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Effective management of risk and knowledge is critical to ensure the success of industry–university collaboration (IUC) projects. However, the intricate dynamics through which these factors influence the performance of IUC projects have yet to be fully investigated. The purpose of this study is to explore the interplay between risk management and knowledge management capabilities and their impact on IUC project performance.

A model was constructed and evaluated through the examination of a sample of 188 collaborative innovation projects located in the United Arab Emirates (UAE), utilizing structural equation models (SEM) and hierarchical regression analysis.

The findings indicate that social system risk, technical system risk and project management risk have a negative impact on the performance of university–industry collaboration (UIC) projects, while cultural, technical and structural knowledge management capabilities can mitigate the negative impact of these risks on the performance of IUC projects.

The study concludes with three recommendations aimed at improving the management of UIC projects, including the establishment of a distinct and precise management strategy, the deployment of a comprehensive and systematized management methodology and the adoption of a balanced management framework.

The originality and value of this study lie in its exploration of the interplay between risk management and knowledge management capabilities in IUC projects. While previous studies have examined either risk management or knowledge management in IUC projects separately, this study provides a comprehensive analysis of both factors and their combined impact on project performance. The study also contributes to the literature by highlighting the specific risks and knowledge management capabilities that are most relevant to the context of IUC projects in the UAE. The practical recommendations offered by the study can help project managers and stakeholders to improve the success of collaborative innovation projects.

The article broaches the important topic of the relationships between governance operationalizations and productivity at the start-up level. It proposes a new approach to reconnect the contingency factors to the optimization of productivity. This helps us to identify the changing characteristics that influence the determinants of decisions, actions and management of the technological projects of the mainly innovative enterprises.

The study uses techniques that effectively solve unobserved endogeneity and heterogeneity problems in enterprises: an empirical–structural design. With this method, this study enables rich empirical conceptualization and helps with extending theory. However, there is a need to further the research by taking into account the system analysis and the complexity of the research object: one of the options might be to explore a possible follow-up of the research through drawing on ethnostatistics and qualimetrics.

The analysis reveals that the phenomenon of technological project productivity in operational governance context is thus manifested by the coexistence of the applied governance configuration variables, the contingency factors operationalization, the optimizing productivity mechanisms and this with the secular innovation and stagnation and stagnation. Ceteris paribus, the governance operationalizations have an important role in the productivity of technological projects of the innovative enterprises.

This research is the first to mobilize as major determinants of the operationalization of governance, the oversight of the capital, the dividend strategy and the system control, the managerial follow-up, the detection of opportunistic behaviours and the application of governing incentives (among others) as governance configuration variables in order to highlight their interactions with productivity in the innovative firm technological projects. For this reason alone, the paper will be referenced by other authors in the future.

Suppliers are essential partners in innovation projects, as they own resources, knowledge assets and capabilities that complement those of buying firms. In today’s competitive environment, firms may choose to collaborate with suppliers beyond dyads, forming triadic or three-party relationships. Using the theoretical lens of the relational view (RV), this study aims to explore what type of triad configurations firms use to govern supplier relationships in collaborative innovation projects, how they choose to share resources and implications for project performance.

The authors use interview data from buyers and suppliers in six case studies of firms involved in ten collaborative innovation projects. The four constructs of the RV are used to observe how firms govern triadic relationships, combine complementary resources, invest in relationship-specific assets and manage information and knowledge exchange with and between suppliers in innovation projects.

Four archetypes of triadic relationships in innovation projects – labeled Triangle, A-frame, D-Frame and Line – are presented and characterized in terms of their structural and relational features. The authors discuss how each triad archetype is applicable to different innovation projects according to specific project characteristics.

This study is pioneering in its empirical examination of triadic relationships in collaborative innovation projects. It provides a novel typology of four archetypes of triad from the perspective of collaborative relationships with suppliers. Through applying the RV, it advances understanding of how triadic relationships are governed, how they invest in relationship-specific assets, how they combine complementary resources and how they exchange knowledge and information in each type of triad appropriate to different innovation project settings. To date, much of the extant literature has focused on dyads.

The purpose of this paper is to examine a series of environmental factors and industrial conditions governing the construction industry in China. The outcome of this part of the analysis sheds light on the development of appropriate competitive strategies and important resources and competencies (IRCs) to establish long‐term competitive advantages.

The overarching conceptual framework consists of both external and internal analyses. Since, the scope of work is very broad, the materials presented in this paper is limited to external analysis of environmental factors. The study is primarily derived from a literature review and synthesis of data gathered from various public sources. Certain parts of the analysis utilize frameworks developed by other researchers and selective statistical methods.

Some environmental factors, such as government intervention and legal and regulatory systems require the development of Guanxi (relationships) to cope with. Other factors including market structure, project procurement systems, horizontal market segments related to construction, regional characteristics and upstream and downstream functions within the construction value chain are suggestive of five potential types of competitive strategies: cost leadership, differentiation, market/product diversification, geographical diversification, and vertical/functional integration.

The research study as a whole is targeted at large construction firms in China that belong to the First class qualification category. Therefore, the proposed competitive strategies and IRCs may not be applicable to small and medium construction enterprises.

Application of strategic management theories and empirical findings related to the Chinese construction industry is lacking. This research fills this gap and builds a foundation for future studies related to this industry.

Leadership behaviour of R&D project managers (RDPMs) is a matter of ongoing interest, as they require a number of traits in order to potentially influence the delivery of projects. However, little empirical evidence exists on factors explaining the traits of RDPMs, making it difficult for industry managers to develop tailored strategies and criteria for selecting people with right skills and behaviours. The purpose of this paper is to fill this gap in knowledge.

The authors test 45 traits with data from a survey of 208 RDPMs, using exploratory factor analysis to establish factors of RDPMs’ traits and the associated measurement items.

The study finds that selected 45 traits can be consolidated in a set of higher order variables/factors that RDPMs need to have including creativity, reasoning and learning; risks and failure acceptance; analytical and originality attributes; realistic and objective approach among others.

The study shows that traits have strong inter-relationship represented by empirically robust underlying factors.

Practically, the results will help industry mangers in implementing tailored strategies in consolidated areas (as identified through factors) and be more effective in skills and competencies development of research and development staff and potentially save costs on human inventory management.

The study empirically established new managerial and leadership behavioural factors.

The purpose of this paper is twofold: to analyze to what extent innovation output of R & D collaborations, proxied by co-patenting activities in terms of quantity, characteristics and value, differs depending on whether the engaged R & D partners have a certain type of relationship (allies, suppliers and subsidiaries); to identify possible automakers co-patenting patterns taking into account the differences in the innovation output with their R & D partners.

To reach the aims, the authors matched two types of data: co-assigned patent portfolio of four automakers and relationship type between automakers and their co-assignees. Matching the company names of the two data sources allowed the authors to obtain the final data set used to carry out extensive descriptive and regression analysis, both on a firm- and patent-level.

Results show differences in the characteristics and the technological value of patented inventions in relation with the type of collaboration partner; they also support the authors in the identification of four co-patenting patterns (contingent, purposive, watchful and advanced) according to the co-patenting propensity and the presence of a preferred relationship type.

The paper contributes to the literature by investigating the presence of differences across the patenting activities of a selection of automakers and their supplier, allied and subsidiary firms. The issue related to patent value represents an emerging area of interest in the field of collaborations for innovation. The methodology constitutes a novelty by matching two different sources and standardizing the company names (“name game”) through an automated algorithm and a double manual check, by searching company web sites and corporate trees.

How to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and abstracts of articles.

The authors conduct a comparison study of topic modeling on full-text paper and corresponding abstract to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.

The authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding abstract is higher when more documents are analyzed.

First, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or countries in their efforts to develop and market new products. Looks at the issues from different strategic levels such as corporate, international, military and economic. Presents 31 case studies, including the success of Japan in microchips to the failure of Xerox to sell its invention of the Alto personal computer 3 years before Apple: from the success in DNA and Superconductor research to the success of Sunbeam in inventing and marketing food processors: and from the daring invention and production of atomic energy for survival to the successes of sewing machine inventor Howe in co‐operating on patents to compete in markets. Includes 306 questions and answers in order to qualify concepts introduced.

The purpose of this paper is to analyze the determinants of the performance of regional industrial technology development programs among the regional strategic industrial development program that the central government and Daegu metropolitan city jointly promoted between 2004 and 2012. Specifically, in this research, the authors are trying to identify the effects of R&D capabilities and technical development tasks on technological and managerial performance.

The dependent variables of this study are technical and economic performance. Technical performance, product and process innovation, economic performance, sales and export increases were measured using five-point Likert scales. The authors added the contribution of sales through technology development to economic performance. The independent variable is the company’s R&D capability, measured by the number of R&D staff compared to the average total number of employees from 2004 to 2012. The characteristics of the technology development tasks were measured by technical characteristics, market characteristics and collaborative research types. The technological characteristics were measured by seven factors, including technological change, technical difficulty, potential in commercialization, competition between domestic and foreign competitors, difficulty in introducing overseas technology and the technological gap. Market characteristics were largely divided into complexity, dynamics and competitiveness. The types of collaborative research were divided into whether or not there were collaborative research with the participation of large corporations. The control variables are firm size (number of employees) and firm age. Regression analysis was used to analyze the determinants of performance, and a difference analysis was conducted to determine the effect of collaborative research on performance.

The main determinants of the regional industrial technology development program performance are the characteristics of the technology development task rather than the internal R&D capability; moreover, the technical characteristics, complexity of the developed product market and participation of large corporations had significant effects on R&D capability. The R&D capacity of firms in internal R&D capacity had a significant effect only on the improvement of technology development ability. Therefore, R&D capacity, which is the main determinant of technology innovation, did not have a significant effect on the performance of short-term technology development tasks. Technological change, technological difficulty, competition between domestic and foreign competitors and the technological gap had positive effects on performance, excluding sales contributions. In addition, the complexity of the developed product market such as the diversification of demand, competitive product and sales distribution channels had positive influences on the performance of technology development programs, unlike dynamics and competitiveness. In this study, the authors cannot confirm the effect of collaborative research on the performance of the technology development programs, but they confirmed that collaborative research involving large corporations had a positive influence on performance.

The results of the analysis of the determinants of regional industrial technology development programs suggest some implications in the future evaluation of these regional industrial technology development programs. It is necessary to review the application qualification and merit, advance review of the business plans and confirmation, an examination of the research results and performance of the applicants and a review of the technology and market situation of the project. For this, the authors suggest that the written review from the relevant technical experts be submitted to the evaluation committees. Also, when establishing regional industrial development programs, they should be evaluated thoroughly, including detailed information and contents about the technical and market characteristics of the local industry.

This research is one of the first to investigate the achievements of R&D support programs among regional industrial development programs in Korea. The results of this study can substantially contribute to the development and implementation of the R&D support policies of the central and local governments. Furthermore, the findings suggest guidelines for improving the performance of R&D support programs in the future. A theoretical model for enhancing the efficiency of government R&D support programs may be established, and an empirical analysis may be conducted to provide practical and academic implications for further research.