Assist. Prof. Dr. Christos Kakarougkas | Motivation and Employee Engagement | Strategic Business Management Award

University of the Aegean | Greece

Christos S. Kakarougkas is an Assistant Professor specializing in Human Resource Management of Tourism Enterprises and Organizations. He holds a Doctoral Diploma from the University of the Aegean, where his research focused on the impact of reward systems on organizational culture change in Greek five-star hotels. He also earned a Master’s Degree in Hospitality Management from Thames Valley University and a Bachelor’s Degree in Tourism Business Management from ATEI Larisa. With extensive academic and professional experience, he has taught in undergraduate and postgraduate programs across Greek universities, including the University of the Aegean, University of West Attica, and Hellenic Open University, as well as international programs in collaboration with Metropolitan College and Queen Margaret University, Edinburgh. His teaching covers Human Resource Management, Strategic Management, Entrepreneurship, Global Booking Systems, and Hospitality Administration. Beyond teaching, he has supervised numerous graduate and postgraduate theses, developed vocational training curricula, and contributed to adult education programs in leadership, tourism management, and entrepreneurship. His research interests include organizational culture, human resource practices in tourism, and strategic management of hospitality enterprises. He has been recognized for his scholarly contributions and active engagement in educational innovation. Christos continues to advance knowledge in tourism management while fostering excellence in academic and professional development.

Profiles:  Google Scholar 

Featured Publications

Katsoni, V., Upadhya, A., & Stratigea, A. (2017). Tourism, culture and heritage in a smart economy. Springer Proceedings in Business and Economics, 38.

Stavrinoudis, T., & Kakarougkas, C. (2017). A theoretical model of weighting and evaluating the elements defining the change of organizational culture. In Tourism, culture and heritage in a smart economy: Third International Conference (pp. xx–xx).

Stavrinoudis, T., & Kakarougkas, C. (2017). Factors of human motivation in organizations: A first scientific modeling for a more effective application in the hospitality industry. International Journal of Cultural and Digital Tourism, 4(2), 20–30. https://doi.org/xxxx

Stavrinoudis, T., Kakarougkas, C., & Vitzilaiou, C. (2022). Hotel front line employees’ perceptions on leadership and workplace motivation in times of crisis. Tourism and Hospitality Management, 28(2), 257–276. https://doi.org/xxxx

Kakarougkas, C., & Stavrinoudis, T. (2021). COVID-19 impact on the human aspect of organizational culture and learning: The case of the Greek hospitality industry. In Organizational learning in tourism and hospitality crisis management (Vol. 8, pp. 49–xx).

Kakarougkas, C., & Stavrinoudis, T., & Psimoulis, M. (2023). Evaluating the COVID-19 pandemic changes on hotel organizational culture. Journal of Global Business Insights, 8(1), 80–94. https://doi.org/xxxx

Kakarougkas, C., & Papageorgakis, E. (2023). Evaluating the effectiveness of training methods on the performance of human resources in Greek hotel businesses. Journal of Advances in Humanities Research, 4863, 11–xx. https://doi.org/xxxx

Assoc. Prof. Dr. Surbhi Agrawal | Innovative Leadership | Research Excellence Award

RV Institute of Technology and Management, India

Profiles:  Google Scholar 

Featured Publications

Bora, K., Saha, S., Agrawal, S., Safonova, M., Routh, S., & Narasimhamurthy, A. (2016). Cd-hpf: New habitability score via data analytic modeling. Astronomy and Computing, 17, 129–143.

Saha, S., Basak, S., Safonova, M., Bora, K., Agrawal, S., Sarkar, P., & Murthy, J. (2018). Theoretical validation of potential habitability via analytical and boosted tree methods: An optimistic study on recently discovered exoplanets. Astronomy and Computing, 23, 141–150.

Agrawal, S., Basak, S., Mathur, A., Theophilus, A. J., Deshpande, G., & Murthy, J. (2021). Habitability classification of exoplanets: A machine learning insight. The European Physical Journal Special Topics, 230, 2221–2251.

Viquar, M., Basak, S., Dasgupta, A., Agrawal, S., & Saha, S. (2018). Machine learning in astronomy: A case study in quasar-star classification. In Emerging Technologies in Data Mining and Information Security (pp. xxx–xxx). (Publisher details not provided).

Basak, S., Saha, S., Mathur, A., Bora, K., Makhija, S., Safonova, M., & Agrawal, S. (2020). Ceesa meets machine learning: A constant elasticity earth similarity approach to habitability and classification of exoplanets. Astronomy and Computing, 30, 100335.

Naik, P., Agrawal, S., & Murthy, S. (2015). A survey on various task scheduling algorithms toward load balancing in public cloud. American Journal of Applied Mathematics, 3(1-2), 14–17.

Sarkar, J., Saha, S., & Agrawal, S. (2014). An efficient use of principal component analysis in workload characterization—a study. AASRI Procedia, 8, 68–74.

Saha, S., Agrawal, S., Bora, K., Routh, S., & Narasimhamurthy, A. (2015). ASTROMLSKIT: A new statistical machine learning toolkit: A platform for data analytics in astronomy. arXiv preprint arXiv:1504.07865.

Safonova, M., Mathur, A., Basak, S., Bora, K., & Agrawal, S. (2021). Quantifying the classification of exoplanets: In search for the right habitability metric. The European Physical Journal Special Topics, 230(10), 2207–2220.