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EN
The paper focuses on a formal approach to the diagnosis and design of enterprise management systems when there is a lack of complete and accurate information. It first discusses the multicriteria evaluation system, in which the preferences of the decision-maker are modeled based on outranking relations. The binary outranking relation is typically used in ELECTRE methods. These methods involve a set of analytical procedures which allow the user to select, categorise and rank decision alternatives. The overall outranking preference in this method is developed according to the principle of concordance and disconcordance. In the article the basic relationships and thresholds used in preferences modeling are defined. The ELECTRE I method was introduced to illustrate this type of approach. The last part of the paper presents a method for determining the weights of evaluation criteria recommended for the ELECTRE methods. This method can also be used in other approaches to solve complex managerial decision problems.
EN
The MCDA technique has been extensively and successfully applied for supporting decision making in negotiation processes. The mostly used techniques SAW, AHP or TOPSIS are based on direct preference information which requires from negotiator a clear and precise definition all the parameters of the preference model (e.g. issue weights, option rates, aspiration and reservation values etc.), so those techniques can be successfully applied in well-structured negotiation problems. But, many real negotiation problems are illstructured, that means that the negotiation space is imprecisely defined, and the negotiator’s preferences the vagueness or imperfect. The main purpose of this paper is to investigate the potentials and the applicability the UTA method, one of the techniques based on indirect preference information, in evaluation of negotiation offers, especially in ill-structured negotiation problems. The UTA (Jacquet-Lagreze and Siskos, 1978, 1982, 2001) is a multicriteria decision making method which is based on the linear programming model for inferring additive utility functions from a set of representative decision data. The example is also presented to elaborate and demonstrate the holistic judgment and the usefulness UTA approach for evaluation negotiation offers.
EN
The paper discusses the impact of the decision-making profiles on the consistency of rankings obtained by three multiple criteria methods, i.e. DR, AHP and TOPSIS. The online decision making experiment was organized, based on an electronic questionnaire which is a hybrid of the internet survey system and the decision support system. The participants of the experiment were 418 students of Polish universities. To describe the decision-making profile, the REI test was used which allows to distinguish two decision-making styles: rational and intuitive. The Kendall rank correlation coefficient was used to test the consistency of the rankings obtained by the considered methods. Using different grouping methods, the relationship between the decision profile and the ability to express one’s preferences by means of these methods, that differ in cognitive requirements, was examined. The results of the research may be helpful for supporting the decision-maker in decision processes by choosing the method that fits their profile best.
EN
In this paper the method of the Analytic Hierarchy Process (AHP) is described. At the beginning the general assumptions of the method are characterized and discussed. These are related to assumptions held within General Systems Theory. Then the problems of pairwise comparisons of elements, with its use of a specific scale, as well as the resulting reciprocal matrix are presented. There are many ways of estimating the eigenvectors of this matrix. These eigenvectors reflect weights of preferences. Despite the fact that we are able to evaluate the consistency of judgements the problem of acceptable weights still remains. Therefore, by way of an illustration, the method for the sensitivity analysis of preferences is also discussed in the paper.
EN
This paper described the main idea of the MACBETH approach and M-MACBETH software to multicriteria negotiation analysis. The MACBETH is based on the additive value model and requires only qualitative judgments about differences of attractiveness to help a decision maker quantify the relative value of options or criteria. The main goal of this procedure is to support interactive learning about evaluation problems and to provide the recommendations to select and rankordering options/criteria in decision making processes. We proposed to use MACBETH methodology as well M-MACBETH software to support ill-structure negotiation problems, i e. evaluation of negotiation offers in an environment with uncertain, subjective and imprecise information and not precisely defined decision makers preferences. An numerical example showing how M-MACBETH software can be implemented in practice, in order to help a negotiator to define numerical values of options/criteria based on verbal statements and next build a scoring system negotiation offers taking into account different types of issues in negotiation problems is presented. More detail we describe the main key points of M-MACBETH software related to structuring the negotiation model, building value scales for evaluation negotiation packages, weighting negotiation issues and selected elements of sensitivity analyzes.
EN
Scoring the negotiation template and building a scoring system for negotiation offers is a starting point for analysis of negotiation. It is usually done by means of a classical additive scoring model. Recent research confirms, however, that TOPSIS may be a good alternative to SAW-based models, since it significantly facilitates the processes of template definition and elicitation of negotiator’s preferences. Fundamental ideas of the TOPSIS, VIKOR and BIPOLAR methods have been analysed and attempts were made to hybridize some of their notions to propose an alternative method for evaluating negotiation offers.
PL
Skalowanie dynamiczne jest zbiorem metod, w których dokonuje się geometrycznej prezentacji danych podobieństw uzyskanych dla T różnych okresów. Celem artykułu jest przedstawienie zastosowania dwóch metod skalowania dynamicznego do badania zmian zachodzących w preferencjach. W pierwszej, rozmieszczenia punktów na mapie percepcyjnej dokonuje się na podstawie rozbudowanej macierzy podobieństw. W drugiej metodzie przeprowadza się skalowanie wielowymiarowe dla poszczególnych okresów, a następnie dopasowuje otrzymane konfiguracje punktów za pomocą przekształceń zachowujących proporcje odległości między punktami. Prezentacja metod zostanie zilustrowana przykładem empirycznym, w którym obliczenia przeprowadzono z wykorzystaniem pakietów SPSS i New MDSX.
EN
Dynamic scaling is a set of methods in which the geometrical representation of the similarity data for T different time periods is made. This article presents the use of two-dynamic scaling methods for studying changes in the preferences. In the first method the location of points on the perceptual map is made on the basis of the super-dissimilarity matrix. In the second method multidimensional scaling for the respective periods is carried out and the obtained configurations are matched by transformations preserving the proportions of distances between points. The presentation of the methods is illustrated by an empirical example in which calculations were performed with use of SPSS and New MDSX packages.
PL
Punktem wyjścia w skalowaniu wielowymiarowym jest symetryczna macierz niepodobieństw. Jednak macierz danych o zmianach preferencji (np. prawdopodobieństwo, że konsument dokonuje zakupu marki j pod warunkiem, że przy wcześniejszych zakupach była to marka i, liczba osób deklarujących, że marka j jest przez nich najbardziej preferowana, mimo że we wcześniejszym okresie była to marka i i in.) nie jest symetryczna. Dla takich danych uśrednienie odpowiednich wartości niepodobieństw prowadzi do utraty cennych informacji dotyczących analizowanego zjawiska, stąd konieczność stosowania metod właściwych dla danych niesymetrycznych. Spośród wybranych metod niesymetrycznego skalowania wielowymiarowego szczególną uwagę zwrócono na metodę wektorów dryfu. Metoda ta umożliwia równoczesną prezentację na mapie percepcyjnej konfiguracji punktów reprezentujących analizowane obiekty, jak również wektorów wskazujących kieru­nek i siłę zmian zachodzących w preferencjach respondentów.
EN
The matrix of  switch preference data (e.g. one’s preference for brand j, given that one has already defined his/her first choice for brand i) is not symmetric. The averaging of  appropriate off-diagonal proximity entries for such data leads to the loss of information, hence the necessity to use appropriate methods for asymmetric data. Among the chosen methods of asymmetric multidimensional scaling, particular attention was paid to the drift vectors method. This method enables to present simultaneously on the perceptual map both the configuration of points representing the analyzed objects and the vectors indicating the direction and the strength of changes in the respondents preferences.
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