Call for Papers
The large knowledge-based projects – CERN, the Human Genome Project, Hubble, The International Space Station, etc. – that
characterize 'big science' operate under conditions of high uncertainty and do not readily lend themselves to top-down control
procedures. To cope, some of them self-organize under broadly specified boundary conditions and a culture of trust and openness
that achieves mutual alignment under the influence of shared goals and values (Knorr-Cetina, 1999).
While Chester Barnard took coordination to constitute the essence of management (Barnard, 1938), what we witness in such projects is management conducted largely without managers as the role is understood in the world of business. How, then, does such coordination achieve the complex, high-performance outcomes that successfully take humanity to the very edge of what can be known? Do the forms of coordination adopted in big science projects provide offer tested alternatives to the command-and-control modes that modern business inherited from industrial and military organizations? Are such forms likely to be available to commercial and other types of organization?
The success of open source software projects and the growing interest in open innovation (Chesborough, Vanhaverberke & West, 2006) suggest that they might be. Yet the questions raise issues that H. Simon first addressed in 1962 under the heading "the architecture of complexity" (Simon, 1962). Simon points out that complexity is best handled through a process of hierarchical decomposition, and it was always assumed that such decomposition would be tightly coupled, and either mechanical or organic in nature. Some of the large scientific and technologically-driven collaborations, however – both commercial and non-commercial – are more ecological and loosely coupled than organic and tightly coupled. In effect, in line with the processes of sub-theme 03 of this colloquium, they are engaged in a kaleidoscopic process of assembling, disassembling, and re-assembling.
Do the dynamics of globalization, of ever faster technology cycles, coupled with the rise of the knowledge economy, favour this kind of organization? If so, could big science, open source, etc., be providing us with some of the organizational models that we will need to adapt to the challenges involved? The track aims to explore the issue and we would welcome papers that address its different facets from either a theoretical or an empirical perspective. Such facets might include:
- What types of organization face knowledge-based challenges similar to those faced by big science and open source organizations? How do they deal with them?
- Does the complexity of knowledge-based organization place some upper limit on their size?
- Does the size of a knowledge-based organization – scientific, technological, or other – place some upper limit on the complexity that it can handle?
- What alternatives to managerial coordination exist in knowledge-based organizations?
- What are the costs and benefits associated with managing without managers?
- How kaleidoscopic do knowledge-based organizations need to be?
- How do 'ecological organizations' differ from 'organizational ecologies'?
- Does the knowledge economy favour ecological organizations?
- How does an 'ecological organization' manage its knowledge strategically?
These questions are indicative and do not exhaust the theme. We also welcome contributions that explore other issues relevant
to the theme.
Barnard, C.I. (1938): The Functions of the Executive.
Cambridge, MA: Harvard University Press.
Chesborough, H., W. Vanhaverbeke & J. West (eds.) (2006): Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press.
Knorr-Cetina, K. (1999): Epistemic Cultures: How the Sciences Make Knowledge. Cambridge, MA: Harvard University Press.
Simon, H.A. (1962): "The architecture of complexity." Proceedings of the American Philosophical Society, 106, 467-482.