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Life cycle costing methodology for sustainable commerical office buildings

机译:可持续商业办公楼的生命周期成本核算方法

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摘要

The need for a more authoritative approach to investment decision-making and cost control has been a requirement of office spending for many years now. The commercial offices find itself in an increasingly demanding position to allocate its budgets as wisely and prudently as possible. The significant percentage of total spending on buildings demands a more accurate and adaptable method of achieving quality of service within the constraints on the budgets. By adoption of life cycle costing techniques with risk management, practitioners have the ability to make accurate forecasts of likely future running costs. udThis thesis presents a novel framework (Artificial Neural Networks and probabilistic simulations) for modelling of operating and maintenance historical costs as well as economic performance measures of LCC. The methodology consisted of eight steps and presented a novel approach to modelling the LCC of operating and maintenance costs of two sustainable commercial office buildings. Finally, a set of performance measurement indicators were utilised to draw inference from these results.udTherefore, the contribution that this research aimed to achieve was to develop a dynamic LCC framework for sustainable commercial office buildings, and by means of two existing buildings, demonstrate how assumption modelling can be utilised within a probabilistic environment.udIn this research, the key themes of risk assessment, probabilistic assumption modelling and stochastic assessment of LCC has been addressed. Significant improvements in existing LCC models have been achieved in this research in an attempt to make the LCC model more accurate and meaningful to estate managers and high-level capital investment decision makersudA new approach to modelling historical costs and forecasting these costs in sustainable commercial office buildings is presented based upon a combination of ANN methods and stochastic modelling of the annual forecasted data. These models provide a far more accurate representation of long-term building costs as the inherent risk associated with the forecasts is easily quantifiable and the forecasts are based on a sounder approach to forecasting than what was previously used in the commercial sector.udA novel framework for modelling the facilities management costs in two sustainable commercial office buildings is also presented. This is not only useful for modelling the LCC of existing commercial office buildings as presented here, but has wider implications for modelling LCC in competing option modelling in commercial office buildings. udThe processes of assumption modelling presented in this work can be modified easily to represent other types of commercial office buildings. Discussions with policy makers in the real estate industry revealed that concerns were held over how these building costs can be modelled given that available historical data represents wide spending and are not cost specific to commercial office buildings. udSimilarly, a pilot and main survey questionnaire was aimed at ascertaining current level of LCC application in sustainable construction; ranking drivers and barriers of sustainable commercial office buildings and determining the applications and limitations of LCC. ududThe survey result showed that respondents strongly agreed that key performance indicators and economic performance measures need to be incorporated into LCC and that it is important to consider the initial, operating and maintenance costs of building when conducting LCC analysis, respondents disagreed that the current LCC techniques are suitable for calculating the whole costs of buildings but agreed that there is a low accuracy of historical cost data.
机译:多年来,办公室投资一直需要一种更具权威性的投资决策和成本控制方法。商业办公室发现自己的要求越来越高,需要尽可能明智和谨慎地分配预算。建筑物总支出的很大一部分要求在预算限制内采用更准确和适应性更高的方法来获得服务质量。通过将生命周期成本核算技术与风险管理一起采用,从业人员可以对未来可能的运营成本做出准确的预测。 ud本文提出了一个新颖的框架(人工神经网络和概率模拟),用于对LCC的运营和维护历史成本以及经济绩效指标进行建模。该方法包括八个步骤,并提出了一种新颖的方法来对两座可持续商业办公楼的运营成本和维护成本进行LCC建模。最后,使用一组性能测量指标从这些结果中得出推论。 ud因此,本研究旨在实现的贡献是为可持续的商业办公建筑开发了动态LCC框架,并借助两座现有建筑进行了演示。在本研究中,LCC的风险评估,概率假设建模和随机评估的关键主题已得到解决。本研究已对现有LCC模型进行了重大改进,以期使LCC模型对房地产经理和高层资本投资决策者更准确和更有意义 ud一种用于模拟历史成本并预测可持续商业成本的新方法基于ANN方法和年度预测数据的随机建模的组合,展示了办公楼。这些模型提供了长期建筑成本的更准确的表示,因为与预测相关的固有风险可以轻松量化,并且预测基于比以前在商业领域中使用的更合理的预测方法。还介绍了用于建模的两座可持续商业办公楼的设施管理成本。这不仅对此处介绍的现有商业办公楼的LCC建模有用,而且对于在商业办公楼的竞争性期权建模中对LCC建模具有更广泛的意义。 ud可以轻松修改此工作中提出的假设建模过程,以表示其他类型的商业办公楼。与房地产行业决策者的讨论表明,鉴于可用的历史数据代表了广泛的支出,而不是针对商业办公楼的特定成本,因此人们对如何模拟这些建筑成本感到担忧。 ud同样,试点和主要调查问卷旨在确定LCC在可持续建设中的应用水平。对可持续商业办公楼的驱动因素和障碍进行排名,并确定LCC的应用和局限性。 ud ud调查结果表明,受访者强烈同意关键绩效指标和经济绩效指标必须纳入LCC,并且在进行LCC分析时必须考虑建筑物的初始,运营和维护成本,因此受访者不同意当前的LCC技术适用于计算建筑物的整体成本,但同意历史成本数据的准确性较低。

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