986 resultados para Monica Project Populations


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From the perspective of network, a project team’s social capital consists of conduits network, and resource exchange network. Prior research intensively studies the effect of the structure of conduits network on the team’s performance, assuming knowledge transfer is the causal mechanism linking conduits network to performance. This paper attempts to explore the interrelations between conduits network and knowledge network, and further distinguish the different influence between various conduit networks, and hypothesizes that a project team’s knowledge network mediates the effect of various conduit networks on the team’s performance. This research can enrich our knowledge of disparate influence of the various conduit networks on knowledge transfer, and imply some management practices to enhance the organization’s social capital, and hence improve the organization’s performance.

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Most infrastructure projects share the same characteristics in term of management aspects and shortcomings. Human factor is believed to be the major drawbacks due to the nature of unstructured problems which can further contribute to management conflicts. This growing complexity in infrastructure projects has shift the paradigm of policy makers to adopt Information Communication Technology (ICT) as a driving force. For this reason, it is vital to fully maximise and utilise the recent technologies to accelerate management process particularly in planning phase. Therefore, a lot of tools have been developed to assist decision making in construction project management. The variety of uncertainties and alternatives in decision making can be entertained by using useful tool such as Decision Support System (DSS). However, the recent trend shows that most DSS in this area only concentrated in model development and left few fundamentals of computing. Thus, most of them were found complicated and less efficient to support decision making within project team members. Due to the current incapability of many software aspects, it is desirable for DSS to provide more simplicity, better collaborative platform, efficient data manipulation and reflection to user needs. By considering these factors, the paper illustrates four challenges for future DSS development i.e. requirement engineering, communication framework, data management and interoperability, and software usability

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Building Information Modelling (BIM) is an information technology [IT] enabled approach to managing design data in the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry. BIM enables improved interdisciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. Despite the apparent benefits the adoption of BIM in practice has been slow. Workshops with industry focus groups were conducted to identify the industry needs, concerns and expectations from participants who had implemented BIM or were BIM “ready”. Factors inhibiting BIM adoption include lack of training, low business incentives, perception of lack of rewards, technological concerns, industry fragmentation related to uneven ICT adoption practices, contractual matters and resistance to changing current work practice. Successful BIM usage depends on collective adoption of BIM across the different disciplines and support by the client. The relationship of current work practices to future BIM scenarios was identified as an important strategy as the participants believed that BIM cannot be efficiently used with traditional practices and methods. The key to successful implementation is to explore the extent to which current work practices must change. Currently there is a perception that all work practices and processes must adopt and change for effective usage of BIM. It is acknowledged that new roles and responsibilities are emerging and that different parties will lead BIM on different projects. A contingency based approach to the problem of implementation was taken which relies upon integration of BIM project champion, procurement strategy, team capability analysis, commercial software availability/applicability and phase decision making and event analysis. Organizations need to understand: (a) their own work processes and requirements; (b) the range of BIM applications available in the market and their capabilities (c) the potential benefits of different BIM applications and their roles in different phases of the project lifecycle, and (d) collective supply chain adoption capabilities. A framework is proposed to support organizations selection of BIM usage strategies that meet their project requirements. Case studies are being conducted to develop the framework. The results of the preliminary design management case study is presented for contractor led BIM specific to the design and construct procurement strategy.

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The Safety Effectiveness Indicators (SEI) Project has used extensive research to determine what safety effectiveness measures can be developed by industry, for industry use to improve its safety performance. These indicators can measure how effectively the 13 safety management tasks1 (SMTs) selected for this workbook are undertaken. Currently, positive performance indicators (PPIs) are only able to measure the number of activities undertaken. They do not provide information on whether each activity is being undertaken effectively, and therefore do not provide data which can be used by industry to target areas of focus and improvement. The initial workbook contained six SMTs, and was piloted on various construction sites during August 2008. The workbook was refined through feedback from the pilot, and 13 SMTs were used in a field trial during the months of October, November and December 2008. The project team also carried out 12 focus groups in Brisbane, Canberra, Sydney and Melbourne during April, May and June 2008, and developed an initial format of this workbook through these groups and team workshops. Simplification of the language was a recurring theme, and we have attempted to do this throughout the project. The challenge has been to ensure we keep the descriptions short, to the point and relevant to all companies, without making them too specific. The majority of the construction industry participants also requested an alteration to the scale used, so a ‘Yes’/‘No’/’Not applicable’ format is used in this workbook. This workbook, based on industry feedback, is for use on site by various construction companies and contains 13 SMTs. However, you are invited to personalise the SEI tools to better suit your individual company and workplaces.

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Effective knowledge transfer can prevent the reinvention of systems and ideas as well as the repetition of errors. Doing so will save substantial time, as well as contribute to better performance of projects and project-based organisations (PBOs). Despite the importance of knowledge, PBOs face serious barriers to the effective transfer of knowledge, while their characteristics, such as unique and innovative approaches taken during every project, mean they have much to gain from knowledge transfer. As each new project starts, there is the strong potential to reinvent the process, rather than utilise learning from previous projects. In fact, rework is one of the primary factors contributing to construction industry's poor performance and productivity. Current literature has identified several barriers to knowledge transfer in organisational settings in general, and not specifically PBOs. However, PBOs significantly differ from other types of organisations. PBOs operate mainly on temporary projects, where time is a crucial factor and people are more mobile than in other organisational settings. The aim of this research is to identify the key barriers that prevent effective knowledge transfer for PBOs, exclusively. Interviews with project managers and senior managers of PBOs complement the analysis of the literature and provide professional expertise. This research is crucial to gaining a better understanding of obstacles that hinder knowledge transfer in projects. The main contribution of this research is exclusive for PBO, list of key barriers that organisation and project managers need to consider to ensure effective knowledge transfer and better project management.

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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 Semester 1 2007, a Monitoring Student Engagement study, conducted as part of the Enhancing Transition at Queensland University of Technology (ET@QUT) Project and extending earlier work in the Project by Arora (2006), aimed at mapping the processes and resources used at that time to identify, monitor and manage students in their first year who were at risk of leaving QUT (Shaw, 2007). This identified a lack of documentation of the processes and resources used and revealed an ad-hoc rather than holistic and systematic approach to monitoring student engagement. One of Shaw’s recommendations was to: “To introduce a centralised case management approach to student engagement” (p. 14). That provided the genesis for the Student Success Project that is being reported on here. The aim of the Student Success Project is to trial, evaluate and ultimately establish holistic and systematic ways of helping students who appear to be at-risk of failing or withdrawing from a unit to persist and succeed. Students are profiled as being at-risk if they are absent from more than 2 tutorials in a row without contacting their tutor or if they fail to submit their first assignment. A Project Officer makes personal contact with these students to suggest ways they can get further assistance depending on their situation.

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This document reports on the Innovations Working Group that met at the 10th International Conference “Models in Developing Mathematics Education” from the 11-17th September 2009 in Dresden, Saxony. It briefly describes the over arching and consistent themes that emerged from the numerous papers presented. The authors and titles of each of the papers presented will be listed in Table 2.

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The Exercise for Health program is a telephone-delivered exercise intervention for women with breast cancer (BC) living in regional Queensland. The effect of the program is being evaluated in the context of a randomised controlled trial. Consenting, newly diagnosed BC patients, treated in one of 8 regional Queensland hospitals, were randomly allocated to telephone-based exercise counselling (EC) or usual care (UC) at 6-weeks post-surgery. EC participants received an exercise workbook and 16 calls from an exercise physiologist over 8 months. Physical activity levels (PA) (Active Australia & CHAMPS), quality-of-life (FACTB+4), upper-body function (DASH) and fatigue (FACIT-Fatigue) were assessed at baseline (4-6 weeks post-surgery), 6- and 12-months post-surgery. Preliminary analyses of available 6-month data were conducted using t-tests and repeated measures ANCOVAs. Participating women (n=143; EC n=73, UC n=70) were aged 53±9 years and 30% met PA guidelines at baseline. Up to two thirds of the women received adjuvant therapy during the first 6 months following surgery. Greater improvements (mean change+SD) occurred for the EC vs UC group in weekly sessions of walking (1.83±4.3 vs -0.5±5.5, p=0.029) moderate-vigorous PA (5.0±6.5 vs -1.1±6.1, p=0.005) and strength training (1.9±2.9 vs -0.5±4.2 p<0.001), and in upper-body function, reflected by lower log-transformed disability scores (-0.34±0.44 vs -0.17±0.28, p=0.038). More EC than UC participants met PA guidelines at 6 months (46.3% vs 32.7%). Preliminary findings from this ongoing trial suggest that the telephone is a feasible and effective medium for delivering exercise counselling to newly diagnosed BC patients living in regional areas.

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Campus Kindergarten is a community-based centre for early childhood education and care located on campus at the University of Queensland (UQ) in Brisbane, Australia. Being located within this diverse community has presented many opportunities for Campus Kindergarten. It is creating and embracing possibilities that has formed the basis for ongoing projects for children and teachers involving research and investigation. In 2002 Campus Kindergarten embarked on a collaborative project with the Art Museum bringing together these two departments within the university community.

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There is increasing agreement that understanding complexity is important for project management because of difficulties associated with decision-making and goal attainment which appear to stem from complexity. However the current operational definitions of complex projects, based upon size and budget, have been challenged and questions have been raised about how complexity can be measured in a robust manner that takes account of structural, dynamic and interaction elements. Thematic analysis of data from 25 in-depth interviews of project managers involved with complex projects, together with an exploration of the literature reveals a wide range of factors that may contribute to project complexity. We argue that these factors contributing to project complexity may define in terms of dimensions, or source characteristics, which are in turn subject to a range of severity factors. In addition to investigating definitions and models of complexity from the literature and in the field, this study also explores the problematic issues of ‘measuring’ or assessing complexity. A research agenda is proposed to further the investigation of phenomena reported in this initial study.

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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.