884 resultados para Knowledge Based Urban Development
Resumo:
The sale of residential property by auction is a preferred sale method by real estate agents, but not always preferred by some vendors and most residential property buyers. In many residential property markets, the performance and measure of residential property market activity is based on the number of properties offered for sale by auction, auction clearance rates and the number of properties sold prior to auction. However, in many specific residential property markets, sale by auction may not be the preferred or supported method of sale. This paper will review the type of residential property sale within the Sydney residential property market and track the auction sales and clearance rates for Sydney over the past 5 months and compare these results in relation to clearance rates, passed in sales, and properties sold prior to auction This will provide a breakdown of real estate agency sale practice over a large metropolitan region to determine the impact of geographic location and socio-economic factors on the auction of residential property. In addition the paper will analyse the weekly auction sales in the Sydney residential property market to determine what areas of Sydney have the greatest number of house auctions and the performance of the auctions in relation location and socio economic factors.
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Large cities provide a broad range of residential property types, as well as a range of socio-economic locations. This results in a significant variation in residential property prices across both the city itself and the individual suburbs. The only constant across such a diverse range of residential property is the need for the majority of residential property owners to employ the services of a real estate agent to sell their property or to purchase a residential property. This paper will analyse the Sydney residential property market over the period 1994 to 2002 to determine the change in real estate offices numbers over the period, the profitability of real estate agency offices based on the residential house price performance of houses and units in these specific locations and the extent of changing residential house prices on agency profitability. Suburbs have been selected to provide a full range of housing types, socio-economic areas, older established and developing residential suburbs and location from the
Resumo:
Investment in residential property in Australia is not dominated by the major investment institutions in to the same degree as the commercial, industrial and retail property markets. As at December 2001, the Property Council of Australia Investment Performance Index contained residential property with a total value of $235 million, which represents only 0.3% of the total PCA Performance Index value. The majority of investment in the Australian residential property market is by small investment companies and individual investors. The limited exposure of residential property in the institutional investment portfolios has also limited the research that has been undertaken in relation to residential property performance. However the importance of individual investment in residential property is continuing to gain importance as both individuals are now taking control of their own superannuation portfolios and the various State Governments of Australia are decreasing their involvement in the construction of public housing by subsidizing low-income families into the private residential property market. This paper will: • Provide a comparison of the cost to initially purchase residential property in the various capital city residential property markets in Australia, and • Analyse the true cost and investment performance of residential property in the main residential property markets in Australia based on a standard investment portfolio in each of the State capital cities and relate these results to real estate marketing and agency practice.
Resumo:
The importance of agriculture in many countries has tended to reduce as their economies move from a resource base to a manufacturing industry base. Although the level of agricultural production in first world countries has increased over the past two decades, this increase has generally been at a less significant rate compared to other sectors of the economies. Despite this increase in secondary and high technology industries, developed countries have continued to encourage and support their agricultural industries. This support has been through both tariffs and price support. Following pressure from developing economies, particularly through the World Trade Organisation (WTO), GATT Uruguay round and the Cairns Group developed countries are now in various stages of winding back or de-coupling agricultural support within their economies. A major concern of farmers in protected agricultural markets is the impact of a free market trade in agricultural commodities on farm incomes, profitability and land values. This paper will analyse both the capital and income performance of the NSW rural land market over the period 1990-1999. This analysis will be based on several rural land use classifications and will compare the total return from rural properties based on the farm income generated by both the average farmer and those farmers considered to be in the top 20% of the various land use areas. The analysis will provide a comprehensive overview of rural production in a free trade economy.
Resumo:
Rural land has not always been considered as a major long-term investment with both institutional investors and absentee owners in countries such as U.K. and Australia. Although rural land is included in both single asset and mixed asset portfolios in the U.S, it is not at the same levels as either commercial or industrial property. Rural land occupies over 50% of the total area of Australia, and comprises over 115,000 economic farm properties (excludes rural residential, hobby farms and rural lifestyle blocks. However, less than 1.6% of the total economic farm numbers are actually owned by corporate or institutional investors. This low level of corporate involvement in the Australian rural property market has limited both the investment performance research and inclusion of this rural land type in both property and mixed asset investment portfolios. In the U.S. rural land is also the most extensive real estate type based on total area occupied. The United States Department of Agriculture statistics (1998) show that in 1997 there were 2.06 million farms in the U.S., covering 968 million acres, with a total value of $912 billion and generating an annual income of $202 billion. The level of corporate ownership of farms in the U.S. is also higher than the level of corporate farm ownership in Australia. This high level of institutional ownership in rural land in U.S has provided the opportunity for the rural property asset class to be analysed in relation to it’s investment performance and possible role in a mixed asset or mixed property investment portfolio.
Resumo:
The importance of agriculture in many countries has tended to reduce as their economies move from a resource base to a manufacturing industry base. Although the level of agricultural production in first world countries has increased over the past two decades, this increase has generally been at a less significant rate compared to other sectors of the economies. Despite this increase in secondary and high technology industries, developed countries have continued to encourage and support their agricultural industries. This support has been through both tariffs and price support. Following pressure from developing economies, particularly through the World Trade Organisation (WTO), GATT Uruguay round and the Cairns Group Developed countries are now in various stages of winding back or de-coupling agricultural support within their economies. A major concern of farmers in protected agricultural markets is the impact of a free market trade in agricultural commodities on farm incomes and land values. This paper will analyse the capital and income performance of the NSW rural land market over the period 1990-1999. This analysis will be based on land use and will compare the total return from rural properties based on world agricultural commodity prices.
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This paper is a deductive theoretical enquiry into the flow of effects from the geometry of price bubbles/busts, to price indices, to pricing behaviours of sellers and buyers, and back to price bubbles/busts. The intent of the analysis is to suggest analytical approaches to identify the presence, maturity, and/or sustainability of a price bubble. We present a pricing model to emulate market behaviour, including numeric examples and charts of the interaction of supply and demand. The model extends into dynamic market solutions myopic (single- and multi-period) backward looking rational expectations to demonstrate how buyers and sellers interact to affect supply and demand and to show how capital gain expectations can be a destabilising influence – i.e. the lagged effects of past price gains can drive the market price away from long-run market-worth. Investing based on the outputs of past price-based valuation models appear to be more of a game-of-chance than a sound investment strategy.
Resumo:
Rivers and water are valuable natural resources for human life, environment and national development. Recognition of water resources as national heritage will contribute towards more long term sustainable property development. Waterfront development is already a well-established phenomenon internationally. In Malaysia, as the economy began to change in 1980s, so did the land uses along many of the river and waterfront locations. The pressures of new technology coupled with an urban population growth and urbanization began to force a transition from water dependent industry to a variety of non-water dependent developments such as apartments, offices, and retail shopping areas. Residential waterfront development has taken advantage of available land and water amenities and incorporated as a feature or “selling point” of the development. It has been found that wide views of water add an average of 59% to the value of waterfront property, as well as providing attractive landscaping and better property neighborhoods respectively. Development of waterfront lands in Malaysia occurred with limited federal, state, or municipal planning guidance; resulting in cost aspects like flooding and pollution. Although some waterfront development projects continue to remain profitable with a maintained successful public access component, many have not. This paper provides a brief introduction to the research project to address this issue, which is currently on-going.
Resumo:
Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.
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Growing participation is a key challenge for the viability of sustainability initiatives, many of which require enactment at a local community level in order to be effective. This paper undertakes a review of technology assisted carpooling in order to understand the challenge of designing participation and consider how mobile social software and interface design can be brought to bear. It was found that while persuasive technology and social networking approaches have roles to play, critical factors in the design of carpooling are convenience, ease of use and fit with contingent circumstances, all of which require a use-centred approach to designing a technological system and building participation. Moreover, the reach of technology platform-based global approaches may be limited if they do not cater to local needs. An approach that focuses on iteratively designing technology to support and grow mobile social ridesharing networks in particular locales is proposed. The paper contributes an understanding of HCI approaches in the context of other designing participation approaches.
Resumo:
The paper analyses the expected value of OD volumes from probe with fixed error, error that is proportional to zone size and inversely proportional to zone size. To add realism to the analysis, real trip ODs in the Tokyo Metropolitan Region are synthesised. The results show that for small zone coding with average radius of 1.1km, and fixed measurement error of 100m, an accuracy of 70% can be expected. The equivalent accuracy for medium zone coding with average radius of 5km would translate into a fixed error of approximately 300m. As expected small zone coding is more sensitive than medium zone coding as the chances of the probe error envelope falling into adjacent zones are higher. For the same error radii, error proportional to zone size would deliver higher level of accuracy. As over half (54.8%) of the trip ends start or end at zone with equivalent radius of ≤ 1.2 km and only 13% of trips ends occurred at zones with equivalent radius ≥2.5km, measurement error that is proportional to zone size such as mobile phone would deliver higher level of accuracy. The synthesis of real OD with different probe error characteristics have shown that expected value of >85% is difficult to achieve for small zone coding with average radius of 1.1km. For most transport applications, OD matrix at medium zone coding is sufficient for transport management. From this study it can be drawn that GPS with error range between 2 and 5m, and at medium zone coding (average radius of 5km) would provide OD estimates greater than 90% of the expected value. However, for a typical mobile phone operating error range at medium zone coding the expected value would be lower than 85%. This paper assumes transmission of one origin and one destination positions from the probe. However, if multiple positions within the origin and destination zones are transmitted, map matching to transport network could be performed and it would greatly improve the accuracy of the probe data.
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This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.
Resumo:
Purpose – The purpose of this paper is to examine the use of bid information, including both price and non-price factors in predicting the bidder’s performance. Design/methodology/approach – The practice of the industry was first reviewed. Data on bid evaluation and performance records of the successful bids were then obtained from the Hong Kong Housing Department, the largest housing provider in Hong Kong. This was followed by the development of a radial basis function (RBF) neural network based performance prediction model. Findings – It is found that public clients are more conscientious and include non-price factors in their bid evaluation equations. With the input variables used the information is available at the time of the bid and the output variable is the project performance score recorded during work in progress achieved by the successful bidder. It was found that past project performance score is the most sensitive input variable in predicting future performance. Research limitations/implications – The paper shows the inadequacy of using price alone for bid award criterion. The need for a systemic performance evaluation is also highlighted, as this information is highly instrumental for subsequent bid evaluations. The caveat for this study is that the prediction model was developed based on data obtained from one single source. Originality/value – The value of the paper is in the use of an RBF neural network as the prediction tool because it can model non-linear function. This capability avoids tedious ‘‘trial and error’’ in deciding the number of hidden layers to be used in the network model. Keywords Hong Kong, Construction industry, Neural nets, Modelling, Bid offer spreads Paper type Research paper
Resumo:
As part of a Doctor of Business Administration degree programme jointly run by Curtin University, Perth, Australia and Lingnan University, Hong Kong, a research thesis relating organizational effectiveness to the organizational culture of Hong Kong construction firms involved in public housing is being undertaken. Organizational effectiveness is measured by the Housing Department (HD) Performance Assessment Scoring System (PASS) and organizational culture traits and strengths have been measured by using the Denison Organizational Culture Survey (OCS), developed by Daniel Denison and William S. Neale and based on 16 years of research involving over 1,000 organizations. The PASS scores of building contractors are compared with the OCS scores to determine if there is any significant correlation between highly effective companies and particular organizational strengths and traits. Profiles are then drawn using the Denison Model and can be compared against ‘norms’ for the industry sector on which the survey has been carried out. The next stage of the work is to present the results of the survey to individual companies, conduct focus group interviews to test the results, discover more detail on that company’s culture and discuss possible actions based on the results. It is in this latter stage that certain value management techniques may well prove very useful.
Resumo:
Successful project delivery of construction projects depends on many factors. With regard to the construction of a facility, selecting a competent contractor for the job is paramount. As such, various approaches have been advanced to facilitate tender award decisions. Essentially, this type of decision involves the prediction of a bidderÕs performance based on information available at the tender stage. A neural network based prediction model was developed and presented in this paper. Project data for the study were obtained from the Hong Kong Housing Department. Information from the tender reports was used as input variables and performance records of the successful bidder during construction were used as output variables. It was found that the networks for the prediction of performance scores for Works gave the highest hit rate. In addition, the two most sensitive input variables toward such prediction are ‘‘Difference between Estimate’’ and ‘‘Difference between the next closest bid’’. Both input variables are price related, thus suggesting the importance of tender sufficiency for the assurance of quality production.