Proceedings of the 22nd International Scientific Conference on Applications of Mathematics and Statistics in Economics (AMSE 2019)

Multivariate methods for survey evaluation: A case study of Big Data and the New Digital Divide

Authors
Jana Cibulková, Richard Novák, Zdeněk Šulc
Corresponding Author
Jana Cibulková
Available Online October 2019.
DOI
https://doi.org/10.2991/amse-19.2019.7How to use a DOI?
Keywords
multivariate methods, cluster analysis, factor analysis, survey, Big Data, New Digital Divide
Abstract
The paper evaluates the results of a survey regarding challenges connected to the Big Data phenomenon and the New Digital Divide. Following the authors’ previous research, these challenges consist of issues such as business advantage, privacy intrusion, or big brother effect. Perception of these challenges by respondents (IT students and IT professionals) is studied in the paper, and multivariate methods are applied to the survey data to obtain a deeper insight and to discover hidden patterns in the data. The goal of the study is to identify groups of challenges based on respondents’ judgment. For this purpose, cluster analysis and factor analysis are used. Results obtained using these methods are compared and evaluated.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
22nd International Scientific Conference on Applications of Mathematics and Statistics in Economics (AMSE 2019)
Part of series
Atlantis Studies in Uncertainty Modelling
Publication Date
October 2019
ISBN
978-94-6252-804-8
ISSN
2589-6644
DOI
https://doi.org/10.2991/amse-19.2019.7How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jana Cibulková
AU  - Richard Novák
AU  - Zdeněk Šulc
PY  - 2019/10
DA  - 2019/10
TI  - Multivariate methods for survey evaluation: A case study of Big Data and the New Digital Divide
BT  - 22nd International Scientific Conference on Applications of Mathematics and Statistics in Economics (AMSE 2019)
PB  - Atlantis Press
SP  - 62
EP  - 69
SN  - 2589-6644
UR  - https://doi.org/10.2991/amse-19.2019.7
DO  - https://doi.org/10.2991/amse-19.2019.7
ID  - Cibulková2019/10
ER  -