Datasets for sustainability reporting index of agricultural & plantation companies in Malaysia

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-03-19 DOI:10.1016/j.dib.2025.111491

Nurfara Hasyikin Hanapi, Waleed M. Alahdal, Hafiza Aishah Hashim, Zalailah Salleh, Roshaiza Taha, Shayuti Mohamed Adnan

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引用次数: 0

Abstract

This article provides extensive information about how firms adhere to sustainability reporting guidelines set by Bursa Malaysia Sustainability Reporting Guideline (SRG) 2015 and Global Reporting Initiative (GRI) Sustainability Reporting Standard 2021. This research contains panel data for 56 Malaysian listed firms (agriculture and plantation sector) in Bursa Malaysia. This dataset was collected from 2016 to 2023. Information provided was obtained from the sustainability reports and annual reports of each firm, which had been downloaded from Bursa Malaysia website.

The researcher can use the data effectively to create and calculate a sustainability reporting index that involves seventy-five sustainability reporting disclosure item and is comprised of three weighted sub-indices. The initial sub-index, “Economic Disclosure” consists of 8 items. The “Environmental Disclosure” sub-index consists of 31 items. The final sub-category, “Social Disclosure” consists of 36 items. Therefore, the researchers can assess companies using an overall index score provided by the unweighted sustainability reporting index.

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.