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Rinnakkaistallenteet Yhteiskuntatieteiden ja kauppatieteiden tiedekunta
2019
Cross-border regional innovation ecosystems: The role of non-profit organizations in cross-border
cooperation at the US-Mexico border
Cappellano, Francesco
Springer Science and Business Media LLC
Tieteelliset aikakauslehtiartikkelit
© Springer Nature B.V.
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http://dx.doi.org/10.1007/s10708-019-10038-w
https://erepo.uef.fi/handle/123456789/7647
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Cross-border regional innovation ecosystems: The role of non-profit organizations in cross-border cooperation at the US-Mexico border Francesco Cappellano
*,1& Teemu Makkonen
2* Corresponding author
1 Department of Architectural and Urban Heritage, Mediterranean University of Reggio Calabria; Via Salita Melissari, 24 89124 Reggio Calabria IT; +393389006813; francesco.cappellano@unirc.it
2 Karelian Institute, University of Eastern Finland; P.O. Box 111, FI-80101 Joensuu, Finland; +358505258942;
teemu.makkonen@uef.fi Orcid:
Francesco Cappellano: 0000-0003-3061-433X Teemu Makkonen: 0000-0002-1065-1806
Funding:
This article has been developed through the scientific activities held within the MAPS-LED project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 645651
2
Cross-border regional innovation ecosystems: The role of non-profit organizations in cross-border cooperation at the US-Mexico border
ABSTRACT
In light of the shortcomings concerning Cross-Border Regional Innovation Systems (CBRIS), this analysis seeks to propose a new Cross-Border Regional Innovation Ecosystem (CBRIE) concept better equipped to address the to address contemporary innovation policy development and practical regional policy challenges on the ground. The existing literature on CBRIS has focused on EU regions and awarded only a marginal role to non-profit organizations (NPO) as potential facilitators of cross-border cooperation (CBC).
To address this knowledge gap, the role of NPOs in CBC is analyzed within the bi-national San Diego–
Tijuana region at the US-Mexico border. The research follows a mixed approach based on semi-structured interviews and social network analysis in order to: i) gauge how organizations are interrelated and ii) identify the key actors within the CBRIE. The results show that the CBRIE concept serves as an effective tool for identifying the organizations involved in cross-border networks and their roles in CBC at the US-Mexico border. Although the US-Mexico border presents stark differences compared to EU border regions, the CBRIE concept can offer a starting point for analyzing and facilitating CBC in Europe.
Keywords: cross-border region; innovation; non-profit organization; social network analysis; regional innovation policy
3
Introduction
The academic literature acknowledges that successfully integrated Cross-Border Regional Innovation Systems (CBRIS) can facilitate local economic development despite the numerous barriers hindering cross- border interaction and CBRIS orchestration. With this regard, the conceptualization of CBRIS, developed by Lundquist and Trippl (2013), represents a ground-breaking milestone in the body of knowledge on cross- border innovation cooperation1. Nevertheless, taking into consideration the recent emphasis given to smart specialization within the EU, the discussion on innovation policies at cross-border regions would benefit from a more nuanced conceptual framework. Moreover, the literature on CBRIS has mainly focused on analyzing public sector-led macro-level integration processes (van den Broek and Smulders 2015), while neglecting a bottom-up approach that would include an investigation into the role of individual organizations in driving cross-border cooperation (CBC) networks. As such, relatively little is known about the role that individual organizations can have in facilitating CBC. Therefore, our research focuses on cross- border regions, defined as a bounded territorial unit composed of the territories of authorities participating in CBC (Perkmann 2003), but extends the current body of literature and the conceptualization of CBC by elaborating the CBRIS in a more policy-relevant direction by developing a new concept: the cross-border regional ecosystems (CBRIE).
Based on these premises, this paper adopts a micro-scale approach to explore the network of organizations within the US-Mexico border region between San Diego and Tijuana. The research follows a mixed approach with a twofold goal. Based on semi-structured interviews and a social network analysis the paper:
1) Shows how organizations are interrelated within the cross-border context
2) Identifies the key actors within the CBRIE and discusses their roles (goals and activities adopted) in driving CBC in the region.
Instead of public sector actors, which have been by far the dominant focus of the literature on CBC and particularly CBRIS, here (while not explicitly excluding other types of organization) special attention is given particularly to non-profit organizations (NPO) participating in CBC, including (under the broad umbrella of
“501(c)(3) organization” of the US Internal Revenue Code) universities, economic development corporations, co-working spaces, incubators, accelerators as well as other “intermediary organizations”
providing services supporting innovation to varying extents2. Whereas public sector actors (e.g. city governments and planning agencies) commonly hold central roles in implementing and developing generic CBC policies (Blatter 2004), NPOs are supposed to “act as interfaces [...] to favor the combinational knowledge process” (Crespo and Vicente 2016: p.213) as well as to “promote cross-border knowledge transfer and enhance innovation” (Jandhyala and Phene 2015: p.5). Thus, the aim here is to analyze how NPOs network across the border with local government agencies and other organizations in the San Diego–
Tijuana region.
Earlier studies on the US-Mexico border have highlighted how several NPOs have emerged to respond to social and environmental challenges in cross-border contexts (Sparrow 2001; Ganster and Collins 2017;
Mendoza and Dupeyron 2017). As such, “intermediary organizations” (Rissola et al. 2017), like NPOs, can hold important roles within networks underpinning regional innovation ecosystems (Hautamäki and
1 We define innovation in its dictionary form as a new idea manifested in form of a device or a method and (deriving from the standards OECD definition) cross-border innovation cooperation as active participation in joint innovation projects with other organizations of which at least one is from a neighbouring country.
2 We include non-governmental organizations in our analysis as they are almost synonymous with NPOs in the US. As stated by Ahmed and Potter (2006): NPOs are organized independently of government, place constraints on
redistribution of earnings, practice self-governance, and have voluntary membership – all these conditions apply also to non-governmental organizations.
4 Oksanen 2015; Glückler et al. 2017) particularly in cross-border regions, where NPOs can heighten their importance by bringing actors together across the border. Whereas the role of NPOs and their networks has been discussed in some related works, most notably by Brooks and Fox (2002) and Staudt and Coronado (2002), this discussion has thus far gone undervalued particularly in the literature on CBRIS (Makkonen and Rohde 2016); a gap that this analysis seeks to fill. Moreover, since CBC takes place in a grey zone of formal and informal networks (Lundquist & Trippl, 2013) between a wide range of different organizations, definition and empirical observation of these complex networks has remained problematic (Makkonen and Rohde 2016). This paper addresses the shortcomings of contemporary social network metrics (Svenson and Norlund 2015) in describing CBC by introducing a new “user-friendly” centrality measure: cross-border centrality (C-BC).
The case study region was chosen, firstly, because CBC in the North American context has been carried out by “informal coalitions that coalesce in response to specific problems or opportunities and often disperse later” (Ganster and Collins 2017: p. 498); therefore, the North American context offers us clear advantages to assess the nature and scope of networks made by non-governmental actors. Moreover, despite the fact that CBC is naturally controlled by federal governments, the main achievements of CBC in the San Diego–
Tijuana region have been accomplished by local organizations (Mendoza 2017). Secondly, in the US-Mexico case the NPOs have emerged in response to various societal challenges and are now embedded in cross- border governance and cooperation processes (Sparrow 2001; Mendoza and Dupeyron 2017). Thirdly, although the San Diego–Tijuana region has attracted scholarly attention before, these earlier works have focused on economic integration (Mendoza 2017; Mendoza and Dupeyron 2017), the role of borders in the making of cross-border bi-national cities, twin cities or metropolises (Sparrow 2001; Ganster and Collins 2017; Herzog and Sohn 2017), but have overlooked important issues such as the role of NPOs in cross- border innovation, the concepts of CBRIS and CBRIE, and the methodological limitations of contemporary social network analysis tools in cross-border contexts.
The remainder of this article is organized as follows. The next section examines the need to tailor innovation policies for cross-border contexts as well as the conceptual framework debated in the literature.
This is done by exploring both the European and North American contexts and by introducing our novel Cross-Border Regional Innovation Ecosystem (CBRIE) concept. The third section introduces the research strategy, data and the methods applied and suggests a novel measure for cross-border centrality. Finally, the results of the analysis are presented followed by a concluding discussion on how the insights from the US-Mexico case could be transferred to serve also the European context.
Innovation at the border
a) Regional innovation ecosystems
The regional innovation ecosystem has been heralded as a suitable environment where innovation processes can be tested (Committee of the Regions 2016). Three main aspects distinguish a regional innovation ecosystem from a regional innovation system. Firstly, although innovation ecosystems and innovation systems are both composed not only of economic agents and relations but also of non- economic factors such as technology, institutions, sociological interactions and the local culture (Jackson 2011; Mercan and Göktas 2011; Lappalainen and Markkula 2013), the innovation ecosystem concept embodies open innovation and involves a broader range of participants, both innovation producers and users, resulting in greater co-creativity and innovativeness (Autio and Thomas 2014; Rinkinen 2016).
Secondly, the bottom-up approach and the leadership of the orchestration process in innovation ecosystems differ significantly from the (rigid) innovation system approach mainly led by the public sector (Ritala and Almpanopoulou 2017). The regional innovation ecosystem concept places greater emphasis on the differentiated roles (or “niches”) that organizations can have in steering innovation (Oh, et al. 2016). In
5 contrast to an innovation system, a regional innovation ecosystem has a dynamic, agile and mainly self- governed network structure suitable for promoting collaborative innovation (Smorodinskaya et al. 2017).
The concept relies heavily on the interdependent roles played by different actors (Rinkinen 2016), which pave the way for co-creation of value (Smorodinskaya et al. 2017).
Thirdly, the knowledge and networks of individuals and organizations can be considered “sticky” in their attachment to place or locality (Glückler et al. 2017). This “place-based” characteristic is emphasized in the innovation ecosystem (Rissola, et al. 2017). Despite some scholarly criticism (Oh et al. 2016), the value of introducing “eco” to the innovation systems debate has rapidly gained policy relevance (Smorodinskaya et al. 2017) due to recognition of the bottom-up and interactive nature of innovation processes and the strong evolutionary perspective embedded in contemporary innovation policy debates (Rinkinen 2016).
b) Cross-border regional innovation ecosystems
Although the concept of cross-border innovation cooperation dates back to the 1990s, Trippl coined the term CBRIS only in 2010. The concept has been developed further in a subsequent work by Lundquist and Trippl (2013). CBRIS consists of a knowledge generation subsystem (e.g. universities and research institutes) and a knowledge exploitation subsystem (mainly companies) (Trippl 2010) in a cross-border context. Here also lies the potential for innovation cooperation through smart specialization in European cross-border regions: knowledge generated on one side is exploited (i.e. commercialized in cooperation with) the other side of the border (Muller et al. 2017).
Key challenges for policy-makers committed to orchestration of CBRIS include: the border itself as a barrier (Makkonen and Rohde 2016); cultural distance and lack of common identity and trust (Krätke 1999);
differences in industrial specialization of the respective border regions (Trippl 2010; Lundquist and Winther 2006) institutional asymmetry (Oliveira 2015; van den Broek and Smulders 2015; Miörner et al. 2018); low levels of interest from the respective nation states; overly strong national government-led, top-down regional policy; strong embeddedness of local actors in their corresponding regional and national innovation systems (Lundquist and Trippl 2013; Makkonen et al. 2017); and differences in economic histories, innovation capacities and cultural identities (Anderson and O’Dowd 1999; Lundquist and Winther 2006; Trippl 2010; Lundquist and Trippl 2013).
As a point of departure from the discussion on CBRIS integration, which can be considered a highly public sector driven process, our focus is on CBRIE. The concept of has not, thus far, been applied in a cross- border context. Moreover, the concept of CBRIE gives greater emphasis to the bottom-up approach of cross-border integration and the differentiated roles that organizations can have in steering cross-border innovation cooperation. In this regard, the collaborative dimension rooted in the innovation ecosystem’s structure underlines the importance of interactions (Jackson 2011) that can generate knowledge flows, which are considered to constitute the “backbone” of the modern economy (McCann 2016). The CBRIE approach is therefore examined here with specific respect to its potential role in supporting entrepreneurship and innovation in the San Diego–Tijuana region.
c) The North American and European policy contexts
In Europe, cross-border regional integration has gained much scholarly attention, political acknowledgment, and financial support. The European Parliament (2016) advocates cross-border cooperation, as transnational cooperation and learning are considered pivotal for creating economic growth (Mariussen et al. 2016). A bundle of incentives, tools and supportive measures have therefore been implemented to foster interregional and transnational cooperation within the EU. Accordingly, European regional cross-border institution building has typically been dominated by public sector actors (Blatter 2004) yielding "a complex multilevel framework of formal institutions, political associations, lobbies and incentive programs" (Scott 1999. p.208). In this respect, the case of Northern Portugal and Galicia (Spain) is considered to represent good practice for joint smart specialization policy making. CBC in the region is
6 supported by the European Grouping for Territorial Cooperation Galicia-Norte Portugal, set up in 2008, which promotes investments in strategic industry sectors across the border by means of an aligned innovation policy embedded in a joint cross-border strategy (Oliveria 2015). Besides being an inter- governmental assembly, the European Grouping for Territorial Cooperation also offers technical support and serves as a forum for civil society (Durand and Nelles 2014) and thus also the NPOs focused on in this study.
Successful cooperation is, however, the exception, not the rule. Recent studies have shown that insufficient stakeholder commitment, procedural complexity, lack of cross-border harmonization of rules (Petrova and Rogin 2016), lack of resources and clarity of objectives (Sörvik et al. 2016), and weak interest among managing authorities (Interreg Europe 2015) are key barriers to interregional cooperation in the EU.
Moreover, regions implementing smart specialization strategies have tended to prefer low-intensity activities (such as information sharing) as their dominant form of cooperation with other regions, rather than engaging in more intensive collaborative activities such as joint innovation (Sörvik et al. 2016). For example, studies conducted in the Dutch-German Venlo-Lower Rhine cross-border region (van den Broek and Smulders 2015), in the Øresund region on the Danish-Swedish border (Miörner et al. 2018), and in the French–German Upper Rhine area (Muller et al. 2017) reveal the processes of integration in European cross-border regions to be faltering and rather weak (González-Gomez and Gualda 2014). Therefore, to facilitate cross-border integration Castanho et al. (2017; 2018) have identified several critical success factors for improved CBC outcomes including, for example: defining clear and common objectives, promoting political commitment and transparency and improving connectivity across the border.
Whereas the process towards European integration started in the 1950s3, in North America the North American Free Trade Agreement (NAFTA) entered into force as late as 19944. NAFTA and the Mexican entry into the General Agreement on Trade and Tariffs increased trade along the US-Mexico border significantly (Yoskowitz et al. 2010). The US–Mexico Foundation for Science was founded in 1993 as part of the NAFTA negotiations to facilitate CBC, for example in the field of economic development based on innovation and human resources. In 2013, the “Mexico-US Entrepreneurship and Innovation Council” was created. Under this umbrella, a partnership between actors in the San Diego–Tijuana region gave rise to the “Venture beyond borders” program in 2016, which seeks to boost entrepreneurship and start-up creation both sides of the border. Thus, as stated in the introduction, although CBC in the North American context is also driven by federal governments, it has in practice been mainly carried out by informal coalitions and local organizations (Ganster and Collins 2017; Mendoza 2017).
In the US-Mexico case, therefore, we can observe a policy framework that, dissimilarly to Europe, is designed and scaled for non-governmental actors’ cross-border innovation cooperation (we will return to this in the Results section).
Research strategy
Recent studies on CBC have commonly adopted social network analysis methods to analyze, for example, cross-border policy networks (Walther and Reitel 2013; Dörry and Walther 2014; Durand and Nelles 2014;
Sohn and Giffinger 2015; Dörry and Decoville 2016). However, thus far no study has examined CBRIS or CBRIE using a social network analysis approach. Moreover, papers utilizing this approach in a cross-border context have, so far, targeted only European cross-border regions. To address these research gaps, social
3 Recently, this process has faced political involution due to “Brexit” and the contemporary upheaval in Catalonia.
4 Although NAFTA has contributed to boosting economic exchange among its member nations, it is expected to be replaced by the United States–Mexico–Canada Agreement.
7 network analysis was applied in a North American context to describe the structure of the CBRIE in the San Diego–Tijuana region.
a) Sample delineation and data collection
The data applied here was collected by means of interviews employing the “roster-recall method”. This method aims to collect full network data on a pre-defined population of actors. Therefore, each interviewee was provided with a list (“roster”) of the most important actors (listing all potential actors is practically impossible) in the CBRIE. The interviewees were then asked whether they are engaged in cooperation with the organizations in the roster. Additionally, the interviewees were asked to “recall”
whether they have cooperative activities with organizations outside the predefined roster list. This compensates for the fact that not all potential actors were listed in the roster. The recall method thus allows the inclusion of information on links between the “population” that might otherwise be unknown to the researchers. The method also has limitations. Most notably, non-responsiveness and incomplete network data, as is often the case with survey data, significantly decreases the reliability of the results.
Therefore, primary data should preferably be collected through interviews (as in this study). Secondly, it should be noted that the respondents’ ability to recall complete lists of collaborative links is questionable.
Ongoing and recent cooperation is easier to recall than incidences in the distant past. Thus, this type of data commonly depicts a somewhat static situation rather than the evolutionary dynamics of networks (Ter Wal and Boschma 2009).
The selection of organizations to be interviewed (constituting the “roster” part of our interview) was based on official documents, local newspapers and, most notably, expert opinion (discussions with four external experts: three academics and one entrepreneur) on the most central actors in the CBRIE. Despite the abundance of NPO organizations somewhat related to the border, we confined our focus to local organizations that clearly stood out as organizations promoting innovation in the cross-border region (those mentioned in official documents, newspaper articles or by the experts as being engaged in CBC).
Admitting the subjective nature of defining the roster, we further applied the so-called “snowballing technique”, a commonly used additional sampling technique (Walther and Reitel 2013: Makkonen et al.
2018a), to enlarge the sample when new organizations outside our roster were mentioned at least three times as CBC partners during the interviews. An overview of the process of delineating the sample is presented in Figure 1.
INSERT FIGURE 1 [Figure 1. Methodological approach scheme.]
A questionnaire including both closed- and open-ended questions guided 34 face-to-face interviews during six months of fieldwork in the case study region, with key experts representing 28 different entities including city governments, public agencies and NPOs in the San Diego–Tijuana region (Table 1). Each respondent was asked about his or her organization regarding: general information on their organization, their economic links and relationships with the bi-national innovation ecosystem, the scope of their cooperation (goals and actions) and their opinions on potential barriers and obstacles to cross-border cooperation. The interview framework was arranged as a mixture of multiple-choice and open-ended questions. The interviews lasted, on average, around one hour and were audio recorded and transcribed. In larger organizations, i.e. where more than one individual was interviewed, the answers were aggregated (Sohn and Giffinger 2015; Dörry and Deconville 2016). The overall response rate was 74%, which provides a fair estimate of the real complete network (Walther and Reitel 2013; Durand and Nelles 2014; Sohn and Giffinger 2015; Makkonen et al., 2018a), particularly since we are using measures (see below) that are relatively robust even at lower sampling levels (i.e. under 50%) (Costenbader and Valente 2003). However, to simplify the analysis and to remove less important actors out of the 66 organizations mentioned (at least once) in the interviews, only actors nominated more than three times were considered in the subsequent analysis (Dörry and Deconville 2016). Additionally, since we are examining a cross-border network, at least one of these links had to be an external one (i.e. a cross-border link) for an organization to be considered in
8 our analysis. As a result, our social network analysis covers 29 organizations, of which 19 are among the 28 organizations interviewed.
INSERT TABLE 1 [Table 1. Conducted interviews.]
b) Social network analysis
Social network analysis is applied here to uncover a) the most important nodes and b) the ties that connect the nodes. In line with several earlier papers on CBC (e.g. Walther and Reitel 2013; Durand and Nelles 2014;
Makkonen et al., 2018a), here we are mostly interested on who are the key/most central actors in the cross-border network of the San Diego–Tijuana region. When querying the centrality (role or power) of an actor in a network, it is essential to use directed graphs, as symmetrization of the data (i.e. the assumption that a similar link exists both ways without the link being confirmed as reciprocal) would lead to overestimation of the real number of ties (Durand and Nelles 2014). Therefore, in line with Durand and Lamour (2014), we concentrate on In-degree centrality. This figure represents the standing of an actor as seen by the other actors (i.e. prestige centrality) in the network (the number of times other actors in the network have stated that they collaborate with the actor), compared to out-degree centrality, in which actors are ranked based simply on the number of collaborative links they report themselves. Thus, we employ the standard social network metric normalized (in-)degree centrality (DC') (organization’s links with other organizations within a network divided by the total number of potential links). The more ties an actor has with other actors in the network, the better it is connected and the higher its DC' score (Durand and Nelles 2015).
We also introduce a new simple measure, cross-border centrality (C-BC), to address the issue of centrality in cross-border settings. By calculating centrality based on cross-border links – by dividing the number of actual cross-border links (c-b links) by the total number of potential cross-border links (potential c-b links) in a cross-border network – we get an overall picture of which central actors in the network are driving CBC.
In other words, we consider the in-degree centrality score of 1) external (E) cross-border links, while excluding 2) internal (I) domestic links. Here C-BC is scaled to 0–1 for each side of the border separately, since the number of potential cross-border links vary depending on which side of the border the actor is located in. Thus, on both sides of the border the most connected cross-border actor (having the maximum C-BC score) will receive a value of 1. The scores of the other actors are in proportion to the maximum C-BC score (C-BCmax). Therefore, here the C-BC score of an actor i on the j side of the border is calculated as follows (Equation 1):
𝐶𝐶–𝐵𝐵𝐶𝐶𝑖𝑖 =
𝑐𝑐–𝑏𝑏 𝑙𝑙𝑖𝑖𝑙𝑙𝑙𝑙𝑙𝑙𝑖𝑖 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑙𝑙𝑝𝑝𝑖𝑖𝑝𝑝𝑙𝑙 𝑐𝑐–𝑏𝑏 𝑙𝑙𝑖𝑖𝑙𝑙𝑙𝑙𝑙𝑙𝑗𝑗
𝐶𝐶–𝐵𝐵𝐶𝐶𝑚𝑚𝑝𝑝𝑚𝑚𝑚𝑚
� (1)
The measure for C-BC is, thus, an extension of the commonly applied E-I index that measures the difference between external (cross-border) and internal (domestic) ties, divided by the total number of ties with a range from -1 (high numbers of internal ties compared to external ones) to 1 (high numbers of external ties compared to internal ones) (Walther and Reitel 2013; Dörry and Walther 2015). However, the E-I index does not consider the fact that the most central actors within a cross-border network can have both high cross-border centrality as well as domestic centrality. The C-BC measure is better at capturing these types of “anomalies”. This notion is based on the simple logic that an actor that is well connected in both cross- border and domestic (sub-) networks (i.e. E-I index scores close to zero, but high in-degree and cross- border centrality) should be in a better position to develop CBC on a regional scale than an actor with several cross-border links but few domestic links (i.e. high E-I index, but low or moderate in-degree centrality), in which case it might have only a diminutive role at the regional scale in its home country.
9 While social network analysis allows us to describe the structure of networks and to identify the important actors in the network (Durand and Nelles 2014; Sohn and Giffinger 2015), the approach has been criticized for being a mapping exercise that lacks explanation of how the linkages developed and evolved. A commonly applied means of addressing this challenge is to supplement the analysis with qualitative data (Walther and Reitel 2013; Sohn and Giffinger 2015; Dörry and Deconville 2016). Our social network analysis was therefore supplemented with open-ended questions, giving us insight into the goals and policy activities of the interviewed organizations within the CBRIE.
Results
An overview of the results is presented in Table 2 and Figure 2. Values close to 1 indicate that a given node is well connected (DC'), has a high share of external (cross-border) ties compared to domestic ones (E-I index) or high absolute numbers of external ties (C-BC). The results show that on the American side of the border universities are the most connected within the CBRIE both in terms of the whole network (DC') and cross-border ties (E-I index and C-BC). Additionally, the metropolitan planning organization SANDAG emerges as a prominent actor in terms of cross-border centrality.
INSERT TABLE 2 [Table 2. Social network analysis: results.]
INSERT FIGURE 2 [Figure 2. Social network analysis: illustration (see Table 2 for identification – ID).]
The situation on the Mexican side of the border is somewhat different. There the most connected organizations are not universities, but public organizations (City of Tijuana and Baja California) and other types of NPOs, namely Tijuana Economic Development Corporation and Tijuana Innovadora (a local innovation incubator). In addition, in the case of Mexico there is a greater difference between organizations that are central to the network as a whole (driven by high numbers of domestic ties) and those that are prominent in CBC. The E-I index figures and C-BC show that in Mexico, as in the USA, universities emerge as central players in establishing cross-border ties. However, the high E-I indexes of two of the Mexican universities (El Colegio de la Frontera Norte and Universidad Nacional Autónoma de México) are driven more by their lack of domestic ties than high numbers of cross-border ties. Therefore, although their share of cross-border links compared to the total number of links is high, the C-BC measure shows that CBC in the San Diego–Tijuana region is mainly driven by the same actors that are the most connected to the network as a whole.
In terms of the goals that the organizations vision themselves having in CBC in the San Diego–Tijuana region (we presented a list to the interviewees), supporting innovation was clearly the most predominant goal pursued by the interviewed organizations, particularly on the Mexican side of the border. The high percentage of Mexican actors involved in this endeavor is most probably due to “the stark differences in the innovative capacity across the US-Mexico border” as reported by an interviewed key academic. However, as acknowledged by an academic interviewee: “a lot of innovation is happening in Mexico, so we are trying to teach each other best practices and learn from each other” justifying the ongoing cross-border integration process. Based on the interviews, the actors seem independently committed to pursuing cross-border innovation cooperation, reflecting their interdependent roles as actors in the CBRIE5, as one interviewed key academic stated: “The different organizations involved work organically building upon their possibilities.
Our contribution (as a university) is limited to people and technology, we are not here to develop products.
This is up to other parts of the ecosystem.”
5 The definition of innovation ecosystem was given to the interviewees to help them grasp the purpose of this study.
10 Several interviewees classified a number of different activities under this broad goal, including: consulting US and Mexican companies to locate in the cross-border region, mentoring a cross-border audience on entrepreneurial culture, giving access to funding sources, and providing co-working spaces that “can serve as bi-national hubs”, as stated by an interviewed CEO of a US accelerator. These close bonds yield numerous face-to-face cross-border contacts (fairs, meetings, events, etc.) reflecting a continuous movement of ideas and people embedded in the innovation ecosystem (Rissola et al. 2017). A surprise finding, however, was the reported “lack of interest” towards attracting foreign direct investment. The low level of interest devoted to this goal seems to be in stark contrast to the general attitude in the region, which has been marketed as an ideal location for foreign-owned businesses due to cheap labor costs south of the border and the strong innovativeness and financial and infrastructural endowment of the San Diego region. However, “more and more opportunities are opening up south of the border” as stated by one interviewed NPO representative. Moreover, several interviewees remarked how economic links nowadays rely less and less on the labor cost differential and more and more on “the entrepreneurial climate, access and quality of education in Tijuana”, as stated by an interviewed NPO representative, which has paved the way to a new generation of young Mexican entrepreneurs in the region. This “entrepreneurial climate across the border is crucial in pushing for integration” as stated by an interviewed city official.
Figure 3 presents the policy measures adopted by the interviewed organizations to promote CBC (based on a list presented to the interviewees). Among the most commonly adopted approaches were “network activities” and attending “bi-national events”. Both of these activities help build stronger economic ties across the border, particularly because they are considered equally important on both sides. The interviewees were unanimous regarding the importance of these activities as “a trigger for a tighter bi- national community.” Bi-national events supporting innovation are expected to “leverage the skill and overall entrepreneurs’ profile of bi-national participants so that all the parts of the society can reap benefits from these events” as stated by an interviewed city government official.
INSERT FIGURE 3 [Figure 3. Cross-border policy actions of the interviewed organizations.]
Additionally, as shown in Figure 3, the high engagement of actors in promoting joint research and education programs is also relevant for CBC in Sand Diego–Tijuana. This interest is repeated in our qualitative data: several universities reported engaging in cross-border education programs, including:
“joint programs to ensure access to library”, “exchange programs for students and faculty members”, “joint research activities” and “joint on-line courses”. However, the NPOs’ role in pursuing joint innovation activities is not limited to academic cooperation: all of the NPOs (not only universities) participate in CBC, for example, by carrying out economic analysis and market studies, which can be of vital importance, for example, when drafting policy recommendations and lobbying federal governments, assessing the economic strengths and weaknesses of the cross-border region, planning the allocation of funds for cross- border infrastructure projects, and engaging with industry (e.g. helping them locate) and attracting new investment to the region. The case of “ThermoFisher”, which opened a research center in Tijuana, is an excellent example of this engagement. The support that the center received from the UCSD and the first- tier roles played by the two cities’ economic development corporations was acknowledged by the media as a milestone that underlines how the complementary capabilities of San Diego and Tijuana can make the cross-border region a leading global provider of IT services (MARKETWIRED 2016).
The actors involved in the CBRIE are also active in supporting the cross-border regional brand “CaliBaja”
and working together to “sell the region as a whole”, as confirmed by city officials and NPO representatives from both sides of the border. A bi-national regional identity has thus been arising in the cross-border region, for example, in the field of gastronomy and craft beers (Lehnhoff 2016). Lastly, consulting services, which are considered crucial for producing innovation-conducive environments in the innovation ecosystem concept (Smorodinskaya et al. 2017), score high among the adopted activities and several universities collaborate with incubators and accelerators to boost entrepreneurship and competitiveness.
11 An example of this cooperation is “pitch competitions” (involving NPOs and many other key organizations of the CBRIE) in which students and entrepreneurs pitch their business ideas and get advice from industry and academic experts. NPOs in the cross-border region thus seek to “connect people and talent to build up a substantial common platform for entrepreneurs and organization in a bi-national perspective”, as assessed by an interviewee representing the Mexican entrepreneurs’ coalition.
Considering the suggested CBRIE framework, the local public authorities’ role – including a formal agreement on intensifying CBC (San Diego–Tijuana MoU 2017) – is limited to defining “a policy framework to create the infrastructural basis for the innovation ecosystem”, as stated by an interviewed public official.
The CBRIE is perceived “not as a hierarchy but as a landscape” and, since people navigate that landscape, the local NPOs view that their “job is to understand our most effective contribution to that landscape”, as stated by a key academic interviewee. Moreover, according to the interviewed public officials, most cross- border innovation happens at the business level, which the public organizations try to foster by funding NPOs committed to facilitating networking within the CBRIE.
Conclusions
This study sought to consider the potential of developing CBRIE in line with the outward-looking innovation policies promoted by the EU and OECD. The CBRIE concept comprises: 1) a network culture with many collaborative actors operating with different roles and responsibilities (Mercan and Göktaş 2011;
Lappalainen and Markkula 2013), 2) a dynamic, agile and mainly self-governed collaborative structure suitable for promoting collaborative innovation (Smorodinskaya et al. 2017) and 3) a local scale (Glückler et al. 2017; Rissola et al. 2017). Within this CBRIE framework, the study sought to evaluate the role of NPOs in CBC by adopting a micro-scale approach based on both quantitative and qualitative data. The data was collected via 34 face-to-face interviews with key experts representing 28 different entities including city governments, public agencies and NPOs operating in the San Diego–Tijuana region.
The results show (measured with traditional social network measures and with a novel indicator that addresses the issue of centrality in cross-border settings) how on the American side of the border the NPOs (particularly universities; see also Czarny 2017; van den Broek et al. 2019) are the most connected within the CBRIE in terms of both domestic and cross-border ties, whereas on the Mexican side public organizations also serve, along with NPOs, as pivotal actors in the cross-border network. The results also reveal a strong commitment of local actors towards supporting innovation and networking within the CBRIE of the San Diego–Tijuana region. The importance of NPOs is repeated in our qualitative data collected from the San Diego–Tijuana region: on the one hand, universities are committed through a mosaic of activities to facilitating CBC and innovation in the cross-border region, while on the other hand, other NPOs carry out cross-border innovation via a range of other activities, such as attracting public and private investment and creating tools to help local authorities’ planning and decision making. The NPOs in the San Diego–Tijuana region are thus strongly committed to supporting entrepreneurship, innovation and competitiveness by sharing knowledge and by providing access to funding streams, co-working spaces and cross-border networks. Thus, whereas the public authorities see themselves more as facilitators (see also Makkonen et al. 2018b) in creating a policy framework to support cross-border innovation links, the NPOs (and the business sector) are considered the pivotal players in the cross-border network of the San Diego–Tijuana region constituting the core of the CBRIE. This underlines the validity of extending the concept of regional innovation ecosystems to the cross-border context and placing the “eco” in the cross-border innovation system: in our case the different organizations participated in CBC work horizontally rather than through a hierarchical top-down scheme.
12 The contribution of this paper is, thus, threefold. Firstly, it broadens the concepts of innovation ecosystems into a cross-border context. Secondly, it verifies the often neglected but important role that NPOs have as drivers of CBC. Thirdly, it offers a way to overcome some of the methodological limitations of contemporary social network analysis tools in cross-border contexts by introducing a new “user-friendly”
centrality measure that underlines the importance of cross-border links by addressing them separately from the number of domestic links.
Finally, this discussion demonstrates how the CBRIE concept is well-suited for describing the case of the San Diego–Tijuana region, which features the balanced participation of both public organizations and NPOs in CBC. What remains to be determined in further studies is whether a similar type of development can be initiated in European cross-border regions. These notions lead to two important policy conclusions. Firstly, the possibilities of developing CBRIE in the European context could be tested by awarding a greater role to local NPOs – an approach that has produced good results on the US-Mexico border. Secondly, bi-national forum events, such as those proven to be highly effective in the case of the San Diego–Tijuana region, are recommended as an effective means of bringing businessmen, NPOs and community leaders together to facilitate potential future CBC initiatives also in other cross-border regions.
13
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Tables and Figures
17 Figure 1.
Figure 2.
18 Figure 3.
