Subtopic Deep Dive

Group Decision Making in MCDM
Research Guide

What is Group Decision Making in MCDM?

Group Decision Making in MCDM applies multi-criteria techniques to aggregate preferences from multiple experts, build consensus, and elicit heterogeneous opinions for collective decisions.

This subtopic covers aggregation operators, consensus measures, and methods like AHP and VIKOR adapted for groups. Key papers include Opricović and Tzeng (2003) on VIKOR-TOPSIS comparison (4588 citations) and Ishizaka and Labib (2011) on AHP developments (1162 citations). Over 100 papers address large-scale group frameworks and behavioral aspects since 2000 (Mardani et al., 2015).

Curated Papers

Key Challenges

Why It Matters

Group MCDM supports policy decisions in environmental projects by balancing sociopolitical and economic factors (Kiker et al., 2005, 900 citations). In corporate settings, it aids dispute resolution through SWARA weighting for rational method selection (Keršulienė et al., 2010, 1387 citations). Ho (2007) shows integrated AHP applications in supply chain group decisions (1128 citations), enhancing governance outcomes.

Key Research Challenges

Heterogeneous Preference Aggregation

Aggregating diverse expert opinions in MCDM requires operators handling uncertainty, as in q-rung orthopair fuzzy sets (Liu and Wang, 2017). VIKOR and TOPSIS differ in compromise solutions for groups (Opricović and Tzeng, 2003). Consensus building remains inconsistent across methods (Mardani et al., 2015).

Consensus Measurement Reliability

Measuring group consensus in large-scale MCDM faces scalability issues with methods like DEMATEL (Si et al., 2018, 956 citations). Behavioral biases affect preference elicitation reliability (Ishizaka and Labib, 2011). Fuzzy MCDM reviews highlight gaps in validation (Mardani et al., 2015).

Large-Scale Group Scalability

Handling hundreds of experts in MCDM demands efficient frameworks beyond traditional AHP (Ho, 2007). EDAS classification struggles with group inventory decisions (Keshavarz-Ghorabaee et al., 2015, 1218 citations). Environmental applications show trade-off complexities (Kiker et al., 2005).

Essential Papers

Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS

Serafim Opricović, Gwo‐Hshiung Tzeng · 2003 · European Journal of Operational Research · 4.6K citations

SELECTION OF RATIONAL DISPUTE RESOLUTION METHOD BY APPLYING NEW STEP‐WISE WEIGHT ASSESSMENT RATIO ANALYSIS (SWARA)

Violeta Keršulienė, Edmundas Kazimieras Zavadskas, Zenonas Turskis · 2010 · Journal of Business Economics and Management · 1.4K citations

The paper considers major principles of application of the multi‐attribute systems to solve legislative tasks. In order to assess dispute resolution methods from economic, social and other points o...

Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS)

Mehdi Keshavarz-Ghorabaee, Edmundas Kazimieras Zavadskas, Laya Olfat et al. · 2015 · Informatica · 1.2K citations

An effective way for managing and controlling a large number of inventory items or stock keeping units (SKUs) is the inventory classification. Traditional ABC analysis which based on only a single ...

Review of the main developments in the analytic hierarchy process

Alessio Ishizaka, Ashraf Labib · 2011 · Expert Systems with Applications · 1.2K citations

Integrated analytic hierarchy process and its applications – A literature review

William Ho · 2007 · European Journal of Operational Research · 1.1K citations

Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Abbas Mardani, Ahmad Jusoh, Khalil Md Nor et al. · 2015 · Economic Research-Ekonomska Istraživanja · 1.1K citations

Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and appro...

DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications

Shengli Si, Xiao‐Yue You, Hu‐Chen Liu et al. · 2018 · Mathematical Problems in Engineering · 956 citations

Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating ...

Reading Guide

Foundational Papers

Start with Opricović and Tzeng (2003) for VIKOR-TOPSIS compromise basics (4588 citations), then Ho (2007) for AHP group applications (1128 citations), and Kiker et al. (2005) for environmental trade-offs (900 citations).

Recent Advances

Study Keshavarz-Ghorabaee et al. (2015) on EDAS group classification (1218 citations), Si et al. (2018) DEMATEL review (956 citations), and Liu and Wang (2017) q-ROFS operators (869 citations).

Core Methods

Core techniques: VIKOR/TOPSIS aggregation (Opricović and Tzeng, 2003), SWARA weighting (Keršulienė et al., 2010), AHP hierarchies (Ishizaka and Labib, 2011), DEMATEL interdependencies (Si et al., 2018).

How PapersFlow Helps You Research Group Decision Making in MCDM

Discover & Search

Research Agent uses searchPapers and citationGraph to map group MCDM literature from Opricović and Tzeng (2003), revealing VIKOR extensions. exaSearch finds 50+ papers on fuzzy aggregation; findSimilarPapers links to Liu and Wang (2017) q-ROFS operators.

Analyze & Verify

Analysis Agent applies readPaperContent to extract consensus algorithms from Ishizaka and Labib (2011), then verifyResponse with CoVe checks aggregation claims against Keršulienė et al. (2010). runPythonAnalysis simulates VIKOR rankings via NumPy; GRADE scores evidence strength in group preference studies.

Synthesize & Write

Synthesis Agent detects gaps in large-scale consensus via contradiction flagging across Mardani et al. (2015) reviews. Writing Agent uses latexEditText, latexSyncCitations for AHP group models, and latexCompile to generate decision matrices; exportMermaid diagrams fuzzy operator flows.

Use Cases

"Compare VIKOR and TOPSIS for group consensus in policy making"

Research Agent → searchPapers('group VIKOR TOPSIS') → Analysis Agent → runPythonAnalysis (reproduce Opricović-Tzeng rankings) → GRADE verification → researcher gets Python-validated comparison table.

"Draft LaTeX paper on fuzzy aggregation for large-scale GDM"

Synthesis Agent → gap detection (Mardani 2015) → Writing Agent → latexEditText (add SWARA section) → latexSyncCitations (Ho 2007) → latexCompile → researcher gets compiled PDF with group MCDM framework.

"Find code for DEMATEL group decision implementation"

Research Agent → paperExtractUrls (Si et al. 2018) → Code Discovery → paperFindGithubRepo → githubRepoInspect → researcher gets verified Python repo for DEMATEL cause-effect graphs.

Automated Workflows

Deep Research workflow scans 50+ papers via citationGraph from Opricović-Tzeng (2003), producing structured review on aggregation operators with GRADE scores. DeepScan applies 7-step CoVe to verify consensus measures in Ishizaka-Labib (2011). Theorizer generates hypotheses on q-ROFS scalability from Liu-Wang (2017).

Try Doxa for Group Decision Making in MCDM Research

Frequently Asked Questions

What defines Group Decision Making in MCDM?

It aggregates multi-criteria preferences from groups using operators, consensus building, and methods like VIKOR for heterogeneous experts (Opricović and Tzeng, 2003).

What are core methods in this subtopic?

Key methods include AHP for group hierarchies (Ishizaka and Labib, 2011), SWARA weighting (Keršulienė et al., 2010), and fuzzy operators (Mardani et al., 2015).

What are influential papers?

Opricović and Tzeng (2003, 4588 citations) on VIKOR-TOPSIS; Ho (2007, 1128 citations) on integrated AHP; Si et al. (2018, 956 citations) on DEMATEL.

What open problems exist?

Scalable consensus for large groups, behavioral bias mitigation in elicitation, and hybrid fuzzy-VIKOR validation remain unsolved (Keshavarz-Ghorabaee et al., 2015; Mardani et al., 2015).