An evaluation of viability of public private partnerships in social infrastructure procurement projects in Queensland, Australia

Public private partnerships (PPP) have been widely used as a method for public infrastructure project delivery not only locally and internationally, however the adoption of PPPs in social infrastructure procurement has still been very limited. The objective of this paper is to investigate the potential of implementation of current PPP framework in social affordable housing projects in South East Queensland. Data were collected from 22 interviewees with rich experiences in the industry. The findings of this study show that affordable housing investment have been considered by the industry practitioners as a risky business in comparison to other private rental housing investment. The main determents of the adoption of PPPs in social infrastructure project are the tenant-related factors, such as the inability of paying rent and the inability of caring the property. The study also suggests the importance of seeking strategic partnership with community-based organisation that has experiences in managing similar tenants’ profiles. Current PPP guideline is also viewed as inappropriate for the affordable housing projects, but the principle of VFM framework and risk allocation in PPPs still be applied to the affordable housing projects. This study helps to understand the viability of PPP in social housing procurement projects, and point out the importance of developing guideline for multi-stakeholder partnership and the expansion of the current VFM and PPPs guidelines.

Moving towards a knowledge city : Brisbane's experience in knowledge-based urban development

In the global knowledge economy, knowledge-intensive industries and knowledge workers are extensively seen as the primary factors to improve the welfare and competitiveness of cities. To attract and retain such industries and workers, cities produce knowledge-based urban development strategies, where such strategising is also an important development mechanism for cities and their economies. This paper investigates Brisbane’s knowledge-based urban development strategies that support generation, attraction, and retention of investment and talent. The paper provides a clear understanding on the policy frameworks, and relevant applications of Brisbane’s knowledge-based urban development experience in becoming a prosperous knowledge city.

Creativity, culture and tourism : the case of Istanbul and London film industries

During the last decade many cities have sought to promote creativity as a driver for economic growth. They have done this by encouraging specific sectors of creative industries. This paper focuses on the film industry as one of these sectors which also has a high level of interaction with place. Film industry, has had an important role in incubating the creativity potential. It can be a powerful magnet for creative people, fostering indigenous creativity and attracting outside talent, and might thus contribute to the formation of creative cities. This recent research suggests that the film industry has positively effect on tourism by increasing place recognition through the locations used in films and for cities that host film festivals. Film festivals provide events, workshops and experiences that allow visitors to express themselves through interaction with the place and its living culture. This paper examines the importance of creative industries for both urban development and sustainable tourism. To explore the relation between creative tourism, culture and the film industry and its effect on successful tourism planning this paper presents the preliminary findings of case studies of the film industry in Beyo

Spatial restructuring of cities in the age of knowledge economy : insights from Australian cities

In the age of knowledge economy, knowledge production, and where, how and by whom it is produced, has become one of the most important factors in determining the quality of life and competitiveness of a city. In different parts of the world, cities that are the centres of knowledge production are branded under different names, e.g. knowledge city, creative city, ubiquitous eco city, smart city. This paper focuses on the core building block of these cities: ‘knowledge precincts’ that are the catalytic magnet infrastructures impacting knowledge production. The paper discusses the increasing importance of knowledge-based urban development within the paradigm of knowledge economy, and the role of knowledge community precincts as an instrument to seed the foundation of knowledge production. This paper explores knowledge based urban development, particularly knowledge community precinct development, potentials of Sydney, Melbourne and Brisbane, and benchmarks them against Boston. The paper also draws conclusions and recommendations for other cities considering knowledge based development.

Intellectual disability and sexuality : attitudes of disability support staff and leisure industry employees

Background: The attitudes of support staff and others in the community towards the sexuality of individuals with an intellectual disability (ID) have the potential to influence opportunities for normalised life experiences in the area of sexuality. ----- Method: A sample of 169 disability support staff and 50 employees from leisure and services industries completed the Attitudes to Sexuality Questionnaires (Individuals with an Intellectual Disability [ASQ–ID], and Individuals from the General Population [ASQ–GP]). ----- Results: Support staff and leisure workers reported generally positive attitudes towards the sexuality of individuals with an ID, but men were seen as having less self-control than women. Support staff were more cautious in their views about parenting, and both groups considered a lower level of sexual freedom to be desirable for women with an ID compared to women who are developing typically. Conclusions Attitudes of both groups are generally quite positive in relation to ID and sexuality.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Evolutionary optimisation methods with uncertainty for modern multidisciplinary design in aeronautical engineering

One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.

Innovation and the city : a macromarketing approach to industry development

Purpose – The purpose of this paper is to propose and demonstrate the relevance of marketing systems, notably the process of product management and innovation, to urban development challenges. Design/methodology/approach – A macromarketing perspective is adopted to construe the city as a product and begin the application of the innovation process to urban management, following the steps commonly proposed for successful innovation in product management. An example of the application of the initial new product development steps of idea generation and opportunity identification is presented. Findings – The innovation process provides guidelines and checkpoints that enable corporations to improve the success rate of their development initiatives. Cities, like corporations, need to innovate in order to maintain their image and functionality, to provide a myriad benefits to their stakeholders and, thereby, to survive and grow. The example here shows how the preliminary NPD steps of idea generation and opportunity identification enrich the process of identifying and analysing new industry opportunities for a city. Practical implications – By conceptualising the city as a multifaceted product, the disciplined planning and evaluation processes pertinent to NPD success become relevant and helpful to practitioners responsible for urban planning, urban development and change. Originality/value – The paper shows how pertinent concepts and processes from marketing can be effectively applied to urban planning and economic development initiatives.

Value-mapping for major economic infrastructure projects

The establishment of corporate objectives regarding economic, environmental, social, and ethical responsibilities, to inform business practice, has been gaining credibility in the business sector since the early 1990’s. This is witnessed through (i) the formation of international forums for sustainable and accountable development, (ii) the emergence of standards, systems, and frameworks to provide common ground for regulatory and corporate dialogue, and (iii) the significant quantum of relevant popular and academic literature in a diverse range of disciplines. How then has this move towards greater corporate responsibility become evident in the provision of major urban infrastructure projects? The gap identified, in both academic literature and industry practice, is a structured and auditable link between corporate intent and project outcomes. Limited literature has been discovered which makes a link between corporate responsibility; project performance indicators (or critical success factors) and major infrastructure provision. This search revealed that a comprehensive mapping framework, from an organisation’s corporate objectives through to intended, anticipated and actual outcomes and impacts has not yet been developed for the delivery of such projects. The research problem thus explored is ‘the need to better identify, map and account for the outcomes, impacts and risks associated with economic, environmental, social and ethical outcomes and impacts which arise from major economic infrastructure projects, both now, and into the future’. The methodology being used to undertake this research is based on Checkland’s soft system methodology, engaging in action research on three collaborative case studies. A key outcome of this research is a value-mapping framework applicable to Australian public sector agencies. This is a decision-making methodology which will enable project teams responsible for delivering major projects, to better identify and align project objectives and impacts with stated corporate objectives.

A new day breaks for the Aussie film industry

The Australian film industry is evolving. The days when government film agencies handed out millions of taxpayers' dollars for filmmakers to produce "Australian stories" with little regard to commercial returns are limited. If the Australian film industry is to reach mainstream audiences – and increase its relevance – then filmmakers need to take greater notice of genre movies and the possibilities they create within the financial restraints of the local industry. The $20 million Aussie vampire movie, Daybreakers, is a prototype for how this can be achieved.

Experimental study of the mechanical properties of light gauge cold-formed steels at elevated temperatures

In recent times, light gauge cold-formed steel sections have been used extensively as primary load bearing structural members in many applications in the building industry. Fire safety design of structures using such sections has therefore become more important. Deterioration of mechanical properties of yield stress and elasticity modulus is considered the most important factor affecting the performance of steel structures in fires. Hence there is a need to fully understand the mechanical properties of light gauge cold-formed steels at elevated temperatures. A research project based on experimental studies was therefore undertaken to investigate the deterioration of mechanical properties of light gauge cold-formed steels. Tensile coupon tests were undertaken to determine the mechanical properties of these steels made of both low and high strength steels and thicknesses of 0.60, 0.80 and 0.95 mm at temperatures ranging from 20 to 800ºC. Test results showed that the currently available reduction factors are unsafe to use in the fire safety design of cold-formed steel structures. Therefore new predictive equations were developed for the mechanical properties of yield strength and elasticity modulus at elevated temperatures. This paper presents the details of the experimental study, and the results including the developed equations. It also includes details of a stress-strain model for light gauge cold-formed steels at elevated temperatures.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Rivalry within and between strategic networks : an investigation of the United States Automotive Industry

As a consequence of the increased incidence of collaborative arrangements between firms, the competitive environment characterising many industries has undergone profound change. It is suggested that rivalry is not necessarily enacted by individual firms according to the traditional mechanisms of direct confrontation in factor and product markets, but rather as collaborative orchestration between a number of participants or network members. Strategic networks are recognised as sets of firms within an industry that exhibit denser strategic linkages among themselves than other firms within the same industry. Based on this, strategic networks are determined according to evidence of strategic alliances between firms comprising the industry. As a result, a single strategic network represents a group of firms closely linked according to collaborative ties. Arguably, the collective outcome of these strategic relationships engineered between firms suggest that the collaborative benefits attributed to interorganisational relationships require closer examination in respect to their propensity to influence rivalry in intraindustry environments. Derived in large from the social sciences, network theory allows for the micro and macro examination of the opportunities and constraints inherent in the structure of relationships in strategic networks, establishing a relational approach upon which the conduct and performance of firms can be more fully understood. Research to date has yet to empirically investigate the relationship between strategic networks and rivalry. The limited research that has been completed utilising a network rationale to investigate competitive patterns in contemporary industry environments has been characterised by a failure to directly measure rivalry. Further, this prior research has typically embedded investigation in industry settings dominated by technological or regulatory imperatives, such as the microprocessor and airline industries. These industries, due to the presence of such imperatives, are arguably more inclined to support the realisation of network rivalry, through subscription to prescribed technological standards (eg., microprocessor industry) or by being bound by regulatory constraints dictating operation within particular market segments (airline industry). In order to counter these weaknesses, the proposition guiding research - Are patterns of rivalry predicted by strategic network membership? – is embedded in the United States Light Vehicles Industry, an industry not dominated by technological or regulatory imperatives. Further, rivalry is directly measured and utilised in research, thus distinguishing this investigation from prior research efforts. The timeframe of investigation is 1993 – 1999, with all research data derived from secondary sources. Strategic networks were defined within the United States Light Vehicles Industry based on evidence of horizontal strategic relationships between firms comprising the industry. The measure of rivalry used to directly ascertain the competitive patterns of industry participants was derived from the traditional Herfindahl Index, modified to account for patterns of rivalry observed at the market segment level. Statistical analyses of the strategic network and rivalry constructs found little evidence to support the contention of network rivalry; indeed, greater levels of rivalry were observed between firms comprising the same strategic network than between firms participating in opposing network structures. Based on these results, patterns of rivalry evidenced in the United States Light Vehicle Industry over the period 1993 – 1999 were not found to be predicted by strategic network membership. The findings generated by this research are in contrast to current theorising in the strategic network – rivalry realm. In this respect, these findings are surprising. The relevance of industry type, in conjunction with prevailing network methodology, provides the basis upon which these findings are contemplated. Overall, this study raises some important questions in relation to the relevancy of the network rivalry rationale, establishing a fruitful avenue for further research.