Maximum entropy methods are used to infer the true trip-distribution matrix in cases where parts of the data are suppressed due to privacy concerns. Large proportions of the suppressed data are found to be inferred correctly when the marginal totals in the trip distribution are known....

Road tolls are a well established way of dealing with problems of congestion. Over recent years, the literature has expanded to take account of how congestion charges might interact with imperfections in other markets. In this paper, we consider the case where congestion occurs within a complex...

Road pricing is a popular congestion reduction strategy. However, there may be wider impacts associated with a road toll. We consider a factor which is sometimes overlooked, namely that workers and firms may choose to change location in response to changes in the travel costs. A spatial...

In this paper we propose a new spatial equilibrium model, and use it to discuss issues related to rural depopulation. The discussion focuses on how investments in transport infrastructure and the spatial distribution of basic sector jobs can promote a relatively balanced growth of peripheral and...

In this study, we extend the single-period newsvendor problem with stochastic demand into a multi-period and time-dependent one and find a solution for it. We analyze the multi-period newsvendor problem with stochastic demand in a Stackelberg framework where the wholesaler is the leader and the...

In this paper, we use probabilistic methods to analyze learning effects in a behavioral experiment on the newsvendor model. We argue why we should believe that suggested orders follow a multinomial logit distribution, and use the single parameter in that model to extract information on learning...