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Primary Advantage (primary + advantage)

Distribution by Scientific Domains

Medical Sciences	50%
Business, Economics, Finance and Accounting	50%

Selected Abstracts

A Knowledge Accessing Theory of Strategic Alliances

JOURNAL OF MANAGEMENT STUDIES, Issue 1 2004
Robert M. Grant
ABSTRACT The emerging knowledge-based view of the firm offers new insight into the causes and management of interfirm alliances. However, the development of an effective knowledge-based theory of alliance formation has been inhibited by a simplistic view of alliances as vehicles for organizational learning in which strategic alliances have presumed to be motivated by firms' desire to acquire knowledge from one another. We argue that the primary advantage of alliances over both firms and markets is in accessing rather than acquiring knowledge. Building upon the distinction between the knowledge generation (,exploration') and knowledge application (,exploitation'), we show that alliances contribute to the efficiency in the application of knowledge; first, by improving the efficiency with which knowledge is integrated into the production of complex goods and services, and second, by increasing the efficiency with which knowledge is utilized. These static efficiency advantages of alliances are enhanced where there is uncertainty over future knowledge requirements and where new products offer early-mover advantages. Compared with alternative learning-based approaches to alliance formation, our proposed knowledge-accessing theory of alliances offers the advantages of greater theoretical rigour and consistency with general trends in alliance activity and corporate strategy. [source]

Real-time adaptive sequential design for optimal acquisition of arterial spin labeling MRI data

MAGNETIC RESONANCE IN MEDICINE, Issue 1 2010
Jingyi Xie
Abstract An optimal sampling schedule strategy based on the Fisher information matrix and the D-optimality criterion has previously been proposed as a formal framework for optimizing inversion time scheduling for multi-inversion-time arterial spin labeling experiments. Optimal sampling schedule possesses the primary advantage of improving parameter estimation precision but requires a priori estimation of plausible parameter distributions that may not be available in all situations. An adaptive sequential design approach addresses this issue by incorporating the optimal sampling schedule strategy into an adaptive process that iteratively updates the parameter estimates and adjusts the optimal sampling schedule accordingly as data are acquired. In this study, the adaptive sequential design method was experimentally implemented with a real-time feedback scheme on a clinical MRI scanner and was tested in six normal volunteers. Adapted schedules were found to accommodate the intrinsically prolonged arterial transit times in the occipital lobe of the brain. Simulation of applying the adaptive sequential design approach on subjects with pathologically reduced perfusion was also implemented. Simulation results show that the adaptive sequential design approach is capable of incorporating pathologic parameter information into an optimal arterial spin labeling scheduling design within a clinically useful experimental time. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc. [source]

Efficient Universal Portfolios for Past-Dependent Target Classes

MATHEMATICAL FINANCE, Issue 2 2003
Jason E. Cross
We present a new universal portfolio algorithm that achieves almost the same level of wealth as could be achieved by knowing stock prices ahead of time. Specifically the algorithm tracks the best in hindsight wealth achievable within target classes of linearly parameterized portfolio sequences. The target classes considered are more general than the standard constant rebalanced portfolio class and permit portfolio sequences to exhibit a continuous form of dependence on past prices or other side information. A primary advantage of the algorithm is that it is easily computable in a polynomial number of steps by way of simple closed-form expressions. This provides an edge over other universal algorithms that require both an exponential number of computations and numerical approximation. [source]

Fluorescence In Situ Hybridization (FISH) in Diagnostic and Investigative Neuropathology

BRAIN PATHOLOGY, Issue 1 2002
Christine E. Fuller MD;
Over the last decade, fluorescence in situ hybridization (FISH) has emerged as a powerful clinical and research tool for the assessment of target DNA dosages within interphase nuclei. Detectable alterations include aneusomies, deletions, gene amplifications, and translocations, with primary advantages to the pathologist including its basis in morphology, its applicability to archival, formalin-fixed paraffin-embedded (FFPE) material, and its similarities to immunohistochemistry. Recent technical advances such as improved hybridization protocols, markedly expanded probe availability resulting from the human genome sequencing initiative, and the advent of high-throughput assays such as gene chip and tissue microarrays have greatly enhanced the applicability of FISH. In our lab, we currently utilize only a limited battery of DNA probes for routine diagnostic purposes, with determination of chromosome 1p and 19q dosage in oligodendroglial neoplasms representing the most common application. However, research applications are numerous and will likely translate into a growing list of clinically useful markers in the near future. In this review, we highlight the advantages and disadvantages of FISH and familiarize the reader with current applications in diagnostic and investigative neuropathology. [source]