FDI location variables

Competitiveness frameworks have emerged as an explanatory tool to help define location characteristics and conditions, applicable at the national, regional, and city level, which can explain either the success or failure of cities economically, as well as some of the reasons for their differing attractiveness to investment flows. However, these frameworks fail to make a conscious distinction in their models between domestic and foreign investors and have been developed and applied at a geographical scale of regions and cities as a whole. Specific

research into the causes and effects of FDI within both the regional and city levels must be considered, providing a more detailed understanding of the distinct FDI needs and demands of locations from within host cities. The attraction of investment and the generation of growth inside a given city then depends not only on the type of social, cultural, or regulatory environment a city has to offer, but also on the specific demands and needs of companies looking to invest. Therefore, the outcome of this analysis will be a multi-level model of location variables affecting competitiveness at the geographic scales of nations, regions, cities, and neighbourhoods.

The available research for FDI business decision-making has been conducted at a number of different spatial scales from the national level, to more or less generalised regions inside a given nation, to the city level, and the intra-urban level. A summarised literature review is presented here that explores FDI location decision-making from the national level down to the intra-urban spatial scale, specifically noting a considerable shortage of research that actually investigates FDI location making within cities, the smallest scale at which FDI decision-making occurs. Most of the current research into FDI location characteristics has been done at the spatial level of nations or regions, as supported by work done by Oum & Park (2004) and Berkoz & Turk (2008) in their systematic reviews of FDI location decision-making literature. An extensive body of research exists that has looked at FDI investments in different host nations and regions, examining a set of either industry sectors, such as manufacturing, logistics, business services, or specific markets, i.e., France, Germany, Poland, and Italy.

Looking first at FDI investment choices at the host nation scale, a set of common location variables were found to be relevant to FDI location making. Inbound FDI decision-making was influenced mainly by: (1) size of market and economic growth rate, (2) market access factors and market potential , (3) manufacturing productivity, (4) labour costs and unemployment rates, (5) the extent of unionisation of the workforce, (6) geographical proximity of the host country to the home country, (7) government policies towards foreign investment, and (8) infrastructure quality and technological capability of the host country (Wheeler & Mody 1992).

At the regional scale of FDI investment decision-making, the location variables are similar, including market access and demand potential, labour market characteristics, and the quality of infrastructure and transport networks. The attractiveness of regions to FDI investors is also defined by the existence of pre-existing FDI industry clusters (Porter 2000; Cheng & Kwan

2000). Previous investments are deemed to have a positive self-reinforcing effect consistent with the agglomeration effect identified by (Head & Ries 1996) in their investigation of city choice for FDI in China, meaning FDI companies will seek regions and cities with pre-existing FDI clusters (Wheeler & Mody 1992) . Specifically, the FDI investment patterns of French firms are presented by Procher (2009), who examines French FDI investment abroad. Procher found that agglomeration effects from the existing presence of French firms in a given country positively attract new investments, and thus lead to agglomeration economies. This view is also repeated in studies of FDI in Poland (Cieslik 2005) and Italy (De Propris et al. 2005).

The investigation of agglomeration economies amongst FDI investors has attracted criticism in the past because of crude measurement methods, for example using total manufacturing employment as a proxy for specific industry agglomeration economies, as well as highly aggregated regions (US states), making spatial co-location of firms a very vague concept (Guimarães et al. 2000; Coughlin et al. 1991). A notable study sharpening the focus on this issue was done by Smith & Florida (1994). The authors defined a set of detailed regions (US counties) and a very specific FDI population (Japanese car manufacturing) to see if there are specific agglomeration economies affecting FDI investment decisions. In this clearly defined case study, there was significant evidence that Japanese car manufacturing firms locate in proximity to suppliers in order to enable the manufacturers to profit from external spatial economies and the just-in-time inventory system.

Crozet et al. (2004) took a more detailed spatial definition of regions and looked at foreign firms’ location decisions on a regional level in France (90 territorial units). The authors were particularly interested in spatial patterns of co-location between firms of the same nationality and/or same industry sector. A regression analysis was developed incorporating factors such as demand at location; costs; number of other foreign firms, either from same country, overseas or France; distance to home market; and finally, local public policy context. The findings of the study revealed that there were indeed clustering effects linking firms from either the same industry sector or the same nationality. Industry clustering was explained mainly by perceived positive agglomeration effects, such as knowledge spillovers for spatial clusters of activities in specific sectors. As for common national firms, new firms tended to start out in France close to their home market (for example, a German company locating close to the German border), before moving on to locate closer to their French consumers.

Apart from regional clusters of activities in the same sector or from the same FDI source country, regional regulatory and tax incentives can play a positive effect as well, as

demonstrated for China as a FDI recipient (Head & Ries 1996; Cheng & Kwan 2000), where Special Economic Zones and their tax benefits act as significant positive attractors of FDI.

Specifically for the UK, Hill & Munday (1992) identified a scarcity of studies looking at foreign investment at a sub-national level in the UK, along with a lack of appropriate measures on the nature and level of inward investment into the UK and its regions. Hill & Munday investigated the success of certain regions of the UK in attracting FDI. Apart from the previously presented regional level location variables, they also identified the potential effectiveness of regional policy as a guiding tool to ensure a more even distribution of FDI and its benefits to different regions of the UK. Jones & Wren (2008) investigated the effectiveness of grants for FDI investment at the regional level in the UK. They found that grants have a significant positive influence on FDI investors into the UK, but also noted that the influence of regional grants has declined since the 1990’s. Both the Hill & Munday and Jones & Wren studies only addressed FDI investment distribution at a regional level, crucially lumping together London with the wider South-East, and did not address FDI investment at an intra-urban level.

Extending beyond the regional view of FDI investments, the spatial scale of individual cities and their constituting urban areas or neighbourhoods offers the most detailed view of FDI location decisions. Wu (2000) offers one view on FDI investment into Guangzhou, and offers a specific look at location dependant variables which influenced the location choice. First, Wu found, as other studies have, that there is pronounced clustering of FDI resulting from location factors such as transport networks (highway accessibility), labour availability, distance to the Central Business District (CBD), quality of the local infrastructure (hotels, communications), as well as the regulatory environment, in this case special trade zones and business parks, set up by the Chinese government inside the city.

In a later paper, Wu & Radbone (2005) distinguish FDI industry sector-specific location variables for Shanghai. For example, services FDI tends to locate close to existing clusters of services, while manufacturing FDI is attracted to specific government-designated zones, such as industrial and commercial parks. Turkish authors (Berkoz & Eyuboglu 2007; Berkoz & Turk 2008) studied the spatial distribution of FDI in Istanbul specifically for services and

manufacturing. They found that FDI service companies were attracted by a good quality infrastructure, co-location with existing services firms, and access to a qualified workforce.

Manufacturing type businesses were attracted to the suburban areas because of the availability of a larger pool of cheap labour, along with accessibility to major transport hubs, such as railway and harbours. Corroborating evidence from a study (Ihlanfeldt & Raper 1990) not specifically targeted at FDI, identifies similar location effects. Specifically, Ihlandfelt &

Raper identify a significant influence of support services on the location choices of new independent office firms. FDI investors entering a new market can be described as similar to new independent firms, lacking the pre-existing support service networks, such as banks, accountants, and lawyers that existing firms already have established.

Specifically for the UK, and London, Keeble & Nachum (1999; 2000; 2002; 2003) looked in more detail at both foreign and indigenous business services and media firms and their clustering behaviour within London. They found significant clustering behaviour, with the business services located in Central London as a highly integrated industry cluster, driven by accessibility to clients, both local and global, through London’s excellent travel links. These benefits stand in contrast to areas outside of London, where decentralised firms do not have these advantages. For the media sector, Keeble & Nachum (2003) identify a similar, even more localised cluster in Soho, a neighbourhood in the West End of London, with companies looking for extensive and deep connections between firms in the localised sector cluster, taking advantage of external economies benefits.