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.

[1]  J. Deneubourg,et al.  Dynamic Models of Competition between Transportation Modes , 1979 .

[2]  T. Schelling Micromotives and Macrobehavior , 1978 .

[3]  R. Kubo,et al.  Fluctuation and relaxation of macrovariables , 1973 .

[4]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[5]  Alan Wilson,et al.  Catastrophe Theory and Bifurcation : Applications to Urban and Regional Systems , 1980 .

[6]  N. Kampen,et al.  a Power Series Expansion of the Master Equation , 1961 .

[7]  Walter Isard,et al.  Models of transition processes , 1977 .

[8]  R. Duncan Luce,et al.  Individual Choice Behavior , 1959 .

[9]  R. Thom Stabilité structurelle et morphogenèse , 1974 .

[10]  Walter Isard Strategic elements of a theory of major structural change , 1977 .

[11]  D. J. Bartholomew,et al.  Stochastic Models for Social Processes. , 1968 .

[12]  F. Bass A new product growth model for consumer durables , 1976 .

[13]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  W. R. Buckland,et al.  Stochastic Models for Social Processes , 1967 .

[15]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[16]  Michèle Sanglier,et al.  Dynamic models of urban growth , 1978 .

[17]  D. Sattinger Topics in stability and bifurcation theory , 1973 .

[18]  J. Hearon,et al.  The kinetics of linear systems with special reference to periodic reactions , 1953 .

[19]  Karmeshu,et al.  Stochastic evolution of a nonlinear model of diffusion of information , 1980 .

[20]  John Conlisk,et al.  Interactive markov chains , 1976 .

[21]  A. Palma,et al.  Simplification procedures for a probabilistic choice model , 1981 .

[22]  M. J. Faddy,et al.  Stochastic compartmental models as approximations to more general stochastic systems with the general stochastic epidemic as an example , 1977, Advances in Applied Probability.

[23]  T. Kurtz Strong approximation theorems for density dependent Markov chains , 1978 .

[24]  George H. Weiss,et al.  Stochastic theory of nonlinear rate processes with multiple stationary states , 1977 .

[25]  Stanley R. Pliska,et al.  Controlled jump processes , 1975 .

[26]  J. Lehoczky Approximations for interactive Markov chains in discrete and continuous time , 1980 .

[27]  Ralph B. Ginsberg,et al.  Critique of probabilistic models: Application of the Semi‐Markov model to migration , 1972 .

[28]  H. D. Miller,et al.  The Theory Of Stochastic Processes , 1977, The Mathematical Gazette.