nep-net New Economics Papers
on Network Economics
Issue of 2010‒03‒13
five papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Unique Equilibrium in Two-Part Tariff Competition between Two-Sided Platforms By Markus Reisinger
  2. Discriminatory fees, coordination and investment in shared ATM networks By Stijn Ferrari
  3. Experimenting with Strategic Experimentation: Risk Taking, Neighborhood Size and Network Structure By Niels D. Grosse
  4. Strategyproof Approximation Mechanisms for Location on Networks By Noga Alon; Michal Feldman; Ariel D. Procaccia; Moshe Tennenholtz
  5. Improved Bid Prices for Choice-Based Network Revenue Management By Joern Meissner; Arne Strauss

  1. By: Markus Reisinger (Department of Economics, University of Munich)
    Abstract: Two-sided market models in which platforms compete via two-part tariffs, i.e. a subscription and a per-transaction fee, are often plagued by a continuum of equilibria. This paper augments existing models by allowing for heterogeneous trading behavior of agents on both sides. We show that this simple method yields a unique equilibrium even in the limit as the heterogeneity vanishes. In case of competitive bottlenecks we find that in this equilibrium platforms benefit from the possibility to price discriminate if per-transaction costs are relatively large. This is the case because two-part tariffs allow platforms to better distribute these costs among the two sides. Under two-sided single-homing price discrimination hurts platforms if per-transaction fees can be negative.
    Keywords: Two-Sided Markets, Per-Transaction Fee, Subscription Fee, Two-Part Tariffs, Unique Equilibrium
    JEL: D43 L13
    Date: 2010–02
  2. By: Stijn Ferrari (National Bank of Belgium, Financial Stability Department; Catholic University of Leuven)
    Abstract: This paper empirically examines the effects of discriminatory fees on ATM investment and welfare, and considers the role of coordination in ATM investment between banks. Our main findings are that foreign fees tend to reduce ATM availability and (consumer) welfare, whereas surcharges positively affect ATM availability and the different welfare components when the consumers' price elasticity is not too large. Second, an organization of the ATM market that contains some degree of coordination between the banks may be desirable from a welfare perspective. Finally, ATM availability is always higher when a social planner decides on discriminatory fees and ATM investment to maximize total welfare. This implies that there is underinvestment in ATMs, even in the presence of discriminatory fees
    Keywords: investment, coordination, ATMs, network industries, empirical entry models, spatial discrete choice demand models
    JEL: G21 L10 L50 L89
    Date: 2010–01
  3. By: Niels D. Grosse (School of Economics and Business Administration, Friedrich-Schiller-University Jena)
    Abstract: This paper investigates the effects of neighborhood size and network structure on strategic experimentation. We analyze a multi-arm bandit game with one safe and two risky alternatives. In this setting, risk taking produces a learning externality and an opportunity for free riding. We conduct a laboratory experiment to investigate whether group size and the network structure affect risk taking. We find that group size has an effect on risk taking that is qualitatively in line with equilibrium predictions. Introducing an asymmetry among agents in the same network with respect to neighborhood size leads to substantial deviations from equilibrium play. Findings suggests that subjects react to changes in their direct neighborhood but fail to play a best-response to their position within the network.
    Keywords: strategic experimentation, experiment, bandit game, risk taking
    JEL: C91 D81 D85 O33
    Date: 2010–02–23
  4. By: Noga Alon; Michal Feldman; Ariel D. Procaccia; Moshe Tennenholtz
    Abstract: We consider the problem of locating a facility on a network, represented by a graph. A set of strategic agents have different ideal locations for the facility; the cost of an agent is the distance between its ideal location and the facility. A mechanism maps the locations reported by the agents to the location of the facility. Specifically, we are interested in social choice mechanisms that do not utilize payments. We wish to design mechanisms that are strategyproof, in the sense that agents can never benefit by lying, or, even better, group strategyproof, in the sense that a coalition of agents cannot all benefit by lying. At the same time, our mechanisms must provide a small approximation ratio with respect to one of two optimization targets: the social cost or the maximum cost. We give an almost complete characterization of the feasible truthful approximation ratio under both target functions, deterministic and randomized mechanisms, and with respect to different network topologies. Our main results are: We show that a simple randomized mechanism is group strategyproof and gives a tight approximation ratio of 3/2 for the maximum cost when the network is a circle; and we show that no randomized SP mechanism can provide an approximation ratio better than 2-o(1) to the maximum cost even when the network is a tree, thereby matching a trivial upper bound of two.
    Date: 2010–02
  5. By: Joern Meissner (Department of Management Science, Lancaster University Management School); Arne Strauss (Department of Management Science, Lancaster University Management School)
    Abstract: In many implemented network revenue management systems, a bid price control is being used. In this form of control, bid prices are attached to resources, and a product is offered if the revenue derived from it exceeds the sum of the bid prices of its consumed resources. This approach is appealing because once bid prices have been determined, it is fairly simple to derive the products that should be offered. Yet it is still unknown how well a bid price control actually performs. Recently, considerable progress has been made with network revenue management by incorporating customer purchase behavior via discrete choice models. However, the majority of authors have presented control policies for the booking process that are expressed in terms of which combination of products to offer at a given point in time and given resource inventories. The recommended combination of products as identified by these policies might not be representable through bid price control. If demand were independent from available product alternatives, an optimal choice of bid prices is to use the marginal value of capacity for each resource in the network. But under dependent demand, this is not necessarily the case. In fact, it seems that these bid prices are typically not restrictive enough and result in buy-down effects. We propose (1) a simple and fast heuristic that iteratively improves on an initial guess for the bid price vector; this first guess could be, for example, dynamic estimates of the marginal value of capacity. Moreover, (2) we demonstrate that using these dynamic marginal capacity values directly as bid prices can lead to significant revenue loss as compared to using our heuristic. Finally, (3) we investigate numerically how much revenue performance is lost due to the confinement of product combinations that can be represented by a bid price. Our heuristic is not restricted to a particular choice model and can be combined with any method that provides estimates of the marginal values of capacity. In our numerical experiments, we test the heuristic on some popular networks examples taken from peer literature. We use a multinomial logit choice model which allows customers from different segments to have products in common that they are considering purchasing. In most instances, our heuristic policy results in significant revenue gains over some currently available alternatives at low computational cost.
    Keywords: revenue management, network, bid prices, choice model
    JEL: C61
    Date: 2010–01

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