The impact of contractor’s characteristics in gauging level satisfaction

The outcomes of the construction projects can be evaluated in numerous ways. One method is to measure the satisfaction of participants as represented by the differences between their expectations and perceptions. This measurement is used widely in construction as it promises benefits, such as the improvement of product delivery, and enhances services quality by identifying some necessary changes. Commonly satisfaction measurement is gauged by evaluating the level of client satisfaction of construction performance. The measurement of customer satisfaction on the other hand, is based on the quality of the end product. This evaluation is used to encourage contractors to improve their performance to a required level and to ensure that the projects are delivered as expected- in terms of time, budget and quality. Several studies of performance measurement have indicated that contractor performance is still not satisfactory, as the outcome delivered is not as required (because of cost overruns, time overruns or because it is generally unsatisfactory). This drawback may be due to the contractors’ lack of expertise, motivation and/or satisfaction. The measurement of performance based on contractor satisfaction levels is still new and very few studies have yet taken place in the construction industry. This paper examines how the characteristics of a contracting organisation – namely its experience in the industry, background, past performance, size of organisation and financial stability- may influence its satisfaction levels with regards to project performance. Previous literature reviews and interviews are used as research tools in the preliminary investigation. The outcome is expected to present a basic understanding of contractor satisfaction measurement and its potential for improving the performance of project outcomes.

Knowledge-based development for cities and societies : integrated multi-level approaches

Over the past twenty years, the conventional knowledge management approach has evolved into a strategic management approach that has found applications and opportunities outside of business, in society at large, through education, urban development, governance, and healthcare, amongst others. Knowledge-Based Development for Cities and Socieities: Integrated Multi-Level Approaches enlightens the concepts and challenges of knowledge management for both urban environments and entire regions, enhancing the expertise and knowledge of scholars, resdearchers, practitioners, managers and urban developers in the development of successful knowledge-based development policies, creation of knowledte cities and prosperous knowledge societies. This reference creates large knowledge base for scholars, managers and urban developers and increases the awareness of the role of knowledge cities and knowledge socieiteis in the knowledge era, as well as of the challenges and opportunities for future research.

Towards the adoption of low-cost rail level crossing warning devices in regional areas of Australia : a review of current technologies and reliability issues

This paper discusses major obstacles for the adoption of low cost level crossing warning devices (LCLCWDs) in Australia and reviews those trialed in Australia and internationally. The argument for the use of LCLCWDs is that for a given investment, more passive level crossings can be treated, therefore increasing safety benefits across the rail network. This approach, in theory, reduces risk across the network by utilizing a combination of low-cost and conventional level crossing interventions, similar to what is done in the road environment. This paper concludes that in order to determine if this approach can produce better safety outcomes than the current approach, involving the incremental upgrade of level crossings with conventional interventions, it is necessary to perform rigorous risk assessments and cost-benefit analyses of LCLCWDs. Further research is also needed to determine how best to differentiate less reliable LCCLWDs from conventional warning devices through the use of different warning signs and signals. This paper presents a strategy for progressing research and development of LCLCWDs and details how the Cooperative Research Centre (CRC) for Rail Innovation is fulfilling this strategy through the current and future affordable level crossing projects.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Does sea-level rise have an impact on saltwater intrusion?

Climate change effects are expected to substantially raise the average sea level. It is widely assumed that this raise will have a severe adverse impact on saltwater intrusion processes in coastal aquifers. In this study we hypothesize that a natural mechanism, identified as the “lifting process” has the potential to mitigate or in some cases completely reverse the adverse intrusion effects induced by sea-level rise. A detailed numerical study using the MODFLOW-family computer code SEAWAT, was completed to test this hypothesis and to understand the effects of this lifting process in both confined and unconfined systems. Our conceptual simulation results show that if the ambient recharge remains constant, the sea-level rise will have no long-term impact (i.e., it will not affect the steady-state salt wedge) on confined aquifers. Our transient confined flow simulations show a self-reversal mechanism where the wedge which will initially intrude into the formation due to the sea-level rise would be naturally driven back to the original position. In unconfined systems, the lifting process would have a lesser influence due to changes in the value of effective transmissivity. A detailed sensitivity analysis was also completed to understand the sensitivity of this self-reversal effect to various aquifer parameters.

The validity and structure of culture-level personality scores: Data from ratings of young adolescents

We examined properties of culture-level personality traits in ratings of targets (N=5,109) ages 12 to 17 in 24 cultures. Aggregate scores were generalizable across gender, age, and relationship groups and showed convergence with culture-level scores from previous studies of self-reports and observer ratings of adults, but they were unrelated to national character stereotypes. Trait profiles also showed cross-study agreement within most cultures, 8 of which had not previously been studied. Multidimensional scaling showed that Western and non-Western cultures clustered along a dimension related to Extraversion. A culture-level factor analysis replicated earlier findings of a broad Extraversion factor but generally resembled the factor structure found in individuals. Continued analysis of aggregate personality scores is warranted.

The level and quality of Value-at-Risk disclosure by commercial banks

In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.

Identification of area-level influences on regions of high cancer incidence in Queensland, Australia : a classification tree approach

Background: Strategies for cancer reduction and management are targeted at both individual and area levels. Area-level strategies require careful understanding of geographic differences in cancer incidence, in particular the association with factors such as socioeconomic status, ethnicity and accessibility. This study aimed to identify the complex interplay of area-level factors associated with high area-specific incidence of Australian priority cancers using a classification and regression tree (CART) approach. Methods: Area-specific smoothed standardised incidence ratios were estimated for priority-area cancers across 478 statistical local areas in Queensland, Australia (1998-2007, n=186,075). For those cancers with significant spatial variation, CART models were used to identify whether area-level accessibility, socioeconomic status and ethnicity were associated with high area-specific incidence. Results: The accessibility of a person’s residence had the most consistent association with the risk of cancer diagnosis across the specific cancers. Many cancers were likely to have high incidence in more urban areas, although male lung cancer and cervical cancer tended to have high incidence in more remote areas. The impact of socioeconomic status and ethnicity on these associations differed by type of cancer. Conclusions: These results highlight the complex interactions between accessibility, socioeconomic status and ethnicity in determining cancer incidence risk.