382 resultados para Management Service Organizations


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This study aimed to explore how a new model of integrated primary/secondary care for type 2 diabetes management, the Brisbane South Complex Diabetes Service (BSCDS), related to improved diabetes management in a selected group of patients. We used a qualitative research design to obtain detailed accounts from the BSCDS via semi-structured interviews with 10 patients. The interviews were fully transcribed and systematically coded using a form of thematic analysis. Participants’ responses were grouped in relation to: (1) Patient-centred care; (2) Effective multiprofessional teamwork; and (3) Empowering patients. The key features of this integrated primary/secondary care model were accessibility and its delivery within a positive health care environment, clear and supportive interpersonal communication between patients and health care providers, and patients seeing themselves as being part of the team-based care. The BSCDS delivered patient-centred care and achieved patient engagement in ways that may have contributed to improved type 2 diabetes management in these participants.

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The decentralisation reform in Indonesia has mandated the Central Government to transfer some functions and responsibilities to local governments including the transfer of human resources, assets and budgets. Local governments became giant asset holders almost overnight and most were ill prepared to handle these transformations. Assets were transferred without analysing local government need, ability or capability to manage the assets and no local government was provided with an asset management framework. Therefore, the aim of this research is to develop a Public Asset Management Framework for provincial governments in Indonesia, especially for infrastructure and real property assets. This framework will enable provincial governments to develop integrated asset management procedures throughout asset‘s lifecycle. Achieving the research aim means answering the following three research questions; 1) How do provincial governments in Indonesia currently manage their public assets? 2) What factors influence the provincial governments in managing these public assets? 3) How is a Public Asset Management Framework developed that is specific for the Indonesian provincial governments‘ situation? This research applied case studies approach after a literature review; document retrieval, interviews and observations were collated. Data was collected in June 2009 (preliminary data collection) and January to July 2010 in the major eastern Indonesian provinces. Once the public asset management framework was developed, a focus group was used to verify the framework. Results are threefold and indicate that Indonesian provincial governments need to improve the effectiveness and efficiency of current practice of public asset management in order to improve public service quality. The second result shows that the 5 major concerns that influence the local government public asset management processes are asset identification and inventory systems, public asset holding, asset guidance and legal arrangements, asset management efficiency and effectiveness, and, human resources and their organisational arrangements. The framework was then applied to assets already transferred to local governments and so included a system of asset identification and a needs analysis to classify the importance of these assets to local governments, their functions and responsibilities in delivering public services. Assets that support local government functions and responsibilities will then be managed using suitable asset lifecycle processes. Those categorised as surplus assets should be disposed. Additionally functions and responsibilities that do not need an asset solution should be performed directly by local governments. These processes must be measured using performance measurement indicators. All these stages should be guided and regulated with sufficient laws and regulations. Constant improvements to the quality and quantity of human resources hold an important role in successful public asset management processes. This research focuses on developing countries, and contributes toward the knowledge of a Public Asset Management Framework at local government level, particularly Indonesia. The framework provides local governments a foundation to improve their effectiveness and efficiency in managing public assets, which could lead to improved public service quality. This framework will ensure that the best decisions are made throughout asset decision ownership and provide a better asset life cycle process, leading to selection of the most appropriate asset, improve its acquisition and delivery process, optimise asset performance, and provide an appropriate disposal program.

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In Amci Pty Ltd ACN 124 249 485 v Corcoal Management Pty Ltd [2013] QSC 50 Jackson J considered an application for an order under r117 of the Uniform Civil Procedure Rules 1999 (Qld) (UCPR) in relation to informal service of an originating process on a corporation registered in the Ajman Free Zone in the United Arab Emirates. The decision appears to be the first time a Queensland court has examined the scope of r117 of the UCPR, and relevant considerations influencing the exercise of the discretion under the rule, when the defendant is outside Australia.

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Despite its potential multiple contributions to sustainable policy objectives, urban transit is generally not widely used by the public in terms of its market share compared to that of automobiles, particularly in affluent societies with low-density urban forms like Australia. Transit service providers need to attract more people to transit by improving transit quality of service. The key to cost-effective transit service improvements lies in accurate evaluation of policy proposals by taking into account their impacts on transit users. If transit providers knew what is more or less important to their customers, they could focus their efforts on optimising customer-oriented service. Policy interventions could also be specified to influence transit users’ travel decisions, with targets of customer satisfaction and broader community welfare. This significance motivates the research into the relationship between urban transit quality of service and its user perception as well as behaviour. This research focused on two dimensions of transit user’s travel behaviour: route choice and access arrival time choice. The study area chosen was a busy urban transit corridor linking Brisbane central business district (CBD) and the St. Lucia campus of The University of Queensland (UQ). This multi-system corridor provided a ‘natural experiment’ for transit users between the CBD and UQ, as they can choose between busway 109 (with grade-separate exclusive right-of-way), ordinary on-street bus 412, and linear fast ferry CityCat on the Brisbane River. The population of interest was set as the attendees to UQ, who travelled from the CBD or from a suburb via the CBD. Two waves of internet-based self-completion questionnaire surveys were conducted to collect data on sampled passengers’ perception of transit service quality and behaviour of using public transit in the study area. The first wave survey is to collect behaviour and attitude data on respondents’ daily transit usage and their direct rating of importance on factors of route-level transit quality of service. A series of statistical analyses is conducted to examine the relationships between transit users’ travel and personal characteristics and their transit usage characteristics. A factor-cluster segmentation procedure is applied to respodents’ importance ratings on service quality variables regarding transit route preference to explore users’ various perspectives to transit quality of service. Based on the perceptions of service quality collected from the second wave survey, a series of quality criteria of the transit routes under study was quantitatively measured, particularly, the travel time reliability in terms of schedule adherence. It was proved that mixed traffic conditions and peak-period effects can affect transit service reliability. Multinomial logit models of transit user’s route choice were estimated using route-level service quality perceptions collected in the second wave survey. Relative importance of service quality factors were derived from choice model’s significant parameter estimates, such as access and egress times, seat availability, and busway system. Interpretations of the parameter estimates were conducted, particularly the equivalent in-vehicle time of access and egress times, and busway in-vehicle time. Market segmentation by trip origin was applied to investigate the difference in magnitude between the parameter estimates of access and egress times. The significant costs of transfer in transit trips were highlighted. These importance ratios were applied back to quality perceptions collected as RP data to compare the satisfaction levels between the service attributes and to generate an action relevance matrix to prioritise attributes for quality improvement. An empirical study on the relationship between average passenger waiting time and transit service characteristics was performed using the service quality perceived. Passenger arrivals for services with long headways (over 15 minutes) were found to be obviously coordinated with scheduled departure times of transit vehicles in order to reduce waiting time. This drove further investigations and modelling innovations in passenger’ access arrival time choice and its relationships with transit service characteristics and average passenger waiting time. Specifically, original contributions were made in formulation of expected waiting time, analysis of the risk-aversion attitude to missing desired service run in the passengers’ access time arrivals’ choice, and extensions of the utility function specification for modelling passenger access arrival distribution, by using complicated expected utility forms and non-linear probability weighting to explicitly accommodate the risk of missing an intended service and passenger’s risk-aversion attitude. Discussions on this research’s contributions to knowledge, its limitations, and recommendations for future research are provided at the concluding section of this thesis.

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Business process management systems (BPMS) belong to a class of enterprise information systems that are characterized by the dependence on explicitly modeled process logic. Through the process logic, it is relatively easy to manage explicitly the routing and allocation of work items along a business process through the system. Inspired by the DeLone and McLean framework, we theorize that these process-aware system features are important attributes of system quality, which in turn will elevate key user evaluations such as perceived usefulness, and usage satisfaction. We examine this theoretical model using data collected from four different, mostly mature BPM system projects. Our findings validate the importance of input quality as well as allocation and routing attributes as antecedents of system quality, which, in turn, determines both usefulness and satisfaction with the system. We further demonstrate how service quality and workflow dependency are significant precursors to perceived usefulness. Our results suggest the appropriateness of a multi-dimensional conception of system quality for future research, and provide important design-oriented advice for the design and configuration of BPMSs.

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The purpose of Business Process Management (BPM) is to increase the efficiency and effectiveness of organizational processes through improvement and innovation. Despite a common understanding that culture is an important element in these efforts, there is a dearth of theoretical and empirical research on culture as a facilitator of successful BPM. We develop the BPM culture construct and propose a validated instrument with which to measure organizational cultures’ support of BPM. The operationalization of the BPM culture concept provides a theoretical foundation for future research and a tool to assist organizations in developing a cultural environment that supports successful BPM.

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Geographical market expansion is included in various definitions of entrepreneurship as it entails the opening up of new markets (for example, Davidsson 2003). Expansion into new international markets and launch of new products in international markets are also consistent with definitions of entrepreneurship which center on the pursuit of opportunities {e.g.\Stevenson, 1983 #922;Gartner, 1993 #931}. Accordingly, the decision by managers of small, internationally active businesses to continue to internationalize can be viewed as an entrepreneurial act. In spite of the fact that both start-ups and existing firms can behave entrepreneurially by expanding into new international markets, the attention of entrepreneurship researchers interested in international activities has largely focused on international new ventures (INVs); that is, business organizations that internationalize from inception (Oviatt, and McDougall 1994; Oviatt, and McDougall 1997). Consequently, pursuit of international opportunities by established small and medium-sized enterprises (SMEs) lacks theoretical understanding and empirical investigation through an entrepreneurship lens. This paper contributes to the body of knowledge at the entrepreneurship-internationalization interface by testing whether Stevenson’s opportunity-based conceptualization of entrepreneurial management (Stevenson 1983; Stevenson and Gumpert 1985; Stevenson and Jarillo 1990) can explain the attainment of continued entrepreneurial outcomes by SMEs operating in foreign markets. We choose Stevenson’s conceptualization as it gauges firm-level characteristics that are theorized to facilitate the pursuit of entrepreneurial opportunities, which arguably is at the heart of SMEs’ continued venturing into international markets.

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Lean strategies have been developed to eliminate or reduce manufacturing waste and thus improve operational efficiency in manufacturing processes. However, implementing lean strategies requires a large amount of resources and, in practice, manufacturers encounter difficulties in selecting appropriate lean strategies within their resource constraints. There is currently no systematic methodology available for selecting appropriate lean strategies within a manufacturer's resource constraints. In the lean transformation process, it is also critical to measure the current and desired leanness levels in order to clearly evaluate lean implementation efforts. Despite the fact that many lean strategies are utilized to reduce or eliminate manufacturing waste, little effort has been directed towards properly assessing the leanness of manufacturing organizations. In practice, a single or specific group of metrics (either qualitative or quantitative) will only partially measure the overall leanness. Existing leanness assessment methodologies do not offer a comprehensive evaluation method, integrating both quantitative and qualitative lean measures into a single quantitative value for measuring the overall leanness of an organization. This research aims to develop mathematical models and a systematic methodology for selecting appropriate lean strategies and evaluating the leanness levels in manufacturing organizations. Mathematical models were formulated and a methodology was developed for selecting appropriate lean strategies within manufacturers' limited amount of available resources to reduce their identified wastes. A leanness assessment model was developed by using the fuzzy concept to assess the leanness level and to recommend an optimum leanness value for a manufacturing organization. In the proposed leanness assessment model, both quantitative and qualitative input factors have been taken into account. Based on program developed in MATLAB and C#, a decision support tool (DST) was developed for decision makers to select lean strategies and evaluate the leanness value based on the proposed models and methodology hence sustain the lean implementation efforts. A case study was conducted to demonstrate the effectiveness of these proposed models and methodology. Case study results suggested that out of 10 wastes identified, the case organization (ABC Limited) is able to improve a maximum of six wastes from the selected workstation within their resource limitations. The selected wastes are: unnecessary motion, setup time, unnecessary transportation, inappropriate processing, work in process and raw material inventory and suggested lean strategies are: 5S, Just-In-Time, Kanban System, the Visual Management System (VMS), Cellular Manufacturing, Standard Work Process using method-time measurement (MTM), and Single Minute Exchange of Die (SMED). From the suggested lean strategies, the impact of 5S was demonstrated by measuring the leanness level of two different situations in ABC. After that, MTM was suggested as a standard work process for further improvement of the current leanness value. The initial status of the organization showed a leanness value of 0.12. By applying 5S, the leanness level significantly improved to reach 0.19 and the simulation of MTM as a standard work method shows the leanness value could be improved to 0.31. The optimum leanness value of ABC was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level to the case organization. Sensitivity analsysis and a t-test were also performed to validate the model proposed. This research advances the current knowledge base by developing mathematical models and methodologies to overcome lean strategy selection and leanness assessment problems. By selecting appropriate lean strategies, a manufacturer can better prioritize implementation efforts and resources to maximize the benefits of implementing lean strategies in their organization. The leanness index is used to evaluate an organization's current (before lean implementation) leanness state against the state after lean implementation and to establish benchmarking (the optimum leanness state). Hence, this research provides a continuous improvement tool for a lean manufacturing organization.

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Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

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This article presents the first narrative analysis of the areas of research that have developed within the destination marketing field since its commencement in 1973. Given the broad extent of the field, and the absence of any previous reviews in four decades, a key challenge is in providing a focus for such a disparate body of knowledge. The review is structured around one principal question: ‘To what extent is the Destination Marketing Organisation (DMO) responsible for the competitiveness of the destination’? In pursuit of this underlying question, we address a number of themes including nomenclature and the DMO, the evolution of the destination marketing literature, competitiveness as the DMO reason d’être, and DMO effectiveness including issues of branding and positioning, and future research themes in the field.

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In this research, we suggest appropriate information technology (IT) governance structures to manage the cloud computing resources. The interest in acquiring IT resources a utility is gaining momentum. Cloud computing resources present organizations with opportunities to manage their IT expenditure on an ongoing basis, and are providing organizations access to modern IT resources to innovate and manage their continuity. However, cloud computing resources are no silver bullet. Organizations would need to have appropriate governance structures and policies in place to ensure its effective management and fit into existing business processes to leverage the promised opportunities. Using a mixed method design, we identified four possible governance structures for managing the cloud computing resources. These structures are a chief cloud officer, a cloud management committee, a cloud service facilitation centre, and a cloud relationship centre. These governance structures ensure appropriate direction of cloud computing resources from its acquisition to fit into the organizations business processes.

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This research suggests information technology (IT) governance structures to manage cloud computing resources. The interest in acquiring IT resources as a utility from the cloud is gaining momentum. Cloud computing resources present organizations with opportunities to manage their IT expenditure on an ongoing basis, and are providing organizations access to modern IT resources to innovate and manage their continuity. However, cloud computing resources are no silver bullet. Organizations would need to have appropriate governance structures and policies in place to manage the cloud resources. The subsequent decisions from these governance structures will ensure effective management of cloud resources. This management will facilitate a better fit of cloud resources into organizations existing processes to achieve business (process-level) and financial (firm-level) objectives. Using a triangulation approach, we suggest four possible governance structures for managing the cloud computing resources. These structures are a chief cloud officer, a cloud management committee, a cloud service facilitation centre, and a cloud relationship centre. We also propose that these governance structures would relate to organizations cloud-related business objectives directly and indirectly to cloud-related financial objectives. Perceptive field survey data from actual and prospective cloud service adopters confirmed that the suggested structures would contribute directly to cloud-related business objectives and indirectly to cloud-related financial objectives.

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This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include a definition of KG in PBOs, a conceptual framework to investigate KG and a methodological framework for empirical inquiry into KG in PBO settings. Our definition highlights the contingent nature of KG processes in relation to their organizational context. The conceptual framework addresses macro- and micro-level elements of KG and their interaction. The methodological framework proposes five different research approaches, structured by differentiation and integration of various ontological and epistemological stances. Together these contributions provide a novel platform for understanding KG in PBOs and developing new insights into the design and execution of research on KG within PBOs.

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Research and practice has observed a shift toward service-oriented approaches that depend on input from users and community as co-producers of services. Yet, in delivering public infrastructure the focus is still on assets rather than services. The contribution of external stakeholders in the co-production of public services is still limited. Using the Policy Delphi with a panel of experts, we found that although practitioners understand the need for asset management to follow the service approach, guidelines and policies still lack that service-centric perspective. Findings revealed a range of obstacles to effective service delivery, related to the sub-optimal involvement of stakeholders’, asymmetric levels of power, the lack of accountability, transparency and availability of government, and the lack of genuine consultations between government and stakeholder groups. The paper concludes by offering directions and strategies for asset managers and policymakers to support and reconnect disengaged government-citizen relations for optimal service delivery outcomes in asset management.

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Emergency management and climate change adaptation will increasingly challenge all levels of government because of three main factors. First, Australia is extremely vulnerable to the impacts of climate change, particularly through the increasing frequency, duration and/or intensity of disasters such as floods and bushfires. Second, the system of government that divides powers by function and level can often act as a barrier to a well-integrated response. Third, policymaking processes struggle to cope with such complex inter-jurisdictional issues. This paper discusses these factors and explores the nature of the challenge for Australian governments. Investigations into the 2009 Victorian bushfires, the 2011 Perth Hills bushfires, and the 2011 Brisbane floods offer an indication of the challenges ahead and it is argued that there is a need to: improve community engagement and communication; refocus attention on resilience; improve interagency communication and collaboration; and, develop institutional arrangements that support continual improvement and policy learning. These findings offer an opportunity for improving responses as well as a starting point for integrating disaster risk management and climate change adaptation policies. The paper is based on the preliminary findings of an NCCARF funded research project: The Right Tool for the Job: Achieving climate change adaptation outcomes through improved disaster management policies, planning and risk management strategies involving Griffith University and RMIT. It should be noted from the outset that the purpose of this research project is not to criticise the actions of emergency service workers and volunteers who do an incredible job under extreme circumstances, often risking their own lives in the process. The aim is simply to offer emergency management agencies the opportunity to step back and rethink their overall approach to the challenge they face in the light of the impacts of climate change.