853 resultados para Process Management, Maturity Model, CMM, Delphi Study


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Epithelial to mesenchymal transition (EMT) is considered an important mechanism in tumor resistance to drug treatments; however, in vivo observation of this process has been limited. In this study we demonstrated an immediate and widespread EMT involving all surviving tumor cells following treatment of a mouse model of colorectal liver metastases with the vascular disruptive agent OXi4503. EMT was characterized by significant downregulation of E-cadherin, relocation and nuclear accumulation of b-catenin as well as significant upregulation of ZEB1 and vimentin. Concomitantly, significant temporal upregulation in hypoxia and the pro-angiogenic growth factors hypoxia-inducible factor 1-alpha, hepatocyte growth factor, vascular endothelial growth factor and transforming growth factor-beta were seen within the surviving tumor. The process of EMT was transient and by 5 days after treatment tumor cell reversion to epithelial morphology was evident. This reversal, termed mesenchymal to epithelial transition (MET) is a process implicated in the development of new metastases but has not been observed in vivo histologically. Similar EMT changes were observed in response to other antitumor treatments including chemotherapy, thermal ablation, and antiangiogenic treatments in our mouse colorectal metastasis model and in a murine orthotopic breast cancer model after OXi4503 treatment. These results suggest that EMT may be an early mechanism adopted by tumors in response to injury and hypoxic stress, such that inhibition of EMT in combination with other therapies could play a significant role in future cancer therapy.

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Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.

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Enterprise Resource Planning (ERP) software is the dominant strategic platform for supporting enterprise-wide business processes. However, it has been criticised for being inflexible and not meeting specific organisation and industry requirements. An alternative, Best of Breed (BoB), integrates components of standard package and/or custom software. The objective is to develop enterprise systems that are more closely aligned with the business processes of an organisation. A case study of a BoB implementation facilitates a comparative analysis of the issues associated with this strategy and the single vendor ERP alternative. The paper illustrates the differences in complexity of implementation, levels of functionality, business process alignment potential and associated maintenance.

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Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

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This research seeks a better and more detailed understanding of the processes of implementing design-led innovation in the mining equipment technology services (METS) sector, in a context where the traditional approach to manufacturing is being challenged. This longitudinal research specifically investigated the barriers to design-led innovation and opportunities that developed throughout this research, to understand how the organisation and culture of a METS company evolved, in order to progress towards design-led change. The significance of these findings is shown in the combined implementation of design imperatives leading towards design-led change at all business levels of an organisational structure.

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Phytochemical lures such as methyl eugenol (ME) and cue-lure are used in the management of Bactrocera fruit flies for monitoring and control. These lures are not just attractants, but also trigger physiological changes in males that lead to enhanced mating success. Additionally, in the cue-lure-responsive Bactrocera tryoni, females mated with lure-fed males exhibit changes in fecundity, remating receptivity and longevity. While the lures show current generation effects, no research has been carried out on possible multigenerational effects, although such effects have been hypothesized within a ‘sexy-son’ sexual selection model. In this study, we test for indirect, cross-generational effects of lure exposure in F1offspring of B. tryoni females mated with cue-lure-fed, zingerone-fed and lure-unfed (=control) males. The F1 attributes we recorded were immature development time, immature survival, adult survival and adult male lure foraging. No significant differences were found between treatments for any of the three life-history measurements, except that the offspring sired by zingerone-fed males had a longer egg development time than cue-lure and control offspring. However, indirect exposure to lures significantly enhanced the lure-foraging ability of F1 adult males. More offspring of cue-lure-fed males arrived at a lure source in both large flight cages and small laboratory cages over a 2-h period than did control males. The offspring of zingerone-fed males were generally intermediate between cue-lure and control offspring. This study provides the first evidence of a next generation effect of fruit fly male lures. While the results of this study support a ‘sexy-son’ sexual selection mechanism for the evolution of lure response in Bactrocera fruit flies, our discussion urges caution in interpreting our results in this way.

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This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.

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Decision-making for conservation is conducted within the margins of limited funding. Furthermore, to allocate these scarce resources we make assumptions about the relationship between management impact and expenditure. The structure of these relationships, however, is rarely known with certainty. We present a summary of work investigating the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that achieving robustness in conservation decisions can require a triage approach, and emphasize the need for managers to consider triage not as surrendering but as rational decision making to ensure species persistence in light of the urgency of the conservation problems, uncertainty, and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park, Indonesia. To conserve our environment, conservation managers must make decisions in the face of substantial uncertainty. Further, they must deal with the fact that limitations in budgets and temporal constraints have led to a lack of knowledge on the systems we are trying to preserve and on the benefits of the actions we have available (Balmford & Cowling 2006). Given this paucity of decision-informing data there is a considerable need to assess the impact of uncertainty on the benefit of management options (Regan et al. 2005). Although models of management impact can improve decision making (e.g.Tenhumberg et al. 2004), they typically rely on assumptions around which there is substantial uncertainty. Ignoring this 'model uncertainty', can lead to inferior decision-making (Regan et al. 2005), and potentially, the loss of the species we are trying to protect. Current methods used in ecology allow model uncertainty to be incorporated into the model selection process (Burnham & Anderson 2002; Link & Barker 2006), but do not enable decision-makers to assess how this uncertainty would change a decision. This is the basis of information-gap decision theory (info-gap); finding strategies most robust to model uncertainty (Ben-Haim 2006). Info-gap has permitted conservation biology to make the leap from recognizing uncertainty to explicitly incorporating severe uncertainty into decision-making. In this paper we present a summary of McDonald-Madden et al (2008a) who use an info-gap framework to address the impact of uncertainty in the functional representations of biological systems on conservation decision-making. Furthermore, we highlight the importance of two key elements limiting conservation decision-making - funding and knowledge - and how they interact to influence the best management strategy for a threatened species. Copyright © ASCE 2011.