969 resultados para construction-specific indices


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The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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This paper explores the use of purchasing power parity (PPP) in the comparison of construction costs between different countries, and whether the development of construction-specific indices will improve reliability.

The approach adopted is to compare the construction cost of a typical five star international hotel per square metre in each of ten major cities using a range of PPP methods and to comment on their variability. In particular, this paper looks at whether an index based on the price of a McDonalds Big Mac3 hamburger is a viable alternative when compared against the mainstream methods. The recent publication of construction-specific indices as part of the Eurostat-OECD joint PPP program is also compared against generic indices and the discrepancy is calculated.

The paper concludes with reflections about which approach is preferable when attempting to assess global construction relativities and what further research is needed.

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While there have been many attempts at comparisons of construction performance over the past 50 years, the results have generally been inconclusive and/or contradictory.

Such comparisons are of great interest to industry, governments and theorists alike but there is little agreement as to how they are best done. A variety of methodologies have been used, however, the lack of satisfactory outcomes has been due largely to one factor, the lack of a truly reliable method for comparing construction costs in different currencies

Exchange rates are recognised as being unsuitable, and while purchasing power parity (PPP) has a long history, the method still has many critics. In addition, the nature of the building industry and its products makes the establishment of reliable construction PPPs very difficult. Both the UN’s International Comparison Program (ICP) and the European Union gather data for the production of construction-specific PPP indices, but neither body publishes them, as there is too much doubt about their reliability.

New approaches are being developed and some are soon to be trialled. This paper looks at the problems, describes and discusses some new approaches, and assesses their potential.

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Purpose: To provide recommendations for construction clients who design and implement financial incentive mechanisms (FIMs) on projects. ---------- Methodology: Four large Australian building projects commissioned by government clients under managing contractor contracts and completed between 2001 and 2005 were examined to explore the ‘drivers’ that promoted motivation toward financial incentive goals. The results were triangulated across data sources, projects and stakeholder types. ---------- Findings: FIM design should incorporate: 1. flexibility to modify goals and measurement procedures over time, 2. multiple goals covering different project areas, 3. distribution of rewards across all the key organizations contributing to team performance (e.g. potentially not just the contractor, but the subcontractors and consultants) and a reward amount sufficient to be valued by potential recipients. FIM benefits are maximized through the following complementary procurement initiatives: 4. equitable contract risk allocation, 5. early contractor involvement in design, 6. value-driven tender selection, 7. relationship workshops, and 8. future work opportunities.---------- Research Limitations: This paper provides practical recommendations to industry and hence does not emphasize theoretical aspects.---------- Practical Implications: The uptake of these recommendations is likely to increase the impact of FIMs on motivation and improve project and industry outcomes. Although the study focuses on government clients of building projects, all the recommendations would seem to apply equally to private-sector clients and to non-building projects.---------- Originality: In order to improve motivation and reward high performance, clients are increasingly using FIM in their construction contracts. Despite the rising use of financial incentives, there is a lack of comprehensive construction-specific knowledge available to help clients maximize outcomes. The study addresses this gap in the literature.

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A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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Building information modeling (BIM) is an emerging technology and process that provides rich and intelligent design information models of a facility, enabling enhanced communication, coordination, analysis, and quality control throughout all phases of a building project. Although there are many documented benefits of BIM for construction, identifying essential construction-specific information out of a BIM in an efficient and meaningful way is still a challenging task. This paper presents a framework that combines feature-based modeling and query processing to leverage BIM for construction. The feature-based modeling representation implemented enriches a BIM by representing construction-specific design features relevant to different construction management (CM) functions. The query processing implemented allows for increased flexibility to specify queries and rapidly generate the desired view from a given BIM according to the varied requirements of a specific practitioner or domain. Central to the framework is the formalization of construction domain knowledge in the form of a feature ontology and query specifications. The implementation of our framework enables the automatic extraction and querying of a wide-range of design conditions that are relevant to construction practitioners. The validation studies conducted demonstrate that our approach is significantly more effective than existing solutions. The research described in this paper has the potential to improve the efficiency and effectiveness of decision-making processes in different CM functions.

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In recent years, there has been a growing interest from the design and construction community to adopt Building Information Models (BIM). BIM provides semantically-rich information models that explicitly represent both 3D geometric information (e.g., component dimensions), along with non-geometric properties (e.g., material properties). While the richness of design information offered by BIM is evident, there are still tremendous challenges in getting construction-specific information out of BIM, limiting the usability of these models for construction. In this paper, we describe our approach for extracting construction-specific design conditions from a BIM model based on user-defined queries. This approach leverages an ontology of features we are developing to formalize the design conditions that affect construction. Our current implementation analyzes the component geometry and topological relationships between components in a BIM model represented using the Industry Foundation Classes (IFC) to identify construction features. We describe the reasoning process implemented to extract these construction features, and provide a critique of the IFC’s to support the querying process. We use examples from two case studies to illustrate the construction features, the querying process, and the challenges involved in deriving construction features from an IFC model.

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A model of the information and material activities that comprise the overall construction process is presented, using the SADT activity modelling methodology. The basic model is further refined into a number of generic information handling activities such as creation of new information, information search and retrieval, information distribution and person-to-person communication. The viewpoint could be described as information logistics. This model is then combined with a more traditional building process model, consisting of phases such as design and construction. The resulting two-dimensional matrix can be used for positioning different types of generic IT-tools or construction specific applications. The model can thus provide a starting point for a discussion of the application of information and communication technology in construction and for measurements of the impacts of IT on the overall process and its related costs.

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In the present paper we compare clustering solutions using indices of paired agreement. We propose a new method - IADJUST - to correct indices of paired agreement, excluding agreement by chance. This new method overcomes previous limitations known in the literature as it permits the correction of any index. We illustrate its use in external clustering validation, to measure the accordance between clusters and an a priori known structure. The adjusted indices are intended to provide a realistic measure of clustering performance that excludes agreement by chance with ground truth. We use simulated data sets, under a range of scenarios - considering diverse numbers of clusters, clusters overlaps and balances - to discuss the pertinence and the precision of our proposal. Precision is established based on comparisons with the analytical approach for correction specific indices that can be corrected in this way are used for this purpose. The pertinence of the proposed correction is discussed when making a detailed comparison between the performance of two classical clustering approaches, namely Expectation-Maximization (EM) and K-Means (KM) algorithms. Eight indices of paired agreement are studied and new corrected indices are obtained.

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Anticipating the future is increasingly being seen as a useful way to align, direct and improve current organizational strategy. Several such 'future studies' have been produced which envision various construction industry scenarios which result from technological and socio-economic trends and influences. Thirteen construction-related future studies are critically reviewed. Most studies fail to address the complexities and uncertainties of both the present and the future, and fail to explore the connections between global, local, construction-specific and more widespread factors. The methodological approaches used in these studies do not generate any significantly different advice or recommendations for the industry than those emerging from the much larger canon of non-future oriented construction research. As such, these reports are less about the future than the present. If future studies are to make a worthwhile contribution to construction, it is critical that they develop our appreciation of the practical ability of stakeholders to influence some aspects of the future and not others, and an awareness of the competing agendas and the relative benefits and disadvantages of specific futures within the construction sector. Only then can future studies provide insights and help in preparing for the opportunities and threats the future may bring.

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Research on construction prices is significant for contractors and traders. A comprehensive understanding of construction prices may influence crucial decisions in business operation and arbitrage activities. This study focuses on the cointegration relationships of regional construction prices in Australia by using a range of econometric techniques including the stationarity test, the Engle-Granger cointegration approach examines the long run equilibrium relationships within the regional markets, and the error correction models explore the short run disequilibrium relationships. Finds of this study reveal that the economic system in which the construction industry participants operate is characterized by a highly competitive, integrated marketplace, Especially in Melbourne and Sydney. But exclude Northern Territory and Queensland. Furthermore, the results of long term relationships estimation suggest that there are 15 pairs of regional construction prices have long term equilibrium relationships. Additionally, the causalities and diffusion among the construction price indices in six states and two territories of Australia are estimated in this study. These outcomes suggest that causal links between regions mainly exist among adjoining states.

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Research on construction prices is significant for contractors and traders. A comprehensive understanding of construction prices may influence crucial decisions in business operation and arbitrage activities. This study focuses on the cointegration relationships of regional construction prices in Australia by using a range of econometric techniques including the stationarity test, the Engle-Granger cointegration approach and error correction model. The cointegration relationships amongst the regional construction prices are detected in this study. The application of the Engle-Granger cointegration approach examines the long run equilibrium relationships within the regional markets, and the error correction models explore the short run disequilibrium relationships. Results of this study suggest that the economic system in which construction industry participants operate is characterised by a highly competitive integrated marketplace. Furthermore, the causalities and diffusion patterns among the construction price indices in six states and two territories of Australia are drawn by the cointegration analysis. These outcomes reveal a pattern of diffusion paths and network linkages among the six states and two territories, and then expose the regional price linkages.

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Linkages among different construction markets have attracted great of attention from the construction economist. With notable exceptions, most of this infestation has carried out by using input-output analysis. Interactions among regional construction markets have been discussed in few studies and none of them investigate spatial effects on the regional construction markets. This study employed spatial econometric techniques, spatial autocorrelation and convergence tests, to analysis interactions and linkages among construction price indices in Australian six states and two territories. The empirical results indicate the presence of significant positive spatial correlation between the construction prices in Australian eight construction markets and the degree of dependence decrease sufficiently quickly as the space between units increase. The results of convergence test further present evidence on "ripple effect" in the construction prices in Australian regional markets and the changes in regional construction price would positively influence neighboring states first, and then spread out into others, and then the regional prices converge and reach a long-run equilibrium in the following quarters. Urban development policymakers and construction developers could benefit from the analysis of spatial linkages in regional construction markets.

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The linkages among different construction markets have recently attracted much attention from construction economists. The interactions among regional construction markets have been discussed in a few studies, most of which have been carried out by using input-output methods, and none of them investigated spatial effects on the regional construction markets. This study employed spatial econometric techniques, including spatial autocorrelation and convergence tests, to analyse interactions and linkages among construction price indices in Australian six states and two territories. The empirical results indicate the presence of significant positive spatial correlation among the construction prices in Australian eight construction markets and the degree of dependence decreasing sufficiently quickly as the space between regions increases. The results of convergence test further provide evidence of existence of a ripple effect in construction prices among the Australian regional markets and the changes in construction prices in a state would first positively influence neighbouring states, and then spread out into other non-neighbouring states or territories.

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Body fat distribution is a cardiovascular health risk factor in adults. Body fat distribution can be measured through various methods including anthropometry. It is not clear which anthropometric index is suitable for epidemiologic studies of fat distribution and cardiovascular disease. The purpose of the present study was to select a measure of body fat distribution from among a series of indices (those traditionally used in the literature and others constructed from the analysis) that is most highly correlated with lipid-related variables and is independent of overall fatness. Subjects were Mexican-American men and women (N = 1004) from a study of gallbladder disease in Starr County, Texas. Multivariate associations were sought between lipid profile measures (lipids, lipoproteins, and apolipoproteins) and two sets of anthropometric variables (4 circumferences and 6 skinfolds). This was done to assess the association between lipid-related measures and the two sets of anthropometric variables and guide the construction of indices.^ Two indices emerged from the analysis that seemed to be highly correlated with lipid profile measures independent of obesity. These indices are: 2*arm circumference-thigh skinfold in pre- and post-menopausal women and arm/thigh circumference ratio in men. Next, using the sum of all skinfolds to represent obesity and the selected body fat distribution indices, the following hypotheses were tested: (1) state of obesity and centrally/upper distributed body fat are equally predictive of lipids, lipoproteins and apolipoproteins, and (2) the correlation among the lipid-related measures is not altered by obesity and body fat distribution.^ With respect to the first hypothesis, the present study found that most lipids, lipoproteins and apolipoproteins were significantly associated with both overall fatness and anatomical location of body fat in both sex and menopausal groups. However, within men and post-menopausal women, certain lipid profile measures (triglyceride and HDLT among post-menopausal women and apos C-II, CIII, and E among men) had substantially higher correlation with body fat distribution as compared with overall fatness.^ With respect to the second hypothesis, both obesity and body fat distribution were found to alter the association among plasma lipid variables in men and women. There was a suggestion from the data that the pattern of correlations among men and post-menopausal women are more comparable. Among men correlations involving apo A-I, HDLT, and HDL$\sb2$ seemed greatly influenced by obesity, and A-II by fat distribution; among post-menopausal women correlations involving apos A-I and A-II were highly affected by the location of body fat.^ Thus, these data point out that not only can obesity and fat distribution affect levels of single measures, they also can markedly influence the pattern of relationship among measures. The fact that such changes are seen for both obesity and fat distribution is significant, since the indices employed were chosen because they were independent of one another. ^