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This paper aims to examine how the dynamic interplay of governance mechanisms of the university-firm R&D alliance reduces obstacles and enables the successful commercialization of research collaboration output.

A longitudinal case research and retrospective strategy were used to collect relevant data and information in the four university-and-firm alliance teams collaborating on R&D projects in Thailand during 2008-2014. In-depth interviews and meetings were conducted with representatives of all partners and R&D project teams.

The authors found that formal and informal control mechanisms act as complementary forms of governance. The informal control (trust) serves as the frame of intentions whether the formal control is interpreted as a guideline or a commitment. Both formal and informal control mechanisms must be put in place to successfully and sustainably develop collaborative research into a commercial product.

This study investigated four Thai government-funded research collaboration teams from a single industry. It would be worth investigating such research collaboration in other industries and those without any government funding.

This study applied an exploratory case research method which is rarely used in research on R&D alliance teams. It generates cross-functional insights on how to build trust in such R&D context, especially in an emerging economy.

How does university-firm collaboration affect the performance of both universities and firms? The purpose of this paper is to evaluate university-firm collaborations aimed at expanding the treatment effects of collaboration ambition on university academic performance as well as collaboration ambition focused on the firm’s production of innovation and financial performance for the top 110 US universities and the top 200 US R&D performing firms.

“Two studies, based on the three archival data sets (National Bureau of Economic Research-Rensselaer Scientific Papers Database and the Harvard Dataverse Network (DVN) US Patent Citations database and Compustat database), are undertaken in the top 110 US universities and the top 200 US R&D performing firms.” The study introduces a theoretical model that explicitly addresses collaboration diversity, number of collaborations, knowledge stock and the endogeneity problem that is generated by self-selection of collaboration ambition in university and firm’s performance.

The results suggest that the effects of adopting proactive collaboration decision on academic performance are insignificant in the firm subsample. However, more interestingly, the authors find supporting evidence of the negative impact of collaboration on university groups. The authors also find that collaboration diversity, knowledge stock and collaboration ambition lead to stronger firm performance but the number of collaborations is smaller on firm performance. Furthermore, the authors find that collaboration ambition moderates the positive effect of the number of collaborations on firm performance.

University-firm collaboration is a multifaceted relationship, suggesting that the empirical analysis can be interpreted through the university and the firm view to enhance the understanding of the collaboration for performance creation. This study articulates the positive role of collaboration diversity, knowledge stock and collaboration ambition and the negative role of the number of collaborations on university-firm collaboration in terms of university and firm performance. Moreover, proactive collaboration ambition has the positive effect of a higher number of collaborations on firm performance. The authors conclude that policy should refrain from overly focusing on collaboration diversity, number of collaborations, knowledge stock and collaboration ambition, and the authors consider the interactions between the number of collaborations and collaboration ambition on university-firm collaboration when discussing their effects on mutual performance.

This study demonstrates the effects of university-firm collaboration on academic performance. In addition, the authors discuss the factors that influence collaboration to help the firm to increase its innovation and financial performance. Therefore, it would be interesting to see simultaneously how university-firm collaboration affects the performance of both partners.

The purpose of this study is to introduce a conceptual framework for knowledge transfer between Chinese firms and universities around the world, based on a joint learning process. The transfer of knowledge is important to increase the innovative capabilities of Chinese firms by accessing more sources of new knowledge not available locally.

The framework is derived from the resource‐based perspective. Its main characteristics are defined, and the required stages are explained. The framework stresses the dynamic relationship among all stages, and the active interaction between interorganizational and intraorganizational learning processes.

Having a suitable process for selecting a partner is the pre‐condition for achieving effective knowledge transfer between university and firm, because it determines similar capabilities and how both partners can enhance the requirements of each other. In addition, the joint learning experience between university and firm will be rewarding to a large extent if high transparency, collaborative intent, informal communication and organizational commitment are adopted as the basis for joint learning.

The study proposes a conceptual framework for knowledge transfer between Chinese firms and universities around the world, based on previous research in this domain. An empirical study will be beneficial to support this framework and to suggest needed modifications.

The study provides a greater understanding of the importance of a joint learning process between university and firm to support the innovative capacity of a firm. It emphasizes that the successful collaboration with a university can make a firm function as an external R&D hub.

This paper aims to explore the determinants of firms’ attitudes to R&D cooperation with universities with the goal to propose a model of knowledge transfer university-firm.

By understanding university-industry cooperation as a process, the model in this study is based on two factors: the “promoter of university-industry relations” (PUIR) and a technological system that is able to match the research supply of universities with the demand for innovation of the firms. A total of 375 firms, 420 research groups and 18 experts in knowledge transfer from Spain, Portugal and France have been involved in this study.

This study provides the first evidences of the relation between the number of matches’ demand-supply of research, the number of university-firm relations and the willingness to cooperate; all of these presented in the knowledge transfer model. Results also reinforce the utility of the role of PUIR and the matching system in the open innovation process.

However, more evidences are necessary to get a complete validation of the model. In the future, the continuous utilization of the matching system by the PUIRs of the selected regions will allow the authors to evaluate how well the system is working by analysing the possible increases in formal collaboration university-firm in the area of R&D.

This study contributes to the literature through aligning the open innovation and intellectual capital theories in the specific and complex context of university-firm collaboration. Also, little research regarding this topic has been noticed in SUDOE European Union (EU) countries (SUDOE is an EU territorial cooperation programme that supports regional development by funding transnational projects).

This study aims to understand in what way international cooperation between universities and/or firms can be seen as a vehicle in the transfer of knowledge and innovation for implementation of environmentally sustainable practices.

To do so, a qualitative approach was adopted, resorting to the case study method: the EdgeWise project. Data were obtained from interviews, documentation provided by partners and observation, and the content analysis technique was also used.

The results lead to the conclusion that this type of international cooperation is supported by solid dimensions, such as knowledge transfer and appropriate choice of partners. In addition, the dimension related to organisational culture is not considered a barrier in the cooperation process studied here, but rather as a form of learning among partners.

The empirical evidence suggests that it will add value to the understanding of the various issues surrounding resources (water and energy) that differ from country to country. However, the administrative-bureaucratic dimension is identified as a barrier to this type of cooperation/project, with its analysis being suggested for future studies.

This innovative study shows that the literature and the case study made identified various dimensions; motivations, barriers and drivers, of knowledge transfer, choice of partners and organisational culture. In addition, this study contributes for international universities-firms cooperation in sustainability area.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This chapter aims at providing an understanding of the research and devlopment (R&D) process in the pharmaceutical industry, by exploring the methodological challenges and approaches in the assessment of the determinants of innovation in the pharmaceutical industry. It (i) discusses possible methodological approaches to model occurrence of events; (ii) describes in detail competing risks duration models as the best methodological option in light of the nature of pharmaceutical R&D processes and data; (iii) concludes with an estimation strategy and overview of potential covariates that have been found to correlate with the likelihood of failure of R&D pharmaceutical projects.

This paper aims to analyse the influence of cooperation on the degree of novelty of technological innovations introduced by industrial firms in Argentina. This influence is analysed from three perspectives: cooperation by partner type [business partners or scientific and technological centres (S&T) partners]; cooperation by number of partner types, from no cooperation to cooperation with two partner types; and cooperation by goals pursued by firms.

The data come from one of the last national innovation surveys conducted in Argentina. The study controls for endogeneity, using instrumental variable procedures within the conditional mixed-process (CMP) framework.

The main result is the influence of cooperation with universities and S&T centres on the introduction of more novel innovations, which was found both in estimations with and without endogeneity correction. This influence was verified for more complex goals (R&D, technology transfer and industrial design and engineering) as well as for less complex ones (tests and trials, human resources training, quality management and certification). Business cooperation seems to impact only on a lower degree of novelty for more complex goals. The increase in the number of partners that the firm cooperates with, from no cooperation to joint cooperation with two partner types, influences more novel innovations.

Limitations and proposals for future research are discussed at the end of the study.

The results of this study contrast with the high propensity to cooperate with business partners shown by firms in Argentina and other Latin American countries. Therefore, this paper may help formulate more effective policies to promote cooperation conducive to firm innovation performance. Limitations and proposals for future research are discussed at the end of the study.

Although there is empirical evidence on this topic for developed countries, firm-level studies on cooperation and degree of novelty are scarce for Latin America. In addition, this paper analyses cooperation not only by type of partner but also by type of goal. This study attempted to control for endogeneity by using instrumental variables within the CMP framework.

This paper attempts to propose an integrated model for measuring the knowledge transfer effectiveness in university‐industry alliances. The so‐called “RDCE” model is thereby proposed as an integrated model for measuring the knowledge transfer effectiveness. By combining inter‐organizational relations (IORs), knowledge‐based view (KBV) and resource‐based view (RBV) of firms, this paper aims to focus on the influence of determinant factors such as partner complementarities, partner attributes, the characteristics of the coordination and relationship quality between industrial companies and universities that may lead to the effectiveness of knowledge transfer.

This framework thereby clarifies how mediating variables influenced the paths that constitute the direct, indirect and total effects of mediated models by integrating moderated regression analysis together with bootstrap resampling methods to ensure the precision in estimating confidence intervals of indirect effects and path analysis using structural equation models to test all the hypotheses simultaneously for the robustness of the results and conclusions.

The statistical results reveal that the proposed model has a significant mediating effect that contributes to knowledge transfer effectiveness. Only partner attributes and relationship factors have a direct impact on the effectiveness of knowledge transfer. This appears plausible since mere complementarities and coordination between partners may not lead to learning or knowledge transfer, which requires a certain depth of the partner interaction in terms of the specific attributes of partners, coordination and relationship quality.

The authors assumed that the alliance constitutes partnerships between firms of roughly equal size and market power. Therefore, this study provided only broad perspectives of collaboration among alliance partners, and did not capitalize on different degree of alliance integration and different types of collaboration.

Managerial suggestions on how to improve their knowledge transfer effectiveness are also provided at the end of the text.

There are numerous studies examining alliance network performance. Very few studies, however, have examined detailed collaborative activities in dyadic university‐industry partnerships and potential constructs for measuring knowledge transfer and commercialization in the research and development alliance between industrial firms and university context.