Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems : Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence

sustainability Article Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence Yuzhuo Cai 1,* , Borja Ramis Ferrer 2and Jose Luis Martinez Lastra 2 1Faculty of Management and Business, Tampere University, 33014 Tampere, Finland 2Faculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, Finland *Correspondence: [email protected] Received: 5 July 2019; Accepted: 21 August 2019; Published: 26 August 2019   Abstract: This paper presents a potential solution to fill a gap in both research and practice that there are few interactions between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems. To strengthen the synergies between TIC and TUC for innovation, the first step is to match suitable industrial firms from two countries for collaboration through their common connections to transnational university/academic partnerships. Our proposed matching solution is based on the integration of social science theories and specific artificial intelligence (AI) techniques. While the insights of social sciences, e.g., innovation studies and social network theory, have potential to answer the question of why TIC and TUC should be looked at as synergetic entities with elaborated conceptualization, the method of machine learning, as one specific technic offAI, can help answer the question of how to realize that synergy. On the way towards a transdisciplinary approach to TIC and TUC synergy building, or creating transnational university-industry co-innovation networks, the paper takes an initial step by examining what the supports and gaps of existing studies on the topic are, and using the context of EU–China science, technology and innovation cooperation as a testbed. This is followed by the introduction of our proposed approach and our suggestions for future research. Keywords: transnational industry cooperation; transnational university cooperation; transnational innovation ecosystem; EU–China; science, technology and innovation cooperation; transdisciplinary approach; artificial intelligence; machine learning 1. Introduction While there is growing awareness of the role of digital technologies in transforming organizations and social relationships [ 1 ], the new economy (called platform economy or digital platform economy) based on digital technologies is changing the nature of globalization [ 2 ], in which the focus has been shifted from countries (globalization 1.0) and companies (globalization 2.0) to individuals and groups (globalization 3.0) [ 3 ]. The involvement of individuals or citizens in multi-faced social life is crucial in sustainable development [ 4 – 6 ] in ecological, social, and economic dimensions [ 7 ]. In this paper, we try to bring interactions of key actors in transnational innovation processes, previously mainly explored through social science approaches, into the digital domain, applying some specific artificial intelligence (AI) technologies, i.e., machine learning and knowledge representation and reasoning. Our focus is on the relations between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems (see more descriptions about the concept of transnational innovation ecosystem in the following section), which share basic assumptions of Sustainability 2019,11, 4633; doi:10.3390/su11174633 www.mdpi.com/journal/sustainability Sustainability 2019,11, 4633 2 of 23 sustainability and globalization 3.0. TIC is concentrated on joint research and development (R&D) and co-production; TUC is mainly concerned with academic research collaboration. The research problem of TIC and TUC synergy building, as described below, has emerged in the context of innovation studies and their adjacent fields. We try to resolve the problem by integrating relevant studies in social sciences (in the fields of innovation studies, higher education research and international relations with respect to EU and China) and AI technologies (i.e., machine learning and knowledge representation and reasoning). The literature of innovation studies, which conceptualizes reciprocal relations and proactive interactions between universities, industry, government and citizens for promoting innovation [ 8 , 9 ], stresses the importance of synergy building between cross-sector organizations. Particularly, university and industry (U–I) interactions constitute a core area in innovation studies [ 10 ]. While the innovation processes are becoming globally interconnected [ 11 – 14 ], there is also an urgent demand to extend cross-sectoral organizational synergy building to the transnational context. For instance, it has been evidenced, though mainly in the industrial context, that technological capabilities for innovation are dispersed in international innovation networks [ 15 ] and the degree of R&D internationalization is increasing [ 16 , 17 ]. Thus, actors from both university and industry sectors, as key contributors to technological capabilities and R&D, are likely to become international [13]. However, academic research is far behind the needs for further integration between TIC and TUC arising from the practices of transnational STI cooperation. Although one widely shared view in innovation studies is that universities have a prominent role in the national or regional innovation system, e.g., through co-creation partnerships with industry [ 8 , 18 , 19 ], the research of U–I cooperation in transnational contexts is rare in the literature. For instance, in their literature review of U–I international knowledge transfer, Govind and Küttim [ 20 ] only found 26 articles (mainly in the fields of innovation studies and higher education research) meeting their search criteria in the Scopus and Web of Science databases. Amongst the 26 articles, U–I interactions in the transnational context are mainly seen in the form of universities from one country interacting with enterprises from another country, which is echoed in other literature e.g., [ 21 – 23 ]. Other studies deal with joint R&D between universities and branches of international companies e.g., [ 24 ]. The patterns of transnational U–I interactions examined in the existing literature can be illustrated in Figure 1. When innovation systems become global [ 25 ] or internationalized [ 26 ], international university cooperation could added value to the process [ 27 ]. Some rare studies e.g., [ 23 , 28 – 30 ] do touch upon the issues of how TUC could be aligned with and supportive of broader societal priorities and development goals in transnational contexts. However, there is a lack of profound exploration in this area, particularly from theoretical and methodological perspectives. In the context of transnational innovation networks, the interactions between TIC and TUC can be understood as synergetic entities or transnational U–I co-innovation networks (Figure 2). In such networks, new ideas and approaches from various internal and external sources are integrated in a platform to generate shared values [ 31 ]. The core elements of co-innovation include “collaboration, coordination, co-creation, convergence, and complementary” [32] (p. 361). Figure 2demonstrates that two industrial firms that are unfamiliar with each other, respectively from Country A and Country B, could be connected for potential collaboration by utilizing their common connections to existing university collaborations (especially individual collaborators) between the two countries. Although our focus is on how TUC can support TIC, once TIC and TUC synergetic entities are formed, the TIC would enhance the quality and value of TUC. Sustainability 2019,11, 4633 3 of 23 Sustainability 2019, 11, x FOR PEER REVIEW 3 of 27 Figure 1. Examples of transnational university and industry (U–I) interactions examined in the existing literature. When innovation systems become global [25] or internationalized [26], international university cooperation could added value to the process [27]. Some rare studies e.g., [23,28–30] do touch upon the issues of how TUC could be aligned with and supportive of broader societal priorities and development goals in transnational contexts. However, there is a lack of profound exploration in this area, particularly from theoretical and methodological perspectives. In the context of transnational innovation networks, the interactions between TIC and TUC can be understood as synergetic entities or transnational U–I co-innovation networks (Figure 2). In such networks, new ideas and approaches from various internal and external sources are integrated in a platform to generate shared values [31]. The core elements of co-innovation include “collaboration, coordination, co-creation, convergence, and complementary” [32] (p. 361). B Country A Country B U U I I UU U U I I I U: University; I: Industrial firm; B: An industrial firm’s brunch in another country Figure 1. Examples of transnational university and industry (U–I) interactions examined in the existing literature. Sustainability 2019, 11, x FOR PEER REVIEW 4 of 27 Figure 2. The transnational industry cooperation (TIC) and transnational university cooperation (TUC) synergetic entities (or transnational U–I co-innovation networks) to be tackled in our research. Figure 2 demonstrates that two industrial firms that are unfamiliar with each other, respectively from Country A and Country B, could be connected for potential collaboration by utilizing their common connections to existing university collaborations (especially individual collaborators) between the two countries. Although our focus is on how TUC can support TIC, once TIC and TUC synergetic entities are formed, the TIC would enhance the quality and value of TUC. Compared to existing studies on U–I interactions in transnational context (Figure 1), our investigation of U–I co-innovation networks (Figure 2) is novel in two aspects. First, although the subject of university and industry interactions in transnational context is not new in research, our study is different to existing approaches by discovering unobvious/hidden links between TUC and TIC. When links are hidden, it means that the links are unobvious or the data revealing the links are scarce or not apparent. Second, when it comes TIC, we not only look at existing collaboration of industrial firms across countries as examined by current studies, but specifically explore how missing links between potential transnational industrial partners could be bridged through utilizing the hidden links. The dash lines in Figure 2 represent either hidden or missing links that are rarely examined in the existing studies but will be the focus of our proposed approach. Missing links demonstrate that the actors with potential for reciprocal collaboration are not connected. However, the actors can be connected by leveraging the hidden links. Third, while current research related to the topic are mainly in the field social science studies, we seek an approach integrating insights of both social sciences and AI technology. The lack of interaction between TIC and TUC is also seen in the practices of transnational science, technology and innovation (STI) cooperation. For instance, as indicated by the first author’s recent interviews of actors involved in EU–China STI cooperation, in the EU–China context, when European high-tech firms, especially smalland medium-sized enterprises (SMEs), seek Chinese counterparts for cooperation, they normally go directly to the industry sector, sometimes through business brokers. As a result, the Chinese partners that first appear to them are not necessarily the most suitable ones. This could be explained by three causes. First, the business brokers, e.g., consulting companies or governmental business promotion agencies, have a limited pool of Chinese companies as candidates to be matched with European SMEs. Second, when matching collaborators, human decisions are often subject to the “homophily principle”—a tendency in which people form ties with I Country A Country B U I I UUU I I I U: University; I: Industrial firms Unobvious/hidden links Unobvious/hidden links Missing links Figure 2. The transnational industry cooperation (TIC) and transnational university cooperation (TUC) synergetic entities (or transnational U–I co-innovation networks) to be tackled in our research. Compared to existing studies on U–I interactions in transnational context (Figure 1), our investigation of U–I co-innovation networks (Figure 2) is novel in two aspects. First, although the subject of university and industry interactions in transnational context is not new in research, our study is different to existing approaches by discovering unobvious/hidden links between TUC and TIC. When links are hidden, it means that the links are unobvious or the data revealing the links are scarce or not apparent. Second, when it comes TIC, we not only look at existing collaboration of Sustainability 2019,11, 4633 4 of 23 industrial firms across countries as examined by current studies, but specifically explore how missing links between potential transnational industrial partners could be bridged through utilizing the hidden links. The dash lines in Figure 2represent either hidden or missing links that are rarely examined in the existing studies but will be the focus of our proposed approach. Missing links demonstrate that the actors with potential for reciprocal collaboration are not connected. However, the actors can be connected by leveraging the hidden links. Third, while current research related to the topic are mainly in the field social science studies, we seek an approach integrating insights of both social sciences and AI technology. The lack of interaction between TIC and TUC is also seen in the practices of transnational science, technology and innovation (STI) cooperation. For instance, as indicated by the first author’s recent interviews of actors involved in EU–China STI cooperation, in the EU–China context, when European high-tech firms, especially smalland medium-sized enterprises (SMEs), seek Chinese counterparts for cooperation, they normally go directly to the industry sector, sometimes through business brokers. As a result, the Chinese partners that first appear to them are not necessarily the most suitable ones. This could be explained by three causes. First, the business brokers, e.g., consulting companies or governmental business promotion agencies, have a limited pool of Chinese companies as candidates to be matched with European SMEs. Second, when matching collaborators, human decisions are often subject to the “homophily principle”—a tendency in which people form ties with similar others [ 33 ]. Selecting a “friend of a friend” helps strengthen existing social clusters [ 33 ], but does not help to reach those unknown communities and individuals [ 34 ], who could potentially contribute to innovation [ 35 ]. Third, although one may notice the limitation of professional social matching based on human decisions, it is difficult to find suitable tools and data to resolve the problem [34]. Our proposition is that European and Chinese industrial firms can be best matched through their connections to existing university cooperation between both sides. In so doing, transnational U–I co-innovation networks are formed, which are crucial for enhancing the performance of EU–China STI cooperation. This has also been implied by the interviews mentioned above. Now there is a great opportunity to exploit EU–China university cooperation to support EU–China industry cooperation, because EU–China higher education cooperation has reached an unprecedented level, demonstrated by not only a large scale of student/staffexchange but also increasingly deeper research collaboration and joint education programs [ 30 ]. For instance, there were 383 participating institutions from China in 274 projects in the EU’s Seventh Framework Program (2007–2013). Although China is no longer considered to be a beneficiary country in the Horizon 2020, the Chinese Ministry of Science and Technology provides co-funding to support Chinese research organizations involved in the EU’s Horizon 2020 projects. In the Web of Science database, the number of co-authored publications between Chinese and European authors has increased from 12,669 in 2011 to 35,218 in 2018. The EU–China context is used as a testbed for three reasons. First, there is huge potential for STI cooperation between the EU and China. Second, the scales of both higher education and industry in the EU and China are tremendous, which provide abundant data for testing and application. Third, since the EU and China have different, sometimes contrasting, social structures and value systems, if we can find effective solutions to build TIC and TUC synergies in EU–China STI cooperation, the approach is likely to be applied (with possible adjustment) in other transnational contexts. While using a specific EU–China context helps illustrate our research problem, the underlying research gaps concerning TIC and TUC synergy building are general. To narrow the gaps, we must first clearly see what the gaps are. Thus, this paper will analyze how the state-of-the-art studies have shed light on the following questions as well as limitations in answering these questions: •Why should TIC and TUC be looked at as synergetic entities? •How can the synergy building be theoretically elucidated? •How can the synergy building be methodologically realized? Sustainability 2019,11, 4633 5 of 23 After that, we will present our proposed approach in brief, and discuss how it could help advance the frontier of research on the topic. It should be mentioned that the paper is primarily on the conceptual level. When it comes to our proposed AI-based approach we focus on developing operating principles rather than final technological solutions. The method in this paper is primarily based on reviewing, analyzing and synthesizing relevant literature. 2. Why Should TIC and TUC Be Looked at as Synergetic Entities? The synergy building between TIC and TUC in the context of EU–China STI cooperation, which takes place when innovation ecosystems of both the EU and China come across (as illustrated in Figure 3). Despite our focus on the sectors of university and industry, it should be noted that the EU–China transnational innovation ecosystem consists not only of enterprises and universities but also governmental agencies and various intermediary organizations. When building the TIC and TUC co-innovation networks in the EU–China context, it is essential to discover the hidden links and bridge the missing links as show in Figure 3. Sustainability 2019, 11, x FOR PEER REVIEW 6 of 27 Innovation ecosystem in EU states Innovation ecosystem in China Transnational innovation systems Universities Industrial firms Universities Industrial firms Governmental agencies Governmental agencies Intermediary organisations Figure 3. EU–China university cooperation and EU–China industry cooperation in the context of the EU–China transnational innovation ecosystem. The insights of the following three research areas may provide hints on why TIC and TUC synergy building (in the EU–China context) is necessary, namely (1) the conceptualization of transnational innovation ecosystems, (2) research on universities’ third mission and (3) studies on EU–China STI cooperation. 2.1. Transnational Innovation Ecosystems Due to the increasing importance of international linkages in the knowledge-based society and a growing public awareness of the need for environmentally sustainable economic development, the term “transnational or global innovation ecosystem” has gradually become popular in both scholarly literature and policy rhetoric. While the concept of the transnational ecosystem has been applied on both the system level [36] and the sector and company levels [25], what is most relevant to the present research is the system-level literature. A transnational innovation ecosystem generally refers to the integration process between two or more innovation ecosystems across national borders with different levels of transnational integration [37,38]. To further understand the transnational innovation ecosystem, one must understand what an innovation ecosystem is. In a commonly cited definition, innovation ecosystems are regarded as “complex relationships that are formed between actors or entities whose functional goal is to enable technology development and innovation” [39] (p. 2). The innovation ecosystem shares most of its features with the innovation system, which consists of complex functions and interactions amongst various organizations and institutions [40,41]. What is new in the innovation ecosystem is its ecological aspect, characterized by the interdependency among different collaborative actors and the co-evolution/co-creation that binds them together over time, along with the sustainable development dimension [42–44]. The literature on transnational innovation ecosystem has indicated, though implicitly, that TIC and TUC could be looked at as synergetic entities. Based on analyzing several definitions of “ecosystem”, Sotarauta, Heinonen, Sorvisto, and Kolehmainen [38] suggested several key features of the innovation ecosystem, including “interconnectedness” (everything is connected to everything), “organic nature” (the system evolves through its components’ continuous adaptation to changing situations) and being “multi-locational” (knowledge flows and innovation processes take place in multiple geographical locations) (pp. 31–32). All these infer that complex interactions amongst a variety of (transnational and cross-sectoral) actors shape adaptation processes in an innovation ecosystem. Such generic inferences may imply that TIC and TUC could form symbiotic relations to better adapt to increasingly complex and fast-changing environments. Figure 3. EU–China university cooperation and EU–China industry cooperation in the context of the EU–China transnational innovation ecosystem. The insights of the following three research areas may provide hints on why TIC and TUC synergy building (in the EU–China context) is necessary, namely (1) the conceptualization of transnational innovation ecosystems, (2) research on universities’ third mission and (3) studies on EU–China STI cooperation. 2.1. Transnational Innovation Ecosystems Due to the increasing importance of international linkages in the knowledge-based society and a growing public awareness of the need for environmentally sustainable economic development, the term “transnational or global innovation ecosystem” has gradually become popular in both scholarly literature and policy rhetoric. While the concept of the transnational ecosystem has been applied on both the system level [ 36 ] and the sector and company levels [ 25 ], what is most relevant to the present research is the system-level literature. A transnational innovation ecosystem generally refers to the integration process between two or more innovation ecosystems across national borders with different levels of transnational integration [37,38]. To further understand the transnational innovation ecosystem, one must understand what an innovation ecosystem is. In a commonly cited definition, innovation ecosystems are regarded as “complex relationships that are formed between actors or entities whose functional goal is to enable technology development and innovation” [ 39 ] (p. 2). The innovation ecosystem shares most Sustainability 2019,11, 4633 6 of 23 of its features with the innovation system, which consists of complex functions and interactions amongst various organizations and institutions [ 40 , 41 ]. What is new in the innovation ecosystem is its ecological aspect, characterized by the interdependency among different collaborative actors and the co-evolution/co-creation that binds them together over time, along with the sustainable development dimension [42–44]. The literature on transnational innovation ecosystem has indicated, though implicitly, that TIC and TUC could be looked at as synergetic entities. Based on analyzing several definitions of “ecosystem”, Sotarauta, Heinonen, Sorvisto, and Kolehmainen [ 38 ] suggested several key features of the innovation ecosystem, including “interconnectedness” (everything is connected to everything), “organic nature” (the system evolves through its components’ continuous adaptation to changing situations) and being “multi-locational” (knowledge flows and innovation processes take place in multiple geographical locations) (pp. 31–32). All these infer that complex interactions amongst a variety of (transnational and cross-sectoral) actors shape adaptation processes in an innovation ecosystem. Such generic inferences may imply that TIC and TUC could form symbiotic relations to better adapt to increasingly complex and fast-changing environments. Some other studies draw specific attention to the role of universities in the transnational innovation ecosystem. In a report on case studies of transnational innovation systems, Chaminade and Nielsen [ 36 ] addressed the importance of identifying already existing transnational initiatives (i.e., university and industry sectors) in forming transnational innovation systems. They suggested that available resources should support existing bottom-up transnational initiatives rather than start new ones from scratch in a top-down matter. Raunio, et al. [ 45 ] noted that “the transnational innovation infrastructures could be based more on the activities of universities or regional actors” (p. 2). They further suggested that the global university campuses could potentially help bridge the gap between the national innovation system and relevant innovation systems abroad. 2.2. Universities’ Third Mission One may intuitively assume that transnational university cooperation in the transnational innovation ecosystem is a well-studied topic. This is because of a widely shared understanding regarding the prominent role of universities in national or regional innovation systems, reflected in studies dealing with the third mission of universities [ 46 ], both in higher education research (inside-out view) e.g., [ 18 , 47 – 49 ] and innovation system studies literature (outside-in view) e.g., [ 8 , 40 , 41 , 50 ]. As recently stated by UNESCO’s Chief of Higher Education, Peter J. Wells, “Perhaps never before in recent history has the role of higher education been so intricately tied to the economic, social, and environmental fabric of the modern world” [ 51 ] (p. 31). Since the knowledge-based society is becoming more globally interconnected, universities’ societal engagement should also be conducted on a global scale. However, most studies on transnational university cooperation are in the field of internationalization of higher education, which is primarily concerned with the teaching and research missions of universities [ 52 , 53 ] or with the mobility of knowledge from the perspective of human geography [ 54 ]. The studies on international graduate employability e.g., [ 55 , 56 ] are closest to addressing the relevance of international higher education to industry in a global context. Nevertheless, some rare studies e.g., [ 23 , 28 , 29 ] do shed light on how transnational university cooperation could be aligned with and supportive of broader societal priorities and development goals in transnational contexts. Heide, Sijde, and Terlouw [ 28 ] explicitly explored transnational university cooperation in knowledge transfer. However, the authors solely focused on transnational research cooperation in the EU context mainly concerning types of cooperation and universities’ motivations for the cooperation, and did not extend their discussion to the links of transnational university cooperation to industry sectors. Cai [ 30 ] clearly stated that China-EU higher education cooperation should be planned and developed in the broader context of Sino-EU strategic partnership building, as a call for further research. Sustainability 2019,11, 4633 7 of 23 2.3. EU–China Transnational STI Cooperation The booming practices of EU–China STI cooperation have rarely been explored scientifically, remaining marginal in EU–China studies. The existing literature on the EU–China relationship e.g., [ 57 – 59 ] deals with three main pillars of cooperation between the EU and China, namely the strategic dialogue initiated in 2005, the economic and trade dialogue commenced in 2008 and the “People-to-People Dialogue” launched in 2012 to improve cooperation in education, culture, youth and research. However, the necessity of TIC and TUC synergy building can be foreseen in the burgeoning interests of the EU and China in STI cooperation, which has been expedited by the signing of the “EU–China Innovation Cooperation Dialogue” in 2012. The Dialogue complements and ensures synergy with the “Agreement on Science and Technology Cooperation between the EU and China” in 1998. The innovation cooperation involves both industrial organizations and universities (as well as research institutes) [ 60 ]. The progress of EU–China STI cooperation in both higher education and industry is not merely a matter of quantity; its very nature is undergoing a transformation. The nature of the EU industry’s cooperation with China is changing from a conception of China as an important market and trade partner to that of an innovation partner [ 61 , 62 ], because China is not only the second largest economy in the world but also a powerful STI player [ 63 ]. China has overtaken the United States in terms of total number of science publications [ 64 ] and dominates a global ranking of the most-cited research papers published in the 30 most popular technology fields [ 65 ]. In such a context, EU–China industry cooperation is not confined to the business domain but expanded to the sector of knowledge generation. In the field of higher education, EU–China university cooperation is facing increasing demands from society and stakeholders calling for universities to adapt their internationalization strategy from an emphasis on international scholarship exchange to being more responsible regarding the broader needs to develop the EU–China partnership [ 30 ]. This echoes the general trend in the internationalization of higher education in the EU, which has been increasingly influenced by the globalization of economics and societies, as well as the importance of knowledge in economic development and competition [ 66 ]. 2.4. Limitations of Existing Literature The literature on both transnational innovation ecosystems and universities’ third mission has implied why synergy building between TIC and TUC is important in transnational innovation ecosystems, but the inferences are implicit and hypothetical. Both theoretical and empirical efforts on the topic are lacking. Recent studies and reports on EU–China relations indicate that the changing nature of EU–China cooperation requires synergy building between cooperation in both the university and industry sectors. However, it is surprising how little interaction exists between the two areas of cooperation on both the levels of policy-making and organizational practice. Neither has synergy been addressed in research on EU–China STI cooperation, which tends to report on cooperation separately in the university sector e.g., [67] and the industry sector e.g., [68]. 3. How Can the TIC and TUC Synergy Building Be Theoretically Elucidated? Although state-of-the-art research reflects fast-growing attention to TIC and TUC synergy building, there are no theoretical frameworks that elucidate relations amongst diverse actors in transnational innovation ecosystems. Even the concept of the innovation ecosystem exists on a high level of abstraction and is used loosely. It is often understood as a metaphor rather than as a theory or framework [ 42 ]. Oh, Phillips, Park, and Lee [ 42 ] noted that the mimetic quality of the term “innovation ecosystem” mainly appeals to the news media, demonstrating the public relations value of the term, but not its value in research. They found “few academic articles using ‘innovation ecosystem’ in a manner that would distinguish an innovation ecosystem from an innovation system” [ 42 ]. Along the same lines, Ritala and Almpanopoulou [ 69 ] called for future research to improve the conceptual, Sustainability 2019,11, 4633 8 of 23 theoretical and empirical rigor regarding the notion of the innovation ecosystem. Nevertheless, some other social science theories may provide useful, theoretical accounts of the mechanisms underlying the interactions between TIC and TUC, though in a direct manner, such as the Helix models of innovation, institutional theory and social network theory. 3.1. Helix Models of Innovation Helix models of innovation, discussed here, include three concepts, namely Triple Helix Model [ 8 ], Quadruple Helix Model [ 9 ], and Triple Helix of sustainability [ 70 ]. The three concepts with different emphasis on the key dimensions innovation and societal development can supplement one another for a comprehensive understanding of the nature of contemporary society with respect to innovation. Although the thesis of the Triple Helix Model [ 71 ] was originally developed based on empirical observations of successful regional innovation systems, its core theoretical assumptions can be applied to transnational or global contexts. Following this perspective, a transnational innovation ecosystem consists of the triple helix interactions of three functional spaces, namely transnational knowledge space, transnational innovation space and transnational consensus space [ 8 , 72 ]. The three spaces are respectively related to three functions, namely novelty production, normative control and wealth generation [ 73 ]. In each space, there are three overlapping spheres of transnational cooperation evolving in the respective sectors of university, industry and government, but one kind of sphere may outweigh the others. Such a Triple Helix Model of transnational innovation ecosystem is illustrated in Figure 4. Sustainability 2019, 11, x FOR PEER REVIEW 10 of 27 Figure 4. Triple Helix Model of the transnational innovation ecosystem. The foundational statement of the Triple Helix Model is that the interactions between university, industry, and government sectors provide optimal conditions for innovation [8]. The core mechanism underlying these interactions is “taking the role of the other” [8]. Organizations taking on nontraditional roles are viewed as a major potential source of innovation. In the meantime, they still retain their traditional functions. To add the sustainability or ecosystem dimension in the Triple Helix model, the role of university must go beyond production and capitalization of knowledge [82], as main function of the third mission of universities. In transnational contexts, the roles of transnational university cooperation are more than producing and transferring knowledge across national borders. There are two additional roles, namely fostering institutional change (concerning norms and values) in transnational innovation ecosystems and building trust between various actors in the systems [83]. The development of innovation systems is largely concerned with institutional change [40,41] and successful cooperation in research, development, and innovation relies on trust between the collaborators [84]. Both institutional change and trust building are even more salient in transnational innovation ecosystems because of the more complicated institutional configurations and distance between the collaborators in a transnational context [36]. The role of university as institutional entrepreneur [85] or social trust builder [86] is relevant to sustainable development because the it brings in social capital into the analytical foci of innovation ecosystem [6], in addition to human and financial capital as emphasizes of the concept of university’s “third mission”. The two roles concerning institutional change and trust building can be respectively explained by institutional logics theory and social network theory. 3.2. Institutional Theory From the perspective of institutional theory, there are two essential issues in forming an innovation (eco)system, namely institutional conditions enabling innovation [78] and the agency of actors to change the institutional context [87,88]. These two factors can be respectively explained by the institutional logics approach and the notion of institutional entrepreneurship. Figure 4. Triple Helix Model of the transnational innovation ecosystem. Carayannis and Campbell [ 9 ] developed the Quadruple Helix model from the basis of the Triple Helix in order to address the “media-based and “culture-based public”, “arts, artistic research and arts-based innovation” (p. 218), by adding the ‘fourth helix’ also called as the “civil society” [ 74 ] (p. 5). The core rationale of Quadruple Helix centers on Mode 3 knowledge production, which is developed on the basis of Mode I and Mode 2 types of knowledge production by Gibbons et al. [ 75 ], who predicted a shift in knowledge production from Mode 1 to Mode 2. Mode 1 refers to basic university research on Sustainability 2019,11, 4633 9 of 23 disciplinary basis. The Mode 2 in turn, emphasizes knowledge application, interdisciplinary research and problem solving. Mode 3 type of knowledge production is an extension for Mode 1 and 2 type of knowledge production [75]. It “allows and emphasizes the co-existence and co-evolution of different knowledge and innovation paradigms” [ 9 ] (p. 201). Mode 3 is the nexus of the emerging 21st century innovation ecosystem, where people, culture and technology meet and interact to catalyze creativity, trigger invention, and accelerate innovation across scientific and technological disciplines, public and private sectors, in a top-down, policy-driven as well as bottom-up, entrepreneurship-empowered fashion [ 9 , 76 ].There is a seemingly shared view about the possible extension from Triple Helix to Quadruple Helix (adding civil society as the fourth helix) [ 76 , 77 ]. However, we take the position that civil society is considered too important to be merely treated as an additional helix in the Quadruple Helix. Rather, it is an institutional foundation [ 78 , 79 ] or “a launch pad for the take-offof triple helix interactions” [ 72 ] (p. 20). Thus, citizens’ engagement is positioned in Figure 4as the foundation of transnational Triple Helix interactions. Nevertheless, we admit that the Triple Helix Model has not explicitly addressed the emerging phenomena or new characteristics in innovation ecosystems. Meanwhile, we consider that the relatively more elaborated theoretical foundations of Triple Helix Model may help enhance the explanation power of Quadruple Helix [80], which was conceptualized to cope with the innovation ecosystem of the 21st Century [6]. Moreover, Triple Helix model is needed to be further improved with the dimension of sustainable development. In this regards, Scalia, Barile, Saviano and Farioli [ 70 ] suggested the model of Triple Helix of sustainability based on both the concept of Triple Bottom Lines of Elkington [ 7 ] and the Triple Helix Model of innovation Leydesdorffand Etzkowitz [ 81 ]. It implies that interactions between society, economy and environment must be considered when studying innovation, either approached by the Triple Helix Model or Quadruple Helix Model. The foundational statement of the Triple Helix Model is that the interactions between university, industry, and government sectors provide optimal conditions for innovation [ 8 ]. The core mechanism underlyingtheseinteractionsis“takingtheroleoftheother”[ 8 ]. Organizationstakingonnon-traditional roles are viewed as a major potential source of innovation. In the meantime, they still retain their traditional functions. To add the sustainability or ecosystem dimension in the Triple Helix model, the role of university must go beyond production and capitalization of knowledge [ 82 ], as main function of the third mission of universities. In transnational contexts, the roles of transnational university cooperation are more than producing and transferring knowledge across national borders. There are two additional roles, namely fostering institutional change (concerning norms and values) in transnational innovation ecosystems and building trust between various actors in the systems [ 83 ]. The development of innovation systems is largely concernedwithinstitutional change [ 40 , 41 ] andsuccessful cooperationinresearch, development, and innovation relies on trust between the collaborators [ 84 ]. Both institutional change and trust building are even more salient in transnational innovation ecosystems because of the more complicated institutional configurations and distance between the collaborators in a transnational context [ 36 ]. The role of university as institutional entrepreneur [ 85 ] or social trust builder [ 86 ] is relevant to sustainable development because the it brings in social capital into the analytical foci of innovation ecosystem [ 6 ], in addition to human and financial capital as emphasizes of the concept of university’s “third mission”. The two roles concerning institutional change and trust building can be respectively explained by institutional logics theory and social network theory. 3.2. Institutional Theory From the perspective of institutional theory, there are two essential issues in forming an innovation (eco)system, namely institutional conditions enabling innovation [ 78 ] and the agency of actors to change the institutional context [ 87 , 88 ]. These two factors can be respectively explained by the institutional logics approach and the notion of institutional entrepreneurship. Sustainability 2019,11, 4633 16 of 23 statements that will extend the ontology. Furthermore, the semantic model consistency is validated within a semantic reasoner. In this approach, the Pellet reasoner is used for such a validation. Finally, once the model is populated and validated, the third stage regards finding the potential cooperation between parties within the TIC and TUC matching phase. This is achieved within the inference of ontological descriptions enriched within semantic rules. More precisely, Semantic Web Rule Language (SWRL) rules are used, as they are compatible with Resource Description Framework (RDF)-based models and hence OWL ontologies. The finding of implicit relations between ontological resources within similar interaction of technologies and languages havebeen demonstrated on previous research work by the authors [125,126]. One of the benefits of this approach is that the described stages are automatically executed with only the need for the profiles of university and industry actors. The platform engines manage the tasks regarding the corresponding data and present the results, i.e., the potential cooperation, to the collaborative partnerships. This is provided to the platform owner as a report to be later shared with the platform users. 5.2. Potential to Answer the Research Questions Using the Transdisciplinary Approach Once our proposed approach has been developed, it will better answer the three research questions raised at the outset of the paper. To make clear how our approach advances state-of-the-art research, we contrast the potential contributions of our proposed approach to the research questions and the limitations of existing literature (Table 1). Table 1. Answers to research questions by existing literature and our proposed approach. Research Questions Limitations of Existing Literature Potential Contributions Offered by Our Proposed Approach Why should TIC and TUC be looked at as synergetic entities? The synergies between TIC and TUC are hypothetical. Scarce data are available for empirical exploration. A large scale of transnational U–I co-innovation networks will be detected and developed. This will enable deep empirical investigations and even big data analyses. How can the synergy building be theoretically elucidated? The theories, to varying extents, elucidate the mechanisms underlying the synergy building between obvious actors crossing sectors/communities, but mainly in a domestic context. The relations between the actors are one to one (or one to more). The AI algorithms will be based on integrating several social science theories, which provide theoretical foundations concerning developing collaborative relations (networks) between unobvious (cross-sectoral) actors in a transnational context. Our frameworks address the relations between different pairs of collaborators. How can the synergy building be methodologically realized? SNA: lacks efficiency in exploring hidden/missing links. Professional social matching (PSM): not for matching in a cross-sectoral and transnational context. AI technologies: no suitable algorithms and training data ready to use. A comprehensive method will be developed by integrating social science studies and AI in the context of transnational innovation ecosystems. It is not only for detecting potential collaborators and links between them, but also for building the networks. 6. Conclusions This paper has demonstrated how social sciences and AI could be integrated to develop a transdisciplinary approach to TIC and TUC synergy building, thus contributing to the knowledge pool in which studies on TIC and TUC have been separately reported in spite of a growing awareness on necessary of synergy building between TIC and TUC. Specifically, the originality of our research lies in four aspects. First, while the research on TIC and TUC synergy building is almost an uncharted field, our research maps a landscape of the research area with identification of specific research gaps through extensive analysis of relevant literature. Our efforts are around discussions on how existing research Sustainability 2019,11, 4633 17 of 23 may offer useful insights and have limits in answering three questions: Why should TIC and TUC be looked at as synergetic entities? How can the synergy building be theoretically elucidated? How can the synergy building be methodologically realized? The diagnose of advantages and weaknesses of state-of-the-art research in the field not only serves as clear point of departure of our research on TIC and TUC synergy building, but also helps guide more scholars to plunge into the field. Second, we propose a transdisciplinary approach to TIC and TUC synergy building by integrating insights of social sciences, such as Helix Model of innovation, institutional theory and social network theory, and AI, such as ML and KR and R. While the insights from social sciences have the potential to answer the question of why TIC and TUC should be regarded as synergetic entities, AI technologies can help answer the question of how such synergies can be realized. Current methods using AI (i.e., ML) in social science research tend towards two extremes: they are used either for verifying assumptions about human intelligence or for independent prediction, thus tending to replace human intelligence. We try to integrate between social-science-based theoretical modelling and data-based computational modelling, particularly regarding the understanding of TIC–TUC interactions. Empirical findings guided by social sciences theories will help improve ML algorithm by providing validation and test data. The models learnt by machine will be useful input for advancing understanding of TIC and TUC synergy building in social sciences studies. Third, our proposed approach will specifically identify/predict hidden/missing connections between actors in TIC and TUC co-innovation networks by analyzing unstructured data from various sources, such as public databases (e.g., research projects, co-publications, patents), website text (on cooperation activities) and auto-generated survey data. In doing so, on one hand we try to advance current social network analyses, which mainly map out anticipated networks by processing classified data [ 107 ]. On the other hand, we will open new horizons for studies on professional social matching [34] from both cross-sectoral and transnational perspectives. Finally, our approach of AI-based matching system will help realize the potential role of university for institutional change and trust building, which are important to the sustainable dimension of innovation ecosystem development. Nevertheless, our paper is primarily on the conceptual level discussions. Despite promising potential of our approach, it must be first tested and verified with sample data. This will be our next research task. It should also be noted that matching TIC and TUC, e.g., in the EU and China context, is just the first step to building EU–China transnational co-innovation networks. To achieve full synergy of the networks, there are also other important issues that need to be deeply explored, such as research and innovation policies, entrepreneurship, knowledge management, intellectual property rights, and inter-cultural communications. This will indeed open a new area of multidisciplinary research. Studying the TIC and TUC synergy building in the EU and China context also propels an urgent demand for closer communication between two separate research communities, namely international researchers and Chinese researchers both conducting research on the topic [127]. Author Contributions: Overall research design: Y.C.; Designing and describing AI-based approach: Y.C., B.R.F. and J.L.M.L.; Writing original draft: Y.C.; Extensive review and editing: B.R.F. and J.L.M.L. Funding: The APC was funded by MDPI. Acknowledgments: We are grateful to the four peer reviewers’ valuable comments, which has greatly helped us to improve the paper. We also appreciate our colleagues Martti Juhola, Nina Helander, and Thomas Olsson, with whom we have been working together to prepare a research project proposal around the ideas addressed in the paper. Their insights in our discussions on planning the research proposal provide us inspirations for writing the paper. 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