University-industry knowledge transfer - unpacking the “black box”: an introduction

1. Introduction

Nowadays, the greater openness of globalisation in access to research data and new forms of funding, such as crowd funding for research, are changing the way institutions foster the knowledge transfer (KT) from universities to society (e. g. OECD, 2013). The need to share knowledge between university and industry has become gradually obvious in recent years (Carayannis, Grigoroudis, Stamati, & Valvi, 2019).

Over time, research institutions were perceived as a source of new ideas and industry offered a natural path to maximise the use of these ideas (EC, 2007). KT refers in a broader sense to the multiple ways in which knowledge from universities (and public research institutions) can be exploited by industry in order to create economic, social value and competitiveness (Carayannis, Provance, & Grigoroudis, 2016a; Ferreira, Raposo, Rutten, & Varga, 2013).

At the same time, it has become clear that universities need to play a more dynamic role in the industry relationship in order to maximise the use of research results. This new role (commonly called as third mission) requires specialised staff to identify and manage knowledge resources with business potential (EC, 2007).

This Special Issue (SI) aims to contribute to the debate on U-I KT and on the changing organisation of knowledge creation (and co-creation) activities. Furthermore, it attempts to elucidate the complex nature of this subject combine to offer a wide range of interesting questions and claim a multiplicity of research methodologies in this area.

Several research questions were at the foundation of this SI:

How effective are universities and research institutions in exploiting and commercialising their research?

How different are the attitudes of universities and firms towards knowledge spillovers and technology transfer?

What are the most widespread forms of collaboration and KR channels between U-I interactions?

What are the benefits, impacts and/or obstacles to U–I collaboration?

What university scientists think about cooperation with private enterprises?

What kind of internal context facilitates the institutionalisation of KT activities between industry and university research centers?

How KT mechanisms interweave with one another? What follows what in U-I interactions?

This special edition contains twelve articles in which each of them makes a valuable contribution to the search for answers to one or more of these questions.

2. University-industry knowledge transfer

Relationship between University – Industry (U-I) can be as part of the more general open innovation framework. Universities are an important external source of innovations for business (Carayannis, Goletsis, & Grigoroudis, 2018; Hanel & St-Pierre, 2006; Link, Siegel, & Bozeman, 2007; Silva, Ferreira, Carayannis, & Ferreira, 2019). Firm size and scientific excellence also matter, large firms innovate more openly than small firms and are more likely to cooperate with university or government institutions on innovation (OECD, 2008).

Patents, licences and spin-offs are undoubtedly important channels for commercialising of research, but other channels such as collaborative research (e.g. public-private partnerships, university-industry cooperation), mobility of students and faculty seem to evidence an increasing relevance (Carayannis, Rozakis, & Grigoroudis, 2016b; Hermans & Castiaux, 2017). Entrepreneurship education has emerged as a motivation to promote KT. Licencing and technology transfer offices (TTOs) are also evolving in search of more effective operational models. Many universities have pursued to change TTOs, creating new models and exploring new approaches to intellectual property ownership.

Initiatives to increase KT have become a complex, multifaceted, multi-actor and multi-level endeavour. Due to policy makers’ recognition of the broader channels resulting from research beyond the patent-licence-idea model, KT policies have expanded and are often combined with the university, economic, industrial, and regional policies to enable a systematic impact and broader synergies.

New transfer initiatives have not only become institutionalised by governments, but also by public research organisations. As consequences of increased university autonomy and a changing global and local environment, institutions themselves are reforming and experimenting with initiatives that reflect each institution’s legislative, financial and cultural context.

Moreover, dealing in complex environments, implying the application of continuously changing “spots” of knowledge, assumes that firms do not have this knowledge within their borders, which requires strong connections with players and organisations outside these limits (Anand, Glick, & Manz, 2002). Firms pursue universities knowledge for a variety of reasons (e.g. OECD, 2013) and there are different ways for firms to directly access university knowledge (e.g. licencing, collaborative research partnerships, contract research, etc.).

In addition to firms, there are also benefits and costs that arise for academic partners. Governments offer incentives for business to engage in alliances and cooperative research efforts. Due to the growing complexity of technologies, the formation of strategic university-industry-government R&D consortia has intensified in recent years.

These new trends open new “windows of opportunity” for universities, as potential partners for firms (and industry). Greater collaboration in U-I relations can transform into greater economic development (Casaramona, Sapia, & Soraci, 2015), either through instruments capable of generating technological and knowledge spillovers (Audretsch & Link, 2019; Ferreira, Dana, & Ratten, 2017;) to accurate market failures in the field of innovation (Jonsson, Baraltu, Larsson, Forsberg, & Severinsson, 2015; Laine, Leino, & Pulkkinen, 2015), and to obtain a superior return on R&D investments or able of enhancing the emergence of a greater number of start-ups, the increase in the number of patents and licences, joint R&D projects (Cohen, Nelson, & Walsh, 2002), or joint scientific publications.

Large differences arise in the way KT takes place in diverse countries and diverse universities (Ferreira et al., 2013; Polt, Rammer, Gassler, Schibany, & Schartinger, 2001). Research that enhances insight in the properties and performance of KT in different countries, regions, industries, and universities can help policymakers to enhance their policy regarding KT, and by doing this they can enhance economic growth.

3. Contents of the special issue

The twelve papers in this special issue cover a series of inter-related topics. However, it is possible to identify three central themes approached by the authors (see Table 1): 1) University knowledge transfer; 2) University-Industry collaboration; and 3) University-Industry knowledge transfer issues.

Table 1. Overview: university-industry knowledge transfer – unpacking the “black-box”.

Themes	Topics	Authors
University knowledge Transfer (KT)	Multi-criteria decision system for university KT	Almeida et al. (2019)
	Science and university innovation performance	Peris-Ortiz, García-Hurtado, and Devece (2019)
	Formal-informal channels of business schools	Dang et al. (2019)
University-Industry (U-I) Collaboration	U-I collaboration and regional innovation	Hong et al. (2019)
	U-I collaboration bases on sex criteria	Calvo et al. (2019)
	U-I collaboration and scenario analysis	Ashyrov et al. (2019)
	Innovation through U-I partnership	Thomas and Justin Paul (2019)
	Cooperation between universities and firms	Teixeira et al. (2019)
University-Industry (U-I) Knowledge Transfer (KT) issues	U-I KT strategies and leveraging social capital	Robertson et al. (2019)
	U-I KT on the smart specialisation strategy	Marques et al. (2019)
	Knowledge heterogeneity in U-I	Huosong et al. (2019)
	Public policy and U-I R&D nexus	Faria et al. (2019)

3.1. University knowledge transfer (KT)

Almeida, Ferreira, and Ferreira (2019) developed a multiple-criteria decision support system for evaluating knowledge transfer from university and performance. Based on the basis on a panel of knowledge transfer specialists, with different professional perspectives and experiences from Portugal, this study shows an evaluation system based on the multiple-criteria decision analysis (MCDA) approach. This instrument is a valuable tool for the strategic management of universities driving up levels of connectivity between university and economic actors. Specifically, the authors suggest that university managers can use the techniques applied to make strategic decisions when looking for to foster the knowledge transfer to society at large.

Peris-Ortiz et al. (2019) investigate the influence of balanced scorecard implementation on Latin American universities’ research and innovation performance. Based on data from interviews with managers at the universities, the study revealed similar patterns of indicators to measure performance in public universities and evidence that these indicators develop favourably following the implementation of the balanced scorecard tool. Furthermore, the authors argue that the use of the balanced scorecard has led to considerable advances in the performance of theses universities, fundamentally because of the assessment, promotion and payment system.

The study of Dang, Jasovska, Rammal, and Schlenker (2019) is based on knowledge transfer practices of 10 Australian universities and provide understandings into how these universities respond to the funding cuts faced by the university sector. Based on a case study approach, the authors explore the strategic responses of Australian universities on science, technology, engineering, and mathematics areas. They found that the universities use mutually formal and informal channels to transfer knowledge with industry partners.

3.2. University-industry (U-I) collaboration

Hong, Zhu, Hou, and Wang (2019) examine the effect of academia-industry collaboration on regional innovation convergence in China, taking into account the flow of talents, regional economic development level, and degree of openness. Using the methods of σ-convergence and β-convergence to analyse panel data of 30 provinces, from 2005–2015, the results show that academia-industry collaboration stimulates regional innovation convergence in the central area. The authors found that both university-industry cooperation and industry-research-institute cooperation inhibit innovation.

Calvo, Fernández-López, and Rodeiro-Pazos (2019) attempt to analyse the attitudes and decisions of research groups led by men or women towards the collaboration with firms in research and development joint projects. Based on a sample of 420 research groups of eight regions of Spain, France, and Portugal, the authors analysed the interest of the research groups to collaborate and if this interest change according to the sex criteria. The evidence shows that women are worse positioned in the social networks of collaboration and commercialisation with industry than men are. It is shown that the effect of some variables in collaborating with firms differs depending on the sex of the research group leader.

On the other hand, Ashyrov, Alunurm, Pentus, and Maaja Vadi (2019) aim to forecast the future of the knowledge-intensive economy in Estonia context. Based on a scenario analysis approach, the results reveal that sustaining free-market competition is one of the crucial elements of knowledge-intensive economy. At the same time, the authors used this forecast as a basis for providing policy suggestions looking at plausible future scenarios for Estonia, which U-I collaboration is seen as a sustainable knowledge transfer mechanism.

Based on an integrated view, Thomas and Justin Paul (2019) developed a theoretical model that attempts to enrich the quality and effectiveness of the KT and its utilisation for inducing innovation and technology. The authors aim to understand the factors influencing the KT in a U-I and to finding how social capital can facilitate knowledge KT in that context. The authors argue that the relationship between KT determinants, mediators, and innovation as an outcome of social capital will help industries and universities to conceive ways on how to foster and stimulate KT among network members. Furthermore, they suggest establish and validate the proposed model in future research.

Teixeira, Veiga, and Fernandes (2019) analyse how the KT takes place between the higher education sector and the companies. Based on a sample of 500 Portuguese companies, they show that there is cooperation between companies and institutions of higher education when entrepreneurs are younger, and companies are located in urban areas. The authors argue that this cooperation is favourable to greater innovation as well as greater financial performance.

3.3. University-industry (U-I) knowledge transfer (KT) issues

Robertson, McCarthy, and Pitt (2019) argue that U-I partnerships emphasise the transformation of knowledge into products and processes which can be commercially exploited. Thus, they attempt to understand how social capital in university-industry partnerships affect knowledge transfer strategies, which impacts on collaborative innovation developments, across three different countries (Canada, Malta, and South Africa). The authors attempt to explore the comparative presence of social capital in KT strategies supports in better understanding how U-I partnerships can position themselves to facilitate innovation. A social capital U-I KT framework is offered to guide U-I knowledge partners to align their knowledge strategy with their competitive domain.

Marques, Marques, Braga, and Marques (2019) attempt to assess the perceptions stakeholders on the implementation of the smart specialisation strategy in a region of Portugal, with a particular focus on technology transfer activities. Based on a qualitative methodology through interviews applied to the actors in the region based on the eight priority domains of smart specialisation strategy in this region. They conclude that the stakeholders’ perception did not match with the smart specialisation strategy defined by the policy makers. They attempt to contribute to a better understanding of the real perception of universities and industry on TT in the context of smart specialisation strategy and they suggest a need for ongoing evaluation and adjustments of smart specialisation strategy domains by policy makers to address them to the real necessities of the industry.

Huosong, Qingdi, and Zhang (2019) conduct an exploratory case analysis based on the successful knowledge transfer between a textile university professor and Shandong Xu’s Ruyi Textile Enterprise in China. Based on interview and video data, the authors attempt to investigate the existing problems in U-I KT from the perspective of knowledge heterogeneity. They found out that the successful industrialisation of university research is narrowly related to its KT.

Faria, Mixon, and Upadhyaya (2019) address under-theorization of the Triple Helix hypothesis examining how public policies affect the production of basic science at universities, facilitate interaction between universities, governments and firms. Bases on an economic model, the authors conclude that the interaction between U-I is mediated, regulated and incentivised by the government, which puts forward four specific policies: past investments in science capital; stimulus of patenting efforts; innovations subsidies; and regulation of researchers’ employment and compensation.

4. Conclusion and future agenda

The objective of this special issue was to bring together recent developments and methodological contributions that attempting to unpack the “black box” within the University-Industry knowledge transfer field. Mostly, the papers in this issue contribute to a better understanding of the University-Industry knowledge transfer topic. Furthermore, the papers included in this special edition suggest some topics for future agenda and they can be shortened as follows:

1. Conducting comparative studies to confirm the importance of knowledge transfer evaluation systems with a broader scope and greater capability to focus the attention of both university and economic actors;

2. Understanding better the role of universities in the process of KT. Definitely, the growing need to improve the education system to adjust to current industry demands has led to the implementation of organisational performance measurement systems as strategic tools;

3. Identifying how different national research and funding agendas quick strategic responses from universities, and specific practices in their U-I KT efforts;

4. Exploring the role of different stakeholders on the effective flow of technology among academic organisations and industrial sectors by breaking the barriers to knowledge spillovers and building intermediary platforms for technology transfer;

5. Analysing policies and incentives systems that motivate leaders to show concern in cooperation with firms and evaluating the success of these mechanisms in encouraging KT in areas dominated by female researchers;

6. Conducting longitudinal studies to monitor the change in U-I collaboration positioning over a period of time or to assess what dimensions impact the output of the U-I partnership;

7. Understanding the degree of knowledge heterogeneity between the U-I partners. The U-I KT cooperation needs to adapt to different situations to ensure effective value creation;

8. Refining the theory and stimulate further research on the domain of U-I KT.

We assume that this special edition will pave the way for future research, as there is a number of challenges which not been addressed here and they certainly deserve a future reflection.

Acknowledgments

We are grateful to KMR&P Editors, Giovanni Schiuma, Tom Jackson, and Antti Lönnqvist, as well as to our team of reviewers for insight and critical comments. Without their support, it would not have been possible to do this special issue.

Disclosure statement

No potential conflict of interest was reported by the authors.