Forthcoming and Online First Articles

International Journal of Economics and Accounting

International Journal of Economics and Accounting (IJEA)

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International Journal of Economics and Accounting (3 papers in press)

Regular Issues

  • Multilevel consultation in the development of IFRS: a comparative content analysis of comment letters sent to EFRAG and the IASB   Order a copy of this article
    by Martin Gäumann 
    Abstract: This paper examines characteristics of the content of comment letters (CLs) written by European constituents and sent to the European Financial Reporting Advisory Group (EFRAG) and International Accounting Standards Board (IASB) to influence the development of International Financial Reporting Standards (IFRS). Following a multi-issue, multi-period approach, the study presented here involves a manual content analysis to compare the scope (i.e., organisation-specificity), form (i.e., completeness and level of detail), and tone (i.e,. level of support) of the content of 892 pairs of CLs sent to EFRAG and the IASB between 2008 and 2016. Overall, the findings illuminate the participatory practices of European constituents in a cross-organisational setting, thereby challenging the common assumption that they send almost only highly similar or identical CLs to EFRAG and the IASB, as well as elucidate EFRAG’s intermediary role in setting international accounting standards.
    Keywords: European Financial Reporting Advisory Group; EFRAG; International Accounting Standards Board; IASB; standard setting; International Financial Reporting Standards; IFRS; comment letters; due process.
    DOI: 10.1504/IJEA.2022.10052057
     
  • Human resource disclosure practices in corporate sector in India: an item-wise analysis   Order a copy of this article
    by Kirti Aggarwal 
    Abstract: The objective of the present study is to examines the item-wise human resource disclosure practices in corporate sector in India. The present study is based on 336 companies listed on NSE-500 Index for the time period of eight years (F.Y. 2012-2013 to 2019-2020). The outcome of the study shows that on an average, Human Resource Policy and Vision component has got highest disclosure percentage in the year 2019-2020 (82.96) and the lowest disclosure percentage is got by Importance of Human Resource to the Organisation component in the year 2012-2013 (2.41). It clearly shows that Indian listed companies are focusing on HR policies and vision because, they are serving as a reference point for the future. On the other hand, the Indian listed companies are not considering HR as an important or strategic asset for their organisation.
    Keywords: human resource; content analysis; annual report; human resource disclosure index; HRDI; trend; India.
    DOI: 10.1504/IJEA.2022.10052279
     
  • If humans fail, machines take action: assessment of accounting error detection using machine learning   Order a copy of this article
    by Marius Gros, Anika Hanke 
    Abstract: Various accounting scandals have documented that current enforcement systems may fail to detect erroneous reporting or identify fraudulent actions. Therefore, enforcement systems should continuously reassess and update the applied methods. Existing studies have shown that textual information and machine learning techniques can substantially support accounting error detection. We use proprietary data from enforcement investigations conducted by the German enforcement system to gain insights into the feasibility of such applications. Our classification models consider a wide range of classification and feature selection methods based on three indicator categories: financial, linguistic, and content. In contrast to many previous studies, we evaluate the classification performance using a realistic imbalanced holdout sample. We observe that content features are particularly important error indicators, and the combination of indicator categories has a significant impact on error detection. Additionally, feature selection plays an essential role in preventing indicator overload.
    Keywords: enforcement; error detection; feature selection; synthetic minority oversampling technique; SMOTE; topic modelling.
    DOI: 10.1504/IJEA.2022.10052508