Transcript No Slide Title

The Evolution of e-Commerce in the Airline Industry
AGIFORS Reservations and Yield Management Study Group
New York - March 24, 2000 by Richard Ratliff
Overview
 Introduction
 The History of Distribution
 The Internet: a New Distribution Channel
 Impact of the Internet on Distribution and
Planning Systems
 Future Outlook
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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)
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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
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The History of Distribution
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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
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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
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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
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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
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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
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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
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New Capabilities in the
1980’s and 1990’s
 Additional functions become available
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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)
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GDS - Relationship Changes
1976-1993
1. Basic Distribution
1976 - 1985 (10 years)
2. Advanced Distribution
1986 - 1999 (14 years)
In 1994, Easy Sabre on
Prodigy and AOL
In 1997, the Internet
arrived.
1994 - 1999
Supplier
Supplier
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GDS
GDS
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Agency
Agency
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Traveler
|
Traveler
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The Internet: a New Distribution
Channel
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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
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Reverse Auctions
Virtual Travel Agents
Airlines Sites
Global Distribution Systems
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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
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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
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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
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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
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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)
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Impact of the Internet on
Distribution and Planning Systems
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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 reengineered to fit the new business problem
 Example OR applications follow in the next few slides
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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
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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
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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
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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 legbased 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
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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)
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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 routing is 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
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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 lastminute shipments and drive large changes from
historical booking behavior
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Future Outlook
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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 semineutral 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
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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
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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?
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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
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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
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Thanks
 Other colleagues at Sabre who assisted in
material presented here
 Dan Delph
 Dirk Guenther
 Beju Rao
 Barry Smith
 Pat Trapp
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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
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Questions?
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