Geographical pathways for SMEinternationalization: insights

from an Italian sampleAlfredo D’Angelo

Adam Smith Business School, University of Glasgow, Glasgow, UK

Antonio Majocchi and Antonella ZucchellaDepartment of Economics and Management, Universita degli Studi di Pavia,

Pavia, Italy, and

Trevor BuckAdam Smith Business School, University of Glasgow, Glasgow, UK

Abstract

Purpose – The purpose of this paper is to examine the determinants of two distinct geographicpathways to internationalization for small and medium-sized enterprises (SMEs). Regional and globalpathways are juxtaposed to study the influence on export performance of selected key intangibleresources, namely, innovation, human resource management, networking and the firm’s experience.Design/methodology/approach – Building upon a resource-based view of the firm, Tobitregression models are used to test the hypotheses on a sample of 2,657 Italian manufacturing firms.Findings – The paper provides empirical evidence that the determinants of SME export performancevary in line with the geographic scope of internationalization. While product innovation (innovation)positively impacts on SME export performance, irrespective of export destination, other factors do soselectively. For example, location in industrial districts (networking) and the deployment of externalmanagers (human resource management) exclusively exert their positive impact respectively onregional and global export performance. The firm’s age (experience) does not seem to guaranteesuccess on regional or global export markets.Practical implications – Investing in product innovation and hiring specialist non-familyexecutives are associated with success on global export markets. Industry clustering provides theresources that are useful for internationalization up to a point (export growth in regional markets), butit is not effective in the case of expansion on distant international markets.Originality/value – Exporting beyond the regional market exposes firms to the liability offoreignness to a greater degree, thus requiring more dedicated and specialized resources andcompetences. This paper supports the hypothesis that export drivers differ between regional andglobal markets and calls for a definition of export performance that distinguishes between them.

Keywords Small to medium-sized enterprises, Italy, Exports, Manufacturing industries, Innovation,Human resource management, Internationalization, Regionalization, Geographic pathways,Export performance

Paper type Research paper

IntroductionIn the literature on the internationalization of small and medium enterprises (SMEs),the terms “patterns” or “pathways” usually involves contrasting the traditional“stages” models (e.g. Johanson and Vahlne, 1977) with those describing born globals orinternational new ventures (INVs) (e.g. Knight and Cavusgil, 2004; Moen, 2002; Oviattand McDougall, 1994) and with born-again global firms (Bell et al., 2001). However,regional and global internationalization also represent two distinct geographicpathways available to SMEs (Chetty and Campbell-Hunt, 2003) emphasizing theimportance of geo-political, institutional and cultural factors in determining the level of

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Received 30 June 2011Revised 14 February 20123 October 20124 January 2013Accepted 16 January 2013

International Marketing ReviewVol. 30 No. 2, 2013pp. 80-105r Emerald Group Publishing Limited0265-1335DOI 10.1108/02651331311314538

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effort and resources needed to internationalize through entering countries within afirm’s home region compared with those needed outside the region (Rugman andVerbeke, 2004), where the liability of foreignness is more serious and costly.

Previous studies reported that the greater liability of foreignness between broadinternational regions (Rugman and Verbeke, 2004, 2007; Rugman et al., 2009 inter alia) hasconstrained even large firms, which traditionally have more resources and competenciesfor international operations, and that only a small number of large companies were able toconsistently penetrate and achieve sales globally (i.e. beyond regional markets); themajority of firms that cross-national borders were still mainly focused on their homeregions (i.e. EU for Italian, French and German firms; NAFTA for American; ASEAN forJapanese). This constraint may therefore be considered to be even stronger for SMEs,which traditionally lack the resources to support such ventures (Andersen, 1993; Knight,2000; Pangarkar, 2008). The purpose of this paper is to examine the influence of some keyresources deployed by SMEs to succeed on regional and global markets and whether thoseresources impact differently on the export performance of firms when they followthese two distinct geographic pathways to internationalization.

The literature on the internationalization of SMEs (Aaby and Slater, 1989; Cavusgiland Zou, 1994; Chetty and Hamilton, 1993; Katsikeas et al., 2000; Leonidou andKatsikeas, 1996; Leonidou et al., 2002; Sousa et al., 2008; Wheeler et al., 2008; Wolffand Pett, 2000; Zou and Stan, 1998) establishes exporting as a dominant entry modeinto international markets. SMEs tend to move into foreign markets mainly asexporters because exporting is the cheapest, simplest and quickest way to achieveinternationalization (Leonidou et al., 2010; Majocchi et al., 2005). Accordingly, exportperformance, along with its main determinants, is one of the most intensivelyresearched topics in international marketing (Chetty and Hamilton, 1993; Katsikeaset al., 2000; Knight, 2000; Morgan et al., 2004; Zou and Stan, 1998; Zou et al., 2003).However, the issue of the determinants of export performance remains one of the leastunderstood in the literature (Leonidou et al., 2010). One of the main reasons is that, overthe last five decades of research into SME export activities, limited attention has beendevoted to differentiate the regional and global scope of internationalization (Katsikeaset al., 2000; Kuivalainen et al., 2007; Pangarkar, 2008).

Earlier literature reports anecdotal evidence on the dichotomic (regional vs global)nature of international activities of SMEs (Chetty and Campbell-Hunt, 2003; Dimitratoset al., 2010; Lopez et al., 2009). Empirical studies have analysed the export activitiesof regional and global SMEs (Baleska-Spasova and Glaister, 2009), but with littleattention to the regional/global distinction itself (Nkongolo-Bakenda et al., 2010).One partial exception is Kuivalainen et al. (2007) who investigated whether firmsexporting to regional markets and “truly global” firms had different characteristics.Their results show that the level of global diversity is influenced by the levelof entrepreneurial pro-activeness and by the level of environmental turbulence inan industry sector. However, their analysis is directed specifically at firmsinternationalizing within the first three years after their establishment. Othernotable studies examining the role of regional markets/countries in SMEinternationalization are those conducted by Reuber and Fischer (1997), Zahra et al.(2000) and McNaughton (2003). However, they focused on the internationalizationprocess of small entrepreneurial, knowledge-intensive firms only. In contrast, ouranalysis embraces all kinds of SMEs. Using a large set of Italian manufacturing SMEs,we aim to fill a research gap by investigating the key determinants of export successfor SMEs and whether they vary in line with the geographical scale of operations.

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Exporting is by definition a risk-taking activity, as the firm operates in anenvironment that is characterized by a certain degree of uncertainty. Therefore, firmsneed resources and competencies to successfully overcome obstacles to foreigndevelopment and to manage a process of international growth. Previous studiesacknowledged that both internal and external resources can be leveraged by SMEsto overcome obstacles to internationalization (Bell et al., 2003; Sousa et al., 2008;Stoian et al., 2010; Wheeler et al., 2008). Innovation is one of the key resourcesto gain access to international markets (Cassiman and Golovko, 2011; Knight andCavusgil, 2004; Rodriguez and Rodriguez, 2005 inter alia). In addition to the key roleplayed by innovation in contributing to SMEs export success, we analyse the effectof two further resources that are a special feature of Italian small-firm capitalism,i.e. a family-oriented approach to human resource management and networkingactivities within the company’s home market. Previous research support the idea thatexport growth “[y] is strongly influenced by background variables from the localbusiness environment” (Stottinger and Holzmuller, 2001, p. 23). Finally we consider therole of the firm’s experience as a potential influence on the internationalizationpathways of firms, which may be affected by the incremental accumulationover time of the resources and capabilities necessary to face foreign market uncertainty( Johanson and Vahlne, 1977). Our analysis builds on previous studies to testwhether exporting beyond regional markets is particularly subject to the liability ofinter-regional foreignness, and thus requires more dedicated and specializedresources and competences than those needed for success within the regionalmarket. Our results confirm that, while factors such as product innovation(innovation) impact positively on SME export performance irrespective of exportdestination, others do so selectively. For example, location in industrial districts(networking) and the deployment of external (non-family) managers (humanresource management) exert their positive impact exclusively on regionaland global export performance, respectively. On the other hand, a firm’s age(experience) does not seem to be a pre-requisite for success on regional or globalexport markets.

The rest of the paper is organized as follows. Section 1 discusses the theoreticalbackground to the study and reviews the literature on exporting in order to developworking hypotheses. Section 2 describes our sample and methodology used. Section 3reports the empirical results. Section 4 provides a discussion of the main findingsand implications for practitioners. Section 5 concludes by claiming our theoreticalcontribution, outlining limitations and by advancing suggestions for future research.

Literature review and hypothesis developmentPrevious studies related to SMEs’ export success have often been criticized as lackinga valid body of theory, but Katsikeas et al. (2000) in their seminal paper proposedthe adoption of the resource-based view (RBV) to enhance knowledge on exportperformance and its determinants. Subsequently, many scholars have deployed theRBV as a theoretical framework to test exporting models (Dhanaraj and Beamish, 2003;Rodriguez and Rodriguez, 2005; Stoian et al., 2010; Westhead et al., 2001; Wolff andPett, 2000). This paper follows this tradition by testing hypotheses developed froman RBV perspective in the volatile environment of a large, rich cross-sectional databaseof 2,657 Italian SMEs.

It is argued that this context provides circumstances that could be expected toweaken the importance of static resources, and thus expose the RBV to a strong test.

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For example, Eisenhardt and Martin (2000) claim that in high-velocity markets(p. 1106) static resources are exposed to “simple, experiential, unstable processes thatrely on quickly created new knowledge and iterative execution to produce adaptive,but unpredictable outcomes”. Similarly, Kraaijenbrink et al. (2010) make a plea forstudies to explain competitive advantage (p. 351) “[y] especially beyond predictable,stable environments”, since the RBV (p. 353) “[y] applies only to large firms withsignificant market power”.

SMEs represent the antithesis of “predictable, stable environments”, with small-firmsize and relatively low-capital costs resulting in low-entry barriers for an industry,low-monopoly power and high turnover rates of firms. Together, these factors may allbe expected to militate against the power of static resources.

SME exporting has already been studied in the RBV literature, but Knight andCavusgil (2004) observe that little of this research focuses on small firms. As furthersupport for our tests on the RBV in a small-firm environment, Barney et al. (2011, p. 8)appeal for studies that expose the RBV to different governance regimes besides thelarge MNEs that have been the focus of most of the exporting literature (e.g. Bernardand Jensen, 2004). Our focus on small, mainly family-managed, exporting SMEs inItaly represents a response to this appeal. Our study also responds to the generalappeal of RBV critics (e.g. Armstrong and Shimizu, 2007, p. 973) for multi-industrysettings to increase sample sizes and generalizability.

Grounded on the pioneering work of Penrose (1959), the RBV sees firms as a uniqueand heterogeneous bundle of tangible and intangible resources (Barney, 1991; Peteraf,1993; Wernefelt, 1984). While combinations of resources may give an initial competitiveedge, advantage may be sustainable only if firms are able to prevent subsequentimitation by competitors, and imitation is most difficult with causal ambiguity inthe context of intangible resources such as technological knowledge embedded ininnovation, managerial practices, social context and customer awareness (Peteraf,1993; Collis and Montgomery, 1995). While unable to analyse the full range ofintangible resources, this paper focuses on certain key resources previously identifiedas being important to SME exporting, i.e. innovation (e.g. Rodriguez and Rodriguez,2005), human resource management ( Jones and Coviello, 2005), external networks(Bell et al., 2003) and firms’ experience (Brouthers and Nakos, 2005).

Among intangible resources, great importance has been placed on innovation inrelation to internationalization. Indeed, at a conceptual level, innovation has beenprominent as a leading ownership advantage in Dunning’s eclectic theory ofinternationalization (see Brouthers et al., 1999). However, most of the internationalization/exporting literature has been at an operational level, focusing on constructs (Cassimanand Golovko, 2011; Knight and Cavusgil, 2004; Westhead et al., 2001).

Empirical evidence supports the idea that innovation is an important sourceof competitive advantage in international markets and a significant determinant ofexport success (Basile, 2001; D’Angelo, 2012; Golovko and Valentini, 2011; Rodriguezand Rodriguez, 2005; Nassimbeni, 2001; Roper and Love, 2002; Sterlacchini, 1999;Wakelin, 1998). Innovation may apply to a firm’s products, processes and structures,and according to Adams et al. (2006) innovation is a complex phenomenon measuredby a plethora of indicators distinguishing input measures (e.g. R&D expenditure, R&Demployees, etc.) from output measures (e.g. product, process, patents, marketingactivities, etc.). Export studies using R&D expenditure or intensity as a proxy tomeasure the impact of innovation on firms’ export performance have producedcontrasting results (e.g. Rodriguez and Rodriguez, 2005; Nassimbeni, 2001; Roper and

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Love, 2002; Sterlacchini, 1999). This is mainly due to the fact that SMEs often do notpossess a formal R&D department (Brouwer and Kleinknecht, 1996), and theirpublished accounts often do not distinguish between R&D and operating costs(Lefebvre et al., 1998; Nassimbeni, 2001; Sterlacchini, 1999). As a result, using R&Dexpenses may be misleading in the case of small firms, producing unreliable results ofthe impact of innovation on SMEs’ export performance (Brouwer and Kleinknecht,1996; Hoffman et al., 1998). Consequently, some authors (Lefebvre et al., 1998;Rodriguez and Rodriguez, 2005) suggested taking into account innovation outputsmeasures in order to fully capture the firm’s innovative effort, and we focus on productinnovation as the result of the firm’s innovative process (De Jong and Vermeulen, 2006)to measure the impact of innovation activities on SMEs’ export performance.According to RBV theorists (e.g. Barney, 1991; Wernefelt, 1984), the distinctiveness ofinnovative products (or services) should provide longer term competitive advantagesthan low price alone, on condition that they are considered by customers to haveunique and difficult to imitate characteristics. Oviatt and McDougall (1994)acknowledged that SMEs with a unique product (or service) might want to exploitthe innovation before it is imitated by competitors transforming innovative ideas intosales. Given increasing competition and the relatively short life cycle of innovations,firms may seek to commercialize their new products (or services) on multiple marketsin order to take advantage of higher global demand (Dimitratos et al., 2003). Althoughthe main thrust of this paper is directed at the distinction between exports to regionaland global markets, we propose here that any influence of innovative products onexports will be universal. We therefore propose the following hypothesis:

H1. There will be a positive association between a firm’s product innovation andexporting to (a) regional and (b) global markets.

As the RBV developed beyond its “introductory” stage up to 1991 (Barney et al., 2011),its emphasis on accumulated stocks of resources that could eventually be imitated bycompetitors was gradually extended to embrace the firm’s orchestration of suchresources (Sirmon et al., 2011). As noted above, the firm’s ability to enter internationalmarkets will depend, inter alia, on its ability to bring innovations down to markets,transforming innovative ideas into sales. However, it could also depend on process andorganizational capabilities that lower marginal costs and increase competitiveness.In this context human resource management can play an important role as anintangible element of the entrepreneurial internationalization process ( Jones andCoviello, 2005). This is particularly true in the context of small firms facingresource constraints (Bell et al., 2004; Etemad, 1999) and it is in line with previousresearch that supports the idea that innovation can be a source of competitiveadvantage on international markets when managed effectively (Stoian et al., 2010).

Maritan and Peteraf (2011) propose two separate mechanisms as sources ofcompetitive advantage: internal resource accumulation (e.g. innovation, see above) andresource acquisition on strategic factor markets, and this can apply to human resourcemanagement, e.g. the recruitment of external managers.

The assembly of top management teams (TMTs) is a crucial part of strategicresource acquisition, as opposed to internal staff development. Given the size anduniqueness of SMEs, it is unlikely that managerial routines and processes will beformalized and therefore be imitable by other firms, owing to causal ambiguity withinsmall, flexible teams. Thus TMT composition and processes are likely to represent the

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firm’s most valuable resources. In Italian SMEs, however, families are the mostimportant shareholders. Precise data are lacking but according to a recent survey bythe Italian Central Bank (Banca d’Italia, 2008), families own around 64 per cent of largequoted firms with estimates of much higher percentage for SMEs. Families typicallymaintain control of firms not only through ownership but also by appointingexecutives on the basis of family connections (Enriques and Volpin, 2007). However, ifmanagers are mainly selected on the basis of such connections rather than on the basisof their proven experience and knowledge, exporting performance may be impaired.This selection bias tends to limit the access of these firms to the specific resourcesand capabilities that professional managers have and that are needed for theinternationalization process. Fernandez and Nieto (2006), for example, discovered anegative relationship between family ownership and export intensity with a sampleof Spanish SMEs. George et al. (2005) found in a Swedish sample that internallyappointed CEOs and senior executives tend to be more risk-averse than their externalequivalents, and hence tend to reduce the scale and scope of SME internationalization.

In contrast, the involvement of non-family managers has also been identified in theliterature as having a positive influence on performance (Kor and Misangyi, 2008;Kor and Sundaramurthy, 2009; McConaughy, 2000) in that such involvement mayprovide the firm with crucial managerial competencies. These competenciescan take the form of both knowledge about foreign markets, international legitimacyand reputation, and of a global network of external ties that promoteinternationalization (Zou and Stan, 1998). Gomez-Mejia et al. (2010), for example,show that family firms wanting to diversify internationally are forced to hirenon-family specialists that have specific knowledge of international markets. Reuberand Fischer (1997) showed that experienced TMTs represent a resource that has amajor part in the degree of internationalization of SMEs. Exporting of course requiresthe development of external and international ties, and Barney et al. (2003) showthat family ties hamper a firm’s ability to develop other cross-border ties. In the case ofItalian SMEs, it is well established that, besides the employment of non-familyexecutives in TMTs, firms may also have access to exporting knowledge from theircontacts within their industrial agglomerations (or “districts”), see H3. Indeed,non-family executives and location in industrial districts may be alternative(i.e. substitute) sources of different types exporting knowledge, e.g. concerningregional or global export markets.

At this stage, however, we postpone any further consideration of this possibility of asubstitution effect until empirical testing and propose that any role for non-familymanagers should be valid universally, i.e. for exporting success on both regional andglobal markets, since external managers with the necessary knowledge of regionaland global markets should be available, at a price, on the executive labourmarket. Previous studies have underlined the importance of specialists to successfullymanage foreign activities (George et al., 2005; Katsikeas et al., 2000), and wetherefore propose that:

H2. There will be a positive association between the hiring of non-family managersand exporting to (a) regional and (b) global markets.

One of the main criticisms aimed at the RBV of the firm is its main strength: the theoryis inward-looking (Priem and Butler, 2001). However, the fact that the RBV focuses onthe internal characteristics of the firm does not imply a lack of regard for its external

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environment as a valid source of additional resources available on strategic factormarkets (Maritan and Peteraf, 2011). Leveraging external assets into markets throughexternal linkages and networking activities does not shift the attention away from aninternal view of the firm (Chetty and Wilson, 2003); it rather completes the missingparts of the firm’s value chain, making access to market-based assets an importantcomplementary part of the RBV (Srivastava et al., 1998). Different authors havegenerally recognized the firm’s ability to leverage heterogeneous external resources asan important intangible asset to overcome limitations occurring in the SME’sinternationalization process (Bell et al., 2003).

Newbert (2007) refers to this ability as (p. 124) “webs of relationships” that favour thecoordination and deployment of resources. Previous studies (Smallbone et al., 1993;Storey, 1994) showed that there is a strong correlation between a firm’s home locationand its growth. In the context of resource acquisition, Kraaijenbrink et al. (2010) raise theissue that resources may be shared by more than one firm rather than owned exclusively.In particular, they note that business knowledge need not be deployed in a rivalrousmanner, and (p. 362) “[y] its deployment by one firm, or for one purpose, does notprevent its redeployment by the same or another firm or for another purpose”. It followsthat the spatial proximity of firms may be considered to be very important inencouraging unprogrammed dialogues between firms and knowledge exchange.Kraaijenbrink et al. (2010) conclude that (p. 363), “[y] cooperation and codevelopmentmay prove to be effective ways of obtaining strategically significant knowledge”.

Abstract notions of knowledge externalities and networks with other managers, firmsand institutions correspond neatly with the unique empirical reality of Italian industrialdistricts, and we consider their “combinative” attributes. In the case of Italian industrialclusters (or districts), firms from the same industry located in the same area fiercelycompete on international markets but, at the same time, collaborate on local projectsfostering learning and innovation (Majocchi and Presutti, 2009). This process is enhancedby the existence of a rooted local culture with specific norms, values and institutions thatpromote the transfer of tacit forms of knowledge between co-localized partners (Porter,1998; Enright, 1998). Italian firms located in agglomerated industrial districts thus benefitfrom a complex system of interrelations that help them overcome the resource limitationsof SMEs that urgently seek international growth (Le Gales et al., 2001).

A large number of studies (Gordon and McCann, 2005; Malmberg and Maskell,1999) have argued and empirically tested the claim that SMEs localized inside anindustrial district benefit from this location. These studies have shown that SMEconcentration promotes knowledge exchanges, as localization within industrialdistricts facilitates information contacts and the exchange of tacit knowledge.At the same time, fierce competition within the district among local competitorsstimulates new experiments and combinations of knowledge, promoting furtherinnovation. With specific reference to knowledge regarding export markets Becchettiand Rossi (2000) found evidence that external economies in the provision of exportservices, and exchanges of information about foreign markets, have a positive effect onthe probability that small industrial district firms will start to export and increase theiraccess to overseas markets.

Of course a reliance on exporting knowledge available within local industrialdistricts may generate a narrower spread of exporting information than hiring from (intheory) an infinitely wide executive labour market. However, external, professionalmanagers are a rarity in Italian firms, and only around 1 per cent of SMEs in our largesample had managers hired externally. It follows that most of the benefits accruing to

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an SME from location in agglomerations must follow from relationships betweenfamily managers within one firm and family managers within another nearby, and itmay be expected that such network contacts may breed more parochial attitudesto strategy than the more outward-looking appointment of external managers.We tentatively hypothesize, therefore:

H3. There will be a positive association between location in an industrial districtand exporting to (a) regional but not (b) global markets.

The RBV argues that a superior stock of resources and the effective orchestration ofsuch resources (Sirmon et al., 2011) over time should allow the firm to deal moreconfidently with the uncertainties of internationalization (Westhead et al., 2001). Inother words, as firms grow older, they acquire resources over time and buildcapabilities and positional advantage, and the costs of engaging in internationalbusiness operations should be mitigated by this accumulation process. This importantstrand of the literature emphasizes experience-based organizational learning(Belderbos, 2003) and incrementalism in exporting success associated with theUppsala School ( Johanson and Vahlne, 2009). This theoretical view, stressingthe importance of a firm’s experience to international performance, found empiricalsupport in previous exporting studies that reported a positive and robust relationshipbetween a firm’s age and export performance (Brouthers and Nakos, 2005; Majocchiet al., 2005). However, as firms age, structural inertia and “competency traps” (Cohenand Levinthal, 1990) may develop, representing constraints, and also organizationalroutines that are difficult to change or unlearn. In exporting studies, this concept wasa feature in early work by Kirpalani and McIntosh (1980) who found a negativerelationship between a firm’s age and exporting. Other studies also reported aninsignificant relationship between age and export performance (Andersson et al., 2004)or only a limited explanatory power (Zou and Stan, 1998; Baldauf et al., 2000).

Exporting may be affected by the incremental accumulation over time of theresources and capabilities necessary to face foreign market uncertainty (e.g. Johansonand Vahlne, 1977). Alternatively, exporting success may be determined by the“learning advantage of newness” (Autio et al., 2000). This is a much debated issue ininternational business and entrepreneurship studies that juxtapose the traditionalinternationalization for SMEs and born-global pathways (Kuivalainen et al., 2007;Saarenketo et al., 2004). Thus, the relationship between a firm’s experience andexporting is very complex and leads us to adopt an agnostic position on therelationship between an SME’s age and export performance. Such agnosticism makesit difficult to derive hypotheses unambiguously in relation to the age of firms.We tentatively propose, therefore, that we would expect that older firms with greatermarket experience will also show higher levels of exporting, but if this hypothesis isrefuted, there is no shortage of potential explanations:

H4. There will be a positive association between the firm’s experience andexporting to (a) regional and (b) global markets.

Data and methodologyThe data setThe data used in this paper come from the ninth wave of a “Survey on ManufacturingFirms” conducted in Italy by the research department of Capitalia (now Unicredit), a

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large Italian bank. The data are based on responses to questionnaires sent out every threeyears by the bank to its clients. Responses were provided by human resource managers.These responses were matched with firms’ financial statement data which were filed withthe bank. The joint use of each source of information (i.e. financial statement and surveys)represents a form of triangulation (Canibano et al., 2000). This database has already beenused by several scholars to research managerial (Cerrato, 2009; D’Angelo, 2012) andeconomic (Hall et al., 2009 inter alia) topics. According to the Survey of ManufacturingEnterprises, the sample collates 3,452 observations and represents 11.3 per cent of totalmanufacturing industry in Italy. Within this data set, we focused on SMEs, whichrepresent nearly 80 per cent of the whole sample, and we imposed two employee numberthresholds, (410 and o250) and a total turnover threshold (o50 million euro) proposedby the European Commission (2003). Data cleansing operations involved dropping certainobservations where responses were both incomplete and non-recoverable. As a result, thefinal working sample consisted of 2,657 Italian manufacturing SMEs. Within this sample,1,846 firms were exporters to EU countries (522 just in the EU and 1,324 both in theEU and outside) and 811 were non-exporters; for markets beyond the EU, 1,433were exporters (109 firms only outside the EU and not within the region) and 1,224non-exporters (see Table II). Out of 1,846 firms 702 did not report any kind of export.

The variablesAccording to Sullivan (1994), internationalization is a multi-faceted concept and thereis no consensus in the literature on how to measure export performance. For example,Katsikeas et al. (2000) distinguished between economic and non-economic measures.Zucchella et al. (2007) described export performance on the basis of three indicators,namely, the speed of entry into a foreign market, the geographic scope of exportingactivities and the level of export intensity (measured as the ratio of export sales to totalsales). While this first indicator addresses INVs or born global studies (Moen, 2002;Oviatt and McDougall, 1994), the literature has mainly employed the other twoindicators to measure the degree of export internationalization in SMEs (Pangarkar,2008). The number of markets to which SMEs actively export is a measure of the scopeor breadth of foreign involvement (Lu and Beamish, 2001) and it gives an idea of thekind of geographic coverage attained by exporting SMEs. However, it does notconsider the level of performance achieved. In contrast, export intensity (i.e. the export-to-sales ratio), the most common measure of performance in empirical research(Katsikeas et al., 2000; Leonidou and Katsikeas, 1996; Majocchi et al., 2005; Sousa et al.,2008 inter alia), offers a precise measurement of the ability of firms to enter and succeedin foreign markets. However, it treats all foreign markets indiscriminately.

Following Leonidou et al. (2010) who suggested the measurement of exportperformance with composite indices, we modified export intensity by incorporating thegeographic scope of foreign activities and the relative distribution of sales (Katsikeaset al., 2000; Pangarkar, 2008). Exploiting the distinction of Rugman and Verbeke (2004),our dependent variable measures the ratio of export sales (i.e. sales outside the domesticmarket) from both inside (exp intEU27 ) and outside the EU (exp outEU27 ) to the totallevel of sales. The first variable gauges regional export performance, whereas the secondis a measure of the export performance achieved in global markets.

Our independent variables consist of a series of measures that build on our RBV,and aim to describe the key distinctive resources that influence export performance interms of product innovation, external managerial resources, industrial district location,together with the knowledge and competencies associated with a firm’s age.

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Corporate innovation embraces a firm’s products, processes and structures, is anotoriously complex process, and a variety of measures are available. Due to theunreliable nature of R&D expenditure as a measure of SMEs innovation (Hoffmanet al., 1998), innovation was measured with a dummy variable that took the value of 1when firms reported some kind of product innovation and 0 if they reported none(Prod_inn) (Brouwer and Kleinknecht, 1996; De Jong and Vermeulen, 2006).

Following Chua et al. (2003), we considered the ratio of external managers to thetotal number of employees (Ext manag) to measure the managerial characteristicsof the firms. We think that this variable is appropriate to measure the presence ofspecialist executives in a setting where most firms are family owned. In other words,this measure gauges the presence of managers who are apparently independent of thegoverning family (Enriques and Volpin, 2007).

Italian “industrial districts” represent unique agglomerations of related industriesthat have received significant levels of state encouragement and sponsorship overdecades (Majocchi and Presutti, 2009) and industrial districts in general have beenwidely recognized in the literature as powerful engines of export promotion (Fernhaberet al., 2008). We refer to industrial districts as territorial agglomeration of people, firmsand institutions where positive externalities from physical proximity are likely toemerge (Enright, 1998; Malmberg and Maskell, 1999) and propose a dummy variable(District) with unit value when SMEs were located in an industrial district, definedaccording to whether the firm’s main location was within or outside one of theindustrial districts defined by the Italian authority for National Statistics. In oursample 1,230 firms (46 per cent of the sample) were located in an industrial district.

Finally, as a measure of the firm’s experience we simply observed the number ofyears since foundation (Age).

Additionally, standard measures were inserted as controls (Katsikeas et al., 2000).Using Pavitt’s (1984) well-known classification, we defined SME sector-specificdummy variables. Using the most traditional sector, i.e. the supplier-dominated group,as the reference value, we defined the following three dummies: Sector spec forspecialized-suppliers, Sector HT for science-based industries and Sector scale forscale-intensive industries. Given the well documented role of geography in promotinginternationalization (Dunning, 1997), we also defined the geographic location of theSMEs and thus distinguished between the North-West (North-West), the Centre(Centre), the South (South) and the two main Italian islands of Sardinia and Sicily(Island). The North East part of Italy was taken as the reference. Previous literature(Fernhaber and Li, 2010) has shown that larger firms typically have greater resourcesand that this might influence their ability to internationalize. Following previous workon the determinants of export performance (Dhanaraj and Beamish, 2003; Majocchiet al., 2005), we chose the log value of the total number of firms’ employees as a proxyfor the firm’s size (Size). The technological competence of the firms was measured bythe ratio of R&D employees to the total number of employees (R&D empl).

The descriptive statistics for our variables are reported in Table I, together witha correlation matrix. The low value of the interrelationships among the predictorvariables suggests that multi-collinearity is not a concern.

The methodOur dependent variables are percentages (percentages of export to both regional andglobal markets over total sales), whose values range from 0 to 100 per cent. Since eachdependent variable is censored with high percentages (30.5 per cent for regional and

89

Geographicalpathways

46.0 per cent for global markets) comprising lower limits, we adopted the Tobitregression methodology (Bowen and Wiersema, 2004; Greene, 2002; Nassimbeni, 2001)in order to take these limits into account. Due to the possibly endogenous nature of ourindependent variables, which might cause potential correlation between the regressorsand the error terms, which in turn would render our estimates biased and inconsistent(Spanos et al., 2004), we relied on the use of three years’ lagged rather thancontemporaneous independent variables. This strategy not only improves econometricmethodology by avoiding potential endogeneity problems, but also follows aneconomic logic, since we can assume that exports are typically the consequences ofactions taken in previous years. Using the procedures with the Intercooled-STATA 9.2statistical package, we ran Tobit maximum likelihood estimates on the two differentmeasures of export performance. However, in a censored regression, the conditionalmean of the dependent variable is a non-linear function of the regression. Therefore,the estimated coefficients do not measure the effects of a change in the independentvariables on the dependent variables. This limitation is not a problem if the hypothesestest only the sign of the effects (Bowen and Wiersema, 2004). However, the ideathat operating in global markets differs from regional markets, led us to computemarginal effects. Marginal effects are the effects on the conditional mean of thedependent variable of changes in the regressors. These results allow us to measurethe relative effects of the different explanatory variables on both regional andglobal export performance.

ResultsTable II reports the results of the Tobit estimates, while the values of the marginaleffects for the more general model (Model 5) are reported in Table III. We initiallyconsidered a model that only included control variables. Subsequently, we specifiedfour additional models that included the independent variables that allow us to test ourhypotheses. w2-statistics indicate good model significance for each model comparedwith the simple model, which does not include all explanatory variables (Bowen andWiersema, 2004). Regression coefficients are quite constant across the various models,suggesting stability.

The first model includes only the control variables, i.e. industry dummies, regionallocation, size and R&D employees. Industry dummies and geographic location aregenerally significant for regional and global export intensity, and thus confirm theirexplanatory power as reported in previous studies (Dunning, 1997; Leonidou andKatsikeas, 1996). Firm size is strongly positive and significant across all models and

Average SD Size Age R&D empl Ext manag

Exp intEU27 17.84 21.17Exp extEU27 10.88 18.24Size 3.70 0.755 1Age 27.61 17.85 0.144*** 1R&D empl 0.006 0.20 0.015* 0.003 1Ext manag 0.011 0.025 0.071*** �0.011 0.093*** 1

Notes: aCorrelations between continuous variables were conducted applying Pearson’s coefficients.The low value of interrelationships suggested no problem with multi-collinearity (results are availableon request). *po0.1; **po0.05; ***po0.01

Table I.Descriptive statisticsand correlationsa

90

IMR30,2

Mod

el1

Mod

el2

Mod

el3

Mod

el4

Mod

el5

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Con

stan

t�

24.1

77**

*�

33.4

60**

*�

24.0

89**

*�

33.4

58**

*�

24.0

92**

*�

33.4

07**

*�

25.7

10**

*�

33.2

72**

*�

24.6

73**

*�

33.7

51**

*

(2.9

42)

(3.2

41)

(2.9

26)

(3.2

32)

(2.2

97)

(3.2

28)

(3.0

21)

(3.3

19)

(3.0

52)

(3.3

60)

Sec

tor

scale

�6.

485*

**�

9.79

0***

�6.

527*

**�

9.93

7***

�6.

531*

**�

9.96

2***

�6.

377*

**�

9.97

7***

�6.

513*

**�

9.91

4***

(1.5

56)

(1.7

44)

(1.5

48)

(1.7

43)

(1.5

49)

(1.7

40)

(1.5

49)

(1.7

42)

(1.1

54)

(1.7

43)

Sec

tor

spec

4.89

4***

11.4

49**

*3.

938*

**10

.442

***

3.88

5***

10.1

05**

*3.

895*

**10

.105

***

3.67

7***

10.2

10**

*

(1.2

87)

(1.3

66)

(1.2

88)

(1.3

69)

(1.2

93)

(1.3

72)

(1.2

92)

(1.3

72)

(1.2

94)

(1.3

77)

Sec

tor

HT

�8.

397*

*�

5.56

3�

2.27

1**

�6.

770

�9.

373*

*�

7.50

0*�

8.97

5***

�7.

534*

*�

9.12

2***

�7.

462*

*

(3.3

97)

(3.6

62)

(3.3

81)

(3.6

64)

(3.3

90)

(3.6

70)

(3.3

92)

(3.6

76)

(3.3

88)

(3.6

67)

Nor

th-W

est

1.79

1*1.

906

1.76

5*1.

906

1.73

5*1.

697

1.94

8*1.

678

2.35

5*1.

483

(1.3

09)

(1.4

10)

(1.3

02)

(1.4

06)

(1.3

04)

(1.4

06)

(1.3

07)

(1.4

10)

(1.3

18)

(1.4

26)

Cen

tre

�1.

026

3.98

2**

�0.

841

4.23

5**

�0.

844

4.20

4**

�0.

336

4.16

2**

�0.

511

4.22

7**

(1.5

86)

(1.7

09)

(1.5

77)

(1.7

04)

(1.5

77)

(1.7

02)

(1.5

91)

(1.7

18)

(1.5

90)

(1.7

19)

Sou

th�

5.66

0***

�2.

541

�5.

422*

**�

2.29

7�

5.43

7***

�2.

403

�4.

173*

*�

2.51

1�

4.51

2**

�2.

345

(1.9

35)

(2.1

17)

(1.9

25)

(2.1

13)

(1.9

26)

(2.1

11)

(2.0

09)

(2.1

99)

(2.0

12)

(2.2

06)

Isla

nds

�13

.660

***

�1.

216

�13

.225

***

�0.

4950

�13

.264

***

�0.

705

�11

.743

***

�0.

834

�11

.637

***

�0.

889

(3.3

09)

(3.4

88)

(3.2

92)

(3.4

71)

(3.2

94)

(3.4

67)

(3.3

63)

(3.5

45)

(3.3

57)

(3.5

46)

Siz

e9.

502*

**7.

957*

**8.

869*

**7.

273*

**8.

850*

**7.

135*

**8.

865*

**7.

134*

**9.

094*

**7.

026*

**

(0.7

23)

(0.7

81)

(0.7

25)

(0.7

84)

(0.7

26)

(0.7

84)

(0.7

26)

(0.7

84)

(0.7

33)

(0.7

92)

R&

Dem

pl47

.317

***

48.3

44**

*33

.658

***

33.7

96**

*33

.392

***

31.9

91**

*33

.141

***

32.0

16**

*33

.066

***

32.0

56**

*

(7.6

89)

(8.1

02)

(7.9

45)

(8.3

97)

(7.9

71)

(8.4

08)

(7.9

66)

(8.4

09)

(7.9

53)

(8.4

09)

Pro

d_in

n7.

255*

*7.

841*

**7.

268*

*7.

925*

**7.

260*

**7.

928*

**7.

228*

**7.

932*

**

(1.1

59)

(1.2

48)

(1.1

60)

(1.2

46)

(1.1

58)

(1.2

46)

(1.1

57)

(1.2

46)

Ext

manag

9.00

961

.552

***

11.2

2161

.344

***

9.70

562

.024

***

(21.

279)

(22.

572)

(21.

291)

(22.

603)

(21.

275)

(22.

611)

Dis

tric

t2.

515*

*�

0.21

62.

463*

*-

0.19

5

(1.1

46)

(1.2

35)

(1.1

44)

(1.2

36)

(con

tinu

ed)

Table II.The output of Tobit

regressions for exportperformance within and

outside the Europeanregional market

91

Geographicalpathways

Mod

el1

Mod

el2

Mod

el3

Mod

el4

Mod

el5

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Exp

intE

U27

Exp

extE

U27

Age

�0.

065*

*0.

030

(0.0

30)

(0.0

33)

Lef

t-ce

ns

obs

811

1,22

481

11,

224

811

1,22

481

11,

224

811

1,22

4

Unce

ns.

obs

1,84

61,

433

1,84

61,

433

1,84

61,

433

1,84

61,

433

1,84

61,

433

LRw2

(9)¼

337.

99

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

9,30

9.77

Pse

ud

o

R2¼

0.09

35

LRw2

(9)¼

334.

89

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

7,53

5.41

Pse

ud

o

R2¼

0.08

15

LRw2

(10)¼

377.

07

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

9,29

0.23

Pse

ud

o

R2¼

0.10

27

LRw2

(10)¼

374.

59

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

7,51

5.56

Pse

ud

o

R2¼

0.08

64

LRw2

(11)¼

377.

25

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

9,29

0.14

Pse

ud

o

R2¼

0.10

28

LRw2

(11)¼

381.

97

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

7,51

1.87

Pse

ud

o

R2¼

0.08

84

LRw2

(12)¼

382.

06

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

9,28

7.74

Pse

ud

o

R2¼

0.10

36

LRw2

(12)¼

382.

00

Pro

b4w2¼

0.00

Log

lik

elih

ood

¼�

7,51

1.86

Pse

ud

o

R2¼

0.08

85

LRw2

(13)¼

386.

64

Pro

b4w2

¼0.

00

Log

lik

elih

ood

¼�

9,28

5.44

Pse

ud

o

R2¼

0.10

61

LRw2

(13)¼

382.

88

Pro

b4w2

¼0.

00

Log

lik

elih

ood

¼�

7,51

1.42

Pse

ud

o

R2¼

0.08

86

Note

:*po

0.1;

**po

0.05

;**

*po

0.01

Table II.

92

IMR30,2

re-emphasizes the positive relationship between firm size and export intensity(Dhanaraj and Beamish, 2003; Fernhaber and Li, 2010; Verwaal and Donkers, 2002inter alia). Finally, the significant and positive value of the coefficient on the ratio ofR&D employees suggests that human resources employed in innovative processes arealso an important competitive variable for exporting SMEs, regardless of thegeographical destination of exports. This result is interesting because it confirms theappropriateness of using the R&D employees to total employees (R&D empl) as ameasure of in-house R&D activities in smaller firms (Hoffman et al., 1998) and possiblyfacilitating the absorption of knowledge external to the firm (Cohen and Levinthal,1990) as encountered in international market operations.

In Model 2 we tested the impact of product innovation on regional and globalexporting. Results show that product innovation had a positive regional and globalimpact, confirming earlier results (Cassiman and Golovko, 2011; Roper and Love, 2002;Wakelin, 1998). The results of Table III show that the marginal effects on regional andglobal export performance are consistent, positive and similar for both variables. OurH1 assuming a positive relationship between product innovation and exporting inregional and global markets is thus confirmed.

For our Ext manag variable, the coefficient for the regional performance variable isnot significant, while the coefficient of the global variable is positive and highlysignificant (Model 3). Moreover, the marginal effect of external executive recruitmenton global export performance is large and significant (Table III). Since our datavalidate the strongly positive effect of Ext manag on global export performance, wecan only partially confirm H2. However, we can propose that the drivers of regionaland global export performance are different.

The positive and significant value of the coefficient for regional exports in Model 4confirms that being located in an industrial district has a positive impact on regionalexport performance, but this effect is not significant for global exports. H3 is, therefore,confirmed, and it highlights, once again, that the drivers of export success in SMEs aredifferent when considering the geographical dimension of the two international pathways.Together with the positive impact on global exporting of outside executive recruitment(i.e. partial support for H2), it may be argued that a reliance on exporting knowledgeobtained from a local industrial district (i.e. partial support for H3) may generate anarrower (regional) spread of exporting information than hiring from a wide andknowledge-rich executive labour market. In this sense, the two explanatory variables areseen to have a complementary, rather than a substitute, relationship.

Finally, in Model 5 we insert the variable relating to the age of the firm. Thisvariable shows a coefficient which is negative and significant with regard to regional,EU-bound exporting, and demonstrates that younger firms in our sample export more

Model 5Exp intEU27 Exp extEU27

Prod_inn 3.485*** 2.932***Ext manag 4.607 22.515***District 1.171** �0.0709Age �0.031** 0.0112

Notes: aME for conditional mean specification E (y|x, y40); ME is for discrete changes in the dummyvariable from 0 to 1. *po0.1; **po0.05; ***po0.01

Table III.Marginal effects (MEs)

for explanatory variablesa

93

Geographicalpathways

extensively to European markets. This result contradicts H4, which predicted thatolder firms should show higher levels of exports and does not support the presence of“born globalness” in our sample of SMEs, i.e. firms which start operating globally fromtheir inception or early years (Moen, 2002; Oviatt and McDougall, 1994). On thecontrary, we find that a “born regional” strategy seems to prevail in younger firms(Lopez et al., 2009).

DiscussionBuilding on the RBV, we consider the possibility that the influences of a specific firm’skey resources on export performance vary when regional and global exports aredistinguished. This is arguably because international operations impose differentuncertainties on firms, which in turn require different kinds of resources and levels ofspecialized knowledge. Overall, our research shows that while some resources influenceexport performance regardless of the geographical scale of their foreign activities, othersare specific to the regional or global scope of exports. With regard to the specifichypotheses tested in this paper, we found that product innovation (e.g. De Jong andVermeulen, 2006) represents an important variable in explaining universal exportperformance in both closer and distant markets. This emphasizes that innovating SMEsare able to sustain competitiveness in international markets (Pangarkar, 2008), andsuggests that, in order to compensate for the additional hurdles to exporting, SMEsshould be able to generate sales effectively on the back of innovation.

This, in turn demands international knowledge and skills from managers (e.g.Stoian et al., 2010). Special attention has been devoted by the SME literature to the roleof external managers, i.e. professionals engaged on the basis of their experience andnetworks, not belonging to the family that owns the business. External managers canbe considered as a gateway to the knowledge and to the system of ties needed toovercome the liability of outsidership ( Johanson and Vahlne, 2009). Their role seemsparticularly relevant and significant when a firm enters global markets. The presenceof specialist executives to manage international operations in the distant and morecomplicated markets that lie beyond the regional market seems to be crucial (Buckleyand Ghauri, 1999). This is understandable given the fact that within the regionalmarket (Europe, in our case) the degree of homogeneity may be greater in terms of acommon currency, cultures, markets and institutions, etc.

In Italy, SMEs have traditionally relied on family members to fill managerialpositions and may have accessed the needed competencies by relying on theknowledge available in the local industrial district (export consortia, enterprisesassociations, etc.). According to our findings, being located in such a district supportsregional export performance, but has no significant influence on global export sales,only on regional exports (Sorenson et al., 2006). These findings contribute to the recentdebate on the role of industrial districts in particular, and of geographical location ingeneral, in the promotion of export activities. Pla-Barber and Puig (2009) for exampleconclude that the role of industrial districts in promoting export activities is stillimportant, but that this role is decreasing as industries become more globalized.Our results support this conclusion and show how the kind of knowledge sharedwithin industrial districts serves regional but not global exporting. Researchershave emphasized that the importance of location within a district can also depend onthe nature and the kind of the knowledge exchanged (Davenport, 2005; Sorensonet al., 2006). When such knowledge is highly specific, which is the case of companiesseeking to enter distant and complex markets, the beneficial effect of being part of an

94

IMR30,2

industrial district can be minimal or, according to some authors (Gordon and McCann,2005) even detrimental.

Finally, we consider the effect of a firm’s age as a proxy for its experience. The roleof time is considered crucial to building internal knowledge resources throughexperiential learning processes which are often seen to determine the speed, scope andmode of international growth ( Johanson and Vahlne, 1977). The impact of a firm’s ageon regional exporting is found to be significant but negative, but is insignificant inrelation to global exporting. These results contribute to the “born global” debate,suggesting that younger firms tend to export significantly more regionally but notglobally. This finding concurs with other recent findings (Lopez et al., 2009).

Our analysis also shows interesting results for the control variables weinvestigated. Size – a frequently used proxy for the overall resources of a firm – anda firm’s technological competences (R&D empl ) – are confirmed to be significantdrivers of all export performance. The dominant emerging pattern is one in whichthose SMEs with greater size and R&D competencies are likely to perform better on allexport markets.

Conclusions and limitationsRecent research has pointed out that most firms are engaged in international activitieswithin their regional markets (Rugman and Verbeke, 2004, 2007; Rugman et al., 2009inter alia). This may be the consequence of regional integration policies aimed atcreating “intra-regional” integrated economic platforms. Since the Second World War,various geographic areas have experienced a process of gradual regional integration(Europe with the EU, North America with NAFTA and southeast Asia countries withASEAN). This process has been particularly pronounced in Europe, where a commonmarket, common institutions and a single currency have been developed over the last50 years. This has in turn developed a favorable environment and an ongoing processof SME intra-regional internationalization. For many firms, EU-27 is graduallyevolving into their domestic market (Veron, 2006). In contrast, many SMEs are stillprevented from exporting outside their regional market because they perceive that inorder to face a more unfamiliar environment they need to bridge a bigger resources gap(Zucchella et al., 2010). For these reasons, a regional economy such as the EU’s that islargely dominated by SMEs constitutes an important arena within which to analyseand compare regional and global pathways to internationalization.

In terms of theoretical contribution, such a focus on SMEs in a volatile exportingenvironment provides a strong test of the RBV, yet our study has added its conclusionsto the accumulated 98 per cent of tests of the RBV that have confirmed the validity ofits logic (Newbert, 2007). Moreover, our study responds to the appeal to expose theRBV to different contexts (Barney et al., 2011) besides the large MNEs that have beenthe focus of most of the exporting literature (e.g. Bernard and Jensen, 2004).Our findings emphasize the liability of inter-regional foreignness (Rugman andVerbeke, 2007) for SMEs and the validity of an RBV approach as an appropriateframework with which to analyse SME export performance and its determinants.They also reveal that the determinants of export performance differ according towhether exports follow regional or global pathways to internationalization.

Our results have several important implications for entrepreneurs, policy makersand export scholars. First and foremost, resources and capabilities matter. Investmentin product innovation (De Jong and Vermeulen, 2006) is important for SME exports(Basile, 2001; Cassiman and Golovko, 2011; Wakelin, 1998 inter alia) in both regional

95

Geographicalpathways

and global markets, and the ability to generate high volumes of export sales fromproduct innovation is essential to recoup R&D investments and to sustaincompetitiveness in international markets (Pangarkar, 2008). Moreover, the hiring ofspecialist non-family executives is important for the management of the liability offoreignness in distant international markets (Buckley and Ghauri, 1999; Johanson andVahlne, 2009). The RBV argues that a superior stock of resources and the effectiveorchestration of such resources (Sirmon et al., 2011) over time should allow the firmto face foreign market uncertainties more confidently (Westhead et al., 2001). Ourevidence shows that the incremental accumulation over time of resources andcapabilities (e.g. Johanson and Vahlne, 1977) does not necessarily guarantee success onregional or global export markets. However, the effect of the “learning advantage ofnewness” (Autio et al., 2000) also seems to be limited within to regional exporting only.This finding supports Zou and Stan’s (1998) view that a firm’s age, expressed asnumber of years in business, has only limited power in explaining export intensity.This may be due to the different knowledge acquisition and learning practicesoccurring within SMEs, which may idiosyncratically affect their internationalizationpathways (De Clercq et al., 2012; Madsen and Servais, 1997; Saarenketo et al., 2004).The apparent impact of the firm’s age as a proxy for the firm’s experience mayreflect this limitation.

Important implications for policy makers can also be derived from this research.The importance of industrial districts as contributors to the development andcompetitiveness of SME internationalization has increasingly gained policy makers’attention (UNIDO, 2003). Such districts have been identified as focal institutions forsharing resources and integrating export marketing activities in a collaborative modethat enables partners to develop their international activity more effectively. However,our results advise caution: industry clustering provides the resources that are usefulfor internationalization up to a point (growth in regional markets), but it is not effectivein the case of global markets. From a policy perspective, our evidence alsosuggests that SMEs with greater size and R&D competencies may perform better oninternational markets (both regional and global). Since R&D employees are associatedwith firm size (Table I), we share Mancinelli and Mazzanti’s (2009) view favouringfiscal and innovation policies that promote firms’ R&D and enlargement throughmerger and acquisitions, even among SMEs.

Last but not least, this study provides export scholars with a more specificdefinition of export performance, one that considers regional vs global exports.The politico-economical policies of regional integration that have marked the last50 years cannot be neglected when studying export performance and its maindeterminants. Numerous earlier studies have considered export intensity as a viablemeasure of export performance without specifying whether exports were regional orglobal. However, without this specification of the internationalization pathways, thefindings of studies on export performance and its main determinants risk beingheavily dependent on the distribution of export sales in the samples used.

This study would not be complete without reference to its limitations. First, ourresults refer to a specific area, i.e. Italy within the EU market, and to a specific period,so that the usual problem of generalization across time and space arises. Second,our data do not allow us to discriminate between firms on the basis of the kindsof strategy followed. For example, it may well be that significant differences in exportperformance could also be the effects of differences in SME industrial affiliation. SMEsthat are concentrated in more narrowly defined industries may try to compensate for

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the thinness of the segment with a broader geographic scope. Third, our analysislacked the data specificity that would have allowed us to discriminate betweendiffering types of industrial districts, such as fast growing and declining ones. Studies(Pouder and StJohn, 1996; Fernhaber et al., 2008) have shown that the differingcharacteristics of districts could promote or hamper performance, and this is certainlyan issue that deserves future research. Fourth, it may be important in future to analysepotentially important interactions between resources, e.g. innovation and therecruitment of external managers, that may moderate relationships between variables.

Despite these limitations, we suggest that our findings offer a new perspective onthe analysis of export performance and its determinants, and we look to futureresearch for the empirical validation and elaboration of our main findings in a varietyof geographical and institutional contexts.

AcknowledgementsThe authors gratefully acknowledge comments from the anonymous reviewers and theIMR Special Issue editorial team, particularly Olli Kuivalainen, for providing helpfulfeedback. The authors also acknowledge comments from the audiences at the AdamSmith Business School (University of Glasgow), the AIB-UKI Conference 2011(University of Edinburgh), and the McGill International Entrepreneurship Conference2012 (Universita degli Studi di Pavia) on earlier versions of this paper. The authorswish to thank Antonio Riti and the research department at Capitalia (now Unicredit)for the provision of the firm-level data set used in this paper. Antonio Majocchigratefully acknowledges financial support from Cariplo Foundation InternationalRecruitment Call: The Internationalization of Italian Firms: The Role of Intangibles,Managerial Resources, and Corporate Governance. Alfredo D’Angelo gratefullyacknowledges financial support from Adam Smith Research Foundation SeedcornFunds (Project Code 20646), University of Glasgow.

Note

1. The questions reported here are extracted from the ninth wave of a “Survey onManufacturing Firms” conducted in Italy by the research department of Capitalia (nowUnicredit). For more information contact: Antonio Riti, UniCredit S.p.a. Largo Fochetti 16 –00154 ROMA. Ph. þ 39 06 54454599; Faxþ 39 06 54454737; e-mail: antonio.riti@unicredit.it

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Appendix. The questionnaire[1]Section A: General Information

(1) Year of establishment of the company

(2) Main activity of the company

(3) Geographic location of the company

. North West

. North East

. Centre

. South and Islands

(4) Is the company a member of an industrial district?

Section B: Labour Force

(1) Numbers of total employees in the last three financial years

(2) How many of them are:

. Family managers

. Non-family managers

(3) How many employees did take part to R&D activities in the last three complete financialyears

Section C: Investment, Technological Innovation, and Research and Development

. Has the company realized product innovations during the last three complete financial years?

. How much has the company spent on R&D in the last three complete financial years?

Section D: Internationalization

(1) Has the company exported in the last compete financial year?

(2) What proportion of total turnover was exported in the last complete financial year?

(3) What proportion of export sales was destined for:

. EU(15)

. The 10 new EU entrants since 2004

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. Russia, Turkey and other European countries

. Africa

. Asia (excluding China)

. China

. United States, Canada and Mexico

. Central and South America

. Australia and Oceania

About the authors

Alfredo D’Angelo is Lecturer in International Business at Adam Smith Business School,University of Glasgow (UK). He obtained his PhD from the Universita degli Studi di Pavia (Italy).His research interests are focussed in the areas of entrepreneurship, innovation andinternationalization of SMEs. His work has been published in the Industry and Innovation,

Journal of Business Economics and Management, Journal of Management and Governance,

Journal of Small Business and Enterprise Development and other international journals. AlfredoD’Angelo is the corresponding author and can be contacted at: alfredo.d’angelo@glasgow.ac.uk

Antonio Majocchi is Associate Professor in International Business at the Department ofEconomics and Management, Universita degli Studi di Pavia (Italy). His main research interestsfocus on SMEs’ internationalization, the relationship between corporate governance andinternationalization and MNCs location strategies. His publications have appeared in theInternational Business Review, Management International Review, International Small Business

Journal, Journal of Small Business Management and other international journals.Antonella Zucchella is Professor in Marketing and International Entrepreneurship at the

Department of Economics and Management, Universita degli Studi di Pavia (Italy). She holdsvisiting positions at Universite Robert Schuman in Strasbourg, IECS and Universite Lyon 3 inLyon. Her research interests are in the field of international marketing and internationalentrepreneurship. Her work has been published in the Journal of Institutional Economics, Journal

of World Business, International Business Review, International Small Business Journal, Journal

of Management and Governance and other international journals.Trevor Buck is Research Professor in International Business and Business Policy at Adam

Smith Business School, University of Glasgow (UK). He has worked as Lecturer/Professor atuniversities in Belfast, Nottingham, Perth (Australia), Leicester and Loughborough. He haspublished widely in leading management journals including the Journal of International

Business Studies, Entrepreneurship Theory and Practice, International Journal of Human

Resource Management, Management International Review, International Business Review andother international journals.

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