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We examine the determinants of multinational firms’ propensity to conduct R&D activities in host countries, with specific attention to the influence of host countries’ university research. We consider heterogeneous locational drivers related to the type of R&D activity: basic research, applied research, development for local markets, and development for global markets. Drawing on official survey data on R&D activities by 498 Japanese multinational firms in 24 host countries and estimating two-stage models, we find that the likelihood that firms conduct R&D in a host country is generally increasing in the strength of university research. Conditional on a firm’s R&D presence, university research strength is associated with a greater propensity to conduct (basic) research activities rather than (local) development, while the intensity of host country university–industry collaboration is most strongly associated with applied research. Host country experience and the depth of the firm’s manufacturing presence are also associated higher propensities to engage in research.

The purpose of this paper is to construct a novel delay grey incidence analysis model to analyze drivers and obstacles of university R&D performance.

With respect to the fact that university R&D activities typically experience two stages of knowledge creation and technology transfer, and different drivers and obstacles come into play to affect the conversion of R&D investment to outcomes at each stage, based on the thought of grey incidence analysis and the specific characteristics of science and technology (sci-tech) development, a novel delay grey incidence analysis model is proposed in this paper, and then according to the yearbook statistical data, Chinese university R&D activities are investigated and the drivers and obstacles of university R&D performance are analyzed.

The results show that the R&D full-time staff and R&D funds of basic research are the key drivers of influencing factors, and the sci-tech innovation talents in universities’ R&D institutions and experiment development funds are the restraining factors to improve R&D performance in the stage of knowledge creation; the expenses of R&D achievement application and technology service and the full-time staff of achievement application and technology service are the key drivers and obstacles of influencing the aggregate amount of patent sale respectively.

This research helps policy makers to reflect on their university R&D policies and understand how to enhance the technology transfer rate in China.

The paper succeeds in identifying key drivers and obstacles of affecting university R&D performance in China by examining the input and output incidence at both the knowledge creation and technology transfer stages.

This paper aims to determine the mediating effects of government-funded research and development (R&D) projects in the relationship between the competence factors of universities and the performance of university–industry cooperation.

This study has been conducted to analyze the mediating effect of government- and enterprise-funded R&D projects in consideration of the performance during university–industry cooperative projects. In this study, a three-step analysis of the mediating effects (Baron and Kenny, 1986) and Sobel Test are taken for the empirical analysis.

In the result, R&D funding from the central government partially mediates the performance of university–industry cooperation when the research capacity of the full-time faculty and the size of the Technical Licensing Office (TLO) are taken as independent variables. R&D funding from the central government does not mediate university–industry cooperation when the size of the center for university–industry cooperation is an independent variable. However, R&D funding from a local government does not mediate the performance of university–industry cooperative projects for any chosen independent variables. The results of this study suggest a direction for governmental funding in R&D projects to promote performance during university–industry cooperation. Another requirement is for universities to expand their research capacity and the operations of their TLO.

The majority of former research studies on university–industry cooperation and its performance have focused on the university’s research capacity, the competence of the TLO and the traits of the university.

It is widely accepted that enterprises obtaining academic discoveries through R&D collaboration improve their innovation performance. However, it is not necessarily true in emerging economies, such as China and post-socialist countries in Europe. The purpose of this paper is to fill the gap by investigating how R&D collaboration between industry and academia (i.e. universities and research institutes) affects the industrial innovation performance; and whether and how intermediaries moderate their relationships.

This paper constructs the research model according to the knowledge production function, and the pooled ordinary least square regression is used to verify our hypotheses.

Evidence from a sample of Chinese industrial enterprises in thirty provinces spanning from 2009 to 2014 suggests that R&D collaboration with research institutes (CWR) is positively related to innovation output, while R&D collaboration with universities (CWU) exerts negative effect on innovation output measured by sales revenue of new product (NPSR). The significant moderating role of technology transfer institutions is confirmed in the negative relationship between CWU and NPSR.

This paper empirically examines the moderating role of intermediary organisations in academia–industry cooperation and industrial innovation, and has practical implications for the government to formulate policies to improve the quality and effectiveness of cooperation between academic and industrial sectors. These results vary in inland and coastal areas, which suggest the policy makers to formulate policies according to local conditions not only in China but also in other countries, like European countries.

Triple helix theory stresses co‐evolution and interaction among governments, enterprises and universities, and is paid great attention by governments, universities and enterprises worldwide. The purpose of this paper is to investigate the role that Chinese government R&D investments play in the interaction between enterprises and universities.

Basing on provincial panel data of Chinese universities from 2004‐2010, the impact of government R&D investments on patent technology transfer activities of Chinese universities is studied by empirical analysis. More specifically, the paper examines the impact of both Chinese government R&D funding and national R&D programs on the number and the revenue of patent technology transfer contracts.

The study finds that the amount of government R&D funding and the number of 973 Programs in one region have significantly increased the number and the revenue of patent technology transfer contracts in that region. Moreover, the number of National S&T Pillar Programs, 863 Program and National Natural Science Foundation Program are also determinants of the number of patent technology transfer contracts.

This paper studies government's role in university‐enterprise patent technology transfer activities in a Chinese context. It reveals a government‐dominant position to promote patent technology transfer activities in Chinese triple helix model. It also provides a reference for decision makers in governments, industries and universities.

This issue is a selected bibliography covering the subject of leadership.

The purpose of this paper is to examine the collaboration strategies employed by collaborating small‐ and medium‐sized enterprises (SMEs) and university researchers for initiating and optimizing the process and outcome of R&D collaboration.

The paper is based upon a qualitative study of the total population of university departments and SMEs involved in collaborative research projects sponsored by a new governmental programme in Denmark, the aim of which was to build new R&D alliances between industry and universities.

The findings show how partners choose to pursue difference short‐ or long‐term strategies to optimize the process and outcome of university‐industry (UI) collaboration. Some collaborations were thus informed by a short‐term strategy aimed at achieving immediate R&D results. However, to a high extent, many SME partners relied upon a long‐term strategy aiming at developing UI relations beyond the immediate project and practical learning. A variety of shifting strategies shape researchers' decisions during UI collaborations, which thus convey different notions of success.

The findings of the present research point to the importance of taking the diverse reasons and micro strategies informing collaborative efforts into account when studying UI collaborations.

Different strategies may prove successful in optimizing the outcome of UI collaborations depending upon, e.g. partners' previous collaborative experiences. Policies should incorporate some openness towards the differential premises and reasons for UI collaboration.

Relatively little research has addressed the development of UI relationships from the micro‐level perspective of the discretionary decisions and strategies of collaborating researchers.

The purpose of this paper is to present an approach to start industry–university (I-U) collaboration through a stepped process aimed at building a portfolio of research and development (R&D) projects.

It devises from an 18-month action-research program held between a multinational automotive manufacturer and the a top-ranked Brazilian university.

The three-stage R&D shared portfolio methodology results from a combined application of quality function deployment-like correlation matrices and roadmapping. A first matrix tackles industry interests and correlates product performance dimensions and components to reveal broad research areas of interest. A second matrix correlates research areas and engineering competences, highlighting the types of the required know-how from the university standpoint. Thirdly, academic experts help to fill a roadmap-like layer with possible collaborative R&D deliverables over time.

Since the study lies on a single experience, extensions to other contexts should be made with care. However, the proposal offers robust rationale and a set of supporting tools to nurture new applications.

Theoretical and methodological reflections help managers tackling the long-standing problem of setting a shared R&D agenda.

Literature on I-U collaboration tends or to over-emphasize the role of technology transfer offices in promoting the partnerships or to seek implications for public policy. This research offers a valuable approach to build shared R&D project portfolio from a managerial viewpoint, filling an academic gap and offering guidance for managers in both sides.

The purpose of this paper is to study how transactive memory systems (TMS) facilitate the transfer and absorption of knowledge in the presence of quality management (QM) within a university research and development (R&D) environment.

The data come from a simple random sampling of 257 Spanish university R&D groups in nine different areas of knowledge. To verify the hypotheses, the authors used multiple linear regression analysis with a moderating effect.

The conclusions show that the relationship between knowledge transfer (KT) and TMS is significant when QM practices are included as a moderating variable but that this is not the case for knowledge absorption (KA), which does not show any effect.

The effects described were found in a sample composed of various R&D sectors taken from a single country and not distributed equally. Further, the perception analyzed represents the judgment of a single manager.

It is interesting to study this interaction in university R&D because of the important role R&D plays in the development of regions. Improving the internal processes of this research helps to make its results more competitive. This study contributes information on non‐business management and introduces university R&D to the use of QM practices.

The authors found no studies that test empirically the moderating effect of QM practices on the relationships studied in university R&D. The paper's results contribute information to help fill this gap and demonstrate once again that QM practices can be applied to any environment.

The purpose of this paper is to assess how technology‐based university research drives innovation in Europe and China.

This paper draws on extensive theoretical research and literature reviews, and presents a framework based on theories on networking, knowledge creation and innovation. It then introduces three European cases to illustrate practical applications of the framework, and also links the findings to three Chinese cases to make comparative observations as well as recommendations related to Triple Helix concepts and their implications in the China context. It addresses the issue of how learning from universities can enhance company flexibility and performance in innovation, and outlines three different models of collaboration.

The framework and empirical research suggests that weak ties are useful for inspiration in exploration, but that strong industry‐university (I‐U) ties are required to support exploitation. This finding applies both to Europe and China in the industries covered.

This paper provides a new theoretical rationale for I‐U learning alliances as a natural way out from the managerial problem of trying to perform both exploration and exploitation within the same company boundaries. Through the theoretical framework, the academic science domain becomes a logical partner to handle the full phase of exploration and support the process of exploitation. The presented European cases of Bang & Olufsen, Combibloc and Porsche offer new insights into how to perform this act in practice, while the three China‐related cases allow us to cross analyse empirical findings and draw initial conclusions with policy implications for China.