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Revenue Management Performance Drivers
Transcript of Revenue Management Performance Drivers
Empirical findings are brought up due to the concepts and theories of previous conceptual research
The article examines the nine drivers which contribute to effective RM as well as conducting an empirical study that will test this hypothesis through quantitative research consisting of interviews and surveys. Article Weaknesses Article Strengths However, given the sample size, and our R2 value of 0.15, the survey had a calculated power of 0.96 (Lenth, 2006)for the objective model.
This research finds that both technical and social drivers impact RM performance and suggests that researchers should broaden their perspectives to include the domain of social drivers to better understand how to improve RM performance.
This study helps to contribute to the conceptual research that was previously studied through empirical testing
With the results narrowed down, it was found that more research must be conducted on forecasting methods due to the fact that it had the most impact on RM performance.
As hypothesized, both models show that technical and social skills impact RM performance.
This research contributes to the previous literature by empirically studying individual aspects of RM performance. Studying the RM systems set in place provides standard data against their competition. Main Concepts This study is an answer to Belobaba's study in the article, Future of revenue management: Back to the Future?
He Found that through his research that improvemnet nees to be made in the organizational development of both technical and social processes
He recommended increase in Rm research.
The authors of this article focus on the technical and social RM performance drivers. Specifically, they define nine performance drivers of both technical and social.
The Authors use qualitative research in the form of interviews. Key Research questions of the Article: 1) Which RM practices drive performance?
2) To what extent do there practices drive
performance? Ideas and Thoughts The Authors! Carrie C. Queenan, & Jeff K. Stratman Mark E. Ferguson •Ms. Queenan is currently working for Informs as the newsletter editor for the pricing and revenue Management subdivision.
•Carrie is also an assistant Professor of Operations Management at the University of Notre Dame’s Mendoza College of Business
•Ms. Queenan has many publications one of them being revenue management research in journals such as Production and Operations Management of Interfaces.
•Before earning her PhD at Georgia Tech, Carrie worked in operations management for both Shell and Siemens •Mr. Ferguson is a Wendy Wells Associate Professor of Operations Management in the College of Management at the Georgia Institute of Technology.
•Mark Ferguson is also a Steven A. Denning Professor of Technology and Management.
•Prior to joining the faculty, Mr. Ferguson worked for five years as an engineer as well as an inventory manager at IBM.
•Mr. Ferguson has won best paper awards for two of his own papers at the national Production and Operations Management conferences which has been supported by the National Science Foundations •Jeff K. Stratman is an Associate Professor in the Operations & Information Systems Department at the DavidEccles School of Business, University of Utah.
•Stratman holds a PhD in Business Administration with a concentration in Operations Management from the University of North Carolina at Chapel Hill, and a BSE in Mechanical and Aerospace Engineering from Princeton University.
•He has published in Production and Operations Management, the Journal of Operations Management, Decision Sciences, R&D Management and Supply Chain
& Logistics Journal. Research Biography Biography Biography Nine RM Performance Drivers: Technical Drivers A process of grouping customers based on observed characteristics, behaviors and preferences
This helps to maximize revenue and differentiate customers willingness to pay and preference over time Market Segmentation Forecasting Defined as a process of setting rates to gain optimal revenue from customers At the operational level the main concern is with the overall quality of rather than the step by step procedure used to arrive at the forecast Pricing By definition "to accept or reject an offer to buy; hot to allocate capacity to different segments or channels;when to withhold a product from the market and sell at later points in time".
With this hospitality operations management has incorporated no shows and improving single-leg to network control Capacity Allocation IT system is the hardware, software and people necessary to configure and maintain information systems
Decisions are made on huge amounts of data stored, cleaned and analyzed within the systems Information Technology Nine RM Performance Drivers: Social Drivers A combination of executive commitment and devotion as a cross functional effort to improve RM.
Both show that a firm values the project, initiative or dicipline Aligned Incentives By definition is "The extent to which a firm gives motivation to individuals to choose the best action for the firm".
The Principal-Agent theory The hierarchy in which a firm operates with.
This affects the organizational performance and must fit with the firms strategies, the external competitive environment and many more factors. Organizational Structure Education & Training Organizational
Focus Involves educating employees of the fundamentals and how to work in the environment with the resources available Our Evaluations!!! Hard to Grasp, layout and form of results
Valuable to RM due to depth of analysis
The concepts examined perceptual vs objective The Research was conducted using data collected from individual hotel locations within two different hotel corporations (X&Y)
These companies represent many different brands and chains.
Both companies had been utilizing revenue management for five years when the research was conducted.
A web based survey was sent to revenue managers throughout the companies, a total of 1997 surveys were sent out and 166 came back fully completed. The authors felt that previous research lacked broad examination of technical and social elements of effective RM.
It is thought that the nine performance drivers will ultimately lead to an increase of overall RM performance.
Many RM system users do not grasp the concepts or models which leads to poor decision making. The results from this survey must be examined with care because the main focus was solely on the hotel industry to test the RM hypothesis.
It was acknowledged that the results did not prove that all skills and traits impacted RM performance. Therefore meaning that the study did not show evidence of all skills influencing RM performance.
Although RM in the hotel industry is viable for its tenure, decentralized structure and standardized performance measure the information gathered may not correlate with other industries.
Even though the two hotel companies limited the sampling which helped to reduce irrelevant effects, it also limits the generalization of the two brands. Implications for Practitioners This article thoroughly describes many performance drivers for RM.
We think that this would greatly contribute to the knowledge of a revenue manager because these practices can be implicated to improve RM practices.
Not only this but it also examines which performance drivers best indicate an impact on the performance within the hotel industry.
This article also broadens the concept of RM by examining the empirical studies conducted. Thank you for listening! Object model:
Three main Objective Drivers are
organizational focus, forecasting and market segmentation Perceptual Model shows that six proposed drivers significantly impact performance: pricing, forecasting , IT ,organizational focus , organizational structure , and education and training
Market segmentation, capacity allocation and aligned incentives were not significant predictors of performance.