Francesco Rizzi - New urban environments - an entrepreneurial perspective

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Francesco Rizzi [email protected] Madrid, 2013-12-16 Action COST “People friendly cities in a data rich world” WG 2 “Knowledge platform” New urban environments: an enterpreneurial perspective
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Action COST TU1204 - WG2 meeting, Madrid, 2013-12-16

Transcript of Francesco Rizzi - New urban environments - an entrepreneurial perspective

Page 1: Francesco Rizzi - New urban environments - an entrepreneurial perspective

Francesco Rizzi [email protected]

Madrid, 2013-12-16

Action COST “People friendly cities in a data rich world” WG 2 “Knowledge platform”

New urban environments: an enterpreneurial perspective

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Big cities: a valuable business environment

Chapter 1: The state of the planet page 59

IVORY COAST

8.6

PERU21.073%

CANADA26.380%

ROMANIA11.6

54

BEIJING12.7

SHANGHAI17.3

GUANDONG7.3

CHINA559.242%

INDIA329.329%

AUSTRALIA18.389%

BANGLADESH38.226%

INDONESIA114.150%

JAPAN84.766%

N KOREA14.162%

S KOREA39.081%

MALAYSIA18.169%

MYANMAR16.532%

THAILAND21.533%

VIETNAM23.327%

PHILIPPINES55

64%

PAKISTAN59.336%

SEOUL23.2 OSAKA

16.6

MANILA15.4

TOKYO33.4

DHAKA13.8

KOLKATA15.5

UZBEKISTAN10.137%

KAZAKH-STAN8.6

SYRIA10.251%

IRAN48.468%

IRAQ 20.367%

SAUDI ARABIA20.981%

TURKEY51.168%

AFGHAN-ISTAN

7.8

UKRAINE30.968%

RUSSIA103.673%UK

5490%

SWEDEN7.6

NETHERLANDS13.381%

BELGIUM10.297% CZECH

REPUBLIC7.4

FRANCE46.977%

GERMANY62

75%

ITALY39.668%

POLAND23.962%

SPAIN33.677%

US246.281%

NEW YORK21.8

LOS ANGELES

17.9

LONDON12

MEXICO84.392

77% MEXICO

CITY22.1

MOSCOW13.4

MUMBAI21.3

LAGOS10.0

ANGOLA9.3

ALGERIA22.0

MOROCCO19.460%

NIGERIA68.650%

MOZAM-BIQUE

CAMEROON9.5

CONGO, DR OF20.233%

EGYPT33.143%

ETHIOPIA13

16%GHANA

11.349%

KENYA7.6

TANZANIA9.925%

S AFRICA28.660%

SUDAN16.343%

TUNISIA

BRAZIL162.685%

ARGENTINA35.690%

COLOMBIA34.373%

VENEZUELA26

94%

CHILE14.688%

RIO DE JANEIRO

12.2

BUENOSAIRES13.5

SÃO PAULO20.4

TEHERAN12.1

NEW DELHI21.1

KARACHI14.8

ISTANBUL11.7

CAIRO15.9

JAKARTA14.9

IVORY COAST

8.6

PERU21.073%

CANADA26.380%

ROMANIA11.6

54

BEIJING12.7

SHANGHAI17.3

GUANDONG7.3

CHINA559.242%

INDIA329.329%

AUSTRALIA18.389%

BANGLADESH38.226%

INDONESIA114.150%

JAPAN84.766%

N KOREA14.162%

S KOREA39.081%

MALAYSIA18.169%

MYANMAR16.532%

THAILAND21.533%

VIETNAM23.327%

PHILIPPINES55

64%

PAKISTAN59.336%

SEOUL23.2 OSAKA

16.6

MANILA15.4

TOKYO33.4

DHAKA13.8

KOLKATA15.5

UZBEKISTAN10.137%

KAZAKH-STAN8.6

SYRIA10.251%

IRAN48.468%

IRAQ 20.367%

SAUDI ARABIA20.981%

TURKEY51.168%

AFGHAN-ISTAN

7.8

UKRAINE30.968%

RUSSIA103.673%UK

5490%

SWEDEN7.6

NETHERLANDS13.381%

BELGIUM10.297% CZECH

REPUBLIC7.4

FRANCE46.977%

GERMANY62

75%

ITALY39.668%

POLAND23.962%

SPAIN33.677%

US246.281%

NEW YORK21.8

LOS ANGELES

17.9

LONDON12

MEXICO84.392

77% MEXICO

CITY22.1

MOSCOW13.4

MUMBAI21.3

LAGOS10.0

ANGOLA9.3

ALGERIA22.0

MOROCCO19.460%

NIGERIA68.650%

MOZAM-BIQUE

CAMEROON9.5

CONGO, DR OF20.233%

EGYPT33.143%

ETHIOPIA13

16%GHANA

11.349%

KENYA7.6

TANZANIA9.925%

S AFRICA28.660%

SUDAN16.343%

TUNISIA

BRAZIL162.685%

ARGENTINA35.690%

COLOMBIA34.373%

VENEZUELA26

94%

CHILE14.688%

RIO DE JANEIRO

12.2

BUENOSAIRES13.5

SÃO PAULO20.4

TEHERAN12.1

NEW DELHI21.1

KARACHI14.8

ISTANBUL11.7

CAIRO15.9

JAKARTA14.9

Figure 38: The number of people living in cities in each country of the world in 2010, together with the percentage of the population in countries with large urban populations.In the developed world, the proportion of people living in cities is typically higher than 75%, and often exceeds 85%. The largest urban population in the developed world is in the USA (246 million). However, in China, even though the proportion of people living in cities is under 50%, the total number of urban dwellers is greatest (559 million). In India, by comparison, the number is 329 million (UN population division). (Figure drawn by the World Business Council for Sustainable Development in WBCSD, 2012, based on data from the UN Population Division UN, 2010)

TODAY’S URBAN POPULATION:

3,307,905,000Key

Cities over 10 million people (greater urban area)

Predominantly urban 75% or over

Predominantly urban 50 - 74%

Urban 0 - 49%

IN 2050, TWO OUT OF EVERY THREE PEOPLE WILL LIVE IN A CITY (UN, 2009)

Number of people that live in cities and percentage of inhabitants in big cities (2010). Source: WWF, 2012 !

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The problem

Public debt (%GDP)

Source: Wikipedia on data from Eurostat (2012) and US.CIA (2013)

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The challenge

How to do better things

Without increasing costs?

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The opportunity

City = platform

For an efficient use of

resources

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The value of data

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Smart meters: lessons learnt

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20 IEEE power & energy magazine january/february 2010

system engineering, assisted by an array of new approaches, technologies and applications, allows the existing grid to tra-verse the complex yet staged trajectory of architecture, proto-cols, and standards towards the smart grid.

Smart Grid DriversAs the backbone of the power industry, the electricity grid is now the focus of assorted technological innovations. Utilities in North America and across the world are taking solid steps towards incorporating new technologies in many aspects of their operations and infrastructure. At the core of this trans-formation is the need to make more effi cient use of current assets. Figure 4 shows a typical utility pyramid in which asset management is at the base of smart grid development. It is on this base that utilities build a foundation for the smart grid through a careful overhaul of their IT, communication, and circuit infrastructure.

As discussed, the organic growth of this well-designed layer of intelligence over utility assets enables the smart grid’s fundamental applications to emerge. It is interesting to note that although the foundation of the smart grid is built on a lateral integration of these basic ingredients, true smart grid capabilities will be built on vertical integration of the upper-layer applications. As an example, a critical capability such as demand response may not be feasible without tight integration of smart meters and home area networks.

As such, one may argue that given the size and the value of utility assets, the emergence of the smart grid will be more likely to follow an evolutionary trajectory than to involve a

drastic overhaul. The smart grid will therefore materialize through strategic implants of distributed control and moni-toring systems within and alongside the existing electric-ity grid. The functional and technological growth of these embryos over time helps them emerge as large pockets of distributed intelligent systems across diverse geographies. This organic growth will allow the utilities to shift more of the old grid’s load and functions onto the new grid and so to improve and enhance their critical services.

These smart grid embryos will facilitate the distributed generation and cogeneration of energy. They will also pro-vide for the integration of alternative sources of energy and the management of a system’s emissions and carbon foot-print. And last but not least, they will enable utilities to make more effi cient use of their existing assets through demand response, peak shaving, and service quality control.

The problem that most utility providers across the globe face, however, is how to get to where they need to be as soon as possible, at the minimum cost, and without jeopardizing the critical services they are currently providing. Moreover, utilities must decide which strategies and what road map they should pursue to ensure that they achieve the highest possible return on the required investments for such major undertakings.

As is the case with any new technology, the utilities in the developing world have a clear advantage over their counter-parts in the developed world. The former have fewer legacy issues to grapple with and so may be able to leap forward without the need for backward compatibility with their exist-ing systems.

Intelligent Grid

Digital

Two-Way Communication

Distributed Generation

Network

Sensors Throughout

Self-Monitoring

Self-Healing

Adaptive and Islanding

Remote Check/Test

Pervasive Control

Many Customer Choices

Existing Grid

Electromechanical

One-Way Communication

Centralized Generation

Hierarchical

Few Sensors

Blind

Manual Restoration

Failures and Blackouts

Manual Check/Test

Limited Control

Few Customer Choices

figure 1. The smart grid compared with the existing grid.

Increasin

g Capabilit

ies

DistributionAutomation

End-to-EndCommunication

DataManagement

UtilityApplications

The first

step in

the evo

lution of th

e electricit

y

grid st

arts at th

e distrib

ution si

de, enablin

g

new applicatio

ns and operatio

nal effic

iencies

to be intro

duced in

to the sy

stem.

figure 2. Utility-desired capabilities.

Regardless of how quickly various utilities embrace smart grid concepts, technologies, and systems, they all agree on the inevitability of this massive transformation.

12

the catalogue fall in the Smart Meters category; these projects involve the installation of more than

40 million devices for a total investment of around €3 billion. Estimates forecast about 240 million

smart meters to be installed by 2020 [Pike Research, 2011].

AT

6.1%

BE

4.2%

DE

11.1%

DK

22.0%

EL

2.0%

ES

8.7%

FI

1.5%

FR

4.2%

IE

2.4%

IT

5.5%

NL

6.8% PT

2.4%SE

5.0%

UK

6.8%

SK 0.7%

SI 3.1%

RO 0.6%

PL 1.7%

MT 0.4%

LV 0.7%

LT 0.4%

HU 1.1%

EE 0.2%

CZ 1.7%

CY 0.4%

BG 0.4%

Others 11.3%

Figure 2. Distribution of projects between EU15 and EU12 Countries

Figure 3 - Geographical distribution of investments and project categories

EU12 Member States: Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia

Source: EC-JRC USA-DOE

Who can do that?

Smart meters: lessons learnt

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Successes and failures

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Successes and failures

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The theoretical perspective

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Last 20 years of inventions in the field of RESs

Bold: Belgium, Denmark, France, Germany, Greece, Italy, Netherland, Spain, Sweden, Switzerland, United Kingdom

Italic: World regions with the exclusion of Europe, North America, West Asia

Isomorphism threats & the opportunities for smart communities

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Characteristics of the problem

Focal agent’s need for distant search

Reliability of the crowd as problem solver

Evaluability of the solutions

Pervasiveness of the information platform

Ease

of d

elin

eatio

n an

d tr

ansm

issio

n

Mod

ular

izab

ility

of th

e pr

oble

m

Effe

ctive

dist

ance

of k

now

ledg

e

Taci

tnes

s an

d co

mpl

exity

of t

he s

olut

ion

Perv

asive

ness

of k

now

-how

in th

e cr

owd

Mot

ivatio

ns o

f pot

entia

l sol

vers

Nat

ure

of th

e so

lutio

n N

uber

of e

valu

ator

s

Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3), 355-375.!

Crowdsourcing: the alternative way

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Crowdsourcing and urban sustainability governance

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Crowdsourcing and urban sustainability governance

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Francesco Rizzi Istituto di Management Scuola Superiore Sant’Anna [email protected]