Journal of Multi-Criteria Decision Analysis最新文献

{"title":"Structuring the Prison Life Index Through Value Focused Thinking Methodology","authors":"Lola Martin-Moro,&nbsp;Meltem Öztürk,&nbsp;Florence Laufer","doi":"10.1002/mcda.70003","DOIUrl":"https://doi.org/10.1002/mcda.70003","url":null,"abstract":"<p>Building a composite index (CI) is a task that requiring a series of decisions, the consequences of which will determine the scope of the tool. This is especially true for the very first steps of this construction: the definition of the theoretical framework and the selection of relevant indicators, usually referred to as the construction of the structure. However, the literature seems to focus more on the other aspects, quite often eluding those first steps or considering it a self-evident process. How to ensure the soundness of those tools when the values that they convey are not even clearly expressed? How to ensure the completeness of the structure according to the reality that it ought to synthesise when it is a highly complex or abstract one? Each of these steps involves hypotheses and presuppositions that must be explained and evaluated with care. In this article, we seek to identify a coherent method that will allow us to build the structure of CI answering those demands. The construction of a composite indicator can be conceptualised as a multi-criteria decision aiding problem (MCDA), given that it entails the aggregation of evaluations pertaining to distinct attributes. The MCDA is rich in structuring methodologies, such as Ralph Keeney's Value Focused Thinking (VFT) approach. Using a real-life application, the construction of the Prison Life Index (PLI), we try to show the relevance of those primary hypotheses by displaying the structure of the index and summarising the stage of its construction. This adapted methodology can guide index builders in the determination of a structure that comprehensively fits its intended purpose and that is not overly dependent on available data. Our article endeavours to underscore the importance of the structuring phase, arguing that it should take priority according to the ethical and moral values of the decision-maker. It should not be solely reliant on data availability, as it is the case with most composite indices. We demonstrate, through the implementation of the PLI structure developed using VFT, that it can achieve a high degree of conformity with internationally established standards pertaining to human rights. This approach not only facilitates a comprehensive understanding of the interconnections among various normative texts but also provides jurists with a visual representation of these relationships.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"32 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Barriers to Innovative Marketing in MSMEs: An Analysis Using a BWM-ISM Multi-Criteria Decision-Making Framework","authors":"Sourav Mondal,&nbsp;Saumya Singh,&nbsp;Himanshu Gupta","doi":"10.1002/mcda.70005","DOIUrl":"https://doi.org/10.1002/mcda.70005","url":null,"abstract":"<div>\u0000 \u0000 <p>In today's dynamic business landscape, organisations increasingly realise the pivotal role of innovative marketing approaches (IMA) in gaining a competitive edge and driving sustainable growth. However, many organisations encounter formidable barriers to adopting and developing IMA, despite the growing importance of innovative approaches in marketing. The purpose of this research is to identify, prioritise, establish the inter-relationships and propose a ‘level-wise structural model’ of the barriers that an organisation faces in adopting and developing IMA. The research employed a mix of quantitative and qualitative methods. An exhaustive review of related literature and theoretical frameworks (namely the ‘resource-based view’ (RBV) theory, the ‘social capital theory’ (SCT) theory, the ‘innovation resistance theory’ (IRT) theory, and the ‘institutional theory’ (IT) theory), along with expert feedback, are used to categorise and finalise the barriers. Further, a case study from ‘micro, small and medium enterprises’ (MSMEs) in a developing nation such as India along with hybrid ‘multi-criteria decision-making’ (MCDM), that is, best-worst method (BWM), was applied to prioritise the barriers. While ‘interpretive structural modelling’ (ISM) was used to establish contextual relationships, and ‘matrice d'impacts croisés multiplication appliquée á un classment’ (MICMAC) analysis was employed to cluster the barriers. The findings suggest that among the main category technology-related barriers and from subcategories, infrastructure supports the top barriers and works as a driving obstacle while building IMA for sustainable development. The findings from this study can help develop effective marketing strategies that align profitability with environmental and social responsibility.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"32 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency Criteria for Multicost Variational Models Driven by H-Type I Functionals","authors":"Savin Treanţă,&nbsp;Anca-Oana Bibic,&nbsp;Simona-Mihaela Bibic","doi":"10.1002/mcda.70004","DOIUrl":"https://doi.org/10.1002/mcda.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates a family of multicost variational models driven by <i>H</i>-type I functionals. Concretely, under <i>H</i>-type I assumptions of the involved functionals, we state and prove necessary and sufficient criteria of efficiency for a feasible point in the considered class of controlled variational models.</p>\u0000 <p><b>MSC 2020 Classification:</b> 49K20, 58E17, 58E25, 90C30</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Why We Need Desirable Properties in Pairwise Comparison Methods?","authors":"Radomír Perzina,&nbsp;Jaroslav Ramík","doi":"10.1002/mcda.70002","DOIUrl":"https://doi.org/10.1002/mcda.70002","url":null,"abstract":"<div>\u0000 \u0000 <p>Pairwise comparison matrices (PCMs) are inevitable tools in some important multiple-criteria decision-making methods, for example AHP/ANP, TOPSIS, PROMETHEE and others. In this paper, we investigate some important properties of PCMs which influence the generated priority vectors for the final ranking of the given alternatives. The main subproblem of the Analytic Hierarchy Process (AHP) is to calculate the priority vectors, that is, the weights assigned to the elements of the hierarchy (criteria, sub-criteria, and/or alternatives or variants), by using the information provided in the form of a pairwise comparison matrix. Given a set of elements, and a corresponding pairwise comparison matrix, whose entries evaluate the relative importance of the elements with respect to a given criterion, the final ranking of the given alternatives is evaluated. We investigate some important and natural properties of PCMs called the desirable properties, particularly, the non-dominance, consistency, intensity and coherence, which influence the generated priority vectors. Usually, the priority vector is calculated based on some well-known method, for example, the Eigenvector Method, the Arithmetic Mean Method, the Geometric Mean Method, the Least Square Method, and so forth. The novelty of our approach is that the priority vector is calculated as the solution of an optimization problem where an error objective function is minimised with respect to constraints given by the desirable properties. The properties of the optimal solution are discussed and some illustrating examples are presented. The corresponding software tool has been developed and demonstrated in some examples.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Analytical Framework for the Multiplicative Best-Worst Method","authors":"Harshit M. Ratandhara,&nbsp;Mohit Kumar","doi":"10.1002/mcda.1840","DOIUrl":"https://doi.org/10.1002/mcda.1840","url":null,"abstract":"<div>\u0000 \u0000 <p>The Best-Worst Method (BWM) is a well-known Multi-Criteria Decision-Making (MCDM) method. Numerous models of BWM have been developed by integrating various distance functions with the core principles of the method. This article addresses the multiplicative model of BWM. We first formulate an optimization model that is equivalent to the existing multiplicative model. This model provides a robust foundation for deriving analytical forms of optimal interval-weights, the Consistency Index (CI) and the Consistency Ratio (CR). The proposed approach eliminates the need for optimization software, enhancing its ease of implementation and time efficiency. Moreover, the derived analytical form of CR enables it to function as an input-based consistency measure. We then introduce a secondary objective function to select the best optimal weight set from the collection of all optimal weight sets. Finally, we present numerical examples to illustrate the proposed approach.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-Objective Optimization for Determination of Sustainable Crop Pattern Using Game Theory","authors":"Narges Ganjali,&nbsp;Caner Guney","doi":"10.1002/mcda.70000","DOIUrl":"https://doi.org/10.1002/mcda.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>Amid growing concerns about environmental sustainability in agriculture, this study explores the potential of a game-theoretic approach to identify and implement sustainable crop patterns in the Marvdasht–Kherameh sub-basin, Iran. Employing a cooperative game-theoretic framework, the study considers farmers, environmental advocates and policymakers as stakeholders with distinct objectives: maximising profit, minimising environmental pollution and optimising water consumption. This research aims to develop and apply a comprehensive model that effectively integrates these diverse objectives, proposing practical, sustainable agricultural strategies for the region. The game-theoretic model is integrated with data analysis and optimization techniques to identify Pareto-optimal solutions that balance the competing objectives of stakeholders with vested interest. The advantage of this approach is its ability to produce a robust, spatially visualised solution using GIS-based mapping, which improves communication and aids in implementing sustainable crop patterns. Using regression models, an equilibrium point, defined as the intersection of the three polynomial regression models representing profit, nitrate fertiliser amount and water consumption objectives is identified. The optimised crop pattern corresponding to this equilibrium point is determined using a single-objective optimization model. Key findings include a 40% reduction in wheat cultivation and significant increases in barley (143%) and paddy rice (113%), leading to enhanced resource efficiency and sustainability by optimising water and nitrate fertiliser use. The results offer significant benefits, including detailed spatial visualisation and stakeholder-specific optimization for sustainable crop patterns, which can be adapted to other agricultural regions facing similar challenges.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142714676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-Criteria Decision Support Tool for Shared Decision Making in Clinical Consultation","authors":"Ceren Tuncer Şakar,&nbsp;Chloe Keith-Jopp,&nbsp;Barbaros Yet,&nbsp;Christopher Joyner,&nbsp;Adele Hill,&nbsp;James Roberts,&nbsp;William Marsh,&nbsp;Dylan Morrissey","doi":"10.1002/mcda.70001","DOIUrl":"https://doi.org/10.1002/mcda.70001","url":null,"abstract":"<div>\u0000 \u0000 <p>In clinical consultation, Shared Decision Making (SDM) between the patient and clinician can inform the patient about available treatment options, likely harms and benefits in order to reach a joint decision that accommodates the patient's preferences. Multi-Criteria Decision Analysis (MCDA) can be beneficial for this complex problem by offering systematic approaches to elicit preferences for multiple conflicting criteria and evaluate alternatives accordingly. We propose an online SDM tool based on MCDA to guide decisions in clinical consultation where there are multiple treatment options whose outcomes in different factors vary according to the patient. The tool was designed with a panel of domain experts and it enables rapid elicitation of patient preferences and clinician judgements. It is based on Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) to produce a comprehensive evaluation of the options. The patient-specific outcomes used in the SDM tool are derived from predictive machine learning models or published evidence. The tool was firstly qualitatively evaluated using a fictitious shoulder pain scenario with three focus groups of consultant and specialist physiotherapists. It was evaluated further with patients via structured interview format. The general response was positive; stating that the tool was informative about options and their performance in multiple criteria, and also useful in making a joint decision. The tool is ready to be incorporated into clinical care and evaluated by clinicians and patients in parallel with existing processes.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bibliometric Exploration of Multiple Criteria Decision Aid and Clustering—A Conceptual Taxonomy","authors":"Pavlos Delias,&nbsp;Michalis Doumpos","doi":"10.1002/mcda.1839","DOIUrl":"https://doi.org/10.1002/mcda.1839","url":null,"abstract":"<p>This work explores the intersection of Multiple Criteria Decision Aid (MCDA) and clustering techniques, revealing unexploited potential and novel perspectives arising from their integration, challenging their conventional separation. It serves as a compass, guiding researchers through a bibliometric exploration and a conceptual taxonomy consolidating existing knowledge. Employing a two-fold methodology, we first sketch the field's contours through a bibliometric lens, uncovering its intellectual structure, thematic landscape, and social dynamics. Then, using science mapping techniques like co-word analysis, historiography, and collaboration network analysis, we examine patterns, revealing an interconnected mosaic of concepts. Our findings unveil a natural grouping into three categories: (1) Mixed-yet-not-integrated approaches, explores sequential applications—clustering followed by MCDA or vice versa—where one method precedes and informs the other. (2) ‘Relational/ordered clustering’ leveraging criteria dependency to refine structures. (3) Using MCDA to improve clustering mechanics through similarity metrics, domain knowledge incorporation, and robustness. We conclusively propose a taxonomy along three axes: Units of Analysis, Instrumentalisation, and Objective. The key takeaway emphasises the collaborative potential of MCDA, envisioning a landscape where the integration of MCDA and clustering not only enhances existing methodologies but also spawns innovative paradigms, fostering a symbiotic relationship that transcends conventional boundaries.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 5-6","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.1839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Charting the evolutionary conceptual pathway of analytic network process research: A main path analysis","authors":"Carlos Vílchez-Román,&nbsp;Anna Florek-Paszkowska,&nbsp;Enrique Mu","doi":"10.1002/mcda.1837","DOIUrl":"https://doi.org/10.1002/mcda.1837","url":null,"abstract":"<p>This study delves into the flow and structure of knowledge prevalent in Analytic Network Process (ANP) literature. It traces the evolutionary pathway of ANP research, spotlighting seminal works and unfolding the development of topics over time. Analysing 4583 ANP literature records from 1986 to 2022, this research utilizes two pivotal data sources: Web of Science (WoS) and Dimensions. This main path analysis (MPA) approach is coupled with techniques such as citation analysis, social network analysis, and centrality measures to identify most influential papers, as well as using a search path algorithm (SPC) to provide higher weights to papers that serve as bridges connecting different research paths rather than simply counting all citations equally. Key works emerged as focal points in both datasets, including notable contributions from Lee, Kheybari and Büyüközkan, with the Dimensions dataset uniquely highlighting Saaty as the initial conceptual knowledge source of the ANP. The centrality measures unearthed persistent bridge roles undertaken by key contributors such as Saaty and Sarkis over different time periods. Furthermore, a detailed topic analysis discerned eight distinctive thematic clusters among the two data sources: analytical network process, network process, fuzzy analytic, evaluation laboratory, supply chain, quality function, hierarchy process, and information systems. These clusters emerged, providing a comprehensive map of ANP topics and their evolution. The study offers a comprehensive framework for scholars to navigate the expansive domain of ANP research. Identifying pivotal works and emergent themes provides direction for future research endeavours. It allows practitioners to gain invaluable insights into the foundational and transformative works in the ANP realm, enhancing their understanding and application of the methodology. This paper proposes of a dual methodological strategy: First, by using traditional academic data sources (WoS) along with a more encompassing Dimensions database; and second, by using a SPC algorithm to weight MPA papers based on their connecting role among different research paths. At the discipline level, this study carves out a novel vantage point in understanding the ANP research landscape. It offers an integrated portrayal of the field's conceptual evolution, identifying specific cluster topics as an indispensable resource for scholars, practitioners, and students.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 3-4","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring Sustainable Development Goals: Stepwise Benchmarking Approach","authors":"Ana Krstić Srejović,&nbsp;Mladen Stamenković,&nbsp;Nemanja Vuksanović","doi":"10.1002/mcda.1838","DOIUrl":"https://doi.org/10.1002/mcda.1838","url":null,"abstract":"<div>\u0000 \u0000 <p>We present a multiple criteria decision aiding approach to monitor countries' progress on Sustainable Development Goals indicators and obtain policy measures for improvement. We do it using stepwise benchmarking, a method that provides recommendations on a country level and potential direction for improvement by providing direct and ideal benchmarks, pointing out areas where improvements can be achieved. The results from stepwise benchmarking are based on the underlying outranking procedure. To show the effectiveness of the approach, we used ELECTRE III as the method to rank European countries on the progress on equality of educational opportunities and then applied stepwise benchmarking to provide policy recommendations. This approach has the potential to evaluate progress and propose improvements to all aspects of the Sustainable Development Agenda.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"31 3-4","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}