Exploratory simulation of collective innovative behavior in global participatory science communities
Pages 708 - 719
Abstract
Better understanding of how and why networks of open innovation and global participatory science communities form and evolve, and how they can be governed or influenced toward sustainable innovation and productive states are critical questions. To this end, a simulation-based exploratory study is conducted to better understand the conditions that confer increased rates of innovation in such socio-technical systems. Three types of open science communities are identified and simulated using agent simulation as a method of inquiry. Simulation results show that centrality, as a measure of degree of connectedness, exhibits positive influence for innovation output in exploratory and service communities up to a point. Also, utility-oriented communities have social network structures with low density and high centrality, suggesting high potential for innovation.
References
[1]
Bos, N., A. Zimmerman, J. Olson, J. Yew, J. Yerkie, E. Dahl, and G. Olson. 2003, May. From shared databases to communities. Technical Report: Oxford Technical Institute.
[2]
Cowan, R., and N. Jonard. 2004. Network structure and the diffusion of knowledge. Journal of Economic Dynamics & the Diffusion of Knowledge 28:1557--1575.
[3]
Crane, D. 1972. Invisible colleges: Diffusion of scientific knowledge in scientific communities. Chicago, IL: The University of Chicogo Press.
[4]
Csikszenthmihalyi, M. 1999. Implications of a systems perspective for the study of creativity. Handbook of Creativity:313--338.
[5]
Dhanaraj, C., and A. Parkhe. 2006. Orchestrating innovation networks. Academy of Management Review 31 (3): 659--669.
[6]
Edmonds, B. 2007. Artificial science - a simulation to study the social processes of science. Social Simulation: Technologies, Advances and New Discoveries:61--67.
[7]
Foster, I. 2005, May. Service-oriented science. Science 308:814--817.
[8]
Gilbert, N. 1997. A simulation of the structure of academic science. Sociological Research Online 2 (2): http://www.socresonline.org.uk/socresonline/2/2/3.html.
[9]
Harrison, J. R., and G. R. Carroll. 2006. Culture and demography in organizations. Princeton, NJ: Princeton University Press.
[10]
Holland, J. H. 1995. Hidden order: How adaptation builds complexity. Perseus Books.
[11]
Hovland, C., and E. Hunt. 1960. The computer simulation of concept attainment. Behavioral Science 5:265--267.
[12]
Klahr, D., and H. A. Simon. 1999. Studies of scientific discovery: Complementary approaches and convergent findings. Psychological Bulletin 125 (5): 524--543.
[13]
Mann, G. S., D. Mimno, and A. McCallum. 2006. Bibliometric impact measures leveraging topic analysis. Proceedings of the 2006 JCDL Conference:25--34.
[14]
NanoHUB 2009, May. Network for computational nanotechnology. http://nanohub.org/.
[15]
Smith, B., and M. Ashburner. 2007. The obo foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25 (11): 1251--1255.
[16]
Stankiewicz, R. 1992, Springer-Verlag. Technology as an autonomous socio-cognitive system. Dynamics of Science-Based Innovation.
[17]
Ward, T. B., S. M. Smith, and J. Vaid. 1997. Conceptual structures and processes in creative thought. Creative Thought: An Investigation of Conceptual Structures and Processes:1--30.
[18]
Yilmaz, L. 2009. An agent simulation study on conflict, community climate, and innovation in open source communities. International Journal of Open Source Software and Processes 1 (4): 1--25.
Index Terms
- Exploratory simulation of collective innovative behavior in global participatory science communities
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Information
Published In
December 2010
3519 pages
ISBN:9781424498642
- Editors:
- Björn Johansson,
- Sanjay Jain,
- Jairo Montoya-Torres,
- Program Chair:
- Enver Yücesan
Sponsors
- IIE: Institute of Industrial Engineers
- INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
- SCS: Shanghai Computer Society
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
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Winter Simulation Conference
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Published: 05 December 2010
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WSC10
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- IIE
- INFORMS-SIM
- SCS
- SIGSIM
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WSC '10 Paper Acceptance Rate 184 of 281 submissions, 65%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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