Airline Terminology and
Measures
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Airline Demand
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RPM = Revenue Passenger Mile
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Yield = Revenue per RPM
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ASM = Available Seat Mile
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One aircraft seat flown 1 mile
Unit Cost = Operating Expense per ASM (“CASM”)
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Average fare paid by passengers, per mile flown
Airline Supply
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One paying passenger transported 1 mile
Average operating cost per unit of output
Average Load Factor = RPM / ASM
Unit Revenue = Revenue/ASM (“RASM”)
Example: Airline Measures
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A 200-seat aircraft flies 1000 miles, with 140
passengers:
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Assume total revenue = $16,000; total operating
expense = $15,000:
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RPM = 140 passengers X 1000 miles = 140,000
ASM = 200 seats X 1000 miles = 200,000
Yield = $16,000 / 140,000 RPM = $0.114 per RPM
Unit Cost = $15,000 / 200,000 ASM = $0.075 per ASM
Unit Revenue = $16,000 / 200,000 ASM = $0.080 per ASM
Average Load Factor = RPM / ASM
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ALF = 140,000 / 200,000 = 70.0%
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For single flight, also defined as passengers / seats
US Airline Traffic 2001-2004
US Airline Capacity 2001-2004
US Airline Losses Almost $40
Billion From 2001 to 2005
Load Factors are at Record Levels
Airline Supply Terminology
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Flight Leg (or “flight sector” or “flight segment”)
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Flight
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One or more flight legs operated consecutively by a single aircraft
(usually) and labeled with a single flight number (usually)
NW945 is a two-leg flight BOS-MSP-SEA operated with a B757
Route
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Non-stop operation of an aircraft between A and B, with associated
departure and arrival times
Consecutive links in a network served by single flight numbers
NW operates 2 flights per day on one-stop route BOS-MSP-SEA
Passenger Paths or Itineraries
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Combination of flight legs chosen by passengers in an O-D market
to complete a journey (e.g., BOS-SEA via connection at DTW)
Airline Planning Decisions
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FLEET PLANNING
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ROUTE EVALUATION
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How often, at what times and with which aircraft on each
route?
PRICING
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What network structure to operate and city-pairs to be
served?
SCHEDULE DEVELOPMENT
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What aircraft to acquire/retire, when and how many?
What products, fares and restrictions for each O-D market?
REVENUE MANAGEMENT
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How many bookings to accept, by type of fare, to maximize
revenue on each flight and over the network?
FLEET PLANNING
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Long-term strategic decision for an airline:
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Affects financial position, operating costs, and
especially the ability to serve specific routes.
Huge capital investment with lasting impacts:
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US $40-60 million for narrow-body aircraft
$200+ million for wide-body long-range 747-400
Depreciation impacts last 10-15 years
Some aircraft have been operated economically
for 30+ years
ROUTE PLANNING
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Given a fleet, selection of routes to be flown
Economic considerations dominate :
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Forecasts of potential demand and revenues
Airline’s market share of total forecast demand
Opportunity cost of using aircraft on this route
Network implications for costs, revenues and “profit”
Practical considerations just as important:
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Aircraft with adequate range and proper capacity
Performance and operating cost characteristics
Operational constraints and aircraft/crew rotation issues
Regulations, bilaterals, and limited airport slots
Route Profitability Models
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OR models designed to perform such route
evaluations, used by some airlines:
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Demand, cost and revenue forecasts for specific route,
perhaps for multiple years into the future
Select routes to maximize profits, given set of candidate
routes and estimated demands
Subject to fleet and capacity constraints
Assessments should be based on total network impacts
Built on highly simplified assumptions:
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Profit estimates entirely dependent on accuracy of demand
estimates and market share models
Ability to integrate competitive effects is limited
SCHEDULE DEVELOPMENT
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Involves several interrelated decisions, which to date have not
been fully integrated:
Frequency Planning
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Timetable Development
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Flight departure and arrival times, including connections at airline
hubs
Fleet Assignment
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Number of departures to be offered on each route, non-stop versus
multi-stop
Aircraft type for each flight, based on demand and operating cost
estimates
Aircraft Rotation Planning
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Links consecutive flights to ensure balanced aircraft flows on the
network.
OR Models in Airline
Scheduling
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Airline scheduling problems have received
most operations research (OR) attention
Use of schedule optimization models has led
to impressive profit gains in:
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Aircraft rotations; fleet assignment
Crew rotations; maintenance scheduling
Current focus is on “solving” larger problems:
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Timetable optimization is still not feasible--too
many dimensions and constraints
PRICING DECISIONS
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“Differential pricing” by airlines is universal:
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Classes of service (First, Business, Coach)
Different “fare products” within the coach cabin, with
different restrictions, at different prices
Virtually every airline in the world offers multiple price points
(even low-fare carriers with “simplified” fare structures)
Economic trade-off in pricing decisions:
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Stimulation of new demand; increased market share for
airline
Diversion of existing demand to lower fares; reduced
revenues
Recent pricing difficulties of network airlines due in part to
greater diversion of revenues than stimulation of demand
Pricing Models
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Pricing theory has not kept pace with airline
competitive pricing practices
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Some airlines are now implementing “Pricing Decision
Support Systems”
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Difficult to estimate price elasticity, willingness to pay,
potential for stimulation and diversion
No practical tools for airlines to determine “optimal” prices
Primarily monitoring of price changes
Little competitive modeling of pricing impacts
Dominant practice is to match low fares to fill planes
and retain market share.
REVENUE MANAGEMENT
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Inventory control for airlines
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Given a scheduled flight, capacity and prices, how
many bookings to accept by fare type
Objective is to maximize revenue --fill each seat
with highest possible revenue
Computerized RM systems used by airlines to
increase revenues by 4-6%:
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Generate forecasts by flight date and fare class
Optimize seat allocations to different fare classes
Overbooking models to minimize costs of denied
boarding and “spoilage”
Example of Third Generation RM System
Basic Airline Profit Model
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Operating Profit = Revenues -Operating Expense
Operating Profit = RPM x Yield -ASM x Unit Cost
The use of individual terms in this profit equation to
measure airline success can be misleading:
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High Yield is not desirable if ALF is too low; in general, Yield
is a poor indicator of airline profitability
Low Unit Cost is of little value if Revenues are weak
Even ALF on its own tells us little about profitability, as high
ALF could be the result of extremely low fares (yields)
Airline profit maximizing strategy is to increase
revenues, decrease costs, but the above terms are
interrelated.
Yield vs. Distance -- Top 50 O-D Markets
Air Travel Markets
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City-pair market
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Airport-pair market
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Demand for air travel between Boston and Chicago
City-pair demand disaggregated to different airports BOSO’Hare and BOS-Midway
Parallel air travel markets
Region-pair market
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Demand between entire Boston metropolitan area and
Chicago metropolitan area
Additional parallel airport-pair markets including Providence
and Manchester to O’Hare and Midway
Origin-Destination Market
Demand
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Air travel demand is defined for an origin-destination market,
not a flight leg in an airline network:
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Number of persons wishing to travel from origin A to destination B
during a given time period (e.g., per day)
Includes both passengers starting their trip at A and those
completing their travel by returning home to B (opposite markets)
Typically, volume of travel measured in one-way passenger trips
between A and B, perhaps summed over both directions
Airline networks create complications for analysis of market
demand and supply:
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Not all A-B passengers will fly on non-stop flights from A to B, as
some will choose one-stop or connecting paths
Any single non-stop flight leg A-B can also serve many other O-D
markets, as part of connecting or multi-stop paths
Dichotomy of Demand and
Supply
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Inherent inability to directly compare demand and supply at the
“market” level
Demand is generated by O-D market, while supply is provided
as a set of flight leg departures over a network of operations
One flight leg provides joint supply of seats to many O-D
markets
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Number of seats on the flight is not the “supply” to a single market
Not possible (or realistic) to determine supply of seats to each O-D
Single O-D market served by many competing airline paths
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Tabulation of total O-D market traffic requires detailed ticket
coupon analysis
Implications for Analysis
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Dichotomy of airline demand and supply complicates many
facets of airline economic analysis
Difficult, in theory, to answer seemingly “simple” economic
questions, for example:
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Because we cannot quantify “supply” to an individual O-D market,
we cannot determine if the market is in “equilibrium”
Cannot determine if the airline’s service to that O-D market is
“profitable”, or whether fares are “too high” or “too low”
Serious difficulties in proving predatory pricing against low-fare
new entrants, given joint supply of seats to multiple O-D markets
and inability to isolate costs of serving each O-D market
In practice, assumptions about cost and revenue allocation are
required:
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Estimates of flight and/or route profitability are open to question
Demand Models
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Demand models are mathematical representations of
the relationship between demand and explanatory
variables:
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Based on our assumptions of what affects air travel demand
Can be linear (additive) models or non-linear (multiplicative)
Model specification reflects expectations of demand behavior
(e.g., when prices rise, demand should decrease)
A properly estimated demand model allows airlines to
more accurately forecast demand in an O-D market:
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As a function of changes in average fares
Given recent or planned changes to frequency of service
To account for changes in market or economic conditions
Airline Demand
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Demand for carrier flight f of carrier i in OD market j is a
function of:
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Characteristics of flight f
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Characteristics of carrier i
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Flight schedule in market j (frequency, timetable), airport amenities of
carrier, frequent flyer plan attractiveness, etc.
Market characteristics
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Departure time, travel time, expected delay, aircraft type, in-flight
service, etc.
Price
Distance, business travel between two cities, tourism appeal
Characteristics (including price) of all rival products:
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Other flights on carrier i
Flights on other carriers in market j (carrier and flight characteristics)
Competing markets’ products (other airports serving city-pair in j, other
transport modes, etc.)
Total Trip Time from Point A
to B
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Next to price of air travel, most important factor affecting
demand for airline services:
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Access and egress times to/from airports at origin and destination
Pre-departure and post-arrival processing times at each airport
Actual flight times plus connecting times between flights
Schedule displacement or wait times due to inadequate frequency
Total trip time captures impacts of flight frequency, path quality
relative to other carriers, other modes.
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Reduction in total trip time should lead to increase in total air travel
demand in O-D market
Increased frequency and non-stop flights reduce total trip time
Increases in total trip time will lead to reduced demand for air
travel, either to alternative modes or the “no travel” option
Total Trip Time and Frequency
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T = t (fixed) + t (flight) + t (schedule displacement)
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Fixed time elements include access and egress, airport processing
Flight time includes aircraft “block” times plus connecting times
Schedule displacement = (K hours / frequency), meaning it
decreases with increases in frequency of departures
This model is useful in explaining why:
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Non-stop flights are preferred to connections (lower flight times)
More frequent service increases travel demand (lower schedule
displacement times)
Frequency is more important in short-haul markets (schedule
displacement is a much larger proportion of total T)
Many connecting departures through a hub might be better than 1
non-stop per day (lower total T for the average passenger)
Airline Competition
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Airlines compete for passengers and market share based
on:
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Frequency of service and departure schedule on each route
served
Price charged, relative to other airlines, to the extent that
regulation allows for price competition
Quality of service and products offered --airport and in-flight
service amenities and/or restrictions on discount fare
products
Passengers choose combination of flight schedules, prices
and product quality that minimizes disutility of air travel:
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Each passenger would like to have the best service on a
flight that departs at the most convenient time, for the
lowest price
Market Share / Frequency
Share
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Rule of Thumb: With all else equal, airline market
shares will approximately equal their frequency
shares.
But there is much empirical evidence of an “S-curve”
relationship as shown on the following slide:
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Higher frequency shares are associated with
disproportionately higher market shares
An airline with more frequency captures all passengers
wishing to fly during periods when only it offers a flight, and
shares the demand wishing to depart at times when both
airlines offer flights
Thus, there is a tendency for competing airlines to match
flight frequencies in many non-stop markets, to retain
market share
MS vs. FS “S-Curve” Model
Airline Prices and O-D Markets
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Like air travel demand, airline fares are defined for
an O-D market, not for an airline flight leg:
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Airline prices for travel A-B depend on O-D market demand,
supply and competitive characteristics in that market
No economic theoretical reason for prices in market A-B to
be related to prices A-C, based strictly on distance traveled
Could be that price A-C is actually lower than price A-B
These are different markets with different demand
characteristics, which might just happen to share joint
supply on a flight leg
Dichotomy of airline demand and supply makes
finding an equilibrium between prices and distances
more difficult.
Price Elasticity of Demand
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Inelastic (-0.8) business demand for air travel means less
sensitivity to price changes:
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Elastic (-1.6) leisure demand for air travel means greater
sensitivity to price changes
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10% price increase leads to only 8% demand reduction
Total airline revenues increase, despite price increase
10% price increase causes a 16% demand decrease
Total revenues decrease given price increase, and vice versa
Recent airline pricing practices are explained by price
elasticities:
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Increase fares for inelastic business travelers to increase revenues
Decrease fares for elastic leisure travelers to increase revenues
Time Elasticity of Demand
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Business demand responds more than leisure
demand to reductions in total travel time:
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Leisure demand not nearly as time sensitive:
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Increased frequency of departures is most important way for
an airline to reduce total travel time in the short run
Reduced flight times can also have an impact (e.g., using jet
vs. propeller aircraft)
More non-stop vs. connecting flights will also reduce T
Frequency and path quality not as important as price
But there exists a “saturation frequency” in each
market:
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Point at which additional frequency does not increase
demand
Theoretical Pricing Strategies
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For determining prices to charge in an O-D market, airlines can
utilize one of following economic principles:
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Cost-based pricing
Demand-based pricing
Service-based pricing
In practice, most airline pricing strategies reflect a mix of these
theoretical principles:
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Prices are also highly affected by competition in each O-D market
In the US, severe competition in some markets has led to “pricebased costing”, meaning airlines must reduce costs to be able to
match low-fare competitors and passengers’ price expectations
Price Discrimination vs.
Product Differentiation
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Price discrimination:
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Product differentiation:
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The practice of charging different prices for same product
with same costs of production
Based solely on different consumers’ “willingness to pay”
Charging different prices for products with different
characteristics and costs of production
Current airline fare structures reflect both strategies:
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Differential Pricing based on differentiated fare products
But higher prices for fare products targeted at business
travelers are clearly based on their willingness to pay
Differential Pricing Theory
(circa 2000)
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Market segments with different
“willingness to pay” for air
travel
Different “fare products” offered
to business versus leisure
travelers
Prevent diversion by setting
restrictions on lower fare
products and limiting seats
available
Increased revenues and higher
load factors than any single fare
strategy
Why Differential Pricing?
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It allows the airline to increase total flight revenues with little
impact on total operating costs:
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Incremental revenue generated by discount fare passengers who
otherwise would not fly
Incremental revenue from high fare passengers willing to pay more
Studies have shown that most “traditional” high-cost airlines could
not cover total operating costs by offering a single fare level
Consumers can also benefit from differential pricing:
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Most notably, discount passengers who otherwise would not fly
It is also conceivable that high fare passengers pay less and/or
enjoy more frequency given the presence of low fare passengers
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