Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/28948
Author(s): | Trigueiros, D. Taffler, R. |
Date: | 1996 |
Title: | Neural networks and empirical research in accounting |
Journal title: | Accounting and Business Research |
Volume: | 26 |
Number: | 4 |
Pages: | 347 - 355 |
Reference: | Trigueiros, D., & Taffler, R. (1996). Neural networks and empirical research in accounting. Accounting and Business Research, 26(4), 347-355. https://dx.doi.org/10.1080/00014788.1996.9729524 |
ISSN: | 0001-4788 |
DOI (Digital Object Identifier): | 10.1080/00014788.1996.9729524 |
Abstract: | This article seeks to provide an overview of the potential role of neural network (connectionist) methodology in empirical accounting research. It highlights how the accounting task domain differs substantially from those for which neural network techniques were originally developed. A non-technical overview of neural network methodology is given along with guidelines to help accounting researchers interested in applying these new tools to recognise the potential dangers and strengths underlying their use. An illustrative example is provided. The paper suggests research areas in accounting where neural network approaches could make a potential contribution. Explicit recommendations for prospective authors are made. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Size | Format | |
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article_34146.pdf | 209,66 kB | Adobe PDF | View/Open |
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