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European Planning Studies

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Bridging the gap: citizenship diversity and globalinnovation networks in small and medium sizecompanies

Markus Grillitsch & Cristina Chaminade

To cite this article: Markus Grillitsch & Cristina Chaminade (2018) Bridging the gap: citizenshipdiversity and global innovation networks in small and medium size companies, European PlanningStudies, 26:12, 2279-2303, DOI: 10.1080/09654313.2018.1520812

To link to this article: https://doi.org/10.1080/09654313.2018.1520812

© 2018 The Author(s). Published by InformaUK Limited, trading as Taylor & FrancisGroup

Published online: 21 Sep 2018.

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Bridging the gap: citizenship diversity and global innovationnetworks in small and medium size companiesMarkus Grillitsch a and Cristina Chaminade b

aDepartment of Human Geography & Circle, Lund University, Lund, Sweden; bDepartment of EconomicHistory, Lund University, Lund, Sweden

ABSTRACTRecent literature stresses the increasing importance of globalinnovation networks (GINs) as a mechanism to organizeinnovation across geographical space. This paper investigates whyand to what extent citizenship diversity of the firm´s employeesrelates to the engagement of small and medium size companiesin GINs. Citizenship diversity provides knowledge about theinstitutional context of other countries, increased capabilities todeal with institutional differences, larger social networks to buildGINs and a broader search space. Further, the paper examineshow the absorptive capacity of firms mediates the relationshipbetween citizenship diversity and GINs. The empirical study isbased on a linked employee-employer dataset with 6,771observations of innovative small and medium size firms inSweden. It provides strong evidence that the engagement in GINsis positively related to citizenship diversity, depending, however,on the absorptive capacity of firms.

ARTICLE HISTORYReceived 18 August 2017Revised 14 August 2018Accepted 30 August 2018

KEYWORDSGlobal innovation networks;citizenship diversity;absorptive capacity; openinnovation; institutions

1. Introduction

The new global innovation landscape characterized by increased technological complexity,open models of innovation and modularization together with the upgrading of technologi-cal capabilities in middle income countries has dramatically altered the geography of inno-vation (Cano-Kollmann, Hannigan, & Mudambi, 2018). The globalization ofmanufacturing and production that spurred the studies on global production networksin the early 2000’s (Coe et al., 2004; Henderson, Dicken, Hess, Coe, & Yeung, 2002) isnow being followed by a wave of globalization of innovation activities that builds uponcomplex networks of actors pinned down to specific locations all over the world. Thisnew –networked- configuration of innovation activities at a global scale – which someauthors refer to as global innovation networks (GINs) – is increasingly calling the atten-tion of scholars in the intersect between economic geography, international business andinnovation studies (Barnard & Chaminade, 2017; Cano-Kollmann et al., 2018; Cooke,2013a, 2013b; Cooke & Kemeny, 2017; Degelsegger-Marquez, Remøe, & Trienes, 2018;

© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis GroupThis is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License(http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in anymedium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

CONTACT Markus Grillitsch markus.grillitsch@keg.lu.se Department of Human Geography & Circle, Lund Uni-versity, Lund, Sweden

EUROPEAN PLANNING STUDIES2018, VOL. 26, NO. 12, 2279–2303https://doi.org/10.1080/09654313.2018.1520812

Martin, Aslesen, Grillitsch, & Herstad, 2018; Mudambi et al., 2018; Shakirov, 2017; Silva &Klagge, 2013). By bringing insights from the three disciplines scholars are trying to under-stand how innovation processes are organized at a global scale, who the main actors anddrivers are and what the impact of these global networks for innovation is, both for com-panies and regions in both the developed and developing world.

Global innovation and knowledge networks are an important factor for regional devel-opment. Most contemporary studies have acknowledged that global innovation andknowledge networks contribute to path development in different regional innovationsystems (Aslesen, Hydle, & Wallevik, 2017; Isaksen & Trippl, 2016; Martin et al., 2018;Trippl, Grillitsch, & Isaksen, 2017). GINs are considered to be crucial particularly for per-ipheral regions with limited local knowledge resources (Grillitsch & Nilsson, 2015; Tripplet al., 2017) and in institutionally and organizationally thin regional innovation systems(Chaminade & Plechero, 2015). GINs can play an important role as a complementaryor compensatory mechanism to local or regional knowledge linkages (Fitjar & Rodrí-guez-Pose, 2013; Grillitsch & Nilsson, 2015; Mudambi et al., 2018). Furthermore, thereis growing amount of evidence on the role of the geography of networks on the degreeof novelty of innovations which suggests that local and regional linkages are associatedwith incremental innovation while global linkages tend to lead to more radical inno-vations. The underlying rationale is that local and regional networks tend to provideaccess to similar knowledge (Asheim & Isaksen, 1997; Visser & Boschma, 2004) whileGINs enable the firm to tap into new pools of knowledge (Herstad, Aslesen, & Ebersberger,2014; Laursen & Salter, 2006; Plechero & Chaminade, 2016). It follows from this line ofargument that GINs are desirable if the aim is to achieve innovations with higherdegrees of novelty.

Given the potential role of GINs for regional development, it is critical to understand thefactors that enable or constrain companies and other organizations located in a particularregion to engage in GINs. From existing evidence we know that firm-specific characteristicssuch as the level of education of the workforce, research and development activities, exports,foreign ownership or size are positively related to the propensity of firms to engage in GINs(Ebersberger & Herstad, 2013). However, with the sole exception of Solheim and Fitjar(2018) the issue of diversity of the labour force in terms of country of origin has beenwidely neglected as a factor influencing the propensity of firms to engage in GINs1,2.

We argue that institutional barriers between national boundaries are a specific and fun-damental challenge for firms’ engagement in GINs and that citizenship diversity can allevi-ate this challenge through several causal mechanisms, namely by providing knowledgeabout the institutional context of the migrants’ home countries, by enhancing firms’ capa-bilities to cope with institutional differences (Grillitsch, 2015), a broadened search space offirms (Ebersberger, Herstad, Iversen, Kirner, & Som, 2011; Laursen, 2012; Østergaard, Tim-mermans, & Kristinsson, 2011) as well as social networks to individuals and organizationslocated in other countries (Agrawal, Cockburn, & McHale, 2006; Saxenian & Sabel, 2008).

We test the proposition that firms with a diverse labour force, captured by the citizen-ship of the employees, engage more in GINs on a representative sample of 6,771 obser-vations of innovative small and medium size firms generated from merging four wavesof the Community Innovation Survey (CIS) in Sweden. The CIS provide informationabout the spatial configuration of firms’ innovation networks as well as numerouscontrol variables. This data is merged with linked employer-employee data provided by

2280 M. GRILLITSCH AND C. CHAMINADE

the Statistical Office of Sweden (SCB) in order to measure diversity of the labour force.Instead of treating international linkages as a black box, this paper investigates theimpact of diversity on innovation networks within Sweden, within Europe, outsideEurope and global (networks with partners in all geographical areas) thus truly investi-gating GINs.

In this paper we focus on small and medium size companies (SMEs) for several reasons.First, small and medium size innovation performance is considered to be paramount forthe dynamics of regions (Kemeny, 2011). Second, in line with the extensive literature onborn globals (Knight & Cavusgil, 2004), there is growing evidence of the capacity of smallfirms to engage in GINs (Barnard & Chaminade, 2017) as well as their positive effect onthe degree of novelty (Aslesen & Harirchi, 2015). However, most of the existing literatureon the drivers of engagement in GINs tend to focus on large multinational companies. Candiversity of the employees in terms of citizenship support SMEs in their efforts to engagein global networks to innovate?

The paper proceeds as follows: Section 2 elaborates on the concept of firm-level citizen-ship diversity, and in particular why and how citizenship diversity contributes to theengagement of firms in GINs. Section 3 presents the empirical strategy followed by a dis-cussion of the results in section 4. Section 5 concludes the paper.

2. Diversity and its effect on GINs

2.1. Citizenship diversity, firm performance and innovation

The role of diversity of the labour force on firm performance has long been discussed inmanagement studies (Horwitz, 2005), but it has only recently been used in connection toinnovation performance (Østergaard et al., 2011; Solheim & Fitjar, 2018). Existing empiri-cal evidence suggests that the impact of diversity on the general performance of the firm ishighly contingent on the type of diversity. Ruef, Aldrich, and Carter (2003) distinguishbetween ascribed and achieved attributes of diversity; the ascribed attributes are relatedto demographic characteristics such as gender, age, ethnicity and nationality, while theacquired attributes are mostly related to education, experience or job function. The laterare also referred to in the literature as job-related attributes. Generally speaking, job-related attributes of diversity, like educational background and functional backgroundare positively related to firm performance3 while the impact of other diversity attributeslike gender, race or citizenship are often associated with conflicts and thus negativefirm performance (Bell et al., 2010; Horwitz, 2005; Pelled, 1996) although the resultsare highly contingent of the group in which the analysis is performed (Shore et al.,2009). The negative impact of ascribed diversity on performance is generally explainedin terms of conflicts, miscommunication and lack of trust of the different group orteam members (Horwitz, 2005; Shore et al., 2009). Of all demographic traits of diversity,ethnicity has been identified as the one with potential to affect firm performance positivelyby bridging the knowledge gap with potential markets (Cox & Blake, 1991; cf Horwitz,2005). For instance, Cooke and Kemeny (2017) and Kemeny and Cooke (2018) findthat diversity of the workforce in terms of migrant origin is positively related to higherproductivity, particularly in jobs that require complex-problem solving and are of highrelational nature, thus suggesting a possible link between diversity and innovation.

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The relationship between innovation and diversity has been far less studied. Simonenand McCann (2008) provide evidence of a positive relationship between recruitment oflabour from other regions and product and process innovations. Lee and Nathan(2010) find that workforce and ownership diversity contributes to product and processinnovations. The study by Nathan and Lee (2013) reports a small but significant positiveeffect of diversity on firm innovation and surprisingly the effect is stronger for less knowl-edge-intensive sectors. Kerr (2013) provides evidence for the US on how diversity of theworkforce enabled by migration is positively related to innovation and entrepreneurshipin organizations.

Interestingly, some of the attributes, which are considered to affect general firm per-formance negatively, are found to be positively related to innovation. Ozgen, Nijkamp,and Poot (2013) show that diversity of foreign nationalities contributes to firm innovative-ness. In a similar vein, Parrotta, Pozzoli, and Pytlikova (2014) find that ethnic diversity ispositively related to firms’ patenting behaviour. Østergaard et al. (2011) find a positiverelation between diversity in education years, education background and gender withinnovation and a negative relation between diversity in age and innovation, while theresults for ethnicity are not significant. The authors hypothesize that the diversity of theworkforce is positively related to innovation if it helps the firm to tap into and combinedifferent forms of knowledge needed to innovate thus pointing out to the role of inno-vation networks as a liaison between diversity and innovation. Analogously, Fey and Bir-kinshaw (2005) found that partnerships, particularly with university, are positively relatedto R&D performance. However, such relationship is strongly mediated by the ‘openess tonew ideas’ of the company.

2.2. Citizenship diversity and global innovation networks

The main aim of this section is to carve out why citizenship diversity of the firm affectsengagement in GINs positively. We do this firstly by identifying the challenges forfirms’ engagement in GINs, and secondly by developing the argument why and how citi-zenship diversity contributes to alleviating these challenges. GINs are understood as theglobally organized web of collaborative interactions between different organizations(firms and/or non-firm organizations) engaged in knowledge production that is relatedto and resulting in innovation. Thus, a defining feature of GINs is that it concerns activitiescrossing national boundaries and on a global scale (Parrilli, Nadvi, & Yeung, 2013). Thisimplies that firms have to overcome institutional barriers in the form of differences in lawsand regulations such as intellectual property rights, business law, labour law, and environ-mental regulations; differences in how the legal system works; as well as more informalaspects such as divergent norms, values, believes and how to interact with business part-ners. Recent studies show that managing the complexity of different institutional contextsis one of the most important barriers for firms as regards their participation in GINs andthat consequently the ability to cope with different institutional environments should bepositively related with the propensity of firms to engage in internationalization of pro-duction and innovation activities (Alvandi, Chaminade, & Lv, 2014; Dachs et al., 2012;Hsu, Lien, & Chen, 2015).

We argue below that citizenship diversity of the workforce helps firms to overcomeinstitutional barriers erected between nation states through the following mechanisms:

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i) the provision of knowledge about the institutional context in other countries, ii) theincreased capabilities to deal with institutional differences, iii) social network effects,and iv) a broader search space.

First, migrant workers who had exposure to their home country, for instance whengrowing-up, working or interacting with family and friends, will have some knowledgeabout the institutional context of their home country. This may put such migrants in anadvantageous position to deal with the legal and regulatory environment in their homecountry. Furthermore, familiarity with the socio-cultural context facilitates knowledgeexchange and interactive learning (Boschma, 2005). In other words, less is lost in translation.

Second, citizenship diversity may also increase the capability of firms to cope withdifferent contexts beyond the migrants’ home countries. One reason is that integratingindividuals with divergent institutional heritage is a social learning process of how to com-municate and interact without misunderstandings, how to build relationships and trust,and how to exchange knowledge despite institutional differences. This learning processpotentially builds the capabilities of individuals and firms to overcome institutional bar-riers that exist with collaboration partners in different parts of the world. This is importantnot only for establishing global networks but also in making them a successful learningexperience contributing to the innovation performance of firms. This resonates wellwith empirical evidence showing that the impact of internationalization on firm´s pro-ductivity is highly influenced by previous international experience, particularly inter-national breath – that is the number of countries in which the firm operates (Kafouros,Buckley, & Clegg, 2012). However, too much diversity in the networks might alsoimpact negatively the performance of the firm insomuch as network complexity increases(Bahlmann, 2014). Another reason is related to the fact that migrants, particularly researchmigrants, are likely to collaborate with individuals from their home country, even whenthose are located in third countries (Scellato, Franzoni, & Stephan, 2015). In thisrespect, citizenship diversity might help the establishment of collaborations for innovationnot only in the home country but also worldwide.

Third, citizenship diversity goes hand in hand with a greater breath of social networks,on which a firm can draw for engaging in GINs. The relevance of social networks in thisregard is justified by i) the higher likelihood of establishing social networks in close geo-graphic proximity and ii) the durability of social networks over time even if individualschange locations. Social networks are often forged when individuals interact face-to-face, at for instance university, their workplace or where they live. In this regard, it hasbeen shown that regional labour mobility is an important factor explaining local knowl-edge spillovers (Breschi & Lissoni, 2009) and that firms dominantly recruit regionally inorder to source knowledge (Grillitsch, Tödtling, & Höglinger, 2015; Plum & Hassink,2013). Geographic proximity can thus be seen as intermediary factor that increases thelikelihood that people meet, interact, and build social relationships, even though not allindividuals and firms in a given location are equally engaged in local networking orhave equal access to networks (Giuliani, 2007; Morrison, 2008).

While co-location increases the propensity to build social networks, they are main-tained when people move to other places (Agrawal et al., 2006; Saxenian & Sabel, 2008;Trippl, 2013). Social networks facilitate the exchange of information and interactive learn-ing as well as reduce the likelihood of opportunistic behaviour (Granovetter, 1985, 2005).Thus social networks contribute to overcoming geographic distance and institutional

EUROPEAN PLANNING STUDIES 2283

barriers. This implies that the social networks that individuals have built over time wherethey grew up, lived and worked can potentially be activated in order to facilitate theengagement of firms in GINs (Crescenzi, Nathan, & Rodríguez-Pose, 2016). As regardsGINs, it can thus be expected that the social networks of migrants to their homecountry are an important factor strengthening a firm’s ability to engage and draw valuefrom GINs (Oettl & Agrawal, 2008).

Forth, citizenship diversity and the related social networks translate into a broaderinformation and knowledge search space of firms (Laursen, 2012; Østergaard et al.,2011). A wide search space in the context of GINs means that firms are able to drawon reliable information about potential collaboration partners for their innovation activi-ties in different parts of the world. The wide search space may be attributed to migrants’knowledge of relevant organizations in their home country, their ability to gather suchknowledge through social networks, and their understanding of social and institutionalparticularities.

In sum, we have carved out four mechanisms through which citizenship diversity of theworkforce facilitates firms’ engagement in GINs, relating to the direct benefit of under-standing the institutional environment of the migrants’ home country, the indirectbenefit of developing firm capabilities to deal with institutional differences, socialnetwork effects, and a broader search space. As discussed, these mechanisms directlyaddress some of the key complexities and challenges of firms’ engagement in GINs,which is why we consider that citizenship diversity is a causal driver for GINs. Hence,our first hypothesis is:

Hypothesis 1: Firms with a high degree of citizenship diversity have a higher likelihood toparticipate in global innovation networks.

2.3. Citizenship diversity, absorptive capacity and GINs

So far, we discussed why citizenship diversity at the level of the firm should be positivelyrelated to the likelihood that firms engage in GINs. However, does this apply to all firmsequally? There are important reasons to assume that the effect of firm-level citizenshipdiversity on the engagement in GINs is mediated by a number of factors related to theabsorptive capacity of the firm (Cohen & Levinthal, 1990; Zahra & George, 2002), particu-larly the educational level of the workforce. Fitjar and Rodríguez-Pose (2014) find thateducation increases the likelihood of Norwegian firms to establish international collabor-ation linkages at the expense of local links. Furthermore, Solheim and Fitjar (2018) arguethat citizenship may be related to performance and the propensity of firms to collaborateinternationally to the extent to which they are highly educated or hold higher positions inthe company.

GINs are characterized by high complexity, partly due to the need of dealing withdifferent institutional contexts. Furthermore, the purpose of establishing innovation net-works is to engage in learning processes, which largely depends on the capacity of firms toidentify relevant knowledge and appropriate it for innovations. Lacking absorptivecapacity, it will be difficult for firms to establish and draw benefits from GINs. Hence,firm-level citizenship diversity is expected to be largely ineffective for firms with lowlevels of absorptive capacity. In contrast, for firms with high levels of absorptive capacity,

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we expect a strong relationship between GINs and firm-level citizenship diversity. Hence,our second hypothesis is the following:

Hypothesis 2: The relationship between citizenship diversity and firms’ participation inglobal innovation networks is stronger for firms with a high absorptive capacity.

3. Empirical strategy

3.1. Data sources

The study uses data provided by the Statistical Office of Sweden (SCB) comprising theCommunity Innovation Survey (CIS), longitudinal individual registry data, business reg-istry data, firm and establishment dynamic data and business statistics data. The CIS is alarge-scale European survey that captures innovation activities and innovation networksof firms. The methodology for the CIS has been developed by Eurostat and implementedby the national statistical offices of the participating countries. The CIS is conducted intwo-year intervals and for the purpose of increasing representativeness we merge fourwaves covering the periods 2004–2006, 2006–2008, 2008-2010, and 2010–2012. In theanalysis, we include only firms with less than 250 employees (small- and medium-sizedenterprises) because the link between diversity and international engagement is moredifficult to establish for large firms with potentially many establishments abroad andthe possibility and need to recruit international staff to cover foreign markets. The longi-tudinal individual registry includes among others data on individuals’ occupations, edu-cation, citizenship, and respective employers for each individual registered in Swedenand aged above 16 years. The individual registry data is measured each year on the 31st

of December except for some variables like employment for which the measurement isundertaken in November. In order to account for this, the analysis is performed on indi-vidual data one year before each CIS period. For instance, individual registry data for 2003is used in combination with the CIS wave covering the period from 2004 to 2006. As thedatabase includes all individuals registered in Sweden, important characteristics of theworkforce of Swedish firms can be represented. In particular, it constitutes a highly reliablesource for measuring citizenship diversity as well as human capital within a firm. Thebusiness registry data, firm establishment and dynamics data and business statisticsdata are used to construct the control variables as further explained below.

3.2. Dependent variable

The dependent variable captures whether a firm had innovation collaborations in differentworld regions during the specific period of each CIS wave. The following world regions arecovered in the CIS: Sweden, Europe, USA, China, India, and Others. This allows us todefine different scales of innovation collaborations:

Swedeni,t = 1 if firm i had innovation collaborations in Sweden in time period t, otherwise 0

Europei,t = 1 if firm i had innovation collaborations in Europe (excluding Sweden) in timeperiod t, otherwise 0

Outside Europei,t = 1 if firm i had innovation collaborations in USA, China, India or others intime period t, otherwise 0

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Globali,t = 1 if firm i had innovation collaborations in all world regions in time period t,otherwise 0

where, time period t corresponds to the respective CIS wave. The variable of main interestis Globali,t., which is compared to networks at other spatial scales in order to carve out theparticularity of GINs.

3.3. Independent variables

The operationalization of diversity depends on the conceptual idea this construct rep-resents. Harrison and Klein (2007) distinguish between diversity understood as separation,variety or disparity. Separation aims to capture differences in position or opinion betweengroup members that potentially reduce cohesiveness and introduces conflict. Variety con-ceptualizes diversity in a positive manner as complementary types of knowledge or experi-ence. Disparity concerns differences in the share held by individual agents in sociallyvalued assets such as income, power, or status. In the context of this paper, citizenshipdiversity is conceptualized as a proxy for variety in social networks, knowledge aboutdifferent institutional contexts and search spaces, which facilitate the engagement offirms in GINs. Hence, the Blau index, a typical and frequently used operationalizationof diversity, is used to operationalize citizenship diversity:

CitizenshipDiversity = 1−∑K

k=1

p2k (1)

where p denotes the share of highly qualified individuals belonging to citizenship groupsk = 1,… , K in the total of highly qualified staff of a firm.

Highly qualified individuals refer to those who are in a position to influence innovationnetworks. They are identified using occupational data available in the longitudinal individ-ual register. The Swedish classification of occupations SSYK 96 follows the InternationalStandard Classification of Occupations ISCO-88 and orders occupations in a hierarchicalframework. It captures the ‘set of tasks or duties designed to be executed by one person’,‘the degree of complexity of constituent tasks’, and ‘the field of knowledge required forcompetent performance of the constituent tasks’ (Statistical Office of Sweden, 1998,p. 17). SSYK classifies occupations in 10 major groups out of which group one (managers),two (professionals) and three (technicians and associate professionals) contain occu-pations that are very relevant in innovation processes and require high skill levels. Indi-viduals classified in one of these three groups are thus identified as highly qualified.Occupational data has important advantages over educational data because it capturesthe actual work individuals are performing at present while educational data may referto qualifications that were required long time back or that are not utilized in the activitiesand tasks of an employee. The citizenship groups provided by the longitudinal individualregistry comprise: Sweden, Nordic countries (but Sweden), Europe (but Nordic countries),Africa, North America, South America, Asia, and other.

In hypothesis 2 we test whether the relationship between the engagement in GINs andcitizenship diversity is mediated by the absorptive capacity of a firm. The notion of absorp-tive capacity stipulates that firm-internal knowledge and skills are a precondition forappropriating and using new knowledge acquired through innovation networks

2286 M. GRILLITSCH AND C. CHAMINADE

(Cohen & Levinthal, 1990; Zahra & George, 2002). Accordingly, the absorptive capacity iscaptured by the qualification of the human capital of a firm measured as the share ofhighly qualified staff in the total staff of a firm based on occupational data as described above.

The measurement and data source of all control variables used in the study aredescribed in Table 1 and Annex 1 reports descriptive statistics.

3.4. Identification strategy

Data on innovation networks is per definition only available for firms that are innovationactive, thus potentially causing a selection bias (Heckman, 1979). Consequently, aHeckman selection model is applied similar to other studies using CIS data (Ebersberger& Herstad, 2012; Frenz & Ietto-Gillies, 2009; Herstad et al., 2014; Lööf & Heshmati, 2002)with the following selection model:

innovation active = a+ b firm+ dmetropolitan+ g industry + l time+ 1 (2)

The dependent variable captures firms that are active in innovation and is a function offirm characteristics (firm), effects of location in a metropolitan area (metropolitan),industry effects (industry), time effects (time) and random errors (ε) with ɛ ∼ N(0,1).As regards firm characteristics, the selection equation includes human capital,foreign sales, size, the capacity to finance innovations and whether the firm is new.The latter two variables are relevant to explain whether a firm is innovation activebut have no theoretical or statistical relationship with the likelihood that firmsengage in GINs. The function is estimated with a probit regression applying standarderrors clustered at the level of the firm in order to adjust them for repeated obser-vations. The coefficients of the selection equation are presented in Table 2. As expected

Table 1. Description of control variables.Control Variable: Measurement: Data source:

Human Capital Share of individuals that are classified in the major occupationalgroup 1 ‘managers’,), 2 (professionals) and 3 (technicians andassociate professionals) in total workforce

Longitudinal individualregistry data

New Firm Firm registered within three years before the respective CISwave

Firm and establishmentdynamic data

Financial capacity Cash flow in million SEK per total assets Business statistics dataIntramural R&D Expenditures for intramural R&D in million SEK per employee,

cubic root transformedCIS/Longitudinalindividual registry data

International networkswithin the group

Dummy variable: 1 for firms that have innovation collaborationsabroad with firms of the same corporate group.

CIS

Foreign Owner Dummy variable: 1 for firms that have a foreign owner; 0 forother firms

CIS

Foreign Sales Dummy variable: 1 for firms that have sold products abroad; 0 forother firms

CIS

Size Natural logarithm of the number of employees of each firm Longitudinal individualregistry data

Metropolitan Area Dummy variable: 1 for firms with headquarters in Stockholm,Gothenburg or Malmö; 0 for other firms

Business registry

Industry Categorical variable grouping firms in 7 industries based on twodigit NACE codes: Mining and utilities (05–10 & 35–41),manufacturing (10–35), whole sales (45–49), transportation(49–55), information and communication (58–64), financialand insurance (64–68), professional, scientific, technicalactivities (68–77).

CIS

Time Dummies for the respective CIS waves CIS

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the qualification of the human capital, foreign sales and firm size are positively relatedto the probability that firms are innovative. Also, firms with a strong financial capacityand firms that have been established within three years before the respective CIS waveare more likely to be innovative. Somewhat surprising is the negative effect of beinglocated in a metropolitan area, suggesting that negative agglomeration economies out-weigh positive ones. A potential interpretation is that one of the main effects of metro-politan areas, namely access to a thick labour market, may be absorbed in the humancapital indicator at the level of the firm.

The inverse Mills ratio (imr) is calculated from the above probit regression:

imr = e−0.5y2

����2p

√F(y)

(3)

where y stands for the linear predictors of the selection function. The inverse Mills ratio isincluded as one of the explanatory variables in the outcome model, which is used to testhypothesis 1:

Global = a+ w diversity + b firm+ dmetropolitan+ z imr+ g industry

+ l time+ 1 (4)

The outcome model explains the engagement of firms in GINs (global) as a function ofcitizenship diversity (diversity), a set of firm characteristics (firm), the effect oflocation in a metropolitan area (metropolitan), the inverse Mills ratio (imr), industrycharacteristics (industry), time effects (time) and random errors (ε) with ɛ ∼ N(0,1).The firm characteristics include human capital, intramural R&D, international net-works within the corporate group, foreign ownership, foreign sales, and size. The

Table 2. Probit Regression on the selection equation.Innovation active

Human Capital 0.7451***(0.0494)

Foreign Sales 0.5101***(0.0269)

Size 0.1456***(0.0124)

Financial Capacity 0.9668***(0.1584)

New Firm 0.0522*(0.0316)

Metropolitan Area −0.1182***(0.0341)

Constant −0.7745***(0.0470)

Industry Dummies YesTime Dummies YesObservations 14035Pseudo R2 0.083AIC 17863.1BIC 17976.3Log Likelihood Fitted −8916.5Likelihood Ratio Chi2 1196.3***

Note: Presented coefficients and standard errors clustered at the level of the firmin brackets; ***, **, and * indicate significance at the 1, 5, and 10% level.

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outcome model is estimated applying probit regression and standard errors clusteredat the level of the firm.

In order to investigate whether the effect of citizenship diversity is mediated by the levelof human capital (human_capital) an interaction variable between the two variables isintroduced in the outcome equation:

Global = a+ w1diversity + w2diversity∗human capital+ b firm

+ dmetropolitan+ z imr+ g industry + l time+ 1 (5)

The main interest of the interaction model is to identify the relationship between citizen-ship diversity and the engagement of firms in GINs conditional to the level of humancapital. It is not uncommon that the average marginal effect of a variable at certainlevels of the specified condition is significant although the interaction term itself isinsignificant, which is why the average marginal effects are reported (Brambor, Clark, &Golder, 2006).

4. Results

Table 3 presents basic distributional statistics. The total sample comprises 14,035 obser-vations out of which approximately half are from innovative firms. Out of the observationsfor innovative firms 37% have networks with Swedish partners, 25% with partners inEurope but outside Sweden, 15% with partners located outside Europe, and 4% aretruly global with networks in all world regions covered by this study. Overall the employ-ment of non-Swedish staff is rather common among innovative firms. It turns out to bemost likely (55%) for firms that maintain GINs compared to 31%, 38%, and 44% forfirms with network partners in Sweden, Europe, and outside Europe respectively.However, the share of non-Swedish staff tends to be rather low and ranges between2.89% for firms with innovation networks in Sweden and 4.50% for firms with GINs.The mean number of unique citizenship groups in a firm ranges between 1.4 and 1.9for firms with Swedish and GINs respectively. The measure for citizenship diversity

Table 3. Sample characteristics.

Number of observations

Total Innovative Firms14035 6771

Innovation networks in

Sweden Europe Outside Europe Global

Number of observations 2532 1660 966 267Share of innovative firms 37.39% 24.52% 14.27% 3.94%Firms with non-Swedish employeesNumber of observations 794 624 426 146Share 31.36% 37.59% 44.10% 54.68%Share of non-Swedish employeesMean 2.89% 3.47% 3.85% 4.50%Standard deviation 0.0758 0.0834 0.0772 0.0674Number of unique citizenship groupsMean 1.424 1.531 1.684 1.914Standard deviation 0.843 0.901 1.017 1.088Citizenship diversityMean 0.0453 0.0541 0.0635 0.0782Standard deviation 0.0910 0.0987 0.1026 0.1041

EUROPEAN PLANNING STUDIES 2289

takes the lowest value for firms with networks in Sweden (0.0453) and turns out highest forfirms with GINs (0.0782). Hence, the descriptive statistics provide an indication for a posi-tive relationship between citizenship diversity and GINs. However, the results also indicatethat this relationship may hold more generally for international innovation networks.

Before moving to the main focus of this paper, the identification of relationshipsbetween citizenship diversity and firms’ engagement in GINs, we confirm in Table 4that innovation networks indeed contribute to the innovativeness of firms. As informationon innovation networks is only collected for firms that have declared to be innovative, it isnot possible to use non-innovative firms as counterfactual. Hence, we investigate whetherinnovation networks make it more likely that firms have introduced innovations that arenew to the world, which is the most radical form of innovation about which the CIS pro-vides information. We introduce innovation networks at the four spatial scales investi-gated in the study and find indeed that all of them are positively and highlysignificantly correlated with the likelihood that firms introduce innovations new to themarket.

Table 5 tests the hypothesis that firms with a high degree of citizenship diversityhave a higher likelihood to participate in GINs. It shows models without (Models

Table 4. Probit regression: innovation networks on introduction of innovations new to the market.(1) (2) (3) (4)

Innovation networksSweden 0.3152***

(0.0353)Europe 0.2774***

(0.0400)Outside Europe 0.2991***

(0.0490)Global 0.2691***

(0.0894)Human Capital 0.3982

(0.3427)0.3428(0.3494)

0.2932(0.3393)

0.3628(0.3478)

Intramural R&D 0.5827***(0.0821)

0.5974***(0.0823)

0.6126***(0.0838)

0.6612***(0.0844)

Foreign Owner 0.0317(0.0447)

0.0130(0.0446)

0.0227(0.0446)

0.0173(0.0446)

Foreign Sales 0.1784(0.2420)

0.1247(0.2468)

0.1080(0.2394)

0.1484(0.2454)

Size 0.0278(0.0645)

0.0218(0.0657)

0.0193(0.0637)

0.0316(0.0654)

Metropolitan Area −0.0249(0.0673)

−0.0215(0.0682)

−0.0194(0.0668)

−0.0261(0.0678)

Mill’s Ratio 0.0621(0.7223)

−0.0489(0.7368)

−0.1265(0.7127)

−0.0451(0.7327)

Constant −0.6020(0.9303)

−0.3987(0.9489)

−0.2784(0.9185)

−0.4176(0.9440)

Industry Dummies Yes Yes Yes YesTime Dummies Yes Yes Yes YesObservations 6771 6771 6771 6771Pseudo R2 0.070 0.066 0.065 0.062AIC 8751.1 87867.0 8800.1 8828.0BIC 8867.0 8902.9 8916.0 8944.0Log Likelihood Fitted −4358.5 −4376.5 −4383.0 −4397.0Likelihood Ratio Chi2 501.8*** 453.2*** 426.2*** 399.5***

Note: Presented are the coefficients and standard errors clustered at the level of the firm in brackets; ***, **, and * indicatesignificance at the 1, 5, and 10% level.

2290 M. GRILLITSCH AND C. CHAMINADE

Table 5. Probit regression: citizenship diversity on innovation networks at different spatial scales.(1) Sweden (2) Europe (3) Outside Europe (4) Global (5) Sweden (6) Europe (7) Outside Europe (8) Global

Citizenship Diversity 0.1239(0.2063)

0.4143**(0.2099)

0.5073**(0.2271)

0.8896***(0.3198)

0.2958(0.2208)

0.4019*(0.2223)

0.1617(0.2480)

0.9430***(0.3184)

Intra-firm networks in:Sweden 2.1909***

(0.0710)Europe 1.8715***

(0.0687)Outside Europe 1.6055***

(0.0785)Global 1.2926***

(0.1323)Human Capital 0.1663

(0.2985)0.7304*(0.3840)

1.8124***(0.5123)

2.5614***(0.7404)

0.6256**(0.2854)

0.9724**(0.4188)

1.5314***(0.5270)

2.7022***(0.7545)

Intramural R&D 1.0009***(0.0770)

0.9938***(0.0805)

0.9838***(0.0763)

0.7974***(0.0788)

0.8477***(0.0802)

0.8042***(0.0953)

0.7945***(0.0809)

0.6841***(0.0899)

Foreign Owner −0.1348***(0.0464)

0.0381(0.0493)

−0.0897(0.0575)

−0.0188(0.0766)

−0.0106(0.0497)

−0.4275***(0.0589)

−0.3272***(0.0684)

−0.0414(0.0801)

Foreign Sales 0.0429(0.2098)

0.6697**(0.2756)

1.1994***(0.3793)

2.1582***(0.5852)

0.4377**(0.2012)

0.8301***(0.2980)

1.0290***(0.3897)

2.4615***(0.5981)

Size 0.1496***(0.0564)

0.2487***(0.0729)

0.3734***(0.0978)

0.6338***(0.1457)

0.1773***(0.0537)

0.2231***(0.0786)

0.2807***(0.1003)

0.6284***(0.1492)

Metropolitan Area −0.0361(0.0638)

−0.0601(0.0756)

−0.1158(0.0953)

−0.1591(0.1406)

−0.1220*(0.0654)

−0.1356*(0.0817)

−0.0624(0.0997)

−0.2126(0.1430)

Mill’s Ratio −0.1686(0.6292)

0.7303(0.8394)

2.2730*(1.1639)

4.6674***(1.7682)

0.8519(0.5939)

1.2809(0.8982)

1.7870(1.1880)

5.2495***(1.7883)

Constant −0.9661(0.8070)

−3.0217***(1.0664)

−5.8194***(1.4719)

−9.5990***(2.2268)

−2.2916***(0.7625)

−3.5783***(1.1490)

−5.0651***(1.5062)

−10.2703***(2.2655)

Industry Dummies Yes Yes Yes Yes Yes Yes Yes YesTime Dummies Yes Yes Yes Yes Yes Yes Yes YesObservations 6771 6771 6771 6771 6771 6771 6771 6771Pseudo R2 0.076 0.120 0.166 0.184 0.270 0.255 0.258 0.233AIC 8302.2 6673.9 4661.6 1870.9 6573.8 5654.7 4155.1 1760.6BIC 8418.1 6789.8 4777.6 1986.9 6696.6 5777.5 4277.9 1883.4Log Likelihood Fitted −4134.1 −3319.9 −2313.8 −918.5 −3268.9 −2809.4 −2059.5 −862.3Likelihood Ratio Chi2 413.2*** 532.4*** 603.4*** 325.3*** 1133.9*** 1105.3*** 900.2*** 375.8***

Note: Presented are the coefficients and standard errors clustered at the level of the firm in brackets; ***, **, and * indicate significance at the 1, 5, and 10% level.

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1–4) and with the inclusion of inter-firm networks (Models 5–8). The reason forshowing these separately is that a high international engagement of firms can bethe cause for high citizenship diversity. We take necessary precautions to controlfor this in the regressions through the following variables: foreign sales, foreign own-ership, and most importantly intra-firm innovation networks. Neglecting intra-firminnovation networks, citizenship diversity is positively related to innovation collabor-ations at all investigated spatial scales (Models 1–4). However, if we include intra-firmnetworks, citizenship diversity only remains highly significant and positive for GINs(Model 8). Conversely, intra-firm networks are strongly related to innovationnetwork with external partners at all geographical scales.

The control variables exercise highly significant effects on innovation networks.There are three variables where the coefficient is substantial higher for GINs thanfor other spatial scales: human capital, firm size, and foreign sales. The first two vari-ables are close proxies for the absorptive capacity of firms and therefore this pattern isnot surprising as an increasing level of global engagement also increases complexitydue to the need to coordinate a large number of units embedded in different insti-tutional environments. Foreign sales is one of the mechanisms (besides citizenshipdiversity, global intra-firm collaboration, and foreign ownership) that can facilitateGINs by enlarging networks abroad, enhancing the search space for partners, andincreasing capability to deal with institutional differences. However, foreign owner-ship, which has also been identified as a proxy for international engagement, is sur-prisingly not positively related to GINs and is even negatively correlated withnetworks at the European scale and outside Europe. This indicates that foreign own-ership rather aims at capturing knowledge in Sweden than facilitating the capturing ofknowledge of Swedish firms abroad. It is worth looking into this more deeply becausethe implication would be that foreign investments trigger larger knowledge out- thaninflows and thereby endanger Swedish competitiveness. Location in a metropolitanarea does not positively affect engagement in GINs, which is in line with recentempirical studies (Chaminade & Plechero, 2015; Grillitsch & Nilsson, 2015; Tödtling,Grillitsch, & Höglinger, 2012).

In order to interpret these results, Table 6 as well as Figures 1 and 2 present the like-lihood to engage in GINs conditional to certain levels of citizenship diversity and con-ditional to whether the firm has global intra-firm networks or not. The chosen levels of

Table 6. Likelihood to engage in GINs conditional to fixing citizenship diversity and intra-firm networksat the indicated levels.

(1) (2) @ intra-firm networks = 0 (3) @ intra-firm networks = 1

@Citizenship Diversity = 0 (median) 0.0351***(0.0026)

0.0289***(0.0024)

0.2185***(0.0336)

@Citizenship Diversity = 0.03 (p75) 0.0370***(0.0024)

0.0307***(0.0023)

0.2266***(0.0340)

@Citizenship Diversity = 0.15 (p90) 0.0449***(0.0033)

0.0381***(0.0032)

0.2573***(0.0374)

@Citizenship Diversity = 0.24 (p95) 0.0519***(0.0056)

0.0447***(0.0054)

0.2822***(0.0421)

Observations 6771 6771 6771

Note: Presented are the probabilities for a positive outcome and standard errors clustered at the level of the firm in brack-ets; ***, **, and * indicate significance at the 1, 5, and 10% level.

2292 M. GRILLITSCH AND C. CHAMINADE

citizenship diversity are 0, 0.03, 0.15, and 0.24, which correspond respectively to the 50th

(no citizenship diversity), 75th, 90th, and 95th (high citizenship diversity) percentiles. Com-paring the 50th and 95th percentiles, Figure 1 (and Column 1/Table 6) shows that the like-lihood to engage in GINs increases from 3.5% to 5.2%. Figure 2 (and Columns 2 & 3/Table

Figure 1. Likelihood to engage in GINs at specific levels of Citizenship Diversity (with 90% confidenceintervals).

Figure 2. Likelihood to engage in GINs at specific levels of Citizenship Diversity and inter-firm networks(with 90% confidence intervals).

EUROPEAN PLANNING STUDIES 2293

6) shows that i) intra-firm networks play a crucial role, and that ii) firms with a high citi-zenship diversity tend to have a higher likelihood to engage in GINs. The likelihood toengage in GINs at the 50th and 95th percentiles are 2.9% and 4.4% respectively for firmswithout intra-firm networks. For firms with global intra-firm networks the likelihood toengage in GINs is 21.9% for firms with no citizenship diversity (50th percentile) and28.2% for highly diverse firms (95th percentile).

The above analysis provides support for the assumed relationship between citizen-ship diversity and firms’ participation in GINs (hypothesis 1). As robustness check,Table 7 depicts how sensitive the relationship is to the included control variables.The first line shows the coefficient of citizenship diversity. The following rowsreport, which control variables are included in the respective models. Accordingly,in all cases the coefficient remains highly significant and shows only minor deviationsin magnitude between 0.8793 and 1.0494 depending on which control variable isexcluded.

The results provide empirical evidence that citizenship diversity at the level of the firmis positively related to the likelihood that firms engage in GINs. However, does this applyto all firms equally? In the theory section, we have argued that the effect ofcitizenship diversity on the participation of firms in GINs depends on the absorptivecapacity of firms. Without the cognitive ability to identify relevant knowledge, exchangeknowledge and create new knowledge in GINs, citizenship diversity is assumed to beineffective.

In order to investigate this relationship, we interact the citizenship diversity with thehuman capital variable. Table 8 presents the average marginal effects of citizenshipdiversity on GINs conditional to certain levels of human capital and conditional towhether global intra-firm innovation networks exist. The results show that citizenshipdiversity has no effect for firms with low levels of human capital but a highly positiveand significant effect for firms with high shares of qualified staff over the total staff ofthe firm, thus backing hypothesis 2. Graphically, the average marginal effects of citizen-ship diversity at different levels of human capital are depicted in Figure 3. The averageshare of qualified employees in the sample is approximately 45%, which is the level atwhich the citizenship diversity variable turns significant. In the sample, 1.051 firms(16%) have a human capital level of larger than 90% and 527 firms (8%) of 100%.For these firms the marginal effects come up to 0.3529 and 0.4441 respectively(Table 8, Column 1). This general pattern holds also if average marginal effects are cal-culated conditional to the existence of global intra-firm networks. It suggests that evenif intra-firm innovation networks exist, citizenship diversity only contributes positivelyto the engagement in GINs if the firm has a certain level of absorptive capacity. At100% human capital, the average marginal effect has a similar magnitude for both,firms with and without intra-firm networks (Figure 4). However, the pattern indicatesthat the average marginal effect increases faster with human capital for firms withintra-firm networks. However, due to the high standard errors, this difference inshape cannot be established statistically.

In summary, our results suggests that citizenship diversity has a strong effect on thelikelihood that firms engage in GINs contingent to the level of absorptive capital,measured here as human capital.

2294 M. GRILLITSCH AND C. CHAMINADE

Table 7. Probit regression: citizenship diversity on GINs.(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Citizenship 0.8896*** 0.9075*** 1.0494*** 0.9331*** 0.8910*** 0.8793*** 0.9006*** 0.8940*** 0.9393*** 0.8824***Diversity (0.3198) (0.3151) (0.2941) (0.3159) (0.3153) (0.3106) (0.3173) (0.3164) (0.3141) (0.3162)Global intra-firm networks – Yes Yes Yes Yes Yes Yes Yes Yes YesHuman Capital Yes – Yes Yes Yes Yes Yes Yes Yes YesIntramural R&D Yes Yes – Yes Yes Yes Yes Yes Yes YesForeign Owner Yes Yes Yes – Yes Yes Yes Yes Yes YesForeign Sales Yes Yes Yes Yes – Yes Yes Yes Yes YesSize Yes Yes Yes Yes Yes – Yes Yes Yes YesMetropolitan Area Yes Yes Yes Yes Yes Yes – Yes Yes YesMill’s Ratio Yes Yes Yes Yes Yes Yes Yes – Yes YesIndustry Dummies Yes Yes Yes Yes Yes Yes Yes Yes – YesTime Dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes –Constant Yes Yes Yes Yes Yes Yes Yes Yes Yes YesObservations 6771 6771 6771 6771 6771 6771 6771 6771 6771 6771

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Table 8. Average marginal effect of citizenship diversity on the likelihood to engage in GINs conditionalto fixing human capital and intra-firm networks at the indicated levels.

(1) (2) @ intra-firm networks = 0 (3) @ intra-firm networks = 1

@Human Capital = 0% −0.0028(0.0090)

−0.0023(0.0074)

−0.0235(0.0749)

@Human Capital = 10% −0.0011(0.0131)

−0.0010(0.0113)

−0.0078(0.0889)

@Human Capital = 20% 0.0039(0.0183)

0.0035(0.0165)

0.0214(0.1000)

@Human Capital = 30% 0.0150(0.0245)

0.0139(0.0228)

0.0652(0.1061)

@Human Capital = 40% 0.0354(0.0318)

0.0337(0.0304)

0.1221(0.1066)

@Human Capital = 50% 0.0686*(0.0415)

0.0664(0.0405)

0.1878*(0.1031)

@Human Capital = 60% 0.1176**(0.0552)

0.1151**(0.0548)

0.2558**(0.0999)

@Human Capital = 70% 0.1831**(0.0735)

0.1808**(0.0736)

0.3187***(0.1035)

@Human Capital = 80% 0.2632***(0.0946)

0.2617***(0.0951)

0.3698***(0.1185)

@Human Capital = 90% 0.3529***(0.1159)

0.3525***(0.1166)

0.4041***(0.1429)

@Human Capital = 100% 0.4441***(0.1372)

0.4453***(0.1381)

0.4194**(0.1704)

Observations 6771 6771 6771

Note: Presented are average marginal effects and standard errors clustered at the level of the firm in brackets; ***, **, and *indicate significance at the 1, 5, and 10% level.

Figure 3. Average marginal effects of citizenship diversity on the probability to engage in GINs atspecific levels of human capital (with 90% confidence intervals).

2296 M. GRILLITSCH AND C. CHAMINADE

5. Conclusions

In the last decades, we have witnessed an increase in the global distribution of inno-vation networks (De Prato & Nepelski, 2012; Herstad et al., 2014) and a number ofstudies have shown how GINs significantly contribute to the innovativeness and econ-omic performance of firms (Plechero & Chaminade, 2016) and regions. But engagingin truly global networks implies that actors need to overcome institutional barriersassociated with location in different regional and national contexts. Therefore, weargue in this paper that citizenship diversity at the level of the firm should be animportant factor explaining the engagement of firms in GINs. In contrast to most ofthe existing literature that treats international linkages as a black box, this paper inves-tigates the impact of diversity on innovation networks outside Sweden but withinEurope, Outside Europe and truly global (networks with partners in all geographicalareas). Our results indeed show that firms with a high citizenship diversity are morelikely to have truly global innovation linkages and that in contrast, we have no evidencethat high citizenship diversity affects the propensity of firms to engage in other formsof international innovation networks.

While diversity has many dimensions, it is argued that diversity related to the countryof citizenship of the firm’s workforce is highly relevant for GINs as it relates to the nationalinstitutional context conditions in which individuals have been socialized. Conceptuallywe identify four reasons why citizenship diversity should be positively related to GINs.Workers with different citizenships have knowledge about the institutional context con-ditions in their respective home countries, thus reducing institutional barriers related toGINs. In addition, citizenship diversity within a firm may stimulate learning about howto deal with institutional differences, i.e. how to overcome institutional barriers.

Figure 4. Average marginal effects of citizenship diversity on the probability to engage in GINs atspecific levels of human capital and intra-firm networks (with 90% confidence intervals).

EUROPEAN PLANNING STUDIES 2297

Furthermore, firm-level citizenship diversity is related to the breath of social networks. Forinstance, studies have shown that migrants’ social networks with their home countries cansupport innovation collaboration (Agrawal et al., 2006; Trippl, 2013). Finally, the capa-bility to overcome institutional barriers and social networks contribute to a broadsearch space for information and knowledge (Ebersberger et al., 2011; Laursen, 2012;Østergaard et al., 2011), for instance about organizations in different countries thathold required competencies for innovation processes.

Our empirical study also shows that that the relationship between firm-level citizenshipdiversity and engagement in GINs is contingent on the absorptive capacity of firms.Without a minimum cognitive level, firms will not be able to successfully search,capture and integrate the knowledge acquired through global networks and manage thecomplexity of internationalization. As absorptive capacity increases, captured by the qua-lification of the labour force, the relationship between firm-level citizenship diversity andengagement in GINs becomes stronger.

In conclusion, our discussion and analysis provide novel inputs to the emergent scho-larly work on GINs by providing insights into the mechanisms through which firm-levelcitizenship diversity is expected to stimulate small and medium-sized firms’ participationin GINs (as a distinct form of international networks) as well as evidence of their positiverelation.

Notes

1. The authors refer to partners in general, without specifying the type of partnership or if thepartnership is related to innovation. Additionally, the authors do not make a distinctionbetween international and global networks.

2. A particular subset of literature focuses only on the diversity of the top management. Carpen-ter & Fredrickson (2001), using data of US firms, find that the diversity of the top manage-ment team is positively related to a higher propensity to pursue innovative strategies in globalmarkets. Barkema & Shvyrkov (2007) provide evidence that diversity of the top managementteam has a positive impact on the foreign expansion of the firm but that the final effect ismediated by the tenure of the team as well as the cultural distance between the different man-agers. Caligiuri, Lazarova, & Zehetbauer (2004) find that the diversity of nationalities amongtop managers positively influences the propensity to internationalize through exports,foreign direct investments and through recruitment. Furthermore their evidence showsthat diversity of the top management team has special impact on the breath of internationa-lization, that is the number of countries in which the firm operates which, in turn, as dis-cussed earlier has a higher impact on productivity (Kafouros et al., 2012).

3. Diversity in educational level is however negatively associated with performance (Bell et al.,2010).

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by Marianne and MarKus Wallenberg Foundation [grant number2012.0194].

2298 M. GRILLITSCH AND C. CHAMINADE

ORCID

Markus Grillitsch http://orcid.org/0000-0002-8406-4727Cristina Chaminade http://orcid.org/0000-0002-6739-8071

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Annex 1. Descriptive Statistics

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