research on commercial vehicles

Indian Commercial Vehicle Industry

“Factors -favorable or Unfavorable”

Submitted by-Gaurav Gupta

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CONTENTS

Title Page number

Chapter-1 Introduction

1.1 Overview 3

1.2 What is shaping India’s commercial vehicle industry 4

1.3 Summary 4

Chapter-2 Research methodology

2.1 Introduction 5

2.2 Need for study 5

2.3 Statement of the problem 5

2.4 Research objectives 5

2.5 Hypothesis 6

2.6 Literature review 6

2.7 Survey method 7

2.8 Sampling 8

2.9 Data collection 9

2.10 Method of data analysis 9

2.11 Summary 9

Chapter-3 Data Analysis & Interpretation

3.1 Introduction 10

3.2 Demographic details of the respondents 10

3.3 Frequency of response 11

3.4 Descriptive statistics 11

3.5 Testing of hypothesis 12

3.6 Summary 17

Chapter-4 Summary, Finding, Conclusions and Recommendations

4.1 Summary 18

4.2 Findings 18

4.3 Limitation 18

4.4 Conclusions 19

4.5 Recommendation 20

Appendix A- Questionnaire 21

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Executive Summary

Scope & objective

The aim of the study made through this project is to know the impact of the various

factors on the demand of commercial vehicles in India & use various statistical tools to

substantiate the results.

Research methodology

1. research design

2. sampling plan

3. instruments of collection of data

4. data analysis and interpretation

The questionnaire method is adopted for the collection of data. The level of agreement to

the 13 statements are allowed to mark in 5 point score Likert-scale. The sample has been

drawn from the population based on the judgment method. The duly filled questionnaire

is collected from the respondents. The frequency and descriptive statistical analysis of

responses are carried out. The statistical approach ANOVA, T test is used for the analysis

of responses.

Conclusion

Various factors contribute in the increase in sales & demand of commercial vehicles in

India & based on the questionnaire survey conducted we can conclude that manufacturing

process , freight rate , fuel price , road connectivity will affect the demand & sales of

commercial vehicles in India.

Limitation

Within the limit period of time it is too difficult to cultivate in a whole market. Cost is

also a major factor of pushing back to us in our research.

Recommendation

The research analysis recommended that the company & government may look into the

following aspects reviewed in this research in Likert-scale, to increase sales & demand of

commercial vehicles.

Improvement in manufacturing process

Reduction in freight rate

Reduction in fuel price

Reduction in interest rate

Improvement in road connectivity

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Chapter 1

Introduction

1.1 Overview

The Indian commercial vehicles (CV) industry has a long history, possibly dating back to

the passenger vehicles industry. Telco, the first entrant in the segment, continues to be the

largest till date, with a market reach unrivalled by its competitors. Telco pioneered

production of commercial vehicles in the country with technical collaboration with

Daimler-Benz of Germany in 1954.

The industry has made a significant contribution to the country’s industrialization and

progress. In fact, India achieved self-sufficiency in commercial vehicles, except in the

high-tonnage classes, where the demand has nonetheless been limited. The entry of

Ashok Leyland, with technology from British Leyland, marked the beginning of

competition in the truck and bus segment

Emerging from a two year down cycle

After two years of down cycle, some segments of the domestic Commercial Vehicle (CV)

industry have shown signs of recovery in FY 2015. In the first ten months of the fiscal,

the pace at which domestic CV sales have been declining has reduced to 4.6% compared

to a contraction of 20.2% witnessed during FY 2014(Exibit-1). Within the CV space, the

Medium & Heavy Commercial Vehicle (M&HCV) Truck segment has in fact posted

a positive growth of 19.0% in 10m FY 2015 while the HCV (16T+) segment,

which accounts for almost half of total M&HCV (Truck) sales has been witnessing

strong demand (up 42.6% in 10m FY 2015) on back of replacement demand (following

two years of deferment) and capacity addition by organized fleet operators to

some extent.

While the M&HCV Truck segment seems to have bottomed out, the LCV Truck

segment is still experiencing sluggish trends (down13.8% YoY) as significant

capacity addition over the past few years and constrained financing environment amidst

rising delinquencies remains a challenge for the segment.

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1.2 What is shaping India’s commercial vehicle industry?

After a few years of strong growth, the Indian commercial vehicle (CV) industry hit a

rough patch last year, impacted by the overall economic slowdown, delay in

infrastructure projects and weak investment sentiment. However, the industry has long-

term growth potential, subject to the economy accelerating back to 7–8% GDP growth

per annum and the government expediting policies that support growth in manufacturing

and infrastructure development While deregulation of diesel prices will make the industry

dependent on subsidies, it is likely to create demand uncertainty in the short-term as truck

owners and manufacturers adjust to the new normal

To prepare for the years ahead, industry participants in the Indian CV industry should

answer the following questions to evaluate how well they are positioned to respond to the

emerging opportunities and challenges:

How will the demand & sales of trucks (Heavy vehicles) evolve?

How will products need to adapt?

How will business models need to adapt?

What are the new market dynamics?

What are the supply or value chain issues and implications?

With respect to above industry analysis we had identified following mega trends that are

likely to impact and change the face of the Indian CV industry

1.3 Summary

In this context we will identify the most important factors among the 6 factors that will

impact the sales & demand of commercial vehicles in India. With this project we also

identify new factors that can impact the demand of commercial vehicles in India

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Chapter 2

Research methodology

2.1. Introduction

According to Green and Tall “A research design is the specification of the methods and

procedures for acquiring the information needed. It is the overall operational pattern or

framework of the project that stipulates which information is to be collected, from where

it is to be collected and by what procedures.”

The research methodology used is to evaluate the accuracy and effectiveness of the

findings & its effect on demand of commercial vehicles. The quantitative data is collected

by questionnaire method from a convenience sample. The responses are analyzed and

arrived at conclusions

2.2. Need for study

1. Crucial role in Make in India campaign

2. Very crucial for Indian growth story as it is a major component of supply chain of

goods and transport

3. The project is of interest to both domestic and international automobile

manufacturers

2.3 Statement of purpose

The study is aimed at to evaluate the various factors which affect the demand & sales of

commercial vehicle in India.

2.4 Research objectives

It’s always better to start your search with a predefined objective, rather than beating

around the bush. An objective will give you a direction to work upon and proceed your

further research. Therefore, my project objective is,

Identify the various factors which affect the demand & sales of the commercial

vehicles in India.

Illustrate the way in which the identified factors affect the commercial vehicles.

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2.5 HYPOTHESIS

The suggested hypothesis for each of the research objectives is developed .The

hypothesis as per the research objectives are as follows

a) Interest rate , Fuel price & Freight rate will impact the sales of CV

b) Goods Roads and connectivity will improve sales of CV

c) Regulatory (legal) provisions will impact sales of CV.

d) Improvement in manufacturing process will increase sales of CV

2.6 LITERATURE REVIEW

The literature review is conducted to identify the similarities & differences among the

articles in research results, theoretical claims & methodological approaches. It will also

help us identify the open questions or directions for further research that authors identify

or questions that warrant further investigation. The literature review also explains the

relationship between material in the articles & research questions. The literature review is

helps to identify various gaps & limitation which will affect our research. The literature

review for our research is given below,

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The various findings from the literature are as follows,

1. The improvement in freight rate & infrastructure projects will increase the demand for

commercial vehicles in India.

2. The reduction in the interest rate & excise duty will bring back buyers.

3. Export to BRIC countries will improve sales

4. Improvemnet in manufacturing processes will result in high sales.

2.7 SURVEY METHOD

The research process based on primary data analysis and secondary data analysis will be

clearly defined to meet the objectives of the study.

1. Primary survey method- A questionnaire was designed in accordance with our

mentor in MDI. I chose a sample of about 50 respondent customers around the Delhi

NCR region from which I can get the instant information of whose analysis will give me

the desired outcome of my research project.

The questionnaire based survey is used in this study. The data collection and analysis is

carried-out based on statistical theories. The questionnaire is composed of 13 questions to

evaluate the response of the employees. The questionnaire was issued in person. The

questionnaire consists of different types of questions. The information about

demographic data of the participants is gathered using multiple choice questions (closed),

for which the respondents are required to tick the right answers. Demographic questions

are used to correlate the response between different types of groups. This is very

important to find whether the responses are consistent across the group. The main part of

the questionnaire, which is related to the hypothesis of the thesis, consists of likert-scale

questions. Answer to these questions helps to find how strongly the respondents agree

with the particular statement. The answers of the questions are based on the five-level

scale and options are strongly agree, agree, neither agree nor disagree, disagree, strongly

disagree. The questionnaire is given in Appendix A

1. Secondary survey method -collected some data from the secondary sources like

published Company documents, internet, literature etc. to substantiate my primary

data.

2.8 Sampling

In statistics and survey methodology, sampling is concerned with the selection of a subset

of individuals from within a statistical population to estimate characteristics of the whole

population. Two advantages of sampling are that the cost is lower and data collection is

faster.

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Probability samples are selected from the population and are considered as the

representative of the population. They provide the most valid or credible results because

they reflect the characteristics of the population from which they are selected. Non-

probability samples are not truly representative and less desirable than probability

samples. Non-probability samples are used when a researcher may not be able to obtain a

random or stratified sample, or it may be too expensive. A researcher may not care about

generalizing to a larger population. The validity of non-probability samples can be

increased by trying to approximate random selection, and by eliminating as many sources

of bias as possible.

In this study, judgment sampling is used. Judgment sampling is a non-probability

sampling technique where the researcher selects the sample based on judgment. In this

method, the researcher may decide to draw the entire sample from one "representative"

group identified, even though the population includes all such groups. When using this

method, the researcher must be confident that the chosen sample is truly representative of

the entire population. In the present study, the response was collected from the people in

& around the Delhi NCR region. Out of the sample population of 100 people, 50 people

responded. The response of 50 people was collected with the aid of questionnaire.

2.9 Data collection

The information in the thesis is collected by questionnaire method. The questionnaire was

composed of 13 questions relating to the parameters, interest rate, fuel price, freight rate,

operational efficiency, inventory management, after sales service, road connectivity. The

paper copies of questionnaire were given in hand to the respondents as well as online

survey is floated and requested to fill up.

The questionnaire consists of different types of questions. The information about

demographic data of the participants is gathered from the multiple choice question

(closed), for which just required that right answers be ticked by the respondents. The

main part of the questionnaire, which is focused to evaluate the postulates given in the

hypothesis, consists of Likert-scale questions. These questions help to find how strongly

the respondents agree with the particular statement. The answers to the questions are

based on the five-level scale and the options are strongly agree, agree, nether agree nor

disagree, disagree and strongly disagree.

2.10 Method of data analysis

The statistical analysis of the data collected based on the questionnaire is carried out. The

frequency of the responses is determined and compared. The score was assigned to the

options strongly agree, agree, nether agree nor disagree, disagree and strongly disagree

are 5 to 1. The minimum, maximum, mean, standard deviation and variance of the scores

of the responses corresponding to each statement is computed and reported in this thesis.

The descriptive statistical analysis is carried out using SPSS software.

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Cronbach's alpha is a measure of internal consistency, that is, how closely related a set of

items are as a group. Cronbach's alpha is coefficient or reliability. Cronbach's alpha is

given by

2

X

N

1i

2

iY

11N

N

where N is the number of components or statements and equal to 50 persons in the

present study. 2

X is the variance of observed test score and 2

iY is the component i in

the sample of persons.

Pearson’s correlation coefficient (r) is given by

n

1i Y

i

X

i YYXX

1N

1r

where

X

i XX

, X and X are the standard score, sample mean, and sample standard

deviation, respectively.

ANOVA is use to test the hypothesis the computation details for testing more than 2

parameters while T test is used for testing of 1 parameter or 2 parameters.

2.11 SUMMARY

The various aspects of design of experiments are described. The questionnaire method is

adopted for the collection of data. The level of agreement to the 13 statements are

allowed to mark in 5 point score Likert-scale. The sample has been drawn from the

population based on the judgment method. The duly filled questionnaire is collected from

the respondents. The frequency and descriptive statistical analysis of responses are

carried out.

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Chapter 3

DATA ANALYSIS AND INTERPRETATIONS

3.1 Introduction

The duly filled-up questionnaire was collected from 50 respondents in & around the

Delhi NCR region. The data of response is analyzed using SPSS & Microsoft excel

software. The ratio of the response to the total number of respondents is computed and

expressed in percentage. The response for the questions related to the subject area of the

study is collected in Likert-scale. The descriptive statistical method is also used to

analyze the data. The minimum, maximum, mean, standard deviation and variance have

been computed based on the five point scale response of the respondent.

3.2 Demographic details of the respondents

The first part of the questionnaire was designed to collect the demographic details of the

respondents. The demographic information gives the details of gender, age, education and

experience. The demographic information of the respondents are given in

Table .1. Gender statistics

The gender statistics of the respondents are given in Fig 5.1. The male respondents are

found to be 90 percent.

The age statistics of the respondents is given in Fig 5.2. The respondents having formal

age less than 35 years is found to 98 percent.

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The education statistics of respondents is given in Fig 5.3. The managers having formal

education greater than bachelors degree is found to 100 percent. The majority of the

respondents are well educated.

3.3 FREQUENCY OF response

The second part of the questionnaire is connected with hypothesis of the research. There

were 13 statements on various aspects of factors impacting the demand of commercial

vehicles in India and the respondents are requested to tick the level of agreement or

disagreement in a Likert scale.

3.4 Descriptive statistics

The statements in the questionnaire have been reviewed statistically. Descriptive statistics

quantitatively describes the main features of a collected data. For this purpose, the scores

assigned to various options are as follows:- 5 to ‘strongly agree’, 4 to ‘agree’, 3 to

‘neither agree or disagree’, 2 to ‘disagree’ and 1 to ‘strongly disagree’. The Descriptive

analysis is represented by maximum, minimum, standard deviation and variance

Statistics of scores of response for statements in questionnaire is given below in FigureA

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The minimum score for every statement in the questionnaire is given in second column of

Figure A. The highest score in second columns is 3, which corresponds to the response

‘uncertain’ and is for statement no. 1. The lowest score in the second column is 1, which

corresponds to the response ‘disagree’, and is for statement number 4 & 10. This

indicates that there is scope for improvement for the parameters pointed out in statement

number 4 & 10. The maximum score of the statements are given in third column of

Figure A. The maximum score for all statements is 5, which corresponds to the response

‘strongly agree’.

The mean of score is given in fourth column of Figure A. Higher the magnitude of mean

indicates that higher is the level of agreement on the statement and vice versa. Highest

magnitude of means is found to be 4.14 and is for statement number 8. This indicates that

the improvement in safety standards of commercial vehicles will improve sales. The

lowest magnitude of mean is found to be 3.14 and is found to be for statement number 4.

This indicates that availability of substitutes affect the sales only marginally. .

The standard deviation and variance of the score data indicate the spread of the data from

the mean and is given in Figure A. The deviation is 0.528 for statement number 1. This

indicates that the low interest rate & easy financing will increase the demand &

procurement of commercial vehicles. The deviation is 0.953 for statement number 7. This

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indicates that toll rate will not have large effect on demand & a sale of commercial

vehicles.The variance is indicative of variation from the mean. The variance is correlated

standard deviation; the arguments placed for standard deviation can be extended to

variance also 3.5 Testing of hypothesis

The initial questionnaire testing is given in Figure B. The hypothesis of the research work

was

e) Interest rate , Fuel price & Freight rate will impact the sales of CV

f) Goods Roads and connectivity will improve sales of CV

g) Regulatory (legal) provisions will impact sales of CV.

h) Improvement in manufacturing process will increase sales of CV.

The range of scores of the responses is 2 to 5. The magnitude of mean of scores is an

indication to the overall satisfaction level of respondent. The mean of scores is 3.687,

which is greater than mid value of maximum score (equal to 2.17).The deviation of

collected data from the mean is low and hence the interpretation based on mean is can be

acceptable. The variance is 0.801. Cronbach’s alpha is 0.754, a magnitude greater than

0.7 indicates that the data is reliable for testing the hypothesis.

The research hypothesis is to study the level of satisfaction of employees on the

performance appraisal of the company. The aspect of satisfaction is explicitly stated in

the questionnaire.

Hypothesis 1: Interest rate, Fuel price & Freight rate will impact the sales of Commercial vehicles

1. Reduction in interest rate will help the fleet owners to go for procurement of

new vehicles.

2. Deregulation of fuel prices will impact the commercial vehicles demand?

3. Do you agree that freight rate will affect the sales of CV? (CV-commercial

vehicle)

Parameter-1 Interest rate

Parameter-2 Fuel price

Parameter -3 Freight rate

The responses of the various statements in the questionnaire are combined to evaluate

each parameter. The sum of the scores of responses of statements is assumed to be the

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response of each of three parameters. The statistical analysis, namely, correlation

coefficient and ANNOVA F-test are carried out.

Analysis of variance is carried out for testing the hypothesis. F-statistics of the responses

for satisfaction and paratemeters1 to 3 is computed for testing hypothesis.

The null hypothesis is:-

The demand & sales of commercial vehicles is unrelated to Interest rate bank

charge for procurement of vehicle.

The demand & sales of commercial vehicles is unrelated to Fuel price

The demand & sales of commercial vehicles is unrelated to Freight rate.

Impact

N Mean Std.

Deviation

Std.

Error

95% Confidence Interval for

Mean

Minimu

m

Maximu

m

Lower Bound Upper Bound

interest

rate 50 3.92 .528 .075 3.77 4.07 3 5

fuel price 50 3.90 .580 .082 3.74 4.06 2 5

freight rate 50 3.76 .822 .116 3.53 3.99 2 5

Total 150 3.86 .656 .054 3.75 3.97 2 5

ANOVA

Impact

Sum of Squares Df Mean Square F Sig.

Between Groups .760 2 .380 .882 .416

Within Groups 63.300 147 .431

Total 64.060 149

The calculated F-value & significant value of ANOVA is given in Table 1. It may be

noted that the calculated significant value is 0.416, which indicate that the null hypothesis

is accepted and it may be concluded that the parameters, namely, interest rate, fuel price

& freight rate are not related to the demand of commercial vehicles.

Hypothesis 2: Goods Roads and connectivity will improve sales of CV

1. Roads connectivity will increase the sales & demand for commercial vehicle.

2. Good roads will increase the demand for commercial vehicle in a

Parameter-1 Roads connectivity

Parameter-2 Good roads



response of each of three parameters. The statistical analysis, namely, independent T test

will be used for statistical analysis.

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Analysis of variance is carried out for testing the hypothesis. T test statistics of the

responses and paratemeters1 to 2 is computed for testing hypothesis.


The demand & sales of commercial vehicles is unrelated to roads connectivity.

The demand & sales of commercial vehicles is unrelated to good roads.

The calculated significant value of T test is given in Table 1. It may be noted that the

calculated significant value is 0.143, which indicate that the null hypothesis is accepted

and it may be concluded that the parameters, namely, good road connectivity is not

related to the demand of commercial vehicles.

Hypothesis 3: Improvement in manufacturing process will increase sales of CV

1. Do you agree that improvement in operational efficiency will address demand?.

2. Efficient inventory management, i.e., keeping stock ready as soon as order is

placed, will enable increase in sales volume.

3. Do you agree that Focus on after-sales service will create demand of CV? (CV-

commercial vehicle).

Parameter-1 operational efficiency

Parameter-2 Inventory Management

Parameter-3 After sales service



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response of each of three parameters. The statistical analysis, namely, correlation

coefficient and ANNOVA F-test are carried out.

Analysis of variance is carried out for testing the hypothesis. F-statistics of the responses

for satisfaction and paratemeters1 to 3 is computed for testing hypothesis.


The demand & sales of commercial vehicles is unrelated to operational efficiency.

The demand & sales of commercial vehicles is unrelated to inventory

management.

The calculated F-value & significant value of ANOVA is given in Table 3. It may be

noted that the calculated significant value is 0.310, which indicate that the null hypothesis

is accepted and it may be concluded that the parameters, namely, operational efficiency,

inventory management,& after sales service are not related to the demand of commercial

vehicles

Hypothesis 4: Goods Roads and connectivity will improve sales of CV

1. Do you agree that CV which don’t follow statutory regulation of emission, there

demand will decrease?

2. Do you agree that CV (trucks) safety standards in vehicles will impact demand?

Parameter-1 Emission standard

Parameter-2 safety standard



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response of each of three parameters. The statistical analysis, namely, independent T test

will be used for statistical analysis.

Analysis of variance is carried out for testing the hypothesis. T test statistics of the

responses and paratemeters1 to 2 is computed for testing hypothesis.


The demand & sales of commercial vehicles is unrelated to emission standard.

The demand & sales of commercial vehicles is unrelated to safety standard.

The calculated significant value of T test is given in Table 1. It may be noted that the

calculated significant value is 0.041, which indicate that the null hypothesis is rejected

and it may be concluded that the parameters, namely, safety standards & emission rate is

related to the demand of commercial vehicles.

3.6 Summary

The data analysis & interpretation shows that our hypothesis that interest rate, fuel price,

freight rate, operational efficiency, inventory management, after sales service, road

connectivity will impact the sales & demand of commercial vehicles is accepted while

hypothesis that statutory regulations such as emission & safety standards is rejected.

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Chapter 4

2. Summary, findings, CONCLUSIONS AND

RECOMMENDATIONS

4.1 Summary

The effect of various factors on the demand & sales of commercial vehicles is studied..

The factors influencing the demand of commercial vehicles are identified. The

parameters, namely, interest rate , fuel price , freight rate , operational efficiency ,

inventory management , after sales service , statutory regulations(such as emission ,

safety) , substitutes , toll price ,road connectivity are considered for the analysis. A

questionnaire containing 13 statements is prepared and the response is collected. The

frequency of the responses is analyzed. The responses are mapped to a 5 point score

Likert’s scale. The descriptive statistical analysis of the score of the responses is carried

out using correlation, ANOVA, T test approaches.

4.2 FINDINGS

The findings of the questionnaire based research are:-

1. Majority of the respondent is males.

2. Majority of the respondent are in the age group of 25 to 35 years

3. Majority of the respondents is having formal education more than bachelors

degree

4. The descriptive statistical analysis indicated that the mean of the score is greater

than 3.0 for all 13 statements in the questionnaire

5. The standard deviation of the score is less than 1.0 for all 13 statements in the

questionnaire.

6. The mean score for all the questions and all the respondents is found to 3. 97.

7. The ANOVA indicated that the interest rate, fuel price & freight are not correlated

with demand of commercial vehicles with 95% confidence level.

8. The ANOVA indicated that the operational efficiency, after sales service &

inventory management are not correlated with demand of commercial vehicles

with 95% confidence level.

9. The T test indicated that the roads connectivity & demand of commercial vehicles

are not correlated.

10. The T test indicated that the statutory regulations such as emission rate, safety

standard are related to demand of commercial vehicles.

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4.3 Limitation of the study

1. Money was the major constraint during my project.

2. Duration of the study also limited for further intensive study.

3. Mostly stress was given on primary data collection and it was difficult to collect

secondary data from organization and dealers.

4. Limited coverage area was also a major constraint while conducting the study.

4.4 Conclusion

The analysis of the research suggests that fair improvement in various factors such as

interest rate, fuel price, freight rate, operational efficiency, inventory management, after

sales service, road connectivity is required to improve the demand of commercial

vehicles in India. Based on the questionnaire survey conducted, it can be concluded that

manufacturing process, roads connectivity, & reduction in freight rate, fuel price, and

interest rate will not affect the sales & demand of commercial vehicles.

4.5 Recommendation

The research analysis is done on the sample of 50 respondents which is not the correct

representation of the entire population so we can recommend that more responses are

required to correctly predict the factors responsible for the increase in the demand of

commercial vehicle.

Based on questionnaire & sample selected we predict that factors such as interest rate,

fuel price, freight rate, operational efficiency, inventory management, after sales service,

road connectivity will not affect CV demand while statutory regulation such as emission

& safety standards will affect the demand.

So further research & analysis is recommended for the research topic.

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Appendix A - Questionnaire

research on commercial vehicles

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