Professor Pervaiz Akhtar
Pervaiz Akhtar, Chair (Full Professor) in Business Analytics, Big Data & Supply Chains/PhD, MSc, MBA, BSc, PCAP & HE UK Senior Fellow
Pervaiz Akhtar is Director of the MBA suite of programmes and Chair (Full Professor) in Business Analytics, Big Data and Supply Chains. Professor Akhtar utilises mixed methods and modelling to optimize and de-risk operational performance, supply chains and business value. He was Associate Dean of Graduate Studies before joining the University of Aberdeen. He has been a Visiting Professor of Big Data and Business Analytics/Management Science (e.g., IESSEG, France) and a member of Executive Groups. He is also associated with Imperial College London, as his philosophy of continuous learning.
Due to his all-round excellence in leadership, research and teaching, he is one of only 155 academics across all disciplines in the UK who earned their Professorship under the age of 35 as per HE records and became the youngest professor from his country of origin (out of over 212 million population). He has also set consecutive promotion records.
Professor Akhtar has capitalised on over 20 years of academic, consulting and industrial experiences from the UK, France, New Zealand and other countries – played leading roles in teaching and research. By integrating informatics, analytics and big data applications in undergraduate and postgraduate programmes, Professor Akhtar serves to bridge the gap between academic practices and industrial requirements. He has played multiple senior management roles in industry and worked with private and non-profit-making organizations such as UNICEF, JCCP, Oxfam, MSF, Islamic Relief, Red Cross, Unilever and Reckitt Benckiser.
Along with his intriguing interdisciplinary education (BSc in Double Major Mathematics and Statistics, MBA, MSc in Logistics and Supply Chains, PCAP, Senior UKHE Fellowship, PhD in Supply Chain and Operations Management with extensive Data Science Applications), his research has appeared in top-ranked journals (i.e., A*/FT50/CABS4/Q1) spanning a range of domains and industries including food, healthcare, FMCG, manufacturing, humanitarian operations, performance measurement, business value creation, logistics, supply chains, technology, big data analytics and data science skills.
He has extensive experience of supervising UG, PG and PhD students and warmly welcomes all students. PhD students are particularly encouraged to apply in his area of interest such as big data, blockchain technology, analytics, humanitarian logistics and business operations.
Professor Akhtar has worked on multiple projects with more than 20 companies and organizations worldwide (e.g., United Kingdom, United States, Canada, Australia, New Zealand, India, Malaysia, Pakistan and Europe). He has completed more than 10 funded projects and received awards – the value more than £5 million.
Professor Akhtar is a Senior Associate Editor of International Journal of Physical Distribution and Logistics Management (impact factor greater than 9) as well as on Editorial Board of the British Journal of Management (Chartered ABS 4-ranked).
Professor Akhtar’s research interests and current projects include:
- Business applications of the Internet of things, blockchain technology and big data analytics
- Building resilient data and information processing capabilities for operational agility
- Optimization, simulation, risk management, performance measurement and operational sustainability
- Network analysis, social media and their applications in supply chains/logistics/transportation
- The role of technology (e.g., the Internet of Things, drones technology, RFID, cloud computing and ERP/SAP) in humanitarian and non-humanitarian operations
- Quantifying risk and optimising performance
- Research methodologies and techniques (e.g., the analytic hierarchy process and analytic network process, network analysis, structural equation modelling, partial least square, multiple regression, multi-level modelling, machine learning methods, methodological urban legends and challenges, experimental research design, qualitative comparative analysis, case studies and operational research techniques)
The keywords of his research interest encompass big data analytics, big data skills, business analytics, network analytics, technology, modelling, operations management, supply chains, logistics, performance measurement, blockchain applications & business value creation.
PhD students are strongly encouraged to apply for their studies; particularly those who are willing to modify their research proposals and incorporate Professor Akhtar’s research interests (see the details and topics referenced in his research interests).
Professor Akhtar has supervised more than 50 UG and PG research students, including PhD completions. The recent examples of PhD theses include:
- Big data analytics for evidence-based decision making
- Food processing and relative manufacturing industry: automated technologies and sustainability-based performance
- Terrorism affected regions: the impact of different supply chain risk management strategies on financial performance
- New technological implications to improve food productivity and security
Professor Akhtar utilises mixed methods and various software for consultancy, projects, research and teaching – AMOS, Mplus, SmartPLS, R/RStudio, (network analysis, text mining and machine learning techniques), Tableau, Power BI, Python, Spark, Risk Simulator, Gephi, SAS Enterprise Miner, SPSS, Minitab, SuperDecisions, Nvivo, Freeplane, Mind Mapping, among others. The examples of his tangible skills encompass – unstructured data mining, analytics, network analysis, machine learning/big data/data science techniques (e.g. neural works, cluster analysis and basket analysis), time series analysis, multi-level modelling and panel/longitudinal data handling, data cleansing, data quality checks, moderating and mediating analysis, big data analytics, structural equation modelling, partial least square, multiple regression, logistic regression, discriminant analysis, endogeneity solutions, dealing with urban legends, queuing modelling, forecasting, inventory modelling, simulation, optimisation, six-sigma applications, qualitative comparative analysis, among others. Professor Akhtar has incorporated modern data-driven and machine learning for contemporary business students, who focus on technology-oriented learning (e.g., SAP applications and evidence-based decision making using analytical insights from complex structured and unstructured datasets).
Professor Akhtar has worked on multiple projects with more than 20 companies and organizations worldwide (e.g., United Kingdom, United States, Canada, Australia, New Zealand, India, Malaysia, Pakistan and Europe). He has completed more than 10 funded projects and received awards – the value more than £5 million
Association for Computing Machinery (https://www.acm.org/)
British Academy of Management (https://www.bam.ac.uk/)
Centre for the Advancement of Research Methods and Analysis (www.http://carma.wayne.edu)
Problem solving Australasian Research Management Society (www.http://researchmanagement.org.au/)
Reviews and member of scientific committees:
- Research Policy
- Journal of Business Ethics
- European Journal of Operations Research
- British Journal of Management
- International Journal of Production EconomicsEnterprise Information Systems (Guest Editor)
- Production, Planning and Control
- Tékhne - Review of Applied Management Studies (Editorial Board)
- Journal of Humanitarian Logistics and Supply Chain Management
- Journal of Business Research
- R&D Management
- Expert Systems With Applications
- Journal of Knowledge Management (Editorial Board)
- Abasyn Journal of Social Sciences (Editorial Board)
Research workshops attended or co-organised:
- 2018, March 28–29, The 3rd Abasyn International Conference on Technology and Business Management (AICTBM) (http://peshawar.abasyn.edu.pk/images/upcoming/AICTBM.pdf )
- 2016, September 5–9. The 21st SAP Academic Conference and Workshop on Analytics, Germany, (http://events.sap.com/sap-academic-conference-emea-2016/en/whyattend).
- 2015, July 7th (full day). Food and Drink IT Summit, (http://www.itfoodsummit.com/)
- 2015, July 1st (half day). Big Data Analytics
- 2014, Jun 17–20. The Workshops on Algorithms for Modern Massive Data Sets (MMDS), University of California, Berkeley (http://mmds-data.org/)
- 2014, 15th July 2014 (full day). Making Connections with Big Data (http://hubs.hull.ac.uk/bigdata/)
Keynote speaker and guest lectures:
- Big data, value creation and de-risking business operations, the 2019 European Convention in Quantitative Methods & Risk Management (EURiskConvention), 15-19 July 2019.
- Big data, business value creation and implications, 3rd Abasyn International Conference on Technology and Business Management (AICTBM), 28-29 March 2018, (http://peshawar.abasyn.edu.pk/images/upcoming/AICTBM.pdf).
- Essential micro-foundations for contemporary business operations: Top management tangible competencies, relationship-based business networks and environmental sustainability, University of Leeds (https://business.leeds.ac.uk/about-us/article/centre-for-operations-and-supply-chain-research-coscr-seminar-2/), 8 November 2017.
- Essential micro-foundations for contemporary business operations: Top management tangible competencies, relationship-based business networks and environmental sustainability, University of Kent, 15 November 2017.
Examples of programmes taught/developed/overseen
MBA, Big Data, Analytics and Digitisation (MBA BDAD)
MSc, Big Data and Business Analytics
MSc, Business Analytics/Data Science and Consulting
MSc, Logistics and Supply Chain Management
BSc, Logistics and Supply Chain Management
BSc, Project Management
Big Data Analytics and Visualisation
Operations Management and Digital Transformation
Information Management and Big Data
Supply Chain Analytics
Text Mining and Machine Learning
Modelling and Analysis
Decision Making Techniques for Logistics and Supply Chain Management
Enterprise Systems Enterprise Systems and Business Intelligence/SAP
Supply Chain Planning and Control (optimization, simulation and other quantitative tools for measuring quality)
Procurement & Supply Chain Management
Business Project Management
Page 1 of 2 Results 1 to 10 of 14
Impact of IoT on manufacturing industry 4.0: A new triangular systematic reviewSustainability (Switzerland), vol. 13, no. 22, 12506Contributions to Journals: Review articles
The role of big data analytics in manufacturing agility and performance: moderation- mediation analysis of organizational creativity and of the involvement of customers as data analystsBritish Journal of ManagementContributions to Journals: Articles
Analysing corporate governance and accountability practices from an African neo-patrimonialism perspective: Insights from KenyaCritical Perspectives On Accounting, vol. 78, 102260Contributions to Journals: Articles
Real-time information sharing, customer orientation, and the exploration of intra-service industry differences: Malaysia as an emerging marketTechnological Forecasting and Social Change, vol. 167, 120684Contributions to Journals: Articles
Towards customization: Evaluation of integrated sales, product, and production configurationInternational Journal of Production Economics, vol. 229, 107775Contributions to Journals: Articles
Coordination and collaboration for humanitarian operational excellence: Big data and modern information processing systemsProduction Planning and ControlContributions to Journals: Articles
Emancipatory Ethical Social Media Campaigns: Fostering Relationship Harmony and PeaceJournal of Business Ethics, vol. 164, no. 2, pp. 287-300Contributions to Journals: Articles
Exploring Perceptions of Advertising Ethics: An Informant-Derived ApproachJournal of Business Ethics, vol. 159, no. 3, pp. 727-744Contributions to Journals: Articles
Big Data-Savvy Teams’ Skills, Big Data-Driven Actions and Business PerformanceBritish Journal of Management, vol. 30, no. 2, pp. 252-271Contributions to Journals: Articles
Effective contracting for high operational performance in projectsInternational Journal of Operations and Production Management, vol. 39, no. 2, pp. 294-325Contributions to Journals: Articles