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Abstract Understanding why animals (including humans) choose one thing over another is one of the key questions underlying the fields of behavioural ecology, behavioural economics and psychology. Most traditional studies of food choice in animals focus on simple, single‐attribute decision tasks. However, animals in the wild are often faced with multi‐attribute choice tasks where options in the choice set vary across multiple dimensions. Multi‐attribute decision‐making is particularly relevant for flower‐visiting insects faced with deciding between flowers that may differ in reward attributes such as sugar concentration, nectar volume and pollen composition as well as non‐rewarding attributes such as colour, symmetry and odour. How do flower‐visiting insects deal with complex multi‐attribute decision tasks?Here we review and synthesise research on the decision strategies used by flower‐visiting insects when making multi‐attribute decisions. In particular, we review how different types of foraging frameworks (classic optimal foraging theory, nutritional ecology, heuristics) conceptualise multi‐attribute choice and we discuss how phenomena such as innate preferences, flower constancy and context dependence influence our understanding of flower choice.We find that multi‐attribute decision‐making is a complex process that can be influenced by innate preferences, flower constancy, the composition of the choice set and economic reward value. We argue that to understand and predict flower choice in flower‐visiting insects, we need to move beyond simplified choice sets towards a view of multi‐attribute choice which integrates the role of non‐rewarding attributes and which includes flower constancy, innate preferences and context dependence. We further caution that behavioural experiments need to consider the possibility of context dependence in the design and interpretation of preference experiments.We conclude with a discussion of outstanding questions for future research. We also present a conceptual framework that incorporates the multiple dimensions of choice behaviour.
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Attribute-based choice
Alternative-based approaches to decision making generate overall values for each option in a choice set by processing information within options before comparing options to arrive at a decision. By contrast, attribute-based approaches compare attributes (such as monetary cost and time delay to receipt of a reward) across options and use these attribute comparisons to make a decision. Because they compare attributes, they may not use all available information to make a choice, which categorizes many of them as heuristics. Attribute-based models can better predict choice compared to alternative-based models in some situations (e.g., when there are many options in the choice set, when calculating an overall value for an option is too cognitively taxing). Process data comparing alternative-based and attribute-based processing obtained from eye-tracking and mouse-tracking technology support these findings. Data on attribute-based models thus align with the notion of bounded rationality that people make use of heuristics to make good decisions when under time pressure, informational constraints, and computational constraints. Further study of attribute-based models and processing would enhance our understanding of how individuals process information and make decisions.
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- Award ID(s):
- 1658837
- PAR ID:
- 10211592
- Editor(s):
- Viale, R.
- Date Published:
- Journal Name:
- Routledge handbook of bounded rationality
- Page Range / eLocation ID:
- 242–253
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.4324/9781315658353-16
