Prepared for the

Appalachian Regional Commission

by

Edward Feser

Harvey Goldstein

Henry Renski

Catherine Renault

Office of Economic Development

University of North Carolina at Chapel Hill

August 2002

Regional Technology Assets and Opportunities:

The Geographic Clustering of High-Tech Industry,

Science and Innovation in Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia i

EXECUTIVE SUMMARY

Regional Technology Assets and Opportunities:

The Geographic Clustering of High-Tech Industry,

Science and Innovation in Appalachia

High-tech activities cluster and clustering spurs competitiveness. That is the message of a rapidly

growing body of research showing that the geographic co-location of businesses, universities, colleges,

and labs often yields powerful clusters of technology-related activity that continue to expand through

initial market leadership and economies of scale. Well-known examples are information technology

and biotechnology California’s Silicon Valley and Boston’s Route 128, software and aircraft in Seattle,

and electronics and pharmaceuticals in North Carolina’s Research Triangle. Such clusters have contributed to substantial increases in their regions’ prosperity while also supplying the innovations that

drive national economic growth.

This study constitutes a systematic location analysis of the technology assets of Appalachia. Specifically, the report identifies and documents sub-regional concentrations of technology-related employment, R&D, and applied innovation within and immediately adjacent to the 406-county service

area of the Appalachian Regional Commission. By assembling and analyzing an extensive set of data at

high levels of functional and spatial detail, the study reveals localized technology strengths that might

be nurtured through focused economic development policy.

The study found 100 technology clusters — joint spatial concentrations of high-tech employment

and innovative activity — within and adjacent to the ARC region. The clusters vary significantly in

size, depth, and overall competitive strength. They span eight general technology areas: chemicals and

plastics; motor vehicles and related; industrial machinery; information technology and instruments;

aerospace; communications services and software; and pharmaceuticals and medical technologies.

Chemicals and plastics, industrial machinery, and motor vehicles and related industries account for a

majority of the technology clusters. Some of the detailed findings in the report include:
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia ii

 Overall, Appalachia’s technology sector is comparatively small but expanding.

There were roughly 1.07 million workers employed in the region’s high-tech industries in 1998, up from 959,000 in 1989, an increase of 11.2 percent. The rate of

net technology employment growth between 1989 and 1998 was about two-thirds

of the overall private sector growth rate. Most of the high tech gains occurred in

sectors classified as “moderately technology-intensive,” such as chemicals, electronic components, transportation equipment, instruments, and hospitals and healthrelated labs.

 In terms of a diversity of high-tech industry employment, there are five leading

metropolitan areas in Appalachia: Binghamton, Greenville-Spartanburg, Huntsville, Johnson City, and Pittsburgh. We found evidence of high-tech concentrations in four or more high-tech sectors in at least parts of each of those cities (six

and seven sectors in the cases of Greenville-Spartanburg and Huntsville, respectively). A second group of cities that are also home to multiple sectoral concentrations include Asheville, Decatur, Erie, Knoxville, and State College.

 Spatial employment concentrations in industrial machinery, chemicals/plastics, and

motor vehicles tend to be larger in geographic extent (comprised of larger multicounty areas) than the other technology industries. That is, their presence in (or

sometimes extension into) rural counties is more extensive than sectors such as

information technology, communication services, and software.

 Within the ARC region proper, there is clearly an orientation of high-tech activity

to the northern and southern thirds of the region, with activity in the central region

very sparse in several key technology sectors. Chemicals and plastics industries

exhibit the strongest presence in the central third of the ARC area, whether measured by value chain employment or occupational employment.

 Appalachian metro areas have a significantly lower complement of scientists, engineers, and technicians than the U.S. as a whole. Scientists and engineers are

somewhat better represented in the MSAs that line the region’s borders. Washington, DC accounts for a significant share of the total scientists and engineers employed in the 62 metro areas included in the study. Excluding the Washington, DC

MSA finds the southern third of the extended region the most “science and engineering-intensive” based on occupational employment indicators.

 Based on national ratings of faculty quality, there are six major nodes of highest

competitive research strength in the universities in Appalachia (either within or

adjacent to the ARC region): Cornell (Ithaca, NY), Carnegie-Mellon (Pittsburgh,

PA), Georgia Tech and Emory University (Atlanta, GA), Penn State (State College,

PA), and Virginia Tech (Blacksburg, VA).

 According to faculty quality rankings, the greatest competitive strengths among

Appalachian research universities as a group are oriented toward the engineering

and physical sciences. According to national R&D funding rankings, some Appalachian universities are also very strong in the life sciences.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia iii

 A number of Appalachian universities boast research programs that are rising

steadily in the national rankings (based on R&D funding and graduate student enrollments). The majority of such “emergent programs” are at Carnegie-Mellon,

Georgia Tech, Ohio State, Penn State, the University of Kentucky, Virginia Tech,

West Virginia University, and Mississippi State.

 Small Business Innovation Research (SBIR), Small Business Technology Transfer

(STTR), and Advanced Technology Program (ATP) award winners are concentrated

in a relatively small number of places, namely Huntsville, Blacksburg, Pittsburgh,

State College, and Ithaca, with smaller concentrations in Birmingham and Knoxville/Oak Ridge. The nature of the SBIR/STTR/ATP programs favors locations near

universities and government labs.

 Industrial machinery is easily the most common technology focus among the some

220 SBIR/STTR/ATP awards in fiscal year 2000. That may reflect the dominance of

the region’s traditional industry sectors (textiles, apparel, furniture, and metals).

 There are a great many state-funded technology assistance, transfer, and modernization programs and agencies in the ARC region. Comparatively few, however,

are focused on the two technology areas that are projected to drive significant

growth in the next decade: information technology and biotechnology.

 Surprisingly, given the region’s industry mix, Appalachian four-year universities

and colleges grant proportionately fewer degrees in industrial engineering and related sciences than universities nationwide. Indeed, based on degree completions

in 1997/98, Appalachian universities and colleges grant proportionately more degrees in basic medical science, environmental engineering and controls, mathematics, materials engineering and science, and biochemistry and biomedical engineering than national averages would predict.

 The share of annual degrees awarded in the computer and communications sciences by two-year colleges and institutes in Appalachia is substantially below the

national average. That may reflect the comparatively limited job opportunities in

IT-related industries in the region (a problem of labor demand) or an inadequate

training network for an emerging industry (a problem of labor supply).

 Two- and four-year higher education institutions with an emphasis in technology

are comparatively few in central Appalachia (Tennessee, Kentucky, West Virginia).

 The spatial distribution of the 100 technology clusters in Appalachia is highly

uneven. Nearly half (45 in total) are located in the northern third of the region

(New York, Pennsylvania, and northern Ohio). Only nineteen clusters were identified for central Appalachia (an area that includes southern Ohio, West Virginia,

Virginia, and Kentucky), with Cincinnati and Washington, DC accounting for nine

of those nineteen. In the southern third of the region, Atlanta, GreenvilleSpartanburg, and Huntsville account for sixteen of 29 clusters identified.

 The uneven geography of the clusters in the region varies substantially by technology sector. The chemicals/plastics and information technology/instruments clus-
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia iv

ters are relatively evenly distributed amongst the northern, central, and southern

thirds of the region. Industrial machinery, on the other hand, is nearly exclusively

a northern and southern strength.

 Just over half of the technology clusters in the region are located on the periphery

and are anchored in core metropolitan centers outside the region (such as Cincinnati, Atlanta, and Washington, DC). That means that the ARC region’s current hightech prospects are heavily dependent on spillover effects from neighboring cities

and metropolitan areas. Unfortunately, those spillovers are neither certain nor necessarily positive.

The analysis and findings in this report have three major implications for state and local officials

concerned with economic development in Appalachia. First, the technology clusters are potential targets for focused entrepreneurship and recruitment strategies. Each sub-regional technology cluster

highlighted in this report can be subjected to further detailed analysis to identify linked end-market or

supplier sectors that represent attractive growth prospects, or related industries that offer higher wages.

Those prospects can then become the focus of comprehensive development strategies designed to nurture their growth.

Second, the report findings can be used to guide state investments in “centers of excellence” in

the research universities, expanded specialized education and training programs in the region’s teaching universities and community colleges, and in technology transfer and industrial extension programs.

Some of the 100 technology clusters are characterized by a very strong base of science, innovation, and

training. However, most are not, especially within the ARC region proper. While innovation and R&D

strengths are in evidence in the case of all technology clusters, the clusters vary greatly in the depth and

diversity of that strength. Moreover, some clusters are better served than others by the region’s university and community college education and training system.

Third, a common step in many states’ efforts to develop and expand technology clusters is the

establishment of an industry association or other private sector entity charged with documenting and

championing specific clusters’ interests in the policy arena. Such organizations also often provide a

venue for collaboration and joint problem solving among cluster firms (networking), thereby increasing opportunities for productivity-enhancing spillovers that are a critical part of firms’ competitiveness. States and regions should view the clusters identified in this report as potential candidates for

such “cluster organizing” and networking efforts.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia v

Contents

Executive Summary ............................................................................................................................. i

Tables and Figures.............................................................................................................................. vi

1 Introduction ............................................................................................................................ 1

1.1 The High Technology Antidote ......................................................................................... 2

1.2 Appalachia’s Technology Base .......................................................................................... 4

1.3 Study Objectives................................................................................................................ 6

1.4 Conceptual Framework and Report Organization ............................................................. 7

2 Appalachia’s High-Tech Industrial Base ............................................................................. 9

2.1 Technology-Intensive Industry Employment .................................................................. 10

2.2 High-Tech Value-Chains.................................................................................................. 14

2.3 Scientists, Engineers and Technicians............................................................................. 27

2.4 Summary .......................................................................................................................... 32

3 Appalachia’s Knowledge Infrastructure ........................................................................... 34

3.1 Appalachia’s Science and Innovation Assets .................................................................. 35

3.1.1 R&D Performers.................................................................................................. 35

3.1.2 State Science and Technology Programs............................................................ 58

3.2 Appalachia’s Higher Education Infrastructure ................................................................ 59

3.3 Summary .......................................................................................................................... 67

4 Technology Clusters in the ARC Region ............................................................................ 69

4.1 Identifying Technology Clusters ..................................................................................... 69

4.2 Findings ........................................................................................................................... 81

4.3 Policy Implications and Guides ....................................................................................... 85

4.3.1 Industrial Targeting............................................................................................. 87

4.3.2 Knowledge Infrastructure ................................................................................... 87

4.3.3 Leveraging Spillovers and Agglomeration Economies...................................... 89

4.4 Further Research .............................................................................................................. 89

References .......................................................................................................................................... 91

Methods Appendix: Measures of Concentration and Spatial Association .................................. 94

Appendix Tables .............................................................................................................................. 101
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia vi

Tables and Figures

Tables

1. Technology industry employment and wages, 1989, 1998 .................................................................... 4

2. Study measurement of high-tech industrial activity ..................................................................... 10

3. Technology-intensive value-chain employment and wages, 1989, 1998........................................... 17

4. Estimated employment: Scientists, engineers and technicians, 1999 ............................................... 28

5. Employment shares: Scientists, engineers and technicians, 1999 ..................................................... 29

6. Location quotients: Scientists, engineers and technicians, 1999 ....................................................... 30

7. Study measurement of innovative activity ................................................................................... 35

8. Rankings of faculty quality: Appalachian research universities, 1995 ............................................. 38

9. Rankings of R&D funding: Appalachian research universities, 1999 ............................................... 39

10. Emergent strengths in Appalachian universities, 1991–1999 ............................................................. 40

11. Graduate student enrollment rankings: Appalachian research universities, 1999 .......................... 41

12. Patents issued and gross license income, 1999 ..................................................................................... 42

13. Appalachian non-university research organizations..................................................................... 43

14. Utility patent grants over period 1990–1999, U.S. and ARC region .............................................. 44

15. Estimated degree completions, 1997/98, ARC 4-year colleges and universities........................... 61

16. Estimated degree completions, 1997/98, ARC 2-year colleges and institutes ............................... 62

17. Technology area concordances ..................................................................................................... 70

18. University R&D strengths by technology area.............................................................................. 71

19. Technology clusters in Appalachia ............................................................................................... 72

Figures

1. Recent employment growth, technology-intensive industry, 1989–98 ................................................ 5

2. Technology-intensive sector mix, 1998.................................................................................................... 6

3. Study conceptual framework and report organization.................................................................... 7

4. Study area, Appalachia and border region ................................................................................... 12

5. Spatial concentration: Very tech-intensive industries, 1998 ............................................................... 14

6. Spatial concentration: Moderately tech-intensive industries, 1998................................................... 15
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia vii

7. Spatial concentration: Somewhat tech-intensive industries, 1998 .................................................... 16

8. Percent private sector employment by value-chain, 1998 ................................................................... 18

9. Spatial concentration: Chemicals and plastics value-chain ......................................................... 19

10. Spatial concentration: Motor vehicles value-chain ...................................................................... 20

11. Spatial concentration: Industrial machinery value-chain ............................................................. 21

12. Spatial concentration: Information technology and instruments value-chain .............................. 22

13. Spatial concentration: Communications services and software value-chain ............................... 23

14. Spatial concentration: Aerospace value-chain ............................................................................. 24

15. Spatial concentration: Household appliances value-chain ........................................................... 25

16. Spatial concentration: Pharmaceuticals and medical technologies value-chain .......................... 26

17. Scientists, engineers and technicians by metro area: Northern Appalachia, 1999 ......................... 31

18. Scientists, engineers and technicians by metro area: Central Appalachia, 1999 ............................ 31

19. Scientists, engineers and technicians by metro area: Southern Appalachia, 1999 ......................... 32

20. Major research universities within and adjacent to ARC boundary ............................................. 36

21. Spatial concentration: Industrial machinery patent grants, 1990–1999............................................. 46

22. Spatial concentration: Chemicals and plastics patent grants, 1990–1999 ......................................... 47

23. Spatial concentration: Metals and metalworking patent grants, 1990–1999 .................................... 48

24. Spatial concentration: Information technology patent grants, 1990–1999 ....................................... 50

25. Spatial concentration: Pharmaceuticals patent grants, 1990–1999 .................................................... 51

26. Spatial concentration: Aerospace patent grants, 1990–1999............................................................... 52

27. Spatial concentration: Scientific instruments patent grants, 1990–1999 .......................................... 53

28. Spatial concentration: Household appliances patent grants, 1990–1999 .......................................... 54

29. Spatial concentration: Motor vehicles and related patent grants, 1990–1999 .................................. 55

30. Spatial concentration: Patent grants in all other categories, 1990–1999 ........................................... 56

31. SBIR/STTR/ATP award winners in the ARC region, FY 2000 ............................................................. 57

32. Total degree completions by county, four-year universities and colleges, 1997/98 ........................ 63

33. Total degree completions by county, two-year colleges and institutes, 1997/98 ............................. 64

34. Technology intensity, four-year universities and colleges, 1997/98 .................................................. 65

35. Technology intensity, two-year colleges and institutes, 1997/98 ....................................................... 66

36. Technology clusters: Chemicals and plastics ............................................................................... 76

37. Technology clusters: Motor vehicles and related ......................................................................... 77

38. Technology clusters: Industrial machinery ................................................................................... 78

39. Technology clusters: Information technology and instruments ................................................... 79

40. Technology clusters: Communications services and software ..................................................... 80

41. Technology clusters: Aerospace ................................................................................................... 82

42. Technology clusters: Household appliances................................................................................. 83

43. Technology clusters: Pharmaceuticals and medical technologies................................................ 84
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia viii

Appendix Tables

1. SIC-Technology classification .................................................................................................... 101

2. Metropolitan areas within and bordering Appalachia ................................................................ 102

3. Spatial concentration of technology-intensive employment in ARC MSAs ............................... 103

4. Technology value-chain classification ....................................................................................... 105

5. Spatial concentration of value-chain employment in ARC MSAs .............................................. 107

6. Science and technology occupational classification .................................................................. 110

7. Location quotients: Scientists and engineers, 1999 ........................................................................... 111

8. Location quotients: Technicians, 1999 ................................................................................................. 113

9. Concordance: Patents to technology groups............................................................................... 115

10. Spatial concentration of patenting activity (1990–1999) ................................................................... 116

11. SBIR/STTR/ATP award winners in ARC region, FY 2000 .................................................................. 118

12. State-funded technology agencies and programs in ARC region ............................................... 122

13. Science and engineering CIP codes ............................................................................................ 125

14. Selected excluded CIP codes ...................................................................................................... 129
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 1

1 Introduction

Over the last 40 years, economic development progress has been substantial in many parts of Appalachia, the 406-county region that is the focus of the Appalachian Regional Commission (ARC). A recent

study shows that the number of ARC counties identified as distressed declined from 214 to 106 between

1960 and 1990 (Wood and Bischak 1999).1 That study attributes those gains to the growth of the manufacturing sector in predominantly southern rural counties, while also noting that they have come partly

at the expense of traditional northern manufacturing centers. The study also noted the significance of

positive spillovers from high growth metropolitan areas that border the Appalachian region, particularly in the South (with Atlanta as the premier example).

At the same time, Wood and Bischak report that about one-quarter of ARC counties that were

distressed four decades ago remain distressed today. Furthermore, the prospects for the continued economic progress of Appalachia are uncertain, even in many of its currently non-distressed sub-regions.

Much of Appalachia remains heavily dependent on unstable and cost-sensitive manufacturing, agriculture, and minerals extraction activity. Just as inexpensive labor and a more permissive regulatory environment initially brought manufacturing to southern Appalachia, foreign locations are now using similar advantages to lure those jobs away. As U.S.-based businesses substitute capital for labor to minimize costs, they are displacing workers, spurring out-migration from smaller communities with

few alternative job opportunities, and increasing demands on workforce education and retraining

programs.2

1. See also Feser and Sweeney (2002) who utilize an alternative methodology to compare 25–30 year trends in

economic distress for all commuter zones in the contiguous U.S. Using distress thresholds based on long run

trends, they identify eight Appalachian commuter zones as unemployment distressed in 1999 (the share of

Appalachian population in those zones was 1.2 percent). Forty-two zones, accounting for 12.9 percent of

Appalachian residents, were found to be income-distressed in the late 1990s.

2. Labor-saving technologies also continue to increase productivity in agriculture while reducing farm employment.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 2

1.1 The High Technology Antidote

A growing number of state and local policymakers believe that a strong base of science and technology

is a necessary foundation for sustained prosperity.3

 The view rests on three major arguments. First is

the notion that with increasingly open international markets, businesses based in the U.S. must seek

competitive advantage in America’s knowledge infrastructure, including its world-leading private and

public R&D institutions, educated workforce, tradition of risk-taking and entrepreneurship, advanced

physical infrastructure, and stable and transparent social and political institutions. Concerns over issues like the “digital divide,” equal access to education, and worsening income inequality are heightened by fears that two sectors are coming to dominate long-term domestic employment growth prospects: high skilled technology-intensive activities that are dependent on advanced knowledge infrastructure and low-skilled basic consumer services that serve immediate local market needs. While the

prospect of a “two-tiered economy” remains hypothetical rather than an empirically-verified fact, it has

gained significant traction in policy debates at the state and local levels.

The second argument for a close link between technology and regional economic performance is

based on studies of recent sectoral growth trends. For example, in an analysis predating the 2001 recession, Hecker (1999) projected that high-tech and related employment would grow twice as fast as employment in the rest of the economy over the 1996 to 2006 period. Another study finds that the global

market for the products of four research-intensive industries — aerospace, computers and office machinery, electronics and communications, and pharmaceuticals — expanded over twice as fast as the

markets for other manufactured goods over the 1980 to 1995 period (Rausch 1998). Certainly, not all

industries cited by various studies as “technology-intensive” are posting employment or output gains.

Indeed, some tech sectors faced significant declines during the 1990s. But even with uncertainty over

the recent recession as well as how best to define the technology sector (e.g., see Pollak 1999 and Wirtz

2001), most studies show that gains in technology-related employment have been strong relative to

other industries over the last decade. By most measures, technology sectors also pay considerably

higher wages than more traditional industries, particularly in the manufacturing sector.

The third argument for technology as a key to regional economic development is that technologyrelated activity must necessarily cluster in specific regions because knowledge spillovers are localized

(Glaeser 2000). Knowledge spillovers — the primary engine in the most recent theories of long-run

3. A recent statement of the importance of high technology for cities and regions that has been highly influential

in policy circles is Atkinson and Court (1998). The support for technology policy often is based as much on a

hunch than a research consensus. As one government report claims OTP (2000, p. 1-1), “the relationship

between measures of economic prosperity and science and technology capacity is intuitive. Such relationships have lead to public policies to support economic development through science and technology

investments.”
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 3

economic growth — are the ability of economic agents to utilize a new technology or innovation without fully compensating its original source or owner (Grossman and Helpman 1991). Innovations initially occur in companies, universities, and laboratories located in specific places. The subsequent

spread (or diffusion) of such innovations, as well as the spillovers they generate, may occur more

readily among economic actors located in close proximity, either because the innovation is tacit in

nature or because its successful utilization requires an element of hands-on learning-by-doing. Increasing returns to innovation, coupled with a localized diffusion effect, imply that technology-oriented

activity and R&D are likely to concentrate geographically. Technology businesses locate near other

high tech companies and R&D performers in order to share in the spillovers, further enhancing the

attractiveness of the growing cluster for still more high tech enterprises. The cluster expands through a

process of cumulative advance.4

Indeed, a growing body of empirical work indicates that a combination of geographically colocated private sector producers of R&D, related manufacturing and services industries, linked or related suppliers and producer services providers, leading research universities and teaching institutions,

and government sponsored labs and technology programs can combine to create powerful clusters of

technology-related activity that continue to expand through initial market leadership (often called “firstmover effects”) and economies of scale (Porter 1990; Saxenian 1994; Porter 1998; Porter 2000; den

Hertog, Bergman et al. 2001). Well-known examples are California’s Silicon Valley and Boston’s Route

128 (in information technology and biotechnology), greater Seattle (in software and aircraft), and North

Carolina’s Research Triangle Park (in electronics, computers, and pharmaceuticals/biotechnology).

4. It has long been understood that technological change is the leading contributor to long-run economic growth

(Nelson 1996). But prior to the mid-1980s, growth economists essentially viewed technological change as

something that dropped from the sky. That is, the neoclassical perspective as laid out initially by Solow (1956,

1957) viewed technology as exogenous: not a direct function of the everyday process of capital accumulation,

but rather a separate unexplained dynamic that confers productivity gains to capital, thereby ensuring sustained investment and perpetual growth in the long-run. Sustained long-run growth is, of course, what is

observed in industrialized countries. The attractiveness of the exogenous technological change assumption,

despite its limited face validity, must be understood in the context of growth economists’ desire to retain the

assumption of competitive markets (see Krugman 1995 for a good discussion).

The new growth theory, following advances by Romer (1986, 1990) and Lucas (1988), brings technological

change into the model (i.e., makes it endogenous) through the mechanism of increasing returns. As a form of

knowledge, a new technology is both nonrivalrous (the use of the technology by one economic agent does not

preclude its use by another) and nonexcludable (the prevention of the unauthorized use of the technology by

other economic agents is difficult). Those public good features are what give rise to knowledge spillovers.

Resources are utilized to create new knowledge, some part of which “spills over to the research community,

and thereby facilitates the creation of still more knowledge” (Grossman and Helpman 1991, p. 17). Because

spillovers imply that the process of invention exhibits increasing returns to scale, returns to new productivityenhancing technologies and ideas are always sufficient to maintain the incentive to invest in still more innovation. The result is long-run perpetual growth. Cortright (2001) provides an introductory treatment of new

growth theory.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 4

Such clusters have contributed to substantial increases in their regions’ prosperity while also supplying

the innovations that drive long-run national economic growth.

1.2 Appalachia’s Technology Base

Appalachia’s technology sector is comparatively small but expanding. By our count, there were roughly

1.07 million workers employed in the region’s high-tech industries in 1998, up from 959,000 in 1989, an

increase of 11.2 percent (see Table 1 and Figure 1).

5

 The rate of net technology employment growth

between 1989 and 1998 was about two-thirds of the overall private sector growth rate. Most of the high

tech gains occurred in sectors classified as “moderately technology-intensive,” such as chemicals, electronic components, transportation equipment, instruments, and hospitals and health-related labs. The

typical worker in Appalachia’s technology sector earned $35,204 in 1998, 135 percent of the region’s

average private sector wage (of $26,041). With 12.6 percent of its private sector workforce employed in

high tech industries in 1998, compared to a 14.2 percent nationwide, Appalachia is less technologyintensive than the U.S. as a whole.

5. The data in Table 1 and Figures 1 and 2 are based on a classification of technology sectors developed by the

North Carolina Employment Security Commission, which based its scheme on U.S. Bureau of Labor Statistics and National Science Foundation studies of the share of science and engineering workers by sector. The

full classification is reported in Appendix Table 1. The source data are confidential U.S. BLS employment

statistics (described in the Methods Appendix). Note that the U.S. figures exclude data for Alaska, Hawaii,

and Wyoming, states that did not grant us permission to use their confidential employment data.

United States*

Sectors

1989

(000's)

1998

(000's)

% private 

sector '98

% Change 

'89-'98

1998

(Mil $)

% private 

sector '98

Average 

wage $

Very tech-intensive 4,105 4,687 4.5 14.2 268,592 8.1 57,311 

Moderately tech-intensive 6,638 7,575 7.3 14.1 286,022 8.6 37,757 

Somewhat tech-intensive 2,484 2,497 2.4 0.5 102,387 3.1 41,001 

All tech sectors 13,226 14,759 14.2 11.6 657,001 19.8 44,515 

Total private sector 96,029 104,258 100.0 8.6 3,310,187 100.0 31,750 

Appalachia

Sectors

1989

(000's)

1998

(000's)

% private 

sector '98

% Change 

'89-'98

1998

(Mil $)

% private 

sector '98

Average 

wage $

Very tech-intensive 190 206 2.4 8.4 8,995 4.1 43,628 

Moderately tech-intensive 525 614 7.3 17.0 19,761 9.0 32,164 

Somewhat tech-intensive 243 246 2.9 0.9 8,777 4.0 35,738 

All tech sectors 959 1,066 12.6 11.2 37,534 17.1 35,204 

Total private sector 7,292 8,443 100.0 15.8 219,867 100.0 26,041 

Source: U.S. Bureau of Labor Statistics, ES-202 files. *U.S. figures exclude Alaska, Hawaii, and Wyoming. Appalachia includes only the 

406-county ARC region.

Employment

Employment

Payroll

Payroll

Table 1

Technology industry employment and wages, 1989, 1998
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 5

While U.S. technology employment growth only outpaced Appalachia’s by a slight margin over

the 1989 to 1998 period, many of the national gains occurred in industries classified as “very technology

intensive,” such as pharmaceuticals, computers, aerospace, software, and research and testing organizations. In 1998, those industries’ paid average annual wages that were 181 percent of the U.S. private

sector average. Overall in 1998, the national average “technology wage premium” — the ratio of wages

in the technology sector to the private sector average wage — was six points higher than Appalachia’s

(at 141 percent), reflecting an Appalachian technology sector that is modestly skewed toward the less

technology-intensive of the technology industries (see Figure 2).

Table 1 reports only private sector, non-educational employment in technology-related manufacturing and non-manufacturing industries.6

 Other components of Appalachia’s science and technology

base include its major research universities (eleven in total), network of teaching universities and community colleges (granting over 35,000 degrees in fifteen major science and engineering fields in 1997/

98), and non-university laboratories (e.g., Redstone Arsenal in Alabama, Oak Ridge in Tennessee, and

NASA in West Virginia). Also contributing to the region’s science base are technology-intensive businesses, universities, colleges, and labs ringing its border.

6. Employment in private universities is also not included.

Figure 1

Percent employment growth, technology-intensive industry, 1989-98

8.4

17.0

0.9

11.2

15.8

14.2

14.1

0.5

11.6

8.6

0 5 10 15 20

Very T-I

Moderate T-I

Somewhat T-I

All tech-intensive

(T-I)

Total private sector

Shaded bar: U.S.*

White bar: Appalachia

Source: U.S. Bureau of Labor Statistics. *Excludes WY, AK, & HI.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 6

20%

55%

25%

32%

51%

17%

0%

10%

20%

30%

40%

50%

60%

Very T-I Moderate T-I Somewhat T-I

1.3 Study Objectives

How important is technology to Appalachia? Behind the hype on high-tech are a series of often

unexamined claims about the role of knowledge infrastructure in the economy. Solid evidence of a

dramatic shift in U.S. comparative advantage toward knowledge-intensive production and services is

surprisingly sparse, some regions have achieved considerable economic growth even with modest science and technology assets, and the proliferation of information technologies would seem to imply that

the localization of innovation may be less critical for productivity than it once was. Even the view that

the U.S. economy is becoming significantly more open, a common explanation for manufacturing job

losses in the non-recessionary 1990s, has been subject to dispute (e.g., see Krugman 1995).

While such questions are extremely important, they are beyond the scope of this study. We take as

a point of departure that the state and local governments of Appalachia are looking to nurture their

promising technology assets. Doing that effectively requires knowledge of the location and characteristics of those assets. In that context, the principal objectives of this study are to systematically inventory the R&D, innovation, and technology specializations in the 406-county Appalachian region, and,

most importantly, to expose and document any localized clusters of such activity. The report aims to

provide a detailed analysis of the spatial distribution and concentration of Appalachia’s science and

technology strengths, as well as examine the strengths and concentrations of neighboring regions that

may spillover into the Appalachian region. We also discuss the policy implications of the findings,

particularly in light of the uncertain evidence of the exact relationship between knowledge infrastructure and regional economic growth.

Figure 2

Technology-intensive sector mix (T-I), 1998

Percent share of total technology employment by sector

Source: U.S. Bureau of Labor Statistics. *Excludes WY, AK, & HI.

Shaded bar: U.S.*

White bar: Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 7

1.4 Conceptual Framework and Report Organization

Figure 3 summarizes the study conceptual framework. We examine technology-related assets within

and near Appalachia from two perspectives: the industrial base (technology-related goods and services

production and employment) and the knowledge base (knowledge creating institutions and programs).

Our objective in both cases is to identify functional and spatial clusters of activity that are legitimate

existing or potential strengths in the region vis-à-vis the broader U.S. economy.7 We define the areas of

overlap between the industry and the knowledge/innovation strengths as Appalachia’s unique technology

clusters.

The methodology is based on a strategy of triangulation. Given the myriad plausible ways that

high-tech activity might be defined, measured (in terms of quantity), and assessed (in terms of quality),

we opt to use multiple data sources, classification schemes, and indicators to screen locations. The

logic is that we can be more confident of the strength and depth of the science and technology base of

a given Appalachian sub-region if it stands out along several science and technology dimensions.

7. There is a significant difference between relative and absolute analyses of the region’s strengths. In the

context of university R&D strengths, the relative approach implies an explicit assessment of Appalachian

universities against an outside referent (e.g., a U.S. benchmark). An absolute approach would simply identify

the key R&D strengths within and around Appalachia itself. In the case of the former, it is possible that no

strengths would be identified. In the case of the latter, the top disciplines in the region — irrespective of their

position in a national ranking — would be highlighted. A relative analysis is far superior to an absolute one

from a policy perspective since Appalachian businesses, universities, colleges, and labs are not competing

solely with each other, but also with entities elsewhere in the United States.

Knowledge

creation,

innovation,

education

Geography

Specializations

Geography

Specializations

Goods &

services

production

Tech

Clusters

Tech-intensive industry

Technology value-chains

Science & technical workers

Section II Section III

Section IV

Organization of the report:

University R&D

Private research houses

Federal R&D labs

SBIR grants

State programs

Teaching universities

Community colleges

Industry patents

Figure 3

Study conceptual framework & report organization
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 8

In Section 2 we first identify geographic concentrations of private sector employment in technologyintensive industries, broadly construed. We then reorganize those industries into groups based on an

analysis of potential buyer-supplier linkages and similarities in production technologies. The groups of

linked and related industries (or value-chains) become the units of analysis for a second look at the

geographical pattern of employment in the region. Analysis of the spatial distribution of science and

technology occupations provides further evidence of industrial technology assets. Overlaying the industry and occupational employment data allows us to highlight and describe the heaviest concentrations of technology-intensive industrial activity.

Section 3 documents the region’s strengths from the perspective of knowledge infrastructure:

science, innovation, and, to a more limited extent, education and training. It analyzes university research strengths by discipline, the location and size of federal (or federally-funded) research laboratories, the spatial and functional distribution of utility patents and federal grants for innovation and R&D

(e.g. Small Business Innovation Research, or SBIR, grants), the incidence of state-supported technology initiatives, and the extensiveness of science and engineering training in the region’s network of

teaching universities and community colleges.

Section 4 combines the findings from Sections 2 and 3 to identify localized concentrations where

technology-intensive industrial and knowledge creation assets overlap within specific functional areas.

Those regions, which we label technology clusters, are places where a moderately to highly sophisticated knowledge infrastructure is joined with a substantial related industrial base. As such, they are

natural first candidates for development policy initiatives designed to increase the general complement

of technology activity in Appalachia. Section 4 concludes by discussing the policy implications of the

findings and suggesting actions state and local governments can take to further explore and nurture the

technology clusters, even given uncertainty about what elements of the regional knowledge infrastructure contribute most directly to traditional economic development aims (such as job growth). We also

discuss the need for further research, especially with respect to documenting sub-specializations within

identified clusters and assessing the general performance of the clusters over time.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 9

2 Appalachia’s High-Tech Industrial Base

Rather than utilize a single definition and measure of high-technology industrial activity, we characterize Appalachia’s industrial base by synthesizing findings generated with three kinds of related information:

 The location of employment by sectors classified according to three levels of

technology intensity;

 The location of employment in eight high-tech value-chains, where each valuechain is a group of linked technology-intensive industries as revealed by an

analysis of 1992 input-output patterns;

 The location of science and engineering workers in thirteen technology categories.8

In the cases of sectoral employment and value-chain employment, we use county-level data and

statistical measures of spatial association to identify unique multi-county areas where technologyrelated activity is significantly concentrated.9

 We cannot use the same approach for the occupation

analysis since data on science and engineering workers are available only for metropolitan areas. Thus

an exact screening of individual counties based on the three measures is impossible. Nevertheless, we

produce graphic overlays of the results to aid identification of those sub-regions within and along the

border of Appalachia where technology-related activity is especially pronounced. Concepts, measures,

and data sources utilized in this section are summarized in Table 2.

8. There is no single widely accepted means of characterizing the geography of a region’s technology-intensive

industrial base. Standard definitions of high-technology industry are necessarily problematic, secondary data

sources are limited (often representing some sectors better than others), and government-defined sectoral

definitions are imprecise. While high-technology industries might be viewed as those sectors undertaking

significant R&D or employing scientists and engineers (the “input” view), definitions based on the technology-intensity of the production process (e.g., the adoption of advanced production machinery and methods;

the “process” view) or the complement of technology in the final product (the “output” view) are equally

useful in various research and policy contexts.

9. We also use ZIP codes as a unit of analysis in the case of high-tech employment.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 10

We recognize that even with the use of varying industry and occupational classification schemes,

our approach may obscure some important underlying industrial strengths in advanced technology. Our

approach is a compromise between the obvious desirability of a highly detailed county-by-county investigation and the practical need for a methodology that is manageable for a large and diverse 406-

county region. Our objective is to shed light on the broader spatial pattern of technology-oriented

activity in Appalachia, to identify focus areas for strategic policy design, and to derive a set of subregions that can be subjected to more detailed investigation.

2.1 Technology-Intensive Industry Employment

We begin by identifying spatial concentrations of private sector industry employment by grouping

high-tech sectors into three categories based on their utilization of scientists/engineers and volume of

R&D spending: very technology-intensive (VTI), moderately technology-intensive (MTI), and somewhat technology-intensive (STI).

10 The specific SIC codes included under each category are reported in

Appendix Table 1. The following gives a broad (and non-exhaustive) indication of the components of

each group:

 VTI sectors: Pharmaceuticals, computer and communications equipment, aircraft,

computer programming services and software, engineering services, commercial

and noncommercial research houses, and testing laboratories;

 MTI sectors: Industrial chemicals, plastics, electronic components, vehicles, medical

instruments, general hospitals, and medical and dental labs;

10. The classification, which is from the North Carolina Employment Security Commission as originally utilized

in NCACTs 1995, was based on early BLS studies of the proportion of scientists and engineers by sector and

National Science Foundation data on the conduct of R&D by sector (personal communication with Dr. Walter

Plosila, former executive director of the North Carolina Alliance for Competitive Technologies).

Table 2

Study measurement of high-tech industrial activity

Concept Classification Variable Year(s)

Concentration 

measure Areal unit Data source

Technologyintensive 

industry

Three levels: Very technology-intensive, 

moderately technology-intensive, 

somewhat technology-intensive; from 

U.S. Bureau of Labor Statistics

Industry 

employment

1989, 

1998

Location 

quotient,

G statistic

Counties, 

zip codes

Confidential ES-202 series, U.S. 

Bureau of Labor Statistics

Value-chains Eight value chains developed via an inputoutput analysis of buyer-supplier patterns 

among high-technology sectors

Industry 

employment

1989, 

1998

Location 

quotient,

G statistic

Counties, 

zip codes

Confidential ES-202 series, US 

Bureau of Labor Statistics; 1992 

benchmark input-output accounts, 

U.S. Bureau of Economic Analysis

Scientists & 

engineers

Scientific, engineering, and engineering 

technician ccupations

Occupational 

employment

1999 Location 

quotient

Metro 

areas

U.S. Bureau of Labor Statistics 

Occupational Employment Survey
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 11

 STI sectors: Miscellaneous chemicals, engines, machinery, household appliances,

electrical equipment, truck and bus bodies and trailers, medical appliances and

supplies, and miscellaneous communications services.

Data are from the confidential unsuppressed Unemployment Insurance Data Base (UDB) of the

U.S. Bureau of Labor Statistics, obtained with special permission.11 The UDB data, which contain employment and wage figures by establishment for all fifty states, permit us to take a fine-grained look at

employment patterns even in very small counties. Publicly available sources of employment data, such

as County Business Patterns, contain significant data suppression for detailed industries in small counties, either limiting the analysis to aggregated industries or requiring data estimation schemes that

introduce unknown error. Geographic identifiers in the UDB also permit the use of alternative spatial

units of analysis. We compare results using both counties and ZIP codes in order to minimize the

potential bias that can result from examining geographical patterns using arbitrarily shaped areal units.12

We use simple county-level location quotients as well as a measure of spatial association called a

G statistic to identify localized concentrations of activity. While a location quotient indicates a concentration of activity within a single county that is relatively high compared to the national average, the G

statistic helps reveal broader multi-county areas where technology-related activity is especially pronounced. The G works by analyzing the full multi-county spatial distribution of values of a given

indicator, such as high-tech employment, to detect where high and low values of the indicator are

clustered together. The details of the location quotient and G calculations are described in the Methods

Appendix.

Because the impacts of neither technology-oriented industries nor knowledge infrastructure respect jurisdictional boundaries, the study area includes the 406 counties under the policy jurisdiction of

11. The ES-202 file reports employment and wage data for all firms subject to federal and state employment

security law, with only the very smallest enterprises and sole proprietorships excluded. At the time of study,

1998 was the most recent year available, with reliable data stretching back to 1989. The UDB data, along with

the BLS’ new Longitudinal Establishment Microdata (or LDB), are described in Pivetz, Searson et al. 2000.

Strengths and limitations of BLS ES-202 data are discussed generally in White, Zipp et al. (1990) and Davis,

Haltiwanger et al. (1996).

12. We use counties as the primary spatial unit because of the stability of their boundaries over time, their roughly

similar size within the study region, and the relative accuracy with which the ES-202 data could be aggregated

to this unit. For the most part, counties are large enough to reflect a relatively homogenous economic unit, but

small enough to capture local specializations. Yet counties are still an arbitrary unit of analysis for measuring

economic interactions; county boundaries were developed independent of the concentrations of economic

activity we are attempting to identify. This creates a unique methodological dilemma known as the modifiable area unit boundary problem (MAUP). MAUP implies that a redrawing of spatial boundaries (or altering

the spatial aggregation) on which a given analysis is based could very well generate different results

(Fotheringham and Wong 1991; Amrhein 1995; Wrigley 1995). To offset the possibility of MAUP error at the

county level, we conduct supplementary analyses using approximated ZIP code boundaries. ZIP codes are

typically much smaller than counties, especially in urban areas, and help to pick up areas of tight spatial

concentration that get “washed-out” at the county level.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 12

the Appalachian Regional Commission along with a border area of counties and metropolitan areas

roughly adjacent to the ARC region.13 Figure 4 depicts both the ARC and broader study boundaries; as

well all included metropolitan areas. Note that metro areas with at least one county either adjacent to or

within the ARC region are included. All 62 metropolitan areas in the study area are listed in Appendix

Table 2 along with a code that identifies their location on the map in Figure 4.

Although the VTI, MTI, and STI sectors are too aggregated to draw substantive conclusions about

localized specializations, they do provide an indication of the general functional and spatial distribution of high-tech activity in the region. In the introduction to this report, we noted that the VTI sector is

under-represented in Appalachia compared the U.S. as a whole, while its employment growth during

13. Also included are eight independent cities in Virginia. The Census Bureau gives a separate county level FIPS

code to these cities and thus they are treated as independent entities in our spatial analysis. Note that, in some

cases, counties wedged between two adjacent counties were also included in the border region.

Figure 4

Study area, Appalachia and border region

Numbers correspond to listing

in Appendix Table 1

(Internal) ARC boundary

Included metro areas

(External) Study boundary
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 13

the 1990s was sluggish (see Table 1). Likewise, although Appalachia is slightly over-represented compared to the nation in the STI sector, employment in STI industries are barely expanding (a mere 0.5

percent net growth in employment between 1990 and 1998). Indeed, the trends suggest that Appalachia’s

high-tech industrial base is shifting toward industries in the MTI category. MTI industries as a group

posted the fastest rate of job growth among the three sectors between 1989 and 1998 (17 percent growth

in Appalachia compared to 14.1 percent at the national level). They also account for the largest share of

technology-related employment in the region (at 7.3 percent of private sector activity). As we show

below, MTI concentrations are also well represented throughout northern, central, and southern Appalachia.

To characterize the spatial distribution of VTI, MTI, and STI employment, we calculated our

measures of concentration (the local G statistic and location quotient) several different ways. First, we

calculated employment location quotients for each county for 1998. Next, we computed G statistics

first using counties and then ZIP codes as the units of analysis, with 1998 employment as the variable of

study. Finally, we calculated county-level local G statistics with the change in employment between

1989 and 1998 as the variable of interest. Figures 5–7 overlay the results, highlighting only significant

values for each measure. In the case of the G, highlighted values are those that are statistically significant at the 95 percent level. In the case of the location quotient, highlighted values are those in excess

of 1.1. Employment location quotients appreciably greater than 1.0 indicate that there is a higher share

of the given activity in the study county than the U.S. as a whole (thus suggesting a relative specialization in that county).14

Figure 5 shows that substantial multi-county concentrations of VTI employment in the region are

very few (as represented by the significant G values for counties and ZIP codes). They are found in the

Binghamton, Knoxville, Huntsville, and greater Atlanta metro areas. There are no concentrations of

VTI employment growth within Appalachia, though there is some activity along its northwest border in

New York (near Rochester) and its northeastern border (associated with the Albany area, greater New

York City, and Washington DC).

By contrast, Figure 6 reveals roughly fifteen significant concentrations of MTI employment scattered throughout the region, with the most extensive in the vicinities of Charleston, WV (and extending

north to Parkersburg), Pittsburgh, Johnson City, Birmingham/Tuscaloosa, and Greenville-Spartanburg.

Employment growth in the MTI sector over the 1990s was especially concentrated in the Birmingham/

14. Many of the counties posting significant location quotients or G values are in metro areas. For convenience,

Appendix Table 3 indicates whether evidence of spatial concentration was determined in at least one county

or ZIP code in each metro area in the study region. The table should be interpreted cautiously. It does not

indicate a concentration for an entire metro area but rather for one or more counties/ZIP codes within given

metro areas.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 14

Tuscaloosa area, as well in the Carolinas (Asheville, NC and Greenville, SC). Border concentrations of

MTI activity are found in New York (Buffalo, Rochester, Albany, Newburgh), Akron, and central Kentucky.

While MTI concentrations are distributed throughout Appalachia, concentrations of STI employment and employment growth are oriented toward the north (in New York, Pennsylvania, and Ohio)

and the south (Tennessee, the Carolinas, Georgia and Alabama). Interestingly, there are no substantial

STI concentrations in West Virginia or eastern Kentucky (see Figure 7). Indeed, only a few counties in

those areas even post location quotients above 1.1.

2.2 High-Tech Value-Chains

Given a general sense of how Appalachia’s industrial high-tech base is oriented toward sectors that are

moderately to somewhat technology-intensive, we next utilized a different industrial classification

scheme that acknowledges functional relationships between sectors to consider the region’s specific

strengths by industry. Specifically, we re-sorted the four-digit SIC components of the STI, MTI, and VTI

Figure 5

Spatial concentration: Very tech-intensive industries, 1998

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 15

sectors into new groups that represent distinct value-chains, or groups of high-tech industries that are

significant trading partners.

The value-chains are based on a detailed analysis of national 1992 input-output patterns and,

therefore, represent the core technology-intensive buyer-supplier chains in the U.S. economy.15 The

details of their derivation are summarized in the Methods Appendix. Each of the eight chains, which

are listed in Table 3, is comprised of between eight and thirty diverse four-digit SIC codes (see Appendix Table 4). For example, the motor vehicles value-chain includes chemicals, machinery, electronics

and transportation equipment industries. The value-chains are not mutually exclusive since some sec15. The technology value-chains are derived from a statistical analysis of national input-output data. Input-output data provide a useful characterization of trading patterns and general technological similarities among all

U.S. industries, but with an emphasis on manufacturing. The value-chains are therefore groups of technologically intensive industries that constitute final market producers and their first, second, and third tier supplier

sectors. Their derivation is discussed in the Methods Appendix; a discussion of general issues related to the

identification of linked industries is available in Bergman and Feser 1999.

Figure 6

Spatial concentration: Moderately tech-intensive industries, 1998

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 16

tors are linked to multiple industries, a feature that reinforces their characterization of interdependence

in the economy.16 The high-tech value-chains are a good starting point for assessing unique industrial

specializations in Appalachia since they go beyond simple sectoral definitions to include groups of

industries that share similar competitive pressures and, in some cases, utilize similar production

technologies.

In employment terms, the largest high-tech value-chains in Appalachia are information technology and instruments, communications software and services, chemicals and plastics, and motor ve16. There are 149 four-digit SIC codes classified as very, moderately, or somewhat technology-intensive in Appendix Table 1. In the input-output analysis, nineteen of those sectors failed to link to any other major groups

of sectors. The largest of these in terms of employment in Appalachia and the U.S. is general hospitals.

Twelve of the nineteen sectors are classified in the STI sector; only one (noncommercial research organization, SIC 8733) is classified in the VTI sector. Because it is questionable whether general hospitals can be

regarded as high-tech industries, and because most of the remaining eighteen sectors were in the low-technology category, the nineteen “unlinked” industries are not included in the value-chain analysis.

Figure 7

Spatial concentration: Somewhat tech-intensive industries, 1998

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 17

hicles (see Table 3). However, both information technology/instruments and communications software/services are significantly under-represented in the region compared to the U.S. Over-represented

chains — arguably Appalachian specializations — are chemicals/plastics and industrial machinery (see

Figure 8). The two fastest growing chains in Appalachia during the 1990s were communications software/services and motor vehicles. The latter has become an important industrial strength in the region

as automotive production and related supplier industries have shifted south. The emergence of endmarket vehicle production in Ohio, Kentucky, Tennessee, South Carolina, and Alabama has undoubtedly helped drive an increase in vehicle-related employment in Appalachia of nearly 34 percent between 1989 and 1998, well above national growth of 11 percent. In contrast, even at 35 percent over the

period, employment growth in the Appalachian communications services/software value-chain fell

well below the national rate of growth (at 56 percent).

United States*

Value-chains

1989 

(000's)

1998 

(000's)

% private 

sector '98

% 

Change 

'89-'98

1998 

(Millions $)

% private 

sector '98

Average 

wage $

Chemicals and plastics 1,218.7 1,384.8 1.3 13.6 59,213 1.8 42,760 

Information technology & instruments 2,887.5 3,573.0 3.4 23.7 202,588 6.1 56,700 

Industrial machinery 550.1 568.0 0.5 3.3 23,040 0.7 40,564 

Motor vehicles 1,375.8 1,523.3 1.5 10.7 70,242 2.1 46,111 

Aerospace 1,097.2 848.8 0.8 -22.6 42,557 1.3 50,136 

Household appliances 94.6 91.5 0.1 -3.2 3,233 0.1 35,330 

Communication software & services 1,877.2 2,918.6 2.8 55.5 163,049 4.9 55,866 

Pharmaceuticals & medical technologies 840.9 982.7 0.9 16.9 49,930 1.5 50,807 

Total private sector 96,029.3 104,258.3 100.0 8.6 3,310,187 100.0 31,750 

Appalachia

Value-chains

1989 

(000's)

1998 

(000's)

% private 

sector '98

% 

Change 

'89-'98

1998 

(Millions $)

% private 

sector '98

Average 

wage $

Chemicals and plastics 119.0 129.7 1.5 9.0 5,107 2.3 39,377 

Information technology & instruments 151.0 167.2 2.0 10.7 6,494 3.0 38,852 

Industrial machinery 65.7 60.0 0.7 -8.6 2,276 1.0 37,926 

Motor vehicles 90.7 121.4 1.4 33.9 4,356 2.0 35,884 

Aerospace 40.7 40.1 0.5 -1.4 1,572 0.7 39,222 

Household appliances 5.2 5.7 0.1 10.7 171 0.1 29,965 

Communication software & services 98.2 132.4 1.6 34.8 5,845 2.7 44,140 

Pharmaceuticals & medical technologies 54.1 56.9 0.7 5.1 2,286 1.0 40,194 

Total private sector 7,292.4 8,443.1 100.0 15.8 219,867 100.0 26,041 

Source: U.S. Bureau of Labor Statistics, ES-202 files. *U.S. figures exclude Alaska, Hawaii, and Wyoming. Appalachia includes only the 

406-county ARC region. Value-chains are not mututally exclusive and do not include all technology-intensive industries that make up 

the STI, MTI, and VTI sectors in Table 1.

Employment

Employment

Payroll

Payroll

Table 3

Technology-intensive value-chain employment & wages, 1989, 1998
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 18

As in the case of the STI, MTI, and VTI sectors, we calculated and compared the two different

measures of concentration for several different units of analysis (counties, ZIP codes) and variables

(employment, employment growth). Figures 9–16 plot the indicators using the same overlay approach.

Evidence of localized clustering in the region is strongest for three value-chains: chemicals and

plastics (Figure 9), motor vehicles (Figure 10), and industrial machinery (Figure 11). Sub-regional

concentrations of chemicals and plastics employment, in particular, can be found in a large number of

locations in Appalachia, including the Pittsburgh area, central and eastern Pennsylvania, West Virginia

and Southern Ohio (near Parkersburg and Charleston), northeastern Tennessee, the Carolinas, and central Alabama (Birmingham and Tuscaloosa). In contrast, motor vehicles employment closely tracks the

I-71, I-65, and I-85 corridors, putting most of the localized activity along the region’s borders. Particularly heavy concentrations with potential spillovers to Appalachia are found in central Kentucky (home

of Ford, GM, and Toyota), central Ohio, western North Carolina (a key location for vehicle parts manufacturing) and the Greenville-Spartanburg area (home of BMW). Smaller concentrations are found in

northern Pennsylvania, Tennessee, and northern Alabama. Concentrations of industrial machinery

employment are particularly heavy in Pennsylvania (Johnstown, Pittsburgh), New York, western Virginia, and an extended region that runs from Charlotte through Greenville-Spartanburg to Atlanta.

The remaining technology value-chains show only limited evidence of localization in the region.

As noted above, Appalachia is relatively weak in information technology and instruments. The valuechain (essentially production of IT-related hardware) is concentrated in Binghamton (IBM is the pro1.3 

3.4 

0.5 

1.5 

0.8 

0.1 

2.8 

0.9 

1.5 

2.0 

0.7 

1.4 

0.5 

0.1 

1.6 

0.7 

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 

Pharmaceuticals/med techs

Communications services/software

Household appliances

Aerospace

Motor vehicles

Industrial machinery

IT/instruments

Chemicals and plastics

Figure 8

Percent private sector employment by value-chain, 1998

Shaded bar: U.S.*

White bar: Appalachia

Source: U.S. Bureau of Labor Statistics. *Excludes WY, AK, & HI.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 19

genitor in this case), State College, and Huntsville (Figure 12). Concentrations of communications

software and services are found Pittsburgh, Knoxville, Huntsville, and Atlanta (Figure 13), while aerospace activity is localized in northwestern Pennsylvania (south of Erie in a region anchored by Crawford

county), Huntsville, and greater Atlanta (Figure 14). Activity in the aerospace concentration in Pennsylvania is driven primarily by tool and die and precision machinery activities as core suppliers to the

aircraft industry.

Localized activity in household appliances value-chain are found in south central Kentucky (with

some spillover into the ARC region), Johnson City, Greenville-Spartanburg, and Decatur, Alabama,

with key border concentrations in the Canton and Montgomery areas (Figure 15). There are several

small areas of geographic concentration of pharmaceuticals and medical technologies activity within

Appalachia (Figure 16). They are found mainly in Pennsylvania and northern West Virginia, Tennessee, western North Carolina, western South Carolina, and northern Alabama (Huntsville).

Figure 9

Spatial concentration: Chemicals and plastics value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 20

Figure 10

Spatial concentration: Motor vehicles value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 21

Figure 11

Spatial concentration: Industrial machinery value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 22

Figure 12

Spatial concentration: Information technology and instruments value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 23

Figure 13

Spatial concentration: Communications services & software value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 24

Figure 14

Spatial concentration: Aerospace value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 25

Figure 15

Spatial concentration: Household appliances value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 26

Figure 16

Spatial concentration: Pharmaceuticals and medical technologies value-chain

significant Gi, county growth

ARC boundary

location quotient > 1.1

significant Gi

, counties, zips

Map Legend

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 27

17. The 1999 OES survey is described in BLS (2001). OES data are accessible directly via the Internet at http://

www.bls.gov/oes.

18. We also identified a reduced set of 36 occupations that includes scientists and engineers only (no technicians). Location quotients for scientists/engineers and technicians separately are reported in Appendix Tables

7 and 8.

Appendix Table 5 summarizes these findings by metro area. In terms of a diversity of technologyrelated industry, there are clearly five leading or “first-tier” metropolitan areas in Appalachia:

Binghamton, Greenville-Spartanburg, Huntsville, Johnson City, and Pittsburgh. We found evidence of

high-tech concentrations in four or more value-chains in at least parts of each of those cities (seven and

six in the cases of Huntsville and Greenville-Spartanburg, respectively). A second tier of cities that are

also home to multiple value-chain concentrations include Asheville, Decatur, Erie, Knoxville, and

State College, PA. In Section 3, we consider the spatial distribution of patent grants in technology areas

that roughly correspond to those of the value-chains, allowing us to eventually compare a measure of

productive activity (employment) with innovation.

2.3 Scientists, Engineers, and Technicians

Occupational employment statistics provide a third means of characterizing the location of technologyintensive activity, where the latter is broadened to include both the private and public sectors. Sub-state

occupational employment data are available from the U.S. Bureau of Labor Statistics’ Occupational

Employment Statistics (OES) series.17 The OES data are available only for metropolitan areas however,

forcing us to ignore rural areas and to use only the location quotient measure of concentration. Nevertheless, the metro-level analysis of the region’s scientific, engineering and technician workforce is a

useful supplement to our analyses of the geography of industry employment and patents.

From the 709 occupations reported in the 1999 OES data, we identified 56 specific science, engineering, and engineering technician occupations. We organized the 56 occupations into thirteen substantive groups that roughly parallel, though are more detailed, than the eight value-chain industries

(see Table 4). The 56 included occupations and their match to one of thirteen aggregate categories are

reported in Appendix Table 6.18

A few of the remaining 653 occupations in the 1999 OES data bear mentioning since the reasons

for excluding them from our classification of scientists and engineers helps clarify our objectives. For

example, we did not include civil engineers/technicians and opthalmic and dental lab technicians among

the 56 science and engineering occupations. The vast majority of individuals employed as civil engineers or health lab technicians are not engaged in science or innovation activities. We also did not

include teachers in the various science and engineering fields in the set of 56 S&T occupations. Because

there are such a large number of teachers in a broad array of fields (a significant share of whom are
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 28

engaged primarily in instruction rather than research), they tend to dominate other occupational categories. As an indicator of science and engineering activity, occupational employment loses much of

its precision when teachers are added to the mix. The role of post-secondary educational institutions in

both teaching and research is considered in Section 3.

As survey-based data, BLS occupation statistics must be used very cautiously. The data for many

metro areas, particularly smaller ones, are often incomplete due to inadequate sample sizes and data

confidentiality regulations that necessitate suppression or non-reporting. BLS also does not report data

for occupations with fewer than 50 workers. The publicly available metro-level data therefore often

constitute undercounts for smaller MSAs when they are aggregated up from detailed occupational categories. Yet because data are generally reported for occupations with a substantial number of workers

and employing companies, they can still be useful for highlighting significant industrial specializations

in various technology areas.

There were some 4.21 million scientists, engineers, and technicians (excluding teachers) employed in the U.S. in 1999, constituting about 3.3 percent of the total workforce (see Table 5). Of those,

2.41 million (or 57 percent of the 4.21 million) were in information technology and related fields.

Electrical engineers/technicians and industrial and mechanical engineers/technicians accounted for a

respective 13 and 11 percent of the total employed pool of scientists and engineers.

Available BLS estimates for the 62 MSAs in the extended Appalachian study region place the

science and engineering workforce at just over 622,000, or about 3 percent of total metro employment.

Table 4

Estimated employment: Scientists, engineers and technicians, 1999

Occupational category Code US ARC US ARC ARC LQ

IT scientists, engineers, and programmers IT 2,407,450 406,900 57.2 65.4 1.04

Mathematicians, statisticians and physicists Math 73,680 10,900 1.8 1.8 0.91

Agricultural scientists and engineers AgSci 27,030 640 0.6 0.1 0.15

Biological scientists and technicians Bio 69,290 5,300 1.6 0.9 0.47

Chemists and chemical engineers Chem 181,200 25,430 4.3 4.1 0.86

Environmental and resource scientists and technicians Enviro 190,440 19,700 4.5 3.2 0.63

Medical scientists and engineers Med 41,260 2,710 1.0 0.4 0.40

Electrical engineers and technicians Elect 538,510 72,100 12.8 11.6 0.82

Materials engineers and scientists Matrl 29,930 3,530 0.7 0.6 0.72

Aerospace engineers and technicians Aero 111,790 7,530 2.7 1.2 0.41

Geoscientists and engineers Geo 55,460 1,580 1.3 0.3 0.17

Nuclear engineers and technicians Nucl 12,220 180 0.3 0.0 0.09

Industrial and mechanical engineers and technicians Indust 468,070 65,820 11.1 10.6 0.86

All scientists, engineers, and technicians 4,206,330 622,320 100.0 100.00 0.91

Employment

Pct share, total 

sci/eng emp

Source: Occupational Employment Statistics, U.S. Bureau of Labor Statistics. Note: U.S. figures are for entire country (metro and 

nonmetro). ARC figures are for metro areas only.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 29

Again, that figure is likely a modest undercount, given suppressed data and non-reporting in the base

data. The science and engineering workforce in the 62 metro areas within and nearby Appalachia appears to be comprised more heavily of occupations in the information technology field. IT scientists,

engineers, and programmers constitute an estimated 65 percent of all scientists, engineers, and technicians in the MSAs included in the study.

Table 5 suggests that if Washington, DC is excluded from the analysis, the southern third of the

study region is slightly more “science and engineering-intensive” than the northern and central regions,

at least as measured by the share of scientists and engineers in the workforce. Indeed, it is notable that

absent Washington, the share of scientists and engineers in the metro Appalachian workforce would

fall to roughly 2.2 percent, well below the 3.3 percent national average. Table 5 also shows that the

metro science and engineering workforce in and nearby Appalachia is evenly split between scientists/

engineers and less skilled technicians (each group accounting for about 1.5 percent of the total workforce).

Nationwide, less skilled technicians account for a somewhat smaller share of employment in science

and engineering occupations.

Employment location

quotients by study MSA for

the thirteen science and engineering occupation categories are reported in Table 6

and displayed in Figures 17–

19.

19 Relatively few MSAs

wholly within Appalachia

post location quotients significantly above 1.0 (e.g.,

>1.25), indicating a specialization in the given technology area. Exceptions are Binghamton and State

College in electrical engineering; Birmingham in medicine and material sciences; Charleston, Decatur,

Greenville-Spartanburg, and Erie in chemicals; Pittsburgh in materials sciences and mathematics; and

Huntsville in information technology, electrical engineering, aerospace, and industrial engineering.

There are much more substantial concentrations of scientists and engineers in metro areas along

the border of the region, primarily in the areas of chemicals, materials, and industrial engineering. The

legacy of chemicals production in and around the region is especially pronounced in the north, with

19. A blank cell in Table 6 or Appendix Tables 7 or 8 indicates that OES data were not available due to few

employees in the occupational category, confidentiality restrictions, or inadequate sample size.

Region

Scientists, 

engineers, & 

technicians

Scientists & 

engineers 

only

Technicians 

only

US (Metro and Nonmetro) 3.3 1.8 1.5 

ARC MSAs 3.0 1.5 1.5 

 Northern 2.2 1.1 1.1 

 Central 4.4 2.3 2.1 

 Central (w/o Washington, DC) 2.4 1.3 1.1 

 Southern 2.8 1.4 1.4 

Source: Occupational Employment Statistics, U.S. Bureau of Labor Statistics.

Table 5

Employment shares: Scientists, engineers and technicians

Percent total employment in each region, 1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 30

ID MSA

ITMathAgSciBioChemEnviroMedElectMatrlAeroGeoNuclIndust

4 I Altoona, PA 0.6 0.5

5 I Anniston, AL 0.4 0.3

6 I Asheville, NC 0.3 1.0 0.5 0.4

10 I Binghamton, NY 1.1 1.4 1.1

11 I Birmingham, AL 1.1 0.3 0.3 0.6 8.1 0.8 1.6 0.2 0.8

14 I Charleston, WV 0.3 1.3 0.5

16 I Chattanooga, TN-GA 0.3 0.3 0.3 0.4 0.7

21 I Cumberland, MD-WV 

22 I Decatur, AL 0.1 2.1 0.6 0.8

23 I Elmira, NY 0.1 0.3 0.9

24 I Erie, PA 0.3 1.8 0.5 1.8 1.0

25 I Florence, AL 0.2 1.0 0.6 0.8

26 I Gadsden, AL 0.1

28 I Greenville-Spartanburg-Anderson, SC 0.5 0.3 2.0 0.3 1.0 1.5

29 I Hagerstown, MD 0.1 0.7

33 I Huntington-Ashland, WV-KY-OH 0.2 1.1 0.3 0.1

34 I Huntsville, AL 1.7 0.6 0.5 3.4 32.8 2.8

35 I Jamestown, NY 0.1 0.6

36 I Johnson City-Kingsport-Bristol, TN-VA 0.2 0.5 0.5 0.4

37 I Johnstown, PA 0.1 0.2 0.2

38 I Knoxville, TN 0.4 1.0 1.0 0.9 0.4 0.6

47 I Parkersburg-Marietta, WV-OH 0.0 0.5 0.7 0.8

48 I Pittsburgh, PA 0.8 1.2 0.4 0.3 0.4 0.8 2.6 0.2 0.9

52 I Scranton-Wilkes-Barre-Hazleton, PA 0.5 0.4 0.2 0.7 0.5

53 I Sharon, PA 0.4

54 I State College, PA 0.2 1.5 0.3

55 I Steubenville-Weirton, OH-WV 0.1 1.1 0.6

60 I Wheeling, WV-OH 0.2

61 I Williamsport, PA 0.2 1.1

2 B Albany-Schenectady-Troy, NY 0.8 1.3 0.3 0.4 0.3 0.1

3 B Allentown-Bethlehem-Easton, PA 0.6 0.2 2.4 0.4 0.5 1.0 0.7

7 B Athens, GA 0.1 0.8 0.6 0.6

8 B Atlanta, GA 1.7 1.3 0.5 0.7 0.9 1.0 0.6 1.1 0.4 0.7 0.3 0.9

13 B Canton-Massillon, OH 0.3 0.2 0.9

17 B Cincinnati, OH-KY-IN 1.0 0.4 0.9 1.2 0.9 0.5 1.0 1.0

27 B Greensboro-Winston-Salem-High Point, NC 0.8 0.1 0.2 0.9 0.2 1.1 2.8 0.8

31 B Harrisburg-Lebanon-Carlisle, PA 1.0 0.2 0.7 0.6 0.5 0.4 0.7

32 B Hickory-Morganton-Lenoir, NC 0.3 0.6 0.6 0.4 0.7 0.6

39 B Lexington, KY 0.6 0.4 0.4 0.4 0.4 1.0

43 B Montgomery, AL 0.8 0.5 0.5 0.1

50 B Roanoke, VA 0.8 0.5 0.9 0.9 0.8 0.8

57 B Tuscaloosa, AL 0.0 0.2

59 B Washington, DC-MD-VA-WV 2.4 4.9 1.3 2.7 0.1 1.5 3.2 1.6 0.5 1.5 1.1 0.7

62 B Youngstown-Warren, OH 0.2 0.2 0.3 0.2 2.8 0.8

1 O Akron, OH 0.6 1.4 0.1 0.9 1.2

9 O Auburn-Opelika, AL

12 O Buffalo-Niagara Falls, NY 0.5 1.2 0.5 0.5 1.2 1.0

15 O Charlotte-Gastonia-Rock Hill, NC-SC 1.1 0.5 1.0 0.7 0.4 0.8 0.6 2.8 1.2

18 O Cleveland-Lorain-Elyria, OH 0.9 0.1 1.4 0.5 0.3 1.1 1.4 1.7

19 O Columbus, GA-AL 0.3 2.1 0.3 0.2

20 O Columbus, OH 1.5 0.5 0.9 0.7 0.2 0.6 0.3 0.8

30 O Hamilton-Middletown, OH 0.4 0.8 0.8 0.4

40 O Lynchburg, VA 0.4 0.5

41 O Mansfield, OH 0.2 0.7 2.0

42 O Memphis, TN-AR-MS 0.6 0.9 0.3 1.2 0.4 0.4 0.4 0.2 0.3 0.6

44 O Nashville, TN 0.6 0.6 1.2 0.3 1.4 0.7 0.2 0.2 0.5

45 O Newark, NJ 1.0 4.9 1.5 0.9 0.5 0.9

46 O Newburgh, NY-PA 0.4 2.6 0.6 0.4 0.3

49 O Reading, PA 0.1 1.7 0.8 1.1 1.6 0.9

51 O Rochester, NY 0.8 0.2 1.4 0.2 0.4 2.0 1.7

56 O Syracuse, NY 0.8 0.1 0.9 0.8 0.7 1.2

58 O Utica-Rome, NY 0.3 0.5 0.6 0.3

Source: Occupational Employment Statistics, U.S. Bureau of Labor Statistics. I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian 

border; O: MSA completely outside Appalachia, with borders at least 10 miles from region boundary. N/A: Missing. Blank: No estimate available (see text for 

explanation). Values > 1.2 are shaded.

Table 6

Location quotients: Scientists, engineers and technicians, 1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 31

Albany: Enviro

Binghamton: Elect

Newark: Chem, Enviro

Allentown: Chem

Reading: Chem, Matrl

State College: Elect

Rochester: Chem, Matrl, Indust

Akron: Chem

Pittsburgh: Math, Matrl

Cleveland: Newburgh: Chem

Chem,

Matrl, Indust

Erie: Chem, Matrl

Youngstown: Matrl

Metro area

ARC boundary

Map Legend

State boundary

Analysis buffer

Metro areas with employment location quotients > 1.25 in given technology area indicated.

Source: BLS Occupational Employment Survey, 1999. See Table 5 for abbreviated codes.

Figure 17

Scientists, engineers and technicians by metro area: Northern Appalachia, 1999

Columbus, OH: IT

Charleston, WV: Chem

Washington, DC: IT, Math,

AgSci, Bio, Enviro, Med,

Elect, Aero

Mansfield: Indust

Figure 18

Scientists, engineers and technicians by metro area: Central Appalachia, 1999

Metro areas with employment location quotients > 1.25 in given technology area indicated. Source: BLS Occupational

Employment Survey, 1999. See Table 5 for abbreviated codes.

Metro area

ARC boundary

Map Legend

State boundary

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 32

above average shares of chemists and chemicals engineers in several MSAs in eastern Pennsylvania and

northern Ohio. By the location quotient measure, Columbus, Atlanta, and Washington are specialized

in IT-related science and engineering.

2.4 Summary

We have sought to characterize the high-tech industrial base of Appalachia using two basic indicators

(industry employment and occupational employment) and three related sectoral classification schemes

(technology-intensity, value-chain linkages, and occupational category). While the concordances are

imperfect, it is possible to map the occupational categories to the eight value-chain categories to permit

a focus on a manageable set of technology areas or sectors. Overlaying the employment and occupation

data then generates a rich picture of technology-intensive industrial specializations and strengths within

and nearby the ARC region. We present those detailed overlay maps in Section 4, along with additional

data layers representing various dimensions of Appalachia’s knowledge infrastructure (the subject of

Metro area

ARC boundary

Map Legend

State boundary

Analysis buffer

Figure 19

Scientists, engineers and technicians by metro area: Southern Appalachia, 1999

Metro areas with employment location quotients > 1.25 in given technology area indicated.

Source: BLS Occupational Employment Survey, 1999. See Table 5 for abbreviated codes.

Atlanta: IT, Math

Greenville-Spartanburg: Chem, Indust

Charlotte: Nucl

Greensboro-Winston-Salem: Matrl

Birmingham: Med, Elect, Matrl

Nashville: Enviro

Columbus: Chem

Huntsville: IT, Elect,

Aero, Indust

Decatur: Chem
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 33

20. Throughout the report, we often label concentrations of activity according to the nearest major city. However,

because many concentrations encompass several cities and even adjoining rural areas, the labels themselves

should be viewed as indicating only the general vicinity of the given cluster.

the analysis in Section 3).20 Focusing just on the results to this point, however, we can identify the

following major findings:

 Overall, Appalachia’s greatest strengths appear to be in sectors of moderate

technology-intensity. Sectors classified as moderately technology-intensive are well

represented in the region and grew at rates well above the national trend during the

1990s. Industries of very high technology-intensity are comparatively few in the

region, while sectors on the low-end of the technology spectrum are not expanding.

 The same story is reflected in the mix of high tech-value chains in the region,

where the principal strengths are in the areas of chemicals/plastics and industrial

machinery. Chemicals/plastics and industrial machinery account for most of the

spatial concentrations of technology-related employment found in or immediately

adjacent to the ARC region.

 In terms of a diversity of technology-related industry, there are five leading metropolitan areas in Appalachia: Binghamton, Greenville-Spartanburg, Huntsville,

Johnson City, and Pittsburgh. We found evidence of high-tech concentrations in

four or more value-chains in at least parts of each of those cities (seven and six in

the cases of Huntsville and Greenville-Spartanburg, respectively). A second group

of cities that are also home to multiple value-chain concentrations include Asheville,

Decatur, Erie, Knoxville, and State College, PA.

 The industrial machinery, chemicals/plastics, and motor vehicles concentrations

tend to be larger in spatial extent (comprised of larger multi-county areas) than the

other technology areas. That is, their presence (or sometimes extension into) rural

counties is more extensive than sectors such as information technology, communication services, and software.

 Within the ARC region proper, there is clearly an orientation of high-tech activity

to the northern and southern thirds of the region, with activity in the central region

very sparse in several key technology areas. Chemicals and plastics industries exhibit the strongest presence in the central third of the ARC area, whether measured

by value chain employment or occupational employment.

 Appalachian metro areas have a significantly lower complement of scientists, engineers, and related technicians than the U.S. as a whole. Scientists and engineers

are somewhat better represented in the MSAs that line the region’s borders. Washington, DC accounts for a significant share of the total scientists and engineers

employed in the 62 metro areas included in the study. Excluding the Washington,

DC MSA finds the southern third of the extended region the most “science and

engineering-intensive” based on occupational employment indicators.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 34

3 Appalachia’s Knowledge Infrastructure

Appalachia’s knowledge infrastructure is comprised of two major components: organizations conducting scientific research and applied innovation and the network of universities and colleges engaged in

developing the region’s human capital base.21 (In the case of major research universities, the two components come together.) Appalachia’s science and innovation assets are based in eighteen research

universities and a limited number of other research institutions (such as federal government laboratories), non-profit R&D organizations, state-sponsored technology agencies, and private sector businesses

engaged in innovation. The R&D activities within universities span almost all academic disciplines in

the sciences, applied sciences, and engineering, and also describe a large variety of technology-related

specialties within non-university institutions. Although the research universities and other R&D institutions are located in twelve states in the ARC region, the most competitive disciplines and technology

areas are concentrated in a fairly small number of nodes.

Appalachia’s higher education network consists of over 250 universities, colleges, and community colleges offering degree programs and specialized training in fifteen science and engineeringrelated fields. In 1997/98, four-year institutions conferred over 23,600 science and engineering degrees

while two-year colleges and institutes granted an additional 12,200 degrees. Available programs and

training are extensive in some technology areas (e.g., communications and computer sciences, aerospace engineering and aviation sciences, industrial engineering, agricultural sciences, and basic medical sciences) but comparatively sparse in others (e.g., biochemistry and biomedical engineering at the

two-year level). An analysis of the mix of programs relative to U.S. averages provides an excellent

picture of the education and training orientation of Appalachia’s teaching colleges and universities in

technology-related fields.

21. A strong case could also be made for including primary education as a component of knowledge infrastructure. Indeed, the foundation for lifelong learning necessary to sustain a knowledge-intensive economy is laid

in the primary and secondary schools. However, since this report’s aim is to identify specific technologyoriented strengths, it focuses exclusively on institutions of higher education.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 35

3.1 Appalachia’s Science and Innovation Assets

The science and innovation component of Appalachia’s knowledge infrastructure consists of performers of R&D (universities, labs, and private firms) and a support system of state-funded technology

agencies and programs. The latter generally do not conduct R&D, but rather seek to diffuse best practice technologies through the provision of a variety of subsidized industrial extension services. The

following sub-sections explore the innovation assets of the region using the set of complementary

indicators summarized in Table 7.

3.1.1 R&D Performers

The major categories of R&D performer in Appalachia are research universities, non-university R&D

organizations (including federal government labs), and private sector firms. The comparative strength

of the universities is easiest to evaluate since data on faculty quality, R&D funding, enrollments, patents, and gross license income are available. The lack of reliable performance data for non-university

laboratories and private sector R&D performers (i.e., private businesses) precludes systematic comparative evaluation of those sectors. However, proxy indicators (budget figures for federal labs and

patents and federal grants participation for businesses) can provide at least limited information on the

level and location of science and innovation activity in those sectors. Moreover, in the case of private

business, science and innovation activity is partly indicated by the size, mix, and spatial distribution of

technology-intensive industries analyzed in Section 2.

Research Universities. There are eleven research universities located in the 406-county ARC

region: Carnegie-Mellon, Clemson, Cornell, Mississippi State, Ohio University (consolidated, but domiRating of faculty quality, research universities, by 

academic discipline

1995 National Research Council

Research expenditures (all sources), research 

universities by academic discipline

1991, 1999 NSF CASPAR database

Enrolled graduate students, research universities, by 

academic discipline

1991, 1999 NSF CASPAR database

Patents issued, research universities (all disciplines) 1999 AUTM Survey

Gross license income, research universities (all 1999 AUTM Survey

Non-university research organizations receiving federal 

funds in the ARC region, by location and technology 

area

1999, 2000 NSF, various

Utility patent grants by county, measured as location 

quotients and G statistics

1990-1999 US Patent and Trademark 

Office

SBIR, STTR, and ATP award winners in ARC region, FY 

2000, by location and technology area

2000 Federal government agency 

databases

Table 7

Study measurement of innovative activity
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 36

z z

z

z

z

zz

z

z

z

z

z

z

z

zz

z

z

 

 

 

Cornell U

Penn State

Carnegie Mellon U

West Virginia U

U of Pittsburgh

U of Kentucky

U of Georgia Emery U

Ohio U

Virginia Polytech

U of Tennessee

at Knoxville

U of Alabama

at Huntsville

U of Alabama

at Birmingham Georgia Institute

of Technology

U of Mississippi

Auburn U

Mississippi State

Clemson U

nated by Ohio State), Penn State, the University of Alabama at Birmingham, the University of Pittsburgh, the University of Tennessee, Virginia Tech, and West Virginia University. There are an additional six research universities situated adjacent to or very nearby the ARC boundary: Auburn University, Georgia Tech, Emory University, the University of Georgia, and the University of Mississippi. We

included the six adjacent schools in the analysis on the assumption that their close spatial proximity

yields a high potential spillover effect into the ARC region. We also added one additional institution not

classified as a doctoral university (extensive) by the Carnegie Foundation — the University of Alabama

at Huntsville — because of its strong technology focus.22 The locations of the eighteen research universities in the study are plotted in Figure 20.

22. We assembled our list of doctoral-research universities inside and nearby the ARC region from the Carnegie

Foundation’s recently revised classification of institutions of higher education (McCormick 2001). The newly

revised classification system includes two categories of doctoral-research universities. Doctoral research

footnote continues next page

ARC boundary

Map Legend

Analysis buffer

Figure 20

Major research universities within and adjacent to ARC boundary
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 37

We developed three measures of university competitiveness or strength by discipline: 1) perceived faculty quality as judged by peers in 1995; 2) external research funding receipts in 1991 and

1999; and 3) the number of full-time graduate students enrolled in 1991 and 1999. Two additional measures of competitiveness — the number of patents issued to universities and gross license income in

1991, 1995, and 1999 — could not be disaggregated by discipline.23 To establish a common scale for

combining the disparate dimensions of research strength, we converted the measures of perceived

faculty quality, research funding, and enrollment into national rankings.24

Based on ratings of faculty quality, there are six major nodes of highest competitive strength in

Appalachia: Cornell (Ithaca, NY), Carnegie-Mellon (Pittsburgh, PA), Georgia Tech (Atlanta, GA), Emory

University (Decatur, GA), Penn State (State College, PA), and Virginia Tech (Blacksburg, VA). Each of

those universities ranks among the top-twenty universities in the U.S. in at least one science or engineering discipline and among the top-forty universities nationally in at least three other disciplines.

Eight additional universities rank in the U.S. top forty in at least one discipline: University of Alabama

at Birmingham, University of Alabama at Huntsville, Auburn, Clemson, University of Georgia, University of Kentucky, University of Pittsburgh, and the University of Tennessee.

By discipline, the faculty quality rankings indicate that the greatest competitive strengths among

Appalachian research universities as a group are oriented toward the physical sciences and engineering

rather than the biological and medical sciences (see Table 8). Overall, the disciplines of greatest strength

are mechanical engineering, civil engineering, electrical engineering, industrial engineering, materials

science, chemistry, statistics, and computer science. Among the biomedical disciplines, only five deuniversities (extensive) are institutions that grant fifty or more doctoral degrees per year across at least fifteen

disciplines; doctoral research universities (intensive) are institutions that grant ten or more doctoral degrees

per year across three or more disciplines, or at least twenty doctorates per year overall. All of the universities

included in this study but the University of Alabama-Huntsville are doctoral-research universities (extensive). We added the University of Alabama at Huntsville to the group of universities in the study because of

National Science Foundation data indicating comparatively high rankings on research funding in several

engineering and scientific disciplines.

23. The faculty quality ratings are from the National Research Council’s 1995 National Survey of Graduate

Faculty (Goldberger, Maher et al. 1995). The survey asks peer faculty to rate doctoral programs within their

respective disciplines on a scale of zero (lowest) to five (highest). The ranks are based on mean scores for

each university. Research expenditures (external funding) and the number of full-time graduate students

enrolled by academic discipline are from the National Science Foundation’s Internet-based webCASPAR database (http://caspar.nsf.gov). Data on the number of patents issued to universities and gross license income

are from the Association of University Technology Managers (AUTM 1991, 1995, 1999).

24. In the case of faculty quality, patents, and license income, the classification of disciplines is from the National

Research Council. The discipline classification for research funding and enrollments is from the National

Science Foundation. While there is a close match between the NRC and NSF categories in engineering and the

physical sciences, the NSF classification is more aggregated in the biological sciences than the NRC scheme.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 38

partments are among the top twenty nationally: Cornell and University of Georgia in ecology, Emory in

pharmacology, and Virginia Tech and the University of Alabama at Birmingham in physiology. Physiology was the strongest biomedical discipline overall, with three universities boasting top-forty departments (Cornell, Emory, and Penn State).

A more objective indicator than faculty quality rankings is the national ranking of a university by

its total garnered R&D funding, by discipline. An institution’s R&D rank is an excellent quantity indicator of its relative contribution to the generation of new knowledge. The analysis of the rankings of the

universities in the ARC region in 1999 reveals a surprising number of competitive strengths spread over

a diverse number of disciplines and spatial nodes. Indeed, the pattern of R&D spending suggests that

Appalachian universities are stronger in the life sciences disciplines than suggested by the faculty

quality rankings.

Of the fifteen disciplines in the natural sciences and engineering for which data are available,

there are eleven in which there is at least one Appalachian (or nearby) university with a top-ten ranking

(see Table 9). In two of those disciplines (computer science and agricultural sciences), there are three

universities with top-ten departments, and in five other disciplines (aerospace engineering, electrical

engineering, mechanical engineering, materials engineering, and chemistry), there are two universities

Discipline UA at Birmingham

UA at HunstvilleAuburnCarnegie MellonClemsonCornellEmoryGeorgia TechU of GeorgiaU of KentuckyMississippi State UU of MississippiOhio UPenn State UU of PittsburghU of Tennessee at KnoxvilleVirginia TechWest Virginia U

Average*

Aerospace Engineering 32 6 9 17 31 15 18

Biomedical Engineering 25 33 19 26

Civil Engineering 54 12 62 6 17 53 86 32 50 65 19 66 44

Chemical Engineering 71 12 81 13 30 71 93 92 23 44 59 42 68 54

Electrical Engineering 95 59 12 73 7 13 97 102 85 28 63 66 27 88 58

Industrial Engineering 35 20 31 1 9 23 8 18

Materials Science 55 61 64 11 3 44 62 9 45 38 39

Mechanical Engineering 94 75 19 63 7 18 71 17 69 77 29 85 52

Astronomy 9 21 15

Chemistry 126 123 74 94 6 38 64 49 99 159 157 147 18 34 78 67 130 86

Computer Sciences 97 87 4 5 32 65 99 54 43 66 55

Physics 127 114 128 28 6 61 75 91 141 83 55 40 72 71 78

Ecology 119 80 4 16 72 112 107 26 92 40 70 67

Geo-Sciences 9 76 76 83 12 75 61 27 98 57

Math 130 93 40 92 15 44 58 71 136 124 37 61 77 66 75

Statistics 62 16 4 51 49 19 37 41 35

Biochemistry 49 175 22 76 112 66 93 185 45 89 165 130 128 103

Cellular Development 48 157 126 35 52 178 132 76 144 56 69 78 115 97

Molecular Genetics 45 91 23 32 90 40 100 32 46 95 81 61

Neurosciences 24 33 85 67 40 50

Pharmacology 77 110 65 15 88 31 107 125 75 44 50 72

Physiology 20 105 112 31 22 85 72 119 37 47 2 85 61

Average* 71 88 82 23 87 15 40 53 69 72 118 120 116 32 53 74 45 90 56

Source: National Research Council. Averages are only calculated on ranked values; missing values are not included. 

Dark shading = Top 20; light shading = Top 40.

Table 8

Rankings of faculty quality: Appalachin research universities, 1995
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 39

with top-ten departments. All fifteen disciplines have at least one university in or near Appalachia with

a top-twenty ranking. Leading universities in the biological or medical life sciences include Cornell,

the University of Alabama at Birmingham, the University of Georgia, the University of Pittsburgh, and

Emory University.

The distribution of strengths among the universities is also noteworthy. Of the eighteen research

universities within the ARC region, nine boast at least one top-ten department, and twelve have at least

one top-twenty department. The leading schools are Georgia Tech, Cornell, Penn State, and Virginia

Tech in terms of the number of highly ranked disciplines, but there are competitive strengths spread out

among almost all of the other universities. Moreover, there are a number of programs whose funding

rank improved substantially between 1991 and 1999, even if the rank in 1999 was still below the top-ten

or twenty. Table 10 identifies 34 such programs in total. Among the leaders with at least three emergent

disciplines apiece (based on funding rank) are Carnegie-Mellon, Georgia Tech, Ohio, Penn State, University of Kentucky, Virginia Tech, West Virginia University, and Mississippi State. Emory University

and University of Alabama at Birmingham each boast two emergent disciplines.

Discipline Auburn U, All Campuses

Carnegie Mellon UClemson UCornell U, All CampusesEmory UGA Tech, All CampusesMississippi State UOhio U, All CampusesPenn State U, All CampusesU of Alabama at BirminghamU of Alabama at HuntsvilleU of GeorgiaU of Kentucky, All CampusesU of Mississippi, All CampusesU of Pittsburgh, All CampusesU of Tennessee Univ-WideVirginia TechWest Virginia U

ENGINEERING 56 29 37 17 2 36 85 4 93 60 94 43 109 89 42 16 55

 Aerospace Engineering 32 12 4 30 16 22 9 18

 Chemical Engineering 28 30 77 42 13 61 67 22 47 55 99 35 36 39 73

 Civil Engineering 61 55 32 37 7 73 69 13 97 89 100 99 98 20 12 30

 Electrical Engineering 70 23 37 16 1 59 97 5 110 47 91 108 100 60 17 80

 Mechanical Engineering 55 33 36 78 4 68 95 7 25 63 102 98 14 21

 Materials Engineering 49 20 26 10 69 1 22 59 55 46 44 30 68

PHYSICAL SCIENCES 113 71 87 6 86 35 116 106 15 111 70 66 89 101 60 54 75 103

 Astronomy 39 5 42 20 36

 Chemistry 118 80 79 8 57 29 95 120 7 110 105 51 86 123 49 70 52 106

 Physics 103 51 77 6 112 25 119 73 14 99 41 70 74 69 71 35 100 82

GEOSCIENCES 104 83 92 65 30 74 101 13 120 61 33 99 105 39 18 73

MATH AND COMPUTER SCIENCES 110 3 68 11 100 7 76 125 53 111 40 39 84 124 57 38 52 113

 Mathematics and Statistics 96 20 39 28 75 19 86 120 23 97 50 13 77 124 66 83 34 117

 Computer Science 114 3 73 10 110 7 66 118 76 113 29 54 77 116 50 23 61 101

LIFE SCIENCES 80 111 79 13 22 107 72 120 50 17 128 26 38 115 18 59 68 92

 Agricultural Sciences 24 32 15 51 8 33 3 12 27 5 45

 Biological Sciences 85 106 59 29 40 110 122 102 22 16 126 15 115 125 96 64 89 88

 Medical Sciences 94 98 17 21 76 83 63 13 64 38 81 7 51 89 69

S&E TOTAL 92 64 84 12 44 29 79 126 14 36 113 34 48 127 33 54 49 102

Source: National Science Foundation WebCASPAR Database System. Dark shading = Top 20; light shading = Top 40. National rankings for Research I & II 

universities (131 universities ranked). R&D data for the industrial engineering discipline were are not reported by NSF, though graduate enrollment data are reported 

Table 9

Rankings of R&D funding: Appalachin research universities, 1999

Research expenditures by academic discipline
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 40

Similar to R&D expenditures, the number of graduate students enrolled by academic discipline is

a quantity indicator of a university’s academic strength in a given field. Enrollments indicate universities’ potential contribution of highly skilled human capital. Table 11 reports 1999 national graduate

student enrollment rankings by discipline for the eighteen universities in or adjacent to the ARC region.

There is an impressive distribution of strengths across a wide variety of disciplines and universities.

Fourteen of the sixteen disciplinary areas are represented by top-ten university departments, and all

sixteen have top-twenty representatives. Specifically, there are three top-ten university programs in

industrial engineering in or adjacent to the region (Georgia Tech, Virginia Tech, and the University of

Alabama at Huntsville), and two top-ten programs in civil engineering (Georgia Tech and Virginia

Tech), materials engineering (Georgia Tech and Penn State), and computer science (Carnegie-Mellon

and the University of Pittsburgh).

Aerospace Engineering Ohio Universitya

, West Virginiab

Chemical Engineering Carnegie-Mellona

, Georgia Techc, Penn Statea, University of AlabamaHuntsvillea

, University of Kentuckya

Civil Engineering Virginia Techc

, West Virginiac

Electrical Engineering Penn Statec

, Virginia Techb

Mechanical Engineering Carnegie-Mellona

, Mississippi Statea, West Virginiaa

Materials Engineering Carnegie-Mellona

, Ohio Universitya, University of AlabamaBirminghama

, Penn Stateb

Astronomy Auburna

, Ohio Universitya

Chemistry None

Physics Georgia Techa

, Penn Statec, University of Kentuckya, West Virginiaa

Geosciences Georgia Techa

, Virginia Techa, University of Georgiab, University of 

Alabama-Huntsvilleb

Mathematics and Statistics Carnegie-Mellona

, Emorya, Mississippi Statea, University of Georgiac, 

Cornellb

, Georgia Techb, University of Kentuckyb

Computer Science Mississippi Statea

, University of Alabama-Huntsvillea, University of 

Kentuckya

, University of Pittsburgha, Carnegie-Mellonb, Virginia Techb, 

West Virginiab

Agricultural Sciences Virginia Techa

Biological Sciences Emorya

, University of Alabama-Birminghamb, Pittsburghb

Medical Sciences Georgia Techa

, Emoryb

Source: National Science Foundation and authors' calculations. aSubstantial shift in national R&D 

funding rank between 1991 and 1999. b

Substantial shift in graduate student enrollment rank between 

1991 and 1999. c

Substantial shift in both R&D funding and graduate student enrollment rank 

between 1991 and 1999.

Table 10

Emergent strengths in Appalachian universities, 1991–1999

Ranking shifts based on R&D expenditures and enrollments, 1991–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 41

The principal spatial nodes of strength based on graduate student enrollments are similar to those

for R&D funding. Georgia Tech, Penn State, Cornell, and Virginia Tech are the leading locations. Yet

eight universities boast at least one top-ten program, and thirteen have at least one top-twenty department. There are also twenty university programs that can be classified as emergent based on improvements in their national enrollment rankings between 1991 and 1999 (see Table 10). They are distributed

among twelve of the disciplines. There are three emergent programs apiece at Penn State, Virginia

Tech, and West Virginia; two apiece at Georgia Tech and University of Georgia; and one apiece at

Emory, Carnegie-Mellon, University of Alabama at Huntsville, University of Kentucky, AlabamaBirmingham, University of Pittsburgh, and Cornell.

Two final indicators of university strength are the number of patents issued and total gross license

income (see Table 12). Both are measures of innovative activity that has the potential for application in

the marketplace. According to data collected by the Association of University Technology Managers

(AUTM), twelve research universities in or nearby the ARC region generated at least ten patents in 1999.

25

Auburn U, All CampusesCarnegie Mellon UClemson UCornell U, All CampusesEmory UGeorgia Tech, All CampusesMississippi State UOhio U, All CampusesPenn State, All CampusesU of Alabama at BirminghamU of Alabama at HuntsvilleU of GeorgiaU of Kentucky, All CampusesU of Mississippi, All CampusesU of Pittsburgh, All CampusesU of Tennessee Univ-WideVirginia TechWest Virginia U

ENGINEERING 67 40 44 30 1 73 87 14 99 100 116 71 104 39 38 8 46

 Aerospace Engineering 25 31 1 30 20 29 11 35

 Chemical Engineering 47 13 69 24 9 63 70 22 90 75 91 23 38 59 66

 Civil Engineering 62 57 22 20 3 97 90 26 87 98 51 88 49 36 10 39

 Electrical Engineering 95 30 51 34 3 44 64 26 105 54 70 101 37 81 11 69

 Mechanical Engineering 61 42 30 31 3 91 54 11 99 55 82 100 53 43 21 34

 Materials Engineering 28 25 29 17 7 6 45 51 56 36 46 35

 Industrial Engineering 41 39 1 56 54 21 6 63 28 19 3 36

PHYSICAL SCIENCES 102 92 55 17 87 38 117 91 4 120 106 59 66 119 34 52 73 97

 Astronomy 17 23

 Chemistry 89 101 71 34 51 31 108 91 9 122 124 42 70 120 26 64 52 96

 Physics 104 69 84 11 117 47 120 67 3 103 52 96 53 105 42 35 98 90

GEOSCIENCES 98 97 34 58 67 53 7 68 46 77 94 88 66 54 79

MATH AND COMPUTER SCIENCES 71 11 56 26 118 23 82 101 36 105 72 52 58 104 10 42 16 51

 Mathematics and Statistics 71 48 67 4 98 51 97 49 23 119 103 43 28 122 34 37 30 56

 Computer Science 67 6 50 45 16 66 41 93 54 56 84 83 8 43 14 48

LIFE SCIENCES 80 126 82 29 14 125 91 116 38 9 110 35 34 96 19 36 70 53

 Agricultural Sciences 21 24 17 15 28 19 30 41 13 32

 Biological Sciences 99 126 85 7 59 124 101 118 16 15 125 14 44 97 46 53 82 100

 Medical Sciences 62 65 2 79 68 13 56 44 74 29 17 64 66

S&E TOTAL 85 60 78 25 67 21 101 110 17 58 111 64 50 118 26 46 32 61

SOURCE: NSF WebCASPAR Database System. Dark shading = Top 20; light shading = Top 40. National rankings for research I and II universities (131 universities 

ranked).

25. Note that the AUTM data are reported only for university-wide systems in the case of Ohio University, the

University of Tennessee, and the University of Pittsburgh.

Table 11

Graduate student enrollment rankings: Appalachian research universities, 1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 42

The leading schools were Cornell (70 patents),

Penn State (46 patents), Emory (44 patents),

Virginia Tech (37 patents), and CarnegieMellon (30 patents). Appalachian and nearby

universities garnered roughly $48.6 million in

gross license income in 1999, with Emory

University accounting for one-third of the total. Ten schools generated gross license income of at least $1 million in 1999.

Federally Funded Non-University Research Organizations. The second major category of R&D performer in the Appalachian

region is the non-university-based organization that receives federal research funds. We

used National Science Foundation data on

federal funds provided to non-university R&D

performers, federal agency web sites, and information from state development officials

and other individuals familiar with the science and technology base of each state to identify eighteen

qualifying facilities located in six Appalachian states (see Table 13). We were able to document research-funding levels only for defense-related labs.26

There are several significant federal government research complexes in the ARC region. They are

clustered in two principal locations: Huntsville, Alabama (aerospace and related activities) and Oak

Ridge, Tennessee (energy-related research). Both are places without major research universities and

outside the cores of large metropolitan areas. Another smaller complex is the NASA facility at Green

Bank, West Virginia (astronomy research). There are additional, less-well-known federal government

research operations in Pittsburgh (the NSF Data Storage Center), in Watervliet, New York (Army Benét

Laboratories), and at Arnold Air Force Base, Tennessee (the Engineering Development Center). Several state government and non-profit research organizations, but which are primarily funded through

the National Science Foundation, also operate in the ARC region.

Private Sector R&D. A third and extremely important element of Appalachia’s science and innovation base are the many private sector businesses actively engaged in research, applied innovation,

Institution

Patents 

Issued

Gross License 

Income

Emory University 44 16,166,848

Cornell University 70 6,400,000

Carnegie Mellon University 30 5,892,284

Clemson University 2 4,648,141

University of Georgia 21 3,208,427

Pennsylvania State University 46 2,830,448

University of Kentucky 24 2,496,786

Georgia Institute of Technology 23 2,038,078

University of Alabama at Birmingham 24 1,562,778

Virginia Polytechnic Institute 37 1,328,343

*Ohio University 4 635,611

*University of Tennessee 17 620,903

*University of Pittsburgh 30 608,851

Auburn University 12 186,738

West Virginia University 2 41,800

Mississippi State University NI NI

University of Mississippi NI NI

Source: Association of University Technology Managers Licensing 

Survey , Fiscal Year 1999, Table 8. *Data available only for all 

campuses. NI: Institution was not included in the AUTM survey. 

26. The funding data are from Department of Defense budget documents.

Table 12

Patents issued and gross license income, 1999

(Sorted by gross license income)
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 43

and development. Unfortunately, data on private sector R&D activity are very limited. Even the National Science Foundation’s industry surveys are based on very small samples and cannot be disaggregated to the sub-state level.27 While counts of both patents and federal innovation grants (under the

Small Business Innovation Research program, Small Business Technology Transfer Research program,

and Advanced Technology Program) cannot be regarded as direct proxies of private sector R&D generally, they can provide a partial picture of the geographical distribution of private sector science and

innovation in the region.

Utility Patents. A patent is an attempt by an inventor to appropriate fully and exclusively any

returns derived from her innovation, at least for a limited period. Utility patent grants by sector are thus

a partial indicator of applied innovative activity.28 While some patents are granted to universities and

non-profit R&D performers, the vast majority are secured by private industry.

We use 1990 to 1999 county-level utility patent data provided by the U.S. Patent and Trademark

Office (USPTO) to calculate G statistics and location quotients for the extended Appalachian study

27. One NSF official also noted that even the state-level industrial R&D estimates published by his agency are

suspect, given very small samples and a strong bias toward large companies.

28. The difficulties of working with patent data and some of the caveats that must be considered in their use are

discussed in Griliches (1990) and Feser, Goldstein et al. (1998).

Name City/Town State Technology Funding 1997 Source

Southern Research Institute Birmingham AL Other

Army Space and Missile Defense Command Huntsville AL Aerospace

Marshall Space Flight Center Huntsville AL Aerospace

Army Aviation and Missile Command RD&E Redstone Arsenal AL Aerospace

Army Redstone Technical Test Center Redstone Arsenal AL Aerospace

Army Missile Research Dev and Engineering Ctr Redstone Arsenal AL Aerospace

Army Benet Laboratories Watervliet NY Aerospace $697,986,000 3

NSF Data Storage Center Pittsburgh PA Comm services & software

Software Engineering Institute Pittsburgh PA Comm services & software

SC Research Institute SC Other

Air Force Arnold Engineering Development Ctr Arnold AFB TN Aerospace

Oak Ridge Institute for Science and Education Oak Ridge TN Other

Oak Ridge National Laboratory Oak Ridge TN Industrial machinery $233,785,000 1

National Radio Astronomy Observatory Green Bank WV Aerospace $532,000 2

National Energy Technology Laboratory Morgantown WV Industrial machinery $16,395,000 1

NASA Independent Validation and Verification Facility Fairmont WV Comm services & software $21,659,000 2

WV High Tech Consortium Fairmont WV Other $202,000 2

WV Research Corp WV Other $5,540,000 2

1: NSF, Federal Funds for Research and Development: Fiscal Years 1997, 1998 and 1999, NSF 99-333. 

2: NSF, Federal Science and Engineering Support to Universities, Colleges and Nonprofit Institutions, Fiscal Year 1998, NSF-00-315. 

3: NSF, State Science and Engineering Profiles and R&D Patterns: 1997-98, NSF 00-329

Table 13

Appalachian non-university research organizations
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 44

region. The USPTO assigns patents to counties based upon residence of the inventor.29 Utility patents

are initially classified by invention or product, which the USPTO then re-classifies into industries using

the 1972 SIC definitions. Using the USPTO SICs, we organized patents into ten technology sectors that

roughly correspond to the high-tech value-chains (see Table 14). Appendix Table 9 lists the USPTO SIC

components of each aggregated sector. The USPTO commonly assigns a single patent to multiple SICs

and therefore a patent may be included in more than one technology sector. Figures 21–30 display the

mapped overlays of the concentration indicators.30

29. At best, this is only a rough approximation of the location of innovation. It assumes that the county of residence is an accurate representation the individual or institution that took a primary role in creating the invention. Many inventions are developed in multiple places while others are developed in one particular place

before another person or institution in a different location subsequently patents them. Furthermore, it is

unclear whether an inventor’s place of work or residence is the more accurate way to identify innovative

places. It may make more sense to think of innovative regions rather than try to pinpoint the site of innovation. Under typical metropolitan commuting patterns, residential areas are peripheral to work sites in the

urban core. But these patterns are changing and suburb-to-suburb commuting has become the norm in many

regions. Furthermore, the conduit for the spread of innovation and ideas is a complex web of economic and

social interactions that might be limited by geography, but is not necessarily subject to imaginary boundaries

between work and home.

Note that patents with multiple inventors living in different counties are weighted by the total number of

inventors. For example, if a single patent has two inventors that live in different counties, each county is

assigned half of the patent. Because the Gi statistic is designed to reveal spatial association among counties,

it helps offset the discrepancy caused by differences in inventor residency and work locations.

30. We adopted the slightly stricter standard of 1.25 for highlighting location quotient values in Figures 21–30

since the magnitude of patent grants is much lower than employment. The lower the magnitude of a given

variable in the location quotient formula, the greater the variation in the indicator.

Technology area Total

Pct 

share Total

Pct 

share LQ Total

Pct 

share LQ

Chemicals and plastics 224,930 20.3 33,404 24.5 0.97 5,848 23.8 1.17

Information technology 363,069 32.8 34,617 25.4 0.93 5,767 23.5 0.72

Instruments 180,424 16.3 23,844 17.5 0.73 3,134 12.8 0.78

Industrial machinery 230,781 20.8 26,132 19.2 1.28 6,015 24.5 1.18

Motor vehicles 153,722 13.9 16,466 12.1 1.17 3,462 14.1 1.02

Aerospace 54,160 4.9 5,099 3.7 1.26 1,153 4.7 0.96

Household appliances 14,136 1.3 2,027 1.5 1.09 396 1.6 1.26

Pharmaceuticals 65,733 5.9 10,896 8.0 0.45 889 3.6 0.61

Metals 116,818 10.5 16,263 11.9 1.21 3,556 14.5 1.37

Other 72,272 6.5 11,353 8.3 1.21 2,463 10.0 1.54

Total (not sum) 1,108,391 136,425 24,562

U.S. 13 ARC states ARC counties

Source: U.S. Patent and Trademark Office (special data request). Categories are not mutually 

exclusive.

Table 14

Utility patent grants over period, 1990–1999, U.S. & ARC region
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 45

Our analysis of the spatial distribution of patenting activity by technology area using the G statistic indicates that localized concentrations of patent grants are almost always located in metropolitan

areas, regardless of technology sector, a result that supports the conventional wisdom that cities, and

the suburbs where their workers live, are the primary hotbeds of applied innovative activity. It is also

noteworthy that many of those concentrations are in the same few metropolitan areas even across

different technology sectors. Also, much of the localized activity is just outside the ARC boundary, and

for the most part, is more likely to be adjacent to northern Appalachia than the central or southern parts

of the region. It is important to note that these results are partly a function of the spatial unit of analysis

(i.e., counties). The application of the G measure tends to favor metropolitan areas because an MSA is

large enough to include several adjacent counties with significant patenting activity. Location quotients indicate more concentrations of patenting in Appalachia than the G measure, although, again,

those concentrations are still often located in metropolitan areas.

As in the case of value-chain employment analyzed in Section 2, the incidence of localized patenting tends to fall into two groups: a set of sectors with evidence of concentration in the region and a

set with only minimal concentration. Among the former are patents in the areas of industrial machinery,

chemicals and plastics, and metals and metalworking. Industrial machinery patents accounted for most

utility patents granted in the region between 1990 and 1999 (6,015 in total, one-quarter of all patent

grants). Local concentrations are found in Jamestown, Binghamton, Pittsburgh, and GreenvilleSpartanburg (Figure 21). Several counties in Pennsylvania, New York, North Carolina, Tennessee, and

Georgia (near Atlanta) also post high location quotients.

Patent grants in chemicals and plastics accounted for slightly less of one-quarter of total patenting

activity in Appalachia between 1990 and 1999 (with an overall regional location quotient of 1.2). Most

of the significant spatial concentrations of chemicals and plastics patents as measured by the G analysis

are in areas adjacent to northern Appalachia; there are no G-based concentrations in Appalachia itself.

High location quotients, however, were found for Appalachian metro counties in Pennsylvania, West

Virginia, Tennessee and Alabama (Figure 22). Concentrations of metals and metalworking patents are

also located primarily in the north (New York and Pennsylvania, including Pittsburgh, Johnstown, and

Jamestown); key border concentrations include Atlanta, Cincinnati, Akron, Reading, Newburgh, Rochester/Buffalo, and Albany (Figure 23).
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 46

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 21

Spatial concentration: Industrial machinery patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 47

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 22

Spatial concentration: Chemicals and plastics patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 48

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 23

Spatial concentration: Metals and metalworking patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 49

We found considerably fewer spatial concentrations of patent grants among the remaining technology categories. The most important include:

 In information technology: Binghamton and eastern New York, with high location

quotients for Huntsville and the Roanoke area (Figure 24);

 In pharmaceuticals: high location quotients in Birmingham and in Chenango County,

New York (home to Proctor & Gamble), with border concentrations near Reading,

Washington, Newburgh, and Cincinnati (Figure 25);

 In aerospace: Johnson City and Owego in New York (home to Lockheed Martin

facilities), Pittsburgh, Greenville-Spartanburg, and Erie, with key border concentrations in Albany, Rochester, York, Akron, and Middletown, Ohio (Figure 26);

 In scientific instruments: high location quotients in Asheville and Knoxville, with

border concentrations in Rochester and Utica, New York (Figure 27);

 In household appliances: greater Atlanta, with border concentrations in New York

and Ohio (Figure 28);

 In motor vehicles: high location quotients for the Syracuse area; Scranton,

Williamsport, Pittsburgh, and Bedford County in Pennsylvania; Parkersburg in

West Virginia; Johnson City and Chattanooga in Tennessee; and border concentrations in the Cincinnati, Akron, Rochester, Albany, Newburgh, and Reading areas

(Figure 29).

A significant number of patent grants in the ARC region over the 1990s fell into a variety of

miscellaneous categories. Miscellaneous patents accounted for 10 percent of Appalachia’s total between 1990 and 1999, compared to 6.5 percent for the U.S. as a whole. Key geographical concentrations

are found in Atlanta, Greenville-Spartanburg, and a large region that extends from Rochester south to

Elmira and Owego (including a number of non-metro counties). Places such as Pittsburgh, Asheville

and Chattanooga also contained counties with high patent location quotients (Figure 30). A summary of

the spatial findings by metropolitan area is provided in Appendix Table 10.

Federal Innovation Programs. To assemble a data set of SBIR/STTR/ATP winners in the ARC

region, we reviewed program competition announcements for fiscal year 2000 to identify winners with

ZIP codes in the 406-county ARC area. As in the case of patents, each grant was mapped to a set of

technology areas that roughly are consistent with the value-chain industry classification utilized in

Section 2. We then calculated the total number of SBIR/STTR/ATP grants by location for each technology category.31

31. The seven technology area categories were based on a compromise between the competing objectives of 1)

minimizing error in the assignment of grants and organizations to specific areas (given incomplete descriptions) and 2) the eventual need to develop a concordance table between the innovative activity described in

this section and the industry activity analyzed in Section 2.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 50

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 24

Spatial concentration: Information technology patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 51

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 25

Spatial concentration: Pharmaceuticals patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 52

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 26

Spatial concentration: Aerospace patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 53

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 27

Spatial concentration: Scientific instruments patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 54

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 28

Spatial concentration: Household appliances patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 55

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 29

Spatial concentration: Motor vehicles and related products patent grants, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 56

significant Gi, counties

ARC boundary

location quotient > 1.25

Map Legend

Analysis buffer

Figure 30

Spatial concentration: Patent grants in all other categories, 1990–1999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 57

 There were over 220 SBIR, STTR, or ATP awards given to mostly small, for-profit businesses

conducting R&D in the ARC region in FY 2000. The distribution of awards by technology area is as

follows: information technology and instruments (52 awards); pharmaceuticals and medical technologies (49 awards); communications services and software (41 awards); aerospace (38 awards); chemicals and plastics (24 awards); industrial machinery (18 awards); and motor vehicles (1 award).32 Appendix Table 11 is the complete list of SBIR/STTR/ATP award winners for FY 2000.

Figure 31 plots the location of award winners. Awardees were concentrated in a relatively small

number of places, especially Huntsville, Blacksburg, Pittsburgh, State College, and Ithaca, New York.

Secondary nodes of concentration were Birmingham and Knoxville/Oak Ridge. When disaggregated

32. Some awards are classified in two categories. Four awards could not be classified. See Appendix Table 11.

• •

• ••

•

•

• •••

•

•

•

•

•

•

•

•

•

•

•

•

•

• • •

•

•

• •

•

•

• •

•

•

•• •

•

•

•

•

•

•

•

• • ••••

• •

•••••

•

• • •

•

• ••

•

•

•••

•

•

•

•

• •

•

••

•

••

Blacksburg

Pittsburgh

State College

Knoxville/Oak Ridge

Huntsville

Birmingham

Dots scaled by number

of awardees per zip code.

Binghamton

Ithaca

Figure 31

SBIR/STTR/ATP award winners in the ARC region, FY 2000

All technology categories
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 58

by major technology area, a more distinct spatial specialization pattern emerges. The following are the

principal nodes of concentration for each major technology area:

 Information technology and instruments: Huntsville, Oak Ridge, Blacksburg, and

State College;

 Pharmaceuticals and medical technologies: Birmingham, Pittsburgh, Knoxville/

Oak Ridge, and Blacksburg; note that Birmingham and Pittsburgh are the home of

universities with prominent medical schools and teaching hospitals;

 Communications services and software: Huntsville, Pittsburgh, Ithaca, and Starkville

(the location of Mississippi State University);

 Aerospace: a very large percentage of awardees were located in Huntsville, while

there were smaller concentrations of awards in Blacksburg, State College, Chattanooga, and Ithaca;

 Chemicals and plastics: Pittsburgh, Blacksburg, Knoxville/Oak Ridge, and Huntsville.

Industrial machinery is the technology area with the most widely dispersed awardees. While

minor nodes are found in Huntsville, Pittsburgh, and Blacksburg, there were one or two awardees in a

number of other places. There were no SBIR/STTR/ATP awards in the ARC region in 2000 in the area of

household appliances.

3.1.2 State Science and Technology Programs

State government-funded organizations involved in technology-based economic development and technology diffusion are an important element of Appalachia’s science and innovation base. While such

programs do not generally engage in R&D themselves, they often support science and innovation by

diffusing new ideas and technology or providing assistance with technology-related problems facing

smaller firms.

In this section, we discuss programs in Appalachia that are centrally focused on technology issues. For example, we include manufacturing modernization programs but not general business incubators. Also, we consider only state-funded programs; local or regional programs are not included

unless they utilize state funding.33 Where possible, we classified the activity of the program or organization by technology area that corresponds, as closely as possible, with the industrial technology categories utilized in Section 2. However, there are a substantial number of organizations that provide

33. We used several sources to generate a draft list technology-based economic development agencies for each

state, including Coburn and Berglund (1995); State Science and Technology Institute staff for a list of contacts within the lead science and technology organization within each state; the membership directory of the

National Business Incubator Association (http://www.nbia.org); and each state’s web site. We then sent the

draft list to the key contact person in the state’s lead science and technology organization for review and

inclusion of any omitted programs or organizations. This process was implemented in December 2000 and

January 2001. Note that a number of new programs that had been announced by several states but were not yet

in place are not included in our list.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 59

broad technology-related services to businesses that span a wide range of industries. Such organizations could not be classified into any one technology area.

As might be expected, state S&T initiatives are distributed more evenly geographically than are

R&D performers. Many state-funded organizations have as a principal mission the provision of services

(technical assistance, consulting, education and training) to a broad region, so the actual delivery of

services is even more geographically dispersed than would be suggested by the location of the organizations themselves.34

A large share of the state-funded S&T assets are based at smaller branches of public universities

or community colleges, rather than concentrated at flagship research universities or in larger metropolitan areas. The smaller branch universities are intended to increase the number of state residents with

access to higher education. Likewise the placement of technical assistance, support, and training functions at non-research public universities and community colleges is meant to target technology-based

small- and medium-sized businesses located in more peripheral areas. Appendix Table 12 reports the

full list of state-funded science and technology organizations we were able to identify. Industrial machinery is easily the most common technology focus. Within the ARC region, there are at least thirty

different locations of technical assistance services targeted to that general industry, reflecting an emphasis on manufacturing modernization and process innovation in some of the region’s traditional

industry sectors (textiles, apparel, furniture, and metals).

Two technology areas are particularly important given projections for growth in related industries: information technology and biotechnology. State programs and initiatives targeted at those areas

appear to be very few in the ARC region. There are only twelve programs focused primarily on the

information technology industry (either instruments or communications services and software): four in

West Virginia, two in Virginia, two in Alabama, and one each in Georgia, Ohio, Pennsylvania, and New

York. It is notable that we were not able to identify any major IT-related extension or tech transfer

programs in the Appalachian regions of Kentucky, Tennessee, North Carolina, South Carolina, and

Mississippi. In the case of biotechnology, we identified three programs that receive some state support:

the Georgia Biotechnology Center, the Edison Biotechnology Institute in Ohio, and the Cornell Institute for Biotechnology and Life Sciences.

3.2 Appalachia’s Higher Education Infrastructure

The higher education and training component of Appalachia’s knowledge infrastructure in the sciences

and engineering fields is comprised of the over 250 universities, colleges, and institutes that offer

degree programs in fifteen technology-related disciplines. The literature on technology-related regional

34. Unfortunately, we were not able to obtain detailed data on the location of clients or actual service delivery.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 60

growth has long emphasized the important role major research universities play in conducting R&D,

transferring technology, and generating spin-off companies (Bozeman and Crow 1991; Coursey and

Bozeman 1993; Lee and Gaertner 1994; Chrisman, Hynes et al. 1995). However, four-year teaching

universities and colleges and two-year community colleges and institutes are also critical suppliers of

necessary human capital and common sites for publicly-funded business modernization programs (Luger

and Goldstein 1997). Community colleges, in particular, play a key role both in preparing and upgrading technology workers in a wide range of applied fields and in supplying focused training and modernization assistance to technology-intensive firms.

This section evaluates the human capital dimension of the Appalachia’s colleges and universities

using the 1997/98 data on degrees granted by program from the U.S. Department of Education’s Integrated Postsecondary Education Data System (IPEDS).

35 IPEDS data ultimately derive from the Department of Education’s surveys of all postsecondary institutions that participate in federal financial aid

programs. The surveys essentially cover every conventional university, college, and community college in the U.S., as well as many specialized trades schools and technical institutes.36 The IPEDS degree

completions data are reported at a very high level of programmatic detail. We aggregated the figures

into fifteen disciplinary/program areas that parallel, as much as possible, the National Science Foundation discipline classification.37 Appendix Tables 13 and 14 detail our classification scheme.

Academic year 1997/98 degree completions at four-year colleges and universities in the 406-county

ARC region are reported in Table 15. Consistent with the distribution of degrees nationwide, two fields

accounted for just under half of the total 23,635 degrees granted in Appalachia: agricultural sciences/

technology and industrial engineering/technology. Indeed, a comparison with the national distribution

of degrees by discipline indicates that the overall mix of programs in Appalachian four-year schools

parallels the national mix fairly closely. Judging by total degrees completed, Appalachian universities’

35. The Integrated Postsecondary Education Data System (IPEDS), along with all technical documentation, is

accessible via the Internet at http://nces.ed.gov/ipeds/index.html.

36. The Department of Education’s universe for its completions surveys are all institutions with which it has

Program Participation Agreements (PPAs) regarding Title IV federal financial aid programs, or some 9,519

schools in the fifty states and District of Columbia. The 1997/98 overall response rate for the survey (actually

two separate instruments) was 74 percent. Four-year institutions responded at 89 percent, two-year schools at

88 percent, and less than two-year institutions at 53 percent. Although responding institutions account for the

vast majority of degrees granted, the IPEDS completions data must be regarded as slight undercounts of total

degree completions.

37. Degree completions in the IPEDS data are disaggregated by over 550 Classification of Instructional Programs

(CIP) codes (see http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=91396). We used judgment and the National Science Foundation science and engineering disciplines as guides to first identify 190 CIP codes as

technology-related programs, and then aggregate the 190 selected codes to fifteen substantive categories. The

included CIP codes along with their classification to the fifteen aggregate categories are reported in Appendix Table 13. Appendix Table 14 lists the excluded CIP codes.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 61

programs in basic medical science, environmental engineering and controls, mathematics, materials

engineering and science, and biochemistry and biomedical engineering are slightly larger than the

national average while industrial engineering and science is significantly smaller than the national

average.

As compared to the national average, proportionately more Appalachian students at two-year

colleges earn degrees in agricultural sciences/technology, industrial engineering/technology, and mechanical engineering, physics, and systems engineering, while proportionately fewer earn degrees in

the computer and communications sciences (see Table 16). That likely reflects the region’s orientation

toward agriculture and heavy traditional industry. In general, Appalachia’s two-year schools are more

heavily specialized in a few disciplinary areas than the national average. Four principal disciplines

dominate: communications and computer sciences and technologies (50 percent of degrees granted in

1997/98); mechanical engineering, engineering physics, and systems engineering (28 percent); agricultural sciences and technology (11 percent); and industrial engineering and technology (5 percent).

Although communications and computer sciences/technology account for half of all technology-related degrees at two-year schools in the region, the share of students earning such degrees is well below

the national average of 61 percent.

Aggregated disciplinary area title

InstitutionsDegree 

completions

Pct 

share

US pct 

share*

Aerospace Engineering, Aviation Science, & Astrophysics 137 1,346 5.7 6.1

Agricultural Sciences & Technology 149 5,672 24.0 23.8

Basic Medical Science 131 2,286 9.7 8.2

Biochemistry & Biomedical Engineering 10 345 1.5 0.8

Botany, Biology, Bacteriology, & Biotechnology 9 119 0.5 0.5

Chemical Engineering & Technology 13 216 0.9 0.8

Communications & Computer Sciences & Technologies 15 168 0.7 1.5

Environmental Engineering & Controls 21 1,898 8.0 6.0

Forestry Science & Forestry Technology 55 666 2.8 2.5

Geological & Geophysical Engineering 6 126 0.5 0.3

Industrial Engineering & Technology 137 5,455 23.1 28.6

Materials Engineering & Science 64 2,756 11.7 10.9

Mathematics 32 1,245 5.3 3.6

Mechanical Engineering, Engineering Physics & Science, & Systems Engineering 52 712 3.0 3.4

Physics & Nuclear Engineering 80 625 2.6 2.8

TOTAL 23,635 100.0 100.0

Source: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System,

Completions survey, 1997-1998 and Consolidated survey, 1998. *Total US completions in disciplinary area as a share of all US 

completions for 4-year institutions. Disciplinary areas were defined by the authors as aggregates of related Classification of 

Instructional Programs (CIP) codes. Completions include any degrees or certification programs offered, whether 4 years or less in 

duration.

Table 15

Estimated degree completions, 1997/98, ARC 4-year colleges and universities

4-year public and private postsecondary educational institutions in 406-county ARC region
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 62

Figures 32 and 33 plot the spatial distribution of total 1997/98 degree completions by county. The

maps show two things: first, the location of two- and four-year institutions offering degrees in sciencerelated fields (only counties with at least one school are highlighted), and second, the quantity of

science and engineering degrees by location. While four-year schools are more evenly distributed

throughout the region than two-year schools on the whole, small concentrations of four-year institutions can still be identified (e.g., in Pennsylvania). The dominance of larger institutions such as Penn

State in Central Pennsylvania is also evident. Among two-year schools, the extensive programs in

North and South Carolina, and to a lesser extent Pennsylvania and Alabama, contrast sharply with the

very limited evidence of substantial degree programs in Tennessee, eastern Kentucky, and West Virginia. Indeed, the IPEDS completions data suggest that central Appalachia is relatively poorly served

by two- and four-year institutions offering degree programs in technology-related areas.

Many two- and four-year schools in Appalachia are below the national average in terms of “technology intensity,” or the ratio of technology-related degree completions to total degree completions.

Figures 34 and 35 plot technology intensity in percentage terms by county.38 Only counties at or above

Aggregated disciplinary area title

InstitutionsDegree 

completions

Pct 

share

US pct 

share*

Aerospace Engineering, Aviation Science, & Astrophysics 2 61 0.5 0.4

Agricultural Sciences & Technology 3 1,288 10.5 2.0

Basic Medical Science 0 0 0.0 0.0

Biochemistry & Biomedical Engineering 3 10 0.1 5.4

Botany, Biology, Bacteriology, & Biotechnology 6 28 0.2 2.3

Chemical Engineering & Technology 10 201 1.6 0.8

Communications & Computer Sciences & Technologies 139 6,168 50.4 60.8

Environmental Engineering & Controls 19 117 1.0 2.7

Forestry Science & Forestry Technology 8 77 0.6 0.3

Geological & Geophysical Engineering 3 103 0.8 0.8

Industrial Engineering & Technology 29 655 5.4 3.4

Materials Engineering & Science 1 12 0.1 0.0

Mathematics 5 16 0.1 0.8

Mechanical Engineering, Engineering Physics & Science, & Systems Engineering 71 3,480 28.4 18.9

Physics & Nuclear Engineering 4 23 0.2 1.3

TOTAL 12,239 100.0 100.0

Source: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System,

Completions survey, 1997-1998 and Consolidated survey, 1998. *Total US completions in disciplinary area as a share of all US 

completions for 2 year institutions. Disciplinary areas were defined by the authors as aggregates of related Classification of 

Instructional Programs (CIP) codes. Completions include any degrees or certification programs offered, whether 2-year or less in 

duration.

38. The measure is the ratio of total technology degrees to all degrees in county i, expressed as a percent, where

degree completions for all schools in the county are summed. Four-year (Figure 34) and two-year (Figure 35)

institutions are evaluated separately.

Table 16

Estimated degree completions, 1997/98, ARC 2-year colleges and institutes

2-year public and private postsecondary educational institutions in 406-county ARC region
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 63

Figure 32

Total degree completions by county, four-year universities and colleges, 1997/98

All technology-related fields

1-100

Total completions:

Map Legend

101-500

501-2,500

Over 2,500

ARC boundary

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 64

Figure 33

Total degree completions by county, two-year universities and institutes, 1997/98

All technology-related fields

1-100

Total completions:

Map Legend

101-500

501-2,500

Over 2,500

ARC boundary

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 65

Figure 34

Technology intensity, four-year universities and colleges, 1997/98

Technology degrees as percent share of total degrees

6.6-10.0%

Ratio of technology to

Total completions

Map Legend

10.1-25.0%

25.1-50.0%

ARC boundary

U.S. average is 6.6 percent.

Analysis buffer
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 66

Figure 35

Technology intensity, two-year universities and institutes, 1997/98

Technology degrees as percent share of total degrees

ARC boundary

Analysis buffer

3.4-5.0%

Ratio of technology to

Total completions

Map Legend

5.1-25.0%

25.1-45.9%

U.S. average is 3.4 percent.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 67

the national average are depicted. Technology-intensive two-year schools are concentrated primarily in

Pennsylvania, Virginia, North and South Carolina, West Virginia, and Alabama. Appalachian Tennessee, Kentucky, and northern Georgia have few, if any, technology intensive two-year schools. Again,

technology-intensive four-year schools are somewhat more evenly distributed, though such institutions

are again concentrated somewhat in Pennsylvania.

3.3 Summary

This section examined the competitive strength and sub-regional geographic distribution of the two

major components of Appalachia’s knowledge infrastructure: its performers of R&D and its institutions

of higher education. The former consist of eighteen research universities and a limited number of other

research institutions (such as federal government laboratories), non-profit R&D organizations, statesponsored technology agencies, and private sector businesses engaged in innovation. The latter are the

over 250 universities, colleges, and community colleges offering degree programs and specialized training

in fifteen science and engineering-related fields.

We demonstrate that there are clearly a number of nationally competitive R&D strengths within

the ARC region. They span a number of technology areas, including all major disciplines of engineering, computer science, mathematics and statistics, and the agricultural sciences. Geographically, most

of the R&D strength is located at around fifteen nodes anchored by major research universities, as well

as near large federal government labs in Oak Ridge and Huntsville. Unsurprisingly, the large majority

of SBIR/STTR/ATP award winners are located within or close to those same nodes. Only state-funded

R&D assets aimed at providing direct services to technology-oriented businesses or to individuals seeking advanced training are broadly distributed in the region. The principal R&D nodes tend to have

strengths within a number of technology areas, rather than being highly specialized. Thus, even though

Huntsville’s principal strength is in aerospace, there are also notable strengths in other disciplines

including industrial engineering, chemical engineering, and computer science. The following are specific findings from this section:

 Based on national ratings of faculty quality, there are six major nodes of highest

competitive strength in the universities in Appalachia (either within or adjacent to

the ARC region): Cornell (Ithaca NY), Carnegie-Mellon (Pittsburgh PA), Georgia

Tech (Atlanta GA), Emory University (Decatur, Georgia), Penn State (State College PA), and Virginia Tech (Blacksburg, VA).

 While faculty quality rankings indicate that the greatest competitive strengths among

Appalachian research universities as a group are oriented toward the physical sciences and engineering rather than the biological and medical sciences, national

R&D funding rankings suggests some Appalachian universities are actually very

strong in the life sciences disciplines.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 68

 A number of Appalachian universities boast programs that are rising steadily in

the national rankings (based on R&D funding and graduate student enrollments).

The majority of such “emergent programs” are at Carnegie-Mellon, Georgia Tech,

Ohio, Penn State, University of Kentucky, Virginia Tech, West Virginia University, and Mississippi State.

 SBIR/STTR/ATP award winners tend to be concentrated in a relatively small number of places, namely Huntsville, Blacksburg, Pittsburgh, State College, and Ithaca,

with smaller concentrations in Birmingham and Knoxville/Oak Ridge. The nature

of those federal programs tends to favor locations nearby universities or labs.

 Industrial machinery is easily the most common technology focus among the some

220 SBIR/STTR/ATP awards in fiscal year 2000. That may simply reflect the dominance of the region’s traditional industry sectors (textiles, apparel, furniture, and

metals).

 There are a great many state-funded technology assistance, transfer, and modernization programs and agencies in the ARC region. Comparatively few, however,

are focused on technology areas that are projected to drive significant growth in

the next decade: information technology and biotechnology.

 Somewhat surprisingly, Appalachian four-year universities and colleges grant proportionately fewer degrees in industrial engineering and related sciences than their

counterparts elsewhere in the U.S. Indeed, based on degree completions in 1997/

98, Appalachian universities and colleges grant proportionately more degrees in

basic medical science, environmental engineering and controls, mathematics, materials engineering and science, and biochemistry and biomedical engineering than

national averages would predict.

 The share of annual degrees awarded in the computer and communications sciences by two-year colleges and institutes in Appalachia is substantially below the

national average. That may reflect the comparatively limited job opportunities in

IT-related industries in the region (a problem of labor demand) or an inadequate

training network for an emerging industry (a problem of labor supply).

 Two- and four-year higher education institutions with an emphasis in technologyrelated areas are comparatively few in central Appalachia (namely Tennessee,

Kentucky, and much of West Virginia).
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 69

4 Technology Clusters in the ARC Region

By combining the information on the spatial concentration of industrial and occupational employment

with data on R&D performers (research universities and federal labs), private sector innovative activity

(as proxied by patents and participation in the SBIR/STTR/ATP programs), state technology services

agencies, and educational infrastructure, we can identify Appalachian sub-regions characterized by

joint industrial and research/innovation strength in specific technology areas. We call such sub-regions

Appalachia’s technology clusters. We explicitly define a cluster, in this case, as a localized concentration of joint industrial and innovative activity.39 This section first outlines the standards we used to

combine the results from multiple indicators to identify a reduced set of sub-regions. It then discusses

general findings, policy implications, and avenues for further research.

4.1 Identifying Technology Clusters

To identify specific technology clusters, we require a means of evaluating the degree of overlap between geographic distributions of technology-related industry (including S&T workers) described in

Section 2 and the information on leading university research programs, corporate patenting, SBIR/

STTR/ATP grants, technology agencies, and higher education infrastructure analyzed in Section 3. Our

first step was to use judgment to establish concordances between the set of technology-intensive valuechains described in Section 2 and the university R&D disciplines, degree completion disciplines, and

S&T occupational categories utilized in Section 3. As one example, we matched the following disciplines and occupations to the chemicals and plastics value-chain: the chemical engineering, materials

engineering, and chemistry R&D disciplines; the chemical engineering and technology; materials engineering and science degree completions disciplines; and the chemists/chemical engineers and materials

engineers/scientists occupations. Table 17 reports the full set of technology area concordances.

39. There are many valid ways of defining industry clusters, with the appropriateness of a given definition depending primarily on research and policy concerns at hand. See the discussion in Bergman and Feser (1999).
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 70

To develop rankings of Appalachian universities by technology category rather than discipline,

we then averaged the rankings across the disciplines within each technology area. For example, Cornell

University’s rank for sponsored research relevant to the chemicals and plastics industry is the arithmetic average of its ranks for chemical engineering, materials engineering, and chemistry. We produced rankings by technology area for three indicators: sponsored research funding, faculty quality,

and number of enrolled graduate students.40

Given the rankings on the three indicators, we identified Tier 1 universities as those with an

average rank in the U.S. top twenty for at least two out of the three measures. Tier 2 schools are those

with: a) an average rank in the U.S. top twenty for research funding or faculty quality; b) an average

rank in the U.S. top forty for all three measures; or c) an average rank in the U.S. top twenty for number

of graduate students and a rank in the U.S. top forty for either (or both) faculty quality or research

Technology area University Disciplines Degree Completions Disciplines S&T Worker Categories

Chemicals and plastics Chemical engineering, materials 

engineering, chemistry

Chemical engineering & technology; 

materials engineering and science

Chemists & chemical engineers; 

materials engineers & scientists

IT and instruments Electrical engineering, mechanical 

engineering, materials engineering, 

physics, mathematics and statistics

Communications & computer 

sciences/technology; mechanical 

engineering, engineering physics & science, 

systems engineering

IT scientists, engineers, and 

programmers; electrical 

engineers & technicians

Industrial machinery Mechanical engineering, industrial 

engineering, physics

Mechanical engineering, engineering 

physics & science, systems engineering; 

Industrial engineering & technology

Industrial & mechanical 

engineers & technicians

Motor vehicles Electrical engineering, mechanical 

engineering, industrial engineering

Mechanical engineering, engineering 

physics & science, systems engineering; 

Industrial engineering & technology

Electrical engineers & 

technicians; industrial & 

mechanical engineers & 

technicians

Household appliances Electrical engineering, mechanical 

engineering, industrial engineering

Mechanical engineering, engineering 

physics & science, systems engineering

Electrical engineers & 

technicians

Aerospace Aerospace engineering, astronomy, 

geosciences, mathematics and statistics, 

computer science, physics

Aerospace engineering, aviation science & 

astrophysics; mathematics

Mathematicians, statisticians, 

and physicists

Communications 

services & software

Computer science, mathematics and 

statistics, geosciences

Communications & computer 

sciences/technology; mathematics

IT scientists, engineers, and 

programmers

Pharmaceuticals, 

medical technologies

Biological sciences, medical sciences, 

computer science

Biochemistry & biomedical engineering; 

botony, biology, bacteriology, & 

biotechnology; basic medical science

Biological scientists & 

technicians; medical scientists & 

engineers

Note: National Research Council discipline categories for faculty quality differed slightly from NSF categories, particularly in the medical and biological sciences. The 

NRC categories were aggregated to match the NSF classification to derive a uniform set of university disciplines.

40. Each measure indicates a different but complimentary dimension of university research competitiveness. In

the absence of a compelling rationale favoring one dimension over the other, we elected to weight each

indicator equally.

Table 17

Technology area concordances
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 71

funding. Our criteria effectively consider sponsored research and faculty quality as the leading barometers of a university’s research capacity and output. The results of the combined rankings are presented

in Table 18.

University research strengths by technology area in or immediately adjacent to the ARC region

are highly concentrated in a few institutions, namely Carnegie-Mellon, Cornell, Georgia Tech, and

Penn State. Virginia Tech boasts Tier 1 programs in two technology areas, while Tier 2 programs are

found at the University of Alabama at Huntsville, Clemson, and University of Tennessee at Knoxville.

Eight of the eighteen universities in the

study do not possess highly ranked research programs in any of the eight major

technology areas by our criteria, though some

have relatively strong individual disciplines

or disciplines of emerging strength (as reported in Section 3).

To identify areas of joint industrial

and innovative strength for each of the

eight technology areas, we used a geographic information system (GIS) to overlay multiple variables: technologyintensive value chain employment by

county, science and engineering occupational employment by metro area, Tier 1

and 2 research universities by city,

technology-related utility patent grants by

county, the location of state technology

programs, and SBIR/STTR/ATP award winners by county. We also mapped total degree completions in related fields for both

two-year and four-year institutions, although we focused on the presence of industry and innovative/R&D activity (rather

than educational programs) as the formal

criteria for identifying technology clusters.

We then visually inspected the maps along

University

Chemicals & plasticsIT & instrumentsIndustrial machineryMotor vehiclesAerospaceHousehold appliancesComm software & servicesPharm & med tech

U of Alabama at Birmingham

U of Alabama at Huntsville 22 2

Auburn U

Carnegie Mellon U 2 12122

Clemson U 2

Cornell U 11111111

Emory U 2

GA Institute of Technology 1111212

U of Georgia

U of Kentucky

Mississippi State U

U of Mississippi

Ohio U

Pennsylvania State 1111212

U of Pittsburgh 2

U of Tennessee at Knoxville 2

Virginia Polytechnic Institute 2 1 12

West Virginia U

Note: Based on evaluation of national rank on three measures: research 

funding, faculty quality (based on peer rankings), and number of gradute 

students. Universities were ranked on sixteen disciplines. Each discipline 

was assigned to one or more of the eight technology categories (see 

Appendix Table 8). Average rankings across the disciplines in the given 

technology area were then used to determine the institution's overall rank 

on the given measure. Tier 1 schools are those with an average rank in the 

U.S. top 20 for at least two out of the three measures. Tier 2 schools are 

those with: a) an average rank in the U.S. top 20 for research expenditures 

or faculty quality; or b) an average rank in the U.S. top 40 for all three 

measures; or c) an average rank in the U.S. top 20 for number of graduate 

students and a rank in the U.S. top 40 for either (or both) faculty quality or 

research expenditures.

Table 18

University R&D strengths by technology area

1st and 2nd tier strengths based on U.S. rank
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 72

Chemicals & plastics V P S U A Notes

Buffalo, Rochester, NY ✓✓✓

Ithaca and Binghamton, NY ✓✓✓✓✓ Cornell ranked as 1st tier in disciplines related to chemicals and plastics

Pittsburgh, PA ✓✓ ✓

Albany-Schenectady, NY ✓ ✓

Newburgh, NY, PA ✓✓✓

Cleveland-Canton, OH corridor ✓✓✓

State College, PA ✓ ✓✓

Reading/Allentown PA ✓✓✓

Wheeling, WV ✓✓ ✓

Charleston, WV ✓✓✓ Not a major strength of West Virginia University; Ohio University 

Parkersburg, WV ✓✓ ✓ (all campuses) ranked 16th in research dollars in chemical engineering

Cincinnati, OH ✓ ✓

Washington, DC ✓✓✓

Johnson City, TN ✓✓ ✓

Asheville, NC ✓ ✓

Greenville-Spartanburg, SC ✓✓✓

Chattanooga, TN ✓ ✓

Atlanta, GA ✓ ✓

Auburn, AL ✓✓✓

Huntsville, Decatur, AL ✓✓✓ Chemical engineering an emergent strength at UA-Huntsville; UA-Huntsville ranked 6th in 

number of graduate students in industrial engineering

Motor vehicles & related V P S U A Notes

Rochester, NY ✓✓✓

Syracuse, NY ✓ ✓

Binghamton, NY ✓✓✓✓

Scranton, PA ✓ ✓ Large two-year college programs in related fields

Central Pennsylvania ✓✓✓✓

Reading, PA ✓ ✓ Large two-year college programs in related fields

Altoona, PA ✓ ✓

Cleveland, Akron, OH ✓✓✓

Mansfield, OH ✓ ✓

Cincinnati, OH ✓ ✓

Harrisburg, PA ✓✓ ✓

Blacksburg, VA ✓

Johnson City, TN ✓ ✓

Greenville-Spartanburg, SC ✓✓✓✓

Huntsville, AL ✓ UA-Huntsville ranked 6th in number of graduate students in industrial engineering; also a 

2nd tier strength in disciplines related to motor vehicles

with a set of detailed cross-tabulations to detect a total of 100 sub-regions where both high tech industry

and related R&D and innovation activity are in evidence. The results are summarized in Table 19 and

Figures 36–43.

Our analysis indicated that heavy spatial concentrations of degree completions for four-year colleges and universities tend to coincide with the locations of major research universities. That is

unsurprising given that the research universities are some of the largest educators in the region. Therefore, in Figures 36–43 we depict only degree completions for two-year higher education institutions.

That has the advantage of emphasizing synergies between the universities and the key applied education and training role of community colleges. To maintain readability in the face of multiple data layers,

Figures 36–43 do not depict the location of state technology agencies.

Table 19 continues next page

Table 19

Technology clusters in Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 73

Industrial Machinery V P S U A Notes

Buffalo, Rochester, NY ✓✓✓

Erie, PA ✓ ✓

Albany-Schenectady, NY ✓ ✓

Binghamton, NY ✓✓ ✓ Cornell a 1st tier university in related disciplines

State College, PA ✓ ✓ Penn State a 1st tier university in related disciplines

Reading, Allentown, PA ✓ ✓

Harrisburg, PA ✓ ✓

Pittsburgh, PA ✓✓ ✓ Carnegie-Mellon an emerging strength in mechanical and materials engineering

Northeastern Ohio ✓✓✓

Mansfield, OH ✓✓✓

Altoona, PA ✓ ✓

Johnstown, PA ✓✓ ✓

Lynchburg, VA ✓ ✓ Virginia Tech an emerging strength in electrical engineering

Cincinnati, Middleton, OH ✓✓ ✓

Greensboro, NC ✓ ✓

Statesville, NC ✓ ✓

Charlotte, NC ✓ ✓

Nashville-Davidson, TN ✓ ✓

Asheville, NC ✓ ✓

Greenville-Spartanburg, SC ✓✓✓

Atlanta ✓✓ ✓ Georgia Tech a 1st tier university in related disciplines

Huntsville, AL ✓✓✓ Weak industry employment but concentrated related occupations and 2nd tier university

Starkville, Columbus, MS ✓✓ ✓

Information technology & instruments V P S U A Notes

Rochester, NY ✓ ✓ Weak industry employment; large community college programs in related fields

Binghamton, NY ✓✓✓✓✓ Cornell ranked as 1st tier university in related disciplines

Poughkeepsie, NY ✓ ✓

State College, PA ✓✓✓✓

Washington, DC ✓ ✓ Very large community college programs in related fields

Columbus, OH ✓✓✓ ✓ Community college programs in related fields

Lynchburg-Blacksburg, VA ✓ ✓✓ Weak industry employment in Blacksburg; community college programs in related fields

Atlanta, GA ✓✓✓✓✓ Georgia Tech a first-tier university in related disciplines

Huntsville, AL ✓ ✓ University of Alabama-Huntsville an emerging strength in computer science

Communications services & software V P S U A Notes

Ithaca, NY ✓✓ ✓✓ Cornell a 1st tier strength in related disciplines

Albany-Schenectady, NY ✓ ✓

Newburgh-Poughkeepsie, NY ✓ ✓

State College, PA ✓ ✓✓ Penn State a 2nd tier strength

Harrisburg, PA ✓ ✓

Pittsburgh, PA ✓ ✓✓ CMU a 2nd tier strength; NSF Data Storage Center; Software Engineering Institute

Columbus, OH ✓ ✓ Large two-year college programs in related fields

Washington, DC ✓✓✓ Large two-year college programs in related fields

Blacksburg, VA ✓ ✓✓

Atlanta, GA ✓ ✓✓✓ Georgia Tech a 2nd tier strength in related discipline; two-year college programs

Huntsville, AL ✓✓✓ ✓ University of Alabama-Huntsville an emerging strength in computer science

Table 19 continues next page

Table 19 continued

Technology clusters in Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 74

Aerospace V P S U A Notes

Erie, PA ✓ ✓

Elmira, Ithaca, NY ✓✓ ✓ Cornell a 1st tier strength in related disciplines

Cleveland, Akron, OH ✓ ✓

Pittsburgh, PA ✓✓✓✓✓ CMU a 2nd tier strength in related disciplines

Washington, DC ✓ ✓

Cincinnati, Middleton, OH ✓ ✓

Atlanta, GA ✓ ✓✓ Georgia Tech a 2nd tier strength in related disciplines

Manchester, TN ✓ ✓ Nearby Arnold Air Force Base

Huntsville, AL ✓ ✓✓ University of Alabama-Huntsville an emerging strength in geosciences; Army Space and 

Missile Defense Command, Marshall Space Flight Center, Army Aviation and Missile 

Command, Army Redstone Technical Test Center, Army Redstone Missile Research 

Development and Engineering Center

Household appliances V P S U A Notes

Cleveland, Akron, OH ✓ ✓

Middleton, OH ✓ ✓

Greenville-Spartanburg, SC ✓ ✓

Huntsville, AL ✓ ✓✓ University of Alabama-Huntsville a 2nd tier strength in related disciplines

Pharmaceuticals & med technologies V P S U A Notes

Rochester, NY ✓ ✓

Ithaca, NY ✓ ✓✓ Cornell a 1st tier strength in related disciplines

Chenango County, NY ✓ ✓

Newburgh, NY ✓ ✓

Reading, PA ✓ ✓

Pittsburgh, PA ✓ ✓✓ CMU and Pitt 2nd tier strengths; Pitt an emerging strength biological sciences

Washington, DC ✓✓✓

Cincinnati, OH ✓

Birmingham, AL ✓✓✓ ✓

Legend and Notes: V = Concentration of employment in pertinent value-chain (either significant G or location quotient > 1.1, 1998). P = Concentration of patenting activity 

in related technology areas (either significant G or location quotient > 1.25, 1999). S = Concentration of scientists, engineers, and technicians in related fields (location 

quotient > 1.25; data available for metro areas only, 1999). U = Presence of a research university with related programs in 1st or 2nd tier based on national ranks (various 

years; see text for ranking criteria). A = One or more SBIR/STTR/ATP award winners in Fiscal Year 2000. Locations indicate general vicinity only. See text for data sources and 

general methodology.

Table 19 continued

Technology clusters in Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 75

The following results should be interpreted with care and especially with a mind toward the

study’s specific objectives. We adopted a fairly liberal standard for designating clusters: at least some

evidence of joint industrial and innovative activity in the same vicinity. Given the less-developed nature of much of the Appalachian region, we sought to avoid overlooking sub-regions with potential for

expansion in various technology areas. Certainly, some identified clusters are much stronger than others. An understanding of differences in the relative depth of clusters in various areas can be derived

from Table 19, which indicates the types of technology activity found in each sub-region.

More generally, the measurement of technology-related industrial activity and innovative output

(by industries, universities, and other research performers) is hampered both by limited data and the

complexity of the technology sector itself. The problem is compounded when the goal is to isolate

localized, sub-state geographic concentrations of such activity over a broad and diverse 406-county

area. Data and measurement limitations include, among other things, industrial classification schemes

that fail to properly characterize the activities of individual businesses; the lack of consistent sub-state

data for indicators such as value-added and productivity; inexact concordances between patent, disciplinary, and industrial technology areas; and the diversity of the technology sector itself, which mitigates against adhering to a narrow set of technology categories. Some smaller and more focused

technology-related strengths in the region are undoubtedly missed when industries and programs are

aggregated into a smaller set of technology areas.

At the same time, a methodology that is consistent across places and sectors is precisely what

makes it possible to define technology clusters that are legitimate strengths in the U.S. economy from

the perspective of industrial, academic, and federal/state program size and performance. The adoption

of relatively narrow and self-contained definitions and the utilization of transparent complimentary

analytical techniques (e.g., input-output, spatial statistics, and university rankings), while not without

costs, is what permits the systematic evaluation of technology-related activity in and nearby the ARC

region against a national benchmark.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 76

Cincinnati

Charleston

Huntsville,

Decatur

Erie, Cleveland, Akron

Reading, Allentown

Newburgh

Buffalo, Rochester

State College

Binghamton

AlbanySchenectady

Washington, DC

Greenville, Spartanburg

Johnson City

Asheville

Parkersburg

Wheeling

Pittsburgh

Atlanta

Chattanooga

Auburn

GA Tech

Penn State

Cornell

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All indicators

are specific to technology area.

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

=1-3 SBIR/STTR/ATP awards (scaled)

Figure 36

Technology clusters: Chemicals and plastics
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 77

Rochester

Reading

Cincinnati

Cleveland, Akron

Huntsville

Mansfield

Syracuse

Greenville, Spartanburg

Johnson City

Harrisburg

Penn

State

Cornell

Central PA

Altoona

Blacksburg

Binghamton

Carnegie

Mellon

U. of Alabama, 

Huntsville

GA Tech

Virginia Tech

Scranton

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award

Figure 37

Technology clusters: Motor vehicles and related
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 78

Buffalo, Rochester

AlbanySchenectady

Reading,

Allentown

Cincinnati,

Middleton

Cleveland, Canton,

Akron, Youngstown

Greenville-Spartanburg

Lynchburg

Binghamton

Johnstown

Erie

Pittsburgh

Mansfield

Charlotte

Asheville

NashvilleDavidson

Harrisburg

U. of Alabama, 

Huntsville

Penn

State

Cornell

U. of Tennessee,

Knoxville

Greensboro

Statesville

Atlanta

Starkville,

Columbus

Huntsville

Altoona

State College

GA Tech

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award

Figure 38

Technology clusters: Industrial machinery
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 79

Huntsville

Binghamton

Columbus

Atlanta

Rochester

Washington, DC

Lynchburg

Poughkeepsie

State College

Penn

State

Cornell

Carnegie

Mellon

Virginia

Polytechnic

GA Tech

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

Figure 39

Technology clusters: Information technology and instruments

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 80

AlbanySchenectady

Huntsville

Atlanta

Washington, DC

Columbus Harrisburg

Newburgh,

Poughkeepsie

Ithaca

Virginia

Polytechnic

GA Tech

Penn

State

Cornell

Carnegie

Mellon

State College

Pittsburgh

Blacksburg

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

Figure 40

Technology clusters: Communications services and software

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 81

4.2 Findings

While there is no need to discuss every cluster in Table 19 individually, there are several general

findings that emerge from the analysis. First, Appalachia’s principal localized technology-related

strengths at the present time are in three major areas: chemicals/plastics, industrial machinery, and

motor vehicles and related industries.41 Those three traditional “sectors” account for 58 of the 100

clusters identified. Only four to eleven localized clusters could be found for each of the remaining six

technology areas. Moreover, in the remaining six technology areas, the Washington, DC, Huntsville,

Pittsburgh, Atlanta, and Ithaca/Binghamton regions account for eighteen of the 42 clusters identified.

Second, the distribution of clusters throughout Appalachia is highly uneven. Nearly half (45 in

total) of the region’s technology clusters are located in the northern third of the region (New York,

Pennsylvania, and northern Ohio). Only nineteen clusters were identified for central Appalachia (an

area that includes southern Ohio, West Virginia, Virginia, and Kentucky), with Cincinnati and Washington, DC accounting for nine of those nineteen. In the southern third of the region, Atlanta, GreenvilleSpartanburg, and Huntsville account for sixteen of 29 clusters identified. The geography of clustering

in the region is a function of both the general historical distribution of industrial activity as well as the

limited presence of leading universities in central and southern Appalachia. The distribution of federal

grants (e.g., SBIR/STTR/ATP) also tends to favor the north, especially if grants in the Huntsville area

(originating from organizations linked to large area federal labs and defense installations) are excluded.

Third, the uneven geography of the clusters in the region varies substantially by technology area.

The chemicals/plastics and information technology/instruments clusters are relatively evenly distributed amongst the northern, central, and southern thirds of the region. Industrial machinery, on the other

hand, is nearly exclusively a northern and southern strength. Indeed, there are two large-scale dominant

concentrations of industrial machinery activity in the region: along the northern ARC border in the

states of Ohio and New York and extending over much of Pennsylvania, and along the Interstate 85

corridor of North Carolina, South Carolina, and Georgia. Other clusters are most common in the north:

communications services and software, aerospace, and pharmaceuticals and medical technologies.

41. It is important to note that the specific geography of the clusters is inexact. Modifiable areal unit problems

and limitations in individual measures limit our capacity to isolate the exact boundaries of concentrated

activity. That is why we include multiple measures (location quotients, G statistics) and units of analyses

(metropolitan areas, counties, and ZIP codes). We have focused on locations where results from the different

indicators and units of analysis tend to overlap. It follows that our areal labels in Table 19 and in Figures 36–

43 describe only the general vicinity of given clusters and should not be interpreted narrowly or exclusively

(e.g., most of the clusters labeled as “Pittsburgh” extend across the greater Pittsburgh region).
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 82

Elmira,

Ithaca

Huntsville

Atlanta

Washington, DC

Pittsburgh

Cincinnati,

Middleton

Cleveland, Akron

Erie

GA Tech

Penn

State

Cornell

Carnegie

Mellon

Manchester

Arnold

AFB

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

Figure 41

Technology clusters: Aerospace

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 83

Cleveland, Akron

Middleton

GA Tech

Penn

State

Cornell

Carnegie

Mellon

Virginia

Polytechnic

U. of Alabama, 

Huntsville

Clemson

Greenville-Spartanburg

Huntsville

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

Figure 42

Technology clusters: Household Appliances

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 84

Cincinnati

Rochester

Reading

Washington, DC

Newburgh

Birmingham

Emory

Carnegie

Mellon

U. of Pittsburgh

Cornell

Pittsburgh

Chenango

Ithaca

Concentrations of both production (value-chain or S&T

occupational employment) and innovation (patents, ranked

universities, or federal innovation grants) are labeled. All

indicators are specific to technology area.

Figure 43

Technology clusters: Pharmaceuticals and medical technologies

ARC boundary

Map Legend

Sig. emp. Gi or LQ> 1.1, counties

Sig. patent Gi or LQ > 1.25, counties

Analysis buffer

Metro area, S&T workers LQ >1.25

Research universities, 1st Tier

Research universities, 2nd Tier

Two-year college completions, 1997/98

100 - 249 250 - 749 > 750

=1 SBIR/STTR/ATP award
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 85

Fourth, just over half of the technology clusters in the region are located on the periphery and are

anchored in core metropolitan centers outside the region (such as Cincinnati, Atlanta, and Washington,

DC). There are few predominantly rural clusters, as is expected given a methodology that essentially

considers both relative and absolute size as barometers of a cluster’s strength.42 The following summarizes findings for each technology area, with an emphasis on identifying the clusters of greatest competitive strength.

 Chemicals and plastics: Particularly strong clusters are in the areas of Binghamton

and Ithaca, Newburgh, Reading/Allentown, Cleveland and Akron, Charleston,

Greenville-Spartanburg, and Auburn, AL. State College, anchored by R&D activity at Penn State, is another significant area of chemicals and related activity.

 Motor vehicles and related: Strongest clusters are in Rochester, Binghamton, Cleveland and Akron, and Greenville-Spartanburg. Most industrial employment in motor vehicles and related supplier industries is situated along the border of the region and tracks Interstates 71 and 75 through Ohio, Kentucky, and Tennessee. In

this cluster, the location of industry activity is coincident with innovative activity

only infrequently.

 Industrial machinery: Strongest clusters are in Buffalo and Rochester, northeastern Ohio, Mansfield, and Greenville-Spartanburg. Lynchburg and Cincinnati are

the only two clusters identified in central Appalachia.

 Information technology and instruments: Strongest clusters are in Binghamton

(birthplace of IBM), State College, Washington, Atlanta, and Huntsville. Community colleges provide substantial training in related fields, particularly in Washington, DC, eastern Pennsylvania, northern and central Ohio, and Pittsburgh. Overall,

the region’s knowledge infrastructure in information technology is considerably

stronger than its industrial base.

 Communications services and software: Strongest clusters are in Washington, DC,

Atlanta, and Huntsville. As in the case of information technology, the industrial

component of the cluster is much weaker than the knowledge and innovation

component.

 Aerospace: Strongest clusters are in Pittsburgh, Atlanta, and Huntsville. Washington, DC boasts a heavy complement of scientists and engineers in related occupations but a comparatively modest industry concentration, perhaps reflecting the

dominance of federal government activity (e.g., defense) in the area.

 Household appliances: Very little evidence of clustering in Appalachia; leading

concentrations in Cleveland and Akron, Huntsville, and Greenville-Spartanburg.

42. It is important to emphasize as well that the current study does not consider the degree to which peripheral

Appalachian communities actually do enjoy spillovers from metropolitan clusters located adjacent to the

ARC region. However, the analysis in this study — especially that in Chapter 2 — can identify candidates for

additional research focused on that question.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 86

 Pharmaceuticals and medical technologies: Dominant clusters are near Ithaca and

Chenango County, NY, Pittsburgh, Washington, DC, and Birmingham. There is a

substantial concentration of related industry employment in Huntsville but a weak

supporting knowledge infrastructure.

4.3 Policy Implications and Guides

This study has identified 100 sub-regional concentrations of technology-related economic activity and

innovation within and immediately adjacent to the 406-county ARC region. Many of the clusters are in

traditional manufacturing (chemicals, motor vehicles, and industrial machinery). Overall, we found

that Appalachia’s industrial base is oriented toward high tech industries of moderate technology-intensity. The most technology-intensive industries — including information technology, software, aerospace, and scientific instruments — are under-represented in the region relative to the national average

industry mix. Likewise, the joint spatial clustering of business and innovation/R&D in some very hightech sectors such as information technology, software, and aerospace is limited. While some Appalachian universities boast significant existing or emerging R&D strengths in science and engineering

disciplines, often those universities are not located nearby significant concentrations of industrial employment in related sectors. Likewise, while Appalachia has its share of federal laboratories and other

non-university R&D institutions, they are not always spatially coincident with the technology-oriented

industrial base.

Furthermore, a great many of the region’s clusters are located on its periphery. The ARC region’s

current high-tech prospects are therefore heavily dependent on spillover (or “spread”) effects from

neighboring cities and metropolitan areas. Unfortunately, those spillover effects are neither certain nor

necessarily positive. High-tech concentrations in border metro areas such as Washington, DC, Cincinnati, Columbus, and Atlanta may draw away talented graduates from Appalachia’s colleges and universities, leaving the region without the human capital base necessary to fuel technology-related growth.

Given the power of first mover advantages and subsequent agglomeration economies common to technology-based industries, the prospect of negative geographic spillover (or “backwash”) effects from

larger neighboring jurisdictions is a very real one. Backwash effects result when growth in urban centers drains human and financial resources from peripheral regions.

What should regional policymakers do with the extensive information on Appalachia’s technology clusters that this report provides? How can technology clusters in Appalachia be nurtured and

expanded? The concept of a technology cluster — a joint concentration of industrial production and

innovative activity — suggests three principal avenues of intervention: targeting cluster sectors for

growth and expansion by entrepreneurship and recruitment programs (addressing the business component of clusters); improving research and education capabilities in scientific and technical fields (the
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 87

knowledge infrastructure component of clusters); and leveraging productivity-enhancing agglomeration economies and knowledge spillovers shared by cluster firms and supporting institutions (usually

by maximizing opportunities for collaboration, learning, networking, joint problem-solving, and

the like).

4.3.1 Industrial Targeting

One of the most common and direct applications of the cluster concept is the application of conventional economic development strategies (especially recruitment and entrepreneurship programs) to underdeveloped elements of industry clusters (Anderson 1994). Cities and states in the ARC region can

subject each individual technology cluster identified in this report to further detailed analysis to determine that cluster’s underlying industry mix, its recent pattern of growth and decline by sector, and the

growth prospects of related industries that are under-represented or entirely absent. Promising sectors

can then be evaluated for feasibility as development targets based on their typical location requirements (in terms of infrastructure, workforce, market, input supply, amenities, and environmental impact). The idea is to implement a business development strategy that plays to — and expands — the

region’s demonstrated strengths in production and R&D, thereby increasing the complement of higher

wage, technology-oriented activity.

4.3.2 Knowledge Infrastructure

Another area of public sector intervention is the development of a high quality knowledge infrastructure. What characterizes technology clusters is not only high-tech businesses, but also the presence of

important supporting institutions such as research universities, teaching universities and community

colleges, and non-profit and private-sector contract research houses and laboratories. DeVol (2000, p.

34) argues that “research centers and institutions are indisputably the most important factor in incubating high-tech industries.” The concept of clusters has piqued the interest of state, regional, and federal

development agencies because it implies clear avenues for policy in areas in which the public sector

has traditionally, and often very successfully, engaged. The finest research and teaching universities in

the country — whether private or public — owe a good part of their success to federal and/or state

funding, the federal government has long been a major supporter of basic research, and many states are

becoming direct players in the technology arena by establishing centers for biotechnology, information

technology, electronics, and other areas of applied research (Jankowski 1999, Schacht 2002). Given the

limited success of efforts to recruit relocating businesses (high-tech or otherwise), governments are

increasingly attempting to aid the growth of technology clusters by doing what they have traditionally

done well: support basic research, education, and training.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 88

That is not to argue that government support for research and technology-oriented education and

training in a specific region is guaranteed to generate or expand a technology cluster with dynamic

high-tech, high wage companies at its core. Exactly how to implement such a strategy is still unclear

and much research remains to be done both on the link between research and education and job creation

and on the rationale for government support for business R&D (e.g., see Tassey 1999; Wallsten 2000b;

Wallsten 2000a). Most states are currently in various stages of policy experimentation, with some focusing on university technology transfer, others establishing “centers of excellence” in specific areas

of research, and still others funneling resources into applied science and engineering training at the

community college level. But the attractiveness of such strategies, even in the face of uncertainty with

regard to efficacy, is explained by their potential to yield a broad range of benefits with different

degrees of certainty. The establishment of a leading research focus area (or “center of excellence”)

within a university or non-profit organization, for example, is a benefit aside from its potential to

attract companies or spin off new business ventures. Likewise, education and training yield civic,

social, and quality of life benefits apart from the immediate connection between quality human capital

and business investment. Thus the pursuit of technology clusters offers the prospect of a more diverse

portfolio of social outcomes and benefits than conventional business recruitment and marketing strategies.43

Cities and states in the ARC region should use the findings in this report to identify investments in

knowledge infrastructure that will do two things: first, ensure that there is a sufficiently skilled labor

force for technology-related industrial growth; and, second, maximize complementarities between innovation and industrial competencies. The workforce skills question can be addressed by determining

whether university and community college programs are meeting the needs of technology sectors in

identified clusters within specific Appalachian sub-regions. Given the narrow requirements of many

technology businesses, a case-by-case analysis is necessary as a follow-on to our general assessment.

Synergies between the industrial and innovation components of the clusters can be fostered by strengthening university or non-profit R&D strengths in disciplines that dovetail with growing technology sectors. Again, the first step is to take the technology clusters identified in this document and break them

down further into much narrower areas of industrial and R&D strength.

43. The logic presumes that the given investment, in this case an engineering school, is pursued based on criteria

apart from — or at least in conjunction with — business creation objectives. There is a very real risk that

government will over-supply research and education in its effort to create technology jobs. A partial example

of this pitfall is documented by Luger and Goldstein (1991) in an analysis of the university research park

craze of the 1980s.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 89

4.3.3 Leveraging Spillovers and Agglomeration Economies

A third area of development policy intervention implied by the cluster concept is the promotion or

leveraging of productivity-enhancing spillovers and economies shared by the technology businesses at

the core of each cluster. In point of fact, aside from promoting the growth of the cluster to encourage

external economies of scale, appropriate policy options are limited to establishing venues or mechanisms for business collaboration and information exchange. Cities or states can encourage the creation

of a trade association or other private sector organization charged with defending and promoting the

shared interests of firms in a given cluster. Typically, such organizations also help market the region as

a location for related businesses, hold networking events and conferences, and provide a natural standing venue for businesses to bring infrastructure, workforce development, regulation, and taxation concerns to the attention of public agencies, universities, and community colleges. Absolutely essential to

the success and efficacy of such organizations is a clear articulation of the benefits firms can gain —

even if they are direct competitors — by collaboration on at least some issues (e.g., regulatory reform,

public infrastructure, etc; see Dalsgaard 2001). A common thread in the research literature to date is

that firms rarely know they are part of clusters, let alone that they benefit from efforts to further develop the same.

4.4 Further Research

This study provides only the broadest picture of the regional distribution and orientation of Appalachia’s

technology-related assets and activities. A number of important issues with respect to the proper formulation of economic development policy in Appalachia remain unaddressed. Possible avenues for

further research that builds on and expands the findings in this report include:

 The question of whether Appalachian sub-regions with a strong joint complement

of industrial and innovative activity are growing faster — in income, employment,

output, and/or productivity terms — than those without a strong knowledge infrastructure component. Some studies (e.g., O’Malley and Van Egeraat 2000) have

found little evidence of a strong positive relationship between clustering and manufacturing growth, implying that public policies aiming to develop clusters will not

yield significant growth impacts.

 The net spillovers impact of border technology clusters that are anchored outside

the ARC region. Information on the migration trends of graduates from ARC universities, the location patterns of spin-offs from technology businesses and universities in the region, and cross-border linkages among firms in border clusters, while

difficult to assemble, would provide a critical understanding of the likely influence

of border cluster development on the economic prospects of Appalachia itself.

 The functional and organizational differences among otherwise similar technology clusters in Appalachia and the implications of those differences for the net
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 90

economic impact of technology clusters. Some clusters may be dominated by multilocational firms headquartered outside the region while others may be indigenously

based. Similarly, some clusters — the automotive cluster emerging in GreenvilleSpartanburg — may be dominated by foreign-owned companies. Locally-based

cluster companies may be more likely to generate spin-offs within the region, as

well as link more closely with the research efforts of Appalachian universities and

labs, therefore generating more significant economic impacts in the long-run.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 91

References

Amrhein, C G. 1995. Searching for the elusive aggregation effect: Evidence from statistical simulations.

Environment and Planning A 27: 105-19.

Anderson, G. 1994. Industry clustering for economic development. Economic Development Review: 26-32.

Atkinson, R D and R H Court. 1998. The New Economy Index. Progressive Policy Institute, Washington, DC.

AUTM. 1991. AUTM Licensing Survey: Fiscal Year 1991. Association of University Technology Managers,

Inc., Northbrook, IL.

AUTM. 1995. AUTM Licensing Survey: Fiscal Year 1995. Association of University Technology Managers,

Inc., Northbrook, IL.

AUTM. 1999. AUTM Licensing Survey: Fiscal Year 1999. Association of University Technology Managers,

Inc., Northbrook, IL.

Bergman, E M and E J Feser. 1999. Industrial and Regional Clusters: Concepts and Comparative Applications. Morganton, WV: Regional Research Institute, West Virginia University. http://www.rri.wvu.edu/

regscweb.htm.

BLS. 2001. Occupational Employment and Wages, 1999. Bureau of Labor Statistics, U.S. Department of

Labor, Washington, DC.

Bozeman, B and M Crow. 1991. Technology transfer from U.S. Government and university R&D laboratories.

Technovation 11: 231-45.

Chrisman, J J, T Hynes and S Fraser. 1995. Faculty entrepreneurship and economic development: The case of

the University of Calgary. Journal of Business Venturing 10: 267-81.

Coburn, C M and D Berglund. 1995. Partnerships: A Compendium of State and Federal Cooperative Technology Programs. Battelle Memorial Institute, Columbus, OH.

Cortright, J. 2001. New Growth Theory, Technology and Learning: A Practitioner’s Guide. U.S. Economic

Development Administration, Washington, DC.

Coursey, D and B Bozeman. 1993. University-industry cooperative R&D: Issues and roles in state economic

development. In Economic Development Strategies for State and Local Governments, edited by R. P. M. a.

E. J. Ottensmeyer, 13-25. Chicago: Nelson-Hall.

Czamanski, S. 1974. Study of Clustering of Industries. Institute of Public Affairs, Dalhousie University,

Halifax, Canada.

Dalsgaard, M H. 2001. Danish cluster policy: Improving specific framework conditions. In Innovative Clusters: Drivers of National Innovation Systems, edited by P. den Hertog, E. M. Bergman and D. Charles, 347-

60. Paris: OECD.

Davis, S J, J C Haltiwanger and S Schuh. 1996. Job Creation and Destruction. Cambridge, MA: MIT Press.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 92

den Hertog, P, E M Bergman and D Charles, Eds. 2001. Innovative Clusters: Drivers of National Innovation

Systems. Paris: Organisation for Economic Cooperation and Development.

DeVol, R C. 2000. Blueprint for a High-Tech Cluster: The Case of the Microsystems Industry in the Southwest.

Milken Institute, Santa Monica, CA.

Feser, E, H Goldstein and M Luger. 1998. At the Crossroads: North Carolina’s Place in the Knowledge

Economy of the Twenty-First Century. North Carolina Board of Science and Technology, Raleigh, NC.

Feser, E J and S H Sweeney. 2002. Out-migration, depopulation and the geography of U.S. economic distress.

Forthcoming in International Regional Science Review.

Feser, E J, S H Sweeney and H C Renski. 2001. A descriptive analysis of discrete U.S. industrial complexes.

Working paper, Department of City and Regional Planning, UNC-Chapel Hill.

Fotheringham, A S and D W S Wong. 1991. The modifiable areal unit problem in multivariate statistical

analysis. Environment and Planning A 23: 1025-44.

Getis, A and J K Ord. 1992. The analysis of spatial association by use of distance statistics. Geographical

Analysis 24: 189-206.

Glaeser, E L. 2000. The new economics of urban and regional growth. In The Oxford Handbook of Economic

Geography, edited by G. L. Clark, M. P. Feldman and M. S. Gertler, 83-98. Oxford, UK: Oxford University

Press.

Goldberger, M L, B A Maher and P E Flattau. 1995. Research Doctorate Programs in the United States:

Continuity and Change. National Research Council, Washington, DC.

Griliches, Z. 1990. Patent statistics as economic indicators: A Survey. Journal of Economic Literature 28:

1661-707.

Grossman, G M and E Helpman. 1991. Innovation and Growth in the Global Economy. Cambridge, MA: MIT

Press.

Hecker, D. 1999. High-technology employment: A broader view. Monthly Labor Review (June): 18-28.

Jankowski, J E. 1999. What is the State Government Role in the R&D Enterprise? Division of Science Resources Studies, National Science Foundation, Washington, DC.

Krugman, P. 1995. Development, Geography, and Economic Theory. Cambridge, MA: MIT Press.

Lee, Y and R Gaertner. 1994. Technology transfer from university to industry: A large-scale experiment with

technology development and commercialization. Policy Studies Journal 22: 384-99.

Lucas, R E, Jr. 1988. On the mechanics of economic development. Journal of Monetary Economics 22: 3-42.

Luger, M and H Goldstein. 1997. What is the role public universities play in regional economic development?

In Dilemmas of Urban Economic Development, edited by R. D. Bingham and R. Mier, 104-34. Thousand

Oaks, CA: Sage.

Luger, M I and H A Goldstein. 1991. Technology in the Garden. Chapel Hill, NC: University of North Carolina

Press.

McCormick, A C. 2001. The Carnegie Classification of Institutions of Higher Education, 2000 Edition.

Carnegie Foundation for the Advancement of Teaching, Menlo Park, CA. http://

www.carnegiefoundation.org/Classification/index.htm.

NCACTs. 1995. Making Manufacturing and Technology Work for North Carolina. North Carolina Alliance for

Competitive Technologies, Research Triangle Park, NC.

Nelson, R R. 1996. The Sources of Economic Growth. Cambridge, MA: Harvard University Press.

O’Malley, E and C Van Egeraat. 2000. Industry clusters and Irish indigenous manufacturing: Limits of the

Porter view. Economic and Social Review 31: 55-79.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 93

OTP. 2000. The Dynamics of Technology-Based Economic Development: State Science and Technology

Indicators. Office of Technology Policy, Technology Administration, U.S. Department of Commerce,

Washington, DC.

Pivetz, T R, M A Searson and J R Spletzer. 2000. Measuring job flows and establishment flows with BLS

longitudinal establishment microdata. Working paper, U.S. Bureau of Labor Statistics, Washington, DC.

Pollak, M. 1999. Counting the S&E workforce: It’s not that easy. Issue Brief. Washington, DC, Division of

Science Resources Studies, National Science Foundation.

Porter, M E. 1990. The Competitive Advantage of Nations. New York: Free Press.

Porter, M E. 1998. Clusters and the new economics of competition. Harvard Business Review: 77-90.

Porter, M E. 2000. Location, competition, and economic development: Local clusters in a global economy.

Economic Development Quarterly 14: 15-34.

Rausch, L M. 1998. High-tech industries drive global economic activity. Issue Brief. Washington, DC, Division

of Science Resources Studies, National Science Foundation.

Romer, P M. 1986. Increasing returns and long-run growth. Journal of Political Economy 94: 1002-37.

Romer, P M. 1990. Endogenous technological change. Journal of Political Economy 98: s71- s100.

Saxenian, A. 1994. Regional Advantage: Culture and Competition in Silicon Valley and Route 128. Cambridge, MA: Harvard University Press.

Schacht, W H. 2002. Cooperative R&D: Federal Efforts to Promote Industrial Competitiveness. Congressional

Research Service, Washington, DC.

Solow, R M. 1956. A contribution to the theory of economic growth. Quarterly Journal of Economics 70: 65-94.

Solow, R M. 1957. Technical change and the aggregate production function. Review of Economics and Statistics 39: 214-31.

Tassey, G. 1999. R&D Trends in the U.S. Economy: Strategies and Policy Implications. National Institute of

Standards and Technology, Washington, DC.

Wallsten, S J. 2000a. The effects of government-industry R&D programs on private R&D: The case of the

Small Business Innovation Research program. RAND Journal of Economics 31: 82-100.

Wallsten, S J. 2000b. The R&D boondoggle. Regulation 23: 12-16.

White, S B, J F Zipp, W F McMahon, P D Reynolds, J D Osterman and L S Binkley. 1990. ES202: The data

base for local employment analysis. Economic Development Quarterly 4: 240-53.

Wirtz, R A. 2001. Chasing the tail of high-tech. The Region, September.

Wood, L and G Bischak. 1999. Progress and Challenges in Reducing Economic Distress in Appalachia: An

Analysis of National and Regional Trends Since 1960. Appalachian Regional Commission, Washington, DC.

Wrigley, N. 1995. Revisiting the modifiable areal unit problem and the ecological fallacy. In Diffusing Geography: Essays for Peter Haggett, edited by A. D. Cliff, P. R. Gould, A. G. Hoare and N. J. Thrift, 49-71.

Oxford, UK: Blackwell.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 94

Measures of Concentration

and Spatial Association

We apply two different indicators of spatial concentration to data on employment and patents by sector

and value-chain: the simple location quotient and the local G statistic (Gi). A location quotient is a

basic summary measure of relative size:

where e represents employment (or patents) in an Appalachian sub-region, E denotes U.S. employment

(or patents), i subscripts the areal unit of analysis (the county), j subscripts sector (or value-chain or

occupation), and t denotes total. A location quotient of 1.0 indicates that the share of activity in the

county matches the comparable share for the nation. Location quotients significantly above one (e.g.,

1.1 or higher in the case of industry employment, 1.25 or higher in the case of patent grants and occupational employment) indicate a specialization in the given category, i.e. that the given sub-region has a

larger share of activity than what we would expect based on the prevailing national sectoral mix.

Location quotients can be misleading when applied at small spatial scales. They do not account

for the volume of activity in any particular place, only the share. As a result, small, narrowly specialized economies often post high location quotients that yield a spurious picture of relative specialization. Clearly absolute size, and not just relative size, is an important dimension of functional industrial

specialization. To offset the problem of high location quotients in very small counties, we plot location

quotients only for counties with at least fifty workers in the given industry or fifty patents in the given

technology area.

A location quotient only measures concentrated activity within a sub-region rather than across or

between neighboring sub-regions. Our second measure of local spatial concentration, the Gi statistic,

e

e

E

E

ij

it

j

t





 



 ÷ 



 




The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 95

measures concentrations of activity both within and across jurisdictional boundaries. The Gi is essentially a share-based measure of spatial concentration, i.e. the amount of activity in a multi-unit region

divided by the total activity across all units in the nation, measured in standard deviations from the

mean. The results are roughly interpretable as z-scores along the normal curve. We use a 95 percent

significance level to identify sub-regions with significant concentration in given technology areas. We

calculate Gi statistics for both ZIP codes and counties.

The measure for areal unit i for a given industry cluster is calculated as:

G

w x Wx

s nS W n

all j i

j ij j i

i i

*

( )/( ) = , ∑ −

1 − − 2 1

x = ∑ x ( ) n −1

j j

= ∑j i wij S 2

1

,

and ( ) 2 2 2

s x n 1 (x) j = ∑ j − −

w

X X

X X j

i j

j i j

= ∑

. Although the normality of Gi

*

 depends partially on the

where x is the variable of interest (e.g. employment or patents), {wij} is a spatial weights matrix that

defines neighboring areas j to areal unit i, Wi

 is the sum of weights in {wij},

number of neighbors (Getis and Ord 1992), we make the common simplifying assumption that Gi

*

follows a normal distribution for each county. Significant areas (counties or ZIP codes) are identified as

those posting values of 1.96 or greater, the 95 percent significance level from a two-tailed normal

distribution.

The first step in calculating Gi

*

 is to develop a spatial weights matrix {wij}. The spatial weights

matrix acts first as a filter so that only cluster residual employment of neighboring areas are included in

the calculation of local concentration. In this study we use a weighted matrix, with adjacency defined

by immediate neighbor areas (counties or ZIP codes) inclusive of the area itself. Non-neighboring areal

units are given a weight of zero. The value x of neighboring area j to area i is weighted by the degree of

expected interaction between areas j and i:

where upper-case X is total exportable (or basic sector) employment and the denominator is the sum of

interactions between areal unit i and all its neighboring areas j. Dividing by the sum of interactions

row-standardizes the matrix, turning each cell’s weight into a percentage of the total interactions between adjacent areas. The logic behind the weighting scheme is essentially the notion that larger cen1. The gravity specification of the weights is far better at identifying discrete concentrations of activity than the

more common binary weights.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 96

ters typically exert a heavier influence on neighbor areas than do smaller centers. There is also an

implicit assumption that non-neighboring areas do not interact.1

To detect unique clusters of activity in and around Appalachia, we also need a means of controlling for the general tendency of industry to concentrate geographically. To the extent that much commerce serves the local population, we should expect more employment in urban centers simply because

there is more activity there to begin with. In this study, we are more interested in finding local concentrations of activity beyond those that might be expected by the general distribution of employment and

population.

To do this, we use a procedure we developed for a previous study.2

 The first step is to estimate a

linear regression model with sectoral employment (or patents) as the dependent variable and total

export-base employment as the sole explanatory variable, where counties or ZIP codes are the units of

analysis. The regression predicts local employment (or patents) in the sector or cluster based on the

distribution of total export-base employment. The difference between the predicted and actual employment or patents, i.e. the residual, is an estimate of local activity beyond that expected by the overall size

of the place. The Gi

 is then calculated using the residuals to identify areas with significant concentrations of technology-related activity.3

 The residuals constitute that portion of employment in the given

sector unexplained by the general distribution of economic activity.

Although not infallible, the residual method tends to successfully exclude very small and overly

specialized places, because such places are also likely to have small residuals. A downside is that the

approach sometimes misses concentrations that are entirely confined within the borders of a single

spatial unit. Thus the reason for comparing results using Gi with findings generated with county-level

location quotients.4 We also calculate Gi based on county-level growth residuals between 1989 and 1998

in an attempt to identify emerging technology clusters.5

2. See Feser, Sweeney et al. (2001).

3. In the case of patents, Gi

 statistics are calculated on the residuals of a linear regression with the number of

county patents in a technology sector as the dependent variable, and the average county population between

1990 and 1999 as the independent variable. The residuals correspond to the expected county patenting activity beyond that explained by the population of the county. Because patents are coded to the residence of the

inventor, population is a better control than employment.

4. G statistics are only calculated for ZIP codes within 60 miles of the ARC region, due to the large number of

ZIP codes and the difficulties involved in their computation. Nevertheless, the ZIP codes Gi’s are derived

using national totals as a baseline and therefore are relative to activity in the entire continental U.S.

5. Reporting Gi values by county or ZIP code does not violate U.S. BLS confidentiality rules since actual employment volumes cannot be derived by examination of the coefficients. The statistical coefficients are

actually more informative than raw employment totals in searching for spatial concentration, because they

control for the size of the local economy and spillovers across jurisdictions.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 97

Derivation of High Tech Value-Chains

Our goal was to develop a consistent set of value-chains comprised of linked technology-oriented

industries. We began by analyzing value-chain relationships via a factor analysis of 1992 U.S. inputoutput (I-O) data.6

 To do this, we first developed a standard 491 by 491 inter-industry transactions

matrix from the detailed industry by commodity benchmark input-output accounts. Specifically, following Czamanski (1974) we formed — from the 491 by 491 matrix of inter-industry transactions, A —

two matrices, X and Y, with elements:

where aij is the dollar value of goods and services sold by industry i in some period to industry j, and a+j

and ai+ are total intermediate good purchases and sales, respectively, of industries i and j over the same

period. xij is intermediate good purchases by sector j from i as a proportion of j’s total intermediate good

purchases. The columns of X are the intermediate input purchasing pattern of each industry j, while the

rows of Y are the intermediate output sales pattern of each industry i.

For any two industries (A and B) with the column vectors of X defined as xA, and xB and the row

vectors of Y defined as yA and yB, four correlations on the sales and purchasing vectors of any two

industries may be derived (again, following Czamanski): 1) r(xAzxB) measures the similarity in input

purchasing patterns of industries A and B; 2) r(yAzyB) measures the degree to which A and B possess

similar output selling patterns, i.e. the degree to which they sell goods to a similar mix of intermediate

input buyers; 3) r(xAzyB) measures the degree to which the buying pattern of industry A is similar to the

selling pattern of industry B, i.e. the degree to which industry A purchases inputs from industries in

which B supplies (a second-tier linkage); and 4) r(xBzyA) measures the degree to which the buying

pattern of industry B is similar to the selling pattern of industry A, i.e. the degree to which industry B

purchases inputs from industries in which A supplies. A linkage matrix, L, comprising the largest of

these four correlations for each pair of sectors, summarizes the degree of linkage between and among

xi j = ai j

a+j , yi j = ai jai+

6. The base input-output data are from the Benchmark Input-Output Accounts of the United States, 1992

(Washington, DC: U.S. Department of Commerce), accessible via the Internet at http://www.bea.doc.gov/

bea/dn2/i-o.htm.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 98

all 491 sectors. To derive a group of technology-intensive value-chains, we reduced L to represent only

SIC sectors commonly identified as technology-intensive.7

To derive the clusters, we wrote a program using SAS software that conducted a factor analysis on

the linkage matrix L over multiple times, changing the number of components subject to rotation by

one on each iteration.8

 The program aided the analysis by sorting the rotated factors by loading, attaching detailed SIC industry labels to each I-O sector, and producing scree plots and tables reporting the

relative proportion of variance explained by each component and the size of the associated eigenvalues. After inspecting each set of results in terms of indicators of fit, economic plausibility, and general

interpretability, we selected a final model revealing eight components.

Associated with a given component is a reduced set of variables — in this case, sectors — which

constitute its key statistical element. The indicator for determining this element is the individual loading, which is a measure of the relative strength of the relationship between a given variable and each

derived component. The magnitudes of the loadings therefore determine the membership in each cluster. I-O sectors were generally included in the value-chain if their loading was equal to or exceeded

0.35, though in some cases we eliminated sectors after inspecting underlying input-output patterns in

each cluster.9

 All eight components could be interpreted (i.e., labeled) in a straightforward manner by

examining underlying input-output linkages. Note that the eight value-chains are not mutually exclusive; any given underlying industry may be a member of multiple chains.

Summary of Data Sources

The following summarizes the principal sources of data used in the report. Manipulations of the data to

derive specific indicators are documented in the report proper (and its extensive set of endnotes).

Industry employment and wages. Employment and wage data by sector are from the confidential

U.S. Bureau of Labor Statistics Unemployment Insurance Data Base (UDB), used via special permission. The UDB file is constructed from unemployment insurance tax records assembled by the states

7. The following 109 I-O codes concord to 148 technology-intensive SIC industries: I130100, I270100, I270201,

I270202, I270300, I270401, I270402, I270403, I270404, I270405, I270406, I280100, I280200, I280300, I280400,

I290100, I290201, I290202, I290203, I290300, I300000, I430100, I430200, I450100, I450200, I450300, I460100,

I460200, I460300, I460400, I470100, I470200, I470300, I470401, I470402, I470404, I470405, I470500, I480100,

I480200, I480300, I480400, I480500, I480600, I490100, I490200, I490300, I490500, I490600, I490700, I490800,

I510102, I510103, I510104, I510400, I530200, I530300, I530400, I530500, I530700, I530800, I540100, I540200,

I540300, I540400, I540500, I540700, I550100, I550200, I550300, I560100, I560200, I560300, I560500, I570100,

I570200, I570300, I580100, I580200, I580400, I580600, I580700, I590100, I590200, I590301, I590302, I600100,

I600200, I600400, I610603, I620101, I620102, I620200, I620300, I620400, I620500, I620600, I620800, I620900,

I621000, I621100, I630200, I630300, I660100, I730104, I730112, I730302, I770200, I770305.

8. All calculations were performed using SAS Interactive Matrix Language (IML) software as well as the SAS

FACTOR procedure. We used a Promax rotation. Promax produces an orthogonal pre-rotation (equivalent to

Varimax) followed by an oblique rotation. Oblique rotation is favored when a high degree of overlap across

factors is expected.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 99

under the ES-202 program. At the time of study, 1998 was the most recent year available, with reliable

data starting in 1989. The primary limitation of ES-202 data is the exclusion of sole proprietorships. ES202 data are estimated to include some 95 percent of businesses in the U.S. Our national data exclude

Alaska, Hawaii, and Wyoming since we lacked permission to use those states’ files.

Occupational employment. Metropolitan occupational employment figures are from the 1999

Occupational Employment Statistics files of the U.S. Bureau of Labor Statistics. The data are

downloadable from http://www.bls.gov/oes/home.htm.

Faculty quality ratings. The faculty quality ratings are from the National Research Council’s

(NRC) 1995 National Survey of Graduate Faculty. The findings of the survey are reported in the NRC

publication Research-Doctorate Programs in the Untied States: Continuity and Change, which is available online at http://books.nap.edu/html/researchdoc/. Institutional rankings by discipline are available

at: http://books.nap.edu/html/researchdoc/researchdoc_tables.html.

Reputation measures such as that used to determine faculty quality, are inherently subjective and

tend to change only very slowly. The NRC notes, however, that pooling raters’ responses generates

strong consensus on both the strongest and weakest programs, though considerably less agreement

exists on programs in the middle range. Further, the NRC recognizes that, “differences in ranked order

between two programs may reflect very small, unreliable, or insignificant differences in the actual

quality of a program, and should be regarded by readers with great caution.”

University research funding. Data on research and development expenditures were obtained through

the National Science Foundation’s CASPAR and WebCASPAR Database Systems (http://caspar.nsf.gov).

The underlying data are from the Survey of Scientific and Engineering Expenditures at Universities

and Colleges, a survey conducted annually since fiscal year 1972. All science and engineering doctorate-granting institutions and/or all other institutions conducting at least $50,000 annually in separately

budgeted R&D are included in the survey. Over the years, approximately 97 percent of more than 500

institutions nationwide participate in the survey. Moreover, NSF estimates that this survey accounts for

approximately 98 percent of all academic R&D expenditures in the United States.

Graduate student enrollments. Graduate science and engineering student enrollment data were

obtained from the WebCASPAR Database System. The underlying source is NSF’s Graduate Students

and Postdoctorates in Science and Engineering (GSS) survey. Conducted annually since 1975, the GSS

survey collects data from close to 100 percent of all institutions granting masters or higher level degrees

in science and engineering disciplines.

University patents and gross license income. Data on the number of patents issued to universities

and gross license income are from the Association of University Technology Managers (AUTM 1991,

1995, 1999). Participants in the AUTM survey include U.S. universities, hospitals and research insti-
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 100

tutes, Canadian institutions, and third-party patent management firms. Of the nearly 196 universities

surveyed in FY 1995, approximately 62 percent responded. Among the top 100 research institutions (as

measured by total federal dollar support), 87 percent responded. See http://www.autm.net/index_ie.html.

Non-university research organizations and labs. Derived from our own independent research

along with Coburn and Berglund 1995 and the membership directory of the National Business Incubator Association (http://www.nbia.org).

Utility patent grants by county. Obtained by special request from the U.S. Patent and Trade Office

for states with at least one county in the ARC region. Our analysis utilizes patents awarded between

1990 and 1999 (the most recent year available at the time of the study). A full description of the USPTO

patent database (along with technical documentation) is available online at http://www.uspto.gov.

SBIR, STTR, and ATP awards by ZIP code. Derived from program competition announcements for

fiscal year 2000. See http://www.sba.gov/SBIR/indexsbir-sttr.html.

Degree completions. College and university completions data were complied from the U.S. Department of Education, National Center for Education Statistics’ Integrated Postsecondary Education

Data System (IPEDS) completions survey (1997–98) and consolidated survey (1998). The IPEDS universe includes all public and private post-secondary educational institutions that have Program Participation Agreements (PPAs) regarding Title IV federal financial aid programs, some 9,519 schools in the

U.S. Degree completions in the IPEDS are disaggregated by over 550 Classification of Instructional

Programs (CIP) codes. For the 1997–98 survey year, the IPEDS completions survey response rates vary

between 89 percent for four-year institutions, 88 percent for two-year schools, and 53 percent for less

than two year institutions. Although survey respondents cover the vast the majority degrees granted,

the IPEDS completion data technically must be regarded as a slight undercount of total degrees granted.

The IPEDS data and associated technical documentation are available online at http://nces.ed.gov/ipeds/.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 101

SIC Sector title SIC Sector title

2830 Drugs 7373 Computer integrated systems design

3570 Computer and office equipment 7374 Data processing and preparation

3660 Communications equipment 7375 Information retrieval services

3720 Aircraft and parts 7379 Computer related services, nec

3760 Guided missiles, space vehicles, parts 8711 Engineering services

3812 Search and navigation equipment 8731 Commercial physical research

3820 Measuring and controlling devices 8733 Noncommercial research organizations

7371 Computer programming services 8734 Testing laboratories

7372 Prepackaged software

2810 Industrial inorganic chemicals 3844 X-ray apparatus and tubes

2820 Plastics materials and synthetics 3845 Electromedical equipment

2860 Industrial organic chemicals 3851 Ophthalmic goods

3670 Electronic components and accessories 3861 Photographic equipment and supplies

3711 Motor vehicles and car bodies 8062 General medical and surgical hospitals

3714 Motor vehicle parts and accessories 8071 Medical laboratories

3716 Motor homes 8072 Dental laboratories

3841 Surgical and medical instruments 8090 Health and allied services, n.e.c.

2840 Soap, cleaners and toilet goods 3630 Household appliances

2851 Paints, varnishes, lacquers, etc. 3640 Electric lighting and wiring equipment

2873 Agricultural chemicals 3650 Household audio and video equipment

2890 Misc chemical products 3690 Misc electrical equipment and supplies

3510 Engines and turbines 3713 Truck and bus bodies

3530 Construction and related machinery 3715 Truck trailers

3540 Metalworking machinery 3821 Laboratory apparatus and furniture

3550 Special industry machinery 3842 Surgical appliances and supplies

3560 General industrial machinery 3843 Dental equipment and supplies

3610 Electric distribution equipment 4899 Communications services, nec

3620 Electrical industrial apparatus

Classification from the North Carolina Employment Security Commission.

Somewhat technology-intensive

Very technology-intensive

Moderately technology-intensive

Appendix Table 1

SIC-Technology classification
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 102

ID Metropolitan area

Location ID Metropolitan areaLocation

1 Akron, OH PMSA O 32 Hickory-Morganton-Lenoir, NC MSA B

2 Albany-Schenectady-Troy, NY MSA B 33 Huntington-Ashland, WV-KY-OH MSA I

3 Allentown-Bethlehem-Easton, PA MSA B 34 Huntsville, AL MSA I

4 Altoona, PA MSA I 35 Jamestown, NY MSA I

5 Anniston, AL MSA I 36 Johnson City-Kingsport-Bristol, TN-VA MSA I

6 Asheville, NC MSA I 37 Johnstown, PA MSA I

7 Athens, GA MSA B 38 Knoxville, TN MSA I

8 Atlanta, GA MSA B 39 Lexington, KY MSA B

9 Auburn-Opelika, AL MSA O 40 Lynchburg, VA MSA O

10 Binghamton, NY MSA I 41 Mansfield, OH MSA O

11 Birmingham, AL MSA I 42 Memphis, TN-AR-MS MSA O

12 Buffalo-Niagara Falls, NY MSA O 43 Montgomery, AL MSA B

13 Canton-Massillon, OH MSA B 44 Nashville, TN MSA O

14 Charleston, WV MSA I 45 Newark, NJ PMSA O

15 Charlotte-Gastonia-Rock Hill, NC-SC O 46 Newburgh, NY-PA PMSA O

16 Chattanooga, TN-GA MSA I 47 Parkersburg-Marietta, WV-OH MSA I

17 Cincinnati, OH-KY-IN PMSA B 48 Pittsburgh, PA MSA I

18 Cleveland-Lorain-Elyria, OH PMSA O 49 Reading, PA MSA O

19 Columbus, GA-AL MSA O 50 Roanoke, VA MSA B

20 Columbus, OH MSA O 51 Rochester, NY MSA O

21 Cumberland, MD-WV MSA I 52 Scranton–Wilkes-Barre–Hazleton, PA MSA I

22 Decatur, AL MSA I 53 Sharon, PA MSA I

23 Elmira, NY MSA I 54 State College, PA MSA I

24 Erie, PA MSA I 55 Steubenville-Weirton, OH-WV MSA I

25 Florence, AL MSA I 56 Syracuse, NY MSA O

26 Gadsden, AL MSA I 57 Tuscaloosa, AL MSA B

27 Greensboro, Winston-Salem, High Point MSA B 58 Utica-Rome, NY MSA O

28 Greenville-Spartanburg-Anderson MSA I 59 Washington, DC-MD-VA-WV PMSA B

29 Hagerstown, MD PMSA I 60 Wheeling, WV-OH MSA I

30 Hamilton-Middleton, OH PMSA O 61 Williamsport, PA MSA I

31 Harrisburg-Lebanon-Carlisle, PA MSA B 62 Youngstown-Warren, OH MSA B

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia, with 

borders at least 10 miles from region boundary. MSA boundaries correspond to the 1999 definitions released by the Office of Management and 

Budget.

Appendix Table 2

Metropolitan areas within and bordering Appalachia
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 103

ID MSA name Cnty Zips LQ Gro Cnty Zips LQ Gro Cnty Zips LQ Gro

4 I Altoona, PA MSA X

5 I Anniston, AL MSA

6 I Asheville, NC MSA X X X X X

10 I Binghamton, NY MSA X X X X X X

11 I Birmingham, AL MSA X X X X X

14 I Charleston, WV MSA X X X

16 I Chattanooga, TN-GA MSA X X

21 I Cumberland, MD-WV MSA X X

22 I Decatur, AL MSA X X X X

23 I Elmira, NY MSA X X X X

24 I Erie, PA MSA X XX

25 I Florence, AL MSA X

26 I Gadsden, AL MSA X

28 I Greenville-Spartanburg-Anderson MSA X X X X X X X

29 I Hagerstown, MD PMSA X X

33 I Huntington-Ashland, WV-KY-OH MSA X X

34 I Huntsville, AL MSA X X X X X X

35 I Jamestown, NY MSA X X X X

36 I Johnson City-Kingsport-Bristol, TN-VA MSA X X X X X

37 I Johnstown, PA MSA X X X X X

38 I Knoxville, TN MSA X X X X X

47 I Parkersburg-Marietta, WV-OH MSA X X X

48 I Pittsburgh, PA MSA X X X X X X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA X X

53 I Sharon, PA MSA X

54 I State College, PA MSA X X

55 I Steubenville-Weirton, OH-WV MSA X X

60 I Wheeling, WV-OH MSA X X

61 I Williamsport, PA MSA X X

2 B Albany-Schenectady-Troy, NY MSA X X X X X X X X X X

3 B Allentown-Bethlehem-Easton, PA MSA X X X X X X X

7 B Athens, GA MSA X X X

8 B Atlanta, GA MSA X X X X X X X

13 B Canton-Massillon, OH MSA X XX

17 B Cincinnati, OH-KY-IN PMSA X X X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X X X X X X X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X X X X

32 B Hickory-Morganton-Lenoir, NC MSA X X

39 B Lexington, KY MSA X X X X X X

43 B Montgomery, AL MSA X X X X

50 B Roanoke, VA MSA X X X X X

57 B Tuscaloosa, AL MSA X X X X

59 B Washington, DC-MD-VA-WV PMSA X X X X X X X X

62 B Youngstown-Warren, OH MSA X X X X X

1 O Akron, OH PMSA X X X X X XX

9 O Auburn-Opelika, AL MSA X

12 O Buffalo-Niagara Falls, NY MSA X X X X X X

Very Moderately Somewhat

Appendix Table 3

Spatial concentration of technology-intensive employment in ARC MSAs

(1998, and growth 1989-1998), by degree of technology-intensity

Appendix Table 3 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 104

Appendix Table 3 continued

Spatial concentration of technology-intensive employment in ARC MSAs

(1998, and growth 1989-1998), by degree of technology-intensity

ID MSA name Cnty Zips LQ Gro Cnty Zips LQ Gro Cnty Zips LQ Gro

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X X X X

19 O Columbus, GA-AL MSA X X X

20 O Columbus, OH MSA X X X X X X X

30 O Hamilton-Middleton, OH PMSA X X X X X

40 O Lynchburg, VA MSA X X X X

41 O Mansfield, OH MSA X X X

42 O Memphis, TN-AR-MS MSA X X

44 O Nashville, TN MSA X X X X X

45 O Newark, NJ PMSA X X X X X X X X

46 O Newburgh, NY-PA PMSA X X

49 O Reading, PA MSA X X X X

51 O Rochester, NY MSA X X X X X X X

56 O Syracuse, NY MSA X X X X X

58 O Utica-Rome, NY MSA X X X X

Very Moderately Somewhat

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia, with 

borders at least 10 miles from region boundary. Cnty: Significant employment G for at least one county in the metro area. Significant employment 

G for at least one zip code in the metro area. Gro: Significant employment growth G for at least one county in the metro area. LQ: Employment 

location quotient in excess of 1.1 for at least one county in the metro area.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 105

SIC Sector title SIC Sector title

Chemicals and plastics Information technology and instruments cont.

2812 Alkalies and chlorine 3674 Semiconductors and related devices

2813 Industrial gases 3675 Electronic capacitors

2816 Inorganic pigments 3676 Electronic resistors

2821 Plastics materials and resins 3677 Electronic coils and transformers

2822 Synthetic rubber 3678 Electronic connectors

2823 Cellulosic manmade fibers 3679 Electronic components, nec

2824 Organic fibers, noncellulosic 3694 Engine electrical equipment

2841 Soap and other detergents 3699 Electrical equipment & supplies, nec

2842 Polishes and sanitation goods 3812 Search and navigation equipment

2843 Surface active agents 3821 Laboratory apparatus and furniture

2844 Toilet preparations 3822 Environmental controls

2851 Paints, varnishes, lacquers, enamels, etc. 3823 Process control instruments

2865 Cyclic crudes and intermediates 3824 Fluid meters and counting devices

2869 Industrial organic chemicals, nec 3825 Instruments to measure electricity

2873 Nitrogenous fertilizers 3826 Analytical instruments

2874 Phosphatic fertilizers 3827 Optical instruments and lenses

2875 Fertilizers, mixing only 3829 Measuring & controlling devices, nec

2879 Agricultural chemicals, nec 3844 X-ray apparatus and tubes

2891 Adhesives and sealants 3845 Electromedical equipment

2893 Printing ink 7371 Computer programming services

2899 Chemical preparations, nec 7372 Prepackaged software

3559 Special industry machinery, nec 7373 Computer integrated systems design

3624 Carbon and graphite products 7374 Data processing and preparation

3692 Primary batteries, dry and wet 7375 Information retrieval services

3843 Dental equipment and supplies 7379 Computer related services, nec

8071 Medical laboratories

8072 Dental laboratories Industrial machinery

8092 Kidney dialysis centers 3511 Turbines and turbine generator sets

8093 Specialty outpatient facilities, nec 3532 Mining machinery

8099 Health and allied services, nec 3535 Conveyors and conveying equipment

3610 Electric distribution equipment 3536 Hoists, cranes, and monorails

3620 Electrical industrial apparatus 3541 Machine tools, metal cutting types

3542 Machine tools, metal forming types

Information technology and instruments 3546 Power-driven handtools

3571 Electronic computers 3547 Rolling mill machinery

3572 Computer storage devices 3549 Metalworking machinery, nec

3575 Computer terminals 3553 Woodworking machinery

3577 Computer peripheral equipment, nec 3555 Printing trades machinery

3578 Calculating and accounting equipment 3556 Food products machinery

3579 Office machines, nec 3559 Special industry machinery, nec

3625 Relays and industrial controls 3561 Pumps and pumping equipment

3629 Electrical industrial apparatus, nec 3563 Air and gas compressors

3631 Household cooking equipment 3564 Blowers and fans

3643 Current-carrying wiring devices 3565 Packaging machinery

3644 Noncurrent-carrying wiring devices 3612 Transformers, except electronic

3661 Telephone and telegraph apparatus 3621 Motors and generators

3663 Radio & TV communications equipment

3669 Communications equipment, nec

3672 Printed circuit boards

Appendix Table 4

Technology value-chain classification

Appendix Table 4 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 106

Appendix Table 4 continued

Technology value-chain classification

SIC Sector title SIC Sector title

Motor vehicle manufacturing Communications services and software

2851 Paints, varnishes, lacquers, enamels, etc. 4899 Communications services, nec

2893 Printing ink 7371 Computer programming services

3519 Internal combustion engines, nec 7372 Prepackaged software

3531 Construction machinery 7373 Computer integrated systems design

3534 Elevators and moving stairways 7374 Data processing and preparation

3537 Industrial trucks and tractors 7375 Information retrieval services

3548 Welding apparatus 7379 Computer related services, nec

3641 Electric lamps 8711 Engineering services

3645 Residential lighting fixtures 8712 Architectural services

3646 Commercial lighting fixtures 8713 Surveying services

3647 Vehicular lighting equipment 8731 Commercial physical research

3648 Lighting equipment, nec 8732 Commercial nonphysical research

3651 Household audio and video equipment 8734 Testing laboratories

3691 Storage batteries

3694 Engine electrical equipment Pharmaceuticals and medical technologies

3711 Motor vehicles and car bodies 2833 Medicinals and botanicals

3713 Truck and bus bodies 2834 Pharmaceutical preparations

3714 Motor vehicle parts and accessories 2835 Diagnostic substances

3715 Truck trailers 2836 Biological products exc. diagnostic

3634 Electric housewares and fans

Aerospace 3841 Surgical and medical instruments

3544 Special dies, tools, jigs & fixtures 3842 Surgical appliances and supplies

3545 Machine tool accessories 8731 Commercial physical research

3721 Aircraft 8732 Commercial nonphysical research

3724 Aircraft engines and engine parts 8734 Testing laboratories

3728 Aircraft parts and equipment, nec

3761 Guided missiles and space vehicles

3764 Space propulsion units and parts

3769 Space vehicle equipment, nec

Household appliances

3632 Household refrigerators and freezers

3633 Household laundry equipment

3635 Household vacuum cleaners

3639 Household appliances, nec

3716 Motor homes

Source: Factor analysis of input-output data; see Methods Appendix.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 107

Appendix Table 5

Spatial concentration of value-chain employment in ARC MSAs

(1998, and growth 1989-1998)

ID MSA name Cnty Zips LQ Gro Cnty Zips LQ Gro Cnty Zips LQ Gro

4 I Altoona, PA MSA

5 I Anniston, AL MSA

6 I Asheville, NC MSA X X X X X X

10 I Binghamton, NY MSA X X X X X X X

11 I Birmingham, AL MSA X X X X X

14 I Charleston, WV MSA X X X

16 I Chattanooga, TN-GA MSA X X X

21 I Cumberland, MD-WV MSA

22 I Decatur, AL MSA X X X

23 I Elmira, NY MSA X X X

24 I Erie, PA MSA X X X X

25 I Florence, AL MSA X

26 I Gadsden, AL MSA

28 I Greenville-Spartanburg-Anderson MSA X X X X X X X X

29 I Hagerstown, MD PMSA X

33 I Huntington-Ashland, WV-KY-OH MSA X X X X X

34 I Huntsville, AL MSA X X X X

35 I Jamestown, NY MSA X X X

36 I Johnson City-Kingsport-Bristol, TN-VA MSA X X X X X

37 I Johnstown, PA MSA X X

38 I Knoxville, TN MSA X X

47 I Parkersburg-Marietta, WV-OH MSA X X X

48 I Pittsburgh, PA MSA X X X X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA X X

53 I Sharon, PA MSA XXX

54 I State College, PA MSA X X X X X X

55 I Steubenville-Weirton, OH-WV MSA

60 I Wheeling, WV-OH MSA X X

61 I Williamsport, PA MSA

2 B Albany-Schenectady-Troy, NY MSA X X X X X X X X

3 B Allentown-Bethlehem-Easton, PA MSA X X X X X X X X

7 B Athens, GA MSA X X X X

8 B Atlanta, GA MSA X X X X X X X X X

13 B Canton-Massillon, OH MSA X X X X X X

17 B Cincinnati, OH-KY-IN PMSA X X X X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X X X X X X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X X X X

32 B Hickory-Morganton-Lenoir, NC MSA X X

39 B Lexington, KY MSA X X X X X

43 B Montgomery, AL MSA X X X X X

50 B Roanoke, VA MSA X X X X X

57 B Tuscaloosa, AL MSA X X

59 B Washington, DC-MD-VA-WV PMSA X X X X X X X X X

62 B Youngstown-Warren, OH MSA XXX

1 O Akron, OH PMSA XXXX X XXX

9 O Auburn-Opelika, AL MSA

12 O Buffalo-Niagara Falls, NY MSA X X X X X X X X

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X X X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X X X X X

19 O Columbus, GA-AL MSA X X

20 O Columbus, OH MSA X X X X X X X

30 O Hamilton-Middleton, OH PMSA X X X X X

40 O Lynchburg, VA MSA X X X X X X

41 O Mansfield, OH MSA XXX

42 O Memphis, TN-AR-MS MSA X X X X X

44 O Nashville, TN MSA X X X X X X X

45 O Newark, NJ PMSA X X X X X X X X

46 O Newburgh, NY-PA PMSA X X X

49 O Reading, PA MSA X X X

51 O Rochester, NY MSA X X X X X X X X

56 O Syracuse, NY MSA X X X X

58 O Utica-Rome, NY MSA X X X X X

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia, with 

borders at least 10 miles from region boundary.

Chemicals and plastics Industrial machinery Information technology

Appendix Table 5 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 108

Appendix Table 5 continued

Spatial concentration of value-chain employment in ARC MSAs

(1998, and growth 1989-1998)

ID MSA name Cnty Zips LQ Gro Cnty Zips LQ Gro Cnty Zips LQ Gro

4 I Altoona, PA MSA

5 I Anniston, AL MSA

6 I Asheville, NC MSA X

10 I Binghamton, NY MSA X

11 I Birmingham, AL MSA X

14 I Charleston, WV MSA X

16 I Chattanooga, TN-GA MSA X

21 I Cumberland, MD-WV MSA X

22 I Decatur, AL MSA X X X X X

23 I Elmira, NY MSA X X

24 I Erie, PA MSA X

25 I Florence, AL MSA X X

26 I Gadsden, AL MSA X

28 I Greenville-Spartanburg-Anderson MSA X X X X X

29 I Hagerstown, MD PMSA X X

33 I Huntington-Ashland, WV-KY-OH MSA

34 I Huntsville, AL MSA X X X X X

35 I Jamestown, NY MSA X X X

36 I Johnson City-Kingsport-Bristol, TN-VA MSA X X X X X X X

37 I Johnstown, PA MSA X

38 I Knoxville, TN MSA X X X

47 I Parkersburg-Marietta, WV-OH MSA

48 I Pittsburgh, PA MSA X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA X

53 I Sharon, PA MSA X X

54 I State College, PA MSA

55 I Steubenville-Weirton, OH-WV MSA

60 I Wheeling, WV-OH MSA

61 I Williamsport, PA MSA X

2 B Albany-Schenectady-Troy, NY MSA X

3 B Allentown-Bethlehem-Easton, PA MSA X X

7 B Athens, GA MSA

8 B Atlanta, GA MSA X X X X X

13 B Canton-Massillon, OH MSA X X X X

17 B Cincinnati, OH-KY-IN PMSA X X X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X X X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X

32 B Hickory-Morganton-Lenoir, NC MSA X X

39 B Lexington, KY MSA X X X X X

43 B Montgomery, AL MSA X X X X X X

50 B Roanoke, VA MSA

57 B Tuscaloosa, AL MSA X X

59 B Washington, DC-MD-VA-WV PMSA X X X

62 B Youngstown-Warren, OH MSA X X X X X X

1 O Akron, OH PMSA XXX XX XXX

9 O Auburn-Opelika, AL MSA X

12 O Buffalo-Niagara Falls, NY MSA X X X

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X X X

19 O Columbus, GA-AL MSA X X

20 O Columbus, OH MSA X X

30 O Hamilton-Middleton, OH PMSA X X X X

40 O Lynchburg, VA MSA

41 O Mansfield, OH MSA X X

42 O Memphis, TN-AR-MS MSA X

44 O Nashville, TN MSA X X X X X

45 O Newark, NJ PMSA X

46 O Newburgh, NY-PA PMSA X

49 O Reading, PA MSA X X

51 O Rochester, NY MSA X X X

56 O Syracuse, NY MSA X X

58 O Utica-Rome, NY MSA

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia, with 

borders at least 10 miles from region boundary.

Motor vehicles Aerospace Household appliances

Appendix Table 5 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 109

ID MSA name Cnty Zips LQ Gro Cnty Zips LQ Gro

4 I Altoona, PA MSA

5 I Anniston, AL MSA

6 I Asheville, NC MSA

10 I Binghamton, NY MSA

11 I Birmingham, AL MSA X

14 I Charleston, WV MSA X

16 I Chattanooga, TN-GA MSA

21 I Cumberland, MD-WV MSA X

22 I Decatur, AL MSA X X

23 I Elmira, NY MSA

24 I Erie, PA MSA X

25 I Florence, AL MSA

26 I Gadsden, AL MSA X

28 I Greenville-Spartanburg-Anderson MSA X X

29 I Hagerstown, MD PMSA

33 I Huntington-Ashland, WV-KY-OH MSA X

34 I Huntsville, AL MSA X X X X X X

35 I Jamestown, NY MSA

36 I Johnson City-Kingsport-Bristol, TN-VA MSA X X

37 I Johnstown, PA MSA X X X

38 I Knoxville, TN MSA X X X X

47 I Parkersburg-Marietta, WV-OH MSA

48 I Pittsburgh, PA MSA X X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA

53 I Sharon, PA MSA

54 I State College, PA MSA X X

55 I Steubenville-Weirton, OH-WV MSA

60 I Wheeling, WV-OH MSA

61 I Williamsport, PA MSA

2 B Albany-Schenectady-Troy, NY MSA X X X X X X X X

3 B Allentown-Bethlehem-Easton, PA MSA X X

7 B Athens, GA MSA

8 B Atlanta, GA MSA X X X X X X

13 B Canton-Massillon, OH MSA

17 B Cincinnati, OH-KY-IN PMSA X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X X X X

32 B Hickory-Morganton-Lenoir, NC MSA X

39 B Lexington, KY MSA X

43 B Montgomery, AL MSA

50 B Roanoke, VA MSA

57 B Tuscaloosa, AL MSA

59 B Washington, DC-MD-VA-WV PMSA X X X X X X X X

62 B Youngstown-Warren, OH MSA

1 O Akron, OH PMSA X X

9 O Auburn-Opelika, AL MSA

12 O Buffalo-Niagara Falls, NY MSA X

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X

19 O Columbus, GA-AL MSA X X

20 O Columbus, OH MSA X X X X X X

30 O Hamilton-Middleton, OH PMSA X

40 O Lynchburg, VA MSA

41 O Mansfield, OH MSA

42 O Memphis, TN-AR-MS MSA

44 O Nashville, TN MSA X X X

45 O Newark, NJ PMSA X X X X X X X X

46 O Newburgh, NY-PA PMSA X X

49 O Reading, PA MSA X X X X X

51 O Rochester, NY MSA X X X X

56 O Syracuse, NY MSA X X

58 O Utica-Rome, NY MSA

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely 

outside Appalachia, with borders at least 10 miles from region boundary.

Comm svcs, software Pharm, med techs

Appendix Table 5 continued

Spatial concentration of value-chain employment in ARC MSAs

(1998, and growth 1989-1998)
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 110

Defini- DefiniAggregated Group OES Code OES Title tion 1 tion 2

IT scientists, engineers 15-1011 Computer & Information Scientists, Research X X

and programmers 15-1021 Computer Programmers X X

15-1031 Computer Software Engineers, Applications X X

15-1032 Computer Software Engineers, Systems Software X X

15-1041 Computer Support Specialists X 

15-1051 Computer Systems Analysts X 

15-1061 Database Administrators X 

15-1071 Network & Computer Systems Administrators X 

15-1081 Network Systems & Data Communications Analysts X 

17-2061 Computer Hardware Engineers X X

Mathematicians, 15-2021 Mathematicians X X

statisticians, and 15-2031 Operations Research Analysts X X

physicists 15-2041 Statisticians X X

15-2091 Mathematical Techs X 

19-2012 Physicists X X

Agricultural scientists 17-2021 Agricultural Engineers X X

and engineers 19-1010 Agricultural & Food Scientists X X

19-4011 Agricultural & Food Science Techs X 

Biological scientists 19-1021 Biochemists & Biophysicists X X

and technicians 19-1022 Microbiologists X X

19-4021 Biological Techs X 

19-1041 Epidemiologists X X

Chemists and 19-4031 Chemical Techs X 

chemical engineers 17-2041 Chemical Engineers X X

19-2031 Chemists X X

Environmental and 19-2041 Environmental Scientists & Specialists, Incl. Health X X

resource scientists 19-1023 Zoologists & Wildlife Biologists X X

and technicians 19-1031 Conservation Scientists X X

19-4091 Environmental Science & Protection Techs, Incl. Health X 

19-4093 Forest & Conservation Techs X 

17-2081 Environmental Engineers X X

17-3025 Environmental Engineering Techs X 

Medical scientists 19-1042 Medical Scientists, Except Epidemiologists X X

and engineers 17-2031 Biomedical Engineers X X

51-9082 Medical Appliance Techs X 

Electrical engineers 17-2071 Electrical Engineers X X

and technicians 17-2072 Electronics Engineers, Except Computer X X

17-3023 Electrical & Electronic Engineering Techs X 

17-3024 Electro-Mechanical Techs X 

Materials engineers 17-2131 Materials Engineers X X

and scientists 19-2032 Materials Scientists X X

Aerospace engineers 19-2021 Atmospheric & Space Scientists X X

and technicians 17-2011 Aerospace Engineers X X

17-3021 Aerospace Engineering & Operations Techs X 

49-2091 Avionics Techs X 

Geoscientists 19-2043 Hydrologists X X

and engineers 19-4041 Geological & Petroleum Techs X 

19-2042 Geoscientists, Except Hydrologists & Geographers X X

17-2171 Petroleum Engineers X X

17-2151 Mining & Geological Engineers, Incl. Mining Safety Engineers X X

Nuclear engineers 19-4051 Nuclear Techs X 

and technicians 17-2161 Nuclear Engineers X X

Industrial and 17-2112 Industrial Engineers X X

mechanical engineers 17-2141 Mechanical Engineers X X

and technicians 17-3026 Industrial Engineering Techs X 

17-3027 Mechanical Engineering Techs X 

Source: Selected from 709 total occupations included in 1999 Occupational Employment Statistics data (U.S. Bureau of 

Labor Statistics). Definition 1 includes all occupations; Definition 2 excludes technicians.

Appendix Table 6

Science and technology occupational classification
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 111

Appendix Table 7

Location quotients: Scientists and engineers, 1999

Employment location quotients for scientists and engineers only

ID MSA

ITMathAgSciBioChemEnviroMedElectMatrlAeroGeoNuclIndust

4 I Altoona, PA 0.4 0.5

5 I Anniston, AL 0.4 0.3

6 I Asheville, NC 0.1 1.0 0.3 0.4

11 I Binghamton, NY 1.5 2.5 1.1

12 I Birmingham, AL 0.9 0.3 0.3 0.6 0.3 1.6 0.2 0.9

15 I Charleston, WV 0.5 1.3

17 I Chattanooga, TN-GA 0.4 0.3 0.1 0.8

22 I Cumberland, MD-WV 

23 I Decatur, AL 0.1 1.5 0.8

24 I Elmira, NY 0.1 0.9

25 I Erie, PA 0.3 1.8 1.0

26 I Florence, AL 0.6 0.8

27 I Gadsden, AL 

29 I Greenville-Spartanburg-Anderson, SC 0.4 0.3 1.7 0.3 0.7 1.5

30 I Hagerstown, MD 0.1

34 I Huntington-Ashland, WV-KY-OH 0.1 0.6 0.2 0.1

35 I Huntsville, AL 1.8 0.6 0.5 4.3 32.8 3.1

36 I Jamestown, NY 0.6

37 I Johnson City-Kingsport-Bristol, TN-VA 0.2 0.5 0.4

38 I Johnstown, PA 0.0 0.2

39 I Knoxville, TN 0.3 1.0 0.6 0.4 0.6

48 I Parkersburg-Marietta, WV-OH 0.5 0.8

49 I Pittsburgh, PA 0.7 1.2 0.3 0.3 0.5 0.8 2.6 0.2 0.9

53 I Scranton–Wilkes-Barre–Hazleton, PA 0.5 0.1 0.3 0.6

54 I Sharon, PA 0.4

55 I State College, PA 0.9 0.3

56 I Steubenville-Weirton, OH-WV 0.6

61 I Wheeling, WV-OH 

62 I Williamsport, PA 0.1

2 B Albany-Schenectady-Troy, NY 0.3 1.3 0.4 0.3 0.1

3 B Allentown-Bethlehem-Easton, PA 0.4 0.2 2.3 0.4 1.0 0.8

7 B Athens, GA 0.1 0.8 0.6

8 B Atlanta, GA 1.7 1.3 1.2 1.0 1.4 0.6 1.4 0.4 0.3 0.8

14 B Canton-Massillon, OH 0.0 0.2 1.1

18 B Cincinnati, OH-KY-IN 0.9 0.9 1.3 0.7 0.5 1.0 1.2

28 B Greensboro–Winston-Salem–High Point, NC 0.8 0.1 1.0 0.0 1.3 2.8 0.8

32 B Harrisburg-Lebanon-Carlisle, PA 0.5 0.2 0.5 0.3 0.4 0.8

33 B Hickory-Morganton-Lenoir, NC 0.2 0.4 0.7 0.6

40 B Lexington, KY 0.4 0.4 0.3 0.5 0.4 1.0

44 B Montgomery, AL 0.5 0.5 0.1

51 B Roanoke, VA 0.8 0.5 0.8 0.7

58 B Tuscaloosa, AL 0.2

60 B Washington, DC-MD-VA-WV 2.2 4.9 1.3 2.4 0.2 1.8 3.2 2.3 0.5 1.8 1.1 0.8

64 B Youngstown-Warren, OH 0.2 0.2 0.3 0.2 2.8 0.9

Appendix Table 7 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 112

Appendix Table 7 continued

Location quotients: Scientists and engineers, 1999

Employment location quotients for scientists and engineers only

ID MSA

ITMathAgSciBioChemEnviroMedElectMatrlAeroGeoNuclIndust

1 O Akron, OH 0.5 1.2 0.1 0.9 1.4

9 O Auburn-Opelika, AL

10 O Baltimore, MD 0.7 1.4 0.4 1.2 0.6 0.6 1.2 0.8 0.8 0.2 1.1

13 O Buffalo-Niagara Falls, NY 0.5 1.2 0.4 1.2 1.0

16 O Charlotte-Gastonia-Rock Hill, NC-SC 1.0 0.5 0.8 0.6 0.6 2.8 1.0

19 O Cleveland-Lorain-Elyria, OH 0.6 0.1 1.8 0.6 0.3 1.3 1.4 1.8

20 O Columbus, GA-AL 0.1 0.2

21 O Columbus, OH 1.6 0.5 0.8 0.7 0.2 0.9 0.3 1.0

31 O Hamilton-Middletown, OH 0.5 0.4 0.8 0.4

41 O Lynchburg, VA 0.2 0.2

42 O Mansfield, OH 0.1 0.9 2.0

43 O Memphis, TN-AR-MS 0.3 0.9 0.9 0.4 0.4 0.3 0.2 0.3 0.5

45 O Nashville, TN 0.5 0.6 2.3 0.3 2.0 0.3 0.2 0.1 0.4

46 O Newark, NJ 1.4 4.7 1.5 1.1 0.5 0.9

47 O Newburgh, NY-PA 0.6 0.3

50 O Reading, PA 0.0 1.1 0.8 1.6 0.9

52 O Rochester, NY 0.6 1.4 0.1 0.4 2.0 1.8

57 O Syracuse, NY 0.6 0.1 1.1 1.0 0.7 1.1

59 O Utica-Rome, NY 0.4 0.5 0.3 0.3

63 O York, PA 0.1 0.2 0.3 0.8 2.1

Source: Occupational Employment Statistics, U.S. Bureau of Labor Statistics. I: MSA entirely contained within the Appalachian region; B: MSA 

spans Appalachian border; O: MSA completely outside Appalachia, with borders at least 10 miles from region boundary. N/A: Missing. Blank: No 

estimate available (see text for explanation). Values > 1.2 shaded.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 113

ID MSA

ITMathAgSciBioChemEnviroMedElectMatrlAeroGeoNuclIndust

4 I Altoona, PA 0.7

5 I Anniston, AL 

6 I Asheville, NC 0.5 0.8 0.3

11 I Binghamton, NY 0.7 0.4

12 I Birmingham, AL 1.3 0.2 8.1 1.2 0.5

15 I Charleston, WV 0.0 0.5

17 I Chattanooga, TN-GA 0.3 0.3 0.6 0.3

22 I Cumberland, MD-WV 

23 I Decatur, AL 0.1 2.9 0.6

24 I Elmira, NY 0.1 0.3 0.9

25 I Erie, PA 0.3 1.8 0.5

26 I Florence, AL 0.2 1.0

27 I Gadsden, AL 0.1

29 I Greenville-Spartanburg-Anderson, SC 0.5 2.5 0.3 1.3 1.2

30 I Hagerstown, MD 0.1 0.7

34 I Huntington-Ashland, WV-KY-OH 0.3 1.7 0.4

35 I Huntsville, AL 1.6 2.5 1.6

36 I Jamestown, NY 0.1

37 I Johnson City-Kingsport-Bristol, TN-VA 0.3 0.5

38 I Johnstown, PA 0.1 0.2

39 I Knoxville, TN 0.5 1.0 1.2 0.8

48 I Parkersburg-Marietta, WV-OH 0.0 0.7

49 I Pittsburgh, PA 1.0 0.6 0.2 0.8 1.1

53 I Scranton–Wilkes-Barre–Hazleton, PA 0.5 0.7 0.2 1.0 0.3

54 I Sharon, PA 

55 I State College, PA 0.2 2.1

56 I Steubenville-Weirton, OH-WV 0.1 1.1 0.6

61 I Wheeling, WV-OH 0.2

62 I Williamsport, PA 0.2 1.1

2 B Albany-Schenectady-Troy, NY 1.2 0.3

3 B Allentown-Bethlehem-Easton, PA 0.8 2.5 0.4 0.6 0.3

7 B Athens, GA 0.1 0.8 0.3

8 B Atlanta, GA 1.7 0.5 0.3 0.8 0.2 0.8 0.7 1.1

14 B Canton-Massillon, OH 0.5 0.3 0.3

18 B Cincinnati, OH-KY-IN 1.0 0.4 0.9 1.4 0.5 0.3

28 B Greensboro–Winston-Salem–High Point, NC 0.7 0.2 0.8 0.4 1.0 0.6

32 B Harrisburg-Lebanon-Carlisle, PA 1.5 0.7 0.8 0.7 0.4

33 B Hickory-Morganton-Lenoir, NC 0.3 1.0 0.6 0.4 0.4

40 B Lexington, KY 0.8 0.6 0.3

44 B Montgomery, AL 1.1 0.5

51 B Roanoke, VA 0.8 0.9 0.9 0.8 1.3

58 B Tuscaloosa, AL 0.0

60 B Washington, DC-MD-VA-WV 2.6 3.4 2.8 0.0 0.8 0.9 0.6 0.7

64 B Youngstown-Warren, OH 0.2 0.8

Appendix Table 8

Location quotients: Location quotients: Technicians, 1999

Employment location quotients for technicians only

Appendix Table 8 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 114

Appendix Table 8 continued

Location quotients: Location quotients: Technicians, 1999

Employment location quotients for technicians only

ID MSA

ITMathAgSciBioChemEnviroMedElectMatrlAeroGeoNuclIndust

1 O Akron, OH 0.7 1.6 0.3 0.5

9 O Auburn-Opelika, AL

10 O Baltimore, MD 1.1 0.7 0.9 0.5 1.2

13 O Buffalo-Niagara Falls, NY 0.5 1.2 0.5 0.5 1.1

16 O Charlotte-Gastonia-Rock Hill, NC-SC 1.2 1.1 0.8 0.4 1.0 0.6 1.6

19 O Cleveland-Lorain-Elyria, OH 1.1 1.0 0.4 0.9 1.5

20 O Columbus, GA-AL 0.5 2.1 0.3

21 O Columbus, OH 1.3 1.0 0.4 0.1

31 O Hamilton-Middletown, OH 0.4 1.3

41 O Lynchburg, VA 0.6 0.7

42 O Mansfield, OH 0.3 0.6

43 O Memphis, TN-AR-MS 0.9 0.3 1.7 0.4 0.6 0.9

45 O Nashville, TN 0.7 0.3 0.2 1.1 0.5 0.7

46 O Newark, NJ 0.6 5.2 0.6 0.8

47 O Newburgh, NY-PA 0.4 2.6 0.4

50 O Reading, PA 0.2 2.5 0.8 1.4

52 O Rochester, NY 1.1 0.2 0.4 1.7

57 O Syracuse, NY 1.1 0.6 0.6 1.4

59 O Utica-Rome, NY 0.3 0.8

63 O York, PA 0.3 0.4 0.6 0.6

Source: Occupational Employment Statistics, U.S. Bureau of Labor Statistics. I: MSA entirely contained within the Appalachian region; B: MSA 

spans Appalachian border; O: MSA completely outside Appalachia, with borders at least 10 miles from region boundary. N/A: Missing. Blank: 

No estimate available (see text for explanation). Values > 1.2 shaded.
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 115

Appendix Table 9

Concordance: Patents to technology groups

Product Field SIC

Chemicals and plasticsInformation technologyInstrumentsIndustrial machineryMotor vehiclesAerospaceHousehold appliancesPharmaceuticalsPharma+K25 + med techsMetalsOther

Food & kindred products 20 X

Textile mill products 22 X

Industrial inorganic chemistry 281 X

Industrial organic chemistry 286 X

Plastics materials & synthetic resins 282 X

Agricultural chemicals 287 X

Soaps, detergents, cleaners, perfumes, cosmetics & toiletries 284 X

Paints, varnishes, lacquers, enamels, & allied products 285 X X

Miscellaneous chemical products 289 X

Drugs & medicines 283 X X

Petroleum & natural gas extraction & refining 13, 29 X

Rubber & miscellaneous plastics products 30 X

Stone, clay, glass & concrete products 32 X

Primary ferrous products A* X

Primary & secondary non-ferrous metals B* X

Fabricated metal products C* X

Engines & turbines 351 X X

Farm & garden machinery & equipment 352 X

Construction, mining & material handling machinery & equipment 353 X X

Metal working machinery & equipment 354 X X

Office computing & accounting machines 357 X

Special industry machinery, except metal working 355 X

General industrial machinery & equipment 356 X

Refrigeration & service industry machinery 358 X

Miscellaneous machinery, except electrical 359 X

Electrical transmission & distribution equipment 361, 3825 X

Electrical industrial apparatus 362 X X

Household appliances 363 X X

Electrical lighting & wiring equipment 364 X

Miscellaneous electrical machinery, equipment & supplies 369 X X

Radio & television receiving equipment except communication types 365 X X

Electronic components & accessories & communications equipment 366-367 X

Motor vehicles & other motor vehicle equipment 371 X

Guided missiles & space vehicles & parts 376 X

Ship & boat building & repairing 373 X

Railroad equipment 374 X

Motorcycles, bicycles, & parts 375 X

Miscellaneous transportation equipment D* X

Ordinance except missiles 348, 3795 X

Aircraft & parts 372 X

Professional & scientific instruments E* X X

All other SIC's 99 X

* Note; patent to SIC assignment is from the US PTO based on the 1972 Standard Industrial Classifications. A: SICs 331, 332, 3399, 3462; B: 

SICs 333-336, 339 (ex. 3399), 3463; C: SICs 34 (ex. 3462, 3463, 348); D: SICs 379 (except 3795); E: SICs 38 (except 3825).
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 116

ID MSA name Cnty LQ Cnty LQ Cnty LQ Cnty LQ Cnty LQ

4 I Altoona, PA MSA X

5 I Anniston, AL MSA

6 I Asheville, NC MSA X X

10 I Binghamton, NY MSA X X X

11 I Birmingham, AL MSA X

14 I Charleston, WV MSA X

16 I Chattanooga, TN-GA MSA X X

21 I Cumberland, MD-WV MSA

22 I Decatur, AL MSA

23 I Elmira, NY MSA

24 I Erie, PA MSA X X

25 I Florence, AL MSA X

26 I Gadsden, AL MSA

28 I Greenville-Spartanburg-Anderson MSA X X X X

29 I Hagerstown, MD PMSA

33 I Huntington-Ashland, WV-KY-OH MSA

34 I Huntsville, AL MSA X X

35 I Jamestown, NY MSA X

36 I Johnson City-Kingsport-Bristol, TN-VA MSA X X

37 I Johnstown, PA MSA

38 I Knoxville, TN MSA X X

47 I Parkersburg-Marietta, WV-OH MSA X X

48 I Pittsburgh, PA MSA X X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA X X

53 I Sharon, PA MSA

54 I State College, PA MSA

55 I Steubenville-Weirton, OH-WV MSA

60 I Wheeling, WV-OH MSA X

61 I Williamsport, PA MSA X X

2 B Albany-Schenectady-Troy, NY MSA X X X X X X X X

3 B Allentown-Bethlehem-Easton, PA MSA X X X X X X

7 B Athens, GA MSA X

8 B Atlanta, GA MSA X X X X

13 B Canton-Massillon, OH MSA X X X X

17 B Cincinnati, OH-KY-IN PMSA X X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X X

32 B Hickory-Morganton-Lenoir, NC MSA

39 B Lexington, KY MSA X

43 B Montgomery, AL MSA X

50 B Roanoke, VA MSA X X X X

57 B Tuscaloosa, AL MSA

59 B Washington, DC-MD-VA-WV PMSA X X X X

62 B Youngstown-Warren, OH MSA X X

1 O Akron, OH PMSA XX XX XX

9 O Auburn-Opelika, AL MSA X

12 O Buffalo-Niagara Falls, NY MSA X X

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X X

19 O Columbus, GA-AL MSA

20 O Columbus, OH MSA X

30 O Hamilton-Middleton, OH PMSA X X X X X X

40 O Lynchburg, VA MSA X X X

41 O Mansfield, OH MSA X

42 O Memphis, TN-AR-MS MSA X

44 O Nashville, TN MSA X X

45 O Newark, NJ PMSA

46 O Newburgh, NY-PA PMSA X X X X X

49 O Reading, PA MSA X X X X

51 O Rochester, NY MSA X X X X X X X X

56 O Syracuse, NY MSA X X X X X

58 O Utica-Rome, NY MSA X

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia 

but adjacent to region.

Chemicals, 

plastics

Motor 

Instruments vehicles

Information 

technology

Industrial 

machinery

Appendix Table 10

Spatial concentration of patenting activity by technology area, (1990-1999)

Appendix Table 10 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 117

Appendix Table 10 continued

Spatial concentration of patenting activity by technology area, (1990-1999)

ID MSA name Cnty LQ Cnty LQ Cnty LQ Cnty LQ Cnty LQ

4 I Altoona, PA MSA

5 I Anniston, AL MSA

6 I Asheville, NC MSA X

10 I Binghamton, NY MSA X

11 I Birmingham, AL MSA X

14 I Charleston, WV MSA

16 I Chattanooga, TN-GA MSA X X

21 I Cumberland, MD-WV MSA

22 I Decatur, AL MSA

23 I Elmira, NY MSA X X X X

24 I Erie, PA MSA X X

25 I Florence, AL MSA

26 I Gadsden, AL MSA

28 I Greenville-Spartanburg-Anderson MSA X X X X

29 I Hagerstown, MD PMSA

33 I Huntington-Ashland, WV-KY-OH MSA

34 I Huntsville, AL MSA

35 I Jamestown, NY MSA X

36 I Johnson City-Kingsport-Bristol, TN-VA MSA

37 I Johnstown, PA MSA X

38 I Knoxville, TN MSA

47 I Parkersburg-Marietta, WV-OH MSA

48 I Pittsburgh, PA MSA X X X X X

52 I Scranton–Wilkes-Barre–Hazleton, PA MSA X

53 I Sharon, PA MSA X

54 I State College, PA MSA

55 I Steubenville-Weirton, OH-WV MSA X

60 I Wheeling, WV-OH MSA

61 I Williamsport, PA MSA X

2 B Albany-Schenectady-Troy, NY MSA X X X X X X X

3 B Allentown-Bethlehem-Easton, PA MSA X X X X X

7 B Athens, GA MSA X

8 B Atlanta, GA MSA X X X X X X

13 B Canton-Massillon, OH MSA X X X X

17 B Cincinnati, OH-KY-IN PMSA X X X X X X

27 B Greensboro, Winston-Salem, High Point MSA X

31 B Harrisburg-Lebanon-Carlisle, PA MSA X X

32 B Hickory-Morganton-Lenoir, NC MSA X

39 B Lexington, KY MSA

43 B Montgomery, AL MSA

50 B Roanoke, VA MSA

57 B Tuscaloosa, AL MSA

59 B Washington, DC-MD-VA-WV PMSA X X X X

62 B Youngstown-Warren, OH MSA X

1 O Akron, OH PMSA XX X X X

9 O Auburn-Opelika, AL MSA

12 O Buffalo-Niagara Falls, NY MSA X X X X X

15 O Charlotte-Gastonia-Rock Hill, NC-SC X X X

18 O Cleveland-Lorain-Elyria, OH PMSA X X X X X X

19 O Columbus, GA-AL MSA

20 O Columbus, OH MSA X X X

30 O Hamilton-Middleton, OH PMSA X X X X X X X X

40 O Lynchburg, VA MSA

41 O Mansfield, OH MSA

42 O Memphis, TN-AR-MS MSA X

44 O Nashville, TN MSA X X X

45 O Newark, NJ PMSA

46 O Newburgh, NY-PA PMSA X X X X X

49 O Reading, PA MSA X X X X

51 O Rochester, NY MSA X X X X

56 O Syracuse, NY MSA X X X X

58 O Utica-Rome, NY MSA

Note: I: MSA entirely contained within the Appalachian region; B: MSA spans Appalachian border; O: MSA completely outside Appalachia 

but adjacent to region.

Aerospace Metals Other

Household 

appliances

Pharma 

ceuticals
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 118

Appendix Table 11

SBIR/STTR/ATP award winners in ARC region, FY 2000

Company Name City St. Type Amount Technology

TENSION SYSTEMS L.L.C. Madison AL SBIR Aerospace

ADVANCED OPTICAL SYSTEMS, INC. Huntsville AL SBIR Aerospace

CFD Research Corp. Huntsville AL SBIR Aerospace

EAST WEST ENTERPRISES INC. Huntsville AL SBIR Aerospace

EAST WEST ENTERPRISES INC. Huntsville AL SBIR Aerospace

EAST WEST ENTERPRISES, INC. Huntsville AL SBIR Aerospace

GOMEZ RESEARCH ASSOC., INC. Huntsville AL SBIR Aerospace

SIMULATION TECHNOLOGIES, INC. Huntsville AL SBIR Aerospace

Aegis Technologies Group, Inc. Huntsville AL SBIR Aerospace

Aegis Technologies Group, Inc. Huntsville AL SBIR Aerospace

PLASMA PROCESSES, INC. Huntsville AL SBIR Aerospace

NEOTERIC TECHNOLOGIES, INC. Huntsville AL SBIR Aerospace

AI Signal Research, Inc. Huntsville AL SBIR Aerospace

Jaycor, Inc. Huntsville AL SBIR Aerospace

SRS Technologies Huntsville AL SBIR Aerospace

CUSTOM ANALYTICAL ENGINEERING SYSTEM Flintstone MD SBIR Aerospace

Odyssey Research Associates, Inc. Ithaca NY SBIR Aerospace

LANCORP Advanced Systems, Inc. Imperial PA SBIR $68,769 Aerospace

NANOMAT, INC. Somerset PA SBIR Aerospace

COMBUSTION PROPULSION & BALLISTIC State College PA SBIR Aerospace

PRESCHUTTI & ASSOC., INC. State College PA SBIR Aerospace

TRS Ceramics, Inc. State College PA SBIR Aerospace

TRS Ceramics, Inc. State College PA SBIR Aerospace

HVS TECHNOLOGIES, INC. STATE COLLEGE PA SBIR Aerospace

LYTEC LLC TULLAHOMA TN SBIR Aerospace

Accurate Automation Corp. Chattanooga TN SBIR Aerospace

Accurate Automation Corp. Chattanooga TN SBIR Aerospace

Luna Innovations, Inc. Blacksburg VA SBIR Aerospace

NanoSonic, Inc. Christiansburg VA SBIR Aerospace

F&S, Inc. Blacksburg VA SBIR Aerospace

Information Systems Laboratories, Inc. Huntsville AL STTR Aerospace

Accurate Automation Corp. Chattanooga TN STTR Aerospace

Luna Innovations, Inc. Blacksburg VA SBIR Aerospace, Industrial Machinery

Technology in Blacksburg, Inc. Blacksburg VA SBIR Aerospace, Industrial Machinery

Innovative Dynamics, Inc. Ithaca NY SBIR Aerospace, Motor Vehicles

AZ TECHNOLOGY Huntsville AL SBIR Chemicals

Physitron, Inc. Huntsville AL SBIR Chemicals

CAT Flight Services, Inc. Huntsville AL SBIR Chemicals

Super-Pulse Ithaca NY SBIR $100,000 Chemicals

E. H. Hall/Westfield Tanning Company Westfield PA SBIR $58,694/6 Months Chemicals

EXPORTech Company Inc New Kensington PA SBIR $400,000 Chemicals

EXPORTech Company Inc New Kensington PA SBIR $96,202 Chemicals

EXPORTech Company, Inc. New Kensington PA SBIR Chemicals

Media and Process Technology, Inc. Pittsburgh PA SBIR Chemicals

Nanomat, Inc. North Huntingdon PA SBIR Chemicals

SURFACE TREATMENT TECHNOLOGIES, INC. Tullahoma TN SBIR Chemicals

White Cliff Biosystems Co. Kingsport TN SBIR Chemicals

ATMOSPHERIC GLOW TECHNOLOGIES Rockford TN SBIR Chemicals

PETNet Pharmaceutical Services, Inc. Knoxville TN SBIR Chemicals

Cryogenic Applications F, Inc. Clinton TN SBIR Chemicals

Luna Innovations, Inc. Blacksburg VA SBIR Chemicals

NanoSonic, Inc. Christiansburg VA SBIR Chemicals

NanoSonic, Inc. Christiansburg VA SBIR Chemicals

HY-Tech Research Corp Radford VA SBIR $399,996 Chemicals

Luna Innovations, Inc. Blacksburg VA SBIR Chemicals

F&S, Inc./Luna Innovations, Inc. Blacksburg VA SBIR $69,974 Chemicals

Appendix Table 11 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 119

Appendix Table 11 continued

SBIR/STTR/ATP award winners in ARC region, FY 2000

Appendix Table 11 continues next page

Company Name City St. Type Amount Technology

TOUCHSTONE RESEARCH LABORATORY, LTD. Triadelphia WV SBIR Chemicals

RJ Lee Group, Incorporated Monroeville PA STTR Chemicals

SDR Plastics, Inc. Ravenswood WV STTR Chemicals

Time Domain Corporation Huntsville AL ATP $6,801,000 Communications services, software

Medical Archival Systems Incorporated Pittsburgh PA ATP $3,535,000 Communications services, software

CompAS Controls Inc. Indiana PA ATP $5,706,000 Communications services, software

Pennsylvania State University University Park PA ATP Communications services, software

Engineering Sciences Inc Huntsville AL SBIR $100,000 Communications services, software

CFD Research Corp. Huntsville AL SBIR Communications services, software

CFD Research Corp. Huntsville AL SBIR $399,985 Communications services, software

CFD Research Corp. Huntsville AL SBIR $399,946 Communications services, software

CFD Research Corp. Huntsville AL SBIR $99,984 Communications services, software

CFD Research Corp. Huntsville AL SBIR $99,947 Communications services, software

OPTICAL SCIENCES CORP. Huntsville AL SBIR Communications services, software

FlowLynx, Inc. Huntsville AL SBIR Communications services, software

Physitron, Inc. Huntsville AL SBIR $50,000 Communications services, software

AZ Technology, Inc. Huntsville AL SBIR Communications services, software

Earth Mapping International, Inc. Gainesville GA SBIR $99,996 Communications services, software

SEARCH TECHNOLOGY, INC. Norcross GA SBIR Communications services, software

MPI Software Technology, Inc. Starkville MS SBIR $75,000 Communications services, software

MPI SOFTWARE TECHNOLOGY, INC. Starkville MS SBIR Communications services, software

MPI Software Technology Starkville MS SBIR $400,000 Communications services, software

MPI Software Technology Starkville MS SBIR $400,000 Communications services, software

WETSTONE TECHNOLOGIES, INC. Freeville NY SBIR Communications services, software

3DVIS TECHNOLOGIES, INC. Vestal NY SBIR Communications services, software

DIAMOND VISIONICS LLC Vestal NY SBIR Communications services, software

Munex, Inc. Ithaca NY SBIR $69,011/6 Months Communications services, software

Odyssey Research Associates, Inc. Ithaca NY SBIR Communications services, software

MAYA Design Group, Inc. Pittsburgh PA SBIR Communications services, software

TerraSim, Inc. Pittsburgh PA SBIR Communications services, software

Quantum Simulations, Inc. Murrysville PA SBIR $50,000 Communications services, software

Discovery Machine, Inc. Montgomery PA SBIR Communications services, software

Platform Digital, LLC Pittsburgh PA SBIR Communications services, software

Psychology Software Tools Pittsburgh PA SBIR $99,558 Communications services, software

TELE-TRACKING TECHNOLOGIES PITTSBURGH PA SBIR $100,000 Communications services, software

Q-CHEM, INC. EXPORT PA SBIR $551,979 Communications services, software

QSI Murrysville PA SBIR $100,000 Communications services, software

Accurate Automation Corp Chattanooga TN SBIR $399,999 Communications services, software

Genome Informatics Corporation Oak Ridge TN SBIR Communications services, software

IntraSpec, Inc. Oak Ridge TN SBIR Communications services, software

American Research Corporation of Virginia Radford VA SBIR $50,000 Communications services, software

D.N. American, Inc. Fairmont WV SBIR Communications services, software

Kraus Communication LLC Fairmont WV SBIR $299,974 Communications services, software

GrammaTech, Inc. Ithaca NY STTR Communications services, software

Torrington Company Norcross GA ATP Industrial Machinery

Hardinge, Inc. Elmira NY ATP $11,747,000 Industrial Machinery

Carnegie-Mellon University Pittsburgh PA ATP $13,720,000 Industrial Machinery

Kennametal Latrobe PA ATP Industrial Machinery

Aegis Technologies Group, Inc. Huntsville AL SBIR Industrial Machinery

CFD Research Corp. Huntsville AL SBIR Industrial Machinery

SRS Technologies Huntsville AL SBIR Industrial Machinery

Plasma Processes, Inc. Huntsville AL SBIR Industrial Machinery

Thortek Irvine KY SBIR Industrial Machinery

Global Aircraft Corp. Starkville MS SBIR $100,000 Industrial Machinery

AGILE SYSTEMS, INC. Bethel OH SBIR Industrial Machinery

LANCORP Advanced Engineering & Syst Pittsburgh PA SBIR Industrial Machinery
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 120

Appendix Table 11 continued

SBIR/STTR/ATP award winners in ARC region, FY 2000

Appendix Table 11 continues next page

Company Name City St. Type Amount Technology

Surface Treatment Technologies, Inc. Tullahoma TN SBIR Industrial Machinery

VPT, Inc. Blacksburg VA SBIR Industrial Machinery

NanoSonic, Inc. Christiansburg VA SBIR Industrial Machinery

NanoSonic, Inc. Christiansburg VA SBIR $399,800 Industrial Machinery

Rainbow Displays, Inc. Endicott NY ATP $4,568,000 IT and instruments

CFD Research Corp. Huntsville AL SBIR IT and instruments

CFD Research Corp. Huntsville AL SBIR IT and instruments

CFD Research Corp. Huntsville AL SBIR IT and instruments

Morgan Research Corporation Huntsville AL SBIR IT and instruments

Physitron Huntsville AL SBIR $100,000 IT and instruments

Aegis Technologies Group, Inc. Huntsville AL SBIR IT and instruments

United Applied Technologies, Inc. Huntsville AL SBIR IT and instruments

United Applied Technologies, Inc. Huntsville AL SBIR IT and instruments

Alabama Cryogenic Engineering, Inc. Huntsville AL SBIR IT and instruments

AI Signal Research, Inc. Huntsville AL SBIR IT and instruments

Photon-X, Inc. Huntsville AL SBIR IT and instruments

Search Technology, Inc. Norcross GA SBIR IT and instruments

GESAC, Inc. Boonsboro MD SBIR $97,897 IT and instruments

Applied Pulsed Power, Inc. Ithaca NY SBIR IT and instruments

Sunpower, Inc. Athens OH SBIR IT and instruments

ChemIcon Inc. Pittsburgh PA SBIR IT and instruments

TRS CERAMICS, INC. STATE COLLEGE PA SBIR $98,942 IT and instruments

Atolytics, Inc. State College PA SBIR $300,000 IT and instruments

Licom Technologies, Inc. State College PA SBIR IT and instruments

Licom Technologies, Inc. State College PA SBIR IT and instruments

SPECTRUMEDIX CORPORATION STATE COLLEGE PA SBIR $374,937 IT and instruments

LANCORP Advanced Engineering & Syst Pittsburgh PA SBIR IT and instruments

Nuclear Safeguards and Security Systems, LLC Clinton TN SBIR IT and instruments

CRYOMAGNETICS, INC. OAK RIDGE TN SBIR $152,260 IT and instruments

IntraSpec, Inc. Oak Ridge TN SBIR IT and instruments

LAMBDA INSTRUMENTS Blacksburg VA SBIR IT and instruments

LAMBDA INSTRUMENTS Blacksburg VA SBIR IT and instruments

Luna Innovations, Inc. Blacksburg VA SBIR IT and instruments

Luna Innovations, Inc. Blacksburg VA SBIR IT and instruments

Luna Innovations, Inc. Blacksburg VA SBIR IT and instruments

Luna Innovations, Inc. Blacksburg VA SBIR IT and instruments

PhotoSonic, Inc. Blacksburg VA SBIR IT and instruments

PRIME PHOTONICS, INC. Blacksburg VA SBIR IT and instruments

World Physics Tech., Inc. Blacksburg VA SBIR $100,000 IT and instruments

F&S, Inc. Blacksburg VA SBIR IT and instruments

F&S, Inc. Blacksburg VA SBIR IT and instruments

NanoSonic, Inc. Christiansburg VA SBIR IT and instruments

NanoSonic, Inc. Christiansburg VA SBIR IT and instruments

NanoSonic, Inc. Christiansburg VA SBIR IT and instruments

NanoSonic, Inc. Christiansburg VA SBIR $74,999 IT and instruments

Luna Innovations, Inc. Blacksburg VA SBIR IT and instruments

F&S, Inc. Blacksburg VA SBIR IT and instruments

Airak Engineering New Castle VA SBIR $100,000 IT and instruments

American Research Corporation of Virginia Radford VA SBIR IT and instruments

Touchstone Research Laboratory, Ltd Triadelphia WV SBIR IT and instruments

American Magnetics, Inc. Oak Ridge TN STTR IT and instruments

Envir Eng Group, Inc Knoxville TN STTR $448,547 IT and instruments

Luna Innovations, Inc. Blacksburg VA STTR $99,981 IT and instruments

Luna Innovations, Inc. Blacksburg VA STTR $99,962 IT and instruments

NanoSonic, Inc. Christiansburg VA STTR IT and instruments

Luna Innovations, Inc. Blacksburg VA STTR IT and instruments
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 121

Appendix Table 11 continued

SBIR/STTR/ATP award winners in ARC region, FY 2000

Company Name City St. Type Amount Technology

PPL Therapeutics, Inc. Blacksburg VA ATP $2,695,000 Pharm. and Medical Technologies

GEM PHARMACEUTICALS, INC. PELHAM AL SBIR $134,283 Pharm. and Medical Technologies

SOUTHERN BIOTECHNOLOGY BIRMINGHAM AL SBIR $106,000 Pharm. and Medical Technologies

VECTORLOGICS, INC. BIRMINGHAM AL SBIR $344,294 Pharm. and Medical Technologies

CFD Research Corp. Huntsville AL SBIR $500,766 Pharm. and Medical Technologies

X-RAY IMAGING INNOVATIONS BIRMINGHAM AL SBIR $113,923 Pharm. and Medical Technologies

BIOELASTICS RESEARCH, LTD BIRMINGHAM AL SBIR $373,079 Pharm. and Medical Technologies

IBBEX, INC. BIRMINGHAM AL SBIR $357,791 Pharm. and Medical Technologies

SOUTHERN BIOSYSTEMS, INC. BIRMINGHAM AL SBIR $99,579 Pharm. and Medical Technologies

VINE BROOK RESEARCH CORPORATION BIRMINGHAM AL SBIR $99,935 Pharm. and Medical Technologies

TRANSMOLECULAR, INC. BIRMINGHAM AL SBIR $260,053 Pharm. and Medical Technologies

ELGAVISH PARAMAGNETICS, INC. BIRMINGHAM AL SBIR $348,846 Pharm. and Medical Technologies

CYTRX CORPORATION NORCROSS GA SBIR $206,051 Pharm. and Medical Technologies

COMPUTER SOURCE GAINESVILLE GA SBIR $99,212 Pharm. and Medical Technologies

GLYCOBIOTICS, INC. COMER GA SBIR $100,000 Pharm. and Medical Technologies

BIOLINX, LLC HAGERSTOWN MD SBIR $114,270 Pharm. and Medical Technologies

Anasazi BioMedical Research, Inc. WINSTON-SALEM NC SBIR $105,000 Pharm. and Medical Technologies

Anasazi BioMedical Research, Inc. Winston-Salem NC SBIR Pharm. and Medical Technologies

CIELO INSTITUTE, INC ASHEVILLE NC SBIR $374,982 Pharm. and Medical Technologies

RED TAIL HAWK CORPORATION BINGHAMTON NY SBIR $98,797 Pharm. and Medical Technologies

BIOLIFE SOLUTIONS BINGHAMTON NY SBIR $189,747 Pharm. and Medical Technologies

BioLife Technologies Inc. Binghamton NY SBIR $100,000 Pharm. and Medical Technologies

TRANSONIC SYSTEMS, INC. ITHACA NY SBIR $531,710 Pharm. and Medical Technologies

BIOMED RESEARCH & TECHNOLOGIES WEXFORD PA SBIR $199,781 Pharm. and Medical Technologies

DYNAMIC CONTOURS, LLC ALLISON PARK PA SBIR $103,515 Pharm. and Medical Technologies

SEQUEL GENETICS, INC. PITTSBURGH PA SBIR $98,960 Pharm. and Medical Technologies

PROLX PHARMACEUTICALS, LP PITTSBURGH PA SBIR $1,087,690 Pharm. and Medical Technologies

BIOPORE, INC. STATE COLLEGE PA SBIR $98,925 Pharm. and Medical Technologies

REMCOM, INC. State College PA SBIR Pharm. and Medical Technologies

FOX FARSIGHT PRODUCTIONS, INC. BRIDGEVILLE PA SBIR $221,872 Pharm. and Medical Technologies

COMPUTATIONAL DIAGNOSTICS, INC. PITTSBURGH PA SBIR $237,525 Pharm. and Medical Technologies

CYBERGENETICS COMPANY PITTSBURGH PA SBIR $176,582 Pharm. and Medical Technologies

NEO GEN SCREENING, INC. PITTSBURGH PA SBIR $456,662 Pharm. and Medical Technologies

PSYCHOLOGY SOFTWARE TOOLS, INC. PITTSBURGH PA SBIR $382,079 Pharm. and Medical Technologies

AUTOMATED CELL, INC. PITTSBURGH PA SBIR $375,573 Pharm. and Medical Technologies

Clinical & Industrial Tech Seneca SC SBIR $399,892 Pharm. and Medical Technologies

ATOM SCIENCES, INC. OAK RIDGE TN SBIR $133,783 Pharm. and Medical Technologies

ATMOSPHERIC GLOW TECHNOLOGIES KNOXVILLE TN SBIR $102,430 Pharm. and Medical Technologies

SCI-TEC, INC. KNOXVILLE TN SBIR $124,251 Pharm. and Medical Technologies

BioNeutrics, Inc. Knoxville TN SBIR Pharm. and Medical Technologies

PETNet Pharmaceutical Services, Inc. Knoxville TN SBIR Pharm. and Medical Technologies

ApoCom, Inc. Knoxville TN SBIR Pharm. and Medical Technologies

TECHLAB, INC. BLACKSBURG VA SBIR $300,000 Pharm. and Medical Technologies

F&S, Inc./Luna Innovations, Inc. Blacksburg VA SBIR $69,953 Pharm. and Medical Technologies

American Research Corporation of Virginia Radford VA SBIR $200,000 Pharm. and Medical Technologies

SUMMIT CROSSROADS PRESS BERKELEY WV SBIR $98,166 Pharm. and Medical Technologies

Touchstone Research Laboratory, Ltd. Triadelphia WV SBIR Pharm. and Medical Technologies

CHEM-SPACE ASSOCIATES PITTSBURGH PA SBIR $99,844 Pharm. and Medical Technologies

F & S, Incorporated Blacksburg VA STTR $449,464 Pharm. and Medical Technologies

Automatika, Inc. Pittsburgh PA SBIR Other

Diamond Visionics Company Vestal NY Tibbetts Other

Transonic Systems, Inc. Ithaca NY Tibbetts Other

Cryomagnetics, Inc. Oak Ridge TN Tibbetts Other
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 122

Appendix Table 12

State-funded technology agencies and programs in ARC region

Appendix Table 12 continues next page

Name City/Town St. Technology Funding 2000 Type

Army Space and Missile Defense Command Huntsville AL Aerospace Research

NASA MSFC Tech Transfer Program Huntsville AL Aerospace $13,427,000 SBIR/STTR nationally

Army Aviation and Missile Command Redstone Arsenal AL Aerospace $95,000,000 Research

Center for Commercial Space Communications Blacksburg VA Aerospace Research

NSF Center for Materials Research, Lexington KY Chemicals Research

Center for Advanced Ceramic Technology Alfred NY Chemicals Research

Ceramics Corridor Innovation Center Alfred NY Chemicals Incubator

Material Research Science and Eng Center Pittsburgh PA Chemicals $900,000 Research

Center for Advanced Ceramic Materials Blacksburg VA Chemicals Research

Entrepreneurial Center, Birmingham AL Comm. services, software $600,000 Incubator

EBusiness Labs Alpharetta GA Comm. services, software Incubator

IT Alliance of Appalachian Ohio* Athens OH Comm. services, software N/A Tech Cntr

Pittsburgh Digital Greenhouse Pittsburgh PA Comm. services, software $3,500,000 Research

Virtual Environments Lab Morgantown WV Comm. services, software Research

Byrd Center for Educational Technologies Wheeling WV Comm. services, software Research

Challenger Learning Center, Wheeling WV Comm. services, software Research

Center for Identification Technical Research (CITER) a NSF Center WV Comm. services, software Research

Auburn Industrial Extension Service Auburn AL Industrial Machinery $900,000 MEP

Metropolitan Manufacturing Technology Center Birmingham AL Industrial Machinery $779,000 MEP

Bevill Manufacturing Technology Center Gadsen AL Industrial Machinery $1,083,000 MEP

Center for Automation and Robotics Huntsville AL Industrial Machinery $1,170,000 MEP

Alabama Productivity Center Tuscaloosa AL Industrial Machinery $569,000 MEP

Georgia Manufacturing Extension Partnership Atlanta GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Carrolton GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Cartersville GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Dalton GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Gainsville GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Newman GA Industrial machinery MEP

Georgia Tech, Econ Dev Institute Reg. Office Rome GA Industrial machinery MEP

Center for Manufacturing Systems Lexington KY Industrial machinery Research

Center for Robotics and Manufacturing Systems Lexington KY Industrial machinery Research

Kentucky Technology Service Morehead KY Industrial machinery MEP/SBIR

Kentucky Technology Service Somerset KY Industrial machinery MEP/SBIR

Technology Extension Service Hagerstown MD Industrial machinery MEP

NC Industrial Extension Service, MEP Kings Mountain NC Industrial machinery MEP

Alliance for Manufacturing and Technology Binghamton NY Industrial machinery MEP

Great Lakes Manufacturing Center*** Cleveland OH Industrial machinery N/A MEP

Manufacturing Resource Office*** Columbus OH Industrial machinery N/A MEP

NW PA Industrial Resource Center Erie PA Industrial machinery MEP

SW PA Industrial Resource Center Pittsburgh PA Industrial machinery MEP

Penn State Engineering Research Center University Park PA Industrial machinery $1,000,000 Research

Penn State Semiconductor Mfg Tech Initiative University Park PA Industrial machinery $2,000,000 Research

Manufacturing Technology Center York PA Industrial machinery MEP

Manufacturing Field Office Greenville SC Industrial machinery MEP

University of Tennessee Center for Industrial Services Chattanooga TN Industrial machinery MEP

The Manufacturing Center at Tennessee Technical Univ Cookeville TN Industrial machinery Research

University of Tennessee Center for Industrial Services Knoxville TN Industrial machinery MEP

Center for Coal and Mining Technologies Blacksburg VA Industrial machinery Research

NSF Center for Power Electronics Blacksburg VA Industrial machinery Research

VPMEP Harrisonburg VA Industrial machinery MEP

VPMEP Roanoke VA Industrial machinery MEP

Manufacturing Technology Center of SW VA Wytheville VA Industrial machinery MEP

WV MEP Bridgeport WV Industrial machinery MEP

Byrd Institute for Advanced Flexible Manufacturing Huntington WV Industrial machinery Research

WV MEP Huntington WV Industrial machinery MEP

WV MEP Rocket Center WV Industrial machinery MEP

WV MEP South Charleston WV Industrial machinery MEP

Lehigh Univ Center for Optical Technologies Industrial machinery $1,000,000 Research

Lehigh Univ Visteam Systems/PennState Industrial machinery $1,000,000 Research

BizTech Huntsville AL IT and instruments $225,000 Incubator

Integrated Electronics Engineering Center Binghamton NY IT and instruments Research

Fiber and Electro-optics Research Center Blacksburg VA IT and instruments Research

Center for Wireless Telecommunications Blacksburg VA IT, instruments, Comm. services, software Research
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 123

Appendix Table 12 continued

State-funded technology agencies and programs in ARC region

Name City/Town St. Technology Funding 2000 Type

Ohio SBDC at Ohio University Athens OH N/A $222,823 SBIR

Ohio SBDC at OMEGA Cambridge OH N/A $16,755 SBIR

Ohio SBDC at Kent State U., Columbiana East Liverpool OH N/A $87,234 SBIR

Ohio SBDC at Southern State Community College Hillsboro OH N/A $74,930 SBIR

Ohio ITAC at Marietta College Marietta OH N/A $48,862 SBIR

SBDC at Marietta College Marietta OH N/A $159,653 SBIR

Ohio SBDC at Kent State U., Tuscarawas New Philadelphia OH N/A $101,129 SBIR

Ohio Mfg. SBDC at OSU Piketon Piketon OH N/A $26,688 SBIR

Southeast Ohio SBDC Southpoint OH N/A $160,344 SBIR

Ohio SBDC at Jefferson County Steubenville OH N/A $153,459 SBIR

Shoals Entrepreneurship Center Florence AL Other $330,000 Incubator

Center for Environmental Technology Muscle Shoals AL Other $779,000 MEP

Learning and Performance Support Lab, Athens GA Other Research

Center for Agriculture MD Other Research

Georgia Biotechnology Center Athens GA Pharm. and Medical Technologies Research

Medical Imaging Development Center Atlanta GA Pharm. and Medical Technologies Research

Cornell Institute for Biotechnology & Life Sciences Technology Ithaca NY Pharm. and Medical Technologies Research

Edison Biotechnology Institute Athens OH Pharm. and Medical Techno $2,300,000 Res Cntr

Ohio University Innovation Center** Athens OH Pharm. and Medical Techno $111,000 Incubator

OADI Technology Center Birmingham AL Pharm. and Medical Techno $266,000 Incubator

Center for Textile and Apparel Technology Alexander City AL Textile and Apparel $595,000 MEP

Alabama EPSCOR statewide AL $14,200,000 Research

Alabama Research Institute statewide AL $400,000 Research

Technology Assistance Program statewide AL in-kind only SBIR

Carroll Business Incubator Carrolton GA Incubator

SBIR Resource Program at Kennesaw State Univ. Kennesaw GA SBIR

EPSCOR program KY Research

Hagerstown Community College Technology Innovation Ctr Hagerstown MD Incubators

Allegany-Garrett ATC MD Research

Challenge Investment Program (Western winners?) MD Research

Maryland Industrial Partnership Program (Western winners?) MD Research

Potomac ATC MD Research

Regional Managers of DBED MD SBIR

Strategic Investment Fund (Western winners?) MD Research

Western MD SBDC MD SBIR

Northeast Business Incubator System Corinth MS Incubator

North Mississippi Entrepreneurship Institute Oxford MS Incubator

Mississippi Research Consortium (EPSCOR) Starkville MS Research

Mississippi Technology Center Starkville MS Incubator

NC SBTDC Asheville NC SBIR

NC SBTDC Boone NC SBIR

Haywood Community College Clyde NC MEP

NC SBTDC Cullowhee NC SBIR

Catawba Valley Community College Hickory NC MEP

NC SBTDC Hickory NC SBIR

NC SBTDC Winston-Salem NC SBIR

MVATC Technology and Incubator Center Utica NY Incubator

Ben Franklin Partnership – North East Bethlehem PA Incubator/SBIR

Innovation Works, Inc. Pittsburgh PA Incubator/SBIR

Ben Franklin Partnership– Central and Northern University Park PA Incubator/SBIR

PENNTAP, Penn State Technical Assistance Program University Park PA $655,014 MEP

Clemson Research Park Clemson SC Research

SBDC-Clemson University Region Clemson SC SBIR

First Base Ventures Greenville SC Incubator

SBDC-Greenville Area Greenville SC SBIR

SBDC-Spartanburg Area Greenville SC SBIR

SBDC-Upper Savannah Area Greenwood SC SBIR

EPSCOR SC Research

Chattanooga/Hamilton Business Development Center Chattanooga TN SBIR

SE Development District Chattanooga TN SBIR

Cleveland State Community College Cleveland TN SBIR

Regional Business Technology Incubator Cookeville TN Incubator

East Tennessee State University Johnson City TN SBIR

Appendix Table 12 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 124

Appendix Table 12 continued

State-funded technology agencies and programs in ARC region

Name City/Town St. Technology Funding 2000 Type

Fairview Technology Center Knoxville TN Incubator

Pellisippi State Technical Community College Knoxville TN SBIR

Tennessee Technology Development Corporation Knoxville TN Research

Oak Ridge Incubation Center Oak Ridge TN Incubator

Technology 2020 Oak Ridge TN Incubator

Tennessee Research Institute TN

TSBDCs TN

Business-Technology Center Blacksburg VA Incubator

CIT Blacksburg VA SBIR

CIT Roanoke VA SBIR

CIT Wise VA SBIR

PROMISE WV SBIR

W.Va. EPSCOR WV Research
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 125

Appendix Table 13

Science and engineering CIP codes

Science and engineering Classification of Instructional Programs codes by major disciplinary areas

Aggregated disciplinary area CIP code title CIP code

Aerospace Engineering, Aviation Science Aerospace, Aeronautical & Astronautic 14.0201

& Astrophysics Aeronautical & Aerospace Engineering Tech 15.0801

Aviation & Airway Science 49.0101

Astrophysics 40.0301

Biochemistry & Biomedical Engineering Biochemistry 26.0202

Biophysics 26.0203

Bioengineering & Biomedical Engineering 14.0501

Biological & Physical Sciences 30.0101

Biopsychology 30.1001

Botany, Biology, Bacteriology Botany, General 26.0301

 & Biotechnology Plant Pathology 26.0305

Plant Physiology 26.0307

Botany, Other 26.0399

Cell Biology 26.0401

Molecular Biology 26.0402

Cell & Molecular Biology, Other 26.0499

Biology, General 26.0101

Biological Sciences/life Sciences, Other 26.9999

Biological Tech./technician 41.0101

Microbiology/bacteriology 26.0501

Anatomy 26.0601

Ecology 26.0603

Marine/aquatic Biology 26.0607

Neuroscience 26.0608

Nutritional Sciences 26.0609

Parasitology 26.0610

Radiation Biology/radiobiology 26.0611

Toxicology 26.0612

Genetics, Plant & Animal 26.0613

Biometrics 26.0614

Biostatistics 26.0615

Biotechnology Research 26.0616

Evolutionary Biology 26.0617

Biological Immunology 26.0618

Virology 26.0619

Misc. Biological Specializations, Oth. 26.0699

Communications & Computer Sciences Educational/instructional Media Tech. 10.0101

& Technologies Photographic Tech./technician 10.0103

Radio & Television Broadcasting Tech. 10.0104

Communications Technol./technicians, Oth 10.0199

Computer & Information Sciences, Gen. 11.0101

Computer Programming 11.0201

Data Processing Tech./technician 11.0301

Information Sciences & Systems 11.0401

Computer Systems Analysis 11.0501

Computer Science 11.0701

Computer & Information Sciences, Other 11.9999

Computer Engineering 14.0901

Computer Engineering Tech./technician 15.0301

Electrical, Electronics & Communication 14.1001

Elec., Electronic & Comm. Engin. Tech. 15.0303

Laser & Optical Tech./technician 15.0304

Appendix Table 13 continues next page Electrical & Electronic Engin.-rel. Tech 15.0399
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 126

Appendix Table 13 continued

Science and engineering CIP codes

Science and engineering Classification of Instructional Programs codes by major disciplinary areas

Aggregated disciplinary area CIP code title CIP code

Environmental Engineering & Controls Water Quality/wastewater Treatment Tech 15.0506

Environmental & Pollution Control Tech. 15.0507

Environmental Control Tech, Oth. 15.0599

Environmental/environmental Health Engin 14.1401

Agricultural Sciences & Technology Agricultural Engineering 14.0301

Agriculture/agricultural Sciences, Gen. 02.0101

Agriculture/agricultural Sciences, Other 02.9999

Animal Sciences, General 02.0201

Agricultural Animal Breeding & Genetics 02.0202

Agricultural Animal Health 02.0203

Agricultural Animal Nutrition 02.0204

Agricultural Animal Physiology 02.0205

Dairy Science 02.0206

Poultry Science 02.0209

Animal Sciences, Other 02.0299

Food Sciences & Tech. 02.0301

Plant Sciences, General 02.0401

Agronomy & Crop Science 02.0402

Horticulture Science 02.0403

Plant Breeding & Genetics 02.0405

Agricultural Plant Pathology 02.0406

Agricultural Plant Physiology 02.0407

Plant Protection (pest Management) 02.0408

Range Science & Management 02.0409

Plant Sciences, Other 02.0499

Soil Sciences 02.0501

Zoology, General 26.0701

Entomology 26.0702

Pathology, Human & Animal 26.0704

Pharmacology, Human & Animal 26.0705

Physiology, Human & Animal 26.0706

Zoology, Other 26.0799

Forestry Science & Forestry Technology Forest Harvesting & Production Tech. 03.0401

Forest Products Tech./technician 03.0404

Forestry Sciences 03.0502

Wood Science & Pulp/paper Tech. 03.0509

Forestry & Related Sciences, Other 03.0599

Geological & Geophysical Engineering Atmospheric Sciences & Meteorology 40.0401

Geology 40.0601

Geochemistry 40.0602

Geophysics & Seismology 40.0603

Geological & Related Sciences, Other 40.0699

Earth & Planetary Sciences 40.0703

Geological Engineering 14.1501

Geophysical Engineering 14.1601

Mining Tech./technician 15.0901

Petroleum Tech./technician 15.0903

Mining & Petroleum Technol./tech, Other 15.0999

Mining & Mineral Engineering 14.2101

Ocean Engineering 14.2401

Appendix Table 13 continues next page Petroleum Engineering 14.2501
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 127

Appendix Table 13 continued

Science and engineering CIP codes

Science and engineering Classification of Instructional Programs codes by major disciplinary areas

Aggregated disciplinary area CIP code title CIP code

Mathematics Operations Research 27.0302

Applied Mathematics, Other 27.0399

Mathematical Statistics 27.0501

Mathematics, Other 27.9999

Mathematics 27.0101

Applied Mathematics, General 27.0301

Mathematics & Computer Science 30.0801

Basic Medical Science Medical Anatomy 51.1301

Medical Biochemistry 51.1302

Medical Physics/biophysics 51.1304

Medical Cell Biology 51.1305

Medical Genetics 51.1306

Medical Immunology 51.1307

Medical Microbiology 51.1308

Medical Molecular Biology 51.1309

Medical Neurobiology 51.1310

Medical Nutrition 51.1311

Medical Pathology 51.1312

Medical Physiology 51.1313

Medical Toxicology 51.1314

Basic Medical Sciences, Other 51.1399

Physics & Nuclear Engineering Nuclear Engineering 14.2301

Physical Sciences, General 40.0101

Miscellaneous Physical Sciences, Other 40.0799

Physical Sciences, Other 40.9999

Physical Science Technol./technicians, Oth 41.0399

Science Technol./technicians, Other 41.9999

Physics, General 40.0801

Chemical & Atomic/molecular Physics 40.0802

Elementary Particle Physics 40.0804

Plasma & High-temperature Physics 40.0805

Nuclear Physics 40.0806

Optics 40.0807

Solid State & Low-temperature Physics 40.0808

Acoustics 40.0809

Theoretical & Mathematical Physics 40.0810

Physics, Other 40.0899

Industrial Engineering & Technology Industrial/manufacturing Tech/technician 15.0603

Plastics Tech./technician 15.0607

Metallurgical Tech./technician 15.0611

Industrial Product. Technol./techn, Oth 15.0699

Quality Control Tech./technician 15.0702

Hydraulic Tech./technician 15.1103

Industrial/manufacturing Engineering 14.1701

Industrial Radiologic Tech./technician 41.0204

Nuclear/nuclear Power Tech./technician 41.0205

Nuclear & Industrial Radiologic Tech.,other 41.0299

Appendix Table 13 continues next page Textile Sciences & Engineering 14.2801
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 128

Appendix Table 13 continued

Science and engineering CIP codes

Science and engineering Classification of Instructional Programs codes by major disciplinary areas

Aggregated disciplinary area CIP code title CIP code

Mechanical Engineering, Engineering Biomedical Engineering-related Tech. 15.0401

Physics & Science, & Systems Computer Main. Tech./technician 15.0402

Engineering Electromechanical Tech./technician 15.0403

Instrumentation Tech./technician 15.0404

Robotics Tech./technician 15.0405

Electromechanical Instrum. & Maint. Tech 15.0499

Heating, Air Condition. & Refrig. Tech. 15.0501

Energy Management & Systems Tech./techn 15.0503

Engineering Design 14.2901

Engineering Mechanics 14.1101

Engineering Physics 14.1201

Engineering Science 14.1301

Engineering, General 14.0101

Engineering-related Tech/technician, Gen 15.1101

Engineering, Other 14.9999

Engineering-related Technol./techn, Oth 15.9999

Mechanical Engineering 14.1901

Automotive Engineering Tech./technician 15.0803

Mechanical Engineering/mechanical Tech. 15.0805

Mechanical Engineering-related Tech, Oth 15.0899

Systems Engineering 14.2701

Systems Science & Theory 30.0601

Materials Engineering & Science Ceramic Sciences & Engineering 14.0601

Material Engineering 14.1801

Materials Science 14.3101

Metallurgical Engineering 14.2001

Metallurgy 40.0701

Polymer/plastics Engineering 14.3201

Chemical Engineering & Technology Chemical Engineering 14.0701

Organic Chemistry 40.0504

Chemistry, General 40.0501

Analytical Chemistry 40.0502

Inorganic Chemistry 40.0503

Medicinal/pharmaceutical Chemistry 40.0505

Physical & Theoretical Chemistry 40.0506

Polymer Chemistry 40.0507

Chemistry, Other 40.0599

Chemical Tech./technician 41.0301
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 129

CIP code title CIP code CIP code title CIP code

Agricultural Business And Mgmt., General 01.0101 Financial Services Marketing Operations 08.0401

Agricultural Business/agribusiness Oper 01.0102 Floristry Marketing Operations 08.0503

Agricultural Economics 01.0103 Food Products Retail And Wholesale Opns 08.0601

Farm And Ranch Management 01.0104 Auctioneering 08.0701

Agricultural Business & Management, Oth 01.0199 General Buying Operations 08.0704

Agricultural Mechanization, General 01.0201 General Retailing Operations 08.0705

Agricultural Power Machinery Operator 01.0204 General Selling Skills And Sales Opns. 08.0706

Agricultural Mechanization, Other 01.0299 General Marketing Operations 08.0708

Ag. Prod. Workers And Managers, Gen. 01.0301 General Distribution Operations 08.0709

Ag. Animal Husbandry & Prod. Mgmt. 01.0302 Gen. Retail & Whlsale Opns. & Skills,oth 08.0799

Aquaculture Operations And Prod. Mgmt. 01.0303 Home Products Marketing Operations 08.0809

Crop Production Operations & Management 01.0304 Home & Office Products Mrkting Opns, Oth 08.0899

Ag. Prod. Workers And Managers, Other 01.0399 Hospitality & Rec. Marketing Opns, Gen 08.0901

Ag. & Food Products Process. Op. & Mgmt 01.0401 Hotel/motel Serv. Marketing Operation 08.0902

Ag. Supplies Retailing & Wholesaling 01.0501 Recreation Products/serv. Marketing Opns 08.0903

Animal Trainer 01.0505 Food Sales Operations 08.0906

Eques./equine Stds., Horse Mgmt. & Trgn 01.0507 Hospitality & Recrtn. Market. Opns, Oth 08.0999

Ag. Supplies And Related Svcs, Other 01.0599 Insurance Marketing Operations 08.1001

Horticulture Svcs. Ops. And Mgmt., Gen. 01.0601 Tourism Promotion Operations 08.1104

Ornamental Horticulture Ops. And Mgmt. 01.0603 Travel Services Marketing Operations 08.1105

Greenhouse Operations And Management 01.0604 Tourism & Travel Serv. Market. Opns,oth 08.1199

Landscaping Operations And Management 01.0605 Vehicle Parts & Accessories Market. Opn 08.1203

Nursery Operations And Management 01.0606 Vehicle Marketing Operations 08.1208

Turf Management 01.0607 Vehicle & Petrol. Prods. Market. Ops, Oth 08.1299

Horticulture Svcs. Ops. And Mgmt., Oth. 01.0699 Health Products & Services Marketing Ops 08.1301

International Agriculture 01.0701 Marketing Opns/market. & Distrib.,other 08.9999

Agricultural Business & Production, Oth 01.9999 Communications, General 09.0101

Agricultural Extension 02.0102 Advertising 09.0201

Natural Resources Conservation, General 03.0101 Journalism 09.0401

Environmental Science/studies 03.0102 Broadcast Journalism 09.0402

Natural Resources Management And Policy 03.0201 Mass Communications 09.0403

Nat. Resrcs. Law Enforce. & Protect. Svc 03.0203 Journalism And Mass Communication, Other 09.0499

Nat. Resrcs. Mgmt. & Protectv Svcs, Oth 03.0299 Public Relations & Organizational Comm. 09.0501

Fishing And Fisheries Sciences And Mgmt 03.0301 Radio And Television Broadcasting 09.0701

Forest Production And Processing, Other 03.0499 Communications, Other 09.9999

Forestry, General 03.0501 Card Dealer 12.0203

Forest Management 03.0506 Gaming & Sports Officiating Serv., Oth. 12.0299

Wildlife And Wildlands Management 03.0601 Funeral Services And Mortuary Science 12.0301

Conservation & Renewable Nat. Resrs, Other 03.9999 Cosmetic Services, General 12.0401

Apparel & Accessories Market. Opns, Gen 08.0101 Barber/hairstylist 12.0402

Fashion Merchandising 08.0102 Cosmetologist 12.0403

Fashion Modeling 08.0103 Electrolysis Technician 12.0404

Apparel & Accessories Market. Opns, Other 08.0199 Massage 12.0405

Business Services Marketing Operations 08.0204 Make-up Artist 12.0406

Personal Svcs Marketing Operations 08.0205 Cosmetic Services, Other 12.0499

Bus. & Personal Ser. Market. Opns, Oth 08.0299 Baker/pastry Chef 12.0501

Entrepreneurship 08.0301 Bartender/mixologist 12.0502

Culinary Arts/chef Training 12.0503 Aircraft Mechanic/technician, Airframe 47.0607

Food & Beverage/restaurant Opns. Manager 12.0504 Aircraft Mechanic/technician, Powerplant 47.0608

Kitchen Personnel/cook & Asst. Trng. 12.0505 Aviation Systems And Avionics Main. Tech 47.0609

Meatcutter 12.0506 Motorcycle Mechanic And Repairer 47.0611

Waiter/waitress And Dining Room Manager 12.0507 Vehicle & Mobile Equip. Mechanics & Repair 47.0699

Appendix Table 14

Selected excluded CIP codes

CIPs considered, but not included, in final list of science & engineering programs

Appendix Table 14 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 130

Appendix Table 14 continued

Selected excluded CIP codes

CIPs considered, but not included, in final list of science & engineering programs

CIP code title CIP code CIP code title CIP code

Culinary Arts & Related Services, Other 12.0599 Mechanics And Repairers, Other 47.9999

Personal & Miscellaneous Services, Other 12.9999 Drafting, General 48.0101

Architectural Engineering 14.0401 Architectural Drafting 48.0102

Civil Engineering, General 14.0801 Civil/structural Drafting 48.0103

Geotechnical Engineering 14.0802 Electrical/electronics Drafting 48.0104

Structural Engineering 14.0803 Mechanical Drafting 48.0105

Transportation And Highway Engineering 14.0804 Drafting, Other 48.0199

Water Resources Engineering 14.0805 Graphic & Printing Equip. Operator, Gen 48.0201

Civil Engineering, Other 14.0899 Mechanical Typesetter And Composer 48.0205

Naval Architecture & Marine Engineering 14.2201 Lithographer And Platemaker 48.0206

Engineering/industrial Management 14.3001 Printing Press Operator 48.0208

Architectural Engineering Techno/tech 15.0101 Computer Typography & Composition Equip 48.0211

Civil Engineering/civil Tech./technician 15.0201 Desktop Publishing Equipment Operator 48.0212

Occupational Safety & Health Tech./techn 15.0701 Graphic & Printing Equip. Operator, Oth 48.0299

Quality Control & Safety Technol./tech. 15.0799 Upholsterer 48.0303

Construction/building Tech./technician 15.1001 Shoe, Boot And Leather Repairer 48.0304

Surveying 15.1102 Leatherworkers And Upholsterers, Other 48.0399

Astronomy 40.0201 Machinist/machine Technologist 48.0501

Paleontology 40.0604 Machine Shop Assistant 48.0503

Oceanography 40.0702 Sheet Metal Worker 48.0506

Electrical And Electronics Equipment Ins 47.0101 Tool And Die Maker/technologist 48.0507

Business Machine Repairer 47.0102 Welder/welding Technologist 48.0508

Communication Sys. Installer & Repairer 47.0103 Precision Metal Workers, Other 48.0599

Computer Installer And Repairer 47.0104 Woodworkers, General 48.0701

Indus. Electronics Installer & Repairer 47.0105 Furniture Designer And Maker 48.0702

Major Appliance Installer And Repairer 47.0106 Cabinet Maker And Millworker 48.0703

Electrical And Electronics Equipment Ins 47.0199 Woodworkers, Other 48.0799

Heating, Air Conditioning And Refrigerat 47.0201 Precision Production Trades, Other 48.9999

Heavy Equipment Main. And Repairer 47.0302 Aircraft Pilot And Navigator (professional) 49.0102

Industrial Machinery Main. And Repairer 47.0303 Aviation Management 49.0104

Indus. Equip. Main. And Repairers, Oth. 47.0399 Air Traffic Controller 49.0105

Instrument Calibration And Repairer 47.0401 Flight Attendant 49.0106

Gunsmith 47.0402 Aircraft Pilot (private) 49.0107

Locksmith And Safe Repairer 47.0403 Air Transportation Workers, Other 49.0199

Musical Instrument Repairer 47.0404 Construction Equipment Operator 49.0202

Watch, Clock And Jewelry Repairer 47.0408 Truck, Bus & Oth. Commercial Vehicle Op 49.0205

Miscellaneous Mechanics & Repairers, Oth 47.0499 Vehicle And Equipment Operators, Other 49.0299

Stationary Energy Sources Installer/oper 47.0501 Fishing Tech/comm Fishing 49.0303

Auto/automotive Body Repairer 47.0603 Diver (professional) 49.0304

Auto/automotive Mechanic/technician 47.0604 Marine Main. And Ship Repairer 49.0306

Diesel Engine Mechanic And Repairer 47.0605 Marine Science/merchant Marine Officer 49.0309

Small Engine Mechanic And Repairer 47.0606 Water Transportation Workers, Other 49.0399

Transportation And Materials Moving Work 49.9999 Medical Laboratory Technician 51.1004

Chiropractic (d.c., D.c.m.) 51.0101 Medical Technology 51.1005

Communication Disorders, General 51.0201 Optometric/ophthalmic Laboratory Tech. 51.1006

Audiology/hearing Sciences 51.0202 Health & Medical Laboratory Tech., Oth. 51.1099

Speech-language Pathology 51.0203 Pre-dentistry Studies 51.1101

Speech-language Pathology And Audiology 51.0204 Pre-medicine Studies 51.1102

Sign Language Interpreter 51.0205 Pre-pharmacy Studies 51.1103

Communication Disorders Sci & Serv, Oth 51.0299 Pre-veterinary Studies 51.1104

Community Health Liaison 51.0301 Health & Med. Preparatory Programs, Oth 51.1199

Dentistry (d.d.s., D.m.d.) 51.0401 Medicine (m.d.) 51.1201

Appendix Table 14 continues next page
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 131

Appendix Table 14 continued

Selected excluded CIP codes

CIPs considered, but not included, in final list of science & engineering programs

Appendix Table 14 continues next page

CIP code title CIP code CIP code title CIP code

Dental Clinical Sciences/graduate Dentis 51.0501 Medical Clinical Sciences (m.s., Ph.d.) 51.1401

Dental Assistant 51.0601 Alcohol/drug Abuse Counseling 51.1501

Dental Hygienist 51.0602 Psychiatric/mental Health Services Tech 51.1502

Dental Laboratory Technician 51.0603 Clinical And Medical Social Work 51.1503

Dental Services, Other 51.0699 Mental Health Services, Other 51.1599

Health System/health Services Admin. 51.0701 Nursing (r.n. Training) 51.1601

Hospital/health Facilities Admin. 51.0702 Nursing Administration (post-r.n.) 51.1602

Health Unit Coordinator/ward Clerk 51.0703 Nursing, Adult Health (post-r.n.) 51.1603

Health Unit Manager/ward Supervisor 51.0704 Nursing Anesthetist (post-r.n.) 51.1604

Medical Office Management 51.0705 Nursing, Family Practice (post-r.n.) 51.1605

Medical Records Administration 51.0706 Nursing, Maternal/child Health (post-r. 51.1606

Medical Records Tech./technician 51.0707 Nursing Midwifery (post-r.n.) 51.1607

Medical Transcription 51.0708 Nursing Science (post-r.n.) 51.1608

Health & Medical Admin. Services, Oth. 51.0799 Nursing, Pediatric (post-r.n.) 51.1609

Medical Assistant 51.0801 Nursing, Psych./mental Health (post-r.n 51.1610

Medical Laboratory Assistant 51.0802 Nursing, Public Health (post-r.n.) 51.1611

Occupational Therapy Assistant 51.0803 Nursing, Surgical (post-r.n.) 51.1612

Ophthalmic Medical Assistant 51.0804 Practical Nurse (l.p.n. Training) 51.1613

Pharmacy Technician/assistant 51.0805 Nurse Assistant/aide 51.1614

Physical Therapy Assistant 51.0806 Home Health Aide 51.1615

Physician Assistant 51.0807 Nursing, Other 51.1699

Veterinarian Assistant/animal Health Tec 51.0808 Optometry (o.d.) 51.1701

Health And Medical Assistants, Other 51.0899 Opticianry/dispensing Optician 51.1801

Cardiovascular Tech./technician 51.0901 Optical Technician/assistant 51.1802

Electrocardiograph Tech./technician 51.0902 Ophthalmic Medical Technologist 51.1803

Electroencephalograph Tech./technician 51.0903 Orthoptics 51.1804

Emergency Medical Tech./technician 51.0904 Ophthalmic/optometric Services, Other 51.1899

Nuclear Medical Tech./technician 51.0905 Osteopathic Medicine (d.o.) 51.1901

Perfusion Tech./technician 51.0906 Pharmacy (b. Pharm., Pharm.d.) 51.2001

Medical Radiologic Tech./technician 51.0907 Pharmacy Administration & Pharmaceutics 51.2002

Respiratory Therapy Technician 51.0908 Medical Pharmacology & Pharmaceutical Sci 51.2003

Surgical/operating Room Technician 51.0909 Pharmacy, Other 51.2099

Diagnostic Medical Sonography 51.0910 Podiatry (d.p.m., D.p., Pod.d.) 51.2101

Health & Med. Diagnostic & Treat Svc, Ot 51.0999 Public Health, General 51.2201

Blood Bank Tech./technician 51.1001 Environmental Health 51.2202

Cytotechnologist 51.1002 Epidemiology 51.2203

Hematology Tech./technician 51.1003 Health And Medical Biostatistics 51.2204

Health Physics/radiologic Health 51.2205 Franchise Operation 52.0702

Occupational Health & Industrial Hygiene 51.2206 Enterprise Management & Operation, Oth. 52.0799

Public Health Education And Promotion 51.2207 Finance, General 52.0801

Public Health, Other 51.2299 Actuarial Science 52.0802

Art Therapy 51.2301 Banking And Financial Support Services 52.0803

Dance Therapy 51.2302 Financial Planning 52.0804

Hypnotherapy 51.2303 Insurance And Risk Management 52.0805

Movement Therapy 51.2304 International Finance 52.0806

Music Therapy 51.2305 Investments And Securities 52.0807

Occupational Therapy 51.2306 Public Finance 52.0808

Orthotics/prosthetics 51.2307 Financial Management And Services, Other 52.0899

Physical Therapy 51.2308 Hospitality/administration Management 52.0901

Recreational Therapy 51.2309 Hotel/motel And Restaurant Management 52.0902

Vocational Rehabilitation Counseling 51.2310 Travel-tourism Management 52.0903

Rehabilitation/therapeutic Services, Oth 51.2399 Hospitality Services Management, Other 52.0999
The Geographic Clustering of High-Tech Industry, Science & Innovation in Appalachia 132

Appendix Table 14 continued

Selected excluded CIP codes

CIPs considered, but not included, in final list of science & engineering programs

CIP code title CIP code CIP code title CIP code

Veterinary Medicine (d.v.m.) 51.2401 Human Resources Management 52.1001

Veterinary Clinical Sciences (m.s., Ph.d.) 51.2501 Labor/personnel Relations And Studies 52.1002

Health Aide 51.2601 Organizational Behavior Studies 52.1003

Acupuncture And Oriental Medicine 51.2701 Human Resources Management, Other 52.1099

Medical Dietician 51.2702 International Business 52.1101

Medical Illustrating 51.2703 Mgmt. Info. Systems & Bus. Data Process 52.1201

Naturopathic Medicine 51.2704 Business Computer Programming/programmer 52.1202

Psychoanalysis 51.2705 Business Systems Analysis And Design 52.1203

Health Professions & Rel. Sciences, Oth 51.9999 Business Systems Networking And Telecomm 52.1204

Business, General 52.0101 Business Computer Facilities Operator 52.1205

Business Administration & Mgmt., Gen. 52.0201 Business Information And Data Processing 52.1299

Purchasing, Procurement & Contracts Mgmt 52.0202 Management Science 52.1301

Logistics And Materials Management 52.0203 Business Statistics 52.1302

Office Supervision And Management 52.0204 Bus. Quantitative Methods & Mgmt.,oth. 52.1399

Operations Management And Supervision 52.0205 Business Marketing/marketing Management 52.1401

Non-profit And Public Management 52.0206 Marketing Research 52.1402

Business Administration & Mgmt., Oth. 52.0299 International Business Marketing 52.1403

Accounting 52.0301 Marketing Management And Research, Other 52.1499

Accounting Technician 52.0302 Real Estate 52.1501

Accounting, Other 52.0399 Taxation 52.1601

Administrative Assistant/secretarial Sci 52.0401 Business Management & Admin. Serv., Oth 52.9999

Executive Assistant/secretary 52.0402

Legal Administrative Assistant/secretary 52.0403

Medical Administrative Asst./secretary 52.0404

Court Reporter 52.0405

Receptionist 52.0406

Information Processing/data Entry Tech. 52.0407

General Office/clerical & Typing Serv. 52.0408

Administrative & Secretarial Serv., Oth 52.0499

Business Communications 52.0501

Business/managerial Economics 52.0601

Enterprise Management & Operation, Gen. 52.0701

Note: Specific codes were selected from the following major CIP categories: 01 (Agricultural business and production), 02 (Agricultural 

sciences), 03 (Conservation and renewable natural resources), 08 (Marketing operations, marketing and distribution), 09 (Communications), 

10 (Communications technologies), 11 (Computer and information sciences), 12 (Personal and miscellaneous services), 14 (Engineering), 15 

(Engineering-related technologies), 26 (Biological sciences/life sciences), 27 (Mathematics), 40 (Physical sciences), 41 (Science technologies), 

47 (Mechanics and repairers), 48 (Precision production trades), 49 (transportation and materials moving workers), 51 (Health professions 

and related sciences), and 52 (business management and administrative services). See text discussion of criteria of selection within each 

category.