Journal of Multi-Criteria Decision Analysis最新文献

{"title":"Laplacian Ranking (LaRa): A Convex Graph-Regularized Model for Multi-Criteria Ranking","authors":"Valdecy Pereira,&nbsp;Marcio Pereira Basilio,&nbsp;Fatih Yigit","doi":"10.1002/mcda.70042","DOIUrl":"https://doi.org/10.1002/mcda.70042","url":null,"abstract":"<div>\u0000 \u0000 <p>Laplacian Ranking (LaRa) is a graph-regularized multi-criteria decision analysis method that incorporates relational geometry among alternatives into ranking while preserving convexity, interpretability and deterministic reproducibility. LaRa combines quantile normalization, metric-weighted distances, a sparse similarity graph, a reference-oriented prior and an optional quadratic pairwise target-gap term. Its base score is the unique minimizer of a strictly convex quadratic objective, obtained by solving a symmetric positive definite linear system, with an optional deterministic dominance-repair step. We evaluate LaRa on seven literature-grounded real-data problems spanning materials, manufacturing equipment, industrial robotics, renewable-energy siting, and energy-technology selection, together with a controlled synthetic pharmaceutical-style benchmark. Five cross-domain cases use one common fixed configuration and sensitivity grid rather than dataset-specific tuning. Results show that the graph contribution is regime-dependent. It is ordinally inert for cryogenic materials and clean-energy technologies, measurable but non-disruptive for flywheel selection, improves concordance with published rankings for CNC machine tools, arc-welding robots and Colombian solar-PV siting, and reduces concordance for gear-material selection, which is retained as an explicit failure boundary. On the fixed synthetic benchmark, the high-smoothing configuration attains Kendall's <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>τ</mi>\u0000 <mi>b</mi>\u0000 </msub>\u0000 <mo>=</mo>\u0000 <mn>0.987</mn>\u0000 </mrow>\u0000 <annotation>$$ {tau}_b=0.987 $$</annotation>\u0000 </semantics></math> and Spearman's <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>ρ</mi>\u0000 <mo>=</mo>\u0000 <mn>0.998</mn>\u0000 </mrow>\u0000 <annotation>$$ rho =0.998 $$</annotation>\u0000 </semantics></math>, reduces mean absolute rank error from 0.556 for TOPSIS to 0.111, and exactly recovers the Top-3 set. These findings position LaRa as a relational refinement of pointwise MCDA whose usefulness depends on whether neighbourhood geometry is substantively meaningful and empirically supported. Accordingly, graph smoothing should be activated as a conditional modelling component and accompanied by sensitivity analysis rather than assumed beneficial in practical MCDA applications.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205698","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":"Integrating Multi-Criteria Decision Analysis and Game Theory: A Systematic Review and Structural Perspective","authors":"Yiqi Zhao,&nbsp;Jun Zhuang","doi":"10.1002/mcda.70041","DOIUrl":"https://doi.org/10.1002/mcda.70041","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we present a systematic review of 103 peer-reviewed studies published between 1991 and 2025 on the integration of multi-criteria decision analysis (MCDA) and game theory (GT). Beyond synthesizing the literature, we introduce a structural criterion for evaluating the depth of MCDA–GT integration, focusing on whether multi-criteria preferences remain active within the equilibrium formulation rather than being aggregated ex ante and introduced as fixed inputs. Applying this criterion, we find that most reviewed studies rely on relatively weak forms of integration: MCDA outputs typically enter game-theoretic models as fixed payoff parameters while the strategic solution process remains largely unaffected by the multi-criteria structure, and the literature is further dominated by static, perfect-information game models combined with aggregated utility representations. By contrast, a smaller group of studies achieves deeper integration by preserving multi-criteria preferences within the strategic solution process. Across these studies, two broad approaches emerge—some retain preference incomparability through order-based representations and dominance relations on vector payoffs, while others embed trade-offs directly within optimization and equilibrium structures—yet both allow multi-criteria preferences to influence strategic outcomes throughout the solution process. Based on this assessment, we identify four recurring limitations: limited structural embedding of multi-criteria preferences, underuse of imperfect-information and adaptive game models, inadequate representation of stakeholder heterogeneity and limited attention to policy and governance settings. For each area we outline representative research directions that may support closer integration of multi-criteria evaluation and strategic reasoning. Overall, the review suggests that the field has progressed beyond simple method combination but remains uneven in the depth of integration achieved, and this paper clarifies the modelling choices associated with deeper integration and highlights opportunities for future methodological development.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146357","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":"When Compensatory Indices Mislead: Non-Compensatory Two-Stage Sorting of Financial Inclusion in Lower-Middle-Income Countries","authors":"Sevgi Eda Tuzcu","doi":"10.1002/mcda.70039","DOIUrl":"https://doi.org/10.1002/mcda.70039","url":null,"abstract":"<div>\u0000 \u0000 <p>We extend the non-compensatory ELECTRE TRI-B inspired sorting model with multiple evaluators with a two-stage membership procedure to categorise 27 lower-middle-income countries (LMICs) based on their financial inclusion (FI) levels. By employing four access and four usage FI dimensions, we impose an ‘access-first’ constraint and require the joint satisfaction of access and usage constraints for high, mid, and low FI classification. Unlike commonly used multivariate techniques and compensatory methods, this access-first approach prevents an advantage in FI usage from offsetting a weakness in FI access, therefore providing a clearer picture for LMICs' FI levels. The results indicate that once the access condition is met, the usage FI dimensions decide whether to confirm or upgrade the category of a given country. Countries such as Nepal, Mauritania, and Nigeria show relatively better performance on some usage dimensions, but not in the access block; hence, they are sorted in mid or low FI categories.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994276","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":"On the Diverse Uses of Multiple Criteria Decision Aiding Tools in Complex Decision Problems","authors":"Maria Franca Norese","doi":"10.1002/mcda.70038","DOIUrl":"https://doi.org/10.1002/mcda.70038","url":null,"abstract":"<p>Several multicriteria methods have been created for use in problem situations that are considered complex because multiple actors and/or organisations are involved. Such methods are easily combined with problem shaping and structuring methods to reduce complexity when a situation is new, ill- or not well-structured. These situations can also be dealt with by resorting to multiple criteria decision aiding MCDA approaches that use certain tools. Such tools are not only multicriteria methods but also logical and analytical models, interactive procedures and critical analyses of method results, which can be directly oriented towards activating mutual learning processes. Indeed, combining multicriteria methods with other tools, which are oriented more towards posing a decision problem than to solving it, can aid the perception and description of the nature and complexity of the situation in the initial phase of a decision aid process, orient a decision aid intervention and improve its effectiveness. An easy visualisation and understandability of the model components, of the used data and of the method application results facilitate a critical revision of the original problem formulation and modelling, and they can activate steps of mutual learning, improvements of the model and results, and of the generation of robustness, not only of the results but also of the model, and the decision and decision aid processes. This interpretation of how an integration of MCDA models, methods and other tools can be used to deal with complex decision problems is not new. Bernard Roy called this approach MCDA ‘description problematic’, but this methodological approach is rarely put into practice and still needs conceptual definition and structural clarity. An analysis framework is here presented to distinguish between some different MCDA situations where the outranking methods are oriented towards a description problem statement. Two complex cases are proposed to describe the main characteristics of four situations, which influence an analyst's behaviour and decision aid results, and suggest that some multicriteria models and methods should be used in complex situations first and foremost to facilitate understanding and communication.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943067","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":"Balance and Baselines: An Impossibility Theorem and an Axiomatisation of Additive Aggregation","authors":"Alec Morton,&nbsp;Lars Peter Østerdal","doi":"10.1002/mcda.70037","DOIUrl":"https://doi.org/10.1002/mcda.70037","url":null,"abstract":"<p>A feature in many multicriteria problems is a preference for ‘balance’, understood as achieving a desired distribution (e.g., equality or target proportions) of resources across stakeholders or conceptual categories. This paper presents a normative exploration of the implications of balance preferences when baselines are uncertain or contested. We prove an impossibility theorem showing that if a decision maker is strictly outcome-based yet expresses a strict preference for balance over gains whatever the baseline, then an inconsistency arises. We then show that if the balance preference is weakened and combined with standard conditions (such as monotonicity and continuity), the only consistent aggregation rule is a simple additive one. Our results highlight that deliberative decision making necessarily involves reconciling preference intuitions ‘in the small’ (over a fragment of the decision space) and ‘in the large’ (over the whole of that space).</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 2","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148462921","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":"Structuring and Modelling Stakeholders' Preferences for Transportation Infrastructure Development in Post-Conflict Zones","authors":"Richard S. John,&nbsp;Adam Rose,&nbsp;Denton Cohen,&nbsp;Terry Clower,&nbsp;Camilla Bosanquet,&nbsp;Frank Gunter,&nbsp;Peter Nijkamp,&nbsp;Karima Kourtit,&nbsp;Eli Berman,&nbsp;Laurie Schintler,&nbsp;Genevieve Giuliano,&nbsp;Luis Visot,&nbsp;Kieran Donaghy,&nbsp;Kingsley Haynes,&nbsp;Anas Morshed,&nbsp;Mariam Ihsan,&nbsp;Sue Dexter,&nbsp;Sirarpi Muradian","doi":"10.1002/mcda.70034","DOIUrl":"https://doi.org/10.1002/mcda.70034","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper develops an expert elicitation (EE) process to identify, structure and quantify stakeholder values and concerns related to infrastructure development, and applies it to post-conflict Iraq. Transportation improvements are key to stabilising Iraq economically and politically and helping prevent it from becoming a failed state that could lead to a major breeding ground for terrorism. The EE process includes: (1) identification of relevant stakeholders connected to transportation infrastructure development, (2) application of Value Focused Thinking (VFT) to develop an objectives hierarchy for each stakeholder, (3) development of possible future uncertain scenarios and policy alternatives relevant to transportation infrastructure, (4) construction of a multi-attribute utility (MAU) model for each stakeholder, (5) comparison of MAU scores across stakeholders and future scenarios and policy alternatives and (6) construction of a weighted stakeholder model that aggregates scores across stakeholders for different future scenarios and policy alternatives. This case-study presents a novel application of three different decision analysis methodologies: (1) VFT to identify stakeholder objectives; (2) MAU to quantify stakeholder trade-offs among conflicting objectives and quantify performance of scenario alternatives on constructed metrics and (3) prescriptive weighted stakeholder aggregation to indicate a ranking of scenario options. The EE process is applied to analysing the goals of 16 stakeholder groups, representing a broad cross-section of parties of interest in a hypothetical investment allocation decision regarding the development of viable, resilient and sustainable transportation infrastructure systems in Iraq. Each stakeholder considers investment allocations among alternatives that emphasise seaport development, land-based transportation development, accessibility and safety under various conditions. Two alternative approaches to aggregating stakeholder preferences to form a group ranking are examined, including a prescriptive model for group decision analysis. The results indicate that investments focusing on land transportation and accessibility were ranked highest across stakeholder groups. All four alternative investment allocations were preferred to the default investment option. The analysis allows us to identify conflicts among stakeholders related to trade-offs among competing objectives, disagreements about the projected outcomes of various investment alternatives on stakeholder-defined attributes. It also identifies win-win investment allocations.</p>\u0000 </div>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 2","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281898","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":"Multiobjective Optimisation for Others: How Anchoring Effects Change Based on Who Guides the Interaction","authors":"Maura E. Halstead,&nbsp;Manuel López-Ibáñez,&nbsp;George Farmer,&nbsp;Paul A. Warren","doi":"10.1002/mcda.70036","DOIUrl":"https://doi.org/10.1002/mcda.70036","url":null,"abstract":"<p>It is common in many real-world scenarios for decisions to be made on behalf of others. However, Multicriteria Decision Aiding methods often implicitly assume that the person whose preferences operate the methods, known as the decision-maker, is the source of those preferences. This assumption could influence interactive Multiobjective Optimisation, where the Pareto-optimal solutions are not known in advance and their discovery depends on continual feedback from the decision-maker. Due to this iterative nature, anchoring—defined as initial information influencing subsequent choices—could cause the decision-maker to stop interacting before they find the best solution according to the preference information, the Most Preferred Solution. Surprisingly, there are very few behavioural studies of anchoring and Decision-Making-for-Others in Multicriteria Decision Aiding and even fewer that have considered interactive Multiobjective Optimisation. We address this gap by studying whether anchoring in interactive Multiobjective Optimisation differs when the decision-maker uses their own or someone else's preferences. We conducted a behavioural experiment with 128 participants that acted as decision-makers using an interactive goal programming task that does not restrict the participant's choices to solve a two-objective problem. We found that anchoring arises in interactive Multiobjective Optimisation; it causes decision-makers to miss the Most Preferred Solution, and that it is stronger when the decision-maker uses someone else's preferences. These findings indicate that interactive methods should account for preference source and initialisation when designing elicitation and search methods.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 2","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281891","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":"Intertemporal Judgements in Multi-Attribute Decision-Making: Biases and Mitigation Ideas","authors":"Pelin Gülüm,&nbsp;Yousef Maknoon,&nbsp;Jafar Rezaei","doi":"10.1002/mcda.70035","DOIUrl":"https://doi.org/10.1002/mcda.70035","url":null,"abstract":"<p>Intertemporal judgements are susceptible to biases that can distort evaluations and lead to inconsistent choices. While time-related biases have been studied extensively from a descriptive perspective, little attention has been given to prescriptive approaches and the complex trade-offs involved in multi-attribute decision-making (MADM). This study provides a comprehensive review of the effects of such biases on the MADM process. Drawing on evidence from behavioural economics, psychology, and decision analysis, we identify six time-related biases and analyse the vulnerabilities they can introduce at each step of the MADM procedure. We also outline preliminary ideas that may help analysts and decision-makers reduce these biases in the unique context of intertemporal multi-attribute problems. Our findings highlight the importance of addressing biases from the earliest stages, such as problem structuring, and underscore the need for further empirical research to test and refine these proposed strategies.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174436","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":"SMAA-Based FITradeoff: An Efficient Framework for Pairwise Elicitation in Multicriteria Decision Analysis","authors":"Qian Zhao,&nbsp;Elia Balugani,&nbsp;Rita Gamberini,&nbsp;Francesco Lolli","doi":"10.1002/mcda.70031","DOIUrl":"https://doi.org/10.1002/mcda.70031","url":null,"abstract":"<p>The Flexible and Interactive Tradeoff Elicitation (FITradeoff) method is a Multi-Attribute Decision-Making (MADM) approach designed to capture the preferences of a Decision Maker (DM) while minimising cognitive effort. To reduce the frequency of interactions and optimise the preference elicitation process, this paper introduces an innovative FITradeoff method integrated with Stochastic Multi-Attribute Acceptability Analysis-2 (SMAA-2). The proposed method follows six steps: (1) It identifies the central weight vectors of each potentially optimal alternative obtained through SMAA-2. (2) It formulates pairwise tradeoffs based on their ratios and selects the most informative ones based on their probability of identifying potentially optimal alternatives. (3) It selects the most informative pairwise tradeoff and its ratio based on the minimum number of potentially optimal alternatives. (4) It engages the DM to express a preference relation. (5) It constructs an updated weight space with the identified pairwise tradeoff constraint and iterates the previous steps until an optimal alternative is identified. (6) A Genetic Algorithm-based Linear Programming (GA-based LP) model is developed to evaluate the robustness and efficiency of our approach. To prove the feasibility and validate the effectiveness of the proposed approach, a case study on the selection of Battery Energy Storage Systems (BESS) is conducted. Additionally, a comparative analysis with the traditional FITradeoff method is included; the results demonstrate that the proposed method identifies the optimal solution while reducing the DM's cognitive burden, highlighting its potential to improve decision-making processes.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148066078","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":"Anytime Lexicographic Enumeration of the Pareto Front in Multi-Objective Combinatorial Optimisation","authors":"Marco Foschini,&nbsp;Dimos Tsouros,&nbsp;Bistra Dilkina,&nbsp;Tias Guns","doi":"10.1002/mcda.70029","DOIUrl":"https://doi.org/10.1002/mcda.70029","url":null,"abstract":"<p>Multi-objective combinatorial optimisation problems are widespread in real-world scenarios, including resource allocation, scheduling and logistics, where multiple competing objectives need to be optimised simultaneously. In industrial contexts, lexicographic optimisation is often used to solve these problems, requiring the decision-maker (DM) to only rank the objectives according to their importance. However, a major limitation of this approach is that the resulting solution may not completely align with the DM's preferences. Alternatively, other approaches enumerate the entire Pareto front, allowing the DM to select their preferred solution. However, computing the full Pareto front can be time-consuming and may overwhelm the DM. Moreover, these methods are unable to account for preference information such as lexicographic order, which would enable the specification of a ranking of the objectives. In this paper, we investigate how to lexicographically enumerate the Pareto front in an anytime fashion; with the goal of quickly providing a limited set of the lexicographically best non-dominated solutions. As such, we propose two new exact anytime algorithms designed for this task: Fix-Improve (FI) and Fix-Worsen-Improve (FWI). As our experimental evaluation shows, our proposed methods are able to enumerate these solutions more efficiently than existing methods.</p>","PeriodicalId":45876,"journal":{"name":"Journal of Multi-Criteria Decision Analysis","volume":"33 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcda.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147567923","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}