Robust Revenue Management with Limited Information PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Robust Revenue Management with Limited Information PDF full book. Access full book title Robust Revenue Management with Limited Information by Yingjie Lan. Download full books in PDF and EPUB format.
Author: Yingjie Lan
Publisher:
ISBN:
Category : Revenue management
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Yingjie Lan
Publisher:
ISBN:
Category : Revenue management
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Yingjie Lan
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Robust revenue management has received much interest from both academics and practitioners alike. But the airlines have not embraced it for its current inadequacy to address the practical needs for both fine control of conservatism and the adaptability to changing environments. The single-leg capacity control problem is studied to address such needs with limited information on demand uncertainty. A robust optimization framework with the adjustable regret criterion is employed along competitive analysis, which only requires the lower and upper bounds on demand, and comes with a performance guarantee. The analysis finds one extreme scenario for each fare class to formulate a linear program of modest size, providing nested booking limit policies that are proved optimal among online policies. Closed-form solutions to continuous problems are found, and shown theoretically to be less conservative for a larger control parameter, and their effectiveness in adaptability and fine control of conservatism is demonstrated by a simulation study. A robust single-leg capacity control method is available to allow by fine-tune its level of conservatism forcontrolled response to real time key performance indicators or to a more optimistic outlook from textual data analysis or artificial intelligence. If the control parameter is well calibrated, the simulation study shows that the new method can achieve a less than 2% revenue gap from the EMSR policies, and an improvement of up to 3% in average revenue over the absolute regret robust policies.
Author: Ben Vinod
Publisher: Springer Nature
ISBN: 3031143027
Category : Business & Economics
Languages : en
Pages : 412
Get Book Here
Book Description
This book provides an end-to-end view of revenue management in the hospitality industry. The book highlights the origins of hotel reservations systems and revenue management, challenges unique to hotels, revenue management models, new generation retailing, and personalization and steps required to remain competitive in the marketplace. This book is intended for practitioners to understand the basics and have a comprehensive view of the impacts of revenue management on product distribution, reservations, inventory control, including the latest advances in the field of attribute-based room pricing and inventory control. There are several aspects of revenue management that are not covered in books and journal articles such as hotel pricing, hotel fully allocated costs, content parity, impact of Online Travel Agencies on hotels, competitive revenue management and attribute-based room pricing and inventory control which represents the last frontier in hotel revenue management with intelligent retailing. Leveraging emerging technologies, such as Artificial Intelligence and Blockchain and the future state of revenue management, are also addressed.
Author: Kalyan T. Talluri
Publisher: Springer Science & Business Media
ISBN: 0387273913
Category : Business & Economics
Languages : en
Pages : 731
Get Book Here
Book Description
Revenue management (RM) has emerged as one of the most important new business practices in recent times. This book is the first comprehensive reference book to be published in the field of RM. It unifies the field, drawing from industry sources as well as relevant research from disparate disciplines, as well as documenting industry practices and implementation details. Successful hardcover version published in April 2004.
Author: Aurélie Thiele
Publisher:
ISBN:
Category :
Languages : en
Pages : 176
Get Book Here
Book Description
(Cont.) representations of randomness that make few assumptions on the underlying probabilities, remain numerically tractable, incorporate the decision-maker's risk aversion, and provides theoretical insights into the structure of the optimal policy.
Author: Ronald Huefner
Publisher: Business Expert Press
ISBN: 1631570943
Category : Business & Economics
Languages : en
Pages : 237
Get Book Here
Book Description
This book describes the emerging field of revenue management and its applications across a broad spectrum of business activity. It recounts the history and development of revenue management and addresses the analytical tools needed to integrate revenue management into management generally and financial and accounting practice in particular. Revenue Management discusses and assesses various pricing practices and other revenue management techniques. It gives particular attention to the role of capacity analysis and the connection of revenue management to the theory of constraints. While revenue management originated in the service industries, it is now practiced across a broad spectrum of business and not-for-profit organizations. This book will be a useful guide to managers at all levels who wish to give greater consideration to the importance of revenue management in their organizations. The second edition reorganizes the presentation of the subject, adds many new examples, and concludes with a chapter on emerging issues.
Author: I. Yeoman
Publisher: Springer
ISBN: 0230294774
Category : Business & Economics
Languages : en
Pages : 290
Get Book Here
Book Description
Pricing is about deciding your market position whereas revenue management is the strategic and tactical decisions firms take in order to optimize revenues and profits. This book offers insights into research, theories, applications and innovations and how to makes these work in different industries.
Author: Michael J. Dziecichowicz
Publisher:
ISBN: 9781124454269
Category :
Languages : en
Pages : 161
Get Book Here
Book Description
In this dissertation we investigate robust optimization techniques for timing decisions in revenue management and finance. Our main contribution is to develop optimization models for decision times under uncertainty that require little information on the probability distribution, have an adjustable level of conservatism to ensure performance, and allow us to study how time affects the structure of the optimal policy in finance and revenue management problems. The managerial insights gained from our models assist a decision-maker determine his optimal strategy in settings where limited recourse is available when the manager has implemented his decision, such as putting items on sale, increasing plant capacity, or selling a stock.
Author: Michael Becher
Publisher: Springer Science & Business Media
ISBN: 3834996505
Category : Business & Economics
Languages : en
Pages : 185
Get Book Here
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: Dave Roberts
Publisher: Business Expert Press
ISBN: 1637421923
Category : Business & Economics
Languages : en
Pages : 183
Get Book Here
Book Description
This book guides the reader from the building blocks of revenue management, to pricing science and merchandising, and to broader issues of setting objectives in support of a revenue strategy. The discipline is evolving, and that evolution has been accelerated by the COVID-19 pandemic. Leaders in hotel revenue management, and more broadly in sales & marketing, need to understand these changes, and lead and adapt accordingly. This will require a strong foundation in analytics–not just modeling, but also business analytics in support of a holistic strategy. As more of the tactics of revenue management are executed through automation, and powered by machine learning, revenue managers will become more focused on strategy and will need to think about revenue management in the context of marketing, loyalty, and distribution. As the strategy component of the discipline increases, so too must the breadth of knowledge of revenue managers.
