A STUDY ON LIQUIDITY ANALYSIS OF SELECTED …apjor.com/downloads/190920163.pdf · The automobile...

Asia Pacific Journal of Research ISSN (Print) : 2320-5504

ISSN (Online) : 2347-4793

www.apjor.com Vol: I. Issue XLIII, September 2016

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A STUDY ON LIQUIDITY ANALYSIS OF SELECTED AUTOMOBILE

COMPANIES IN INDIA

1Ms. A.NILAFOR NISHA,*

2 Dr. S. DAVID SOUNDARARAJAN

1PH.D RESEARCH SCHOLAR, CHIKKANNA GOVERNMENT ARTS COLLEGE, TIRUPUR

2ASSISTANT PROFESSOR OF COMMERCE, CHIKKANNA GOVERNMENT ARTS COLLEGE , TIRUPUR.

ABSTRACT

The automobile industry is one of the key drivers that boosts the economic growth of the country. Since the de-licensing of the

sector in 1991 and the subsequent opening up of 100 percent FDI through automatic route, Indian automobile sector has come a long

way. The automobile sector today is one of the key sectors of the country contributing majorly to the economy of India. It directly and

indirectly provides employment to over 10 million people in the country. The Indian automobile industry has a well established name

globally being the second largest two wheeler market in the world, fourth largest commercial vehicle market in the world, and

eleventh largest passenger car market in the world and expected to become the third largest automobile market in the world only

behind USA and China. The Indian auto industry is one of the largest in the world. The industry accounts for 7.1 percent of the

country’s Gross Domestic Product(GDP).The industry has attracted Foreign Direct Investment(FDI) worth US 14.32 billion during

the period April 2000 to December 2015,according to data released by Department of Industrial Policy and Promotion(DIIP).

INTRODUCTION

Transport sector plays a key role in a country’s economic growth and development. Transportation throughout the world has

made possible unprecedented level of mobility across the geographical boundaries. Automobile industry is a major constituent of

surface transport. Automobiles include passenger cars, commercial vehicles, two and three wheelers; India has growing market

potential for automobiles due to rise in demand. India has emerged as Asia’s fourth largest exporter of automobiles, behind Japan,

South Korea and Thailand. There are two views of the financial strength of every organization based on the period of lending i.e., the

short term and long term. Short term financial strength relates to the technical solvency of an organization in the near future, while the

long term financial strength depends on the structure that has been imposed in financing more permanent asset requirements. The

present study focuses on short term liquidity position of selected Automobile companies in India. In financial analysis, a ratio is used

for evaluating the financial performance of a company.

STATEMENT OF THE PROBLEM

In India, the automobile industry is one of the largest industries. It is one of the key sectors of the economy. The industry has

shown great advances since de-licensing and opening up of the sector to Foreign Direct Investment (FDI) in 1991-92. It has deep

forward and backward linkages with the rest of the economy, and hence has strong multiplier effect. The automobile industry




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including manufacturing of component is estimated to provide employment directly to approximately 5 lakhs of people and indirectly

to around 50million people. This results in the automobile industry being the driver of economic growth and India is keen to use it as a

level of accelerated growth in the country.Since the Automobile companies face threats to their viability, this study bears a relevance

to the present problems. This study is made to know the liquidity, profitability, solvency position against the background above

situation. Under this environment, the researcher considered it necessary to study financial performance of Automobile industries with

the following objectives.

REVIEW OF LITERATURE

Narayanan K. (1997) has attempted to analyze the effects of de-regulation policy introduced in India during eighties on technology

acquisition and competitiveness in the Indian automobile industry. Following evolutionary theoretical framework, the study argues

that asymmetry among firms in terms of technology acquisition explain much of the firm level differences in competitiveness.

Asymmetry in technology acquisition is largely due to differences in the firms' ability to bring about technological paradigm. The

results of the econometric exercise support the view that, even in the era of capacity licensing, development of competitive skills

crucially dependent upon the ability to build specific technology advantages. This is achieved successfully by complementing

imported technology with in-house technological efforts. Competitiveness in a deregulated regime would, however, depend upon the

ability of the firm to bring about technological paradigm shifts. New firms which are dependent on intra-firm transfer of technology

and firms with in-house R & D efforts, to accomplish paradigm shifts, appear more successful. Furthermore, in a liberal regime,

advantages of vertical integration also appear to be important determinants of competitiveness.

Dr. A. Vijayakumar (2012) made a study on Economic Value Added (EVA) And Other Accounting Performance Indicator: An

Empirical Analysis Of Indian Automobile Industry with the objective to study examine whether EVA has got a better predictive

power relative to the traditional accounting measures such as EPS, ROCM, RONW, capital productivity and labour productivity. The

study supports the claim that the EVA is the better predictor of market value compared to other accounting measures. EVA are

analysed using trend analysis and regression analysis. The study concluded that the result showed that 53 per cent to 76 per cent of the

sample companies have registered negative EVA during the terminal years of the study period. The top five companies in generating

EVA include Bajaj Auto Ltd, Hero Honda Motors Ltd(two and three wheelers sector), Mahindra and Mahindra Ltd ( passenger cars

and multi utility vehicles sector), Ashok Leyland Ltd and Tata Motors Ltd(commercial vehicles sector). The study indicates that there

is strong evidence to support Stern Stewart’s claim that EVA is superior to the traditional performance measures in its association with

MVA.The period for this study covered ten years from 2004-05 to 2013-14.

OBJECTIVES OF THE STUDY

To analyse the short term financial position of the selected Automobile Companies in India.

HYPOTHESES

1. There is no significant difference of current ratio of selected Automobile Companies in India.

2. There is no significant difference of quick ratio of selected Automobile Companies in India.

PERIOD OF THE STUDY:

The period of the study covered ten years from 2004-05 to 2013-14.

METHODOLOGY

The study is based on secondary data. The data were collected from the official directory and database of CMIE namely

PROWESS. The data for this study has been selected based on stratified sampling technique. The Indian Automobile Industry consists

of two sectors namely (i) automobiles (ii) auto ancillaries The Automobiles consist 77 companies in the capital line database. Out of

which 17 public limited companies have been selected on the basis of availability of 10 years (financial year) data from March 2004-

05 to March 2013-14. The study concentrates on automobile sectors includes Lcv/ hcv - 4 companies, Motor cycle - 3 companies,

Scooters - 4 companies, Tractor - 4 companies and passenger vehicles- 2 companies.

The list of the companies are with code: C1-Ashok Leyland Ltd,C2-Force Motors Ltd,C3-SML ISUZU Ltd,C4-Tata Motors

Ltd,C5-Hero Moto Corp Ltd,C6-Majestic Auto Ltd,C7-Tvs Motors Company Ltd,C8-Atul Auto Ltd,C9-Maharastra Scooters Ltd,C10-




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Scooters India Ltd,C11-VCCL Ltd,C12-Hind Motors Ltd,C13-Maruti Suzuki Ltd,C14-HMT Ltd,C15-International Tractors Ltd,C16-

Tractors and Farm Equipment Ltd and C17-VST Tillers Tractors Ltd.

STATISTICAL TOOLS

Statistical tools such as mean, standard deviation, variance and coefficient of variations are used to ascertain the liquidity and

solvency position of the selected automobile companies in India. ANOVA is used to this study.

LIMITATIONS OF THE STUDY

The study is based on secondary data obtained from the published annual reports and as such its finding depends entirely on

the accuracy of such data. Non-availability of some required financial data for the period of study has restricted the size of the sample.

Therefore, the limitation of the small sample is also prevalent in this study.

ANALYSIS OF SHORT TERM FINANCIAL OR LIQUIDITY POSITION

Liquidity refers to the ability of a firm to pay its short term obligations as and when these become due. The short-term

obligations are met by realizing amounts from current, floating or circulating assets. The current assets should either be liquid or near

liquidity. These should be convertible into cash for paying obligations of short term nature.

To measure the liquidity of a company, the following ratios can be calculated:

1. Current ratio

2. Quick ratio

1.CURRENT RATIO

Current ratio may be defined as the relationship between current assets and current liabilities. It is a measure of general

liquidity and it is most widely used to make the analysis of a short-term financial position or liquidity of a firm.

Current Assets

Current ratio = -------------------

Current Liabilities

TABLE . 4.1.CURRENT RATIO

S.NO

YR/C0M

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 AVG S.D C.V MIN MAX

1

2004-05

1.54 1.29 1.13 0.87 0.36 0.87 0.76 1.48 0.89 2.22 0.05 1.03 1.42 2.61 1.57 1.59 1.93 1.27 0.64 50.46 0.05 2.61

2

2005-06

1.5 1.17 1.24 1.08 0.42 0.88 0.84 1.32 0.89 1.93 0.04 0.88 1.73 2.17 1.86 1.49 1.86 1.25 0.57 45.36 0.04 2.17

3

2006-07

1.34 1 1.2 1.07 0.53 0.79 0.94 1.19 0.76 1.59 0.03 0.92 1.52 2.36 2.14 1.47 1.78 1.21 0.58 47.39 0.03 2.36

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4

2007-08

1.2 0.82 1.13 0.86 0.52 0.7 0.99 1.09 0.44 1.36 0.02 1 1.13 2.51 2.23 1.6 1.83 1.14 0.63 55.13 0.02 2.51

5

2008-09

1.22 0.82 1.13 0.63 0.47 0.66 0.97 1.07 0.65 1.07 0.02 0.87 1.22 2.28 2.5 1.8 1.87 1.13 0.65 57.48 0.02 2.5

6

2009-10

1.27 0.96 1.15 0.52 0.54 0.85 1.03 1.1 0.81 0.96 0.02 0.73 1.19 2.16 2.58 1.76 2.12 1.16 0.66 56.56 0.02 2.58

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2010-11

1.08 0.97 1.27 0.51 0.36 0.87 0.98 1.05 0.54 0.9 0.01 0.63 1.13 1.67 2.5 1.65 2.06 1.07 0.63 58.53 0.01 2.5

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2011-12

0.87 1.59 1.34 0.5 0.25 0.84 0.81 1.16 0.76 0.73 0 0.54 1.08 1.34 2.44 1.8 1.95 1.06 0.63 59.74 0 2.44

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2012-13

0.77 2.03 1.35 0.44 0.41 0.91 0.8 1.37 1.4 0.9 0 0.52 0.86 1.25 2.05 1.81 2.5 1.14 0.67 59.05 0 2.5

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2013-14

0.72 1.66 1.45 0.43 0.51 1.15 0.85 1.57 0.89 2.07 0 0.59 0.69 1.68 1.77 1.85 2.34 1.19 0.66 55.75 0 2.34

11 AVG 1.15 1.23 1.239 0.691 0.437 0.85 0.897 1.24 0.8 1.37 0.01 0.77 1.197 2.003 2.16 1.68 2.02

12 S.D 0.28 0.41 0.112 0.256 0.095 0.13 0.095 0.18 0.26 0.55 0.01 0.19 0.304 0.484 0.34 0.14 0.23

13 C.V 25 33.1 9.047 37.02 21.63 15.5 10.62 14.9 32.3 39.8 90.9 24.9 25.4 24.14 16.1 8.33 11.6 IND.AVG:1.16

14 MIN 0.72 0.82 1.13 0.43 0.25 0.66 0.76 1.05 0.44 0.73 0 0.52 0.69 1.25 1.57 1.47 1.78

15 MAX 1.54 2.03 1.45 1.08 0.54 1.15 1.03 1.57 1.4 2.22 0.05 1.03 1.73 2.61 2.58 1.85 2.5

Source: Annual Reports, Prowess Database

Table 4.1 explains the current ratio of selected automobile companies in India during the study period from 2004-05 to 2013-

14.The industry average ratio was 1.16.Analysis the companies individually will show the liquidity of the particular company. The

company C1 has mean ratio of 1.15 and ranged between 1.54 and 0.72 with the standard deviation of 0.29 and C.V of 25 percent. The

company C2 has mean ratio of 1.23 and ranged between 2.03 and 0.82 with the standard deviation of 0.41 and C.V of 33.1 percent.

The company C3 has mean ratio of 1.24 and ranged between 1.45 and 1.13 with the standard deviation of 0.11 and C.V of 9.05

percent. The company C4 has mean ratio of 0.69 and ranged between 1.08 and 0.43 with the standard deviation of 0.26 and C.V of 37

percent. The company C5 has mean ratio of 0.44 and ranged between 0.54 and 0.25 with the standard deviation of 0.09 and C.V of

21.6 percent. The company C6 has mean ratio of 0.85 and ranged between 1.15 and 0.66 with the standard deviation of 0.13 and C.V

of 15.5 percent. The company C7 has mean ratio of 0.9 and ranged between 1.03 and 0.76 with the standard deviation of 0.1 and C.V

of 10.6 percent. The company C8 has mean ratio of 1.24 and ranged between 1.57 and 1.05 with the standard deviation of 0.18 and

C.V of 14.9 percent. The company C9 has mean ratio of 0.8 and ranged between 1.4 and 0.44 with the standard deviation of 0.26 and

C.V of 32.3 percent. The company C10 has mean ratio of 1.37 and ranged between 2.22 and 0.73 with the standard deviation of 0.55

and C.V of 39.8 percent. The company C11 has mean ratio of 0.02 and ranged between 0.05 and 0 with the standard deviation of 0.02

and C.V of 91 percent. The company C12 has mean ratio of 0.77 and ranged between 1.03 and 0.52 with the standard deviation of

0.19 and C.V of 25 percent. The company C13 has mean ratio of 1.2 and ranged between 1.73 and 0.69 with the standard deviation of

0.3 and C.V of 25.4 percent. The company C14 has mean ratio of 2 and ranged between 2.61 and 1.25 with the standard deviation of

0.48 and C.V of 24.1 percent. The company C15 has mean ratio of 2.16 and ranged between 2.58 and 1.57 with the standard deviation

of 0.35 and C.V of 16.1 percent. The company C4 has mean ratio of 0.69 and ranged between 1.08 and 0.43 with the standard

deviation of 0.26 and C.V of 37 percent. The company C16 has mean ratio of 1.68 and ranged between 1.85 and 1.47 with the

standard deviation of 0.14 and C.V of 8.33 percent. The company C17 has mean ratio of 2.02 and ranged between 2.5 and 1.78 with

the standard deviation of 0.24 and C.V of 11.6 percent.




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The year wise analysis shows fluctuating trend. From 2005 to 2007 the mean ratio were more than the industry average

1.16,but later it was slightly decreased during the year 2008 and 2009 and it was equal to the industry average during the year 2010.

The mean ratio were lower than the industry average during the year 2011 to 2013 and it was higher than the industry average during

the year 2014.To conclude, companies namely C2,C3,C8,C10,C13,C14,C15,C16 and C17 were above the industry average 1.16.

These companies were having good proportion of current assets and current liabilities during the study period. The other companies

were having very less current ratio. They are not even up to the industry average, 1.16. These companies should improve their current

ratio. The company C10 and C17 maintaining current ratio of 2.07 and 2.34 were above the ideal ratio 2:1 , it should reduce its current

assets.

ANOVA –CURRENT RATIO

Source of Variation Sum of squares Degrees of

freedom Mean square F P-value F Crit Remarks

Between Groups 52.89348471 16 3.305843 42.51513 5.24E-48 1.710007 NS

Within Groups 11.8968 153 0.077757

Total 64.79028471 169

S.NO

YR/C0M

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 AVG S.D C.V MIN MAX

1

2004-05

1.36 0.67 0.896 0.839 0.233 1.129 0.548 2.368 0.521 1.669 0.00 0.71 1.434 5.323 1.42 1.37 1.51 1.29 1.19 91.81 0.09 5.32

2

2005-06

0.94 0.72 1.229 1.077 0.381 1.113 0.507 1.271 0.529 1.683 0.00 0.51 1.446 4.422 1.65 1.19 1.14 1.16 0.95 82.09 0.00 4.42

3

2006-07

0.92 0.57 1.206 1.037 0.431 0.808 0.679 1.271 0.459 1.093 0.00 0.71 1.205 5.028 1.35 1.31 1.39 1.14 1.07 93.53 0.00 5.03

4

2007-08

0.72 0.55 1.053 0.747 0.339 0.706 0.652 1.465 0.371 0.798 0.00 0.60 0.729 3.336 1.23 1.36 1.27 0.93 0.73 77.73 0.00 3.34

5

2008-09

0.85 0.6 1.248 0.674 0.334 0.783 0.926 1.168 0.884 0.829 0.00 0.42 1.349 3.339 2.10 1.60 1.13 1.07 0.76 71.17 0.00 3.34

6

2009-10

0.84 0.69 0.978 0.493 0.506 1.654 0.92 0.905 0.678 0.616 0.00 0.42 0.719 3.164 1.54 1.16 1.68 1 0.71 71.51 0.00 3.16

7

2010-11

0.50 0.52 0.937 0.551 0.109 1.512 0.607 0.472 0.389 0.579 0.00 0.37 1.094 1.887 1.61 1.32 1.24 0.80 0.54 68.01 0.00 1.89

8

2011-12

0.51 1.7 1.019 0.458 0.239 1.534 0.479 0.651 1.904 0.603 0.00 0.41 0.853 1.605 1.62 1.56 1.72 0.99 0.62 62.66 0.00 1.9

9

2012-13

0.64 0.95 1.393 0.317 0.406 1.249 0.561 1.066 1.254 0.925 0.00 0.22 0.663 1.293 0.98 1.36 2.24 0.91 0.54 59.74 0.00 2.24

10

2013-14

0.71 1.01 0.605 0.206 0.389 1.491 0.596 1.411 0.562 1.99 0.00 0.63 0.544 3.546 0.82 1.59 1.20 1.02 0.83 82.15 0.00 3.55

AVG 0.80 0.80 1.056 0.639 0.336 1.198 0.647 1.205 0.755 1.079 0.00 0.50 1.003 3.294 1.43 1.38 1.45

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There is no significant difference in current ratio of selected Automobile companies in India. The analysis showed the not

significant result. It can be seen from the table that the calculated value of F was found as 42.515, while the table value of F was

1.711, at 5% level of not significance. The value of P, being more than the 0.05 percent level, the null hypothesis accepted and

alternative hypothesis rejected at 5% level of significance. So it proves that the no differences among the average of this group were

no significant and the average current ratio of the groups of the Indian Automobile industries does not much differ.

2. QUICK RATIO

Quick ratio also known as Acid test ratio or Liquid ratio, is a more rigorous test of liquidity than the current ratio. The term

liquidity refers to the ability of a firm to pay its short term obligations as and when they become due.

Quick Assets

Quick ratio = ----------------

Current Liabilities

TABLE . 4.2. CURRENT RATIO

Source: Annual Reports, Prowess Database

Table 4.2 explains the quick ratio of selected automobile companies in India during the study period from 2004-05 to 2013-

14. The industry average ratio was 1.04. Analysis the companies individually will show the liquidity of the particular company. The

company C1 has mean ratio of 0.8 and ranged between 1.36 and 0.5 with the standard deviation of 0.25 and C.V of 31.2 percent. The

company C2 has mean ratio of 0.8 and ranged between 1.7 and 0.52 with the standard deviation of 0.36 and C.V of 44.5 percent. The

company C3 has mean ratio of 1.06 and ranged between 1.39 and 0.61 with the standard deviation of 0.22 and C.V of 21.2 percent.

The company C4 has mean ratio of 0.64 and ranged between 1.08 and 0.21 with the standard deviation of 0.29 and C.V of 45.3

percent. The company C5 has mean ratio of 0.34 and ranged between 0.51 and 0.11 with the standard deviation of 0.12 and C.V of

34.2 percent. The company C6 has mean ratio of 1.2 and ranged between 1.65 and 0.71 with the standard deviation of 0.35 and C.V of

29 percent. The company C7 has mean ratio of 0.65 and ranged between 0.93 and 0.48 with the standard deviation of 0.16 and C.V of



64 percent. The company C10 has mean ratio of 1.08 and ranged between 1.99 and 0.58 with the standard deviation of 0.52 and C.V

of 47.9 percent. The company C11 has mean ratio of 0 and ranged between 0.01 and 0 with the standard deviation of 0 and C.V of

49.2 percent. The company C12 has mean ratio of 0.5 and ranged between 0.72 and 0.23 with the standard deviation of 0.16 and C.V

of 31.8 percent. The company C13 has mean ratio of 1 and ranged between 1.45 and 0.54 with the standard deviation of 0.34 and C.V

of 34.1 percent. The company C14 has mean ratio of 3.29 and ranged between 5.32 and 1.29 with the standard deviation of 1.39 and

C.V of 42.1 percent. The company C15 has mean ratio of 1.44 and ranged between 2.11 and 0.82 with the standard deviation of 0.37

and C.V of 25.5 percent. The company C15 has mean ratio of 0.69 and ranged between 1.08 and 0.43 with the standard deviation of

0.26 and C.V of 37 percent. The company C16 has mean ratio of 1.39 and ranged between 1.61 and 1.17 with the standard deviation

of 0.16 and C.V of 11.3 percent. The company C17 has mean ratio of 1.46 and ranged between 2.24 and 1.14 with the standard

deviation of 0.35 and C.V of 23.9 percent.

The year wise analysis shows decreasing trend. From 2005 to 2007 the mean ratio were more than the industry average

1.04,but later it was slightly decreased during the year 2008 and it was more than the industry average during the year 2009. The mean

ratio were lower than the industry average during the last five year. To conclude, companies namely C3,C6,C8,C10,C13,

C14,C15,C16 and C17 were above the industry average 1.04. These companies were having good proportion of liquid assets and

current liabilities during the study period. The other companies were having very less quick ratio. They are not even up to the industry

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12 S.D 0.25 0.35 0.224 0.289 0.115 0.347 0.157 0.519 0.483 0.516 0.00 0.16 0.342 1.387 0.36 0.15 0.34

13 C.V 31.2 44.5 21.24 45.29 34.18 29 24.29 43.1 64.03 47.87 49.1 31.8 34.12 42.10 25.4 11.2 23.9 IND.AVG:1.04

14 MIN 0.50 0.52 0.605 0.206 0.109 0.706 0.479 0.472 0.371 0.579 0.03 0.22 0.544 1.293 0.82 1.16 1.13

15 MAX 1.36 1.7 1.393 1.077 0.506 1.654 0.926 2.368 1.904 1.99 0.00 0.71 1.446 5.323 2.10 1.60 2.24




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average, 1.04. These companies should improve their quick ratio. The company C14 maintaining quick ratio of 3.55 was above the

ideal ratio 1:1 , it should reduce its quick assets.

ANOVA – QUICK RATIO

Source of Variation Sum of squares Degrees of

freedom

Mean

square F P-value F Crit Remarks

Between Groups 79.50123775 16 4.968827 23.46156 2.74E-33 1.710007 NS

Within Groups 32.40324546 153 0.211786

Total 111.9044832 169

There is no significant difference in quick ratio of selected automobile companies in India. The analysis showed the not

significant result. It can be seen from the table that the calculated value of F was found as 23.46, while the table value of F was 1.711,

at 5% level of significance. The calculated value of F, being more than the table value of F, the null hypothesis rejected at 5% level of

significance. So it proves that the no differences among the average of this group were significant and the average quick ratio of the

groups of the Indian Automobile industries does much differ.

SUGGESTIONS

1.To strengthen the financial efficiency, long-term funds have to be used to finance on core current assets and a part of temporary

current assets. It is better if the companies can reduce the oversized short term loans and advances and eliminate the risk by arranging

finance regularly.

2. Improper planning and delays in implementation of projects lead to a rise in their cost. So proper planning should be done to

standardize and optimize the use of cash balance, proper techniques may be adopted for planning and control of cash. The investments

in inventories should be reduced

3.The few companies, which did not follow a definite policy of financing current assets, should follow short term sources of finance

CONCLUSION

The Automobile sector has huge demand in our country. This demand attracts the giant automobile suppliers throughout the

world to come and invest in the Indian Automobile Industry. The findings of the study strongly suggest that the financial sources and

their significant improvements. Almost all the select companies in the Automobile Industry entered into foreign collaborations after

liberalization of FDI policies which led to increase in performance of this industry. Government should encourage export of this

industry by providing required infrastructure and reliefs to enhance performance. It should continue the importance given to this

industry to have a better growth of our economy.

REFERENCES

1. K. Narayanan (1997), “Technology Acquisition, De-regulation and competitiveness: A study Of Indian Automobile

Industry’’,discussion paper No.3, Institute for New Technologies, United Nations University.

2. Maksymiuk (2006), “The Attractiveness of the Automotive Industry in Poland for Foreign Direct Investments” ,Working Paper No.

2, MBA Poznao-Atlanta, ISSN: 1895- 5479.

3. Kale Dinar (2011), “Sources of Innovation and Technology Capability Development in the Indian Automobile Industry”,

Innovation Knowledge Development, The Open University, Working paper No.60.

4. Ray Sarbapriya (2012), “An Insight into the Performance of Indian Automobile Industry,” Science Education Development

Institute, ISSN: 2276 – 6715, Vol. 2(5), pp 191-197




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5. 1Amarjit Singh, 2Dr. Vinod Gupta (2012), “Impact of Financial Globalisation on Automobile Industry: Indian Perspective”,

International Journal of Research in Mechanical Engineering and Technology,Vol. 2, Issue No.2, ISSN : 2249-5762 (Online) | ISSN :

2249-5770 (Print)

6. Dr. A. Vijayakumar (2012), “A study on Economic Value Added (EVA) And Other Accounting Performance Indicator: An

Empirical Analysis Of Indian Automobile Industry”, International Journal of Marketing and Technology, Volume 2, Issue

No.3, ISSN: 2249-1058

7. A.Dharmaraj and Kathirvel , “Financial Performance of Indian Automobile Industry – A Comparative study during pre and post

foreign Direct Investment”, International Journal of Scientific Research, Vol.2,issue .9 ,ISSN 2277-8179.

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