Factors impacting university–industry collaboration in European countries

Ćudić, Bojan; Alešnik, Peter; Hazemali, David

doi:10.1186/s13731-022-00226-3

Cited by 27 publications

(15 citation statements)

References 64 publications

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“…Compared to other studies (López-Martínez et al, 2007;Boardman and Ponomariov, 2009;Giuliani et al, 2010;Morales, 2019;Cudic et al, 2021;Da Silva and Sartori, 2022), only López-Martínez et al (2007) and Morales (2019) applied instruments similar to the EA-COOPTEC to measure UIC from the researchers' perspective. However, López-Martínez et al (2007) reported no evidence of validity or reliability.…”

Section: Discussionmentioning

confidence: 99%

“…1; (b) expand the sample to be representative by age strata and other variables of interest so that the results can be generalized to other states, at the national level, and in other countries in the region with a similar science and technology system; (c) expand the sample of participating female researchers to reduce possible biases when comparing with the male sample; (d) increase, based on the recommendations of UIC specialists and solid theoretical foundations, the number of items of the Regulation and Normality factor so that the construct faithfully represents the reality to be measured; (e) accompany the application of the EA-COOPTEC v0. 1 with the measurement of other variables in order to provide evidence of concurrent, discriminant and predictive validity, especially those variables associated with institutional factors, human factors, linkage factors, framework factors, intangible product indicators and tangible product indicators (Cudic et al, 2021); and (f) Conduct a study based on the Bayesian Mindsponge Framework (BMF) to consolidate the conceptualization, construction and fit the theoretical model underlying EA-COOPTEC v0. 1 and improve estimation with small sample sizes used for the study of UIC in science and technology systems worldwide (Nguyen et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…There are currently a variety of indicators to measure different types of UIC activities (Gardner et al, 2010;Seppo and Lilles, 2012). In particular, the measurement of perception of T-Rs to UIC is a little explored field, the closest studies are those of López-Martínez et al (2007), Boardman and Ponomariov (2009), Giuliani et al (2010), Cudic et al (2021), Da Silva andSartori (2022), andMorales (2019). Cudic et al (2021) measured UIC by constructing indicators based on data reported by different sources with the purpose of studying the relationship between predictors of UIC and its outcomes.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, the measurement of perception of T-Rs to UIC is a little explored field, the closest studies are those of López-Martínez et al (2007), Boardman and Ponomariov (2009), Giuliani et al (2010), Cudic et al (2021), Da Silva andSartori (2022), andMorales (2019). Cudic et al (2021) measured UIC by constructing indicators based on data reported by different sources with the purpose of studying the relationship between predictors of UIC and its outcomes. For the construct measures, the authors based the theoretical framework of this research on a systematic review of the relevant academic literature, taking into account the availability of variable data.…”

Section: Introductionmentioning

confidence: 99%

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Psychometric properties and invariance of the scale to measure attitude of researchers for university-industry collaboration

et al. 2023

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The psychometric properties of the Scale to measure the attitude of researchers for scientific-technological collaboration between universities and industry (EA-COOPTEC, for its acronym in Spanish) were analyzed, specifically evidence of construct validity of the internal structure and invariance for gender and age was obtained. The EA-COOPTEC was administered to 179 academic Teachers–Researchers (T-Rs) involved in Universities-Industry Collaboration (UIC) activities: 50 women and 129 men. Participants had a median age of 36–40 years. A descriptive analysis was implemented, as well as an Exploratory and Confirmatory Factor Analysis (EFA and CFA), and a method of succession of nested models for invariance testing. A four-factor model explaining the perception of UIC activities was generated and evidence of invariance for gender and partial invariance for age was obtained. Acceptable fit indices were obtained for the configurational, weak, strong and strict. Given the results, we recommend the use of the EA-COOPTEC v0.1 for the analysis of the mean differences between genders and age in T-Rs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Psychometric properties and invariance of the scale to measure attitude of researchers for university-industry collaboration

et al. 2023

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“…UIC inputs for these activities are further classified into tangible resources including financial resources and physical resources, and intangible resources (e.g. intellectual property, brand and culture), human-related resources and collaboration capabilities ( Cudi c et al, 2022;Galan-Muros and Davey, 2017;Philbin, 2012). Results from UIC consist of outputs (i.e.…”

Section: The Integrated Conceptual Framework For University-industry ...mentioning

confidence: 99%

Toward the identification of mechanisms to ensure effective university-industry collaboration in sub-Saharan Africa

Nsanzumuhire

Groot

Cabus³

et al. 2023

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Purpose 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). Design/methodology/approach 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 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. Research limitations/implications 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. Practical implications 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. Social implications 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. Originality/value 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.

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University–Enterprise Linkages: A Bayesian SEM Approach Toward MIS Major

Nguyen

2024

Studies in Systems, Decision and Control

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Factors impacting university–industry collaboration in European countries

Cited by 27 publications

References 64 publications

Psychometric properties and invariance of the scale to measure attitude of researchers for university-industry collaboration

Psychometric properties and invariance of the scale to measure attitude of researchers for university-industry collaboration

Toward the identification of mechanisms to ensure effective university-industry collaboration in sub-Saharan Africa

University–Enterprise Linkages: A Bayesian SEM Approach Toward MIS Major

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