JOURNAL ARTICLE
Publication trends in the Journal of International Financial Management and Accounting: A retrospective review.
Published In: Journal of International Financial Management & Accounting, 2023, v. 34, n. 2. P. 131 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Baker, H. Kent; Kumar, Satish; Goyal, Kirti 3 of 3
Abstract
This study uses bibliometric analysis to assess Journal of International Financial Management & Accounting (JIFMA's) evolution between 1989 and 2021. In this retrospective review, we investigate the journal's performance, authorship trends, and intellectual structure. The journal's international focus is primarily on cross‐country studies and the effects of country‐level factors on various accounting and finance outcomes. The collaborative network of JIFMA's authors has also grown substantially consistent with rise in research collaboration in general across the world. We identify nine major themes making up JIFMA's knowledge structure: (1) value relevance of accounting information relating to the adoption of International Financial Reporting Standards, (2) voluntary corporate disclosure, (3) corporate use of financial derivatives, (4) corporate governance, (5) equity valuation, (6) stock return seasonalities, foreign equity ownership, and cost of capital, (7) earnings announcements and pecking order behavior, (8) triple‐bottom‐line disclosures, and (9) managerial ownership and earnings management. Our findings will likely benefit JIFMA's editorial board and other journal stakeholders including future researchers. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of International Financial Management & Accounting. 2023/06, Vol. 34, Issue 2, p131
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2023
- ISSN:0954-1314
- DOI:10.1111/jifm.12176
- Accession Number:164779722
- Copyright Statement:Copyright of Journal of International Financial Management & Accounting is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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