Search results

Despite evaluating the performance of university-industry alliances being extremely important, scholars have not developed any structured and commonly accepted systems of indicators aimed at measuring the results of these collaborations. In this article, the aim is to review the literature on the evaluation of the performance of university-industry alliances and to identify a series of issues that future studies on this topic should take into account.

The paper opts for a literature review on university-industry collaborations. The review is based on papers in management, economics, and organization science. Systems of indicators to evaluate the performance of these collaborations are discussed. Directions for further research are proposed.

The literature review on firm-industry collaborations highlights a large number of contributions on the topic. However, it shows that there is still room for further inquiry on systems of indicators to evaluate the performance of these collaborations.

The literature review offers a good guideline to researchers intending to study the performance of industry-university collaborations. The discussion on the system of indicators paves the way to further empirical research on the topic.

The authors are confident that the paper has interesting practical implications. Indeed, it is a valuable guideline for policymakers, university managers, and entrepreneurs interested in evaluating the performance of industry-university collaborations.

Industry collaborations are the third mission of university systems. When this mission is accomplished in a proper manner, it benefits firms, universities, and society at large.

The paper adds to the debate on university-industry collaborations by offering literature on the topic with a particular emphasis on an under-researched theme: systems of indicators to evaluate the performance of these collaborations.

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.

Strategic alliances generally represent inter‐firm cooperative agreements aimed at achieving competitive advantage for the partners. In recent years, there has a dramatic increase in strategic alliances by multinational firms.This paper aims to explore the essence of these alliances and why they have become such a growing area of research in business in recent years.

Discusses strategic alliances between corporations and institutions of higher education. The major underlying motives for creating these alliances and the critical success factors are also discussed. The paper also analyzes the success stories.

Highlights the major advantages for the academic community – research funding and practical learning opportunities for students – and for industry – lower research and development costs and technology transfer opportunities that affect competitiveness. The drawbacks may include the partners’ different working cultures and values. Finds that alliances must be supported by continuous learning and restructuring processes to overcome the differences.

Extracts the valuable lessons that might help others to effectively utilize strategic alliances between corporations and institutions of higher education.

To clarify divergent conclusions on the impact of alliances on green innovation (GI), this study aims to examine the non-linear relationships between dual alliance and GI, as well as the mediation of green knowledge reconstruction (GKR) and the moderation of alliance tie strength.

Based on the theory of knowledge-based view, a moderated intermediary model is constructed by introducing GKR and alliance tie strength. The hypotheses are validated by using hierarchical regression analysis and bootstrapping method, with questionnaire survey data collected from 316 manufacturing firms in China.

Empirical results show that both exploratory alliance and exploitative alliance have an inverted U-shaped effect on GI, in which GKR plays a mediating role in the above relationship. Moreover, alliance tie strength weakens the intermediary role of GKR in the relationship between exploratory alliance and GI, whereas it enhances the intermediary role of GKR in the relationship between exploitative alliance and GI.

Findings reveal the non-linear effects of dual alliance on GI and clarify the inconsistent conclusions by proposing the moderated intermediary effect model. Moreover, this research reveals the mechanism of dual alliance on GI through the mediation of GKR and enriches the boundary conditions by integrating the moderating role of alliance tie strength.

The purpose of this paper is to synthesize the extant literature on green innovation (GI), and more importantly, to provide future directions for GI research from the innovation ecosystem (IE) perspective.

A systematic literature review is conducted to summarize the status of current GI research, followed by content analysis to identify connectivity and crossovers between key concepts in the bodies of GI and IE literature. Then, the authors propose a green innovation ecosystem (GIE) framework and offer recommendations for future research on GI.

It is evident that the bodies of GI and IE literature overlap on the roles of external actors, and yet, there is scant research investigating GI activities from the IE perspective. Moreover, there are multiple directions worthy of future research applying the proposed GIE framework.

Though the concept of ecosystem has become pervasive in innovation management research, this study is one of the first works to introduce IE concepts and propositions in the GI research context. This paper provides new knowledge on GIEs and sets the basis for further investigation.

Pressures from globalization and the knowledge‐based economy are transforming the traditional role of universities. Universities are being targeted by policy makers because they are the largest “knowledge‐based” institutions in the regions. They have concluded that universities will aid economic regeneration if they disseminate their knowledge and expertise through industry linked partnerships. The paper argues that this is a rationally driven economic strategic plan which fails to acknowledge that the alliance process is a very high risk strategy at the level of implementation, with reports of as many as two thirds failing. The direct causal link between universities and economic regeneration is contentious. The paper calls for greater understanding of the complex partnership process by drawing on the strategic alliance literature on how to minimize risk. It critically analyses the case of a long established partnership between university‐industry‐government – the teaching company scheme. Important governance issues are identified followed by an analysis of the two stages in the process of partner selection and implementation. The process is promoted as an exemplar to inform the increasing number of public/private sector partnerships.

There is an acknowledged need to advance the supply chain management (SCM) learning agenda, with an emphasis on integration. This paper discuss an Australian university–industry collaboration aimed at accelerating SCM learning and offers some insight into models for building a forward-looking SCM.

The research is an exploratory case study of the industry–university collaboration, using grounded theory procedures. The primary data involved 25 interviews with key participants from the university and industry partners, and from the first cohort of students in the undergraduate program developed within the collaboration.

A theoretical framework for accelerating SCM learning was developed from the case study data; it comprises six constructs that influence, at strategic and operational levels, the acceleration of SCM learning. Four cross-construct concepts from the framework that form the cornerstones of accelerated learning are discussed in some detail.

The framework facilitates an examination of successes and shortfalls in the case study collaboration and generates a deeper understanding of critical elements for progressing the SCM learning agenda, and expanding SCM education. As with all qualitative research, the results may not be generalisable; testing the relevance and usefulness of the framework with the field will be an important next step.

As the framework identifies conditions, characteristics and capacities of organisations and individuals that support the acceleration of SCM learning, it can provide assistance in designing future university–industry collaborations for advancing SCM learning.

The framework identifies critical success factors for alliances and partnerships aimed at accelerating learning in an emerging body of knowledge such as SCM.

The purpose of this paper is to improve the understanding of university‐industry research collaboration through the development of a new process model.

A literature review was carried out on collaborative partnering and supporting factors namely social capital and the role of knowledge. Empirical research involved a series of 32 structured interviews with relevant stakeholders, with subsequent grouping and conceptualisation allowing common themes to be identified and a new process model to be proposed.

The study finds that there is a lack of integrative frameworks for the management of research collaborations. Through building on the suggested best practice described in the paper, application of the model to the management of an engineering research programme has allowed the benefits of this approach as well as some of the underlying issues to be explored in detail.

The research focused on university‐industry research collaborations and although it may be applicable to other forms of collaborations, e.g. industry‐to‐industry, there could be features that are particular to the area under investigation.

A model has been proposed, which is a logical methodology that can be utilised by practitioners from both academia and industry in order to improve the process of research collaboration and facilitate more effective transfer of knowledge.

The model builds on previous literature on alliance and collaboration management but crucially is based on an innovative new process‐based methodology, which provides practitioners with a “route map” of how to develop and manage research collaborations. The model uses a holistic approach to collaboration through capturing process, knowledge and social elements.

With the evolution of the turbulent environment constantly triggering the emergence of a trust crisis between organizations, how can university–industry (U–I) alliances respond to the trust crisis when conducting green technology innovation (GTI) activities? This paper aims to address this issue.

The authors examined the process of trust crisis damage, including trust first suffering instantaneous impair as well as subsequently indirectly affecting GTI level, and ultimately hurting the profitability of green innovations. In this paper, a piecewise deterministic dynamic model is deployed to portray the trust and the GTI levels in GTI activities of U–I alliances.

The authors analyze the equilibrium results under decentralized and centralized decision-making modes to obtain the following conclusions: Trust levels are affected by a combination of hazard and damage (short and long term) rates, shifting from steady growth to decline in the presence of low hazard and damage rates. However, the GTI level has been growing steadily. It is essential to consider factors such as the hazard rate, the damage rate in the short and long terms, and the change in marginal profit in determining whether to pursue an efficiency- or recovery-friendly strategy in the face of a trust crisis. The authors found that two approaches can mitigate trust crisis losses: implementing a centralized decision-making mode (i.e. shared governance) and reducing pre-crisis trust-building investments. This study offers several insights for businesses and academics to respond to a trust crisis.

The present research can be extended in several directions. Instead of distinguishing attribution of trust crisis, the authors use hazard rate, short- and long-term damage rates and change in marginal profitability to distinguish the scale of trust crises. Future scholars can further add an attribution approach to enrich the classification of trust crises. Moreover, the authors only consider trust crises because of unexpected events in a turbulent environment; in fact, a trust crisis may also be a plateauing process, yet the authors do not study this situation.

First, the authors explore what factors affect the level of trust and the level of GTI when a trust crisis occurs. Second, the authors provide guidelines on how businesses and academics can coordinate their trust-building and GTI efforts when faced with a trust crisis in a turbulent environment.

First, the interaction between psychology and innovation management is explored in this paper. Although empirical studies have shown that trust in U–I alliances is related to innovation performance, and scholars have developed differential game models to portray the GTI process, building a differential game model to explore such an interaction is still scarce. Second, the authors incorporate inter-organizational trust level into the GTI level in university–industry collaboration, applying differential equations to portray the trust building and GTI processes, respectively, to reveal the importance of trust in CTI activities. Third, the authors establish a piecewise deterministic dynamic game model wherein the impact of crisis shocks is not equal to zero, which is inconsistent with most previous studies of Brownian motion.

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.