930 resultados para interval-valued fuzzy set


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Market orientation (MO) and marketing performance measurement (MPM) are two of the most widespread strategic marketing concepts among practitioners. However, some have questioned the benefits of extensive investments in MO and MPM. More importantly, little is known about which combinations of MO and MPM are optimal in ensuring high business performance. To address this research gap, the authors analyze a unique data set of 628 firms with a novel method of configurational analysis: fuzzy-set qualitative comparative analysis. In line with prior research, the authors find that MO is an important determinant of business performance. However, to reap its benefits, managers need to complement it with appropriate MPM, the level and focus of which vary across firms. For example, whereas large firms and market leaders generally benefit from comprehensive MPM, small firms may benefit from measuring marketing performance only selectively or by focusing on particular dimensions of marketing performance. The study also finds that many of the highest-performing firms do not follow any of the particular best practices identified.

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The advisability of analyzing the banks liquidity and profitability as the key factor when building the comparative estimate of their functioning is considered. The procedure of formal description of the bank stable functioning indices is substantiated. Fuzzy interpretation of the bank management efficiency estimation is offered. The possibility to formalize the bank functioning estimates on the basis of the corresponding fuzzy set levels hierarchy is analyzed. The comparative estimate of different bank systems functioning is given.

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The paper gives an overview about the ongoing FP6-IST INFRAWEBS project and describes the main layers and software components embedded in an application oriented realisation framework. An important part of INFRAWEBS is a Semantic Web Unit (SWU) – a collaboration platform and interoperable middleware for ontology-based handling and maintaining of SWS. The framework provides knowledge about a specific domain and relies on ontologies to structure and exchange this knowledge to semantic service development modules. INFRAWEBS Designer and Composer are sub-modules of SWU responsible for creating Semantic Web Services using Case-Based Reasoning approach. The Service Access Middleware (SAM) is responsible for building up the communication channels between users and various other modules. It serves as a generic middleware for deployment of Semantic Web Services. This software toolset provides a development framework for creating and maintaining the full-life-cycle of Semantic Web Services with specific application support.

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We introduce a modification of the familiar cut function by replacing the linear part in its definition by a polynomial of degree p + 1 obtaining thus a sigmoid function called generalized cut function of degree p + 1 (GCFP). We then study the uniform approximation of the (GCFP) by smooth sigmoid functions such as the logistic and the shifted logistic functions. The limiting case of the interval-valued Heaviside step function is also discussed which imposes the use of Hausdorff metric. Numerical examples are presented using CAS MATHEMATICA.

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Market orientation (MO) and marketing performance measurement (MPM) are two of the most widespread strategic marketing concepts among practitioners. However, some have questioned the benefits of extensive investments in MO and MPM. More importantly, little is known about which combinations of MO and MPM are optimal in ensuring high business performance. To address this research gap, the authors analyze a unique data set of 628 firms with a novel method of configurational analysis: fuzzy-set qualitative comparative analysis. In line with prior research, the authors find that MO is an important determinant of business performance. However, to reap its benefits, managers need to complement it with appropriate MPM, the level and focus of which vary across firms. For example, whereas large firms and market leaders generally benefit from comprehensive MPM, small firms may benefit from measuring marketing performance only selectively or by focusing on particular dimensions of marketing performance. The study also finds that many of the highest-performing firms do not follow any of the particular best practices identified.

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Paid reproductive work, especially in the case of cleaning and home-care for elderly people, is an important sector for foreign women in Italy. For this reason, since the beginning of the current economic crisis, scholars have wondered about the impact of the recession on migrant domestic workers. They have looked particularly at possible competition with Italian women entering the sector for lack of better alternatives. Our paper takes this discussion a step further by assessing the overall changes affecting migrant women in the Italian labour market, 2007-2012. We will look at how their position has been transformed, by taking both an ethnic perspective, in relation to Italian women, and a gender perspective, in relation to migrant men. By way of a conclusion, the argument will be made that there is a substantial lack of competition between Italian and foreign women in the care and domestic sector due to differences in their earnings, hours of work and activities.

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Typologies have represented an important tool for the development of comparative social policy research and continue to be widely used in spite of growing criticism of their ability to capture the complexity of welfare states and their internal heterogeneity. In particular, debates have focused on the presence of hybrid cases and the existence of distinct cross-national pattern of variation across areas of social policy. There is growing awareness around these issues, but empirical research often still relies on methodologies aimed at classifying countries in a limited number of unambiguous types. This article proposes a two-step approach based on fuzzy-set-ideal-type analysis for the systematic analysis of hybrids at the level of both policies (step 1) and policy configurations or combinations of policies (step 2). This approach is demonstrated by using the case of childcare policies in European economies. In the first step, parental leave policies are analysed using three methods – direct, indirect, and combinatory – to identify and describe specific hybrid forms at the level of policy analysis. In the second step, the analysis focus on the relationship between parental leave and childcare services in order to develop an overall typology of childcare policies, which clearly shows that many countries display characteristics normally associated with different types (hybrids and. Therefore, this two-step approach enhances our ability to account and make sense of hybrid welfare forms produced from tensions and contradictions within and between policies.

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This essay explores whether the gender constructions in Joe Abercrombie’s Best Served Cold and Juliet Marillier’s Daughter of the Forest question or contribute to existing gender categories. The analysis is performed using Raewynn Connell’s gender structure model, Brian Attebery’s theory of fantasy as a "fuzzy set" and Maria Nikolajeva’s schedule for stereotypical gender traits. Thus, both of the texts were analyzed to determine if their contents, structures and reader responses create opportunities or act limiting, how the main characters are portrayed and how the books various power-, production-, emotional- and symbolic relations look like. The result of the analysis is that both of the books portray patriarchal worlds, sexual division of labor, misogyny and gender-binding statements. The characters in Daughter of the Forest are quite stereotypical, with some traits that exceed their gender, whilst the characters in Best Served Cold are all portrayed with traditionally manly traits (even the female main character). Therefor one can say that Best Served cold’s female protagonist is the only element in the books that fully questions prevailing gender categories.

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The thesis begins with the classical cooperation and transfers it to the digital world. This work gives a detailed overview of the young fields of research smart city, shareconomy and crowdsourcing and links these fields with entrepreneurship. The core research aim is the finding of connections between the research fields smart city, shareconomy and crowdsourcing and entrepreneurial activities and the specific fields of application, success factors and conditions for entrepreneurs. The thesis consists of seven peer-reviewed publications. Based on primary and secondary data, the existence of entrepreneurial opportunities in the fields of smart city, shareconomy and crowdsourcing could be confirmed. The first part (publications 1-3) of the thesis are literature reviews to secure the fundamental base for further research. This part consists of newly created definitions and an extreme sharpening of the research fields for the near future. In the second part of the thesis (publications 4-7), empirical field work (in-depth interviews with entrepreneurs) and quantitative analyses (fuzzy set/qualitative comparative analysis and binary logistic regression analysis) contribute to the field of research with additional new insights. Summarizing, the insights are multi-layered: theoretical (e.g. new definitions, sharpening of the research field), methodical (e.g. first time application of the fuzzy set/qualitative comparative analysis in the field of crowdfunding) and qualitative (first time application of in-depth interviews with entrepreneurs in the fields of smart city and shareconomy). The global research question could be answered: the link between entrepreneurship and smart city, shareconomy and crowdfunding could be confirmed, concrete fields of application could be identified and further developments could be touched upon. This work strongly contributes to the young fields of research through much-needed basic work, new qualitative approaches, innovative methods and new insights and offers opportunities for discussion, criticism and support for further research.

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Nowadays, risks arising from the rapid development of oil and gas industries are significantly increasing. As a result, one of the main concerns of either industrial or environmental managers is the identification and assessment of such risks in order to develop and maintain appropriate proactive measures. Oil spill from stationary sources in offshore zones is one of the accidents resulting in several adverse impacts on marine ecosystems. Considering a site's current situation and relevant requirements and standards, risk assessment process is not only capable of recognizing the probable causes of accidents but also of estimating the probability of occurrence and the severity of consequences. In this way, results of risk assessment would help managers and decision makers create and employ proper control methods. Most of the represented models for risk assessment of oil spills are achieved on the basis of accurate data bases and analysis of historical data, but unfortunately such data bases are not accessible in most of the zones, especially in developing countries, or else they are newly established and not applicable yet. This issue reveals the necessity of using Expert Systems and Fuzzy Set Theory. By using such systems it will be possible to formulize the specialty and experience of several experts and specialists who have been working in petroliferous areas for several years. On the other hand, in developing countries often the damages to environment and environmental resources are not considered as risk assessment priorities and they are approximately under-estimated. For this reason, the proposed model in this research is specially addressing the environmental risk of oil spills from stationary sources in offshore zones.

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In this paper, the IEEE 14 bus test system is used in order to perform adequacy assessment of a transmission system when large scale integration of electric vehicles is considered at distribution levels. In this framework, the symmetric/constr ained fuzzy power flow (SFPF/CFPF) was proposed. The SFPF/CFPF models are suitable to quantify the adequacy of transmission network to satisfy “reasonable demands for the transmission of electricity” as defined, for instance, in the European Directive 2009/72/EC. In this framework, electric vehicles of different types will be treated as fuzzy loads configuring part of the “reasonable demands”. With this study, it is also intended to show how to evaluate the amount of EVs that can be safely accommodated to the grid meeting a certain adequacy level.

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Kommuner, regioner och landsting utgör en betydande del av den svenska offentliga sektorn och tillhandahåller tjänster som är betydelsefulla för landets medborgare. Några exempel är vård av äldre och funktionshindrade, utbildning samt hälso- och sjukvård. Under senare år har den andel av verksamheten som tillhandahålls direkt av kommuner, regioner och landsting minskat. Istället har förekomsten av privata utförare ökat inom många områden. Eftersom den upphandlade verksamheten motsvarar stora belopp och omfattningen kontinuerligt ökar är det viktigt att dessa beställare ser till att de privata utförarna levererar verksamhet på överenskommet sätt och med utlovat resultat. Denna forskningsrapport syftar till att beskriva och förklara hur offentliga beställare styr privata utförare i olika styrsituationer avseende konkurrenssituationen och vilken verksamhet som upphandlas. Det empiriska materialet är insamlat genom intervjuer både med kommuner och med privata utförare.

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Logistic regression is a statistical tool widely used for predicting species’ potential distributions starting from presence/absence data and a set of independent variables. However, logistic regression equations compute probability values based not only on the values of the predictor variables but also on the relative proportion of presences and absences in the dataset, which does not adequately describe the environmental favourability for or against species presence. A few strategies have been used to circumvent this, but they usually imply an alteration of the original data or the discarding of potentially valuable information. We propose a way to obtain from logistic regression an environmental favourability function whose results are not affected by an uneven proportion of presences and absences. We tested the method on the distribution of virtual species in an imaginary territory. The favourability models yielded similar values regardless of the variation in the presence/absence ratio. We also illustrate with the example of the Pyrenean desman’s (Galemys pyrenaicus) distribution in Spain. The favourability model yielded more realistic potential distribution maps than the logistic regression model. Favourability values can be regarded as the degree of membership of the fuzzy set of sites whose environmental conditions are favourable to the species, which enables applying the rules of fuzzy logic to distribution modelling. They also allow for direct comparisons between models for species with different presence/absence ratios in the study area. This makes themmore useful to estimate the conservation value of areas, to design ecological corridors, or to select appropriate areas for species reintroductions.

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This study proposes a novel non-parametric method for construction of prediction intervals (PIs) using interval type-2 Takagi-Sugeno-Kang fuzzy logic systems (IT2 TSK FLSs). The key idea in the proposed method is to treat the left and right end points of the type-reduced set as the lower and upper bounds of a PI. This allows us to construct PIs without making any special assumption about the data distribution. A new training algorithm is developed to satisfy conditions imposed by the associated confidence level on PIs. Proper adjustment of premise and consequent parameters of IT2 TSK FLSs is performed through the minimization of a PI-based objective function, rather than traditional error-based cost functions. This new cost function covers both validity and informativeness aspects of PIs. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Quantitative measures are applied for assessing the quality of PIs constructed using IT2 TSK FLSs. The demonstrated results for four benchmark case studies with homogenous and heterogeneous noise clearly show the proposed method is capable of generating high quality PIs useful for decision-making.

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This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.