This study proposes a novel attention-based deep neural network (AttDNN) model specifically designed for predicting mergers and acquisitions (M&A). The model extends existing deep learning frameworks by incorporating M&A-specific features, regularization layers, and an attention mechanism that...

This paper proposes a new resilience index, CLARE (Causal machine Learning Approach to Resilience Estimation), which is rooted in an impact evaluation framework and causal machine learning algorithms applied to longitudinal household survey data. The indicator is model-agnostic, data-driven,...

We examine the impact of generative AI on the youth labor market in Finland by replicating the key analyses of Brynjolfsson et al. (2025) with comprehensive population-level data. Contrary to the US findings, we find no systematic displacement effects linked to AI exposure among youth in...

Early adoption of artificial intelligence (AI) reshaped how firms responded to market dynamics by enhancing data collection and analysis. Linking China's universe of customs shipments to millions of online job ads, we tracked AI hiring in sales, marketing, and analytics to build a firm-level...

We develop a novel sentiment measure derived from survey data to empirically vali date the Minsky-Kindleberger view on financial crises. Using survey data from multiple countries, we decompose beliefs into components explained by public information that are orthogonal to optimal machine beliefs,...

This paper provides new evidence on how the adoption of artificial intelligence (AI) affects productivity and employment in Europe. Using matched EIBIS-ORBIS data on more than 12,000 non-financial firms in the European Union (EU) and United States (US), we instrument the adoption of AI by EU...

Companies, not governments, are at the cutting edge of developing new artificial intelligence (AI) technologies for military use, and regulation needs to keep pace with these advances. Yet geopolitical tension is undermining international cooperation on AI in the military domain. This paper...

This paper examines how digital financial platform engagement influences financial inclusion in the Philippines and explores how financial institutions are deploying artificial intelligence (AI) in enhancing these platforms. It combines nationally representative data from the World Bank Global...

We examine the changing attention that ECB Governing Council members pay to different policy objectives by analysing more than 4,600 speeches given between the establishment of the ECB and the summer of 2024. Alongside the primary objective of price stability, we consider the following potential...

Generative artificial intelligence (GenAI) is increasingly recognized as a transformative technology that is reshaping organizational processes, individual work practices, and workplace interactions. While its benefits for efficiency and productivity are widely acknowledged, its impact on...

This paper investigates the relationship between institutional and regulatory quality, and high-tech sector investment. Using data from 25 European Union (EU) countries from 2004 to 2019 (extended to 2023 for artificial intelligence-specific analyses), the study examines how institutional...

As artificial intelligence (AI) adoption accelerates globally, its sustainability implications remain insufficiently integrated into organizational capability frameworks. This study develops and validates the organizational sustainable AI capabilities (OSAIC) construct, extending dynamic...

The rapid evolution of artificial intelligence (AI) from expert systems and fuzzy logic to sophisticated technologies such as deep learning and big data analytics has transformed modern management practices. This study explores how AI-driven management practices can effectively bridge...

Generative artificial intelligence (GenAI), with its potential to autonomously generate new content in the form of text, video, audio and code, holds disruptive potential to revolutionize knowledge management (KM) processes. An enormous number of studies have been published in recent years on...

Purpose This conceptual study explores how artificial intelligence (AI) is transforming the nature of work and reconfiguring the experience of humanness, particularly among low-skilled and informal workers. Method Using an integrative literature review methodology, the study synthesises...

This study introduces a novel machine learning-based methodology for detecting and forecasting the strength of weak signals in the labor market, using Greece as a case study and utilizing Eurostat time series data (2000-2023). Weak signals, conceptualized as subtle anomalies within otherwise...

Amidst global decarbonization dynamics, Artificial Intelligence (AI), the Digital economy, and energy prices are shaping the energy transition in a way that has never been more critical. Using MMQR and IVQR, this research investigates the effects of AI, research and development (R&D), and energy...

Global warming and energy security challenges have intensified globally, compelling nations to pursue sustainable energy transition pathways. Artificial intelligence (AI) plays a pivotal role in addressing complex systemic challenges and enhancing industrial efficiency, and is widely recognized...

Artificial intelligence (AI) applications in China's smart city initiatives are widely regarded as having the potential to enhance energy efficiency, yet whether such applications may trigger or exacerbate the energy rebound effect remains an open empirical question. Using panel data for 279...

Accurate wind power forecasting is crucial for the effective scheduling and scientific management of wind energy, enhancing the safety and reliability of power grids. To handle the inherent intermittency of wind energy, forecasting methodologies have evolved from traditional statistical models...