Critical Success Factors of University-Industry R&amp;D Collaborations

Fernandes, Gabriela; Santos, José Manuel Riesco; Ribeiro, Pedro; Ferreira, L. S.; O’Sullivan, David; Barroso, Daniela; Pinto, Eduardo B.

doi:10.1016/j.procs.2023.01.458

Cited by 8 publications

(7 citation statements)

References 28 publications

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“…Instead, in this study, the conclusions are based on statistical data and economic-mathematical calculations for several countries of the world, which proves their impartiality. Fernandes et al (2023) tried to find the most success factors (thirty-four) of university-industry R&D collaborations based on literature review and a case study between Bosch Car Multimedia in Portugal and University of Minho. However, among them the author does not clearly single out the digitization factor, which is the key to achieving those indicators that the authors position as critically successful factors.…”

Section: Resultsmentioning

confidence: 99%

Is digital development a factor of university-industry R&D collaboration and vice versa?

Kuzior,

Samoilikova,

Kossek

et al. 2024

Production Engineering Archives

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The purpose of the article is to determine and characterize relationships and their causality between indicators of digitalization of social relations and level of university-industry R&D collaboration. To conduct the research, a sample was formed for 20 countries of the world leaders in University-Industry R&D Collaboration indicator (as a part of Global Innovation Index) in 2022, which covers the following indices for period from 2011 to 2020: indicators of university-industry R&D collaboration, access to ICT, government online services, online creativity (as assessed by WIPO Global Innovation Index), and export of ICT goods (according to the World Bank). The methodological basis of the study was methods of correlation analysis (Pearson or Spearman, depending on data distribution, for which Shapiro-Wilk test for normal data distribution was previously applied) taking into account possible lags in time, VAR modelling, Granger test, and corresponding toolkit of STATA 18 software. As a result of the research, it was confirmed that the level of university-industry R&D collaboration is affected by such indicators of digitalization of social relations as online creativity (in 16 from 20 sample countries), access to ICT (in 12 countries) and the share of ICT goods exports in total exports (in 11 countries). At the same time, university-industry R&D collaboration is a cause of changes in the level of online creativity (in 15 from 20 sample countries), access to ICT (in 11 countries), public online services (in 10 from 19 sample countries) and the share of ICT goods exports (in 10 from 20 sample countries). The obtained results can be useful for stakeholders in R&D, innovative activities, development of state policy in the innovation and information sphere for making the most effective decisions in the context of stimulating the role of cooperation.

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Section: Resultsmentioning

confidence: 99%

Is digital development a factor of university-industry R&D collaboration and vice versa?

Kuzior,

Samoilikova,

Kossek

et al. 2024

Production Engineering Archives

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“…With the increasing occurrence of R&D projects and programs in the context of university-industry collaborations, there follow associated reports of failure. Hence, considerable research has been carried out to identify critical management success factors [9]. Some of these key success factors have been identified which facilitate collaborative R&D programs and projects, where risk analysis, management, and control are emphasized [10].…”

Section: University-industry Randd Collaborationsmentioning

confidence: 99%

“…According to the literature, an example of such complexity might involve conflicts over intellectual property, and freedom of expression in publications, as well as differences in priorities, time horizons, and areas of interest/research focus [4]. Thus, research has been forced to identify critical success factors of these types of projects and programs [9]. UICs have revealed several critical success factors that are essentially generic, such as RM [9].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, research has been forced to identify critical success factors of these types of projects and programs [9]. UICs have revealed several critical success factors that are essentially generic, such as RM [9]. According to Pinto and Pinto [10], the identification and analysis of, and search for solutions to the risks involved in a project, should be carried out on a continuous basis to support the key decision-making of the project.…”

Section: Introductionmentioning

confidence: 99%

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Risk Management in University–Industry R&D Collaboration Programs: A Stakeholder Perspective

et al. 2022

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Current knowledge of risk management (RM) is mainly limited to single organizations. This paper investigates RM practices from a stakeholders’ perspective applicable to university–industry R&D collaboration (UIC) programs, a particular form of inter-organizational relationship. With a view to reducing the negative impact of risk associated with such UICs, and, as a result, increasing the success rate of the related programs and projects, an RM methodology has been developed from the perspective of the main stakeholders. The results reported here are based on a large-scale UIC between the Bosch Car Multimedia in Portugal and the University of Minho. Three research methods were applied in a complementary way: participant observation over seven years, analysis of various documents supporting the management of the programs and projects, and focus group involving seven key participants from different roles. The proposed RM methodology takes into account the three main stakeholders and their respective RM roles—Program Manager, Program and Project Management Officer, and Project Manager—and helps to manage the risks incurred by a UIC program while, at the same time, emphasizing the importance of taking the stakeholders’ perspective. In inter-organizational contexts, particularly in the case of university and industry, where there is a cultural gap between members, misunderstandings may occur about the role each key stakeholder should play. This paper provides a comprehensive guideline for the application of the methodology by means of a proposed set of specific RM practices. However, the research was conducted using a single case study, therefore limiting the results’ potential for generalization.

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“…Collaboration with R&D sectors(SF 8): Collaboration between the R&D sector and the cloud computing industry is crucial for advancing cloud technology and driving innovation. It can lead to new breakthroughs, drive innovation, and ensure that cloud technology is meeting the needs of customers and industries[54,55]. Aesthetic values in cloud computing can play a significant role in how users perceive and interact with the technology, as well as in promoting values such as sustainability and user-centered design[42,57,58].•Interactive information usage (SF 11): Interactive information usage in cloud computing refers to the ability of users to access, manipulate, and share information stored in the cloud in a collaborative and interactive manner.…”

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confidence: 99%

Analyzing the Critical Parameters for Implementing Sustainable AI Cloud System in an IT Industry Using AHP-ISM-MICMAC Integrated Hybrid MCDM Model

Yenugula¹,

Goswami

Kaliappan³

et al. 2023

Mathematics

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This study aims to identify the critical parameters for implementing a sustainable artificial intelligence (AI) cloud system in the information technology industry (IT). To achieve this, an AHP-ISM-MICMAC integrated hybrid multi-criteria decision-making (MCDM) model was developed and implemented. The analytic hierarchy process (AHP) was used to determine the importance of each parameter, while interpretive structural modeling (ISM) was used to establish the interrelationships between the parameters. The cross-impact matrix multiplication applied to classification (MICMAC) analysis was employed to identify the driving and dependent parameters. A total of fifteen important parameters categorized into five major groups have been considered for this analysis from previously published works. The results showed that technological, budget, and environmental issues were the most critical parameters in implementing a sustainable AI cloud system. More specifically, the digitalization of innovative technologies is found to be the most crucial among the group from all aspects, having the highest priority degree and strong driving power. ISM reveals that all the factors are interconnected with each other and act as linkage barriers. This study provides valuable insights for IT industries looking to adopt sustainable AI cloud systems and emphasizes the need to consider environmental and economic factors in decision-making processes.

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Critical Success Factors of University-Industry R&D Collaborations

Cited by 8 publications

References 28 publications

Is digital development a factor of university-industry R&D collaboration and vice versa?

Is digital development a factor of university-industry R&D collaboration and vice versa?

Risk Management in University–Industry R&D Collaboration Programs: A Stakeholder Perspective

Analyzing the Critical Parameters for Implementing Sustainable AI Cloud System in an IT Industry Using AHP-ISM-MICMAC Integrated Hybrid MCDM Model

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