Deep learning in financial fraud detection: innovations, challenges, and applications
June 2026
This study presents a systematic literature review of 108 peer-reviewed publications (2019–2024) on the application of deep learning (DL) to financial fraud detection. It examines advances in model...
Factors influencing readiness for artificial intelligence: a systematic literature review
June 2025
Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task,...
An explainable feature selection framework for web phishing detection with machine learning
June 2025
In the evolving landscape of cyber threats, phishing attacks pose significant challenges, particularly through deceptive webpages designed to extract sensitive information under the guise of legitimacy....
Effects of information quality on information adoption on social media review platforms: moderating role of perceived risk
March 2021
With the integration of social media and e-commerce, social media review platforms provide consumers with a place to share information and create electronic word of mouth (e-WOM). Information from e-WOM...
Investigating customer churn in banking: a machine learning approach and visualization app for data science and management
March 2024
Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer...
Explainable prediction of loan default based on machine learning models
September 2023
Owing to the convenience of online loans, an increasing number of people are borrowing money on online platforms. With the emergence of machine learning technology, predicting loan defaults has become...
Artificial intelligence in corporate boards: a dual-dimensional framework for integration across autonomy and structural levels
June 2026
This study examines the integration of artificial intelligence (AI) into corporate governance, with a specific focus on board-level decision-making. It critically evaluates five progressive stages of...
Assessing the impact of artificial intelligence on customer performance: a quantitative study using partial least squares methodology
September 2024
The purpose of this research is to examine the impact of artificial intelligence (AI) on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,...
AI-driven innovation in emerging markets: extending the technology acceptance model-technology-organization-environment framework in small- and medium-sized enterprises
December 2025
This study examined the impact of artificial intelligence (AI) adoption on innovation outcomes in Pakistani manufacturing small- and medium-sized enterprises (SMEs), addressing a critical gap in the...
Using multi-criteria decision-making and machine learning for football player selection and performance prediction: a systematic review
June 2024
Evaluating and selecting players to suit football clubs and decision-makers (coaches, managers, technical, and medical staff) is a difficult process from a managerial-financial and sporting perspective....
The impact of consumer perceived value on repeat purchase intention based on online reviews: by the method of text mining
September 2021
The progress of IT technology such as social network and mobile payment and the change of social economic environment promote the emergence of sharing economy. As a subversive business model, the sharing...
A model for predicting dropout of higher education students
March 2025
Higher education institutions are becoming increasingly concerned with the retention of their students. This work is motivated by the interest in predicting and reducing student dropout, and consequently...
Systematic review of data-centric approaches in artificial intelligence and machine learning
September 2023
Artificial intelligence (AI) relies on data and algorithms. State-of-the-art (SOTA) AI smart algorithms have been developed to improve the performance of AI-oriented structures. However, model-centric...
Challenges and prospects of artificial intelligence in aviation: a bibliometric study
June 2025
The primary motivation for this study is the recent growth and increased interest in artificial intelligence (AI). Despite the widespread recognition of its critical importance, a discernible scientific...
Unlocking the power of machine learning in big data: a scoping survey
December 2025
Machine learning (ML) plays a crucial role in big data (BD) by serving as the cornerstone of efficient data processing and analysis. In particular, ML provides BD with the ability to extract valuable...
Machine learning-based approach: global trends, research directions, and regulatory standpoints
December 2021
The field of machine learning (ML) is sufficiently young that it is still expanding at an accelerating pace, lying at the crossroads of computer science and statistics, and at the core of artificial...
How do information systems drive organizational technology adaptation and innovation? An integrative review
Available online 10 July 2026
The continuous emergence of new technologies presents organizations with unprecedented opportunities and challenges. Faced with the rapid evolution of technologies such as artificial intelligence and...
NLP-driven customer segmentation: A comprehensive review of methods and applications in personalized marketing
Available online 19 September 2025
In an era of digital interactions and data proliferation, understanding customer behavior and preferences has become crucial for businesses that aim to enhance brand loyalty and optimize marketing strategies....
A Review of Research on Multi-Agent Technology for Solving Collaborative Scheduling Problems
Available online 11 July 2026
The increasing complexity and dynamics of modern industrial environments challenge traditional centralized scheduling methods, necessitating more adaptive and intelligent approaches. This review systematically...
Data clustering: a fundamental method in data science and management
March 2026
This study investigates the pivotal role of data clustering in both data science and management, focusing on core methodologies, tools, and diverse applications. It examines traditional clustering techniques...
Exploring artificial intelligence for sustainable business development: a review
June 2026
Artificial intelligence (AI) has revolutionized business practices and enabled relevant techniques in various sectors to drive efficiency and innovation. This study examines the impact of AI across...
In GPT we trust: perceptions of the future of work with artificial intelligence on online forums
June 2026
This study analyzes over 10 years of Reddit discussions on artificial intelligence (AI)’s impact on the labor market using a state-of-the-art robustly optimized bidirectional encoder representations...
Enabling innovation with big data analytics capabilities: the moderating role of organizational learning culture
March 2026
Big data analytics (BDA) capabilities for innovation are an area of growing interest; however, empirical results on this pivotal relationship remain inconclusive. This study investigates how BDA capabilities...
The impact of digital transformation on sustainable supply chain performance: the mediating effect of service innovation
September 2026
Amid accelerating global economic integration and escalating imperatives for sustainable development, digital transformation (DT) and service innovation (SI) have evolved into pivotal drivers of sustainable...
Artificial intelligence dimensions and design features for the knowledge-based work of the future: a socio-technical perspective
March 2026
With recent advances in transformative technologies, such as the Internet of Things, cloud computing, and mobile devices, jobs have become more knowledge-based. To implement successful technologies...