Multiple Criteria Decision Support Research Articles

Multiple criteria decision support system for customer segmentation using a sorting outranking method

For companies, customer segmentation plays a key role in improving supply chain management by implementing appropriate marketing strategies. The objectives of this research are to design and validate a multicriteria model to support decision making for customer segmentation in a business to business context. First, the model based on the transactional customer behaviour is extended by a hierarchy with three main criteria: Recency, Frequency and Monetary (RFM), customer collaboration and growth rates. Customer collaboration includes quota compliance, variety of products and customer commitment to sustainability (reverse logistics and shared information). Second, the Global Local Net Flow Sorting (GLNF sorting) algorithm is implemented and validated using real company data to classify 8,157 customers of a multinational healthcare company. Third, the SILS quality indicator has been implemented and validated to assess the quality of preference-ordered customer groups and its parameters have been adapted for contexts with thousands of alternatives. The results are also compared with an alternative model based on data mining (K-means). The multicriteria system proposed allows to segment thousands of customers in ordered categories by preferences according to company strategies. The segments generated are more homogeneous, robust and understandable by managers than those from alternative methods. These advantages represent a relevant contribution to automating supply chain management while providing detailed analysis tools for decision making.

Multiple criteria decision support analysis for manufacturing process parameters selection of metallic bipolar plates for polymer electrolyte membrane fuel cells

The multi-criteria decision-making method, along with experimental and finite-element (FE) methods, was employed to determine the optimal process parameter values for rubber pad forming of metallic bipolar plates. To achieve this aim, the rubber pad forming process was modeled by FE software, and the results were validated by conducting experimental tests. Three significant rubber pad forming parameters—punch force, hardness, and the thickness of the rubber layer—were considered as input variables. A full-factorial design involving 27 experiments was used to assess the alternatives. Filling percentage, thinning ratio, and stress were considered as distinct evaluation criteria. To solve the multi-criteria decision-making problem, a hybrid approach was used to weigh the alternatives. According to the results, the applied method was capable of selecting the optimal values of process parameters while considering different criteria simultaneously. The results demonstrated that a punch force of 50 kN, rubber hardness of 55 Shore A, and rubber thickness of 3.5 mm were the best processing conditions. For these parameters, the filling percentage, thinning ratio, and stress were 97.6%, 28.5%, and 1005 MPa, respectively.

A Fuzzy Analytic Hierarchy Process Model to Evaluate Logistics Service Expectations and Delivery Methods in Last-Mile Delivery in Brazil

Nowadays, postal services and third-party logistics services (3PL) have been pressured by the increasing demand for delivery services. Therefore, they need to improve their last-mile delivery strategies to meet customers’ expectations. This paper aims to investigate how logistics service expectations affect the delivery process in urban areas using a multiple-criteria decision support system based on the Fuzzy Analytic Hierarchy Process (FAHP). We developed a decision-making model employing six criteria and five delivery methods indicated in the literature and collected information from 27 experts working in academia and local and multinational third-party logistics providers in Brazil to validate this model. The results indicate that cost (21.4%) and tracking and tracing (19.3%) are the most important two criteria in the decision model, and the best delivery methods are smart lockers (21.8%) followed by small trucks (21.3%). Our results suggest that service expectations regarding last-mile delivery are aligned with extensive use of road transport and the increase in e-commerce sales can raise greenhouse gas emissions and compromise the environment in urban areas.

Multiparameter-analysis of CO2/Steam-enhanced gasification and pyrolysis for syngas and biochar production from low-cost feedstock

• Low-cost feedstock valorization by pyrolysis and gasification. • Products optimization via multi-criteria decision method. • CO 2 /Steam gasification showed clear energetic and H 2 exergy efficiency improvements. • HHV enhancement up to 19.42 and 83.11% for SCG and BSG biochar. • Better ignitability and combustibility for pyrolysis at lower temperatures. The disposal of spent coffee grounds (SCG) and brewers' spent grains (BSG) has become an environmental issue. Thus, the waste-to-energy valorization of these two low-cost feedstocks was performed via gasification and pyrolysis to assess their potential as syngas and biochar fuels. The processes’ optimum conditions were investigated by a multiple-criteria decision support method. Firstly, both raw materials were gasified at 1000 °C with O 2 /N 2 , O 2 /CO 2 /N 2 and O 2 /H 2 O/N 2 atmospheres. The characteristics and energy performance of the producer gas were evaluated. In addition, the exergy analysis of green-H 2 production was assessed. The pyrolysis experiments were conducted at 300, 500 and 700 °C, followed by a comprehensive characterization of the biochar properties and its combustion behavior. The syngas production based on CO 2 /Steam-enhanced gasification has indicated clear energetic and exergetic improvements against O 2 /N 2 with a promising increase of 32.97% LHV syngas for BSG. Obtained biochar possesses favorable fuel characteristics promoting an HHV enhancement up to 19.42% (SCG) and 83.11% (BSG). Furthermore, the combustion index indicated a great potential of using SCG and BSG as solid biofuel for straightforward application to heat generation in small-scale systems. Therefore, syngas and biochar characteristics encourage feasible biofuels from low-cost feedstocks for energy generation.

Pythagorean fuzzy likelihood function based on beta distributions and its based dominance ordering model in an uncertain multiple criteria decision support framework

The concept of Pythagorean fuzzy (PF) sets represents a superior tool to model complex uncertainties in an ambiguous and equivocal decision-making framework. In consideration of the significant capacity for exhibiting the uncertainty of subjective appraisals and estimations under the aegis of the PF theory, this paper presents a simple-to-operate decision-making approach that is grounded in some beneficial concepts of original likelihood functions and measurements of dominating and dominated characters. On the strength of beta distributions, this paper seeks to propound new notions of PF likelihood functions and likelihood-oriented dominating/dominated characters and to launch an exploitable multiple criteria evaluation method by means of a dominance ordering model for treating decision analysis within PF environments. This paper initiates an efficient beta distribution-based approach to the construction of novel PF likelihood functions that can quantify the possibility degrees of outranking and outranked relationships between Pythagorean membership grades. The applicable satisfaction and dissatisfaction estimations are established on the likelihood-oriented dominating and dominated characters, respectively. Furthermore, this paper formulates a straightforward dominance ordering model to obtain the ultimate dominance ranking orders of candidate alternatives and accomplish multiple criteria decision-making issues involving complicated uncertainty. A financing decision-making problem concerning working capital requirements is investigated to validate the application results using the advanced methodology. The real-world application is implemented to examine the reasonableness and efficacy of the established techniques. Moreover, comparative studies through the utility of a sensitivity analysis are performed to demonstrate the efficacy and merits of the dominance ordering model. The comparison results manifest that the initiated methodology is an advantageous and reliable decision-making technique that can enhance the methodological development regarding the multiple criteria evaluation model under PF uncertainty. Finally, recommendations for future research directions are also presented in the conclusions.

Living Cost Gap in the European Union Member States

The living cost gap refers to the differential amongst income, expenditures, and poverty lines. It is important since it addresses a number of aspects that point towards historic and continued living standards. The purpose of this study is to identify, measure, and compare the living cost gap in the Europe Union member states. Twenty-nine indicators/criteria from Eurostat and World Bank, covering the period 2008–2017, are employed. In order to rank and compare living cost gap by countries, objective functions for each criterion are defined and applied. The importance of each criterion is assessed independently. The composite living cost gap indicator for each MS is calculated using multiple criteria decision support methods. The relationship between the compound annual growth rates of this indicator and each single criterion is estimated and evaluated. The findings of the study suggest that living cost gap is higher where unemployment rates and households’ expenditure on basic needs (housing, food etc.), are larger, while living cost gap is lower where households’ income and expenditure on optional needs are higher. The living cost gap in the majority of countries tends to narrow/decrease, along with the increase in the household income and expenditures. Our research highlights the need to mitigate unemployment and households’ low net income in order to alleviate living cost gap. The analysis and assessment of living cost gap might help identifying the most vulnerable social profiles and groups, and hence might contribute to the adequate formulation and implementation of targeted policy responses and interventions at European Union, national, and regional level.

SUPPLY CHAIN MANAGEMENT BASED ON HIERARCHICAL DECISION SUPPORT MODEL

Background. Information is one of the key elements for effective supply chain (SC) management. Availability of timely information ensures the continuous movement of commodity flows, minimizes the company's losses associated with the lack of goods or excess stocks, allows you to plan production and financial flows, take into account changes in consumer interests. The systems of information exchange between the participants of the SC are used. Predicting future sales is necessary to control the flow of goods, so firms do consumer demand forecasting.Objective. Since the explicit information has different usefulness for forecasting and decision-making for different SC participants, the problem arises of assessing the priority of various types of information in the SC management system in order to obtain a more accurate forecast of consumer demand. The aim of the work is to develop an algorithm for calculating the values of the relative importance or priority of various types of information in the SC based on a hierarchical model of criteria using the opinions of the SC participants.Methods. The task of systemic assessment of the priority of information needs in the SC management system is formulated as a task of multi-criteria decision support. There are several types of information that can be used to predict consumer demand, these are alternative solutions. A hierarchical model of SC has been built, which includes criteria for the cost of obtaining information from other participants of the SC, accuracy and reliability of the source of information, degree of its use and other criteria affecting the efficiency of using information for forecasting demand.Results. An algorithm for analyzing the SC management system based on a decision support hierarchical model is proposed. The functional capabilities of the developed decision support system for solving multiple criteria decision support problems are shown, when the input information are evaluations of the SC subjects.Conclusions. The developed algorithm is used for a wider class of decision support problems, in particular when part of the expert assessments is not sufficiently consistent. In this case, the most inconsistent assessments are searched without the participation of an expert, the set of expert evaluations is adjusted by various methods depending on the properties of the corresponding pairwise comparison matrices. The proposed algorithm includes several methods for calculating the local weights of the elements of decision support hierarchical model and various methods of aggregating these weights, which increase the reliability of the obtained results.

Developing a multi-criteria decision support system for evaluating knowledge transfer by higher education institutions

ABSTRACTThis study sought to develop a multiple-criteria decision support system for evaluating transfers of knowledge from higher education institutions (HEIs) to society at large. Drawing on a panel of knowledge transfer specialists, we developed the evaluation system by completing the three phases of the multiple-criteria decision analysis (MCDA) approach. The structuring phase used the strategic options development and analysis (SODA) methodology and cognitive mapping techniques. The evaluation phase applied the measuring attractiveness by a categorical-based evaluation technique (MACBETH), which allowed us to evaluate HEIs’ local and overall performance. The third phase consisted of formulating recommendations. Assuming a constructivist process-oriented stance, this research included a real-world application of the proposed system to Portuguese public HEIs. Our study demonstrates that HEI administrators can use the techniques applied to make strategic decisions when seeking to foster the transfer of knowledge to society at large.

The Relationship between Non-Financial Stakeholders and Capital Structure

Financial accountong literatures have highlighted the important role of non-financial factors such as intellectual capital (IC) as a main value added factor for companies, and perceived environmental uncertainty (PEU) as unpredictable contingency factor from a dynamic environment on the corporate performance (CP). Therefore, it is important for organizations to rely more on non-financial than financial factors to achieve higher competitive advantage. Identifying the most important non-financial factors affecting corporate performance from these environments and their relationship with capital structures is the main issue in today's dynamic conditions. This research examined the relationship between non-financial factors of IC and PEU and evaluated their influence on CS directly or indirectly by considering corporate performance as mediator. Questionnaires were distributed to 339 public listed Iranian manufacturing companies selected by census. Data were analysed using structural equation modeling. The main findings of this study are IC can enhance corporate performance, PEU is positively linked to corporate performance, and corporate performance is positively linked to capital structure. The results also indicated a full mediating role of corporate performance in the relationship between PEU and capital structure. This study contributes to determining capital structure decision making, by considering IC and PEU in the context of companies in Iran. Also, we analyze intellectual capital relation with and 1) traditional vs. secular-rational values and 2) survival vs. self-expresion values. Based on the analysis of existing knowledge, neutral networks, expert and decision support systems and in order to determine most effective versions of intellectual capital an Intellectual capital multiple criteria decision support (ICMCDS) system consisting of a database, databa management system, model-base, model-base management system and user interface was developed. Further in-depth research is needed to examine this links betwwen non-financial factors with different measurement perspectives and capital structure to develop a deeper understanding of their effect on capital structure.DOI: http://dx.doi.org/10.5755/j01.ee.28.4.16812

Multiple-Criteria Decision Support for a Sustainable Supply Chain: Applications to the Fashion Industry

With increasing globalization and international cooperation, the importance of sustainability management across supply chains has received much attention by companies across various industries. Companies therefore strive to implement effective and integrated sustainable supply chain management initiatives to improve their operational and economic performance while also minimizing unnecessary damage to the environment and maintaining their social reputation and images. The paper presents an easy-to-use decision-support approach based on multiple-criteria decision-making (MCDM) methodologies that aim to help companies develop effective models for timely decision-making involving sustainable supply chain management strategies. The proposed approach can be used by practitioners to ultimately build a comprehensive Analytic Network Process model that will adequately capture and reveal all the interrelationships and interdependency among the elements in the problem, which is often a very difficult task. To facilitate and simplify this complex process, we propose that hierarchical thinking be used first to structure the essences of the problem capturing only the major issues, and an Analytic Hierarchy Process (AHP) model be built. Users can learn from the modeling process and gain much insight into the problem. The AHP can then be extended to an Analytic Network Process (ANP) model so as to capture the relationships and interdependencies among the elements. Our approach can reduce the sustainable expertise, effort and information that are often needed to build an ANP model from scratch. We apply our approach to the evaluation of sustainable supply chain management strategies for the fashion industry. Three main dimensions of sustainability—environmental, economic and social—are considered. Based on the literature, we identified four alternative supply chain management strategies. It was found that the Reverse Logistics alternative appears to be the recommended solution by the AHP model. However, the Socially Leagile Supply Chain is recommended by the ANP model, thereby demonstrating the necessity and importance of considering interdependencies in the model.

A web-based multiple criteria decision support system for evaluation analysis of carpooling

Several researches in the scientific, industrial and commercial fields are supporting the reduction of traditional combustion cars’ use. The main purpose is to increase the quality of life into the metropolitan cities through the reduction of CO2 emissions and global warming. Accordingly, one of the most successful models is the carpooling system. Currently, people are investigating the sustainability and durability of carpooling business model from both economic and organizational point of view. The present research aims to develop a Multicriteria Decision Support System (MDSS) in order to offer a carpooling system’s platform based on different criteria. The MDSS is developed from driver’s point of view and settled on two levels of optimization. Firstly, a genetic algorithm is proposed to solve an orienteering problem that optimizes the total revenue of driver based on the car’s capability and the time schedule. Secondly, the best optimization solutions are compared with multicriteria analysis respect to other criteria not included in the first optimization. The outcome of MDSS is a schedule for drivers, which gives maximum satisfaction in terms of profitability, punctuality and comfort of the travel.

A study on the competitive strategy of the universal postal service provider

ABSTRACTWe analysed how the universal postal service providers could employ their specificities to achieve an advantage over the growing competition. The basic input for the model is expert opinions. We interviewed 18 experts in five stages. As a multiple criteria decision support method, we used an analytic hierarchy process. Further, we proposed a geometric method for determining the business area where a company should focus its biggest attention to achieve the best result. By implementing the proposed model, a company should obtain two types of business directions, the first related to the proposed activities and the second to the business areas. To demonstrate the applicability of the proposed methodology, we tested and verified it in the case of the Serbian universal postal service provider which is a state-owned company called the Post of Serbia.

Incorporating MCDS and voting into SWOT: Basic idea and experiences

The idea in using Multiple Criteria Decision Support (MCDS) and voting methods within a SWOT framework is to evaluate systematically the SWOT factors, and to assess them with respect to their priorities. The MCDS method applied initially, and most often, with SWOT has been the Analytic Hierarchy Process (AHP), and the hybrid AHP-SWOT approach has been called the A’WOT. Any MCDS method can, however, be applied; the choice of the method depending on the strategy process in question. In this article, experiences of using the A’WOT method with AHP, SMART and SMAA-O techniques is summarized. In addition, an illustrative example of making use of social choice theory within SWOT framework is presented. The hybrid MCDS-SWOT approach has gained growing popularity, and it has been applied in different fields world-widely. It may provide not only a solid decision support but also an effective framework for learning in strategic decision support, as well as for communication in strategy processes with multiple stakeholders. The Voting-SWOT approach (VotSWOT) fits especially well with participatory strategy processes, as it reflects decision makers’ and stakeholders’ natural ways of communication.

SETTING RENTS IN RESIDENTIAL REAL ESTATE: A METHODOLOGICAL PROPOSAL USING MULTIPLE CRITERIA DECISION ANALYSIS

The real estate sector has been negatively affected by the recent economic recession, which has forced structural changes that impact property value and price. Recent pressures have also motivated reduced liquidity and access to credit, causing a drop in property sales and, thus, boosting the rental housing market. It is worth noting, however, that the rental housing segment is not with-out difficulties and complexity, namely in terms of legislation and rental value revaluation. In light of this reasoning, this study aims to develop a multiple criteria decision support system for calculation of residential rents. By integrating cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH), we also aim to introduce simplicity and transparency in the decision making framework. The practical implications, advantages and shortfalls of our proposal are also analyzed.

DECISION MODEL FOR SELECTION OF MODERNIZATION MEASURES: PUBLIC BUILDING CASE

The aim of our study is to present the decision model for selection of optimal combinations of modernization measures. the presented algorithm of decision synthesis method comprises method for integrated significance determination of efficiency indicators and multiple criteria decision methods. the paper also presents the case study illustrating the application of proposed model. as the alternative modernization measures can generate many alternative combinations the decision tree model was proposed as an efficient tool facilitating the analysis of big data and included in algorithm. three multiple criteria decision support methods based on quantitative measurements included in algorithm used to increase the reliability of the decision. the proposed algorithm is very suitable for evaluation of modernization decisions of the building and enables decision-maker to select the best performing alternative in terms of energy consumption, cost of instalment and other relevant criteria.

A MULTIPLE CRITERIA DECISION SUPPORT SYSTEM FOR ANALYZING THE CORRELATION BETWEEN THE THICKNESS OF A THERMO-INSULATION LAYER AND ITS PAYBACK PERIOD OF THE EXTERNAL WALL

A case study provides the correlation analysis of the thickness of the thermo-insulation layer (expanded polystyrene – EPS70) of the typical details of the external wall and energy performance class in a modern newly constructed residential low-energy building (one and two-room apartment). The conducted analysis focused on what impact different geographical areas of building construction and different energy performance classes of the building may had on the thickness of the thermo-insulation layer. Lithuania was chosen as the object of this study. Calculations were carried out in seven towns, including Vilnius, Klaipeda, Kaunas, Siauliai, Panevezys, Utena and Dukstas. According to requirements for legal acts passed in the Republic of Lithuania and to Directive 2010/31/EU (2010), as a result, the necessary thickness of thermo-insulation layers (EPS70) and a payback period were calculated. A multiple criteria decision support system for analyzing the correlation between the thickness of the thermo-insulation layer and its payback period of the external wall (DSS-ACTILPW) consisting of a database, a database management system, a model-base, a model-base management system and a user interface was developed. Information on the performed analysis is important to building designers, energy consumption auditors and investment experts who make the final decisions on energy efficiency of buildings in the residential building sector.

A cloud-based multi-criteria decision support system for selecting urban housing projects

Abstract This paper proposes a Cloud based multiple criteria decision support system (DSS) for Selecting Urban Housing Sustainable Development Projects in order to help the decision makers to choose the best urban project with conflicting criteria. The DSS is deployed on a platform Cloud (CloudBees) and managed by the OpenStack infrastructure. The Cloud based multiple criteria DSS we designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making (MCDM) method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project.

Measurements of risk in fisheries management

An important goal in many fisheries management problems is perceived to be minimisation of risk. This paper examines the problem of measuring risk by means of meaningful attributes or surrogate measures, for use in multiple criteria decision support systems. It is found that exponential utility functions, which are associated in this context with geometric discounting of the future, give a poor fit in many cases relative to power functions. The implication is that conventional mean-variance measures of risk may be less appropriate than cumulative probability measures.

Avaliação de sintetizadores de voz para leitura em livros digitais

A acessibilidade digital indica meios para acesso à informação em mídias digitais que auxiliam pessoas com diferentes tipos de deficiência a uma melhor interação com o computador, independente de suas limitações. Parte destas ferramentas é composta pelos sintetizadores de voz, que supostamente permitem facilitar o acesso dessas pessoas a qualquer conhecimento registrado através de tecnologias digitais. Contudo tais ferramentas surgiram inicialmente em países de língua estrangeira. O que nos leva ao seguinte problema de pesquisa: os sitentizadores de voz estão adequados a leituras de livros digitais em língua portuguesa? O objetivo deste trabalho foi analisar e classificar diferentes ferramentas de software sintetizadores de voz em conjunto com software de leitores de livros digitais para apoio à acessibilidade aos e-books em língua portuguesa. Por meio de revisão bibliográfica foram identificados aplicativos de software sintetizadores de voz, que compõem a amostra analisada neste trabalho. Foi usado uma versão simplificada do Método de Multicritério de Apoio à Decisão – MMDA, para avaliar estas. Na pesquisa foram considerados 12 leitores de e-books e 11 softwares sintetizadores de voz, testados com seis formatos de e-books (E-pub, PDF, HTML, DOC, TXT e Mobi). De acordo com os resultados apurados, o software Virtual Vision atingiu a maior pontuação. Com relação aos formatos, foi constatado que o PDF aferiu uma melhor pontuação, quando somado os resultados dos três sintetizadores. Dentro do universo estudado, contatou-se que muitos sintetizadores simplesmente não podem ser utilizados por não terem suporte a língua portuguesa.

Defining a quality index for electric power utilities using multiple criteria decision support and time series analysis

This paper presents a hybrid multi-criteria method developed through the combination of the Analytical Hierarchy Process (AHP) and exponential smoothing techniques applied in time series forecasting. To illustrate its use, a model was developed with the aim of creating a quality index for electric power distribution utilities. The conclusions highlight the need to take into account the results obtained in the latest months for those utilities, but giving less attention to those obtained in the earlier months. This characteristic of the problem led to the idea of incorporating the mathematical formulation of the exponential smoothing into the aggregation function of the AHP. At the end, the utility company is given a score between 0 (zero) and 10 (ten).