78 resultados para Values-based decision-making

em Aston University Research Archive


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The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

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Group decision making is the study of identifying and selecting alternatives based on the values and preferences of the decision maker. Making a decision implies that there are several alternative choices to be considered. This paper uses the concept of Data Envelopment Analysis to introduce a new mathematical method for selecting the best alternative in a group decision making environment. The introduced model is a multi-objective function which is converted into a multi-objective linear programming model from which the optimal solution is obtained. A numerical example shows how the new model can be applied to rank the alternatives or to choose a subset of the most promising alternatives.

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The goal of evidence-based medicine is to uniformly apply evidence gained from scientific research to aspects of clinical practice. In order to achieve this goal, new applications that integrate increasingly disparate health care information resources are required. Access to and provision of evidence must be seamlessly integrated with existing clinical workflow and evidence should be made available where it is most often required - at the point of care. In this paper we address these requirements and outline a concept-based framework that captures the context of a current patient-physician encounter by combining disease and patient-specific information into a logical query mechanism for retrieving relevant evidence from the Cochrane Library. Returned documents are organized by automatically extracting concepts from the evidence-based query to create meaningful clusters of documents which are presented in a manner appropriate for point of care support. The framework is currently being implemented as a prototype software agent that operates within the larger context of a multi-agent application for supporting workflow management of emergency pediatric asthma exacerbations. © 2008 Springer-Verlag Berlin Heidelberg.

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Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data. In this paper, we propose a semi-oriented radial measure, which permits the presence of variables which can take both negative and positive values. The model is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA: The modified slacks-based model suggested by Sharp et al. [Sharp, J.A., Liu, W.B., Meng, W., 2006. A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs. Journal of Operational Research Society 57 (11) 1–6] and the range directional model developed by Portela et al. [Portela, M.C.A.S., Thanassoulis, E., Simpson, G., 2004. A directional distance approach to deal with negative data in DEA: An application to bank branches. Journal of Operational Research Society 55 (10) 1111–1121]. A further example explores the advantages of using the new model.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

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Shared decision-making (SDM), a component of patient-centered care, is the process in which the clinician and patient both participate in decision-making about treatment; information is shared between the parties and both agree with the decision. Shared decision-making is appropriate for health care conditions in which there is more than one evidence-based treatment or management option that have different benefits and risks. The patient's involvement ensures that the decisions regarding treatment are sensitive to the patient's values and preferences. Audiologic rehabilitation requires substantial behavior changes on the part of patients and includes benefits to their communication as well as compromises and potential risks. This article identifies the importance of shared decision-making in audiologic rehabilitation and the changes required to implement it effectively.

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Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

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Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

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Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

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Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

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Supplier evaluation and selection problem has been studied extensively. Various decision making approaches have been proposed to tackle the problem. In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria rather than considering a single factor-cost. This paper reviews the literature of the multi-criteria decision making approaches for supplier evaluation and selection. Related articles appearing in the international journals from 2000 to 2008 are gathered and analyzed so that the following three questions can be answered: (i) Which approaches were prevalently applied? (ii) Which evaluating criteria were paid more attention to? (iii) Is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.

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Information systems have developed to the stage that there is plenty of data available in most organisations but there are still major problems in turning that data into information for management decision making. This thesis argues that the link between decision support information and transaction processing data should be through a common object model which reflects the real world of the organisation and encompasses the artefacts of the information system. The CORD (Collections, Objects, Roles and Domains) model is developed which is richer in appropriate modelling abstractions than current Object Models. A flexible Object Prototyping tool based on a Semantic Data Storage Manager has been developed which enables a variety of models to be stored and experimented with. A statistical summary table model COST (Collections of Objects Statistical Table) has been developed within CORD and is shown to be adequate to meet the modelling needs of Decision Support and Executive Information Systems. The COST model is supported by a statistical table creator and editor COSTed which is also built on top of the Object Prototyper and uses the CORD model to manage its metadata.

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Despite being in the business agenda for almost thirty years, stakeholder management is still an under explored field in the public management context. The investigation presented in this doctoral thesis aims to ensure that stakeholder management is a useful technique able to raise issues about power and interests to public organisation’s strategic management processes. Stakeholder theory is tested in an exploratory study carried out with English Local Authorities whose focus is place on decision-making. The findings derive from two distinct and complementary studies: a cross-sectional survey undertaken with chief executives based on the quantitative approach and a qualitative investigation based on cross-sectional case studies and in-depth interviews of validation. While the first study aimed to produce a reliable and comprehensive list of stakeholders able to raise issues in decision-making, the second study aimed to depict the arena in which decision-making comes about. The findings indicate that local government decision-making is a multistakeholder process in which influences are exerted according to stakeholders’ power and interest. The findings also indicate that local government managers should take into account these tissues to avoid losing resources and legitimacy from its environmental supporters. Another issue raised by the investigation is related to the ethics upon which these types of relationships are based. According to the evidence gathered throughout the investigation, the formal model of accountability does not cover the whole set of stakeholders engaged in the process.

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This research compared decision making processes in six Chinese state-owned enterprises during the period 1985 to 1988. The research objectives were: a) To examine changes in the managerial behaviour over a period of 1985 to 1988 with a focus on decision-making; b) Through this examination, to throw light on the means by which government policies on economic reform were implemented at the enterprise level; c) To illustrate problems encountered in the decentralization programme which was a major part of China's economic reform. The research was conducted by means of intensive interviews with more than eighty managers and a survey of documents relating to specific decisions. A total of sixty cases of decision-making were selected from five decision topics: purchasing of inputs, pricing of outputs, recruitment of labour, organizational change and innovation, which occurred in 1985 (or before) and in 1988/89. Data from the interviews were used to investigate environmental conditions, relations between the enterprise and its higher authority, interactions between management and the party system, the role of information, and effectiveness of regulations and government policies on enterprise management. The analysis of the data indicates that the decision processes in the different enterprises have some similarities in regard to actor involvement, the flow of decision activities, interactions with the authorities, information usage and the effect of regulations. Comparison of the same or similar decision contents over time indicates that the achievement of decentralization varied according to the topic of decision. Managerial authority was delegated to enterprises when the authorities relaxed their control over resource allocation. When acquisition of necessary resources is dependent upon the planning system or the decision matter is sensitive, because it involves change to the institutional framework (e.g. the Party), then a high degree of centralization was retained, resulting in a marginal change in managerial behaviour. The economic reform failed to increase decision efficiency and effectiveness of decision-making. The prevailing institutional frameworks were regarded as negative to the change. The research argues that the decision process is likely to be more contingent on the decision content than the organization. Three types of decision process have been conceptualized, each of them related to a certain type of decision content. This argument gives attention to the perspectives of institution and power in a way which facilitates an elaboration of organizational analysis. The problems encountered in the reform of China's industrial enterprises are identified and discussed. General recommendations for policies of further reform are offered, based on the analysis of decision process and managerial behaviour.