Data Envelopment Analysis (DEA) method is a non-parametric statistical approach used in economics that serves as a comparative analysis considering operational efficiency, profitability and productivity of the selected companies by considering their respective raw material cost, expenses for power and fuel, salary and wages and Operating Revenue. Finally, the paper also attempts to understand how the companies are affected from the ongoing Covid-19 pandemic. DEA with constant returns to scale (CRS) has been used with the help of Excel Solver to evaluate the operational efficiency of top 5 Automobile companies in the Indian market. Super efficiency is calculated to rank the organizations in cases with efficiency of 1. A descriptive statistical analysis has been made based on the data obtained to understand the relative efficiencies of the organizations and how the pandemic induced lockdown has affected the automobile industry. The efficiency and super efficiency values evaluated, found that most organizations with the exception of Tata Motors are operating efficiently and have further room to expand their operations.

3.
M.
Popovic
,
M.
Kuzmanović
,
G.
Savić
,
2018
,
A comparative empirical study of Analytic Hierarchy Process and Conjoint Analysis: Literature review
Decision Making: Applications in Management and Eng.
,
1
(
2
), pp.
153
163
.
4.
D.
Nandy
,
2012
,
Efficiency Study of Indian Automobile Companies Using DEA Technique: A Case Study of Select Companies
The IUP J. of Operations Management
10
(
4
), pp
39
50
.
5.
N.
Kumar
,
A.
Satya
,
R.M.
Singari
,
2017
,
Evaluation of Efficiency of Automobile Manufacturing Companies in India Using Data Envelopment Analysis
Int. J. of Advanced Production and Industrial Eng.
,
2
, pp.
2455
8419
.
6.
S.
Murugan
,
T.R. Ganesh
Babu
and
C.
Srinivasan
,
2017
Underwater Object Recognition Using KNN Classifier
Int. J. of M.C. Square Sci. Res.
,
9
(
3
), pp.
48
52
.
7.
S.
Murugan
,
B.
Anjali
and
T. R.
Ganeshbabu
,
2015
Object recognition based on empirical wavelet transform
Int. J. of MC Square Sci. Res.
,
7
(
1
), pp.
74
80
.
8.
G.
Oggioni
,
R.
Riccardi
,
R.
Toninelli
,
2011
,
Eco-efficiency of the world cement industry: A data envelopment analysis
.
Energy Policy
,
39
(
5
), pp.
2842
2854
.
9.
M.
Karimzadeh
,
2012
,
Efficiency Analysis by using Data Envelop Analysis Model: Evidence from Indian Banks
Int. J. of Latest Trends in Finance and Economic Sc.
,
2
(
3
), pp.
228
237
.
10.
N.
Ferreira
,
A. Mendonça
Souza
,
2015
,
Efficiency in Stock Markets with DEA: Evidence from PSI20
Int. J. Latest Trends Fin. Eco. Sc
,
5
(
1
).
11.
A.
Mansouri
,
E.
Naser
,
M.
Ramazani
,
2014
,
Ranking of Companies based on TOPSIS-DEA Approach Methods
.
Pakistan J. of Statistics and Operation Res.
,
10
(
2
), pp.
189
.
12.
M.
Abbasi
,
M.A.
Kaviani
,
2016
,
Operational efficiency-based ranking framework using uncertain DEA methods
An Application to the Cement Industry in Iran
,
54
(
4
), pp.
902
928
.
13.
G.
Prakash
,
B.
Vyas
,
V.R.
Kethu
,
2014
,
Secure & efficient audit service outsourcing for data integrity in clouds
Int. J. of MC Square Scientific Res.
,
6
(
1
), pp.
5
60
.
This content is only available via PDF.
You do not currently have access to this content.