1. Survey in Existing and New area
in domestic PNG segment
Bhaumik Gandhi
Gaurang Agarwal
SUBMITTED TO:
MR. Tilak Yagnik
1
2. Project Definition
The objective of our project is to study the domestic PNG
market and estimate the potential domestic customers in the
new and the existing areas.
In the new area, we had to spread the awareness about the
PNG and determine the customers who would purchase the
PNG connection.
In the existing areas we had to find out the penetration in the
villages of Gandhinagar, find out the reasons for not using
PNG and we had to market the PNG by explaining benefits of
PNG compared to other fuels.
3. For the new area, we carried out the survey in Bayad and
Dhansura region of Aravalli district.
For the existing area, we carried out the survey in villages of
Gandhinagar namely, Dashela, Shioli, Alampur and Ratanpur.
In addition of carrying out the survey at these two areas, we
were taught about PNG pricing in domestic segment and also
about the technicalities in the domestic PNG segment.
4. BAYAD
Bayad is a Municipality city in district of Aravalli, Gujarat.
The Bayad Municipality has population of 17,886.
3954 is the no of families.
Out of total population, 6,914 were engaged in work or
business activity.
Of total 6914 working population, 82.92 % i.e.5740 were
engaged in Main Work while 17.08 % of total workers were
engaged in Marginal Work.
5.
6. Dhansura
Dhansura is small village located in Dhansura Taluka of
Aravalli district, Gujarat.
Dhansura village has population of 12424
2665 is the no of families.
In Dhansura village out of total population, 4912 were
engaged in work activities. 75.90 % i.e.3684 are permanent
workers.
7.
8. Research Proposal for New
area(Dhansura & Bayad)
Research Objective-To study the new market and determine
the potential customers who would purchase the gas
connection.
Management Decision Problem-After establishing the
network, whether the consumer would purchase the gas
connection or not?
Research Problem
1. What is the level of awareness regarding PNG in the area?
2. What is the current fuel usage status?
3. What are the economic profiles of the population?
9. Hypotheses for the test:
1. H0 – There is no significance impact of income on buying
behavior
Ha – There is significance impact of income on buying behavior
2. Ho – There is no significance impact of number of cylinders on
buying behavior
Ha – There is significance impact of Number of cylinders on
buying behavior
3. Ho – There is no significance impact of Occupation on buying
behavior
Ha – There is significance impact of Occupation on buying
behavior
10. Research Approach-Our research approach will be quantitative
in nature. We have devised the questions so that we get
quantitative data.
Research Methodology- We have adopted the descriptive
research and Exploratory research methodology. We have tried to
know the different factors which would affect the decision to buy
PNG connection.
Sample Size and Sampling Type-we surveyed 250 households
in these two regions. We chose clustered/Area sampling type. The
cluster contained different types of households (based on their
household income and awareness level).
11. Population definition
Sampling Element:- PNG gas connection
Sampling Unit: - Number of the households.
Sampling Frame: - Selection of the households depending upon the type
of its locality.
Scope: Dhansura and Bayad (Aravalli district)
Limitations
Relatively smaller sample size due to time and the resource constraint.
Respondents were not ready to divulge the correct data regarding their
monthly house hold income so the result may not be the best
representation of the current scenario.
In some of the household men were not present and we were informed
that they were the decision maker of the house, so the information given
by the women of those houses may be somewhat unreliable.
12. Graphical Representation of Output
Graph for Occupation:-This Graph below shows the Occupation
of people in Dhansura and Bayad Village. The majority of people
are either doing business (41.60%) or job (46%). Also amidst job
doers most of them were teachers.
13. Graph for House members:-The graph below shows the
family size of the people living in Dhansura and Bayad. The
families with members < 2 are very less. Most of the families
had 2-4 members (34%) and 4-5 members (38.40%).
14. Graph for monthly income:-The graph below shows the monthly
income of the people living in Dhansura and Bayad. Most of the
families’ income ranges from 10K-30K.The families with income
less than 10K were just 16.40%.
15. Graph for Current Fuel:-This Graph below shows the current
fuel which is been used by people of Dhansura and Bayad. It is
clear from the graph that most of the people used LPG as fuel
(83%). Based on their number of cylinders usage, the company
can tap the potential customer.
16. Graph for Awareness:-This graph below shows the awareness of
people towards PNG. Most of the people were not aware about PNG
(59.60%). Amongst those who were aware most of them knew either
through other cities or they knew that it provides facility of meter
billing, thus before laying the pipelines, company should make aware
the people regarding its cost and benefits.
17. Graph for Chances of buying:-The graph below shows the
chances of buying of PNG connection on a 5 point Likert scale.
18. Graph for Price Sensitivity/Insensitivity:-The graph below
shows the respondents who were price sensitive or price
insensitive. This was judged by us based on their views and
perceptions. We found out that 60% were price sensitive and 40%
were price insensitive. This decision was judged considering their
preferred mode of payment, their urge and need to buy and based
on the questions they asked us.
Insensitive
40%
Sensitive
60%
(blank)
0%
Price Sensitivity
19. Analysis of Output
The aim of our project is to determine the customer preference
about chances of buying.
Our dependent variable is chances of buying. The variable that
affects the buying decision are monthly income, usage of current
fuel and their Occupation (Independent Variables).
The non parametric alternative of Anova is Kruskal Wallis test,
hence we would be using Kruskal Wallis test.
Using the kruskal Wallis test, we would be comparing each
independent variables group with the dependent variable and
would identify where the difference occurs.
20. Kruskal-Wallis test to compare the effect of chances of buying
and Monthly Income:-
From the output table, we are getting the Sig. value as 0.000,
which is lesser then 0.05, therefore we would reject the null
hypothesis.
We conclude that there is significant impact of income on buying
behavior.
Post ad-hoc analysis to compare the income groups <10K and
10K-20K:-
From the output table, we are getting the Sig. value as 0.008,
which is lesser then 0.05, therefore we conclude that income
groups, less then <10k and 10k-20k are different with respect to
buying behavior.
21. Post ad-hoc analysis to compare the income groups 20K-30K
and >30K:-
From the output table, we are getting the Sig. value as 0.072,
which is greater than 0.05, therefore we conclude that the income
groups, 20k-30k and greater than 30k are indifferent with respect
to buying behavior.
22. Cross tabulation between chances of buying and Monthly
Income to have an idea of about which income group has high
chances and low chances of buying:
chances of buying * monthly income Cross tabulation
Count
monthly income
Total<10k 10K-20K 20K-30K >30K
chances of buying Very High
1 4 12 18 35
High
8 25 30 27 90
Moderate
20 29 23 19 91
Low
8 9 7 3 27
Very Low
4 1 2 0 7
Total
41 68 74 67 250
23. From the output table, we can find that the customer with very
high chances of buying are in the income group of 20K-30K
and greater then 30k.
The customer with high chances are higher in these two
income groups in comparison to the other two income groups,
this argument is also supported by the fact that these two
income groups are indifferent in buying behavior.
24. Kruskal-Wallis test to compare the effect of chances of buying
and Consumption of Cylinders:-
From the output table, we are getting the Sig. value as 0.200,
which is greater than 0.05; therefore we cannot reject the null
hypothesis and conclude that there is no significant impact of
number of cylinders on buying behavior.
This led us to important observation that market is not aware about
the PNG pricing. This could well be seen from awareness chart
where we found that 59.6% is not aware about PNG.
25. Kruskal-Wallis test to compare the effect of chances of
buying and Occupation:-
From the output table, we are getting the Sig. value as 0.05,
which is equal to 0.05; therefore we would reject the null
hypothesis and conclude that there is significant impact of
occupation on buying behavior.
Post ad-hoc analysis to compare is there any difference or
indifference amongst Farmers and Businessman in buying
behavior:-
From the output table, we are getting the Sig. value as 0.04,
which is lesser then 0.05, therefore we conclude that the Farmers
and Businessman are different with respect to buying behavior.
26. Post ad-hoc analysis to compare is there any difference or
indifference amongst Farmers and Working People (Jobs) in
buying behavior:-
From the output table, we are getting the Sig. value as 0.009,
which is lesser then 0.05, therefore we conclude that the Farmers
and Job doing samples are different with respect to buying
behavior.
Post ad-hoc analysis to compare is there any difference or
indifference amongst Businessman and Working People (Jobs)
in buying behavior.
From the output table, we are getting the Sig. value as 0.720,
which is greater than 0.05, therefore we conclude that the
Businessman and Job doers are not different with respect to
buying behavior.
27. Cross tabulation between chances of buying and
Occupation to have an idea of about which Occupation has
high chances and low chances of buying:-
From the output table, we can find that the Samples with very
high and high chances of buying is doing job or business.
we saw that these groups are indifferent in terms of buying
behavior. The farmers with high chances of buying are very
less in comparison with businessmen and job doers.
occupation
TotalFarmer job business others
chances of buying Very High 0 16 19 0 35
High 8 49 33 0 90
Moderate 15 35 38 3 91
Low 5 12 10 0 27
Very Low 0 3 4 0 7
Total 28 115 104 3 250
28. Cross tabulation between chances of buying and Price sensitivity:-
The chances of buying were directly asked to respondent where as price
sensitivity was decided by us based on the reactions from respondents.
Out of total 87 perceived price insensitive respondents 26 said to have very
high chance of buying, 45 with high chance of buying, 15 with moderate
chance of buying, 1 low and 0 very low chance of buying.
chances of buying * price sensitive/insensitive Cross tabulation
Count
price sensitive/insensitive
TotalSensitive Insensitive
chances of buying Very High 9 26 35
High 45 45 90
Moderate 76 15 91
Low 26 1 27
Very Low 7 0 7
Total 163 87 250
29. Estimation of customer who would
purchase PNG connection
Out of 2665 families in Dhansura, 76% are permanently
employed.
Thus we can cut it down to 2025 families.
Out of 3954 families in Bayad, 83% are permanently employed.
Thus we can cut it down to 3281 families.
The houses with permanent employment comes down to 5306
houses.
83.6% of the surveyed sample uses LPG. This reduces the figure
to 4436 families.
30. The houses with very high and high chances of buying were
close to 68%.This reduces the number of houses to 3016.
We found that 40% of samples were price insensitive, thus we
can say that 1200 customers would purchase PNG connection
within one year.
31. Survey in Existing area
Research proposal
Summary – To study the existing domestic Market, finding
the reason for not choosing PNG and explaining the benefits of
using PNG over other fuels.
Research Motivation –In Gandhinagar, Sabarmati gas has
been operating since many years but some of the areas had
penetration less than 30%, keeping that in mind we tried to
find out the reason for not choosing PNG over other fuels.
Beneficiaries of the research outcome-The primary
beneficiary of this study would be Sabarmati Gas. From this
study they can find the reason why people do not prefer PNG
and overcoming those gaps they can increase their penetration
in these areas.
32. Management Decision Problem
Why people are not purchasing the PNG connection?
How to increase the customer in these areas?
Research Problem
What is the level of awareness regarding PNG in the area?
What is the reason for not choosing PNG over other fuels?
What are the economic profiles of the population?
Research Approach
Our research approach will be quantitative in nature. We have
devised the questions so that we get quantitative data.
33. Research Methodology- We have adopted the descriptive
research and Exploratory research methodology. We have tried to
know the different factors which would affect the decision to buy
PNG connection.
Sample Size and Sampling Type-We surveyed 30 households in
each of these villages . We chose clustered/Area sampling type.
Population definition
Sampling Element:- PNG gas connection
Sampling Unit: - Number of the households.
Sampling Frame: - Selection of the households depending upon
the type of its locality.
Scope:- Gandhinagar
42. Cross tabulation between chances of buying and current
fuel:-
Out of the 115 respondents, 32 customers wanted to buy the
connection.
Amongst those 32, the customers who are using LPG are 27 and
those using wood are 5.
current fuel * chances of buying Cross tabulation
Count
chances of buying
Totalyes no dont know
current fuel LPG 27 26 6 59
wood 5 50 1 56
Total 32 76 7 115
43. Amongst those 27 who are using LPG, 12 customers were
using more than 7 cylinders and 12 customers were using
between 5-7 cylinders and 3 customers were using less than 5
cylinders.
current fuel consumption * chances of buying Cross tabulation
Count
chances of buying
Totalyes no dont know
current fuel consumption <5 cylinders
3 12 1 16
5-7 cylinders
12 9 2 23
7-10 cylinders
5 4 0 9
>10 cylinders
7 1 3 11
Total
27 26 6 59
44. Challenges faced in existing Areas
Customers find PNG costly.
People are not much aware about the benefits of PNG and have
myths regarding it.
It takes considerably more time to establish a PNG connection.
