University-industry Knowledge Research Articles

University-industry knowledge collaborations in emerging countries: the outcomes and effectiveness in Vietnam

ABSTRACT University-industry knowledge collaborations (UICs) significantly influence countries’ innovation capabilities and future workforce development. For a developing country like Vietnam, the goal of developing a knowledge-based emerging economy puts even higher expectations on UICs. However, UICs in Vietnam have not kept up well with the country’s ambition to survive and thrive in the new context. This study investigates the current status of the outcomes and effectiveness of knowledge exchange mechanisms as perceived by different stakeholders, including faculty members, students, and industries. Results show that UICs’ social and institutional outcomes are dominant in Vietnam. From the university side, the areas of training, university locations, and university types could affect UICs’ outcomes and effectiveness. However, there are discrepancies between faculty members and students in the perception of UICs’ effectiveness. Firms’ ownership types and locations also affect UICs’ effectiveness.

Building Bridges of Knowledge: Investigating the Nexus of Strategic Alignment in University-Industry Collaborations

University-industry collaboration (UIC) has emerged as a key driver of innovation through enabling knowledge transfer in meeting the evolving needs of partner institutions. This research explores the profound impact of strategic alignment on the effectiveness of university-industry knowledge exchange while exploring the determinants that drive the formation of strategic alignment. This research uses mixed methods, namely a concurrent embedded model with qualitative and quantitative approaches as the main and secondary approaches. Based on empirical data collected from a survey of 126 university and industry collaborations in Indonesia. The results of this research provide substantial insight into this area and confirm the central role of strategic alignment in the success of collaborative initiatives, especially at the team level. In particular, this research underscores the superiority of cognitive expertise in teams, compared with exclusive reliance on personality traits. This research also identifies trust and bond strength as important foundations of team dynamics, while highlighting the positive influence of operational and cultural fit on organizational factors. Significantly, this research challenges initial assumptions by not finding a direct relationship between shared understanding, strategic flexibility, balancing commitments, and achieving strategic alignment. These findings have profound implications for the strategic planning and implementation of UIC initiatives. In a broader context, this research provides theoretical and managerial contributions.

Conceptualising the Role of the UAE Innovation Strategy in University-Industry knowledge Diffusion Process

Universities are considered one of the primary sources of knowledge and an essential component of the triple helix theory. They fuel the industries with the required expertise and pool of resources to operate efficiently. Moreover, entrepreneurial universities successfully contributed to regional development and employment growth by supporting entrepreneurial activities and incubation programmes. Thus, university-industry collaboration is vital for enhancing knowledge-based industries' knowledge diffusion as well as the regional innovation atmospheres. On the other hand, countries and regional authorities strive to stimulate their regional development by encouraging innovation and entrepreneurship activities. For example, the UAE announced its 2015 innovation strategy that focused on seven industries: education, technology, renewable energy, transportation, education, health, water, and space. The strategy stressed the role of universities R & R&D, first-class research, and promoting incubation services as one of the country's main innovation enablers. Thus, universities, scholars and industry should concentrate on the identified sectors to achieve the strategic innovation goals. This work aims to conceptualise and test the relationship and collaboration between industry and universities in the UAE and the impact of the innovation strategy on this relationship. Therefore, we critically analyse literature on the university-industry relationship and connect it with the UAE innovation strategy that resulted in a conceptual university-industry relationship model where the innovation strategy and UAE government act as a moderator of this relationship. The initial results show that the conceptual model includes research and curriculum collaboration. Research collaboration includes joint research, research fund, commercialisation of the research output, while curriculum collaboration includes the programmes and courses updates and joint training programmes. The developed model is still in its early stage of development and requires further updates based on interviews with the HEIs researchers and the survey results.

University–Industry Technology Transfer: Empirical Findings from Chinese Industrial Firms

The knowledge and innovation generated by researchers at universities is transferred to industries through patent licensing, leading to the commercialization of academic output. In order to investigate the development of Chinese university–industry technology transfer and whether this kind of collaboration may affect a firm’s innovation output, we collected approximately 6400 license contracts made between more than 4000 Chinese firms and 300 Chinese universities for the period between 2009 and 2014. This is the first study on Chinese university–industry knowledge transfer using a bipartite social network analysis (SNA) method, which emphasizes centrality estimates. We are able to investigate empirically how patent license transfer behavior may affect each firm’s innovative output by allocating a centrality score to each firm in the university–firm technology transfer network. We elucidate the academic–industry knowledge by visualizing flow patterns for different regions with the SNA tool, Gephi. We find that innovation capabilities, R&D resources, and technology transfer performance all vary across China, and that patent licensing networks present clear small-world phenomena. We also highlight the Bipartite Graph Reinforcement Model (BGRM) and BiRank centrality in the bipartite network. Our empirical results reveal that firms with high BGRM and BiRank centrality scores, long history, and fewer employees have greater innovative output.

Academic Scientists Mobility: The Hidden Pipe of Tacit Knowledge Transfer from Academia to Industry

Knowledge transfer (KT) from academia to industry is critical to support economic growth and to contribute to a local open innovation ecosystem. Research on university-industry knowledge transfer (UIKT) mainly focuses on codified knowledge. However, the vast majority of knowledge produced by academia is tacit and, in some cases, cannot be made explicit thus remaining embodied in individuals. Building on knowledge management theory and social network theory, this article proposes that socialization occurs in two forms, weak and strong socialization, and that strong socialization is needed for tacit UIKT. We propose that professional mobility of PhD graduates is an instrument to measure tacit UIKT. Through a database of the PhD graduates of a large pluridisciplinary European university, our results show that fields hardness and applicability have a positive effect on tacit UIKT and that alignment with national industrial specialization and free-movement policies influence tacit KT to the national industry. We contribute to knowledge management theory by exploring academic scientists’ mobility as a pipe of tacit UIKT as well as by extending the concept of socialization from intra-organizational to inter-organizational settings, by proposing the concepts of weak and strong socialization, and by showing how strong socialization and tacit UIKT depend on knowledge, industrial and political dimensions.

New business models for public innovation intermediaries supporting emerging innovation systems: The case of the Internet of Things

In several countries, governments have assigned to public innovation intermediaries (PIIs) the mandate to support the digital transition, by facilitating the development and adoption of new digital technologies on the part of firms and other organisations. This new mandate requires PIIs to upgrade their business models, moving beyond their traditional involvement in firms’ technology upgrading and university-industry knowledge transfer, toward supporting the creation of new innovation systems around the emerging digital technologies. To understand how PIIs are reconfiguring their business models to support the digital transition, we study four cases of PIIs operating in the United Kingdom and France, whose mandates include providing support for firms and other organisations in the implementation of new digital technologies, focusing in particular on the Internet of Things (IoT). We show that, despite their differences, all four PIIs have substantially reconfigured their business models in similar ways in order to fulfil these mandates. Both the formal legitimacy arising from their policy mandate, and the knowledge resources and informal legitimacy they have developed, have played a decisive role in their ability to orchestrate the development of innovation systems around IoT.

University-Industry Knowledge Transfer: The Case of the Godfathers of Artificial Intelligence

Though university-industry linkages are channels for two-way knowledge sharing, in the case of breakthrough research, it is the path from scientific discovery to commercial application that is of primary interest. The central question is whether knowledge can be codified and disseminated in disembodied form, or if engagement with knowledge creators, either explicit engagement through collaborative relationships or potential engagement made possible by geographic proximity, is required. We consider the case of the godfathers of artificial intelligence (AI), Geoffrey Hinton (University of Toronto), Yoshua Bengio (Université of Montréal) and Yann LeCun (New York University), who collectively won the 2018 Turing Award, the Nobel prize of computing, and examine the factors that affect the ability of private technology developments to absorb and build upon their research. We construct a dataset consisting of the modern AI patent universe and use patent citations to godfather research as an indicator of knowledge transfer, modelling the likelihood that an AI patent will cite godfather research as a function of geographic proximity and social relations. We find strong effects for geographic proximity, where inventors were former co-inventors or co-authors of the godfathers, and for absorptive capacity as a crucial control.

Innovation ability of universities and the efficiency of university–industry knowledge flow: the moderating effect of provincial innovative agglomeration

PurposeThe purpose of this paper is to examine the influence of the innovation ability of universities (IAU) on the efficiency of University–Industry knowledge flow and investigate whether the level of provincial innovative agglomeration (PIA) moderates the relationship between IAU and the efficiency of the University–Industry knowledge flow.Design/methodology/approachThis study uses the super-efficiency data envelopment analysis model to measure knowledge research efficiency (KRE) and knowledge transformation efficiency (KTE) and then studies the influencing mechanism of the two kinds of efficiency using the spatial Tobit model with panel data from 2008 to 2017.FindingsThe results show that the overall KRE in Chinese universities is higher than the KTE. IAU has a significantly positive impact on KRE and KTE. PIA has a significantly inverted U-shaped influence on KRE and KTE and positively moderates the promoting effect of IAU on KRE and KTE.Research limitations/implicationsDue to the limitations of the data, this paper only selects several secondary indicators to measure KRE and KTE with reference to previous studies.Practical implicationsThis study enriches the future research of University–Industry cooperation and knowledge flow and it is conducive to promoting the efficiency of University–Industry knowledge research and transformation from the perspective of universities, enterprises and local governments.Originality/valueThis study proposes the concept of University–Industry knowledge flow and divides the knowledge flow into the knowledge research stage and the knowledge transformation stage based on the knowledge supply chain theory. Moreover, the paper expands the theoretical framework of the impact of IAU on the efficiency of University–Industry knowledge flow and provides findings on the moderating effect of PIA.

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.

Open Innovation Community for University–Industry Knowledge Transfer: A Colombian Case

Academia–enterprise collaboration is understood as a determinant that improves innovation and competitiveness. The mechanisms by which this collaboration occurs have awakened increasing interest among academics, as well as in the business sector. This research aims to identify how open innovation communities can mediate the academia-enterprise relationship, as well as the factors that are more affected by this mediation. Based on the literature, the article addresses the definition of open innovation communities (OICs), university–enterprise cooperation, knowledge transfer (KT), as well as an understanding of OICs as a mechanism for academia–enterprise transfer. An analysis of twelve OICs, conformed by professors, students, graduates, and experts from a Colombian higher education institution is performed. For the data analysis, a factor analysis involving structural equation modeling is carried out. Our results highlight the most important characteristics to take into account in the study of knowledge transfer when OICs are involved, and they also indicate the level of connection between these factors.

Knowledge creation in complex inter-organizational arrangements: understanding the barriers and enablers of university-industry knowledge creation in science-based cooperation

PurposeThis study aims to explore the factors undergirding knowledge creation in the university-industry complex inter-organizational arrangement. It builds upon social capital and relationship marketing theories.Design/methodology/approachThis study uses a qualitative research design. In total, 36 innovation champions involved in knowledge creation were interviewed to provide detailed insights into the process. A thematic analysis of the in-depth interviews was conducted.FindingsThe principal finding was that opportunistic behavior was a significant barrier to knowledge creation. In severe cases, the knowledge creation process was destroyed, resulting in lost investment. Principled behavior and investment in affect-based and cognition-based trust, through five critical trust development activities, provided the best path to successful knowledge creation.Originality/valueThis study contributes to the knowledge management literature by providing insights into the enablers and barriers to the formation of cooperation, a crucial antecedent to knowledge creation literature. It also affords practical implications for innovation managers and policymakers on how they can improve knowledge creation by using social capital and relationship marketing theory in complex inter-organizational arrangements.

Contribution of academics to university–industry knowledge exchange: A study of open innovation in Sri Lankan universities

Collaboration between universities and industry is currently seen as a vehicle to improve innovation throughout the economy by means of knowledge and technology transfer. This paper examines the contributions of university staff to the promotion of knowledge exchange between universities and industry in Sri Lanka. In this quantitative explanatory study the authors apply a deductive research method and develop a conceptual framework that incorporates demographic and institutional factors as moderators. Academics of state universities constituted the survey population and 178 responses were received. SPSS and AMOS statistical packages assisted in the data analysis and a structural equation model was employed to explore the moderating effects. The findings revealed that the engagement of academic staff in joint research, contract research, human resource mobility and training was very low, and that the participation of males was greater than that of females. The impact of age on knowledge exchange was not linear in Sri Lanka. Further, the study ascertained that only joint research and training were important in knowledge exchange and that the university–industry relationship was significantly moderated by institutional factors. Other than the quality of academic work, other individual factors did not significantly moderate the relationship. The authors provide policy recommendations based on the findings.

University-Industry Knowledge Collaboration in Chinese Water Pollution Abatement Technology Innovation System

University-Industry Knowledge Collaboration in Chinese Water Pollution Abatement Technology Innovation System

A University-industry knowledge transfer online education approach via a cloud-based database global solution

Knowledge sharing between different types of organisations, in this case the University-Industry (U-I) relation, contains barriers related to the differentiation of structure and purpose for each organisation. Both the university and industry have to make sure that they have access to data and information. This accessibility enables the value-added process of transforming data into knowledge. The purpose of this paper is the analysis of U-I cooperation– especially under the new online requirements – an illustration of how the knowledge is created and shared in the organisation based on the socialisation, externalisation, combination, and internalisation (SECI) model and how this is aligned to the value proposition. As a knowledge management example case, a database for the Centre for Energy Technologies of Aarhus University was developed that will overtime help the university to increase its value proposition and be the heart of knowledge exchange with the industry in an organised way. The value of this work is intended to pave the way in building structured working relations between the industry and academia, facilitating the means in order to achieve a higher degree of overall efficiency.

Why Most University-Industry Partnerships Fail to Endure and How to Create Value and Gain Competitive Advantage through Collaboration – A Systematic Review

<p><strong>Purpose</strong>: The collaborative work between universities and enterprises is increasingly important given the growing competitive environment, transformed by intense global competition, rapid technological change and shorter product life cycles. In this article several case studies are analysed, as well as relevant academic literature, to get an insight concerning the current relationship status between enterprises and universities.</p><p><strong>Methodology/Approach</strong>: The methodology is grounded on the literature review on University-Industry Partnerships, selected from indexed sources, and targeted to case-based experiences where practical feedback is given.</p><p><strong>Findings: </strong>It is shown that university-industry knowledge transfer contributes significantly to an increase of quality, productivity and economic value of businesses. It is found that the lack of controlling mechanisms and lack of efficient communication paths have a strong negative impact in collaboration. Key collaboration factors that support stronger relationships were compiled and discussed in support of better mitigation strategies.</p><p><strong>Research Limitation/implication</strong>: The limited availability of case studies reporting on operative improvements introduced by policy changes hinders the effectiveness of the findings.</p><strong>Originality/Value of paper</strong>: The paper analyses the collaboration of the university with industry based on case studies with a focus on value creation and how to gain a competitive advantage through collaboration.

Do demographic factors matter in university-industry knowledge exchange? A study based on Sri Lankan university system

Purpose This study aims to identify the effect of demographic factors on the relationship between academic contribution and university–industry knowledge exchange in Sri Lanka. Design/methodology/approach This study is of quantitative and explanatory type , which applied the deductive research method, and is conducted with minimum interference of researcher taking individual academics as the unit of analysis. The study collected data from 178 academics randomly through a structured questionnaire designed to analyze through statistical package for the social sciences and analysis of a moment structure statistical software. A structural equation model is applied to collected data to explore the moderating impact of the demographic factor on the university–industry knowledge exchange. Findings Overall involvement of academic staff in joint research, contract research, human resource mobility and the training with industry were was low in Sri Lanka. However, all four independent variables significantly associated with the knowledge exchange process from which only joint research and training had a statistically significant effect on university–industry knowledge exchange . Concerning demographic factors, only the quality of academic research significantly moderated the relationship between academic contribution and university–industry knowledge exchange process in Sri Lanka. Research limitations/implications This study considered only the university side of the university–industry knowledge exchange process. Practical implications This paper implies that gender, age and area of specialization did not have significant power to moderate the relationship between academic contribution and university–industry knowledge exchange process. Originality/value There is a lack of research literature discussing the moderating effect of demographic factors on the university–industry knowledge exchange process. In Sri Lanka, money and commercial benefits that received through industry partnerships had not been valued by academics. The majority considered the connection with industry and exchange knowledge as a responsibility that they should perform in return to free education received from grade one to graduation.

Knowledge transfer from universities to low- and medium-technology industries: evidence from Italian winemakers

The aim of the study is to explore the links that firms from low and medium technology (LMT) industries establish with universities for innovative purposes. Even though knowledge transfer from university to industry has generally increased over time, it has mostly been directed at firms in high-tech industries (HT) due to the belief that firms from LMT industries often lack the absorptive capacity necessary to take advantage of external knowledge. In the case of LMT industries, university-industry knowledge transfer has received less attention from management and innovation studies, and understanding the specific conditions where universities may contribute to the innovative effort of LMT firms largely remains unexplored. With the aim of contributing to this debate, the paper focuses on the wine sector, generally considered an LMT industry. Firstly, the study assesses to which type of innovation promoted by winemakers do universities effectively contribute. Secondly, the study examines under what conditions universities assume a relevant role in the innovative activity of LMT firms. To test our hypotheses, the study uses primary data collected through a survey targeting Italian wine SMEs and runs a set of econometric evaluations. Findings show that universities represent a relevant source of knowledge mainly for organizational and commercial innovation, but not for product innovation. For these purposes, university knowledge related to social sciences has a more relevant input for firms than does knowledge with higher scientific and technological content.

Varied university-industry knowledge transfer channels and product innovation performance in Guangdong manufacturing firms

ABSTRACT This study aims to investigate the extent to which Chinese firms engage in varied university-industry knowledge transfer channels and the impact on product innovation performance. Data was collected on 14 distinct types of channels used by manufacturing firms located at the centre of the pearl river delta in Guangdong Province of China. Our results revealed that varied channels has a curvilinear relationship with product innovation. Moreover, it exhibits a curvilinear moderating effect on internal R&D capability–innovation relationship. It negatively moderates R&D capability–innovation relationship at low range of varied channels, but the negative moderating effect weakens as the range increases and eventually is converted to a positive one after the range reaches a turning point. The findings furthered our understanding on varied university-industry knowledge transfer channels and the associated innovation benefits.

Forms and varieties of research and industry collaboration across disciplines.

Academic scientists' engagement with industry is a central mechanism in university-industry knowledge transfer and the development of collaborative research. However, most empirical studies are limited to researchers in technical disciplines. We extend the analysis beyond engineers to include broader disciplinary fields, including humanists, economists, medicine, biosciences and cross-disciplinary scientists. Our findings suggest that cross-disciplinary researchers and researchers in technical sciences engage in more industry interaction than their peers. The motivations for the choice of research area play an important role in industry collaboration. Furthermore, we identify three types of industry interaction (interaction modes) among researchers: 1. educational interaction, consisting of conferences or seminars, corporate training programs, or supervising thesis work; 2. research interaction, consisting of shared publications, research-related consulting, public research programs and contract research; 3. integrated interaction, consisting of joint research in shared premisesand employment contracts with companies.Of these, the educational and research interaction modes (1 and 2) are motivated by the possibility of individual academic advancement. Integrated interaction (3) is rare and significantly correlates with only one of the three types of industry cooperation motivations: commercialization of research findings. We conclude by identifying future research needs, opportunities for methodological improvement and policy interventions.

IMPACT OF INSTITUTION FACTORS TO UNIVERSITY-INDUSTRY KNOWLEDGE EXCHANGE: A STUDY BASED ON SRI LANKAN UNIVERSITY SYSTEM

Purpose: The study explored the impact of institutional factors have on the university-industry knowledge exchange based on the Sri Lankan university system.
 Methodology: The study is quantitative and explanatory by nature and it applied the deductive method and questionnaire survey strategy. The study conducted with minimum interference of researcher and individual academics is the unit of analysis. The types of knowledge interaction, university-industry knowledge exchange, and institutional factors were the independent, dependent and moderating variables respectively. A Structural Equation Model is deployed on collected data to explore the moderating impact of the institutional factor on the university-industry knowledge exchange.
 Implications: It implies that the level of joint, contract research activities, human resource mobility, and training of academic staff are largely wider on the conducive environment and sophisticated facilities of the university.
 Main Findings: First, study evidence that there are statistically significant impacts of type of interactions and institutional factors on university-industry knowledge exchange. Further, the study confirmed the moderating power of institutional factors over the knowledge exchange process.
 Novelty: There is a lack of research literature discussing the moderating effect of institutional factors on the university-industry knowledge exchange process.