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The academic experience of top management team (TMT) has a positive impact on firms' innovation performance. However, existing studies predominantly focus on the educational qualifications and institutional prestige of TMT, failing to comprehensively evaluate whether TMT possess genuine academic experience and the role of academic competence. This article aims to examine whether TMT academic competence has a potential influence on firm innovation performance and to understand the mechanisms behind this relationship.

Using firm-level metrics of Chinese listed firms and TMT scholarly publication data spanning 2000–2021, this paper investigates whether TMT academic competence can promote firms' innovation performance and conducts a moderated mediating effect analysis.

(1) Academic competence of TMT can contribute positively to firms’ innovation performance; (2) university–industry collaboration partially mediates this relationship; (3) the mediating effect is enhanced by cognitive proximity and (4) distance proximity does not diminish the mediating effect.

Outcome of this study can assist academia in further understanding the impacts of TMT on firm innovation and aid government in promoting university–industry collaboration. Simultaneously, it can help firms adjust their TMT selection and training strategies to enhance innovation performance.

This article, as the first to construct an index of academic competence and to explore whether it has an impact on firms' innovation performance and its inherent mechanism, can provide a new research perspective for the study of the impact of TMT's characteristics on firms' innovation.

This 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.

This 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.

The 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.

This 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.

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.

The purpose of this paper is to investigate how knowledge management and university-industry-government collaboration – including the triple helix – relate with each other in influencing organizations’ performance. In the competitive environment nowadays, an organization’s ability to create and use knowledge becomes ever more essential in the search for sustainable competitive advantage, even leading to the search for new forms of inter-organizational arrangements.

The representatives of such collaborations selected for this study are the National Institutes of Science and Technology. The categorical content analysis technique was used for the qualitative analysis of the data.

The principal contribution was the proposal of an analytical model relating the knowledge management and triple helix theories and the proposed dimensions (namely, structural, relational, cognitive and the context), considering the peculiarities of the Brazilian context. The findings show that the organizational structure (structural) influences not only the relationship among members (relational) but also the flow of knowledge (cognitive), as well as how relational elements (collaborative culture, trust and leadership) facilitate knowledge sharing. Moreover, the context affects these three other dimensions. The main obstacles identified were cultural differences, bureaucracy and the socio-economic reality, while facilitators were the existence of technology parks and incubators, government incentives and geographical proximity between universities and industry.

This topic was chosen as there are few empirical studies that comprehensively relate the topics of knowledge management and university-industry-government cooperation focusing on the Brazilian context.

This study aims to make government usage of technology research grants more efficient and to evaluate how to use university–industry–research cooperation to promote industrial innovation in Taiwan.

This case study aims to use the triple helix model and other references to develop indicators which can estimate the performance of university–industry–research cooperation in Taiwan. The study selects three facets: “(prior) mechanisms,” “(in-progress) regulations” and “(post-hoc) operations” to find out the critical indicators contributing the final outcome. The study found that a successful university–industry–research cooperation requires the following factors: strengthening review methods for the mechanisms; its relationships of rights and obligations; policy needs in regulations; and plan incentives in operations.

It is recommended that, to promote university–industry–research cooperation in Taiwan, resource distributors and program management units should not only continue program application incentives and strengthen interdepartmental resource integration, they should also consider the establishment of a fair, just and open review mechanisms, and they should enhance the relationship between the rights and obligations of university–industry–research cooperation.

The study of this program includes application review before, during and after the program, management examination and performance evaluation to formulate recommendations as reference points for resource distributors and grant recipients. And because of industry–university cooperation being the main way of research and technology development, the findings and suggestions of this study may also be helpful for other grant systems in the world.

This study aims to identify the effect of demographic factors on the relationship between academic contribution and university–industry knowledge exchange in Sri Lanka.

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.

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.

This study considered only the university side of the university–industry knowledge exchange process.

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.

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.

The 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.

This 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.

The 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.

Due to the limitations of the data, this paper only selects several secondary indicators to measure KRE and KTE with reference to previous studies.

This 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.

This 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 projects provide special challenges in understanding and expressing the values required of project management (PM) in delivering stakeholder benefits. This paper presents a framework for understanding, identifying and managing the values of PM in major university–industry R&D projects.

The value framework identifies for each of the key stakeholders, the key PM values that may require to be managed and are largely derived from research literature. Empirical research then explores, prioritises and selects key PM values that need to be managed for a specific project. A large case study is used involving one university and one industry collaborating on a multi-million Euro initiative over six years. Empirical research was conducted by researchers who observed at close quarters, the challenges and successes of managing the competing values of key stakeholders.

The value framework takes a stakeholders' perspective by identifying the respective PM values for each of six stakeholders: university–industry consortium, university, industry, R&D external entities, funding entity and society.

The research was performed using only one case study which limits the generalisability of its findings; however, the findings are presented as a decision support aid for project consortia in developing values for their own collaboration.

Guidance and decision support are provided to multi-stakeholder research consortia when selecting values that need to be managed for achieving tangible and intangible project benefits.

The paper demonstrates a proposed framework for designing and managing the value of PM in large multi-stakeholder university–industry R&D projects.

There is little known about investigating the importance of all proximity dimensions simultaneously as a result of geographical proximity on university-industry collaborative innovation. This paper aims to answer the question of how geographically proximate university and industry influence cognitive, social, organizational, institutional and cultural proximity within university-industry joint laboratories and finally, what is the outcome of these interplays on collaborative innovation.

The study uses an exploratory multiple-case study approach. The results are derived from 53 in-depth, semistructured interviews with laboratory directors and representatives from both the company and the university within 8 joint laboratories of Telecom Italia (TIM). The data collection was carried out in 2014 and 2015. The analysis follows a multi-grounded theory approach and relies on a mix of deductive and inductive reasoning with the final goal of theoretical elaboration.

This study finds the role of social and cultural proximity at the individual level as a result of geographical proximity as an enabler of collaborative innovation by triggering mutual learning, trust formation and frequent interactions. Cognitive proximity at the interface level could systematically influence collaborative innovation, while organizational and institutional proximity has marginal roles in facilitating collaborative innovation. The qualitative analysis offers a conceptual framework for proximity dimensions and collaborative innovation within university-industry joint laboratories.

The framework not only advances state-of-the-art university-industry collaboration and proximity dimension but also offers guidance for managers in designing collaborative innovation settings between university and industry.

With this study, the paper advances the understanding beyond solely the relationship between proximity and collaboration and shed light on the interplay between geographical proximity and other proximity dimensions in this context, which has received limited scholarly attention.

Collaboration with universities is an important innovation strategy for enterprises. However, currently very little research has focused on how such university-industry collaborative innovation activities should be managed. The paper aims to discuss this issue.

This paper introduces the university-industry collaborative innovation practices of Zhejiang NHU Company in China. By using a case study as the method, this paper aims to illustrate the mechanism of university-industry collaborative innovation and how to manage the collaborative innovation activities efficiently.

Zhejiang NHU Company established a university-industry collaborative innovation link through three innovation platforms: the technology R&D center, the ZJU-NHU joint-research center, and the national engineer center. Zhejiang NHU Company manages its collaborative relationships with universities through this innovation network.

NHU Company managed the collaborative relationship efficiently with the institutions, representing an effective degree of university-industry collaborative innovation management.