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Probabilistic time‐driven activity‐based costing
Author(s) -
Sánchez Marisa A.,
Batista Marianela De
Publication year - 2020
Publication title -
journal of corporate accounting and finance
Language(s) - English
Resource type - Journals
eISSN - 1097-0053
pISSN - 1044-8136
DOI - 10.1002/jcaf.22468
Subject(s) - probabilistic logic , activity based costing , computer science , interval (graph theory) , operations research , total cost , monte carlo method , consumption (sociology) , statistics , mathematics , artificial intelligence , economics , accounting , social science , combinatorics , sociology , microeconomics
This article proposes a Probabilistic Time‐driven Activity‐based costing model. Time consumption is represented using probabilistic variables and Monte Carlo simulation technique is used to forecast total cost. The simulation experiments provide data to estimate a confidence interval for the total cost of a cost object. Hence, simulation can easily address variations in time forecasts and provide a more realistic characterization of total cost. The definition of the number of resources (e.g., employees) as decision variables allows analyzing alternatives and answer “what‐if questions”. The proposal would be very useful for an operation manager in analyzing uncertain scenarios and providing information indicating under what conditions different cost estimates are feasible.