Labor-leisure choice : is everything as straightforward as one might have thought?

We argue that a full understanding of a rational labor supply choice in a standard dynamic life cycle framework is obscure, despite the framework’s being seemingly self-explanatory, straightforward, and intuitively sensible. In a completely friction-free environment, we, to our knowledge, are the first to provide a complete analytic solution to the benchmark model that presumes a kind of labor supply behavior that is typically taken as the standard in economic studies. We find thatsuch standard behavior holds only for a narrow set of parameters. For many alternative parameterizations, the labor supply behavior of a rational agent is either highly unrealistic, or extremely hard to predict and interpret. A complete understanding of a rational, intertemporal labor supply choice requires further analysis.

Social Security, interest rates, and life cycle consumption /

Prepared for Manpower Administration, Washington, D.C. Office of Manpower Research and Development.

Life cycle assessment in the supply chain: a review and case study

The paper addresses the use of Life Cycle Assessment as a tool for analysing freight transport activity in product supply chains. Published works that have assessed freight transport energy use in supply chain operations are reviewed and their results summarized. A case study of the energy use in the supply chains for jeans sold in both the UK and France is presented. The results of this case study indicate that the location from which cotton is sourced can have a major impact on the total energy used in commercial transport in the jeans supply chain. However, overall, this has a limited impact on the total energy used in producing and supplying jeans. This is because the vast majority of total energy used in the supply chain is consumed during cotton cultivation, denim production and jeans manufacture. The work also demonstrates that the amount of energy used by consumers transporting jeans to their homes by car can be greater than the total commercial transport energy used in the supply chain (per kg of jeans transported).

Survival misperception, time inconsistency, and implications for life-cycle saving and welfare

Some empirical studies firmly reveal that people tend to form overly pessimistic survival expectations for relatively less distant ages and overly optimistic survival expectations for relatively more distant ages. We incorporate this observation into a life-cycle continuous time overlapping-generations model of consumption/saving with a general form for a subjective survival function. Resulting time-inconsistent optimal control problem has been analytically solved. At the micro level, time inconsistency leads to higher consumption at young and old ages, but this alone fails to improve lifetime well-being since micro-level decisions made with a lack of information about true mortality are suboptimal. In general equilibrium, however, such time inconsistent behavior with survival misperception is conducive to aggregate capital accumulation and greater equilibrium bequest income. The latter effects can produce substantial welfare gains. We also note that empirically observed old age optimistic bias is an important phenomenon, as it helps to avoid unrealistic very old-age debt accumulation within a life-cycle model. In addition, if for a given level of optimistic bias we increase early-life pessimism, this would result in slower capital accumulation, lower bequest income, and thus be detrimental to welfare. Since recent literature reports that young-age survival pessimism has grown over time, it raises some concerns.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Ironmongeries life cycle costing and quality satisfaction

Most commonly, residents are always arguing about the satisfaction of sustainability and quality of their high rise residential property. This paper aim is to maintain the best quality satisfaction of the door hardware by introducing the whole life cycle costing approach to the property manager of the public housing in Johor. This paper looks into the current situation of ironmongeries (door hardware) of 2 public housings in Johor, Malaysia and testing the whole life cycle costing approach towards them. The calculation and the literature review are conducted. The questionnaire surveys of 2 public housings were conducted to make clear the occupants’ evaluation about the actual quality conditions of the ironmongeries in their house. As a result, the quality of door hardware based on the whole life cycle costing approach is one of the best among their previous decision making tool that have been applied. Practitioners can benefit from this paper as it provides information on calculating the whole life costing and making the decisions about ironmongeries selection of their properties.

Whole life cycle costing and quality satisfaction : public housing floor material

Most commonly, residents are always arguing about the satisfaction of sustainability and quality of their high rise residential property. This paper aim is to maintain the best quality satisfaction of the floor materials by introducing the whole life cycle costing approach to the property manager of the public housing in Johor. This paper looks into the current situation of floor material of two public housings in Johor, Malaysia and testing the whole life cycle costing approach towards them. The cost figures may be implemented to justify higher investments, for examples, in the quality or flexibility of building solutions through a long-term cost reduction. The calculation and the literature review are conducted. The questionnaire surveys of two public housings were conducted to make clear the occupants’ evaluation about the actual quality conditions of the floor material in their house. As a result, the quality of floor material based on the whole life cycle costing approach is one of the best among their previous decision making tool that was applied. Practitioners can benefit from this paper as it provides information on calculating the whole life costing and making the decisions for floor material selection for their properties.

A streamlined life-cycle assessment and decision tool for used tyres recycling

In order to achieve progress towards sustainable resource management, it is essential to evaluate options for the reuse and recycling of secondary raw materials, in order to provide a robust evidence base for decision makers. This paper presents the research undertaken in the development of a web-based decision-support tool (the used tyres resource efficiency tool) to compare three processing routes for used tyres compared to their existing primary alternatives. Primary data on the energy and material flows for the three routes, and their alternatives were collected and analysed. The methodology used was a streamlined life-cycle assessment (sLCA) approach. Processes included were: car tyre baling against aggregate gabions; car tyre retreading against new car tyres; and car tyre shred used in landfill engineering against primary aggregates. The outputs of the assessment, and web-based tool, were estimates of raw materials used, carbon dioxide emissions and costs. The paper discusses the benefits of carrying out a streamlined LCA and using the outputs of this analysis to develop a decision-support tool. The strengths and weakness of this approach are discussed and future research priorities identified which could facilitate the use of life cycle approaches by designers and practitioners.

Distortionary Taxation and Labor Supply: Evidence from Canada.

This paper examines empirically the effects of distortionary taxation on labor supply using a general equilibrium framework. The long-term relations predicted by the model are derived and tested using Canadian data between 1966 and 1993. While the cointegrating predictions of the model without taxation are rejected, the ones of the model with labor taxation are not. Persistent labor tax rate increases appear to play an important role in the observed downward trend in hours worked.

Model-based life cycle cost and assessment tool for sustainable building design decision

There is a growing concern in reducing greenhouse gas emissions all over the world. The U.K. has set 34% target reduction of emission before 2020 and 80% before 2050 compared to 1990 recently in Post Copenhagen Report on Climate Change. In practise, Life Cycle Cost (LCC) and Life Cycle Assessment (LCA) tools have been introduced to construction industry in order to achieve this such as. However, there is clear a disconnection between costs and environmental impacts over the life cycle of a built asset when using these two tools. Besides, the changes in Information and Communication Technologies (ICTs) lead to a change in the way information is represented, in particular, information is being fed more easily and distributed more quickly to different stakeholders by the use of tool such as the Building Information Modelling (BIM), with little consideration on incorporating LCC and LCA and their maximised usage within the BIM environment. The aim of this paper is to propose the development of a model-based LCC and LCA tool in order to provide sustainable building design decisions for clients, architects and quantity surveyors, by then an optimal investment decision can be made by studying the trade-off between costs and environmental impacts. An application framework is also proposed finally as the future work that shows how the proposed model can be incorporated into the BIM environment in practise.