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This study aims at advancing the understanding of University-Industry Collaboration (UIC) by proposing an adapted conceptual model for comprehensive contextual analysis taking industry perspective and identifying effective mechanisms for stimulating UIC in sub-Saharan Africa (SSA).

This study was designed as a multicase qualitative study. Data were collected through interviews of focus groups representing 26 agro-processing companies operating in Rwanda. The process consisted of two sessions evaluating the current collaboration patterns, and two sessions identifying the desired future and the mechanisms to realize it. Data were analyzed using ATLAS.ti software with the grounded theory techniques.

Findings indicate that current interactions are unidirectional and focus on educational collaboration. Results are short-term and do not yield sufficient benefit for the companies involved. Industry aspirations for future collaboration were identified, along with linkages between inputs, activities and outcomes.

This study has two noteworthy limitations. First, this study did not consider the capacity of firms to collaborate. Second, for simplification purposes, this study did not integrate other complementary sources of knowledge for firms. To overcome these omissions, a short introduction of University–Industry Collaboration (UIC) was presented to participants highlighting and justifying the scope of the study. As research implications, this paper presents a new integrated conceptual framework, which can be useful for studies focusing on a comprehensive analysis of the UIC context and identifying effective mechanisms for improvement in the future. A construct of policies that stimulate UIC is proposed, thereby facilitating further operationalization and testing of context-specific hypotheses on policy stimuli.

In practice, the identified conceptual framework allows to holistically capture and reflect on the interrelationships between UIC factors and outcomes for a specific context, hence, informing better UIC decision-making. In this way, this paper advances the operationalization of the argument for reconciling organizational theories with their practices.

This paper presents a systemic means for organizational theories to perform their adaptive role in society. Indeed, as demonstrated by the empirical results, the proposed framework is effective not only in systematically assessing the current situation, but also in predicting the desired state in the future. In other words, the proposed framework facilitates prescience theorizing, which is a mechanism for ensuring that organizational theories adapt to future requirements of the society.

This study develops a new integrative conceptual framework to accommodate the interaction between UIC’s institutional decision-making and existing macrolevel frameworks of innovation ecosystems. In terms of methodology, the value of this study lies in its adoption of an ex ante approach to the development of mechanisms to stimulate UIC. This use of prescience theory (Corley and Gioia, 2011) constitutes an important – but long-neglected – approach to UIC and its adaptive role in society.

The purpose of the study was to examine the factors that are important for strengthening university–industry collaboration (UIC). This study also investigates the outcome of UIC in the light of creativity, skill, knowledge, and research work.

A survey method has been used to collect data for the study. This study applied a purposive judgmental sampling technique where particular types of respondents like university faculty members and the top officials of the organizations were selected who are knowledgeable and can provide the desired information. The current study used the structural equation modeling method to analyze the data. In the first stage, this research assessed the demographic factors of the respondent. Then this study conducts confirmatory factors analysis and convergent and discriminant validity and reliability test. Finally, the hypotheses are tested by using nonparametric.

This study finds that knowledge transfer mechanism, governmental factors, organizational design factors, technology transfer and the collaborative network has a significant impact on strengthening UIC, which ultimately facilitates creativity, knowledge creation, skills development and supply of graduate according to the requirement of the industry, good research work.

The current study identified some important determinant that has a substantial influence on strengthening UIC. According to the study organizational design, government, technology, collaborative network and mechanism for knowledge transfer play very crucial roles in strengthening collaboration that ultimately increases the creativity, skills, knowledge and research capability of graduates.

As the university–industry collaboration (UIC) gradually attracts the attention of various national governments, the number of studies on UIC has increased substantially. Past UIC studies have mostly focused on investigating the incentives and the motivation for UIC, forms of UIC and performance output of UIC. However, they have not actively identified the key technologies and technology distribution that are conductive to the commercialization of UIC outcomes. Therefore, this study aims to adopt the licensed UIC patents as the basis for analysis and to construct a patent licensing technology network.

This study focused on licensed patents because past studies have indicated that such patents usually have higher value. Moreover, patent licensing can be seen as the final step for the commercialization of UIC outcomes. Finally, past studies have rarely explored patent examiners’ views on key technologies. However, during the substantive examination of patents, patent examiners often use their background knowledge regarding the technology to include citations to other patented technologies that they consider valuable or indispensable. Therefore, this study focused on investigating the patents recognized and cited by patent examiners and conducted key technology identification.

The results indicated that past key technologies in UIC focused on surveying, medicine, biochemistry and electric digital data processing; these fields are crucial to the commercialization of key UIC technologies. Finally, the USA, Japan, Sweden and Germany play critical roles in the network of global university–industry cooperation and technology licensing.

Patent examiners’ perspectives were adopted to establish a patent licensing technology network, through which the key technologies that could promote UIC patent licensing were mined. This study can also serve as a reference for resource allocation in university research and development and for governments to promote new technologies.

This paper aims to forecast the future development of UIC technology according to the changes of IPC in different time periods. The findings also provide a theoretical basis for the UIC policymakers of energy-saving environmental protection industry.

The present study will take energy-saving technology as an example, through using a two-mode network analysis method to build the four-stage IPC code UIC innovation-technology network, researching UIC innovation network applicant heterogeneity, UIC technology network and technology relevance.

Through the establishment of UIC innovation-technology two-mode network, namely, applicant node CN and IPC node TN, this paper analyzes the important applicants, focal technologies, correlation of focal technologies and the development trends of energy saving technology in the future by using the related theories and methods of two-mode network.

At present, only about 11% of energy-saving enterprises in China have R&D activities. The government needs to implement top-level design, improve industrial policies, strengthen investment in technology R&D and build a platform for technological innovation in energy-saving industries to support the R&D of common and key technologies in energy-saving industries.

The engagement with industry actors is a key element in the transition towards an entrepreneurial university model. The purpose of this paper is to explore the university–industry collaboration (UIC) drivers from the industry side. It analyses how, and to what extent, policy interventions could increase the engagement of industry actors in UICs.

An experimental research design has been used involving a feasibility and pilot study (January to June 2018) with 36 firms, in a non-urban region context, with a satellite university campus. The pilot study explores a randomised control trial (RCT) design, with a training intervention to a randomized group of participants in the pilot study.

Firms involved in universities’ students (academic forms of UICs) might not necessarily consider the university as a research partner, even in a geographic proximity setting. In addition, there is a potential “dark-side” to proximity, when industry participants build their perceptions using second-hand experiences or indirect information. A training intervention facilitates to overcome pre-existing biases but does not trigger a substantial change in the UIC’s behaviour of the firms in the short-term.

The pilot study provides valuable insights for researchers interested in a larger RCT. It also provides insights for university managers who want to understand the motivations of industry participants in UICs.

The experimental approach of the research generates evidence on the feasibility to intervene in the activation of UICs from an industry perspective, a central aspect in transition towards an entrepreneurial university model.

In online user innovation communities (UICs), firms adopt external innovations beyond their internal resources and capabilities. However, little is known about the influences of organizational adoption or detailed adoption patterns on subsequent user innovation. This study aims to examine the influence of organizational adoption, including its level and timing, on users' subsequent innovation behavior and performance.

This research model was validated using a secondary dataset of 17,661 user–innovation pairs from an online UIC. The effect of organizational adoption on users' subsequent innovation likelihood was measured by conducting a panel logistic regression. Furthermore, the effects of organizational adoption on subsequent innovation’ quality and homogeneity and those of the adoption level and timing on subsequent innovation likelihood were tested using Heckman's two-step approach.

The authors found that organizational adoption negatively affects the likelihood of subsequent innovation and its homogeneity but positively affects its quality. Moreover, more timely and lower-level adoption can increase the likelihood of users' subsequent innovation.

This study comprehensively explores organizational adoption's effects on users' subsequent innovation behavior and performance, contributing to the literature on UICs and user innovation adoption. It also provides valuable practical implications for firms on how to optimize their adoption decisions to maintain the quantity, quality, and diversity of user innovations.

This study examined academic motives to enter university-industry collaboration (UIC) and how they affect collaboration performance. Given that UIC performance is context-dependent, we also explored the moderating role of relationship governance.

The study population was academics working at a public research university while collaborating with industry. Data were collected through a cross-sectional survey. The measurement items were adapted from previous studies. Exploratory factor analysis and confirmatory factor analysis were conducted using IBM SPSS statistics 26 (SPSS 26). This study utilized a hierarchical moderated regression analysis to examine the research model.

The results indicated that government and institutional policies and knowledge generation and dissemination are critical indicators of necessity that motivate academics to enter UIC and positively influence performance outcomes. Different governance mechanisms also play varying roles in the relationship between motivation and UIC performance.

Institutional programs designed to encourage academics to collaborate with industry should consider the types of academic motivation and carefully manage collaboration efficiency using various kinds of relationship governance.

This study contributes to existing knowledge by determining how different relationship governance mechanisms moderate the relationship between academic motivation and collaboration performance.

The purpose of this paper is to examine which stakeholder values are created by a well-performing network-structured university-industry collaboration (UIC). These results should provide initial conclusions for the design of UICs with the aim to overcome critical barriers to effective technology transfer.

The research is designed as a comprehensive single case study and follows a qualitative approach in order to obtain a deep understanding of the various stakeholder values created by Austrian Center of Competence in Mechatronics (ACCM), a unique, well-performing UIC-network.

The results show that on the one hand ACCM provides stakeholder values that are largely common for UICs or networks (access to resources and industry problems, funding, know-how dialogue, solution of practical problems, etc.). On the other hand ACCM offers very special values which are often realized in UICs to a low degree only. The study indicates that by the special construct of ACCM, with its deep value added chain, the common problem of converting basic research results into industrial solutions can be managed.

The research shows that the ACCM construct of a network-structured UIC has many benefits for the stakeholders and offers a new way to overcome critical barriers to effective technology transfer.

Given the absence of fundamental work in this area, the study is significant both academically as well as practically in terms of effective technology transfer in network-structured UICs and their values for various stakeholders.

Technology transfer (TT) in industry to university collaboration (UIC) literature focuses primarily on a macro view within an SME environment. While these discussions are important to establish the significance of encouraging UIC's as the value is important to both parties, there is a need for further research at a micro level to help understand key approaches to ensuring the success of the TT. By looking at how value created from TT for a multi-national corporation (MNC) with a project based within a single subsidiary, this research effectively looks at the issue from both a SME level (the subsidiary independently) and a MNC level.

The research uses a longitudinal knowledge transfer partnership and action research to form a case study of Parker Hannifin's Gas Separation and Filtration Europe, Middle East and Africa (GSFE) division.

The research highlights the key areas to focus on in ensuring a successful TT within an UIC such as: once identifying the gap that a UIC is filling in the company, identifying internal barriers before the project starts; education of why change is necessary and then using knowledge experts to educate on the new processes being introduced and finally; incorporation of a full range of personnel, not just those directly involved in the day-to-day of the UIC.

As a case study, further research is required to make the results more generalisable. One way to do this would be to evaluate previous successful and unsuccessful UIC's and determine if the success criteria identified were present in these programmes.

There are three critical points that can be taken away from this research and applied to any company looking to use UIC for TT and value co-creation. Education, external knowledge experts and business wide inclusion were highlighted in the findings as being potentially critical turning points and need to be addressed for successful TT.

Successful UIC's further encourage investment in such programmes which has greater societal benefits. Not only can we see greater leaps in industry through better, more specific knowledge being transferred from the university, the industry knowledge fed into universities helps to guide research and teachings.

The micro level view created by action research based from the industry partner perspective adds another level of importance as the “how” for overcoming barriers is clearly addressed. Furthermore, the research looks at how a multi-national corporation can have value added through UIC's within subsidiaries which often is not addressed in the literature.

This study aims to explore the findings related to data literacy skills for students to succeed in the digital age labor market and the role of university-industry collaborations (UICs) in the co-design and co-delivery of curriculum for the development of students’ data literacy.

The study uses an interview-based research methodology to gather insights from industry partners and stakeholders. The interviews focus on identifying key data literacy skills, understanding the significance of these skills and exploring the role of UICs in enhancing students’ data literacy.

The findings reveal several important data literacy skills for students. The most commonly mentioned skills include data evaluation/analysis, identifying the relevance of data and data protection in a sensitive manner. Participants also emphasized the importance of recognizing the interrelationships among data, adapting data across different contexts and strategically combining diverse data. The study emphasizes the role of universities in providing a well-rounded educational setting that fosters the development of data literacy skills. Additionally, it highlights the value of practical collaborations between universities and industries, enabling students to apply theoretical knowledge in real-world contexts.

The study highlights the interconnected nature of various data skills and emphasizes the significance of data literacy in navigating the complexities of the digital age labor market. It also sheds light on the role of UICs in codesigning and codelivering curricula to enhance students’ data literacy. The findings provide valuable insights into the practical implications for UICs in preparing students for the data-driven job market.