RaulJavier ChangTam | Data Science and Analytics | Best Researcher Award

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Prof. Dr. RaulJavier ChangTam | Data Science and Analytics | Best Researcher Award

Profesor Investigador | Universidad Latina de Costa Rica | Costa Rica

Prof. Dr. RaulJavier ChangTam  is a multidisciplinary researcher whose work connects technology adoption, entrepreneurship, and sustainable innovation in Latin America. His research explores how emerging technologies influence entrepreneurial ecosystems, digital transformation, and user behavior within both business and social contexts. Drawing upon models such as UTAUT2, his studies provide empirical insights into the acceptance and use of new technologies by entrepreneurs, SMEs, and professionals in fields like healthcare and finance. He also contributes to studies on sustainable finance and FinTech, emphasizing the role of digital platforms and neobanks in promoting environmentally responsible entrepreneurship. Beyond business and technology, his work extends into socio-cultural domains examining global consumption patterns such as sneaker culture and analyzing trade dynamics in ornamental species markets. Chang-Tam’s ongoing research reflects a strong orientation toward understanding the intersection of innovation, digitalization, and sustainability, with an applied perspective that links academic insight to real-world economic and cultural transformations. His research has received 3 citations across 9 documents, with an h-index of 1.

Profiles : ORCID | Scopus  | ResearchGate

Featured Publications

1. Taboada Álvarez, J. E., Chang-Tam, R. J., Rueda Varón, M. J., & Hunter Torrealba, R. (2025). Analysis of the entrepreneurial motivational demand in a learning management process in incubators.

2. Araya, J. L. G., Robles Herrera, A. E., & Chang-Tam, R. J. (2025). Analysis of trends in exports and imports of continental and marine ornamental species of aquariums in Costa Rica.

3. Chang-Tam, R. J., Caldera-Gutiérrez, V., & Rivera Shaik, V. (2025). Influence of IT technology on the development of SME entrepreneurs in Costa Rica: Applied study of the adapted model of the Unified Theory of Acceptance and Use of Technology (UTAUT2).

4. Chang-Tam, R. J., Garita Quesada, R., Masís Muñoz, R., & Chang Caldera, A. P. (2025). Influence of new IT technology trends in dental care processes between dental professionals and patients: An analysis of the UTAUT2 theory.

5. Palos-Sanchez, P. R., Chang-Tam, R. J., & Folgado-Fernández, J. A. (2025). The role of neobanks and fintech in sustainable finance and technology: The customer/user perspective for entrepreneurs. Sustainable Technology and Entrepreneurship, 100109.

Jun Peng | Big Data Analysis | Best Researcher Award

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Prof. Jun Peng | Big Data Analysis | Best Researcher Award

Professor | Ningbo University | China

Prof. Jun Peng is a distinguished scholar in the field of educational technology with expertise in big data in education, artificial intelligence in learning, blended learning, and curriculum design. He earned his PhD in Education from the University of Hong Kong and has built a strong academic career through teaching, research, and international collaborations. Currently serving as a professor and doctoral supervisor at Ningbo University, he has also contributed to the University of Hong Kong and the City University of Macau in research and teaching capacities. His professional experience includes leading several funded projects across China and Macau, with a focus on AI integration in education and innovative digital learning models. His research interests span online learning environments, project-based education, and sustainable approaches to technology-enhanced learning, reflected in numerous publications in leading SSCI, SCI, and Scopus-indexed journals such as Computers & Education, Education and Information Technologies, and Sustainability. Recognized with multiple commendations for research excellence, he has also received awards for educational innovation and course design. Prof. Peng is active in academic service as an editorial board member, peer reviewer for reputed journals, and keynote speaker at international conferences. His research skills include quantitative and qualitative analysis, big data applications, machine learning for education, and curriculum development. With a proven record of impactful research, leadership, and mentoring, he continues to advance the field of educational technology while contributing to the global academic community.

Profile: ORCID

Featured Publications

1.Shu, X., Peng, J., & Wang, G. (2023). Deciding alone or with others: Employment anxiety and social distance predict intuitiveness in career decision making. International Journal of Environmental Research and Public Health, 20(2), 1484.
2. Su, B., & Peng, J. (2023). Sentiment analysis of comment texts on online courses based on hierarchical attention mechanism. Applied Sciences, 13(7), 4204.
3. Zhou, J., Ran, F., Li, G., Peng, J., Li, K., & Wang, Z. (2022). Classroom learning status assessment based on deep learning. Mathematical Problems in Engineering, 2022, 7049458.
4. Peng, J., Yuan, B., Sun, M., Jiang, M., & Wang, M. (2022). Computer-based scaffolding for sustainable project-based learning: Impact on high- and low-achieving students. Sustainability, 14(19), 12907.
5. Li, Y., & Peng, J. (2022). Evaluation of expressive arts therapy on the resilience of university students in COVID-19: A network analysis approach. International Journal of Environmental Research and Public Health, 19(13), 7658.