The ordinal dominance theory as applied to the most attractive retail cities of the Benelux area

An important estate broker for retail in Europe has performed statistical research on retail business in cities in the Benelux area (Belgium, the Netherlands, Luxemburg). The broker choose five characteristics to rate 30 Benelux cities on their retail business. However, summing these ranks is not allowed as they do not represent cardinal numbers. Hence, calculating the medians and quartiles of this ordinal number series signifies a possible alternative. The disadvantages of this approach are: many ex aequos and to be operational at least six terms are needed, whereas only five characteristics are present here. Instead, an Ordinal Dominance Theory was developed that only needs at least three terms. Finally, a SWOTanalysis was made concerning retail business for the main Belgian cities, Brussels, Antwerp and Ghen

Robustness of the multi‐objective MOORA method with a test for the facilities sector

The definition of robustness in econometrics, the error term in a linear equation, was not only broadened, but in addition moved to the meaning of common language: from a cardinal to a qualitative one. These interpretations were tested by an application on the Facilities Sector in Lithuania. The application is multi‐objective: like costs, experience and effectiveness at the side of the contractors; quality, duration of the work and cost price at the side of the owners. These objectives having all different units the dimensionless ratios of the MOORA method avoids the difficulties of normalization. In a first part of MOORA these ratios were aggregated and in a second one they were used as distances to a reference point. The results of both parts control each other, a test on robustness. Additionally, MOORA shows a robust domination on all other methods of multi‐objective optimization. For the Facilities Sector in Lithuania, both parts of MOORA resulted in a comparable ranking. In this way a double check was made on the robustness of the results. Santrauka Patikimumo apibrėžimas ekonometrikoje, kaip neteisingas terminas tiesinėje lygtyje, buvo ne tik papildytas, bet ir išreikštas įprasta kalba: nuo kiekybinio prie kokybinio. Šios interpretacijos buvo patikrintos taikant jas Lietuvos paslaugų sektoriuje. Taikymas yra daugiatikslis: iš rangovo pusės kaip išlaidos, patirtis, efektyvumas; kokybė, darbo trukmė, kaina iš užsakovo pusės. Minėtieji tikslai turi skirtingus matavimo vienetus. O jų santykiniai dydžiai neturi mato vienetų, todėl taikant MOORA metodą yra išvengiama sunkumų juos normalizuojant. Pirmoje MOORA metodo taikymo dalyje šie santykiai yra sujungiami, o antroje dalyje ieškoma atstumo iki geriausio sprendinio. Abiejų metodo dalių rezultatai pagrindžia sprendinio teisingumą. Tai rodo aiškų MOORA metodo pranašumą, palyginti su kitais daugiatikslio optimizavimo metodais. Taikant abi MOORA metodo dalis Lietuvos paslaugų sektoriui buvo sudarytas lyginamasis rangavimas, buvo atliktas dvigubas rezultatų patikimumo patikrinimas. First published online: 21 Oct 2010 Reikšminiai žodžiai: MOORA, patikimumas, daugiatiksliai metodai, patobulintas naminalių grupių metodas, Delph

How to invest in Belgian shares by MULTIMOORA optimization

Different multiple objectives expressed in different units make optimization difficult. Therefore, the internal mechanical solution of a Ratio System, producing dimensionless numbers, is preferred to weights, which are most of the time used to compare the different units. In addition, the ratio system creates the opportunity to use a second approach: a non-subjective Reference Point Theory. Therefore, the Reference Point Theory uses the ratios found in the ratio system as co-ordinates for the alternative solutions, which are then compared to a Maximal Objective Reference Point. The two approaches form a control on each other. This overall theory is called MOORA (Multi-Objective Optimization by Ratio Analysis). The results are still more convincing if a Full Multiplicative Form is added, three methods assembled under the name of MULTIMOORA. At that moment, the control by three different approaches forms a guaranty for a solution being as non-subjective as possible. As to calculate the sum of three obtained ranks is not allowed, a theory of Ordinal Dominance is developed in order to remain in the ordinal sphere. MULTIMOORA is used to decide upon an investment in Belgian shares on basis of a ranking in the BEL20 Index

Is credit rating reserved territory for credit rating agencies? A MULTIMOORA approach for European firms and countries

Credit Rating Agencies rate firms and countries by internal experts but with a final qualitative judgment by their management acting as decision makers. These ratings on their turn influence the countries credit rating and ipso facto of their enterprises. The work of the CRA is in fact double: credit rating of firms and other organizations at one side and countries on the other. Considering the credit rating of firms, the CRA made significant mistakes during the Recession 2007−2009 and their judgment is too much American oriented, in any way from a European point of view. Consequently, in Europe many efforts were made to come to a new agency, but all efforts failed. It could be different for the rating of countries. Is a more scientific approach, eventually on a quantitative and structural basis, not possible? Therefore, MULTIMOORA, a quantitative method, is suggested. The study was made for all countries of the European Continent. Based on data available in 2013 and on their extrapolation, the results are quite comparable to the results of Standard & Poor’s Credit Rating System of the moment. As the classifications of Moody’s and Fitch are very similar to those of Standard & Poor’s the outcome would be similar for these other Credit Rating Agencies

VIŠECILJNA OPTIMIZACIJA BLAGOSTANJA U ZEMLJAMA ČLANICAMA EU-ROPSKE UNIJE

Well-being is of crucial importance for both individual and society as a whole. It is therefore important to quantify performance and progress made by certain states, regions, communities, social groups, and individuals in improving their well–being. The aim of study was to offer a new framework for multi–criteria assessment as well as international comparison of objective well–being. Well–being is a multi–dimensional phenomenon; hence the appropriate indicator system should be capable to identify the most important underlying processes influencing well–being. For our research we have established the indicator system of twelve indicators identifying various dimensions of well–being. Therefore we propose MULTIMOORA, a model which can be used for approaching the objective of societal well–being. It is applied for international comparison of the well-being in the EU Member States. Consequently, it was revealed that Ireland, the Netherlands, Denmark, Austria, France, Cy-prus, Finland, Germany, and Belgium have achieved the highest level of well–being as of 2009. At the other end of spectrum, Czech Republic, Lithuania, Slovakia, Bulgaria, Poland, Hungary, Estonia, Lat-via, and Romania can be considered as those peculiar with relatively lowest well–being.Blagostanje je od ključnog značaja kako za pojedinca tako i za društvo u cjelini. Stoga je važno kvantificirati performanse i napredak određenih država, regija, zajednica, društvenih grupa i pojedinaca kako bi se unaprijedilo njihovo blagostanje. Cilj istraživanja je ponuditi novi okvir za višeciljnu procjenu kao i međunarodnu usporedbu objektivnog blagostanja. Blagostanje je višedimenzionalna pojava; stoga bi prikladni sustav indikatora trebao biti u mogućnosti identificirati najvažnije temeljne procese koji utječu na blagostanje. Za potrebe našeg istraživanja ustanovili smo indikatorski sustav od dvanaest indikatora koji identificiraju razne dimenzije blagostanja. Stoga predlažemo MULTIMOORA, model koji se može koristiti za približavanje cilju društvenog blagostan-ja. Primjenjuje se u svrhu međunarodne usporedbe blagostanja u zemljama članicama EU. Tako se otkrilo da su Irska, Nizozemska, Danska, Austrija, Francuska, Cipar, Finska, Njemačka i Belgija do-segle najviši stupanj blagostanja od 2009. Na drugom kraju spektra se nalaze Češka, Litva, Slovačka, Bugarska, Poljska, Mađarska, Estonija, Latvija i Rumunjska u kojima je blagostanje najniže

A Bipolar Fuzzy Extension of the MULTIMOORA Method

The aim of this paper is to make a proposal for a new extension of the MULTIMOORA method extended to deal with bipolar fuzzy sets. Bipolar fuzzy sets are proposed as an extension of classical fuzzy sets in order to enable solving a particular class of decision-making problems. Unlike other extensions of the fuzzy set of theory, bipolar fuzzy sets introduce a positive membership function, which denotes the satisfaction degree of the element x to the property corresponding to the bipolar-valued fuzzy set, and the negative membership function, which denotes the degree of the satisfaction of the element x to some implicit counter-property corresponding to the bipolar-valued fuzzy set. By using single-valued bipolar fuzzy numbers, the MULTIMOORA method can be more efficient for solving some specific problems whose solving requires assessment and prediction. The suitability of the proposed approach is presented through an example