Organisations’ business models are evolving and leveraging networks of individuals to orchestrate service creation and delivery. Such use of networks enables co-creation leading to competitive scale, reduced cost and increased revenue growth.
Co-creation activities facilitate a venue for innovation through a collaborative process in a multi-actor network. Consequently, today we are shifting to a world of dynamic and rapidly adapting collaborative networks. These are loose and complex configurations of service systems that engage in mutually beneficial relationships.
The success of these collaborative networks depends on the network’s sharing of knowledge and other intangible assets such as competence, including their ability to form strong relationships through mutually beneficial collaboration.
Such a network provides an effective platform to collaborate and facilitates the process of co-creation through strong and positive interactions.
The research activities you will work on will depend on your study level:
To better understand collaborative and complex service systems, you will perform a systematic literature review on analysis of collaborative networks in the context of co-creation context.
Honours and Masters
You will be using social computing as a methodological approach to explore co-creation systems and services.
A standard social computing method, such as network analysis, will be used to analyse interactions in a collaborative network, such as GitHub.
Interactions, ties, relations, groups and other metrics between users will be used to understand how the network’s collaborative efforts result in value formation.
You will conduct a case study approach to illustrate the value of social network analysis methods in understanding co-creation systems.
The objective of our research is to understand:
- the value of social network analysis methods in understanding co-creation systems by conducting a systematic literature review
- how the network’s collaborative efforts result in value formation using social computing techniques.
We expect to publish the performed research in high-quality conferences and journals.
Skills and experience
We are looking for highly motivated students with reasonable skills and understanding in:
- qualitative or quantitative research methods (Honours/Masters)
- Python programming language or R (Honours/Masters).
- Collaborative network
- Co-creation activities
- Social computing
- Social network analysis
- Service system
Contact Dr. Reihaneh Bidar for more information.