886 resultados para Heterogeneous firms trade model
Resumo:
The present study aims to validate the current best-practice model of implementation effectiveness in small and mid-size businesses. Data from 135 organizations largely confirm the original model across various types of innovation. In addition, we extended this work by highlighting the importance of human resources in implementation effectiveness and the consequences of innovation effectiveness on future adoption attitudes. We found that the availability of skilled employees was positively related to implementation effectiveness. Furthermore, organizations that perceived a high level of benefits from implemented innovations were likely to have a positive attitude towards future innovation adoption. The implications of our improvements to the original model of implementation effectiveness are discussed.
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With the growing significance of services in most developed economies, there is an increased interest in the role of service innovation in service firm competitive strategy. Despite growing literature on service innovation, it remains fragmented reflecting the need for a model that captures key antecedents driving the service innovation-based competitive advantage process. Building on extant literature and using thirteen in-depth interviews with CEOs of project-oriented service firms, this paper presents a model of innovation-based competitive advantage. The emergent model suggests that entrepreneurial service firms pursuing innovation carefully select and use dynamic capabilities that enable them to achieve greater innovation and sustained competitive advantage. Our findings indicate that firms purposefully use create, extend and modify processes to build and nurture key dynamic capabilities. The paper presents a set of theoretical propositions to guide future research. Implications for theory and practice are discussed. Finally, directions for future research are outlined.
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Discovering factors that help or impede business model change is an important quest, both for researchers and practitioners. In this study we present preliminary findings based on the CAUSEE survey of young and nascent firms in Australia. In particular, we seek to determine an association between business model adaptation and external orientation among young and nascent firms within the random sample and amongst an oversample of high potential firms. The concept of external orientation is made operational by asking respondents whether, and to what extent, they rely on certain sources of advice and information. We find that high potential firms are more likely to have made at least some change to their business model, that greater use of external sources of advice is generally significantly associated with business model adaptation, but also that there appear to be different patterns of behaviour between the random sample and the over sample.
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This research was a step forward in developing a data integration framework for Electronic Health Records. The outcome of the research is a conceptual and logical Data Warehousing model for integrating Cardiac Surgery electronic data records. This thesis investigated the main obstacles for the healthcare data integration and proposes a data warehousing model suitable for integrating fragmented data in a Cardiac Surgery Unit.
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A holistic consideration of innovation and associated activities is still very new to consulting engineering firms. This research will have benefits for both industry and academia. The final outcome of this research is a prioritised decision making innovation model that can be used by consulting engineering firms to make informed decisions by investing in appropriate innovation activities that positively impact project performance. This helps by using an informed approach towards investing rather than 'hit-and-miss' trialling.
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A model for heterogeneous acetalisation of poly(vinyl alcohol) with limited solution volume is proposed based on the grain model of Sohn and Szekely. Instead of treating the heterogeneous acetalisation as purely a diffusion process, as in the Matuzawa and Ogasawara model, the present model also takes into account the chemical reaction and the physical state of the solid polymer, such as degree of swelling and porosity, and assumes segregation of the polymer phase at higher conversion into an outer fully reacted zone and an inner zone where the reaction still proceeds. The solution of the model for limited solution volume, moreover, offers a simple method of determining the kinetic parameters and diffusivity for the solid-liquid system using the easily measurable bulk solution concentration of the liquid reactant instead of conversion-distance data for the solid phase, which are considerably more difficult to obtain.
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Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.
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Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving clock speed, reducing energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires which leads to delay in execution and significantly high energy consumption.In this paper, we propose a new instruction scheduling algorithm that exploits scheduling slacks of instructions and communication slacks of data values together to achieve better energy-performance trade-offs for clustered architectures with heterogeneous interconnect. Our instruction scheduling algorithm achieves 35% and 40% reduction in communication energy, whereas the overall energy-delay product improves by 4.5% and 6.5% respectively for 2 cluster and 4 cluster machines with marginal increase (1.6% and 1.1%) in execution time. Our test bed uses the Trimaran compiler infrastructure.
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Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO(2) emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO(2) emissions via increased electricity use. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
[EN] Based on an extensive theoretical review, the aim of this paper is to carry out a closer examination of the differences between exporters according to their commitment to the international market. Once the main disparities are identified by means of a non-parametric test, a logistic analysis based upon data collected from small and medium sized manufacturing firms is conducted in order to construct a classificatory model.
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The purpose of the paper is to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. We use zero-accounting gravity models to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. The chemical standards on which we focus include chloramphenicol required performance limit, oxytetracycline maximum residue limit, fluoro-quinolones maximum residue limit, and dichlorodiphenyltrichloroethane (DDT) pesticide residue limit. The study focuses on the three most important seafood markets: the European Union’s 15 members, Japan, and North America.