How cognitive modeling can identify response biases in negotiations
Using Drift Diffusion Modeling for lab and field bargaining to study how responders strategically manipulate their response times
Collaborators: Ian Krajbich, Wenjia Joyce Zhao
Programming: R, stan
Skills: Bayesian Statistics, Model Comparison, Sequential Sampling Models, Supercomputing Resources
๐ญ About
Many decisions involve a process of comparing and accumulating net evidence in favor of the choice options up to a predetermined boundary, a process which takes time and reflects the strength of the net evidence. The evidence reflects the agentโs evaluation of the choice options โ an agent deciding between an apple ( ๐ย ) and an orange ( ๐ย ) must weigh the benefits and costs of the apple against those of the orange.
If these two evaluations are roughly equal ( ๐ย ~ ๐), the agent will struggle to decide which item to choose ( ๐ขย ). On the other hand, if the agent finds the orange to be much more attractive than the apple ( ๐ย > ๐ย or ๐ย > ๐), then their choice will be quick and predictable ( ๐ย ). This relation between strength-of-preference and response time (RT) is a basic feature of evidence-accumulation or sequential-sampling models, such as the drift-diffusion model (DDM, Figure 1).
![example image](/assets/img/project_4_images/project_4_fig_1.png)
In the bargaining example, the seller must weigh the buyerโs offer against the utility of the car and/or future offers. If the seller rejects ( ๐ย ) the buyerโs offer quickly ( ๐ย ), they signal to the buyer that the offer was far too low; if the seller rejects ( ๐ย ) the offer slowly ( ๐ขย ), they signal to the buyer that the offer was competitive.
![example image](/assets/img/project_4_images/project_4_fig_2.png)