The visual environment and attention in decision making.

Abstract

Visual attention is a fundamental aspect of most everyday decisions, and governments and companies spend vast resources competing for the attention of decision makers. In natural environments, choice options differ on a variety of visual factors, such as salience, position, or surface size. However, most decision theories ignore such visual factors, focusing on cognitive factors such as preferences as determinants of attention. To provide a systematic review of how the visual environment guides attention we meta-analyze 122 effect sizes on eye movements in decision making. A psychometric meta-analysis and Top10 sensitivity analysis show that visual factors play a similar or larger role than cognitive factors in determining attention. The visual factors that most influence attention are positioning information centrally, q = .43 (Top10 = .67), increasing the surface size, q = .35 (Top10 = .43), reducing the set size of competing information elements, q = .24 (Top10 = .24), and increasing visual salience, q = .13 (Top10 = .24). Cognitive factors include attending more to preferred choice options and attributes, q = .36 (Top10 = .31), effects of task instructions on attention, q = .35 (Top10 = .21), and attending more to the ultimately chosen option, q = .59 (Top10 = .26). Understanding real-world decision making will require the integration of both visual and cognitive factors in future theories of attention and decision making. Public Significance StatementVisual attention in decision making is influenced by the relevance of information and by how information is presented, that is, by visual factors like the position, salience, and size of information and the number of competing information elements. We show that how information is presented is more important to attention than the relevance of the information. Policymakers and companies can leverage visual factors to mislead or guide our attention to information that enhances welfare supporting behaviors.

Modeling Eye Movements During Decision Making: A Review

“…A critical assumption of traditional DDMs is that visual information uptake is randomly distributed across alternatives. Therefore, these models imply that eye movements are uniformly distributed over alternatives (and attributes), which is similar to the implicit assumption in compensatory decision models that people attend equally to all information in the choice task (Glöckner & Herbold, 2011;Orquin et al, 2021). Despite some challenges in generalizing DDMs, and SSMs more generally, to multi-alternative preferential choice in realistic contexts (e.g., Mormann & Russo, 2021), the models provide an important step toward connecting neuro-physiological processes to unobserved preference formation.…”

“…2, P3), and exert a large influence especially during object localization. These visual factors have strong effects on attention, comparable in size to those of top-down factors such as task instructions (Orquin et al, 2021). Basic perceptual features, such as luminance, edges, contours, and colors (Treisman & Gelade, 1980;Wolfe, 1994), are extracted and combined into a salience map, or attention priority map (Fig.…”

Toward an attentional turn in research on risky choice

“…Unbalanced attention allocation might also be driven by specific features of the options—leading to regularities such as the Allais paradox and the fourfold pattern. Among such stimulus features might be the size and salience of stimuli (Orquin et al, 2021 ). Although in standard paradigms font size and display features are usually kept constant (but see Weber and Kirsner, 1997 ), the options might still differ in visual properties.…”

Covert attention leads to fast and accurate decision-making.

“…Nutrition, health, or sustainability information on products is, for instance, often not gazed at by consumers (Bartels et al, 2018; Orquin et al, 2020). Rather than blaming consumers for lack of motivation, it is necessary to understand that more than half of the variance in decision-makers’ attention is determined by visual factors such as the surface size, visual salience, and position of information (Orquin et al, 2021). These visual factors can help decision-makers to attend to information relevant to their own goals, but visual factors are ultimately controlled by producers and retailers (Orquin & Wedel, 2020).…”