Dr. Jashim Khan l Consumer Behaviour | Best Researcher Award

Dr. Jashim Khan | Consumer Behaviour | Best Researcher Award

Associate Professor at University of Surrey, china

Jashim Khan Sebastin is a distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles

Scopus profile

Orcid profile

Google scholar

Researchgate

Academic Achievements

Doctor of Philosophy: Auckland University of Technology, New Zealand (2012) – PhD thesis titled “Cash or Card: Consumer Perceptions of Payment Modes.”

Master of Management (Distinction): Massey University, New Zealand (2005)

Postgraduate Diploma in Business Administration: Massey University (2004)

Graduate Diploma in Tertiary Teaching: AUT University, New Zealand (2012)

P.G. Certificate in Management Education: University of Surrey, UK (2022) – Awarded 80% average/Distinction

Bachelor of Business Administration: Newport University, USA (2000)

Advanced Diploma in Business Administration: The City College London, UK (1999)

Employment History

Dr. Jashim Khan has held various esteemed academic positions:

Associate Professor of Marketing: University of Surrey, UK (August 2022 – Present)

Director, International Business Management: Surrey International Institute, University of Surrey, UK (February 2020 – Present)

Senior Lecturer: University of Surrey, UK (February 2016 – July 2022)

Lecturer: University of Surrey, UK (August 2015 – February 2016)

Academic Management Highlights

Instrumental in planning the 1+3 International Business Management, Accounting & Finance, International Tourism Management program at Surrey International Institute. Led curriculum development catering to the needs of Chinese students, focusing on employability, resilience, digital capabilities, and sustainability. Convenor of Leadership Entrepreneurship Ability Development (LEAD) SII student-led industry collaboration institute-wide, partnering with major companies. Provided exceptional leadership during the Covid-19 pandemic, overseeing the transformation to online teaching at Surrey International Institute. Implemented an electronic attendance system in the VLE platform for all students in the institute, collaborating with the Director of L&T in Guildford.

Professional Experience & Consulting

Dr. Khan’s professional experience includes  Conducting workshops and seminars on topics such as collaborative consumption, mixed methods research, and the sharing economy. Organizing and chairing international conferences and scholarly visits. Collaborations with various industries and organizations, including Accenture, Cisco, Wipro, Baidu.com, IBM, and more, fostering research and student development. Collaboration with Plunket Organization in New Zealand and joint efforts in industry cooperation for sustainable cities.

Teaching Excellence & Module Evaluation

Received exceptional Module Evaluation Questionnaire (MEQ) scores, achieving the highest in several modules taught at the University of Surrey. Dr. Jashim Khan’s career spans extensive academic achievements, management excellence, and a robust contribution to curriculum development and industry collaboration, enhancing both student experiences and academic research.

📊 Citation Metrics (Google Scholar):

  • Citations by: All – 444, Since 2018 – 361
  • h-index: All – 11, Since 2018 – 11
  • i10 index: All – 15, Since 2018 – 15

 

📖 Publications  Top Note :

Measuring consumer perceptions of payment mode  paper publication in 2017 cite by 57

Validation in marketing experiments revisited   paper publication in 2011 cite by 56

”Cashless”transactions: perceptions of money in mobile payments    paper publication in 2009 cite by 56

Winery website loyalty: The role of sales promotion and service attributes        paper publication in 20118 cite by 31

Factors explaining shared clothes consumption in China: Individual benefit or planet concern?      paper publication in 2019 cite by 28

Handbook of research on social marketing and its influence on animal origin food product consumption     paper publication in 2018 cite by 22

Handbook of research on higher education in the MENA region: Policy and practice: policy and Practice   paper publication in 2014 cite by 21

Autocorrelation, trend analysis, and forecasting

Autocorrelation, trend analysis, and forecasting

This conference is dedicated to advancing the knowledge and application of statistical methodologies in the domain of engineering data analysis. It provides a platform for experts to exchange ideas, discuss innovative approaches, and explore the critical topics of autocorrelation, trend analysis, and forecasting in engineering contexts.

Time Series Forecasting for Demand Planning

Explore advanced time series forecasting techniques tailored to engineering applications, enabling precise demand forecasting, production planning, and inventory optimization in industries like manufacturing and supply chain management.

Autocorrelation Analysis for Sensor Data

Investigate how autocorrelation analysis can reveal hidden patterns and dependencies in sensor data from engineering systems, aiding in anomaly detection and predictive maintenance strategies.

Trend Detection in Environmental Monitoring

Delve into the use of statistical methods to detect and analyze trends in environmental data, such as air quality, water levels, and temperature variations, to inform sustainability and resource management efforts.

Longitudinal Data Analysis for Product Performance

Examine methodologies for analyzing longitudinal data to assess product performance over time, ensuring product reliability and compliance with quality standards.

Engineering Data Mining for Predictive Maintenance

Explore data mining techniques in engineering data to develop predictive maintenance models, optimizing equipment uptime and minimizing unplanned downtime in critical systems.