994 resultados para Asset structure


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Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

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A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.

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This paper presents a comparative study of primarily Australian (and limited international) practices and guidelines on Buildings Asset Management (BAM). The objective of this study was to identify potential gaps in current practices and potential areas of research for further improvement. The paper starts with an overview of BAM. Later sections cover current BAM practices and guidelines across different states of Australia; give a limited overview of international practices and concludes with the authors’ observations.

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Australias civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. To effectively manage road infrastructures, road agencies firstly need to optimise the expenditure for data collection whilst not jeopardising the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates can be accurately calculated. Finally, the prediction of budgets for maintenance and rehabilitation must be reasonably reliable.

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Historically, asset management focused primarily on the reliability and maintainability of assets; organisations have since then accepted the notion that a much larger array of processes govern the life and use of an asset. With this, asset management’s new paradigm seeks a holistic, multi-disciplinary approach to the management of physical assets. A growing number of organisations now seek to develop integrated asset management frameworks and bodies of knowledge. This research seeks to complement existing outputs of the mentioned organisations through the development of an asset management ontology. Ontologies define a common vocabulary for both researchers and practitioners who need to share information in a chosen domain. A by-product of ontology development is the realisation of a process architecture, of which there is also no evidence in published literature. To develop the ontology and subsequent asset management process architecture, a standard knowledge-engineering methodology is followed. This involves text analysis, definition and classification of terms and visualisation through an appropriate tool (in this case, the Protégé application was used). The result of this research is the first attempt at developing an asset management ontology and process architecture.

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A study investigated the reliability and construct validity of the Children's Depression Scale. The revised subscales were shown to have strong construct and face validity and high reliability.

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The crystal structure of the hydrated proton-transfer compound of the drug quinacrine [rac-N'-(6-chloro-2-methoxyacridin-9-yl)-N,N-diethylpentane-1,4-diamine] with 4,5-dichlorophthalic acid, C23H32ClN3O2+ . 2(C8H3Cl2O4-).4H2O (I), has been determined at 200 K. The four labile water molecules of solvation form discrete ...O--H...O--H... hydrogen-bonded chains parallel to the quinacrine side chain, the two N--H groups of which act as hydrogen-bond donors for two of the water acceptor molecules. The other water molecules, as well as the acridinium H atom, also form hydrogen bonds with the two anion species and extend the structure into two-dimensional sheets. Between these sheets there are also weak cation--anion and anion--anion pi-pi aromatic ring interactions. This structure represents only the third example of a simple quinacrine derivative for which structural data are available but differs from the other two in that it is unstable in the X-ray beam due to efflorescence, probably associated with the destruction of the unusual four-membered water chain structures.

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The research on project learning has recognised the significance of knowledge transfer in project based organisations (PBOs). Effective knowledge transfer across projects avoids reinventions, enhances knowledge creation and saves lots of time that is crucial in project environment. In order to facilitate knowledge transfer, many PBOs have invested lots of financial and human resources to implement IT-based knowledge repository. However, some empirical studies found that employees would rather turn for knowledge to colleagues despite their ready access to IT-based knowledge repository. Therefore, it is apparent that social networks play a pivotal role in the knowledge transfer across projects. Some scholars attempt to explore the effect of network structure on knowledge transfer and performance, however, focused only on egocentric networks and the groups’ internal social networks. It has been found that the project’s external social network is also critical, in that the team members can not handle critical situations and accomplish the projects on time without the assistance and knowledge from external sources. To date, the influence of the structure of a project team’s internal and external social networks on project performance, and the interrelation between both networks are barely known. In order to obtain such knowledge, this paper explores the interrelation between the structure of a project team’s internal and external social networks, and their effect on the project team’s performance. Data is gathered through survey questionnaire distributed online to respondents. Collected data is analysed applying social network analysis (SNA) tools and SPSS. The theoretical contribution of this paper is the knowledge of the interrelation between the structure of a project team’s internal and external social networks and their influence on the project team’s performance. The practical contribution lies in the guideline to be proposed for constructing the structure of project team’s internal and external social networks.

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In recent years, practitioners and researchers alike have turned their attention to knowledge management (KM) in order to increase organisational performance (OP). As a result, many different approaches and strategies have been investigated and suggested for how knowledge should be managed to make organisations more effective and efficient. However, most research has been undertaken in the for-profit sector, with only a few studies focusing on the benefits nonprofit organisations might gain by managing knowledge. This study broadly investigates the impact of knowledge management on the organisational performance of nonprofit organisations. Organisational performance can be evaluated through either financial or non-financial measurements. In order to evaluate knowledge management and organisational performance, non-financial measurements are argued to be more suitable given that knowledge is an intangible asset which often cannot be expressed through financial indicators. Non-financial measurement concepts of performance such as the balanced scorecard or the concept of Intellectual Capital (IC) are well accepted and used within the for-profit and nonprofit sectors to evaluate organisational performance. This study utilised the concept of IC as the method to evaluate KM and OP in the context of nonprofit organisations due to the close link between KM and IC: Indeed, KM is concerned with managing the KM processes of creating, storing, sharing and applying knowledge and the organisational KM infrastructure such as organisational culture or organisational structure to support these processes. On the other hand, IC measures the knowledge stocks in different ontological levels: at the individual level (human capital), at the group level (relational capital) and at the organisational level (structural capital). In other words, IC measures the value of the knowledge which has been managed through KM. As KM encompasses the different KM processes and the KM infrastructure facilitating these processes, previous research has investigated the relationship between KM infrastructure and KM processes. Organisational culture, organisational structure and the level of IT support have been identified as the main factors of the KM infrastructure influencing the KM processes of creating, storing, sharing and applying knowledge. Other research has focused on the link between KM and OP or organisational effectiveness. Based on existing literature, a theoretical model was developed to enable the investigation of the relation between KM (encompassing KM infrastructure and KM processes) and IC. The model assumes an association between KM infrastructure and KM processes, as well as an association between KM processes and the various levels of IC (human capital, structural capital and relational capital). As a result, five research questions (RQ) with respect to the various factors of the KM infrastructure as well as with respect to the relationship between KM infrastructure and IC were raised and included into the research model: RQ 1 Do nonprofit organisations which have a Hierarchy culture have a stronger IT support than nonprofit organisations which have an Adhocracy culture? RQ 2 Do nonprofit organisations which have a centralised organisational structure have a stronger IT support than nonprofit organisations which have decentralised organisational structure? RQ 3 Do nonprofit organisations which have a stronger IT support have a higher value of Human Capital than nonprofit organisations which have a less strong IT support? RQ 4 Do nonprofit organisations which have a stronger IT support have a higher value of Structural Capital than nonprofit organisations which have a less strong IT support? RQ 5 Do nonprofit organisations which have a stronger IT support have a higher value of Relational Capital than nonprofit organisations which have a less strong IT support? In order to investigate the research questions, measurements for IC were developed which were linked to the main KM processes. The final KM/IC model contained four items for evaluating human capital, five items for evaluating structural capital and four items for evaluating relational capital. The research questions were investigated through empirical research using a case study approach with the focus on two nonprofit organisations providing trade promotions services through local offices worldwide. Data for the investigation of the assumptions were collected via qualitative as well as quantitative research methods. The qualitative study included interviews with representatives of the two participating organisations as well as in-depth document research. The purpose of the qualitative study was to investigate the factors of the KM infrastructure (organisational culture, organisational structure, IT support) of the organisations and how these factors were related to each other. On the other hand, the quantitative study was carried out through an online-survey amongst staff of the various local offices. The purpose of the quantitative study was to investigate which impact the level of IT support, as the main instrument of the KM infrastructure, had on IC. Overall several key themes were found as a result of the study: • Knowledge Management and Intellectual Capital were complementary with each other, which should be expressed through measurements of IC based on KM processes. • The various factors of the KM infrastructure (organisational culture, organisational structure and level of IT support) are interdependent. • IT was a primary instrument through which the different KM processes (creating, storing, sharing and applying knowledge) were performed. • A high level of IT support was evident when participants reported higher level of IC (human capital, structural capital and relational capital). The study supported previous research in the field of KM and replicated the findings from other case studies in this area. The study also contributed to theory by placing the KM research within the nonprofit context and analysing the linkage between KM and IC. From the managerial perspective, the findings gave clear indications that would allow interested parties, such as nonprofit managers or consultants to understand more about the implications of KM on OP and to use this knowledge for implementing efficient and effective KM strategies within their organisations.

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Physiological responses to environmental stress are increasingly well studied in scleractinian corals. This work reports a new stress-related skeletal structure we term clypeotheca. Clypeotheca was observed in several livecollected common reef-building coral genera and a two to three kya subfossil specimen from Heron Reef, Great Barrier Reef and consists of an epitheca-like skeletal wall that seals over the surface of parts of the corallum in areas of stress or damage. It appears to form from a coordinated process wherein neighboring polyps and adjoining coenosarc seal themselves off from the surrounding environment as they contract and die. Clypeotheca forms from inward skeletal centripetal growth at the edges of corallites and by the merging of flange-like outgrowths that surround individual spines over the surface of the coenosteum. Microstructurally, the merged flanges are similar to upsidedown dissepiments and true epitheca. Clypeotheca is interpreted primarily as a response to stress that may help protect the colony from invasion of unhealthy tissues by parasites or disease by retracting tissues in areas that have become unhealthy for the polyps. Identification of skeletal responses of corals to environmental stress may enable the frequency of certain types of environmental stress to be documented in past environments. Such data may be important for understanding the nature of reef dynamics through intervals of climate change and for monitoring the effects of possible anthropogenic stress in modern coral reef habitats.

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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.

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The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.