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Interpretable hydropower forecasting method using two-stage decomposition and its management applications

Jiacheng Lin; Binrong Wu; Ruiyu Gao dkk.

Data Science and Management, Vol. 9 No. 3 · 2026 · Inggris · DOAJ Scopus

As a premier renewable energy source for power generation, hydropower boasts substantial construction scale and robust generation capacity. Amid the global energy crisis, precise hydropower forecasting is becoming increasingly crucial, providing governments with a vital foundation for devising…

Immersion for all? Rethinking equity and fatigue in the XR era: a literature review of immersive technology

Eunji Choi; Jian Mou

Data Science and Management, Vol. 9 No. 3 · 2026 · Inggris · DOAJ Scopus

Immersive technologies, including virtual, augmented, mixed, and extended reality (XR), are transforming how people learn, heal, travel, and consume. This literature review analyzed 95 peer-reviewed publications published between 2017 and 2025 across six domains: education, healthcare, tourism and…

Information systems auditing of psychiatric diagnoses using context-enriched QA-based language models

William (Hongmin) Du; Guanghua Wang; Jiahui (Norah) Xu dkk.

Data Science and Management, Vol. 9 No. 3 · 2026 · Inggris · DOAJ Scopus

The growing use of artificial intelligence (AI)-driven decision support systems (DSS) in healthcare requires effective auditing frameworks to ensure diagnostic accuracy and transparency. This study introduces a novel information system (IS) approach for psychiatric diagnosis auditing, transforming…

Breathing rewards: dynamic market-aware portfolio optimization

Qing Zhu; Baoqin Xie; Yuze Li dkk.

Data Science and Management, Vol. 9 No. 3 · 2026 · Inggris · DOAJ Scopus

In recent years, rising geopolitical tensions, trade protectionism, and demand for safe-haven assets have driven a notable surge in financial market volatility, exposing the limitations of both traditional static and prediction-driven investment strategies. Existing reinforcement learning (RL)…

Generative artificial intelligence in education: a comprehensive analysis based on bibliometrics

Xiaojie Ma; Wenlong Zhu

Data Science and Management, Vol. 9 No. 3 · 2026 · Inggris · DOAJ Scopus

Currently, generative artificial intelligence (GAI) is advancing rapidly and being increasingly adopted. However, systematic and comprehensive analyses of its integration into educational management are scarce. This study employs bibliometric analysis supplemented by visualization tools to conduct…

A context-aware BERT framework for detecting and modeling the mental health impact of online toxic language

Ayodeji Olusegun Ibitoye; Oladosu Oyebisi Oladimeji; Isaac Olayemi Olaleye dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

Toxic language in online communities poses significant risks to mental health, often exacerbating conditions, such as anxiety, depression, and stress. While existing methods for detecting toxic language in online spaces have made progress, they struggle to understand the underlying context…

Exploring artificial intelligence for sustainable business development: a review

Jintao Yu; Ximing Zhan; Giridhar Reddy Bojja

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

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 business sectors by automating tasks, supporting intelligent decisions, and integrating into core…

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

Manal Ahdadou; Ayoub Ahdadou; Abdellah Aajly dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

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 AI adoption—assisted, augmented, amplified, autonomous, and autopoietic—against the criteria of…

In GPT we trust: perceptions of the future of work with artificial intelligence on online forums

Szabina Fodor; Bettina Boncz

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

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 from transformer (BERT) pretraining approach (RoBERTa) model, for sentiment analysis and emotional…

Multi-source heterogeneous data fusion using vector concatenation for quality fluctuation analysis

Sheng Hu; Xinyu Zheng; Qingan Qiu dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

Big data mining is an important driver of quality control in intelligent manufacturing; however, conventional approaches often rely on a single data source, limiting their accuracy and applicability. In this study, a multi-source heterogeneous data integration method was developed for modeling…

Integrating lean management and emerging technologies for enhanced sustainable performance: empirical evidence based on double machine learning approach

Anna Presciuttini; Stefano Frecassetti; Matteo Ferrazzi dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

The rapid increase in sustainability has pushed manufacturing firms to rethink their production systems to make them more efficient, produce less waste, and improve their working conditions. In this landscape, many manufacturing firms that rely on traditional quality improvement methods such as…

Suspiciousness of social media accounts: examining the role of conversational consistency using machine learning approach

Kunal Rao; Gaurav Dixit

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

The proliferation of social media platforms has led to an upsurge in suspicious accounts that spread misinformation and manipulate public opinion. A few of these accounts with significant followings might play a prominent role in shaping people’s inclination towards social issues. Our study…

Deep learning in financial fraud detection: innovations, challenges, and applications

Yisong Chen; Chuqing Zhao; Yixin Xu dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

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 architectures, such as convolutional neural networks, long short-term memory networks, transformers…

Trust or distrust? AIGC trustworthiness and an extended analysis within nomology framework

Mingqian Li; Rong Du; Shizhong Ai dkk.

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

Given the dizzying advancements in artificial intelligence (AI) applications such as ChatGPT and DeepSeek, AI-generated content (AIGC) has attracted considerable attention from scholars, practitioners, and policymakers, each of whom is grappling with fundamental issues involving individual…

Investors’ behavior-based nonlinear goal programming models for financial portfolio selection considering future stock market trends

Mohamed Sadok Cherif; Nabil Mansour

Data Science and Management, Vol. 9 No. 2 · 2026 · Inggris · DOAJ Scopus

Financial markets are ever-changing, and portfolio selection (PS) problems frequently involve multiple optimization objectives in an imprecise investment environment. Real-world investors attempt to select a portfolio based on their preferences for each objective and their decision-making…

Introducing article numbering to Data Science and Management

Data Science and Management, Vol. 9 No. 1 · 2026 · Inggris · DOAJ Scopus

Efficient management of medical image datasets for content-based case retrieval via sparse annotation and bidirectional label propagation

Chengyue Gong; Ziyu Guan; Jianguo Ju

Data Science and Management, Vol. 9 No. 1 · 2026 · Inggris · DOAJ Scopus

Efficient management of medical image datasets is critical for clinical decision-making. However, current methods lack fine-grained annotation management and content-based case retrieval capabilities. Existing systems struggle to handle the annotation burden and to efficiently retrieve similar…

Data clustering: a fundamental method in data science and management

Tai Dinh; Hauchi Wong; Daniil Lisik dkk.

Data Science and Management, Vol. 9 No. 1 · 2026 · Inggris · DOAJ Scopus

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 such as partitional and hierarchical methods, alongside more advanced approaches, including…

Cross-domain aspect term extraction using pre-trained language models with pre-training and fine-tuning strategy

Chunjun Zhao; Meiling Wu; Xuzhuang Sun dkk.

Data Science and Management, Vol. 9 No. 1 · 2026 · Inggris · DOAJ Scopus

As an important subtask of fine-grained sentiment analysis, aspect term extraction (ATE) aims to identify aspect terms within user-generated comments. ATE supervised learning approaches are heavily based on the availability of annotated data with token-level labels. However, obtaining these…

Unveiling the footprints of explainable AI in Industry 4.0/5.0: a systematic review and bibliometric exploration

Oladosu Oyebisi Oladimeji; Gbadegesin Adetayo Taiwo; Dauda Adeite Adenusi

Data Science and Management, Vol. 9 No. 1 · 2026 · Inggris · DOAJ Scopus

Progress in artificial intelligence (AI) is driving transformations that compel an increasing number of companies to embrace the Industry 4.0 and 5.0 paradigms and adopt advanced AI solutions. However, the lack of explainability in evaluating and justifying the decisions of AI models raises…