Explore the vast range of titles available.

We describe an equilibrium model of peer-to-peer product sharing, or collaborative consumption, where individuals with varying usage levels make decisions about whether or not to own a homogeneous product. Owners are able to generate income from renting their products to nonowners while nonowners are able to access these products through renting on an as-needed basis. We characterize equilibrium outcomes, including ownership and usage levels, consumer surplus, and social welfare. We compare each outcome in systems with and without collaborative consumption and examine the impact of various problem parameters. Our findings indicate that collaborative consumption can result in either lower or higher ownership and usage levels, with higher ownership and usage levels more likely when the cost of ownership is high. Our findings also indicate that consumers always benefit from collaborative consumption, with individuals who, in the absence of collaborative consumption, are indifferent between owning and not owning benefitting the most. We study both profit-maximizing and social-welfare–maximizing platforms and compare equilibrium outcomes under both in terms of ownership, usage, and social welfare. We find that the difference in social welfare between the profit-maximizing and social-welfare–maximizing platforms is relatively modest. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2970 . This paper was accepted by Gad Allon, operations management.

This paper investigates the impact of ride-hailing services, particularly the integration of autonomous vehicles (AVs), on urban transportation systems. The paper discusses the challenges faced by ride-hailing platforms in managing a fleet of both AVs and conventional vehicles (CVs) within the spatial network of a city. It examines the approaches and methods used to manage demand allocation for AVs and CVs, considering the strategic behavior of human drivers and considerations for possible regulations. Using mean-field game theory, this paper proposes efficient strategies for managing fleet operations along with those of traffic optimization and service efficiency. The analysis highlights the complexities of integrating AVs into existing transportation systems and advocates for the development of robust theoretical traffic models for regulatory decisions and improved urban mobility.

As a model for an ATM switch we consider the overflow frequency of a queue that is served at a constant rate and in which the arrival process is the superposition of N traffic streams. We consider an asymptotic as N → ∞ in which the service rate Nc and buffer size Nb also increase linearly in N. In this regime, the frequency of buffer overflow is approximately exp(– NI ( c, b )) , where I ( c, b ) is given by the solution to an optimization problem posed in terms of time-dependent logarithmic moment generating functions. Experimental results for Gaussian and Markov modulated fluid source models show that this asymptotic provides a better estimate of the frequency of buffer overflow than ones based on large buffer asymptotics.

As a model for an ATM switch we consider the overflow frequency of a queue that is served at a constant rate and in which the arrival process is the superposition of N traffic streams. We consider an asymptotic as N → ∞ in which the service rate Nc and buffer size Nb also increase linearly in N. In this regime, the frequency of buffer overflow is approximately exp(–NI(c, b)), where I(c, b) is given by the solution to an optimization problem posed in terms of time-dependent logarithmic moment generating functions. Experimental results for Gaussian and Markov modulated fluid source models show that this asymptotic provides a better estimate of the frequency of buffer overflow than ones based on large buffer asymptotics.

How is efficiency affected when demand excesses over supply are signalled through waiting in queues? We consider a class of congestion games with a nonatomic set of players of a constant mass, based on a formulation of generic linear programs as sequential resource allocation games. Players continuously select activities such that they maximize linear objectives interpreted as time-average of activity rewards, while active resource constraints cause queueing. In turn, the resulting waiting delays enter in the optimization problem of each player. The existence of Wardrop-type equilibria and their properties are investivated by means of a potential function related to proportional fairness. The inefficiency of the equilibria relative to optimal resource allocation is characterized through the price of anarchy which is 2 if all players are of the same type (\\(\\infty\\) if not).

This paper considers UMTS networks in which users request services other than telephony that last for long time intervals. It defines an auction-based mechanism for nearly consistent reservation of the resources of a UMTS (or GPRS) network by the users that value them the most, in order to satisfy the longer time scale requirements of their service sessions. Each of these sessions has a fixed target bit-rate. The mechanism is based on a series of Generalized Vickrey Auctions and a set of predefined user utility functions that are proposed. Bidding is performed automatically on behalf of the users on the basis of each user's selection of one of these utility functions and his declaration of a total willingness to pay. The effectiveness of this resource reservation mechanism is demonstrated by means of experiments. It appears that most of the users either are served very satisfactorily or essentially are not served at all. The mechanism is implemented at the network base station, and is applicable in practical cases of networks with large numbers of users whose sessions last for many slots.

We study usage-sensitive charging schemes for broadband communications networks. We argue that a connection's \"effective bandwidth\" is a good proxy for the quantity of network resource that the connection consumes and can be the basis for a usage charge. The determination of effective bandwidth can be problematic, however, since it involves the moment-generating function of the cell arrival process, which may be difficult to model or measure. This article describes methods of computing usage charges from simple measurements and relating these to bounds on the effective bandwidth. Thus we show that charging for usage on the basis of effective bandwidths can be approximated well by charges based on simple measurements.

Given the proximity of many wireless users and their diversity in consuming local resources (e.g., data-plans, computation and energy resources), device-to-device (D2D) resource sharing is a promising approach towards realizing a sharing economy. This paper adopts an easy-to-implement greedy matching algorithm with distributed fashion and only sub-linear O(log n) parallel complexity (in user number n) for large-scale D2D sharing. Practical cases indicate that the greedy matching's average performance is far better than the worst-case approximation ratio 50% as compared to the optimum. However, there is no rigorous average-case analysis in the literature to back up such encouraging findings and this paper is the first to present such analysis for multiple representative classes of graphs. For 1D linear networks, we prove that our greedy algorithm performs better than 86.5% of the optimum. For 2D grids, though dynamic programming cannot be directly applied, we still prove this average performance ratio to be above 76%. For the more challenging Erdos-Renyi random graphs, we equivalently reduce to the asymptotic analysis of random trees and successfully prove a ratio up to 79%. Finally, we conduct experiments using real data to simulate realistic D2D networks, and show that our analytical performance measure approximates well practical cases.

We consider UMTS networks in which users request services other than telephony that last for long time intervals: e.g., video clips that last for several minutes. The duration of network time-slots over which resource units are allocated is much shorter. This complicates consistent reservation of resources over longer time scales, where consistent reservation is required to ensure that service quality is constant throughout the entire service session. In this paper, we define an auction-based mechanism for nearly consistent reservation of the resources of a UMTS (or GPRS) network by the users that value them the most, in order to satisfy the longer time scale requirements of their service sessions. Each of these sessions has a fixed target bit-rate. The mechanism is based on a series of Generalized Vickrey Auctions and a set of predefined user utility functions that we propose. Bidding is performed automatically on behalf of the users on the basis of each user's selection of one of these utility functions and his declaration of a total willingness to pay. We argue that under our mechanism the user does not have a clear incentive of not performing a truthful selection of a bidding function according to his own utility. The utility functions we define express appropriately the preferences of the users with respect to the resource allocation pattern in the cases where perfectly consistent allocation cannot be attained. We also provide a mapping of these functions to the UMTS service classes. The effectiveness of our resource reservation mechanism is demonstrated by means of experiments. It appears that most of the users either are served very satisfactorily or essentially are not served at all. The mechanism is implemented at the network base station, and is applicable in practical cases of networks with large numbers of users whose sessions last for many slots.