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November 1, 2024Journal of Accounting Literature10 citationsOpen Access

A review of ex ante and ex post materiality measures, and consequences and determinants of material disclosures in sustainability reporting

AHAsif HuqMMMahsa Mohammadrezaei

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Abstract

Purpose The purpose of the review is to synthesize the research on materiality measures of sustainability reporting and highlight how preparers, users, auditors, regulators and other stakeholders assess or determine the materiality in sustainability reporting. The review further summarizes the findings on consequences and determinants of material disclosures in sustainability reporting. Several directions for future research are also discussed. Design/methodology/approach This study provides a systematic review of materiality measures developed in the context of sustainability reporting. This synthesis of the literature summarizes the existing methodologies of measuring materiality. It also evaluates the strength and limitations of existing methods and approaches of measuring materiality in sustainability disclosures. Findings We find that the ex post materiality measures are simplistic and unidirectional in nature and ex ante materiality measures lack external validity and are generally narrow in focus – for example, focused on single firms or industries. Another major limitation in the current literature is the absence of robust empirical investigation of double materiality in sustainability reporting and a vast majority of the measures are developed without stakeholder engagement. Lastly, we document that the findings on determinants of material disclosure are fragmented and inconclusive and that the literature on consequences of material disclosure is rather un-explored. Originality/value The study explains the connections and differences between the various materiality measures. We document that materiality is measured in two distinct ways, ex ante and ex post and often times without stakeholder engagement. Moreover, given that a vast majority of the measures rely on manual content analysis, we find that they suffer from reproducibility and scalability.

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Cite This Study

Huq et al. (2024) studied this question.

synapsesocial.com/papers/6a6375e61ec0c1a689b6feaehttps://doi.org/10.1108/jal-04-2024-0084
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