870 resultados para international new ventures
Resumo:
As the field of international business has matured, there have been shifts in the core unit of analysis. First, there was analysis at country level, using national statistics on trade and foreign direct investment (FDI). Next, the focus shifted to the multinational enterprise (MNE) and the parent’s firm specific advantages (FSAs). Eventually the MNE was analysed as a network and the subsidiary became a unit of analysis. We untangle the last fifty years of international business theory using a classification by these three units of analysis. This is the country-specific advantage (CSA) and firm-specific advantage (FSA) matrix. Will this integrative framework continue to be useful in the future? We demonstrate that this is likely as the CSA/FSA matrix permits integration of potentially useful alternative units of analysis, including the broad region of the triad. Looking forward, we develop a new framework, visualized in two matrices, to show how distance really matters and how FSAs function in international business. Key to this are the concepts of compounded distance and resource recombination barriers facing MNEs when operating across national borders.
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Aircraft Maintenance, Repair and Overhaul (MRO) agencies rely largely on row-data based quotation systems to select the best suppliers for the customers (airlines). The data quantity and quality becomes a key issue to determining the success of an MRO job, since we need to ensure we achieve cost and quality benchmarks. This paper introduces a data mining approach to create an MRO quotation system that enhances the data quantity and data quality, and enables significantly more precise MRO job quotations. Regular Expression was utilized to analyse descriptive textual feedback (i.e. engineer’s reports) in order to extract more referable highly normalised data for job quotation. A text mining based key influencer analysis function enables the user to proactively select sub-parts, defects and possible solutions to make queries more accurate. Implementation results show that system data would improve cost quotation in 40% of MRO jobs, would reduce service cost without causing a drop in service quality.
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Nicholas Alexander's (2011. British overseas retailing, 1900–60: International firm characteristics, market selections and entry modes. Business History, 53, 530–556) survey of British overseas retailers from 1900 to 1960 provides pathbreaking new evidence of international retailing activity during the first globalisation boom. The article surveys this and other recent evidence, and confirms that international retailing was far more significant up to 1929 than previously thought. This activity was overwhelmingly undertaken by non-retailers, however, and hence by multinationals whose advantages in retailing were fundamentally unsustainable over the long run. Even the department store format, the principal retail innovation of the period, was not internationalised primarily by multinationals. Rather it was diffused via indigenous entrepreneurs, driven by a rapidly growing global demand for western style fashion and dress.
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Structural, organizational, and technological changes in British industry during the interwar years led to a decline in skilled and physically demanding work, while there was a dramatic expansion in unskilled and semiskilled employment. Previous authors have noted that the new un/semiskilled jobs were generally filled by “fresh” workers recruited from outside the core manufacturing workforce, though there is considerable disagreement regarding the composition of this new workforce. This paper examines labour recruitment patterns and strategies using national data and case studies of eight rapidly expanding industrial centres. The new industrial workforce is shown to have been recruited from a “reserve army” of workers with the common features of relative cheapness, flexibility, and weak unionization. These included women, juveniles, local workers in poorly paid nonindustrial sectors, such as agriculture, and (where these other categories were in short supply) relatively young long-distance internal migrants from declining industrial areas.
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This paper proposes a way of addressing unresolved issues in international business theory by modelling the multinational enterprise as a coordinator of supply chains. It identifies a new market seeking strategy that is an alternative to conventional strategies such as exporting, licensing and FDI, and analyses the conditions under which it will be adopted by firms. The new strategy involves the off-shoring of production and the out-sourcing of R&D, and is implemented through co-operation between a source country firm and a host country firm.
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Government targets for CO2 reductions are being progressively tightened, the Climate Change Act set the UK target as an 80% reduction by 2050 on 1990 figures. The residential sector accounts for about 30% of emissions. This paper discusses current modelling techniques in the residential sector: principally top-down and bottom-up. Top-down models work on a macro-economic basis and can be used to consider large scale economic changes; bottom-up models are detail rich to model technological changes. Bottom-up models demonstrate what is technically possible. However, there are differences between the technical potential and what is likely given the limited economic rationality of the typical householder. This paper recommends research to better understand individuals’ behaviour. Such research needs to include actual choices, stated preferences and opinion research to allow a detailed understanding of the individual end user. This increased understanding can then be used in an agent based model (ABM). In an ABM, agents are used to model real world actors and can be given a rule set intended to emulate the actions and behaviours of real people. This can help in understanding how new technologies diffuse. In this way a degree of micro-economic realism can be added to domestic carbon modelling. Such a model should then be of use for both forward projections of CO2 and to analyse the cost effectiveness of various policy measures.
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Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.
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This is a special issue of the International Journal of Bilingualism. This special issue brings together approaches to transfer in L2 learners, bilinguals, multilinguals and attriters. Researchers working in SLA are often unaware of research done on transfer in bilinguals and vice versa, and this special issue bridges important gaps between researchers from a range of fields.