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From Innovation to Entrepreneurship

Connectivity-based Regional Development

Yasuyuki Motoyama

Innovation and entrepreneurship are often considered two sides of the same coin. But are the links between innovation and entrepreneurship as inextricable as we think? From Innovation to Entrepreneurship questions this seemingly interdependent relationship, highlighting the different requirements of innovation and entrepreneurship. This book disentangles theories of innovation and entrepreneurship, empirically revealing the overlaps and differences between them. Demonstrating that the pursuit of entrepreneurship is the key to economic development, Yasuyuki Motoyama explores the concept that people are at the heart of entrepreneurship ecosystems.
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Index

Yasuyuki Motoyama

Acs, Z. 12, 1719, 223, 289, 34, 39

Amezcua, A.S. 129, 131, 136

anchor companies 6, 43, 6061, 78, 83

Application Developers Alliance 99

Arch Grants

aim to promote and celebrate entrepreneurship 61, 131, 136

background to 634

business plan competition 114

connectivity at multiple levels 134

as “great environment” for startups 122

interactions

beyond industrial sector 66

proximity to enhance 667, 90

knowledge exchange 11516

as major support organization 62

number of participants interviewed 132

peer-based learning 645, 90, 11617

performance of firms 11415

recipients and supports

location of 68

network map of 70

scaling up companies 120

seed money 120, 131

support

collaboration and co-ordination between organizations of 712, 124

multiple layers of 6771, 123

psychological 656

Twitter accounts 99, 111, 123

Association for University Technology Managers (AUTM) 127, 1389

Audretsch, D.B. 1213, 17, 19, 23, 31, 34, 39

“big business” city 60

BioGenerator 62, 71

BioSTL 612, 6970, 106, 109

bootstrapping 3, 8791, 120, 129, 131

Business Dynamics Statistics (BDS)

limitations of data 29

longevity of new firms 134

metropolitan areas 35

in regression analysis 35, 144

reliability of data 29

revealing sharp rise of startup activities in St. Louis 61

startup rates in all industries 30, 144

business mentors 814, 91, 11112, 117

business plan competition 6, 635, 114, 130, 139

business plans 115, 13031, 138

business service companies 7785, 114, 11718

Cambridge Innovation Center (CIC) 1, 62, 121, 136

Capital Innovators 612, 678, 712, 99, 106, 111, 1234

Center for Emerging Technologies 62, 69, 99, 106, 111, 123

City of Fountains see Kansas City

co-ordination

between ESOs 1245

between support organizations 712, 90

collaboration

at local level 556

between support organizations 712

vertical 13

communities of Twitter accounts

Kansas City 1037, 11011, 123

St. Louis 10612, 123

connectivity

Arch Grants as locus of 64

embed in entrepreneurial context

recommendation 1345

universities’ ability to 139

between entrepreneurs and support organizations as crucial 137

facilitating local 556

increase within regions

recommendation 134

universities’ ability to 139

organized at regional level 42

as primary source of entrepreneurship development 140

as process activity 140

social media and content analysis enriching 141

continuous learning 45

CORTEX 612, 67, 90

Cultivation Capital 612, 712, 109, 111, 123

data for entrepreneurship 13941

Defense Advanced Research Projects Agency (DARPA) 128

Drucker, P.F. 910, 19

Economic Development Administration (EDA) 1278

ecosystem catalysis 567, 58

ecosystem studies 245

Edquist, C. 89, 1112

entrepreneurs

captivating 1367

classic versus casual styles 14, 113

cultivating variety of sources 1234, 129, 132

defining 910

developing and using new technologies 13, 131

ESOs

benefitting from co-ordination between 1245

importance of 1212

go-to place for 56, 58, 95, 135

importance of learning 45, 11516, 136

importance of peer- and mentor-based feedback and support organizations 11618

interviews

1 Million Cups 528, 116, 132

Arch Grants 6392, 132, 134

local learning system 1223

multiple layers of support for lone 6771

as people who create inventions 20

as people who execute business plans 130

as people who start new companies 2021

power of incremental and internal growth 12021, 131

role to identify market niche 11820, 130

Twitter accounts 947, 1038, 11112

universities increasing connectivity of 139

entrepreneurship

5-50 rule 34, 114

as buzzword 910

caveats and analogy 1324

commercialization opportunities 13

concept 810

data for 13941

definition 9

differentiating with innovation 910, 20, 22, 125

as driven by human-based activities 412

as driver of economic development 212

ecosystem studies 245

future research avenues 141

iceberg analogy 1334

just-in-time production system and 1378

as largely local phenomenon 22

local system of 256, 110, 1234, 141

measures of

areas covered 35

correlation with purchasing power 34

establishment-based 289

Inc. firms 31, 33

new firm creation in all industries 2930

new firm creation in high-tech industries 29, 312

regression analysis 3541, 1424

research activities 34

self-employment 278

as output and process 2026

policy recommendations

avoiding provision of full services 1367

avoiding public venture funds and incubators 136

creating go-to place for entrepreneurs 135

embedding connectivity 1345

increasing connectivity within regions 134

regional factors associated with 223, 41, 48

as risky business with major reorientation 11415

role of universities 139

Twitter accounts related to

information sources followed 95103

Kansas City 1037, 11011, 123

possibility of hidden 112

St. Louis 10612, 123

entrepreneurship model

comparison with innovation model 12932

summary of 129

entrepreneurship support organizations (ESOs)

co-ordination between 1245

importance of 1212

Kansas City 1047, 110, 123

network connections 70

St. Louis 62, 106, 109, 111, 123

Twitter accounts 968, 100, 1047, 10911, 123

see also support organizations

establishment-based measure 289

5-50 rule 34, 114

Feldman, M.P. 1213, 1617, 1920, 22, 24, 31

Freeman, C. 9, 11, 16

Gateway City see St. Louis

“go-getters” 84, 91

go-to place for entrepreneurs 56, 58, 95, 135

Godin, B. 7, 14, 126, 140

government

role of 7, 128

Twitter accounts 967, 100107, 10911

government support

Inc. firms 89

ineffectiveness 1289

linear model in 1278

provision of seed money 129

research funding 34, 38, 40, 66, 133, 139

growth

based on market niche 758, 9091, 119

incremental 87, 91, 12021, 129, 131

in innovation and entrepreneurship models 129, 131

waves of 10

health companies 768, 81, 846, 119, 132

Helzberg Entrepreneurship

Mentorship Program (HEMP)

82–3, 117

“hidden industrial policy” 128

high-growth companies

definition 31

facing pivots 114

hyper growth and survival 1334

interviews in Kansas City and St. Louis 7292, 145

model

college completion rate 39

map of firm ratios 33

regression analysis 357, 1424

significance of SBIR 38

similarity to high-tech startup model 37

VC-type investment 389, 120

prior studies on 25

valuing business mentors 117

high-tech

as not driving economy through entrepreneurship 40

synonymy with innovation 1920

high-tech companies

bias towards as cause of ineffectiveness 1289

Kansas City

as home to 434

survey of 4551, 578, 119

high-tech industries

as innovation measure 1516, 18

new firm creation, as measure of entrepreneurship 29, 312

high-tech model

college completion rate 39

population flux 3940

regression analysis 357, 1424

similarity to high-growth firm model 37

universities 38

use of variables 34

VC-type investment 38

human capital

education level and population flux as factors of 40

as element of local entrepreneurship ecosystem 24

importance of 39

innovation as function of 34

startup activities and 35

human transfer 1389

iceberg analogy 1334

Inc. firms

as entrepreneurship measure 31, 33

financial sources 89

as high-growth firms 31

interviews

advantages 73

bootstrapping and self-finance 8791, 120

business mentors 814, 91, 117

changes and pivots 7881, 91, 11415

cities conducted in 735, 1223

descriptive statistics 74

growth based on market niche 758, 9091, 119

locally recruited and trained talent 847, 912

number of participants 132

target firms 73

map of firm ratios 33

regression analysis 357, 1424

results 3842

incremental growth 87, 91, 12021, 129, 131

incubators

aim to provide comprehensive service 1312

recommendation to re-tailor operations 136

role of public sector 131

in St. Louis 62

survival during incubated period 129

T-Rex functioning as 61, 667, 121

individual company level

entrepreneurs having to learn 11516

entrepreneurship as risky 11415

identifying market niche 11820

importance of peer- and mentor-based feedback and support organizations 11618

power of incremental and internal growth 12021

Innovate VMS 61, 71

innovation

as buzzword 910

as coming from something other than research 47

definition 89, 74

differentiating with entrepreneurship 910, 20, 22, 125

dominant approach to promoting 7

Kansas City having right assets for 41, 44

measures and limitations 1420, 140

in relation to knowledge spillover 1214, 38

synonymy with high-tech 1920

systems of innovation theory 1012

see also linear model of innovation

“innovative entrepreneurship” sectors 28

interaction

beyond industrial sector 66

with business mentors 812

connectivity and 1345

importance of embedding 136

local nature of 1223

peer-based learning 534, 645, 115, 117

proximity to enhance 667, 90

psychological support 656

with specific universities 4850, 57

internal growth 12021

interviews

of 1 Million Cups entrepreneurs 528

advantages and drawbacks 141

of high-growth firms 7292, 145

possibly having selection bias 119, 132

invention 89, 16, 11920, 1257

IT companies 756, 78, 80, 838, 11718, 12021

ITEN 612, 678, 71, 93, 109, 111, 121, 123, 135

Jaffe, A.B. 12, 16, 31

job creation 212, 27, 6061, 89

just-in-time production system 1378

Kansas City

background to 435, 59

having right assets for innovation and entrepreneurship activities 41

interviews of high-growth firms 7292, 118, 12022, 125, 135

as metropolitan area 43

multiple circles of mentorships 117

startup rates in 412

survey of high-tech firms 4551, 578, 119

Twitter accounts

communities 1037, 11011, 123

most followed academic accounts 102

most followed association accounts 99

most followed ESO accounts 979

most followed government accounts 100102

most followed service providers 100

number of entries 94

number of followers 95

number of sources 945

types of 967, 123

see also 1 Million Cups (1MC)

Kauffman, E.M. 6, 823, 117, 123, 136

Kauffman Foundation 6, 45, 523, 82, 945, 97, 99, 106, 11011

KCSourceLink 94, 123

knowledge

“new” 14, 125

sharing 65

stock of 256

types to acquire 11516

knowledge spillover

dependent variable 34

literature on 1213, 20, 31, 34

taking place between entrepreneurs 4

knowledge spillover theory 14, 23, 25, 389, 48

KU Med 489

see also University of Kansas (KU)

Lab 1500 62, 69, 989, 109, 111

learning

continuous 45

experimental 116

importance for entrepreneurs 45, 11516, 136

interviews for portraying nature and level of 141

local system of 1223

as process activity 116, 140

see also peer-based learning

linear model of innovation

assumed processes of 7, 1256

caveats and analogy 1324

comparison with entrepreneurship model 12932

current policy following 125, 129

in government support 1278

ineffectiveness in 1289

revisited and applied to entrepreneurship 13941

summary of 129

in technology commercialization offices by universities 1267

local connections, facilitation of

55–6

local learning system 1223

locally recruited and trained talent 847

market niche

growth based on 758, 9091, 119

identifying 11820, 130

Marshall, A. 22

Mayer, H. 41, 43, 46, 5051

measures

of entrepreneurship 2735

of innovation 1420

mentor-based feedback 11618

mentors

contrasted to Twitter-based relationship 11112

presence of 814

as source of new ideas 4850, 56

St. Louis 62, 689, 71

metropolitan areas

divided between two states 44

Kansas City as 30th largest US 43

number and definition of 35

regression results at level of 445, 92, 120

right assets for innovation activities 41

startup rates 42

universities 38, 92

used as unit of analysis 29

Michael Jordan analogy 133

MIT 79, 11920

Mosaic Project 61

National Establishment Time-Series (NETS)

provision of detailed industry information 29

in regression analysis 356, 144

startup rates in high-tech sectors 32, 144

National Institute of Standards and Technology (NIST) 25, 128

National Institutes of Health (NIH) 34, 38, 40, 70, 144

National Nanotechnology Initiative 128, 140

National Science Foundation (NSF) 14, 140

National Venture Capital Association (NVCA) 889

network analysis

for community detection 1038

general Twitter following patterns 96103

methodology 935

missing data due to non-response as problematic 95

summary of results 10811

new firm creation

in all industries 2930

establishment-based data limitation 28

in high-tech industries 29, 312

niche market see market niche

1 Million Cups (1MC)

background to 523

demographic attracted to 141

difficulties of developing networks prior to attending 578, 122

entrepreneur interviews

ecosystem catalysis 567

facilitating local connections 556, 58

value of peer-to-peer learning 534, 57, 90, 116

example of embedding connectivity 1345

as major support organization 62, 70

number of participants interviewed 132

serving as go-to place for entrepreneurs 56, 58, 95, 135

open innovation systems 13

output

blurring with innovation input 1920

entrepreneurship as 2026

patents as measure of innovation 12, 1718, 140

of scientific and technological activities 14

patents

entrepreneurship and 140

as innovation measure 1619

innovation model 130, 1323

knowledge spillover and 12

startup activities 359, 40, 42, 445, 144

technology transfer office 1267

top US patent granted organizations 19

peer-based feedback 11618

peer-based learning

importance of

1MC 534, 57, 90, 116

Arch Grants 645, 90, 11617

interaction 534, 645, 115, 117

psychological support 656

value of 534, 57, 90, 116

peer-to-peer learning see peer-based learning

pivots and changes 7881, 91, 11415, 123, 131

policy and practice, current

comparison of models 12934

linear model

assumed processes of 7, 1256

in government support 1278

ineffectiveness in 1289

in technology commercialization offices by universities 1267

summary of models 129

policy implications

data for entrepreneurship 13941

entrepreneurship and just-in-time production system 1378

future research avenues 141

from technology transfer to human transfer 1389

policy recommendations

avoid captivating entrepreneurs or providing full services 1367

avoid public venture funds and incubators 136

connectivity

embed in entrepreneurial context 1345

increase within regions 134

create go-to place for entrepreneurs 135

Porter, M.E. 11, 1516, 22, 24, 110, 116

process

entrepreneurship as 2026

learning as 116, 140

Prosper 612

proximity 667, 90

psychological support 656

public venture funds 136

R&D

entrepreneurship rates and 23

in high-tech sectors 45, 489

as innovation measure

activities 1415, 1920

intensity 1516, 1819

personnel and expenditure 14, 18

in life cycle of technology transfer 127

regional case studies see Kansas City; St. Louis

regional clusters 40

regional divergence example 39

regional factors

associated with entrepreneurship 23, 41

for firms’ development 478, 51, 57

regional industrial structure 223

Regional Innovation Strategies (RIS) program 128

regional level

connectivity of entrepreneurs organized at 42

cultivation of variety of sources 1234

entrepreneurship support organizations

co-ordination between 1245

importance of 1212

importance of role model entrepreneurs 25

local learning system 1223

recommendation to increase connectivity 134

regional innovation system 1112

stock of knowledge 256

Twitter accounts 97, 99, 110

where production and innovation system is organized 11

regression analysis 3537, 1424

results 3842

San Jose 412, 142

Sandia National Laboratories 128

Schumpeter, J.A. 810, 2021, 74

seed money 1289, 1312

self-employment 278, 31

self-finance 8790, 120

Silicon Valley 22, 29, 41, 60, 75

SixThirty 612

Skandalaris Center 62, 712, 93, 1023, 106, 1089, 111, 121, 124

Small Business Administration (SBA) 13, 1718, 100101, 103, 105, 114, 128, 135

Small Business Innovation Research (SBIR) 12, 358, 40, 66, 11516, 144

St. Louis

Arch Grants

interaction beyond industrial sector 66

multiple layers of support 6771

peer-based learning 645

proximity to enhance interactions 667

psychological support 656

seed money 131

and startup ecosystem 634

background to 6, 5961

having right assets for innovation and entrepreneurship activities 41

interviews of high-growth firms 7292, 117, 12022

level of entrepreneurship 6, 29

major support organizations in

co-ordination between 712, 1245

location 68

names 62

network 70

overlapping functions 124

Twitter accounts

communities 10612, 123

most followed academic accounts 1023

most followed association accounts 99

most followed ESO accounts 979

most followed government accounts 100102

most followed service providers 100

number of entries 94 number of followers 95 number of sources 945 types of 967, 123

St. Louis Regional Chamber 61, 99, 106, 109

startup companies

in all industries 30, 35, 39, 144

effects of little population growth of low flow of people 40

in high-tech sectors 32, 356, 39, 40, 144

as net job creators in US 21

rates in metro areas and US 412

in St. Louis 6372, 122

university-based 129, 1389

startup ecosystem 6372

startup-related Twitter accounts 949, 103, 105, 11011

STL VentureWorks 71

support organizations

collaboration and co-ordination between 712

importance of 11618

see also entrepreneurship support organizations (ESOs)

surveys

advantages and drawbacks 141

of financial sources of Inc. firms 89, 120

of high-tech companies 4551, 578, 93, 1323

as innovation measure 1718

possibly having selection bias 119, 132

systems of innovation theory 1012, 14

T-Rex 3, 612, 667, 90, 111, 121, 136

talent

locally recruited and trained 847, 912

technology 478, 50

Taylor, F.W. 1378

technological infrastructure 20

technology commercialization offices

bridging efforts 13940

ineffectiveness 1289

linear model in 1267

Twitter accounts 102

technology talent 478, 50

technology transfer 1389

see also technology commercialization offices

Twitter

analysis

advantages and drawbacks 141

caution 110

methodology of 935

as novel 110

community detection

Kansas City 1036, 11011, 123

St Louis 10612, 123

following patterns 96103

local nature of interaction reflected by 123

summary of results 10812

universities

different roles in entrepreneurship 139

generation of startups 129, 1389

interaction with 4850, 57

linear model in technology commercialization offices 1268

local 79, 85, 912

patents or licenses from regional 132

research 245, 34, 358, 40, 44, 46, 51, 92, 139

Twitter accounts 96, 1023, 108, 110

University of Kansas (KU) 44, 4850, 85, 92, 102, 107, 110

University of Missouri – Kansas City (UMKC) 44, 4850, 85, 102

US Patent and Trademark Office (USPTO) 1, 16, 19

“valley of death” 7, 128, 139

venture capital (VC)

essential for entrepreneurial culture 24

government role to provide 128

not prerequisite for firm growth 25

as significant research factor 356

in St. Louis 62

venture capitalists (VCs)

business plans and 130

as financial source of Inc. firms 89

interviewed firms using finance from 88, 90

known to invest in high-tech sectors and high-growth companies 38

role of 889, 91, 12021

Washington University (WashU) 612, 72, 85, 923, 1023, 106, 1089, 111, 121, 124

work ethic 867