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Pricing and incentive design in applications of green technology subsidies and revenue management

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dc.contributor.advisor Georgia Perakis. en_US
dc.contributor.author Lobel, Ruben en_US
dc.contributor.other Massachusetts Institute of Technology. Operations Research Center. en_US
dc.coverage.spatial e-gx--- en_US
dc.date.accessioned 2012-09-13T18:56:01Z
dc.date.available 2012-09-13T18:56:01Z
dc.date.copyright 2012 en_US
dc.date.issued 2012 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/72846
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 139-147). en_US
dc.description.abstract This thesis addresses three issues faced by firms and policy-makers when deciding how to price products and properly incentivize consumers. In the first part of the thesis, we focus on a firm attempting to dynamically adjust prices to maximize profits when facing uncertain demand, as for example airlines selling flights or hotels booking rooms. In particular, we develop a robust sampling-based optimization framework that minimizes the worst-case regret and dynamically adjusts the price according to the realization of demand. We propose a tractable optimization model that uses direct demand samples, where the confidence level of this solution can be obtained from the number of samples used. We further demonstrate the applicability of this approach with a series of numerical experiments and a case study using airline ticketing data. In the second part of the thesis, we propose a model for the adoption of solar photovoltaic technology by residential consumers. Using this model, we develop a framework for policy makers to find optimal subsidy levels in order to achieve a desired adoption target. The technology adoption process follows a discrete choice model, which is reinforced by network effects such as information spread and learning-by-doing. We validate the model through an empirical study of the German solar market, where we estimate the model parameters, generate adoption forecasts and demonstrate how to solve the policy design problem. We use this framework to show that the current policies in Germany could be improved by higher subsidies in the near future and a faster phase-out of the subsidy program. In the third part of the thesis, we model the interaction between a government and an industry player in a two-period game setting under uncertain demand. We show how the timing of decisions will affect the production levels and the cost of the subsidy program. In particular, we show that when the government commits to a fixed policy, it signals to the supplier to produce more in the beginning of the horizon. Consequently, a flexible policy is on average more expensive for the government than a committed policy. en_US
dc.description.statementofresponsibility by Ruben Lobel. en_US
dc.format.extent 147 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Operations Research Center. en_US
dc.title Pricing and incentive design in applications of green technology subsidies and revenue management en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Operations Research Center. en_US
dc.identifier.oclc 807184022 en_US


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