7 research outputs found

    Modeling 21st century project teams: docking workflow and knowledge network computational models

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    This paper reports on an attempt to integrate and extend two established computational organizational models\u2014SimVision\uae and Blanche\u2014to examine the co-evolution of workflow and knowledge networks in 21st century project teams. Traditionally, workflow in project teams has been modeled as sets of sequential and/or parallel activities each assigned to a responsible participant, organized in a fixed structure. In the spirit of Jay Galbraith\u2019s (1973) information processing view of organizations, exceptions\u2014situations in which participants lack the required knowledge to complete a task\u2014are referred up the hierarchy for resolution. However, recent developments in digital technologies have created the possibility to design project teams that are more flexible, self-organizing structures, in which exceptions can be resolved much more flexibly through knowledge networks that extend beyond the project or even the company boundaries. In addition to seeking resolution to exceptions up the hierarchy, members of project teams may be motivated to retrieve the necessary expertise from other knowledgeable members in the project team. Further, they may also retrieve information from non-human agents, such as knowledge repositories or databases, available to the project team. Theories, such as Transactive Memory, Public Goods, Social Exchange and Proximity may guide their choice of retrieving information from a specific project team member or database. This paper reports on a \u201cdocked\u201d computational model that can be used to generate and test hypotheses about the co-evolution of workflow and knowledge networks of these 21st century project teams in terms of their knowledge distribution and performance. The two computational models being docked are SimVision (Jin & Levitt, 1999) which has sophisticated processes to model organizations executing project-oriented workflows, and Blanche (Hyatt, Contractor, & Jones, 1997), a multiagent computational network environment, which models multitheoretical mechanisms for the retrieval and allocation of information in knowledge networks involving human and non-human agents. This paper was supported in part by a grant from the U.S. National Science Foundation for the project \u201cCo-Evolution of Knowledge Networks and 21st Century Organizational Forms (IIS- 9980109)

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Made to Fit: How Practices Vary As They Diffuse

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    We extend research on the diffusion of corporate practices by providing a framework for studying practice variation during diffusion processes. Specifically, we theorize about how population-level mechanisms of diffusion link with organization-level mechanisms of implementation that lead to the adaptation of practices. We also identify technical, cultural, and political elements of fit (or misfit) between diffusing practices and adopters and analyze how the process of attaining fit across these elements can trigger different patterns of adaptation
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