Case-Based Reasoning and Dynamic Choice Modeling
用非线性案例推理方法模拟决策者的认知过程，通过比较过去与当前问题的相似性形成预期，并以康涅狄格州休闲渔民的地点选择为例验证模型有效性。
Estimating discrete choices under uncertainty typically rely on assumptions of expected utility theory. We build on the dynamic choice modeling literature by using a nonlinear case-based reasoning approach based on cognitive processes and forms expectations by comparing the similarity between past problems and the current problem faced by a decision maker. This study provides a proof of concept of a behavioral model of location choice applied to recreational fishers’ location choice behavior in Connecticut. We find the case-based decision model does well in explaining the observed data and provides value in explaining the dynamic value of attributes.