Airline ticket price fluctuations and revenue management strategies

Airline ticket price fluctuations and revenue management strategies A key element of a profitable global aviation industry is the ability of airlines to generate a sufficient amount of revenue from passengers on each route. Airlines rely on a team of revenue management analysts to ensure that every seat sold is done so at the maximum price possible. When revenue management get it wrong, the airline will either not fill enough seats due to high prices or fill too many seats at low prices. Both scenarios will result in lost revenue and lower profits. For this reason airlines incorporate price discrimination whereby similar seats are sold at different prices depending of passenger demand and time of booking. The general perception amongst passengers is that the earlier you buy the ticket the cheaper it is. However, this is not always the case and dependant on the revenue strategy implemented by the airline. As part of this assignment, you are to collect airline ticket price data for a number of commercial routes on a daily basis. It is important that you correctly chose the route, airlines and flights for the data you plan to collect. Poor planning will result in poor data making it difficult for you to get a high mark. The following is the specification for data you need to collect: • Select: – two short-haul leisure destination routes – two short-haul business destination routes • Select one-way, direct flights only. • Select a departure date in late November. • Select a mix of low-cost and full-service airlines for each route. • Record the lowest available ticket price for a minimum of two airlines per route. • Aim to record prices daily for at least 40 days before the departure date. • Identify the aircraft type operating the route to estimate the seat capacity. To be able to compare the prices and trends between airlines, you should: • Select flights departing and arriving at the same airport. • Select similar departure and arrival times. • Record ticket prices at a similar time of day. • Only use the airlines own websites to obtain prices. While price comparison sites such as Skyscanner, Expedia, Ebookers etc. can be used to plan the data you intend to collect, do not use these sites for collecting the daily ticket prices. • Delete internet cookies before requesting prices. • Be careful not to choose two airlines operating a codeshare. Typical leisure destinations are: – Spanish and Greek islands, – the Mediterranean coast – the North African coast, – Las Vegas, – Florida, – Caribbean Islands, – Indian Ocean Islands – South Asia (Thailand, Malaysia, Bali etc) Typical business routes are: – Major European financial cities – Some North American cities such as New York, Washington, Seattle, Montreal, Toronto – Some Asian cities such as Hong Kong, Tokyo, Singapore, Seoul, Beijing, Shanghai. A data collection template spreadsheet is available in the module on Blackboard. You are strongly advised to check the flights you have selected with the module tutor, before embarking on the daily collection of prices. Once you have collected all the data, you need to write up a 2000 word report of your findings. Your report should: (i) Explain which routes, airlines and flights you chose to collect data for and the reasons for doing so. Identify any situations where the data collected was outside the norm such as sold out flights etc. (ii) Present the data using clear and appropriate graphical methods. Price fluctuations with time should be clear. (iii) Apply data analysis to compare and discuss the ticket price trends between different routes and airlines and suggest possible reasons for the trends. Can you identify the optimum time to buy a ticket? Is there a day of the week when prices are the cheapest? Can you identify specific revenue management strategies implemented by the airlines? (iv) As an additional activity you should collect ticket price data for a single route, served by an airline for multiple ticket numbers increased incrementally. You should then record the ticket price per ticket and comment on the results observed. The submitted assignment should be structured as a technical report and must be a maximum of 2000 words. You should include a word count at the end of your report. You may use diagrams wherever appropriate to clarify your explanations. You should keep a spreadsheet of the data you have collected but you do not need to include it in the report. You may find it useful to read airline revenue management books and journal articles to explain your data. Please remember to reference any sources used.

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