chapter 5 consumer behaviour and...

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Chapter 5CONSUMER BEHAVIOUR AND PREFERENCES

5.1 Introduction

The consumer behaviour, in general, is prompt by number of factors viz. Psycho

graphical, Economical, Social, Politico legal and Demographical. The list is not

exhaustive but it is sufficient to have the deep understanding of the factors influencing

the decision.

Psycho graphical factors are those factors that include the behavioral aspect of the

individual viz. lifestyle, living standard. Here purchase decision in influenced by

those issues that affect the lifestyle of the consumer or in the other that reflects the

status. For e.g.: purchase decision related to buying of car and that to Mercedes Benz.

Talking specifically to the insurance sector, here customer will buy only that policy

that has got high premium or that type of policy which company is promoting to

limited high-income level group only. e.g. "Classic Life premier" policy of Birla Sun

life insurance is meant for only those individual, who can pay at least Rs. 25000/- per

annum.

Economical factors affect the purchase decision by influencing the issues pertaining

to money and income level of the individual. Consumers buy only that product which

will not have any negative effect on his pocket e.g. decision to buy an insurance

policy is influenced by the deepness in the pocket.

Social factor affects the purchase decision by influencing the issues pertaining to

social beliefs and morals.

Politico legal is the macro level environment. It effects in a way, say IRDA has

restricted the sale of Key Man Insurance policy through Term Plan only.

Demographical factor is that factor which has got the maximum of its effect in the

purchase decision of the product and especially if that product is life insurance

product. It is so because these factors incorporate other above said factors and

includes those factors that can influence the buying decision to maximum extent viz.

Occupational factor (service/business), Age factor, Gender, Marital status factor and

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Income level etc. It cannot be denied that buying decision of the individual who is

unmarried and is into business, having the income level of the range Rs. 2.4 lakh per

annum, is into the age group of say 25 years will have the entirely different approach

towards purchase of the life insurance policy with the individual who is into service

and is married, is into the age group of, say 35, and is earning Rs. 30000/- per month.

5.2 Consumer Behavior towards Life Insurance in the State of

HaryanaTo investigate the consumer behavior towards Life Insurance in the state of Haryana,

around 300 people were contacted to collect primary data.

However, 121 respondents gave the information as per our requirement.

On the basis of the collected data and to achieve the objective following hypotheses

were tested applying chi-square test:

1. The type of life insurance plan purchased is not effected by the education

level/ income level/family size

2. The percentage of income spent on life insurance is not effected by the

education level/ family size

3. The person for which the life insurance policy is purchased is not effected by

the education level/ income level/family size

4. The person whose recommendations affect the consumer is not effected by the

education level/ income level

5. The premium payment plan is not effected by the education level/ income

level

6. The purpose to purchase life insurance policy is not effected by the income

level

7. The interest to know facts about the insurance policy is not effected by the

education level/ income level

8. The having of insurance policy either of private or public company is not

effected by the education level/ income level

On rejection of a particular hypothesis i.e. on finding the dependence between the two

factors (for example education and type of plan) the test has been applied to see

whether there is any significant difference for opting the public and private sector

with regard to each category coming under a factor (for example this has been seen in

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case of the categories below graduate, graduate and post graduate coming under the

factor education)

A detailed analysis covering the above mentioned aspects has been done as follows:

5.2.1 Type of Life Insurance Policy Purchased in Respect to Education

Table 5.1: Education and Type of Plan

Which type of plan you like TotalLow risk with

secured &low returns

Moderate riskmoderatereturns

High riskhigh

returnsEducation Below graduation 34 4 2 40

Graduation 26 17 3 46Post graduation/Professional 17 9 9 35

Total 77 30 14 121

Table 5.2.1: Chi-Square Tests

Value DfAsymp. Sig. (2-

sided)Pearson Chi-Square 19.328(a) 4 .001

The Table 5.2.1 reveals that the hypothesis is rejected at 5 percent level of

significance and hence it is concluded that the type of life insurance purchased

depends on the education i.e. education affects the decision to purchase the type of

life insurance policy.

Now to see whether there is any significant difference for opting the public and

private sector with regard to each category coming under the factor education, chi-

square test is applied as under:

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Table 5.2.2: Which Company's Insurance Policies do you have/Which Type ofPlan You Like/Education

Education Which type of plan you like TotalLow risk

with secured& lowreturns

Moderaterisk

moderatereturns

High riskhigh

returnsBelowgraduation

Whichcompany'sinsurancepolicies doyou have

LIC

30 3 0 33

PRIVATE 3 1 1 5Total 33 4 1 38

Graduation whichcompany'sinsurancepolicies doyou have

LIC

21 10 3 34

PRIVATE 5 6 0 11Total 26 16 3 45

Postgraduation/Professional

whichcompany'sinsurancepolicies doyou have

LIC

13 8 7 28



education Value dfAsymp. Sig. (2-

sided)below graduation Pearson Chi-Square 7.569(a) 2 .023

N of Valid Cases 38graduation Pearson Chi-Square 2.830(b) 2 .243

N of Valid Cases 45postgraduation/professional

Pearson Chi-Square .605(c) 2 .739

N of Valid Cases 35

The Table 5.2.3 reveals that the factors “below graduate consumers” and “the

companies whose life insurance policies, they are having”, are dependent i.e. less

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educated people opt for the public sector i.e. LIC. They do not feel secure opting the

private sector.

The Table 5.2.3 also reveals that the “graduate/post graduate consumers” purchase

their life insurance policies irrespective of the sectors i.e. they can go for any

company if satisfied with the policy.

5.2.2: Type of Life Insurance Policy Purchased with Respect to Family Size

Table 5.2.4: Family Size and Type of Plan like by Consumers

Which type of plan you like

Total

Low risk withsecured & low

returns


High riskhigh returns

Family size Less than 5 46 20 8 745 to 7

members 26 9 6 41

More than 7members 5 1 0 6

Total 77 30 14 121


Value df Asymp. Sig. (2-sided)Pearson Chi-Square 1.897 4 .755

N of Valid Cases 121

The Table 5.2.5 reveals that the hypothesis is accepted i.e. the type of life insurance

plan purchased is not affected by the family size. Here, the significant difference is

more than 5 per cent and we can say that family size and type of life insurance

purchased are independent i.e. family size does not make any difference for opting the

decision to purchase the type of life insurance policy. It means that the person having

different size of family whether it is small, medium or large can opt for public sector

i.e. LIC or private sector.

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5.2.3: Type of Life Insurance Policy Purchased in Respect to Income

Table 5.2.6: Income per Month and the Type of Plan Like by Consumers

Which type of plan you like TotalLow risk withsecured & low

returns


High riskhigh

returnsIncomeper month

Less than25000 66 18 10 94

Between 25000to 50000 8 10 2 20

More than50000 3 2 2 7

Total 77 30 14 121


Value df Asymp. Sig. (2-sided)Pearson Chi-Square 11.105 4 .025N of Valid Cases 121

The Table 5.2.7 reveals that the hypothesis is rejected that the type of life insurance

plan purchased is not affected by the income of the consumer. Here the significant

difference is less than 5 percent and we can say that income per month and type of life

insurance purchased is not independent i.e. income per month of the consumer affects

the decision to purchase the type of life insurance policy.


private sector with regard to each category coming under the factor income per

month, again the test has been applied as under:

Table 5.2.8: Type of Company whose Insurance Policies Having byConsumer/the type of plan like by consumer / income per months

Incomeper month Which type of plan you like Total

Low riskwith

secured &low returns

Moderaterisk

moderatereturns

Highriskhigh

returnsLess thanRs. 25000

Whichcompany'sinsurancepolicies do youhave

LIC

59 12 8 79

PRIVATE 7 6 1 14

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Total 66 18 9 93BetweenRs. 25000to Rs.50000


LIC

3 7 1 11


More thanRs. 50000


LIC

2 2 1 5



Income per month Value dfAsymp. Sig. (2-

sided)Less than Rs. 25000 Pearson Chi-

Square 5.834 2 .054

N of Valid Cases 93Between Rs. 25000 toRs. 50000

Pearson Chi-Square 2.137 2 .343

N of Valid Cases 18More than Rs. 50000 Pearson Chi-

Square 1.283 2 .526

N of Valid Cases 7

The Table 5.2.9 reveals that the factors income per month of consumer and the

companies whose life insurance policies, they are having are independent

The Table 5.2.9 also reveals that the factor income per month of consumer and the

companies whose life insurance they are having are, independent. Private and public

sector does not matter for higher, average or low income group. They can opt any of

the company if satisfied with the policy.

However, the people earning less than Rs. 25,000 per month, the probability of

acceptance are near 0.05 and hence we can conclude that they are on the margin and

for some of them the type of sector i.e. public or private matters.

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5.2.4: Percentage of Income Spent on Life Insurance in Respect To Family Size

Table 5.2.10: Family Size / Percentage of Income Spent on Life Insurance

% age of income spent on lifeinsurance Total

Up to10%

Between 10% to 20%

More than20%

Family size Less than 5 55 16 3 745 to 7 members 33 8 0 41More than 7 members 5 1 0 6

Total 93 25 3 121



The Table 5.2.11 reveals that the hypothesis is accepted that the percentage of income

spent on life insurance is not affected by the family size. Here the significant

difference is more than 5 percent and we can say that family size and percentage of

income spent on life insurance is independent i.e. family size does not matter for

investing the percentage of their income towards life insurance policies. It means that

the person having different size of family whether it is small, medium or large can opt

for public sector i.e. LIC or private sector.

5.2.5: Percentage of Income Spent on Life Insurance in Respect to Education

Table 5.2.12: Education / Percentage of Income Spent on Life Insurance% age of income spent on life

insurance TotalUp to10%

Between 10% to 20%

More than20%

Education Below graduation 37 3 0 40Graduation 37 9 0 46Postgraduation/Professional 19 13 3 35

Total 93 25 3 121

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The Table 5.2.13 reveals that the hypothesis is rejected that the percentage of income

spent on life insurance is not affected by the educational level of the consumer. Here

the significant difference is less than 5 percent and we can say that educational level

and percentage of income spent on life insurance is not independent i.e. educational

level of the consumer affects the decision of percentage of income spent on life

insurance.


private sector with regard to each category coming under the factor educational level,

again the test has been applied as under:

Table 5.2.14: Which Company's Insurance Policies do you have / Percentage ofIncome Spent on Life Insurance / Education

Education% age of income spent on

life insurance Total

Up to10%

Between10 % to

20%

Morethan20%

Below graduation Which company'sinsurance policiesdo you have

LIC31 2 33

PRIVATE 5 0 5Total 36 2 38

graduation Which company'sinsurance policiesdo you have

LIC30 4 34



Which company'sinsurance policiesdo you have

LIC16 9 3 28

PRIVATE 3 4 0 7Total 19 13 3 35

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Education Value dfAsymp. Sig. (2-

sided)Below graduation Pearson Chi-Square .320 1 .572

N of Valid Cases 38Graduation Pearson Chi-Square 3.441 1 .064

N of Valid Cases 45Post graduation/Professional


N of Valid Cases 35

The Table 5.2.15 reveals that the factor educational level of consumer having less

educated, average educated and higher educated and companies whose life insurance

policies, they are having are independent.

The Table 5.2.15 also reveals that the selection of company does not matter regarding

the percentage of income spent on life insurance policies whether the consumer is

below graduate, graduate or post graduate. The satisfaction of consumer enables him

to go with any life insurance company whether it is of public sector i.e. LIC or of

public sector

5.2.6: For Whom the Policy is purchased in Respect to Education

Table 5.2.16: Education / Persons for Which You Purchase the Policies

Persons for whom you purchase the policies Total

Self Spouse Children

Otherfamily

members

Self aswell asother

Education Belowgraduation 32 1 4 1 2 40

Graduation 32 1 6 3 4 46Post graduation/Professional 12 6 6 1 10 35

Total 76 8 16 5 16 121



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The Table 5.2.17 reveals that the hypothesis is rejected that the person for whom the

policy is purchased is not affected by the respect of educational level of the consumer.

Here the significant difference is less than 5 percent and we can say that educational

level and person for whom the policy is purchased is not independent i.e. educational

level of the consumer affects the person for whom the policy is purchase.




Table 5.2.18: Which Company's Insurance Policies do you have / Persons forWhich you Purchase the Policies / Education

EducationPersons for which you purchase the

policies Total

Self SpouseChild-

ren

Otherfamily

members

Selfas

wellas

otherBelowgraduation

Whichcompany'sinsurancepoliciesdo youhave

LIC28 3 1 1 33

PRIVATE4 0 0 1 5

Total 32 3 1 2 38Graduation Which

company'sinsurancepoliciesdo youhave

LIC 24 1 4 2 3 34PRIVATE

8 0 2 1 0 11

Total 32 1 6 3 3 45Postgraduation/Professional


LIC10 5 2 1 10 28

PRIVATE

2 1 4 0 0 7

Total 12 6 6 1 10 35

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Education Value df Asymp. Sig. (2-sided)Below graduation Pearson Chi-

Square 2.994 3 .393

N of Valid Cases 38Graduation Pearson Chi-

Square 1.684 4 .794



N of Valid Cases 35

The Table 5.2.19 reveals that the factors below graduate and graduate consumer

and the companies whose life insurance policies, they are having are independent.

Private and public sector does not matter for less educated and average educated.

They can go for either of the companies. It doesn’t get affected by the person for

whom the policy is purchased.

The Table 5.2.19 also reveals that the factor post graduate consumer and the

companies whose life insurance they are having are, dependent. The people having

higher education opt the public sector i.e. LIC. They do not feel secure opting the

private sector.

5.2.7: For Whom the Policy is purchased in Respect to Income

Table 5.2.20: Income per Month/ Persons for Which You Purchase the PoliciesPersons for which you purchase the policies Total


Otherfamily

membersSelf as well

as otherIncomepermonth

Less than Rs.25000 61 6 12 4 11 94

Between Rs.25000 to Rs.50000

11 2 3 1 3 20

More thanRs. 50000 4 0 1 0 2 7

Total 76 8 16 5 16 121

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Table 5.2.21:Chi-Square Tests


The Table 5.2.21 reveals that the hypothesis is accepted that the person for whom the

policy is purchased is not affected by the monthly income level. Here the significant

difference is more than 5 percent and we can say that monthly income level and the

person for whom the policy is purchased is independent i.e. monthly income does not

matter for the person for whom the policy is purchased towards life insurance

policies. It means that the person having different monthly income level can opt for

public sector i.e. LIC or private sector.

5.4.8: For Whom the Policy is purchased in Respect to Family Size

Table 5.2.22: Family Size/Persons for Which You Purchase the PoliciesPersons for which you purchase the policies Total

Self Spouse ChildrenOther

membersSelf and

otherFamilysize

Less than 5 43 3 14 2 12 74

5 to 7 members 30 5 2 2 2 41More than 7 members 3 0 0 1 2 6

Total 76 8 16 5 16 121



The Table 5.2.23 reveals that the hypothesis is rejected that the person for whom the

policy is purchased is not affected by the family size of the consumer. Here the

significant difference is less than 5 percent and we can say that the size of the family

and person for whom the policy is purchased is not independent i.e. family size of the

consumer affects the person for whom the policy is purchase.

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private sector with regard to each category coming under the factor family size, again

the test has been applied as under:

Table 5.2.24: Which Company's Insurance Policies do you have/Persons forWhich You Purchase the Policies/Family

FamilySize

Persons for which you purchase thepolicies Total


Otherfamily

members

Selfas

wellas

otherLess than5


LIC

33 2 7 1 10 53

PRIVATE 10 1 6 1 1 19Total 43 3 13 2 11 72

5 to 7members


LIC

26 4 2 2 2 36

PRIVATE 4 0 0 0 0 4Total 30 4 2 2 2 40

Morethan 7members


LIC

3 1 2 6

Total 3 1 2 6


family size Value dfAsymp. Sig. (2-

sided)Less than 5 Pearson Chi-Square 5.175 4 .270

N of Valid Cases 725 to 7 members Pearson Chi-Square 1.481 4 .830

N of Valid Cases 40More than 7members

Pearson Chi-Square

N of Valid Cases 6

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The Table 5.2.25 reveals that the factors family size having less than five and 5 to 7

members and the companies whose life insurance policies, they are having are

independent. Private and public sector does not matter for these people. So the people

of above mentioned family size can go for either of the companies. It doesn’t get

affected by the person for whom the policy is purchased.

5.2.9: Whose Recommendations Affect the Consumer in Respect to Education

Table 5.2.26: Education/You Purchase Insurance Policies on theRecommendation of

You purchase insurance policies on therecommendation of Total

Insuranceadvisor

Friends/Colleagues Boss Any other

Education Belowgraduation 23 11 0 6 40

Graduation 22 18 4 2 46Post graduation/Professional 17 9 1 8 35

Total 62 38 5 16 121



The Table 5.2.27 reveals that the hypothesis is accepted that the person whose

recommendations affect the consumer is not affected by the education level. Here the

significant difference is more than 5 percent and we can say that educational level and

the person whose recommendations affect the consumer is independent i.e.

educational level does not matter for the person whose recommendations affect the

consumer towards life insurance policies. It means that the person having different

educational level can opt for public sector i.e. LIC or private sector.

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5.2.10: Whose Recommendations Affect the Consumer in Respect to Income

Table 5.2.28: Income per Month/You Purchase Insurance Policies on theRecommendation of

You purchase insurance policies on therecommendation of Total

Insuranceadvisor

Friends/Colleagues Boss

Anyother

Incomepermonths

Less than Rs. 25000 44 33 3 14 94Between Rs. 25000 toRs. 50000 14 4 1 1 20

More than 50000 4 1 1 1 7

Total 62 38 5 16 121



The Table 5.2.29 reveals that the hypothesis is accepted that the person whose

recommendations affect the consumer is not affected by the income level. Here the

significant difference is more than 5 percent and we can say that income level and the

person whose recommendations affect the consumer is independent i.e. various

income groups does not matter for the person whose recommendations affect the

consumer towards life insurance policies. It means that the person having different

monthly income can opt for public sector i.e. LIC or private sector.

5.2.11: Premium Payment Plan in Respect to Income

Table 5.2.30: Income per Months / What Premium Payment Plan You AdoptNormally

What premium payment plan you adoptnormally Total

Monthly Quarterly Half-yearly YearlyIncomepermonths

Less than Rs.25000 2 17 43 32 94

Between Rs.25000 to Rs.50000

7 2 5 6 20

More than Rs.50000 0 2 0 5 7

Total 9 21 48 43 121

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The Table 5.2.31 reveals that the hypothesis is rejected that the premium payment

plan is not affected by the income level not affected by the income per month of the

consumer. Here the significant difference is less than 5 percent and we can say that

the monthly income and the premium payment plan is not independent i.e. monthly

income of the consumer affects the premium payment plan.


private sector with regard to each category coming under the factor monthly income,


Table 5.2.32: Which Company's Insurance Policies Do You Have/What PremiumPayment Plan You Adopt Normally/Income per Month

Incomeper month


Monthly QuarterlyHalf-yearly Yearly

Less thanRs. 25000

whichcompany'sinsurancepolicies doyou have

LIC

1 13 39 26 79

PRIVATE 1 4 4 5 14Total 2 17 43 31 93

BetweenRs. 25000to Rs.50000


LIC

2 1 4 4 11

PRIVATE 4 1 1 1 7Total 6 2 5 5 18

More thanRs. 50000


LIC

1 4 5


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Income per month Value df Asymp. Sig. (2-sided)Less than Rs. 25000 Pearson Chi-Square 4.005 3 .261

N of Valid Cases 93Between Rs.25000to Rs.50000


N of Valid Cases 18More than Rs.50000

Pearson Chi-Square .630 1 .427

N of Valid Cases 7

The Table 5.2.33 reveals that the factor income level of consumer having income less

than 25,000, between 25,000 to 50,000 and more than Rs. 25,000 and companies

whose life insurance policies, they are having are independent.


the premium payment plan on life insurance policies whether the consumer is

belonging to lower income group, middle income group and higher income group.

The satisfaction of consumer enables him to go with any life insurance company

whether it is of public sector i.e. LIC or of public sector.

5.2.12: Premium Payment Plan in Respect to Education

Table 5.2.34: Education / What Premium Payment Plan You Adopt Normally


Monthly Quarterly Half-yearly YearlyEducation Below

graduation 3 9 23 5 40

Graduation 4 10 13 19 46Post graduation/Professional 2 2 12 19 35

Total 9 21 48 43 121


Value df Asymp. Sig. (2-sided)Pearson Chi-Square 18.927(a) 6 .004N of Valid Cases 121

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The Table 5.2.35 reveals that the hypothesis is rejected that the premium payment

plan adopted by the consumer is not affected by the respect of educational level of the

consumer. Here the significant difference is less than 5 percent and we can say that

educational level and premium payment plan adopted by the consumer is not

independent i.e. educational level of the consumer affects the premium payment plan

adopted by the consumer.




Table 5.2.36: Which Company's Insurance Policies Do You Have / WhatPremium Payment Plan You Adopt Normally / Education

EducationWhat premium payment plan you

adopt normally Total

Monthly QuarterlyHalf-yearly Yearly

BelowGraduation


LIC

1 7 22 3 33

PRIVATE 1 2 1 1 5Total 2 9 23 4 38

Graduation Whichcompany'sinsurancepoliciesdo youhave

LIC

2 7 10 15 34

PRIVATE 2 3 3 3 11Total 4 10 13 18 45



LIC

0 1 11 16 28

PRIVATE 2 1 1 3 7Total 2 2 12 19 35

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Education Value dfAsymp. Sig. (2-

sided)Below graduation Pearson Chi-

Square 5.076 3 .166

N of Valid Cases 38Graduation Pearson Chi-

Square 2.184 3 .535



N of Valid Cases 35

The Table 5.2.37 reveals that the factor educational level of consumer having less

educated, average educated and higher educated and companies whose life insurance

policies, they are having are independent.


the premium payment plan adopted by the consumer on life insurance policies

whether the consumer is below graduate, graduate or post graduate. The satisfaction

of consumer enables him to go with any life insurance company whether it is of

public sector i.e. LIC or of public sector.

5.2.13: Purpose to Purchase Policy in Respect to Income

Table 5.2.38: Income per Month/You Purchase Insurance Policy for

You purchase insurance policy for TotalTax

saving Security Savings InvestmentsIncomepermonth

Less than Rs.25000 16 23 48 7 94

Between Rs. 25000to Rs. 50000 5 1 9 5 20

More than Rs.50000 2 2 2 1 7

Total 23 26 59 13 121



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The Table 5.2.39 reveals that the hypothesis is accepted that the purpose to purchase

life insurance policy is not effected by the income level. Here the significant


purpose to purchase life insurance policy is independent i.e. monthly income does not

matter the purpose to purchase life insurance policy. It means that the person having

different monthly income level can opt for public sector i.e. LIC or private sector.

5.2.14: Interest to know Facts about Insurance Policy in Respect to Income

Table 5.2.40: Income per Month/ Level of Involvement before Purchasing theInsurance Policy

What about your level of involvementbefore purchasing the insurance policy Total

Lowinvolvement

Moderateinvolvement

Highinvolvement

Incomepermonths

Less than Rs. 25000 46 45 3 94Between Rs. 25000 toRs. 50000 7 10 3 20

More than Rs. 50000 3 3 1 7

Total 56 58 7 121



The Table 5.2.41 reveals that the hypothesis is accepted that the interest to know facts

about the insurance policy is not effected by the income level. Here the significant


interest to know facts about the insurance policy is independent i.e. monthly income

does not matter for the interest to know facts about the insurance policy. It means that

the person having different monthly income level can opt for public sector i.e. LIC or

private sector.

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5.2.15: Interest to Know Facts about Insurance Policy in Respect to Education

Table 5.2.42: Education/What about Your Level of Involvement beforePurchasing

the Insurance Policy

What about your level of involvement beforepurchasing the insurance policy Total

Lowinvolvement

Moderateinvolvement

Highinvolvement

Education Belowgraduation 21 18 1 40

Graduation 20 24 2 46Post graduation/Professional 15 16 4 35

Total 56 58 7 121Table 5.2.43: Chi-Square Tests

Value df Asymp. Sig. (2-sided)Pearson Chi-Square 3.619(a) 4 .460N of Valid Cases 121

The Table 5.2.43 reveals that the hypothesis is accepted that the interest to know facts

about the insurance policy is not effected by the educational level. Here the significant

difference is more than 5 percent and we can say that the persons having less or more

qualifications and the interest to know facts about the insurance policy is independent

i.e. educational level of consumer does not matter for the interest to know facts about

the insurance policy. It means that the person having different qualification level can

opt for public sector i.e. LIC or private sector.

5.2 16: Which Company’s Insurance Policy do you have in Respect to Education

Table 5.2.44: Education/Which Company's Insurance Policies Do You Have

Which company's insurancepolicies do you have Total

LIC PRIVATEEducation Below graduation 33 5 38

Graduation 34 11 45Postgraduation/Professional 28 7 35

Total 95 23 118

165



The Table 5.2.45 reveals that the hypothesis is accepted that the having of insurance

policy either of private or public company is not effected by the education level. Here

the significant difference is more than 5 percent and we can say that the having of

insurance policy either of private or public company and persons having less or more

qualifications is independent i.e. educational level of consumer does not matter for the

purchase of life insurance policy either of private or public company. It means that the

person having different qualification level can opt for public sector i.e. LIC or private

sector.

5.2.17: Which Company’s Insurance Policy do you have in Respect to Income

Table 5.2.46: Income per Month/Which Company's Insurance Policies Do YouHave

which company's insurance policies doyou have Total

LIC PRIVATEIncomeper month

Less than Rs. 25000 79 14 93Between Rs. 25000 toRs. 50000 11 7 18

More than Rs. 50000 5 2 7Total 95 23 118



The Table 5.2.47 reveals that the hypothesis is accepted that the having of insurance

policy either of private or public company is not effected by the monthly income of

the consumer. Here the significant difference is more than 5 percent and we can say

that the having of insurance policy either of private or public company and persons

belonging to low income group, middle income group and higher income group is

independent i.e. income level of consumer does not matter for the purchase of life

166

insurance policy either of private or public company. It means that the person having

different income group can opt for public sector i.e. LIC or private sector.

5.3: Popularity determination of Private Insurance Companiesamong the Rural and Urban Respondent in the State of Haryana

To determine and investigate which of private life insurance companies has gained

more popularity among the respondents belonging to rural and urban area, primary

data were collected.

Around 300 persons were contracted for the purpose. However, 121 respondents gave

the information as per our requirement for the objective. Out of 121 respondents, 61

and 60 belong to urban and rural area respectively. Each respondent was asked to give

the rank for 1(= most popular to 10 (= least popular) to these life insurance

companies. In other words, this is equivalent to say that the scores on 10 point licker

scale were given by them (Rank 1,2,3_ _ __,10 means score of 10,9,8_ _ _ ,1 points

respectively)

To study whether there is significant difference between the mean scores given to the

10 life insurance companies, the ANOVA was applied separately with respect to rural

area, urban area as well as both the areas taken together, If the difference were found

significant, then paired two sample t test applied taking two insurance companies at a

time and then the most popular company was identified. This study for these different

cases has been explained as under:

5.3.1: Popularity of Private Life Insurance Companies among RuralRespondents

Table 5.3.1: Descriptive StatisticsGroups Count Sum Average Variance

ICICI PRUDENTIAL LIFE 60 511 8.51667 2.52514HDFC STANDARD LIFE 60 443 7.38333 1.79972BAJAJ ALLIANZ 60 415 6.91667 2.55226BIRLA SUNLIFE 60 348 5.8 2.70508SBI LIFE 60 485 8.08333 3.50141RELIANCE LIFE 60 418 6.96667 4.84633KOTAK MAHINDRA 60 220 3.66667 3.81921MAX NEW LIFE 60 149 2.48333 1.4404TATA AIG 60 208 3.46667 2.86328FUTURE GENERALI 60 103 1.71667 2.44379

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Table 5.3.2: Anova

The Table 5.3.1 and 5.3.2 reveals that there is significant difference between the mean

scores given by rural respondents to 10 different life insurance companies.

To see the difference between the mean scores taking two companies at a time pared

two sample t test was first applied between the companies getting highest and next

highest sample mean scores i.e. between the ICICI Prudential and SBI Life is shown

below:

Table 5.3.3: t-Test on Sample Score between ICICI Prudential Life and SBI Lifet-Test: Paired Two Sample for Means

ICICI PRUDENTIAL LIFE SBI LIFEMean 8.516666667 8.083333333Variance 2.525141243 3.501412429t Stat 1.294417521P(T<=t) one-tail 0.100282344t Critical one-tail 1.671093033

The exhibit no. 5.3.3 reveals that there is no significant difference between the

popularity of these two companies. Then the same test as applied to the 1st and 3rd

high mean scorer life insurance companies has shown as follows:

Table 5.3.4: t-Test on Sample Score between ICICI Prudential Life and HDFCStandard Life

t-Test: Paired Two Sample for MeansICICI PRUDENTIAL LIFE HDFC STANDARD LIFE

Mean 8.516666667 7.383333333Variance 2.525141243 1.799717514t Stat 3.939806538P(T<=t) one-tail 0.000109192t Critical one-tail 1.671093033

It is therefore, concluded that there is significant difference between the popularity of

ICICI Prudential life and HDFC Standard Life insurance companies. So the ICICI

Prudential life and SBI Life are equally popular and HDFC Standard life comes to the

position next to them.

ANOVASource of Variation SS df MS F P-value F critBetween Groups 3268.7 9 363.189 127.45 4.1583E-132 1.89574Within Groups 1681.3 590 2.84966Total 4950 599

168

Now to see, what is the position of other companies, as compared to HDFC Standard

life, the paired two sample t test was applied in the similar fashion taking the two

companies at a time. This has been done as under:

Table 5.3.5: t-Test on Sample Score between HDFC Standard Lifeand Reliance Life

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE RELIANCE LIFE


Table 5.3.6: t-Test on Sample Score between HDFC Standard Lifeand Bajaj Allianz Life

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE BAJAJ ALLIANZ


Table 5.3.7: t-Test on Sample Score between HDFC Standard Lifeand Birla Sunlife

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE BIRLA SUNLIFE

Mean 7.383333333 5.8Variance 1.799717514 2.705084746t Stat 7.434020453P(T<=t) one-tail 2.48774E-10t Critical one-tail 1.671093033

Table 5.3.8: t-Test on Sample Scores between Birla Sunlife and Kotak Mahindra

t-Test: Paired Two Sample for MeansBIRLA SUNLIFE KOTAK MAHINDRA


169

Table 5.3.9: t-Test on Sample Score between Kotak Mahindra and Tata AIG

t-Test: Paired Two Sample for MeansKOTAK MAHINDRA TATA AIG


Table 5.3.10: t-Test on Sample Score between Kotak Mahindra and Max NewLife

t-Test: Paired Two Sample for MeansKOTAK MAHINDRA MAX NEW LIFE


Table 5.3.11: t-Test on Sample Score between Max New Life and FutureGenerali

t-Test: Paired Two Sample for MeansMAX NEW LIFE FUTURE GENERALI


It is, therefore, interpreted from the above tables that the popularity of the life

insurance companies under consideration is in the following order:

ICICI Prudential life and SBI Life Insurance Company are equally popular

and at the top most position

HDFC Standard Life Insurance Company, Reliance Life Insurance Company

and Bajaj Allianz Life Insurance Company are equally popular and come to

the next position.

Birla Sunlife Life Insurance Company comes to the third position in the

popularity list.

170

Kotak Life Insurance Company and TATA AIG Life Insurance Company are

equally popular and come to the fourth position

Max New Life Insurance Company comes to the fifth position in the

popularity list

Future Generali Life Insurance Company comes to the fourth position.

5.3.2: Popularity of Private Life Insurance Companies among UrbanRespondents

Table 5.3.12: Descriptive Statistics

ANOVA: Single Factor SUMMARYGroups Count Sum Average Variance

ICICI PRUDENTIAL LIFE 61 524 8.59016393 2.61257HDFC STANDARD LIFE 61 444 7.27868852 5.5377BAJAJ ALLIANZ 61 410 6.72131148 4.57104BIRLA SUNLIFE 61 265 4.3442623 4.56284SBI LIFE 61 424 6.95081967 5.28087RELIANCE LIFE 61 310 5.08196721 6.8765KOTAK MAHINDRA 61 304 4.98360656 7.74973MAX NEW LIFE 61 241 3.95081967 5.58087TATA AIG 61 277 4.54098361 6.38579FUTURE GENERALI 61 159 2.60655738 4.24262

Table 5.3.13: Anova

ANOVASource of Variation SS df MS F P-value F critBetween Groups 1816.45 9 201.828051 37.7951 3.7E-53 1.89547Within Groups 3204.03 600 5.34005464

Total 5020.49 609

The Table 5.3.12 and 5.3.13 reveals that there is significant difference between the

mean scores given by urban respondents to 10 different life insurance companies.

To see the difference between the mean scores taking two companies at a time pared


highest sample mean scores i.e. between the ICICI Prudential and HDFC Standard

Life is shown below:

171

Table 5.3.14: t-Test on Sample Score between ICICI Prudential Life and HDFCStandard Life

t-Test: Paired Two Sample for MeansICICI PRUDENTIAL LIFE HDFC STANDARD LIFE


Here the value of t calculated is greater than critical t value, It is therefore, concluded

that there is significant difference between the popularity of ICICI Prudential life and

HDFC Standard Life insurance companies

Now to see, what is the position of other companies, as compared to HDFC Standard

life, the paired two sample t test was applied in the similar fashion taking the two

companies at a time. This has been done as under:

Table 5.3.15: t-Test on Sample Score between HDFC Standard Life and SBI Life

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE SBI LIFE

Mean 7.278688525 6.950819672Variance 5.537704918 5.280874317t Stat 0.732415676P(T<=t) one-tail 0.233383225t Critical one-tail 1.670648865The Table 5.3.15 reveals that there is no significant difference between the popularity

of these two companies. Then the same test as applied to the 2nd and 4th high mean

scorer life insurance companies has shown as follows:

Table 5.3.16: t-Test on Sample Score between HDFC Standard Life and BajajAllianz

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE BAJAJ ALLIANZ


172

The Table 5.3.16 reveals that there is no significant difference between the popularity



Table 5.3.17: t-Test on Sample Score between HDFC Standard Life and RelianceLife

t-Test: Paired Two Sample for MeansHDFC STANDARD LIFE RELIANCE LIFE

Mean 7.278688525 5.081967213Variance 5.537704918 6.876502732df 60t Stat 4.285577904P(T<=t) one-tail 3.35152E-05t Critical one-tail 1.670648865

It is therefore, concluded that HDFC Standard Life insurance company, SBI Life

insurance company and Bajaj Allianz Life insurance company are equally popular

among urban. There is significant difference between the popularity of HDFC

Standard Life insurance company and Reliance Life insurance company. So the

Reliance Life insurance company comes to the position next to them.

Now to see, what is the position of other companies, as compared to Reliance Life

insurance company, the paired two sample t test was applied in the similar fashion

taking the two companies at a time. This has been done as under:

Table 5.3.18: t-Test on Sample Score between Reliance Life and KotakMahindra

t-Test: Paired Two Sample for MeansRELIANCE LIFE KOTAK MAHINDRA


173




Table 5.3.20: t-Test on Sample Score between Kotak Mahindra and Birla Sunlife

t-Test: Paired Two Sample for MeansKOTAK MAHINDRA BIRLA SUNLIFE


Table 5.3.21: t-Test on Sample Score between Birla Sunlife and Max New Life

t-Test: Paired Two Sample for MeansBIRLA SUNLIFE MAX NEW LIFE


Table 5.3.22: t-Test on Sample Score between Birla Sunlife and Future Generali

t-Test: Paired Two Sample for MeansBIRLA SUNLIFE FUTURE GENERALI


It is, therefore, interpreted from the above exhibits that the popularity of the life


ICICI Prudential life Insurance Company is at the top most position

174

HDFC Standard Life Insurance Company, SBI Life Insurance Company and

Bajaj Allianz Life Insurance Company are equally popular and come to the

next position.

Reliance Life Insurance Company, Kotak Mahindra Life Insurance, TATA

AIG Life Insurance Company and Birla Sunlife Life Insurance Company are

equally popular and come to the third position in the popularity list.

Birla Sunlife Life Insurance Company and Max New Life Insurance Company

are equally popular and come to the fourth position

Future Generali Life Insurance Company comes to the fifth position in the

popularity list

5.3.3: Popularity of Private Life Insurance Companies among both types ofRespondents

Table 5.3.23: Descriptive Statistics

Groups Count Sum Average VarianceICICI PRUDENTIAL LIFE 121 1035 8.553719 2.5491736HDFC STANDARD LIFE 121 887 7.3305785 3.6564738BAJAJ ALLIANZ 121 825 6.8181818 3.55BIRLA SUNLIFE 121 613 5.0661157 4.1455923SBI LIFE 121 909 7.5123967 4.6852617RELIANCE LIFE 121 728 6.0165289 6.7163912KOTAK MAHINDRA 121 521 4.3057851 6.2307163MAX NEW LIFE 121 390 3.2231405 4.0414601TATA AIG 121 485 4.0082645 4.8915978FUTURE GENERALI 121 262 2.1652893 3.5224518

Table 5.3.24: Anova

ANOVASource of Variation SS df MS F P-value F crit

Between Groups 4703.81 9 522.64509 118.81236 3E-159 1.88767Within Groups 5278.69 1200 4.3989118Total 9982.5 1209

175

The Table 5.3.23 and 5.3.24 reveals that there is significant difference between the

mean scores given by urban and rural respondents to 10 different life insurance

companies.

To see the difference between the mean scores taking two companies at a time paired


highest sample mean scores i.e. between the ICICI Prudential and SBI Life is shown

below:

Table 5.3.25: t-Test on Sample Score between ICICI Prudential Life and SBILife

t-Test: Paired Two Sample for MeansICICI PRUDENTIAL LIFE SBI LIFE

Mean 8.553719008 7.512396694Variance 2.549173554 4.685261708t Stat 4.204167305P(T<=t) one-tail 2.53636E-05t Critical one-tail 1.6576509Here in the Table 5.3.25 the value of t calculated is greater than critical t value, It is

therefore, concluded that there is significant difference between the popularity of

ICICI Prudential life and SBI Life insurance companies.

Now to see, what is the position of other companies, as compared to SBI life

insurance company, the paired two sample t test was applied in the similar fashion

taking the two companies at a time. This has been done as under:

Table 5.3.26: t-Test on Sample Score between SBI Life and HDFC Standard Life

t-Test: Paired Two Sample for MeansSBI LIFE HDFC STANDARD LIFE





176

Table 5.3.27: t-Test on Sample Score between SBI Life and Bajaj Allianz

t-Test: Paired Two Sample for MeansSBI LIFE BAJAJ ALLIANZ





It is therefore, concluded that SBI Life insurance company and HDFC Standard Life

insurance company are equally popular among the persons belongs to urban and rural

area.

There is significant difference between the popularity of SBI Life insurance company

and Bajaj Allianz Life insurance company. So the Bajaj Allianz Life insurance

company comes to the position next to them.

Now to see, what is the position of other companies, as compared to Bajaj Allianz

Life insurance company, the paired two sample t test was applied in the similar

fashion taking the two companies at a time. This has been done as under:

Table 5.3.28: t-Test on Sample Score between Bajaj Allianz and Reliance Lifet-Test: Paired Two Sample for Means

BAJAJ ALLIANZ RELIANCE LIFEMean 6.818181818 6.016528926Variance 3.55 6.716391185t Stat 2.604836546P(T<=t) one-tail 0.005176963t Critical one-tail 1.6576509

Table 5.3.29: t-Test on Sample Score between Reliance Life and Birla Sunlifet-Test: Paired Two Sample for Means

RELIANCE LIFE BIRLA SUNLIFEMean 6.016528926 5.066115702Variance 6.716391185 4.145592287t Stat 3.298190233P(T<=t) one-tail 0.000640421t Critical one-tail 1.6576509

177

Table 5.3.30: t-Test on Sample Score between Birla Sunlife and Kotak Mahindra

t-Test: Paired Two Sample for MeansBIRLA SUNLIFE KOTAK MAHINDRA





Table 5.3.32: t-Test on Sample Score between Kotak Mahindra and Max NewLife

t-Test: Paired Two Sample for MeansKOTAK MAHINDRA MAX NEW LIFE


Table 5.3.33: t-Test on Sample Score between Max New Life and FutureGenerali

t-Test: Paired Two Sample for MeansMAX NEW LIFE FUTURE GENERALI


178

It is, therefore, interpreted from the above exhibits that the popularity of the life


ICICI Prudential life Insurance Company is at the top most position

SBI Life Insurance Company and HDFC Standard Life Insurance Company

are equally popular and come to the next position.

Bajaj Allianz Life Insurance Company is at third position

Reliance Life Insurance Company come to the fourth position

Birla Sunlife Life Insurance Company comes to the fifth position in the

popularity list.

Kotak Mahindra Life Insurance and TATA AIG Life Insurance Company are

equally popular and come to the sixth position in the popularity list.

Max New Life Insurance Company come to the seventh position

Future Generali Life Insurance Company comes to the eighth position in the

popularity list

chapter 5 consumer behaviour and...

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