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New Applications in Multiple Criteria Decision Analysis, 3rd Edition
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New Applications in Multiple Criteria Decision Analysis, 3rd Edition

A Special Issue of Information (ISSN 2078-2489) belonging to the section "Information Applications".

Deadline for manuscript submissions: 30 October 2026 | Viewed by 27781

Editor

Prof. Dr. Maria Carmen Carnero

E-Mail Website
Guest Editor
Higher Technical School of Industrial Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Interests: multi-criteria decision making; maintenance; assessment systems; benchmarking; healthcare organisations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multi-Criteria Decision Analysis (MCDA) techniques have been used successfully in many real-world problems, such as in the fields of logistics, finance, environment, diagnostics, technology selection, etc. However, due to the revolution driven by Industry 4.0, with new breakthroughs in data integration, devices, knowledge techniques, innovation, management and technology, which underlines growing digitalisation and cooperative coordination between productive units in the economy, there are new concepts which are not yet involved with MCDA which would be advanced through including these techniques in decision processes. A similar revolution is happening in education, which is increasingly heading towards e-learning and web-based learning, and the management of industrial assets. Furthermore, the concept of corporate social responsibility has evolved to the point of being considered a way of managing companies based on handling the impact of their activity on their clients, employees, shareholders, local communities, the environment and on society in general. This covers social, economic, environmental and ethical/legal aspects, making it essential for organisations to assess their level of compliance with the objectives demanded by society in these areas. This must be achieved both individually and as an integrated part of a supply chain. Additionally, the development of artificial intelligence (AI) can provide a large number of positive contributions and ideas to improve the decision making process, but at the same time many ethical and moral conflicts can be solved or improved with the use of MCDA.

All MCDA techniques are welcome, especially combined techniques, the inclusion of advanced fuzzy sets (for example, type-2 fuzzy sets, rough sets, bipolar fuzzy sets, hesitant fuzzy sets, multi-valued fuzzy sets, interval-valued fuzzy sets, cubic sets, intuitionistic fuzzy sets, etc.), the uncertainies, imprecisions and vagueness characteristics of real decision making problems and applications of new multicriteria techniques. Also of interest are those that improve on those traditionally used, new methodologies for negotiation or group decision making, taking into account all stakeholders and multi-stage multicriteria problems, or sequential decision making over time, created from the definition of scenarios or combination of scenarios.

The scope of this issue is applications in MCDA in new fields, subjects or recent advances related to corporate social responsibility, supply chain, Industry 4.0, IoT or big data, safety and asset management, e-education, AI, etc.; that is, subjects which have recently undergone substantial change and where MCDA techniques have not yet been included in the decision processes.

Topics:

  • Applications in circular economy.
  • Applications in the field of political transparency and objective decision making.
  • Applications in justice and strong institutions.
  • Applications related to national or regional sustainable development.
  • Applications in responsible resource consumption and production.
  • Applications related to assessment of corporate social responsibility.
  • Applications in environmental assessment and climate actions.
  • Applications in selection and/or use of renewable energies.
  • Application in assessment and/or comparison of sustainable procedures, techniques and technologies.
  • Applications in selection, evaluation or optimisation of methodologies and technologies for waste reduction, recycling, and reuse in organisations and supply chains.
  • Applications in security and health and safety at work.
  • Applications in infrastructure or facilities in healthcare organisations.
  • Applications in selection or renewal of medical technologies.
  • Applications in diagnosis and treatment of disease.
  • Applications in service industries.
  • Applications in Industry 4.0.
  • Applications in selection, evaluation or combination of techniques for forecasting or obtaining of forecasting.
  • Applications in macroeconomic or microeconomic diagnosis.
  • Applications in new methodologies or technologies in education, e-learning and web-based learning.
  • Applications in asset management.
  • Application in risk management.
  • Applications in Internet of Things (IoT) and cloud.
  • Applications in IoT data access and integration.
  • Applications in data security, privacy and General Data Protection Regulation (GDPR).
  • Applications in big data.
  • Applications in ethical and moral conflicts related to Industry 4.0.
  • Applications in defence and military.
  • Applications in emergency or crisis situations (pandemics, natural disasters, etc.)
  • Application in social engineering.
  • Applications in risk and uncertainty management.
  • Applications in selection of software and apps.
  • Applications in artificial intelligence (AI) and machine learning.
  • Applications based in use of AI.
  • Applications in ethical and moral conflicts about the use of AI.
  • Applications of AI in education.

Prof. Dr. Maria Carmen Carnero
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-criteria decision analysis
  • decision processes
  • e-learning
  • artificial intelligence
  • advanced fuzzy sets
  • Industry 4.0

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Related Special Issue

Published Papers (15 papers)

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Research

27 pages, 2093 KB  
Article
A Multi-Criteria Decision-Making Framework for Evaluating Interactive Experience in Smart Museums
by Hao Dong, Muze Li, Zhengfeng Yang, Yunhao Zhang and Zuowen Bao
Information 2026, 17(6), 586; https://doi.org/10.3390/info17060586 - 12 Jun 2026
Cited by 1 | Viewed by 473
Abstract
Smart museums increasingly rely on digital media, interactive installations, artificial intelligence, augmented reality, and virtual reality to support cultural communication and visitor engagement. However, existing studies have mainly examined specific technologies, usability, or visitor satisfaction, while a systematic and quantitative framework for comparing [...] Read more.
Smart museums increasingly rely on digital media, interactive installations, artificial intelligence, augmented reality, and virtual reality to support cultural communication and visitor engagement. However, existing studies have mainly examined specific technologies, usability, or visitor satisfaction, while a systematic and quantitative framework for comparing interactive experience across different smart museums remains limited. To address this gap, this study proposes a hybrid multi-criteria decision-making framework for evaluating smart museum interactive experience. Based on the Strategic Experiential Modules, an evaluation system consisting of five dimensions—Sense, Feel, Think, Act, and Relate—and sixteen indicators was constructed. The Analytic Hierarchy Process was used to determine subjective weights from expert judgments, the entropy method was applied to capture the data-driven dispersion characteristics of expert evaluation data, and a game-theoretic combination weighting strategy was used to integrate the two weighting results. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare five representative smart museum cases. The results show that Zhejiang Provincial Museum achieved the highest relative closeness value (Ci = 0.9891), followed by Shanghai Museum (Ci = 0.8457) and Hunan Museum (Ci = 0.5326). Robustness analysis further showed that the ranking order remained consistent under entropy weights, AHP weights, average weights, and game-theoretic combined weights. The Friedman test indicated no significant difference in the relative closeness coefficients across weighting schemes (χ2 = 1.200, p = 0.753). These findings indicate that the proposed framework can effectively identify relative strengths and weaknesses in smart museum interactive experience and provide a replicable decision-support tool for experience-oriented museum design and optimization. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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24 pages, 2868 KB  
Article
The Application of Metaverse Technologies in Supply Chain Management: A Sustainable and Resilient View
by Saiswarup Dash, Sudeshna Rath, Sushanta Tripathy and Deepak Singhal
Information 2026, 17(6), 569; https://doi.org/10.3390/info17060569 - 9 Jun 2026
Viewed by 694
Abstract
In this paper, the different emerging metaverse technologies are identified, and a comprehensive understanding of the various technologies that can empower supply chains in various parts of the world is provided. It also presents a structure that shows how each of these classified [...] Read more.
In this paper, the different emerging metaverse technologies are identified, and a comprehensive understanding of the various technologies that can empower supply chains in various parts of the world is provided. It also presents a structure that shows how each of these classified technologies would work towards a robust and sustainable supply chain. Moreover, the study uses the fuzzy TOPSIS method to determine the most significant metaverse technology that can significantly enhance the resilience and sustainability of the supply chain networks across the world. The basic aim of this research is to arm the organizations with the latest technology in the metaverse, which enables them to develop a future-proof supply chain network capable of surviving in this ever-evolving world. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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35 pages, 366 KB  
Article
A Multi-Criteria Decision Framework for Enterprise LLM Routing
by Marcin Nowak
Information 2026, 17(6), 539; https://doi.org/10.3390/info17060539 - 1 Jun 2026
Viewed by 1118
Abstract
The increasing use of large language models (LLMs) in enterprises creates a need for routing mechanisms that select models according to both technical performance and organizational preferences. This article proposes a multicriteria decision-support framework for enterprise LLM routing that combines AHP-based criterion weighting [...] Read more.
The increasing use of large language models (LLMs) in enterprises creates a need for routing mechanisms that select models according to both technical performance and organizational preferences. This article proposes a multicriteria decision-support framework for enterprise LLM routing that combines AHP-based criterion weighting with SAW-based prompt-level model selection. The framework evaluates prompts according to criteria related to required accuracy, business risk, reasoning depth, cost sensitivity, response-time sensitivity, standardization, and creativity. The empirical evaluation was conducted on 500 heterogeneous business prompts, using GPT-5-nano as the prompt-scoring router, GPT-4o-mini as the cheaper response model, and GPT-5 as the stronger response model. Costs were calculated from actual input and output token counts, including routing overhead. Response sufficiency was assessed using a structured LLM-as-a-judge protocol with three evaluator profiles. The proposed SAW routing variant with confidence margin and risk veto achieved a sufficiency rate of 94.4%, compared with 94.6% for the always-strong strategy and 86.8% for the always-cheap strategy. Relative to always-strong routing, it reduced total cost by 37.4%, with only a 0.2 percentage-point decrease in sufficiency. The framework was also compared with keyword-risk, token-threshold, TF-IDF centroid, logistic-regression, multiplicative-SAW, and TOPSIS baselines. The results indicate that an interpretable multicriteria router can achieve near-strong-model response sufficiency at substantially lower cost while preserving auditability and alignment with enterprise decision criteria. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
18 pages, 317 KB  
Article
Applying Integrated Delphi–AHP to Maintenance Competency Prioritization in Industry 4.0: A Formally Specified Group Decision Framework with Consistency and Sensitivity Diagnostics
by Chin-Wen Liao, Nguyen Van Thanh and Yi-Hsin Tai
Information 2026, 17(5), 500; https://doi.org/10.3390/info17050500 - 19 May 2026
Viewed by 699
Abstract
As Industry 4.0 transforms manufacturing operations, maintenance organizations face a group decision-making problem: how to consolidate diverse expert judgments into a defensible, transparent ranking of the competencies that maintenance personnel most need. This paper applies an integrated Delphi–AHP framework—with explicit notation, operators, and [...] Read more.
As Industry 4.0 transforms manufacturing operations, maintenance organizations face a group decision-making problem: how to consolidate diverse expert judgments into a defensible, transparent ranking of the competencies that maintenance personnel most need. This paper applies an integrated Delphi–AHP framework—with explicit notation, operators, and diagnostics—to prioritize maintenance competencies in advanced-manufacturing settings. The Delphi stage consolidates expert-generated items under median–interquartile-range consensus and round-to-round stability rules, while the Analytic Hierarchy Process (AHP) transforms validated pairwise comparisons into ratio-scale priority weights through geometric-mean Aggregation of Individual Judgments (AIJ) and eigenvector derivation. Consistency screening (CI/CR), inter-rater agreement (Kendall’s W), and perturbation-based sensitivity analysis accompany the resulting weight vector. A bounded AI-assisted consistency-check step supports terminology harmonization during Delphi statement consolidation, subject to explicit human-validation constraints. A panel of fifteen industry experts participated in the study; five competency dimensions and twenty-nine indicators were retained through three Delphi rounds. AHP weighting identified Basic Knowledge and Skills as the highest-priority dimension, followed by Safety and Regulation Awareness and Problem-Solving Ability. Aggregated pairwise comparison matrices, local and global weights, and sensitivity results are reported to support reproducibility. The study contributes a rigorously specified application of combined Delphi–AHP to a domain—Industry 4.0 maintenance asset management—where multi-criteria decision analysis has seen limited formal application, and closes common specification gaps in published Delphi–AHP implementations. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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31 pages, 1885 KB  
Article
Cost Risk Factors in Construction Projects: A Contractor’s Perspective
by Kaleab Tsegaye Belihu, Asregidew Kassa Woldesenbet, Asmamaw Tadege Shiferaw, Worku Asratie Wubet, Mitiku Damtie Yehualaw and Woubishet Zewdu Taffese
Information 2026, 17(3), 226; https://doi.org/10.3390/info17030226 - 27 Feb 2026
Viewed by 2069
Abstract
Cost overrun is a major challenge in the construction industry. However, there is a notable lack of data from empirical studies that exhaustively identify and analyze risk factors contributing to overruns. This study aims to address this gap by systematically identifying and analyzing [...] Read more.
Cost overrun is a major challenge in the construction industry. However, there is a notable lack of data from empirical studies that exhaustively identify and analyze risk factors contributing to overruns. This study aims to address this gap by systematically identifying and analyzing these risk factors. A hybrid methodology was employed. It combined a systematic literature review, a three-round Delphi process, and fuzzy set techniques. Insights from the literature review informed the first-round Delphi questionnaire. Subsequent rounds were refined based on earlier results. In the third round, experts’ opinions on the likelihood and impact of the cost risk factors were collected using a 5-point Likert scale. Finally, a fuzzy approach was employed to assess the severity of cost risk factors based on the combined effects of their likelihood and impact. The results revealed that the primary cost risk factors include escalation and fluctuation in material prices, inflation, material shortages, the country’s political instability, the country’s economic instability, delays in payment to the contractor, and delays in material procurement and delivery. Notably, the significant cost risk factors are largely beyond the contractor’s control and are closely tied to the broader political and economic conditions of the country. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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22 pages, 2315 KB  
Article
Fuzzy-Based MCDA Technique Applied in Multi-Risk Problems Involving Heatwave Risks in and Pandemic Scenarios
by Rosa Cafaro, Barbara Cardone, Ferdinando Di Martino, Cristiano Mauriello and Vittorio Miraglia
Information 2026, 17(1), 97; https://doi.org/10.3390/info17010097 - 18 Jan 2026
Cited by 1 | Viewed by 593
Abstract
Assessing the increased impacts/risks of urban heatwaves generated by stressors such as a pandemic period, such as the one experienced during the COVID-19 pandemic, is complicated by the lack of comprehensive information that allows for an analytical determination of the alteration produced on [...] Read more.
Assessing the increased impacts/risks of urban heatwaves generated by stressors such as a pandemic period, such as the one experienced during the COVID-19 pandemic, is complicated by the lack of comprehensive information that allows for an analytical determination of the alteration produced on climate risks/impacts. The assessment of the increased impacts/risks of urban heatwaves generated by stressors such as those due to the presence of a pandemic is complicated by the lack of comprehensive information that allows for the functional determination of the increased impacts/risks due to such stressors. On the other hand, it is essential for decision makers to understand the complex interactions between climate risks and the environmental and socioeconomic conditions generated by pandemics in an urban context, where specific restrictions on citizens’ livability are in place to protect their health. This study aims to address this need by proposing a fuzzy multi-criteria decision-making framework in a GIS environment that intuitively allows experts to assess the increase in heatwave risk factors for the population generated by pandemics. This assessment is accomplished by varying the values in the pairwise comparison matrices of the criteria that contribute to the construction of physical and socioeconomic vulnerability, exposure, and the hazard scenario. The framework was tested to assess heatwave impacts/risks on the population in the study area, which includes the municipalities of the metropolitan city of Naples, Italy, an urban area with high residential density where numerous summer heatwaves have been recorded over the last decade. The findings indicate a rise in impact/risks during pandemic times, particularly in municipalities with the greatest resident population density, situated close to Naples. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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24 pages, 1510 KB  
Article
An Integrated PLS-SEM-TOPSIS-Sort Approach for Assessing ERP Solutions Acceptance Across Various Industries
by Aleksandra Radić, Samo Bobek, Sanela Arsić, Đorđe Nikolić and Simona Sternad Zabukovšek
Information 2025, 16(11), 954; https://doi.org/10.3390/info16110954 - 3 Nov 2025
Cited by 3 | Viewed by 1756
Abstract
In the context of accelerated digitalization, enterprises are increasingly adopting information-driven solutions to support managerial decision-making, with Enterprise Resource Planning (ERP) systems playing a crucial role in organizational development. Despite its importance, ERP adoption varies significantly across industries, particularly between developed and developing [...] Read more.
In the context of accelerated digitalization, enterprises are increasingly adopting information-driven solutions to support managerial decision-making, with Enterprise Resource Planning (ERP) systems playing a crucial role in organizational development. Despite its importance, ERP adoption varies significantly across industries, particularly between developed and developing economies, where technological and structural differences persist. This paper proposes and validates a classification framework for assessing industry readiness for ERP adoption, based on an integrated PLS-SEM-MCDA methodological approach. PLS-SEM identified statistically significant factors and transformed them into weights to compare ERP user attitudes across eleven industries in Serbia and Slovenia. In addition, the TOPSIS-Sort method classified industries into high, moderate, and low readiness as predefined order classes. Finally, sensitivity analysis and comparative analysis are performed with AHP expert weights and the PROMETHEE-FlowSort method to determine the robustness of the PLS-SEM-TOPSIS-Sort results. The results show that the IT industry is the most consistent in adopting ERP systems. In contrast, other industries exhibit varying levels of readiness, depending on their degree of digital maturity and organizational preparedness. The proposed framework’s methodological flexibility allows it to be adapted to various contexts, making it suitable for future academic research and comparative studies. Additionally, the practical implications of the research are twofold. For ERP suppliers, the findings provide guidance on how to approach market segmentation and strategic positioning tailored to the specific needs of individual industries. For ERP users, their success in ERP adoption can be amplified by using the research insights as a benchmarking model. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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33 pages, 4858 KB  
Article
Multi-Criteria Assessment: A Case Study Integrating Eco-design Principles in Sustainable Manufacturing
by Khadija Sarquah, Caitlin Walls, Marta Revello, Maja Jelić and Gesa Beck
Information 2025, 16(11), 925; https://doi.org/10.3390/info16110925 - 22 Oct 2025
Cited by 1 | Viewed by 1613
Abstract
This study integrates Eco-design principles and the Life Cycle approach in an MCA to evaluate the sustainability performance of manufacturing routes. The assessment is applied to conventional production across five use cases involving complex geometry parts. The aim is to evaluate areas of [...] Read more.
This study integrates Eco-design principles and the Life Cycle approach in an MCA to evaluate the sustainability performance of manufacturing routes. The assessment is applied to conventional production across five use cases involving complex geometry parts. The aim is to evaluate areas of material criticality, environmental impacts, chemical risks, as well as social aspects, including gender dimensions (C-MET-ESG). Outcomes are synthesised into colour-coded hotspot tables and Eco-design recommendations. Key findings highlight opportunities such as substituting high-criticality alloys, increasing material efficiency, and promoting gender inclusive workplace practices. Technological transitions from CNC machining and hazardous post-processing to laser and additive manufacturing further enhance safety, resource efficiency, and resilience. The novelty of this study lies in the integration of LCA principles, the C-MET-ESG matrix, and CRA-SSbD guidelines within an MCA, establishing a hazard-aware, socially inclusive, and technically robust framework. This approach provides life cycle linked evidence that connects early design choices to sustainability outcomes. Furthermore, the study offers a transferable methodology for sustainable manufacturing in both established and emerging technologies. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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15 pages, 1022 KB  
Article
Making Informed Choices: AHP and SAW for Optimal Formwork System Selection
by Ivan Marović, Martina Šopić, Matija Jurčević and Rebeka Radojčić
Information 2025, 16(10), 873; https://doi.org/10.3390/info16100873 - 8 Oct 2025
Cited by 1 | Viewed by 1207
Abstract
The selection of an appropriate formwork system represents a critical decision in the planning of reinforced concrete multi-story buildings. While this decision has traditionally been deferred to the construction phase, increasing evidence of time and cost overruns in construction projects has highlighted the [...] Read more.
The selection of an appropriate formwork system represents a critical decision in the planning of reinforced concrete multi-story buildings. While this decision has traditionally been deferred to the construction phase, increasing evidence of time and cost overruns in construction projects has highlighted the necessity of addressing it during earlier stages, particularly in design and planning. Early identification and selection of the optimal formwork system enhances the likelihood of achieving significant improvements in both time efficiency and cost effectiveness. To facilitate this process, a decision-support framework based on the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods has been developed. This framework provides decision-makers with a structured and systematic approach for evaluating alternatives and selecting the most suitable formwork system for a given project. By offering an analytical foundation for the decision-making process, the framework assists designers and engineers in mitigating risks associated with delays and potential standstills during construction. The findings indicate that the proposed decision-support framework ensures both clarity and consistency in decision-making outcomes, irrespective of the analytical method employed. Consequently, it contributes to more robust planning and execution of construction projects. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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18 pages, 862 KB  
Article
Integration of Multi-Criteria Decision-Making and Dimensional Entropy Minimization in Furniture Design
by Anna Jasińska and Maciej Sydor
Information 2025, 16(8), 692; https://doi.org/10.3390/info16080692 - 14 Aug 2025
Cited by 3 | Viewed by 1984
Abstract
Multi-criteria decision analysis (MCDA) in furniture design is challenged by increasing product complexity and component proliferation. This study introduces a novel framework that integrates entropy reduction—achieved through dimensional standardization and modularity—as a core factor in the MCDA methodologies. The framework addresses both individual [...] Read more.
Multi-criteria decision analysis (MCDA) in furniture design is challenged by increasing product complexity and component proliferation. This study introduces a novel framework that integrates entropy reduction—achieved through dimensional standardization and modularity—as a core factor in the MCDA methodologies. The framework addresses both individual furniture evaluation and product family optimization through systematic complexity reduction. The research employed a two-phase methodology. First, a comparative analysis evaluated two furniture variants (laminated particleboard versus oak wood) using the Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The divergent rankings produced by these methods revealed inherent evaluation ambiguities stemming from their distinct mathematical foundations, highlighting the need for additional decision criteria. Building on these findings, the study further examined ten furniture variants, identifying the potential to transform their individual components into universal components, applicable across various furniture variants (or configurations) in a furniture line. The proposed dimensional modifications enhance modularity and interoperability within product lines, simplifying design processes, production, warehousing logistics, product servicing, and liquidation at end of lifetime. The integration of entropy reduction as a quantifiable criterion within MCDA represents a significant methodological advancement. By prioritizing dimensional standardization and modularity, the framework reduces component variety while maintaining design flexibility. This approach offers furniture manufacturers a systematic method for balancing product diversity with operational efficiency, addressing a critical gap in current design evaluation practices. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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21 pages, 5063 KB  
Article
Flood Susceptibility Assessment Based on the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS): A Case Study of the Broader Area of Megala Kalyvia, Thessaly, Greece
by Nikolaos Alafostergios, Niki Evelpidou and Evangelos Spyrou
Information 2025, 16(8), 671; https://doi.org/10.3390/info16080671 - 6 Aug 2025
Cited by 6 | Viewed by 2306
Abstract
Floods are considered one of the most devastating natural hazards, frequently resulting in substantial loss of lives and widespread damage to infrastructure. In the period of 4–7 September 2023, the region of Thessaly experienced unprecedented rainfall rates due to Storm Daniel, which caused [...] Read more.
Floods are considered one of the most devastating natural hazards, frequently resulting in substantial loss of lives and widespread damage to infrastructure. In the period of 4–7 September 2023, the region of Thessaly experienced unprecedented rainfall rates due to Storm Daniel, which caused significant flooding and many damages and fatalities. The southeastern areas of Trikala were among the many areas of Thessaly that suffered the effects of these rainfalls. In this research, a flood susceptibility assessment (FSA) of the broader area surrounding the settlement of Megala Kalyvia is carried out through the analytical hierarchy process (AHP) as a multicriteria analysis method, using Geographic Information Systems (GIS). The purpose of this study is to evaluate the prolonged flood susceptibility indicated within the area due to the past floods of 2018, 2020, and 2023. To determine the flood-prone areas, seven factors were used to determine the influence of flood susceptibility, namely distance from rivers and channels, drainage density, distance from confluences of rivers or channels, distance from intersections between channels and roads, land use–land cover, slope, and elevation. The flood susceptibility was classified as very high and high across most parts of the study area. Finally, a comparison was made between the modeled flood susceptibility and the maximum extent of past flood events, focusing on that of 2023. The results confirmed the effectiveness of the flood susceptibility assessment map and highlighted the need to adapt to the changing climate patterns observed in September 2023. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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27 pages, 1836 KB  
Article
Benchmarking Virtual Physics Labs: A Multi-Method MCDA Evaluation of Curriculum Compliance and Pedagogical Efficacy
by Rama M. Bazangika, Ruffin-Benoît M. Ngoie, Jean-Roger M. Bansimba, God’El K. Kinyoka and Billy Nzau Matondo
Information 2025, 16(7), 587; https://doi.org/10.3390/info16070587 - 8 Jul 2025
Cited by 3 | Viewed by 1998
Abstract
In this paper, we propose the use of virtual labs (VLs) as a solution to bridge the gap between theory and practice in physics education. Through an experiment conducted in two towns in the Democratic Republic of the Congo (DRC), we demonstrate that [...] Read more.
In this paper, we propose the use of virtual labs (VLs) as a solution to bridge the gap between theory and practice in physics education. Through an experiment conducted in two towns in the Democratic Republic of the Congo (DRC), we demonstrate that our proposed lab (BRVL) is more effective than global alternatives in correcting misconceptions and ensuring compliance with the current curriculum in the DRC. We combine Conjoint Analysis (from SPSS) to weigh selected criteria—curriculum compliance, knowledge construction, misconception correction, and usability—alongside eight MCDA methods: AHP, CAHP, TOPSIS, ELECTRE I, ELECTRE II, ELECTRE TRI, PROMETHEE I, and PROMETHEE II. Our findings show that, among six VLs, BRVL consistently outperforms global alternatives like Algodoo and Physion in terms of pedagogical alignment, curriculum compliance, and correction of misconceptions for Congolese schools. Methodologically, the respondents are consistent and in agreement, despite individual differences. The sensitivity analysis of the ELECTRE and PROMETHEE methods has shown that changes in parameter values do not alter the conclusion that BRVL is the best among the compared VLs. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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41 pages, 1353 KB  
Article
Improving Survey Data Interpretation: A Novel Approach to Analyze Single-Item Ordinal Responses with Non-Response Categories
by Ewa Roszkowska
Information 2025, 16(7), 546; https://doi.org/10.3390/info16070546 - 27 Jun 2025
Cited by 9 | Viewed by 3238
Abstract
Questionnaire data plays a key role in social research, especially when evaluating public attitudes using Likert-type scales. Yet, traditional analyses often merge some ordinal categories and exclude responses such as Don’t Know, No Answer, or Refused—risking the loss of valuable information. This study [...] Read more.
Questionnaire data plays a key role in social research, especially when evaluating public attitudes using Likert-type scales. Yet, traditional analyses often merge some ordinal categories and exclude responses such as Don’t Know, No Answer, or Refused—risking the loss of valuable information. This study introduces BS-TOSIE (Belief Structure-Based TOPSIS for Survey Item Evaluation), a novel method that preserves and integrates all response types, including ambiguous ones. By combining the Belief Structure framework with the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, BS-TOSIE offers a structured approach to ranking and evaluating individual survey items measured on an ordinal scale, even in the presence of missing or incomplete data. Response distributions are transformed into a belief structure vector, enabling comparison against ideal and anti-ideal benchmarks. We demonstrate this approach using data from the Quality of Life in European Cities survey to assess perceptions of local governance in European cities. This study analyzes changes in citizen satisfaction with local public administration across five key dimensions—timeliness, procedural clarity, fairness of fees, digital accessibility, and perceived corruption—in 83 European cities between 2019 and 2023. The findings reveal persistent regional disparities, with Northern and Western European cities consistently outperforming those in Southern and Eastern Europe, although some cities in Central Europe show signs of improvement. Zurich consistently received high satisfaction scores, while other cities, such as Rome and Palermo, showed lower scores. Unlike traditional methods, our approach preserves the full spectrum of responses, yielding more nuanced and interpretable insights. The results show that BS-TOSIE enhances both the clarity and depth of survey analysis, making a methodological contribution to the evaluation of ordinal data and offering empirical insights into public perceptions of local city administration. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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27 pages, 2692 KB  
Article
Developing an Expert System for Hardware Selection in Internet of Things-Based System Design: Grey ITARA-COBRA Approach (With an Example in the Agricultural Domain)
by Taha Ahmadi Pargo and Sarfaraz Hashemkhani Zolfani
Information 2025, 16(6), 425; https://doi.org/10.3390/info16060425 - 22 May 2025
Cited by 1 | Viewed by 1789
Abstract
Internet of Things (IoT) technology is rapidly transforming various industries. Advancements in production technologies have made it more affordable to produce suitable hardware to create IoT-based systems. This has resulted in a wide range of options available at reasonable prices. Having multiple options [...] Read more.
Internet of Things (IoT) technology is rapidly transforming various industries. Advancements in production technologies have made it more affordable to produce suitable hardware to create IoT-based systems. This has resulted in a wide range of options available at reasonable prices. Having multiple options available gives designers creative freedom. However, having more options may confuse designers and make it more difficult to choose hardware that meets design needs. This paper presents an expert system for IoT-based system hardware selection. In the proposed approach, the hardware information and expert knowledge are stored in a database and a knowledge base. Users input their required specifications using a user interface, and then the system’s decision-making module constructs the decision matrix and eventually ranks the alternatives utilizing a hybrid ITARA-COBRA method. Due to the ambiguity in the data, grey numbers are used for decision-making. In the next step, an example of an agricultural IoT-based system design is applied to test the system. The proposed Grey ITARA method is compared with the Grey MEREC and Grey CRITIC methods, and given the use of the indifference threshold concept, it performs well. Moreover, its ability to handle unstructured, vague data is useful for using technical specifications and expert opinions in decision-making. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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19 pages, 780 KB  
Article
Personalized Instructional Strategy Adaptation Using TOPSIS: A Multi-Criteria Decision-Making Approach for Adaptive Learning Systems
by Christos Troussas, Akrivi Krouska, Phivos Mylonas and Cleo Sgouropoulou
Information 2025, 16(5), 409; https://doi.org/10.3390/info16050409 - 15 May 2025
Cited by 14 | Viewed by 4225
Abstract
The growing number of educational technologies presents possibilities and challenges for personalized instruction. This paper presents a learner-centered decision support system for selecting adaptive instructional strategies, that embeds the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in a real-time learning [...] Read more.
The growing number of educational technologies presents possibilities and challenges for personalized instruction. This paper presents a learner-centered decision support system for selecting adaptive instructional strategies, that embeds the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in a real-time learning environment. The system uses multi-dimensional learner performance data, such as error rate, time-on-task, mastery level, and motivation, to dynamically analyze and recommend the best pedagogical intervention from a pool of strategies, which includes hints, code examples, reflection prompts, and targeted scaffolding. In developing the system, we chose to employ it in a one-off postgraduate Java programming course, as this represents a defined cognitive load structure and samples a spectrum of learners. A robust evaluation was conducted with 100 students and an adaptive system compared to a static/no adaptive control condition. The adaptive system with TOPSIS yielded statistically higher learning outcomes (normalized gain g = 0.49), behavioral engagement (28.3% increase in tasks attempted), and learner satisfaction. A total of 85.3% of the expert evaluators agreed with the system decisions compared to the lecturer’s preferred teaching response towards the prescribed problems and behaviors. In comparison to a rule-based approach, it was clear that the TOPSIS framework provided a more granular and effective adaptation. The findings validate the use of multi-criteria decision-making for real-time instructional support and underscore the transparency, flexibility, and educational potential of the proposed system across broader learning domains. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis, 3rd Edition)
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