Stephan Leitner 
Information Quality and Management Accounting [PDF ebook] 
A Simulation Analysis of Biases in Costing Systems

Support

One of the main aims of management accounting is to provide managers with accurate information in order to provide a good basis for decision-making. There is evidence that the information provided by management accounting systems (MAS) is distorted and the occurrence of biases in accounting information is widely accepted among users of MAS. At the same time, the intensity and the frequency of use of MAS increase, too. Consequently, the quality of the provided information is critical. The focus of this simulation study is twofold. On the one hand, the impact of the sophistication of traditional costing systems on error propagation in the case of a set of input biases is investigated. On the other hand, the impact of single and multiple input biases on the quality of the information provided by traditional costing systems is focused. In order to investigate the research questions, a simulation approach is applied.

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Table of Content

Introduction.- Management Accounting.- Conceptual and Theoretical Framework.- Research Design and Model Formalization.- Costing System Sophistication and Quality of Provided Information.- Effects of Single Input Biases on the Quality of Provided Information.- Effects of Multiple Input Biases on the Quality of Provided Information.- Discussion.- Summary and Conclusion.

About the author

Stephan Leitner currently works at the Department for Controlling and Strategic Management at the Alpen-Adria-Universität Klagenfurt. His current research interests include multi objective decision-making, information quality and sustainability. The application of simulation as a research methodology to questions of management science is also an important part of his research.

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Language English ● Format PDF ● Pages 187 ● ISBN 9783642332098 ● File size 3.6 MB ● Publisher Springer Berlin ● City Heidelberg ● Country DE ● Published 2013 ● Downloadable 24 months ● Currency EUR ● ID 2650885 ● Copy protection Social DRM

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