331 resultados para Cost-Informed
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This chapter discusses using phenomenography to study information experience. Phenomenographers aim to investigate people’s experiences of the world around them, which is comprised of the interrelationship between an individual and a phenomenon they are focusing on. Phenomenography has been identified as a research approach suited to the study of information experience. Phenomenographic research investigating experiences of using information in different contexts has led to the development of informed learning, which is an approach to information literacy that emphasizes learning as an outcome of using information. Recent research focusing on information experience has been referred to as informed learning research. The preliminary findings from a current informed learning study illustrate the educative benefits of researching information experience. This study investigates a classroom lesson, in which a teacher outlines an assignment that requires the students to understand a language and gender topic by investigating the evolution of research on the topic. The lesson is experienced in multiple ways by the students and the analysis suggests a way of enhancing the lesson to enable more students to experience it in the way intended by the teacher.
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This study elucidated the shadow price of greenhouse gas (GHG) emissions for 1,024 international companies worldwide that were surveyed from 15 industries in 37 major countries. Our results indicate that the shadow price of GHG at the firm level is much higher than indicated in previous studies. The higher shadow price was found in this study as a result of the use of Scope 3 GHG emissions data. The results of this research indicate that a firm would carry a high cost of GHG emissions if Scope 3 GHG emissions were the focus of the discussion of corporate social responsibility. In addition, such shadow prices were determined to differ substantially among countries, among sectors, and within sectors. Although a number of studies have calculated the shadow price of GHG emissions, these studies have employed country-level or industry-level data or a small sample of firm-level data in one country. This new data from a worldwide firm analysis of the shadow price of GHG emissions can play an important role in developing climate policy and promoting sustainable development.
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This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.
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Japan's fishery harvest peaked in the late 1980s. To limit the race for fish, each fisherman could be provided with specific catch limits in the form of individual transferable quotas (ITQs). The market for ITQs would also help remove the most inefficient fishers. In this article we estimate the potential cost reduction associated with catch limits, and find that about 300 billion yen or about 3 billion dollars could be saved through the allocation and trading of individual-specific catch shares.
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This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.
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Background The aim of this study is to examine the flood fatality with a view to identifying risks which may inform public policy responses to future flood. On July 21st, 2012, Beijing suffered the heaviest rain since 1963. The average rainfall was 215 mm over a 24 hour period in the central city (301mm in Fangshan District). The rain resulted in a flood that caused severe health, social and financial impact. Results This flood caused 79 deaths. Of the 71 deaths for which a specific cause could be identified, 5 were rescue team members, 42 were killed by drowning (11 in the car), and the others by electricity shock, fallen house, falling items and lightning. The total financial cost was estimated to be US$ 1.7 billion. The causations of the deaths inform the risks associated with the flood. Discussion This flood had a catastrophic impact on Beijing, mainly due to the intensity of the rain (the rain was the heaviest in the modern Beijing history; possibly due to global warming and urban heat island effect), the vulnerability of the infrastructure (poor standards of drainage, disorganized water management systems and decreased permeability of the earth as a result of the city’s rapid development), and the capacity of the response system (mainly dependent on the awareness of the citizens, warning systems and the capacity of the emergency rescue). Implication Many risk management measures have been implemented as a result of this flood, including water level warning marks, flood safety education and warnings sent to mobile phones, a project to move about 74,500 farmers away from the flood-prone areas within 5 years. However, further measures targeted at the fundamental issues identified by this analysis are necessary, especially those targeting at health issues. These may include better planning, improved drainage systems and ecological development to increase permeability etc..
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Australian households currently pay the second highest “honesty tax” in the world at $290 per household per year, levied by retailers to offset the $AU1.86 billion in losses they incur from customer theft. Theft is only one type of consumer deviance, which can include behaviours that are against the law, an organisation’s policy, or behaviours that violate normally accepted conduct. An individual’s “deviant behaviour” can vary from one person to the next. My research exploring consumer definitions of right and wrong has found a number of things can inform what an individual thinks is “deviant behaviour”, beyond what the law or organisational policy states as right or wrong. Consumers then use their own justifications to excuse their actions...
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The overarching research work is based on two approaches: - Conceptual Analysis, Extraction and Linking - Experimentation with Product Libraries - Conceptual Analysis, Extraction and Linking: This aspect of the research has been achieved through the development of a conceptual framework for facilitating the understanding of the constituting components of BIM, Specifications and Cost Planning under investigation. The framework builds on theories spanning the constituent research themes and was used as a basis for justifying the elected approaches adopted throughout the research work. By means of tags and codes, a system for classifying building specification information has been developed as a differentiator between the chosen research approach and existing classification strategies in industry. Furthermore, syntactic links between extracted classes of specification information and cost planning have been established and will be adopted as a basis for authenticating the impact of specification information within BIM models. - Experimentation with Product Libraries Following the extraction and classification of BIM, Specifications and Cost Planning information, early experimentation on linking specifications to BIM models by means of a raas-based product library have been successful. A comparative analysis between a range of existing product libraries has also been realised. The outcomes have been amply documented in papers, all of which have received positive reviews. Ongoing experiments and analysis with the product library involve integrating the cost planning component for authenticating the completeness, relevance and impact of embedded specification within BIM models.
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This digital poster (which was on display at "The Cube", Queensland University of Technology) demonstrates how specification parameters can be extracted from a product library repository for use in augmenting the information contents of the objects in a local BIM tool (Revit in this instance).
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Many intervention programs have been designed to decrease the rate of drink driving by altering the behavioural characteristics that may lead a person to drink and drive. However, most programs target high risk and repeat offenders. There is very little research on the feasibility and effectiveness of first offender programs. This project is part of a larger program of research that focuses on first time offenders, in order to reduce the rate of subsequent drink driving which may result in a repeat offence. A number of professional stakeholders were approached and interviewed with a view to capturing and reflecting current drink driving related concerns while developing an intervention in the context of Australian drink driving related legislation. The qualitative interviews involved open ended questioning which led to the themes discussed in the analysis. Included in the interviews were senior representatives from the Magistrates Court, Queensland Transport, Probation & Parole, Queensland Corrective Services, Royal Automobile Club Queensland (RACQ), Intraface Consulting (drug & alcohol EAP), Brisbane Police Prosecution Corps, Queensland Police Service and private practice psychology. Issues such as delivery of interventions, feasibility and cost-effectiveness were discussed, as were potential content and design. It was generally agreed that a tailored online intervention imposed as a sentencing option would be the most effective for first time offenders in terms of cost, ease of delivery and feasibility. The development of an online intervention program for first offenders is widely supported by professional stakeholders.
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A recurring feature of modern practice is the stress placed on project professionals, with both debilitating effects on the people concerned and indirectly affecting project success. Cost estimation, for example, is an essential task for successful project management involving a high level of uncertainty. It is not surprising, therefore, that young cost estimators especially can become stressful at work due to a lack of experience and the heavy responsibilities involved. However, the concept of work stress and the associated underlying dimensions has not been clearly defined in extant studies in the construction management field. To redress this situation, an updated psychology perceived stress questionnaire (PSQ) , first developed by Levenstein et al (1993) and revised by Fliege et al (2005), is used to explore the dimensions of work stress with empirical evidence from the construction industry in China. With 145 reliable responses from young (less than 5 years’ experience) Chinese cost estimators, this study explores the internal dimensions of work stress, identifying four dimensions of tension, demands, lack of joy and worries. It is suggested that this four-dimensional structure may also be applicable in a more general context.
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Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables.