Literatura académica sobre el tema "Revenue management"
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Artículos de revistas sobre el tema "Revenue management"
Specht, Dieter y Christian M. F. Gruß. "Revenue Management". ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb 100, n.º 4 (28 de abril de 2005): 192–96. http://dx.doi.org/10.3139/104.100886.
Texto completoYeoman, Ian. "Revenue management". Journal of Revenue and Pricing Management 19, n.º 6 (16 de noviembre de 2020): 365. http://dx.doi.org/10.1057/s41272-020-00267-x.
Texto completoKimms, A. y R. Klein. "Revenue management". OR Spectrum 29, n.º 1 (1 de septiembre de 2006): 1–3. http://dx.doi.org/10.1007/s00291-006-0042-7.
Texto completoPinchuk, S. "Revenue management does far more than manage revenues". Journal of Revenue and Pricing Management 1, n.º 3 (octubre de 2002): 283–85. http://dx.doi.org/10.1057/palgrave.rpm.5170031.
Texto completoDunleavy, Hugh y Dieter Westermann. "Future of Revenue Management: Future of airline revenue management". Journal of Revenue and Pricing Management 3, n.º 4 (enero de 2005): 380–83. http://dx.doi.org/10.1057/palgrave.rpm.5170122.
Texto completoStubben, Stephen R. "Discretionary Revenues as a Measure of Earnings Management". Accounting Review 85, n.º 2 (1 de marzo de 2010): 695–717. http://dx.doi.org/10.2308/accr.2010.85.2.695.
Texto completoZha Giedt, Jenny. "Modelling Receivables and Deferred Revenues to Detect Revenue Management". Abacus 54, n.º 2 (junio de 2018): 181–209. http://dx.doi.org/10.1111/abac.12119.
Texto completoDugar-Zhabon, R. S. y E. V. Zemlyakov. "ENTERPRISE REVENUE MANAGEMENT". Modern Technologies and Scientific and Technological Progress 1, n.º 1 (12 de abril de 2019): 315–16. http://dx.doi.org/10.36629/2686-9896/2019-1-1-315-316.
Texto completoKimes, Sheryl E., Richard B. Chase, Summee Choi, Philip Y. Lee y Elizabeth N. Ngonzi. "Restaurant Revenue Management". Cornell Hotel and Restaurant Administration Quarterly 39, n.º 3 (junio de 1998): 32–39. http://dx.doi.org/10.1177/001088049803900308.
Texto completoBertsimas, Dimitris y Romy Shioda. "Restaurant Revenue Management". Operations Research 51, n.º 3 (junio de 2003): 472–86. http://dx.doi.org/10.1287/opre.51.3.472.14956.
Texto completoTesis sobre el tema "Revenue management"
Shioda, Romy 1977. "Restaurant revenue management". Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/28250.
Texto completoIncludes bibliographical references (p. 59-60).
We develop two classes of optimization models in order to maximize revenue in a restaurant, while controlling average waiting time as well as perceived fairness, that may violate the first-come-first-serve (FCFS) rule. In the first class of models, we use integer programming, stochastic programming and approximate dynamic programming methods to decide dynamically when, if at all, to seat an incoming party during the day of operation of a restaurant that does not accept reservations. In a computational study with simulated data, we show that optimization based methods enhance revenle relative to the industry practice of FCFS by 0.11% to 2.22% for low load factors, by 0.16% to 2.96% for medium load factors, and by 7.65% to 13.13% for high load factors, without increasing and occasionally decreasing waiting times compared to FCFS. The second class of models addresses reservations. We propose a two step procedure: use a stochastic gradient algorithm to decide a priori how many reservations to accept for a future time and then use approximate dynamic programming methods to decide dynamically when, if at all, to seat an incoming party during the day of operation. In a computational study involving real data from an Atlanta restaurant, the reservation model improves revenue relative to FCFS by 3.5% for low load factors and 7.3% for high load factors.
by Romy Shioda.
S.M.
Ciocan, Dragos Florin. "High dimensional revenue management". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/108211.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 149-153).
We present potential solutions to several problems that arise in making revenue management (RM) practical for online advertising and related modern applications. Principally, RM solutions for these problems must contend with (i) highly volatile demand processes that are hard to forecast, and (ii) massive scale that makes even basic optimization problems challenging. Our solutions to these problems are interesting in their own right in the areas of stochastic optimization, high dimensional learning and distributed optimization. In the first part of the thesis, we propose a model predictive control approach to combat volatile demand. This approach is conceptually simple, uses available demand data in a natural way, and, most importantly, can be shown to generate significant revenue advantages on real-world data from ad networks. Under mild restrictions, we prove that our algorithm achieves uniform relative performance guarantees vis-a-vis a clairvoyant in the face of arbitrary volatility, while simultaneously being optimal in the event that volatility is negligible. This is the first result of its kind for model predictive control. While our approach above is effective at hedging demand shocks that occur over "large" time horizons, it relies on the ability to estimate snapshots of the prevailing demand distribution over "short" time horizons. The second part of the thesis deals with learning the extremely high dimensional demand distributions that are typical in display advertising applications. This work exploits the special structure of the display advertising version of the NRM problem to achieve a sample complexity that scales gracefully in the dimensions of the problem. The third part of the thesis focuses on the problem of solving terabyte sized LPs on an hourly basis given a distributed computational infrastructure; solving these massive LPs is the computational primitive required to make our model predictive control approach practical. Here we design a linear optimization algorithm that fits a paradigm for distributed computation referred to as 'Map-Reduce'. An implementation of our solver in a shared memory environment where we can benchmark against solvers such as CPLEX shows that the algorithm outperforms those solvers on the types of LPs that an ad network would have to solve in practice.
by Dragos Florin Ciocan.
Ph. D.
Uichanco, Joline Ann Villaranda. "Data-driven revenue management". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41728.
Texto completoIncludes bibliographical references (p. 125-127).
In this thesis, we consider the classical newsvendor model and various important extensions. We do not assume that the demand distribution is known, rather the only information available is a set of independent samples drawn from the demand distribution. In particular, the variants of the model we consider are: the classical profit-maximization newsvendor model, the risk-averse newsvendor model and the price-setting newsvendor model. If the explicit demand distribution is known, then the exact solutions to these models can be found either analytically or numerically via simulation methods. However, in most real-life settings, the demand distribution is not available, and usually there is only historical demand data from past periods. Thus, data-driven approaches are appealing in solving these problems. In this thesis, we evaluate the theoretical and empirical performance of nonparametric and parametric approaches for solving the variants of the newsvendor model assuming partial information on the distribution. For the classical profit-maximization newsvendor model and the risk-averse newsvendor model we describe general non-parametric approaches that do not make any prior assumption on the true demand distribution. We extend and significantly improve previous theoretical bounds on the number of samples required to guarantee with high probability that the data-driven approach provides a near-optimal solution. By near-optimal we mean that the approximate solution performs arbitrarily close to the optimal solution that is computed with respect to the true demand distributions.
(cont.) For the price-setting newsvendor problem, we analyze a previously proposed simulation-based approach for a linear-additive demand model, and again derive bounds on the number of samples required to ensure that the simulation-based approach provides a near-optimal solution. We also perform computational experiments to analyze the empirical performance of these data-driven approaches.
by Joline Ann Villaranda Uichanco.
S.M.
Githiri, Duncan. "Airline revenue management performance measurement of South African Airways origin-destination revenue management". Thesis, Rhodes University, 2017. http://hdl.handle.net/10962/59188.
Texto completoZickus, Jeffrey S. (Jeffrey Stuart) 1973. "Forecasting for airline network revenue management : revenue and competitive impacts". Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/10103.
Texto completoMartens, Tobias von. "Kundenwertorientiertes Revenue-Management im Dienstleistungsbereich". Wiesbaden : Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-9503-2.
Texto completoDefregger, Florian. "Revenue management for manufacturing companies /". kostenfrei, 2009. http://deposit.d-nb.de/cgi-bin/dokserv?idn=997408154.
Texto completoChen, Lijian. "Stochastic programming in revenue management". Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1150314352.
Texto completoThraves, Cortés-Monroy Charles Mark. "New applications in Revenue Management". Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112085.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references.
Revenue Management (RM) is an area with important advances in theory and practice in the last thirty years. This thesis presents three different new applications in RM with a focus on: the firms' perspective, the government's perspective as a policy maker, and the consumers' perspective (in terms of welfare). In this thesis, we first present a two-part tariff pricing problem faced by a satellite data provider. We estimate unobserved data with parametric density functions in order to generate instances of the problem. We propose a mixed integer programming formulation for pricing. As the problem is hard to solve, we propose heuristics that make use of the MIP formulation together with intrinsic properties of the problem. Furthermore, we contrast this approach with a dynamic programming approach. Both methodologies outperform the current pricing strategy of the satellite provider, even assuming misspecifications in the assumptions made. Subsequently, we study how the government can encourage green technology adoption through a rebate to consumers. We model this setting as a Stackleberg game where firms interact in a price-setting competing newsvendor problem where the government gives a rebate to consumers in the first stage. We show the trade-off between social welfare when the government decides an adoption target instead of a utilitarian objective. Then, we study the impact of competition and demand uncertainty on the three agents involved: firms, government, and consumers. This thesis recognizes the need to measure consumers' welfare for multiple items under demand uncertainty. As a result, this thesis builds on existing theory in order to incorporate demand uncertainty in Consumer Surplus. In many settings, produced quantities might not meet the realized demand at a given market price. This comes as an obstacle in the computation of consumer surplus. To address this, we define the concept of an allocation rule. In addition, we study the impact of uncertainty on consumers for different demand noise (additive and multiplicative) and for various allocation rules.
by Charles Mark Thraves Cortés-Monroy.
Ph. D.
Konig, Matthias. "Risk considerations in revenue management". Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.547943.
Texto completoLibros sobre el tema "Revenue management"
Yeoman, Ian y Una McMahon-Beattie, eds. Revenue Management. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230294776.
Texto completoFandel, Günter y Hans Botho von Portatius, eds. Revenue Management. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1.
Texto completoCramer, Curt y Andreas Thams. Airline Revenue Management. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-33721-6.
Texto completoHelmold, Marc. Total Revenue Management. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29773-1.
Texto completoHelmold, Marc. Total Revenue Management (TRM). Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46985-6.
Texto completoZatta, Danilo. Revenue Management in Manufacturing. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30240-9.
Texto completoSackey, Jo Ann. Petroleum revenue management manual. Accra: Africa Centre for Energy Policy, 2018.
Buscar texto completoTomczak, Torsten y Wibke Heidig, eds. Revenue Management aus der Kundenperspektive. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-00735-5.
Texto completovon Martens, Tobias. Kundenwertorientiertes Revenue Management im Dienstleistungsbereich. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-9503-2.
Texto completoGallego, Guillermo y Huseyin Topaloglu. Revenue Management and Pricing Analytics. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9606-3.
Texto completoCapítulos de libros sobre el tema "Revenue management"
van Ryzin, Garrett J. y Kalyan T. Talluri. "Revenue Management". En International Series in Operations Research & Management Science, 599–659. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/0-306-48058-1_16.
Texto completoMaglaras, Costis. "Revenue Management". En Encyclopedia of Operations Research and Management Science, 1318–30. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_1153.
Texto completoHaugom, Erik. "Revenue management". En Essentials of Pricing Analytics, 178–87. New York: Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9780429345319-11.
Texto completoWalczak, Darius, E. Andrew Boyd y Roxy Cramer. "Revenue Management". En International Series in Operations Research & Management Science, 101–61. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-1608-1_3.
Texto completoNickel, Stefan, Claudius Steinhardt, Hans Schlenker y Wolfgang Burkart. "Revenue Management". En Graduate Texts in Operations Research, 247–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-65481-1_15.
Texto completoGuilding, Chris y Kate Mingjie Ji. "Revenue management". En Accounting Essentials for Hospitality Managers, 323–49. 4a ed. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003183334-16.
Texto completoRichard, Brendan M. y William P. Perry. "Revenue management". En Encyclopedia of Tourism, 797–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-01384-8_302.
Texto completoKimms, Alf y Robert Klein. "Revenue Management im Branchenvergleich". En Revenue Management, 1–30. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_1.
Texto completoCorsten, Hans y Ralf Gössinger. "Kapazitätssteuerung im Revenue Management". En Revenue Management, 31–52. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_2.
Texto completoSpann, Martin, Joachim Klein, Karim Makhlouf y Martin Bernhardt. "Interaktive Preismaßnahmen bei Low-Cost-Fluglinien". En Revenue Management, 53–78. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_3.
Texto completoActas de conferencias sobre el tema "Revenue management"
Pavić, Ivana, Ivana Mamić Sačer y Lajoš Žager. "Challenges, Advantages and Disadvantages in Implementation of Ifrs 15 in Different Industries". En 2nd International Conference on Business, Management and Finance. Acavent, 2019. http://dx.doi.org/10.33422/2nd.icbmf.2019.11.769.
Texto completoTalluri, Kalyan T., Garrett J. van Ryzin, Itir Z. Karaesmen y Gustavo J. Vulcano. "Revenue management: Models and methods". En 2008 Winter Simulation Conference (WSC). IEEE, 2008. http://dx.doi.org/10.1109/wsc.2008.4736064.
Texto completoTalluri, Kalyan T., Itir Z. Karaesmen, Garrett J. van Ryzin y Gustavo J. Vulcano. "Revenue management: Models and methods". En 2009 Winter Simulation Conference - (WSC 2009). IEEE, 2009. http://dx.doi.org/10.1109/wsc.2009.5429322.
Texto completoMazaraki, Anatolii, Margaryta Boiko, Myroslava Bosovska y Mariia Kulyk. "Revenue Management Data Digital Transformation". En 2022 IEEE 4th International Conference on Modern Electrical and Energy System (MEES). IEEE, 2022. http://dx.doi.org/10.1109/mees58014.2022.10005639.
Texto completoZeng, Xian-ke y Yu-qiang Feng. "Sealed-bid multi-attribute reverse auction strategies and revenue analysis". En 2014 International Conference on Management Science and Engineering (ICMSE). IEEE, 2014. http://dx.doi.org/10.1109/icmse.2014.6930229.
Texto completoZulkarnain, Arif, Anita Swantari y Haryo Wicaksono. "Hotel Revenue Management Implementation in Hotel". En International Conference on Tourism, Gastronomy, and Tourist Destination (ICTGTD 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/ictgtd-16.2017.44.
Texto completoManeesophon, Panaratch y Naragain Phumchusri. "OVERBOOKING MODELS FOR HOTEL REVENUE MANAGEMENT". En International Conference on Engineering, Project, and Production Management. Association of Engineering, Project, and Production Management, 2013. http://dx.doi.org/10.32738/ceppm.201310.0074.
Texto completoJie Seah, Samuel Wei, Detlev Remy y Malcolm Yoke Hean Low. "Hotel Revenue Management Simulation System (HRMSS)". En 2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2019. http://dx.doi.org/10.1109/snpd46140.2019.9132976.
Texto completoWei, Wei y Hoffer Lee. "Hotel Revenue Management Theories and Applications". En 2009 International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2009. http://dx.doi.org/10.1109/bife.2009.195.
Texto completo"CONTINUOUS-TIME REVENUE MANAGEMENT IN CARPARKS". En 1st International Conference on Operations Research and Enterprise Systems. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003762800730082.
Texto completoInformes sobre el tema "Revenue management"
Edjekumhene, Ishmael, Maarten Voors, Päivi Lujala, Christa Brunnschweiler, Charles Kofi Owusu y Andy Nyamekye. Impacts of key provisions in Ghana’s Petroleum Revenue Management Act. International Initiative for Impact Evaluation (3ie), marzo de 2019. http://dx.doi.org/10.23846/tw8ie94.
Texto completoWyatt, Alan. Non-Revenue Water: Financial Model for Optimal Management in Developing Countries. Research Triangle Park, NC: RTI Press, junio de 2010. http://dx.doi.org/10.3768/rtipress.2010.mr.0018.1006.
Texto completoMayega, Jova, Ronald Waiswa, Jane Nabuyondo y Milly Nalukwago Isingoma. How Clean Are Our Taxpayer Returns? Data Management in Uganda Revenue Authority. Institute of Development Studies (IDS), abril de 2021. http://dx.doi.org/10.19088/ictd.2021.007.
Texto completoAllen, Julia H., Gregory Crabb, Pamela D. Curtis, Nader Mehravari y David W. White. CERT Resilience Management Model - Mail-Specific Process Areas: Mail Revenue Assurance (Version 1.0). Fort Belvoir, VA: Defense Technical Information Center, agosto de 2014. http://dx.doi.org/10.21236/ada610098.
Texto completoPrice, Roz. Taxation and Public Financial Management of Mining Revenue in the Democratic Republic of Congo. Institute of Development Studies (IDS), octubre de 2021. http://dx.doi.org/10.19088/k4d.2021.144.
Texto completoSeroa da Motta, Ronaldo. Application of Economic Instruments for Environmental Management: From Theoretical to Practical Constraints: Literature Review and Conceptual Notes. Inter-American Development Bank, febrero de 2003. http://dx.doi.org/10.18235/0006683.
Texto completoQuak, Evert-jan. Missing the Forest for the Trees: Ekiti State’s Quest for Forestry Revenue and its Impact on Forest Management. Institute of Development Studies, julio de 2024. http://dx.doi.org/10.19088/ictd.2024.078.
Texto completoQiao, Baoyun, Xiaoqin Fan, Hanif Rahemtulla, Hans van Rijn y Lina Li. Critical Issues for Fiscal Reform in the People’s Republic of China Part 1: Revenue and Expenditure Management. Asian Development Bank, diciembre de 2022. http://dx.doi.org/10.22617/wps220575-2.
Texto completoBeverinotti, Javier, Gustavo Canavire-Bacarreza, María Cecilia Deza y Lyliana Gayoso de Ervin. The Effects of Management Practices on Effective Tax Rates: Evidence from Ecuador. Inter-American Development Bank, agosto de 2021. http://dx.doi.org/10.18235/0003505.
Texto completoOcchiali, Giovanni y Michael Falade. Missing the Forest for the Trees: Ekiti State’s Quest for Forestry Revenue and its Impact on Forest Management. Institute of Development Studies, agosto de 2023. http://dx.doi.org/10.19088/ictd.2023.039.
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