutions' individual operations codes processed with ArcMap.











The submarkets were categorized using the top 20 metro areas; the primary

submarket ranging from the 4% and above, the secondary submarket from 2% to 3.9%,

and the tertiary submarket from 1.9% and below. Also, figure 33 shows the companies'

counts for each market. The tertiary market has the highest count with 321 companies,

the secondary submarket has a count of 170 companies, and the primary submarket has a

count of 156 companies (Figure 33). The next map illustrates GeoSpatial Solutions'

companies dataset percent of total by state (Figure 34).

To get a better understanding of the influences of GeoSpatial Solutions in each

state a percentage rate of firms by state was analyzed. To analyze this data set further,

data of Establishments (firms) from US Census Bureau from 2000 was acquired. This

new data and the data made available by GeoSpatial Solutions was processed through the

following formula:

(Firms / Establishment) 1000 = Rate of Companies

The analysis was executed using Microsoft Excel and a graph of the rates of

companies by state was created (Table 9). The result was a high concentration of

companies located in Colorado, and a lower concentration in New Mexico, Virginia,

Maryland, and lower concentrations in the other states (Figure 35).



Table 13. GeoSpatial Solutions' percentage of companies by state using data from the
US Census Bureau.
Percentage Rate of Companies by State
Estates GeoSpatial Solutions Companies Establishment Rate of Companies by 1000
Colorado 77 115,893 0.66
New Mexico 10 38,320 0.26
Virginia 36 155,985 0.23
Maryland 23 113,481 0.20
Georgia 34 175,250 0.19











Table 4-10. Continued
Estates GeoSpatial Solutions Companies


Establishment Rate of Companies by 1000


New Hampshire 6 33,146 0.18
California 123 693,987 0.18
Massachusetts 27 154,385 0.17
Alabama 14 91,472 0.15
Utah 7 46,473 0.15
Montana 4 27,140 0.15
Oregon 10 88,292 0.11
District of Columbia 2 17,817 0.11
Washington 15 142,653 0.11
Vermont 2 19,097 0.10
Connecticut 8 83,145 0.10
Texas 40 420,139 0.10
Idaho 3 31,991 0.09
Florida 34 372,132 0.09
Minnesota 11 120,668 0.09
Arizona 9 98,834 0.09
Maine 3 33,721 0.09
Kentucky 7 81,935 0.09
Missouri 9 130,269 0.07
Nebraska 3 44,029 0.07
Wisconsin 8 125,600 0.06
Wyoming 1 15,713 0.06
Pennsylvania 16 267,546 0.06
Ohio 14 246,210 0.06
Mississippi 3 54,368 0.06
Iowa 4 73,436 0.05
Louisiana 5 92,092 0.05
New Jersey 11 205,043 0.05
West Virginia 2 37,800 0.05
Nevada 2 40,211 0.05
Delaware 1 20,478 0.05
South Dakota 1 21,037 0.05
South Carolina 4 86,770 0.05
Kansas 3 67,139 0.04
New York 19 429,397 0.04
North Carolina 8 181,306 0.04
Illinois 11 273,421 0.04
Rhode Island 1 25,139 0.04
Oklahoma 3 76,566 0.04
Tennessee 4 119,362 0.03
Michigan 4 210,508 0.02
Arkansas 1 56,235 0.02
Indiana 2 133,226 0.02
North Dakota 0 18,308 0.00


Source: U.S. Census Bureau


Public Information Office












































Figure 34. GeoSpatial Solutions' US companies data set processed with ArcMap.









































~-I


Figure 35. GeoSpatial Solutions' US companies data set percent by state processed with ArcMap.


-^I v iies


























































Metropolitan area Companies -
tertiary
321 companies
secondary
70 companies
primary
156 companies
I US States 0 800
pe of cs by s u d f t U C Miles



Figure 36. GeoSpatial Solutions' percentage of companies by state using data from the US Census Bureau.















GeoSoatial Solutions Percent Companies by State


0.70


0.60


0.50

o
S0.40


2 0.30


0.20

0.10



0.00
SII IIIIIII III III(4,, 1111 ......





States

Figure 37. GeoSpatial Solutions' percentage rate of companies by state using data from the US Census Bureau.














CHAPTER 5
SOCIAL-ECONOMIC CORRELATIONS

This analysis identifies social-economic (LSP) influences of sub markets with a

high concentration of GIS for their location in the US.

The social-economic correlation directly and/or indirectly affects the location of

GIS industries in a specific area, city, or state.

High Concentration Regions

The market analysis identifies geographic location areas with high concentration

regions of GIS. A further analysis of GeoSpatial Solutions' subscribers was performed to

better understand and graphically see which metropolitan areas have high concentrations

of subscribers in the United States.

To analyze GeoSpatial Solutions' market more in depth, the top metropolitan areas

were created. Using the summary created by CACI Coder/Plus (ESRI), three sub markets

were selected from the Top 20 Metropolitan Statistical Areas (Table 14). Then, based on

a percentage count, a map of top metropolitan areas was created.



Table 14. Geocoding match level summary of top 20 metropolitan areas by percentage
of subscribers from CACI Coder/Plus.
Record Count Percent of Total Subscribers

Top 20 Metropolitan Areas
Washington, DC (8840) 1,372 5.3%

Los Angeles-L.Beach (4480) 657 2.5%
Boston-Wor-Law-Lw-Br (1123) 576 2.2%
Chicago, IL (1600) 566 2.2%










Table 5-1. Continued
Top 20 Metropolitan Areas

New York, NY (5600) 486 1.9%

Atlanta, GA (0520) 421 1.6%

Denver, CO (2080) 421 1.6%

San Diego, CA (7320) 387 1.5%

Houston, TX (3360) 383 1.5%

Philadelphia, PA-NJ (6160) 359 1.4%

Minneapolis-St. Paul (5120) 326 1.3%

Seattle-Bellev-Ev'tt (7600) 321 1.2%

Dallas, TX (1920) 304 1.2%

Orange County, CA (5945) 298 1.1%

Baltimore, MD (0720) 295 1.1%

St. Louis, MO-IL (7040) 279 1.1%

Oakland, CA (5775) 259 1.0%

Phoenix-Mesa, AZ (6200) 255 1.0%

Sacramento, CA (6920) 255 1.0%

Riverside-San Bern. (6780) 247 0.9%

Other MAs 13,219 50.8%

Records not in an MA 4,338 16.7%




These submarkets were divided into primary, secondary, and tertiary markets based

on the percentage count of subscribers in each metropolitan area (Table 15).

This map also shows the three sub markets and their specific counts for each

metropolitan area (Figure 38). These three sub markets were divided according to their

percentage levels. The primary market is formed by subscriber count percentages of 4%

or higher. The secondary sub market is made up of percentages between 2% and 3.9% of

subscribers. The tertiary submarket is comprised of percentages between 1.1% and 1.9%

of total subscribers. To create this map from the subscribers' data set, the MSA was












































Figure 38. GeoSpatial Solutions' top metropolitan areas by subscribers processed with ArcMap.









selected. Metropolitan Statistical Area codes were produced using CACI Coder/Plus

(ESRI) produced.

The primary sub market is formed by the MSA code 8840, which corresponds with

the Washington, DC area. The secondary sub market is formed by the MSA codes: 4480,

the Los Angeles-L Beach area; 1123, the Boston-Wor-Law-Lw-Br area; 1600, and the

Chicago, IL area. The tertiary sub market is formed by the MSA codes: 5600, the New

York area; 0520, the Atlanta area; 2080, the Denver area; 7320, the San Diego area;

3360, the Houston area; 6160, the Philadelphia, PA-NJ area; 5120, the Minneapolis-St.

Paul area; 7600, the Seattle-Bellev-Ev'tt area; 1920, the Dallas area; 5945, the Orange

County area; 0720, the Baltimore, MD area; and 7040, the St. Lois, MO-IL area (Figure

39).



Table 15. Identification of metropolitan areas by count of subscribers from CACI
Coder/Plus
Metro Areas Subscribers Count
First_STATE, Last_STATE, MSA_CODE
DC, WV, 8840
First_STATE, Last_STATE, Count_MSA_CODE
CA, CA, 657
MA, NH, 575
IL, IL, 566
First_STATE, Last_STATE, MSA_CODE
MD, MD, 0720
IL, MO, 7040
CA, CA, 6920
CA, CA, 6780
AZ, AZ, 6200
CA, CA, 5945
0 CA, CA, 5775

































































MefroAreal Subicdrit Co unt
First STATE,LastSTATE,MSA_CODE
DC.VIN.8840
FirstSTATE, LastSTATE, Count_MA_CODE
CA CA6 57
MAINH,575
IL. IL,566
First_STATE, LastSTATE, MSA_CODE
I MD.MD.0720
IL, M0,7040
e CACA 6920
CACA 780
A AZ., 6200
CA CA 5945
CA CA 5775
C. 77. 0 800
I S Miles




Figure 39. GeoSpatial Solutions' top metropolitan areas by count processed with ArcMap.









Also, a geographic representation of the data set of GeoSpatial Solutions

companies was created to show their geographic location in the United States.

To take the analysis of the metropolitan areas one step further, the primary and

secondary MSAs (Metropolitan Statistical Areas) were analyzed individually, and maps

for each of the high concentration areas of the metropolitan areas were also included.

Primary Sub Market

Figure 40 shows the metropolitan areas of Maryland, Virginia, and Washington

DC. This is the strongest sub market in the US for GeoSpatial Solutions subscribers.

There is a concentration of subscribers in the Washington, DC area; this could be because

of the uses of GIS in the government environment. Also, it may be due to an increase in

companies and subscribers in this area because of the recent budget allocations granted to

the home land defense agency.

Secondary Sub Market

Figure 41 shows the secondary metropolitan area, Los Angeles, which is a sub

market area containing a high concentration of subscribers in the US. This might be

because Los Angeles is a high technology industry, which brings a high market for GIS

products. This map shows the secondary sub market that locates in the Massachusetts and

New Hampshire area. The highest concentration locates in the Suffolk and Middlesex

areas (Figure 42). This map shows the secondary sub market that locates in the Illinois

area. The highest concentration is in Cook County (Figure 43).

The tertiary sub market was also created using the MSA; however the

representation of the first two markets shows a more important characteristic for this

analysis. Further analysis of the tertiary sub market can show new and interesting sub












































Figure 40. GeoSpatial Solutions' high concentration areas in Maryland/Virginia processed with ArcMap.











































Figure 41. GeoSpatial Solutions' high concentration areas in California processed with ArcMap.









































S MA, Middlesex. M Suffolk





N MA, Worcester "


Metro Areas Massauitts, Now Hampshire '
Primary matro area subrIbem '
-Isuti MA, Norfolk *
Secondary
"1 Sut \er\
Trary *

US Counties MA, Bristol olvou
[r2 al usot i c r on a i M s Miles



Figure 42. GeoSpatial Solutions' high concentration areas in Massachusetts/New Hampshire processed with ArcMap.











































Figure 43. GeoSpatial Solutions' high concentration areas in Illinois processed with ArcMap.









markets where GeoSpatial Solutions could increase their subscriptions and market area.

So further analysis may be an increasing advantage and an important judgment (category

4 of geographic reasoning) for the company.

Education

The following analysis documents the influences of education to attract the GIS

market to the region. To do this analysis the map for business code University/College,

code 35, was overlain with the GIS business maps. This overlay creates a new layer or

map of education and this shows the correlations between the GeoSpatial Solutions

companies list and the University/Education codes.

Figure 44 shows the total education market in the United States. The data set for

this map was extracted from the subscribers list using the organizational affiliate code for

University/College, code 35. Using this data a new layer was created which shows the

geographic location of universities and colleges in the US.

The result of these layers were buffered bufferingg creates a circular area selected

within a specified radius of the University/College code data set. Four buffers at varying

mile radiuses were formed. These four buffers were established for 10, 12, 15, and 18

miles and applied to the subscriber data to see its characteristics. These buffers show the

influence of the educational sector to attract the GIS market to its area. These buffers, of

10, 12, 15, and 18 miles, were selected in order to find the business geography standard

of 80% (where 80% of the values locate near a target).

Buffer at 10 Miles

Figure 5-8 shows the geographic location of all the universities and colleges, from

GeoSpatial Solutions' data code 35, in the US. These locations where buffered to a 10

miles radius. The buffer and the locations were added to the same layer.










































'I L







Education Market
Education Total Market
US States 0 800
Figure 44. GeoSp ma t p d wh Miles



Figure 44. GeoSpatial Solutions' education business code US market processed with ArcMap.




































00


A E









Education Market
Education Total Market
Education 10 miles Buffer
US States 0 800
It a e Miles



Figure 45. GeoSpatial Solutions' US education market with a buffer at 10 miles processed with ArcMap.









Buffer at 12 Miles

Figure 46 shows all the market for the universities and colleges, from GeoSpatial

Solutions' data code 35, with a geographic location within the 12 miles radius. Then the

two layers were overlapped to shows the educational market and the correspondent 12

miles buffer.

Buffer at 15 Miles

Figure 47 shows the geographic location of all the universities and college in the

US. Also, it shows a buffer of 15 miles radius from each location.

Buffer at 18 Miles

Figure 48 shows the geographic location of universities and colleges based on their

latitude and longitude. The layer of this location was buffered to an 18 miles radius.

Market Attraction

Also, to analyze the influences of the education from the GeoSpatial Solutions

companies' data set, the company map was used to identify the location of the companies

inside the four buffers and indicate the percentages of companies that locate near a

university or college for each area.

This map represents the 647 company locations provided by GeoSpatial Solutions

in the US (Figure 49). The company and the buffer maps were overlapped to form new

data and layers. These new layers were created to show the Education Market Attraction

for GIS companies to locate near universities and colleges. Table 16 represents the

percentage of total companies from the GIS market that fit the 10, 12, 15, and 18 miles

buffers from an educational institution.





































00











Education Market
Education Total Market
SEducation 12 miles Buffer
US States 0 800
S4 o o o U o m w a b a 1 m oMiles


Figure 46. GeoSpatial Solutions' US education market with a buffer at 12 miles processed with ArcMap






































o- 00











Education Market
Education Total Market
Education 15 miles Buffer
US States 0 800
i a Miles


Figure 47. GeoSpatial Solutions' US educationn market with a buffer at 15 miles processed with ArcMap.



















































Education Market
S Education Total Market
Education 18 miles Buffer
US States 0 800
1i mie wMiles



Figure 48. GeoSpatial Solutions' US education market with a buffer at 18 miles processed with ArcMap.
















































Companies Market
Companies
7 US States 0 800
ie 4 G il S i U c i d p i MMiles


Figure 49. GeoSpatial Solutions' US companies dataset processed with ArcMap.