Expectancy × value models of the relations between demographic, psychological, and situational factors and speeding...

This study illustrates how expectancy × value (E × V) models can be created from responses to driving scenarios to model both: (1) reasons for the general tendency to speed in a particular situation and (2) reasons that specific personal or situational factors predict the likelihood of speeding within that situation.

The method was applied to predicting the self-rated likelihood of speeding in a specific driving scenario. Data from 302 participants who completed an online survey were used for the analysis.

The E × V models indicated that the average person tended to see both reasons to speed in this situation, such as to arrive at a meeting on time, and reasons not to speed, such as to avoid a crash or speeding ticket. The results further clarify how specific personal and situational factors were associated with reasoning about speeding. For instance, people who described speeding regularly were modeled as more likely to speed in part due to their greater expectation that speeding would be enjoyable and their greater valuation of being on time. And people who described valuing rules were modeled as less likely to speed in part due to greater expectations that speeding would result in a crash or injury.

We describe how E × V models can be further elaborated to better represent the psychological processes and reasoning underlying speeding and other unsafe driving behaviors.