Transportation management

User Generated

wnz1019nf

Engineering

Description

Pick an airline planning decision and explain the most important or the most difficult challenge regarding that planning decision.

The references only the slide that I am attaching


Unformatted Attachment Preview

Airline Terminology and Measures ◼ Airline Demand ◼ RPM = Revenue Passenger Mile ◼ ◼ Yield = Revenue per RPM ◼ ◼ ASM = Available Seat Mile ◼ ◼ One aircraft seat flown 1 mile Unit Cost = Operating Expense per ASM (“CASM”) ◼ ◼ Average fare paid by passengers, per mile flown Airline Supply ◼ ◼ 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 ◼ A 200-seat aircraft flies 1000 miles, with 140 passengers: ◼ ◼ ◼ Assume total revenue = $16,000; total operating expense = $15,000: ◼ ◼ ◼ ◼ 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 ◼ ALF = 140,000 / 200,000 = 70.0% ◼ 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 ◼ Flight Leg (or “flight sector” or “flight segment”) ◼ ◼ Flight ◼ ◼ ◼ 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 ◼ ◼ ◼ 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 ◼ 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 ◼ FLEET PLANNING ◼ ◼ ROUTE EVALUATION ◼ ◼ How often, at what times and with which aircraft on each route? PRICING ◼ ◼ What network structure to operate and city-pairs to be served? SCHEDULE DEVELOPMENT ◼ ◼ What aircraft to acquire/retire, when and how many? What products, fares and restrictions for each O-D market? REVENUE MANAGEMENT ◼ How many bookings to accept, by type of fare, to maximize revenue on each flight and over the network? FLEET PLANNING ◼ Long-term strategic decision for an airline: ◼ ◼ Affects financial position, operating costs, and especially the ability to serve specific routes. Huge capital investment with lasting impacts: ◼ ◼ ◼ ◼ 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 ◼ ◼ Given a fleet, selection of routes to be flown Economic considerations dominate : ◼ ◼ ◼ ◼ ◼ 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: ◼ ◼ ◼ ◼ 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 ◼ OR models designed to perform such route evaluations, used by some airlines: ◼ ◼ ◼ ◼ ◼ 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: ◼ ◼ Profit estimates entirely dependent on accuracy of demand estimates and market share models Ability to integrate competitive effects is limited SCHEDULE DEVELOPMENT ◼ ◼ Involves several interrelated decisions, which to date have not been fully integrated: Frequency Planning ◼ ◼ Timetable Development ◼ ◼ Flight departure and arrival times, including connections at airline hubs Fleet Assignment ◼ ◼ 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 ◼ Links consecutive flights to ensure balanced aircraft flows on the network. OR Models in Airline Scheduling ◼ ◼ Airline scheduling problems have received most operations research (OR) attention Use of schedule optimization models has led to impressive profit gains in: ◼ ◼ ◼ Aircraft rotations; fleet assignment Crew rotations; maintenance scheduling Current focus is on “solving” larger problems: ◼ Timetable optimization is still not feasible--too many dimensions and constraints PRICING DECISIONS ◼ “Differential pricing” by airlines is universal: ◼ ◼ ◼ ◼ 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: ◼ ◼ ◼ 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 ◼ Pricing theory has not kept pace with airline competitive pricing practices ◼ ◼ ◼ Some airlines are now implementing “Pricing Decision Support Systems” ◼ ◼ ◼ 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 ◼ Inventory control for airlines ◼ ◼ ◼ 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%: ◼ ◼ ◼ 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 ◼ ◼ ◼ 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: ◼ ◼ ◼ ◼ 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 ◼ City-pair market ◼ ◼ Airport-pair market ◼ ◼ ◼ 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 ◼ ◼ 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 ◼ Air travel demand is defined for an origin-destination market, not a flight leg in an airline network: ◼ ◼ ◼ ◼ 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: ◼ ◼ 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 ◼ ◼ ◼ 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 ◼ ◼ ◼ 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 ◼ Tabulation of total O-D market traffic requires detailed ticket coupon analysis Implications for Analysis ◼ ◼ Dichotomy of airline demand and supply complicates many facets of airline economic analysis Difficult, in theory, to answer seemingly “simple” economic questions, for example: ◼ ◼ ◼ ◼ 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: ◼ Estimates of flight and/or route profitability are open to question Demand Models ◼ Demand models are mathematical representations of the relationship between demand and explanatory variables: ◼ ◼ ◼ ◼ 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: ◼ ◼ ◼ 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 ◼ Demand for carrier flight f of carrier i in OD market j is a function of: ◼ Characteristics of flight f ◼ ◼ ◼ Characteristics of carrier i ◼ ◼ Flight schedule in market j (frequency, timetable), airport amenities of carrier, frequent flyer plan attractiveness, etc. Market characteristics ◼ ◼ 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: ◼ ◼ ◼ 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 ◼ Next to price of air travel, most important factor affecting demand for airline services: ◼ ◼ ◼ ◼ ◼ 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. ◼ ◼ ◼ 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 ◼ T = t (fixed) + t (flight) + t (schedule displacement) ◼ ◼ ◼ ◼ 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: ◼ ◼ ◼ ◼ 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 ◼ Airlines compete for passengers and market share based on: ◼ ◼ ◼ ◼ 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: ◼ 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 ◼ ◼ 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: ◼ ◼ ◼ 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 ◼ Like air travel demand, airline fares are defined for an O-D market, not for an airline flight leg: ◼ ◼ ◼ ◼ ◼ 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 ◼ Inelastic (-0.8) business demand for air travel means less sensitivity to price changes: ◼ ◼ ◼ Elastic (-1.6) leisure demand for air travel means greater sensitivity to price changes ◼ ◼ ◼ 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: ◼ ◼ Increase fares for inelastic business travelers to increase revenues Decrease fares for elastic leisure travelers to increase revenues Time Elasticity of Demand ◼ Business demand responds more than leisure demand to reductions in total travel time: ◼ ◼ ◼ ◼ Leisure demand not nearly as time sensitive: ◼ ◼ 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: ◼ Point at which additional frequency does not increase demand Theoretical Pricing Strategies ◼ For determining prices to charge in an O-D market, airlines can utilize one of following economic principles: ◼ ◼ ◼ ◼ Cost-based pricing Demand-based pricing Service-based pricing In practice, most airline pricing strategies reflect a mix of these theoretical principles: ◼ ◼ 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 ◼ Price discrimination: ◼ ◼ ◼ Product differentiation: ◼ ◼ 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: ◼ ◼ 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) ◼ ◼ ◼ ◼ 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? ◼ It allows the airline to increase total flight revenues with little impact on total operating costs: ◼ ◼ ◼ ◼ 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: ◼ ◼ 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
Purchase answer to see full attachment
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

SURNAME 1
Student Name:
Professor’s Name:
Course Name & Number:
Date:
Airline Planning Decisions
Route Evaluation
Airlines across the globe are continuously seeking new destinations to include in their
route network. They conduct numerous route evaluations to determin...


Anonymous
Very useful material for studying!

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Related Tags