Professor Pervaiz Akhtar

Professor Pervaiz Akhtar
Professor Pervaiz Akhtar
Professor Pervaiz Akhtar

Pervaiz Akhtar, Chair (Full Professor) in Business Analytics, Big Data & Supply Chains/PhD, MSc, MBA, BSc, PCAP & HE UK Senior Fellow

Personal Chair

Email Address
Office Address

University of Aberdeen Business School

MacRobert Building

King's College

Aberdeen AB24 5UA

Business School


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.


Research Overview

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

Professional affiliations:

Association for Computing Machinery (

British Academy of Management (

Centre for the Advancement of Research Methods and Analysis (www.

Problem solving Australasian Research Management Society (www.

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:

Keynote speaker and guest lectures:

Professor Akhtar


Teaching Responsibilities

Examples of programmes taught/developed/overseen

PhD, Management

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




Modules taught/developed/overseen

Big Data Analytics and Visualisation

Operations Management and Digital Transformation

Business Analytics

Data Science

Information Management and Big Data

Supply Chain Analytics

Text Mining and Machine Learning

Network Analysis

Modelling and Analysis

Decision Making Techniques for Logistics and Supply Chain Management

Multivariate Analysis

Logistics Technology

Operations 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



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Chapters in Books, Reports and Conference Proceedings

Contributions to Journals