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Relevant bibliographies by topics / Yield Management

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Academic literature on the topic 'Yield Management'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 March 2023

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Journal articles on the topic "Yield Management"

1

Wood, William J. "Yield Management." Industrial Management & Data Systems 85, no. 7/8 (July 1985): 23–25. http://dx.doi.org/10.1108/eb057410.

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Dörnemann, Jörg. "Yield Management." Controlling 12, no. 12 (2000): 615–16. http://dx.doi.org/10.15358/0935-0381-2000-12-615.

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Jones, Peter, and Donna Hamilton. "Yield Management." Cornell Hotel and Restaurant Administration Quarterly 33, no. 1 (February 1992): 89–95. http://dx.doi.org/10.1177/001088049203300126.

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Pannell, David J. "Optimal Yield Management." Agriculture, Ecosystems & Environment 33, no. 1 (November 1990): 91–92. http://dx.doi.org/10.1016/0167-8809(90)90148-7.

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Elkins, Steven B. "Holistic yield management." International Journal of Services Technology and Management 2, no. 1/2 (2001): 46. http://dx.doi.org/10.1504/ijstm.2001.001590.

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Noone, Breffni. "Yield management conference." Progress in Tourism and Hospitality Research 4, no. 3 (September 1998): 293–94. http://dx.doi.org/10.1002/(sici)1099-1603(199809)4:3<293::aid-pth155>3.0.co;2-m.

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Yeoman, I., A. Ingold, and S. E. Kimes. "Yield Management: Editorial Introduction." Journal of the Operational Research Society 50, no. 11 (November 1999): 1083–84. http://dx.doi.org/10.1057/palgrave.jors.2600855.

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Wang, Xiubin, and Fenghuan Wang. "Dynamic network yield management." Transportation Research Part B: Methodological 41, no. 4 (May 2007): 410–25. http://dx.doi.org/10.1016/j.trb.2006.08.001.

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Donaghy, Kevin, Una McMahon, and David McDowell. "Yield management: an overview." International Journal of Hospitality Management 14, no. 2 (June 1995): 139–50. http://dx.doi.org/10.1016/0278-4319(95)00013-3.

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Чхиквадзе, Нелли, and Nelli Chkhikvadze. "HOTEL YIELD MANAGEMENT TECHNOLOGIES." Services in Russia and abroad 7, no. 9 (December 25, 2013): 104–10. http://dx.doi.org/10.12737/1853.

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The article deals with the issue of hotel development stabilization. The author describes Yield Management (Revenue Management) as especially relevant for the hotel industry, identifies the flaws in the current practices, provides details of strategic revenue management tools, dwells on the concept of yield management process and specifies the features requisite for Yield management implementation in the hotel industry.

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Dissertations / Theses on the topic "Yield Management"

1

Maragos, Spyridon A. (Spyriodon Apostolos). "Yield management for the maritime industry." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/12031.

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Mak, Chung Yu. "Revenue impacts of airline yield management." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/26838.

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Sa, Joao. "Reservations forecasting in airline yield management." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/14906.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1987.
MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERO.
Bibliography: leaves 116-117.
by Joao Sa.
M.S.

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Abrahams, Michael (Michael G. ). "Estimating yield curve noise." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118001.

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Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 27-29).
In this paper, I explore methods for estimating noise in the yield curve. I evaluate optimization methods for fitting yield curves using the Nelson-Siegel model where recommendations in the literature remain unclear. I provide open source code on Github including contributions to the QuantLib C++ financial library.
by Michael Abrahams.
S.M. in Management Research

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Schumpf, Etienne. "Preisgerechtigkeit Grenzen des Yield Management bei Airlines /." St. Gallen, 2008. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/05603220001/$FILE/05603220001.pdf.

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Aizikovitz, Jacob. "Yield protection as a risk management strategy." Thesis, Kansas State University, 2018. http://hdl.handle.net/2097/38662.

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Master of Agribusiness
Department of Agricultural Economics
Christine Wilson
Risk management is critical in crop production as the challenges farmers face on a year to year basis are quite variable due to Mother Nature. There are many tools a farmer can utilize to help manage risk such as crop insurance and forward contracting or hedging. In recent years with lower prices, these tools have been more heavily used than they were a few years ago when corn and soybean prices were $8 and $15 per bushel, respectively. Margins in crop production are tight when market prices are low and input prices are high relative to market prices, and due to land cost. In order for farmers to produce greater profit, they must find ways to lower expenses or produce more bushels to increase their revenue. As margins tighten, farmers typically try to lower expenses to be more profitable rather than trying to increase bushels that would ultimately increase their revenue. When farmers try to reduce expenses, agricultural retailers experience lower revenues holding all else equal; distributors have lower revenues because the retailer is not selling as much, and the manufacturers experience lower revenues because the retailer and distributor are not moving the inventory compared to when farmer margins are larger. This thesis examines how yield protection for grain corn can be utilized as a risk management tool for crop production farmers. This thesis explores how increasing bushels and ultimately increasing revenue by protecting the bushels the crop is physically able to produce, can help manage producer risk. This thesis uses yield protection as a tool alongside crop insurance and marketing, rather than as a tool to replace crop insurance or marketing. Data used for yield protection is replicated fungicide, fungicide with an adjuvant, and fungicide with insecticide, that were evaluated against the untreated check over multiple locations and years across the Midwestern United States. Fungicide data were chosen because it is truly the definition of yield protection, protecting the crop against disease. Fungicides are usually the first products cut from a farmer’s crop production program to help reduce expenses and maintain profitability as margins tighten. The results found in this study are consistent with work conducted at Iowa State University. Results exhibited an increase in corn yield, but were not consistently statistical significant across treatments and location. In conclusion, the average yield increase was not enough over multiple years to pay for itself, and it lacked sufficient evidence. Yield protection does not fit a risk management strategy annually. However, yield protection should be utilized when specific thresholds on disease or insects are present to warrant this strategy.

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Cooney, Mackenzie C. "Yield-Curve Momentum." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2244.

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It has been twelve years since the last time the yield curve was inverted. Since 2017, the yield curve has been continuing to flatten and has almost entered an inverted state. The last five recessions have been preceded by the inversion of the yield curve. I examine momentum trading strategy’s ability to outperform during an inverted yield curve state. The yield curve can enter the momentum portfolio strategy through the portfolio’s formation and holding period. I document the increased performance of the momentum strategy’s total portfolio return in an inverted state. These results have implications on the timing a momentum trading strategy might be implemented.

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He, Yuanjie. "Tradeoffs and Random Yield in Supply Chain Management." online version, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1121438339.

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McGill, Jeffrey I. "Optimization and estimation problems in airline yield management." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/30652.

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This thesis addresses problems of optimization and estimation encountered in the process of airline yield management, also called airline seat inventory control. Optimality conditions are given for the problem of setting booking limits for multiple, stochastically independent demand classes that are booked in a nested fashion into a fixed pool of airline seats. These optimality conditions are compared with the approximations given by the EMSR method. Additional conditions are given for two stochastically dependent fare classes, and extensions are made that allow for incorporation of passenger goodwill and upgrades of passengers between fare classes. The model developed for the dependent demand case is also applied to the problem of determining an optimal overbooking limit in a single fare class. Finally, a methodology is developed for using multivariate multiple regression in conjunction with the EM method to estimate the parameters of demand distributions on the basis of historical demand data that have been censored by the presence of booking limits.
Business, Sauder School of
Operations and Logistics (OPLOG), Division of
Graduate

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Hodge, D. J. "Problems of stochastic optimal control and yield management." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604120.

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We present a collection of results in the broad area of stochastic optimization. Our basic model is that of dynamic resource allocation via customer acceptance control. We begin by modelling optimal acceptance to a discrete-capacity service-on-demand system where customers arrive with differing demands and revenues. With strong restrictions on customer types we establish the optimal policy under general arrival processes. With weaker restrictions we establish monotonicity properties under stationary arrivals. We than look at a deterministic demand-curve approach to the same problem; resource allocation over time. We solve the problem of non-overlapping customer demands, for a number of different demand curves. Our main work concerns selling perishable goods via customer acceptance control. We look at the optimal boundary between accepting and declining customers of different types. Existing papers demonstrate this threshold but fail to observe its surprisingly linear nature. We study the problem of finding the best linear threshold and see that, as a heuristic, it performs very well. Our study of linear thresholds educes an interesting problem: sample-path analysis. The problem concerns the evolution of segments of the sample-path in inventory-time space with regions of different downward drift. We succeed in fully characterising the studied sample path segments, finding a remarkable dual use of an interesting identity. In the final chapters, we look at two further problems of stochastic optimization. The first is an innovative approach to modelling future demand, utilizing previous price requests. Using these dynamic demand estimations we demonstrate monotonicity properties of the optimal pricing policy. The second problem is the famous parking problem first introduced by Rényi in the fifties. We study a Markov chain queuing model for the availability of parking spaces. We derive the pay-offs from the class of very natural threshold policies, with respect to an ‘average distance from venue’ objective.

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Books on the topic "Yield Management"

1

D, Rimon, ed. Optimal yield management. Aldershot, England: Avebury, 1988.

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Donaghy, Kevin. Yield management practices. [London]: Cassell, 1997.

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Lindenmeier, Jörg. Yield-Management und Kundenzufriedenheit. Wiesbaden: Deutscher Universitätsverlag, 2005. http://dx.doi.org/10.1007/978-3-322-81194-3.

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Rajagopal. Brand management: Strategy, measurement and yield analysis. New York: Nova Science Publishers, 2007.

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5

Ian, Yeoman, Ingold Anthony, and McMahon-Beattie Una, eds. Yield management: [strategies for the service industries]. 2nd ed. London: Continuum, 2000.

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Sue, Lewry, ed. Front office: Procedures, social skills, yield and management. 2nd ed. Oxford: Butterworth-Heinemann, 1999.

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Burns, J. C. Switchgrass: Establishment, management, yield, nutritive value, and utilization. Raleigh, N.C.]: N.C. Agricultural Research Service, N.C. State University, 2009.

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8

Vinod, Ben. The Evolution of Yield Management in the Airline Industry. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70424-7.

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Brooks, Mary R. Yield management: A phenomonon of the 1980s and 1990s ? Halifax, N.S: Dalhousie University, 1993.

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Gruß, Christian M. F. Revenue-Management-Konzept in der Automobilindustrie: Vorgehenskonzept zur online Neuwagendirektdistribution und Produktionsharmonisierung. Wiesbaden: Gabler, 2008.

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Book chapters on the topic "Yield Management"

1

Hanson, Ward. "Yield Management." In Computational Economics and Finance, 235–50. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2340-5_10.

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Ivanov, Dmitry, Alexander Tsipoulanidis, and Jörn Schönberger. "Yield Management." In Springer Texts in Business and Economics, 625–58. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72331-6_18.

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Issar, Gilad, and Liat Ramati Navon. "Yield, Improvement and Sustaining High Yield." In Management for Professionals, 163–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20699-8_36.

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Dent, David, and Richard H. Binks. "Yield loss." In Insect pest management, 39–66. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781789241051.0039.

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Hagenstein, Frank, and Tim Bangemann. "Yield curve management." In Active Fixed Income and Credit Management, 23–74. London: Palgrave Macmillan UK, 2002. http://dx.doi.org/10.1057/9780230510494_3.

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Pierce, F. J., N. W. Anderson, T. S. Colvin, J. K. Schueller, D. S. Humburg, and N. B. McLaughlin. "Yield Mapping." In The State of Site Specific Management for Agriculture, 211–43. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1997.stateofsitespecific.c11.

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Xylander, Jadwiga K. "Yield Management bei Reiseveranstaltern." In Kapazitätsmanagement bei Reiseveranstaltern, 201–39. Wiesbaden: Deutscher Universitätsverlag, 1985. http://dx.doi.org/10.1007/978-3-322-81632-0_5.

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Lindenmeier, Jörg. "Einleitung." In Yield-Management und Kundenzufriedenheit, 1–3. Wiesbaden: Deutscher Universitätsverlag, 2005. http://dx.doi.org/10.1007/978-3-322-81194-3_1.

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Lindenmeier, Jörg. "Yield-Management — Ein Instrument zur ertragsorientierten Preis- und Kapazitätssteuerung." In Yield-Management und Kundenzufriedenheit, 5–37. Wiesbaden: Deutscher Universitätsverlag, 2005. http://dx.doi.org/10.1007/978-3-322-81194-3_2.

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Lindenmeier, Jörg. "Stand der Forschung und ausstehender Forschungsbedarf." In Yield-Management und Kundenzufriedenheit, 39–76. Wiesbaden: Deutscher Universitätsverlag, 2005. http://dx.doi.org/10.1007/978-3-322-81194-3_3.

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Conference papers on the topic "Yield Management"

1

Meyland, S. J. "Examining safe yield and sustainable yield for groundwater supplies and moving to managed yield as water resource limits become a reality." In WATER RESOURCES MANAGEMENT 2011. Southampton, UK: WIT Press, 2011. http://dx.doi.org/10.2495/wrm110731.

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Whigham, Keith. "Soybean Management for Increased Yield." In Proceedings of the 1995 Integrated Crop Management Conference. Iowa State University, Digital Press, 1997. http://dx.doi.org/10.31274/icm-180809-558.

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Ibsen, Kent B., Mark D. Eickhoff, Z. Mark Ma, Sonya Y. Shaw, Steven D. Carlson, and H. Tomomatsu. "Yield management and reticle defects." In Microlithography '97, edited by Gene E. Fuller. SPIE, 1997. http://dx.doi.org/10.1117/12.275972.

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Gross, David, Katherine Gramling, and Prasad L. Bachiraju. "Fab Fingerprint for Proactive Yield Management : YE: Yield Enhancement/Learning." In 2021 32nd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC). IEEE, 2021. http://dx.doi.org/10.1109/asmc51741.2021.9435686.

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Pond, Andrew D. "Predicting mask yields through the use of a yield model." In 14th Annual BACUS Symposium on Photomask Technology and Management, edited by William L. Brodsky and Gilbert V. Shelden. SPIE, 1994. http://dx.doi.org/10.1117/12.195828.

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Johnson, Gregory M., Andreas Rummel, Matthias Kemmler, Ted Lundquist, and Baohua Nui. "Probing SRAM Signals for Yield Management." In 2019 IEEE 26th International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA). IEEE, 2019. http://dx.doi.org/10.1109/ipfa47161.2019.8984901.

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Biermann, Thomas. "Yield management in the airline industry." In 2007 International Symposium on Logistics and Industrial Informatics. IEEE, 2007. http://dx.doi.org/10.1109/lindi.2007.4343529.

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A, Arunraja, Hareeharan E, Arocamilus A, and Dinesh Perumal S. "E-Farm Management and Yield Prediction." In 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2021. http://dx.doi.org/10.1109/icirca51532.2021.9544759.

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Vitek, T., D. Pachner, and J. Stecha. "Mathematical Models for Hotel Yield Management." In 2007 IEEE International Conference on Control Applications. IEEE, 2007. http://dx.doi.org/10.1109/cca.2007.4389332.

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Vitek, T., D. Pachner, and J. Stecha. "Mathematical Models for Hotel Yield Management." In 2007 IEEE 22nd International Symposium on Intelligent Control. IEEE, 2007. http://dx.doi.org/10.1109/isic.2007.4359776.

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Reports on the topic "Yield Management"

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Helmers, Matt, Xiaobo Zhou, Carl Pederson, and Greg Brenneman. Impact of Drainage Water Management on Crop Yield. Ames: Iowa State University, Digital Repository, 2013. http://dx.doi.org/10.31274/farmprogressreports-180814-1902.

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JOINT CHIEFS OF STAFF WASHINGTON DC. Chemical, Biological, Radiological, Nuclear, and High-Yield Explosives Consequences Management. Fort Belvoir, VA: Defense Technical Information Center, October 2006. http://dx.doi.org/10.21236/ada457099.

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Alexander, Susan J. Sensitivity of TRIM projections to management, harvest, yield, and stocking adjustment assumptions. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1991. http://dx.doi.org/10.2737/pnw-rn-502.

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.

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Mosha, Devotha B., Gilead Mlay, Colin Poulton, and Amrita Saha. Yield and Commercialisation Effects of SRI Interventions in Mngeta, Kilombero District, Tanzania. Institute of Development Studies (IDS), September 2021. http://dx.doi.org/10.19088/apra.2021.025.

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This paper discusses System of Rice Intensification (SRI) interventions and its potential effects on paddy yield and commercialisation in Mngeta division, Kilombero district in Morogoro region, Tanzania. SRI is an innovative agroecological methodology that aims to improve yields and farmers’ profits by creating the most suitable environment for the rice plant to grow. It comprises the precise set of cultivation practices specifically required for careful management of biophysical needs of the rice plant for producing high yields. To assess the effects, we compare between trained and non-trained farmers, as well as between farmers who are members of SRI associations and non-SRI members, on aspects of adoption of SRI interventions, paddy productivity and yields. In turn, the effects of SRI is evaluated in terms of its influence on rice yield per hectare and commercialisation at household level.

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Schott, Linda, Matt Helmers, Carl Pederson, Greg Brenneman, and Myron Rees. Impact of Drainage Water Management on Crop Yield, Drainage Volume, and Nitrate Loss. Ames: Iowa State University, Digital Repository, 2015. http://dx.doi.org/10.31274/farmprogressreports-180814-1492.

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Helmers, Matt, Carl Pederson, Kristina Craft, and Linda Schott. Impact of Drainage Water Management on Crop Yield, Drainage Volume, and Nitrate Loss. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/farmprogressreports-180814-1708.

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Helmers, Matt, Carl Pederson, Kristina TeBockhorst, Greg Brenneman, and Myron Rees. Impact of Drainage Water Management on Crop Yield, Drainage Volume, and Nitrate Loss. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-1939.

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Wasko, Lisa Marie, Gail R. Nonnecke, and Lee Burras. Alternative Weed Management Strategies:Effects on Weed Control and Grapevine Yield in an Established Vineyard. Ames: Iowa State University, Digital Repository, 2010. http://dx.doi.org/10.31274/farmprogressreports-180814-1075.

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Wasko, Lisa Marie, and Gail R. Nonnecke. Alternative Weed Management Strategies Influence Weed Control and Grapevine Yield in an Established Vineyard. Ames: Iowa State University, Digital Repository, 2009. http://dx.doi.org/10.31274/farmprogressreports-180814-2219.

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