ࡱ> ^4bjbjVV q<<2%r O\%%%9998qM9)^,r8-,d-k%67j*\,6767--Q AAA67\-%A67AA~8 b99RX0<%|-h0A~2*4 |-|-|-&A|-|-|-67676767|-|-|-|-|-|-|-|-|- :AIRLINE ROUTE PROFITABILITY MODELLING Mirko Tatalovi, D.Sc. Croatia Airlines Savska 41, 10000 Zagreb, Republika Hrvatska E-mail:  HYPERLINK "mailto:mirko.tatalovic@croatiaairlines.hr" mirko.tatalovic@croatiaairlines.hr Ru~ica `kurla Babi, M. Sc. University of Zagreb Faculty of Transport and Traffic Engineering Vukelieva 4, 10000 Zagreb, Croatia E-mail:  HYPERLINK "mailto:skurla@fpz.hr" skurla@fpz.hr Jasmin Baji, B. Econ. Croatia Airlines Savska 41, 10000 Zagreb, Republika Hrvatska E-mail:  HYPERLINK "mailto:jasmin.bajic@croatiaairlines.hr" jasmin.bajic@croatiaairlines.hr ABSTRACT During the last few years there has been a major change in trends in air transport industry worldwide. The basic aims of the future air transport development are the rising of operating productivity and industry profitability. Liberalization of air traffic, fuel prices and large growth of competition are accelerating the technological processes and the necessity of improving the quality of planning, measuring and modeling financial effects of the route. Various forms of measuring performance indicators (natural and financial) are the subject of professional and scientific research. The paper analyzes the effects according to the methodology of Transport Research Laboratory (38 indicators), which show the trends and results of each individual airline. Revenue optimization per each flight is vital for airlines profitability and it includes the proper application of modern revenue management, revenue integrity and pricing systems together with the improvement of break even analyses methodology. In the core of the route profitability calculations lies the allocation of revenues and expenses to each individual flight and to the whole network accordingly. The paper presents a solution for revenue optimization models taking into account current practice used in applying appropriate business models on the market. Finally, the paper also presents the practical use and achievements of these models in Croatia Airlines. INTRODUCTION Determining route profitability plays a central role in the airline business. Route profitability analysis and network profitability analysis represent two common approaches to measure the profitability of flights. The traditional route profitability approach solely focuses on the onboard segment of a single flight and determines its profitability independent of connecting flights. In contrast, the network profitability approach takes all origin & destination (O&D) traffic into account which traverses through the analyzed flight. Thus, it assesses the financial contribution of the flight to the airlines overall network profitability. In airline practice today network profitability approach is additional tool mainly in use in big long range focused airlines with global network. Negative net profit margin in the airline industry worldwide (-1.2%) with losses of around 40 billion USD in the period 2001 to 2008 clearly indicates the need for route profitability improvements of an airline. In the same period Croatia Airlines (OU) realized negative net profit margin (-1.3%) as well. Across the same period European airline bankruptcies reached the level of 76 airlines. [1] Since the year 2005 five LCC also have gone bankrupt. [1] PERFORMANCE INDICATORS Profitability is the main goal of every economic entity and activity. Besides, it should be emphasized that there are two basic ways in order to express performance efficiency: natural (quantitative); economical (financial). The most adequate and the most consistent productivity forms of an airline is comprehended in three basic categories [2]: aircraft productivity; employee productivity; fuel consumption productivity. Basic aircraft productivity indicators can be defined as following [3]: Passenger load factor (PLF); Weight load factor (WLF); Aircraft utilization; Tonne kilometers per aircraft; Average flight distance; Average speed of aircraft; Average payload capacity per aircraft; Average kilometers performed per aircraft; Average aircraft daily working time... Work productivity results form the number and structure of employees and the need for its optimization, also demands a detailed research due to many productivity forms like as [3]: Available tonne-kilometers per employee Revenue tonne-kilometers per employee Available seat-kilometers per employee Revenue passenger-kilometers per employee Number of passengers carried per employee WLU (Working Load Unit) per employee Number of employees per aircraft Installed seats per employee Carried seats per employee Block hours per cockpit crew Block hours per cabin crew Fuel consumption indicators can be categorized as [4]: Revenue tonne-kilometers per fuel consumption Unit fuel consumption Share of fuel cost in cost structure of an airline Fuel cost per available seat-kilometers Cost index procedure For several years Transport Research Laboratory prepares studies showing overall airline performance indicator for 50 selected airlines. For reliable comparison it is important to make methodological grouping of different air carriers by their size and different business models. Grouping of the carriers was made by the criteria of carried passengers which means: small size carriers (1-6 million passengers) 10 carriers with average 3.33 million passengers (pax) (Aegan Air, Eva Air, Cyprus Airways, Eurowings, Kenya Airways, Luxair, LOT, Croatia Airlines, Pakistan International, Brussels Airlines) medium size carriers (6-20 million passengers) 14 carriers with average 12.47 million passengers (Finnair, China Airlines, Cathay Pacific, Emirates, LAN Chile, Air New Zealand, Austrian Airlines, South African Airways, Singapore Airlines, Turkish, TAP, Malaysian, THAI Airways, Frontier) large size carriers (>20 million passengers) 21 carriers with average 42.45 million passengers (American Airlines, Air Canada, Air France, Alaska Airlines, Alitalia, British Airways, Air China, Continental, Korean Air, China Southern Airlines, China Eastern Airlines, Delta, Iberia, TAM, Japan Airlines, Lufthansa, All Nippon, Northwest Airlines, Qantas, SAS, United Airlines) LCC-no frill carriers 12 carriers with average of 25.48 million passengers (Air Berlin, JetBlue, Air Lingus, Air Tran Airways, Air Asia, Ryanair, Gol, America West, Norwegian Air Shuttle, EasyJet, Southwest Airlines, Westjet) Performance indicator of traffic results and productivity among the above mentioned categories are shown in Table 1. including special attention to the achievements of Croatia Airlines (OU). Table1: Productivity performance indicators 2004-2007 IndicatorLargeMediumSmallLCCOURank 20071. PAX/flight117.3118.287.5106.767.0472. PAX/employee1,2521,0529843,6751,525183. WLU/employee1,4851,2091,0583,7481,565234. RPkm/employee (mill)2,6502,8451,8134,3021,166495. PLF %77.575.270.277.362.2506. Tkm/employee (mill)334430201410108477. A/C utilisation (BH)10.210.98.911.38.147Sources: TRL: Airline Performance Indicators, 2006, Wokingham, 2006; Jacobs Consultancy: Airline Performance Indicators 2008, London 2008, prepared by authors Indicator passenger per flight is obviously related to catchments area of the market, so the biggest and long range carriers are having more passengers per flight compared to small sized carriers. The most significant difference is coming from the indicator passenger per employee or WLU per employee where LCC are 3 to 5 times more productive compared to legacy carriers. Indicator revenue passenger kilometer (rpkm) per employee is similar as in legacy carriers category and twice less compared with LCC. By indicator tkm per employee, the difference is not so significant, which means that LCC are not too much fond of cargo aspect of operations. It is normally assumed that the maximization of aircraft utilization can be regarded as a vital element in an airlines profitability, but comparison of the results suggest that the correlation is very low. Next table shows financial performance indicators of the selected category of carriers. Table 2: Selected financial performance indicators 2004-2007 (in SDR) IndicatorLargeMediumSmallLCCOURank 2007 1. Operating revenue/pax17119315669102342. Staff costs/employee (000)4735264123383. Oper. revenue/employee (000)215203175260155384. Cost per BH (000)8.17.26.53.84.8375. Operating profit per pax57/8433/4222/3037/443/4366. ROCE (less than 4%)40/8414/4215/3014/443/4407. Equity (less than 30%)62/8424/4213/3018/440/4178. Liquidity (> 2)1/840/425/3010/440/4409. Basic earning per share > 037/8430/4211/3035/441/440Source: Ibidem Table 1 Operating revenue per passenger indicates very clearly the difference of business models since average coupon value of the LCC carriers is only 69 SDR (approx. 80 EUR), which is 2.3 to 2.8 times less compared to legacy carriers. Staff costs per employee are higher in large carriers category. Operating revenue per employee is more successful and efficient in LCC category. At the same time cost per block hours are 2 times lower than performance of legacy carriers. Operating profit per passenger is showing that not all legacy carriers are successful (68%-78%), while the percentage of profitability is higher in LCC category (84%). Return on capital employed (ROCE) is calculated by the division of operating profits before interests and tax by total capital including debt. Financial standard of healthy company (more than 4%) achieved only 58% of airline sample. Equity ratio is calculated by the division of capital and reserves by total assets, giving an indication of the way in which assets have been acquired. A high position will tend to indicate that airlines have funded investment from internally generated funds, whereas a low position indicates a greater reliance on debt. Almost 59% of the airlines do not have required financial stability. But the worst situation is with the liquidity ratio indicator which is calculated by the division of current assets by current liabilities and reflects carriers ability to cover short-term funding needs out of cash rather than through debt. It is obvious that only six legacy airlines achieved a figure of above 2 which would generally be regarded as an acceptable economic standard. Situation is slightly better on LCC segment (23% of the sample). Basic earnings per share is also in most cases problematic and not possible to achieve for the legacy carriers with the worse examples of American carriers (Delta, Northwest, American and United), specially during the business 2005 year. Croatia Airlines achieved relatively good results in terms of equity and operating profit per passenger due to acceptable low cost per block hour, closer to the LCC achievement. At the same time the results of ROCE, liquidity and earning per share are not very satisfactory. The worst result was achieved in terms of passenger load factor, since Croatia Airlines is the last ranking company (50/50). With the passenger load factor (PLF) achievement of 65.1%, during the year 2008, on the route area Cross-Border Europe Croatia Airlines is ranked nineteen from the AEA sample of 30 carriers [5]. One of the most appreciated and commonly used performance indicators methods comes from IATA [6], which also represents a combination of natural and financial indicators. Table 3: Selected IATA airline performance indicators 2001-2008  With the average annual growing rate of passengers (4.6%) and cargo (4.7) in new millennium in spite of decent increaser of revenues, due to extremely high growth of fuel costs overall net profit margin and financial result is negative (-37.2 billion $). Share of fuel cost in the year 2001 in overall expenses was only 13.5%, while in the year 2008 obtain the level of 31.9%. Similar was the situation with Croatia Airlines. Share of fuel costs in 2001 was 10.1% in 2008 20.5%). AIRLINE INDUSTRY PRACTICE The main function of network management function in an airline is to understand profit situation of route portfolio through the entire network, and understandably, the importance of this approach is the basis to induce strategic and operative adjustments and to optimize the network structure. That approach is visible from the Figure 1 [7]. Route profitability as a tool is valuable decision support for the route-/network planners, and is the essential reporting tool to the airline management. Route profitability calculation requires deep knowledge of all airline processes, cost drivers, revenue and cost structure as well as a wide range of traffic and financial performance indicators. It is very important to develop awareness that airline costs are driven by fleet and flight schedule. In accordance with the needs of the air transport industry software manufacturers are developing technologies that enables integrated and efficient route profitability monitoring. Below are listed some of these solutions: Route Profitability Business Scenario - SAP; RouteProfitability - Lufthansa Systems AG; Route Pro - OAG Aviation Solutions ARPS (Airline Route Profitability System) - Megabyte Ltd. RTRP (Real Time Route Profitability For Airlines)-Infosys Technologies Limited  Figure 1: Phases and processes of network management With those (and other) solutions, in this challenging environment for airline industry, decision makers can monitor route performance metrics such as cost, revenue performance, load factor and operating/net margin. Also the use of such solutions is important for strategic decisions to manage assets and improve profitability. In Croatia Airlines SAP ERP implementation is in progress, and part of that project is route profitability analysis solution. Also, this theme is in the center of attention of researchers and scientists with interest in airline practices. An empirical study on route and network profitability analysis published interested results. The airlines (30 total including Croatia Airlines) are categorized into three different revenue groups and analyzed respectively: small airlines up to 1 billion US $ 13 (43%); medium airlines up to 5 billion US $ 9 (30%); large airlines more than 5 billion US $ 8 (27%).[7] A high percentage of the airlines (86.8%) conduct the profitability analysis on a monthly basis. Only 9.9% of the carriers compute the route results in shorter intervals namely weekly or daily. Just one airline (3.3%) analyzes the route performance quarterly. In order to be able to optimize planning processes on a short term basis a monthly profitability analysis, however, is mandatory. On the other hand a shorter time period than a month probably is to complex and can not be realized at most airlines. The initiative for developing a profitability analysis in most cases came from the top management of an airline (over 61%), followed by finance (50%), network management (35%) and planning department (31%). On the bottom side are sales, accounting and strategy departments with only 7.7% of total initiators. This shows the strategic importance of this topic. Analyzing the main motivation for introducing a route profitability system shows that most airlines try to establish a closed loop process: the historical route performance is measured in order to enhance future planning processes and through that to optimize the overall profitability of the airline. This result is in line with the statement that the main objective of the analyzed airlines is to improve their profitability [7] (compare Figure 2). Therefore the route profitability analysis can be seen as important instrument to achieve this objective.  Figure 2: Motivation for introducing a route profitability system [7] Furthermore it was analyzed which actions are discussed in general if a flight shows a negative or insufficient result and also which actions are actually initiated if a flight is unprofitable and no potential for optimization is left. Potential actions that are selected are adjustment of frequencies and aircraft type followed by pricing and marketing activities.  Figure 3: Generally considered actions if a flight shows a negative or insufficient result [7] REVENUE MANAGEMENT AND OPTIMIZATION MODELS One of the key management mechanisms of successful airlines is the introduction of various revenue optimization systems, the so-called yield management, revenue integrity, and revenue management system. They are very closed and connected with the variety of pricing systems. The introduction of yield management is generally credited to American Airlines, around the late 1970s reducing the first attempts into three manageable sub-problems overbooking, discounted practice and traffic management. American used YM to determine flight schedules and fares open to the public via the reservation system SABRE (Semi-Automatic Business Research Environment) [8]. All sales must pass through this system and reservations are only accepted if the YM programme allows. This type of business approach has been mostly influenced by the deregulation and liberalization process of air traffic in world and Europe, where the process of yield management has proven to be a powerful means and an adequate answer to the new situation in the air market [3]. Yield management idea is the implementation and justification of the highest possible income per tonne/km or passenger km. The method is much more complex and sophisticated than simple counting of the earned financial amount per flight, or highest average value of the coupon. Revenue integrity additionally improves the process by booking control and analysis in sense of not sticking to the time limits for implementation of ticket selling, elimination of double reservations more restrictive approach to the groups, etc. The consequence is the efficiency increase of the airline. Revenue Management represents a synergic effort in optimizing the network result, without insisting only on maximizing PLF or income per passenger, but on maximal income per flight. All the above specified is organized and carried out due to fluctuations of supply and demand on air transport market. Core requirements for the operation of a yield management system are [9]: Booking patterns Knowledge of the demand patterns by market segments An overbooking policy Knowledge of the effect of price changes A good information system Yield management indicates the differences regarding flight distance and the characteristics of each market which is evident from the following data for the different route areas (Figure 4.). Figure 4: Croatia Airlines passenger yield metrics for different route markets Similar to the passenger yielding econometric models of demand for world scheduled air freight traffic is also closely connected to freight yield. Estimated freight model to the year 2025 is shown in next formula [2]: ln FTK = 8.59 + 1.15ln EXP 0.31ln FYIELD R2= 0.986 (1) Where: FTK = freight tonne-kilometres EXP = world exports in real terms FYIELD = freight revenue per freight tonne-kilometres in real terms One way in which airlines can begin the process of yielding freight is to differentiate value as a priority by using a class system. At its simplest this might be three classes [8]: A High value - must ship. B Medium value - should ship. C Low value - will ship when space is available. Such a system could then be linked to an overbooking system. Class A goods (first class) will never be overbooked. Class B goods (business class) may exceptionally be overbooked. Class C (economy) can always be overbooked and held on standby. Revenue management starts with precise and thoroughly monitoring of passengers behavior rules with extreme importance for choice of good business strategy of the airline regarding the respective dilemmas. The same case is with the everyday, tactical decision referring to particular route or route portfolio and it can be different also due to the part of a day in daily, weekly frequency seasonal traffic oscillations etc., directly influencing on the airline efficiency increase. In order to achieve this, the airlines have to do their best in order to expand the interest of the services users, so that the harvest could last as long as possible with maximal results. Many methods can be applied, with more or less success, like French airline Air Inter example of red, white and blue fare system. The lower prices offered during the blue periods are supposed to stimulate the sensibility of passenger making him change the anticipated date of flight in-peak period, transferring him to off-peak period [10]. However, it is not sufficient from the aspect of real, successful revenue management having to make much more steps in order to obtain efficient and favorable implementation for the airline. In these conditions airlines are facing three types of risks [11]: Risk of empty seats If the company rejects certain number of requests for lower prices providing the seats for late booking passengers, willing to pay the higher price, there is risk of spoilage. Risk of aircraft loading with lower fares If the airline makes an opposite decision giving the priority to the passengers paying lower fare, it faces the risk of part of revenue loss, as due to the advance booking with lower fares, it shall be forced to refuse the passengers willing to pay the higher price spill. Risk of passengers denied boarding - In case of full aircraft occupancy and appearance of additional demand for the seats, the airline must refuse a certain number of passengers with valid booking denied boarding. On the other hand, refusing such requests, the airline faces the problem of carrying empty seats as there are always no-show passengers in spite of confirmed booking. Basic elements of the revenue management system are: demand forecasting, optimization and over-capacity planning. Measurements of airlines system users have proven that the implementation of such a system increases total annual revenue by 2-6 percent. Demand forecasting is a very important element in achieving the maximal results. According to some sources a ten percent increase of forecasting precision with US Majors can result in increase of total annual revenue from ten to sixty million USD [12]. Demand forecasting can be performed at different levels, from macro level (complete network of flights for the whole year) up to micro level (one flight stage for particular class of service). The unstable market conditions, insufficient quality and quantity of history data, impossibility of real demand estimate, extraordinary events etc. are the most important factors affecting the forecasting precision. Airline revenue management represents an important part of daily airline operations. It is the practice of controlling the booking requests such that the planes are filled with the most profitable passengers, using the basic principles of supply and demand economics in a tactical way to generate incremental revenues. There are three essential conditions for revenue management to be applicable: there is a fixed amount of resources available for sale the resources sold are perishable or there is a time limit to selling the resources different customers are willing to pay a different price for using the same amount of resources. Practical complexity of revenue management could be illustrated by its elements [13]: customer behavior and demand forecasting (demand volatility; seasonality, day-of-week variation; special events; sensitivity to pricing actions; demand dependencies between booking classes; return itineraries; batch bookings; cancellations; censorship of historical demand data; defections from delayed flights; diversions; go-shows; group bookings; interspersed arrivals; no-shows; recapture; upgrades) control system (booking lead time; number of controllable booking classes; leg-based, segment-based, or full ODF control; distinct buckets, parallel nesting, or full nesting; reservations systems connectivity; frequency of control updates; overbooking) revenue factors (fare values; uncertainty of fare value; frequent flyer redemptions; company or travel agent special vouchers; cancellation penalties or restrictions) variable cost factors (marginal costs per passenger; denied boarding penalties; goodwill costs; fare products (number of products; restrictions) problem scale (large airline or airline alliance) problem interfaces (market strategy; code-sharing alliances, routing; gate acquisition and schedule planning; fleet assignment). Revenue leakage is a major factor for airlines reduction in profitability. This occurs where the difference between the business that is booked with an airline and the actual revenue that is received after travel has a significant gap. The major causes of this are due to intentional abusage of an airlines inventory by travel agents wishing to undermine the booking processes and rules, and due to a large number of speculative bookings which either result in late cancellations, or no-shows on departure. All of the malpractices can be rectified by the implementation of a good Revenue Integrity solution.  Croatia Airlines applies from October 2008 Calidris revenue integrity application which showed the following results. In first six months total number of new bookings was 556,930 and ratio of PNRs challenged (system activity) was 74%. The number of seats returns was 61.845 (approx. 15%). Taking in the consideration off-peak period (Winter 08/09) revenue recovered is calculated by multiplication of resell percentage (5-15%) average price and seats returned. It means that for period Oct 2008 - March 2009 revenue recovery is amounting on the level of 203.515 EUR. Structure of seats returned is visible from Figure 5. The airline pricing can be considered from economic and from psychological point of view. On one hand it determines revenues and profits of the airline, while on the other side it determines the value of the service for the user. It is quality indicator and creates and maintains the company image. It is also a strategic element for making competitive advantage. The price is one of marketing-mix components making profits. With trends in behavior of consumers and deregulation it becomes a crucial part of the mix. Basic purpose of its application is to maximize the airline revenues. Besides, it is an efficient means for service demand stimulation. Herein after planning criteria and price policy implementation, structure of the low cost carrier pricing is different compared to traditional and low cost-no frill and price distribution shall be considered.  Figure 5: Structure of leakage prevention activities in Croatia Airlines One way of achieving a different willingness to pay is to achieve effective market segmentation by implementing purchase restrictions, length of stay requirements and requiring fees for changing or canceling tickets. Passenger requests are accepted or rejected to maximize the expected future revenue through demand based pricing or availability controls on their reservation systems based on detailed statistical demand forecasts and mathematical optimization. The first step in that process is to create a fare structure in each market consistent with the characteristics of demand with regard to willingness to pay and schedule preferences. The second step is to assign fare bases into a number of booking classes, allocate the seat inventory on future flights amongst those classes, and than to manage the inventory until departure. Revenue management should not be seen as an isolated function, but should be integrated with pricing, marketing, and sales departments. The European low-cost carriers introduced a totally new pricing concept to the market. The major difference between traditional and low-cost concept is that the LCCs use the so-called inventory controlled fares or step pricing instead of the traditional behavior controlled fares. They have moved the control from the fare restrictions to the inventory availability. The customer can buy one-way ticket. This allows the airlines to present to the customer a simpler and more understandable pricing structure which can be advertised on a one-way basis in competition with legacy carriers advertising round-trip prices and their revenue management is much simpler than that of the legacy carriers. The marketing strategy of LCCs is to sell seats at the lowest advertised prices at the beginning of the life-cycle of flight, after which they progressively move to higher fares as the flight fills with passengers up to a certain planned value as the date of departure approaches. In order to stay competitive and make their business models sustainable in the long-run, legacy carriers were forced to make structural changes in their pricing. Many of them introduced simplified pricing models with reduced fare levels and simplification of rules and restrictions attached to fares. Croatia Airlines is using ATPCO pricing global distribution system and Amadeus On-line product named Flex Pricer, which allows access to 459 origin destination combinabilities. During the year 2008 Flex Pricer recorded 45.459 bookings with revenue of 76.2 millions Croatian kunas. BREAK EVEN POINT ANALYSIS Break-even point (BEP) metrics is important tool for any airline company for simulating, analyzing, controlling and planning future profitability of routes. No airline can afford to keep unprofitable routes. It is vital to determine the profitability of a route within a given period of time, compare the profitability of one route to another, and determine whether you should add, change, or eliminate routes. The known basic formula for break even in units is:  EMBED Equation.3  Where: Price - Variable Cost is known as Contribution Margin. In Croatia Airlines it was developed a computer model designed to perform break even analysis for route evaluations. Following example shows the Croatia Airlines BEP analysis based on real data in 2007. Table 4: BEP Analysis for ZAG!VIE route in year 2007 (ATR-42 aircraft)  Source: Prepared by authors In practice is very important to analyze and compare actual load factors with break even load factors. Break-even in airline industry is usually expressed as a percentage of total ASKM. This provides a break even load factor, or a load factor which the airline must meet to recover all its fixed costs. The general formula for airline break-even is the following:  RPKM x RRPKM ASKM x CASKM =0 Where: RPKM = revenue passenger kilometers RRPKM = revenue per passenger kilometers (yield) ASKM = available seat kilometers CASM = cost per available seat kilometers From this basic formula, two passenger load factors can be found [14]:   When applying concrete results for the Great Britain and Austrian markets for the period from 2002 to 2007 year, in the specified formula it is possible to make a proper comparison since the results are completely different (Figure 6).  Figure 6: Croatia Airlines BEP compared with actual PLF for different route markets Actual results for the selected markets (Great Britain -12.6 million EUR vs. Austria +4.9 million EUR) indicate to further strategic issues for route portfolio optimization. ROUTE PROFITABILITY MODELLING PRINCIPLES The fundamental idea of route profitability analysis is to allocate cost and revenues on a flight level basis. But, not all costs and revenues are caused directly by an individual flight. Thats the reason why airlines have to apply specific allocation formulas or cost and revenue drivers for correct calculation. For this quantitative performance data such as number of block hours, flight hours, available seat kilometers (ASK), revenue passenger kilometers (RPK) or distance flown are used. Basic inputs for any route and network profitability analysis are the operating statistics of an airline.  Figure 7 Route Profitability Modeling Process in Croatia Airlines Source: Created and prepared by authors The basic idea of route profitability model in Croatia Airlines is to provide triple view: Profitability by individual routes / network contribution; Profitability by types of traffic and markets served; Profitability by type of aircraft. Importance of those views is reflected through business decisions for the future. Operative, short-term, long term and strategic plans are in direct relation with actual results which must include the elements of corrective actions. This is reflected in future decisions on how to service some individual markets and the selection of the fleet. Model starts with the following necessary factors: Traffic Results Traffic statistics is a source of necessary data on flights, block-hours, passengers, seats, available seats kilometers (ASKM), revenue passenger kilometers (RPKM), transported cargo (freight and mail), tonne kilometers (TKM), etc. All these data are monitored and analyzed per particular type of aircraft and they are basis for allocation of costs and revenues of individual flight, or route. Operating Revenues Evaluation of passenger revenues is based on data of revenue accounting comprising data on revenue average fare per city pairs, being a basis for passenger revenues multiplication per individual flight regarding the number of passengers carried. Passenger revenues in scheduled traffic include also ticket service charge (TSC) and excess baggage revenue. Other revenues include on-board sales (duty free) allocated directly to the specific flight and revenues (marketing, computer reservation system, commissions...) allocated to specific routes based on different criteria (passenger, available seat kilometers, indirect costs...). Operating Costs Categorization and cost classification is expressed in various forms and there is no a unique world methodology. According to ICAO (International Civil Aviation Organization), financial results of scheduled carriers in profit and loss statement and the cost structure is defined with 8 basic categories and 14 subcategories. The IATA (International Air Transport Association) has better developed methodology starting with 8 categories of direct operating costs (cockpit crew, fuel, insurance, maintenance, depreciation, aircraft rentals, landing and navigation) and 5 categories of indirect operating costs (handling, cabin crew, passenger services, sales and marketing, general and administrative). This methodology is accepted by AEA. Scientific and professional papers dealing with structure and allocation of costs of the airline sometimes prefer division to fixed direct operating costs, variable direct operating costs, and indirect costs [15]. Some new terms of costs category are introduced as for example avoidable, incrementalsunk costs, are the costs generating new values (opportunity) [16]. In elaboration of fixed and variable direct operating costs, some authors support the fixed costs of the crew in sense of annual gross salaries and variable costs of the same category in the sense of the daily allowances and accommodation expenses depending on burden of every individual pilot. The similar approach is with more evident division to fixed and variable costs changing with RPKM or ASKM (respectively passenger-miles, seatmiles). Correct classification of operating costs introducing elaboration to the costs connected to the fleet structure and costs referring to the aircraft operations are supported by P. Clark [17]. Calculation of the route operating costs requires cost aggregation of each particular flight done on the specific route, as follows: Fixed direct operating costs; Variable direct operating costs, and Indirect costs. In practice fixed and variable costs can be shown in different manners regarding direct operating costs. Majority of costs contain the elements of fixed part and variability in the same time. The shorter time period of analytical observation of particular cost the bigger fixed component. Similarly, the longer time period of analytical monitoring, the bigger becomes variability component. In conformity with the airline size, traffic model (network carrier within Star Alliance) and competitive position on the air market, Croatia Airlines has established the following structure of operating and financial costs: Schematic presentation of the costs with allocation criteria (within brackets) are shown bellow [18].    where FT1a/c 1,2,3 is fixed cost 1 for particular type of the aircraft (a/c) , and BH (block hours) refer to the particular type of the aircraft. In the below text there is the elaboration of the direct operating costs per type. Cabin crew costs per aircraft type include cash and material income (earnings), training (education) and respective checks, flight plans making, earnings and material costs of handling staff and other costs of the cabin crew. Cockpit crew costs per aircraft type include cash and material earnings, training, transport and accommodation and other cockpit crew expenses. Maintenance costs per aircraft type comprise aircraft checks, engine repair, spare and consumption parts for aircraft, technical support, technical documentation, certificates issuing, cash and material earnings of the maintenance staff, training and other maintenance costs. Depreciation costs per aircraft type comprise depreciation of aircraft and engines, spare parts, tools and equipment and depreciation of other assets. Aircraft rental specified per aircraft type. Insurance costs per aircraft type include the aircraft insurance and other insurance costs for workers and property. Fuel and oil per aircraft type with calculation based upon an average consumption per block hour on particular / specific type of aircraft and averagely paid fuel price for the report period. Airport services costs comprise landing costs as well as handling costs for aircraft, passengers, baggage, as well as freight and mail. Calculation of these costs is based upon the contracted and/or achieved unit prices per aircraft type for each particular airport multiplied with the realized respective number of flights on the specific route. According to the airline industrial practice, landing services staff is a part of airport services, while the route allocation is performed by criteria of realized costs of airport services for each individual route. The following algorithm shows the calculation example of airport services costs for the route A AU(A):  where (AU(A)a/c 1,2,3 average contracted/actual price of airport services for specific aircraft type on the route (A), while L(A) a/c 1,2,3 represents number of flights on specific aircraft type. Air navigation costs comprise enroute and terminal charges. Calculation of these costs is done per every specific aircraft type multiplied with appropriate number of flights on each individual route. Np = Enroute Charges; d = Distance in km; t = Unit rate; MTOW = Maximum take off weight The airline cannot make any influence on this cost value. Even more, in September of 2006 terminal charges were introduced in Croatia making an additional burden for Croatia Airlines with a new amount of EUR 960 thousand in 2006, and 1.8 million EUR in 2007 and 2.6 in the year 2008. Catering costs per routes are calculated against individual specific passenger consumption for any traffic category, multiplied with number of passengers carried on the specific route. According to the aviation industrial practice the personnel connected with food preparation and distribution (catering personnel) is a part of total catering costs, while route allocation is performed separately for each individual route. Computer reservation system costs (CRS) are allocated per particular routes based on unit cost per boarded scheduled revenue passenger, multiplied with a number of revenue passengers carried on each particular route for the corresponding period. This principle is shown in the following algorithm:  Where: CRS(A) is reservation system costs on the route (A), CRSj is average unit cost of reservation system costs per revenue passenger in scheduled traffic, and PP(A)a/c1,2,3 is realized number of revenue passengers per individual type of aircraft. Commission costs comprise commissions to passenger travel and freight sales agents, for credit cards, BSP and interline service charge. Calculation per individual routes is carried out on the basis of the contracted rates, including also stimulating commissions with application of adequate percentage to the revenue passenger commission and/or cargo for each individual route. Indirect costs comprise all other categories of costs not covered by the previously mentioned categorization. The dominant part belongs to general and administrative costs, including wages and salaries of marketing and sales departments, advertising and propaganda, costs of previous years etc. According to aviation standards and practice of the European air carriers the indirect costs are allocated to any particular route. Allocation criteria are fixed costs reflecting cost price of certain capacity in the system shown in the following algorithm for route (A): where: IT = indirect costs; FT = fixed costs. The calculation comprises non-operating financial expenses. The biggest item is interest payable/receivable referring to the fleet financing, again per any specific route. Other financial expenditures are allocated according to the same principles as mentioned before. CONCLUSIONS No airline can afford to keep unprofitable routes. It is vital to determine the profitability of a route within a given period of time, compare the profitability of one route to another, and determine whether you should add, change, or eliminate routes. Satisfactory results of an airline achieved in productivity and economics of operations still do not guarantee the profitability of business. On final profit and loss statement significantly affect several financial factors. Interest burden in airline industry at global level is 2 to 3 percent. At the same time interest burden of Croatia Airlines decreased form 15.3% in the year 2001 close to industrial standard in 2008 (3,2%). Furthermore currency exchange risks together with fuel price risks have led the avio industry in a difficult position. For the improvement of route profitability metrics it is necessary to implement proper activities on dynamic management of fleet capacity, route portfolio optimization, optimization of the fleet maintenance and revenue management models. Airline size and network servicing affect their marketing and strategic positioning. A detailed analysis of the revenue and cost structure of a network is one of the primary tasks when running an airline. It is the basis for making operational or strategic decisions with regard to the configuration of a route network in a profit oriented way. Besides, Croatia Airlines has public service obligation for servicing domestic transportation creating additional difficulties in reaching marginal profitability due to low level of population living standard and negative effects of price elasticity. In airline practice the need for improvement of route profitability models is growing followed the software manufacturers who offer different solutions for variety of airline business models. REFERENCES Booz & Co.: Study on Consumer Protection against Aviation Bankruptcy - Prepared for European Commission DGTREN, Brussels, March 2009. pp.12 ICAO: Outlook for Air Transport to the Year 2025, Montreal, 2007, pp. 13-48. Tatalovic, M.: Optimalizacija produktivnosti zrakoplovne tvrtke, Phd Disertation, Faculty of Traffic Sciences, Zagreb, 2004, pp.73-165. Tatalovic, M., Misetic, I., Malovic Beganovic, I.: Productivity Optimization of an Airline, International Conference ICRAT, }ilina, 2004, pp.152 AEA: Flash Monitor December 2008, Brussels, 2009, pp.4. Pierce, B.: IATA Financial Forecast March 2009,  HYPERLINK "http://www.iata.org/economics" www.iata.org/economics, pp.4. Niehaus, T.: Enhancing Airline Profits through the Application of Route and Network Profitability Analysis, University of Cologne, Cologne, 2008, pp. 4-25. Ingold, A., Huyton, J.R.: Yield Management and the Airline Industry, London, 2000, pp.180-194. Barlow, G.L.: Yield Management in Budget Airlines, London, 2000, pp.209. Daudel, S., Vialle, G.: Yield Management, ITA Study, Paris, 1994, pp.49. Misetic, I.: Upravljanje marketingom zrakoplovne tvrtke, Phd Dissertation, Osijek, 2006, pp.151. Skurla, R. : Unapredjnje sustava za upravljanje kapaciteta zrakoplova, Magistarski rad, Faculty of Traffic Sciences, Zagreb, 2003, pp.14. McGill, J.I., Van Ryzin, G.J.: Revenue Management: Research Overview and Prospects, Transportation Science, 33, No. 2, 1999., pp. 235. Vasigh, B., Fleming, K., Tacker, T.: Introduction to Air Transport Economics,Ashgate; Aldershot, 2008, pp.101. Doganis, R.: Flying off Course, London, 1991., pp. 124. Holloway, S.: Straight and Level Practical Airline Economics, Ashgate, Aldershote, 2003., pp.260-261. Clark, P.: Bying the Big Jets, Aldershote, 2007., pp.172. Miaeti, I., Baji, J., Keglovi Horvat, A.: Regulation and Practice of Managing Domestic Air Traffic, Suvremeni promet, No. 5, 2008, Vol 28, Zagreb, 363-372.  TRL is an independent centre of exellence for research and consultancy in transport issues with around 500 staff off different professional disciplines (ecomists, mathematicians, physicists, psychologists, engineers and statisticians)  Structure of the participants in analysis is changeable including thus 57 airlines  WLU is measure used to combine passenger and cargo traffic, being either one passenger or 100 kg of cargo  Ryanair with utilization of only 8.4 BH/day (rank 41) was the third most profitable company in 2005. 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SDR conversion rate for EUR changed from 1.193 (2004) to 1.1186 (2007).  Selected LCC carriers in Study are the best possible sample. There are numerous LCC which are not efficient and successful  Application of ROCE needs to be treated with some caution because of the practice of off-balance sheet aircraft acquisitions financing, which may distort comparisons.  www.SAP.com  www.LHsystems.com  www.oag.com  www.megabyte.net  www.infosys.com  www.arigroup.org  www.calidris.com  Calidris value statement is 426.090 taking in consideration 7,7 resell percentage and 90 EUR average coupon value.  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