The Triple Helix Perspective of Innovation Systems

Alongside the neo-institutional model of networked relations among universities, industries, and governments, the Triple Helix can be provided with a neo-evolutionary interpretation as three selection environments operating upon one another: markets, organizations, and technological opportunities. How are technological innovation systems different from national ones? The three selection environments fulfill social functions: wealth creation, organization control, and organized knowledge production. The main carriers of this system-industry, government, and academia-provide the variation both recursively and by interacting among them under the pressure of competition. Empirical case studies enable us to understand how these evolutionary mechanisms can be expected to operate in historical instance. The model is needed for distinguishing, for example, between trajectories and regimes

Value-based Innovation: Knowledge and Technology Transfer in Triple Helix Model

In light of globalization, innovation has been determined as a strategy to increase competitive advantage, and, therefore, nurturing innovation through improved policies and practices has become a priority in both the public and private sectors. Globalization has boosted the need for the triple helix of university–industry–government collaboration, which encourages the transfer of knowledge and technology to improve project development and the quality of products. The concept of the triple helix relationship encourages potential cooperation for innovation and thus stimulates economic growth by generating productivity and strengthening competitive advantages. Innovation in the Triple Helix Model The triple helix model provides various alternatives to explore complex innovation and create added value for products and projects. From a triple helix systems perspective, the consolidation of multiple perspectives used to generate new combinations of knowledge and technology in solving problems and improving end results requires the dynamic interaction between triple helix actors in the context of mutual cooperation and consensus. Innovation in the triple helix model is embedded in an interactive system of partnerships, the role of governments in shaping innovation policies (politics), and the relation between universities (education) and the industry (economy) in producing value-added products through advanced knowledge and technologies that suit the public or market needs. Furthermore, one of the key strategies in a successful triple helix cooperation is managing the cross-cultural issues between stakeholders because these might affect the quality of the collaboration and the effectiveness of the transformational learning process for successful knowledge and technology transfer. Knowledge and technology transfer is the process of transferring skills, methods, and facilities among actors and institutions to ensure that scientific and technological developments are accessible for further development into new processes or end results. The transfer of individual and organizational knowledge, such as best practices, then becomes a means to search for sustainable technological solutions in design and product and project development. Various factors need to be clearly defined, including conceptions of technology utilization and collaboration, process activities and capacity transfer, and dissemination and communication models, to achieve efficient and effective knowledge and technology transfer. It is a collaborative and context-specific process based on mutual understanding, so the intended collaboration in the triple helix model provides links to tie together all aspects of technology, namely, knowledge, process, and product results

The Triple Helix, Quadruple Helix, . . ., and an N-tuple of Helices: Explanatory Models for Analyzing the Knowledge-based Economy?

Using the Triple Helix model of university-industry-government relations, one can measure the extent to which innovation has become systemic instead of assuming the existence of national (or regional) systems of innovations on a priori grounds. Systemness of innovation patterns, however, can be expected to remain in transition because of integrating and differentiating forces. Integration among the functions of wealth creation, knowledge production, and normative control takes place at the interfaces in organizations, while exchanges on the market, scholarly communication in knowledge production, and political discourse tend to differentiate globally. The neo-institutional and the neo-evolutionary versions of the Triple Helix model enable us to capture this tension reflexively. Empirical studies inform us whether more than three helices are needed for the explanation. The Triple Helix indicator can be extended algorithmically, for example, with local-global as a fourth dimension or, more generally, to an N-tuple of helices

Can processes make relationships work? The Triple Helix between structure and action

This contribution seeks to explore how complex adaptive theory can be applied at the conceptual level to unpack Triple Helix models. We use two cases to examine this issue – the Finnish Strategic Centres for Science, Technology & Innovation (SHOKs) and the Canadian Business-led Networks of Centres of Excellence (BL-NCE). Both types of centres are organisational structures that aspire to be business-led, with a considerable portion of their activities driven by (industrial) users’ interests and requirements. Reflecting on the centres’ activities along three dimensions – knowledge generation, consensus building and innovation – we contend that conceptualising the Triple Helix from a process perspective will improve the dialogue between stakeholders and shareholders

Can Synergy in Triple-Helix Relations be Quantified? A Review of the Development of the Triple-Helix Indicator

Triple-Helix arrangements of bi- and trilateral relations can be considered as adaptive eco-systems. During the last decade, we have further developed a Triple-Helix indicator of synergy as reduction of uncertainty in niches that can be shaped among three or more distributions. Reduction of uncertainty can be generated in correlations among distributions of relations, but this (next-order) effect can be counterbalanced by uncertainty generated in the relations. We first explain the indicator, and then review possible results when this indicator is applied to (i) co-author networks of academic, industrial, and governmental authors and (ii) synergies in the distributions of firms over geographical addresses, technological classes, and industrial-size classes for a number of nations. Co-variation is then considered as a measure of relationship. The balance between globalizing and localizing dynamics can be quantified. Too much synergy locally can also be considered as lock-in. Tendencies are different for the globalizing knowledge dynamics versus locally retaining wealth from knowledge in industrial innovations

"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.Comment: Journal of Open Innovations: Technology, Market and Complexity, 2(1) (2016) 1-12; doi:10.1186/s40852-016-0039-