J 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 a Tomáš PRAŽÁK

Základní údaje

Originální název

At what lag should economic indicators be applied to predict sales in a transformed economy? Is it worthwhile when e-tailing?

Autoři

BAUEROVÁ, Radka (203 Česká republika, garant, domácí), Halina STARZYCZNÁ (203 Česká republika, domácí) a Tomáš PRAŽÁK (203 Česká republika, domácí)

Vydání

Forum Scientiae Oeconomia, Dąbrowa Górnicza, Faculty of Applied Sciences of WSB University, Dąbrowa Górnicza, 2022, 2300-5947

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50202 Applied Economics, Econometrics

Stát vydavatele

Polsko

Utajení

není předmětem státního či obchodního tajemství

Kód RIV

RIV/47813059:19520/22:A0000349

Organizační jednotka

Obchodně podnikatelská fakulta v Karviné

Klíčová slova anglicky

transformed economies; retail industry; retail sales; economic indicators; cointegration

Příznaky

Recenzováno
Změněno: 30. 12. 2022 14:39, Ing. Radka Bauerová, Ph.D.

Anotace

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.