Geoscience Reference
In-Depth Information
conditions of increasing returns to scale and labor mobility, reinterpreting
the findings of Marshall on agglomerations. In the resulting 'New Economic
Geography' (NEG) model, spatial concentration and dispersion emerge
(Fujita et al.
1999
). The NEG model, however, accounts for only pecuniary
economies, makes no mention of either human capital or technological
spillovers, and has no answers for the contemporary knowledge creation
process and innovation-led growth in urban agglomerations.
(c)
Innovation-led Agglomerations
: This class of models views the increasing
returns associated with regional agglomerations or metros as dynamic loca-
tion advantages attributable to: (1)
Physical Proximity
among economic
actors, facilitating interactions and enabling access to appropriation and
sharing of tacit knowledge, thus promoting innovation (Gertler
2003
),
(2)
Relational Proximity
of economic agents, facilitating cooperative behav-
ior, collective learning, and socialization of innovation risk, (3)
Institutional
Proximity
among the firms in the urban agglomeration in terms of shared
rules, codes and norms of behavior which will promote cooperation in
interactive learning processes (Camagni
2005
; Capello
2011
; Amin and
Cohendet
1999
), and (4) Lowering of
Adaptive Costs
among firms compet-
ing in an environment of rapid pace of change of knowledge (Lakshmanan
and Button
2009
).
18.2.3 Improvements in Metro Transit, High Speed Rail,
and Knowledge-Sector Agglomerations
In the 2000-2007 period, there was a pronounced shift from earlier patterns in
New York from auto commuting to public transportation, an increase in daily
subway ridership, and an upsurge in bicycling (Fig.
18.2
). It was also a period of
considerable growth in New York in the spatially agglomerated knowledge-
intensive sectors such as Finance and Business services.
Over the last decade, a high speed rail service (Acela Express) has operated
between Boston and Washington, DC with a maximum speed of 241 kph and a daily
passenger load of 28,000 (in 2010) along a 585 km, 14 station corridor
characterized by an average number of 178,645 jobs and 219,925 residents
(2008) within a 5 km range (Murakami and Cervero
2012
). Murakami and
Cervero's analysis of the economic stimuli provided around High Speed Rail
(HSR) stations in the Tokyo-Osaka and the BOSWASH corridors (and in London
a major global economy node) appears to support the symbiotic relationships (noted
above) between HSR improvements and the location and growth of knowledge-
intensive economic sectors around major HSR stations in metros such as New York,
a top node in the global economy.
Contemporaneous with the vast improvements in the physical and institutional
transport infrastructures noted here, there were major improvements in Information
and communication technologies (ICT). As has been noted widely, ICT contributes
greatly to productivity, profitability and growth at the firm level. Thus Transport
