Anonymized Dataset for Predicting Financial Reporting Timeliness in a Family Firm

This dataset contains 18 monthly observations of anonymized, engineered variables used to model financial reporting timeliness in a family-owned firm. The study is titled : Predicting Financial Reporting Timeliness with ERP Data: A Machine Learning Case Study of the Governance Bottleneck in a Family-Owned Firm, using Python algorithms.