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Throughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes.

Interest in citizen participation is increasing generally. Almost all operational research (OR) is engaged with clients, but it is mainly in the areas of Soft and Community OR that wider stakeholder and citizen participation has been a significant focus. It is the involvement of citizens that is the subject of this paper. We surveyed OR literature and compiled a corpus of 62 studies, the earliest from 1970, to systematically characterize the involvement of citizens in OR processes. Our review produced three findings: First, some fields of OR have embraced citizen participation, but this is not yet a major concern outside the field of Community OR. Second, citizen participation in OR processes is often driven by a moral rationale. Third, progress in information and communication technology (ICT) enables broad participation, but traditional processes requiring physical presence can also be participatory. From these insights, we formulate research opportunities for OR. (1) OR may join Community OR's endeavor to engage with and empower citizens who have so far rarely been involved in OR processes. (2) OR may identify benefits and drawbacks of digital OR processes in empirical studies. (3) OR may determine whether involving large numbers of citizens is suitable for the societal scale. (4) OR may research building and maintaining trust. (5) OR may join efforts for data protection of participants. (6) OR may systematically report and reflect on participatory OR processes. (7) OR should continue researching the fair aggregation of individual inputs. Citizen participation in OR is topical and challenging. Pursuing these research opportunities will contribute to OR fulfilling its mandate of better decision-making in close cooperation with all affected stakeholders.

Innovative online interfaces informing and consulting citizens about their preferences for multicriteria decision analysis (MCDA) could make public decision-making more participatory. We propose a three-faceted learning for decision-making framework and used it to test newly-designed online weight elicitation interfaces. We investigated two features meant to enhance learning: fully-fledged gamification with a narrative, interaction with nonplayer characters, and ambient music, and learning loops (LL) using consistency checks of elicited weights and the challenge to resolve inconsistencies. We operationalized our framework with a novel systematic set of measure instruments providing complementary data types. We designed a 2 × 2 between-subject experiment with pre- and postquestionnaires. Answers from 769 respondents, representative of the Swiss population in age and gender, indicated that the interfaces successfully raised awareness about wastewater management. Gamification was helpful: respondents performed better in the factual learning test, and unexpected social learning occurred. However, gamification lowered the perception of process understanding. The LL were beneficial: objectively, respondents performed better in the factual learning test. However, respondents perceived the LL as cognitively demanding and their factual learning as lower. Our structured assessment highlighted the need for further research to investigate, for instance, high interpersonal variability and the disparities between tested and perceived learning. Measuring preference construction remains challenging; and social learning should be added to the assessment framework. Applying such structured assessment of learning outcomes to more traditional operational research interventions would provide a baseline for future comparison.