Risk Reduction in Transportation Systems: The Role of Digital Twins According to a Bibliometric-Based Literature Review

Sustainability, Journal Year: 2024, Volume and Issue: 16(8), P. 3212 - 3212

Published: April 11, 2024

Urban areas, with their dense populations and complex infrastructures, are increasingly susceptible to various risks, including environmental challenges infrastructural strain. This paper delves into the transformative potential of digital twins—virtual replicas physical entities—for mitigating these risks. It specifically explores role twins in reducing disaster such as those posed by earthquakes floods, through a comprehensive bibliometric-based literature review. Digital could contribute risk reduction combining data analytics, simulation, predictive modeling creating virtual entities integrating real-time streams better address manage risks urban environments. In detail, they can help city planners decision-makers analyze systems, simulate scenarios, predict outcomes. proactive approach allows both identification vulnerabilities implementation targeted mitigation strategies enhance resilience sustainability. More informed decisions be made relying on simulations, it also possible optimize resource allocation respond emerging challenges. work reviews key publications this domain, aim finding relevant papers that useful policy-makers. The concludes discussing broader implications findings identifying widespread adoption twin technology, privacy concerns need for interdisciplinary collaboration. outlines prospective avenues future research field.

Language: Английский

The Effects of E-Commerce Recommendation System Transparency on Consumer Trust: Exploring Parallel Multiple Mediators and a Moderator

Journal of theoretical and applied electronic commerce research, Journal Year: 2024, Volume and Issue: 19(4), P. 2630 - 2649

Published: Oct. 1, 2024

Recommendation systems are used in various fields of e-commerce and can bring many benefits to consumers but consumers’ trust recommendation (CTRS) is lacking. system transparency (RST) an important factor that affects CTRS. Applying a three-layered model, this paper discusses the influence RST on CTRS domain, demonstrating mediating role perceived effectiveness discomfort moderating domain knowledge. We recruited 500 participants for online hypothetical scenario experiment. The results show mediate relationship between Specifically, (vs. non-transparency) leads higher ( promoting CTRS) lower levels (which inhibits CTRS), turn increasing Domain knowledge positively moderates positive impact effectiveness, while negatively negative discomfort. Further, gender has when purchasing experience products there no effect search products.

Language: Английский

UDIS: Enhancing Collaborative Filtering with Fusion of Dimensionality Reduction and Semantic Similarity

Electronics, Journal Year: 2024, Volume and Issue: 13(20), P. 4073 - 4073

Published: Oct. 16, 2024

In the era of vast information, individuals are immersed in choices when purchasing goods and services. Recommender systems (RS) have emerged as vital tools to navigate these excess options. However, encounter challenges like data sparsity, impairing their effectiveness. This paper proposes a novel approach address this issue enhance RS performance. By integrating user demographic data, singular value decomposition (SVD) clustering, semantic similarity collaborative filtering (CF), we introduce UDIS method. method amalgamates four prediction types—user-based CF (U), demographic-similarity-based (D), item-based (I), semantic-similarity-based (S). generates separate predictions for each category evaluates different merging techniques—the average, max, weighted sum, Shambour methods—to integrate predictions. Among these, average proved most effective, offering balanced that significantly improved precision accuracy on MovieLens dataset compared alternative methods.

Language: Английский