Individual decision‐making in dynamic collective systems

One of the most popular individual choice models is the multinomial logit model (MLM). The basic hypothesis of the MLM is that an individual chooses an alternative among a set of alternatives available to him by comparing the utilities of all the choices. The MLM is, however, limited in its usefulness because it doesn't account for the effects of the time factor and the social interactions between individuals. This work describes a dynamic extension of the MLM that allows for such interactions. The new model is formulated as an interactive continuous‐time Markov process, and is approximated, for a large population, by a deterministic system. Some possible consequences of the interaction phenomena are discussed with a special binary choice model.

Keywords::

• choice models
• multinomial logit model
• interactive continuous‐time Markov process
• approximations for Markov processes
• nonlinear differential equations