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ISSN: 2666-7649
CN: 61-1530/TN
p-ISSN: 2097-3187

Deep Learning in Financial Fraud Detection: Innovations, Challenges, and Applications

This study presents a systematic review of 108 peer-reviewed publications (2019–2024) on the application of deep learning (DL) to financial fraud detection. It examines advances in model architectures,...

DeepSeek: implications for data science and management in the AI era

DeepSeek has emerged as a disruptive force in artificial intelligence (AI). Unlike traditional large language models (LLMs), which demand extensive computational resources, DeepSeek delivers comparable...

Factors influencing readiness for artificial intelligence: a systematic literature review

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,...

Assessing the impact of artificial intelligence on customer performance: a quantitative study using partial least squares methodology

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,...

Investigating customer churn in banking: a machine learning approach and visualization app for data science and management

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...

Effects of information quality on information adoption on social media review platforms: moderating role of perceived risk

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...

Challenges and prospects of artificial intelligence in aviation: a ​bibliometric study

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

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...

A model for predicting dropout of higher education students

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...

NLP-driven customer segmentation: A comprehensive review of methods and applications in personalized marketing

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....

Machine learning-based approach: global trends, research directions, and regulatory standpoints

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...

AI-driven innovation in emerging markets: extending the technology acceptance model-technology-organization-environment framework in small- and medium-sized enterprises

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...

Explainable prediction of loan default based on machine learning models

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...

Enabling innovation with big data analytics capabilities: the moderating role of organizational learning culture

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...

An explainable feature selection framework for web phishing detection with machine learning

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....

The impact of consumer perceived value on repeat purchase intention based on online reviews: by the method of text mining

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...

User-centric avatar design: a cognitive walkthrough approach for metaverse in virtual education

Metaverse, once a concept confined to science fiction, has emerged as a transformative reality during the digital era. As this immersive virtual world gains prominence, the role of avatars and the digital...

Artificial intelligence in corporate boards: a dual-dimensional framework for integration across autonomy and structural levels

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...

Systematic review of data-centric approaches in artificial intelligence and machine learning

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...

Systematic Review on the Influence of Classical and Quantum Machine Learning in the Financial Sector

In the financial sector, machine learning (ML) has emerged as a transformative technology that provides sophisticated solutions to critical challenges, such as in fraud detection, anti-money laundering,...

Data clustering: a fundamental method in data science and management

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...

ESG performance and executive compensation levels: an empirical study

As global environmental concerns grow, corporate environmental, social, and governance (ESG) performance has become an essential indicator for measuring organizational value and sustainability. Considering...

Exploring artificial intelligence for sustainable business development: a review

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...

Using multi-criteria decision-making and machine learning for football player selection and performance prediction: a systematic review

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....

Virtual manufacturing in Industry 4.0: A review

Virtual manufacturing is one of the key components of Industry 4.0, the fourth industrial revolution, in improving manufacturing processes. Virtual manufacturing enables manufacturers to optimize their...

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