Baslé slides congress Smarter cities` attractiveness

Smarter cities’ attractiveness. Testing new criteria or facets: “data scientists” and “data
platforms”.
Maurice Baslé, professeur émérite. Université de Rennes 1 - CREM – CNRS. France.
Chaire jean Monnet ad personam.
Chaire Connaissance et action territoriale, Fondation Université de Bretagne-Sud.
Key-words:
Location theory
Factors of Attractiveness
Smarter cities
Open data, open governance.
Data platforms and interoperability.
Digital society.
Applications and services.
Data sciences, data scientists.
Proposition
Origine de la proposition.
Raisons de la proposition.
Nature innovante de la proposition.
Ce qui reste à réaliser : les tests de la proposition.
Bibliographie.
Proposition
We will explain why, in the new economy emerging with new
internet users, with a lot of new Internet platforms of distance
selling, cities must begin a new promotion campaign based on eadministration services and on the new services using territorial
knowledge (transportation behaviors for example), and also on
data-scientist capacities and the use of data platforms of
territorial data... all these factors of enhancing the local
productivity and of welfare.
Origine de la proposition.
Our exploration and experimentation of the new
possibilities of an interoperable public and private data
platform
ACT-TER-DC
https://act-ter.univ-ubs.fr/
Mixing open public data,
Administrative data from public services furnishers,
Statistical data,
Behavioral data from users…
• Raisons de la proposition.
• Insufficiencies of the traditional indicators of the
attractiveness of a city and the multi-dimensional
ranking of cities in the pre-digital society.
• An increasing number of cities’ indicators of attractiveness have enriched the territorial profiles that have been used in the
economic decision process for choosing a new location (Karlsson, C., Johansson, B., Stough, R.R. (2014)). The profiles now in
use have integrated new social, environmental and cultural dimensions of attractiveness (Darchen, S. Tremblay, D.G. (2010);
Ergazakis, K., Metaxiotis, K. and Psarras, J. (2004)). For example, in Kourtit, Macharis, Nijkamp (2014): For each individual
city, 6 main classes of functions were carefully mapped out and numerically assessed, viz. economy, research and development,
cultural interaction, livability, environment and accessibility.
• Raisons de la proposition.
• In the communication battle between competing cities, the knowledge and value of these
profiles can be demonstrated through correlation between these traditional attractiveness’
indicators and the location-relocation of populations, households, governments and businesses
(for example: The Global Venture Capital and Private Equity Country Attractiveness Index: see
http://blog.iese.edu/vcpeindex/ ).
• The promotion of the traditional cities’ multi-dimensional statistical indicators may have had
some effects on attractiveness. For example, in France, indicators of new industrial sectors in
cities (known as “technopoles”, “competitiveness poles”, “local productive systems”, “French
tech labels”).
• Raisons de la proposition.
• The possibility of a new facet to be shown for the
attractiveness of a city after the digital revolution.
• New Actors in the smarter cities. In the new digital economy, a small number of actors in a
position of leadership in information and telecommunications have become the big actors in
the processing of big data. These well-known actors are, at the beginning of the 21st century,
omnipresent new actors located in a small number of cities in the world, those cities that
“experiment with new approaches to the planning, design, finance, construction, governance,
and operation of urban infrastructure and services that are broadly called Smart Cities, some of
these approaches are related to emerging roles of information technology”
On going Innovation.
Organising the best data mixes of public and private data
that will be transformed on new platforms that will be
based on trust and will be at the service of collective
intelligence (CI); creating data acquisition and processing
systems which assist human intelligence (HI); developing
a creativity public impulsion, a reward for inventiveness
and artificial intelligence (AI)
• In this innovative context, all real digital cities should potentially be favorable
environments for entrepreneurship and propitious to a social participation.
• However, all the cities are not becoming true digital cities.
• In an innovating context, only those which have had
• - the will to organize new cooperative platforms (here called “datathèquesservices”) connecting public and private open data, data from a lot of
heterogeneous sources
• - and the will to develop new services of knowledge for a real digital society,
have not usurped the title of “smarter cities”.
Ce qui reste à réaliser : les tests de la proposition.
The hypothesis of the crucial character of two dimensions (data scientist numbers,
data services platforms) has to be tested (confirmed or infirmed) by empirical
studies:
can these empirical studies confirm that some indicators of the existence of a smart
city (like a capacity for data sciences and data processing) are now better indicators
of future gains in productivity and of local welfare (as suggested by Shapiro, J.M.
(2006))?
• Shapiro, J. M. (2006): Smart Cities: Quality Of Life, Productivity, And the
Growth Effects of Human Capital, Review of Economics and Statistics, Vol.88/2,
pp.324-335.
Merci pour votre attention.
Vos questions et vos remarques?