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«Abstract Information on air passenger flows is potentially a prime data source for assessing spatial patterns in the global city network, but ...»

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Airline data for global city network research: reviewing and refining existing approaches

Ben Derudder*, Frank Witlox*, James Faulconbridge**, Jon Beaverstock***

*

Geography Department

Ghent University

E-mail: ben.derudder@ugent.be, frank.witlox@ugent.be

**

Geography Department

Lancaster University

E-mail: j.faulconbridge@lancaster.ac.uk

***

Geography Department

Nottingham University

E-mail: jonathan.beaverstock@nottingham.ac.uk

Abstract

Information on air passenger flows is potentially a prime data source for assessing spatial patterns in the global city network, but previous analyses have been hampered by inadequate and/or partial data. The ensuing analytical deficiencies have reduced the overall value of these analyses, and this paper examines how some of these deficiencies may be rectified. First, we review the rationale for using airline data to analyse the global city network. Second, we assess the data problems encountered in previous research. Third, we elaborate on the construction of datasets that may circumvent some of these problems. The proposed refinements include the omission of the hub function of major airports and ways to extract relevant business flows from the data.

Keywords: global city network, transnational mobility, business travel, airline data I. Introduction It has become commonplace to underline that recent developments in (the geographies of) transport and communication infrastructures have had a profound impact on the spatial organization of an increasingly globalized society (e.g. Black, 2003; Rodrigue et al., 2006;

Dicken, 2007). One of the most commonly cited evolutions in this context is the alleged demise of the relevance of ‘territoriality’ in favour of ‘networks’, an evolution which leading sociologist Manuel Castells (1996, 2001) famously described as a transition from an international economy organized around ‘spaces of places’ to a global economy organized around ‘spaces of flows’.

Although there is a great deal of debate on the actual significance and implications of this shift, there can be little doubt that the spectacular growth of border-crossing mobility – for the largest part through air transport – is increasingly producing new spatial patterns of economic and social life. This had led some researchers to suggest that radical new ways of structuring our thinking about spatial patterns are required. Sheller and Urry (2006), for instance, attempt to capture these trends by devising a ‘new mobilities paradigm’, which is concerned with the patterning, timing, and causation of the face-to-face copresence so greatly facilitated by the contemporary surge in mobility. Another major strand of research focuses on potential spatial frameworks for capturing these trends, whereby a so-called ‘global city network’ (GCN) appears to be a likely candidate to replace the inter-state system for organizing our knowledge about the world (Taylor, 2004).

Global cities are hereby essentially defined as key points in the organization of the global economy, and increasingly derive their functional importance from their mutual interactions rather than with their proper hinterlands1. In this paper, we will focus on one particular aspect of the interrelation between transnational mobility and this networked geography, i.e. the relevance of data on air passenger flows for revealing the material spatiality of this GCN.

The paper consists of three main parts. The first section presents a general introduction to the GCN literature, with a specific focus on the position of airline-based studies within this research domain. The relevance of air transport for GCN research may seem deceitfully obvious: air transport is all about connections between cities, while airline data are comparatively easy to obtain. Our intention here, however, is to provide a somewhat deeper understanding of the relevance of airline data by situating this information source within the GCN literature at large.

The second section shows how previous airline-based studies have quasi-systematically been hampered by inadequate and/or partial data. The third section, then, presents some possible alternatives to the problem of inadequate data. It is not our intention to provide yet another empirical analysis of global city-formation based on ‘better’ data, but rather to provide a conceptual overview of how airline-based analyses of GCNs may collectively be improved in future research. To this end, we discuss some alternative data sources and propose some data manipulations that, taken together, may advance our understanding of the empirical association between air transport and GCNs. In a short conclusion, we briefly discuss the main implications of this paper and outline some avenues for further research.

1 Some researchers explicitly differentiate between the terms ‘global city’ and ‘world city’ (e.g. Sassen, 2001), and in some cases such distinction is indeed no less than crucial (see Derudder, 2006). However, in the context of the present paper, these conceptual details are of lesser importance, and we will therefore consistently use the generic term ‘global city’ to address the literature at large.

II. The position of air transport-based studies within global city network research

II.1 GCN research: basic assumptions and main critiques





The contemporary GCN literature can be traced back to two interrelated papers by Friedmann and Wolff (1982) and Friedmann (1986). Both texts framed the rise of a global urban system in the context of a major geographical transformation of the capitalist world economy. This restructuring, most commonly referred to as the ‘new international division of labour’, was basically premised on the internationalization of production and the ensuing complexity in the organizational structures of multinational enterprises (MNEs). This increased economicgeographical complexity, Friedmann (1986) argued, requires a limited number of control points in order to function, and global cities were deemed to be such points. The publication of Saskia Sassen’s (1991) The Global City in 1991 marked a shift of attention to global inter-city flows resulting from the critical servicing of worldwide production rather than to its formal command through corporate headquarters of MNEs. Sassen’s approach focuses upon the attraction of advanced producer service firms (providing professional, financial and creative services for businesses) to major cities with their knowledge-rich environments and specialist markets. In the 1980s and 1990s many such service firms followed their global clients to become important MNEs in their own right. These advanced producer service firms thereupon created worldwide office networks covering major cities in most or all world regions, and it is exactly the myriad of interconnections between service complexes that gives, according to Sassen (1991, 2001), way to GCN formation.

A number of fundamental assumptions of GCN research have been criticized from different quarters. A main conceptual limitation of this literature has been the concentration on a relatively few large metropolitan centres to concomitant neglect of all other cities. The most trenchant critique along these lines is by Robinson (2002, p. 536), who complains that “millions of people and hundreds of cities are dropped off the map of much research in urban studies.” This exclusion is from two ‘maps’: (i) the geographical map of world cities wherein most cities in the ‘South’ are missing; and (ii) the conceptual map of global cities which focuses on a narrow range of global economic processes so that myriad other connections between cities are missing.

However, all cities experience contemporary global processes, and globalization can therefore not be construed as affecting just a few privileged cities. Subsequently Robinson (2005, p. 760) has conceded that the GCN literature now covers “a much wider range of cities around the globe” thus lessening the exclusion from the map. This attempt to broaden our understanding of the global city network has seen the postulation of such ideas as ‘globalizing cities’ (Marcuse and van Kempen, 2000) or ‘cities in globalization’ (Taylor et al., 2007).

Empirical GCN research, in turn, the topic on which the present paper focuses, has long remained underdeveloped because of the lack of appropriate data, a problem which Short et al.

(1996) referred to as ‘the dirty little secret of world cities research’. This empirical poverty can, for instance, clearly be read from Castells’ (1996, p. 469) book, which is part of a trilogy that is above all an attempt to reformulate social studies for a global age in which “networks constitute the new social morphology of our societies.” However, when it comes down to providing a basic cartography of this global network society, Castells’ argument falls short of the conceptual shift he advances: the only actual evidence he comes up with in the chapter on the ‘space of flows’ consists of some limited inter-city information gathered from Federal Express. One can therefore only conclude, as Taylor (2004, p. 35) has recently done, that “the evidence [Castells] marshalls is mightily unimpressive.” This gap between theoretical sophistication and evidential poverty is however not a lacuna specific to Castells’ book: it has been a structural feature of research on the GCN, because data for assessing such urban networks are in general insufficient or even totally absent.

II.2. Solutions to the empirical problem

The basic reason for this problem of evidence is that standard data sources are ill-suited for GCN analyses (Taylor, 1997, 2004). To get an evidential handle on big issues, researchers normally rely on the statistics that are available, that is to say, already collected. But such collection is carried out usually by a state agency for the particular needs of government policy rather than for social science research. The result is that such data that are available have an attributional bias (measurements of administrative areas rather than between administrative areas) and are limited to national territories. Where official statistics extend beyond a state’s boundaries they will still use countries as the basic units (e.g. trade data). Thus there is no official agency collecting data on, say, the myriad flows between London and New York. The major result has been that “few of the available data reveal anything about the flows and interdependencies” that are at the heart of this body of literature (Knox, 1998, p. 26), which leads Alderson and Beckfield (2004, p. 814) to note that in the past relatively few of the empirical GCN studies “utilized the sorts of relational data necessary for firmly establishing such rankings empirically.” These data problems have put researchers to work in recent years, and we have therefore witnessed a proliferation of empirical studies that explicitly seek to rectify this situation.

Researchers have hereby relied on a wide variety of data, albeit that some information sources have come to dominate the empirical research as a whole (Derudder, 2006), i.e. (i) information on corporate organization (e.g. data on ownership links between firms across space) and (ii) information on infrastructure networks (e.g. data on the volume of air passenger flows across space). The success of both approaches can, of course, be traced back to their commonsensical appeal: the corporate organization approach acknowledges that well-connected cities derive their status in large part from the presence of key offices of important firms, while the infrastructure approach recognizes that well-connected cities are typified by the presence of vast enabling infrastructures. Put simply: the most important cities harbour the most important airports, while the extensive fiber backbone networks that support the Internet have equally been deployed within and between major cities, hence creating a vast planetary infrastructure network on which the global economy has come to depend almost as much as physical transport networks (Rutherford et al., 2004).

Table 1 summarizes the approaches developed in the empirical GCN literature through an overview of some key studies in this research domain. The table acknowledges that the basic bifurcation between corporate organization and infrastructure needs to be deepened on the basis of the exact types of firms and infrastructures, and equally shows that all this is in practice somewhat more complicated because of the presence of a limited number of studies that (i) make use of other types of data (e.g. Taylor’s (2004b) analysis of non-governmental organizations) and/or (ii) combine indicators from both approaches (e.g. Beaverstock et al., 2000b). In the next section, we focus on empirical GCN studies that utilize data on international air transport flows to map GCNs.

Table 1 about here III. Data issues in airline-based GCN studies Preamble • The starting point of airline-based GCN studies is the rather commonsensical observation that interactions between global cities are in large part facilitated and defined by transnational air transport flows. Following Keeling’s (1995) initial contribution, there have been a large number of empirical researches that draw upon airline data to devise a mapping of the GCN (e.g. Cattan, 1995, 2004; Short et al., 1996; Kunzmann, 1998;

Rimmer 1998; Shin and Timberlake, 2000; Smith and Timberlake, 2001, 2002;

Matsumoto, 2004, 2007; Zook and Brunn, 2005). In principle, the most important advantage of this approach over researches carried out in the corporate organization approach is that airline statistics feature tangible inter-city relations. However, in hindsight, and in spite of the remarkable success of this type of research, it can be noted that most authors have simply asserted the relevance of publicly available airline data, although these are – in our view – downplayed by a number of structural problems (for earlier, but partial assessments, see Taylor, 1999; Beaverstock et al., 2000). In this section, we will provide a systematic overview of these data problems, which will in turn be used in the next section to show how this baleful situation may be rectified.

The first problem: the lack of origin/destination data•



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