7,766 research outputs found
Efficiency Analysis of Cournot Competition in Service Industries with Congestion
No full textWe consider Cournot competition in the presence of congestion effects. Our model consists of several service providers with differentiated services, each competing for users who are sensitive to both price and congestion. We distinguish two types of congestion effects, depending on whether spillover costs exist, that is, where one service provider's congestion cost increases with the other providers' output level. We quantify the efficiency of an unregulated oligopoly with respect to the optimal social welfare with tight upper and lower bounds. We show that, when there is no spillover, the welfare loss in an unregulated oligopoly is limited to 25% of the social optimum, even in the presence of highly convex costs. On the other hand, when spillover cost is present, there does not exist a constant lower bound on the efficiency of an unregulated oligopoly, even with affine cost. We show that the efficiency depends on the relative magnitude between the marginal spillover cost and the marginal benefit to consumers
The effect of supplier capacity on the supply chain profit
No full textIn this paper, we study the role of capacity on the efficiency of a two-tier supply chain with two suppliers (leaders, first tier) and one retailer (follower, second tier). The suppliers compete via pricing (Bertrand competition) and, as one would expect in practice, are faced with production capacity. We consider a model with differentiated substitutable products where the suppliers are symmetric differing only by their production capacity. We characterize the prices, production amounts and profits in three cases: (1) the suppliers compete in a decentralized Nash equilibrium game, (2) the suppliers “cooperate” to optimize the total suppliers’ profit, and (3) the two tiers of the supply chain are centrally coordinated. We show that in a decentralized setting, the supplier with a lower capacity may benefit from restricting her capacity even when additional capacity is available at no cost. We also show that the loss of total profit due to decentralization cannot exceed 25 % of the centralized chain profits. Nevertheless, the loss of total profit is not a monotonic function of the “degree of asymmetry” of the suppliers’ capacities. Furthermore, we provide an upper bound on the supplier profit loss at equilibrium (compared with the cooperation setting) that depends on the “market power” of the suppliers as well as their market size. We show that there is less supplier profit loss as the asymmetry (in terms of their capacities) increases between the two suppliers. The worst case arises when the two suppliers are completely symmetric.Singapore-MIT Alliance for Research and Technology (SMART)National Science Foundation (U.S.) (NSF award 0758061-CMII)National Science Foundation (U.S.) (NSF award 0556106-CMII)National Science Foundation (U.S.) (NSF award 1162034-CMMI
Technical Note—Nonlinear Pricing Competition with Private Capacity Information
No full textWe analyze the equilibrium of an incomplete information game consisting of two capacity-constrained suppliers and a single retailer. The capacity of each supplier is her private information. Conditioned on their capacities, the suppliers simultaneously and noncooperatively offer quantity-price schedules to the retailer. Then, the retailer decides on the quantities to purchase from each supplier to maximize his own utility. We prove the existence of a (pure strategy) Nash equilibrium for this game. We show that at the equilibrium each (infinitesimal) unit of the supply is assigned a marginal price that is independent of the capacities and depends only on the valuation function of the retailer and the distribution of the capacities. In addition, the supplier with the larger capacity sells all her supply
The Houstouns of Georgia
No full textThe Houstouns of Georgia shares the history of one of the oldest families in Georgia, showcasing its influential members and reflecting on the effect of one family throughout the state's history. Established by Sir Patrick Houstoun, who accompanied James Oglethorpe and helped him lay the foundations of the colony, the Houstoun family has called Georgia home since its inception. Over two hundred years after its founding, the author of The Houstouns of Georgia traces her own lineage back to the Houstoun family in her heavily researched account of the family's presence in Georgia from its founding onward. The Georgia Open History Library has been made possible in part by a major grant from the National Endowment for the Humanities: Democracy demands wisdom. Any views, findings, conclusions, or recommendations expressed in this collection, do not necessarily represent those of the National Endowment for the Humanities
Dynamic Pricing through Sampling Based Optimization
No full textIn this paper we develop an approach to dynamic pricing that combines ideas from data-driven and robust optimization to address the uncertain and dynamic aspects of the problem. In our setting, a firm off ers multiple products to be sold over a fixed discrete time horizon. Each product sold consumes one or more resources, possibly sharing the same resources among di fferent products. The firm is given a fixed initial inventory of these resources and cannot replenish this inventory during the selling season. We assume there is uncertainty about the demand seen by the fi rm for each product and seek to determine a robust and dynamic pricing strategy that maximizes revenue over the time horizon. While the traditional robust optimization models are tractable, they give rise to static policies and are often too conservative. The main contribution of this paper is the exploration of closed-loop pricing policies for di fferent robust objectives, such as MaxMin, MinMax Regret and MaxMin Ratio. We introduce a sampling based optimization approach that can solve this problem in a tractable way, with a con fidence level and a robustness level based on the number of samples used. We will show how this methodology can be used for data-driven pricing or adapted for a random sampling optimization approach when limited information is known about the demand uncertainty. Finally, we compare the revenue performance of the di fferent models using numerical simulations, exploring the behavior of each model under diff erent sample sizes and sampling distributions.National Science Foundation (U.S.) (Grant 0556106-CMII)National Science Foundation (U.S.) (Grant 0824674-CMII)Singapore-MIT Allianc
Book Talk: Hin Bredendieck: From Aurich to Atlanta with Gloria Köpnick and Rainer Stamm
No full textPresented online April 25, 2021, 12:00 p.m.-12:59 p.m.This event is hosted by the Georgia Tech Library and the Landesmuseum Oldenburg (Oldenburg State Museum for Art and Cultural History) with sponsorship from the Halle Foundation. Collaborators include Dr. Jennifer Gerndt, the Consulate General of Germany, and the Georgia Tech School of Industrial Design. Special thanks to the family and former students of Hin Bredendieck for their contributions to this exhibit.About the book: Hin Bredendieck (1904–95) graduated from the Bauhaus and was a versatile designer and pioneering teacher of design. A native of Aurich, in East Friesland in Germany, he was a student at the Bauhaus in Dessau from 1927 to 1930. During his time as a student there, Bredendieck worked with Marianne Brandt to design famous lamps such as the “Kandem Bedside Table Lamp,” which can be found on display at the Museum of Modern Art in New York City. In 1937, Bredendieck emigrated to the United States, where he was appointed as a teacher at the New Bauhaus Chicago. From there, he moved on to become the founding director of the Institute for Industrial Design at the Georgia Institute of Technology in Atlanta, and from this perch he established himself as one of the most influential mediators of Bauhaus ideas in America in the postwar years.
This richly illustrated volume showcases Bredendieck’s life and work in lavish detail. Highlighting the breadth of his global network and the wide range of artworks he created, it is a fitting monument to an important artist, and ambassador, of the Bauhaus.Dr. Gloria Köpnick is the director of the Lyonel-Feininger-Gallery in Quedlinburg, Germany. After studying art history at the Freie Universität Berlin, she worked at the Oldenburg State Museum of Art and Cultural History from 2014 to 2020. Her work and research interests include modern art, the cultural history of the Weimar Republic, and the Bauhaus. She is a freelance author, critic, and lecturer.Dr. Rainer Stamm serves as the director of the Oldenburg State Museum for Art and Cultural History. He is an honorary professor of art history at the University of Bremen, with a special focus on modern art history, museum history, the history of photography and art market history of the early 20th century.Runtime: 57:26 minutesThe Georgia Tech Library welcomes Gloria Köpnick and Rainer Stamm in conversation with Dean Leslie Sharp for a lively discussion of their 2020 book Hin Bredendieck: From Aurich to Atlanta
The Data-Driven Newsvendor Problem: New Bounds and Insights
No full textConsider the newsvendor model, but under the assumption that the underlying demand distribution is not known as part of the input. Instead, the only information available is a random, independent sample drawn from the demand distribution. This paper analyzes the sample average approximation (SAA) approach for the data-driven newsvendor problem. We obtain a new analytical bound on the probability that the relative regret of the SAA solution exceeds a threshold. This bound is significantly tighter than existing bounds, and it matches the empirical accuracy of the SAA solution observed in extensive computational experiments. This bound reveals that the demand distribution’s weighted mean spread affects the accuracy of the SAA heuristic.National Science Foundation (U.S.) (Grant DMS-0732175)National Science Foundation (Grant CMMI-0846554)United States. Air Force Office of Scientific Research (Award FA9550-08-1-0369)United States. Air Force Office of Scientific Research (Award FA9550-11-1-0150)National Science Foundation (U.S.) (Grant CMMI- 0824674)National Science Foundation (U.S.) (Grant CMMI-0758061
Solving variational inequality and fixed point problems by averaging and optimizing potentials
No full text"December 1997."Includes bibliographical references (p. 41-46).Supported in part by NSF Grant. 9634736-DMIT.L. Magnanti, G. Perakis
The Impact of a Target on Newsvendor Decisions
No full textGoal achieving is a commonly observed phenomenon in practice, and it plays an important role in decision making. In this paper, we investigate the impact of a target on newsvendor decisions. We take into account the risk and model the effect of a target by maximizing the satisficing measure of a newsvendor’s profit with respect to that target. We study two satisficing measures: (i) conditional value at risk (CVaR) satisficing measure that evaluates the highest confidence level of CVaR achieving the target; (ii) entropic satisficing measure that assesses the smallest risk tolerance level under which the certainty equivalent for exponential utility function achieves the target. For both satisficing measures, we find that the optimal ordering quantity increases with the target level. We determine an optimal order quantity for a target-based newsvendor and characterize its properties with respect to, for example, product’s profit margin
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