Rating defense mega-project success : the role of personal attributes and stakeholder relationships

In this paper, we develop and test a model of the relationships between mega-project leaders’ personal attributes and their ratings of project success in the context of the Australian defense industry. In our model, emotional intelligence, cognitive flexibility, and systemic thinking were hypothesized to be related to project success ratings, mediated by internal and external stakeholder relationships. We tested the model in an online survey study of 373 mega-project leaders. Results were that emotional intelligence and cognitive flexibility were found to be related to the quality of mega-project leader’s relationships with both internal and external stakeholders; and that these relationships in turn were found to be associated with the project leaders’ ratings of project success. We found however that systemic thinking had no relationship with either stakeholder relationships or ratings of project success. We conclude with a discussion of the implications of these findings and make recommendations for future research. In particular, additional research is needed to examine the contribution of a wider range of competencies on stakeholder relationships and project success in mega-projects, and that there is also a need for research in future to attempt to use more objective ratings of project success.

Rating for sustainable subdivision neighbourhood design (RSSND) : case of Bangkok metropolitan region (BMR), Thailand an eco-efficiency modelling approach

Bangkok Metropolitan Region (BMR) is the centre for various major activities in Thailand including political, industry, agriculture, and commerce. Consequently, the BMR is the highest and most densely populated area in Thailand. Thus, the demand for houses in the BMR is also the largest, especially in subdivision developments. For these reasons, the subdivision development in the BMR has increased substantially in the past 20 years and generated large numbers of subdivision developments (AREA, 2009; Kridakorn Na Ayutthaya & Tochaiwat, 2010). However, this dramatic growth of subdivision development has caused several problems including unsustainable development, especially for subdivision neighbourhoods, in the BMR. There have been rating tools that encourage the sustainability of neighbourhood design in subdivision development, but they still have practical problems. Such rating tools do not cover the scale of the development entirely; and they concentrate more on the social and environmental conservation aspects, which have not been totally accepted by the developers (Boonprakub, 2011; Tongcumpou & Harvey, 1994). These factors strongly confirm the need for an appropriate rating tool for sustainable subdivision neighbourhood design in the BMR. To improve level of acceptance from all stakeholders in subdivision developments industry, the new rating tool should be developed based on an approach that unites the social, environmental, and economic approaches, such as eco-efficiency principle. Eco-efficiency is the sustainability indicator introduced by the World Business Council for Sustainable Development (WBCSD) since 1992. The eco-efficiency is defined as the ratio of the product or service value according to its environmental impact (Lehni & Pepper, 2000; Sorvari et al., 2009). Eco-efficiency indicator is concerned to the business, while simultaneously, is concerned with to social and the environment impact. This study aims to develop a new rating tool named "Rating for sustainable subdivision neighbourhood design (RSSND)". The RSSND methodology is developed by a combination of literature reviews, field surveys, the eco-efficiency model development, trial-and-error technique, and the tool validation process. All required data has been collected by the field surveys from July to November 2010. The ecoefficiency model is a combination of three different mathematical models; the neighbourhood property price (NPP) model, the neighbourhood development cost (NDC) model, and the neighbourhood occupancy cost (NOC) model which are attributable to the neighbourhood subdivision design. The NPP model is formulated by hedonic price model approach, while the NDC model and NOC model are formulated by the multiple regression analysis approach. The trial-and-error technique is adopted for simplifying the complex mathematic eco-efficiency model to a user-friendly rating tool format. Credibility of the RSSND has been validated by using both rated and non-rated of eight subdivisions. It is expected to meet the requirements of all stakeholders which support the social activities of the residents, maintain the environmental condition of the development and surrounding areas, and meet the economic requirements of the developers.

Rating defence major project success : the role of personal attributes and stakeholder relationships

In this paper we develop and test a model of the associations between major project managers' personal attributes and project success in the context of the Australian Defence industry. In our model, emotional intelligence, cognitive flexibility and systemic thinking were hypothesised to relate to project success, mediated by internal and external stakeholder relationships. The model was tested in an online survey with 373 major project managers. Emotional intelligence and cognitive flexibility were found to be related to the development, quality and effectiveness of major project managers' relationships with both internal and external stakeholders; and these in turn were associated with their ratings of project success. Systemic thinking, however, had no relationship with either stakeholder relationships or project success. Additional research is needed to examine the contribution of a wider range of personal attributes to stakeholder relationships and project success, and to assess whether this model is applicable in other industries and types of projects.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

NRM engagement between remote dryland communities and government agencies : success factors from Australia

The management of dryland environments involves the interaction of multiple government agencies and citizens, and is required to respond to a wide range of responsibilities and aspirations for a given region. This paper focuses on the characteristics of engagement between management agencies and citizens in a dryland region, presented here as a series of success factors. These factors are based on empirical research carried out in the Lake Eyre Basin in Australia, one of the world’s largest inwardly draining basins. The results reinforce generic and dryland-specific factors supporting successful community engagement. The former, such as building trust, working in partnership, supporting community champions, and maintaining transparency, are necessary but insufficient for achieving successful community engagement in the case study region. In addition, community engagement in the case study region also required respecting the extreme conditions and extraordinary variability of the Basin and committing to longer timeframes even if the outcomes of community engagement are slow to accrue, in order to take advantage of opportunities in more prosperous times.

Fire performance of cold-formed steel wall panels and prediction of their fire resistance rating

Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing Light gauge Steel Frame (LSF) wall systems made of 1.15 mm G500 steel studs and varying plasterboard and insulation configurations (cavity and external insulation) using full scale fire tests. Suitable finite element models of LSF walls were then developed and validated by comparing with test results. In this study, the validated finite element models of LSF wall panels subject to standard fire conditions were used in a detailed parametric study to investigate the effects of important parameters such as steel grade and thickness, plasterboard screw spacing, plasterboard lateral restraint, insulation materials and load ratio on their performance under standard fire conditions. Suitable equations were proposed to predict the time–temperature profiles of LSF wall studs with eight different plasterboard-insulation configurations, and used in the finite element analyses. Finite element parametric studies produced extensive fire performance data for the LSF wall panels in the form of load ratio versus time and critical hot flange (failure) temperature curves for eight wall configurations. This data demonstrated the superior fire performance of externally insulated LSF wall panels made of different steel grades and thicknesses. It also led to the development of a set of equations to predict the important relationship between the load ratio and the critical hot flange temperature of LSF wall studs. Finally this paper proposes a simplified method to predict the fire resistance rating of LSF walls based on the two proposed set of equations for the load ratio–hot flange temperature and the time–temperature relationships.

Synthetic rating procedures for railway bridges

One of the most important parts of any Bridge Management System (BMS) is the condition assessment and rating of bridges. This paper, introduces a procedure for condition assessment, based on criticality and vulnerability analysis. According to this procedure, new rating equations are developed. The inventory data is used to determine the contribution of different critical factors such as environmental effects, flood, earthquake, wind, and vehicle impacts. The criticality of the components to live load and vulnerability of the components to the above critical factors are identified. Based on the criticality and the vulnerability of the components and criticality of factors, and by using the new rating equations, the condition assessment and the rating of the railway bridges and their components at the network level will be conducted. This method for the first time incorporates structural analysis, available knowledge of risk assessment in structural engineering standards, and the experience of structural engineers in a practical way to enhance the reliability of the condition assessment and rating a network of bridges.

The Credit Act Advisory System (CAAS) : conversion from an expert system prototype to a C++ commercial system

CAAS is a rule-based expert system, which provides advice on the Victorial Credit Act 1984. It is currently in commercial use, and has been developed in conjunction with a law firm. It uses an object-oriented hybrid reasoning approach. The system was initially prototyped using the expert system shell NExpert Object, and was then converted into the C++ language. In this paper we describe the advantages that this methodology has, for both commercial and research development.

Sustainability outcomes of infrastructure sustainability rating schemes for road projects

The construction and operation of infrastructure assets can have significant impact on society and the region. Using a sustainability assessment framework can be an effective means to build sustainability aspects into the design, construction and operation of infrastructure assets. The conventional evaluation processes and procedures for infrastructure projects do not necessarily measure the qualitative/quantitative effectiveness of all aspects of sustainability: environment, social wellbeing and economy. As a result, a few infrastructure sustainability rating schemes have been developed with a view to assess the level of sustainability attained in the infrastructure projects. These include: Infrastructure Sustainability (Australia); CEEQUAL (UK); and Envision (USA). In addition, road sector specific sustainability rating schemes such as Greenroads (USA) and Invest (Australia) have also been developed. These schemes address several aspects of sustainability with varying emphasis (weightings) on areas such as: use of resources; emission, pollution and waste; ecology; people and place; management and governance; and innovation. The attainment of sustainability of an infrastructure project depends largely on addressing the whole-of-life environmental issues. This study has analysed the rating schemes’ coverage of different environmental components for the road infrastructure under the five phases of a project: material, construction, use, maintenance and end-of-life. This is based on a comprehensive life cycle assessment (LCA) system boundary. The findings indicate that there is a need for the schemes to consider key (high impact) life cycle environmental components such as traffic congestion during construction, rolling resistance due to surface roughness and structural stiffness of the pavement, albedo, lighting, and end-of-life management (recycling) to deliver sustainable road projects.

The Mobile Application Rating Scale (MARS): A new tool to measure the quality of health mobile applications

Smartphone technology provides free or inexpensive access to mental health and wellbeing resources. As a result the use of mobile applications for these purposes has increased significantly in recent years. Yet, there is currently no app quality assessment alternative to the popular ‘star’-ratings, which are often unreliable. This presentation describes the development of the Mobile Application Rating Scale (MARS) a new measure for classifying and rating the quality of mobile applications. A review of existing literature on app and web quality identified 25 published papers, conference proceedings, and online resources (published since 1999), which identified 372 explicit quality criteria. Qualitative analysis identified five broad categories of app quality rating criteria: engagement, functionality, aesthetics, information quality, and overall satisfaction, which were refined into the 23-item MARS. Independent ratings of 50 randomly selected mental health and wellbeing mobile apps indicated the MARS had excellent levels of internal consistency (α = 0.92) and inter-rater reliability (ICC = 0.85). The MARS provides practitioners and researchers with an easy-to-use, simple, objective and reliable tool for assessing mobile app quality. It also provides mHealth professionals with a checklist for the design and development of high quality apps.

Fire resistance rating of light gauge steel frame walls exposed to realistic design fires : a review and development of time equivalent approach

This paper presents the details of research undertaken on the development of an energy based time equivalent approach for light gauge steel frame (LSF) walls. This research utilized an energy based time equivalent approach to obtain the fire resistance ratings (FRR) of LSF walls exposed to realistic design fires with respect to standard fire exposure [1]. It is based on the equal area concept of fire severity and relates to the amount of energy transferred to the member. The proposed method was used to predict the fire resistance of single and double plasterboard lined and externally insulated LSF walls. The predicted fire resistance ratings were compared with the results from finite element analyses and fire design rules for three different wall configurations. This paper presents the review of the available time equivalent approaches and the development of energy based time equivalent approach for the prediction of fire resistance ratings of LSF walls exposed to realistic design fires.

Productivity growth and biased technological change : Credit banks in Japan

This paper investigates the productivity change of Japanese credit banks with a Malmquist index and the input technological bias during 2000-2006. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity. Our analysis unambiguously shows that management of Shinkin banks has to be improved. These must be based on the improvement of technical efficiency and/or technological change, emulating the procedures of the best-practice banks, i.e., those banks with Malmquist productivity scores higher than one and simultaneously with technical efficiency and technological change higher than one.

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.

Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.