Cut-off models for the ‘go-home’ decision of pedestrians in shopping streets

Many behavioral and nonbehavioral models have been proposed to model pedestrian behavior. Among these, pedestrians’ decision processes have not been explicitly modeled. Utility-maximizing models have been prominently used, but these models may be misspecified owing to their unrealistic assumptions. As an alternative, this paper proposes cut-off models based on the satisficing heuristic founded in bounded rationality theory. The go-home decision of pedestrians in Wang Fujing Street, Beijing, is taken as an example. Results of a multinomial logit model and three cut-off models with increasing complexity are compared. The results show that the cut-off models can fit the data equally as well as the multinomial logit model, suggesting that satisficing heuristics not only have theoretical advantages but also statistical power. Introducing a decision engagement module before the satisficing decision module significantly improves the cut-off model and supports the hypothesis of a hierarchical decision process