859 resultados para CASE-Technology


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Developed and developing economies alike face increased resource scarcity and competitive rivalry. Science and technology increasingly appear as a main source of competitive and sustainable advantage for nations are regions alike. However, the key determinant of their efficacy is the quality and quantity of entrepreneurship-enabled innovation that unlocks and captures the pecuniary benefits of science enterprise in the form of private, public or hybrid goods (for instance, bio-entrepreneur-millionaires, knowledge for the public good - ie: public health awareness, and new public-private research centers funded partly by bio-entrepreneur-millionaires and monies levied as taxes on bio-ventures).

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Traditional explanations of MNE geographic scope formation fit somewhat uncomfortably with recent empirical and theoretical work in IB that suggests (1) that wholesale (not just gradual) changes in MNE geographic scope may be more frequent than previously thought, and (2) that managers’ responses to a world increasingly characterized by random, unpredictable change are more experimental and less optimizing in nature than assumed in most models of international expansion. In this paper we draw from studies portraying industries as dynamic networks, and from the literature on managerial cognition to provide a complementary explanation of the evolution of MNE geographic scope that reconciles the insights of traditional IB models with the questions raised by more recent studies in this field. We illustrate the proposed model through a detailed account of the internationalization process of Telefonica, the Spanish telecommunications company.

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This study aims to provide independent and in-depth insights into how IT professionals move from one region to another within Europe and beyond. This study was carried out by Mikkel Barslund, Research Fellow, and Matthias Busse, Researcher in the Economic Policy research unit at CEPS. The work was commissioned by the business networking website LinkedIn, whose data analysts kindly provided the data used in this study, aggregated by region and in relative and anonymised terms. The authors are solely responsible for the findings and opinions expressed in this study. CEPS is an independent policy research institute in Brussels, whose mission is to produce sound policy research leading to constructive solutions to the challenges facing Europe today. The views expressed in this study are solely those of the authors and should not be attributed to CEPS or to any other institution with which they are associated or to the business networking website LinkedIn.

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This paper discusses the environment around universities in Russia and possible approaches to analyzing and choosing the method for applied research results commercialization as well as selecting promising applied research areas in that environment. Conceptual foundations for decision making during the commercialization and roadmap/action plan creation processes are outlined. These can be useful to both universities for planning their activities aswell as for organizations that plan to cooperate with universities or that are interested in university generated research. This being said, obtained models and used evaluation parameters may be unique and may depend upon the particular project, university, region, and personal preferences of decision makers. Thus, consideration of these parameters and characteristics only has merit when making decisions in the dynamics of change of these parameters. For this purpose statistical information is needed that characterizes the competencies of the research organization (university) inquestion, needs of partner organizations, governmental and societal requirements, and science and technology prospects. After determining the promising research areas it’s time to look at particular projects, which in turn are also characterized by various parameters dependent upon their objectives. Considering the values of these parameters in their dynamics allows control of project parameters in the course of its execution. This in turn allows prediction of negative situations and alleviation of such by setting the target values of parameters and using best practices and standardization of management processes to achieve those values.

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"September 1998."

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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"HRDS-06/10-05(1M)E"--P. [4] of cover.

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Mode of access: Internet.

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Includes bibliographical references (p. 10-11).

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Thesis (Master's)--University of Washington, 2016-06

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In China, protected areas are one of the main destinations attracting tourists and homeland for many poor people living in and around them. Based on a case study, the paper focuses on correlation between tourism and poverty alleviation by tracing the cash flows to the local poor. It also reviews the social and environmental effects of tourism on local area. The case study is conducted in a group of protected areas in Qinling Mountain Region in Shaanxi, a western province in China. Qinling Mountain is one of the most important distribution zones for Giant Panda and some other endangered wildlife such as Golden Takin and Golden Monkey. The tourism development in the region is happening. Research indicates that there is 29.33%, of tourist expenditure is going to local households, directly or indirectly. Tourist spends US$7.11 (13.67%) in food and beverage, and US$6.39 (12.23%) in accommodation service, which are the greatest contributors to local households in terms of tourism benefits. Local households can get US$8.15 from food/beverage and accommodation sectors, taking 56.64% of total income from tourism. Generally, tourism development benefits all stakeholders. However, poor people get less benefit. The paper analyses the barriers for the poor to be involved in tourism development, and discusses the government roles, major issues in implementation of Sustainable Tourism-Eliminating Poverty (ST-EP) model. [ABSTRACT FROM AUTHOR]