194 research outputs found

    Hebben overheidsprogramma's een effect? Een methodologisch-empirische analyse van de PRESTI-acties van de Vlaamse Overheid

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    This paper discusses the results of a performance study of flemish environmental policy for Smal1 and Mediuin Sized companies. Extensive field research, based on interviews and questionnaire surveys with over 20 professional associations and over 700 companies belonging to the sectors stimulated by the Flemish PRESTI-programine, allowed us to assess the effects of a sectoral policy geared towards stimulating SMEs to become more conscious and active on the topic of waste prevention. The PRESTI-programme was specifically aimed at stimulating waste prevention action plans at SMEs via the interface of professional associations at the sector level. The results are encouraging, the more since this research project was the first one that attempted at assessing the impact of a specific programme at the level of Flemish environmental policy.

    Origin and emergence of entrepreneurship as a research field

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    This paper seeks to map out the emergence and evolution of entrepreneurship as an independent field in the social science literature from the early 1990s to 2009. Our analysis indicates that entrepreneurship has grown steadily during the 1990s but has truly emerged as a legitimate academic discipline in the latter part of the 2000s. The field has been dominated by researchers from Anglo-Saxon countries over the past 20 years, with particularly strong representations from the US, UK, and Canada. The results from our structural analysis, which is based on a core document approach, point to five large knowledge clusters and further 16 sub-clusters. We characterize the clusters from their cognitive structure and assess the strength of the relationships between these clusters. In addition, a list of most cited articles is presented and discussed

    Why are we still using 3D masses for cluster cosmology?

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    Large scale structure and cosmolog

    Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

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    The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

    Technology transfer model for Austrian higher education institutions

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    The aim of this paper is to present the findings of a PhD research (Heinzl 2007, Unpublished PhD Thesis) conducted on the Universities of Applied Sciences in Austria. Four of the models that emerge from this research are: Generic Technology Transfer Model (Sect. 5.1); Idiosyncrasies Model for the Austrian Universities of Applied Sciences (Sect. 5.2); Idiosyncrasies-Technology Transfer Effects Model (Sect. 5.3); Idiosyncrasies-Technology Transfer Cumulated Effects Model (Sect. 5.3). The primary and secondary research methods employed for this study are: literature survey, focus groups, participant observation, and interviews. The findings of the research contribute to a conceptual design of a technology transfer system which aims to enhance the higher education institutions' technology transfer performance. © 2012 Springer Science+Business Media, LLC

    University–industry collaboration: using meta-rules to overcome barriers to knowledge transfer

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    This is the final version of the article. Available from Springer Verlag via the DOI in this record.University–industry knowledge transfer is an important source wealth of creation for all partners; however, the practical management of this activity within universities is often hampered by procedural rigidity either through the absence of decision-making protocols to reconcile conflicting priorities or through the inconsistent implementation of existing policies. This is problematic, since it can impede operational effectiveness, prevent inter-organisational knowledge-creation and hamper organisational learning. This paper addresses this issue by adopting a cross-discipline approach and presenting meta-rules as a solution to aid organisational decision making. It is proposed that meta-rules can help resolve tensions arising from conflicting priorities between academics, knowledge transfer offices and industry and help facilitate strategic alignment of processes and policies within and between organisations. This research contributes to the growing debate on the strategic challenges of managing knowledge transfer and presents meta-rules as a practical solution to facilitate strategic alignment of internal and external stakeholder tensions. Meta-rules has previously only been applied in a computer intelligence context however, this research proves the efficacy of meta rules in a university–industry knowledge transfer context. This research also has practical implications for knowledge transfer office managers who can use meta-rules to help overcome resource limitations, conflicting priorities and goals of diverse internal and external stakeholders
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