Dynamic Control Mechanisms for Revenue Management with Flexible Products PDF Download
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Author: Anita Petrick
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Revenue management with flexible products has experienced a growing interest in the academic literature within the last few years. Flexible products allow supply-side substitution between resources and can therefore help to maximize overall revenue as well as capacity utilization in markets with highly uncertain demand. This paper addresses the question of how the mathematical models which have been developed for capacity control with flexible products should be used over time to exploit the substitution opportunities, while keeping practical applicability in mind. Several dynamic control mechanisms are proposed, each of which makes use of the flexibility to a different extent. A comprehensive computational study shows the potential of the different approaches by revealing their strengths and weaknesses.
Author: Anita Petrick
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Revenue management with flexible products has experienced a growing interest in the academic literature within the last few years. Flexible products allow supply-side substitution between resources and can therefore help to maximize overall revenue as well as capacity utilization in markets with highly uncertain demand. This paper addresses the question of how the mathematical models which have been developed for capacity control with flexible products should be used over time to exploit the substitution opportunities, while keeping practical applicability in mind. Several dynamic control mechanisms are proposed, each of which makes use of the flexibility to a different extent. A comprehensive computational study shows the potential of the different approaches by revealing their strengths and weaknesses.
Author: Michael Müller-Bungart
Publisher: Springer Science & Business Media
ISBN: 3540723153
Category : Business & Economics
Languages : en
Pages : 307
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Book Description
This book analyzes revenue management (RM) problems with flexible products and RM in broadcasting companies. It presents models and methods that explicitly take the implications of flexibility into account. In addition, it contains descriptions of algorithms to generate stochastic demand data streams for general RM problems. To help readers with their own simulation studies, it provides an implementation as a Microsoft Windows executable file.
Author:
Publisher: University of Bamberg Press
ISBN: 3863090217
Category :
Languages : en
Pages : 1140
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Book Description
Author: Michael Becher
Publisher: Springer Science & Business Media
ISBN: 3834996505
Category : Business & Economics
Languages : en
Pages : 185
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Book Description
Michael Becher develops a concept for an integrated capacity and price control in revenue management. His concept is based on fuzzy expert controllers and complies with the defined business and application requirements.
Author: Julia Pahl
Publisher: Springer
ISBN: 3642215270
Category : Computers
Languages : en
Pages : 684
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Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Network Optimization, INOC 2011, held in Hamburg, Germany, in June 2011. The 65 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers highlight recent developments in network optimization and are organized in the following topical sections: theoretical problems, uncertainty, graph theory and network design; network flows; routing and transportation; and further optimization problems and applications (energy oriented network design, telecom applications, location, maritime shipping, and graph theory).
Author: Tao Huang
Publisher:
ISBN:
Category : Revenue management
Languages : en
Pages : 204
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Book Description
Author: Dmitry Ivanov
Publisher: Springer Nature
ISBN: 3030723313
Category : Business & Economics
Languages : en
Pages : 673
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Book Description
The third edition of this textbook comprehensively discusses global supply chain and operations management (SCOM), combining value creation networks and interacting processes. It focuses on operational roles within networks and presents the quantitative and organizational methods needed to plan and control the material, information, and financial flows in supply chains. Each chapter begins with an introductory case study, while numerous examples from various industries and services help to illustrate the key concepts. The book explains how to design operations and supply networks and how to incorporate suppliers and customers. It examines how to balance supply and demand, a core aspect of tactical planning, before turning to the allocation of resources to meet customer needs. In addition, the book presents state-of-the-art research reflecting the lessons learned from the COVID-19 pandemic, and emerging, fast-paced developments in the digitalization of supply chain and operations management. Providing readers with a working knowledge of global supply chain and operations management, with a focus on bridging the gap between theory and practice, this textbook can be used in core, specialized, and advanced classes alike. It is intended for a broad range of students and professionals in supply chain and operations management.
Author: Nadja Bauer
Publisher: Springer Nature
ISBN: 3030251470
Category : Computers
Languages : en
Pages : 336
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Book Description
This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
Author: Zizhuo Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
One of the major challenges in revenue management problems is the uncertainty of the customer's demand. In many practical problems, the decision maker can only observe realized demand over time, but not the underlying demand. Methods to incorporate demand learning into revenue management problems remain an important topic both for academic researchers and practitioners. In this dissertation, we propose a class of dynamic learning mechanisms for a broad range of revenue management problems. Unlike methods that attempt to deduce customer demand before the selling season, our proposed mechanisms enable a decision maker to learn the demand "on the fly''. That is, they integrate learning and doing into a concurrent procedure and both learning and doing are accomplished during the selling season. Furthermore, we show that our mechanisms are 1) Robust, that is, our mechanisms work well for a wide range of underlying demand structures and do not need to know the structure beforehand; 2) Dynamic, that is, our mechanisms take advantages of increasing sales data as selling season moves forward and update the demand information along the process and 3) Optimal, that is, our mechanisms achieve near-optimal revenues, as compared to a clairvoyant who has complete knowledge of the demand information beforehand. By comparing with different learning mechanisms, we claim that "dynamic learning" is essential for our mechanism to achieve improved performance and the above features. We consider two widely-used models in this dissertation, a customer bidding model and a posted-price model. For each model, we describe a dynamic learning mechanism with theoretical guarantee of near-optimal performance. Although different models entail different mechanism details and different analysis tools, we show that a common denominator is that the improvement of our mechanisms comes from one unique feature: dynamic learning. We also present numerical tests for both models from which the performance of our mechanisms is verified. We believe that the dynamic learning mechanisms presented in this dissertation have important implications for both researchers and practitioners.
Author: Tadashi Imaizumi
Publisher: Springer Nature
ISBN: 9811527008
Category : Social Science
Languages : en
Pages : 472
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Book Description
This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.
