204 resultados para Market segmentation


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The seminal work of J. B. Jefferys highlighted two unusual features of the Victorian equity market, namely high share denomination and uncalled capital. This article examines the extent to which publicly traded company stocks in the nineteenth century had these features. It also analyses the effect of these features on stock returns using monthly data for the London Stock Market over the period 1825–70. We find that stocks with unpaid capital earned a higher return, which is consistent with investors being rewarded for the risk of a call on their personal assets. We also find that stocks with a high share denomination earned a lower return, which is consistent with the view that this feature was conducive to superior corporate governance.

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This article examines the nature of labour market exclusion in Belfast and policy responses to the dilemmas of ethnic space. It highlights the value of an area-based approach to understanding the way in which social and ethno-sectarian segregation mediates access to production sites and job opportunities in the wider urban economy. Research from the Belfast metropolitan labour market is used to identify the importance of employment in neutral areas, which can stimulate access from ethnically and socially polarised communities. The article argues for a spatial approach to understanding the structuring of labour market opportunities and constraints and it concludes by highlighting the implications for policy and practice in ethnically territorialised spaces.

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Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.

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This article examines the impact of pension deficits on default risk as measured by the premia on corporate credit default swaps (CDS). We find highly significant evidence that unfunded pension liabilities raise one- and five-year CDS premia. However, this relation is not homogeneous across countries, with the U.S. CDS market leading its European counterparts in the pricing of defined-benefit pension risk.

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In late 2008, the Government of the Republic of Ireland set a specific target that 10% of all vehicles in its transport fleet be powered by electricity by 2020 in order to meet European Union renewable energy targets and greenhouse gas emissions reduction targets. International there are similar targets. This is a considerable challenge as in 2009, transport accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the impacts of 10% electric vehicle charging on the single wholesale electricity market for the Republic of Ireland and Northern Ireland is examined. The energy consumed and the total carbon dioxide emissions generated under different charging scenarios is quantified and the results of the charging scenarios are compared to identify the best implementation strategy.

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To meet European Union renewable energy and greenhouse gas emissions reduction targets the Irish government set a target in 2008 that 10% of all vehicles in the transport fleet be powered by electricity by 2020. Similar electric vehicle targets have been introduced in other countries. However, reducing energy consumption and decreasing greenhouse gas emissions in transport is a considerable challenge due to heavy reliance on fossil fuels. In fact, transport in the Republic of Ireland in 2009 accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the effect of electric vehicle charging on the operation of the single wholesale electricity market for the Republic of Ireland and Northern Ireland is analysed. The energy consumed, greenhouse gas emissions generated and changes to the wholesale price of electricity under peak and off-peak charging scenarios are quantified and discussed. Results from the study show that off-peak charging is more beneficial than peak charging.

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The application of the contingent valuation method (CVM) in this paper incorporates a prior preference ordering of several alternative future afforestation programmes which could be implemented in Ireland over the next decade. This particular experimental design is thereby shown to reveal the potentially conflicting preferences of different groups within society. These findings are used to devise appropriate CVM scenarios to take account, not only of the efficiency gains of choosing a single policy alternative over others, but also the effects on the distribution of non market benefit between different groups within society, arising from choice between alternatives. (C) 1998 Elsevier Science Ltd. All rights reserved.