The true cost and performance of individual residential property investment and the implication on real estate agency practice

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.

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.

Mechanisms of improvement in treatment for depression : test of a self-efficacy and performance model

Tested D. J. Kavanagh's (1983) depression model's explanation of response to cognitive-behavioral treatment among 19 20–60 yr old Ss who received treatment and 24 age-matched Ss who were assigned to a waiting list. Measures included the Beck Depression Inventory and self-efficacy (SE) and self-monitoring scales. Rises in SE and self-monitored performance of targeted skills were closely associated with the improved depression scores of treated Ss. Improvements in the depression of waiting list Ss occurred through random, uncontrolled events rather than via a systematic increase in specific skills targeted in treatment. SE regarding assertion also predicted depression scores over a 12-wk follow-up.

Physical performance and self-efficacy under happy and sad moods

Two experiments involving 87 undergraduates examined whether happiness produces increased performance on a physical task and tested whether self-efficacy mediated the results. When mood inductions covered the full range from happy to sad, mood influenced physical performance; however, evidence regarding self-efficacy was equivocal. Efficacy for the performed task was unaffected by mood, although it remained a good predictor of performance. Since mood altered efficacy for a nonperformed but more familiar task, inconsistent efficacy results could reflect task differences. Findings offer prospects for the use of mood inductions in practical sporting situations.

Performance of public private partnerships : an evolutionary perspective

PPPs are held to be a powerful way of mobilising private finance and resources to deliver public infrastructure. Theoretically, research into procurement has begun to acknowledge difficulties with the classification and assessment of different types of procurement, particularly those which do not sufficiently acknowledge variety within specific types of procurement methods. This paper advances a theoretical framework based on an evolutionary economic conceptualisation of a routine, which can accommodate the variety evident in procurement projects, in particular PPPs. The paper tests how the various elements of a PPP, as advanced in the theoretical framework, affect performance across 10 case studies. It concludes, that a limited number of elements of a PPP affect their performance, and provides strong evidence for the theoretical model advanced in this paper.

Monitoring the Performance of Complex Projects from Multiple Perspectives over Multiple Time Frames

When complex projects go wrong they can go horribly wrong with severe financial consequences. We are undertaking research to develop leading performance indicators for complex projects, metrics to provide early warning of potential difficulties. The assessment of success of complex projects can be made by a range of stakeholders over different time scales, against different levels of project results: the project’s outputs at the end of the project; the project’s outcomes in the months following project completion; and the project’s impact in the years following completion. We aim to identify leading performance indicators, which may include both success criteria and success factors, and which can be measured by the project team during project delivery to forecast success as assessed by key stakeholders in the days, months and years following the project. The hope is the leading performance indicators will act as alarm bells to show if a project is diverting from plan so early corrective action can be taken. It may be that different combinations of the leading performance indicators will be appropriate depending on the nature of project complexity. In this paper we develop a new model of project success, whereby success is assessed by different stakeholders over different time frames against different levels of project results. We then relate this to measurements that can be taken during project delivery. A methodology is described to evaluate the early parts of this model. Its implications and limitations are described. This paper describes work in progress.

Does chemometrics enhance the performance of electroanalysis?

This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of not, vert, similar±10% is acceptable.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

Internal audit quality, audit committee independence, growth opportunities and firm performance

This study explores whether the relation between internal audit quality and firm performance is associated with firm characteristics of information asymmetry and uncertainty (growth opportunities) and certain governance controls (audit committee effectiveness). The results from this preliminary study of 60 Malaysian companies show that the association between internal audit quality and firm performance is stronger for firms with high growth opportunities and that this positive association is weakened by increasing audit committee independence. These findings demonstrate the internal auditors conflicting roles and question the governance recommendations that require all members of the audit committee to be non-executive directors.

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

Measuring quality : how does this improve construction performance?

The paper charts the history and development of the Hong Kong Housing Department (HKHD) Performance Assessment Scoring System (PASS) from 1990 to the present day and examines its effect on facilitating change to the quality of construction work of building contractors engaged in the production of public sector housing projects Hong Kong. The paper builds partly on empirical research carried out by the author as part of a doctoral thesis from 2000 to 2005, on experiential knowledge and also on some relevant case studies. The outcomes from this earlier research and validation of PASS based on results derived from the system since the research was originally undertaken are of benefit to practitioners and academics working and studying in the areas of performance assessment and organisational culture and change. The conclusions presented in the paper further underpin the connection established in previous research between strong organisational culture and project and corporate success. Organisational culture was measured using a survey instrument originally developed by Denison and Neale (1994), adapted for the environment of the study, and corporate success was measured by the PASS system mentioned above. The major results of the original study indicate that there is significant linkage between strong organisational cultures and business success and the detailed findings were that, (1) strong organisational culture was positively associated a high level of company effectiveness, (2) a high level of company effectiveness was positively associated with the cultural traits of ‘consistency’, ‘adaptability’ and ‘mission’, and (3) a high level of company effectiveness was positively associated with the combined cultural traits represented by the dimensions of ‘external focus’ and ‘stable culture’. Several opportunities to take forward this research have been identified, including extending the study to other countries and also longitudinally re-evaluating some of the original case studies to ascertain how organisational cultures have changed or further developed in relation to the changing construction climate in Hong Kong.

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.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Controlled Rate Thermal analysis of sepiolite

Controlled rate thermal analysis (CRTA) technology offers better resolution and a more detailed interpretation of the decomposition processes of a clay mineral such as sepiolite via approaching equilibrium conditions of decomposition through the elimination of the slow transfer of heat to the sample as a controlling parameter on the process of decomposition. Constant-rate decomposition processes of non-isothermal nature reveal changes in the sepiolite as the sepiolite is converted to an anhydride. In the dynamic experiment two dehydration steps are observed over the *20–170 and 170–350 �C temperature range. In the dynamic experiment three dehydroxylation steps are observed over the temperature ranges 201–337, 337–638 and 638–982 �C. The CRTA technology enables the separation of the thermal decomposition steps.