Xxxii Conferenza Italiana Di Scienze Regionali

Xxxii Conferenza Italiana Di Scienze Regionali





This paper explores the competitiveness of economic areas at a cluster level in terms of their capacity to attract the location of MNCs. In particular, the study investigates what are the agglomerative forces that drive the location choice of MNCs toward Industrial Districts (IDs).

To this aim, two streams of studies are considered: the first regards the location decisions of MNCs and the second the new theories on the ID competitive advantage.

Based on these studies, four hypotheses concerning the knowledge-based conditions driving the location choice of MNCs in IDs are formulated. To test the hypotheses, an econometric analysis on the 156 Italian IDs, using a OLS model, is conducted.

1. Introduction

The research on industrial districts (IDs) in the recent years is focusing more and more on issues concerning the competitiveness and the survival of these local production systems. The main open questions are “(Biggiero, 2006; Crouch et al., 2001; Rabelotti et al., 2009)”:

-Can the IDs, whose competitive advantage seems to rest on the co-location of various phases of production, survive?

-How can IDs face the challenges due to the globalization and digitalization phenomena?

-Can the delocalization and relocation processes determine the ID’s recession or decline?

The agglomeration economies associated with the spatial concentration of productionand based on “(Marshall, 1920)”the readily available specialized and skilled labour, the privileged access to local suppliers that offers a great variety of highly specialized inputs, and the easy and rapid access to specific technical knowledge,are cost-based benefits for co-located firms (pecuniary externalities).But in a global economy firms can gain a cost based competitive advantage delocalizing their production processes in low cost countries.

This phenomenon has involved some IDs determining a process of hollow-out and has led scholars to theorize a decline of this production model.

Nevertheless the cases of declining IDs, there are examples of successful IDs that continue to grow and that attract the localization of multi-national corporations (MNCs).Examples of such IDs come from: the Montebelluna sportswear system “(Sammarra and Belussi, 2006)” that is marked by the presence of some of the most important multinational companies in the sports shoe sector (e.g. Rossignol, Lange, HTM, Nike); the so-called Etna Valley technology district located in Sicily, which origin was strongly linked to the localization of the ST Microelectronics and now its success is also due to the large presence of important multinational companies, such us Nokia and Omnitel; the Mirandola biomedical districtthat,thanks to the considerable accumulation in the area of specialized knowledge and high quality technical know-how combined with the typical advantages of an ID, has now attracted several multinational companies including Baxter, Mallinkrodt, Braun Carex, Biofil and Hospital Dasco.

In this context where opposite trends are observed, the following research question arises: Is the ID production model still attractive?

This paper explores the attractiveness of IDs in terms of their capacity to draw MNCs that are making location choices. In particular, the main interest of the present study is to investigate what are the agglomerative forces that drive the location choice of MNCs toward the IDs.

To this aim, two streams of studies are integrated: the first regards the location decisions of MNCs and the second the new theories explaining the competitive advantage of IDs. In a knowledge-based economy where knowledge is considered to be a firm’s most important competitive asset, firms that make location choices are interested to search for new sources of knowledge to sustain their competitive advantage. Agglomeration of firms within a geographically bounded area increases the effectiveness of knowledge exchanges among ID firms and enhances the processes of new knowledge creation so creating a competitive advantage for the individual firms as well as for the entire ID “(Chung and Alcacer, 2002; Kalnins and Chung, 2004)”. According to these two perspectives, it is possible to argue that MNCs will prefer to locate in the IDs where the amount of knowledge and the possibility to acquire knowledge are high.

The proposed analysis goes beyond general studies on MNCs in IDs. These in fact have mainly investigated the importance of MNCs for the ID growth due to their connecting role between the ID and to external source of knowledge and their capacity to bring in complementary and not contextual knowledge “(Bagella et al., 1998; Helg, 2003; Menghinello, 2004; Shin et al., 2006)”. On the contrary, very few studies have investigated the benefits that MNCs can gain by locating within IDs as well as the determinants of their location choices “(McCann et al., 2002; DePropris et al., 2005)”. In line with these studies, the paper investigates the importance of two determinants for MNCs location in IDs: the amount of knowledge stock and the level of knowledge transfer characterizing the ID.

The paper is organized as follows. The next section briefly presents the two theoretical streams of study on which the research is based. The third section describes the conceptual model developed to explain the attractiveness of IDs towards firms that are making the location decision. In this section four hypotheses on how the ID knowledge characteristics affect the ID attractiveness towards MNCs are formulated. Then we describe the empirical analysis carried out on the 156 Italian IDs. The methodology section consists of the description of data, variables and the empirical results, and it is followed by a discussion and conclusion.

2. Theoretical background

2.1 The industrial districts

IDs are geographically defined production systems, characterized by a large number of small and medium sized firms that are involved at various phases in the production of a homogeneous product family. These firms are highly specialized in a few phases of the production process, and integrated through a complex network of inter-organizational relationships “(Becattini, 1990;Becattini et al., 2009; Maskell, 2001; Porter, 1998)”.

Diverse streams of study havedeveloped a variety of perspective to explain the IDs competitive success and investigated the different sources of their competitive advantage.

In particular, the studies of economic geography have underlined the benefits associated to the “agglomeration external economies”, mainly due to the lower input costs, the development of common suppliers, specialist labour pools, spillover of technical know-how, and the development of a greater comprehension of the workings of the particular industry by individuals and firms “(Becattini, 1990; Marshall, 1920)”.

Studies on industrial economics have highlighted the reduction of the transactional costs due to geographical proximity of firms and informal and face-to-face contacts among them as one of the most important benefits of IDs “(Mariotti, 1989)”.

Studies on innovation management have pointed out that IDs found the competitive success on their innovative capacity, which is due to the presence of high specialized technical competencies, the existence of networks of formal and informal relationships, and the geographical proximity that creates an environment wherein information, codes, languages, routines, strategies, and knowledge are easy to be transferred and shared “(Cainelli et al., 2005; Cooke and Morgan, 1998; Henry and Pinch, 2002; Lundvall and Johnson, 1994; Storper, 1997)”.

Synthesizing the results of these studies, the competitive success of IDs is mainly based on: the specialization of firms, the presence of a specialized workforce, the division of labour among firms, the accumulation of specific knowledge in the local area, the networking processes among both the economic and social system, the development of a widespread innovative capacity, the presence into the local area of a common system of social-cultural values.

Recently,some scholars have rethought the ID production model shifting their attention from the cost-based benefits to the knowledge-based benefits. These works have proposed a knowledge-based theory of IDs “(Maskell, 2001; Maskell and Malmberg, 2004)”, by investigating the nature of knowledge circulating in IDs “(Tallman et al., 2004)”, the frequency and the effectiveness of the knowledge transfer processes among ID firms “(Gordon and McCann, 2000; Mesquita, 2007)”, and the learning processes activated by firms in IDs “(Albino et al., 2005; Maskell, 2001)”.

According to these studies, the key source of the ID competitive advantage is their superior capacity to support processes of knowledge transferand creation, and to facilitate innovation.

2.2 Location choices of MNCs

MNCs location decisions have been extensively studied in the international business context.

Dunning (1993) identified four categories of motives for foreign direct investments (FDIs) by MNCs: resource seeking,market seeking, efficiency seeking, and strategically motivated seeking. FDI motivated by resource seeking tends to acquire natural resources, raw materials, and technologies available in host country less costly. The market seeking FDI has as a main aim to enter into a new market by avoiding trade barriers and high transportation costs. The FDI that seeks to increase the efficiency of the company are mainly motivated by the reduction of production costs achievable by localizing the production activities into countries with lower labourcosts. Strategic-seeking FDI is engaged by company to promote their strategic objectives, usually that of sustaining or enhancing their international competitiveness.

Firms expand abroad also to exploit local financial incentives, environmental constraints, to overcome export-import constraints, to differentiate the product “(Dunning, 1973; Porter, 1986; Bartlett, 1986; Lessard, 1986; Bartlett and Ghoshal, 1989; Bellini et al., 1998; Dunning, 1998; Fujita et al., 1999)”.

Recently, the analysis of MNCs location choice has been extended by recognizing a further motive to FDI: knowledge seeking, i.e. the exploitation of new technologies, skills, knowledge, and competencies that are not available in their home countries “(Cantwell, 1989; Chung and Alcacer, 2002)”.Even though it is possible to catch new knowledge by imitating products and marketing strategies of the leading firms, the most effective way to transmit and absorb knowledge is to locate close to knowledge sources “(Boschma, 2005)”. A lot of studies have in fact put in evidence that the intensity of knowledge spillovers increases with geographical proximity “(Antonelli, 2000; Audretsch and Feldman, 1996; Jaffe et al., 1993)”.

In line with this view, the literature on the internationalization of R&D contains an increasing amount ofevidence that knowledge sourcing may be a motive for FDI “(Cantwell, 1995; Cantwell and Janne 1999; Pearce, 1999; Florida 1997)”.

Literature has also investigated the link between MNCs location choice and agglomeration.Krugman (1991) highlights that the existence and the development of a local industry makes the location in that area more and more attractive due to the presence of agglomeration externalities. Cantwell (1989;1991) shows that there are significant benefits to both domestic and foreign firms from agglomeration because of the exploitation of localized knowledge that is increasingly important for the advancement of their technological competence.

Le Bas and Sierra (2002) and De Propris and Driffield (2003) developsuch arguments further and focus on a local unit of analysis consisting in the ID. They demonstrate that IDs are important fortechnology sourcing FDI by MNCs because of knowledge spillovers that are significantly greater for IDs, and argue that they are important attractors for FDI.

3. Location of MNCs in Industrial districts

In line with the knowledge seeking FDI motivation, it is possible to argue that the attractiveness of some IDs lieson the valuable opportunities they offer for increasing MNC knowledge due to the knowledge inflows resulting from both the available stock of knowledge and the degree of knowledge transfer characterizing the ID.

In the next,wesustain these arguments by borrowing both the literature on MNCs agglomeration and on ID, and four hypotheses to be empirically tested are developed.

3.1 The ID Knowledge stock

The knowledge stock is the amount of assets a firm. The ID knowledge stock derives from the knowledge embedded into three kinds of actors: the individuals, the firms, and the institutions located in the ID.

As to the individuals, the knowledge stock is associated with their professional skills and knowledge on manufacturing processes and products and on the markets. The individual knowledge stock is continuously increased by the processes of learning by using, by doing and by interacting with other individuals.

As to firm, the knowledge stock concerns the accumulated knowledge assets which are internal to the firm, such as the intangible research capabilities, the technological capabilities, and relational capabilities. The firm knowledge stock is updated by the R&D activities internal to the firms, by interactive learning processes activated with suppliers and customers, and by hiring high specialized workforce.

As to institution, the knowledge stock is mainly the scientific and codified knowledge developed in universities and research centres. This is accumulated by internal R&D activities and by exploiting external knowledge sources.

Literature on agglomeration of MNCs has shown the importance of knowledge and knowledge activities as a motive to agglomerate. A few studies consider the knowledge stock associated with workforce and stress the importance of the educational level as a possible determinant of FDI attraction “(Couglin and Segev, 2000)”. Other studies focus on the knowledge stocks as the result of R&D activities developed by firms and institutions “(Cantwell, 1995; Cantwell and Janne 1999; Pearce, 1999)”. For example, Basile (2004) studies the importance of public research institutions in attracting the FDI in Italy.

In line with these arguments, the following hypotheses are formulated:

Hp1:The higher the intensity of R&D activities,the higher will be the ID attractiveness towards MNCs that are making location choices.

Hp2:The higher the level of ID professional workforce,the higher will be the ID attractiveness towards MNCs that are making location choices.

3.2 The ID knowledge transfer

The degree of knowledge transfer describes the transferability of knowledge. The transferability depends on the nature of knowledge (the more codified, the easier the transfer) and on the existence of factors that enable the knowledge sharing and spread.

Literature on MNCs analyzing the critical role of knowledge as a source of competitiveadvantage, has also stressed that a further critical factor in the process knowledge seeking it is linked not only to the amount of available knowledge but also to the capacity to spill that knowledge. Because knowledge is partially tacit and localized, it is widely recognized that knowledge transfer requires frequent interaction that proximity facilitates. In the IDs the geographical proximity among firms facilitates face-to-face contacts and the inter-firm informal relationships, so as to create an environment conducive of knowledge “(Maskell, 2001)”.

Thus, weposit that:

Hp3. The higher the geographical proximity among firms, the higher will be the ID attractiveness towards firms that are making location choices.

According to the theory of knowledge spillover entrepreneurship “(Acs and Armington, 2006; Acs et al., 2006; Audretsch et al., 2006)”, the start-up of a new venture provides the conduit for the spillover of knowledge from the source firm creating that knowledge to the new venture, actually exploiting and commercializing that knowledge. Thus, the entrepreneurial activity provides the conduit facilitating the knowledge transfer.

To this regard, Garnsey and Heffernan (2005) studying the Cambridge cluster find that the formation of new firms and spin-out from the university and local businesses being channels of knowledge diffusion exerts attraction effects through international subsidiaries and inward FDIs.

The creation of new firms by both academic and not-academic spin-offs is a phenomenon well investigated in the ID literature “(Saxenian, 1994)” as one of the main condition for the development. The generation of a new firm by employees of an existing local organisation as a research centre, a university, and a firm involves the transfer to the newly established firm of know-how and problem solving skills previously learned within the local organization and this in turn activated learning processes and new knowledge.

Therefore, the following hypothesis is formulated:

Hp4. The higher the rate of formation of new firms, the higher will be the ID attractiveness towards firms that are making location choices.

4. Empirical analysis

4.1. Data

The data set is formed by all the Italian Industrial Districts identified by the Italian National Statistical Institute (ISTAT) on the basis of the information provided by the 2001 Industry Census“(ISTAT, 2001)”. In particular, the ID identification comes from the following procedure. First the national territory has been divided into local labour systems (LLS), defined as small areas characterized by internal commuting patters that produce a self-contained labour market. Using information on daily commuting to work contained on the 2001 Population Census and starting from the aggregation of the smallest geographical unit defined for administrative purposes in Italy (municipalities) ISTAT divided the Italian territory into 686 LLSs. Second, for each SSL three distinct indexes are calculated. The first measures the share of manufacturing employment in the local system, the second the share of manufacturing employment in small and medium (less than 250 employees) firms, the third is a sector specialisation index. All the indexes are calculated with respect to national averages. A local system for which the three indexes result simultaneously greater than one is defined as an industrial district.

In this way the data set covers a number of 156 IDs. In Table 1 the main demographic data on IDs and LLSs are reported. Table 2 synthesizes the key characteristics of the Italian IDs.

Table 1. Demographic data of Industrial Districts and Local Labour Systems, 2001.

Indicators / IDs / LLSs / %
Number / 156 / 686 / 22,7
Number of municipalities / 2.215 / 8.101 / 27,3
Area (square Km) / 62.114 / 301.328 / 20,6
Population / 12.591.475 / 56.995.774 / 22,1
Local units / 1.180.042 / 4.755.636 / 24,8
Local units’ employees / 4.929.721 / 19.410.556 / 25,4
Manufacturing local units / 212.410 / 590.733 / 36,0
Manufacturing local units’ employees / 1.928.602 / 4.906.315 / 39,3
Employment density (%) / 39,1 / 34,1 / -
Entrepreneurial density (%) / 9,4 / 8,3 / -

Table 2. Main characteristics of Italian Industrial Districts, 2001.