Aditya Nugroho_Final Report

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COMPLEX DECISION OF BUYING OR NOT BUYING NEW

AIRCRAFT IN AIRLINE COMPANY

IE 5203 DECISION ANALYSIS

ADITYA NUGROHO

HT083276E

DEPARTMENT OF INDUSTRIAL ENGINEERING

NATIONAL UNIVERSITY OF SINGAPORE

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EXECUTIVE SUMMARY

This term paper tries to present a real world problem in Decision Analysis. An airline company ABC in Indonesia is plan to develop Jakarta-Singapore route network on short haul flight within ASEAN countries. The present operation makes use of Boeing 737-300. The company must decide whether to maintain present aircraft or buy a new aircraft that will increase its capacity.

Value-focused thinking was done to identify values that matter to the decision maker. Thus, alternatives were generated. To consider the monetary gain of each alternative in term of NPV, one pass through DA cycle using DPL programme was done. Uncertainties of future income, maintenance cost, and the salvage value of the aircraft was accounted for.

To consider other intangible factors, Analytical Hierarchy Process (AHP) was done using Expert Choice software. Criteria and subcriteria to determine the best alternative were laid down in Tree Hierarchy. The weightage of each criteria and subcriteria were calculated using pairwise comparison technique. All alternatives were then compared to each other. Best alternative was obtained.

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The airline company ABC in Indonesia is plan to develop Jakarta-Singapore route network on short haul flight within ASEAN countries. The present operation makes use of Boeing 737-300. According to air transportation bureau, it is expected that the demand for air passenger would be 65,000 pax per annum. The company is now considering to invest in a new aircraft with huge capacity but suitable with annual passenger demand. By this new aircraft the airline could carrying more passenger for international route.

Making this decision is hard because of the complexity by the many choices of aircraft technologies: the capacity, the reliability of the technology, the market value, after sale service, and so on. However, only some alternatives will be considered in this paper, because of the limited capability of the trial version software used.

In addition there are also many objectives to be fulfilled, such tangible and intangible factors. Considering investment in new aircraft not only the expected payback period and future income but also the ease and safety of using the technology, maintenance, and the possibility of business expansion.Thus, there’s another reason why making this decision is hard, that is because the future is full of uncertainties. This could come from the economic situation in ASEAN countries that will affect the the demand annual passenger.

2.0 FRAMING AND FORMULATION

Value-focused thinking is used to formulate the problem. Values & objectives will be identified and structured. Influence diagram and decision tree will be used to structure the elements of the decision situation.

2.1 Framing

a. Target

 The company needs to earn money

 The company wants to become market leader  The company wants to expand the business b. Alternatives

 Maintain old aircraft: maintain the current profit, limited by the aircraft capacity  Buy new aircraft: invest a sum of money, monetary gain in the future, and increase

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 Alternatives of the new aircraft (2 alternatives have been chosen): - Boeing 737-900ER

- Airbus 330-200 series

Comparison of the two alternatives and estimated value of the investment from the aircraft manufacturer is shown in Table 1.

c. Problems

 The old aircraft is giving problem of limited capacity to carrying more passenger Table 1 Alternatives comparison

Boeing 737-900ER Airbus 330-200 series

Manufacturer Boeing The European Aeronautic

Defence and Space Company Max seat capacity 215 passengers in a

single-class 293 passengers in a two class

Max take off weight

and max range flies Weights 187,700 lb (85,130kg), Flies up to 3,265 nautical miles (6,045 km)

Weights 233,000kg (513,670lb), Flies up to 11,850km (6400nm) Maximum fuel capacity 7,837 U.S. gal (29,660 L) 36,750 US gal. (139,100

Litres) Reputation of

manufacturer Established, pioneer ingmedium aircraft size Established consortium withEuropean company, very active in research

Service Worldwide including

Singapore Worldwide includingSingapore Aircraft safety precision The -900ER is a performance

category D (The -800 is performance category C)

EASA determined that the A330-200F does not present unique characteristics that require flight evaluation. Estimated price US$76.0 - 87.0 (millions) US$170.9 - $200.8 (millions) d. Uncertainties

It is predicted that the future condition is full of uncertainties.

 The monetary gain by investing in new aircraft will be greatly affected by future condition which is determined by the economical situation in ASEAN countries.  The consequences of buy new or maintain current aircraft would is shown in Table 2

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Table 2 Future uncertainties

Economic condition Maintain New investment

Better Limited by capacity Carrying more passenger,

more profitable

Stable Stable Possibility to expand the

international routes

Worse Stay on Lose money

e. Constraints

 Investment in new aircraft required huge initial cost and need credit service from the Bank.

f. Strategic objective

 Value that is absolutely fundamental : more profit

2.2 Formulation

a. Decision variables

 Buy Boeing 737-900ER  Buy Airbus 330-200 series

 Maintain old aircraft Boeing 737-300 b. State or system variables

 Demand (passenger/annual): low, base, high

 Annual maintenance cost (million /year): low, base, high  Salvage value (million): low, base, high

c. Values and preferences

 NPV (Net Present Value) of net income at MARR = 10%  Study period at 15 years

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2.3 Influence diagram and generic decision tree

N

MARR Gross

profit

NPV Demand O&MCost

Salvage Value Investment Choice Low Nominal High Low Nominal High Salvage Value Low Nominal High O&M Cost Buy Boeing 737-900ER

Buy Airbus 330-200 series

Maintain old aircraft Boeing 737-300

Demand Investment

Choice

Figure 1 Influence diagram and generic decision tree of the investment model Table 3 Value model of investment decision

Investment Decision Model Short Haul Flight Decisions

Buy B737 900ER Buy A330-200 Maintain B737-300

Inputs Sensitivity range

Low Base High

Annual passenger demand 65000 35000 65000 95000

O&M cost B737 900ER $19,392,400 $9,696,200 $19,392,400 $29,088,600 O&M cost A330-200 $26,853,353 $13,426,677 $26,853,353 $40,280,030 O&M cost B737-300 $17,636,000 $8,818,000 $17,636,000 $26,454,000 Salvage value B737 900ER $35,000,000 $17,500,000 $35,000,000 $52,500,000 Salvage value A330-200 $80,000,000 $40,000,000 $80,000,000 $120,000,000 Salvage value B737-300 $15,000,000 $7,500,000 $15,000,000 $22,500,000

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Study period 15

MARR 10%

Initial cost of B737 900ER $90,000,000 Initial cost A330-200 $160,000,000 Gross operating cargo profit/pax

B737 900ER $300

A330-200 $500

B737-300 $100

Air fare; per passenger $250

Intermediate values

Uniform series PWF (P/A,10%,20) 7.6061 Single payment PWF (P/F,10%,20) 0.2394 Value model Strategy 1. NPV Buy B 737-900ER $42,795,928 2. NPV Buy A 330-200 $25,698,999 3. NPV Maintain B 737-300 $42,488,371 3.0 DETERMINISTIC ANALYSIS

From the above value invesment decision model thus we will consider deterministic analysis. The purpose of deterministic analysis is to choose sensitive variables, which influence the result greatly with just a little change of value. These variables are called aleatory variables and will be considered further in the probabilistic analysis, while other insensitive variables will be set to the base value.

By using the Sensit software, the state system variables are calculated and deterministic analysis is done and the result is shown as the Tornado Diagram (Figure 2). From the tornado diagram, we can analyzed as follows:

 As the business operating of airline is depend on passenger demand. The model shows that the annual passenger demand influence the total present worth of NPV income greatly.

 Secondly the range of operation and maintenance cost of aircraft also influence the value of NPV income although not as great as the annual passenger demand.

 The fluctuation of salvage value of aircraft costs don’t change the value of present worth significantly.

As a conclusion of this deterministic analysis, it is decided that the variable of annual passenger demand and O&M cost of aircraft will be treated as aleatory variables, while other variables will be set at the base values for subsequent analysis.

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35000 $40,280,030 $29,088,600 $26,454,000 $40,000,000 $17,500,000 $7,500,000 95000 $13,426,677 $9,696,200 $8,818,000 $120,000,000 $52,500,000 $22,500,000 Annual passenger demand

O&M cost A330-200 O&M cost B737 900ER O&M cost B737-300 Salvage value A330-200 Salvage value B737 900ER Salvage value B737-300

-$400.000.000 -$200.000.000 $0 $200.000.000 $400.000.000 $600.000.000

Total NPV

Figure 2 Tornado diagram 4.0 PROBABILISTIC ANALYSIS

In this section the pdf (probability distribution function) of each aleatory variables will be assessed. Using the Pearson-Tukey three-point quick approximation method, the CDF (cumulative distribution frequencies) derived is discretized, resulting in the PMF (Probability Mass Function) for each aleatory variables. Pearson and Tukey suggested using the 5, 50, and 95 percentiles and in this case the branch probabilities of the approximate pmf are [0.185, 0.630, 0.185]. Following figure represent the pmf of each aleatory variables.

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The probability analysis is done using the DPL program by considering aleatory variables in influence diagram (see Figure 4). Some snapshots and results from the DPL analysis are shown in Figure 5 and 6. The optimal decision is shown in Figure 7.

B739 SV A332 SV B733 SV N MARR B7379 I A3302I B7379 P A3302 P B7373 P Airfare NPV NPV B739 NPV A332 NPV B733 Pax demand B739 OM A332 OM B733 OM Investment choice

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Figure 5 Value node definition

Figure 6 Risk profile

As Figure 6 shows, the alternative exhibits non stochastic dominance over the other alternatives. Note, however, in spite of greater variability in parameters associated with the Buy Airbus option, the corresponding risk profile is relatively tight.

Therefore, by considering the monetary gain and future income therefore the optimal decision policy of airline company is to Buy Boeing 737-900ER for operating short haul route for Jakarta-Singapore (see Figure 7).

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Figure 7 DPL Optimal decision policy

5.0 MODEL APPRAISAL

In this section I would like to discuss analysis of value information and control. Value of information is the amount a decision maker would be willing to pay for information prior to making a decision. The value of control is a quantitiative measure of the value of controlling the outcome of an uncertainty variable.

Figure 8 Value of information and control

As shown in Figure 8 the manager of airline company can run a value of control or value of information diagram to see which nodes most directly affect the outcomes. As we have four uncertainty nodes in our model, the graphs show that the passenger demand is important nodes. In addition, the value of control shows the amount of risk that could be reduced given perfect control over each probabilistic node, and that it is clear that passenger demand would be the most important variable for risk managers to control. Admittedly, this is a basic

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example, but with a more complex model, analysts could determine which nodes are positively or negatively affect the outcomes and which uncertainties are most important.

Figure 9 Sensitivity analysis of pax demand node (rainbow diagram)

By using DPL software is allow to easily perform sensitivity analysis on key model assumptions. From the value of information and control above, the Expected Value of passenger demand was highly. We can generate sensitivity analysis such as rainbow diagrams. The rainbow diagram (Figure 9) shows the decision changes as our assumption about the nominal value of passenger demand increases. The different shaded regions represent different decisions. In conclusion the company should control the pax demand variable which would be affect the great outcomes of the model.

6.0 ANALYTIC HIERARCHY PROCESS MODEL

In this section considering decision to buy aircraft is not only based on policy tree of NPV, however there is exist tangible and intangible factors should take into account. Therefore in the AHP analysis these factors will further discuss. In AHP model NPV value for each alternatives will be use to calculate preference. In example the preference for Buying Boeing 737-900ER over the Boeing 737-300 will be 52,067,548/42,488,595=1.225

As can bee seen in Figure 9 by using the AHP hierarchy, the set of main criteria (tangible and intangible) has been considered in second level hierarchy. Each main criteria is decomposed

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into several subcriteria. Each criteria’s and subcriteria’s weightage is obtained by pairwise comparison technique. There are 3 alternatives to be considered. AHP analysis is done using Expert Choice 11.5. The results of expert choice is shown in following figure.

Maximize benefits

Tangible Intangible

NPV Tech nology _precisionSafety Manufacture_reputation After saleservice assurance Buy Boeing 737-900 ER Buy Airbus330-200 Maintain Boeing 737-300 Figure 10 AHP Hierarchy

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Figure 12 Sensitivity analysis with respect to main criterion

As shown in Figure 11 by selecting pairwise graphical comparisons in Choice Expert, therefore the set alternatives with respect to goal can be obtained. Results of Choice Expert shows that the best alternative is still to buy Boeing 737-900 ER instead of maintain current aircraft. The overall inconsistency is good, because the management is not willing to change their judgement in the pairwise comparison. But since the chosen alternative’s priority is not far exceeding the other two alternatives, the decision is more sensitive.

After considering synthesis of alternatives, sensitivity analysis is done to see how the changes of main criteria’s and subcriteria’s weightage affect the ranking of the alternatives. Expert Choice is able to generate 4 kinds of graph to do the analysis (see Figure 12). As can be seen in the dynamic sensitivity result, the chosen alternative (Buy Boeing 737-900ER) is prefered against the other two alternatives in tangible criterion. Under intangible criteria, alternative Buying Boeing 737-900ER is still prefered.This means rank reversal will not occur if the weightage of the main criteria.

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Figure 13 Sensitivity analysis with respect to intangible criterion

As can be seen from the above figure 13, under intangible criteria, preference is sensitive. Preference will change if we change the subcriteria’s weightage. As example, Airbus 330-200 with respect to safety precision subcriteria dominates other 2 alternatives. However,in overall alternative Buy SLA Boeing 737-900ER still dominates over the other 2 alternatives.

7.0 RECOMMENDATIONS AND CONCLUSIONS

Based on DPL and Expert choice results, some recommendations for investment choice as follows:

 Buy Boeing 737-900ER in considering monetary gain

 However, in the case weightage for intangible criteria is changed to more than 50%, the preference will be to buy Airbus 330-200

In regards with Decision Analysis cycle following recommendations are needed for 2nd pass DA cycle :

 Risk neutrality was assumed and the dollar value is used to obtain the expected value of optimal decision in the 1st pass. So for the 2nd pass the risk attitude can be

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 Pearson-Tukey three-point short cut approximation method was used in the 1st pass, so in the 2nd pass a more accurate method can be used to discretize aleatory variables such as using equal area method or fitting a certain distribution to data.

 MARR, study period was set at 10% and 15 years respectively. In the 2nd pass analysis can be done whether the changes of these parameters are significant enough to treat them as aleatory variables.

 The use of AHP implies that an Additive Value Function is used, hence the Additive Independence holds. In reality it might not be the case, so investigation into this must be done, and Multi Attribute Utility Function could be used instead.

 In calculating NPV, the means of financing this investment has not been considered. If financing comes from outside source and there is cash outflow to pay the interest, then it’s more appropriate to calculate the present worth of cash flow after taxes.

In conclusions, this project presented a real world problem in Decision Analysis. It manages to combine tangible and intangible objectives to obtain the best alternative It manages to take into account the risk of future value of demand and the uncertainty of maintenance cost and salvage value of the aircraft.

REFERENCES

R.T. Clemen and T. Reilly, Making hard decisions with DecisionTools. Duxbury Thomson Learning, 2001.

T.L. Saaty, The Analytic Hierarchy Process, McGraw Hill, New York, 1980 K.L. Poh, IE5203 Lecture Notes, 2010 Edition.

Applied Decision Analyis LLC, DPL 4.0: Professional Decision Analysis Software -Academic Edition, Duxbury, 1998.

Source of data information

 http://www.airbus.com/store/mm_repository/pdf/att00011726/media_object_file_ListPric es2008.pdf  http://www.boeing.com/commercial/prices/  http://www.boeing.com/commercial/737family/pf/pf_900ER_fact.html  http://www.airbus.com/en/aircraftfamilies/a330a340/a330-200  http://www.icao.int/icao/en/ro/allpirg/allpirg4/wp28app.pdf

 Using an operating cost model to analyse the selection of aircraft type on short-haul routeshttp://www.saice.org.za/Portals/0/pdf/journal/vol48-2-2006/vol48_n2_a.pdf