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Does Mixed‐Frequency Data Efficiently Predict Future ESG Ratings? A RMIDAS‐Based Machine Learning Approach

Year: 2026

Type: article

Source: Business Strategy and the Environment

DOI: 10.1002/bse.70884

Authors: Yali Zhang, Xinpeng Ding, Liukai Wang, Yangyan Shi

Institutions: Inner Mongolia University, University of Science and Technology Beijing, Capital University of Economics and Business, Macquarie University

Language: English

Topic: Corporate Social Responsibility Reporting

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: closed

Funder: National Natural Science Foundation of China

Awards: G2899493136, G8939379053

OpenAlex ID: W7160029913

FWCI: 6.305

Cites: 56

Cited by: 1

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