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Outcomes of Industry–University Collaboration in Open Innovation: An Exploratory Investigation of Their Antecedents’ Impact Based on a PLS-SEM and Soft Computing Approach

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  • Călin Florin Băban

    (Faculty of Management and Technological Engineering, University of Oradea, 410087 Oradea, Romania)

  • Marius Băban

    (Faculty of Management and Technological Engineering, University of Oradea, 410087 Oradea, Romania)

  • Adalberto Rangone

    (Department of Management and Business Administration, University “G. d’Annunzio” of Chieti-Pescara, 42-65127 Pescara, Italy)

Abstract

The outcomes of industry–university collaboration, in an open innovation context, may be of great support to firms, in their response to the challenges of today’s highly competitive environment. However, there is no empirical evidence on how these outcomes are influenced by their antecedents. Aiming to fill this gap, a research model to investigate the impact of the major antecedents, identified in the literature as motives, barriers and knowledge transfer channels on the beneficial outcomes and drawbacks of open innovation between the two organizations was developed in this study. The research model was empirically assessed, using a dual-stage predictive approach, based on PLS-SEM and soft computing constituents (artificial neural networks and adaptive neuro-fuzzy inference systems). PLS-SEM was successfully used to test the hypotheses of the research model, while the soft computing approach was employed to predict the complex dependencies between the outcomes and their antecedents. Insights into the relative importance of the antecedents, in shaping the open innovation outcomes, were provided through the importance–performance map analysis. The findings revealed the antecedents that had a significant positive impact on both the beneficial outcomes and drawbacks of industry–university collaboration, in open innovation. The results also highlighted the predictor importance in the research model, as well as the relative importance of the antecedent constructs, based on their effects on the two analyzed outcomes.

Suggested Citation

  • Călin Florin Băban & Marius Băban & Adalberto Rangone, 2022. "Outcomes of Industry–University Collaboration in Open Innovation: An Exploratory Investigation of Their Antecedents’ Impact Based on a PLS-SEM and Soft Computing Approach," Mathematics, MDPI, vol. 10(6), pages 1-26, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:6:p:931-:d:771091
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    References listed on IDEAS

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    5. Fernandes, Cristina & Ferreira, João & Raposo, Mario, 2013. "Drivers to firm innovation and their effects on performance: An international comparison," MPRA Paper 46776, University Library of Munich, Germany.
    6. Bruno Cassiman & Reinhilde Veugelers, 2006. "In Search of Complementarity in Innovation Strategy: Internal R& D and External Knowledge Acquisition," Management Science, INFORMS, vol. 52(1), pages 68-82, January.
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    Cited by:

    1. Marius Băban & Călin Florin Băban & Tudor Mitran, 2023. "Universities as an External Knowledge Source for Industry: Investigating the Antecedents’ Impact on the Importance Perception of Their Collaboration in Open Innovation Using an Ordinal Regression-Neur," Mathematics, MDPI, vol. 11(7), pages 1-23, March.
    2. Mohammad Daradkeh, 2023. "Exploring the Curvilinear Relationship between Academic-Industry Collaboration Environment and Innovation Performance: A Multilevel Perspective," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    3. Călin Florin Băban & Marius Băban, 2022. "An Orchestration Perspective on Open Innovation between Industry–University: Investigating Its Impact on Collaboration Performance," Mathematics, MDPI, vol. 10(15), pages 1-23, July.

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