consumer level of impact and satisfaction towards mobile...

© IJARCSMS (www.ijarcsms.com), All Rights Reserved 87 | P a g e

ISSN: 2321-7782 (Online) e-ISJN: A4372-3114 Impact Factor: 7.327

Volume 6, Issue 4, April 2018

International Journal of Advance Research in Computer Science and Management Studies

Research Article / Survey Paper / Case Study Available online at: www.ijarcsms.com

Consumer Level of Impact and Satisfaction towards Mobile

Applications Dr. P. Bruntha

1

Research Guide, Associate Professor & Head

PG & Research Department of Commerce

Nallamuthu Gounder Mahalingam College

Pollachi, India

B. Sivakavin2

Research scholar

PG & Research Department of Commerce

Nallamuthu Gounder Mahalingam College

Pollachi, India

Abstract: In today’s world the smart phone has become an essential part of daily life. While it has become more balanced,

the number of smart phone users has increased drastically. The main objectives of the study are to know the level of impact

and satisfaction towards mobile application. Convenience sampling was also used to determine the sample size for the

respondents. Pollachi and Coimbatore are the study area. A total of 165 respondents are taken as sample for this study. The

study makes use of statistical techniques such as simple percentage analysis, Chi- square test, weighted average rank and

Friedman Rank method in analyzing the data for finding the result. The study recommended that the app developers should

create awareness about the services and special features of their applications and the users should not reveal any personal

information while using the apps to avoid security issues.

Keywords: Smart phone; mobile application; impact; satisfaction; app developers.

I. INTRODUCTION

In recent times, mobile phone becomes the most important part of life. The fascination towards mobile phone is more

among the younger generation and the mounting use may result in addiction. A mobile app is software which is designed to run

on smart phones, tablets, computers and other mobile devices. Apps are available through distribution platforms on concrete app

stores. There are cost free as well as paid apps. Initially some apps are available for free, but later a minimum charge is essential

to relish premium benefits. The iphones influential software, pioneering user interface, and prevailing development platform

had driven an almost overnight explosion of apps. For apps with a price, 20-30% goes to the distribution provider and the rest

goes to the producer of the app. Initially mobile apps were offered for informational and productivity purposes like email,

calendar, contacts, calculator and weather information. Later, with the rapid magnification in the technology the developers

expanded other categories such as mobile games, GPS, banking, ticket purchases, social media, video chats, factory automation,

location based services, fitness apps and recently mobile medical apps.

II. STATEMENT OF THE PROBLEM

The different smart phone users have different opinion about the mobile applications. It is not easy to satisfy the

expectations of the users but there are some common factors that are essential to be fulfilled. The main problem of the study is

to know the various factors that are very important in satisfying the user’s needs and to know how mobile applications are

ensuring its user’s satisfaction.

III. OBJECTIVES OF THE STUDY

To examine the demographic factors of the mobile app users.

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Dr. Bruntha et al., International Journal of Advance Research in Computer Science and Management Studies

Volume 6, Issue 4, April 2018 pg. 87-94

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To study the Internet and Smartphone usage behavior of the students.

To know the user awareness and satisfaction towards mobile application.

IV. SCOPE OF THE STUDY

The study carried out on mobile applications throws light on the benefits and drawbacks in mobile applications. Through

this study the opinion of users can be identified and further studies can be carried out by applying many tools in mobile

applications.

V. METHODOLOGY

Study Area : Pollachi and Coimbatore

Data : Primary and Secondary

Sampling Method : Convenience Sampling

Methods of Data Collection : Questionnaire

Sample Size : 165

Statistical Tools Used : Simple Percentage

Weighted Average Rank Analysis

Friedman Rank Test

Chi-Square

VI. REVIEW OF LITERATURE

Hem Shweta Rathore (2016), in his study entitled on “Adoption of Digital Wallet by Consumers focuses to study the risk

and challenges faced by consumers in using the digital wallet. From the study it is found that the Security and safety of the

funds is the most challenging issue for the users.

Sahana and Basavashree (2016), in their study entitled “A Study on Usability of Savvy Mob Mobile Applications” aims

to identify the factors that affect the usability of Savvy Mob Mobile App. The study recommended that the satisfied user will

directly or indirectly helps in increasing the popularity of the app.

Maha.Alqahtani and Heba. Mohammad (2015), in their study entitled “Mobile Applications’ Impact on Student

Performance and Satisfaction” aims to study the relationship between behavioral factors and perceived usefulness of “Say

Quran”.

VII. ANALYSIS AND INTERPRETATIONS

I. SOCIAL PROFILE

The buying decisions may be impacted by the social factors like Gender, Age, Area of Residence, Type of family,

Educational Qualification, Size of the Family, Earning Members in the Family and Family income per month. Hence an attempt

has been made in this chapter to make a complete profile of the sample respondents.

Table – 1 Demographic Profile

S.No Determinants ( N=165) Percentage (%)

1 Gender

Male Female

40 125

24.2 75.8

2 Age

18-20 years 21-25 years

157 8

95.2 4.8

3

Area of Residence Rural

Semi – urban Urban

99 42 24

60.0 25.5 14.5

4

Type of family Nuclear

Joint

127 38

77.0 23.0




5

Educational Qualification Diploma

Under Graduate Post Graduate

2 157

6

1.2

95.2

3.6

6

Size of the Family Below 4 members

4-6 members More than 6 members

93 63 9

56.4 38.2 5.5

7

Earning Members in the Family 1-2 members 3-4 members

More than 5 members

136 25 4

82.4 15.2 2.4

8

Family income per month Below Rs.10,000

Rs.10,001 to Rs.20,000 Above Rs.20,000

75 84 6

45.5 50.9 3.6

Total 165 100.0

Thus, it could be inferred that majority of 125(75.8%) respondents are female. The majority of 157(95.2%) respondents are

in the age group between 18-20 years. The majority of 99 (60.0%) respondents belong to rural area. Majority of 127 (77.0%)

respondents belong to nuclear family and the majority of 157 (95.2%) are under graduates. 93 (56.4%) of the respondents have

below 4 members in their family. Majority of 136 (82.4%) respondents have 1-2 earning members in their family and the

majority of 84 (50.9%) respondents’ family income per month is Rs. 10,000 to Rs.20,000.

VIII. SMARTPHONE AND INTERNET USAGE BEHAVIOR

Smart phone usage has proliferated in recent years. Some areas of the world are enjoying rapid development and high

penetration of mobile technology. In recent times, the Internet and worldwide web have changed the way the consumers seek

and use information. The Internet was conceptualized as a tool for enhancing information and has become an important place

for business these days.

Table – 2 Smartphone and Internet Usage Behavior

S.No Determinants ( N=165) Percentage (%)

1

Number of Smartphone One Two

More than 2

112 47 6

67.9 28.5 3.6

2

Brand Preference of Smartphone Blackberry

Iphone Lava

Lenova Moto Oppo Redmi

Samsung Sony Vivo

7 9 4

12 4

46 6

53 12 12

4.2 5.5 2.4 7.3 2.4 27.9 3.6 32.1 7.3 7.3

3 Device Preference

Mobile Phone Tablets

163 2

98.8 1.2

4

OS Preference IOS

Android Blackberry

20 138 7

12.1 83.7 4.2

5

Language Preference English

Regional Language

143 22

86.7 13.3




6

Preference of Internet Connection Wifi

Mobile Internet Both

6 95 64

3.6 57.6 38.8

7

Internet Usage per day Less than 500 MB

500 MB - 1 GB 1 GB - 5 GB

More than 5 GB Unlimited

9 73 34 6

43

5.5 44.2 20.6 3.6 26.1

Total 165 100.0

From the table, out of 165 respondents, most 112 (67.9%) respondents own only one Smartphone. Most of the respondents

have preferred Samsung Smart phones especially for their updated features. (98.8%) have preferred mobile phones for using the

apps. 138 (83.7%) respondents have preferred Google android. The maximum143 (86.7%) respondents have preferred English.

The majority 95 (57.6%) of the respondents are using mobile internet and the majority 73 (44.2%) respondents’ uses 500 MB –

1 GB per day.

IX. WEIGHTED AVERAGE RANK ANALYSIS

The weighted average formula is used to calculate the average value of a particular set of numbers with different levels of

relevance. The relevance of each number is called its weight. The weights should be represented as a percentage of the total

relevancy. Therefore, all weights should be equal to 100%, or 1.

Table – 3 Preference on downloading the Apps

The above table 4.22 shows that, the average scores are ranked according to their values. It is clear that among the seven

factors, Popularity has secured first rank, Developers is second, New Arrival is third, Ratings and Reviews is fourth, Need

Based is fifth, Never Mind is sixth and User Recommendation is seventh. Therefore, it is inferred that, “Popularity” has scored

the first rank.

Rank Weight

Popularity Ratings and

Reviews Developers

User

Recommend

ation

New Arrival Need Based Never Mind

No of

respond

ents

score

No of

respon

dents

Score

No of

respon

dents

score

No of

respon

dents

score

No of

respon

dents

score

No of

respon

dents

score

No of

respon

dents

score

I 7 35 245 36 252 52 364 15 105 8 56 15 105 12 84

II 6 39 234 30 180 11 66 12 72 46 276 10 60 9 54

III 5 37 185 15 75 15 75 29 145 33 165 8 40 15 75

IV 4 26 104 21 84 42 168 10 40 16 64 14 56 25 100

V 3 12 36 6 18 30 90 24 72 30 90 58 174 20 60

VI 2 12 24 24 48 7 14 15 30 24 48 48 96 36 72

VII 1 4 4 33 33 8 8 60 60 8 8 12 12 48 48

Total 832 690 785 524 707 543 493

Average 118.86 98.57 112.14 74.86 101.00 77.57 70.43

RANK I IV II VI III V VI




Table – 4 Qualities on downloading the Apps

The above table states the qualities for downloading the apps. Based on respondents opinion, the I rank was given to User

Friendly, the II rank is Look and feel / Appealing, Performance was ranked III, and the IV rank is Uniqueness, the V rank is

Cost, the VI rank is Innovative, the VII rank is Fun and engaging, the VIII rank is Size of an app, the IX rank is Low battery

consumption, the X rank is No advertisement and finally the XI rank was given to Security. It is inferred that, “User Friendly”

has scored the first rank and the average score is 121.45.

Ran

k

Wei

ght

Look and

feel /

appealing

Performa

nce User

Friendly

Cost Uniquene

ss

Innovativ

e

Fun and

engaging

Low

battery

consumpt

ion

No

advertise

ment

Security Size of an

app

No

of

resp

onde

nts

scor

e

No

of

resp

onde

nts

Sco

re

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

No

of

resp

onde

nts

sc

or

e

I 1

1 36

3

9

6 20

2

2

0 34

3

7

4 7

7

7 36

3

9

6 5

5

5 16

1

7

6 6

6

6 8

8

8 9

9

9 4

4

4

II 1

0 24

2

4

0 30

3

0

0 24

2

4

0 35

3

5

0 2

2

0 19

1

9

0 10

1

0

0 3

3

0 6

6

0 4

4

0 12

1

2

0

II

I 9 15

1

3

5 18

1

6

2 39

3

5

1 6

5

4 16

1

4

4 6

5

4 5

4

5 12

1

0

8 11

9

9 6

5

4 33

2

9

7

I

V 8 24

1

9

2 34

2

7

2 22

1

7

6 7

5

6 38

3

0

4 9

7

2 2

1

6 12

9

6 4

3

2 22

1

7

6 5

4

0

V

7 23

1

6

1 21

1

4

7 7

4

9 18

1

2

6 9

6

3 29

2

0

3 30

2

1

0 3

2

1 6

4

2 3

2

1 2

1

4

V

I 6 6

3

6 4

2

4 5

3

0 30

1

8

0 26

1

5

6 39

2

3

4 12

7

2 3

1

8 10

6

0 2

1

2 6

3

6

V

II 5 21

1

0

5 9

4

5 6

3

0 2

1

0 12

6

0 12

6

0 55

2

7

5 15

7

5 6

3

0 3

1

5 8

4

0

V

II

I 4 2 8 14

5

6 12

4

8 22

8

8 9

3

6 21

8

4 9

3

6 56

2

2

4 6

2

4 20

8

0 4

1

6

I

X 3 3 9 6

1

8 8

2

4 12

3

6 5

1

5 19

5

7 9

2

7 20

6

0 77

2

3

1 13

3

9 16

4

8

X

2 6

1

2 6

1

2 6

1

2 17

3

4 6

1

2 2 4 12

2

4 19

3

8 4 8 51

1

0

2 33

6

6

X

I 1 5 5 3 3 2 2 9 9 6 6 4 4 5 5 16

1

6 27

2

7 32

3

2 42

4

2

Total 1299 1259 1336 1020 1212 1017 986 752 701 670 763

Avera

ge 118.09 114.45 121.45 92.73 110.18 92.45 89.64 68.36 63.73 60.91 69.36

RANK II III I V IV VI VII IX X XI VIII




X. FRIEDMAN RANK TEST

The Friedman test is non-parametric. It is used to test know the prominent variable that impact the mobile applications. It is

used to test the differences between groups when the dependent variable being measured is ordinal. It can also be used for

continuous data that has violated the assumptions necessary to run the one-way ANOVAs with repeated measures.

Table – 5 Level of Awareness on Independent App Stores

App Stores Aware Not Aware Using Total Mean Value Rank

Cydia 87 (52.7%) 78 (47.3%) 0 (0.0%) 165 2.5272 2

Get jar app store 23 (13.9%) 142 (86.1%) 0 (0.0%) 165 2.1394 9

F. Droid 52 (31.5%) 113 (68.5%) 0 (0.0%) 165 2.3152 4

Amazon app store 99 (60.0%) 54 (32.7%) 12 (7.3%) 165 2.5273 1

And spot app store 59 (35.8%) 90 (54.5%) 16 (9.7%) 165 2.2606 5

App olicious 22 (13.3%) 131 (79.4%) 12 (7.3%) 165 2.0605 11

Crackberry 47 (28.5%) 112 (67.9%) 6 (3.6%) 165 2.2485 6

Handster 34 (20.6%) 117 (70.9%) 14 (8.5%) 165 2.1212 10

Cisco app HQ 33 (20.0%) 132 (80.0%) 0 (0.0%) 165 2.2000 8

Appia 35 (21.2%) 130 (78.8%) 0 (0.0%) 165 2.2121 7

Opera mobile app store 95 (57.6%) 61 (37.0%) 9 (5.5%) 165 2.5212 3

XI. LEVEL OF USAGE ON MOBILE APPLICATIONS

Student’s level of usage on mobile applications has been measured by assigning the scores to questions relating to the

mobile applications. Twenty Five such questions are included in the questionnaire. Answers to the questions are rated on five-

point scale. The scores allotted to the answers range from one to five. Based on the usage index, the students have been divided

into three groups as students with low, moderate and high level of usage. Accordingly, students with usage index ranging up to

51 are termed as students with low level of usage; those with usage index ranging between 52 and 59 are termed as students

with moderate level of usage and those students with usage index above 59 are termed as students with high level of usage. Out

of 165 students, 45 (27.3%) students are with low level of usage; 47 (28.5%) students are with moderate level of usage and the

rest 73 (44.2%) students are with high level of usage.

Table – 6 Demographic Profile and Level of Usage

S.No Variables D.f Calculated

Value

Table

value Result

1 Gender 2 6.008 5.991 Significant

2 Age 2 4.050 5.991 Not Significant

3 Area of Residence 4 48.605 9.488 Significant

4 Type of family 2 16.185 5.991 Significant

5 Educational Qualification 4 2.818 9.488 Not Significant

6 Size of the Family 4 23.165 9.488 Significant

7 Earning Members in the Family 4 11.452 9.488 Significant

8 Family income per month 4 24.173 9.488 Significant

However, as the calculated value is greater than the table at five per cent level, the null hypothesis is rejected. Therefore

it is concluded that there is a significant association between gender, area of residence, type of family, size of the family,

earning members in the family and family income per month of the respondents and level of usage on mobile applications.

XII. LEVEL OF IMPACT ON MOBILE APPLICATIONS

Student’s level of impact on mobile applications has been measured by assigning the scores to the questions relating to

mobile applications. Twenty two such questions are included in the questionnaire. Answers to the questions have been rated on

five-point scale. The scores allotted to the answers range from one to five. Based on the impact index, the students have been

divided into three group as students with low, moderate and high level of impact of mobile applications. Hence the students

with impact index ranging up to 69 are termed as the students with low level of impact; the impact index ranging between 70




and 79 are termed as the students with moderate level of impact and the students with impact index above 79 are having high

level of impact. Of the 165 students, 91 (55.2%) students are with high level of impact; 39 (21.2%) students are with moderate

level of impact and the rest 35 (23.6%) students are with low level of impact.

Table – 7 Demographic Profile and Level of Impact

S.No Variables D.f Calculated

Value

Table

value Result

1 Gender 2 8.830 5.991 Significant

2 Age 2 2.645 5.991 Not Significant

3 Area of Residence 4 16.817 9.488 Significant

4 Type of family 2 27.377 5.991 Significant

5 Educational Qualification 4 12.436 9.488 Significant

6 Size of the Family 4 14.468 9.488 Significant

7 Earning Members in the Family 4 12.793 9.488 Significant

8 Family income per month 4 23.764 9.488 Significant

However, as the calculated value is greater than the table at five per cent level, the null hypothesis is rejected. Therefore

it is concluded that there is a significant association between gender, area of residence, type of family, educational qualification,

size of the family, earning members in the family, family income per month of the respondents and level of impact on mobile

applications.

XIII. SUGGESTIONS

Google needs to improve their software as it is insufficient to handle the multitasking in Android.

Android needs more strict rules regarding the apps that are uploaded on the Play Store so that the data of people are

more secure.

More of 3D and virtual reality apps can be developed in the future.

Less data and battery consumption apps have to be developed by the developers.

As the consumer wants more features, the smart phone manufacturers can increase the number of features.

XIV. CONCLUSION

The variety and accessibility of mobile applications is mounting rapidly. The smart phone apps have been accepted by the

people. The most preferred apps are gaming and social networking apps as compared to the other apps. The students are

addicted to the mobile applications. The mobile application will get enlarged in future, if high network quality, speed and

reasonable cost of data are provided. The mobile application usage and the app industry continue to be on sharp trail and will be

a technological achievement in the future.

ACKNOWLEDGEMENT

I would like to express my special thanks of gratitude to my Guide Dr. P. Bruntha as well as our principal Dr. P.M.

Palanisamy who gave me the golden opportunity to do this wonderful project and also I would like to thank my parents and

friends who helped me a lot in finalizing this project within the limited time frame. I am really thankful to each and every one

of them who helped me in the completion of the project.

References

1. Dr Hem Shweta Rathore (2016), “Adoption of Digital Wallet by Consumers”, BVIMSR’s Journal of Management Research, Vol 8, Issue 1, pp. 69-75.

2. A.Sahana and Basavashree (2016), “A Study on Usability of Savvy Mob Mobile Applications”, Asia Pacific Journal of Research, Vol I, Issue 1, pp.188-

193.

3. Maha.Alqahtani and Heba. Mohammad (2015), “Mobile Applicationss’ Impact on Student Performance and Satisfaction”, The Turkish Online Journal

of Educational Technology, Volume 14, Issue 4, pp.102 – 112.




4. Chai-Lee Goi and Poh-Yen Ng (2011), “Perception of Young Consumers on Mobile Phone Applications in Malaysia”, World Applied Sciences Journal,

Vol 15, Issue 1, pp.47-55.

5. Md. Rashedul Islam, Md. Rofiqul Islam and Tahidul Arafhin Mazumder (2010), “Mobile Application and Its Global Impact”, International Journal

of Engineering & Technology, Vol 3, Issue 1, pp.72-78.

AUTHOR(S) PROFILE

Dr. P. Bruntha, is an Associate professor in the PG and Research department of Commerce, NGM

College, Pollachi. She has put in 30 years of teaching in the field of Commerce and Management. She

has presented 40 research papers in National and International Seminars and Conferences. She has to

her credit seven publications in Edited Volumes and Nine publications in reputed journals. She has

produced 30 M.Phil., scholars. Her specialization is HR and Banking.

B. Sivakavin, is a Research Scholar in PG and Research department of Commerce, NGM College,

Pollachi. She has presented 4 research papers in National and International Seminars and Conferences.

Her Specialization is marketing.

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