Comparing a New Zealand and an International Accounting Standard: Using artificial neural network software to evaluate differences in the “concept of control”

Grant Samkin
University of Waikato
New Zealand

Annika Schneider
University of Waikato
New Zealand

Abstract:
The purpose of this paper is to illustrate how an artificial neural network programme capable of analysing text can be usefully employed in accounting research.
An artificial neural network programme CATPAC II™ was used to evaluate selected portions of an accounting standard dealing with consolidation developed and issued by the Financial Reporting Standards Board in New Zealand and the equivalent accounting standard developed by the International Accounting Standards Committee and revised by the International Accounting Standards Board.
The analysis of the concepts of control between the two standards showed that differences existed between the two standards. This is confirmed through the use of a hierarchical cluster analysis of 40 unique concepts of each of the two standards and two-dimensional representation of the concepts. The extent of the differences in the concepts was established through a rotational analysis of the two perceptual maps.
This research is limited to the analysis of the concept of control and associated commentary paragraphs and supporting documents associated with two accounting standards. Different results may have been obtained had the whole standard been analysed.
Artificial neural network software confirmed that differences exist in the concept of control detailed in the two accounting standards analysed. These differences could result in different interpretations being taken by the accounting standard users when determining what reporting entities are included in consolidated financial statements. Some uses for artificial neural network software in accounting research are also identified.
This paper is the first in the discipline to use artificial neural network software to analyse and compare different text.