University-industry Innovation Research Articles

Collaborative Synergy: Leveraging Competitive Advantage In University-Industry Innovation

Collaboration between universities and industry is a strategic collaboration that aims to connect the world of education with the world of industry, creating concussion benefits for both. Universities improve curriculum relevance, prepare work-ready graduates, and pursue innovation. Industry can access young talent, face challenges with new thinking, and contribute to the development of science and technology. Through this collaboration, lecturers and students are involved in research and industrial work practices, develop professional skills, and get direct feedback. This collaboration also enhances the transfer of knowledge and technology, with universities disseminating knowledge through research to industry and industry applying it to business innovation. Despite the challenges of different interests, cultures, and timelines, the benefits of collaboration can positively impact both parties and society to increase innovation and competitive advantage.

Discovering the effect metrics for innovation projects

Working life-integrated innovation projects have become a common part of education. An innovation project is a social phenomenon of learning that brings the competence of several individuals together in a social process through which a novel idea is turned into practical reality to convey value to its users. University–industry innovation collaboration research has mainly understood the role of the university as a partner responsible for research. However, these projects are often based on student teamwork, an open challenge from real working life and a predefined intention to produce a concrete, novel, and innovative product, service, or new operating model into use. The outcomes are meant to be taken into use to convey value for business and society. A paucity of empirical research exists on the development and assessment of these innovation education programs based on their effects on the surrounding society. The variables that are important in studying the effects of innovation education projects on surrounding society, participating companies, and organisations must be identified. In this study, a set of effect measurement scale variables were discovered through a document analysis and focus group interviews. The findings imply the importance of recognising the effects of the project both on the clients' and their organisations' goals (project output, benefits of participation, and what survives) and the wider impact of the projects on the surrounding society (impacts on the daily lives of citizens; well-being and health; economy, ecology, digitalisation; and social matters). Thus, a preliminary impact assessment model is suggested. Keywords: Innovation project, university-industry collaboration, impact, higher education, innovation pedagogy, document analysis, focus group

Exploring intermediary practices of collaboration in university–industry innovation: A practice theory approach

The intensity of the global and distributed economy requires innovative efforts that single organizations often cannot develop alone. Collaborative innovation is traditionally studied in terms of collaborative process to maintain and outcomes to implement. However, collaborations relating to innovation often take place in difficult‐to‐explore spaces in‐between. This study adopts a practice‐based approach to explore practices of collaboration developed by the university as an intermediary in innovative projects. Drawing on a case study, we identify four micro‐practices that appear crucial to initiating and sustaining collaboration: networking, partnering, culture making and supporting. We outline the purpose and constituent objects, doings and knowledge of each practice. This article contributes to ongoing debate around improving the effectiveness of collaborative innovation and provides insights into how a set of apparently insignificant, routinized micro‐practices contribute to intermediaries' success in initiating and sustaining collaborations.

Does University-industry innovation community affect firms’ inventions? The mediating role of technology transfer

Does University-industry innovation community affect firms’ inventions? The mediating role of technology transfer

University-industry innovation community dynamics and knowledge transfer: Evidence from China

Much of the emphasis on university-industry (U–I) knowledge transfer has been on facilitating dyadic interactions between universities and firms. However, merely a few studies have investigated knowledge transfer from a community-based innovation perspective. This research unveils the explicit structure and dynamic characteristics of U–I communities and examines the relationship between community dynamics and university knowledge transfer. The results indicate that U–I innovation communities in China present single- and multi-center structures and are evolving from “localizing” to “specializing”. Using membership turnover as a means of measuring community dynamics, we discover that community dynamics significantly affect university knowledge transfer in a curvilinear manner. Moreover, this inverted U-shaped relationship is moderated by a university's within-community position. The results of the other variables show that geographical distance does not significantly affect community-based knowledge transfer, while knowledge diversity positively contributes towards knowledge transfer performance. Our findings advance the innovation community theory by mapping social network mechanisms into community generation, evolution, and knowledge transfer. Notable practical implications are provided for U–I innovation community stakeholders and practitioners who engage in knowledge commercialization and innovation.

The Demola model as a public policy tool boosting collaboration in innovation: A comparative study between Finland and Spain

The next generation of Science, Technology & Innovation (STI) policies will be defined by mission orientation and co-creation processes and implemented by dynamic public-private partnerships. However, the experience of European countries up to now in attempting to boost cooperation in innovation reveals a very different story. Beyond some contextual factors, the characteristics of the agents involved, the dynamics of their relationships and the design of the collaboration tools also have a critical influence at organisational level. This paper aims to identify these organisational factors in different contexts through the analysis of the Demola model, a university-industry innovation platform created in Finland which has spread to other countries, including Spain. Demola applies a standardised model but it has differences in its functioning depending on the national levels of collaboration in the innovation systems. In our case study, we have compared Finland and Spain, bearing in mind the features of the agents involved and their relationships, through a content analysis of primary and secondary information. The results of the study show that the institutional structure of the collaboration and the organisational culture of each institution are key factors in its functioning. These results can be useful for innovation managers, university leaders, educational experts and policy makers.

Knowledge growth in university-industry innovation networks – Results from a simulation study

University-industry innovation networks (UIINs) are important agents of innovation, as they bring together the unique profiles of higher education and industry partners. Knowledge growth in these networks does not happen automatically. We analyze the impact of network density and heterogeneity on knowledge growth in UIINs. Knowledge grows through knowledge transfer, spillover, and knowledge innovation. Knowledge growth is a function of each agent's initial knowledge level, network density, and agent heterogeneity. To analyze these correlates of knowledge growth, we use a knowledge growth model based on multiple agents and simulate knowledge growth in a UIIN. Our results show that network density positively influences knowledge growth. Initially, this positive impact increases and then disappears with a further increase in network density. We also find that heterogeneity moderates the relationship between density and knowledge growth. Through the positive moderating effect of its impact on knowledge innovation, it promotes new knowledge generation in the entire innovation network, thus providing a basis for subsequent knowledge transfer. Our study supports and enriches the contingency view of knowledge growth in innovation networks.

University-industry innovation collaboration: Reconceptualization

This study investigates university-industry (U-I) innovation collaboration and proposes a renewed and empirically tested conceptual approach to analyse it. The motivation for the research emerged from the realisation that the majority of studies on university-industry innovation collaboration on organisational level present limited verification of why some seemingly similar collaboration projects fail while others thrive. Therefore, we aimed for reconceptualization of the way university-industry collaboration is analysed by developing the respective approach that was empirically tested via multiple case-study research of 12 cases. The approach combines elements of the U-I collaboration literature with a model of interaction from semiotics and boundary-crossing ideas from organisation theory. The novelty of this approach lies in explaining the heterogeneity and variation of U-I collaboration on individual level. The interaction model from the semiotics enables distinct U-I collaboration patterns to emerge. In a two-dimensional model it becomes clear that choosing the appropriate partner for potentially successful collaboration means matching the levels of preconditions between partners. The main contribution of this study is twofold: an interdisciplinary approach for analysing U-I collaboration using a multiple case-study research design and the explanation of relevant preconditions – individual rather than institutional levels of motivation and absorptive capacity – as critical aspects that determine the likelihood of the success or failure of such collaboration.

Balancing diversity in innovation networks

Purpose– Although the potential of innovation networks that involve both university and industry actors is great variances in cultures, goals and knowledge poses significant challenges. To better understand management of such innovation networks, the authors investigate different strategies for balancing diversity. The paper aims to discuss these issues.Design/methodology/approach– In this multiple case study, the authors draw on network and trading zone theory to examine the strategies of four research centers that govern university-industry innovation networks.Findings– The authors provide empirically grounded descriptions of strategies for balancing diversity in innovation processes, extend previous theorizations by suggesting two types of trading zones (transformative and performative), and identify four strategy configuration dimensions (means of knowledge trade, tie configuration, knowledge mobility mechanisms and types of trust).Research limitations/implications– Further research is needed on transferability of results when, e.g. cultural collaboration and communication patterns change, and performance implications of different configurations. The research provides conceptual tools for future research on the impact of different diversity strategies.Practical implications– The findings point to the importance of identifying desired types of innovation outcomes and designing the appropriate level of diversity. To implement the selected strategy, managers need to configure communication channels and strength of relationships, establish associated capacity for knowledge transfer and build appropriate levels of trust.Originality/value– While extant research has provided a solid understanding of benefits from diversity in boundary spanning innovation processes, this paper outlines strategies for managing associated challenges.

Examining University-Industry Collaboration as a Source of Innovation in the Emerging Economy of Turkey

Companies in developed countries have clearly benefited from university-industry collaborations but emerging nations around the world have a different series of challenges and barriers to overcome in establishing strong university-industry collaborations. The following article discusses the barrier that 202 Turkish companies experienced while collaborating with local universities. Establishing trust and awareness were found to be major barriers preventing deep research collaborations. Interestingly, Turkish companies did take great advantage of universities' technical infrastructures being their equipment and laboratory facilities to test products, conduct research, and run experiments without formally collaborating, the authors term this "light collaboration." To accelerate university-industry collaborations in Turkey and other emerging nations a simple three tiered model is presented herein and is composed of: building awareness, building trust and exposure, and transitioning companies to full research projects. It is hoped that the ideas proposed herein will positively generate new concepts for grants and programs for emerging countries to support their university-industry innovation collaborations efforts.

Patent Statistics as a Measure of Technical Change

This paper examines a question of long standing: How can one obtain operational indexes of inventive and innovative activity and technical change? Specifically, for a sample of fifty-seven pharmaceutical manufacturing firms, we attempt to determine how well a simple count of invention patents serves as a surrogate for two alternative measures of technical change: the number of research and development personnel employed, reflecting inputs into the innovative process, and the value of new product sales, which reflects outputs of the process.