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REPORT - WORLD KNOWLEDGE
COMPETITIVENESS INDEX
ASHOK BHATLA
TECHNOLOGY MANAGEMENT
CONSULTANT
BS, MS, PMP, MICROSOFT, CISCO
CERTIFIED
ASHOK.BHATLA.WRITER@GMAIL.CO
M

As hok Bhatla – MS – Te c hnology Mgt,
PMP
World Knowledge Competitiveness Index (WKCI)








The WKCI is an integrated and overall benchmark of the knowledge
capacity, capability and sustainability of each region.
It shows the extent to which this knowledge is translated into economic
value, and transferred into the wealth of the citizens of each region.
The competitiveness of a region will depend on its ability to successfully
adapt to internal and external economic and social challenges, by providing
new economic opportunities, including higher quality jobs .
There are some other indexes used in the industry – like BCI – Business
Competitiveness Index, Innovation Index etc.
Center for International Competitiveness










Center for International Competitiveness is a Research organization which
tracks Competitiveness Data for different regions and countries.
The mission of the Centre is to provide a platform for stimulating and
disseminating research on competitiveness across the business,
policymaking, and academic communities.
They started tracking this data from year 2002.
The 2008 edition of the WKCI compares 145 regions across 19 knowledge
economy benchmarks.
Web Site - http://www.cforic.org
Benchmarks used for WKCI


GDP per capita



Economic Activity Rate



No. of managers / 1000 inhabitant



Employment in IT / 1000 inhabitant



Employment in Bio Tech and Chemicals / 1000 inhabitant.



Employment in Instrumentation and Electrical / 1000 inhabitant



Employment in High Tech Services / 1000 inhabitant



Per Capita Expenditure on R&D performed by Govt.



Per capita Expenditure on R&D performed by Business



No. of Patents / Million Inhabitants



Private Equity $ Per Capita



Labor Productivity.



Mean Gross Monthly Earnings



Per Capita Public Expenditure on School Education



Per Capita Public Expenditure on Higher Education
Cities in Top Rankings ( Year 2008 Data)
AMERICAS
AMERICAS
San Jose(1)
San Jose(1)
Los Angeles (11)
Los Angeles (11)
Boston, Cambridge (2)
Boston, Cambridge (2)
Bridgeport,
Bridgeport,
Stamford(4)
Stamford(4)
Hartford (3)
Hartford (3)
Providence (8)
Providence (8)
San Francisco(5)
San Francisco(5)
Grand Rapids (13)
Grand Rapids (13)
San Diego (10)
San Diego (10)
Seattle (7)
Seattle (7)

EUROPE
EUROPE
West Netherlands
West Netherlands
(19) Stockholm (6)
(19) Stockholm (6)
Suomi-Finland (23)
Suomi-Finland (23)
Iceland (14)
Iceland (14)
Denmark (36)
Denmark (36)
Brussels (47)
Brussels (47)
Ile De France (29)
Ile De France (29)
Luxembourg (34)
Luxembourg (34)
Eastern UK (54)
Eastern UK (54)

ASIA
ASIA
Tokyo (9)
Tokyo (9)
Kanagawa, Japan
Kanagawa, Japan
(24)
(24)
Shiga, Japan (12)
Shiga, Japan (12)
Singapore (27)
Singapore (27)
Cities Not in Top
Cities Not in Top
100
100
Shanghai (110)
Shanghai (110)
Seoul (107)
Seoul (107)
Beijing (135)
Beijing (135)
Bangalore (145)
Bangalore (145)
Data and Rankings from 2003


Total – 125 Regions
US and Canada- 55

San Francisco – 1
San Francisco – 1
Shanghai – 121
Shanghai – 121
Bangalore – 125
Bangalore – 125

Europe – 45,
APAC -18,
Asia – 7

Stockholm – 15
Stockholm – 15
Seoul – 109
Seoul – 109
Portland -- 16
Portland 16
Tokyo -- 15
Tokyo 15
Data and Rankings from 2008


Total – 145 Regions Analyzed
US and Canada- 63
Europe – 54

San Jose -1
San Jose -1
Shanghai – 110
Shanghai – 110
Bangalore – 125
Bangalore – 125
Stockholm – 6
Stockholm – 6

APAC -18
Asia – 10

Seoul – 107
Seoul – 107
Portland -- 22 – Gone down
Portland 22 – Gone down
Tokyo -- 9
Tokyo 9
Scenario in Americas










North American regions are seeing a overall decline. Rankings of New
York, Atlanta and Austin have gone down from year 2002.
Higher Education – mainly Maths and Science is becoming a challenge.
Govt. Funding for Basic Research going down. Innovation pipeline is
dried up. R&D Tax credits are not lucrative any more.
US is strong in Software and telecom related services, but manufacturing
base eroding especially in Steel and Automobile.
Interaction between Labs, Universities and Industries is the key to future
innovations – mainly in industries like Bio Tech and Alternative Energy.
Scenario in Europe


Higher Education is free in most of the countries.



Aging Population, Not enough workers available.



Strong in Pharmaceuticals, Heavy Machinery, Transport Systems



(Roche, Siemens, Novartis, ABB).



Scandinavian nations are at the top, followed by West Europe and
then Eastern countries.



Not strong in Software and related services.



Strong interaction between Universities and Industries.
Scenario in Asia










Significant gains have been made by a number of Asian regions, with
Singapore (27th), Kyoto (43rd), Taiwan (53rd) all moving rapidly up
the rankings, and Shanghai now ranked above cities such as Berlin.
Young population, emerging markets – (More cell Phone subscribers
in China than in US)
Lacking in R&D facilities for Basic Research – Govt labs mainly for
Defense Research purposes. Lacking Innovation and creativity.
Although India (or China) produces more engineers than US,
Education and Infrastructure are still remain a challenge.
Research in Bio Tech and Nano Technologies not yet started.
Innovation Model – Constant Interaction
Universities ––
Universities
Higher
Higher
Education and
Education and
Basic
Basic
Research
Research

Govt Policies ––
Govt Policies
(Economic and
(Economic and
Technology)
Technology)
and Govt
and Govt
Research Labs
Research Labs

INNOVATION &
INNOVATION &
COMPETITIVE
COMPETITIVE
ADVANTAGE
ADVANTAGE

Industries ––
Industries
Private Sector
Private Sector
Companies,
Companies,
Venture
Venture
Capitalists etc.
Capitalists etc.
San Jose – California, US


Top class Labs – PARC from Xerox – Even Samsung is partnering
with PARC



Top University System – UC Berkeley, UC Davis



Top Companies – Google, Cisco, Intel, Apple, Ebay, Yahoo



More than 20 Nobel Laureates have ties to Bay Area.





Engine of economic growth for the nation. If treated as a country,
California is the 6th largest economy in the World.
A large no. of venture capitalists in the Bay Area
Stockholm - Sweden


Stockholm is the economic centre of Scandinavia.



Stockholm has one of the largest ICT-clusters in the world



Higher Education is also financed by the state



There are 23 universities & university-colleges in Stockholm



More than 40 % of the inhabitants have some kind of higher
education.



Stockholm region has been awarded 16 Nobel Prizes in the past.



Outside US region, they are the most competitive.
Seoul – South Korea










Innovation is promoted at the National level
Korean Govt have setup small Technology cities called Technopolis (Example - Samsung Advanced Institute of Technology).New
Technopolis for Nano Technologies and Bio Technology “Osong BioTechnopolis” has opened in 2008
Internal competition among the Design Teams
The economy is export-driven, with production focusing on electronics,
automobiles, ships, machinery, petrochemicals and robotics
Korea ranks particularly high in the Education Index, where it is ranked
first in Asia and seventh worldwide
Bangalore - India










Almost 500 MNCs have offices in Bangalore – Google, MS, Intel, GE,
Boeing, SAP, Citibank etc. It’s called the Silicon Valley of India
Factory of Programmers and System Engineers
Some top Govt Research Organizations – ISRO and DRDO operate in
Bangalore
Indian Institute of Mgt, Indian Institute of Science – top Indian Institutes
operate in Bangalore.
Interaction between Universities and Industries is missing
Let’s try to understand this Map ----
Conclusion








Balance of power in the knowledge economy has become more
evenly spread across the globe.
Strong cooperation between Industries, Universities and Govt
Research is the key to innovation and Knowledge economy.
US needs to spend on Math and Science Education instead of
educating Wall Street Executives if it needs to maintain its
technological superiority.
Emerging economies like Russia, India and China need to
implement cohesive Innovation Policies if they want to take
advantage of the huge pool of skilled manpower.
Backup Material
Question 1


Sweden is on the top of the Rankings in Europe. Name some top
Corporations from Sweden.



Ericsson - Telecom



Volvo - Automobile



Electrolux – Appliances, Consumer Goods



Skansa - Construction



Atlas Copco – Capital Goods



H&M – Clothing, Retailing



ABB – Engineering , Heavy Machinery



IKEA - Furnishings
Question 2


500 MNCs operate in Bangalore. Why this city is on the bottom of the list?



Data Missing for Employment in IT and High Tech Services



Very Low employment in Bio Tech and Automotive sector







Low Per capita expenditure on R&D. Lots of Companies doing R&D in
Bangalore, but huge population negates the benefits.
Also, no. of patents applied for is negligible. All R&D effort is in Applied
Research and in Software Sector
Low Per capita expenditure on Primary education
Question 3








What do you see as the future of Portland region?
Portland region used to be called Silicon Forest. Slowly lots of
manufacturing companies moved to Asia for economic reasons.
Lots of thrust into Solar and Alternative Energy – Solar World, Spectra Watt,
Genentech. Skills available.
But then Tax structure seems to discourage small businesses and they can
move to Vancouver – Washington state. They still get to use all the facilities
of Portland – w/o paying Taxes.
Don’t see a bright future. We will have more of retail companies than high
Tech Companies. Retail Companies do not help in Innovation & Technology.
Question 4






Do you think Bay Area can survive on its strength in IT based industries?
I think we have reached a saturation point in IT. Companies cannot keep
on spending 8 % on IT related services.
I see lots of Consolidation in IT industry with the success of Cloud
Computing. Cloud Computing is supposed to reduce the footprint of IT
Infrastructure – meaning fewer IT professionals required.



California’s infrastructure is crumbling.



Not many young people move to California due to high cost of living.
Question 5




Why South Korea is not even in the top 100 although so many MNCs are
based in Seoul?
This was a disappointment. South Korea has lots of industry, research
facilities and business conglomerates. Still they were not in top 100.



I think they are lacking in basic research and not strong in IT and Telecom.



Low no. of Managers. Lacking in Managerial skills.
Question 6


Which region you see at the top in year 2020?



I see Seattle, Boston, Stockholm and Seoul in the top of the list in 2020.









Seoul is investing a lot in new technologies like Bio Tech and Nano Tech.
They already have a very strong industrial base & infrastructure.
Boston region is becoming the hub of all basic research in Nano, Bio Tech
and Alternative Energy. IBM is doing lots of work in Boston region.
Seattle already has good IT companies. Young, dynamic population. Govt
policies are business friendly. Tax structure is good.
European cities will lose out because of aging population.
Appendix (Backup Material)


Analysis based on Regression Technique
What is Regression









Assume you want to run a regression of WAGE on age, work
experience, education, gender, and a dummy for sector of employment
(whether employed in the public sector).
Wage = function(age, work experience, education, gender, sector)
Wage = b1 + b2*age + b3*work experience + b4*education +
b5*gender + b6*sector
Multiple Regression : How the outcome variable depends on the
independent variable / predictor variables
For example, how the Sales Price of a home depends on
variables like Sq. Feet, Bo. Of Bedrooms, crime rate, neighborhood
etc.
Overview of Multiple Regression


Some of the variables can be quantified



Some are subjective – cannot be measured
We need to find out:



What is the relationship between independent variables



What is the significance of an independent variable.



What is the best Predictor variable



If two variables are correlated, then knowing the score on one
variable will allow you to predict the score on the other
variable. The stronger the correlation, the closer the scores
will fall to the regression line and therefore the more accurate
the prediction.
What is SPSS








SPSS - Statistical Package for Social Science
Statistical technique used to establish the relationship of a dependent
variable, such as the home price, and one or more independent
variables, such as Sq. Foot, No. of Bedrooms, Crime Rate etc.
Which of these variables gives the most accurate prediction of the
dependent variable.
Variables which have more significant influence are called Predictor
variables.
Information about SPSS Software




SPSS (temporarily PASW) is a computer program used for
statistical analysis. Between 2009 and 2010 it was called PASW
(Predictive Analytics Software). The company announced July
28, 2009 that it was being acquired by IBM for US$1.2 billion. As
of January 2010, it became "SPSS: An IBM Company".
SPSS is among the most widely used programs for statistical
analysis in social science. It is used by market researchers,
health researchers, survey companies, government, education
researchers, marketing organizations and others
Key Findings based on Regressions


Govt expenditure on R&D is not impacting Knowledge Competency in a
positive way. (Govt. expenditure is highest in Baltimore and DC – but
these two cities do not appear in the top 20)



GDP also does not positively impact WKCI.



No. of Patents does not have a direct impact on the WKCI.





Employment in IT and Telecom greatly impacts the Index. In 2008, San
Jose had the highest employment in ICT and it retained the Rank of 1 in
Competitiveness Index.
No. of Managers/1000 Employees also does not improve the KCI. Eastern
UK had the highest no. of managers, but it’s KCI rank was 54
Regression Data
Data from 2008
Independent Variable
GDP per capita
Economic Activity Rate

Coefficients
0.001057343
-0.083745149

Number of Managers per 1,000 employees

0.022475706

Employment in IT and Computer Manufacturing per 1,000 inhabitants

0.438438231

Employment in Biotech & Chemicals per 1,000 inhabitants

0.109742672

Employment in Automotive and Mechanical Engineering per 1,000 inhabitants

0.00558031

Employment in Instrumentation and Electrical Machinery per 1,000 inhabitants

0.564067439

Employment in High-Tech Services per 1,000 inhabitants
Per Capita Expenditure on R&D performed by Government

0.021808146
-0.002010306

Per Capita Expenditures on R&D performed by Business

0.032391787

Number of Patents Registered per one million inhabitants

-0.002163819

Private Equity $ Per Capita
Labor Productivity
Mean Gross Monthly Earnings

0.012786664
8.84593E-05
0.002580807

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World innovation - Knowledge Competitiveness Index

  • 1. REPORT - WORLD KNOWLEDGE COMPETITIVENESS INDEX ASHOK BHATLA TECHNOLOGY MANAGEMENT CONSULTANT BS, MS, PMP, MICROSOFT, CISCO CERTIFIED ASHOK.BHATLA.WRITER@GMAIL.CO M As hok Bhatla – MS – Te c hnology Mgt, PMP
  • 2. World Knowledge Competitiveness Index (WKCI)     The WKCI is an integrated and overall benchmark of the knowledge capacity, capability and sustainability of each region. It shows the extent to which this knowledge is translated into economic value, and transferred into the wealth of the citizens of each region. The competitiveness of a region will depend on its ability to successfully adapt to internal and external economic and social challenges, by providing new economic opportunities, including higher quality jobs . There are some other indexes used in the industry – like BCI – Business Competitiveness Index, Innovation Index etc.
  • 3. Center for International Competitiveness      Center for International Competitiveness is a Research organization which tracks Competitiveness Data for different regions and countries. The mission of the Centre is to provide a platform for stimulating and disseminating research on competitiveness across the business, policymaking, and academic communities. They started tracking this data from year 2002. The 2008 edition of the WKCI compares 145 regions across 19 knowledge economy benchmarks. Web Site - http://www.cforic.org
  • 4. Benchmarks used for WKCI  GDP per capita  Economic Activity Rate  No. of managers / 1000 inhabitant  Employment in IT / 1000 inhabitant  Employment in Bio Tech and Chemicals / 1000 inhabitant.  Employment in Instrumentation and Electrical / 1000 inhabitant  Employment in High Tech Services / 1000 inhabitant  Per Capita Expenditure on R&D performed by Govt.  Per capita Expenditure on R&D performed by Business  No. of Patents / Million Inhabitants  Private Equity $ Per Capita  Labor Productivity.  Mean Gross Monthly Earnings  Per Capita Public Expenditure on School Education  Per Capita Public Expenditure on Higher Education
  • 5. Cities in Top Rankings ( Year 2008 Data) AMERICAS AMERICAS San Jose(1) San Jose(1) Los Angeles (11) Los Angeles (11) Boston, Cambridge (2) Boston, Cambridge (2) Bridgeport, Bridgeport, Stamford(4) Stamford(4) Hartford (3) Hartford (3) Providence (8) Providence (8) San Francisco(5) San Francisco(5) Grand Rapids (13) Grand Rapids (13) San Diego (10) San Diego (10) Seattle (7) Seattle (7) EUROPE EUROPE West Netherlands West Netherlands (19) Stockholm (6) (19) Stockholm (6) Suomi-Finland (23) Suomi-Finland (23) Iceland (14) Iceland (14) Denmark (36) Denmark (36) Brussels (47) Brussels (47) Ile De France (29) Ile De France (29) Luxembourg (34) Luxembourg (34) Eastern UK (54) Eastern UK (54) ASIA ASIA Tokyo (9) Tokyo (9) Kanagawa, Japan Kanagawa, Japan (24) (24) Shiga, Japan (12) Shiga, Japan (12) Singapore (27) Singapore (27) Cities Not in Top Cities Not in Top 100 100 Shanghai (110) Shanghai (110) Seoul (107) Seoul (107) Beijing (135) Beijing (135) Bangalore (145) Bangalore (145)
  • 6. Data and Rankings from 2003  Total – 125 Regions US and Canada- 55 San Francisco – 1 San Francisco – 1 Shanghai – 121 Shanghai – 121 Bangalore – 125 Bangalore – 125 Europe – 45, APAC -18, Asia – 7 Stockholm – 15 Stockholm – 15 Seoul – 109 Seoul – 109 Portland -- 16 Portland 16 Tokyo -- 15 Tokyo 15
  • 7. Data and Rankings from 2008  Total – 145 Regions Analyzed US and Canada- 63 Europe – 54 San Jose -1 San Jose -1 Shanghai – 110 Shanghai – 110 Bangalore – 125 Bangalore – 125 Stockholm – 6 Stockholm – 6 APAC -18 Asia – 10 Seoul – 107 Seoul – 107 Portland -- 22 – Gone down Portland 22 – Gone down Tokyo -- 9 Tokyo 9
  • 8. Scenario in Americas      North American regions are seeing a overall decline. Rankings of New York, Atlanta and Austin have gone down from year 2002. Higher Education – mainly Maths and Science is becoming a challenge. Govt. Funding for Basic Research going down. Innovation pipeline is dried up. R&D Tax credits are not lucrative any more. US is strong in Software and telecom related services, but manufacturing base eroding especially in Steel and Automobile. Interaction between Labs, Universities and Industries is the key to future innovations – mainly in industries like Bio Tech and Alternative Energy.
  • 9. Scenario in Europe  Higher Education is free in most of the countries.  Aging Population, Not enough workers available.  Strong in Pharmaceuticals, Heavy Machinery, Transport Systems  (Roche, Siemens, Novartis, ABB).  Scandinavian nations are at the top, followed by West Europe and then Eastern countries.  Not strong in Software and related services.  Strong interaction between Universities and Industries.
  • 10. Scenario in Asia      Significant gains have been made by a number of Asian regions, with Singapore (27th), Kyoto (43rd), Taiwan (53rd) all moving rapidly up the rankings, and Shanghai now ranked above cities such as Berlin. Young population, emerging markets – (More cell Phone subscribers in China than in US) Lacking in R&D facilities for Basic Research – Govt labs mainly for Defense Research purposes. Lacking Innovation and creativity. Although India (or China) produces more engineers than US, Education and Infrastructure are still remain a challenge. Research in Bio Tech and Nano Technologies not yet started.
  • 11. Innovation Model – Constant Interaction Universities –– Universities Higher Higher Education and Education and Basic Basic Research Research Govt Policies –– Govt Policies (Economic and (Economic and Technology) Technology) and Govt and Govt Research Labs Research Labs INNOVATION & INNOVATION & COMPETITIVE COMPETITIVE ADVANTAGE ADVANTAGE Industries –– Industries Private Sector Private Sector Companies, Companies, Venture Venture Capitalists etc. Capitalists etc.
  • 12. San Jose – California, US  Top class Labs – PARC from Xerox – Even Samsung is partnering with PARC  Top University System – UC Berkeley, UC Davis  Top Companies – Google, Cisco, Intel, Apple, Ebay, Yahoo  More than 20 Nobel Laureates have ties to Bay Area.   Engine of economic growth for the nation. If treated as a country, California is the 6th largest economy in the World. A large no. of venture capitalists in the Bay Area
  • 13. Stockholm - Sweden  Stockholm is the economic centre of Scandinavia.  Stockholm has one of the largest ICT-clusters in the world  Higher Education is also financed by the state  There are 23 universities & university-colleges in Stockholm  More than 40 % of the inhabitants have some kind of higher education.  Stockholm region has been awarded 16 Nobel Prizes in the past.  Outside US region, they are the most competitive.
  • 14. Seoul – South Korea      Innovation is promoted at the National level Korean Govt have setup small Technology cities called Technopolis (Example - Samsung Advanced Institute of Technology).New Technopolis for Nano Technologies and Bio Technology “Osong BioTechnopolis” has opened in 2008 Internal competition among the Design Teams The economy is export-driven, with production focusing on electronics, automobiles, ships, machinery, petrochemicals and robotics Korea ranks particularly high in the Education Index, where it is ranked first in Asia and seventh worldwide
  • 15. Bangalore - India      Almost 500 MNCs have offices in Bangalore – Google, MS, Intel, GE, Boeing, SAP, Citibank etc. It’s called the Silicon Valley of India Factory of Programmers and System Engineers Some top Govt Research Organizations – ISRO and DRDO operate in Bangalore Indian Institute of Mgt, Indian Institute of Science – top Indian Institutes operate in Bangalore. Interaction between Universities and Industries is missing
  • 16. Let’s try to understand this Map ----
  • 17. Conclusion     Balance of power in the knowledge economy has become more evenly spread across the globe. Strong cooperation between Industries, Universities and Govt Research is the key to innovation and Knowledge economy. US needs to spend on Math and Science Education instead of educating Wall Street Executives if it needs to maintain its technological superiority. Emerging economies like Russia, India and China need to implement cohesive Innovation Policies if they want to take advantage of the huge pool of skilled manpower.
  • 19. Question 1  Sweden is on the top of the Rankings in Europe. Name some top Corporations from Sweden.  Ericsson - Telecom  Volvo - Automobile  Electrolux – Appliances, Consumer Goods  Skansa - Construction  Atlas Copco – Capital Goods  H&M – Clothing, Retailing  ABB – Engineering , Heavy Machinery  IKEA - Furnishings
  • 20. Question 2  500 MNCs operate in Bangalore. Why this city is on the bottom of the list?  Data Missing for Employment in IT and High Tech Services  Very Low employment in Bio Tech and Automotive sector    Low Per capita expenditure on R&D. Lots of Companies doing R&D in Bangalore, but huge population negates the benefits. Also, no. of patents applied for is negligible. All R&D effort is in Applied Research and in Software Sector Low Per capita expenditure on Primary education
  • 21. Question 3     What do you see as the future of Portland region? Portland region used to be called Silicon Forest. Slowly lots of manufacturing companies moved to Asia for economic reasons. Lots of thrust into Solar and Alternative Energy – Solar World, Spectra Watt, Genentech. Skills available. But then Tax structure seems to discourage small businesses and they can move to Vancouver – Washington state. They still get to use all the facilities of Portland – w/o paying Taxes. Don’t see a bright future. We will have more of retail companies than high Tech Companies. Retail Companies do not help in Innovation & Technology.
  • 22. Question 4    Do you think Bay Area can survive on its strength in IT based industries? I think we have reached a saturation point in IT. Companies cannot keep on spending 8 % on IT related services. I see lots of Consolidation in IT industry with the success of Cloud Computing. Cloud Computing is supposed to reduce the footprint of IT Infrastructure – meaning fewer IT professionals required.  California’s infrastructure is crumbling.  Not many young people move to California due to high cost of living.
  • 23. Question 5   Why South Korea is not even in the top 100 although so many MNCs are based in Seoul? This was a disappointment. South Korea has lots of industry, research facilities and business conglomerates. Still they were not in top 100.  I think they are lacking in basic research and not strong in IT and Telecom.  Low no. of Managers. Lacking in Managerial skills.
  • 24. Question 6  Which region you see at the top in year 2020?  I see Seattle, Boston, Stockholm and Seoul in the top of the list in 2020.     Seoul is investing a lot in new technologies like Bio Tech and Nano Tech. They already have a very strong industrial base & infrastructure. Boston region is becoming the hub of all basic research in Nano, Bio Tech and Alternative Energy. IBM is doing lots of work in Boston region. Seattle already has good IT companies. Young, dynamic population. Govt policies are business friendly. Tax structure is good. European cities will lose out because of aging population.
  • 25. Appendix (Backup Material)  Analysis based on Regression Technique
  • 26. What is Regression      Assume you want to run a regression of WAGE on age, work experience, education, gender, and a dummy for sector of employment (whether employed in the public sector). Wage = function(age, work experience, education, gender, sector) Wage = b1 + b2*age + b3*work experience + b4*education + b5*gender + b6*sector Multiple Regression : How the outcome variable depends on the independent variable / predictor variables For example, how the Sales Price of a home depends on variables like Sq. Feet, Bo. Of Bedrooms, crime rate, neighborhood etc.
  • 27. Overview of Multiple Regression  Some of the variables can be quantified  Some are subjective – cannot be measured We need to find out:  What is the relationship between independent variables  What is the significance of an independent variable.  What is the best Predictor variable  If two variables are correlated, then knowing the score on one variable will allow you to predict the score on the other variable. The stronger the correlation, the closer the scores will fall to the regression line and therefore the more accurate the prediction.
  • 28. What is SPSS     SPSS - Statistical Package for Social Science Statistical technique used to establish the relationship of a dependent variable, such as the home price, and one or more independent variables, such as Sq. Foot, No. of Bedrooms, Crime Rate etc. Which of these variables gives the most accurate prediction of the dependent variable. Variables which have more significant influence are called Predictor variables.
  • 29. Information about SPSS Software   SPSS (temporarily PASW) is a computer program used for statistical analysis. Between 2009 and 2010 it was called PASW (Predictive Analytics Software). The company announced July 28, 2009 that it was being acquired by IBM for US$1.2 billion. As of January 2010, it became "SPSS: An IBM Company". SPSS is among the most widely used programs for statistical analysis in social science. It is used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations and others
  • 30. Key Findings based on Regressions  Govt expenditure on R&D is not impacting Knowledge Competency in a positive way. (Govt. expenditure is highest in Baltimore and DC – but these two cities do not appear in the top 20)  GDP also does not positively impact WKCI.  No. of Patents does not have a direct impact on the WKCI.   Employment in IT and Telecom greatly impacts the Index. In 2008, San Jose had the highest employment in ICT and it retained the Rank of 1 in Competitiveness Index. No. of Managers/1000 Employees also does not improve the KCI. Eastern UK had the highest no. of managers, but it’s KCI rank was 54
  • 31. Regression Data Data from 2008 Independent Variable GDP per capita Economic Activity Rate Coefficients 0.001057343 -0.083745149 Number of Managers per 1,000 employees 0.022475706 Employment in IT and Computer Manufacturing per 1,000 inhabitants 0.438438231 Employment in Biotech & Chemicals per 1,000 inhabitants 0.109742672 Employment in Automotive and Mechanical Engineering per 1,000 inhabitants 0.00558031 Employment in Instrumentation and Electrical Machinery per 1,000 inhabitants 0.564067439 Employment in High-Tech Services per 1,000 inhabitants Per Capita Expenditure on R&D performed by Government 0.021808146 -0.002010306 Per Capita Expenditures on R&D performed by Business 0.032391787 Number of Patents Registered per one million inhabitants -0.002163819 Private Equity $ Per Capita Labor Productivity Mean Gross Monthly Earnings 0.012786664 8.84593E-05 0.002580807