Suchergebnisse

A simple decision theory of spatial interaction is proposed in which interaction decisions are postulated to involve a number of distinct factors, relating to properties both of actors and of opportunities, as well as to the spatial separation between them. In particular, it is postulated that favorable conditions for such factors arise as independent random events over space, and that interactions are taken when an appropriate conjunction of such events occurs. Given this theory, the central result of the paper is to show that the asymptotically most probable interaction frequencies predicted by the theory correspond precisely to the solutions of the general interaction model proposed by Alonso. This result thus provides a possible behavioral foundation for the Alonso model, and in particular it yields an explicit behavioral interpretation of its parameters.

The purpose of this paper is to unite two current approaches to modeling dispersed spatial-interaction behavior: the entropy-smoothing approach, and the cost-efficiency approach. The main result of the paper is to show that those interaction flows determined by entropy-smoothing techniques correspond (for large flows) to the most probable flow patterns consistent with cost-efficient spatial-interaction behavior. In addition, it is shown that under very general conditions, these flow patterns are indeed overwhelmingly most probable. Thus, these results establish a clear behavioral foundation for entropy-smoothing techniques in terms of the cost-efficiency theory. Finally, a number of statistical estimation procedures are developed for operationalizing this theory.

A new approach is proposed for the analysis of spatial-interaction behavior under conditions of congestion. This approach, which is based on a cost-efficiency principle of interaction behavior, is shown to lead to a new class of exponential probability models for realized spatial-interaction patterns. In addition, these exponential trip-pattern models are shown to yield a natural stochastic generalization of the deterministic 'user-equilibrium' models currently employed in the analysis of urban traffic flows. In particular, such user-equilibria now constitute the 'most probable states' in these new models.

A set of necessary and sufficient conditions for the existence of additive accessibility measures is presented, which essentially refines the conditions developed by Weibull (1980). In particular, the central axiom in his paper is shown to be equivalent to a pair of independent axioms, designated as the 'cumulative dominance' and 'cumulative separation' properties of perceived-accessibility behavior. In addition, it is shown that the degree of perceived substitutability among spatial alternatives plays an important role in distinguishing the behavior implicit in each of these properties. Finally, it is shown that this axiom system together with that in Weibull's paper offers certain analytical advantages over more classical characterizations of additive accessibility measures.

In a variety of situations involving human interaction, actors compare alternative interaction opportunities in terms of their perceived distance or accessibility to opportunities within some relevant space of attributes. In this paper, a theory of interaction preferences is proposed in which actors implicitly discount potential opportunity interactions in terms of these perceived distances. This form of implicit discounting behavior is shown to be characterized by three general axioms of observable preference behavior. The special case of exponential spatial discounting is also characterized explicitly. In addition, conditions are established under which discounted preferences are representable by utility functions. Finally, the dependence of discounted preferences on the underlying configuration of distances is examined in depth.

This paper critically reexamines the Jaynes interpretation of finite maximum-entropy distributions as limits of the 'most likely' relative-frequency distributions consistent with any given prior information. It is shown that while this interpretation is valid in a number of cases, it fails to hold for many types of prior information. Given this limitation, a weaker form of the Jaynes interpretation is proposed which is shown to hold for a wider class of prior information.