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EconLab

Laboratory for Experimental Economics and Big Data Processing

EconLab is a teaching and research laboratory at EF TUL, which serves as a platform for experimental, behavioral and quantitative research and the introduction of modern methods into teaching. The laboratory was established in 2018 with the support from the OP Science, Research and Education.

 

The facility is equipped with 25 medium-power workstations for students and experiment participants. The workstations are separated by partitions. Furthermore, the laboratory has separate facilities for control and evaluation of experiments. The hardware equipment of the laboratory is complemented by appropriate software, in particular a complete sortware solution for the analytical data process from IBM, i.e. from data collection through data analysis to prediction based on datamining (Data Collection, SPSS Statistics, SPSS Modeler), as well as software for automatic recognition and analysis of facial expressions including refinement methods (e.g. digital photoplethysmography) Noldus FaceReader v.8 and the Z-Tree software for economic experiments, i.e. an environment for designing and implementing economic experiments.

 

At EconLab there are currently solved R&D tasks within the projects of basic and applied research and development projects:

TL01000303: Use of Big Data to assess the socio-economic position of the population in the different territories defined by the Regional Development Strategy 2021+. TACR, Éta Program. Investigator: Ing. Ales Kocourek, Ph.D. Project duration: 2018 - 2021.

GA18-01144S: Empirical study of the impact of cluster existence on member companies' performance. GACR. Investigator: prof. Ing. Miroslav Žižka, Ph.D. Project duration: 2018 - 2020

Project of internal grant competition EF TUL: Improvement of educational activities at EF TUL in the environment of the Laboratory for Economic Experiments and Big Data Processing (EconLab). Project duration: 2019 - 2020.

Laboratory team members

Name

Position Subject of development and research
Ing. Marián Lamr, Ph.D. administrator, teacher Datamining and data-driven decision making
Ing. Jana Šimanová, Ph.D.

contact with practice, teacher of International Economics

Big data, advanced statistical methods
doc. Ing. Aleš Kocourek, Ph.D. teacher in International Economics Big data, advanced statistical methods, GTE modelling
Ing. Jitka Burešová, Ph.D. teacher of Online Marketing Communication The field of behavioural marketing
Mgr. Tomáš Žižka, Ph.D.

web and database administrator, lecturer of professional subjects at the Department of Informatics

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