HALAŠKA, Michal a Roman ŠPERKA. TDABC and Estimation of Time Drivers Using Process Mining. In Jezic G., Chen-Burger J., Kusek M., Sperka R., Howlett R., Jain L. Smart Innovation, Systems and Technologies. Singapore: Springer. s. 489-499. ISSN 2190-3018. doi:10.1007/978-981-16-2994-5_41. 2021.
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Základní 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
Originální 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"
WWW URL
Kód RIV RIV/47813059:19520/21:A0000203
Organizační jednotka Obchodně podnikatelská fakulta v Karviné
ISSN 2190-3018
Doi http://dx.doi.org/10.1007/978-981-16-2994-5_41
Klíčová slova anglicky Process mining; TDABC; Costing systems; Time drivers; Loan process; Enterprise
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnil: doc. RNDr. Ing. Roman Šperka, Ph.D., učo 18157. Změněno: 5. 8. 2021 11:13.
Anotace
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.
VytisknoutZobrazeno: 29. 3. 2024 01:49