EURO Journal on Decision Processes

Ali Jamal Mahdi

Domokos Esztergár-Kiss

Understanding Tourists’ Behavior Toward Transport Mode Choice by Using Machine Learning Methods

理解游客交通方式选择行为的机器学习方法研究

Erik Pohl

Jutta Geldermann

PROMETHEE-Cloud: A web app to support multi-criteria decisions

PROMETHEE-Cloud：支持多准则决策的网络应用

Experts and laypeople often have to make judgements based on a large body of evidence that is uncertain and inconclusive. Theory suggests people are likely to modify their decisions according to how information is framed and structured. This study assesses the effect of information form (text versus numerical) and sequence (bundled versus non-bundled) on decision outcomes regarding the regulation of plants with novel traits. Both experts and laypersons were surveyed and offered one of eight different treatments that tested for the effect of information presentation, the effect of the assigned decision role (as an individual or a member of a decision committee), and the structure of the decision itself. Results show that non-experts are more prone than experts to change their decisions when faced with different structures or decision architectures, especially when the form of information changes.

Rim Lassoued

Hayley Hesseln

Peter W.B. Phillips

Stuart J. Smyth

Effects of information presentation on regulatory decisions for products of biotechnology

信息呈现对生物技术产品监管决策的影响

Toly Chen

Enhancing the efficiency and accuracy of existing FAHP decision-making methods

提高现有模糊层次分析法决策方法的效率和准确性

Decision support consists in helping a decision-maker to improve his/her decisions. However, clients requesting decision support are often themselves experts and are often taken by third parties and/or the general public to be responsible for the decisions they make. This predicament raises complex challenges for decision analysts, who have to avoid infringing upon the expertise and responsibility of the decision-maker. The case of diagnosis decision support in healthcare contexts is particularly illustrative. To support clinicians in their work and minimize the risk of medical error, various decision support systems have been developed, as part of information systems that are now ubiquitous in healthcare contexts. To develop, in collaboration with the hospitals of Lyon, a diagnostic decision support system for day-to-day customary consultations, we propose in this paper a critical analysis of current approaches to diagnostic decision support, which mainly consist in providing them with guidelines or even full-fledged diagnosis recommendations. We highlight that the use of such decision support systems by physicians raises responsibility issues, but also that it is at odds with the needs and constraints of customary consultations. We argue that the historical choice to favor guidelines or recommendations to physicians implies a very specific vision of what it means to support physicians, and we argue that the flaws of this vision partially explain why current diagnostic decision support systems are not accepted by physicians in their application to customary situations. Based on this analysis, we propose that decision support to physicians for customary cases should be deployed in an "adjustive" approach, which consists in providing physicians with the data on patients they need, when they need them, during consultations. The rationale articulated in this article has a more general bearing than clinical decision support and bears lessons for decision support activities in other contexts where decision-makers are competent and responsible experts.

Antoine Richard

Brice Mayag

François Talbot

Alexis Tsoukias

Yves Meinard

What does it mean to provide decision support to a responsible and competent expert?

向负责任且称职的专家提供决策支持意味着什么？

We consider multiobjective combinatorial optimization problems handled by preference-driven efficient heuristics. They look for the most preferred part of the Pareto front based on some preferences expressed by the user during the process. In general, the Pareto set of efficient solutions is searched for in this case. However, obtaining the Pareto set does not solve the decision problem since one or more solutions, being the most preferred for the user, have to be selected. Therefore, it is necessary to elicit their preferences. What we are proposing can be seen as one of the first structured methodologies in facility location problems to search for optimal solutions taking into account the preferences of the user. To this aim, we use an interactive evolutionary multiobjective optimization procedure called NEMO-II-Ch. It is applied to a real-world multiobjective location problem with many users and many facilities to be located. Several simulations have been performed. The results obtained by NEMO-II-Ch are compared with those obtained by three algorithms knowing the user’s “true” value function that is, instead, unknown to NEMO-II-Ch. They show that in many cases, NEMO-II-Ch finds the best subset of locations more quickly than the methods knowing the whole user’s true preferences.

Maria Barbati

Salvatore Corrente

Salvatore Greco

Multiobjective Combinatorial Optimization with Interactive Evolutionary Algorithms: the case of facility location problems

多目标组合优化与交互式进化算法：设施选址问题案例

E-banking offers clients unparalleled convenience but also exposes them to potential fraud from cyber criminals. Traditionally, banks use technical security measures to ameliorate these kinds of threats. These measures, while essential, are not universally efficacious in preventing fraud. It would be wise to augment technical measures with softer measures such as behavioural interventions (i.e., nudges). In this paper, we report on the effectiveness of behavioural nudges designed to dissuade opportunistic "others" from committing e-banking fraud. Here, we report on an investigation into the impact of the deployment of a number of behavioural nudges in an e-banking customer interface. We evaluated their impact through semi-structured interviews with e-banking customers in the United States of America. We found that nudges which emphasise empathy and heightened awareness of traditional security measures were remarkably effective in dissuading dishonesty. Notably, deployment immediately after login yielded optimal results. Our findings highlight the potential of behavioural nudges to reduce e-banking fraud, thereby augmenting traditional technical countermeasures. We conclude with recommendations for future research.

Takudzwa Mutyavaviri

Karl van der Schyff

Karen Renaud

Dishonesty, neutralisation and nudging

不诚实、中性化与助推

This study introduces a novel approach to effectively and efficiently solve Multi-Attribute Decision Making (MADM) problems with a considerable number of attributes. We demonstrate the need to categorize the attributes and facilitate a more systematic expert comparison. Our proposed method utilizes pairwise comparisons to assess attributes without requiring additional computations to evaluate the level of consistency. The proposed method offers greater flexibility and precision with reduced computational complexity. We present a comparative analysis with a widely used numerical example in the MADM literature to demonstrate the effectiveness and efficacy of the method proposed in this study.

Mehdi Soltanifar

Madjid Tavana

A Novel Pairwise Comparison Method with Linear Programming for Multi-Attribute Decision-Making

一种基于线性规划的多属性决策新型配对比较方法

Abbreviation	EURO J. Decis. Process.
Journal Impact	2.32
Quartiles(Global)	MANAGEMENT(Q3)

ISSN	2193-9438, 2193-9446
h-index	19

Publication Information	Publisher: Elsevier B.V.，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2013，Proportion of original research papers: 100.00%，Self Citation Rate:13.00%， Gold OA Rate: 100.00%

EURO Journal on Decision Processes

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Understanding Tourists’ Behavior Toward Transport Mode Choice by Using Machine Learning Methods

PROMETHEE-Cloud: A web app to support multi-criteria decisions

Effects of information presentation on regulatory decisions for products of biotechnology

Enhancing the efficiency and accuracy of existing FAHP decision-making methods

What does it mean to provide decision support to a responsible and competent expert?

Understanding Tourists’ Behavior Toward Transport Mode Choice by Using Machine Learning Methods

PROMETHEE-Cloud: A web app to support multi-criteria decisions

Multiobjective Combinatorial Optimization with Interactive Evolutionary Algorithms: the case of facility location problems

Dishonesty, neutralisation and nudging

A Novel Pairwise Comparison Method with Linear Programming for Multi-Attribute Decision-Making