Group Decision Support Research Articles

Consumer Satisfaction Benchmarking Analysis Using Group Decision Support System (GDSS) PROMETHEE Methodology in a GIS Environment

In today’s competitive environment, multi-branch companies allocate their stores with the aim of expanding their territorial coverage to attract new customers and increase their market share. Consumer satisfaction surveys either produce global performance results or they are not able to differentiate consumer perceptions using location analytics. This research develops a novel framework to assist multi-branch companies in mapping the consumer satisfaction performance of their stores, expanding conventional customer relationship management to the spatial context. The framework developed proposes a decision model that combines the Group Decision Support extension of the PROMETHEE and CRITIC methods in a GIS environment to generate satisfaction performance mappings. The developed decision-making framework converts consumer responses into satisfaction performance maps, allowing the company’s stores and their competitors to be evaluated. Moreover, it provides insight into the potential opportunities and threats for each store. The performance of the proposed framework is highlighted through a case study involving a multi-branch coffeehouse company in a Greek city. Finally, a tool developed to assist the computational part of the framework is presented.

Proposition of a new tool for the election of group decision support system facilitator based on the multi-criteria approach

Proposition of a new tool for the election of group decision support system facilitator based on the multi-criteria approach

Recommendation method for selecting the rice seeds based on group decision support system

<p>In this paper, we provide group recommendations based on each decision makers (DMs) in choosing the best type of rice for replanting. This group decision support system (GDSS) aims to guide stakeholders who have a role in selecting rice types. In this method, we propose using technique for order preference by similarity to ideal solution (TOPSIS) to rank each DM, Borda to rank in groups, and then test it using Spearman's rank correlation to measure the relationship between system results and the method applied. The results of this study show that DM<sub>1</sub> ranks highest in selecting Gelagai rice seeds with a preference of 0.7786. Then DM<sub>2</sub> ranked highest with Ekor Payau rice seeds in preference 0.6529. Meanwhile, DM<sub>3</sub> ranked highest in Gelagai rice seeds with a selection of 0.7728. The final group voting system uses Borda, where Gelagai rice seeds occupy the highest rank with the most accumulated votes from each DMs. The best option or the highest rating based on the assessment of the three DMs, DM<sub>1</sub> as a farmer is the first rank A10 Gelagai with a score of Borda 26 in the decision group selection of superior rice seeds.</p>

An integrated group decision support framework utilizing Pythagorean fuzzy DEMATEL–CoCoSo approach for medicine cold chain logistics provider selection

PurposeThe purpose of this study is to establish a synthetic group decision framework based on the Pythagorean fuzzy (PF) set to select the optimal medicine cold chain logistics provider (MCCLP). Fierce market competition makes enterprises must constantly improve every link in the process of enterprise sustainable development. The evaluation of MCCLP in pharmaceutical enterprises is an important link to enhance the comprehensive competitiveness. Because of the fuzziness of expert cognition and the complexity of the decision procedure, PF set can effectively handle the uncertainty and ambiguity in the process of multi-criteria group decision decision-making (MCGDM).Design/methodology/approachThis paper develops an integrated group decision framework through combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique and combined compromise solution (CoCoSo) approach to select a satisfactory MCCLP within PF circumstances. First, the PF set is used to process the ambiguity and uncertainty of the cognition ability of experts. Second, a novel PF knowledge measure is propounded to measure the vagueness of the PF set. Third, a comprehensive criterion weight determination technique is developed through aggregating subjective weights attained utilizing the PF DEMATEL approach and objective weight deduced by knowledge measure method. Furthermore, an integrated MCGDM approach based on synthetic weight and CoCoSo method is constructed.FindingsThe outcomes of sensibility analysis and comparison investigation show that the suggested decision framework can help decision experts to choose a satisfactory MCCLP scientifically and reasonably. Accordingly, the propounded comprehensive decision framework can be recommended to enterprises and organizations to assess the MCCLP for their improvement of core competitiveness.Originality/valueMCCLP selection is not only momentous for pharmaceutical enterprises to improve transportation quality and ensure medicine safety but also provides a strong guarantee for enterprises to improve their core competitiveness. Nevertheless, enterprises face certain challenges due to the uncertainty of the assessment environment as well as human cognition in the process of choosing a satisfactory MCCLP. PF set possesses a formidable capability to address the uncertainty and imprecision information in the process of MCGDM. Therefore, pharmaceutical enterprises can implement the proposed method to evaluate the suppliers to further improve the comprehensive profit of enterprises.

A consistency and consensus model for group decision support based on the outranking approach

A consistency and consensus model for group decision support based on the outranking approach

Group decision support system based on multi-granular fractional orthotriple fuzzy 2-tuple linguistic information model

The aim of this work is to put forward the concept of a novel decision support model for multi-criteria group decision making problems with multi-granular fractional orthotriple fuzzy 2-tuple linguistic (FOF2TL) information. The idea of fractional orthotriple fuzzy 2-tuple linguistic (2TL) model is put forward by integrating the advantages of fractional orthotriple fuzzy set and 2-tuple linguistic method. We define a transformation function to deal the consistency of multi-granular FOF2TL information. Secondly, the Archimedean coupla as well as the co-coupla are used to define operational laws for fractional orthotriple fuzzy 2-tuple linguistic numbers (FOF2TLNs). We take the relationship between attribute and experts, and defined fractional orthotriple fuzzy 2-tuple linguistic Banzhaf Choquet-Copula aggregation (FOF2TLBCCA) operators. Third, a method explains how to determine the fuzzy measure of expert and attribute sets. Next, the suggested operators are used to develop associated decision-making approaches. Finally, a numerical case is offered to demonstrate the concept's usefulness, along with pertinent comments; the merits of the suggested methodology are also evaluated by comparing it to several existing decision approaches.

Modelling of Flood Hazard Early Warning Group Decision Support System

Early warning of flood hazards needs to be carried out comprehensively to avoid a higher risk of disaster. Every decision on early warning of a flood hazard is carried out in part by one party, namely the government or water resource managers. This research aims to provide a collaborative decision-making model for early warning of flood hazards through a Group Decision Support System Model (GDSS), especially in Indonesia. The novelty of this research is that the GDSS model involves more than one decision-maker and multi-criteria decision-making for early warning of flood hazards in the downstream Kali Sadar River, Mojokerto Regency, East Java Province, Indonesia. The GDSS model was developed using a hybrid method, namely the Analytical Network Process (ANP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). There was more than one decision result; voting was carried out using the BORDA method to produce the decision. The test results of GDSS were obtained using a Spearman rank correlation coefficient of 0.8425 and matrix confusion, an accuracy value of 86.7%, a precision value of 86.7%, a recall value of 86.7%, and an f-measure of 86.7%. Based on the test results, good results were obtained from the GDSS model. Doi: 10.28991/CEJ-2024-010-02-018 Full Text: PDF

A software trustworthiness evaluation methodology for cloud services with picture fuzzy information

VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is one of the most commonly used decision-making technique. This work provides a software trustworthiness evaluation method based on VIKOR technique in a group decision-making (GDM) environment. Entropy is an important measure that refers to the amount of disorder in a decision support system. To quantify the decision quality of decision maker (DM), a new method for determining DM weights is proposed according to the entropy value of decision matrix, which is provided by that DM. A new normalization-projection measure is developed in order to test the closeness between two evaluation matrices in software trustworthiness evaluation process. The group regret measure in VIKOR-based GDM method is based on two negative reference matrices in this model. A new ranking method with classification is also developed in this work. Aiming at the complex and changeable environment, these new measures and methods are expected to enrich VIKOR techniques and to play a constructive role in group decision support systems. The feasibility and practicability of developed method are verified by some experiments. This study finds that the different methods (models) may have different results in situations where the same decision data are provided by DMs; and this study also finds that the different parameters may have different results in situation where the decision model is same. The practical implications of developed GDM method can apply not only to software trustworthiness evaluation, but also to many other product quality evaluations.

The impact of group decision support systems on decision-making

The impact of group decision support systems on decision-making

The impact of group decision support systems on decision-making

The impact of group decision support systems on decision-making

Providing climate change resilient land-use transport projects with green finance using Z extended numbers based decision-making model

As the climate change enforces decision-makers (DMs) to change established policies and strategies, investors are motivated to finance the development of green projects. Because of their environmental effects, land-use transport projects are of special importance in this process. Different types of environment-friendly land-use transportation projects are financed by the private sector or regulatory authorities and institutions. However, the choice of the correct project is a complex issue. In the decision-making process, social concerns are crucial as well as financial, technical and environmental ones. In order to solve the multi-criteria decision-making problem, we propose a novel group decision support model using the Logarithm Methodology of Additive Weights (LMAW) and Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) based on the fuzzy Z extension (ZE)-numbers. The proposed group decision support model has a unique capability for decision. The opinions of two groups of the DMs and experts are used to consider the decision reliability in two different stages to reach an optimal decision. To illustrate the use of model, we create a scenario that considers four small-scale green finance planning alternatives that are evaluated using twelve criteria that reflect the choice problem's economic, environmental, technical, and political aspects. According to the findings, the optimum plan should be both inclusive and equitable, as well as economically efficient. Selection of the best green finance planning involves consideration of socioeconomic variables.

Methodology and Multicriteria Algorithm for Group Decision Support in Classification Problems

In this work, a Group Decision methodology and algorithm for small collaborating teams is introduced. It is based on a multicriteria algorithm for classification decisions, where aggregation of member preferences is executed at the parameter level. The algorithm applies to relatively well-structured problems guided by a process facilitator. Initially, a set of parameters is proposed by the facilitator to the group and next group members evaluate the proposed parameter set and express their preferences in numeric or linguistic format. Individual preferences are aggregated by appropriate operators, and a set of group parameter values is generated, which is used as input for the classification algorithm. NeXClass multicriteria classification algorithm is used for the classification of alternatives, initially at a training set of alternatives and later at the entire set. Finally, group members evaluate results, and consensus, as well as satisfaction metrics, are calculated. In case of a low acceptance level, problem parameters are reviewed by the facilitator, and the aggregation phase is repeated. The methodology is a valid approach for group decision problems and can be utilized in numerous business environments. The algorithm can be also utilized by software agents in multiagent environments for automated decision-making, given the large volume of agent-based decision-making in various settings today.

Software systems supporting remote education – Fuzzy assessment using a multi-criteria group decision-making method

During the COVID-19 pandemic, the demand for systems supporting remote education increased significantly, and after the pandemic this form of education remained in place to supplement the stationary education. Among the tools that comprehensively support remote learning, there are two most popular systems, i.e. Google Workspace for Education and Microsoft Office 365, available in several different variants, differing in the functionalities offered. The aim of the article is to analyse the functionality, as well as to compare and evaluate this software. Since the assessment of e-learning systems is based on the subjective judgements of experts, and the assessment criteria are qualitative in nature, a new MCGDM (Multi-Criteria Group Decision Making) method called NEAT F-PROMETHEE GDSS (New Easy Approach To Fuzzy PROMETHEE – Group Decision Support System) was developed for the purposes of the study. This method captures the uncertain and imprecise qualitative assessments expressed by many experts and aggregates them into an overall quantitative assessment. As a result of the assessment, it was found that all variants of Google Workspace for Education and Microsoft Office 365 meet the basic requirements for tools for conducting remote learning. In addition, the use of the NEAT F-PROMETHEE GDSS method made it possible to create a ranking of individual software variants. Based on the group evaluation, it was determined that the best system in terms of the relationship between the offered capabilities and the cost of use is Google Workspace for Education Plus, with other variants of Google Workspace for Education taking subsequent positions in the ranking. In turn, Microsoft Office 365 solutions received a worse group rating, largely due to the higher cost of use and slightly less ability to control student work.

Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness. In the context of real estate enterprises, credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects. Additionally, it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry. However, Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns, making subjective evaluation approaches inevitable, occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks. To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises, this study proposes an integrated multi-criteria group decision-making approach. First, a credit risk assessment index for Chinese real estate enterprises is established. Then, the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods. This approach is suitable for processing large amounts of data with high uncertainty, which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjective evaluation information. Finally, the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility. This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

A Web-based Group Decision Support System for Retail Product Sales a Case Study on Padang, Indonesia

The industrial sector's growth has led to an increase in the number of industrial products available in the market. However, this has made it more challenging for retail merchants to choose which items to sell due to the overwhelming number of options. The seller must carefully consider various factors such as the type, quality, and probability of selling the goods to turn a profit. This research proposes a group decision support system to assist retail sellers in selecting the products to sell. The system is designed to process various information on comparing retail products against specific criteria, enabling sellers to make quick and accurate decisions. To achieve optimal results, this study combines three methods in the decision-making calculation process: Fuzzy Logic, EDAS, and Borda methods. The Fuzzy Logic method is used to assign a value to an unclear criterion, followed by the EDAS method ranking process, and ending with the combination of the decision-making results using the Borda method. The group decision support system is web-based and has been proven to provide effective solutions for retail business actors to increase sales and reduce losses. By using this system, retail sellers can make informed decisions about their products, enabling them to optimize their profits and reduce their risks. In conclusion, the increase in the number of industrial products has created challenges for retail merchants, but this research proposes a solution in the form of a group decision support system. Combining Fuzzy Logic, EDAS, and Borda methods results in an effective decision-making process that allows retail sellers to make informed decisions and achieve their business goals.

BIM-enabled decision optimization analysis for architectural glass material selection considering sustainability

The careful consideration and choice of Sustainable Architectural Glass Material (SAGM) is a crucial step towards reducing energy consumption and enhancing the overall sustainability of buildings. However, the current techniques employed for selecting architectural glass material do not take into account the aspect of sustainability in the ultimate adoption of material solutions, as perceived by the stakeholders. This study aims to develop a comprehensive evaluation criteria system and introduce a group decision support framework that utilizes Building Information Modeling technology to facilitate the selection of SAGM in large-scale projects, in accordance with the demands of various stakeholders. The proposed framework is utilized to address a selection problem related to SAGM faced by a large construction corporation in Wuhan. The findings indicate that the criteria of daylighting and thermal insulation performance hold significant importance, with insulating glass being a subtype of SAGM exhibiting superior performance. Ultimately, the proposed model is subjected to sensitivity and comparative analyses to validate its advantages over several existing methodologies. The proposed model in this study offers practitioners an optimized methodology for the selection of SAGM, while also providing a framework for the selection of other sustainable building materials.

An ontology-based spatial group decision support system for site selection application

<span lang="EN-US">This paper presents a new ontology-based multicriteria spatial group decision support system (GDSS) dedicated to site selection problems. Site selection is one of the most complex problems in the construction of a new building. It presents a crucial problem in terms of selecting the appropriate site among a group of decision makers with multiple alternatives (sites); in addition, the site must satisfy several criteria. To deal with this, the present paper introduces an ontology based multicriteria analysis method to solve semantic heterogeneity in vocabulary used by participants in spatial group decision support systems. The advantages of using ontology in GDSS are many: i) it enables the integration of heterogeneous sources of data available on the web and ii) it enables to facilitate meaning and sharing of data used in GDSS by participants. In order to facilitate cooperation and collaboration between participants in GDSS, our work aims to apply ontology at the model's structuration phase. The proposed system has been successfully implemented and exploited for a personalized environment.</span>

Group decision support system model to determine supervisor lecturers for student creativity programs

A group decision support system (GDSS) model was created in this study by implementing the weighted product (WP) method and the borda method to determine prospective assistant or supervisor lecturers for student creativity programs (PKMs) that are routinely carried out every year at the Sriwijaya State Polytechnic. This study applies 5 criteria, including i) education level, ii) academic position, iii) group tenure, iv) lecturer certification, and v) achievement in the field of three pillars of higher education. The decision-makers in this study consisted of the head of the department (DM–1), the secretary of the department (DM–2), and the head of the study program (DM–3) where they carried out the decision-making process in groups. The WP method is used to make preferences independently of the decision-makers to determine the best alternative based on predetermined criteria. The borda method is currently used to aggregate the decision-makers to obtain the final result in the form of an alternative ranking. The results of this study are sufficient to be used as a reference in determining the supervisor lecturer for PKM activities at the Department of Computer Engineering, State Polytechnic of Sriwijaya.

Group decision support system model to determine supervisor lecturers for student creativity programs

A group decision support system (GDSS) model was created in this study by implementing the weighted product (WP) method and the borda method to determine prospective assistant or supervisor lecturers for student creativity programs (PKMs) that are routinely carried out every year at the Sriwijaya State Polytechnic. This study applies 5 criteria, including i) education level, ii) academic position, iii) group tenure, iv) lecturer certification, and v) achievement in the field of three pillars of higher education. The decision-makers in this study consisted of the head of the department (DM–1), the secretary of the department (DM–2), and the head of the study program (DM–3) where they carried out the decision-making process in groups. The WP method is used to make preferences independently of the decision-makers to determine the best alternative based on predetermined criteria. The borda method is currently used to aggregate the decision-makers to obtain the final result in the form of an alternative ranking. The results of this study are sufficient to be used as a reference in determining the supervisor lecturer for PKM activities at the Department of Computer Engineering, State Polytechnic of Sriwijaya.

A web-based software for group decision with analytic hierarchy process

The Analytic Hierarchy Process (AHP) is a multi-criteria decision support method and is widely applied in many areas. The original AHP method proposed by Thomas L. Saaty in the 1970s requires (n²-n)/2 comparisons. The number of required comparisons can make using this method challenging for maintaining consistent judgments in problems involving many criteria and/or alternatives. Furthermore, the available software is platform-dependent and generally does not support group decision-making. In this paper, we present software for AHP that demands n-1 comparisons. Additionally, the software supports group decision-making using individual aggregation of priorities with arithmetic and geometric means. The system is available at http://ahpweb.net/ and is accessible from any internet-connected device. It currently has more than 100 users and dozens of decision problems in various areas.•The original AHP formulation requires (n²-n)/2 comparisons per cluster which makes it difficult to make consistent judgments.•AHP avaliable software does not enable group decision making.•The proposed system AHP-WEB fills these gaps. The method demands n-1 comparisons per cluster without any inconsistency and allows group decision making on a web system.