India City Competitiveness Report 2012

Competitiveness of India Cities

Institute for Competitiveness, India

INDIA IS THRIVING – NOW AND WILL IN FUTURE

% contribution in World’s GDP

European Union18% United

States16%

China18%

Japan9%

India4%

Others35%

2030 Projection

European Union26%

United States23%

China9%

Japan9%India

3%

Others31%

2010

0

2

4

6

8

10

12

4.03

5.22

3.77

8.37

8.28

9.32

9.27

9.82

4.93

9.108.81

7.80

5.30

GDP

grow

th (a

nnua

l %)

*value for 2012 and 2011 is for Q1

Source:- World Bank and Institute for Competitiveness Analysis


MAIN CONTRIBUTORS IN INDIA’S GROWTH

Maha-rashtra

Uttar Pradesh

Tamil Naidu

Andhra Pradesh

Gujarat West Bengal

Karnataka Rajasthan Kerala Delhi0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

775,020

394,499

391,372

381,942

365,295

317,786

279,932

204,398

193,383

191,6962010

-11

nom

inal

GD

P (i

n cr

ores

of r

upee

s)

Ahmedabad, Surat

Kolkata Bengaluru

Jaipur Thiruvananthapu-ram

Mumbai, Pune

Lucknow, Kanpur

Chennai Hyderabad

Source:- RBI and Institute for Competitiveness Analysis


TREND IN POPULATION SIZE AND GROWTH RATE (1901-2011)

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011 2021 2031 20410

200

400

600

800

1000

1200

1400

1600

1800

-5

0

5

10

15

20

25

30

238.4 252.09 251.32 278.98318.66

361.09439.23

548.16

683.329999999999

846.42

1028.74

1210.19

1338.64133333333

1494.63076190476

1650.62019047619

0.1

5.75

-0.03

11

14.22

13.31

21.51

24.8 24.6623.85

21.34

17.64

Population (in millions) Decadal Growth rate (in %)

Popu

lati

on (i

n m

illio

ns)

Dec

adal

Gro

wth

Rat

e (i

n %

)

Source:- Government of India Census and Institute for Competitiveness Analysis


THE RURAL-URBAN DIVIDE

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 20110%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

10.8 10.3 11.1 12 13.8 17.3 17.9 19.9 23.3 25.7 28.5 31.2

Urban Rural

10.3 11.1 1210.8 13.8 17.317.9 19.9 23.3

25.7 28.5 31.2



INCREASE IN NUMBER OF TOWNS, UAS AND VILLAGES (1971-2011)

1971 1981 1991 2001 2011

0

1000

2000

3000

4000

5000

6000

7000

8000

2921

40294689 5161

7935

Num

ber o

f Tow

ns

1971 1981 1991 2001 2011

0

50

100

150

200

250

300

350

400

231276

381 382 384

Num

ber o

f UAs

1971 1981 1991 2001 2011

520000

530000

540000

550000

560000

570000

580000

590000

600000

610000

556561 556014

579688

593732

608789

Num

ber o

f Vill

ages

Towns (in Numbers) UAs (in Numbers)

Villages (in Numbers)

Source:- Government of India Census and Institute for Competitiveness Analysis*UAs = Urban Agglomerations


URBANIZATION: SIGN OF A DEVELOPING EOCONOMY

1951 1961 1971 1981 1991 2001 20110

10

20

30

40

50

60

70

80

90

18.33

28.3

34.45

43.57

52.21

64.874

Degree of Urbanization Literacy Rates (%) Registered Motor Vehicles (No.)

Mobile Cellular Subscription (per 100 people)

Source:- Government of India Census, World Bank, Road Transport Year Book& Figure and Institute for Competitiveness Analysis


INDIAN STATES WITH HIGH GROWTH HAVE HIGH URBANIZATION RATE

0 100000 200000 300000 400000 500000 600000 700000 800000 900000 10000000.00

20.00

40.00

60.00

80.00

100.00

120.00

453367.60

5278.88

93867.16 171947.50

120513.18

201308.83

22997.23

413194.19

229352.99

44811.45

39217.9088162.87

326494.60

227049.88

200495.57

887905.30

7209.45

11407.39

4502.65

7663.08

166732.84

205511.09

241676.88

3096.19

409245.21

13561.81

516191.3048353.28

420113.36

GDP (Dec-11) in Rs. Crore

Urba

niza

tion

leve

l (in

%)

DISTRIBUTION OF TOWNS BY SIZE CLASS

Cities Classification Population 1951 1961 1971 1981 1991 2001 2011

Class I > 1,00,000 76 102 148 218 300 393

Class II 50,000-1,00,000 91 129 173 270 345 401

Class III 20,000-50,000 327 437 558 743 947 1151

Class IV 10,000-20,000 608 719 827 1059 1167 1344

Class V 5,000-10,000 1124 711 623 758 740 888

Class VI < 5,000 567 172 147 253 197 191

Class I UAs/Towns 468

Million plus UAs/Towns 53

Mega Cities 3

Greater Mumbai UA (12.05%)

Delhi UA (26.69%)

Kolkata UA(6.87%)




SNAPSHOT OF URBAN INDIA IN 2011

10 - 30 million 5 - 10 million 1 - 5 million 0.1 – 1 million

Cities Size Class By Population

Source:- India Urban Conference 2011: Evidence & Experience - IIHS

Competitiveness is the productivity with which a region utilizes its human, capital, and natural resources

Productivity determines wages and the standard of living – Productivity growth determines sustainable economic growth

It is not what industries a nation competes in that matters for prosperity, but how productively it competes in those industries

Productivity in an economy depends on a combination of domestic and foreign firms

Innovation in products and processes is necessary to drive productivity growth

Only productive businesses can create wealth and jobs States compete to offer the most productive environment for business

The public and private sectors play different but interrelated roles in creating a productive economy

Leading to the prosperity of the region


ENHANCING THE PROSPERITY OF URBAN INDIA via COMPETITIVENESS


INFLUENCES ON COMPETITIVENESS

WORLD ECONOMY

BROAD ECONOMIC AREAS

GROUP OF NEIGHBOURING NATIONS

NATIONS

STATES, PROVINCES

METROPOLITAN AREAS, RURAL AREAS

Multiple Geographic Levels

[Our Focus]

Source:- Institute for Strategy and Competitiveness


DRIVERS OF COMPETITIVENESS

Quality of overall business environment

Concentration of resources and urban growth

Policy Coordination among Multiple Levels of

Geography/Government


MEASURING COMPETITIVENESS: THE FRAMEWORK

Context for Firm Strategy and

Rivalry

Related and Supporting Industries

Demand Conditions

• Local rules and incentives that encourage investment and productivity .

- E.g. performance based salaries, incentives for capital investments, intellectual property protection• Vigorous local competition i.e., - Openness to foreign and local competition - Sophistication of company operations

• Local availability of suppliers and supporting industries

• Presence of clusters instead of isolated firms

Sophisticated and demanding local customers and needs e.g.,- Strict quality, safety, and environmental standards– Consumer protection laws – Government procurement ofadvanced technology – Early demand for products andServices.

Access to high quality business inputs i.e., - Natural endowments - Human resources - Capital availability - Physical infrastructure - Administrative infrastructure - Information infrastructure - Scientific and technological infrastructure

Factor Conditions


HIERARCHY OF CITY COMPETITIVENESS INDEX

Overall Competitiveness

Factor Conditions

Demand Conditions

Context for Strategy & Rivalry

Related & Supporting Industry

1. Financial

2. Physical

3. Communication

4. Administrative

5. Human Capacity

6. Innovation

1. Demographics

2. Income Distribution

and Spending

Pattern

1. Competition

Intensity & Diversity

of Firms

2. Business Incentives

1. Supplier

Sophistication

2. Institutional Support

Nearly 200 Indicators

SrinagarJammu

Shimla

LudhianaAmritsar

ChandigarhDehradun

GurgaonFaridabad

Allahabad

DelhiNoidaAgra

Meerut

LucknowKanpurJaipur

VaranasiPatna

Rajkot

AhmedabadVadodara

Surat

Ranchi Kolkata

Asansol

JamshedpurRaipur

DhanbadJabalpur

IndoreBhopal

BhubaneswarNashik

PuneMumbai

Guwahati

Nagpur

VishakhapatnamHyderabad

Vijayawada

KochiThiruvananthapuram

Kozhikode

BengaluruMysore

PuducherryMadurai

ChennaiCoimbatore


CITIES THAT WE STUDY


EVERY CITY HAS A DIFFERENT STORY

Crucial to understand each city as what is right for one city will not necessarily be right for the other.

“Mega Cities” “Million plus Cities”

Variables DELHI KOLKATA JAMSHEDPUR KOCHI

Population 16753235 4486679 2291032 3279860

No. of Branches of Commercial Banks 2177 1121 179 634

Literacy Rate: Female 80.93 84.98 67.33 94.27

No. of GSM users (per lakh) 265 145 11 19

Molestation Incidence 550 226 6 67

Ownership of consumer durable- Home Theater 23 25 19 31

Share of total passenger traffic (airways) 21.8 15.1 0.7 1.1

Consumer Price Index for Industrial Workers 169 178 103* 158

Starting a business cost (% per capita income) 51.1 39.6 51.5 47.2


LOOK AT THE ENTIRE PICTURE

For instance, Mumbai

Weak Areas Strong Areas

Number of slums

Number of accidental deaths

Total-corruption cases registered

Population density

0

20000

40000

60000

80000

61300

9093

1228

20925

Varia

bles

Media Reach-Press

Literacy rate: Males

Work Force Participation Rate (per 1000)

Paying Taxes (Time)

98.8

94.28

434

271

Varia

bles


Rank City Overall Competitiveness Score Factor Conditions Demand Conditions Context for Firm

Strategy & RivalryRelated & Supporting

Industries

1 Delhi 69.732 1 1 1 10

2 Mumbai 67.856 2 2 2 4

3 Chennai 62.323 4 5 5 2

4 Hyderabad 61.782 3 12 7 1

5 Kolkata 61.464 6 11 6 3

6 Gurgaon 61.167 7 7 4 23

7 Bengaluru 61.100 5 3 8 18

8 Noida 60.406 9 38 3 5

9 Pune 59.854 8 4 9 8

10 Ahmedabad 58.036 15 8 15 7

11 Nagpur 56.942 17 15 12 14

12 Chandigarh 56.842 10 17 25 15

13 Jaipur 56.263 18 6 19 26

14 Coimbatore 55.955 29 45 10 6

15 Kochi 55.884 28 23 14 11

16 Surat 55.726 26 10 17 20

17 Nashik 55.651 33 9 21 9

18 Indore 55.637 11 35 22 37

19 Thiruvananthapuram 55.434 22 18 18 28

20 Kozhikode 55.212 35 19 11 32

21 Mysore 55.118 12 39 30 33

22 Bhubaneswar 54.642 13 42 27 43

23 Vadodara 54.627 32 25 16 25

24 Rajkot 54.607 36 14 20 27

25 Lucknow 54.584 23 16 39 22

A GLIMPSE: CITY COMPETITIVENESS RANK

First 25 Cities


A GLIMPSE: CITY COMPETITIVENESS RANK

Rank City Overall Competitiveness Score Factor Conditions Demand Conditions Context for Firm Strategy

& RivalryRelated & Supporting

Industries

26 Madurai 54.570 38 36 13 24

27 Bhopal 54.322 16 40 28 40

28 Kanpur 54.318 19 49 38 12

29 Faridabad 54.097 20 32 36 34

30 Ludhiana 54.022 27 28 23 42

31 Vijayawada 53.964 30 20 32 30

32 Guwahati 53.961 14 46 31 46

33 Raipur 53.849 25 31 26 38

34 Vishakhapatnam 53.741 34 22 33 31

35 Patna 53.580 37 21 42 21

36 Jabalpur 53.249 24 50 34 35

37 Agra 53.157 39 29 46 16

38 Varanasi 53.039 45 41 37 13

39 Meerut 52.975 43 34 40 17

40 Puducherry 52.905 42 27 29 39

41 Asansol 52.813 47 13 35 36

42 Dehradun 52.725 31 30 47 41

43 Ranchi 52.575 40 33 41 29

44 Allahabad 52.573 46 26 48 19

45 Shimla 52.295 21 43 43 49

46 Amritsar 52.181 41 24 24 47

47 Jammu 50.621 44 47 49 48

48 Jamshedpur 50.475 49 44 44 44

49 Dhanbad 49.829 50 48 45 45

50 Srinagar 49.732 48 37 50 50

Next set of 25 Cities


TOTAL POPULATION VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.000

2000000

4000000

6000000

8000000

10000000

12000000

14000000

16000000

18000000

4380793

7208200

5959798

2490891

7723663

9588910

2368145

22463411054686

4681087

3472578

1698560

16753235

2682662

17989541514085

1260419

40102383272335

2460714

6663971

1526406

2291032

4572951

3279860

4486679

3089543

4588455

34878823041038

3447405

12478447

2994744

4653171

6109052

1674714

5772804

1244464

9426959

40621603799770

2912022

813384

1269751

6079231

3307284

41575683682194

45290094288113

f(x) = 491626.064114559 x − 23111674.8481309R² = 0.45608557418231

Microeconomic Competitiveness Score

Tota

l Pop

ulai

ton


TEACHERS IN GOVERNMENT SCHOOL VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.000

1000

2000

3000

4000

5000

6000

7000

8000

9000

6856

1527

8388

2994

1032 988

2541

2379

3257

962

3455

1960

5838

2881

1299 1433

6539

2706

37194091

5368

1931

2821

5987

1108

6608

1201

5347

3510

2083

4251

1709

2258

3137

7170

2042

5859

954

7254

154

32073544

482

1208

2047

3774

54565092

8128

f(x) = − 26.061098094641 x + 5060.10971761459R² = 0.0018373379481994


Teac

hers

in G

over

nmen

t Sch

ool


FEMALE LITERACY RATE VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.0055

60

65

70

75

80

85

90

95

100

59.16

80.29

62.67

72.8

70.47

84.8

76.6

82.0681.4

87.16

79.1679.61

80.93

64.7

75.2

77.6

85.82

78.4274.975.3017023968698

64.63

77.41

67.33

76.89

94.27

84.98

93.16

73.88

78.276.74

65.69

86.93

66.59

85.07

73.43 72.78

63.72

81.281.13

66.21

75.26

68.2

77.8

63.47

81.02

90.89

74.4

68.269.92

60

f(x) = 1.00161399019652 x + 20.1110934625408R² = 0.232115262095216


Fem

ale

Lite

racy

Rat

e


48.00 53.00 58.00 63.00 68.000.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.523

0.657

0.523

0.73

0.503

0.656

0.4860.496

0.7350.7440.744

0.587

0.72

0.431

0.68 0.68

0.445

0.662

0.4860.486

0.544

0.512

0.431

0.523

0.772

0.503

0.772

0.523

0.730.744

0.523

0.6630.6560.6630.663

0.523

0.421

0.6630.663

0.498

0.657

0.431

0.654

0.512

0.657

0.772

0.657

0.523

0.6620.662

f(x) = 0.010483927453262 x + 0.0204464566923889R² = 0.15918544815916


Educ

ation

Dev

elop

men

t Ind

ex

EDUCATION DEVELOPMENT INDEX VERSUS COMPETITIVENESS


CHEATING INCIDENCE VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.0020

220

420

620

820

1020

1220

1420

266

212

141

275

47

170

1108

163

524

148204

21

154

254240 151

80105

90

461

297

1271

277

750

385

124

234 264

187

53

174

77

663

188

26

168

31

63

126

689

115

209

298294

f(x) = 105.874884875056 x − 5342.86249159677R² = 0.283739149709869


Chea

ting

Inci

denc

e


DECADAL GROWTH RATE VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.000

10

20

30

40

50

60

20.96 22.3120.71

15.48

12.01

46.68

28.5

19.65 17.1

7.77

18.46

32.48

20.96

11.91

31.75

18.95

4.71

32.7

14.4

26.91

12.48

15.53

9.72

5.67.31

25.79

15

17.9515.92

8.01

13.3914.39

22.33

51.52

22.3427.72

30.34

34.65

19.87

23.9

12.58

23.56

42.19

2.25

14.16

17.32

8.15

11.89

f(x) = 0.392096913744252 x − 1.34194088310914R² = 0.0145767385471779


% d

ecad

al g

row

th ra

te (2

001-

11)


OWNERSHIP OF CONSUMER DURABLES - MOBILE VERSUS COMPETITIVENESS

48.00 53.00 58.00 63.00 68.0098

98.5

99

99.5

100

100.5

99

99.4

99.7

99.6

100 100

99.7

98.6

100

99.7

98.6

100100

99.3

99.8

100100

99.6

99.9100 100

100

99.3

99.7

99.3

100

99.3

100

98.6

99.7

99

99.899.7

99.7

100

98.4

98.6

100

99.5

98.6

99.5

98.6

100100

99.5

99.399.399.4

99.799.7f(x) = 0.0166353995871989 x + 98.6175998908751R² = 0.0197344931930818


Ow

ners

hip

of C

onsu

mer

Dur

able

s- M

obile


THE UNTAPPED ASSET OF INDIA: TIER 2-3 CITIES

Consists of a pool of opportunities

Avoids the pitfalls of the megacities

More people are moving towards them as they are facing scarcity of land in Mega cities

Each city has its own competitive edge

Preferred by many people

Tier I cities Tier II and III cities0%

10%

20%

30%

40%

50%

35%

50%

Grow

th (i

n %

)

Growth of organized retail

Source:- Report on “India Boarding” by TCS and Institute for Competitiveness Analysis


URBANIZATION LEVEL OF TIER 2 CITIES

AgraAsansolBhopal

CoimbatoreDhanbad

IndoreJaipur

JamshedpurKanpur

KochiKozhikode

LucknowLudhianaMaduariMeerutNagpurNashikPatnaRajkotSurat

ThiruvananthapuramVadodaraVaranasi

VijaywadaVishakapatnam

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00

45.8766.93

80.8475.83

58.1374.09

52.5155.55

65.9368.07

67.1566.20

59.1460.64

51.1368.30

42.5343.4843.4843.48

53.8049.54

43.4341.01

47.51

Urbanization level (in%)Source:- Census 2011 and Institute for Competitiveness Analysis


UNTANGLING THE LINKAGES BETWEEN CITY, COMPETITIVENESS & ECONOMIC GROWTH

More advanced economies are more urbanized economies

Cities tend to be the only place where companies and individuals find opportunities for successful economic activity

Rise of cities is seen as an inevitable part of development but also as a policy challenge

Avoid a political schism between metropolitan and rural regions

Cities have a different role to play in advanced economies

From the competitiveness perspective, the policy imperative is crucial for cities as well as for rural regions

Cities and the rural regions around them should cooperate closely

The case with Mumbai

Tried to manage the growth by creating artificial boundaries The approach failed and made living conditions worse Different policy approach is required that focuses on better public services and land use inside the city Competitiveness-oriented policy approach can be used that changes the economic fundamentals of where people live and work


SECTORWISE TOTAL INVESTMENTS IN PPP PROJECTS IN INDIA : 2011

Airports

Education

Energy

Health Care

Ports

Railways

Roads

Urban Development

0 50000 100000 150000 200000 250000

19131

1922.47

85141.18

1887.2

82402.67

3913.03

244289.176

99324.61

Project Cost (Rs. Crore)

Source:- PPP Database and Institute for Competitiveness Analysis


URBAN INFRASTRUCTURE: TRANSPORTATION IN INDIAN CITIES

Chaotic situation in most cities except the mega cities where the number of commuters is so high that the transportation seems weak Challenges:

- Vast gaps between demand and supply

- Poor infrastructure such as insufficient routes and roads

- Increase in private vehicles which leads to congestion and also slows down the speed of other vehicles such as buses etc. to 10-12 km

- Leads to environmental pollution

- Absence of comprehensive parking facilities in the city

Chennai Bengaluru Mumbai Ahmedabad Kolkata Delhi0

1000

2000

3000

4000

5000

6000

7000

0

50

100

150

200

250

300

3414

6110

4652

942 956

5771

278.59

205.38

154.02152.71

99.9

138.66

Total Fleet Held Vehicle Productivity (km/Bus/Day)

In N

umbe

r

In k

m/B

us/D

ay

Operations of Road Transportation in Major Cities: 2010-11

Source:- Road Transport and highways Ministry, 2010-11 and Institute for Competitiveness Analysis


OTHER MODES OF TRANSPORTATION

• The other major mode of transportation in cities is Railways• Though it is dominant for the inter city transportation only in cities• Also has a different face in every region such as in

- Delhi – Metro Rapid Transit System (MRTS) is main lifeline but Local Rails are also present

- Kolkata – The Underground Metro, The Local Rails and the tram, all are widely used by commuters

- Mumbai – Local Trains however, metro will be operational after short period, as reported by authorities

- Bengaluru – The introduction of Metro in the city has change the travelling experience of the commuters

United Kingdom

United States

Japan

Germany

China

India

South Africa

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

55019

9518

244235

78582

791158

903465

18865

In million passenger - km

Passengers carried by railways (million passenger-km)

Source:- World Bank and Institute for Competitiveness Analysis


URBAN INFRASTRUCTURE: WATER

Ahmedabad

Amritsar

Bengaluru

Bhopal

Chandiga

rh

Chennai

Coimbato

re

Indore

Jamsh

edpur

Kolkata

Mumbai

Nagpur

Nashik

Rajkot

Surat

Varanasi

Vijayw

ada

Visakh

apatn

am

Averag

e0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0

2

4

6

8

10

12

14

0.168 0.213 0.1850.182

0.332

0.131 0.2860.108

0.808

0.246

0.2460.267 0.248

0.146

0.188

0.2170.22

0.3050.244

2

11

4.5

1.5

12

5

3

0.75

6

8.3

4

5

3.5

0.3

2.5

7

3

1

4.3

Production/Population (m3/d/c) Water availability (hours)

Prod

uctio

n/Po

pula

tion

(m3/

d/c)

Wat

er A

vaila

bilit

y (h

ours

)

AVERAGE= 0.244

Source:- India Infrastructure Report 2011 and Institute for Competitiveness Analysis


URBAN CLUSTERS

“Geographical concentrations of industries that gain performance advantage through co-location”

Brings together companies, suppliers, service providers and associated institutions in a particular field The close proximity – by geography and activities - provides economic benefits Facilitate commercialization and new business formation through spinoffs and startups Cluster initiatives can act as policy catalysts for competitiveness Growth of one competitive firm generate demand for other related industries Forces firms to improve and innovate Facilitate technology and knowledge transfer that strengthens the cluster and promotes future growth

City Industrial Cluster

Raipur Iron & Steel Cluster

Ahmedabad Chemical Cluster

Surat Gem & Jewelry Cluster

Nashik Engineering cluster

Guwahati Bamboo Cluster

Vijayawada, Chennai Auto Components Cluster

Bangalore Machine Tools Cluster

Hyderabad Pharma Cluster

Kanpur Leather Cluster

Ludhiana Textile Cluster


SUCCESS STORY OF CLUSTER IN BENGALURU

The ICT Cluster in Bengaluru has attracted people and is also known as the Silicon Valley of India Currently Boasts of over 1500 IT firms out of about 3500 IT firms in India Indian companies such as Infosys, Wipro, Iflex have strong presence Fully owned subsidiaries of MNCs such as Motorola, Texas Instruments and Hewlett Packard have their base in the city Around 1/3rd of all of India’s software exports are from the city Ranked 4th in the category of global hub of technological innovation by United Nations Human Development Report

Factors that contribute Educational Institutions and training centers (IISC, IIIT, IIM etc.) Research Institutions (ISRO) Government policies (central and local) Y2K Problem (resulted in giving an important impetus to IT development) Quality issues Jobs creation

“Bengaluru is a model of how an agglomeration can bring prosperity to a poor country”

- Edward Glaeser, Harvard University


ESTABLISHED IT/ITES HUBS IN INDIA

NCR Delhi

Kolkata

Mumbai

Hyderabad

Chennai

Bangalore

Pune

Total STPI Registered Units by 2006-07: 1400IT/ITeS Majors: IBM, Genpact Oracle, American Express, Convergys, HP, General Motors

Total STPI Registered Units by 2006-07: 166IT/ITeS Majors: IBM, Cognizant, TCS, Infosys, Wipro

Total STPI Registered Units by 2006-07: 1060IT/ITeS Majors: Hp, Amazon, Verizon, Convergys, EXL, Infosys, TCS

Total STPI Registered Units by 2006-07: 900IT/ITeS Majors: Infosys, Wipro, Accenture, Cognizant

Total STPI Registered Units by 2006-07: 630IT/ITeS Majors: TCS, Infosys, Wipro, Siemens, Accenture

Total STPI Registered Units by 2006-07: 635IT/ITeS Majors: Cognizant, Convergys, EXL, KPIT, Msource

Total STPI Registered Units by 2006-07: 1700IT/ITeS Majors: Wipro, TCS, HP, Siemens, HSBC, CompaqCumulative software exports from

Bangalore are estimated to be US$ 11 billion, positioning it as

the leading IT hub of IndiaSource:- Paper on “Knowledge-based Custer Development in India Opportunities and Challenges”, MIT


AUTOMOTIVE CLUSTERS IN INDIA

Himachal Pradesh

DELHIHaryana

West Bengal

KolkataGujarat

Maharashtra

Mumbai

Karnataka

Bangalore

Andhra Pradesh

Tamil Naidu

Chennai

Maruti Suzuki, Honda, Hero,

Yamaha, LML

NORTH

GM, TATA, Fiat, Bajaj, Mahindra,

Mercedes Benz, Volkswagen,

Eicher, Force, Skoda, Audi,

Mahindra Renault, Swaraj Mazda

TATA, HM

EAST

Hyundai, Ford, Mitsubishi Motors,

TVS, Toyota, Volvo, Royal Enfield,

BMW, Nissan, Renault Nissan

Source:- Harvard Business School – Spring 2012


ENHANCING CITY COMPETITIVENESS

Focus on

1. Public-Private Partnerships

- Increases the ease of business, fetches innovative ideas, provide potential for financing

- One of the successful model is the Delhi Noida Bridge

2. Dealing with Urbanization

3. Urban Poverty

4. Transparency and Civic Engagement

5. Other Common Areas

- Understand the city challenges & search their solutions, improve internal & external environment

- Some Tier-2 & 3 cities like Guwahati, Bhopal, Faridabad, Coimbatore are urbanizing at a fast pace

- Leads to vulnerable conditions, create issues with respect to sanitation, water, health , education etc.

- Government programmes: Swarna Jayanti Shahari Raozgar Yojana (SJSRY), JNNURM, Rajiv Awas Yojana

- Engage major stakeholders in most of the development activities

- A tool for the betterment of the democracy and thus the city

- Includes basic amenities, infrastructure, facilities etc. required for a decent standard of living


GOVERNANCE

Movement of power

Center

State

Urban Local Government

Therefore,

Clear boundaries between Metropolitan governance body and municipal corporation

Need to make institutional arrangements

Empower Local bodies

Create well defined model for governance structure

Focus should be on managing the change wherein expectations of all stakeholders is taken into consideration

provide quality services in adequate quantities to the

residents A ‘GOOD’ City = sound political and governance system

are responsive towards the requirements of the businesses

City Mayor

City Management Service Delivery Agencies


Focus on

1. Build Character

- Governed by planning norms, building controls and urban policy

- Immediate spatial and visual impact of city’s “Hardware” positively influence the psyche of people

2. Urban identity

3. Urban behavior

4. Interstitial urbanism

- Urban contexts of the city strike a deep chord with its residents

- Characteristics such as historicity, accessibility, multi-vocal qualities and inclusive nature are valued

- It replicates itself in recognizable pattern at multiple scales

- Helps to openly engage, individually and collectively

- Adds immeasurable value to the city

- Vitalizes a city, encourage a sense of belonging amongst residents and their engagement with the city

CITY BRANDING FROM WITHIN

Delhi can be branded if following possibilities are looked upon: Innovatively utilizing the old structures even when urban infrastructure are being constructed Enhancing the inclusiveness of the city via urban villages & historic settlements so as to make them vibrant contributors to Delhi’s

urban experience Improving the basic amenities within the city etc.


INDIA CITIES ON GLOBAL BENCHMARK

Tokyo (68)Shanghai (55.2)Los Angeles (61.5)New York (71.4)

London (70.4)

Hong Kong (69.3)

Paris(69.3)Zurich (66.8)

Chicago (65.9)

Singapore (70)

Delhi (46.7)

Kolkata (37.8)

Chennai (38.1)Bangalore (44.6)

Mumbai (46.6)

Ahmedabad (41.9)

Source:- Economist Intelligence Unit and Institute for Competitiveness Analysis

Hyderabad (39.4)


KEYS FOR SUCCESSFUL CITIES

Vision

Entrepreneurship

SpecializationSocial cohesion

Governance

ambition for future + desire + shared value system

shaping people and not merely “shaping knowledge”

understand every city’s unique characteristics

Creative city planning which, addresses social issues

Include principles such as, participation, coherency,

competitiveness, subsidiarity, sustainability


THE CITIES OF FUTURE

Present cities seems stressed on multiple accounts that is, overpopulation, sketchy resources, exorbitantly high cost of living index,

mal governance etc. So the cities of future would primarily be an itsy-bitsy variation of current cities Current cities have built in so many contra forces that they are now leviathan white elephants. However it is being suggested that

city of future would be fragmentisation of population clusters Every employee shall serve many firms Geography and power would no longer correlate 21st century man is absolutely asocial Technology will keep on pouring and will make one city advanced and other obsolete Therefore, cities needs to see their future and then address the stresses bothering them and should not depend on the vacuous

pronouncements of politicians

India City Competitiveness Report 2012

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