The Macbeth Approach for Evaluation Offers in Ill–Structure Negotiations Problems

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.This work was supported by the grant from Polish National Science Center DEC 2011/03/B/HS4/03857e-mail: [email protected] of Economics and Management, University of Bialystok5(71)698

The Application of UTA Method for Support Evaluation Negotiation Offers

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 [email protected] of Economics and Management, University of BialystokBana e Costa C., Vansnick J.-C., 1999, The MACBETH approach: Basic ideas, software, and an application, [in:] Advances in Decision Analysis, N. Meskens, M. Roubens (eds.), Springer.Brzostowski J., Wachowicz T., Roszkowska E., 2012a, Using an Analytic Hierarchy Process to Develop a Scoring System for a set of Continuous Feasible Alternatives in Negotiation, “Operations Research and Decisions”, No. 4.Brzostowski J., Roszkowska E., Wachowicz T., 2012b, Supporting Negotiation by Multi-Criteria Decision-Making Methods, “Optimum. Studia Ekonomiczne”, nr 5 (59).Figueira J., Greco S., Słowiński R., 2009, Building a set of additive value functions representing a reference preorder and intensities of preference: GRIP method, “European Journal of Operational Research”, 195.Górecka D., Roszkowska E., Wachowicz D., 2014, MARS – a hybrid of ZAPROS and MACBETH for verbal evaluation of the negotiation template, [in:] Group Decision and Negotiation 2014, GDN 2014, Proceedings of the Joint International Conference of the INFORMS GDN Section and the EURO Working Group on DSS , P. Zaraté, G. Camilleri, D. Kamissoko, F. Amblard (eds.), Toulouse University, France.Górecka D., Roszkowska E., Wachowicz T., 2016, The MARS Appoach in the Verbal and Holistic Evaluation of the Negotiation Template, Group Decision and Negotiaion, DOI:10.1007/s10726-016-947592016.Greco S., Mousseau V., Slowiński R., 2008, Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions, “European Journal of Operational Research”, 191.Jacquet-Lagrèze E., Siskos J., 1978, Une méthode de construction de fonctions d’ utilité additives explicatives d’ une préférence globale, “Cahier du LAMSADE”, 16, Université de Paris-Dauphine.Jacquet-Lagrèze E., Siskos Y., 1982, Assessing a set of additive utility functions for multicriteria decision making: The UTA method, “European Journal of Operational Research”, 10 (2).Jacquet-Lagrèze E., Siskos Y., 2001, Preference disaggregation: 20 years of MCDA experience, “European Journal of Operational Research”, 130 (2).Ishizaka A., Nemery P., 2013, Multi-Criteria Decision Analysis. Methods and Software, Wiley, United KindgdomKadziński M., Greco S., Słowiński R, 2012, Selection of a representative value function in robust multiple criteria ranking, and choice, “European Journal of Operational Research”, 217.Kersten G. E., Lai H., 2007, Negotiation support and e-negotiation systems: an overview, “Group Decis Negot”, 16(6).Kersten G. E, Noronha S. J., 1999, WWW-based negotiation support: design, implementation, and use, “Decis Support Sys”, 25(2).Larichev O. I., Moshkovich H. M., 1995, ZAPROS-LM – A method and system for ordering multiattribute alternatives, “Eur J Oper Res”, 82(3).Larichev O. I., Moshkovich H. M., 1997, Verbal decision analysis for unstructured problems, Kluwer Academic Publishers, Boston.Moshkovich H. M., Mechitov A. I., Olson D. L., 2005, Verbal Decision Analysis, [in:] Multiple Criteria Decision Analysis: State of the Art Surveys, J. Figueira, S. Greco, M. Ehrgott (eds.), Springer, New York.Mustajoki J., Hamalainen R. P., 2000, Web-HIPRE: Global decision support by value tree and AHP analysis, “INFOR J”, 38(3).Raiffa H., 1982, The Art and Science of Negotiation, The Belknap Press of Harvard University Press, Cambridge (MA).Raiffa H., Richardson J., Metcalfe D., 2002, Negotiation Analysis, The Belknap Press of Harvard University Press, Cambridge.Roszkowska E., Brzostowski J., Wachowicz T., 2014a, Supporting Ill-Structured Negotiation Problems, [in:] Human-Centric Decision-Making Models for Social Sciences, P. Guo, W. Pedrycz (eds.) Springer, London.Roszkowska E., Wachowicz T., 2014, The Multi-Criteria Negotiation Analysis Based on the Membership Function, “Studies in Logic, Grammar and Rhetoric”, Mechanisms and Methods of Decision Making (ed. E. Roszkowska), 37(50).Roszkowska E., Wachowicz T., 2015a, Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems, “Eur J Oper Res”, 242(3).Roszkowska E., Wachowicz T., 2015b, Holistic evaluation of the negotiation template – comparing MARS and GRIP approaches, [in:] The 15th International Conference on Group Decision and Negotiation Letters, B. Kamiński, G. Kersten, P. P. Szufel, M. Jakubczyk, T. Wachowicz (eds.), Warsaw School of Economics Press, Warsaw.Roszkowska E., Wachowicz T., 2016, Negocjacje. Analiza i wspomaganie decyzji, Wolter Kluwer, WarszawaSaaty T. L., 1980, The Analytic Hierarchy Process, McGraw Hill, New York, N.Y.Siskos Y., Grigoroudis E., Matsatsinis N. F., 2005, UTA methods. Multiple criteria decision analysis: State of the art surveys, Springer.Salo A., Hamalainen R. P., 2010, Multicriteria Decision Analysis in Group Decision Processes, [in:] Handbook of Group Decision and Negotiation, D. M. Kilgour, C. Eden (eds.), Springer, New York.Schoop M., Jertila A., List T., 2003, Negoisst: a negotiation support system for electronic business-to-business negotiations in e-commerce, “Data & Knowledge Engineering”, 47(3).Siskos Y., Grigoroudis E., Matsatsinis N. F., 2005, UTA methods. Multiple criteria decision analysis: State of the art surveys, Springer.Wachowicz T., Błaszczyk P., 2013, TOPSIS based approach to scoring negotiating offers in negotiation support systems, “Group Decision and Negotiation”, 22.Wachowicz T., Brzostowski J., Roszkowska E., 2012, Reference Points-Based Methods in Supporting the Evaluation of Negotiation Offers, “Operations Research and Decisions”, No. 4.144-1622(80)14416

Assessment of Multi-Criteria Preference Measurement Methods for a Dynamic Environment

Multi-criteria decision analysis is required in various domains where decision making reoccurs as part of a longer-term process. When the decision context changes or the preferences evolve due to process dynamics, one-shot preference measurement is not sufficient to build an adequate basis for decision making. Process dynamics require taking into account the dimension of time. We investigate six interactive preference measurement methods providing the possibility to assess alternatives in terms of utility for an individual decision maker, whether they are suitable for dynamic preference adjustment. We use a mixed-methods approach to analyse them towards 1) requirements for a dynamic method, and 2) their efficiency, validity, and complexity. Our results show that the best method to be further developed for dynamic context is Adaptive Self-Explication slightly preferable over Pre-Sorted Self-Explication. Our assessment implicates that an extension of the Adaptive Self-Explication will enable efficient dynamic decision support

Decision Support System for Selection of Candidates for PASKIBRAKA Using the TOPSIS Method

Activities in the selection of candidates for PASKIBRAKA every year aim to find the best sons and daughters who will be assigned as heirloom flag raisers. Selection of candidates for PASKIBRAKA members is done manually, to determine the final score of each participant. The selection committee still uses paper and is separate from the assessment to one criterion with the other criteria. In the assessment process with a large number of participants it will take a long time. To simplify the assessment process, a decision support system is needed for the selection of PASKIBRAKA candidates, using the TOPSIS Method (Technique for Order Preference by Similarity to Ideal Solution). TOPSIS is one method that is easy to use to solve multi-criteria problems by taking into account the values ​​of existing criteria. Based on the results of the case example, the candidate PASKIBRAKA selection shows that the results of the experiment use the same system as the manual calculation. And the calculation of the TOPSIS Method will produce output in the form of ranking from PAKIBRAKA candidates &nbsp

Sorting subcontractors’ activities in construction projects with a novel Additive-veto sorting approach

Selection processes in civil engineering infrastructure projects might require more time and effort than the decisionmakers involved in these projects are normally prepared to devote to running them. A novel approach is proposed to sort these activities into classes that represent their impact on the project, namely additive-veto sorting model, which should be considered before any bidding procedure. Therefore, problems regarding the client’s satisfaction caused by subcontractors can be avoided, and the decision-makers involved in the selection problem can devote to each class an effort compatible with the impact that activity might have on the project. The novelty of this method is that it was built to reflect the quasi-compensatory rationality of decision-makers in the construction industry; it provides them with insights on subcontractors’ activities, and it is grounded on and inspired by a real case study. The new parameters proposed within this model introduce the idea of vetoing an activity being assigned to a class when this activity is incompatible with the decision-maker’s preferences. By using this novel method, the authors succeeded in finding results that avoided a complete compensation amongst the factors considered, taking into account ranges that would be of significant importance in the decision process

Application of WINGS method to support decision making with inter-dependence of criteria in negotiations

W negocjacjach częste są sytuacje, w których przestrzeń negocjacyjna i wzorce ofert nie są jasno określone. Jeśli dodatkowo między kwestiami negocjacyjnymi mogą pojawić się zależności, wtedy tradycyjne metody, oparte na sumie ważonej ocen cząstkowych, nie są właściwe dla konstrukcji systemu ocen ofert. Jest to miejsce, w którym swoją użyteczność mogą wykazać podejścia o słabszych założeniach. W artykule zaproponowano zastosowanie metody WINGS (Weighted Influence Non-linear Gauge System) celem wsparcia podejmowania decyzji w procesie negocjacji. Metoda WINGS przedstawia ogólne podejście systemowe pomagające rozwiązywać złożone problemy, w których występują powiązane ze sobą czynniki. W szczególności metoda ta może być użyta do oceny wariantów decyzyjnych w sytuacjach, kiedy zależności między kryteriami nie mogą być pominięte. W ramach wstępnego etapu tej metody zespół negocjacyjny konstruuje, reprezentującą problem negocjacyjny, wspólną sieć konceptów (wierzchołków) i ich relacji (łuków). Taka struktura przypomina mapę poznawczą lub przyczynową. Podstawę sieci stanowią wierzchołki, które odzwierciedlają potencjalne warianty (oferty). U wierzchołka sieci leżą kwestie negocjacyjne (czyli cele, względnie odpowiadające im kryteria). We wnętrzu sieci występują wierzchołki pośrednie, tworzące ścieżki przyczynowe prowadzące od ofert do kwestii. Etap wstępny ma za zadanie pomóc zespołowi negocjacyjnemu w określeniu struktury problemu, a także wspiera proces uczenia się i zrozumienia jego istoty. Drugi, główny etap obejmuje fazę ilościową metody WINGS, pozwalającą zbudować ranking kompromisowych ofert. Użyteczność metody zilustrowano dwoma przykładami przygotowania negocjacji: zakupu partii towaru oraz wyboru systemu informatycznego typu ERP.A situation when negotiation space and templates are not clearly defined is very likely in negotiations. If it also happens that criteria cannot be regarded as independent, then no approach based on weighted additive scoring is suitable for building the offer scoring system. This is an area where other approaches with less limiting assumptions can prove useful. This paper proposes to apply the WINGS (Weighted Influence Non-linear Gauge System) method, a general systemic procedure for supporting decision making in negotiations. The WINGS method helps solve complex problems involving interrelated factors. In particular, it can be used to evaluate alternatives when the interrelations between criteria cannot be neglected. In the introductory stage, the negotiating team builds a common network of concepts (nodes) and their relations (arrows) representing the negotiation problem. This structure resembles a cognitive or causal map. The bottom nodes represent potential alternatives (offers), while the top nodes represent objectives (issues). The intermediary nodes create causal paths leading from the alternatives to the objectives. This stage helps the negotiation team to structure the problem; it also supports learning and comprehension. The main stage involves quantitative evaluations with the WINGS method that make it possible to build a ranking of compromise solutions. The usefulness of the procedure is illustrated with two examples of preparation for negotiations: the purchase of a batch of goods and the choice of an ERP system.Artykuł powstał w ramach projektu sfinansowanego ze środków Narodowego Centrum Nauki przyznanych na podstawie decyzji numer DEC-2013/09/B/HS4/[email protected]ł Informatyki i Komunikacji, Uniwersytet Ekonomiczny w KatowicachBrzostowski J., Roszkowska E., Wachowicz T., 2012a, Using Multiple Criteria Decision-Making Methods in Negotiation Support, ,,Optimum. Studia Ekonomiczne”, nr 3(29).Brzostowski J., Roszkowska E., Wachowicz T., 2012b, Using an Analytic Hierarchy Process to develop a scoring system for a set of continuous feasible alternatives in negotiation, „Operations Research and Decisions”, no. 4.Górecka D., Roszkowska E, Wachowicz T., 2014, MARS – a hybrid of ZAPROS and MACBETH for verbal evaluation of the negotiation template, Group Decision and Negotiation 2014 : GDN 2014 : Proceedings of the Joint International Conference of the INFORMS GDN Section and the EURO Working Group on DSS, P. Zaraté, G. Camilleri, D. Kamissoko, F. Amblard (red.), Toulouse University, France.Górecka D., Roszkowska E., Wachowicz T., 2016, The MARS Approach in the Verbal and Holistic Evaluation of the Negotiation Template, “Group Decision and Negotiation”, DOI: 10.1007/s10726-016-9475-92016.Gürbüz T., Alptekin S. E., Işıklar Alptekin G., 2012, A hybrid MCDM methodology for ERP selection problem with interacting criteria, „Decision Support Systems”, 54, doi:10.1016/j.dss.2012.05.006.Kersten G. E., Noronha S. J., 1999, WWW-based negotiation support: design, implementation, and use, „Decision Support Systems” 25, doi:10.1016/S0167-9236(99)00012-3.Kilic H.S., Zaim S., Delen D., 2014, Development of a hybrid methodology for ERP system selection: The case of Turkish Airlines, „Decision Support Systems” 66, doi: 10.1016/j.dss.2014.06.011.de Medeiros (Jr.) A., Perez G., Lex S., 2014, Using Analytic Network for Selection of Enterprise Resource Planning Systems (ERP) Aligned To Business Strategy, ,,Journal of Information Systems and Technology Management”, no. 11.Michnik J., 2013, Weighted Influence Non-linear Gauge System (WINGS) – An analysis method for the systems of interrelated components, ,,European Journal of Operational Research”, 228.Mustajoki J., Hämäläinen R. P., 1999, Web-HIPRE – Global decision support by value tree and AHP analysis, Presented at the INFOR.Systems Modelling: Theory and Practice, 2004, M. Pidd (ed.), John Wiley & Sons.Roszkowska E., Wachowicz T., 2015, Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems, ,,European Journal of Operational Research” 242, doi:10.1016/j.ejor.2014.10.050.Roszkowska E., Wachowicz T., 2016, Negocjacje. Analiza i wspomaganie decyzji, Wolter Kluwer, Warszawa.Saaty T. L., 2005, Theory and Applications of the Analytic Network Process. Decision Making with Benefits, Opportunities, Costs and Risks, RWS Publications, Pittsburgh.Salo A., Hämäläinen R. P., 2010, Multicriteria Decision Analysis in Group Decision Processes, [in:] Handbook of Group Decision and Negotiation, D.M. Kilgour, C. Eden (eds.), Advances in Group Decision and Negotiation, Springer Netherlands.Wachowicz T., 2013, Metody wielokryterialne we wspomaganiu prenegocjacyjnego rzygotowania negocjatorów, Wydawnictwo Uniwersytetu Ekonomicznego w Katowicach, Katowice.Wei C.-C., Chien C.-F., Wang M.-J. J., 2005, An AHP-based approach to ERP system selection, ,,International Journal of Production Economics” 96, doi:10.1016/j.ijpe.2004.03.004.Wei C.-C., Wang M.-J. J., 2004, A comprehensive framework for selecting an ERP system, ,,International Journal of Project Management” 22, doi:10.1016/S0263-7863(02)00064-9.Wieszała P., Trzaskalik T., Targiel K., 2011, Analytic Network Process in ERP Selection, [in:] Multicriteria Decision Making’10-11, University of Economics in Katowice, Katowice.119-1341(79)11913

SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA GURU SEKOLAH DASAR KECAMATAN GUNUNG ALIP MENGGUNAKAN METODE TOPSIS

Pada setiap instansi pendidikan terkadang diperlukannya suatu sistem penilaian kinerja guru, hal ini bertujuan untuk meningkatkan kualitas guru yang baik. Namun pada Sekolah Dasar Negeri 1 Banjar Negeri penilaian kinerja gurunya masih menggunakan sistem manual, yaitu sistem DP3 dimana nilai tersebut ditulis di kertas dengan format yang sudah ditentukan. Hal ini membutuhkan waktu yang lama, mengingat guru sekolah dasar yang banyak, dengan kriteria yang banyak pula. Permasalahan ini membuat peneliti ingin mengadakan penelitian dan merancang sebuah sistem pendukung keputusan penilaian kinerja guru pada Sekolah Dasar Negeri 1 Banjar Negeri.Metode TOPSIS (Technique For Order Preference bySimiliarity to Ideal Solution) merupakan salah satu metode yang sering digunakan dalam penentuan suatu keputusan, peneliti menggunakan metode ini. Adanya sistem pendukung keputusan ini membantu kepala sekolah dalam menilai guru, sehingga penilaian kinerja guru dapat dilakukan secara cepat dan tepat

Fuzzy extension of the CODAS method for multi-criteria market segment evaluation

One of the important activities of a company that can increase its competitiveness is market segment evaluation and selection (mse/mss). We can usually consider mse/mss as a multi-criteria decision-making (mcdm) problem, and so we need to use an mcdm method to handle it. Uncertainty is one of the important factors that can affect the process of decision-making. Fuzzy mcdm approached have been designed to deal with the uncertainty of decision-making problems. In this study, a fuzzy extension of the codas (combinative distance-based assessment) method is proposed to solve multi-criteria group decision-making problems. We use linguistic variables and trapezoidal fuzzy numbers to extend the codas method. The proposed fuzzy codas method is applied to an example of market segment evaluation and selection problem under uncertainty. To validate the results, a comparison is performed between the fuzzy codas and two other mcdm methods (fuzzy edas and fuzzy topsis). A sensitivity analysis is also carried out to demonstrate the stability of the results of the fuzz codas. For this aim, ten sets of criteria weights are randomly generated and the example is solved using each set separately. The results of the comparison and the sensitivity analysis show that the proposed fuzzy codas method gives valid and stable results

Pembinaan indeks jenayah curi kenderaan dengan pendekatan berbilang kriterium dalam persekitaran kabur

An index is a measure of the performance of a situation that displays the value of the final score resulting from a combination of several criteria values mathematically. The existing index of vehicle theft is built on the assumption that all criteria are equally important and based on numerical data only without considering ambiguity aspect, particularly the causes of the crime. Moreover, there was no decision-makers involvement to assess the level of contribution of criminal criteria based on their knowledge and experience. Therefore, this study developed an improved InJeCK by considering the fuzziness. InJeCK also involves decision-makers in determining the degree of importance of vehicle theft crime criteria, in addition to numerical data analysis obtained from related agencies. The subjective weights in this study utilized Z-numbers through the level of contribution of the criteria evaluated in the representation of two triangular fuzzy numbers. Objective weights used the degree of uncertainty through entropy measurements. These two weights were aggregated to form an aggregated weight that balances the weaknesses of both subjective and objective weights. Next, InJeCK was computed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank 82 areas in Peninsular Malaysia. InJeCK values were visualized using color maps to be more informative. The results show that the criteria of car theft, higher education and unemployment are the three most influential criteria in vehicle theft crime based on the aggregated weights. The InJeCK values show that Kuala Lumpur is the riskiest area for vehicle theft cases. This study has contributed to the field of multi-criteria decision-making by considering fuzzy environment in the development of vehicle theft crime index. Besides, the findings of the study can also assist those involved in curbing vehicle theft in particular and property crime in general