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dc.contributor.advisorIselin, Errol
dc.contributor.authorGadenne, David L.
dc.date.accessioned2019-03-26T23:10:19Z
dc.date.available2019-03-26T23:10:19Z
dc.date.issued1994
dc.identifier.doi10.25904/1912/675
dc.identifier.urihttp://hdl.handle.net/10072/367843
dc.description.abstractThe recent recessionary conditions in Australia precipitated an increase in the number of public company failures. This increase in company failure has consequences for accountants who are concerned with providing interested user groups with information relevant for predictions of the future financial position of the firm. (See Statement of Accounting Concepts, SAC 2). The interested user groups in this context include auditors, bank loan officers, and security analysts. Auditors require this type of information to make going concern judgements; bank loan officers require this information to make corporate loan approvals; whereas security analysts require this information to minimise investment risk. Previous research has found that these user groups are invariably outperformed by environmental models in predicting financial distress. However, this research is problematic in terms of the information set used and the methods of comparison. The research in this thesis aims to overcome these problems. The main objectives of this thesis are (1) to show that human decision performance is not necessarily inferior to that of environmental models when the information set is based on information considered to be useful and important to each of the above three groups, (2) to develop new environmental models which have practical relevance to user groups, (3) to compare the decision performance of all three user groups with environmental models and models of man, and (4) to examine how variation in information condition may affect decision quality, via information load, data load and uncertainty. These objectives were achieved by (1) administering an exploratory survey that elicited the current needs of all three user groups, (2) conducting an experiment that considered the impact of the information found to be useful and important to user groups on decisions involving financial distress prediction, and (3) constructing environmental models and models of man. The results of the exploratory survey indicated that the user groups found certain major classes of information to be useful and important for financial distress prediction. These items were subsequently operationalised in the form of three different levels of information, appropriate for (1) human decision making, and (2) the development of new statistical (environmental) model specifications. The resulting statistical models contained new measures of relative firm/industry performance and relative firm/economy performance. The experiment conducted in this thesis considered the effect of the different levels of information on the decision accuracy of the three user groups. The results revealed some differences between the user groups regarding the effects of information condition on decision accuracy, via the three intervening variables. Information condition was found to (1) significantly affect subjective uncertainty for bank loan officers but not for auditors and security analysts, and (2) significantly affect subjective data load for bank loan officers and security analysts but not for auditors. In the high versus medium information condition comparison, the significant reduction in uncertainty for bank loan officers resulted in higher decision accuracy (which was consistent with the result for the environmental model); however, in the medium versus low information condition comparison, since the reduction in uncertainty was offset by a corresponding increase in data load, there was no significant change in decision accuracy. The significant increase in data load for security analysts did not significantly affect decision accuracy. Comparisons of human decision makers with statistical models showed that in the low and medium information conditions, the decision accuracy of each user group was not significantly different from that of the statistical models; while in the high information condition the accuracy of the statistical model was significantly higher than that of each user group. This result suggests that the higher data load in the high versus medium and low information conditions may have adversely affected the decision accuracy of the three user groups. Comparisons of all three user groups with their respective models of man revealed that (1) bank loan officers were more consistent in their judgement policies than the other two groups, (which may reflect the banks' uniformity in training programs or the bank loan officers' greater experience in dealing with financial distress predictions) and (2) each user group performed at a lower level than the model of man in the higher information condition, (which may reflect the detrimental effect of data load on consistency in judgement policy). Finally, comparisons of all three groups in relation to self insight and confidence assessments revealed no significant differences, irrespective of changes in the level of information condition. The implications of the thesis findings for future practice include (1) training of various user groups in the use of industry and financial markets information for financial distress decisions, (2) use of a statistical model as a decision aid in situations where data load is high, (3) encouragement of accounting policy setters to focus on reporting information that is more directly relevant to the needs of user groups, and (4) improvement in the consistency of judgement policy by providing decision makers with more specific guidelines for financial distress predictions.
dc.languageEnglish
dc.publisherGriffith University
dc.publisher.placeBrisbane
dc.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
dc.subject.keywordsFinancial disclosure
dc.subject.keywordsCorporate finance
dc.subject.keywordsBusiness finance
dc.subject.keywordsManagement
dc.subject.keywordsFinancial services. accounting
dc.titleA Comparative Study of Accounting Information Users and Statistical Models in a Financial Distress Prediction Task
dc.typeGriffith thesis
gro.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
gro.hasfulltextFull Text
gro.identifier.gurtIDgu1335142756454
gro.identifier.ADTnumberadt-QGU20050831.154332
gro.thesis.degreelevelThesis (PhD Doctorate)
gro.thesis.degreeprogramDoctor of Philosophy (PhD)
gro.departmentGriffith Business School
gro.griffith.authorGadenne, David L.


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