The Evolution of e-Commerce in the Airline Industry

1. The Evolution of e-Commerce in the Airline Industry AGIFORS Reservations and Yield Management Study GroupNew York - March 24, 2000 by Richard Ratliff

2. Overview • Introduction • The History of Distribution • The Internet: a New Distribution Channel • Impact of the Internet on Distribution and Planning Systems • Future Outlook

3. Introduction • The travel and transportation industry has a long history of electronic commerce and communications • Developed internal communications infrastructures to coordinate the activities of staff, aircraft and passengers • In the 1950s, business-to-business systems (ARINC and SITA) created to facilitate passenger service across airlines • In the 1960s and 1970s, systems such as Galileo and Sabre developed to consolidate airline product information (schedules, fares and availability) for travel agencies, creating a global electronic marketplace for the airline industry • Airlines have taken advantage of the information and control available in this environment to increase revenues and reduce costs (including development of OR applications)

4. Introduction (cont’d) • Airline industry has a technical and cultural predisposition to e-commerce • Explosive growth of internet and World Wide Web has changed the volume and nature of electronic transactions • Legacy systems have required retooling, new business models have been created • These factors have expanded the actual and potential use of Operations Research within the travel and transportation industry • Review the evolution of e-commerce in the travel and transportation industry • Challenges associated with the current environment • Adapting existing models and new OR opportunities

5. The History of Distribution

6. Relevance • Growth of CRSs and the related use of Operations Research in the airline industry provide a strong foundation to build upon in the newly evolving and expanding world of Internet-based e-commerce • However, the infrastructure that exists today was built up over a 70 year period

7. Early e-Commerce in Air Travel • The pioneering efforts for airline reservations began with the “request and reply” system used in the 1930s • Through the mid-1940s reservations were recorded manually with a pencil on different colored index cards, nicknamed “Tiffany” cards after the lamps with the colored glass shades • Overbooking used to account for misplaced or incorrectly filed reservations (“no recs”) • After World War II airlines began investing in technology

8. How CRSs Originated • In the late 1950s, air travel was on the brink of two key transformations (jet aircraft and IT) • SITA and ARINC were one of the world’s first business-to-business (B-to-B) systems in the 1950s • In 1959, AA and IBM jointly announced plans to develop a Semi-Automated Business Research Environment – better know as the Sabre • CRSs were the first business application of real-time computer technology • Moved from hand-written to electronic passenger information records via automated systems accessible to any agent

9. YM and the Increasing Importance of Airline OR • New,start-up carriers in the 1970’s (e.g. People’s Express and Texas International) • Introduction of supersaver fares • YM fare control began as a defensive measure by majors • Major carriers could utilize the wealth of data available from their reservations systems • Following deregulation, major US carriers were uncompetitive on cost • Saddled with legacy pilot and flight attendant union contractual agreements • Without revenue-enhancing CRS and IT/OR technology, majors would have been unable to respond to competition

10. Connecting to Travel Agencies – Distribution • As passenger volumes increased, travel agents became increasingly concerned about their business • Processes remained paper-intensive and time-consuming, offering slower service than the airlines could • Automation was needed to print itineraries, invoices, tickets and accounting functions • JICRS (Joint CRS initiative) • 1974 - Create one CRS for all airlines (participants included American, Eastern, Trans World, United, Western) • 1975 - Failure to reach agreement; United withdrew • 1976 - Apollo and Sabre installed in travel agencies • 1978 - The US airline industry is deregulated • Actions spawned today’s multi-CRS and GDS environment

11. CRSs are Regulated • Nov. 1984 - several key CRS functions were regulated by the U.S. Civil Aeronautics Board (now known as the US DOT) • Display bias was their primary concern • Timing of fare releases and ATPCO • Competitive advance booking data (e.g. MIDT) made available • No differentiation allowed in booking fees by agent

12. New Capabilities in the 1980’s and 1990’s • Additional functions become available • CRS hosting • Frequent Flyer programs • Hotel, car rental and cruise line availability • Bargain finder (search multiple fares and advise which class is least expensive for flights booked) • Automated yield management • Direct connect availability • E-ticketing • Internet travel sites • Best fare finders (go directly from low fare to flight)

13. 1. Basic Distribution1976 - 1985 (10 years) 2. Advanced Distribution1986 - 1999 (14 years) Supplier | GDS | Agency | Traveler GDS - Relationship Changes 1976-1993 1994 - 1999 Supplier | GDS | Agency | Traveler In 1994, Easy Sabre on Prodigy and AOL In 1997, the Internet arrived.

14. The Internet: a New Distribution Channel

15. Introduction • Today CRSs and GDSs are the main ticket outlet for most airlines • The internet allows airlines and ticket brokers to bypass the travel agent • Customer needs drive the e-design • Legacy systems limit the e-design • Different outlets specialize on different customer groups • Reverse Auctions • Virtual Travel Agents • Airlines Sites • Global Distribution Systems

16. Reverse Auctions Customer View • Web sites like PriceLine.com allow the customer to name a price for a travel product • Customer has to accept any product that matches the price Infrastructure • The broker contacts airlines directly and shops for the best available fare OR Models • Reverse auction models are useful to determine inventory controls in this business model • Help give information on underlying consumer demand

17. The Virtual Travel Agent Customer View • Sites like Sabre’s Travelocity.com and Preview Travel or Microsoft’s Expedia allow customers to pick and choose among different offers online Infrastructure • The sites work on top of existing CRSs and emulate the work of travel agents Data Needs vs. Data Sources • Fares include published, off-tariff and dynamically created • OR methods can be used to build an efficient link between the GDS and customer sites

18. Finding the Best Fares using OR Techniques OR Problem • Optimize among a broad number of flight and fare alternatives and also rank secondary choices Problem Characteristics • Problem space is very large and computational time limited • Side constraints are on the leg and on the path level Special Considerations • Algorithm performance depends on efficient fare enumeration and rule checking • Different types of data have different access times Useful By-Products • Intermediate search results provide the customer with additional information

19. Airline Sites • Many airlines sell tickets directly through their own web sites Customer Pros and Cons • Customers are rewarded by special discounts and offers • But they don't have the opportunity to shop for other airlines Use of OR Methods • Airlines use statistical methods to set up promotional schemes that target special consumer groups • Provide availability processing and best fare search capabilities such as those available in the GDSs

20. Global Distribution Systems Internet • GDSs use the internet to extend their reach What's new? • Travel agents and GDSs provide value added services to compete with new distribution channels (e.g. Virtually There) • Bundling of services and cross-selling OR Applications • Statistical models are used to find cross-selling opportunities • New YM opportunities for more detailed availability control based on customer-specific behavior (creates both real-time and profiling challenges)

21. Impact of the Internet on Distribution and Planning Systems

22. Introduction • Airlines use market analysis and OR based systems to maximize expected revenue • Much of the data that feeds the OR systems are collected by CRSs and GDSs • The advent of a new distribution channel has a major impact on the validity and availability of the data • In some cases the OR models themselves have to be re-engineered to fit the new business problem • Example OR applications follow in the next few slides

23. CRS Simulation • CRSs use a set of rules to determine which flights are presented upon a given request • Screen presence has an extraordinary impact on customer preferences • Simulation models can be used to determine the effects of different strategies on screen presence and market share • Recent innovations such as web outlets and dynamic display rules also need to be considered • Useful for developing e-mail promotions or those via an airline’s web site

24. Passenger Preference Modeling • Passenger preference models became prevalent after industry de-regulation • Schedule design became a very complex problem due to a growing number of airports and increasing demand • Models developed to support schedule design by evaluating schedule profitability • These model take account of market size forecasts, passenger preference parameters, flight schedules, fares and business rules

25. Passenger Preference Modeling (cont’d) • The internet results in a large number of distribution channels with low volume • Preference models have to capture passenger behavior with respect to all types of distribution channels • Smaller booking volumes per outlet increase data variability used to calibrate the customer preference model • Many internet travel sites store customer profiles • May also be used to calibrate passenger preference models • Potential use of “clickstream” data • Captures transactions made by customers on web sites • Similar attempts were made in Sabre by recording agent key strokes during randomly selected sales sessions

26. Passenger Yield Management • Demand and passenger behavior data is necessary to set controls, and CRSs serve as data sources • Advancements in the OR and processing are moving us from separate time-series forecasting and leg-based optimization to econometric models and ODYM • Still mostly batch processes today • Real-time re-forecasting and re-optimization in next five years • Incorporation of still more detailed controls with e-channels (customer-specific availability via on-line access to historical information and rapid profiling of characteristics) • Competitive closures will be less obvious due to reduced use of traditional distribution channels

27. Passenger YM (other impacts) • Internet sales change size and characteristics of demand • Changes in passenger behavior due to internet specific restrictions • May necessitate re-calibration of overbooking and demand forecasts • Hidden shifts in competitive bookings market share due to direct airline web sites • Internet forces a change in pricing strategy (from oligopoly to retail)

28. Cargo YM (B-to-B types) • Medium-term yield management • Various forwarders (bulk customers) submit bids for shipping capacity on airline’s flight network • The airline optimizes the allocation of available capacity to various bids by maximizing the expected revenue over a planning period such as quarter • Cargo routingis useful in determining feasible and profitable routes for satisfying a shipment request • Being extended to the Internet to efficiently integrate the business processes involved with the shipper-forwarder interaction • Can provide dynamic pricing and capacity allocation

29. Cargo YM (B-to-C types) • Short-term yield management to satisfy the ad-hoc shipment demand • Bid prices • Determined by considering the ad-hoc demand, medium-term demand, and available capacity • Used to accept/reject shipment requests over the booking horizon • Improved consumer cargo search engines via the Internet may stimulate additional demand for last-minute shipments and drive large changes from historical booking behavior

30. Future Outlook

31. Regulation of e-Travel Sites? • Will Internet travel websites be regulated? • Neutral, semi-neutral and aligned sites exist • Up-front disclosure of “alignment” is important in semi-neutral sites (e.g. T2 consortium or sites with airline equity investment) • Customers could be misled into thinking that a complete and unbiased range of alternatives will be presented • But even “neutral” infomediaries may be biased • Any system will require an algorithm that determines what to display and the ordering (airlines, mortgages, insurance…) • Volume-based commissions create incentives for bias • Suppliers are paying for essentially two things: 1) to be listed on the website and 2) better presence

32. Regulation of e-Travel Sites? (cont’d) • Bias in e-commerce travel sites is similar to what exists through “brick and mortar” establishments • Booking direct with airlines is biased • Everything equal, agents favor airlines with best commissions • But governments have avoided e-Commerce regulation • Secondary market-driven forces may come to the rescue • Studies of best fare comparisons by consumer advocacy groups (e.g. Consumer Reports) • Authentic “neutrality” may even become a strong selling point among the informediaries

33. Search Robots • Currently, e-commerce on the web is free to the user • Search robots can abuse other sites to shop for free information and re-sell it to the customer • Impacts both the virtual travel agent and airline sites • Increasing sophistication makes robots harder to detect • How can the industry protect itself against this abuse? • Design websites to make it difficult for meta-search engines • “Drilling down” for information several screens deep • More frequent use of member i.d. logins to distinguish genuine users from robots • Usage-based fees?

34. Airline B-to-B Will Grow • Successful alliance implementation requires seamless integration of various business processes and systems • Internet and related technologies provide the communications infrastructure required for the business to business integration • Alliances have a profound impact on the airline OR systems • Need to expanded current models to reflect the collaborative planning, marketing, and operating efforts among the constituent airlines of the alliances • B-to-B vendors will provide central repositories for the data required for alliance related OR systems • Will provide better tools to allow carriers to implementing the policies obtained from the alliance-based OR models • e.g. Sabre / Ariba deal to create Sabre e-Marketplace

35. Impact on the Airline OR Profession • Effective implementation of new e-Commerce business practices requires investigation using OR • Rapid proliferation of e-Commerce practices is putting a strain on the airline OR profession • The OR model life cycles are decreasing • The rewards associated with rapid OR modeling are becoming high but create greater risk of negative impact • The data are more noisy and the business environment is more unstructured than ever before • Ethical and legal ramifications such as “what level of detail data can be used from click-stream data?” • Confidentiality and privacy issues

36. Thanks • Other colleagues at Sabre who assisted in material presented here • Dan Delph • Dirk Guenther • Beju Rao • Barry Smith • Pat Trapp

37. Selected References Gilbert Burck, “’On Line’ in ‘Real Time’”, FORTUNE magazine, April 1964. Copeland, Mason, and McKenney, “Sabre: The Development of Information-Based Competence and Execution of Information-Based Competition” IEEE Annals of the History of Computing, Vol. 17, No. 3, 1995, pg. 30 Lee Davis - UNISYS, “Real Time- The Ultimate O&D”, AGIFORS R&YM, Melbourne, May 1998 Geraghty, Govil, Guarnieri, & Lancaster - Delta Technology, ““Securities Trading Paradigm for Revenue Management”, AGIFORS R&YM, Melbourne, May 1998 Guenther, Rao, Ratliff, and Smith - Sabre, “A Review of the Evolution of e-Commerce and Operations Research in Travel and Transportation”, working paper, March 2000 Max D. Hopper, “Rattling SABRE – New Ways to Compete on Information”, HARVARD BUSINESS REVIEW, No. 90307 May-June 1990. “Startup Muse”, FORBES magazine website (www.forbes.com), Digital Tool feature, August 18, 1999 issue “That’s the Ticket”, WALL STREET JOURNAL, Monday, July 12, 1999, e-Commerce Section, pg. R45

38. Questions?