Official course description:

Full info last published 15/11-23
Course info
ECTS points:
Course code:
Participants max:
Offered to guest students:
Offered to exchange students:
Offered as a single subject:
Price for EU/EEA citizens (Single Subject):
10625 DKK
MSc. Master
MSc in Digital Innovation & Management
Course manager
Associate Professor
Part-time Lecturer
Part-time Lecturer
Course semester
Forår 2024
29 January 2024
23 August 2024
Exam type
ekstern censur
Grade Scale
Exam Language

The course offers a comprehensive exploration of service design and management, equipping students with essential processes, fundamental principles, methods, and tools. The course centers on the strategic design and management of services, incorporating digital components and applying expertise from various service design and management disciplines. Through lectures, in-depth case studies, and interactive hands-on exercises, students explore the characteristics and dynamics of 'service' and 'service ecosystems.' This course enhances students understanding of how services can be designed, efficiently managed, and thoughtfully implemented to deliver substantial value to users, service providers, and other stakeholders.


The course educates professionals capable of leading and managing intricate digital service design processes across various phases of digital transformation in public, private, and non-profit sectors, as well as within complex networks of stakeholders. Students develop expertise in service thinking, service design methods, and tools, enabling them to apply these skills in diverse and dynamic service environments. Additionally, students learn how to initiate and facilitate collaborative processes effectively. The curriculum covers essential topics related to digitalisation of services, including service innovation, value co-creation, specific service design methods and tools, and tailored design management approaches applicable to service design projects.

Formal prerequisites

The course builds upon knowledge from the courses of the 1st semester of the DIM and KDDIT programs and students should have completed those courses or obtained similar knowledge elsewhere.

Intended learning outcomes

After the course, the student should be able to:

  • Account for and apply basic Service Design and Service Management vocabulary, theories, methods, and tools.
  • Recognize and analyze essential characteristics of services and service ecosystems and their stakeholders.
  • Identify and apply appropriate service design and management methods and tools to approach and resolve problems in varying service settings and diverse organizations.
  • Design and evaluate services using a suitable variety of service design methods and tools.
  • Analyse and communicate complex and dynamic service environments and their parts using visuals, e.g., maps and diagrams.
  • Develop and facilitate collaborative action in context of a service environment.
  • Reflect on the complex and dynamic service environments and their parts considering the presented theories, methods and tools.
Learning activities

Teaching consists of lectures, individual and group exercises, and workshops.

Course literature

The course literature is published on the course page in LearnIT.

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 15%
  • Lectures: 15%
  • Exercises: 15%
  • Project work, supervision included: 25%
  • Exam with preparation: 30%
Ordinary exam
Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.
Exam submission description:
Submission: 15 pages +/- 10%
Oral exam: The students give an oral presentation of one or more subjects based on the submission. The following examination is based on the presentation and the fixed syllabus in the Course Catalogue.
If you plan to use ChatGPT (or another generative AI) in the written assignment, it should be indicated and motivated in the methods section of the report. The specific uses of the generative AI, such as data generation, analysis, and interpretation should be described. Additionally, it should be clearly stated how the use of the generative AI contributes to the project and the results obtained from its use. Give proper reference to AI-generated text. Please cite as "Text generated by ChatGPT, developed by OpenAI ( accessed on [date].”
Group submission:
  • 4-6
Exam duration per student for the oral exam:
20 minutes
Group exam form:
Group exam : Joint student presentation followed by a group dialogue. All the students are present in the examination room throughout the examination.

Time and date
Ordinary Exam - submission Thu, 16 May 2024, 08:00 - 14:00
Ordinary Exam Mon, 3 June 2024, 09:00 - 18:00
Ordinary Exam Tue, 4 June 2024, 09:00 - 18:00
Ordinary Exam Thu, 6 June 2024, 09:00 - 18:00
Ordinary Exam Fri, 7 June 2024, 09:00 - 18:00
Reexam - submission Wed, 24 July 2024, 08:00 - 14:00
Reexam Tue, 20 Aug 2024, 09:00 - 17:00