Open Innovation Platforms and Knowledge Transfer Mechanisms in University-Industry Collaborations

Abstract

Changing the current knowledge systems to Open Innovation Platforms (OIPs) is necessary to improve knowledge transfer between industries and universities, create cooperation, and facilitate innovation. This paper uses Multi-Criteria Decision Analysis (MCDA) and Geographic Information Systems (GIS) to analyze the relationships between universities and industries and determine the best models of the knowledge exchange. Statistical research of 15 university-industry partnerships in technology, health, and manufacturing sectors demonstrates that Full Model (MCDA + GIS + Criteria) has yielded the greatest performance results. In particular, the innovation output rose by 25, efficiency rose by 20, and the social acceptance rose by 10 % when OIPs were in place. Another factor that can also be noted in the study is the effect of incorporating GIS because the site suitability assessments were improved by 15 % and decision-making on adopting technology was enhanced. Moreover, the examination reveals that consideration of social impact factors helped to raise the success of collaboration, in accordance with the stakeholders’ expectations and building more effective industry-academic relations. Nonetheless, the omission of GIS decreased collaboration model efficiency by 5% and social impact factor omission decreased social acceptance by 4% thus highlighting the significance of these elements in the optimization of OIP. The findings underline the importance of an integrated approach to partnership, which comprises technical, economical, and social parameters, to guarantee the high effectiveness of university-industry partnerships. In its conclusion, the study will provide the policy makers and the industry executives with the fixation of integrating MCDA and GIS into the decision-making process to make OIPs more effective and serve the sustainability of the sustainable development goals (SDGs). The future of OIPs needs to be employed in other industries and regions with the help of newer technologies such as AI and blockchain to enhance the functionality and scalability of OIPs.