958 resultados para Advantage
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"September 1997."
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Bibliography: leaf 12.
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Goldsmiths'-Kress no. 22556.
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Vol. 2 has title: England's improvement by sea and land. The second part : Containing, I. An account of its scituation, and the growths, and manufactures thereof. II. The benefit and necessity of a voluntary-register. III. A method for improving the Royal-navy, lessening the growing power of France, and obtaining the fishery. IV. Advantageous proposals for the city of London, for the preventing of fires therein; and for lessening the great charge of the trained bands. V. The way to make New-Haven in Sussex, fit to receive ships of burthen. VI. Seasonable discourses of the tin, iron, linnen, and woollen trades; with advantageous proposals for improving them all : Illustrated with seven large copper-plates / By Andrew Yarranton, gent. London : Printed, to be sold by Tho. Parkhurst ..., 1698.
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During the last few decades, identifying and examining the characteristics of market-driven firms have been a dominant theme in strategic marketing research. It has been argued that market-driven firms are superior in their market sensing and customer linking capabilities, enabling market-driven firms to outperform their competitors. This paper reports the findings of a study that examines the role market-focused learning capability and marketing capability in innovation-based competitive strategy on sustainable competitive advantage. The findings indicate that entrepreneurship is an important factor in sustained competitive advantage (SCA) and while market-focused learning capability leads to higher degrees of innovation, marketing capability enables SCA. (C) 2003 Elsevier Inc. All rights reserved.
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Resource-based views of the firm and in particular Kay's (Why Firms Succeed. Oxford: Oxford Univ. Press, 1995) model of sustainable competitive advantage have been used to advance an understanding of differences in the competitive advantage of private-sector firms. We extend the analysis to a public-sector firm where its major purpose includes engaging in public good by giving away its knowledge base and services. The case highlights the paradox that many public-sector organizations face in simultaneously pursuing public good and sustainable competitive advantage. While Kay's model is applicable for understanding intergovernmental agency competition, we find it necessary to incorporate resource dependency theory to address the paradox. Implications for theory and practice are provided. (C) 2002 Elsevier Inc. All rights reseved.
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An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.