International Innovation Alliances: A Case Study of the Influence of Proximity in the Aviation Sector

External sources of knowledge become important complements to the company's internal knowledge base and thus become a critical factor for the development of innovation (Chesbrough, 2003; Hagedoorn & Duysters, 2002). Thus, open strategies enable organizations to access wide varieties of specialized knowledge in order to compete innovatively (Chesbrough, 2003). Accessing technological knowledge through R&D alliances can help companies reduce time to market, in addition to the development of innovations that would be impossible to achieve internally (Narula, 2002).

Tourism and hospitality supporting companies already recognize technological innovation as a way of activating Tourism 4.0. These companies are subject to rapid changes and strategic alliances, especially for resource sharing, which appears to be decisive for improving competitiveness and achieving competitive advantage (Parng & Chen, 2014). For these authors, the benefits of strategic alliances include conserving resources, sharing risks, reducing product development costs and, in particular, improving technological capabilities (Zhang & Lu, 2010; Guido & Franco, 2003).

Despite the benefits, R&D alliances carry risks. Therefore, it can be said that tension exists between sharing and protecting knowledge, leading to other paradoxes, such as a preference for geographically close or distant partners (Martínez-noya & Narula, 2018). However, would it not be a short-sighted view to analyze the relationship of the partners limited only to the spatial aspect? There are other aspects of proximity that also influence interorganizational relations, from knowledge exchange to innovation, such as cognitive, organizational, social and institutional proximity (Boschma, 2005; Knoben & Oerlemans, 2006).

Nevertheless, little is known about the degree of proximity in alliances most likely to maximize innovation (Martínez-Noya & Narula, 2018); since in situations of low proximity between partners, there may be problems of coordination, communication, and even conflicts (Mattes, 2012). As a result, studies on the topic suggest the existence of inter-relational offsetting effects between types of proximity (Boschma, 2005; Hansen, 2015; Huber, 2011). In other words, the different dimensions of proximity are interconnected in order to achieve innovation results, as distance in one type of proximity can be compensated by the existence of another in a different dimension.

Moreover, the desired proximity characteristics may depend on the intended motivations of the partnerships (Hansen, 2014). Exploitative innovation-oriented strategies reinforce existing knowledge and seek to respond to current market conditions by adapting technologies and meeting customer needs. Exploratory innovation challenges organizational learning and aims to respond to environmental trends, creating innovative technologies for new markets (Lubatkin, Simsek, Ling, & Veiga, 2006). Indeed, it is to be expected that there are persistent tensions between exploration and exploitation. This paradox leads us to reflect on whether the antecedents of innovations are neither totally different nor absolutely integrating—that is, the same antecedents can work differently for exploration and exploitation (Liu, Wang, & Li, 2019).

The conception of this research is based on innovations that have transformed the provision of tourism services through improving digital platforms and consumer travel experiences. We intend, therefore, to contribute to advancing the discussion of international innovation alliances, which are recurrent open strategy models (Eisenhardt & Martin, 2000) and characteristic approaches of geographically distant partners. Furthermore, this paper may contribute to the changes inherent to and imposed by the current Covid-19 pandemic. In a global context, in which everyone has been forced to remain physically distant, understanding proximity behaviour can encourage the maintenance of collaboration strategies.

Thus, we propose to answer the following question: What type of proximity compensate geographical distance for different innovation results in international alliances? As a way of looking at this, our specific objectives are to investigate: i) which types of proximity are related to exploration innovation; ii) which types of proximity are related to exploitation innovation and, finally; iii) how companies in the airline sector offset geographical distance to achieve innovation.

In order to achieve our objective, using an exploratory qualitative method, we selected two case studies that operate in the aviation market and implement open technological advancement strategies (Brossard & Gres, 2007). In addition, for the selection of the cases, the difference in innovation strategy was considered, which made it possible to analyze the proximity in the light of exploration and exploitation orientation. Finally, we emphasize offsetting mechanisms for non-spatial proximity, which is missing from the literature, as the focus of most studies is geographical proximity (Steinmo & Rasmussen, 2016).

The typology proposed by Boschma (2005) has gained great importance among researchers and has been considered the most complete (Hansen, 2015). The model proposes that, in addition to the geographic aspect, cognitive, organizational, social and institutional proximity can impact exchange of knowledge and innovation (Boschma, 2005; Broekel & Boschma, 2012).

Cognitive proximity can be defined as similarities in the way the actors perceive, interpret, understand and evaluate the world (Nooteboom, 2000); in other words, they share the same knowledge and experience base and can learn from each other, facilitating communication and effective integration (Boschma, 2005). Furthermore, cognitive overlap is needed in order to transfer or create new knowledge between allies. In this sense, cognitive proximity is likely to increase knowledge transmission, in which the partners’ knowledge base expands and overlaps (Balland, Boschma, & Frenken, 2015).

Oerlemans and Meeus (2005) define organizational proximity as actors who belong to the same space of relationships; Torre and Rallet (2005) define it as actors whose interactions are facilitated by rules, routines, and behaviour and who share the same system of representations or set of beliefs. Similarity of organizational purposes, functions and experience are also characteristics of this dimension (Steinmo & Rasmussen, 2016). According to Boschma (2005), organizational proximity is defined as the extension of relationships in an organizational arrangement, both intra and inter-organizational, thus involving the autonomy and degree of control that can be exercised in the arrangements.

Institutional proximity describes the extent of norms, habits, rules and laws between economic agents, involving both formal and informal institutional aspects (Knoben & Oerlemans, 2006). Thus, the notion of this dimension includes the idea of organizations which shares the same institutional rules and set of cultural habits and values (Boschma, 2005). Institutional proximity, therefore, is also considered as cultural proximity, which has two levels: the first level responsible for examining cultural differences between countries, nations or regions; the second level focusing on differences in organizational culture (Knoben & Oerlemans, 2006).

In essence, economic relations are, in a way, always incorporated in a social context. Social proximity, in turn, is denoted as personal or relational proximity between peers (Schamp, Rentmeister, & Lo, 2004). Such a dimension exists when there is trust based on friendship, kinship and previous experience between the actors (Boschma, 2005). In the meantime, we emphasise that both organizational and social proximity are characterized by strong ties between partners, although different mechanisms are involved (hierarchy and trust, respectively).

Finally, geographical proximity, the most commonly discussed dimension in the literature, denotes territorial, spatial, local or physical proximity between agents (Knoben & Oerlemans, 2006). The geographical dimension can be measured by absolute distance, distance relative to the means of transport (travel times) or how these distances are perceived by the actors (Balland et al., 2015; Knoben & Oerlemans, 2006; Torre & Rallet, 2005). Such a notion implies, therefore, that the actors do not need to be constantly geographically close, since meetings, short visits and temporary presence at the location may be sufficient for the actors to overcome this distance.

In general, as a way of understanding how each dimension impacts innovative performance, we can conclude that although the proximity is essential for agents to connect and exchange knowledge, too much proximity, in any dimension, can harm innovative performance (Boschma & Frenken, 2010). Such a paradox leads us to reflect whether there is an interrelation between dimensions, in which distance in one dimension can be compensated by proximity in another. The compensation mechanism occurs when the distance in one dimension is offset by at least one other dimension (Huber, 2011).

From this perspective, certain studies have been conducted looking for evidence of the interrelationship of types of proximity (Capaldo & Petruzzelli, 2014; Fitjar, Huber, & Rodríguez-Pose, 2016; Hansen, 2015; Huber, 2011). Preliminary results suggest the existence of interrelational effects of compensating between the types of proximity, although they are not specified. Subsequently, it was found that organizational proximity can compensate geographical distance (Capaldo & Petruzzelli, 2014) and cognitive, in turn, replaces geographical distance in collaborative projects for innovation in the clean technology industry (Hansen, 2015). The studies emphasize the relevance of proximity to the results of innovation in collaborative alliances; however, there is little literature that considers both dimensions of proximity and its results for innovation (Hansen, 2015). Therefore, it is worth reflecting on this in more depth, which we do in the next topic.

The literature on innovation is longstanding and organizations’ capacity for innovation is recognized as a determining factor in survival and achieving business success (Wang & Ahmed, 2004). Generating innovative results depends critically on the ability to integrate, build, and reconfigure internal and external skills to deal with rapidly changing environments (Teece, Pisano, & Shuen, 1997), that is, the ability to manage differences.

We cannot speak of innovation without considering learning, since innovation is combining existing knowledge or creating something new (Mattes, 2012). Exploration and exploitation are distinct forms of learning (March, 1991).

In the ambit of innovation technology, Benner and Tushman (2003) argue that exploitative innovation involves improvements to components or architecture within an existing technological trajectory in the organization; exploratory innovation involves adopting a different technological trajectory. Exploration innovations are radical proposals requiring new knowledge, starting from a company's existing knowledge base and, therefore, offering fundamentally new products (Jansen, Vera, & Crossan, 2009; March, 1991). Exploitation innovations are incremental, based on existing knowledge, thus expanding the company's knowledge base and thereby improving established products without changing the basic nature of skills, processes, and structures (Jansen et al., 2009; March, 1991).

It has been already recognized that collaborating with other institutions facilitates learning, as well as enabling access to new knowledge (exploration) and leveraging existing knowledge (exploitation) (Kauppila, 2010); however, they depend on different structures, processes, strategies, capacities and culture (He & Wong, 2004). Despite advances in this area of research, there are still no studies seeking to discover the influences of types of proximity between partners for the different exploration and exploitation alliances (Geerts, Leten, Belderbos, & Van Looy, 2018). Therefore, understanding the influence of types of proximity on types of innovation results can contribute to advancing the topic of proximity and innovation alliances, which this work does.

The methodology used is qualitative exploratory, since analysis of the influence of the types of proximity on the different innovation results is a subject that has not been widely explored, enabling us to present a series of proposals for future investigations. To validate the study and ensure greater credibility, the method adopted was the case study. Following Yin's case study methodology (2010), a protocol was developed with sufficient conditions, mentions, and procedures for the study to be replicated. Data was collected through interviews, document analysis, and secondary sources of information (e.g., scientific articles conducted with companies, reports, public interviews and institutional websites).

The interview script was prepared based on a literature review and was divided into four parts: i) contextualization of the company: in which information on the organization's history was addressed and confirmed; ii) context of the alliance: based on the choice of the most significant innovation partner in the last three years, we investigated the history of the partner, main motivators, results, evolution of relationships and challenges; iii) proximity: in which the respondent's perception of each dimension of proximity and their interrelations was identified and, finally; iv) partnership innovation results.

To achieve the aim of this research, it was deemed necessary to look for cases of companies operating in sectors recognized for technological advances and for open strategies for access to knowledge. Thus, aircraft design and software technology companies were selected, which are sectors of high technological intensity, according to the OECD (2016). Moreover, in order to ensure comparative effect, one of the selected cases has a clear strategy for exploration innovation and the other one for exploitation innovation. Another criterion for choosing the cases was that they carried out alliances with partners from countries other than the countries of origin of the companies, that is, those that were geographically distant. Innovation alliances were analyzed as a research unit, rather than the company as a whole, as conducted by Steinmo and Rasmussen (2016). Regarding the technological competitiveness of companies in developing countries, such as Brazil, this will increasingly depend on companies’ ability to access external knowledge, since the lack of an environment conducive to innovation in the country of origin motivates internationalization (Santos, 2006). In view of the above, it is valid to compare companies from countries with different stages of internationalization, market dimensions, and geographic positioning, that, despite the differences, need to seek competitive strategies beyond their borders.

The data were collected between 2018 and 2020. Employees were interviewed from companies with direct knowledge of both geographically distant partners and the innovative results obtained. At the Portuguese company AlmaDesign, we interviewed the owner and the main collaborator, who owns a small part of the company. At the Brazilian company Monitora Soluções, two project managers and one of the owners were interviewed. Secondary data sources were also used, such as company websites, project performance reports, journalistic reports related to companies, institutional presentations, and academic articles.

Finally, the data processing started with transcription of the recorded interviews in full. Soon thereafter, the data were interpreted, aiming to find broader meanings contemplated in the responses obtained and to link them to other knowledge. Suported by Nvivo software, we codified the data. Twelve categories were created: proximity (cognitive, social, organizational, institutional and geographical); distancing (cognitive, social, organizational, institutional and geographical); innovation (exploration and exploitation). After defining the main categories, we started coding the interview transcripts, intending to identify the “units of thought,” words, lines or passages that represented a fundamental idea or concept of the category. The data collected in the companies’ dossiers were also categorized. Finally, the content analysis methodology was used, which, through the objective and systematic description of the content of the messages, aims to interpret communication and information (Bardin, 2011). We analyzed the contents of the data collected at two levels: first, we considered the content manifested in the text, which can be more easily captured and revealed; second, we sought to identify the latent content, which includes deeper embedded meaning. The results are presented in the next section.

Based on analysis of the case study, some propositions can be established. Firstly, the importance of social proximity for beginning the partnership is highlighted, regardless of the expected innovation result (exploit or explore). As already highlighted in the literature, the existence of previous collaborations (Balland, De Vaan, & Boschma, 2013; Steinmo & Rasmussen, 2016), previous work relationships (Broekel, 2015) or, social interactions with people who work at the partner company (Fitjar, Huber, & Rodríguez-pose, 2015) are forms of social proximity.

Both companies analyzed highlighted that the partnership started from a previous social contact, and there, a certain degree of friendship was established between the owners and other decisive people for the partnership to be formalized. Thus, the first proposition highlights the importance of social proximity for establishing the alliance. It is also noteworthy that active participation in fairs, dissemination of innovation results and previous professional experience enable social bonds to be created and the alliance to emerge.

The results lead us to conclude that it is not necessary to be close in all dimensions to achieve innovation results, as distance in one dimension can be compensated by proximity in others. This study sought to investigate the influence of types of proximity on the different innovation results between international alliances of aviation companies, which are important to support tourism.

Based on the findings, we concluded that the proximities change depending on the type of innovation aimed at by partners. For exploration innovation, cognitive and institutional proximity stand out, while for exploitation innovation, it is cognitive and organizational proximity. We also highlighted that cognitive proximity is known to have a strong influence on the performance of any alliances. This is due to the technical similarities of the companies, which allow understandings between the parties, at the same time that it is possible to access complementary skills. Institutional proximity was essential for alignment between the values and behavior of those directly related to the project in exploration innovation alliances. On the other hand, in exploitation alliances, the organizational proximity played an important role. Additionally, when there is a certain degree of hierarchy in relationships, we noted an alignment which encourages cooperation between individuals and achievement of exploitation results.

Another result is regarding social proximity, which plays a fundamental role at the beginning of the alliance. Moreover, we identified cognitive proximity as a mechanism for offsetting geographical distance, seeking complementarity and overlapping to achieve different results. Finally, we observed that the strength of geographical proximity has minimized success in inter-organizational relations, due to advances in information technology facilitating contact and, also, due to the nature of the research, since for innovation in the high technology sector, the most important thing is to access cutting edge knowledge regardless of the partner's location.

These results are preliminary, and future research is needed to advance understanding of the topic and overcome research limitations. One of the limitations of the study is analysis of only one case per country, as it is an intentional sampling, not allowing generalization of the results; therefore additional investigation must consider research methods that can expand our exploratory findings. Thus, we suggest that other cases should be analyzed in order to add to the results found in the present research. It is also suggested that longitudinal studies may be carried out in order to understand the dynamics of types of proximity over time.