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1

The Influential Knowledge Factors of Companies’ Performance in Slovenia

100%
Rašič K., Mulej M., Čančer V.
Business Systems Research Journal
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2016
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vol. 7
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issue 1
46-58
EN
Background: Knowledge plays a crucial role in supporting the European Union model based on economic growth, social responsibility, and sustainable development. To improve companies’ performance, one must reflect on new forms of knowledge and develop new indicators to measure them. Objectives: The goal of the paper is to investigate the impact of the selected factors of knowledge on companies’ performance in Slovenia. Methods/Approach: A questionnaire was created and sent to small and medium-sized enterprises in Slovenia. The principle axis factoring method was used to identify the factors of knowledge and of companies’ performance, and a regression analysis was conducted to determine the influence of the selected knowledge factors on companies’ performance. Results: The establishment of scientists’ collaboration with companies has a positive impact on companies’ performance, but the obstacles to the establishment of scientists’ collaboration with companies do not have any impact. Conclusions: The results could be useful for governments and companies in the adoption of measures aimed at strengthening scientists’ collaboration with companies. Further research can be oriented toward the common synergy index (e.g., the knowledge triangle).
2

Statistical Computing in Information Society

100%
Domański C., Jędrzejczak A.
Folia Oeconomica Stetinensia
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2015
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vol. 15
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issue 2
144-152
EN
In the presence of massive data coming with high heterogeneity we need to change our statistical thinking and statistical education in order to adapt both - classical statistics and software developments that address new challenges. Significant developments include open data, big data, data visualisation, and they are changing the nature of the evidence that is available, the ways in which it is presented and the skills needed for its interpretation. The amount of information is not the most important issue – the real challenge is the combination of the amount and the complexity of data. Moreover, a need arises to know how uncertain situations should be dealt with and what decisions should be taken when information is insufficient (which can also be observed for large datasets). In the paper we discuss the idea of computational statistics as a new approach to statistical teaching and we try to answer a question: how we can best prepare the next generation of statisticians.
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