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Organizacija
|
2008
|
vol. 41
|
issue 3
108-115
EN
This study is aimed at measuring and summarizing the perceived and expected service quality of passengers of an international airline and to provide the passengers' opinions to the decision makers employing fuzzy logic. The appropriate fuzzification procedure was determined to be the trapezoidal membership function. Using SERVQUAL methodology, the optimal fuzzy interval of the gap scores was determined for each item. The interpretations of these fuzzy intervals were categorized into three areas - optimistic, neutral and pessimistic passenger views - to assist the decision makers in identifying which items of services are satisfactory and which are in need of improvement.
EN
In response to the weakness of traditional efficiency assessment methods taking risk into account, the modification of the Certainty Equivalent method is proposed in this paper. The possibility of connecting solutions from different fields provides for the elaboration of a more effective tool to illustrate and indicate the accurate level of risk in the investment efficiency calculus, which is the matter under consideration in the paper. The authors propose to use the modified method of a Certainty Equivalent that is based on fuzzy numbers. The aim of the method is to make decisions that are less incorrect. The work should be treated as an introduction to proposed further research on the subject.
EN
The Fuzzy SERVQUAL method enables to assess the service quality when the measurement results of the performance perception and expectations are expressed in the form of fuzzy numbers. The measurement results expressed in the form of fuzzy numbers are the results of applying the fuzzy conversion scales which are the most popular form of fuzzy scales. Fuzzy conversion scales assume that their points are expressed in the form of fuzzy numbers. The choice of fuzzy number parameters which describe the various points of measurement scales is most often subjective. The aim of the article is to assess the impact of the choice of the fuzzy conversion scale on the stability of the assessment results of the ser-vice quality using the fuzzy SERVQUAL method. The stability assessment was made both for the individual dimensions and the overall SERVQUAL score. The results of employee satisfaction surveys of the West Pomeranian Province local government were used for the purpose of the assessment. The results suggest that there is no significant impact of the form of fuzzy conversion scales on the stability of the assessment results of the service quality us-ing the fuzzy SERVQUAL method.
EN
Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.
EN
The paper presents various methods of solving systems of linear equations under conditions of uncertainty. In a situation when the parameters of such systems cannot be precisely determined with real numbers, they can be represented by interval numbers, fuzzy numbers or ordered fuzzy numbers. Solutions of systems of linear equations with such representations of parameters are shown in the example of Leontief input-output model. It has also been shown that when ordered fuzzy numbers are applied, their additional feature – orientation – can broaden and deepen economic analysis.
EN
Survival analysis can be defined as a set of methods where the response of interest is the time until a specified event occurred. The most common specified event is death and the related time is called survival time or life time in medical sciences. The Kaplan Meier estimator is one of the popular methods for precise survival times. It is natural that life time is of a continuous nature, therefore it is unrealistic to treat life time observations as precise numbers. In [Viertl 2009] it is shown that life time observations are not precise numbers, but more or less fuzzy. In this study a Generalized Kaplan Meier estimator for fuzzy survival time observations is proposed.
EN
A new application of fuzzy sets theory in social and economic research is a fuzzy measurement of respondents' opinions. In the subject literature fuzzy rating scales or fuzzy conversion scales are being applied. In this second case, a key stage is a choice of such parameters' values of fuzzy numbers which will best illustrate the perception of linguistic values constituting points of measurement scales. In the construction of fuzzy conversion scales the item response theory models can find an application. The transformation method of verbal categories to the form of triangular fuzzy numbers with the application of rating scale model was proposed in this article. Usefulness of a suggested approach was introduced on the basis of the analysis of selected research results on inhabitants' quality of life in one of the Lower Silesian Voivodship districts. The analysis results showed big ambiguity of particular verbal categories and, in consequence, the validity of fuzzy conversion scales application.
EN
The article includes an analysis of a multiple asset portfolio, paying special attention to an imprecision risk, burdening the component instruments. The imprecision of decision premises is modeled in the imprecisely stated present value of portfolio assets, given subjectively by the investor in the form of trapezoidal fuzzy numbers. Next, for each asset and consisting portfolio we define imprecision measures appointed based on a fuzzy discounting factor. Analyzed theoretical model takes into account not only rational premises of a decision, but also allows for an inclusion of behavioral, technical and technological factors. During the performed research, relations between imprecision risk measures of assets and portfolio were found. Imprecision risk assessments are computed based on energy and entropy measures. Also, a case study is given, presenting mechanics of the model and methods of calculating risk measures. Performed analysis led to formulating some conclusions about the form and behavior of imprecision risk burdening a portfolio.
PL
Praca zawiera analizę portfela wieloskładnikowego pod kątem ryzyka nieprecyzyjności. Nieprecyzyjność przesłanek decyzyjnych jest modelowana nieprecyzyjnym określeniem wartości bieżącej instrumentów składowych portfela podanej subiektywnie przez inwestora w postaci trapezoidalnej liczby rozmytej. Dla poszczególnych składników oraz skonstruowanego z nich portfela określone są miary obarczającej je nieprecyzyjności, badanej na podstawie rozmytych czynników dyskontujących. Analizowany model teoretyczny, oprócz przesłanek racjonalnych, uwzględnia czynniki behawioralne oraz techniczne i technologiczne wpływające na decydenta. Oceny ryzyka nieprecyzyjności rozważanego portfela dokonano przy pomocy miar energii i entropii. Przedstawiono również studium przypadku prezentujące sposób działania modelu i metody obliczania miar nieprecyzyjności. Na podstawie przeprowadzonych badań sformułowano wnioski dotyczące postaci i zachowania ryzyka nieprecyzyjności portfela.
EN
The article focuses on the risk assessment of project. The risk assessment is a complexity decision making problem. The assessment risk of projects can be solved with Fuzzy Sets Theory. A Fuzzy Inference System is presented in order to risk assessment of the given project.
PL
Metoda TOPSIS należy do metod porządkowania liniowego, których zadaniem jest ustalenie hierarchii obiektów wielowymiarowych ze względu na przyjęte kryterium syntetyczne. Nowym zastosowaniem tej metody jest możliwość ustalenia kluczowych atrybutów jakości usługi bądź produktu, które decydują o ogólnej ocenie jakości, traktowanej w tym przypadku właśnie jako kryterium syntetyczne. Celem rozważań jest charakterystyka sposobu identyfikacji determinant jakości usług i produktów z zastosowaniem rozmytej metody TOPSIS. Przedstawiono podejście do transformacji punktów skali porządkowej do postaci zbiorów rozmytych, uwzględniając w ten sposób niejednoznaczność i nieprecyzyjność opinii respondentów. Artykuł ma charakter metodologiczny. Użyteczność proponowanego podejścia zaprezentowano na przykładzie oceny jakości strony internetowej Głównego Urzędu Statystycznego. Ze względu na to, że otrzymywane z zastosowaniem proponowanego podejścia wyniki badań mają postać rankingów, artykuł może stanowić inspirację do dalszych zastosowań rozmytej metody TOPSIS, szczególnie w obszarze badań porównawczych jakości usług i produktów.
EN
The TOPSIS method belongs to the linear ordering methods whose task is to determine the multidimensional objects hierarchy by the adopted synthetic criterion. A new application of this method is a possibility to determine the key attributes of quality of the service or product that decide an overall assessment of quality being treated here as a synthetic criterion. An aim of the deliberations is to describe the way of identification of the determinants of quality of services and products applying the fuzzy TOPSIS method. The author presents an approach to transformation of the points of the order scale to the form of fuzzy sets, thus considering ambiguity and imprecision of respondents’ opinions. The article is of a methodological nature. Usefulness of the proposed approach is presented on the example of assessment of quality of the website of the Central Statistical Office in Poland. Having in mind that the research findings obtained with the use of the proposed approach have the form of rankings, the article may be an inspiration for further applications of the fuzzy TOPSIS method, particularly in the area of comparative surveys of services and products quality.
RU
Метод TOPSIS относится к классу методов линейного упорядочивания, задача которых состоит в определении иерархии многомерных объектов по принятому синтетическому критерию. Новым применением этого метода является возможность определения основных атрибутов качества услуги или продукта, которые решают вопрос об общей оценке качества, воспринимаемого в этом случае именно в качестве синтетического критерия. Цель рассуждений – характеристика способа выявления детерминантов качества услуг и продуктов с применением нечеткого (размытого) метода TOPSIS. Представлен подход к преобразованию точек порядковой (ранговой) шкалы в вид нечетких множеств, учитывая таким образом необнозначность и неточ- ность мнений респондентов. Статья имеет методологический характер. Пригодность предлагаемого подхода представили на примере оценки качества вебсайта Центрального статистического управления Польши. Учитывая, что получаемые с применением предлагаемого подхода результаты исследований имеют вид рейтингов, статья может представлять собой инспирацию к дальнейшим применениям размытого метода TOPSIS, в особенности в области со- поставительных исследований качества услуг и продуктов.
PL
W pracy przedstawiono zastosowanie transformaty Mellina do porównania liczb rozmytych będących wynikiem działania metody FSAW. Transformata Mellina wykorzystuje funkcję gęstości prawdopodobieństwa związanej z liczbą rozmytą, po uwzględnieniu transformacji proporcjonalnej. Pozwala to na porządkowanie liniowe liczb rozmytych w oparciu o miary statystyczne (średnią i wariancję). W szczególności przedstawiono zależności matematyczne dla trójkątnych liczb rozmytych. Metodę zilustrowano na przykładzie wieloatrybutowego podejmowania decyzji.
EN
The paper presents the use of Mellin transform to compare fuzzy numbers in the FSAW method. The Mellin transform uses the probability density function (PDF) associated with the fuzzy number. The PDF is calculated with the proportional transformation. The proposed method allows to rank fuzzy numbers based on statistical measures (the mean and the variance). In particular, the mathematical relations for the triangular fuzzy numbers are presented. A numerical example of the fuzzy multi-criteria decision-making is illustrated.
PL
Zasadniczym celem artykułu jest charakterystyka i ocena możliwości aplikacyjnych wybranych rozmytych metod porządkowania liniowego w ustalaniu hierarchii ważności cech jakości usługi. Zaprezentowano wyniki badania, którego celem była ocena jakości strony internetowej Głównego Urzędu Statystycznego. Zastosowano narzędzie WebQual zmodyfikowane przez autora pod względem zarówno wyszczególnionych cech jakości usługi, jak i sposobu pomiaru opinii respondentów. Opracowany kwestionariusz ankiety umożliwia bowiem transformację wyników pomiaru w postaci wartości lingwistycznych do wartości liczbowych za pomocą zbiorów rozmytych. Tak przygotowane dane pierwotne stanowiły podstawę zastosowania rozmytych metod porządkowania liniowego.
EN
The principal aim of the article is to characterise and assess the application possibilities for selected fuzzy linear ordering methods in determining the hierarchy of the importance of service quality characteristics. The report presents the results of a study whose aim was to assess the quality of Poland’s Central Statistical Office’s website. A tool known as WebQual was used, after modification by the author for two areas: quality of listed service characteristics and how respondent opinions were measured. The survey questionnaire enables the transformation of the measurement results from linguistic values to numerical ones using fuzzy sets. The primary data prepared this way formed the basis for the application of fuzzy linear ordering methods.
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