Eyran J. Gisches

Choice of Routes in Congested Traffic Networks: Experimental Tests of the Braess Paradox

The Braess Paradox consists of showing that, in equilibrium, adding a new link that connects two routes running between a common origin and common destination may raise the travel cost for each network user. We report the results of two experiments designed to study whether the paradox is behaviorally realized in two simulated traffic networks that differ from each other in their topology. Both experiments include relatively large groups of participants who independently and repeatedly choose travel routes in one of two types of traffic networks, one with the added links and the other without them. Our results reject the hypothesis that the paradox is of marginal value and its force diminishes with experience. Rather, they strongly support the alternative hypothesis that with experience in traversing the networks financially motivated players converge to choosing the equilibrium routes in the network with added capacity despite sustaining a sharp decline in earnings.

Pre-trip Information and Route-Choice Decisions with Stochastic Travel Conditions: Experiment

This paper studies the effects of pre-trip information on route-choice decisions when travel conditions on two alternative congestible routes vary unpredictably. It presents and discusses an experiment designed to test a model recently proposed in a companion paper by Lindsey et al. (2013). That model predicts that if free-flow costs on the two routes are unequal, travel cost functions are convex, and capacities are positively and perfectly correlated, then in equilibrium, paradoxically, total expected travel costs increase with the provision of pre-trip information about travel conditions on each route. By contrast, when capacities vary independently, total expected travel costs are predicted to decrease with pre-trip information. We re-formulate the model for finite populations, and then test and find support for its predictions in an experiment where under different capacity scenarios, and with and without pre-trip information, subjects are asked to choose routes with payoff contingent on their performance.

Purchasing Scarce Products Under Dynamic Pricing: An Experimental Investigation

Whereas theoretical studies on dynamic pricing typically assume that consumers are either fully strategic or fully myopic, systematic empirical investigations into how consumers behave under dynamic pricing contexts are relatively rare. Focusing on scarce products, we constructed and experimentally tested a two-stage model in which a firm sells a seasonal good under exogenous inventory constraints to a market of strategic buyers. In our experiment, subjects assigned the role of buyers made purchase decisions in response to prices set by an automated seller. We find that equilibrium predictions assuming fully strategic buyers largely accounted for aggregate behavior in the experiment, and the ex post optimal decisions for subjects were overwhelmingly consistent with equilibrium prescriptions. Moreover, subjects tended to become individually more strategic as the session progressed. However, there were also nuanced systematic patterns of deviations from equilibrium that had profit and pricing implications f...

Competitive dynamic pricing with alternating offers: Theory and experiment

We propose an equilibrium model of duopolistic dynamic pricing in which a buyer alternates between two sellers for price offers over a finite time horizon. The game ends when the buyer accepts a price offer or the selling season is over, whichever comes first. Previous research (Granot et al., 2007) shows that there are successive markdowns in equilibrium when the buyer is commonly known to be myopic; our analysis suggests that when she is known to be strategic price offers over the entire selling season are constant. Moreover, lengthening the season increases (generally decreases) both sellersʼ profits when the buyer is myopic (strategic). An experimental study largely supports the equilibrium predictions when the buyer is myopic but not when she is strategic. In the latter case, early in the season sellers overprice the good arguably in an attempt to effectively shorten the season and thereby increase their profits.

Degrading network capacity may improve performance: information effects in the Braess Paradox

The Braess Paradox is a major finding in the equilibrium analysis of routing decentralized traffic in directed networks that are susceptible to congestion. It demonstrates that removing one or more links from a network that is subject to congestion may under certain combinations of cost structure and number of network users decrease the cost of travel for all its users. The Braess Paradox (BP) may be illustrated in networks modeled as non-atomic games where the number of commuters is very large and, as a consequence, each commuter only controls a negligible fraction of the overall traffic. Alternatively, as in the present study, it may be illustrated in networks modeled as atomic selfish routing games, where each commuter has a non-negligible effect on the travel costs of all the other commuters. Arguments have been raised not against the counterintuitive finding of Braess but, rather, against its relevance to real life situations. The argument goes that these are highly abstract networks and their seemingly paradoxical implications arise from the many aspects in which they differ from reality rather than from these aspects that they share with it. If the BP is a rare event in selfish routing networks, restricted to judiciously chosen combinations of parameter values and very simple networks, then interest in it should clearly be limited. But if a substantial fraction of networks in communication and transportation are susceptible to the BP, then the problem of adding links to the basic network or, alternatively, removing links from the augmented network gains practical significance and should, therefore, be approached with considerable care. Our main purpose is to compare to each other two information conditions. In the PUBLIC condition, each user is informed of the route choices and payoffs of all the users. In the PRIVATE condition, each user is only informed of her own payoff. For this purpose, we construct a basic network where each of n=18 players has to choose one of four routes from a common origin to common destination. We also construct an augmented network with two additional cross road segments that give rise to the Braess paradox. We use a computer-controlled within-subject experimental design in which each player first chooses one of six routes in 60 iterations of the augmented network and then one of four routes in 60 additional iterations of the basic network. We show that when the stage game is iterated in time, under both information conditions and in both games aggregate route choices converge to equilibrium.

Dynamic Pricing Decisions and Seller-Buyer Interactions under Capacity Constraints

Focusing on sellers’ pricing decisions and the ensuing seller-buyer interactions, we report an experiment on dynamic pricing with scarcity in the form of capacity constraints. Rational expectations equilibrium solutions are constructed and then tested experimentally with subjects assigned the roles of sellers and buyers. We investigate behavior in two between-subject conditions with high and moderate levels of capacity. Our laboratory market exhibits strategic sophistication: the price offers of sellers and the buyers’ aggregate responses largely approximate equilibrium predictions. We also observe systematic deviations from equilibrium benchmarks on both sides of the market. Specifically, in our experiment the sellers are boundedly strategic: their prices often exhibit strategic adjustments to profit from buyers with limited strategic sophistication, but they are also often biased towards equilibrium pricing even when that would not be ex-post optimal.

Information paradoxes in traffic networks

In this paper, we examine the impact of information on the routing decisions that drivers make in a congestible two route traffic network. We present a model and theoretical predictions of driver choices in this network and compare outcomes under conditions of full information and partial information regarding the capacities of each route. In certain circumstances, the model predicts a paradox: aggregate travel delays increase once drivers are a priori informed regarding (stochastic) travel conditions such as adverse weather. We report evidence supporting this paradox in a computerized laboratory experiment in which a large group of subjects repeatedly interact with one another. We analyze both the travel costs associated with each information condition and the individual and aggregate route choices that generate these costs.