Xiao-Tian Wang | Economics | Best Researcher Award

Best Researcher Award

Researcher Information
Researcher Xiao Tian Wang
Affiliation Chinese University of Hong Kong (Shenzhen)
Country China
Scopus ID 57192633510
Documents 39
Citations 873
h-index 15
Subject Area Economics
Event Scientific World Research Awards
ORCID 0000-0003-1706-2446

Xiao Tian Wang
Chinese University of Hong Kong (Shenzhen)

Xiao Tian Wang is an economics researcher affiliated with the Chinese University of Hong Kong (Shenzhen). His scholarly work explores behavioral decision-making, judgment under uncertainty, social preferences, and economic psychology. His publications contribute to understanding human decision processes through experimental and interdisciplinary approaches, supporting evidence-based policy and behavioral research.[1]

Abstract

This article summarizes the academic profile of Xiao Tian Wang, highlighting research activities in behavioral economics, decision science, and economic psychology. His work combines theoretical and experimental approaches to examine human judgment, temporal preferences, framing effects, and emerging applications of artificial intelligence in behavioral decision-making.[1][2]

Keywords

Behavioral Economics, Decision Science, Economic Psychology, Experimental Economics, Delay Discounting, Framing Effects, Artificial Intelligence, Human Decision-Making, Social Preferences, Policy Analysis

Introduction

Xiao Tian Wang investigates economic decision-making through behavioral experiments, emphasizing how individuals evaluate time, uncertainty, and social interactions. His interdisciplinary research integrates economics, psychology, and computational methods to explain complex human choices while contributing valuable evidence supporting informed policy development and behavioral theory refinement.[1][2]

Research Profile

His research portfolio includes behavioral economics, experimental decision science, economic psychology, and artificial intelligence applications. Using quantitative analysis and controlled experiments, he studies temporal preferences, framing effects, cooperation, and social decision-making, producing internationally recognized scholarly contributions within economics and interdisciplinary behavioral research.[1][3]

Research Contributions

His studies improve understanding of delay discounting, framing dynamics, and prediction of human social decisions using large language models. These contributions strengthen interdisciplinary research by connecting behavioral theory with computational techniques, offering practical insights for economic policy, decision support, and emerging artificial intelligence applications.[1][2][3]

Publications

His publication record demonstrates sustained research productivity in behavioral economics and decision science. Articles addressing temporal decision-making, framing mechanisms, and artificial intelligence reflect methodological diversity while supporting reproducible, evidence-based scholarship published in reputable academic journals with international readership and scholarly recognition.[1][2][3]

Research Impact

The research has influenced discussions on behavioral policy, economic decision-making, and computational social science. Citation performance, interdisciplinary collaborations, and practical relevance indicate continuing academic impact while encouraging future investigations into human behavior, experimental economics, and responsible artificial intelligence within social science research.[1][3]

Award Suitability

Based on documented scholarly productivity, citation metrics, interdisciplinary research contributions, and sustained publication quality, Xiao Tian Wang demonstrates characteristics commonly considered for academic recognition. His work aligns with the objectives of the Scientific World Research Awards by advancing evidence-based research and international scholarly collaboration.[1][2]

Conclusion

Xiao Tian Wang’s academic achievements illustrate meaningful contributions to behavioral economics and decision science. Through rigorous experimentation, interdisciplinary collaboration, and influential publications, his research supports continued advancement of economic theory, policy analysis, and computational approaches for understanding complex human decision-making processes.[1][3]

References

  1. Evaluating the ability of large Language models to predict human social decisions.
    https://www.researchgate.net/publication/395196976_Evaluating_the_ability_of_large_Language_models_to_predict_human_social_decisions
  2. Framing Effects: Dynamics and Task Domains .
    https://www.researchgate.net/publication/4818725_Framing_Effects_Dynamics_and_Task_Domains
  3. Intertemporal meditation regulates time perception and emotions: an exploratory fNIRS study.
    https://www.researchgate.net/publication/395130329_Original_Research_-Neuroscience_Intertemporal_meditation_regulates_time_perception_and_emotions_an_exploratory_fNIRS_study
  4. Elsevier. (n.d.). Scopus author details: Xiao Tian Wang, Author ID 57192633510. Scopus.
    https://www.scopus.com/pages/authors/57192633510

Rym Ghariani | Economics | Best Researcher Award

Dr. Rym Ghariani | Economics | Best Researcher Award

Teacher – Researcher | FSEG Sfax University | Tunisia

Dr. Rym Ghariani is a dedicated Teacher-Researcher in Economics with expertise in supply chain integration, industrial management, and digital transformation in Industry 4.0. She earned her Ph.D. in Economics (2021) from the Faculty of Economics and Management, University of Sfax, Tunisia, with a dissertation on Supply Chain Integration and Business Performance, published on HAL and by Presses Académiques Francophones. She also holds a Master’s degree in Entrepreneurship Research (2016) and a Bachelor’s degree in Economics: Money, Finance, and Banking (2014). Professionally, Dr. Ghariani served as a contractual university lecturer at the University of Gabès (2022–2024), teaching economics and management, mentoring students, and contributing to curriculum development. She actively collaborated with the MGSI (Modeling and Industrial Systems Engineering) research team, engaging in international research projects, conference presentations, and poster contributions. Her research interests focus on innovation orientation, supply chain digitalization, operational and financial performance, and Industry 4.0 technologies, and she has authored multiple peer-reviewed articles in HAL, Growing Science, and Taylor & Francis (Q1 journal), along with an educational book on descriptive statistics. Dr. Ghariani’s research skills include advanced statistical analysis, regression modeling, SPSS, Smart PLS, and applied economic modeling, enabling rigorous analysis of industrial performance. She has been recognized through participation in international conferences such as EFCT2017 and the Economics of Natural Resources conference in 2022. Dr. Ghariani’s combination of research excellence, teaching dedication, international collaboration, and publication record highlights her as a strong contributor to industrial economics research, with potential for future leadership in advancing innovation, mentorship, and global research initiatives in her field.

Featured Publications

Ghariani, R., & Younes, B. (2019). Orientation à l’innovation, intégration de la chaîne logistique et avantage concurrentiel: Cas des entreprises industrielles tunisiennes. Revue Française de Gestion Industrielle, 2.

Ghariani, R., Derbel, A., & Boujelbene, Y. (2025). Industry 4.0: Impact of new technologies on supply chain integration: Empirical evidence from Tunisia. Supply Chain Forum: An International Journal, 1–20.

Ghariani, R., Soltan, G., & Boujelbene, Y. (2025). Digitalization, supply chain integration, and financial performance: Evidence from Tunisia’s agro-industrial sector. Uncertain Supply Chain Management.

Ghariani, R. (2025). Intégration de la chaîne logistique et performance des entreprises. Presses Académiques Francophones.

Ghariani, R. (2024). Approche pédagogique de la statistique descriptive: Ouvrage pédagogique. Éditions Universitaires Européennes.