Determining and prioritizing the components of voluntary disclosure to reduce asymmetry using heuristic factor analysis and structural equation modeling
Subject Areas :
امیر شمس
1
(گروه حسابداری، دانشگاه آزاد اسلامی، واحد نیشابورنیشابور ، ایران)
علیرضا مهرآذین
2
(گروه حسابداری، واحد نیشابور، دانشگاه آزاد اسلامی، نیشابور، ایران)
Keywords:
Abstract :
Abstract
The lack of sufficient research literature on voluntary disclosure has motivated this study. First, to date, no comprehensive disclosure measurement study has been conducted that could guide future researchers when creating their own disclosure scales or accepting existing ones. Second, issues related to measurement in the social sciences and the evaluation of disclosure scales are rarely addressed in the accounting research literature. The present study presents and analyzes the components and indicators of voluntary disclosure in a comprehensive framework by examining the views of experts. Also, after determining the components and weighting them with the approach of reducing information asymmetry, the gap between the current and expected situation was examined by 108 experts. The statistical population of the study includes university professors, experts and managers working in the profession of accounting, auditing and financial management of Iran and Tehran Stock Exchange companies in 1399. Research data were analyzed using heuristic factor analysis test, structural equation model and t-test using SPSS software. The results of heuristic factor analysis showed that three dimensions can be extracted for voluntary disclosure of companies (general information and leadership, performance and innovation and future growth) and also the results of t-test showed that between the current situation (current performance) and expected by experts There is a significant difference. The results of this study may reflect the expectations of experts and users of financial statements regarding voluntary disclosure.
Keywords: Voluntary Disclosure, Tehran Stock Exchange, Exploratory Factor Analysis, Information Asymmetry, Structural Equation Model
