International Research Journal of Management and Commerce Vol. 4, Issue 6, June 2017 Impact Factor- 5.564
ISSN: (2348-9766)
© Associated Asia Research Foundation (AARF)
Website: www.aarf.asiaEmail : [email protected] , [email protected]
IMPACT OF AGE ON USAGE OF MOBILE APPS
(EMPERICAL STUDY OF RELATIONSHIP BETWEEN MOBILE APP
USAGE AND AGE FACTOR)
Swati Agarwal
Research Scholar, CCS University, Meerut, Uttar Pradesh, India
& Vinod Soni
Assistant Professor, IIHS, Indirapuram, Ghaziabad Uttar Pradesh, India
ABSTRACT
India is an emerging economy which is affecting world statistics when it comes to consumption of
latest technology or embracing latest changes in the world. With a growing middle class population
which has improved standard of living, advent of internet, exposure to the world platform, the
Indian population is outshining many developed countries in its consumption patterns. Mobile
phone and mobile app industry is no exception to this trend. Let it be gaming apps, social
networking apps, entertainment apps, banking apps, educational apps or any other categories,
Indian consumer of every age group is trying hands on these apps with different apps and common
apps being used by different age categories simultaneously.
Key Words: Mobile apps, age, gaming apps, entertainment, social networking apps, banking apps
Introduction
The advent of internet severely affected the brick and mortar world with people moving from real
places to the virtual domains. When things were possible at a click, the concept of searching,
market place to the comforts of the computer room and transactions became easier. The long queues
at the railway counters or at the banks became shorter and the waiting time reduced from hours to
minutes. The internet and laptop brought in massive changes into the lifestyle and the working
pedagogy, with the advent of e-commerce.
The laptop than changed its size and most of its features became available on devices that would fit
into the pocket in the form of smart phones, the beginning from Apple‟s iphone in early 2007. This
brought in the new industry of the mobile apps and the world changed its face from e-commerce to
m-commerce with mobile apps in all categories flooding in the market and bringing most of the
work to be done to the comforts of stretched legs in the bedroom. This smartly dressed smartphone
and the associated accessories in the form of mobile software “applications” or “apps” is becoming
increasingly ubiquitous in our daily life. Looking into the growth of this industry the mobile
communication companies have also invested overwhelmingly in the deployment of the
infrastructure which has further added fuel to fire. With a huge tech-savvy population having
affordability of smart phones, and supported by mobile communication industry, developing
countries like India have become a profit haven for companies in this field.
As per the report available about the usage of mobile apps, India has been a forerunner in the global
industry and usage of mobile applications in India grew 43% in 2016, with entertainment and
finance categories witnessing maximum transactions. The reports also indicate that messaging and
social apps remain one of the most used categories in Asia and India wherein the time spent on
messaging and social apps grew by an impressive 52% in India as compared to a global increase of
44%. As quoted in news papers the top three categories of apps which saw growth were music,
media and entertainment followed by business and finance, and utilities and productivity apps, in
India.
As per global statistics, year 2016 saw China becoming the largest market in terms of iOS App
Store revenue and mature markets experienced strong growth patterns. But the most impressive
was the growth visible in the emerging markets, including India, Indonesia, Mexico and Brazil,
which saw even more gains. The devices which have screens between 5” and 6.9” have emerged as
a new market and have created a new segment for themselves in the name of „Phablet‟ and have
become the fastest growing mobile device globally. While the growth of Phablets in the US market
is 48 percent in terms of market share, India has outshined it with a market share of 61 percent.
the global mobile usage six months back and India‟s mobile usage looks a lot like same as per
March 2017 statistics with India‟s usage still ascending on the growth curve but at a faster rate that
was seen the year prior.
While the mobile phone usage has increased multifold, the mobile app usage is not only picking up
but at a much faster rate with one mobile phone becoming home to many apps. While the apps are
available in various categories, people are using them differently in different age groups. Some of
the most common categories of apps being used are - gaming apps, social networking apps,
entertainment apps, banking apps, educational apps, travel and tourism apps, medical apps, personal
utility apps, shopping apps, fooding apps etc, though the list is endless and increasing. The choice
of apps being downloaded by different aged people is seemingly different but the usage of mobile
apps is increasing day by day. Some out of curiosity, some out of usage, some out of fun while
some out of interest and learning, everybody who has a smart phone is using mobile apps for his or
her own personal reasons. The question that really needs to be answered is that: One of the most
important demographic factors which affect the consumer behaviour – Age – is it affecting this
market in choice of apps only or the number of apps used also?
Objectives Of The Study
The current study tries to identify
the usage of mobile apps by different age groups
the different types of apps being used by people of different age groups the relationship between the mobile app usage in different age groups
Hypothesis
This study will test the following three hypotheses:
Hypothesis 1
Ho: Equal number of Mobile Apps is used by Young and Mature.
H1: Equal number of Mobile Apps is not used by Young and Mature. (Young are using
more apps than Mature)
Hypothesis 2
H1: Equal number of Mobile Apps is not used by Young and Senior. (Young are using more
apps than Senior.)
Hypothesis 3
Ho: Equal number of Mobile Apps is used by Mature and Senior.
H1: Equal number of Mobile Apps is not used by Mature and Senior. (Mature are using
more apps than Senior)
Research Methodology
Research is based on primary data collected with the help of questionnaire. Objective of study is to
find out the relation of age factor and number of mobile apps used by the people. The Study will
prove itself useful in making strategies for product planning and identification of target group of
customer of various products. Z-Test is used for analysis of data. Significance level of tabulated
value of z is set at 95%. The usage of mobile apps has been categorized into 3 categories i.e usage
of 1 to 3 apps, 4 to 6 apps and 7 to 9 apps. The age categories defined for study have been classified
as Young (upto 25 years of age), Mature (from 26 to 50) and Seniors (from 51 and above). Formula
for Z-test is used as under:
where and are the means of the two samples, Δ is the hypothesized difference between the
population means (0 if testing for equal means), σ 1 and σ 2 are the standard deviations of the two
populations, and n1 and n2 are the sizes of the two samples.
The tabulated value of z at significance level of 95 % is:
Z(0.05) = 1.96
Data Presentation and Analysis
No. of Apps / Age Group Young (X) Mature (Y) Total
1 to 3 2 5 7
4 to 6 14 19 33
7 to 9 48 48 96
Total 64 72 136
As per the hypothesis 1 considered for the study, null hypothesis states that young (upto 25 years of
age) and mature (26 to 50 years of age) people are using equal number of mobile apps while the
alternate hypothesis states that young and mature people do not use same number of apps and that
young people use more apps in comparison to mature people. Data Calculations for this hypothesis
are as under:
Z = (7.15 – 6.79 – 0) / (2.4025/64 + 3.4225/72)1/2
Z = (0.36) / (0.0375 + 0.0475)1/2
Z = (0.36) / (0.085)1/2
Z = (0.36) / (0.2915)
Z = 1.2915
As Z (calculated) is less than the Z (tabulated), therefore Ho is accepted and it is concluded that
there is no significant difference of usage of mobile apps between young and mature people and
that both young and mature use the mobile apps with similar excitement and thus similar pattern.
(B) For Hypothesis 2
No. of Apps / Age Group Young (X) Seniors (Z) Total
1 to 3 2 28 30
4 to 6 14 20 34
7 to 9 48 25 73
Total 64 73 137
Mean of X 7.15 Mean of Y 6.79
S.D. of X 1.55 S.D. of Y 1.85
Variance of X 2.4025 Variance of Y 3.4225
As per the hypothesis 2 considered for the study, the null hypothesis states that young (upto 25
years of age) and senior (above 51 years of age) people are using equal number of mobile apps
while the alternate hypothesis states that young and senior people do not use same number of apps
and that young people use more apps in comparison to senior people. Data Calculations for this
hypothesis are as under:
Z = (7.15 – 4.88 – 0) / (2.4025/64 + 6.52/73)1/2
Z = (2.27) / (0.0375 + 0.0893)1/2
Z = (2.27) / (0.1268)1/2
Z = (2.27) / (0.3560)
Z = 6.3764
As Z (calculated) is more than the Z (tabulated), therefore Ho is rejected and it is concluded that
there is significant difference of usage of mobile apps between young and senior people and that
young people use more number of apps in comparison to senior people.
(C) For Hypothesis 3
No. of Apps / Age Group Mature (Y) Seniors (Z) Total
1 to 3 5 28 33
4 to 6 19 20 39
7 to 9 48 25 73
Total 72 73 145
Mean of Y 6.79 Mean of Z 4.88
S.D. of Y 1.85 S.D. of Z 2.55
Variance of Y 3.4225 Variance of Z 6.52
N(Y) 72 N(Z) 73
Mean of X 7.15 Mean of Z 4.88
S.D. of X 1.55 S.D. of Z 2.55
Variance of X 2.4025 Variance of Z 6.52
As per the hypothesis 3 considered for the study, null hypothesis states that mature (26 to 50 years
of age) and senior (above 51 years of age) people are using equal number of mobile apps while the
alternate hypothesis states that mature and senior people do not use same number of apps and that
mature people use more apps in comparison to senior people. Data Calculations for this hypothesis
are as under:
Z = (6.79 – 4.88 – 0) / (3.4225/72 + 6.52/73)1/2
Z = (1.91) / (0.0475 + 0.0893)1/2
Z = (1.91) / (0.1368)1/2
Z = (1.91) / (0.3698)
Z = 5.1649
As Z (calculated) is more than the Z (tabulated), therefore Ho is rejected and it is concluded that
there is significant difference of usage of mobile apps between mature and senior people and that
mature people use more number of apps in comparison to seniors.
Interpretations
1. The mobile app industry is growing very fast and influencing every age segment though the
kind of apps that are being used by different age groups are different.
2. Though there is no significant difference between the number of apps used by young and
mature people but the kind of apps being used are different. On the other hand there is
significant difference between the number of apps used by young and seniors people and
also between mature and senior people, and again the type of apps being used are different.
3. While the young are using apps out of curiosity, the mature and seniors are using apps more
based on requirement along with curiosity. The schemes available on downloading the app
for the first time and passing on the benefit to others and earning points is helping create
positive word of mouth about the convenience of mobile app usage.
4. As per the study, the younger generation is using apps related to gaming, social networking,
entertainment, and to a good extent the shopping apps. The mature and senior generations
are using banking apps, booking apps, social networking apps and shopping apps to a very
large extent along with the other apps. A remarkable difference has been found in the app
usage of seniors who were slightly more in age (towards 65 or more) as they are using much
5. As became evident from the study, the „fear of unknown and distrust‟ factor plays an
important role in the apps usage industry. The people who start using the apps and become
aware of their functioning are very easily trying these apps in any numbers, be in whatever
age group, while the people who are yet to overcome these blocks are using very less apps.
But even with these people who are less savvy with apps, the social networking and gaming
apps are popular.
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