Cultural values and digital gap: Overview of behavioral patterns DOI Creative Commons
Maral Jamalova

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0311390 - e0311390

Published: Oct. 1, 2024

The study uses different statistical techniques to understand the relationship between variables explaining digital divide and classification based on Inglehart-Welzel Cultural Map for 2023. To achieve this purpose focusing Digital Penetration (the percentage of internet social media users mobile cellular connections), Operating Systems share (iOS Android), Device Traffic (laptop/mobile phone-based web traffic) as well Mobile Commerce (bills payments using internet) were included in analysis. minimize any effects arithmetic means data was calculated.: results from one-way ANOVA tests indicate significant differences among groups classified by cultural values almost all measured digitalization. mean squares F-values across like connections, users, active are indicating a shift towards more secular self-expressive values. GLM procedure show that portions total variance digitalization associated with membership map. This suggests classifications can explain substantial behavior preferences populations. Spearman’s correlation coefficients showed strong positive correlations Traditional/Secular several metrics, such use phones or payments, negative others traffic device type (mobile vs. laptop/computer). These suggest play role influencing habits accessibility.

Language: Английский

Crypto ecosystem: navigating the past, present, and future of decentralized finance DOI Creative Commons
Paola Bongini,

Francesca Mattassoglio,

Alessia Pedrazzoli

et al.

The Journal of Technology Transfer, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 30, 2025

Language: Английский

Citations

0
Detecting Potential Investors in Crypto Assets: Insights from Machine Learning Models and Explainable AI DOI Creative Commons
Timotej Jagrič,

Davor Luetić,

Damijan Mumel

et al.

Information, Journal Year: 2025, Volume and Issue: 16(4), P. 269 - 269

Published: March 27, 2025

This study explores the characteristics of individual investors in crypto asset markets using machine learning and explainable artificial intelligence (XAI) methods. The primary objective was to identify most effective model for predicting likelihood an investing assets future based on demographic, behavioral, financial factors. Data were collected through online questionnaire distributed via social media personal networks, yielding a limited but informative sample. Among tested models, Efficient Linear SVM Kernel Naïve Bayes emerged as optimal, balancing accuracy interpretability. XAI techniques, including SHAP Partial Dependence Plots, revealed that understanding, perceived risks, benefits influential For individuals with high investing, these factors had strong positive impact, while they negatively influenced those low likelihood. However, moderate investment likelihood, effects mixed, highlighting transitional nature this group. study’s findings provide actionable insights institutions refine their strategies improve investor engagement. Furthermore, it underscores importance interpretable behavior analysis highlights key shaping engagement evolving market.

Language: Английский

Citations

0
The impact of perceived benefits on cryptocurrency adoption among business travelers: Evidence from MICE tourists in Thailand DOI Creative Commons

Maruding Mareh,

Laphassawat Subphonkulanan,

Wanamina Bostan Ali

et al.

Social Sciences & Humanities Open, Journal Year: 2025, Volume and Issue: 11, P. 101377 - 101377

Published: Jan. 1, 2025

Language: Английский

Citations

0
Unraveling the dynamics of digital equality and trust in AI-empowered metaverses and AI-VR-convergence DOI Creative Commons
Seung‐A Annie Jin,

Ehri Ryu

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 210, P. 123877 - 123877

Published: Nov. 27, 2024

Language: Английский

Citations

2
Transformative Role of Artificial Intelligence in Fintech DOI
Ahamed Kameel Mydin Meera,

A. Rathnakumar,

S. Agila

et al.

Advances in finance, accounting, and economics book series, Journal Year: 2024, Volume and Issue: unknown, P. 73 - 102

Published: Dec. 4, 2024

Artificial intelligence (AI) in Fintech refers to the extensive or widespread application of AI functioning financial institutions and related businesses. The focus is on techniques such as Deep Learning, Robotics, Internet Things (IoT), Image Processing, Neural Networks (ANN), Wireless Sensor Networks, Machine Learning (ML). FinTech's use has revolutionized industry by bringing cutting-edge technologies that improve decision-making, expedite procedures, offer customers individualized services. There are many different applications sector due combination FinTech. This chapter addresses their various functional areas fintech industry. Benefits, challenges, case studies, success stories were also discussed.

Language: Английский

Citations

0
Playful exercise focused on microeconomics, applying gamification: “Rompeconomía” DOI

Nathalia Carolina Gómez Sanguino,

Silvia Alejandra Rivera Salamanca,

Martha Liliana Torres-Barreto

et al.

Gamification and Augmented Reality., Journal Year: 2024, Volume and Issue: 2

Published: Sept. 8, 2024

Microeconomics is a branch of economics that focuses on the behavior individual economic agents, such as consumers, businesses, and workers. Coupled with this, it analyzes how they interact in market to determine supply demand, prices allocation resources. It fundamental tool understand economy works daily life. Based development recreational activity was carried out order strengthen theoretical knowledge, well different structures, Industrial Engineering students from University Santander who are taking subject "Economic environment”. To develop activity, we worked small groups through phases, which consist identifying necessary aspects prepare them based case study, focused structure, must analyze detail. This research using - participative action, (IAP) methodology; allowed identification activities skills while instructed studies, microeconomics group work. Gamification for learning constitutes teaching alternative challenges faced by higher education contexts where way obtaining, processing transmitting knowledge transformed.

Language: Английский

Citations

0
Cultural values and digital gap: Overview of behavioral patterns DOI Creative Commons
Maral Jamalova

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0311390 - e0311390

Published: Oct. 1, 2024

The study uses different statistical techniques to understand the relationship between variables explaining digital divide and classification based on Inglehart-Welzel Cultural Map for 2023. To achieve this purpose focusing Digital Penetration (the percentage of internet social media users mobile cellular connections), Operating Systems share (iOS Android), Device Traffic (laptop/mobile phone-based web traffic) as well Mobile Commerce (bills payments using internet) were included in analysis. minimize any effects arithmetic means data was calculated.: results from one-way ANOVA tests indicate significant differences among groups classified by cultural values almost all measured digitalization. mean squares F-values across like connections, users, active are indicating a shift towards more secular self-expressive values. GLM procedure show that portions total variance digitalization associated with membership map. This suggests classifications can explain substantial behavior preferences populations. Spearman’s correlation coefficients showed strong positive correlations Traditional/Secular several metrics, such use phones or payments, negative others traffic device type (mobile vs. laptop/computer). These suggest play role influencing habits accessibility.

Language: Английский

Citations

0