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Survey in Existing and New area in domestic PNG segment

Bhaumik Gandhi Gaurang Agarwal

SUBMITTED TO:MR. Tilak Yagnik

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.

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.

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.

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.

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?

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

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).

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.

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.

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%).

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%.

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.

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.

Graph for Chances of buying:-The graph below shows the chances of buying of PNG connection on a 5 point Likert scale.

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.

Insensitive40%

Sensitive60%

Price Sensitivity

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.

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.

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.

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 >30Kchances of buying Very High

1 4 12 18 35

High8 25 30 27 90

Moderate20 29 23 19 91

Low8 9 7 3 27

Very Low4 1 2 0 7

Total41 68 74 67 250

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.

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.

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.

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.

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 otherschances 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

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 Insensitivechances 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

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.

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.

Survey in Existing areaResearch 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.

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.

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

Occupation

Household Members

Current fuel

Reasoning for not using PNG

Satisfaction of Current fuel

Mode of payment

No. of cylinders

Household who will buy PNG

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 knowcurrent fuel LPG 27 26 6 59

wood 5 50 1 56Total 32 76 7 115

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 cylinders3 12 1 16

5-7 cylinders12 9 2 23

7-10 cylinders5 4 0 9

>10 cylinders7 1 3 11

Total27 26 6 59

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.

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Thank You