Search Results - subject_exact:"Data mining"

Integrating big data into sustainable supply chain management : a pathway to enhanced firm performance in Ghana's food and beverage sector

Nyamah, Edmond Yeboah; Nyamah, Evelyn Yeboah; Agbodza, Mavis - 2026

The study examines how big data analytics moderate the relationship between sustainable supply chain management practices, specifically sustainable design, procurement, and distribution, and impact firm performance in Ghana's food and beverage manufacturing sector.Data were gathered from 295...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015655258

Enhancing a GRASP heuristic for the prize-collecting covering tour problem through data mining techniques

Clímaco, Glaubos; Simonetti, Luidi; Rosseti, Isabel; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015627366

Data-driven circularity in the aerospace sector : a research perspective on cognitive MRO and generative design

Keivanpour, Samira - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015613597

Measuring economic outlook in the news

Beck, Elliot; Eckert, Franziska; Kühne, Linus; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015615555

Adaptive credit card fraud detection : reinforcement learning agents vs. anomaly detection techniques

Mekhlouf, Houda Ben; Moussaid, Abdellatif; Ghanimi, Fadoua - 2026

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015628709

Economic instability and its effect on brand preferences : big data examination of self-image and online shopping conduct

Johnson, Nuraeni Saripudin; Purwanegara, Mustika Sufiati; … - 2026

Purpose - This study will examine how consumer brand preference is impacted by economic instability in the market of e-commerce in Indonesia, the relationship between self-image and purchasing patterns under three different periods; pre-crisis (2017-2019), crisis (2020-2022), and post-crisis...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015644381

An integrated bibliometric analysis of Benefit of the Doubt composite indicators for policy and decision analysis

Nepomuceno, Thyago; Barbosa, Flávia; Vilarinho, Hermilio; … - 2026

The Benefit of the Doubt (BoD) is a non-parametric frontier model derived from Data Envelopment Analysis (DEA), used to construct composite indicators in various sectors of economic activity, with a particular focus on macroeconomic assessments. Based on documents published in the Web of Science...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015652278

An integrated resampling and machine learning framework for predictive analytics of large wildfires

Camacho, Luís; Catry, Filipe X.; Bacao, Fernando - 2026

Accurately predicting the final burned area of wildfires at the moment of ignition is a challenging problem with important implications for disaster management and resource allocation. In this study, we apply recently developed resampling techniques, combined with machine learning algorithms, to...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015652281

Optimal text-based time-series indices

Ardia, David; Bluteau, Keven - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015667961

Adoption and impact of big data analytics in the food industry in South-Western Nigeria

Osakue, Ignatius; Muhyaddin, Sanar; Kuka, Colin; … - 2026

Within the South-Western food industry of Nigeria, the overall impact, associated challenges, and implementation of Big Data Analytics (BDA) have remained underexplored. Thus, this study aimed to investigate the extent of BDA adoption, identify key barriers and enablers, assess the operational...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670096

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

Horani, Omar Mohammed; Al-Adwan, Ahmad Samed; Al-Rahmi, … - 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 influence product, process, and business model innovation while examining the moderating...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015674870

Data clustering : a fundamental method in data science and management

Dinh, Tai; Wong, Hauchi; Lisik, Daniil; Koren, Michal; … - 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 such as partitional and hierarchical methods, alongside more advanced approaches,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015674885

Reddit’s ‘pulse’ on US inflation : forecasting with large language models

Del Monaco, Andrea; Longo, Luigi; Marcucci, Juri; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016062915

An intelligent text analytics approach to sentiment-based portfolio decision making in the electric vehicle market

Ghiassi, Manoochehr; Shah, Kush; Agrawal, Mehak; … - 2026

Investment portfolio management increasingly requires the integration of financial fundamentals with market sentiment derived from rapidly expanding online information sources. The widespread availability of real-time financial news and opinion-based content has heightened the complexity of...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082745

An integrated analytics method for structured accident analysis and safety decision support in construction

Omari, Mohamad Al; Itair, Mohammed; Eslahi, Mojtaba; … - 2026

Construction sites remain high-risk environments, with thousands of accidents occurring each year. Although large amounts of accident records exist globally, much of this information is stored as unstructured free-text comments, limiting its usefulness for systematic analysis. This study...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082684

A formal concept analysis framework for data-driven insurance customer segmentation

Rungruang, Chongkolnee; Saelee, Jarunee; Intarasit, Arthit - 2026

Effective marketing strategies for customer relationship management (CRM) require identifying potential customers and their needs. Marketers can use customer segmentation through cluster analysis to develop practical and profitable business marketing plans. Formal concept analysis (FCA) is a...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082737

An object-centric approach to multi-entity Educational Process Mining

Miri, Najmeh; Khayatbashi, Shahrzad; Zdravkovic, Jelena; … - 2026

Educational Process Mining (EPM) is widely used to analyze learning processes in technology-enhanced learning environments. However, most EPM approaches remain case-centric, linking each event to a single entity (e.g., student or course), which prevents the analysis of learning situations...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082749

Implementing a data driven model for automated dynamic outlier detection during data validation

Velic, Chelsea; Frawley, Katie; Eian, Sarah - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082302

What makes monetary policy more powerful? : a big data approach

Yakut, Dilan Aydın; Byrne, David; Goodhead, Robert - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016072370

Multimodal user-generated content analysis for digital cultural tourism : an explainable machine learning approach to tourist satisfaction

Zhang, Hongyu; Shen, Kaiyuan; Lyu, Long - 2026

Digital cultural tourism is rapidly expanding, yet relevant research on tourist satisfaction predominantly relies on questionnaire surveys or unimodal textual analysis, failing to capture the comprehensive and multidimensional evidence embedded in multimodal User-Generated Content. To...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016081641

Investigating patterns of tourist movement using multiple data sources

Novais, Margarida Abreu; Del Papa, Bruno; Han, Qiwei; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016063942

Measuring data-driven innovation in firms : a multi-source approach using Large Language Models

Abbonato, Diletta; Biggi, Gianluca; Bottai, Carlo; … - 2026

This study presents a comprehensive framework for identifying and measuring Data-Driven Innovation (DDI) at the firm level. We develop a conceptual definition of DDI grounded in the chain-linked model of innovation, where data infrastructure and advanced analytics augment each stage of the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016085784

Multifactor timing with deep learning

Cotturo, Paul; Liu, Fred; Proner, Robert - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016085816

The use of big data analytics in performance management : the antecedents and role in enhancing performance measurement system effectiveness

Phan, Thanh; Baird, Kevin - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016085311

Leveraging large language models for aspect-based sentiment analysis : a restaurant recommendation system for entrepreneurs in Lisbon

Carrasco, Paulo; Esteves, Pedro - 2026

The purpose of this study is to implement a restaurant recommendation system tailored for entrepreneurs within the Lisbon Metropolitan Area (AML), utilising Large Language Models (LLMs) for aspect-based sentiment analysis (ABSA) of online customer reviews. The methodology involved three phases:...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016091552

An analytical approach to sentiment extraction and decision-making using fine-tuned large language models

Bui, Hien; Thanh Ho; Nguyen, Huong; Bui, An - 2026

In the competitive restaurant and food service industry, customer reviews play a crucial role in assisting others to make informed decisions. However, the large volume and linguistic complexity of these reviews make it challenging to extract actionable insights effectively. To address this...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082739

A systematic review of analytical machine learning techniques for optimizing decisions in underground engineering

Niyogisubizo, Jovial; De Dieu Ninteretse, Jean; … - 2026

Population growth and rapid urban development have emerged as significant global challenges. These problems are causing high demand for projects constructed below the ground. Although engineers and researchers involved in underground project design are trying to find possible solutions, they...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016082743

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

Li, Mingqian; Du, Rong; Ai, Shizhong; Hunt, Richard A.; … - 2026

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,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016084092

From data to decisions : enhancing ambidexterity and performance through big data analytics capability and organizational foresight

Nguyen, Vu Van; Phuong Van Nguyen; Nguyen Sam Thi Ngoc; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015611626

Data mining for the adjustment of credit scoring models in solidarity economy entities : a methodology for addressing class imbalances

Bermudez Vera, Ivan Mauricio; Restrepo, Jaime Mosquera; … - 2025

This study addresses the quantification of credit risk in solidarity economy entities, proposing a new methodology to redefine the concept of a "default" in the frequent situations of extreme class imbalances. The objective is to develop and evaluate credit scoring models that enhance risk...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015333680

A comprehensive framework for customer retention in e-commerce using machine learning based on churn prediction, customer segmentation, and recommendation

Jahan, Ishrat; Sanam, Tahsina Farah - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015595626

Modeling a sustainable decision support system for banking environments using rough sets : a case study of the Egyptian Arab Land Bank

Elnagar, Mohamed A.; Aty, Jaber Abdel; Elhady, … - 2025

This study addresses the vast amount of information held by the banking sector, especially regarding opportunities in tourism development, production, and large residential projects. With advancements in information technology and databases, data mining has become essential for banks to...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015338327

Applications and competitive advantages of data mining and business intelligence in SMEs performance : a systematic review

Tsiu, Shao V.; Ngobeni, Mfanelo; Mathabela, Lesley; … - 2025

Small and medium-sized enterprises (SMEs) face unique challenges that can be effectively addressed through the adoption of data mining and business intelligence (BI) tools. This systematic literature review scrutinizes the deployment and efficacy of BI and data mining technologies across SME...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015434557

The drivers and income effect of big data use by e-commerce farmers : evidence from China

Zeng, Yiwu; Li, Baogang; Li, Lili; Zhang, Guojun - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015595720

Discovering heuristics with Large Language Models (LLMs) for mixed-integer programs : single-machine scheduling

Çetinkaya, İbrahim Oğuz; Büyüktahtakın, İ. Esra; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015553004

Integration of data analytics and data mining for machine failure mitigation and decision support in metal-mechanical industry

Araújo, Sidnei Alves de; Bomfim, Silas Luiz; … - 2025

Background: The growing complexity of production processes in the metal-mechanical industry demands ever more effective strategies for managing machine and equipment maintenance, as unexpected failures can incur high operational costs and compromise productivity by interrupting workflows and...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015492745

User-centric design for energy service apps : integrating expectations disconfirmation and innovation theories

Manna, Atanu; Chakraborty, Debarun; Apergis, Nicholas - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015627134

Machine learning applications in finance : special issue reprint

2025 - 2nd edition

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015609822

Emerging trends in tax fraud detection using artificial intelligence-based technologies

Alm, James; Belahouaoui, Rida - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015619641

Big data analytics in Indian healthcare supply chain : a review and bibliometric research

Singh, Twinkle; Poulose, Jeanne; Sharma, Vinod - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015627371

Service quality dimensions in Austrian food retailing : a text mining approach for physical retail stores

Falatouri, Taha; Brandtner, Patrick; Nasseri, Mehran; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015546810

Accurate recommendation method for enterprise product network marketing information under the background of big data

Liu, Chang - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015640319

Engaging tourists from city aesthetics : evidence from multi-modal analysis of computer vision and text mining

Bai, Shizhen; Li, Zhifang; He, Hao; Fan, Weijia - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015640623

Beyond static rankings : a tourist experience-driven approach to measure destination competitiveness

Chen, Jinyan; Wu, Jie; Wang, Danni; Stantic, Bela - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015078076

Do P2P borrowers improve the quality of information disclosure? : an analysis with text mining on loan descriptions

Chen, Yuan; Feng, Ji; Li, Xun; Yu, Shijie - 2025

Most of peer-to-peer (P2P) online borrowers are small business managers. The learning behavior of borrowers in the P2P market is rarely studied. The aim of this paper is to identify the existence of borrowers' learning behavior in the P2P market using a large sample from renrendai.com, which is...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015371227

28. Mining

Sedlmeir, Johannes; Zhou, Yunxiu - 2026

This chapter provides a comprehensive overview of mining in the context of proof-of-work-based consensus mechanisms, which represent the backbone for Bitcoin and many other crypto assets. We first discuss miners’ incentives, the critical role of mining for security, and key design aspects such...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015642734