Keywords

Introduction

The current global environment is  drawing attention to the increasing presence of multinational small-medium enterprises (SMEs) from all over the world. These firms face a number of location-specific disadvantages, as compared with national firms, when they enter a new foreign market (Hymer, 1960). This is commonly referred to as liability of foreignness (Zaheer,1995) and is rooted in the psychological, cultural, and institutional distance between the home and the host country. Besides, these firms face other barriers linked to their size or other factors (liabilities of smallness and newness).

To surpass these liabilities one of the main strategies followed by a foreign direct investment (FDI) option is to co-locate (or collocate) and interact with other firms in specific areas to benefit from externalities and gain advantages from local institutional linkages (positive externalities). However, there are financial costs and risks associated to doing business in clusters due to rivalry, congestion or imitation (negative externalities) that discourage firms to adopt this location mode decision. In other words, the decision to co-locate and grow through networking and clustering has implications for the performance and survival of the subsidiary (Almodovar and Rugman, 2015; Peng and Luo, 2000).

For an effective acquisition and exploitation of these spillovers and to control negative externalities these firms need to concentrate their efforts not only on their internal development but also on the configuration and adoption of business models that best link the FDI with firms located in the same area (Lambert and Davidson, 2013). Our research analyzes the role played by the location mode by analyzing the sign and scope of the externalities that arise from country-of-origin clusters. This is approached from a multidimensional perspective and utilizing a sample of 24 FDI European SMEs localized in China. We compare subsidiaries that are located in country-of-origin clusters in a specific location (Kunshan, Jiangsu, and China) with isolated subsidiaries. China is an investment destination where European firms still face many challenges (Bao et al., 2012) and a country with high institutional distance and instability, which creates an uncertainty that firms compensate through business network knowledge (Hilmersson and Jansson, 2012).

The chapter is organized as follows. In the next section, we provide an overview of the difficulties faced by foreign investors, especially SMEs, and a brief review of agglomeration literature. The subsequent section discusses the methodology, followed by the results. The final section discusses some of the contributions and implications at different levels: academic, managerial, and political.

Theoretical Background

The Challenge of Internationalization for an SME

As various Free Trade Agreements have been implemented and new information and communication technologies have been developed, the competitive landscape of companies has become more turbulent and globalized. To face this new scenario, most companies have reconfigured their corporate, competitive, and functional strategies. SMEs, characterized for having less resources and knowledge, also have to adapt to this process of internationalization, either alone or by establishing links and collaborations with other agents (Paul et al., 2017). Successful global companies used to be large multinational corporations with many divisions and product lines but adopting a global strategy is as important for large firm as it is for SMEs or small organizations.

SMEs are increasingly integrated into the global economy and have gone further than what is often considered the first step of internationalization, that is, exporting and importing (Puig et al., 2018). For many firms, internationalization is a challenge from which the new models (i.e. Johanson and Vahlne, 2009) go beyond the traditional gradual approach in which the company increases its resources and its involvement abroad as it gains experience in the market. In fact, nowadays we can observe different realities characterized by an accelerated internationalization, a high commitment in foreign markets and a prompt global orientation. Within the last 20 years, many SMEs have also accelerated their international commitment by investing in distant countries despite limited market knowledge, limited use of networks, and scarced international experience of the entrepreneurs and managers (Kalinic and Forza, 2012; Puig et al., 2018).

However, as Hollenstein (2005) argued SMEs have to face several barriers within their internationalization process that can be internal limitations of resources (financial, informational, managerial, etc.) and/or external barriers such as laws and regulations. According to Carlos (2011) SMEs have found new ways to deal with smallness and newness but due to their lack of experience, skills, know-how, governance structures, limited capital and management, time or information resources, SMEs are typically constrained in their efforts to reach international markets.

Which aspects drive companies to expand their activities abroad, and which ones are linked to a better international performance? According to the literature, those aspects could be linked to the membership or attachment in territorial networks (i.e. Pla-Barber and Puig, 2009). Various studies have shown that interorganizational relationships are associated with company competitiveness (Powell and Brantley, 1992; Uzzi, 1996). In fact, interorganizational relationships appear to be influential in many internationalization issues as the follows: foreign market selection, market servicing, dynamics of entry, international market development, time of internationalization, or strategic choices and performance. Generally speaking, cooperation can be considered a way to stimulate the development of enterprises in terms of reducing risk, extending markets, introducing new technologies, and so on. So, cooperation can be a strategy for SMEs not only to grow but also to enhance other types of development (Havnes and Hauge, 2004).

Due to a lack of local knowledge, foreign firms are expected to encounter the so-called disadvantage of alien status in host economies (He, 2003), so they find higher benefits from locating in existing clusters of foreign enterprises (Dunning, 1998). In this line, the identification and exploitation of opportunities, the liabilities that firms have due to their size or the lack of market information could be better faced from being a member of a cluster (Tan and Meyer, 2011). Therefore, the relationship between investment and clusters can be seen no longer with clusters as the outcome of FDI, but as the precondition or determinant for attracting FDI (De Propris and Driffield, 2006).

Country-of-Origin Clusters and Co-location Externalities

The literature on geographic agglomeration defines agglomerations as organizational groups that interact, in an economic sector and in a geographically limited territory, where the cooperation and exchange of information and knowledge among the organizations favor growth and regional development (Porter, 1998). These interactions are fostered by the (geographical and cognitive) proximity and the active participation of the companies that are part of that socialnetwork (cluster). Therefore, industrial clusters are made up of a variety of nodes (people, institutions, and businesses) and relationships (formal and informal) that allow the generation of various synergies that increase their competitive advantage.

Since the 1980s, the phenomenon associated with clustering attracted the interest of economists, geographers, sociologists, and so on. Within this approach, different but not exclusive lines of research have studied issues such as the origin, structure, evolution, and conceptual clarification (Martin and Sunley, 2011). Business literature highlights the study of the geographical delimitation/mapping and conceptual clarification, the analysis of the effect that these agglomerations have on the strategic behavior, the performance of companies and the diagnostic of the determinants by which these territorial entities exhibit a heterogeneous performance (Molina-Morales and Martinez-Fernandez, 2004). All this has been translated into a vast scientific production that, from different research approaches, has tried to structure and characterize that literature, as shown by Gonzalez-Loureiro et al. (2018).

In today’s international scenario, we can identify new organizational realities that depend on their actors and the members, where they share (a) a national sectorial platform (cluster initiatives), (b) an economic activity in a given territory (industrial clusters), or (c) a foreign territory and ethnic and cultural ties (country-of-origin/compatriot/ethnic clusters). These realities (Table 6.1) are the object of research of this chapter.

Table 6.1 Different types of clusters
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Clusters “in origin/at home” can serve as a platform in the early stages of internationalization of the firms, for example, to increase their exports. Cluster organizations and initiatives also serve as platform for the members to cooperate and improve their internationalization. These organizations provide services in exchange for a fee, establish relationships that facilitate the creation of business opportunities with external partners, and organize trade missions, among others (Jankowska et al., 2017). Being a member of an industrial cluster could increase the firms’ exports through the network that the cluster offers to position and promote those firms in foreign markets, to increase their global strategic capacity, to advise on financial support for internationalization, or to facilitate access to new business opportunities or entry modes (distributors, agents, etc.) (Pla-Barber and Puig, 2009).

On the other hand, in a more advanced phase of the internationalization process, companies invest in foreign markets through entry modes that require a higher commitment (FDI) (Shen et al., 2017). Country-of-origin clusters or groups of firms from the same or country-of-origin provide a supportive environment to, among other things, acquire legitimacy and negotiation power in the target market, reduce uncertainty and opportunism, or facilitate tacit knowledge sharing and a mutual support ecosystem (Urzelai and Puig, 2018).

Co-location and Entry Reasons

Researchers and academics have come up with different classifications that explain the reasons why firms go international and invest in foreign markets. Authors such as Dunning (1988) classified entry reasons into (1) natural resource seeking (available resources), (2) market seeking (exploit markets, follow customers, etc.), (3) efficiency seeking (availability and costs factors to gain economies of scale and scope), and (4) strategic-asset or innovation seeking (acquire technology, knowledge, etc.).

Jain et al. (2016) found that when a firm wants to exploit their resources they internationalize with a market-seeking or resource-seeking reasons, whereas they are likely to explore new resources with an asset-seeking motive. Country-of-origin cluster has been taken as a strategy-seeking choice where firms are attracted to locate nearby firms from the same country (Mucchielli and Yu, 2011). However, some empirical studies show that these types of clusters are also attractive for firms with other investment reasons. Looking at 31 Spanish firms in China, Puig et al. (2017) found that manufacturing firms were more associated with clustered locations than trading-service firms were. More specifically, Shen and Puig (2017) evidenced that smaller Chinese investors in Germany, with a state background or those that seek market expansion (market seeking) tend to co-locate with their compatriots in the host country, while investors who seek strategic assets (strategic seeking) are more likely to tap into industry clusters. Therefore, it is not clear whether firms that go into country-of-origin clusters follow a single reason when entering that host market.

The Value of Country-of-Origin Clusters

As we have argued before, the influence of clusters on the generation and development of socialnetworks between firms is reasonable, since the social process of interfirm learning works best when partners are close enough to allow a frequent interaction and real exchange of information. Cooperation finds in clusters a proper space for its development, since it is within that context where the basic conditions for its existence are met (geographical and/or cognitive proximity). Social networks and connections are especially useful for cases in which internationalization needs a high degree of mutual trust among the partners (Chang and Park 2005). An efficient functioning of the network limits the coordination cost and minimizes the risk of opportunistic behavior. Thus, geographic proximity, along with the interaction and cooperation, makes these networks generate information and knowledge externalities for their members (Guillén 2002).

As Breschi and Malerba (2005) distinguish, agglomeration drivers for any given sector are location specific and generate agglomeration benefits due to dynamic increasing returns to concentration (e.g. ex ante “intrinsic” differences across territories and cross-sectoral spillovers that cumulatively act upon the existing concentration patters). On the other hand, agglomeration drivers that are entirely sector specific could promote concentration across all territories (e.g. thanks to economies of agglomeration forces that are intrinsically related to the way knowledge is accumulated, innovations are generated).

So, if clustering and networking are so efficient, why have some clusters disappeared and why have some initiatives based on that relational model failed? We think that this is because there are different types of clusters that can bring different types of advantages to international companies. There are inter and intra-cluster differences due to the life cycle of the sector, the absorption capacity of the companies or the characteristics of its participants, which allow to identify a wide and diverse range of combinations and evolutionary stages. For example, if we accept that a Colombian textile cluster will differ from an Italian one due to their different competitive environment (size of companies, customers, suppliers, etc.), and that, due to their differences in origin, a cluster of Chinese compatriot firms in Germany will differ from a cluster of Spanish compatriots in China, then we could accept that a cluster initiative will not have the same effect on all the member firms, as they differ in terms of their abortion capacity or experience, among other factors.

Investors who enter for the first time in a market, and on their own, experience a greater degree of marginality and face more difficulties. In addition, the more tacit the shared knowledge of the network is, the more important the geographical and cognitive proximity will be. For example, as argued by Belderbos and Zou (2009), imagine a group of Japanese companies that decide to establish in India. New investors will have a greater need for local knowledge than those already there. This need will drive them to look for a country-of-origin or ethnic agglomeration. After the initial stage of the activity, an intense social process that is fostered by a shared culture among all these companies will be developed.

In other words, proximity facilitates formal and informal interaction, facilitating the information exchange and potential collaboration (Larson 1992). The value of these networks is the differential between benefits and costs. The benefits can be related to information externalities, reduction of consumer search costs, increased reputation, knowledge and information spillovers or specialized labor and infrastructure (Tan and Meyer 2011). Costs on the other side could be derived from congestion and competition in input and output markets within the cluster (Henderson 2003). However, as we have previously argued, these aspects could be moderated by the strategic reasons of the firms when entering a new market.

Research Methodology

Data was collected through questionnaires and constant emails and visits to the companies in China from March to June 2013. The researcher also spent time with the expatriates during lunch, spare, and traveling time. This is part of a broader research where other areas were also analyzed (challenges faced in China, social capital generated in country-of-origin clusters, etc.). It is important to mention that conducted a pilot study that helped redefine the questionnaire in order to increase its validity.

The sample used for the analysis is formed by 24 subsidiaries: 12 subsidiaries in MKIP (Mondragon Kunshan Industrial Park), 4 subsidiaries in KGIP (Kunshan German Industrial Park), 3 subsidiaries to enter MKIP in 2013, and 5 Basque isolated subsidiaries located in the same city. All the subsidiaries are SMEs that established in Kunshan from 2005 to 2013. In terms of the activity, 96% of the firms are industrial, 87% are related to manufacturing, and 57% to machinery, equipment, furniture, and recycling sector. Most of the subsidiaries analyzed are subsidiaries that are or will be located in industrial parks. Most of the firms are small (62%) and 54% of the firms are on rented facilities. In terms of size, the factories/offices are of less than 5000 square meter and with more direct than indirect workers. Half of the subsidiaries of the sample entered in China due to market-seeking reasons, 21% due to resource and efficiency-seeking reasons, and the rest due to a combination of strategic, market, and resource-seeking motives. It is important to highlight that all the subsidiaries are WFOEs or greenfield investments.

To analyze the value of the country-of-origin cluster as a platform, we have used different variables related to the location, reasons of establishment in China and externalities.

Given that there is no single technique to define when a firm is located in a cluster or not (Alcácer and Zhao, 2016), we decided we could measure the firms’ belonging to a cluster. Then, with visual mapping techniques, this information was contrasted. As a result of it we define the location mode as:

  1. 1.

    Co-located: subsidiaries that are located inside an industrial park (cluster) where they have a membership status.

  2. 2.

    Isolated: subsidiaries that are not members of any industrial park.

Some prior studies have shown that the reason of establishment has a significant impact on MNEs’ location preference (Alcácer and Chung, 2013). Following these authors, we distinguished two types of investment motivations in the sampled firms: production/manufacturing or efficiency seekers (coded as 1) and trading/services or market seekers (coded as 2). The reason makes reference to the availability of resources or to costs factors that facilitate economies of scale and scope. The latter includes activities related to overseas market expansion, either by wholesaling or retailing products or services, and other sales-support activities. A third category was created for those firms with a mixed objective for their investments, taking the value of “3,” implying the double motivation of seeking efficiency and markets. Therefore, we distinguished:

  1. 1.

    Firms searching for cheaper or more available productive factors (resource seeking).

  2. 2.

    Firms searching for market expansion or following the clients (market seeking).

  3. 3.

    Firms with mixed reasons for their investments, implying a double motivation of seeking efficiency as well as markets.

Given that externalities are multidimensional constructs, we have measured the cluster effect by using six areas of analysis, based on different authors in the literature. Besides, we used Cronbach’s Alpha and item-total correlations to check the reliability of the scale and improve the quality of those constructs.

  1. 1.

    Local market knowledge and resources (LMK): this area considers factors such as the knowledge about the establishment process and to surpass country entry barriers, about how to adapt and transform the management routines and business practices to the local setting, or knowledge about the legal environment or local culture (Tan and Meyer, 2011).

  2. 2.

    Industry-specific knowledge and resources (ISK): this area includes factors such as the knowledge about the industrial forecast or technology trends, the suppliers’ behavior, the capacity to find specialized goods and labor, or the access to productive inputs (Makino et al., 2002).

  3. 3.

    Legitimacy and reputation (LEG): this area considers different types of legitimacy (normative, pragmatic, and cognitive), the knowledge on how to achieve local legitimacy, or the firms’ visibility and representation (Lin et al., 2009).

  4. 4.

    Networking and social interaction (NET): this area considers factors such as the access to tacit knowledge, the cooperation on social and professional activities, or the capacity to surpass the liability of outsidership (Chung and Tung, 2013).

  5. 5.

    Market conditions (MARK): this construct embraces variables related to customers, competitors, knowledge about the customers or access to new sales opportunities and business partners (Almeida and Kogut, 1997).

  6. 6.

    Costs (COST): this last area considers the cost of transportation, transaction costs, qualified workers, infrastructure, or financial resources among others (Tan and Meyer, 2011).

The question given to the interviewees to analyze the perceptions was: To what extent does your localization mode (co-located or isolated) positively influence the following factors. We used a Likert scale of 5 point to collect the responses (1 not at all/2 limited extent/3 not sure/4 certain extent/5 large extent).

As the aim was to analyze the association between the cluster effect variables and the co-location mode of the firms or their entry reasons a comparison of means was used to identify and visualize the relations between variables.

Research Findings

Table 6.2 presents the correlations between variables. The correlations between the variables were generally not lower than 0.5, which indicates that there were no serious problems of multicollinearity (Hair et al. 2006), except for justifiable reasons the ones between collocation and NET (0.56), ISK (−0.51), and COST and LEG (0.59).

Table 6.2 Descriptive statistics and correlation coefficients
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Table 6.3 shows the average values and standard deviations of externalities classified by the localization mode and entry reason, as estimated with SPSS-20. The average values give us an indication of how the perceptions about those externality dimensions are evaluated, and the standard deviation values indicate the agreement level of the managers’ perceptions.

Table 6.3 Average punctuations by type of subsidiary
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In general and on an average, none of the factors seems to be very relevant for the firms, which make us think that the location may not be the only factor to explain the externalities gained by the firms. The factor that, individually analyzed, has been punctuated more positively has been NET (3.60) and the lowest factors is MARK (2.21). In a context like China, this might be explained by the fact that the tacit knowledge about how to operate in the country and the support that a firm obtains from other firms and managers are more important than other market related reasons, especially when firms (in this case European subsidiaries) have not much experience in the market.

On one side, in terms of the location mode of the subsidiaries in China, we observe that the factors that were more positive and differently evaluated by two types of location mode were those related to NET (3.53). Moreover, if we analyze other values of isolated firms, we can observe that the higher values are on ISK (3.70) and MARK (3.13). It is remarkable that the isolated firms have a quite high consensus (standard deviation of 0.87) in how their isolated location does not contribute to gain externalities on networking (2.12). Figure 6.1 shows graphically these results.

Fig. 6.1
A radar chart depicts results of co located and isolated of Chinese subsidiaries based on location. There is a hexagon with corners labeled, L M K, I S K, LEG, NET, MARK, and COST. For isolated firms, the values are higher for I S K and MARK at 3.7 and 3.13, respectively. For co located firms, the value is highest for NET at 3.5. The values are approximated.

Externalities by location mode. (Source: Own elaboration)

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On the other side, when studying the externalities by the entry reasons, we notice at least two important aspects: (1) on an average the higher values for the externalities are from firms seeking mixed reasons in China (market and efficiency) and (2) that the highest punctuations are on NET for market-seeking firms (3.44), and NET (3.40) and LEG (3.52) for mixed entry reason. Besides, it should be noted that although firms with mixed entry reasons have higher positive effects on most of the dimensions, industry-specific knowledge and resources (ISK) is higher for resource-seeking firms (Fig. 6.2).

Fig. 6.2
A radar chart depicts results of market, resources and mix based on entry reason. There is a hexagon with corners labeled, L M K, I S K, LEG, NET, MARK, and COST. For Market, the value is highest for NET at 3.5. For resources, the value is highest for L M K at 3. For Mix, the value is highest for LEG at 3.5. The values are approximated.

Externalities by entry reason. (Source: Own elaboration)

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Our results extend the previous work done on the net effect of agglomeration by nationality on innovation (Kim, 2014) by classifying the clustering effect into different and various areas such as networking, industry-specific knowledge or legitimacy. Besides, this research argues, that the co-location status or entry reasons of the firms can also influence these perceptions. Moreover, it is important to notice that firm’s entry reasons also influence diverse opinions on how their location mode provides market benefits. As compared to market-seeking firms, those that enter seeking resources or have mix reasons to enter that market tend to perceive higher significant benefits on market factors. Specifically, market-seeking firms have lower benefits on legal knowledge, the speed of reaction to the market and competitors, or higher cost of qualified workers. Resource-seeking firms get less personal support but higher market knowledge or lower costs of qualified workers. On the other hand, firms with mixed entry reasons have higher benefits on legal knowledge, personal support, speed of reaction, or market knowledge. This is a remarkable finding that relates the entry reasons with externalities. Considering the current managerial concerns about the cost increase in China, cost factors could be the crucial element that makes firms prefer isolated location modes in the future. However, as firms increase their willingness to tap the local Chinese market, they would also look for areas with high connectivity, so both situations can act as centrifugal and centripetal location factors.

To summarize, we can say that co-location per se does not have a positive or negative influence on subsidiaries, but that influence depends on the strategic motives why firms entered in China and the expectations of their investments there. These factors have shown that a heterogeneity exists regarding the benefits of the country-of-origin clusters and the perceptions of the managers.

Conclusions

To face globalization and the liberalization of markets, business cooperation through clustering is essential, especially for the internationalization process of SMEs. As interactions within these clusters can be diverse in nature (formal, temporary, collaborative, etc.), pursue different objectives, and adopt different modalities, we propose that those platforms adopt different modalities: cluster initiatives, country-of-origin clusters, and sectorial clusters. In these interorganizational geographic networks firms are simultaneously interconnected productively, socially, and commercially in origin and destination, and through different types of interactions. In other words, these organizational realities act as platforms for internationalization.

In this work, we argue that country-of-origin clusters in emerging countries can be studied as a platform of relationships that provide the key resources (tangible and intangible) necessary to meet the challenge of internationalization of SMEs successfully. However, due to their origin and participants, we also believe that there is a heterogeneity in the role played for the clustering, which needs further research on organizational (the entrepreneur, the size, etc.), informational (needs), and institutional (host country) issues that characterize these clusters.

From the analysis made we can say that the country-of-origin cluster is perceived as a strategic asset that gives members access to information, resources, markets, and knowledge. Specifically, the co-location is providing the members with externalities related to market and host country knowledge, fostering information sharing about suppliers, financial conditions, HR practices, IP protection methods, legal issues or bureaucracy. They relate proximity and daily interaction (informal meetings, etc.) with the exchange of tacit knowledge (based on experience). Member companies find it important not only the geographic proximity but the social and cognitive proximity. In other words, our study suggests that the role of clustering and the value of the location on externalities are bigger in the dimensions of networking and for the companies established for mixed or various reasons (seeking efficiency as well as markets). However, opposite to what we expected, we could not validate that a general higher positive perception is associated to co-located firms. This could be due to some limitations derived from the size of the sample or the methodology used. We also need to acknowledge the limitation of collecting data from a single manager (the general manager of the subsidiary).

Summarizing, while the research on socialnetworks and multinational SMEs is still scarce on the IB literature, our research offers a new insight suggesting that the country-of-origin cluster may contribute positively in the internationalization in distant markets (China). From a practical point of view this research helps firms to take decisions regarding the location mode that allow them reduce risks and share knowledge key in the process. At a political level, the research can enlighten the design and implementation of policies by stimulating the geographical clustering and facilitating the creation of these types of business agglomerations abroad.