2021
TDABC and Estimation of Time Drivers Using Process Mining
HALAŠKA, Michal a Roman ŠPERKAZákladní údaje
Originální název
TDABC and Estimation of Time Drivers Using Process Mining
Autoři
HALAŠKA, Michal (203 Česká republika, domácí) a Roman ŠPERKA (703 Slovensko, garant, domácí)
Vydání
Singapore, Smart Innovation, Systems and Technologies, od s. 489-499, 11 s. 2021
Nakladatel
Springer
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
50204 Business and management
Stát vydavatele
Singapur
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
tištěná verze "print"
Odkazy
Kód RIV
RIV/47813059:19520/21:A0000203
Organizační jednotka
Obchodně podnikatelská fakulta v Karviné
ISSN
Klíčová slova anglicky
Process mining; TDABC; Costing systems; Time drivers; Loan process; Enterprise
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 5. 8. 2021 11:13, doc. RNDr. Ing. Roman Šperka, Ph.D.
Anotace
V originále
Costing systems play a crucial role in many managerial decisions; thus, it is crucial that costing systems provide appropriate information. Time-driven activity-based costing systems (TDABC) are successors of activity-based costing systems (ABC). ABCs were created in order to address shortcomings of traditional costing systems, while TDABCs were created to address mostly implementational shortcomings of ABCs. In this research, we focus on the advantages of integration of process mining (PM) and TDABC for estimation of activity durations used as time drivers for allocation of overhead costs. Thus, we have stated two research questions: (1) Can PM be used for estimation of time drivers? and (2) What are the benefits of using PM for the estimation of time drivers? To address these questions, we present a proof of concept, where we analyze two real-world datasets representing loan application process. Firstly, we clean both datasets, and then, we use PM techniques to discover process models representing the process. We show that PM can be used for time estimation and time drivers’ determination and that there are potential benefits to this approach. Furthermore, we discuss the possibility of using actual times instead of estimates.