Potential Postgraduate Students, these are issues that we can look at for Master or PhD (Research Mode) under my supervision.

But stitll, the best choice is to look at your expertise and strengths, as well as your working experience.



  1. The effect of digital technologies and digital transformation on particular strategy content approaches, e.g., theory of the firm and firm boundary theories
  2. Digital strategy, digital strategizing, and open strategy
  3. Digital technology-enabled business models, such as business models in digital platforms and ecosystems
  4. Unveiling the underlying practices and process of digital transformation
  5. Exploring multiple value options in digital transformation contexts
  6. Digital innovation, digital entrepreneurship
  7. Impacts of digital transformation on work – individuals, organizations, industry and societal perspectives (workforce, competence, culture).
  8. Digital transformation mindset, culture and roles
  9. Socio-technical factors for managing and sustaining digital  ransformations
  10. The role of analytics and big data in managing and sustaining digital transformation
  11. Information systems development in digital transformation
  12. Governance for digital transformations
  13. Evolving and competing across platforms for digital transformation
  14. Enablers and barriers of managing and sustaining digital transformations
  15. IS ethical and corporate responsibility considerations for digital transformation
  16. Open innovation for digital transformations
  17. Building digital resilience in the face digital transformation
  18. Digital transformation of industry sectors (e.g., health, finance, retail).
  19. Digital transformation driven by ecosystems and platforms.
  20. Regulation and governance of digital transformation.
  21. Multi-disciplinary studies on digital transformation, esp. if leading to novel theoretical perspectives.
  22. Digital transformation of SMEs
  23. Sustainable digitalization (application)
  24. Impact of digital transformation on society
  25. Environmental consequences of digital technologies
  26. Smart technologies
  27. Internal and external drivers of digitalization
  28. Appropriate tools and effect of digital strategies
  29. Appropriate tools for digital transformation
  30. Technological level of digital implementation e.g., use of sensors, creation of databases, networking of components.


  1. Machine Learning Foundations for Data Science
  2. Auto-ML
  3. Information fusion from disparate sources
  4. Feature engineering, embedding, mining and representation
  5. Learning from data with domain knowledge
  6. Reinforcement learning
  7. Heterogeneous, mixed, multimodal, multi-view and multi-distributional learning
  8. Online, streaming, dynamic and real-time learning
  9. Multi-instance, multi-label, multi-class and multi-target learning
  10. Semi-supervised and weakly supervised learning
  11. Deep learning theories and models
  12. Evaluation of data science systems
  13. Data preprocessing, manipulation and augmentation
  14. Autonomous learning and optimization systems
  15. Machine learning for recommender systems, marketing, online and e-commerce
  16. Risk, compliance, regulation, anomaly, debt, failure and crisis
  17. Cybersecurity and information disorder, misinformation/fake detection
  18. Human-centered and domain-driven data science and learning
  19. Privacy, ethics, transparency, accountability, responsibility, trust, reproducibility and retractability
  20. Fairness, explainability and algorithm bias
  21. Green and energy-efficient, scalable, cloud/distributed and parallel analytics and infrastructures
  22. IoT, smart city, smart home, telecommunications, 5G and mobile data science and learning
  23. Government and enterprise data science
  24. Transportation, manufacturing, procurement, and Industry 4.0
  25. Classification-based prediction models
  26. Regression-based prediction models
  27. Forecast using deep learning methods and algorithms
  28. Managing the uncertainty and missing data in forecast
  29. The life cycle of predictive models, and maintaining predictive models
  30. Development and validation of online predictive models
  31. Self-learning predictive models
  32. Predictive analytics in Industry 4.0 (application of sensors, historical experience)
  33. Predictive analysis in healthcare and economy (e.g. patient pathway prediction, predicting complications, customer relationship management,
  34. Risk reduction, churn prevention, market trend and analysis, credit scoring);
  35. Social media and text analysis-based predictive models and systems
  36. Autonomous negotiation & auction based framework


  1. information technology
  2. Information economy
  3. Internet of things
  4. Artificial intelligence
  5. Blockchain technology
  6. Digitalization
  7. Technology assessment
  8. AR/VR
  9. Databases
  10. Computer Networks and Security
  11. Software Engineering
  12. Data Mining
  13. Mobile Networking
  14. Cloud Computing
  15. Parallel Algorithms
  16. Electronic-Business
  17. Smart Computing
  18. Artificial Intelligence
  19. Security Systems


  1. Digital Entrepreneurship and Online communication
  2. Digital marketing
  3. Social media communication
  4. Trends in social media marketing
  5. Brand authenticity social media marketing
  6. Sustainability issues in ecommerce and digital marketing
  7. Social dimension and social impact in ecommerce and digital marketing
  8. The power of nudge in ecommerce and digital marketing
  9. The role of disruptive technologies in ecommerce and digital marketing
  10. The role of sales associates in ecommerce and digital marketing
  11. Influencers and social media marketing
  12. Customer privacy and security protection on social media
  13. Customer Experience Data and Implications
  14. Leveraging Data and Technology to Enhance Customer Experiences
  15. Understanding the Customer Journey using data and analytics
  16. Consumer Insight Mining using novel methods and technologies
  17. Digital Marketing Metrics for Growth.
  18. The Role of Data in Communications
  19. Social Media and Influencer Marketing
  20. Search Marketing
  21. Search Engine Optimisation


  1. Education technology and management systems
  2. Healthcare technology and management systems
  3. Business technology and management systems
  4. IT and computer-based social management systems
  5. Big and thick data analytics for social management
  6. Data analysis and decision-making
  7. Big data and business analytics
  8. Decision support system
  9. Management support systems
  10. Information processing and management
  11. Knowledge management system
  12. Executive information systems
  13. Marketing information systems
  14. Accounting information systems
  15. Human resource management systems
  16. Enterprise resource planning
  17. Supply chain & information systems
  18. Business intelligence
  19. E-commerce and MIS
  20. Project management information system
  21. Information system and innovation
  22. Information securitY
Dr Hariz