Management Accounting Report: Airline Cost Function Analysis

This report analyzes the cost functions of Delta and JetBlue airlines using management accounting techniques. The analysis begins with a comparison of the high-low method to determine fixed and variable costs for both airlines, focusing on salary and revenue passenger mile data. The report then applies linear regression to further analyze the cost functions, providing detailed regression statistics for both companies. The findings indicate that JetBlue operates at a significantly lower cost compared to Delta, with lower fixed and variable costs. The report also examines the implications of these cost structures, suggesting that Delta should focus on reducing costs and the potential for low-cost airline brands. The report concludes by proposing strategies for increasing profitability, such as introducing low-cost carriers and optimizing flight operations.

Running head: MANAGEMENT ACCOUNTING
Management Accounting
Name of the Student:
Name of the University:
Author Note

1MANAGEMENT ACCOUNTING
Table of Contents
Discussion Paper 1....................................................................................................2
Answer to Question 1................................................................................................2
Answer to Question 2................................................................................................3
Answer to Question 3................................................................................................4
Answer to Question 4................................................................................................5
Answer to Question 5................................................................................................5
References.................................................................................................................7

2MANAGEMENT ACCOUNTING
Discussion Paper 1
Answer to Question 1
Particulars Delta JetBlue
Salary Cost:
Highest 1,607,000,000 49000000
Lowest 1,037,000,000 16000000
Range 570,000,000 33,000,000
Revenue Passenger Mile:
Highest 21800000 2016200
Lowest 14000000 599400
Range 7,800,000 1,416,800
Variable Expenses 73.07692308 23.29192547
Fixed Expenses 13923076.92 2038819.876
Cost function
73.08x
[phone]
23.29x +
2038820
The conclusions that can be derived from the comparison of both the cost
functions are that the fixed costs of Delta appear to be high in comparison to that
of JetBlue. This indicates the fact that the firm should consider reducing the costs
of production to increase the total revenue incurred. The fixed cost however, that is
incurred by JetBlue is less in comparison to Delta. The variable cost that is
incurred by the firm is also less. This evidently indicates the fact that the cost for
producing the specified services by JetBlue has been low. A cost function refers to
the total cost that is incurred by a firm when the quantity of production has been
specified. The driver however, in the mentioned question is Revenue Passenger
Miles. The comparisons that can be made out of the different cost functions is that
JetBlue operates at a significant less cost in comparison to Delta.

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Answer to Question 2
SUMMARY OUTPUT -
DELTA
Regression Statistics
Multiple R
0.42004
056
R Square
0.17643
4072
Adjusted R
Square
0.15476
1285
Standard Error
1691418
96.6
Observations 40
ANOVA
df SS MS F
Significa
nce F
Regression 1
2.329E+1
7
2.33E
+17
8.140
811
0.00696
7209
Residual 38
1.08714E
+18
2.86E
+16
Total 39
1.32004E
+18
Coefficie
nts
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
5772635
92.5
2438771
54.1
2.367
026
0.023
129
8356010
4.96
1070967
080
835601
05
1070967
080
Revenue
Passenger Mile
38.2383
6393
13.40187
183
2.853
211
0.006
967
11.1076
9281
65.3690
3504
11.1076
928
65.3690
3504
Cost Function: 38.24x + 577263592
SUMMARY OUTPUT -
JETBLUE
Regression Statistics
Multiple R
0.9867929
21
R Square
0.9737602
69
Adjusted R
Square
0.9685123
23

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Standard Error
1923292.0
71
Observations 7
ANOVA
df SS MS F
Significa
nce F
Regression 1
6.86362E
+14
6.86E
+14
185.5
507
3.82288
E-05
Residual 5
1.84953E
+13
3.7E+
12
Total 6
7.04857E
+14
Coefficients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
3878344.8
75
2268027.
403
1.710
008
0.147
956
-
1951805
.169
970849
4.919
-
195180
5.17
970849
4.919
Revenue
Passenger Mile
21.545861
34
1.581730
627
13.62
17
3.82E
-05
17.4798
9332
25.6118
2936
17.4798
933
25.6118
2936
Cost Function:
21.55x +
3878345
Answer to Question 3
The cost function that has been obtained by the methods of linear regression
shows a significant change in the cost functions of the two different companies.
However, the derived conclusions do not change. In case of the regression analysis
it has been found out that the variable costs for Delta has decreased but the fixed
costs have unprecedentedly increased. In case of JetBlue, both the fixed costs and
the variable costs have decreased indicating that the costs that have been incurred
for the producing the specified services have been lower in comparison to the cost
function that has been determined with the regression analysis. However, it should
be noted here that the conclusions that have been arrived at, both in the cases of
high low method and the regression analysis has been similar.

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Answer to Question 4
The major area where Delta appears to lose the essential revenues of
business is the high costs of service that is charged by the airlines company from
its customers that appears to be out of the range of affordability by the mass. The
particular fact that the airlines company was not being able to generate revenue,
resulted in the company launching a low cost airline brand named Song. The high
costs that have been incurred firm in regards to the fuel costs have also resulted in
the project named Song (Vriens, Alves, & Chen, 2017). The new segment should
in all probabilities would be a success. This is due to the following reasons:
 The flights of the low cost air carrier will run for a price that ranges between
$79 to $299
 Delta is also considering substituting Delta Express with Song and has spend
$65 million to launch the same
 The customer experience provided by Song is also promised to be different
so that the unique selling point of the low cost air carrier service is properly
presented to the customers
Answer to Question 5
The solutions that can be implemented by the airlines companies for
increasing the profitability of the firm are as follows:
 The introduction of the low cost air carriers in order to obtain the required
amount of profits can be a sustainable solution
 In addition to the above specified solution, the airlines company should
remove the facilitation of agency booking which will increase the profit
derived from online flight bookings

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 The airlines company should also consider increasing the daily number of
flights. This will increase the revenue incurred.
 The airlines company should also consider covering long distance flights so
that the customers get the facility of travelling long distances without
having to pay a huge amount (Clewlow, Sussman & Balakrishnan, 2014)

7MANAGEMENT ACCOUNTING
References
Clewlow, R. R., Sussman, J. M., & Balakrishnan, H. (2014). The impact of high-
speed rail and low-cost carriers on European air passenger traffic. Transport
Policy, 33, 136-143.
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets
for low cost carriers: An application of the unified theory of acceptance and
use of technology (UTAUT) model. Tourism Management, 43, 70-88.
Gittell, J. H., & Kochan, T. A. (2016). Partnering to Help a Changing Industry:
The Airline Industry Council. Members-only Library, 8(2).
Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B. (2015). An SEM–artificial-
neural-network analysis of the relationships between SERVPERF, customer
satisfaction and loyalty among low-cost and full-service airline. Expert
Systems with Applications, 42(19), 6620-6634.
Vriens, M., Alves, A. M., & Chen, S. (2017). Brand segmentation using implicit
brand measures. Applied Marketing Analytics, 3(2), 172-182.