Articulation and Sharing of Distributed Design Project and Process Knowledge

The paper reports on the work in the case study of the AC-TIVE project on the use of the combination of knowledge process learning, articulation and sharing technologies for increasing the performance and decreasing the ramp-up efforts in engineering design projects. This knowledge is mined from distributed heterogeneous datasets, fused, and further used for visualizing design project plan information in a way that suggests optimized project plans and fosters collaboration on these knowledge structures in development teams. Software demonstrator architecture, implementation and validation are presented. Validation results indicate that the solution is effective in providing expert assistance to design project managers in performing their typical planning tasks

Social Entrepreneurship and Broader Theories: Shedding New Light on the “Bigger Picture”

This article documents the results of a research workshop bringing together six perspectives on social entrepreneurship. The idea was to challenge existing concepts of the economy, the firm, and entrepreneurship in order to shed new light on social entrepreneurship and on our existing theoretical frameworks. The first two contributions use a macro-perspective and discuss the notion of adaptive societies and the tragedies of disharmonization, respectively. Taking a management perspective, the next two focus on the limits of conventional assumptions in management theory, particularly human capital theory and resource-based view. The final two contributions follow an entrepreneurship perspective highlighting the usefulness of mobilization theory and the business model lens to social entrepreneurship. Despite this diversity, all contributions share the fact that they challenge narrow definitions of the unit of analysis in social entrepreneurship; they illustrate the aspect of social embeddedness, and they argue for an open-but-disciplined diversity of theories in social entrepreneurship research

Innovation Management Techniques and Tools: a review from Theory and Practice

Knowledge is considered to be an economic driver in today’s economy. It has become a commodity, a resource that can be packed and transferred. The objective of this paper is to provide a comprehensive review of the scope, trends and major actors (firms, organizations, government, consultants, academia, etc.) in the development and use of methods to manage innovation in a knowledge-driven economy. The paper identifies the main innovation management techniques (IMTs) aiming at the improvement of firm competitiveness by means of knowledge management. It will specifically focus on those IMTs for which knowledge is a relevant part of the innovation process. The research study, based on a survey at the European level, concludes that a knowledge-driven economy affects the innovation process and approach. The traditional idea that innovation is based on research (technology-push theory) and interaction between firms and other actors has been replaced by the current social network theory of innovation, where knowledge plays a crucial role in fostering innovation. Simultaneously, organizations in both public and private sectors have launched initiatives to develop methodologies and tools to support business innovation management. Higher education establishments, business schools and consulting companies are developing innovative and adequate methodologies and tools, while public authorities are designing and setting up education and training schemes aimed at disseminating best practices among all kinds of businesse

Limits on νμ(νˉμ)→ντ(νˉτ)\nu_\mu(\bar{\nu}_\mu)\to\nu_\tau(\bar{\nu}_\tau) and νμ(νˉμ)→νe(νˉe)\nu_\mu(\bar{\nu}_\mu)\to\nu_e(\bar{\nu}_e) Oscillations from a Precision Measurement of Neutrino-Nucleon Neutral Current Interactions

We present limits on $\nu_\mu(\bar{\nu}_\mu)\to\nu_\tau(\bar{\nu}_\tau)$ and $\nu_\mu(\bar{\nu}_\mu)\to\nu_e(\bar{\nu}_e)$ oscillations based on a study of inclusive $\nu N$ interactions performed using the CCFR massive coarse grained detector in the FNAL Tevatron Quadrupole Triplet neutrino beam. The sensitivity to oscillations is from the difference in the longitudinal energy deposition pattern of $\nu_\mu N$ versus $\nu_\tau N$ or $\nu_e N$ charged current interactions. The $\nu_\mu$ energies ranged from 30 to 500 GeV with a mean of 140 GeV. The minimum and maximum $\nu_\mu$ flight lengths are 0.9 km and 1.4 km respectively. For $\nu_\mu\to\nu_\tau$ oscillations, the lowest 90% confidence upper limit in $\sin^22\alpha$ of $2.7\times 10^{-3}$ is obtained at $\Delta m^2\sim50$~eV$^2$. This result is the most stringent limit to date for $25<\Delta m^2<90$ eV$^2$. For $\nu_\mu\to\nu_e$ oscillations, the lowest 90% confidence upper limit in $\sin^22\alpha$ of $1.9\times 10^{-3}$ is obtained at $\Delta m^2\sim350$~eV$^2$. This result is the most stringent limit to date for $250<\Delta m^2<450$ eV$^2$, and also excludes at 90% confidence much of the high $\Delta m^2$ region favored by the recent LSND observation.Comment: Revised version contains limit on $\nu_\mu\to\nu_e$ oscillations as well as limit on $\nu_\mu\to\nu_\tau$ oscillations found in original. 15 pages, ReVTeX, 3 figures in uuencoded file, submitted to PR