This dissertation discusses the importance of swarming concepts such as self-organization in human crowds in relation to the use of collective intelligence obtained through (voluntary) participation via the Internet. It offers practical advice on how to manage such a (potentially large) group in order to maximize the resulting collective intelligence for application in both scientific inquiry and in business environments, including the development of innovations. Through recent socio-technical developments (i.e., Web 2.0), humans are augmenting the immense computing power of computers to solve difficult problems. They are doing this by contributing human heuristics and collective intelligence. Potentially large groups not necessarily comprised of experts are working on and communicating about problems that could not be solved before by individuals, smaller groups of experts, or machines. This “collective intelligence” is complex as it includes a large number of nonlinear dynamics resulting from interaction of (irrational) individuals with each other. This dissertation addresses the phenomena of crowdsourcing/open innovation currently involving hundreds of thousands of Internet users including public and private organizations. It comprises of an introductory part, including an extended literature review crossing discipline boundaries, and nine separate research papers in the appendix. The dissertation contributes to the theory of collective intelligence by addressing a research terrain previously unexplored that is concerned with the characteristics of distributed problem solving in large groups in both academic and business settings. It also provides an interdisciplinary contribution as it crosses academic discipline boundaries by applying knowledge and techniques from artificial intelligence research to investigating phenomena that, up until now, were mainly described by sociologists and business scholars. Selected results of this dissertation include: · Human groups collaborating through the Internet show many similarities to natural (and artificial) swarms · A few management actions that build on human specifics (like maintaining the diversity of groups against the human tendency to build teams with similar backgrounds) can increase the output from the group beyond pure “swarm intelligence” · Agent design principles compiled by embodied artificial intelligence scholars can be useful for conventional organizations to make the interaction with and within such groups more flexible, scalable, and robust in particular process steps of collaborative problem solving · The process of “crowdsourcing” results in useful inputs for scientists in an academic setting (e.g., a research university) for almost all tasks during a scientific inquiry (e.g., identifying qualified partners or analyzing experimental data) The knowledge gathered in the process of developing this dissertation is synthesized in a multi-agent system that simulates a pivotal set of the interactions mentioned above. First tests in academia and start-up companies indicate that the simulator is a useful tool for both scholars and practitioners. Suggestions for future theory building and research are outlined at the end of the dissertation.weiterlesen