Detailed Information on Publication Record
2022
At what lag should economic indicators be applied to predict sales in a transformed economy? Is it worthwhile when e-tailing?
BAUEROVÁ, Radka, Halina STARZYCZNÁ and Tomáš PRAŽÁKBasic information
Original name
At what lag should economic indicators be applied to predict sales in a transformed economy? Is it worthwhile when e-tailing?
Authors
BAUEROVÁ, Radka (203 Czech Republic, guarantor, belonging to the institution), Halina STARZYCZNÁ (203 Czech Republic, belonging to the institution) and Tomáš PRAŽÁK (203 Czech Republic, belonging to the institution)
Edition
Forum Scientiae Oeconomia, Dąbrowa Górnicza, Faculty of Applied Sciences of WSB University, Dąbrowa Górnicza, 2022, 2300-5947
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
50202 Applied Economics, Econometrics
Country of publisher
Poland
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/47813059:19520/22:A0000349
Organization unit
School of Business Administration in Karvina
Keywords in English
transformed economies; retail industry; retail sales; economic indicators; cointegration
Tags
Reviewed
Změněno: 30/12/2022 14:39, Ing. Radka Bauerová, Ph.D.
Abstract
V originále
Making strategic decisions in retailing is associated with an-alysing sales development, which can indicate the current trends in consumer demand. Determining retail sales indi-cators is a valuable step towards better prediction and helps to make strategic decisions more realistic. However, the ques-tion is to what extent the general assumption of profitability of using retail sales indicators can be applied in the case of a transformed economy. This paper aims to provide informa-tion on the possibility of using selected economic indicators to predict sales in the environment of a transformed economy. The paper analyses the joint time series development of retail sales in the Czech Republic. The Johansen cointegration test has been performed to determine whether retail sales show long-term cointegration with the set of selected indicators. The results establish GDP, total employment, gross wage, and consumer data as leading indicators of retail sales at different levels of delays. In contrast, in the case of online retail sales, no significant influence of the observed factors has been found. The findings suggest that if managers choose to plan their online retail processes based on retail sales estimates, they must respond to changes in these indicators much faster than managers in off line environments.