Many organizations actively plan to introduce artificial-intelligence-based (AI) applications to solve business problems, improve efficiency, and promote innovation. However, in this process, organizations face challenges in identifying AI …

This study addresses whether machine learning models can use technical analysis data to forecast one-day-ahead movements of the S&P 500 stock index. The input data are used to train fifteen machine learning models involving linear regression …

This study presents an Intrusion Detection System (IDS) that addresses challenges in feature selection, model interpretability, and scalability for cybersecurity. By employing a two-step feature selection approach combining a correlation-based …

As AI technology advances, human-AI interactions have become increasingly complex, exhibiting intelligent interactions. However, existing research primarily considers these interactions from a utilitarian perspective, seeing AI as a set of …

Host profile photos constitute a crucial marketing tool that significantly shapes guests’ decision-making on peer-to-peer accommodation platforms. Prior work has primarily examined the static effects of facial attractiveness, but research remains …

As the population of older adults in the UK grows, Socially Assistive Robots (SARs) are increasingly important for supporting independence and enhancing quality of life within the home. This study draws on the Computers Are Social Actors (CASA) …

Critical thinking is a central safeguard for responsibility and accountability in deontologically-governed professions. Artificial intelligence (AI)-assisted decision-making is increasingly being integrated within these professional workflows.

This paper investigates the strategic interactions between two competing high-technology firms engaged in new product development, with a particular focus on their investment decisions. Employing a game-theoretic modeling framework, we examine how …

Abstractive summarization task aims to generate a concise and accurate summary that effectively captures the key information from the input document. In recent years, large language models (LLMs) have emerged as foundational models for developing …

Trustworthiness of AI systems is a core objective of Human-Centered Explainable AI, and relies, among other things, on explainability and understandability of the outcome. While automated machine learning tools automate model training, they often …

Social media is increasingly used for interaction and information sharing. However, the rapid dissemination of harmful content poses significant societal risks, including misinformation and polarization. This study examines resharing mechanisms on …

Accurate financial distress prediction for listed companies is crucial for informed decision-making by investors and financial institutions. Recent advancements have highlighted the potential of graph models due to their ability to represent …

This paper proposes a novel quantum-inspired multi-criteria decision-making (QI-MCDM) framework to assess the structural performance of Chinese banks considering emerging AI technological contexts. By embedding classical bank performance …

This work explores bio-inspired strategies and clustering techniques to propose an automatic clustering algorithm, named Multi-objective Clustering Algorithm (MCA). This algorithm uses a set of measure combinations to define the optimal number of …

With women's empowerment driving socioeconomic development at large, we focus on the women microentrepreneurs running small businesses, marginalized both by gender and socioeconomic status, and examine how mobile payments aid these women in …

Generative AI (GenAI) applications, such as ChatGPT, are increasingly shaping work practices and employee engagement in organizations. Understanding how employees interact with these tools is critical for designing effective and responsible …

Information systems (IS) research has continually evolved alongside rapid technological advancements, shaping its impact on business and society. While past analyses have explored the discipline’s identity and diversity, the accelerating pace of …

Integrating deep learning into healthcare enables personalized care but raises trust issues due to model opacity. To improve transparency, we propose a system for dental age estimation from panoramic images that combines an opaque and a …

Patients are increasingly faced with balancing the efficacy of their care against the privacy of their protected health information (PHI). Research has established that healthcare data breaches erode patients’ willingness to share new health …