COalitions in COOperation Networks (COCOON):Social Network Analysis and Game Theory to Enhance Cooperation Networks

Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.IdSpace, SIK

COCOON vindt de juiste persoon

Sie, R. L. L. (2012, 30 November). COCOON vindt de juiste persoon. Communicatie Online, p. 8.In this article (in Dutch), we discuss how COCOON could be used in communication. COCOON can aid by improving the effectiveness and efficiency of cooperation

Creativiteit en coalitievorming

Sie, R. L. L. (2010). Creativiteit en Coalitievorming. AI-blad De Connectie: 2010, de toekomst?, 3, 26-27.Creativiteit gebruiken we allemaal, de een wat meer dan de ander. Je hoeft je maar te vervelen, en je gaat al op zoek naar nieuwe activiteiten. Je bedenkt mogelijke activiteiten en kiest de beste; je bent dus creatief bezig. Onderwijl leer je allerlei nieuwe dingen. Dat doe je door bestaande kennis, die je dus soms eerst moet verwerven, te combineren. Dit wordt de psychologische P-creativiteit genoemd[1]. Of je kunt totaal nieuwe, innoverende dingen bedenken waar nog nooit iemand eerder op is gekomen, de historische H-creativiteit[1].EU FP7 idSpac

What's in it for me? Recommendation of Peers in Networked Innovation

Sie R. L. L., Bitter-Rijpkema, M., & Sloep, P. B. (2011). What's in it for me? Recommendation of Peers in Networked Innovation. Journal of Universal Computer Science, 17(12), 1659-1672.Several studies have shown that connecting to people in other networks foster creativity and innovation. However, it is often difficult to tell what the prospective value of such alliances is. Cooperative game theory offers an a priori estimation of the value of future collaborations. We present an agent-based social simulation approach to recommending valuable peers in networked innovation. Results indicate that power as such does not lead to a winning coalition in networked innovation. The recommendation proved to be successful for low-strength agents, which connected to high-strength agents in their network. Future work includes tests in real-life and other recommendation strategies.idSpac

The game of co-creativity

Sie, R. L. L. (2009). The game of co-creativity. Presentation at the Open University of the Netherlands Professional communities PhD cluster. March, 17, 2009, Heerlen, The Netherlands.In co-creativity, research has thus far focused on the extension of the set of generated ideas. Though, it is argued that we should look into factors that influence the group process. We propose an approach that uses coalitional game theory as a means to aid the process of co-creativity. A short introduction to game theoretic concepts such as shapley's value and the nucleolus is provided.The work on this publication has been sponsored by the idSpace STREP that is funded by the European Commission's 7th Framework Programme. Contract 216199 [http://www.idspace-project.org

Tweetstorming PLNs: Using Twitter to Brainstorm about Personal Learning Networks

Sie, R., Boursinou, E., Rajagopal, K., & Pataraia, N. (2011). Tweetstorming PLNs: Using Twitter to Brainstorm about Personal Learning Networks. In Proceedings of The PLE Conference 2011. July, 10-12, 2011, Southampton, UK.We start off by giving a short introduction. The introduction defines the scope of the workshop, the purpose, and the means. Particularly, the participants will be asked to identify their personal online learning network. They should identify how they are connected to others (Twitter, LinkedIn, Facebook, offline), and what they think their peers’ expertises are. This will provide us with an elaborate view on how participants perceive their learning network. Next, the Tweetstorm (brainstorm over Twitter) will be introduced and explained. During the Tweetstorm, we discuss what contributes to meaningful cooperation within a learning network. A twitter hashtag (#usePLN) will be used to monitor and aggregate the participants’ utterances. A ‘Twitter wall’ (hashtags.org) will be used to visualise the brainstorm, such that participants see what others have posted, building upon their ideas and reacting to their ideas. Finally, we collect the results and conclude our session with an overview of the learning network and the outcomes of the Tweetstorm session

Factors that influence cooperation in networks for innovation and learning

Networked cooperation fails if the available partnerships remain opaque. A literature review and Delphi study uncovered the elements of a fruitful partnership. They relate to personality, diversity, cooperation, and management. Innovation networks and learning networks share the same cooperative intention, but they too often fail as members of the network do not know which partnerships are valuable. If one plans to build a support service that provides insight into the value of future cooperation, one first needs to know what contributes to effective and efficient cooperation. In addition to carrying out a literature review, we invoked the eDelphi method to answer this question. eDelphi is a method to solicit knowledge from experts anonymously and without geographical constraints. Observations from two eDelphi rounds are reported in this article. The first round focused on factor generation and determined which factors influence cooperation networks; it was conducted with two groups of six representative experts. Experts list open communication, a positive attitude, trust, keeping appointments, and personality as influential factors for cooperation networks. A team of four moderators categorised the factors in a second round, resulting in four core clusters: personal characteristics, diversity, effective cooperation, and managerial aspects. Interestingly the experts failed to list some factors that are mentioned in the literature. This finding is discussed