FACTORS EFFECTIVE ON TIMELINESS OF FINANCIAL REPORTING: USING SYNTHETIC NEURAL NETWORKS AND DECISION TREES TECHNIQUES

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MORADI MAHDI; SOLEYMANI MARESHK MOJTABA; Bagheri Mostafa

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Journal: Journal of Empirical Research in Accounting Year:2015 | Volume:5 | Issue:17 Page(s): 119-137

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Title

FACTORS EFFECTIVE ON TIMELINESS OF FINANCIAL REPORTING: USING SYNTHETIC NEURAL NETWORKS AND DECISION TREES TECHNIQUES

Author(s)

MORADI MAHDI | SOLEYMANI MARESHK MOJTABA | Bagheri Mostafa | Issue Writer Certificate

Keywords

TIMELINESSQ2

REPORTING FINANCIAL STATEMENTSQ2

ACCOUNTING INFORMATION QUALITYQ1

NEURAL NETWORKSQ2

DECISION TREESQ2

Abstract

In decision making, TIMELINESS is one of the useful information features that have increasingly attracted the attention of regulatory agencies. This paper examines factors which are related to the TIMELINESS of annual REPORTING FINANCIAL STATEMENTS in Tehran stock exchange listed firms. The effect on financial reporting TIMELINESS of factors such as the ratio of the investment institutes, major shareholders and institutional shareholders ownership, the ratio of the shares held by the CEO and board, the quantity of the majority shareholders, and the ratio of the non-executive members, duality, big auditor, auditor change, size, age, ROE, good news, consolidate financial reporting and the quality of the costing system, opinion of the independent auditor and industry during the years 2008 to 2011 have been studied. NEURAL NETWORKS and DECISION TREES techniques is utilized for data analysis. The Results show that the institutional shareholders ownership, quantity of the majority shareholders, industry, big auditor, opinion of the independent auditor, ratio of the non-executive members, consolidate financial reporting and ROE have the greatest effect on quality of TIMELINESS, respectively. Also average accuracy of NEURAL NETWORKS technique is higher than DECISION TREES technique.

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APA: Copy

MORADI, MAHDI, SOLEYMANI MARESHK, MOJTABA, & Bagheri, Mostafa. (2015). FACTORS EFFECTIVE ON TIMELINESS OF FINANCIAL REPORTING: USING SYNTHETIC NEURAL NETWORKS AND DECISION TREES TECHNIQUES. JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING, 5(17 ), 119-137. SID. https://sid.ir/paper/241106/en

Vancouver: Copy

MORADI MAHDI, SOLEYMANI MARESHK MOJTABA, Bagheri Mostafa. FACTORS EFFECTIVE ON TIMELINESS OF FINANCIAL REPORTING: USING SYNTHETIC NEURAL NETWORKS AND DECISION TREES TECHNIQUES. JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING[Internet]. 2015;5(17 ):119-137. Available from: https://sid.ir/paper/241106/en

IEEE: Copy

MAHDI MORADI, MOJTABA SOLEYMANI MARESHK, and Mostafa Bagheri, “FACTORS EFFECTIVE ON TIMELINESS OF FINANCIAL REPORTING: USING SYNTHETIC NEURAL NETWORKS AND DECISION TREES TECHNIQUES,” JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING, vol. 5, no. 17 , pp. 119–137, 2015, [Online]. Available: https://sid.ir/paper/241106/en

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