https://doi.org/10.25678/000713

Data for: Gamified environmental multi‐criteria decision analysis: information on objectives and range insensitivity bias

Multi-criteria decision analysis (MCDA) is well suited to address complex public policy problems but could benefit from new tools to involve many laypeople. Online information on specialized topics could be more engaging by including game elements. This paper reports an experiment that assessed a gamified interface to (1) inform laypeople about the objectives to consider in wastewater management decisions, (2) assist them in constructing range-based preferences, and (3) provide a positive experience. We measured the effects with (1) a knowledge pre- and posttest, (2) the elicited weights and a range sensitivity index, and (3) an experience questionnaire based on self-determination theory. Answers from 174 participants indicated that participants learnt about the objectives and constructed preferences in both the gamified and control treatments. However, in neither were weights sufficiently adjusted. Our gamification making the ranges salient did not help overcome this bias. Both treatments were experienced as neutral to positive, the gamified being more entertaining. We discuss implications: if gamification of tools for participatory decision-making is to be promoted, it requires further research. Range insensitivity remains an unresolved bias in MCDA.

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Aubert, A. H., Lienert, J., & von Helversen, B. (2022). Data for: Gamified environmental multi‐criteria decision analysis: information on objectives and range insensitivity bias (Version 1.0) [Data set]. Eawag: Swiss Federal Institute of Aquatic Science and Technology. https://doi.org/10.25678/000713

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The associated article

Aubert, A. H., Lienert, J., & von Helversen, B. (2022). Gamified environmental multi‐criteria decision analysis: information on objectives and range insensitivity bias. International Transactions in Operational Research. https://doi.org/10.1111/itor.13206

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Author	Aubert, Alice H. Lienert, Judit von Helversen, Bettina
Keywords	behavioral OR,wastewater,preference elicitation,learning,Decision Support System,citizen participation,evaluation process,self-determination theory,gamification,factual learning,preference construction,weights,experience
Systems	wastewater management
Timerange	2019-01 TO 2019-03
Geographic Name(s)	Zurich
Review Level	general
Curator	Aubert, Alice
Contact	Lienert, Judit <Judit.Lienert@eawag.ch>
DOI	10.25678/000713