The growth of generative artificial intelligence (GAI), remarkably, Large Language Models (LLMs) such as ChatGPT, converts the educational environment by empowering intelligent, data-driven education and curriculum design innovation. This study aimed to assess the integration of LLMs into higher...

Corporate Social Responsibility (CSR) has evolved into a strategic governance framework through which organisations address environmental sustainability, stakeholder expectations, and long-term institutional viability. In knowledge-intensive organisations such as universities, Green Artificial...

This paper estimates the causal effect of a large language model-based study assistant on student behavior and learning outcomes in a natural field setting with real academic stakes. I design and deploy a course-specific AI assistant (GPT-UAI) for undergraduate econometrics and evaluate it...

Using two waves of nationally representative Danish firm surveys linked to employer- employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technologyspecific. While firm size and...

The expansion of digital technologies has led to a digital transformation of the economy and society. E-commerce, driven by new digital technologies and the restrictions during the COVID-19 pandemic, has increased its share in the overall trade of goods and services, influencing economic growth....

As global sustainable development increasingly intersects with rapid advances in artificial intelligence (AI), understanding how emerging technologies reshape corporate environmental, social, and governance (ESG) behavior has become essential. This study investigates the role of artificial...

Emerging economies confront the dual challenge of accelerating digital transformation while simultaneously mitigating environmental degradation under conditions of institutional and governance heterogeneity. In this context, this study examines how artificial intelligence (AI) capability...

Using two waves of nationally representative Danish firm surveys linked to employer-employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technology-specific. While firm size and...

This study examines the economic returns to education in the U.S. using 2024 CPS data and compares Ordinary Least Squares (OLS) regression with a Double Machine Learning (DML) framework incorporating models such as random forests, boosted trees, lasso, GAMs, and neural networks (MLP). Results...

Recent technological advancements are reshaping pathways to employment by automating the interview process. Asynchronous interviews, in which job applicants submit answers to interview questions via an online platform without interacting with an interviewer, are replacing more traditional...

Purpose: This study addresses a real-world container loading problem (CLP) encountered in a logistics company in Turkey, filling a gap in the literature by solving practical constraints using a state-of-the-art algorithm. The problem involves constraints such as rotations, stackability, loading...

Does artificial intelligence (AI) increase productivity - and does it displace workers? We examine aggregate effects using administrative data covering essentially all U.S. employers in a difference-in-differences design exploiting occupational AI exposure across industries and states. A one...

This study investigates the interplay between entrepreneurial leadership and innovation performance in Jordanian IT firms, with a specific focus on the strategic role of Artificial Intelligence (AI). Grounded in a quantitative methodology, data were collected via a structured questionnaire from...

Technological advances are increasingly influencing how the public sector makes decisions according to citizens' needs and the community's problems. The need for a solution that facilitates the fast adaptation of administration to social context and people's feedback becomes mandatory in order...

We develop a novel sentiment measure from survey forecasts that captures the component of beliefs arising from the systematic misaggregation of public information relative to a machine benchmark based on the same information set. We extend this sentiment measure historically for a panel of 78...

This study examines how technological innovation and sustainability jointly reshape contemporary public administration by integrating digital transformation with public value creation. Using a mixed-method approach, we compile a Scopus-based bibliographic dataset and conduct descriptive and...

Organizations increasingly deploy artificial intelligence (AI) in human resource (HR) decision processes to improve efficiency and strategic execution, yet ethical failures persist when principles remain decoupled from everyday workflow enactment. This paper addresses AI-ethics in HR practice by...

According to administrative data, as many as 25 million children between the ages of 5 and 16 are out-of-school in Pakistan. However, little is known about where these children are in relation to available public and private schooling options. This paper brings together novel data from satellite...

The Independent Evaluation Group’s (IEG) Artificial Intelligence (AI) strategy marks an important milestone in its journey of continuous experimentation, learning, and adaptation to integrate AI in evaluation. It reaffirms IEG's commitment to scale up the use of AI, deliberately and...

This study empirically investigates the performance of Elastic Machine Learning, an industrial, unsupervised anomaly detection tool, in the identification of fraudulent behavior in banking transactions. Using AI-generated datasets that were designed to simulate realistic banking environments,...

Women are essential to the growth of any progressive society. Equal access to employment is necessary for both women's empowerment and global economic growth. However, discrimination against women persists at all career levels, making it challenging for them to overcome barriers to leadership...

The increasing deployment of agentic artificial intelligence (AI) systems and decentralized digital infrastructures has challenged traditional assumptions about organizational administration, control, and governance. While AI has advanced task-level optimization and decision support,...

Nowadays, the European economy faces significant global challenges that threaten the continuity of economic growth, especially in the German manufacturing sector, which is under strain from financial turmoil, resulting in numerous layoffs and firm closures. In this respect, FinTech significantly...

This study investigates the macroeconomic impact of financial corruption and institutional weakness on Pakistan's economy from 1996 to 2023, addressing a critical research gap in quantifying the simultaneous effects of shadow economy operations and poor governance on economic growth. Grounded in...

Robo-advisors are evolving fintech solutions that ask potential clients about their investment purpose and time horizon and then offer investment strategies to reach different goals. This study aims to build on prior research and gain insights into the influence of innovation attributes...

Credit card fraud detection remains a critical challenge for financial institutions, particularly due to extreme class imbalance and the continuously evolving nature of fraudulent behavior. This study investigates two complementary approaches: anomaly detection based on multivariate normal...

Prediction of stock closing price plays a critical role in financial planning, risk management, and informed investment decision-making. In this study, we propose a novel model that synergistically amalgamates Bidirectional GRU (BiGRU) with three complementary attention techniques-Top-k Sparse,...

The purpose of this research is to investigate and explain the extent to which artificial intelligence stimuli and social behavior determinants influence online impulse buying in Pakistan's e-retail sector positioning brand trust as central pathway mechanism among generation Z. Drawing on the...

Das Thema KI-gestützter Entscheidungsunterstützung im Immobilien-Investmentmanagement wird derzeit vor allem im Kontext von Effizienz, Standardisierung und Automatisierung diskutiert. Die vorliegende Arbeit analysiert daher Unterschiede in Argumentationslogik, Gewichtung zentraler...

This paper investigates the methodological performance of Ordinary Least Squares (OLS) regression and Random Forest machine learning algorithms in measuring adjusted gender pay gaps. The research is motivated by the European Union's Pay Transparency Directive (2023/970), which mandates that...

The emergence of artificial intelligence (AI) tools has offered new ways of teaching and learning. Businesses have also highlighted the importance of AI literacy in the workplace as AI is transforming operations and entire industries. Given the importance of obtaining AI skills and the...

This study examines the economic returns to education in the U.S. using 2024 CPS data and compares Ordinary Least Squares (OLS) regression with a Double Machine Learning (DML) framework incorporating models such as random forests, boosted trees, lasso, GAMs, and neural networks (MLP). Results...

Context: The Fourth Industrial Revolution has accelerated the integration of automation technologies into the world of work, raising important questions about the future of Vocational Education and Training (VET). While existing literature has primarily focused on the labor market impacts of...

Utilizing nationally representative cross-sectional and longitudinal data from Finland (2018-2023), we provide a population-level assessment of the relationship between AI and worker wellbeing. Contrary to international evidence suggesting a positive or an inverted U-shaped relationship, we find...

This study examines how large language models (LLMs) respond to varying stake sizes in the Dictator and Ultimatum games using the high-stakes design introduced by Andersen et al. (2011). We test ten leading LLMs chosen for their accessibility, prominence, and differences in reasoning...

Using two waves of nationally representative Danish firm surveys linked to employer- employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technologyspecific. While firm size and...

This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior...

Although Generative Artificial Intelligence (GenAI) has the potential to transform Human Resource Management (HRM), empirical research on its actual use is still rare. This study aims to investigate how HR professionals use GenAI in HRM, the benefits and challenges they associate with it, and...