Market structure and the value of overselling under stochastic demands

In the operations management literature, traditional revenue management focused on pricing and capacity allocation strategies in a two-period model with stochastic demand. Inspired by travel and lodging industries, we examine a two-period model in which each seller may also adopt the overselling strategy to customers whose valuations are differentiated by timing of arrivals. Widely seen as a popular hedge against consumers’ skipping reservations, we extend the stylized approaches of Biyalogorsky, Carmon, Fruchter, and Gerstner (1999) and Lim (2009) to understand the value of overselling under various market structures. We find that contrary to existing literature, the impact of period-two pricing competition from overselling spills over to period-one such that overselling may not always be a (weakly) dominant strategy once unlimited early demand ceases to hold in a duopoly regime. We provide some numerical studies on the existence of multiple equilibria at the capacity allocation level which actually lead to different selling strategies at the equilibrium despite identical market conditions and firm characteristics

Business models for Energy Storage Systems

Recent commitments to reduce greenhouse gas emissions in the electricity industry associated with the electrification of segments of heat and transport sectors pose significant challenges of unprecedented proportions . The unique features of Energy Storage Systems (ESS) coupled with the flexibility of providing services to multiple sectors of the electricity industry, make it a key technology to tackle current and upcoming challenges in the electricity industry. Although ESS have the potential to support future system integration with large amounts of renewable generation, the potential value that ESS brings to stakeholder s and its associated economics are not well understood to date. In addition, further research is needed on its business model in various markets and system conditions, in particular in the value associated with each service or set of services. In this context, the conducted research has addressed ESS operational aspects when considering a multiple services portfolio provided to various stakeholders and sensitive to market and system conditions. New ESS operational frameworks together with a computationally efficient modelling framework are proposed for a better understanding of ESS business models. The novelty introduced with this work is associated with a multiple service business model for ESS which considers services to distribution network operators, system operators, low capacity value generation and participation in the energy market. In addition, the economic aspects of ESS considering various operating policies for maximum revenue is also investigated and enhances the understanding of ESS to develop appropriate market mechanisms and allow efficient deployment of ESS in the electricity industry.Open Acces

Dynamic Pricing with Variable Order Sizes for a Model with Constant Demand Elasticity

We investigate a dynamic pricing model under constant demand elasticity which accounts for customers ordering multiple items at once. A closed form expression for the optimal expected revenue and pricing strategy is found. Models with the same demand are shown to have asymptotically similar expected revenue and pricing strategies, even if the order size distributions of the customers are different. Surprisingly, the relative difference between comparable models is shown to be independent of time and the magnitude of demand. Variations of the model are considered, including different low inventory behavior as well as the effect of advertising. Some numerical simulations are presented to provide better insight on the model

An investigation into customer perception and behaviour through social media research – an empirical study of the United Airline overbooking crisis

Airlines have been adopting yield management to optimise the perishable seat control problem and overbooking is a common strategy. This study outlines the connections between yield management, crises, and crisis communication. Using big data captured on a social media platform, this study aims to combine traditional yield management with emerging social big data analytics. As part of this, we use the twitter data on the 2017 United Airline (UA) to analyse the overbooking crisis. Our findings shed light on the importance of a more effective orchestration of yield management to avoid the escalation of crises during crisis communication phases

Cargo revenue management for space logistics

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 79-82).This thesis covers the development of a framework for the application of revenue management, specifically capacity control, to space logistics for use in the optimization of mission cargo allocations, which in turn affect duration, infrastructure availability, and forward logistics. Two capacity control algorithms were developed; the first is based on partitioning of Monte Carlo samples while the second is based on bid-pricing with high-frequency price adjustments. The algorithms were implemented in Java as a plugin module to SpaceNet 2.0, an existing integrated modeling and simulation tool for space logistics. The module was tested on a lunar exploration concept which emphasizes global exploration of the Moon using mobile infrastructure. Results suggest that revenue management produces better capacity allocations in shorter duration missions, while producing nominal capacity allocations (i.e. those in the deterministic case) in the long run.by Nii A. Armar.S.M

Strategic Activity and Financial Performance of U.S. Rural Hospitals: A National Study, 1983 to 1988

This study examines the effect of 13 strategic management activities on the financial performance of a national sample of 797 U.S. rural hospitals during the period of 1983-1988. Controlled for environment-market, geographic-region, and hospital-related variables, the results show almost no measurable effect of strategic adoption on rural hospital profitability and liquidity. Where statistically significant relationships existed, they were more often negative than positive. These findings were not expected; it was hypothesized that positive effects across a broad range of strategies would emerge, other things being equal. Discussed are possible explanations for these findings as well as their implication for a rural health policy relying on individual rural hospital strategic adaptation to environmental change.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72301/1/j.1748-0361.1994.tb00225.x.pd

Train planning in a fragmented railway: a British perspective

Train Planning (also known as railway scheduling) is an area of substantial importance to the success of any railway. Through train planning, railway managers aim to meet the needs of customers whilst using as low a level of resources (infrastructure, rolling stock and staff) as possible. Efficient and effective train planning is essential to get the best possible performance out of a railway network. The author of this thesis aims, firstly, to analyse the processes which are used to develop train plans and the extent to which they meet the objectives that they might be expected to meet and, secondly, to investigate selected new and innovative software approaches that might make a material difference to the effectiveness and/or efficiency of train planning processes. These aims are delivered using a range of primarily qualitative research methods, including literature reviews, interviews, participant observation and case studies, to understand these processes and software. Conclusions regarding train planning processes include how the complexity of these processes hinders their effectiveness, the negative impact of the privatisation of British Rail on these processes and the conflicting nature of objectives for train planning in the privatised railway. Train planning software is found not to adequately support train planners in meeting the objectives they are set. The potential for timetable generation using heuristics and for timetable performance simulation to improve the effectiveness of train planning are discussed and recommendations made for further research and development to address the limitations of the software currently available