Image, Affect, and Decision Making

Category: heuristic Secondary: ['cognitive_bias'] Difficulty: intermediate Domains: psychology, decision science

IMAGE, AFFECT, AND DECISION MAKING

The early anomalous findings with gambles were laid aside while other means of explaining the differences between ratings, choices, and pricing responses were developed (see Tversky, Slovic, & Kahneman, 1990). At the same time, Slovic and colleagues at Decision Research embarked on a research program designed to test whether introducing a hazardous facility into a region might stigmatize that region and cause people to avoid going there to recreate, retire, or do business (Slovic et al., 1991). Believing self-report to be unreliable (“If they build it, will you not come?”), research on stigmatization was conducted through a number of empirical studies designed to examine the relationship between imagery, affect, and decision making. After conducting these studies, we learned that they fit closely with a large body of existing theory and research, such as the work of Damasio, Mowrer, and Epstein, described earlier.

Several empirical studies have demonstrated a strong relationship between imagery, affect, and decision making. Many of these studies used a wordassociation technique, which involves presenting subjects with a target stimulus, usually a word or very brief phrase and asking them to provide the first thought or image that comes to mind. The process is then repeated a number of times (e.g., three to six), or until no further associations are generated. Following the elicitation of images, subjects are asked to rate each image they give on a scale ranging from very positive (e.g., +2) to very negative (e.g., −2), with a neutral point in the center. Scoring is done by summing or averaging the ratings to obtain an overall index.

This imagery method has been used successfully to measure the affective meanings that influence people’s preferences for different cities and states (Slovic et al., 1991) as well as their support or opposition to technologies such as nuclear power (Peters & Slovic, 1996).

Table 23.2 illustrates the method in a task where one respondent was asked to give associations to each of two cities and, later, to rate each image affectively. The cities in this example show a clear affective preference for San Diego over Denver. Slovic et al. (1991) showed that summed image scores such as these were highly predictive of expressed preferences for living in or visiting cities. In one study, they found that the image score predicted the location of actual vacations during the next 18 months.