JOURNAL ARTICLE
Institutional Theory and Hybrid Accounting and Control Systems.
Published In: Journal of Management Accounting Research, 2024, v. 36, n. 1. P. 1 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Agarwal, Nishant; Krishnan, Ranjani; Weiler, Luke 3 of 3
Abstract
We identify several manifestations of hybridity in accounting and control systems. Hybridity in the form of multiple accounting systems and actual or postural conformity to institutional expectations can enable organizations to overtly, but sometimes ostensibly, combine multiple logics to appease stakeholders. Hybridity increases costs and the risk of internal inconsistency. Consequently, firms decouple some practices to provide an impression of conformance. We offer a typology of three forms of hybridity—compliance, complete decoupling, and partial decoupling—and illustrate using examples from accounting hybridization choices regarding corporate social responsibility (CSR), diversity, equity, and inclusion (DEI), and international reporting standards. We empirically examine hybridity in the context of the voluntary adoption of international financial reporting standards (IFRS). We find that instrumental pressures are associated with adoption through compliance; however, social pressures are likely to be placated through complete decoupling, whereby firms voluntarily adopt multiple systems in policy, but not in practice. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: B50; L21; M41. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Management Accounting Research. 2024/03, Vol. 36, Issue 1, p1
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:1049-2127
- DOI:10.2308/JMAR-2023-024
- Accession Number:175794930
- Copyright Statement:Copyright of Journal of Management Accounting Research is the property of American Accounting Association 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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