chapter 5 data collection and analysis...

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CHAPTER 5

DATA COLLECTION AND ANALYSIS

INTRODUCTION

In this research, primary data collection is done through survey. A simple structured

non-disguised questionnaire is used to collect primary data. Data collection through

questionnaire is more useful when data are to be collected from large number of

respondents. Other benefits of questionnaire tool are – these help to collect data from

geographically wide-spread respondents i.e. respondents from across the district or

state or country. There is no interviewers’ bias. Respondents can take their own time

to think and answer the questions at their convenient.

Accurate data analysis was possible in this research due to pilot study. Necessary

corrections were made in the questionnaire after analyzing pilot study data.

Incomplete questionnaires or the questionnaires with unanswered questions are

discarded. Data editing and coding is done before making data entry in SPSS.

5. 1. Variables

Variables are in relations to awareness, perceptions, and preferences on marketing

communications tools such as Calls, SMS, Spam/Junk, Catalogs/Brochures, Do Not

Call Registry, Consumer Dispute Redressal Commission, and Consumer Protection

Act, respondents’ age, education, occupation, gender, income etc.

5.1.1. Classification of Variables:

Variables are classified according to customers’ Awareness, Perceptions, and

Preferences of marketing communications tools.

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Table 5.1 Classification of Variables

Sr. No Variables Factors1 Age of the Respondents Profile2 Awareness about CDRC office Awareness3 Awareness about Consumer Dispute Redress Commission Awareness4 Awareness about Consumer Protection Act Awareness5 Awareness about CPA contact details Awareness6 Awareness about Do Not Call Registry Awareness7 Awareness about Permission Marketing Awareness8 City of the Respondents Profile9 Disturbance Rank given to Brochures/Catalogs Perception10 Disturbance Rank given to Live Calls Perception11 Disturbance Rank given to Recorded Calls Perception12 Disturbance Rank given to SMS Perception13 Disturbance Rank given to Spam/Junk Perception14 Disturbed by Catalogs/Brochures Perception15 Disturbed by SMS Perception16 Disturbed by Spam/Junk emails Perception17 Disturbed by the Calls Perception18 Education of the Respondents Profile19 Expectations from the Government preference20 Finding Calls interesting Perception21 Finding Calls useful Perception22 Finding Catalogs/Brochures interesting Perception23 Finding Catalogs/Brochures useful Perception24 Finding SMS interesting Perception25 Finding SMS useful Perception26 Finding Spam/Junk emails interesting Perception27 Finding Spam/Junk emails useful Perception28 Frequency of receiving Catalogs/Brochures Profile29 Frequency of receiving Live Calls Profile30 Frequency of receiving Recorded Calls Profile31 Frequency of receiving SMS Profile32 Gender of the Respondents Profile33 Income of the Respondents Profile34 Internet Access Point preference35 Internet Usage preference36 Internet Users Profile37 No. of days since Stop Call request sent preference38 No. of days since Stop SMS request sent preference39 No. of E-mail Ids preference40 Occupation of the Respondents Profile41 Place of receiving Catalogs/Brochures Profile42 Reading Catalogs/Brochures completely Preference43 Thinking Calls should be banned Perception44 Thinking Catalogs/Brochures should be banned Perception45 Thinking SMS should be banned Perception46 Thinking Spam/Junk should be banned Perception47 Treatment with Spam/Junk Preference48 Want to stop Calls Perception49 Want to stop Catalogs/Brochures Perception50 Want to stop SMS Perception51 Want to stop Spam/Junk Perception

When data are entered in statistical software, and these are ready for analysis, the next

step is to decide appropriate tests for data analysis. It is important to start data analysis

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with knowing nature and characteristics of data. The measurement scales used while

collecting information from respondents will help in deciding selection of statistical

tests. Parametric tests can be used only when following four assumptions are met:

1. Data measured at least Interval scale

2. Variables are normally distributed

3. Data are independent

4. Distribution has equal variance

In the present research, measurement scales used are nominal, and ordinal. Data are

nonmetric and information is collected from one sample. First assumption in above

list is not met. To check second assumption about normality Histograms with normal

curve and K-S tests are used as parts of Univariate technique.

5. 2. FREQUENCY, MEASURES OF ASSOCIATION, AND HISTOGRAMSWITH NORMAL CURVE

Table 5.1 Education of the Respondents

Figure 8 Education of the Respondents

Education Frequency PercentProfessional 147 31.8

P.G. 94 20.3Graduate 126 27.3H.S.C. 56 12.1S.S.C. 39 8.4Total 462 100.0

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Majority respondents (31 %) are professionals by education (CA/MBA etc.) followed

by Graduates (27 %), Postgraduates (20 %), HSC (12 %), and SSC (8 %).

Table 5.2 Income of the Respondents

Figure 9 Income of the Respondents

Majority (48 %) respondents belong to the annual income slab of ` 60001 to `

120000. 29 % respondents have income between ` 1,20,001 to ` 2,40,000, 11 %

respondents’ annual income is below ` 60,000 an 10 % respondents have annual

income of more than ` 2,40,000 p.a.

Table 5.3 Occupation of the Respondents

Income (` p.a.) Frequency Percent< 60,000 55 11.9

60,001 to 1,20,000 223 48.31,20,001 to 2,40,000 138 29.9

Above 2,40,000 46 10.0Total 462 100.0

Occupation Frequency PercentProfessional 133 28.8

Govt. Employee 52 11.3Pvt. Employee 139 30.1Self-employed 92 19.9

House-wife 46 10.0Total 462 100.0

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Figure 10 Occupation of the Respondents

Majority (30 %) respondents are the employees of the private organization, 28 % are

Professionals, 19 % are self-employed, 11 % are government employee, and 10 % are

housewife.

Table 5.4 Gender of the Respondents

Figure 11 Gender of the Respondents

69 % respondents are male while 31 % are female.

Gender Frequency PercentFemale 145 31.4Male 317 68.6Total 462 100.0

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Table 5.5 Age of the Respondents

Age Frequency Percent

16 – 25 68 14.72

26 – 35 220 47.62

36 – 45 152 32.90

46 – 55 18 3.90

56 – 65 4 0.87

Total 462 100.00

Figure 12 Age of the Respondents

Mean age of the respondents is 33 years.

Table 5.6 City of the Respondents

City Frequency PercentAhmedabad 80 17.3

Baroda 79 17.1Surat 78 16.9

Rajkot 75 16.2Jamnagar 75 16.2

Anand 75 16.2Total 462 100.0

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Figure 13 City of the Respondents

Data are collected from six major cities of Gujarat state. Cities are - Ahmedabad,

Baroda, Surat, Rajkot, Jamnagar, and Anand. Percentage of respondents from each

city is around 16 %.

Table 5.7 Treatment with Spam/Junk

Figure 14 Treatment with Spam/Junk

Around 70 % respondents delete Spam/junk emails without reading them. Only 30 %

respondents read spam/junk e-mails before deleting these.

Treatment Frequency PercentRead & Delete 140 30.3

Delete w/o reading 322 69.7Total 462 100.0

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Table 5.8 Want to stop Spam/Junk

Figure 15 Want to stop Spam/Junk

Majority (38 %) respondents are neutral about wanting to stop Spam/Junk. Only 13 %

respondents are strongly agreed and no respondent is strongly disagreed about

preferring to stop Spam/Junk.

Table 5.9 Thinking Spam/Junk should be banned

Want to stop Spam/Junk Frequency PercentStrongly agree 64 13.9

Agree 86 18.6Neutral 179 38.7

Disagree 133 28.8Total 462 100.0

Spam/Junk should be banned Frequency PercentStrongly agree 92 19.9

Neutral 276 59.7Disagree 94 20.3

Total 462 100.0

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Figure 16 Thinking Spam/Junk should be banned

Majority (59 %) respondents have neutral opinion about banning Spam/Junk. They

are neither strongly agree nor disagree upon the opinion that government should

legally ban Spam/Junk e-mails.

Table 5.10 Finding Spam/Junk useful

Figure 17 Finding Spam/Junk useful

Spam/Junk useful Frequency PercentAgree 57 12.3


Total 462 100.0

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Majority (75 %) respondents are neutral about usefulness of Spam/Junk. They neither

agree nor disagree that Spam/Junk e-mails are useful.

Table 5.11 Finding Spam/Junk interesting

Figure 18 Finding Spam/Junk interesting

Majority (36 %) respondents are neutral about finding Spam/Junk interesting. They

neither agree nor disagree that Spam/Junk e-mails are interesting.

Table 5.12 Disturbed by Spam/Junk

Spam/Junk interesting Frequency PercentAgree 132 28.6


Strongly disagree 68 14.7Total 462 100.0

Disturbed by Spam/Junk Frequency PercentStrongly agree 46 10.0



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Figure 19 Disturbed by Spam/Junk

40 % respondents are neutral about getting disturbed by Spam/Junk while 30 %

respondents agree that they get disturbed by Spam/Junk.

Table 5.13 Disturbance Rank given to Spam/Junk

Figure 20 Disturbance Rank given to Spam/Junk

Rank Frequency Percent1 53 11.52 87 18.83 52 11.34 52 11.35 218 47.2

Total 462 100.0

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Respondents are asked to rank spam, catalogs, calls, and SMS on 1 to 5 scale, where 1

means the most disturbing and 5 means the least disturbing communication. Majority

(47 %) respondents have ranked Spam/Junk fifth in a five-point disturbance rating

scale. 11 % respondents have ranked it 1st, 18 % have ranked it 2nd, 11 % have ranked

it 3rd, and 11 % have ranked it 4th.

Table 5.14 Number of E-mail Ids

Figure 21 Number of E-mail Ids

60 % respondents use only one e-mail address, 30 % use two e-mail addresses, and 10

% use three e-mail addresses.

Table 5.15 Internet Access Point

No. of E-mail Ids Frequency Percent1 277 60.02 139 30.13 46 10.0

Total 462 100.0

Internet Access Frequency PercentAt Home 139 30.1At Office 277 60.0

At Cyber Café 46 10.0Total 462 100.0

90

Figure 22 Internet Access Point

60 % respondents use internet at their office, 30 % use internet at their home, and 10

% use internet at cyber café.

Table 7 Internet Usage

Figure 23 Internet Usage

Internet Usage Frequency PercentOccasionally 232 50.2Frequently 184 39.8

Very regularly 46 10.0Total 462 100.0

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50 % respondents use internet occasionally, 39 % use internet frequently, and 10 %

use internet very regularly.

Table 8 Reading Catalogs/Brochures completely

Figure 24 Reading Catalogs/Brochures completely

42 % respondents agree that read promotional Catalogs/Brochures completely, 19 %

are strongly agreed while 37 % are neutral about reading catalogs/brochures.

Table 9 Place of receiving Catalogs/Brochures

Reading Catalogs/Brochures completely Frequency PercentStrongly agree 92 19.9

Agree 195 42.2Neutral 175 37.9Total 462 100.0

Place of receiving Catalogs/Brochures Frequency PercentHome 370 80.1Office 92 19.9Total 462 100.0

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Figure 25 Place of receiving Catalogs/Brochures

80 % respondents receive promotional Catalogs/Brochures at their home while 20 %

respondents receive promotional Catalogs/Brochures at their office.

Table 10 Want to stop Catalogs/Brochures

Figure 26 Want to stop Catalogs/Brochures

Want to stop Catalogs/Brochures Frequency PercentStrongly agree 61 13.2


Disagree 83 18.0Strongly disagree 51 11.0

Total 462 100.0

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Majority (33 %) respondents are agreed and 13 % respondents are strongly agreed

that they want to stop receiving unwanted Catalogs/Brochures through Direct mail.

24% are neutral while 11% strongly disagree about preferring to stop

Catalogs/Brochures.

Table 11 Thinking Catalogs/Brochures should be banned

Figure 27 Thinking Catalogs/Brochures should be banned

Majority (39 %) respondents have neutral opinion that government should legally ban

the unwanted Catalogs/Brochures.

Table 12 Frequency of receiving Catalogs/Brochures

Thinking Catalogs/Brochures should be banned Frequency PercentStrongly agree 92 19.9



Frequency of receiving Catalogs/Brochures Frequency PercentOnce / week 46 10.0Once / month 231 50.0Twice / month 138 29.9

More 47 10.2Total 462 100.0

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Figure 28 Frequency of receiving Catalogs/Brochures

10 % respondents receive Catalogs/Brochures once in a week, 50 % receive them

once in a month, 30 % receive them twice in a month, and 10 % receive them for

more than twice in a month.

Table 13 Frequency of receiving Catalogs/Brochures

Figure 29 Frequency of receiving Catalogs/Brochures

Majority (60 %) respondents are neutral about usefulness of Catalogs/Brochures.

Frequency of receiving Catalogs/Brochures Frequency PercentAgree 138 29.9


Total 462 100.0

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Table 14 Finding Catalogs/Brochures interesting

Figure 30 Finding Catalogs/Brochures interesting

Majority (60 %) respondents are neutral about finding Catalogs/Brochures interesting.

30 % believe that Catalogs/Brochures are interesting while only 10 % disagree that

Catalogs/Brochures are interesting.

Table 15 Disturbed by Catalogs/Brochures

Finding Catalogs/Brochures interesting Frequency PercentAgree 139 30.1


Total 462 100.0

Disturbed by Catalogs/Brochures Frequency PercentStrongly agree 92 19.9



Total 462 100.0

96

Figure 31 Disturbed by Catalogs/Brochures

Majority (51 %) respondents are neutral about getting disturbed by

Catalogs/Brochures. 19 % strongly agree that they get disturbed by

Catalogs/Brochures, 10 % agree that they get disturbed by Catalogs/Brochures, 17 %

disagree that they get disturbed by Catalogs/Brochures, only 1 % strongly disagree

that they get disturbed by Catalogs/Brochures.

Table 16 Disturbance Rank given to Brochures/Catalogs

Rank Frequency Percent3 47 10.24 369 79.95 46 10.0

Total 462 100.0

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Figure 32 Disturbance Rank given to Brochures/Catalogs

Respondents are asked to rank spam, catalogs, calls, and SMS from 1 to 5 scale,

where 1 means the most disturbing and 5 means the least disturbing communication.

Majority (79 %) respondents have ranked Catalogs/Brochures fourth in a five-point

disturbance rating scale. 10 % respondents have ranked it 3rd, and 10 % have ranked

these 5th.

Table 17 Number of days since Stop SMS request sent

No. of days Frequency Percent0 416 90.0

30 46 10.0Total 462 100.0

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Figure 33 Number of days since Stop SMS request sent

90 % respondents have not sent request to service provider for stopping unwanted

SMS. Only 10 % respondents have sent request through Do Not Call registration to

stop unwanted calls.

Table 18 Want to stop SMS

Figure 34 Want to stop SMS

Want to stop SMS Frequency PercentStrongly agree 230 49.8



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Majority (49 %) respondents are strongly agreed that they want to stop receiving

unwanted SMS. 19 % are neutral about this, 20 % disagree, and only 10 % strongly

disagree to prefer to stop receiving marketing SMS.

Table 19 Thinking SMS should be banned

Figure 35 Thinking SMS should be banned

Majority (50 %) respondents are strongly agreed that the government should legally

ban unwanted SMS. (29 %) respondents have neutral opinion about this. 10 %

disagree, and 9 % strongly disagree for banning unwanted SMS.

Table 20 Frequency of receiving SMS

Thinking SMS should be banned Frequency PercentStrongly agree 235 50.9



Frequency of receiving SMS Frequency PercentNever 47 10.2

Very often 93 20.1Always 322 69.7Total 462 100.0

100

Figure 36 Frequency of receiving SMS

69 % respondents always receive unwanted SMS. 20 % receive these very often while

10 % never receive unwanted SMS.

Table 21 Finding SMS useful

Figure 37 Finding SMS useful

Finding SMS useful Frequency PercentAgree 110 23.8



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Majority (46 %) respondents are neutral about usefulness of unwanted SMS. 23 %

respondents agree, 14 % disagree, and 14 % strongly disagree that unwanted SMS are

useful.

Table 22 Finding SMS interesting

Figure 38 Finding SMS interesting

Majority (48 %) respondents are neutral about opinion that they find unwanted SMS

interesting. 21 % respondents agree, 19 % disagree, and 10 % strongly disagree that

unwanted SMS are interesting.

Table 23 Disturbed by SMS

Finding SMS interesting Frequency PercentAgree 100 21.6



Disturbed by SMS Frequency PercentStrongly agree 230 49.8

Agree 92 19.9Neutral 140 30.3Total 462 100.0

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Figure 39 Disturbed by SMS

Majority (49 %) respondents are strongly agreed that they get disturbed by unwanted

SMS. 30 % are neutral while 19 % agree about this.

Table 24 Disturbance Rank given to SMS

Figure 40 Disturbance Rank given to SMS

Rank Frequency Percent1 136 29.42 184 39.83 92 19.95 50 10.8

Total 462 100.0

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Respondents are asked to rank spam, catalogs, calls, and SMS from 1 to 5, where 1


(39 %) respondents have ranked SMS second in a five-point disturbance rating scale.

29 % respondents have ranked it 1st, 19 % have ranked it 3rd, and 10 % have ranked it

5th.

Table 25 Number of days since Stop Call request sent

Figure 41 No. of days since Stop Call request sent

90 % respondents have not sent request to service provider for stopping unwanted

calls. Only 10 % respondents have sent request through Do Not Call registration to

stop unwanted calls.

Table 26 Frequency of receiving Recorded Calls

No. of days Frequency Percent0 416 90.0

30 46 10.0Total 462 100.0

Frequency of receiving Recorded Calls Frequency PercentSometimes 47 10.2Very often 277 60.0

Always 138 29.9Total 462 100.0

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Figure 42 Frequency of receiving Recorded Calls

60 % respondents receive recorded calls very often. 29 % respondents receive them

always and 10 % receive them sometimes.

Table 27 Frequency of receiving Live Calls

Figure 43 Frequency of receiving Live Calls

Frequencyof receivingLive Calls

Frequency Percent

Never 93 20.1Sometimes 139 30.1Very often 138 29.9Always 92 19.9Total 462 100.0

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30 % respondents receive live calls sometimes or very often, 29 % receive these very

often, 19 % always receive live calls, and 20 % respondents never receive live calls.

Table 28 Want to stop Calls

Figure 44 Want to stop Calls

Majority (39 %) respondents are strongly agreed about preferring to stop unwanted

calls. 29 % agree, 19 % respondents are neutral about wanting to stop calls. Only 10

% respondents strongly disagree about preferring to stop calls.

Table 29 Thinking Calls should be banned

Want to stop Calls Frequency PercentStrongly agree 184 39.8



Thinking Calls should be banned Frequency PercentStrongly agree 193 41.8



Total 462 100.0

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Figure 45 Thinking Calls should be banned

Majority (41 %) respondents are strongly agreed that government should legally ban

unwanted calls. 19 % agree, 20 % have neutral opinion that government should

legally ban calls. 8 % disagree and 9 % strongly disagree on this opinion.

Table 30 Finding Calls useful

Figure 46 Finding Calls useful

Finding Calls useful Frequency PercentStrongly agree 51 11.0



Total 462 100.0

107

Majority (37 %) respondents are neutral about usefulness of unwanted calls. 11 %

strongly agree, 13 % agree, 19 % disagree, and 18 %strongly disagree about finding

calls useful.

Table 31 Finding Calls interesting

Figure 47 Finding Calls interesting

Majority (46 %) respondents are neutral about finding unwanted calls interesting. 13

% agree, 30 % disagree, and 10 % strongly disagree about finding calls useful.

Table 32 Disturbed by the Calls

Finding Calls interesting Frequency PercentAgree 63 13.6



Disturbed by the Calls Frequency PercentStrongly agree 230 49.8



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Figure 48 Disturbed by the Calls

Majority (49 %) respondents strongly agree, 30 % agree, 10 % are neutral, and 10 %

disagree that they get disturbed by unwanted marketing calls.

Table 33 Disturbance Rank given to Live Calls

Figure 49 Disturbance Rank given to Live Calls

Respondents are asked to rank spam, catalogs, calls, and SMS from 1 to 5, where 1


Rank Frequency Percent2 91 19.73 183 39.64 50 10.85 138 29.9

Total 462 100.0

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(39 %) respondents have ranked live calls third in a five-point disturbance rating

scale. No respondent has ranked it 1st, 19 % have ranked it 2nd, 10 % have ranked it

4th, and 29 % have ranked it 5th.

Table 34 Awareness about Permission Marketing

Figure 50 Awareness about Permission Marketing

Only 14 % respondents are aware about permission marketing. Awareness of

permission marketing is very low.

Table 35 Awareness about Do Not Call Registry

Awareness about Permission Marketing Frequency PercentYes 69 14.9No 393 85.1

Total 462 100.0

Awareness about Do Not Call Registry Frequency PercentYes 185 40.0No 277 60.0

Total 462 100.0

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Figure 51 Awareness about Do Not Call Registry

40 % respondents are aware Do Not Call Registry. Awareness of Do Not Call

Registry is higher compared to 14 % awareness of permission marketing.

Table 36 Awareness about CPA contact details

Figure 52 Awareness about CPA contact details

Awareness about CPA contact details Frequency PercentYes 32 6.9No 430 93.1

Total 462 100.0

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Only 6 % respondents are aware about how to proceed under Consumer Protection

Act in case they want to file a complaint or take an action against marketing

companies.

Table 37 Awareness about Consumer Protection Act

Figure 53 Awareness about Consumer Protection Act

79 % respondents are aware about Consumer Protection Act.

Table 38 Awareness about Consumer Dispute Redress Commission

Awareness Frequency PercentYes 369 79.9No 93 20.1

Total 462 100.0

Awareness Frequency PercentYes 369 79.9No 93 20.1

Total 462 100.0

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Figure 54 Awareness about Consumer Dispute Redress Commission

79 % respondents are aware about Consumer Dispute Redressal Commission.

Table 39 Awareness about CDRC office

Figure 55 Awareness about CDRC office

Only 6 % respondents are aware office address of Consumer Disputer Redressal

Commission.

Awareness about CDRC office Frequency PercentYes 28 6.1No 434 93.9

Total 462 100.0

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5. 3. KOLMOGOROV-SMIRNOV TEST AND SHAPIRO-WILK TESTS

Kolmogorov-Smirnov test is one-sample test. It is goodness of fit test, where the

comparison is made between observed sample distribution and theoretical sample

distribution. When calculated value is greater than the critical value, the null

hypothesis is rejected.

Table 40 Tests of Normality

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic df Sig. Statistic df Sig.Age of the Respondents .067 462 .000 .972 462 .000Income of the Respondents .279 462 .000 .858 462 .000No. of days since Stop Call requestsent

.531 462 .000 .341 462 .000

No. of days since Stop SMS requestsent

.531 462 .000 .341 462 .000

Frequency of receivingCatalogs/Brochures

.292 462 .000 .849 462 .000

Frequency of receiving Live Calls .188 462 .000 .875 462 .000Frequency of receiving RecordedCalls

.330 462 .000 .761 462 .000

Frequency of receiving SMS .404 462 .000 .577 462 .000Internet Usage .318 462 .000 .749 462 .000Reading Catalogs/Brochurescompletely

.245 462 .000 .797 462 .000

Thinking Calls should be banned .243 462 .000 .824 462 .000Thinking Catalogs/Brochures shouldbe banned

.273 462 .000 .819 462 .000

Thinking SMS should be banned .325 462 .000 .777 462 .000Thinking Spam/Junk should be banned .379 462 .000 .735 462 .000Want to stop Calls .233 462 .000 .790 462 .000Want to stop Catalogs/Brochures .215 462 .000 .903 462 .000Want to stop SMS .324 462 .000 .780 462 .000Want to stop Spam/Junk .245 462 .000 .852 462 .000Finding Calls interesting .266 462 .000 .865 462 .000Finding Calls useful .190 462 .000 .902 462 .000Finding Catalogs/Brochuresinteresting

.325 462 .000 .765 462 .000

Finding Catalogs/Brochures useful .326 462 .000 .764 462 .000Finding SMS interesting .283 462 .000 .851 462 .000Finding SMS useful .289 462 .000 .838 462 .000Finding Spam/Junk interesting .235 462 .000 .856 462 .000Finding Spam/Junk useful .377 462 .000 .674 462 .000Disturbance Rank given toBrochures/Catalogs

.400 462 .000 .617 462 .000

Disturbance Rank given to Live Calls .269 462 .000 .826 462 .000

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Disturbance Rank given to RecordedCalls

.372 462 .000 .695 462 .000

Disturbance Rank given to SMS .269 462 .000 .806 462 .000Disturbance Rank given to Spam/Junk .290 462 .000 .791 462 .000Disturbed by Catalogs/Brochures .312 462 .000 .839 462 .000Disturbed by SMS .319 462 .000 .734 462 .000Disturbed by Spam/Junk .231 462 .000 .875 462 .000Disturbed by the Calls .291 462 .000 .762 462 .000City of the Respondents .147 462 .000 .905 462 .000Education of the Respondents .190 462 .000 .874 462 .000Gender of the Respondents .436 462 .000 .584 462 .000Internet Access Point .330 462 .000 .760 462 .000No. of E-mail Ids .372 462 .000 .702 462 .000Occupation of the Respondents .170 462 .000 .873 462 .000Place of receiving Catalogs/Brochures .492 462 .000 .489 462 .000Treatment with Spam/Junk .442 462 .000 .577 462 .000Awareness about Consumer ProtectionAct

.491 462 .000 .491 462 .000

Awareness about CPA contact details .538 462 .000 .275 462 .000Awareness about Do Not CallRegistry

.392 462 .000 .622 462 .000

Awareness about PermissionMarketing

.513 462 .000 .425 462 .000

City of the Respondents .147 462 .000 .905 462 .000a. Lilliefors Significance Correction

Kolmogorov-Smirnov test, and Shapiro-Wilk test results show that distribution in not

normal. Parametric tests cannot be used.

5. 4. HYPOTHESES TESTING

Chi-Square Test

Chi-Square as a test of independence is used to know whether two variable or

attributes are associated with each other or not. With particular level of significance

and degree of freedom, if calculated value of Chi-Square is greater than table value,

then null hypothesis is rejected. It is interpreted that both variables/attributes are

associated. For example, null Hypothesis in 1st hypothesis below is - There is no

significant relationship between customers’ awareness about Do Not Call Registry

and Education, and Occupation of the customers. Null hypothesis assumes that both

attribute/variable (a) Customers’ awareness about Do Not Call Registry and variable

(b) Education, and Occupation of the customers, are independent. Test statistic is

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0.000, which is less than 0.005. Null hypothesis is rejected and it is proved that there

is a significant relationship between variable (a) and variable (b) above.

Hypothesis 1.H0: There is no significant relationship between customers’ awareness about Do

Not Call Registry and Education, and Occupation of the customers.

H1: There is significant relationship between customers’ awareness about Do Not

Call Registry and Education, and Occupation of the customers.

Table 41 Correlations

Awarenessabout Do NotCall Registry

Education ofthe

Respondents

Occupation ofthe

RespondentsSpearman'srho

Awareness aboutDo Not CallRegistry

CorrelationCoefficient

1.000 .096* -.038

Sig. (2-tailed)

. .039 .409

N 462 462 462Education of theRespondents


.096* 1.000 .272**

Sig. (2-tailed)

.039 . .000

N 462 462 462Occupation of theRespondents


-.038 .272** 1.000

Sig. (2-tailed)

.409 .000 .

N 462 462 462*. Correlation is significant at the 0.05 level (2-tailed).**. Correlation is significant at the 0.01 level (2-tailed).

Chi-square statistics

Table 42 Awareness about Do Not Call Registry * Education of the Respondents

Crosstabulation

Education of the Respondents TotalProfessional PG Graduate HSC SSC

Awarenessabout DoNot CallRegistry

Yes Count 94 14 9 53 15 185Expected

Count58.9 37.6 50.5 22.4 15.6 185.0

% withinAwarenessabout DoNot CallRegistry

50.8% 7.6% 4.9% 28.6% 8.1% 100.0%

% withinEducation of

theRespondents

63.9% 14.9% 7.1% 94.6% 38.5% 40.0%

% of Total 20.3% 3.0% 1.9% 11.5% 3.2% 40.0%

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No Count 53 80 117 3 24 277Expected

Count88.1 56.4 75.5 33.6 23.4 277.0


19.1% 28.9% 42.2% 1.1% 8.7% 100.0%


theRespondents

36.1% 85.1% 92.9% 5.4% 61.5% 60.0%

% of Total 11.5% 17.3% 25.3% .6% 5.2% 60.0%Total Count 147 94 126 56 39 462

ExpectedCount

147.0 94.0 126.0 56.0 39.0 462.0


31.8% 20.3% 27.3% 12.1% 8.4% 100.0%


theRespondents

100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 31.8% 20.3% 27.3% 12.1% 8.4% 100.0%

Table 43 Chi-Square Tests

Value df Asymp. Sig. (2-sided)Pearson Chi-Square 186.127a 4 .000

Likelihood Ratio 210.495 4 .000Linear-by-Linear Association 1.647 1 .199

N of Valid Cases 462a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 15.62.

Table 44 Symmetric Measures

Value Approx. Sig.Nominal by Nominal Phi .635 .000

Cramer's V .635 .000Contingency Coefficient .536 .000

N of Valid Cases 462

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Figure 56 Awareness about Do Not Call Registry and Education of the Respondents

Table 45 Awareness about Do Not Call Registry and Occupation of the Respondents

Crosstabulation

Occupation of the Respondents TotalProfessiona

lGovt.

Employee

Pvt.Employe

e

Self-employe

d

House-wife

Awareness aboutDo Not

CallRegistry

Yes

Count 88 5 0 46 46 185Expected

Count53.3 20.8 55.7 36.8 18.4 185.0


47.6% 2.7% .0% 24.9% 24.9% 100.0%

% withinOccupation

of theRespondent

s

66.2% 9.6% .0% 50.0% 100.0%

40.0%

% of Total 19.0% 1.1% .0% 10.0% 10.0% 40.0%No Count 45 47 139 46 0 277

ExpectedCount

79.7 31.2 83.3 55.2 27.6 277.0


16.2% 17.0% 50.2% 16.6% .0% 100.0%

% withinOccupation

of theRespondent

s

33.8% 90.4% 100.0% 50.0% .0% 60.0%

% of Total 9.7% 10.2% 30.1% 10.0% .0% 60.0%Total Count 133 52 139 92 46 462

ExpectedCount

133.0 52.0 139.0 92.0 46.0 462.0

118


28.8% 11.3% 30.1% 19.9% 10.0% 100.0%

% withinOccupation

of theRespondent

s

100.0% 100.0% 100.0% 100.0% 100.0%

100.0%

% of Total 28.8% 11.3% 30.1% 19.9% 10.0% 100.0%


Value Df Asymp. Sig. (2-sided)Pearson Chi-Square 223.362a 4 .000







Figure 57 Awareness about Do Not Call Registry and Occupation of the

Respondents

Hypothesis that there is no significant relationship between customers’ awareness

about Do Not Call Registry and Education and Occupation of the customers is

119

rejected. There is significant relationship between customers’ awareness about Do

Not Call Registry and customers’ education and occupation.

Hypothesis 2.

H0: There is no significant relationship between customers’ awareness about Do

Not Call Registry and City, and Gender of the customers.

H1: There is significant relationship between customers’ awareness about Do Not

Call Registry and City, and Gender of the customers.



City of theRespondents

Gender ofthe

Respondents

Spearman'srho

Awareness about DoNot Call Registry


1.000 .012 -.048

Sig. (2-tailed) . .802 .301N 462 462 462



.012 1.000 .053

Sig. (2-tailed) .802 . .257N 462 462 462

Gender of theRespondents


-.048 .053 1.000

Sig. (2-tailed) .301 .257 .N 462 462 462


Table 49 Awareness about Do Not Call Registry and City of the Respondents

Crosstabulation

City of the Respondents TotalAhmedabad Baroda Surat Rajkot Jamnagar Anand


Yes Count 33 32 31 29 31 29 185Expected

Count32.0 31.6 31.2 30.0 30.0 30.0 185.0


17.8% 17.3% 16.8% 15.7% 16.8% 15.7% 100.0%

% withinCity of the

Respondents

41.2% 40.5% 39.7% 38.7% 41.3% 38.7% 40.0%

% of Total 7.1% 6.9% 6.7% 6.3% 6.7% 6.3% 40.0%No Count 47 47 47 46 44 46 277

ExpectedCount

48.0 47.4 46.8 45.0 45.0 45.0 277.0

120


17.0% 17.0% 17.0% 16.6% 15.9% 16.6% 100.0%

% withinCity of the

Respondents

58.8% 59.5% 60.3% 61.3% 58.7% 61.3% 60.0%

% of Total 10.2% 10.2% 10.2% 10.0% 9.5% 10.0% 60.0%Total Count 80 79 78 75 75 75 462

ExpectedCount

80.0 79.0 78.0 75.0 75.0 75.0 462.0


17.3% 17.1% 16.9% 16.2% 16.2% 16.2% 100.0%

% withinCity of the

Respondents

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 17.3% 17.1% 16.9% 16.2% 16.2% 16.2% 100.0%


Value Df Asymp. Sig. (2-sided)Pearson Chi-Square .229a 5 .999

Likelihood Ratio .229 5 .999Linear-by-Linear Association .062 1 .803






121

Figure 58 Awareness about Do Not Call Registry and City of the Respondents

Crosstabulation

Table 52 Awareness about Do Not Call Registry and Gender of the Respondents

Crosstabulation

Gender of the Respondents TotalFemale Male

Awareness about Do NotCall Registry

Yes Count 53 132 185Expected Count 58.1 126.9 185.0

% within Awarenessabout Do Not Call

Registry

28.6% 71.4% 100.0%

% within Gender of theRespondents

36.6% 41.6% 40.0%

% of Total 11.5% 28.6% 40.0%No Count 92 185 277

Expected Count 86.9 190.1 277.0% within Awarenessabout Do Not Call

Registry

33.2% 66.8% 100.0%


63.4% 58.4% 60.0%

% of Total 19.9% 40.0% 60.0%Total Count 145 317 462

Expected Count 145.0 317.0 462.0% within Awarenessabout Do Not Call

Registry

31.4% 68.6% 100.0%


100.0% 100.0% 100.0%

% of Total 31.4% 68.6% 100.0%


Value df Asymp. Sig.(2-sided)

Exact Sig.(2-sided)

Exact Sig.(1-sided)

Pearson Chi-Square 1.073a 1 .300Continuity Correctionb .872 1 .351

Likelihood Ratio 1.079 1 .299Fisher's Exact Test .308 .175

122

Linear-by-Linear Association 1.071 1 .301N of Valid Casesb 462

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 58.06.b. Computed only for a 2x2 table


Value Approx. Sig.Nominal by Nominal Phi -.048 .300



Figure 59 Awareness about Do Not Call Registry and Gender of the Respondents

Crosstabulation


about Do Not Call Registry and city, and gender of the customers is not rejected.

There is no significant relationship between customers’ awareness about Do Not

Call Registry and customers’ city, and gender.

Hypothesis 3.

H0: There is no significant relationship between disturbance ranks given to

marketing communications by the customers and customers’ preferences to stop

them.

H1: There is significant relationship between disturbance ranks given to marketing

communications by the customers and customers’ preferences to stop them.

123


Correlations Disturbance Rankgiven toBrochures/Catalog

s

Disturbance Rankgiven to

LiveCalls


RecordedCalls


SMS


Spam/Junk

Want tostop Calls

Want tostop

Catalogs/Brochure

s

Want tostop SMS

Want tostop

Spam/Junk

Spearman's rho

Disturbance Rankgiven toBrochures/Catalogs


1.000 -.207** -.354** -.374** .347** -.207** -.102* -.172** .272**

Sig. (2-tailed)

. .000 .000 .000 .000 .000 .028 .000 .000

N 462 462 462 462 462 462 462 462 462Disturbance Rankgiven toLive Calls


-.207** 1.000 .636** -.481** -.802** -.009 .040 .140** -.256**

Sig. (2-tailed)

.000 . .000 .000 .000 .849 .395 .003 .000

N 462 462 462 462 462 462 462 462 462Disturbance Rankgiven toRecordedCalls


-.354** .636** 1.000 -.510** -.668** .520** -.043 .536** -.161**

Sig. (2-tailed)

.000 .000 . .000 .000 .000 .358 .000 .001

N 462 462 462 462 462 462 462 462 462Disturbance Rankgiven toSMS


-.374** -.481** -.510** 1.000 .075 -.060 .168** -.081 .109*

Sig. (2-tailed)

.000 .000 .000 . .106 .197 .000 .081 .019

N 462 462 462 462 462 462 462 462 462Disturbance Rankgiven toSpam/Junk


.347** -.802** -.668** .075 1.000 -.271** -.137** -.391** .145**

Sig. (2-tailed)

.000 .000 .000 .106 . .000 .003 .000 .002

N 462 462 462 462 462 462 462 462 462Want tostop Calls


-.207** -.009 .520** -.060 -.271** 1.000 .002 .778** -.150**

Sig. (2-tailed)

.000 .849 .000 .197 .000 . .974 .000 .001

N 462 462 462 462 462 462 462 462 462Want tostopCatalogs/Brochures


-.102* .040 -.043 .168** -.137** .002 1.000 .107* .064

Sig. (2-tailed)

.028 .395 .358 .000 .003 .974 . .021 .168

N 462 462 462 462 462 462 462 462 462Want tostop SMS


-.172** .140** .536** -.081 -.391** .778** .107* 1.000 .195**

Sig. (2-tailed)

.000 .003 .000 .081 .000 .000 .021 . .000

N 462 462 462 462 462 462 462 462 462Want tostopSpam/Junk


.272** -.256** -.161** .109* .145** -.150** .064 .195** 1.000

Sig. (2-tailed)

.000 .000 .001 .019 .002 .001 .168 .000 .

N 462 462 462 462 462 462 462 462 462**. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).

124


Disturbance Rank given to Brochures/Catalogs and Want to stop Catalogs/Brochures

Crosstabulation

Table 56 Disturbance Rank given to Brochures/Catalogs and Want to stop Catalogs/Brochures

Crosstabulation

Want to stop Catalogs/Brochures TotalStrongly

agreeAgree Neutral Disagree Strongly

disagreeDisturbance Rank

given toBrochures/Catalogs

3 Count 2 5 0 39 1 47Expected Count 6.2 15.8 11.4 8.4 5.2 47.0

% withinDisturbance Rank

given toBrochures/Catalogs

4.3% 10.6% .0% 83.0% 2.1% 100.0%

% within Want tostop

Catalogs/Brochures

3.3% 3.2% .0% 47.0% 2.0% 10.2%

% of Total .4% 1.1% .0% 8.4% .2% 10.2%4 Count 58 132 112 19 48 369

Expected Count 48.7 123.8 89.5 66.3 40.7 369.0% within


Brochures/Catalogs

15.7% 35.8% 30.4% 5.1% 13.0% 100.0%


Catalogs/Brochures

95.1% 85.2% 100.0% 22.9% 94.1% 79.9%

% of Total 12.6% 28.6% 24.2% 4.1% 10.4% 79.9%5 Count 1 18 0 25 2 46



Brochures/Catalogs

2.2% 39.1% .0% 54.3% 4.3% 100.0%


Catalogs/Brochures

1.6% 11.6% .0% 30.1% 3.9% 10.0%

% of Total .2% 3.9% .0% 5.4% .4% 10.0%Total Count 61 155 112 83 51 462



Brochures/Catalogs

13.2% 33.5% 24.2% 18.0% 11.0% 100.0%


Catalogs/Brochures

100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 13.2% 33.5% 24.2% 18.0% 11.0% 100.0%

125





Table 58 Directional Measures

Value Asymp.Std. Errora

Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric -.084 .040 -2.074 .038Disturbance Rank given to

Brochures/Catalogs Dependent-.061 .029 -2.074 .038

Want to stopCatalogs/Brochures Dependent

-.137 .065 -2.074 .038

a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.


Value Asymp. Std.Errora

Approx.Tb

Approx.Sig.

Nominal byNominal

Phi .706 .000Cramer's V .499 .000

ContingencyCoefficient

.577 .000

Ordinal by Ordinal Kendall's tau-b -.091 .044 -2.074 .038Kendall's tau-c -.070 .034 -2.074 .038

Gamma -.162 .077 -2.074 .038Spearman Correlation -.102 .049 -2.209 .028c

Interval by Interval Pearson's R -.093 .045 -2.005 .045c

N of Valid Cases 462a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.c. Based on normal approximation.

Figure 60 Disturbance Rank given to Brochures/Catalogs and Want to stop

Catalogs/Brochures Crosstabulation

126

Table 60 Disturbance Rank given to Spam/Junk and Want to stop Spam/Junk Crosstabulation

Want to stop Spam/Junk TotalStrongly

agreeAgree Neutral Disagree


Spam/Junk

1 Count 6 0 47 0 53Expected Count 7.3 9.9 20.5 15.3 53.0


given toSpam/Junk

11.3% .0% 88.7% .0% 100.0%

% within Want tostop Spam/Junk

9.4% .0% 26.3% .0% 11.5%

% of Total 1.3% .0% 10.2% .0% 11.5%2 Count 0 46 0 41 87

Expected Count 12.1 16.2 33.7 25.0 87.0% within


Spam/Junk

.0% 52.9% .0% 47.1% 100.0%


.0% 53.5% .0% 30.8% 18.8%

% of Total .0% 10.0% .0% 8.9% 18.8%3 Count 52 0 0 0 52



Spam/Junk

100.0% .0% .0% .0% 100.0%


81.2% .0% .0% .0% 11.3%

% of Total 11.3% .0% .0% .0% 11.3%4 Count 6 0 0 46 52



Spam/Junk

11.5% .0% .0% 88.5% 100.0%


9.4% .0% .0% 34.6% 11.3%

% of Total 1.3% .0% .0% 10.0% 11.3%5 Count 0 40 132 46 218



Spam/Junk

.0% 18.3% 60.6% 21.1% 100.0%


.0% 46.5% 73.7% 34.6% 47.2%

% of Total .0% 8.7% 28.6% 10.0% 47.2%Total Count 64 86 179 133 462



Spam/Junk

13.9% 18.6% 38.7% 28.8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 13.9% 18.6% 38.7% 28.8% 100.0%

127







Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .092 .028 3.200 .001Disturbance Rank given to

Spam/Junk Dependent.091 .028 3.200 .001

Want to stop Spam/JunkDependent

.092 .029 3.200 .001




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi 1.186 .000Cramer's V .685 .000


.764 .000

Ordinal by Ordinal Kendall's tau-b .092 .028 3.200 .001Kendall's tau-c .086 .027 3.200 .001

Gamma .114 .035 3.200 .001Spearman Correlation .145 .039 3.141 .002c

Interval by Interval Pearson's R .184 .035 4.004 .000c



Figure 61 Disturbance Rank given to Spam/Junk and Want to stop Spam/Junk

Crosstabulation

128

Table 64 Disturbance Rank given to SMS and Want to stop SMS Crosstabulation

Want to stop SMS TotalStrongly

agreeNeutral Disagree Strongly


given to SMS1 Count 46 0 46 44 136


Disturbance Rankgiven to SMS

33.8% .0% 33.8% 32.4% 100.0%

% within Want tostop SMS

20.0% .0% 49.5% 93.6% 29.4%

% of Total 10.0% .0% 10.0% 9.5% 29.4%2 Count 138 46 0 0 184



75.0% 25.0% .0% .0% 100.0%


60.0% 50.0% .0% .0% 39.8%

% of Total 29.9% 10.0% .0% .0% 39.8%3 Count 46 46 0 0 92



50.0% 50.0% .0% .0% 100.0%


20.0% 50.0% .0% .0% 19.9%

% of Total 10.0% 10.0% .0% .0% 19.9%5 Count 0 0 47 3 50



.0% .0% 94.0% 6.0% 100.0%


.0% .0% 50.5% 6.4% 10.8%

% of Total .0% .0% 10.2% .6% 10.8%Total Count 230 92 93 47 462



49.8% 19.9% 20.1% 10.2% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 49.8% 19.9% 20.1% 10.2% 100.0%





129



Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric -.030 .052 -.583 .560Disturbance Rank given to

SMS Dependent-.031 .053 -.583 .560

Want to stop SMSDependent

-.029 .051 -.583 .560




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi .970 .000Cramer's V .560 .000


.696 .000

Ordinal by Ordinal Kendall's tau-b -.030 .052 -.583 .560Kendall's tau-c -.028 .047 -.583 .560

Gamma -.040 .068 -.583 .560Spearman Correlation -.081 .059 -1.752 .081c




Figure 62 Disturbance Rank given to SMS and Want to stop SMS Crosstabulation

Table 68 Disturbance Rank given to Recorded Calls and Want to stop Calls

Crosstabulation

Want to stop Calls TotalStrongly

agreeAgree Neutral Strongly

disagreeDisturbance Rankgiven to Recorded

Calls


% within 66.7% 16.7% 16.3% .4% 100.0%

130

Disturbance Rankgiven to Recorded

Calls% within Want to

stop Calls100.0% 33.3% 48.9% 2.1% 59.7%

% of Total 39.8% 10.0% 9.7% .2% 59.7%2 Count 0 0 47 46 93



Calls

.0% .0% 50.5% 49.5% 100.0%

% within Want tostop Calls

.0% .0% 51.1% 95.8% 20.1%

% of Total .0% .0% 10.2% 10.0% 20.1%3 Count 0 92 0 1 93



Calls

.0% 98.9% .0% 1.1% 100.0%


.0% 66.7% .0% 2.1% 20.1%

% of Total .0% 19.9% .0% .2% 20.1%Total Count 184 138 92 48 462



Calls

39.8% 29.9% 19.9% 10.4% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 39.8% 29.9% 19.9% 10.4% 100.0%






Value Asymp.Std. Errora

Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .413 .029 16.423 .000Disturbance Rank given toRecorded Calls Dependent

.372 .025 16.423 .000

Want to stop CallsDependent

.465 .034 16.423 .000


131



Approx.Tb

Approx.Sig.

Nominal byNominal

Phi 1.093 .000Cramer's V .773 .000


.738 .000






Figure 63 Disturbance Rank given to Recorded Calls and Want to stop Calls

Crosstabulation

Table 72 Disturbance Rank given to Live Calls and Want to stop Calls Crosstabulation

Want to stop Calls TotalStrongly

agreeAgree Neutral Strongly


given to LiveCalls



given to LiveCalls

50.5% .0% 49.5% .0% 100.0%


25.0% .0% 48.9% .0% 19.7%

% of Total 10.0% .0% 9.7% .0% 19.7%3 Count 92 46 0 45 183


Disturbance Rankgiven to Live

Calls

50.3% 25.1% .0% 24.6% 100.0%

132


50.0% 33.3% .0% 93.8% 39.6%

% of Total 19.9% 10.0% .0% 9.7% 39.6%4 Count 0 0 47 3 50



Calls

.0% .0% 94.0% 6.0% 100.0%


.0% .0% 51.1% 6.2% 10.8%

% of Total .0% .0% 10.2% .6% 10.8%5 Count 46 92 0 0 138



Calls

33.3% 66.7% .0% .0% 100.0%


25.0% 66.7% .0% .0% 29.9%

% of Total 10.0% 19.9% .0% .0% 29.9%Total Count 184 138 92 48 462



Calls

39.8% 29.9% 19.9% 10.4% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 39.8% 29.9% 19.9% 10.4% 100.0%







Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric -.020 .037 -.547 .584Disturbance Rank given to

Live Calls Dependent-.020 .037 -.547 .584

Want to stop CallsDependent

-.020 .037 -.547 .584


133



Approx.Tb

Approx.Sig.

Nominal byNominal

Phi .972 .000Cramer's V .561 .000


.697 .000

Ordinal by Ordinal Kendall's tau-b -.020 .037 -.547 .584Kendall's tau-c -.019 .035 -.547 .584

Gamma -.026 .048 -.547 .584Spearman Correlation -.009 .046 -.191 .849c

Interval by Interval Pearson's R -.097 .033 -2.087 .037c



134


Correlations FindingCalls

interesting

FindingCallsuseful

FindingCatalogs/Broch

uresinteresti

ng

FindingCatalogs/Broch

uresuseful

FindingSMS

interesting

FindingSMSuseful

FindingSpam/J

unkinteresti

ng

FindingSpam/J

unkuseful

Spearman's rho

FindingCallsinteresting


1.000 .591** -.025 .263** .413** .149** -.110* .150**

Sig. (2-tailed)

. .000 .587 .000 .000 .001 .018 .001

N 462 462 462 462 462 462 462 462FindingCallsuseful


.591** 1.000 .306** -.076 .605** .317** -.012 .154**

Sig. (2-tailed)

.000 . .000 .104 .000 .000 .795 .001

N 462 462 462 462 462 462 462 462FindingCatalogs/Brochuresinteresting


-.025 .306** 1.000 .683** .535** .519** .621** .627**

Sig. (2-tailed)

.587 .000 . .000 .000 .000 .000 .000

N 462 462 462 462 462 462 462 462FindingCatalogs/Brochuresuseful


.263** -.076 .683** 1.000 .385** .369** .541** .621**

Sig. (2-tailed)

.000 .104 .000 . .000 .000 .000 .000

N 462 462 462 462 462 462 462 462FindingSMSinteresting


.413** .605** .535** .385** 1.000 .454** .597** .366**

Sig. (2-tailed)

.000 .000 .000 .000 . .000 .000 .000

N 462 462 462 462 462 462 462 462FindingSMSuseful


.149** .317** .519** .369** .454** 1.000 .602** .363**

Sig. (2-tailed)

.001 .000 .000 .000 .000 . .000 .000

N 462 462 462 462 462 462 462 462FindingSpam/Junkinteresting


-.110* -.012 .621** .541** .597** .602** 1.000 .443**

Sig. (2-tailed)

.018 .795 .000 .000 .000 .000 . .000

N 462 462 462 462 462 462 462 462FindingSpam/Junk

CorrelationCoeffic

.150** .154** .627** .621** .366** .363** .443** 1.000

135

Figure 64 Want to stop calls and disturbance ranks given to live calls

Hypothesis that there is no significant relationship between disturbance ranks

given to marketing communications by the customers and customers’ preferences

to stop them is rejected. There is significant relationship between disturbance

ranks given to marketing communications by the customers and customers’

preferences to stop communications.

Hypothesis 4.

H0: There is no significant relationship between customers’ finding marketing

communications interesting and finding the marketing communications useful.

H1: There is significant relationship between customers’ finding marketing

communications interesting and finding the marketing communications useful.

useful ientSig. (2-tailed)

.001 .001 .000 .000 .000 .000 .000 .

N 462 462 462 462 462 462 462 462

**. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).

136


Table 77 Finding Catalogs/Brochures interesting and Finding Catalogs/Brochures useful

Crosstabulation

Finding Catalogs/Brochuresuseful

Total

Agree Neutral DisagreeFinding

Catalogs/Brochuresinteresting

Agree Count 92 47 0 139Expected Count 41.5 82.7 14.7 139.0

% within FindingCatalogs/Brochures

interesting

66.2% 33.8% .0% 100.0%


useful

66.7% 17.1% .0% 30.1%

% of Total 19.9% 10.2% .0% 30.1%Neutral Count 46 228 0 274

Expected Count 81.8 163.1 29.1 274.0% within Finding


16.8% 83.2% .0% 100.0%


useful

33.3% 82.9% .0% 59.3%

% of Total 10.0% 49.4% .0% 59.3%Disagree Count 0 0 49 49



.0% .0% 100.0% 100.0%


useful

.0% .0% 100.0% 10.6%

% of Total .0% .0% 10.6% 10.6%Total Count 138 275 49 462



29.9% 59.5% 10.6% 100.0%


useful

100.0% 100.0% 100.0% 100.0%

% of Total 29.9% 59.5% 10.6% 100.0%





137



Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .670 .034 15.034 .000Finding

Catalogs/Brochuresinteresting Dependent

.671 .035 15.034 .000

FindingCatalogs/Brochuresuseful Dependent

.670 .035 15.034 .000




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi 1.116 .000Cramer's V .789 .000


.745 .000






Figure 65 Finding Catalogs/Brochures interesting and Finding

Catalogs/Brochures useful Crosstabulation

Table 81 Finding Spam/Junk interesting and Finding Spam/Junk useful Crosstabulation

Finding Spam/Junk useful TotalAgree Neutral Disagree

Finding Spam/Junkinteresting

Agree Count 46 86 0 132Expected Count 16.3 99.4 16.3 132.0

138

% within FindingSpam/Junkinteresting

34.8% 65.2% .0% 100.0%

% within FindingSpam/Junk useful

80.7% 24.7% .0% 28.6%

% of Total 10.0% 18.6% .0% 28.6%Neutral Count 0 170 0 170


Spam/Junkinteresting

.0% 100.0% .0% 100.0%


.0% 48.9% .0% 36.8%

% of Total .0% 36.8% .0% 36.8%Disagree Count 0 46 46 92



.0% 50.0% 50.0% 100.0%


.0% 13.2% 80.7% 19.9%

% of Total .0% 10.0% 10.0% 19.9%Stronglydisagree

Count 11 46 11 68Expected Count 8.4 51.2 8.4 68.0

% within FindingSpam/Junkinteresting

16.2% 67.6% 16.2% 100.0%


19.3% 13.2% 19.3% 14.7%

% of Total 2.4% 10.0% 2.4% 14.7%Total Count 57 348 57 462



12.3% 75.3% 12.3% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 12.3% 75.3% 12.3% 100.0%





139



Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .397 .039 9.065 .000Finding Spam/Junk

interesting Dependent.555 .050 9.065 .000

Finding Spam/Junkuseful Dependent

.309 .035 9.065 .000




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi .743 .000Cramer's V .525 .000


.596 .000






Figure 66 Finding Spam/Junk interesting and Finding Spam/Junk useful

Crosstabulation

Table 85 Finding SMS interesting and Finding SMS useful Crosstabulation

Finding SMS useful TotalAgree Neutral Disagree Strongly

disagreeFinding SMS

interestingAgree Count 53 3 22 22 100

Expected Count 23.8 46.8 14.7 14.7 100.0% within 53.0% 3.0% 22.0% 22.0% 100.0%

140

Finding SMSinteresting% within

Finding SMSuseful

48.2% 1.4% 32.4% 32.4% 21.6%

% of Total 11.5% .6% 4.8% 4.8% 21.6%Neutral Count 57 167 0 0 224


Finding SMSinteresting

25.4% 74.6% .0% .0% 100.0%

% withinFinding SMS

useful

51.8% 77.3% .0% .0% 48.5%

% of Total 12.3% 36.1% .0% .0% 48.5%Disagree Count 0 46 46 0 92



.0% 50.0% 50.0% .0% 100.0%

% withinFinding SMS

useful

.0% 21.3% 67.6% .0% 19.9%

% of Total .0% 10.0% 10.0% .0% 19.9%Stronglydisagree

Count 0 0 0 46 46Expected Count 11.0 21.5 6.8 6.8 46.0

% withinFinding SMS

interesting

.0% .0% .0% 100.0% 100.0%

% withinFinding SMS

useful

.0% .0% .0% 67.6% 10.0%

% of Total .0% .0% .0% 10.0% 10.0%Total Count 110 216 68 68 462



23.8% 46.8% 14.7% 14.7% 100.0%

% withinFinding SMS

useful

100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 23.8% 46.8% 14.7% 14.7% 100.0%







Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .442 .050 8.639 .000Finding SMS


141

Finding SMS usefulDependent

.446 .049 8.639 .000




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi 1.108 .000Cramer's V .640 .000


.742 .000






Figure 67 Finding SMS interesting and Finding SMS useful Crosstabulation

Table 89 Finding Calls interesting and Finding Calls useful Crosstabulation

Finding Calls useful TotalStrongly

agreeAgree Neutral Disagree Strongly

disagreeFinding

Callsinteresting

Agree Count 50 13 0 0 0 63Expected

Count7.0 8.2 23.9 12.5 11.5 63.0

% withinFinding

Callsinteresting

79.4% 20.6% .0% .0% .0% 100.0%

% withinFinding

Calls useful

98.0% 21.7% .0% .0% .0% 13.6%

142

% of Total 10.8% 2.8% .0% .0% .0% 13.6%Neutral Count 0 0 175 0 38 213

ExpectedCount

23.5 27.7 80.7 42.4 38.7 213.0

% withinFinding

Callsinteresting

.0% .0% 82.2% .0% 17.8% 100.0%

% withinFinding

Calls useful

.0% .0% 100.0% .0% 45.2% 46.1%

% of Total .0% .0% 37.9% .0% 8.2% 46.1%Disagree Count 0 47 0 92 0 139

ExpectedCount

15.3 18.1 52.7 27.7 25.3 139.0

% withinFinding

Callsinteresting

.0% 33.8% .0% 66.2% .0% 100.0%

% withinFinding

Calls useful

.0% 78.3% .0% 100.0% .0% 30.1%

% of Total .0% 10.2% .0% 19.9% .0% 30.1%Stronglydisagree


Count5.2 6.1 17.8 9.4 8.5 47.0

% withinFinding

Callsinteresting

2.1% .0% .0% .0% 97.9% 100.0%

% withinFinding

Calls useful

2.0% .0% .0% .0% 54.8% 10.2%

% of Total .2% .0% .0% .0% 10.0% 10.2%Total Count 51 60 175 92 84 462

ExpectedCount

51.0 60.0 175.0 92.0 84.0 462.0

% withinFinding

Callsinteresting

11.0% 13.0% 37.9% 19.9% 18.2% 100.0%

% withinFinding

Calls useful

100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 11.0% 13.0% 37.9% 19.9% 18.2% 100.0%





143



Approx.Tb

Approx.Sig.

Ordinal byOrdinal

Somers'd

Symmetric .542 .043 11.859 .000Finding Calls


Finding Calls usefulDependent

.577 .043 11.859 .000




Approx.Tb

Approx.Sig.

Nominal byNominal

Phi 1.479 .000Cramer's V .854 .000


.828 .000






Figure 68 Finding Calls interesting and Finding Calls useful Crosstabulation

Hypothesis that there is no significant relationship between customers’ finding

marketing communications interesting and finding the marketing communications

useful is rejected. There is significant relationship between customers’ finding

marketing communications interesting and finding marketing communications

useful.

144

Hypothesis 5.

H0: There is no significant relationship between customers’ awareness about

Permission Marketing and Education, Occupation, and City of the customers.

H1: There is significant relationship between customers’ awareness about

Permission Marketing and Education, Occupation, and City of the customers.


Awarenessabout

PermissionMarketing

Education ofthe

Respondents

Occupationof the

Respondents


Spearman'srho

AwarenessaboutPermissionMarketing


1.000 -.492** .225** .292**

Sig. (2-tailed)

. .000 .000 .000

N 462 462 462 462Education oftheRespondents


-.492** 1.000 .272** -.290**

Sig. (2-tailed)

.000 . .000 .000

N 462 462 462 462Occupationof theRespondents


.225** .272** 1.000 -.010

Sig. (2-tailed)

.000 .000 . .836

N 462 462 462 462City of theRespondents


.292** -.290** -.010 1.000

Sig. (2-tailed)

.000 .000 .836 .

N 462 462 462 462**. Correlation is significant at the 0.01level (2-tailed).


Table 94 Awareness about Permission Marketing and Education of the Respondents

Crosstabulation

Education of the Respondents TotalProfessional PG Graduate HSC SSC

Awarenessabout

PermissionMarketing

Yes Count 2 6 8 17 36 69Expected

Count22.0 14.0 18.8 8.4 5.8 69.0

% withinAwareness

aboutPermissionMarketing

2.9% 8.7% 11.6% 24.6% 52.2% 100.0%


theRespondents

1.4% 6.4% 6.3% 30.4% 92.3% 14.9%

145

% of Total .4% 1.3% 1.7% 3.7% 7.8% 14.9%No Count 145 88 118 39 3 393

ExpectedCount

125.0 80.0 107.2 47.6 33.2 393.0

% withinAwareness


36.9% 22.4% 30.0% 9.9% .8% 100.0%


theRespondents

98.6% 93.6% 93.7% 69.6% 7.7% 85.1%

% of Total 31.4% 19.0% 25.5% 8.4% .6% 85.1%Total Count 147 94 126 56 39 462

ExpectedCount

147.0 94.0 126.0 56.0 39.0 462.0

% withinAwareness


31.8% 20.3% 27.3% 12.1% 8.4% 100.0%


theRespondents

100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 31.8% 20.3% 27.3% 12.1% 8.4% 100.0%









146

Figure 69 Awareness about Permission Marketing and Education of the

Respondents Crosstabulation

Table 97 Awareness about Permission Marketing and Occupation of the Respondents

Crosstabulation

Occupation of the Respondents TotalProfessiona

lGovt.

Employee

Pvt.Employe

e

Self-employe

d

House-wife

Awareness about

Permission

Marketing

Yes


Count19.9 7.8 20.8 13.7 6.9 69.0

% withinAwareness


58.0% 7.2% 21.7% 1.4% 11.6% 100.0%

% withinOccupation

of theRespondent

s

30.1% 9.6% 10.8% 1.1% 17.4% 14.9%

% of Total 8.7% 1.1% 3.2% .2% 1.7% 14.9%No Count 93 47 124 91 38 393

ExpectedCount

113.1 44.2 118.2 78.3 39.1 393.0

% withinAwareness


23.7% 12.0% 31.6% 23.2% 9.7% 100.0%

% withinOccupation

of theRespondent

s

69.9% 90.4% 89.2% 98.9% 82.6% 85.1%

% of Total 20.1% 10.2% 26.8% 19.7% 8.2% 85.1%

147

Total Count 133 52 139 92 46 462Expected

Count133.0 52.0 139.0 92.0 46.0 462.0

% withinAwareness


28.8% 11.3% 30.1% 19.9% 10.0% 100.0%

% withinOccupation

of theRespondent

s

100.0% 100.0% 100.0% 100.0% 100.0%

100.0%

% of Total 28.8% 11.3% 30.1% 19.9% 10.0% 100.0%









Figure 70 Awareness about Permission Marketing and Occupation of the

Respondents Crosstabulation

148

Table 100 Awareness about Permission Marketing and City of the Respondents

Crosstabulation

City of the Respondents TotalAhmedabad Baroda Surat Rajkot Jamnagar Anand

Awarenessabout

PermissionMarketing

Yes Count 30 21 4 4 3 7 69Expected

Count11.9 11.8 11.6 11.2 11.2 11.2 69.0

% withinAwareness


43.5% 30.4% 5.8% 5.8% 4.3% 10.1% 100.0%

% withinCity of the

Respondents

37.5% 26.6% 5.1% 5.3% 4.0% 9.3% 14.9%

% of Total 6.5% 4.5% .9% .9% .6% 1.5% 14.9%No Count 50 58 74 71 72 68 393

ExpectedCount

68.1 67.2 66.4 63.8 63.8 63.8 393.0

% withinAwareness


12.7% 14.8% 18.8% 18.1% 18.3% 17.3% 100.0%

% withinCity of the

Respondents

62.5% 73.4% 94.9% 94.7% 96.0% 90.7% 85.1%

% of Total 10.8% 12.6% 16.0% 15.4% 15.6% 14.7% 85.1%Total Count 80 79 78 75 75 75 462

ExpectedCount

80.0 79.0 78.0 75.0 75.0 75.0 462.0

% withinAwareness


17.3% 17.1% 16.9% 16.2% 16.2% 16.2% 100.0%

% withinCity of the

Respondents

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 17.3% 17.1% 16.9% 16.2% 16.2% 16.2% 100.0%


Value Df Asymp. Sig. (2-sided)Pearson Chi-Square 60.757a 5 .000







149

Figure 71 Awareness about Permission Marketing and City of the Respondents

Crosstabulation


about Permission Marketing and education, occupation, and city of the customers

is rejected. There is significant relationship between customers’ awareness about

Permission Marketing and education, occupation, and city of the customers.

150

5. 5. MODEL DEVELOPED FROM HYPOTHESES TESTING

Figure 72 Relationship among customers’ awareness, perceptions,and preferences

The above model is developed from the hypotheses testing results of five hypotheses.

Customers’ awareness, perceptions, and preferences are related with four factors viz.

Permission Marketing awareness, DNC awareness, finding marketing

communications interesting, and Disturbance ranks given to marketing

communications. Relationships between these factors and customers’ Education,

151

Occupation, Gender, City, perceived usefulness of communication tools, and

preferences to stop communications is checked. As the above model shows,

customers’ education, occupation, and city are related with customers’ awareness

about permission marketing. Customers’ education and occupation are related with

customers’ awareness about DNC but customers’ city and gender are not related with

awareness about DNC. Customers’ finding marketing communications useful is

related with customers’ finding marketing communications interesting. Finally,

customers’ preferences to stop receiving marketing communications are related with

disturbance ranks given by the customers to these marketing communications.

Additional Chi-Square statistics:

Table 103 Awareness about Consumer Protection Act and Awareness about CPA contact

details Crosstabulation

Awareness about CPAcontact details

Total

Yes NoAwareness about

Consumer ProtectionAct


% within Awarenessabout ConsumerProtection Act

7.3% 92.7% 100.0%

% within Awarenessabout CPA contact

details

84.4% 79.5% 79.9%

% of Total 5.8% 74.0% 79.9%No Count 5 88 93

Expected Count 6.4 86.6 93.0% within Awareness

about ConsumerProtection Act

5.4% 94.6% 100.0%


details

15.6% 20.5% 20.1%



about ConsumerProtection Act

6.9% 93.1% 100.0%


details

100.0% 100.0% 100.0%

% of Total 6.9% 93.1% 100.0%

152



Exact Sig.(2-sided)

Exact Sig.(1-sided)

Pearson Chi-Square .434a 1 .510Continuity Correctionb .185 1 .667

Likelihood Ratio .460 1 .498Fisher's Exact Test .650 .346Linear-by-Linear

Association.433 1 .511

N of Valid Casesb 462a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6.44.b. Computed only for a 2x2 table





Figure 73 Awareness about Consumer Protection Act and Awareness about CPA contact

details Crosstabulation

The above result shows that null hypothesis is not rejected. There is no relationship

between Awareness about Consumer Protection Act and Awareness about CPA

contact details.

Table 106 Awareness about Consu. Dispute Redress Comm. and Awareness about

CDRC office Crosstabulation

Awareness about CDRCoffice

Total

Yes NoAwareness about ConsuDispute Redress Comm.


153

% within Awarenessabout Consu Dispute

Redress Comm.

6.5% 93.5% 100.0%

% within Awarenessabout CDRC office

85.7% 79.5% 79.9%

% of Total 5.2% 74.7% 79.9%No Count 4 89 93

Expected Count 5.6 87.4 93.0% within Awarenessabout Consu Dispute

Redress Comm.

4.3% 95.7% 100.0%


14.3% 20.5% 20.1%

% of Total .9% 19.3% 20.1%Total Count 28 434 462

Expected Count 28.0 434.0 462.0% within Awarenessabout Consu Dispute

Redress Comm.

6.1% 93.9% 100.0%


100.0% 100.0% 100.0%

% of Total 6.1% 93.9% 100.0%



Exact Sig.(2-sided)

Exact Sig.(1-sided)









Figure 74 Awareness about Consumer Dispute Redress Commission and Awareness about

CDRC office Crosstabulation

154


between Awareness about Consumer Dispute Redress Commission and Awareness

about CDRC office.

Table 109 Awareness about Permission Marketing and Gender of the Respondents

Crosstabulation

Gender of the Respondents TotalFemale Male

Awareness aboutPermission Marketing


% within Awarenessabout Permission

Marketing

29.0% 71.0% 100.0%


13.8% 15.5% 14.9%

% of Total 4.3% 10.6% 14.9%No Count 125 268 393


about PermissionMarketing

31.8% 68.2% 100.0%


86.2% 84.5% 85.1%



about PermissionMarketing

31.4% 68.6% 100.0%


100.0% 100.0% 100.0%

% of Total 31.4% 68.6% 100.0%


Value Df Asymp. Sig.(2-sided)

Exact Sig.(2-sided)

Exact Sig.(1-sided)





155


Value Approx. Sig.Nominal by Nominal Phi -.022 .641



Figure 75 Awareness about Permission Marketing and Gender of the Respondents

Crosstabulation


between Awareness about Permission Marketing and Gender of the Respondents.

5. 6. CLUSTERED BAR CHARTS

Comparisons of values between two categories are done by using Clustered Bar

Charts. For the following variables clustered charts are prepared:

1. Permission Marketing awareness, and DNC awareness

2. Willingness to stop Calls, and DNC awareness

3. Willingness to stop Calls, and Occupation of the respondents

4. Willingness to stop Calls, and Education of the respondents

5. Disturbed by Calls, and thinking that calls should be banned

6. Willingness to stop SMS, and DNC awareness

7. Disturbed by SMS, and thinking that SMS should be banned

8. Willingness to stop SMS, and Education of the respondents

9. Willingness to stop SMS, and Occupation of the respondents

10. Disturbed by Spam/Junk, and thinking that Spam/Junk should be banned

11. Willingness to stop Spam/Junk, and Education of the respondents

156

12. Willingness to stop Spam/Junk, and Occupation of the respondents

13. Willingness to stop Catalogs/Brochures, and Education of the respondents

14. Disturbed by Catalogs/Brochures, and thinking that Catalogs/Brochures should

be banned

15. Willingness to stop Catalogs/Brochures, and Occupation of the respondents

Awareness

Figure 76 Permission Marketing awareness, and DNC awareness

88 % respondents are unaware about both - permission marketing and Do Not Call

Registry. 20 % respondents are aware about both – permission marketing and Do Not

Call Registry. 11 % are aware about permission marketing but unaware about Do Not

Call Registry. 79 % respondents are unaware about permission marketing but aware

about Do Not Call Registry.

157

Unwanted Calls

Figure 77 Willingness to stop Calls, and DNC awareness

Among those respondents who are aware about Do Not Call Registry, 95 % strongly

disagree that they prefer to stop receiving unwanted marketing calls. Among those

respondents who are not aware about Do Not Call Registry, 75 % strongly agree that

they prefer to stop receiving unwanted marketing calls.

Figure 78 Willingness to stop Calls, and Occupation of the respondents

95 % Professionals and 5 % government employees strongly disagree that they prefer

to stop receiving unwanted marketing calls. 50 % private sector employees strongly

agree that they prefer to stop receiving unwanted marketing calls.

158

Figure 79 Willingness to stop Calls, and Education of the respondents

64 % Graduate respondents strongly agree that they prefer to stop receiving unwanted

marketing calls while 66 % Professional respondents strongly disagree that they

prefer to stop receiving unwanted marketing calls.

Figure 80 Disturbed by Calls and thinking that calls should be banned

93 % respondents strongly agree that they get disturbed by unwanted marketing calls

and they think that government should ban these types of calls.

159

Unwanted SMS

Figure 81 Willingness to stop SMS and DNC awareness

40 % respondents, who are aware about Do Not Call Registry, strongly agree that they

prefer to stop receiving unwanted marketing SMS.

Figure 82 Disturbed by SMS and thinking that SMS should be banned

97 % respondents strongly agree that they get disturbed by unwanted marketing SMS

and they think that government should ban these types of SMS.

160

Figure 83 Willingness to stop SMS, and Education of the respondents

51 % Graduates strongly agree that they prefer to stop receiving unwanted marketing

SMS while 55 % Professionals strongly disagree that they prefer to stop receiving

unwanted marketing SMS.

Figure 84 Willingness to stop SMS, and Occupation of the respondents

40 % private sector employees, 40 % self-employed, and 20 % housewives strongly

agree that they prefer to stop receiving unwanted marketing SMS while 95 %

Professionals and 5 % government employees strongly disagree that they prefer to

stop receiving unwanted marketing SMS.

161

Spam/Junk e-mail

Figure 85 Disturbed by Spam/Junk, and thinking that Spam/Junk should be banned

50 % respondents, who strongly agree and 50 % who agree, these both types of

respondents strongly agree that spam/junk e-mails should be banned by the

government.

Figure 86 Willingness to stop Spam/Junk, and Education of the respondents

71 % Graduates strongly agree that they prefer to stop receiving spam/junk e-mails

while 80 % Professional degree holders agree that they prefer to stop receiving

spam/junk e-mails.

162

Figure 87 Willingness to stop Spam/Junk, and Occupation of the respondents

71 % Self-employed strongly agree and 53 % Self-employed agree that they prefer to

stop receiving spam/junk e-mails.

Catalogs/Brochures

Figure 88 Willingness to stop Catalogs/Brochures, and Education of the respondents

47 % Professionals strongly agree, 43 % Professional agree, 43 % strongly disagree,

62 % Postgraduates disagree and 64 % Graduates have neutral opinion that they

prefer to stop receiving unwanted catalogs/brochures from companies.

163

Figure 89 Disturbed by Catalogs/Brochures, and thinking that Catalogs/Brochures should be

banned

All the respondents who strongly agree and all the respondents who agree think thatgovernment should ban unwanted catalogs/brochures.

Figure 90 Willingness to stop Catalogs/Brochures, and Occupation of the respondents

90 % Professionals strongly agree and 76 % Professionals strongly disagree that they

prefer to stop receiving unwanted catalogs/brochures from marketing companies.

164

Chapter Bibliography

Books

1. Argyrous George, Statistics for Research: With a Guide to SPSS, Sage

Publications Ltd, 2nd ed, 2005.

2. Belle Gerald Van, Statistics Rules of Thumb¸ 1st ed, Wiley-Interscience, 2002.

3. Field Andy, Discovering Statistics Using SPSS for Windows: Advanced

Techniques for the Beginner, Sage Publications Ltd, 1st ed 2000.

4. Kerr Alistair, Hall Howard and Kozub Stephen, Doing Statistics with SPSS,

SAGE Publications Ltd, 2002.

5. Nargundkar Rajendra, Marketing Research: Text & Cases, 2nd ed, Tata McGraw-

Hill, 2003.

6. Rao A Sajeevan and Tyagi Deepak, Research Methodology with SPSS: Statistical

Package for the Social Sciences, 1st ed, Shree Niwas Publications, Jaipur, 2009.

Websites

1. www.etstrategicmarketing.com, Accessed on Aug 9, 2007

2. www.ezlistmailer.com/images/downloads/EZL-hite-Paper-December-

2006.doc+permission+marketing&hl=en&ct=clnk&cd=5&gl=in, Accessed on

Aug 9, 2007

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