Zahid Sarwar | Big Data Analytics | Best Researcher Award

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Dr. Zahid Sarwar | Big Data Analytics | Best Researcher Award

Postdoctoral Researcher | Shanxi University | China 

Dr. Zahid Sarwar is a dedicated academic and researcher in the field of Business Management, currently serving as a postdoctoral researcher at Shanxi University, China. He earned his Ph.D. in Business Management from Dongbei University of Finance and Economics, Dalian, China, where his dissertation focused on enhancing innovativeness through digital capabilities. Dr. Sarwar’s research spans various topics, including strategic management, technology management, digitalization, and sustainable business strategies, all of which are critical to modern organizational success. With a strong background in both theoretical knowledge and practical application, he continues to contribute valuable insights to the academic community, with a focus on the intersection of technology and strategy.

Profile

Scholar

Education

Dr. Sarwar’s academic journey is marked by a robust foundation in Business Management and related fields. He completed his Ph.D. at Dongbei University of Finance and Economics in 2023, where his research examined the role of digital capabilities in enhancing innovation within organizations. Prior to his doctoral studies, he earned a Master’s in Project Management from COMSATS Institute of Information Technology, Abbottabad, Pakistan, where he achieved a CGPA of 3.37/4.0. His undergraduate studies in Business Administration were completed at Gomal University, Pakistan, in 2014, where he graduated with a CGPA of 2970/4200. These academic credentials, along with his diverse experiences, have equipped him with a deep understanding of business management and research methodologies.

Experience

Dr. Sarwar’s professional experience is a combination of research and practical roles. As a postdoctoral researcher at Shanxi University, his current work explores key topics such as information technology, sustainable strategies, and digitalization in management. Before this, he worked as a full-time research assistant at Iqra National University, Pakistan, where he assisted Dr. Ali with various research projects. Additionally, he gained industry experience as an administrative assistant at Lucky Cement Factory Ltd., assisting in routine administrative and procurement activities. These roles have helped Dr. Sarwar develop not only his research skills but also a strong ability to bridge the gap between academia and industry.

Research Interest

Dr. Sarwar’s research interests lie at the intersection of strategic management, digital transformation, and innovation. He is particularly interested in understanding how digital platforms, big data analytics, and technological capabilities can enhance organizational innovation and performance. His work also delves into sustainable business practices, including the role of organizational culture and strategic alignment in fostering long-term business success. Dr. Sarwar is passionate about exploring the dynamic capabilities that organizations can leverage to remain competitive in an increasingly digitalized business environment. His research has profound implications for managers and policymakers seeking to drive innovation through technology and sustainability.

Awards

Dr. Sarwar’s research excellence has been recognized by numerous academic institutions. He received an Honorary Credential Certificate from Dongbei University of Finance and Economics, highlighting his exceptional contributions to the field. He was also awarded the First Prize for Outstanding Paper in 2023 and the Second Prize for Outstanding Paper in 2022, both by Dongbei University of Finance and Economics. These awards reflect his ability to produce high-quality, impactful research that resonates within the academic community. His work continues to be acknowledged for its rigor and relevance in advancing the field of Business Management.

Publications

Dr. Sarwar’s publication record reflects his expertise in strategic management, digitalization, and sustainability. Notable publications include:

Sarwar, Z., Gao, J., & Khan, A. (2024). Nexus of digital platforms, innovation capability, and strategic alignment to enhance innovation performance in the Asia Pacific region: A dynamic capability perspective. Asia Pacific Journal of Management, 41(2), 867-901.

Sarwar, Z., Song, Z. H., Ali, S. T., Khan, M. A., & Ali, F. (2025). Unveiling the path to innovation: Exploring the roles of big data analytics management capabilities, strategic agility, and strategic alignment. Journal of Innovation & Knowledge, 10(1), 100643.

Sarwar, Z., & Song, Z. (2024). How to improve sustainable business performance: Examining the roles of organizational rationale for sustainability and green organizational culture. Sustainability Accounting, Management and Policy Journal. (Publishing soon)

Gao, J., & Sarwar, Z. (2024). How do firms create business value and dynamic capabilities by leveraging big data analytics management capability? Information Technology and Management, 25(3), 283-304.

Sarwar, Z., & Song, Z. (2023). Machiavellianism and affective commitment as predictors of unethical pro-organization behavior: exploring the moderating role of moral disengagement. Kybernetes.

Sarwar, Z., Khan, M. A., Yang, Z., Khan, A., Haseeb, M., & Sarwar, A. (2021). An Investigation of Entrepreneurial SMEs’ Network Capability and Social Capital to Accomplish Innovativeness: A Dynamic Capability Perspective. SAGE Open, 11(3).

Sarwar, Z., Khan, M. A., & Sarwar, A. (2021). The strategic management model for COVID-19: a race against time: evidence from People’s Republic of China. Gomal University Journal of Research, 37(3), 278-286.

Conclusion

Dr. Zahid Sarwar’s career trajectory showcases a profound commitment to advancing the field of Business Management through rigorous research and scholarship. His focus on digital transformation, sustainable strategies, and innovation reflects the growing demands of today’s global business environment. With numerous publications in top-tier journals and several prestigious awards, Dr. Sarwar has established himself as a significant contributor to both academic knowledge and practical business strategies. His continued research endeavors at Shanxi University promise to further advance our understanding of the complex relationships between digital capabilities, innovation, and sustainability, positioning him as a future leader in his field.

jizhou Cao | Data-Driven Decision Making | Best Scholar Award

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Mr. jizhou Cao | Data-Driven Decision Making | Best Scholar Award

Student | Xinjiang University | China

Mr. Jizhou Cao is a dedicated academic and researcher currently serving at Xinjiang University. With a background in civil engineering and machine learning, he has significantly contributed to the understanding of reinforced concrete (RC) column shear behaviour, integrating advanced machine learning techniques into structural engineering. His work has explored the initial failure process in RC columns and prediction methods for shear capacity, demonstrating a unique synergy between civil engineering and machine learning. Mr. Cao’s research has been published in well-respected journals, furthering the application of machine learning to solve real-world engineering problems.

Profile

Scopus

Education

Mr. Cao earned his master’s degree from Hainan University, where he gained a solid foundation in civil engineering. He continued his academic journey by pursuing further studies at Xinjiang University, which has fostered his research interests in the intersection of civil engineering and machine learning. His educational path reflects a blend of practical expertise and theoretical understanding, particularly in the realm of structural analysis and innovative technologies such as machine learning.

Experience

With years of academic and research experience, Mr. Cao has engaged in multiple projects that apply cutting-edge technologies to civil engineering problems. His work has focused on developing predictive models for the shear capacity of RC columns and understanding the failure processes in concrete structures using machine learning techniques. He has also been involved in consultancy projects, contributing his expertise to real-world applications. His professional journey highlights his commitment to advancing both the scientific understanding and practical application of structural engineering.

Research Interest

Mr. Cao’s primary research interests lie in the integration of machine learning with civil engineering, particularly in structural analysis and the failure mechanisms of reinforced concrete structures. His research aims to bridge the gap between computational techniques and practical engineering solutions, with a special focus on the prediction of shear failure in RC columns. His work seeks to improve the accuracy of structural safety evaluations and enhance the resilience of concrete structures under various loading conditions.

Award

Mr. Cao has been recognized for his contributions to the field of civil engineering and machine learning. His research has garnered attention from leading academic institutions, with multiple nominations for prestigious awards such as the Young Scientist Award and the Excellence in Innovation Award. These accolades reflect his impactful contributions to advancing engineering practices, particularly in the realm of structural safety and the application of machine learning.

Publications

Mr. Cao has authored several influential articles, contributing to the academic discourse on machine learning applications in civil engineering. Some of his key publications include:

“Exploring the initial state of the shear failure process in RC columns based on machine learning,” Journal of Structural Engineering, 2024.

“Prediction of shear capacity of RC columns and discussion on shear contribution via the explainable machine learning,” Structural Safety Journal, 2023. These works have been cited by numerous researchers, highlighting the significance of his research in the field.

His publications have addressed critical aspects of structural engineering and have demonstrated the potential of machine learning to revolutionize the field.

Conclusion

Mr. Jizhou Cao’s work stands as a testament to the potential of machine learning in reshaping civil engineering practices. His academic background, coupled with a strong research focus on shear failure prediction in RC columns, underscores his commitment to advancing both theoretical and applied knowledge in structural engineering. As he continues to explore innovative solutions through machine learning, Mr. Cao is poised to make lasting contributions to the safety and efficiency of civil infrastructure, enhancing the way engineers approach complex structural challenges. His dedication to research and innovation makes him a valuable asset to both academia and the engineering community.