Digital Business Ecosystems and Platforms

2025-2026

General Information

Course Code XM_0176
Credits 6 EC
Period P4
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. J. Gordijn
Examiner dr. J. Gordijn
Teaching Staff dr. J. Gordijn
Part of programme(s)

Practical Information

You need to register for this course yourself. The (de)registration deadlines can be found on VU.nl

Teaching Methods Seminar, Lecture

Target audiences

This course is also available as:

Course Objective

An ecosystem is a collection of parties who work cooperatively and competitively to satisfy customer needs. Well-known examples are Google, Facebook, and Netflix, but there are many other eco-systems in the field, e.g. in Fintech, energy, and automotive industry. In this course, we focus on digital ecosystems which are enabled by Internet- and related technologies. Frequently, these ecosystems are disrupted by innovative information technologies, such as machine learning, blockchain, and 5G mobile. The overall goal of this course is to analyze disruptive opportunities for an eco-system given a particular emerging technology. This year, that technology is blockchain.

Upon completion of this course, students will:

  • have gained knowledge and understanding of the concept of ‘eco-system’ (Knowledge and understanding);
  • have gained knowledge and understanding of various methods for designing and analyzing eco-systems and their e-services, including e3value, trust modelling, BPMN, and UML class modelling (Knowledge and understanding);
  • have gained knowledge and understanding of the selected technology of this year in order to analyze, design and implement a disruptive eco-system (Knowledge and understanding);
  • be able to analyze and design an eco-system offering an e-service from different viewpoints (Applying knowledge and understanding);
  • be able to elicit different e-service (business) ideas that can be provided in an eco-system (Applying knowledge and understanding);
  • be able to explore the e-service idea from a business perspective. In this way, the student will be able to further design and develop the e-service idea using different analysis techniques (Applying knowledge and understanding);
  • be able to transform the business perspective of the e-service design into a design reflecting the IT perspective (Applying knowledge and understanding);
  • be able to implement (part of) the e-service using the selected disruptive technology (Applying knowledge and understanding);
  • be able to make informed decisions about eco-systems and their e-services based on possible risks and opportunities (Making judgments);
  • be able to assess the quality and correctness of the various conceptual models created (Making judgments);
  • be able to pitch a new idea for an eco-system/e-service to investors (Communication skills);
  • be able to concisely present the selected solution (Communication skills);
  • be able to write a scientifically well-founded report about the eco-system/e-service under development in a group of students (Communication skills);
  • have learned to work in a project group and keep each other accountable for agreed results (Learning skills);
  • have learned to improve themselves based on various feedback mechanisms (Learning skills).

Course Content

The course comprises the following topics:

  • Eco-systems and platforms
  • Introduction in the selected technologyof this year
  • Business models and value proposition design
  • The e3value method for understanding business networks
  • The Business Process Modelling Notation for analysing cross-organizational networks
  • The Unified Modelling Language – class modelling
  • Transaction modelling
  • Technological design issues

Additional Information Teaching Methods

The following methods are used:

  • Lectures twice a week. These lectures include in-class workshops to practice the various methods used in this course
  • Group work: teams of about 2/3 students design an eco-system. At the beginning of the course a number of eco- systems are offered as inspiration
  • Group feedback sessions: Each week, students will get personal feedback in face-to-face feedback sessions. Moreover, groups will receive feedback on their submitted reports by email.

Method of Assessment

Individual exam on the theory (50%), Teamwork project assignments (50%).

To pass the course, the scores of each component must be 5.5. or higher.
Compensation: it is not possible to compensate one component with another.
Mode of re-examination: if insufficient, each component can be revised and resubmitted once.

Literature

A (selection of a) list of papers on the course topics. Material distributed on Canvas.

Additional Information Target Audience

Master Artificial Intelligence
Master Computer Science
Master Information Sciences

Custom Course Registration

Further information for this course will be made available online (Canvas).
All students must be enrolled in the course Canvas community. Group enrolment takes place in Canvas.

Recommended background knowledge

The student should have sufficient knowledge about Requirements Engineering and Conceptual Modelling and should master such a modelling method (at least UML class or activity diagrams).