The Influence of Farm Management on NSW Rural Property Income and Total Average Annual Returns

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.

The role of rural land in mixed asset investment portfolios

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.

Total rural land performance in a free trade economy

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.

Bubble geometry and chaotic pricing behaviour

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.

Waterfront Development for Residential Property in Malaysia

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.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

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.

Designing participation in agile ridesharing with mobile social software

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.

Mapping personal trip OD from probe data

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.

Urban network travel time estimation from stop-line loop detector data and signal controller data

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.

Examining the use of bid information in predicting the contractor’s performance

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

Assessing organizational culture? value management to the rescue

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.

Predicting project performance through neural networks

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.

Comparison of molecular markers to detect fresh sewage in environmental waters

Human-specific Bacteroides HF183 (HS-HF183), human-specific Enterococci faecium esp (HS-esp), human-specific adenoviruses (HS-AVs) and human-specific polyomaviruses (HS-PVs) assays were evaluated in freshwater, seawater and distilled water to detect fresh sewage. The sewage spiked water samples were also tested for the concentrations of traditional fecal indicators (i.e., Escherichia coli, enterococci and Clostridium perfringens) and enteric viruses such as enteroviruses (EVs), sapoviruses (SVs), and torquetenoviruses (TVs). The overall host-specificity of the HS-HF183 marker to differentiate between humans and other animals was 98%. However, the HS-esp, HS-AVs and HS-PVs showed 100% hostspecificity. All the human-specific markers showed >97% sensitivity to detect human fecal pollution. E. coli, enterococci and, C. perfringens were detected up to dilutions of sewage 10_5, 10_4 and 10_3 respectively.HS-esp, HS-AVs, HS-PVs, SVs and TVs were detected up to dilution of sewage 10_4 whilst EVs were detected up to dilution 10_5. The ability of the HS-HF183 marker to detect freshsewagewas3–4 orders ofmagnitude higher than that of the HS-esp and viral markers. The ability to detect fresh sewage in freshwater, seawater and distilled water matrices was similar for human-specific bacterial and viral marker. Based on our data, it appears that human-specific molecular markers are sensitive measures of fresh sewage pollution, and the HS-HF183 marker appears to be the most sensitive among these markers in terms of detecting fresh sewage. However, the presence of the HS-HF183 marker in environmental waters may not necessarily indicate the presence of enteric viruses due to their high abundance in sewage compared to enteric viruses. More research is required on the persistency of these markers in environmental water samples in relation to traditional fecal indicators and enteric pathogens.

Prevalence and occurrence of zoonotic bacterial pathogens in surface waters determined by quantitative PCR

The prevalence and concentrations of Campylobacter jejuni, Salmonella spp. and enterohaemorrhagic E. coli (EHEC) were investigated in surface waters in Brisbane, Australia using quantitative PCR (qPCR) based methodologies. Water samples were collected from Brisbane City Botanic Gardens (CBG) Pond, and two urban tidal creeks (i.e., Oxley Creek and Blunder Creek). Of the 32 water samples collected, 8 (25%), 1 (3%), 9 (28%), 14 (44%), and 15 (47%) were positive for C. jejuni mapA, Salmonella invA, EHEC O157 LPS, EHEC VT1, and EHEC VT2 genes, respectively. The presence/absence of the potential pathogens did not correlate with either E. coli or enterococci concentrations as determined by binary logistic regression. In conclusion, the high prevalence, and concentrations of potential zoonotic pathogens along with the concentrations of one or more fecal indicators in surface water samples indicate a poor level of microbial quality of surface water, and could represent a significant health risk to users. The results from the current study would provide valuable information to the water quality managers in terms of minimizing the risk from pathogens in surface waters.

Stakeholder impact analysis of infrastructure project management in developing countries : a study of perception of project managers in state-owned engineering firms in Vietnam

Construction projects can involve a diverse range of stakeholders and the success of the project depends very much on fulfilling their needs and expectations. It is important, therefore, to identify and recognize project stakeholders and develop a rigorous stakeholder management process. However, limited research has investigated the impact of stakeholders on construction projects in developing countries. A stakeholder impact analysis (SIA), based on an approach developed by Olander (2007), was adopted to investigate the stakeholders' impact on state-owned civil engineering projects in Vietnam. This involved the analysis of a questionnaire survey of 57 project managers to determine the relative importance of different stakeholders. The results show the client to have the highest level of impact on the projects, followed by project managers and the senior management of state-owned engineering firms. The SIA also provides suggestions to project managers in developing and evaluating the stakeholder management process.