TDABC and Estimation of Time Drivers Using Process Mining
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F21%3AA0000203" target="_blank" >RIV/47813059:19520/21:A0000203 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-981-16-2994-5_41" target="_blank" >http://dx.doi.org/10.1007/978-981-16-2994-5_41</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-16-2994-5_41" target="_blank" >10.1007/978-981-16-2994-5_41</a>
Alternative languages
Result language
angličtina
Original language name
TDABC and Estimation of Time Drivers Using Process Mining
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Smart Innovation, Systems and Technologies
ISBN
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ISSN
2190-3018
e-ISSN
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Number of pages
11
Pages from-to
489-499
Publisher name
Springer
Place of publication
Singapore
Event location
online
Event date
Jun 14, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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