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.
01
DIGITAL TRANSFORMATION
The effect of digital technologies and digital transformation on particular strategy content approaches, e.g., theory of the firm and firm boundary theories
Digital strategy, digital strategizing, and open strategy
Digital technology-enabled business models, such as business models in digital platforms and ecosystems
Unveiling the underlying practices and process of digital transformation
Exploring multiple value options in digital transformation contexts
Digital innovation, digital entrepreneurship
Impacts of digital transformation on work – individuals, organizations, industry and societal perspectives (workforce, competence, culture).
Digital transformation mindset, culture and roles
Socio-technical factors for managing and sustaining digital ransformations
The role of analytics and big data in managing and sustaining digital transformation
Information systems development in digital transformation
Governance for digital transformations
Evolving and competing across platforms for digital transformation
Enablers and barriers of managing and sustaining digital transformations
IS ethical and corporate responsibility considerations for digital transformation
Open innovation for digital transformations
Building digital resilience in the face digital transformation
Digital transformation of industry sectors (e.g., health, finance, retail).
Digital transformation driven by ecosystems and platforms.
Regulation and governance of digital transformation.
Multi-disciplinary studies on digital transformation, esp. if leading to novel theoretical perspectives.
Digital transformation of SMEs
Sustainable digitalization (application)
Impact of digital transformation on society
Environmental consequences of digital technologies
Smart technologies
Internal and external drivers of digitalization
Appropriate tools and effect of digital strategies
Appropriate tools for digital transformation
Technological level of digital implementation e.g., use of sensors, creation of databases, networking of components.
02
DATA SCIENCE / ARTIFICIAL INTELLIGENCE
Machine Learning Foundations for Data Science
Auto-ML
Information fusion from disparate sources
Feature engineering, embedding, mining and representation
Learning from data with domain knowledge
Reinforcement learning
Heterogeneous, mixed, multimodal, multi-view and multi-distributional learning
Online, streaming, dynamic and real-time learning
Multi-instance, multi-label, multi-class and multi-target learning
Semi-supervised and weakly supervised learning
Deep learning theories and models
Evaluation of data science systems
Data preprocessing, manipulation and augmentation
Autonomous learning and optimization systems
Machine learning for recommender systems, marketing, online and e-commerce
Risk, compliance, regulation, anomaly, debt, failure and crisis
Cybersecurity and information disorder, misinformation/fake detection
Human-centered and domain-driven data science and learning
Privacy, ethics, transparency, accountability, responsibility, trust, reproducibility and retractability
Fairness, explainability and algorithm bias
Green and energy-efficient, scalable, cloud/distributed and parallel analytics and infrastructures
IoT, smart city, smart home, telecommunications, 5G and mobile data science and learning
Government and enterprise data science
Transportation, manufacturing, procurement, and Industry 4.0
Classification-based prediction models
Regression-based prediction models
Forecast using deep learning methods and algorithms
Managing the uncertainty and missing data in forecast
The life cycle of predictive models, and maintaining predictive models
Development and validation of online predictive models
Self-learning predictive models
Predictive analytics in Industry 4.0 (application of sensors, historical experience)
Predictive analysis in healthcare and economy (e.g. patient pathway prediction, predicting complications, customer relationship management,
Risk reduction, churn prevention, market trend and analysis, credit scoring);
Social media and text analysis-based predictive models and systems
Autonomous negotiation & auction based framework
03
INFORMATION TECHNOLOGY
information technology
Information economy
Internet of things
Artificial intelligence
Blockchain technology
Digitalization
Technology assessment
AR/VR
Databases
Computer Networks and Security
Software Engineering
Data Mining
Mobile Networking
Cloud Computing
Parallel Algorithms
Electronic-Business
Smart Computing
Artificial Intelligence
Security Systems
04
DIGITAL MARKETING/TECHNOPRENEURSHIP
Digital Entrepreneurship and Online communication
Digital marketing
Social media communication
Trends in social media marketing
Brand authenticity social media marketing
Sustainability issues in ecommerce and digital marketing
Social dimension and social impact in ecommerce and digital marketing
The power of nudge in ecommerce and digital marketing
The role of disruptive technologies in ecommerce and digital marketing
The role of sales associates in ecommerce and digital marketing
Influencers and social media marketing
Customer privacy and security protection on social media
Customer Experience Data and Implications
Leveraging Data and Technology to Enhance Customer Experiences
Understanding the Customer Journey using data and analytics
Consumer Insight Mining using novel methods and technologies
Digital Marketing Metrics for Growth.
The Role of Data in Communications
Social Media and Influencer Marketing
Search Marketing
Search Engine Optimisation
05
MANAGEMENT INFORMATION SYSTEM / MANAGEMENT SYSTEM
Education technology and management systems
Healthcare technology and management systems
Business technology and management systems
IT and computer-based social management systems
Big and thick data analytics for social management