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Opis: The paper addresses a manifestation of University-Industry collaboration - the Technology Transfer Offices (TTO). The university-industry collaboration is relevant in the age of open innovation, and TTO serves as the meeting point between the two worlds. In this context, we are interested in how three specific cases of TTO operating in three distinct innovation ecosystems understand their role and how they perceive their strengths and weaknesses. The reader of the presented research will get an insight into three innovation ecosystems, each particular in its regard, and will learn that despite the differences among countries and cultures, the questions the TTO are struggling with are less diverse. A qualitative empirical study in three countries included focus group participants and expert representatives of academic-business technology transfer actors. To sum up, the respected countries need to carefully tailor innovation policies and explore the benefits of the TTO in boosting the commercialisation of products developed at universities.
Ključne besede: Slovenia, Italia, Malta, Technology Transfer Offices, University-Industry collaboration, innovations, social field, cognitive frames, networks, institutions
Objavljeno v ReVIS: 14.05.2025; Ogledov: 345; Prenosov: 3
Celotno besedilo (119,73 KB)

Opis: The thesis touches on important concepts of innovation and regional development. Their empirical relevance for economic and social growth is a subject of active debate. Studies revealed that interactions have a major impact, de facto, on the capacity to innovate. Diversifying knowledge sources, joint ventures and co-creational practices can explain much of the locational factors and innovation in a-spatial networks. With the rise of globalisation, scholars found that Multinational Corporations and their global production chains are integrating more and more into regions worldwide. They share practices and engage local stakeholders in their innovation projects. This research aims to explore the importance of locational and global factors in this process. The goal is to see how these two forces contribute to innovation separately and when intertwined regionally, closing the gap between regional and global innovation frameworks. The thesis contributes to science by developing a new synthesis model based on mainstream Innovation theories. It includes the endogenous and exogenous forces that create environmental pressures and opportunities, pushing economic agents to innovate. The central aspect of this model is the acknowledgement of the multiscalar nature of innovation. Local institutions, mindsets and influence from the production chains create conditions and pressures in the network, which motivates companies to innovate. Depending on the local competencies and the needs of production networks, it creates various environments for companies. It is up to enterprises to use created opportunities, which can be local, national or global. Data collected in eight (distinct) regions in Central and Eastern Europe (active in automotive and electronics industries) was used in qualitative and logical analysis to observe patterns in regional behaviour. The results revealed that endogenous and exogenous forces act circumstantially in each region, partially proving all the hypotheses on endogenous and exogenous factors and validating the model. Each region displays different rates of local and regional engagement and, thus, different patterns of innovation, determining their competitive potential. The research also revealed additional factors (e.g., the importance of trust, particularities of information diffusion, etc.) relevant to innovation in Central and Eastern Europe.
Ključne besede: innovation, regional development, transnational value chains, networks, institutions, cognitive mindset, regional-global co-operation
Objavljeno v ReVIS: 25.10.2022; Ogledov: 2750; Prenosov: 84
Celotno besedilo (5,96 MB)

Opis: Higher education institutions (HEIs) are often curious whether students will be successful or not during their study. Before or during their courses the academic institutions try to estimate the percentage of successful students. But is it possible to predict the success rate of students enrolled in their courses? Are there any specific student characteristics, which can be associated with the student success rate? Is there any relevant student data available to HEIs on the basis of which they could predict the student success rate? The answers to the above research questions can generally be obtained using data mining tools. Unfortunately, data mining algorithms work best with large data sets, while student data, available to HEIs, related to courses are limited and falls into the category of small data sets. Thus, the study focuses on data mining for small student data sets and aims to answer the above research questions by comparing two different data mining tools. The conclusions of this study are very promising and will encourage HEIs to incorporate data mining tools as an important part of their higher education knowledge management systems.
Ključne besede: data mining, knowledge management system, student's success rate, data mining for small data set, higher education institutions, educational data mining
Objavljeno v ReVIS: 19.02.2016; Ogledov: 9084; Prenosov: 329  (1 glas)
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