The Economies and Diseconomies of Industrial Clustering: Multinational Enterprises versus Uninational Enterprises.
| Verfasser | Pandit, Naresh R. |
| Posten | RESEARCH ARTICLE - Report |
1 Introduction
The economies and diseconomies of industrial clustering have long been studied by economists and management scholars (Dunning 1998; Marshall 1890; Porter 1998; Swann et al. 1998). Recently, two special issues on multinational enterprises (MNEs) and location in geographical clusters, one in the Journal of Economic Geography in 2011 and the other in the Journal of International Business Studies in 2013, point to a surge and convergence of interest in the subject by economic geography (EG) and international business (IB) scholars. Within IB, a re-evaluation of the spatial organisation of MNE activities has been underway since Dunning's (1998) call for more research on location, and in particular, location in clusters. He concluded: "The extent to which MNEs promote, or gravitate to, spatial clusters within a country or region is an under-researched area" (Dunning 1998, p. 58). This is argued to be "[...] partly because scholars have believed that the principles underlying the locational decisions of firms within national boundaries can be easily extended to explain their cross-border locational preferences" (Dunning 1998, p. 49). This belief is explored in this paper and, in particular, we ask: Do MNEs experience different economies and diseconomies of location within a cluster compared to uninational enterprises (UNEs)?
In order to address this question, this paper begins by assessing cluster economies and diseconomies in a highly productive industrial cluster--the City of London financial services cluster. The City of London is an exemplar cluster (Cook et al. 2007), albeit one embedded as a node in an international network of key financial centres (Amin and Thrift 1992). It is one of the few examples of a cluster which stands serious comparison with the iconic status of Silicon Valley. This financial services cluster supports nearly 2.2 million jobs across the UK, paying more in tax than any other sector and contributing 12% of UK GDP (TheCityUK 2016). It is the global leader in fixed income, currencies and commodities (FICC) trading, cross-border lending, and specialty commercial insurance, and consistently occupies a top three position across other major business lines (The City UK 2016).
Following previous research (Nachum and Keeble 2003; Zaheer 1995; Zaheer and Mosakowski 1997), we adopt comparative analysis to investigate and identify those common and distinctive characteristics between MNEs and UNEs. Based on a data-set drawing from a large-scale mail survey, our analysis shows that MNEs and UNEs do experience different economies and diseconomies of location within the financial services cluster in London. Specifically, we find that social capital and labour pooling are equally important to MNEs and UNEs. However, local competition and congestion costs are more important to MNEs, while the reputational benefit of locating in a strong cluster and access to specialised suppliers are more important to UNEs.
Our study's main contribution is to add sophistication to the extant literature. Scholars of industrial clusters have long studied the economies and diseconomies of cluster participation for firms in general but have not distinguished the effects between MNEs and UNEs (Marshall 1890; Porter 1998; Swann and Prevezer 1996). In contrast to the implicit assumption of this literature, that economies and diseconomies of clusters are valued similarly by all firms, we provide a finer analysis to suggest that the economies and diseconomies of cluster participation are valued differently by MNEs compared to UNEs.
In the next section, based on the established clusters literature and the emerging literature on MNEs in clusters, a set of hypotheses that relate to the research question are generated. Then, the research design of the study is stated describing its unit of analysis and its method of data collection and analysis. Next, we present and discuss the main results and additional results. The final section concludes and states the managerial and policy implications of the study.
2 Literature Review and Hypotheses
Clusters are defined as related firms based in a geographical area (Swann and Prevezer 1996). The geographical concentration of production is not a new phenomenon, and dates back at least to Alfred Marshall who introduced the 'industrial district' concept describing the pattern of industrial organisation in late nineteenth century Britain in his Principles of Economics (Marshall 1890). Cluster participation is theorised as incumbents' desire to access more effectively certain resources in industrial clusters by locating in geographic proximity (Enright 2000; Nachum and Keeble 2003; Porter 1998). A firm is said to participate in a cluster when it is located in geographic proximity to a collection of related firms and maintains various forms of formal and informal linkages with them (Nachum and Keeble 2003).
The economies and diseconomies of cluster participation have attracted much interest among management scholars with notable representatives including Porter (1998), Swann et al. (1998), Dunning (1998), and the two special issues (Journal of Economic Geography in 2011 and Journal of International Business Studies in 2013) on MNEs and location in geographical clusters. Drawing from this stream of literature, the specific economies and diseconomies of locating in a cluster from the perspective of the clustered firm are explained as follows.
Firms may be attracted to a location due to the existence of fixed factors (Swann et al. 1998). These are benefits that exist at a location that are not a function of the co-presence of related firms and institutions and include climate, time zone and language. Beyond these fixed factors, we can distinguish between economies and diseconomies of clustering. The former refer to increased benefits for incumbent firms as each additional firms joins the cluster. The latter refer to decreased benefits for incumbent firms as each additional firm joins the cluster. An additional firm joining the cluster will drive both effects at the same time to differing degrees, which will turn both on the specific identity of the firm and the maturity of the cluster. Net economies give the extent to which economies outweigh diseconomies and so indicate the strength of the cluster. Clusters then vary by strength according to the size of these net economies with rich, strong, high-performing clusters associated with large net economies and shallow, weak, low to average performing clusters associated with small or negative net economies. Economies and diseconomies can arise on both the demand and supply side.
On the demand side, the firm may benefit from customer proximity (Von Hippel 1988) which can be especially important when customers are sophisticated. Such customers can encourage innovation through sophisticated demand and by alerting suppliers of new trends and innovations. The clustered firm may also benefit from reduced customer search costs (Swann et al. 1998). The idea here is that the firm is more likely to be found by customers when it is located in a cluster. This is particularly important when customers have specific requirements. Information externalities on the demand side may also exist, that is, a cluster's reputation rubs off on the firm that is located in it (Kalnins and Chung 2004).
On the supply side, a major benefit is that knowledge spills over in a cluster and this is particularly important when valuable industry knowledge is tacit rather than codified. In a sense, tacit knowledge becomes a public good (Marshall 1890; McCann and Folta 2009). When this happens, innovation can be more prolific. Mechanisms for knowledge spillovers include labour market churn, social interaction, spin-offs and diffusion via clients and suppliers. A second supply side benefit is access to specialised inputs (Marshall 1890; McCann and Folta 2009). As a result, the firm benefits from lower search costs because it can easily recruit from a pool of specialised labour and can tap into a specialised supplier base. Infrastructure benefits (Porter 1998) go beyond access to a good transport network to include institutions that coordinate activities across companies in order to maximise collective productivity, for example, trade associations which set standards and/or conduct marketing for the cluster as a whole. Better motivation can also exist within a cluster as local rivalry can act as a powerful spur. Also, it can be easier to measure performance (benchmark) against local rivals as they share a similar context leading to lower monitoring costs (Porter 1998). Another important supply side benefit is that it can be easier to try out new ideas in a cluster since it is possible to gain instant feedback and all of the inputs (including sympathetic venture capital) required for experimentation (Swann et al. 1998) are likely to be present in the cluster. Finally, a clustered firm may benefit from informational externalities on the supply side (Swann et al. 1998): The firm enjoys lower risk by observing successful production at a location.
With respect to cluster diseconomies, on the demand side, congestion and competition in output markets (Swann et al. 1998) can lead to lower prices and so profits can fall. Also, a cluster specialised in a particular technology can go into decline if that technology is substituted.
On the supply side, congestion and competition in input markets can lead to higher wages and rents which in turn could lead to movement out of the cluster (Pandit et al. 2002). This is a natural process and can be one whereby the cluster strengthens as those firms which can best take advantage of being in the cluster outbid others for factors of production. Three further decline factors can all tempt behaviour that erodes competitive advantage. Being close to competitors tempts cartel formation and isomorphism (herd behaviour) which can have a...
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