D
2020
COMPARISON OF MINING PREDICTION WITH REAL MINING AS A TOOL FOR STRATEGIC MANAGEMENT
PAWLICZEK, Adam, Lenka TKAČÍKOVÁ, Ladislav MORAVEC, Daniela NAVRÁTILOVÁ, Renáta PAVLÍČKOVÁ et. al.
Basic information
Original name
COMPARISON OF MINING PREDICTION WITH REAL MINING AS A TOOL FOR STRATEGIC MANAGEMENT
Authors
PAWLICZEK, Adam (203 Czech Republic), Lenka TKAČÍKOVÁ (203 Czech Republic, belonging to the institution), Ladislav MORAVEC (203 Czech Republic, belonging to the institution), Daniela NAVRÁTILOVÁ (203 Czech Republic, belonging to the institution) and Renáta PAVLÍČKOVÁ (203 Czech Republic, belonging to the institution)
Edition
Bulharsko, 20th International Multidisciplinary Scientific GeoConference SGEM 2020, p. 43-50, 8 pp. 2020
Publisher
International Multidisciplinary Scientific Geoconference SGEM
Other information
Type of outcome
Stať ve sborníku
Field of Study
50204 Business and management
Country of publisher
Bulgaria
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/26867184:_____/20:N0000030
Organization unit
Moravian Business College Olomouc
Keywords in English
Econometric models; comparison of results; managerial decisions; strategic management
V originále
This paper responds to published scientific papers which compile econometric models of extraction of selected mineral resources. Mining prediction models can be new tools to increase the competitiveness of mining enterprises. Comparing the results of mining prediction and real data is important for further research on the issue. Specification of the results will lead to better managerial decisions in strategic and operational management. The results of the paper can lead to the clarification of the so-called random component in econometric models and the refinement of the assembled models. Random components are different from macroeconomic indicators. These components cannot be quantitatively captured in calculations in terms of econometric models. These components are influenced by the economic models of the mineral extraction prediction. The aim of the paper is to estimate random components in the future when using mining predictions as support for managerial decisions. Other mining activities may react differently to other random components.
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