F21DE Digital and Knowledge Economy

Dr Jessica Chen-Burger

Course co-ordinator(s): Dr Jessica Chen-Burger (Edinburgh), Cristine Turcanu (Dubai).


  • To provide an overview of advanced topics in Digital and Knowledge Economy, including current developments and future trends in developed economies resulting from deploying new technologies and utilising emerging knowledge.
  • To discuss e-Business, as a new breed of modern business model that leverages technical advancements to create economic growth.
  • To provide a high level description of business and technological issues related to Digital and Knowledge Economy.
  • To introduce technologies and methodologies so as to provide a deep understanding of the Digital and Knowledge Economy, including business, organisational, knowledge and technology based issues.
  • To impart rigorous technical modelling and analytical methodologies for working with complex problems in this area.
  • To facilitate the dialogue between business and computing personnel, and translate business requirements to computing ones and vice versa.
  • To impart deep understanding of the motivation and rationale behind the conversations between business and IT, as well as other relevant technologies and future trends – so that students can recommend them and/or participate in the decision making process for future planning.

Detailed Information

Course Description: Link to Official Course Descriptor.

Pre-requisites: Fundamentals of logic, grasp of computational thinking.

Location: Dubai, Edinburgh.

Semester: 2.


  • Introduction to Digital and Knowledge Economy
    • Introduction to Digital and Knowledge Economy
    • Its relevance to e-Business
  • Topics in Digital Economy
    • An overview of technologies and tools for e-Business
    • What is a business model? What are the different types of business models?
    • What are the relationships between business models and innovative/disruptive technologies?
    • Current development and future trends in Digital and Knowledge Economy
    • Relevant technology offerings, e.g. Bitcoin, IBM’s cloud computing platform
  • Knowledge based technologies in Knowledge Economy
    • introduction to knowledge management, knowledge modelling technologies, including ontologies
    • Introduction to logic, Intelligent Systems and related technologies, including semantic web based technologies
    • Case studies of Intelligent Systems and Future trends
  • Supply Chain Management and its relation to Digital Economy
    • What is SCM? What are the standard practices in SCM, e.g. SCOR?
    • Introduction to process modelling, business operations and SCM.
    • What is global SCM? Case studies, e.g. IKEA’s global SCM; Current and future trends
  • Business Intelligence: Fundamentals issues and technologies

Learning Outcomes: Subject Mastery

Understanding, Knowledge and Cognitive Skills Scholarship, Enquiry and Research (Research-Informed Learning)

  • In-depth understanding of key issues in Digital and Knowledge Economy.
  • In-depth understanding of ontologies, conceptual and knowledge modelling technologies, in terms of design, critical evaluation and suitable practical uses.
  • In-depth understanding of issues in intelligent systems, supply chain management and business intelligence and the roles technologies may play.
  • In-depth understanding of issues and the motivation and rationale of business and technical problems in Digital and Knowledge Economy.
  • Ability to select and construct conceptual models, including ontologies, and can create appropriate evaluation criteria to assess them.
  • Ability to take self-initiatives to critically review relevant literature independently in Digital and Knowledge Economy.

Learning Outcomes: Personal Abilities

Industrial, Commercial & Professional Practice Autonomy, Accountability & Working with Others Communication, Numeracy & ICT

  • Extensive analytical skills in conceptual modelling methods, including ontologies, process and knowledge modelling, for business problems.
  • Ability to make well-informed evidence-based arguments towards supporting or rejecting technologies to solve business problems.
  • Ability to deal with complex issues and make informed judgements, e.g. about ontologies, knowledge modelling, intelligent and business systems in the absence of complete or consistent data.
  • Exercise extensive autonomy and initiative in addressing digital and knowledge economy challenges.
  • Demonstrate critical reflection on digital and knowledge economy.
  • Ability to judge technology hypes and develop personal opinions on future trends.

Assessment Methods: Due to covid, assessment methods for Academic Year 2021/22 may vary from those noted on the official course descriptor. Please see:
- Maths (F1) Course Weightings 2021/22
- Computer Science (F2) Course Weightings 2021/22
- AMS (F7) Course Weightings 2021/22

SCQF Level: 11.

Credits: 15.