This study explores the wealth of information inherent in online employee reviews as an emerging resource in academic research. The focus is on the fields of finance, accounting, economics, and management, with an emphasis on how employee reviews contribute to our understanding of these areas. A...

This paper examines the prediction of IPO withdrawal using machine learning methods (lasso and random forest) and conventional regression (logit). The dataset comprises 2444 US first‐time IPOs from 1997 to 2014. Results show that random forest outperforms both logit and lasso in in‐sample...

Liquidity planning and forecasting are essential activities in corporate financial planning team. Traditionally, empirical models and techniques based on in‐house expertise have been used to navigate the numerous challenges of this forecasting activity. These challenges become more complex...

How companies report their data is undergoing digitization and sustainable transformation. Sustainability is important; therefore, various stakeholders are interested in sustainability information. Companies provide the required information and strive toward the use of information systems to...

We provide a high-level view on topics addressed in scientific articles about regulatory technology (RegTech), with a particular focus on technologies used. For this purpose, we first explore different denominations for RegTech and derive search queries to search relevant literature portals....