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Export Reference (APA) 
Trigueiros, D. & Taffler, R. (1996). Neural networks and empirical research in accounting. Accounting and Business Research. 26 (4), 347-355
Export Reference (IEEE) 
D. M. Trigueiros and R. Taffler,  "Neural networks and empirical research in accounting", in Accounting and Business Research, vol. 26, no. 4, pp. 347-355, 1996
Export BibTeX 
@article{trigueiros1996_1716163370288,
	author = "Trigueiros, D. and Taffler, R.",
	title = "Neural networks and empirical research in accounting",
	journal = "Accounting and Business Research",
	year = "1996",
	volume = "26",
	number = "4",
	doi = "10.1080/00014788.1996.9729524",
	pages = "347-355",
	url = "https://tandfonline.com/doi/abs/10.1080/00014788.1996.9729524"
}
Export RIS 
TY  - JOUR
TI  - Neural networks and empirical research in accounting
T2  - Accounting and Business Research
VL  - 26
IS  - 4
AU  - Trigueiros, D.
AU  - Taffler, R.
PY  - 1996
SP  - 347-355
SN  - 0001-4788
DO  - 10.1080/00014788.1996.9729524
UR  - https://tandfonline.com/doi/abs/10.1080/00014788.1996.9729524
AB  - 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.
ER  -