Data driven service innovation
5.0 ECTS creditsThe aim of the course is for students to acquire increased knowledge of theories, models, methods, and ethical and legal considerations that underpin the systematic collection of user data, and how these methods and considerations can be employed structurally to provide a foundation for service development and innovation. Different scenarios of data collection and analysis are presented, and students reflect upon these in relation to their own work or previous professional experience.
The course begins with a brief introduction focused on different technical tools and environments that constitute the basis for collecting and analysing user data. The focus of the rest of the course involves what type of data is relevant, where to find it, where it is created, and how an organisation can refine it to generate insights that can feed into service development and innovation.
The course covers theories, models, and methods of data driven service innovation based on the collection of user data, and, in relation to this, various ethical and legal aspects connected to privacy.
The course content is partly contributed and co-created by the students themselves and based on their application of theories, models, and methods to their own experiences. The course involves independent study, continuous reading, and active reflective participation.
The course begins with a brief introduction focused on different technical tools and environments that constitute the basis for collecting and analysing user data. The focus of the rest of the course involves what type of data is relevant, where to find it, where it is created, and how an organisation can refine it to generate insights that can feed into service development and innovation.
The course covers theories, models, and methods of data driven service innovation based on the collection of user data, and, in relation to this, various ethical and legal aspects connected to privacy.
The course content is partly contributed and co-created by the students themselves and based on their application of theories, models, and methods to their own experiences. The course involves independent study, continuous reading, and active reflective participation.
Progressive specialisation:
A1N (has only first‐cycle course/s as entry requirements)
Education level:
Master's level
Admission requirements:
90 ECTS credits in the Social, Behavioural, or Natural Sciences, including at least 30 ECTS credits at the G2F level or higher, and at least 2 years of relevant work experience, plus upper secondary level English 6, or equivalent
Selection:
Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.