Globalization and advances in ICT have allowed the development of increasingly complex logistics networks. From the operational point of view, this evolution is associated with a massive growth in transportation, freight flows and eventually the development of logistics platforms. The logistics functions tend to be located at major gateways and hubs with access to a market area, but also concentrated in hinterland corridors beyond the borders of a metropolitan area (Hesse, 2004; O’Connor, 2010; Holl and Mariotti, 2016). Besides, the importance of maritime ports, within the logistics and global supply chain, has become the subject matter of many studies, from which the concept of port-centric logistics and port regionalization has been derived. Nevertheless, the management, knowledge-intensive and informational functions of logistics firms tend not to follow this dispersive pattern, but they concentrate in few cities. This is due to the advantages that may derive from clustering in knowledge- rich environments (Musso and Ghiara, 2007, 2008; Ghiara, 2012). According to O’Connor et al. (2016), indeed, advanced logistics seem to behave rather similar to Advanced Producer Services (APS) such as finance, marketing, engineering, etc. Referring to the pioneering work on global cities by Sassen (1991), the role of the main APS within the network of global economy has been widely theorized, and analysis of their intrafirm networks becomes the base for Taylor (2001) and his methodological contribution to the GaWC World City Network (WCN) initiative.1 Specifically, Friedmann (1986) argues that in world city networks, key cities are emerging as central locations for global capital, which may result in a complex spatial hierarchy. While it is discussed that the command and control functions of the global economy are concentrated in only a few cities at the top of the urban hierarchy, major world/global cities are due to acquire new roles and functions, emerging from spatial dispersion and global integration (Sassen, 1991, 1994). Within the WCN framework, Peter Taylor reconfigures a different interurban relation of the largest global APS firms which represents the informational feature of the urbanized and liberal economy (see GaWC, 2012). Taylor’s method allows us to identify other major world cities, such as Milan, location of the Italian head office of many transnational companies based in the largest world cities like London (the most connected world city). Taylor integrates city cluster dynamics with city network dynamics: “The external relations of cities are weighted equally with their internal relations. Internal ‘cluster externalities’ and external ‘network externalities’ are critical to vibrant network and consequent economic expansion” (Taylor et al., 2007, p. 282). Following the WCN method, the present chapter aims to investigate the attractiveness of European maritime port cities to the largest global third-party logistics (3PL) providers (only those specialized in knowledgeintensive functions). A database of 208 European maritime port cities has been established. Of those, 29 show a Logistic Global Network Connectivity (LGNC), as developed by Akhavan et al. (2019) through the interlocking network analysis for advanced logistics. The hypotheses have been tested by means of descriptive statistics (correlation analysis) that also allowed us to identify specific typologies of maritime port cities in Europe with commonalities and differences in attractiveness level towards 3PL. The remainder of this chapter is organized as follows. Part 16.2 discusses the theoretical background of port city research in the World City Network theory. Part 16.3 presents a European advanced logistics empirical analysis, and describes the typologies of port cities that have been identified. Specifically, the attractiveness of these typologies to advanced logistics firms is explored. Part 16.4 draws conclusions.

Attractiveness of port-centric advanced logistics clusters

Mina Akhavan;Ilaria Mariotti;
2020-01-01

Abstract

Globalization and advances in ICT have allowed the development of increasingly complex logistics networks. From the operational point of view, this evolution is associated with a massive growth in transportation, freight flows and eventually the development of logistics platforms. The logistics functions tend to be located at major gateways and hubs with access to a market area, but also concentrated in hinterland corridors beyond the borders of a metropolitan area (Hesse, 2004; O’Connor, 2010; Holl and Mariotti, 2016). Besides, the importance of maritime ports, within the logistics and global supply chain, has become the subject matter of many studies, from which the concept of port-centric logistics and port regionalization has been derived. Nevertheless, the management, knowledge-intensive and informational functions of logistics firms tend not to follow this dispersive pattern, but they concentrate in few cities. This is due to the advantages that may derive from clustering in knowledge- rich environments (Musso and Ghiara, 2007, 2008; Ghiara, 2012). According to O’Connor et al. (2016), indeed, advanced logistics seem to behave rather similar to Advanced Producer Services (APS) such as finance, marketing, engineering, etc. Referring to the pioneering work on global cities by Sassen (1991), the role of the main APS within the network of global economy has been widely theorized, and analysis of their intrafirm networks becomes the base for Taylor (2001) and his methodological contribution to the GaWC World City Network (WCN) initiative.1 Specifically, Friedmann (1986) argues that in world city networks, key cities are emerging as central locations for global capital, which may result in a complex spatial hierarchy. While it is discussed that the command and control functions of the global economy are concentrated in only a few cities at the top of the urban hierarchy, major world/global cities are due to acquire new roles and functions, emerging from spatial dispersion and global integration (Sassen, 1991, 1994). Within the WCN framework, Peter Taylor reconfigures a different interurban relation of the largest global APS firms which represents the informational feature of the urbanized and liberal economy (see GaWC, 2012). Taylor’s method allows us to identify other major world cities, such as Milan, location of the Italian head office of many transnational companies based in the largest world cities like London (the most connected world city). Taylor integrates city cluster dynamics with city network dynamics: “The external relations of cities are weighted equally with their internal relations. Internal ‘cluster externalities’ and external ‘network externalities’ are critical to vibrant network and consequent economic expansion” (Taylor et al., 2007, p. 282). Following the WCN method, the present chapter aims to investigate the attractiveness of European maritime port cities to the largest global third-party logistics (3PL) providers (only those specialized in knowledgeintensive functions). A database of 208 European maritime port cities has been established. Of those, 29 show a Logistic Global Network Connectivity (LGNC), as developed by Akhavan et al. (2019) through the interlocking network analysis for advanced logistics. The hypotheses have been tested by means of descriptive statistics (correlation analysis) that also allowed us to identify specific typologies of maritime port cities in Europe with commonalities and differences in attractiveness level towards 3PL. The remainder of this chapter is organized as follows. Part 16.2 discusses the theoretical background of port city research in the World City Network theory. Part 16.3 presents a European advanced logistics empirical analysis, and describes the typologies of port cities that have been identified. Specifically, the attractiveness of these typologies to advanced logistics firms is explored. Part 16.4 draws conclusions.
2020
Geographies of Maritime Transport Transport, Mobilities and Spatial Change
978 1 78897 663 3
Logistics, MNE, port-centric advanced logistics, GaWC World City Network
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1133270
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