13th European Conference on eGovernment – ECEG 2013 1 | Page 55

Leonidas Anthopoulos and Panos Fitsilis
In this context, data from investigative analysis that concern the types of e‐Services that each of the examined case offers together which of them were adopted by smart cities’ updates( Table 2) can be applied on technology roadmapping. The information of( Table 2) generates e‐service groups according to their end‐users( Table 3). The values that are contained on the year column concern the earliest year, when a smart city case appears and offers e‐services from the e‐service group; the frequency column enumerates the cases that match each e‐service group.
Table 3: E‐service groups structured by the examined cases
Service
e‐Services
Year
Freq.
Cases
Group
SGroup1
e‐business, city guides, urban virtualization
1989
6
AOL cities, Bristol, Copenhagen Base, Craigmillar, Osaka, Blacksburg, Amsterdam
SGroup2
E‐Government, e‐ Democracy, e‐learning
1994
9
Bristol, e‐Trikala, Antwerp, Stockholm( Kista), Taipei, Barcelona, Hull, Brisbane, New York
SGroup3
Broadband communications services
1994
14
Craigmillar, Blacksburg, Seoul, Beijing, Helsinki, New York, e‐Trikala, Dubai, New Songdo, Knowledge based cities, Geneva, Barcelona, Amsterdam, Cape Town
SGroup4
E‐health and tele‐care
1995
3
Helsinki, e‐Trikala, Stockholm( Kista)
services, e‐security
SGroup5
Intelligent Transportation, e‐parking
2002
6
Stockholm( Kista), Taipei, e‐Trikala, Brisbane, Amsterdam, Cape Town
SGroup6
Ubiquitous services, communications services
2008
4
Osaka, New Songdo, Masdar, Manhattan Harbour
SGroup7 Eco‐services, smart grids, waste / recycle management
2005
7
Amsterdam, Craigmillar, Malta, Masdar, Tianjin, Dongtan,
Cape Town
Data from( Table 3) extract the path‐dependent roadmap( Li et al., 2009) of( Figure 2), which demonstrates smart city approaches changes and how each change depends on its own past. Path dependency can explain smart city evolution on the basis of the e‐service provision, while paths do not illustrate co‐existences of cases in more than one groups( i. e., e‐Trikala simultaneously belonged to SGroup1, SGroup2 and SGroup3). Some further findings show that SGroup1 and SGroup2 are root nodes in these paths, while SGroup7 is an end‐node, illustrating that this smart city category has not evolved to a different approach yet.
Figure 2: Path‐dependent roadmaps for smart city evolution
4. Discussion
The investigation that was previously presented was performed on a 31 smart cities and returned important findings that answer the questions 1 and 2 of this paper. The term smart city does not describe a city with some particular attributes, but various types of municipal ICT environments. Some researchers have used this
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