328 research outputs found

    Decision-making in the manufacturing environment using a value-risk graph

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    A value-risk based decision-making tool is proposed for performance assessment of manufacturing scenarios. For this purpose, values (i.e. qualitative objective statements) and concerns (i.e. qualitative risk statements) of stakeholders in any given manufacturing scenario are first identified and are made explicit via objective and risk modeling. Next, performance and risk measures are derived from the corresponding objective and risk models to evaluate the scenario under study. After that, upper and lower bounds, and target value is defined for each measure in order to determine goals and constraints for the given scenario. Because of the multidimensionality nature of performance, the identified objectives and risks, and so, their corresponding measures are usually numerous and heterogeneous in nature. These measures are therefore consolidated to obtain a global performance indicator of value and global indicator of risk while keeping in views the inter-criteria influences. Finally, the global indicators are employed to develop minimum acceptable value and maximum acceptable risk for the scenario under study and plotted on the VR-Graph to demarcate zones of “highly desirable”, “feasible”, “and risky” as well as the “unacceptable” one. The global scores of the indicators: (value-risk) pair of the actual scenario is then plotted on the defined VR-Graph to facilitate decision-making by rendering the scenarios’ performance more visible and clearer. The proposed decision-making tool is illustrated with an example from manufacturing setup in the process context but it can be extended to product or systems evaluation

    Densification of spatially-sparse legacy soil data at a national scale: a digital mapping approach

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    Digital soil mapping (DSM) is a viable approach to providing spatial soil information but its adoption at the national scale, especially in sub-Saharan Africa, is limited by low spread of data. Therefore, the focus of this thesis is on optimizing DSM techniques for densification of sparse legacy soil data using Nigeria as a case study. First, the robustness of Random Forest model (RFM) was tested in predicting soil particle-size fractions as a compositional data using additive log-ratio technique. Results indicated good prediction accuracy with RFM while soils are largely coarse-textured especially in the northern region. Second, soil organic carbon (SOC) and bulk density (BD) were predicted from which SOC density and stock were calculated. These were overlaid with land use/land cover (LULC), agro-ecological zone (AEZ) and soil maps to quantify the carbon sequestration of soils and their variation across different AEZs. Results showed that 6.5 Pg C with an average of 71.60 Mg C ha–1 abound in the top 1 m soil depth. Furthermore, to improve the performance of BD and effective cation exchange capacity (ECEC) pedotransfer functions (PTFs), the inclusion of environmental data was explored using multiple linear regression (MLR) and RFM. Results showed an increase in performance of PTFs with the use of soil and environmental data. Finally, the application of Choquet fuzzy integral (CI) technique in irrigation suitability assessment was assessed. This was achieved through multi-criteria analysis of soil, climatic, landscape and socio-economic indices. Results showed that CI is a better aggregation operator compared to weighted mean technique. A total of 3.34 x 106 ha is suitable for surface irrigation in Nigeria while major limitations are due to topographic and soil attributes. Research findings will provide quantitative basis for framing appropriate policies on sustainable food production and environmental management, especially in resource-poor countries of the world

    Enhancing strategic management using a quantified VRIO: Adding value with the MCDA approach

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    The field of strategic management has been popularized since the 1960s, as an aid for the search of success factors amongst the internal and external surroundings of an organization. Strategic management has observed and created strategies that are considered as pillars in the present way of applying contemporary management operations. Even though strategic management relies on managers’ capability to comprehend the current economic trends, this area has left a variety of questions unanswered, especially regarding the analyses of the combination of quantitative and qualitative decision criteria. This dissertation aims to enhance strategic management by developing a quantified valuable, rare, inimitable and organized (VRIO) framework, with the aid of the multiple criteria decision analysis (MCDA) approach. To accomplish this objective, the VRIO framework is combined with the Choquet integral (CI) and a real-life application is carried out to support strategic management. The dual methodology used in this dissertation offers an innovative process for business improvement. The benefits and limitations are also presented and discussed

    Dynamically consistent CEU preferences

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    We give an axiomatic foundation to the updating rule proposed by [Sarin, R. and Wakker, P. P. (1998). Revealed likelihood and knightian uncertainty. Journal of Risk and Uncertainty 16(3):223-250.] for CEU preferences. This rule is dynamically consistent but non-consequentialist, since forgone consequences are relevant for conditioning. Whereas it does not work universally, but only when counterfactuals outcomes are better and/or worse than the ones resulting on the conditioning event, the rule has many interesting features, since it is able to describe Ellsbergtype preferences together with a recursive structure of the criterion

    Proceedings of the First Karlsruhe Service Summit Workshop - Advances in Service Research, Karlsruhe, Germany, February 2015 (KIT Scientific Reports ; 7692)

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    Since April 2008 KSRI fosters interdisciplinary research in order to support and advance the progress in the service domain. KSRI brings together academia and industry while serving as a European research hub with respect to service science. For KSS2015 Research Workshop, we invited submissions of theoretical and empirical research dealing with the relevant topics in the context of services including energy, mobility, health care, social collaboration, and web technologies
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