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

Language

English

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

References:

RIV identification code

RIV/26867184:_____/20:N0000030

Organization unit

Moravian Business College Olomouc

ISBN

978-619-7603-06-4

ISSN

DOI

Keywords in English

Econometric models; comparison of results; managerial decisions; strategic management

Tags

Změněno: 5/5/2021 13:12, Ing. Michaela Nováková

Abstract

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.