Dr. Sherbaz Khan, Jinnah University for Women, Pakistan.
Sherbaz Khan is a dedicated academician and researcher with over a decade of experience in teaching and research across prominent universities in Pakistan. He holds a Ph.D. in Management Sciences and specializes in research methods, marketing, and management. He is the Head of the Business Administration Department at Jinnah University for Women, where he teaches graduate and postgraduate students. His research interests span various qualitative and quantitative methods, including SEM, Artificial Neural Networks(ANN), and Fuzzy Inference Systems (FIS). Dr. Khan has a passion for fostering a research culture and has contributed significantly to student development.
Research Coordinator, Greenwich University (2013-2015)
Suitability For The Award
Dr. Sherbaz Khan, a seasoned academician and researcher, has over a decade of experience in teaching and research at prestigious institutions. With a Ph.D. in Management Sciences, his expertise spans SEM, Fuzzy Inference Systems, Artificial Neural Networks, and Multi-Group Analysis. Currently serving as Head of the Department at Jinnah University for Women, he has supervised numerous research projects, advanced academic standards, and contributed significantly to research culture, making him an exceptional candidate for the Best Researcher Award.
Professional Development
Sherbaz Khan is committed to continuous professional development in the field of academic research and teaching. He regularly participates in workshops and research methodology seminars, which have helped enhance his teaching practices and research supervision skills. Khanβs development includes extensive experience in using advanced research tools such as SPSS, NVIVO, and Smart PLS, empowering students with quantitative and qualitative research skills. His role as a faculty member has enabled him to mentor students in research methods and thesis writing, significantly contributing to their academic success. Additionally, his leadership as Head of Department has nurtured a research-driven environment.
Research Focus
Sherbaz Khanβs research primarily focuses on the intersection of management sciences and research methodologies. His expertise spans quantitative and qualitative methods, including Structural Equation Modeling (SEM), Fuzzy Inference Systems (FIS), Artificial Neural Networks(ANN), and Multi-Group Analysis (MGA). His work emphasizes marketing, business management, and advanced research techniques, with an interest in sociology, psychology, and supply chain management. Khan has contributed significantly to the application of knowledge-based systems (KBS) in research and business settings. His broad knowledge in these areas has positioned him as an influential figure in management research in Pakistan.
Publication Top Notes
The impact of the enablers of green supplier selection and procurement on supply chain performance (2024) International Journal of Procurement Management, 21(3), pp. 349β377
The effect of religiosity, materialism and self-esteem on compulsive and impulsive buying behavior (2024) Journal of Islamic Marketing
A grey decision-making trial and evaluation laboratory model for digital warehouse management in supply chain networks (2023) Decision Analytics Journal, 8, 100293 (19 citations)
Designing a knowledge-based system (KBS) to study consumer purchase intention: the impact of digital influencers in Pakistan (2023) Kybernetes, 52(5), pp. 1720β1744
Supply Chain Resilience During Pandemic Disruption: Evidence from the Healthcare Sector of Pakistan: Evaluating Demand and Supply Chain Resilience (2023) Understanding Complex Systems, Part F1776, pp. 235β254
Phenomenological Study of Pharmaceutical Supply Chain in Pakistan: Innovative Approaches to Minimize Operational Inefficiencies (2023) Understanding Complex Systems, Part F1776, pp. 211β233
Obstacles in Disruption and Adoption of Green Supply Chain Management (GSCM) Practices by Manufacturing Industries (2023) Understanding Complex Systems, Part F1776, pp. 153β179
The role communication, informativeness, and social presence play in the social media recruitment context of an emerging economy (2023) Cogent Business and Management, 10(3), 2251204