Towards a Framework of Students Co-Creation Behaviour in Higher Education Institutions

Magni, Domitilla; Pezzi, Alberto; Vrontis, Demetris

doi:10.1504/ijmfa.2020.10030995

Cited by 8 publications

(17 citation statements)

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“…It is hard to understand the absence of unique definitions that help to conduct and replicate research across levels of analysis and contexts (Manzari et al, 2012). Indeed, given the unexpected external events (e.g., COVID-19 pandemic), future research should also consider the digitalisation into the relationship between IC intellectual and value co-creation process with other collectives like students (Magni et al, 2020(Magni et al, , 2021, technology transfer from academics (Siegel and Guerrero, 2021), government (Johanson et al, 2006), ecosystem agents , supply chain (Mubarik et al, 2021); final users (Rossi and Magni, 2017), non-profit organisations (Blankenburg et al, 2018) and civil society…”

Section: Limitations and Future Research Agendamentioning

confidence: 99%

Does policy enhance collaborative-opportunistic behaviours? Looking into the intellectual capital dynamics of subsidized industry–university partnerships

Guerrero

Herrera

Urbano

2021

JIC

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PurposeLittle is known about how subsidies enhance both collaborative and opportunistic behaviours within subsidized industry–university partnerships, and how partners' behaviours influence the intellectual capital dynamics within subsidized industry–university. Based on these theoretical foundations, this study expects to understand intellectual capital’s (IC's) contribution as a dynamic or systemic process (inputs?outputs?outcomes) within subsided university–industry partnerships. Especially to contribute to these ongoing academic debates, this paper analyses how collaborative and opportunistic behaviours within industry–university partnerships influence the intellectual capital dynamics (inputs, outputs and outcomes) of the subsidized projects.Design/methodology/approachBy combining two sources of information about 683 Mexican subsidized industry–university partnerships from 2009 to 2016, this study adopted the structural equation modelling (SEM) to analyse the effect of collaborative vs opportunistic behaviours in intellectual capital dynamics within subsidized projects.FindingsOur results show three tendencies about the bright/dark side of subsidies within the Mexican industry–university partnerships. The first tendency shows how collaborative behaviours positively influence intellectual capital dynamics within subsidized industry–university partnerships. The second tendency shows how opportunistic behaviours influence intellectual capital impacts (performance) and return to society (job creation). The third tendency shows how initial inputs of subsidized projects generate some expected socio-economic returns that pursued the subsidies (mediation effect of intellectual capital outputs).Research limitations/implicationsThis research has three limitations that provide a future research agenda. The main limitations were associated with our sources of information. The first limitation, we did not match subsidized partnerships (focus group) and non-subsidized partnerships (control group). A qualitative analysis should help understand the effect of subsidies on intellectual capital and partnerships' behaviours. The second limitation, our measures of collaborative/opportunistic behaviours as well as intellectual capital dynamics should be improved by balancing traditional and new metrics in future research. The third limitation is that in emerging economies, the quality of institutions could influence the submission/selection of subsidies and generate negative externalities. Future research should control by geographical dispersion and co-location of subsidies.Practical implicationsFor enterprise managers, this study offers insights into IC dynamics and behaviours within subsidized industry–university partnerships. The bright side of collaboration behaviours is related to IC's positive impacts on performance and socio-economic returns. The dark side is the IC appropriation behind opportunistic behaviours. Enterprise managers should recognize the relevance of IC management to capture value and reduce costs associated with opportunistic behaviours. For the university community, this study offers potential trends adopted by industry–university partnerships to reinforce universities' innovative transformation processes. Specifically, these trends are related to the legitimization of the university's role in society and contribution to regional development through industry–university partnerships' outcomes. Therefore, university managers should recognize the IC benefits/challenges behind industry–university partnerships.Social implicationsFor policymakers, the study indirectly shows the role of subsidies for generating/reinforcing intellectual capital outcomes within subsidized industry–university partnerships. The bright side allows evaluating the cost-benefit of this government intervention and the returns to priority industries. The dark side allows for understanding the need for implementing mechanisms to control opportunistic behaviours within subsidized partnerships. Accordingly, policymakers should understand the IC opportunity-costs related to industry–university partnerships for achieving the subsidies' aims.Originality/valueThis study contributes to three ongoing academic debates in innovation and management fields. The first debate about how intellectual capital dynamic is stimulated and transferred through the collaborative behaviour within industry–university partnerships in emerging economies. The second debate is about the “dark side” of partnerships stimulated by public programmes in emerging economies. The third debate is about the effectiveness of subsidies on intellectual capital activities/outcomes.

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Section: Limitations and Future Research Agendamentioning

confidence: 99%

Does policy enhance collaborative-opportunistic behaviours? Looking into the intellectual capital dynamics of subsidized industry–university partnerships

Guerrero

Herrera

Urbano

2021

JIC

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“…e model also took advantage of the GPU's strengths in floating-point computing, which greatly increased the speed of computing [9]. In the same year, renowned Stanford University machine learning professor Enda Wu developed a deep neural net model in conjunction with the world's leading computer experts [10].…”

Section: Current Status Of Researchmentioning

confidence: 99%

A Quantitative Enhancement Mechanism of University Students’ Employability and Entrepreneurship Based on Deep Learning in the Context of the Digital Era

Meng

Ren

Huang

2021

Scientific Programming

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This paper adopts a deep learning approach to analyze and study the mechanism of quantitative enhancement of college students’ employment and entrepreneurial abilities in the context of the digital era. The deep learning connotation is predetermined as five abilities, which are metacognitive ability, active communication and cooperation ability, deep processing ability, creative practice ability, and learning empathy experience, and, based on this, the deep learning questionnaire is designed, and it is reclassified by exploratory factor analysis to reduce the dimensionality, and the specific indicators and scientific connotation dimensions of the deep learning questionnaire are determined; and, through the deep learning of each dimension, the problems of deep learning of college students are examined and in-depth analysis is conducted, and the inner relationship and correlation among the dimensions of deep learning of college students are derived through correlation analysis. The success of innovation and entrepreneurship depends on the innovation and entrepreneurial ability of college students, and the formation of the ability influenced various factors. Therefore, not only is studying the influencing factors of college students’ innovation and entrepreneurship ability in line with the requirements of the times and social development, but also it can solve real problems. This thesis adopts a combination of two methods, qualitative research and quantitative research, to study the influencing factors of college students’ innovation and entrepreneurship ability and tries to ensure the scientificity, accuracy, and comprehensiveness of the conclusion. In this paper, we analyzed the requirements of the employment prediction system for graduating secondary school students, carried out the software framework and database design of the employment analysis and prediction system for secondary school students, and designed the system modularly based on the analysis results. By applying the proposed deep feedforward neural network prediction model to the prediction system, a software system applicable to the employment prediction and guidance of secondary school students is implemented.

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“…The present study is focused on domain-based reviews and this can be achieved in four manners, namely: Structured reviews (Magni et al , 2020); Framework-based reviews (Paul and Benito, 2018; Lim et al , 2020); Bibliometric reviews; and Hybrid reviews incorporate the rules of two diverse reviews (Dabić et al , 2020). …”

Section: Methodological Approachmentioning

confidence: 99%

“…There are numerous methods and papers on how to conduct systematic reviews (Paul and Rowley, 2020; Paul and Singh, 2017; Magni et al , 2020; Thomas and Gupta, 2021). There are four types of systematic reviews.…”

Section: Methodological Approachmentioning

confidence: 99%

Tacit knowledge in organizations: bibliometrics and a framework-based systematic review of antecedents, outcomes, theories, methods and future directions

Thomas

Gupta

2021

JKM

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Purpose The purpose of this bibliometric and systematic literature review is to survey and evaluate key study’s in tacit knowledge (TK). Through analysing and synthesizing based on the antecedents, decisions, outcomes-theories, context and methods (ADO-TCM) framework, this paper highlights research gaps and avenues for future research. It is important to recognize the antecedents, results and theories in the available literature as it offers enough evidence for encouraging the significance of TK. Design/methodology/approach This research paper follows a bibliometric analysis and systematic approach in identifying, analyzing and synthesizing pertinent literature in TK. A total of 59 research studies were carefully and systematically reviewed with the help of NVivo12 and excel software to code and analyse. Findings With the help of bibliometric analysis and framework-based systematic review, this research paper offers a retrospective view of the TCM framework in the amalgamation with ADO framework, bibliometric analysis and important themes of TK research. Originality/value This paper is different from existing reviews as the authors have to combine bibliometric analysis and framework-based systematic review approach to provide a more robust encapsulation of TK research. To the best of the knowledge, the present research is one of the first systematic reviews based on a framework relating to TK.

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Towards a Framework of Students Co-Creation Behaviour in Higher Education Institutions

Cited by 8 publications

References 0 publications

Does policy enhance collaborative-opportunistic behaviours? Looking into the intellectual capital dynamics of subsidized industry–university partnerships

Does policy enhance collaborative-opportunistic behaviours? Looking into the intellectual capital dynamics of subsidized industry–university partnerships

A Quantitative Enhancement Mechanism of University Students’ Employability and Entrepreneurship Based on Deep Learning in the Context of the Digital Era

Tacit knowledge in organizations: bibliometrics and a framework-based systematic review of antecedents, outcomes, theories, methods and future directions

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