Chokri Aloui | Operations Research and Statistical Optimization | Research Excellence Award

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Dr. Chokri Aloui | Operations Research and Statistical Optimization | Research Excellence Award

University of Sousse | Tunisia

Dr. Chokri Aloui is an Assistant Professor at the Faculty of Economics and Management, University of Sousse, and a researcher at the Laboratory of Research in Innovation Management and Sustainable Development, Sousse Higher Institute of Management, specializing in microeconomics, industrial organization, platform and network economics, environmental economics, and the economic appraisal of development projects. He holds a Ph.D. in Economics from Sousse University, preceded by a Master’s degree from Tunisia Polytechnic School and a Bachelor’s degree from Jendouba University, and his academic trajectory reflects a consistent focus on network externalities, two-sided markets, competition, and digital economy dynamics. His teaching portfolio spans industrial economics, microeconomics at various levels, game theory, markets and strategies, development project appraisal, and business simulation, demonstrating broad expertise across applied and theoretical microeconomics. His research contributions include influential works on platform capacity sharing, congestion pricing, net neutrality, corporate social responsibility in two-sided platforms, and environmental certification within international trade, published in journals such as Economic Modelling, Networks and Spatial Economics, Managerial and Decision Economics, the International Review of Economics, and The Manchester School. Across his scholarly output, he has produced multiple peer-reviewed articles and maintains an active presence on platforms such as Google Scholar and ResearchGate. His Scopus profile reports approximately 43 citations, an h-index of 3, and a set of documents reflecting his ongoing research productivity. Overall, Chokri Aloui stands out as a researcher whose work integrates rigorous modeling with practical economic policy implications, contributing meaningfully to the understanding of digital markets, innovation, environmental responsibility, and development-oriented economic assessments.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

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Dr. Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | MES’s Wadia College of Engineering | India

Dr. Tushar Devidas Bhoite, Ph.D. in Mechanical Technology, M.E. in Machine Design, with over sixteen years of professional experience (including twelve in the automobile industry and four in academics), is a leading researcher and practitioner in integrating advanced IT technologies in auto-component manufacturing. His research interests encompass Industry 4.0, Industrial Internet of Things (IIoT), Digital Twin systems, Generative AI, predictive maintenance, neural and Bayesian networks, real-time monitoring, optimization and efficiency improvements in production environments. To date, he has authored 6 international journal papers and 3 international conference papers, co-authored 2 textbooks, and filed 2 patents, contributing to both theoretical and applied advancements. His master’s project, awarded from RGSTC Mumbai, stands as a landmark in his research portfolio, he has an h-index of 1 and over 1 citations as per his Scopus profile, reflecting strong scholarly impact. In his industrial roles, Dr. Bhoite has successfully led IOT implementations in assembly and press shops, improved Overall Equipment Effectiveness, standardized work systems, deployed TPM and Kaizen methodologies, and developed innovative solutions such as a wet-waste treatment machine. He currently serves as Assistant Professor in Automation & Robotics Engineering at MES’s Wadia College of Engineering, Pune, and continues consulting in production efficiency, resource optimization, and technology integration in manufacturing enterprises.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Bhoite, T. D., Pawar, P. M., & Gaikwad, B. D. FEA based study of effect of radial variation of outer link in a typical roller chain link assembly. International Journal of Mechanical and Industrial Engineering, 1, 65–70.

Bhoite, T. D., & Buktar, R. B. (2025). Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks. Production, 35, e20240047.

Bhoite, T. D., Buktar, R. B., Mahalle, P. N., Khond, M. P., Pise, G. S., & More, Y. Y. (2025). Productivity enhancement in the Indian auto component manufacturing supply chain through IoT, digital twins with generative AI, and stacked encoder-enhanced neural networks. Operations Research Forum, 6(4), 143.

Bhoite, D. T., & Buktar, R. (2025). An investigation into revolutionizing auto component manufacturing: An IoT-based approach for improved productivity and waste elimination. Journal of Information Systems Engineering and Management, 10(9s), 409–429.

Bhoite, D. T., Buktar, R., & Kannukkadan, G. (2024). Leveraging IoT in auto component manufacturing to monitor surface roughness and tool temperature. Journal of Electrical Systems, 20(2s), 563–574.*

Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

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Dr. Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

 Jiangxi University of Finance and Economics | China

Dr. Jianjian Chen is a lecturer in the School of Information Management and Mathematics at Jiangxi University of Finance and Economics, Jiangxi, P. R. China, where he has established himself as a promising scholar in the fields of management science, decision support, and electronic commerce. His research focuses on platform economics, online marketplaces, and decision support methodologies that contribute to both the theoretical and practical advancement of information systems and business strategies. Over the course of his career, Chen has built a solid portfolio of high-quality research, with his work appearing in well-regarded journals including Decision Support Systems, Information Systems Frontiers, Computers & Industrial Engineering, Electronic Commerce Research, and Electronic Commerce Research and Applications. These publications highlight his expertise in applying analytical and empirical methods to understand the complexities of digital platforms and e-commerce ecosystems. According to his Scopus profile Chen has published 7 scholarly documents, which have collectively received 86 citations, resulting in an h-index of 5, reflecting both the productivity and the impact of his research. His contributions not only enrich the academic discourse on decision support and electronic commerce but also offer practical insights for businesses navigating digital transformation and platform-based economies. Chen’s scholarship demonstrates a balance between rigorous methodological development and the application of innovative models to real-world problems, reinforcing his role as a valuable contributor to the intersection of management, information systems, and economics. By combining theoretical frameworks with practical problem-solving approaches, his research provides meaningful support for decision-making in the digital economy and underscores his growing influence within the international academic community.

Profile: Scopus 

Featured Publications

“Traditional e-commerce or live e-commerce? Online sales model selection strategies considering streamers’ bargaining behaviors”