A study to access consumer acceptance level of app only model of e-commerce companies. A research project report involving a survey report with validation of result using analytics.

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Table of Content
Sl.no. Topic Page. No.
1 Introduction 3
1.1 The App Revolution – An Opportunity for Ecommerce 4
1.2 Flipkart and Myntra 7
2 Literature review 8
2.1 App Ecosystem 8
2.2 Decision variable Considered 9
3 Problem Statement 9
3.1 Decision Statement 10
3.2 Research Objective 10
3.3 Research Question 10
3.4 Hypothesis 10
4 Research Methodology 11
4.1 Questionnaire 11
4.2 Sampling 11
4.3 Data Analysis Plan 11
5 Data Analysis 12
5.1 Demography 12
5.2 Checking Assumption 13
5.2.1 Linearity 13
5.2.2 Normality and Auto-correlation 14
5.3 Model Fit 15
5.3.2 Final model 16
5.4 Segments on the basis various parameter 18
5.4.1 Gender 18
5.4.2 Education 18
5.4.3 Usage 19
5.4.4 Age 20
6 Managerial Implication 21
7 References 21
8 Appendix 22

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1. Introduction
About three quarters of Indian population have access to a mobile phone. Mobiles are the most
ubiquitous modern technology in some countries population does not have bank accounts,
electricity or even clean water but have access to mobile phone. Mobile phone has been used
to provide education, health related information and access to various government initiatives.
Wide presence of mobile technology in developing countries have led to various technology
and business innovation such as Multi-sim card phone, mobile payment and low value
recharges. Even use of mobile phones can increase the success rate in overcoming the
development challenges such as digital literacy and social problems compared to other means
of adaption platforms.
With the rapid development and adaption of mobile phones has also led to rapid development
in processing power and technology adaption in mobile which in turn led to faster development
in software programs called mobiles apps. These app mostly run on smart phones and use data
access of these mobile devices to deliver information or perform specific functions such as
gaming, social networking, ecommerce, navigation and other utilities to name a few.
That the rapid growth of apps can have a transformative impact on livelihoods and businesses is
supported by empirical evidence that is being carefully collected across the world. By making
phones more powerful, apps, aided by high-speed networks and innovation can have important
productivity enhancing impacts throughout the economy. It has been repeatedly shown that
access to telecommunications improves productivity by, inter alia, reducing information
asymmetries and containing transactions costs. Because mobiles substitute for fixed lines in
developing economies, the growth impact of mobile phones is higher than that for developed
economies.

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1.1 The App Revolution – An Opportunity for Ecommerce
As smartphone are more in comparison to laptops and PCSs in developing countries like india
so the focus on mobile app by ecommerce site like Flipkart and myntra seemlogical. A purchase
using any medium through brick and mortar stores or online store is a complex process it is not
restricted to researching and buying everything so buying behavior of consumer need to be
taken into considerations.
As from the graph it can be seen that mobile user in india has taken over the laptop or PC user
in 2014 and also the internet penetration is also increasing.

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Source: Morgan Stanley Research
Source: International Telecommunications Union
Myntra and flipkart app-only strategy seems logical as it allow them to manage a single sales
channel, protect consumer data and provide a personalized shopping experience. However,
there are several factors to be considered in Indian context such as consumer behavior,
growing internet adoption, connection speed, device usage, price sensitivity, availability of
product information and recommendations, consumer ratings, growing income of middle class.
1.1.1 INCREASED MOBILE TRAFFIC

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The mobile traffic has increased 10 fold in the last eighteen months and according to a study
conducted by Ericson 58% of the people who do not use e-commerce services on smartphones
said that they would be starting it within a year.
Source: Telecom Companies Annual Reports Avendus Analysis
Number internet user through smartphone has increased to 140 Million by 2014 and according
to flipkart and myntra about 90% of traffic and 70% of purchase are from mobile app.
1.1.2 PERSONALIZATION
By mobile app these ecommerce sites are able to provide a more personalized experience for
example geo tagging the user and providing the user with product list which tailor made for
them according to their location, taste and interest.
1.1.3 RESEARCH OR PURCHASE?
The consumer mostly prefer to buy product online medium only after a close inspection of
product which is sometimes difficult on the low resolution screen of the smart hence smart are
used to research and desktop or laptop and used to inspect the product before buying

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Source: Nielson Informate Mobile Insights
1.1.4 PUSH MESSAGE STRATEGY
These are handy and most of the people carry their mobile with them on daily basis so these
devices could be used by the ecommerce websites like flipkart, snapdeal to send the app
installer the advertisement directly to their devices through notification or push message for
marketing purposes
1.1.5 INDIA – A PRICE SENSITIVE MARKET
India is highly price sensitive market and online buying is still in growing state and most of
the people still do not prefer to buy online and use online shopping occasionally.
From the survey shown by ‘Information on the Survey ExperienceU.com,

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Further Advantages of mobile include
 A rich and more compelling user experience.
 Mobile apps can use smart phone capabilities such as gps, camera and graphics and
other apps to provide a more indulging experience.
 Mobile can run offline i.e with no internet so that user get better performance at all
times
 Apps are easily integrate with m commerce platform and mobile wallets
 Further app provide Front of mind penetration:- as it provides an always visible icon at
the screen which reminds people to use them.
1.2 Case study of Flipkart and Myntra
In 2014 myntra became part of Flipkart and endorsed the app-only strategy of Flipkart. As a
result at the start of 2015 they started to develop their app only strategy and in may myntra
goes app only. The following timeline shows the shit to app only strategy.
Flipkart and myntra thought that they will be able to fully capitalize on the app only medium
and mutually benefit the consumer and themselves through.
 Providing superior customer experience.
 lower Latency
 icon on the home screen
 Faster scrolling
 Push customers notifications and so on
But the consumer did not liked the idea of app only medium which resulted into loss of sales
and U-turn in the strategy by flipkart and myntra no matter how much they incentivized
shopping on the app.

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There are many reason for this to happen:-
 Indian consumer own cheap devices which do not effectively support apps
 Forcing them to buy from a single medium
 Preference of consumer to shop through conventional web browsers
 Losing out on the consumer segment how still does not own Mobile devices but have
desktops or Laptops
 Further selling or retail business is based on the engagement of the customer and
willingness of customer to buy the product So decreasing the no. of ways to indulge was
not a positive move.
 In India, mobile internet network is unreliable which hampers the mobile only
experience.
2.0 Literature Review
2.1 The App Ecosystem
The app Ecosystem is part of the internet ecosystem which consists of network infrastructure,
devices, content and users. Apps are a subset of content and can add to the attractiveness of
the broadband network by providing services that are of considerable practical use. Since it is
part of a highly networked and interdependent ecosystem, the app economy cannot be viewed
in isolation. Its functioning depends on the existence of a robust network infrastructure,
appropriate devices and a supportive OS landscape. Its general purpose nature makes it
ubiquitous across several verticals of which healthcare, education, business and governance,
among others, generate considerable interest due to their ability to address pervasive supply
side bottlenecks.
Figure captures the different dimensions of an app ecosystem. The app Ecosystem consists of
three principal activities which are app development, distribution and demand represented by
the nodes of the pyramid. The three main factors that influence the core activities of the app

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economy are network infrastructure, devices represented as different layers of the pyramid.
Each of these dimensions is discussed below.
2.2 Decision parameters Considered
So basically we are going to concentrate on the demand side of the pyramid and try to
investigate the various factor responsible for the acceptance of the mobile app and their
importance to develop an app only model for ecommerce.
For consumer acceptance of mobile- only medium, we used the proxy of mobile internet, m-
commerce and e-commerce to narrow down the factors which can be responsible for the
effective acceptance of mobile only ecommerce platform. So we narrowed down the parameter
to these
1. Ease of use
2. Security
3. Personalization
4. Discounts/offers
5. Cost of use
6. Ease of social interaction
3.0 Problem statement
Many online retailers are preferring to move to an app only platform. But they are hesitant to
do away with their website model and completely move to an app only platform because the

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factors affecting consumer acceptance towards app only model and subsequent use are
unclear.
3.1 Decision statement
What factors can be used to improve user acceptance and subsequent use of mobile only app
models?
3.2 Research objectives
List the factors that affect user acceptance of mobile only apps and the correlation of these
factors with user acceptance of this model.
3.3 Research questions
 What factors affect the user acceptance and subsequent use of mobile app only
commerce model?
 How important is each factor in affecting the user acceptance?
3.4 Hypothesis
H1: Ease of use is positively related to user acceptance of mobile app only commerce model
As ease of use will have major impact on the usability of app and re-use of app as consumer
consider that the app reduce their work or helps them to shop easily hence it should be
positively correlated to acceptance of mobile only medium.
H2: Perceived security positively affects user acceptance of mobile app only commerce model
As consumer perceive that the mobile app is more secure and reliable the consumer will
seamlessly move to new channel will accept the model.
H3: Personalized catalogues and marketing positively affects user acceptance of mobile app
only commerce model
As consumer would be provide a customized experience matching his/her interest and needs
consumer will be more willing to use app over other medium to minimize the hassle of
shopping and acceptance should increase.
H4: Discounts/offers will shift consumers towards app only model
As consumer would be provide a customized discounts and offers matching his/her interest and
needs consumer will be more willing to use app over other medium to minimize the hassle of
shopping and acceptance should increase.
H5: Cost of using app only model negatively influences user acceptance
Perceived cost include the initial and ongoing costs of using mobile app affects the attitude of
potential adopters and indian consumer are price sensitive so this negatively impact the
acceptance.

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H6: Ease of social interaction through apps improves user acceptance of mobile app only
commerce model
As shopping is more than researching and buying of product it also involve acceptance and
admiration of other parties so improving the social interaction of consumer should positively
impact the acceptance of mobile app based platform.
4.0 Research Methodology
4.1 Questionnaire
Various question where developed using the literature review under various decision variables
through adopting the question for m-commerce and ecommerce to Mobile app only medium
and the question were to be rated on a scale of 7 from disagreeing to fully agreeing to the
statement. (The questionnaire is include in the Appendix)
4.2 Sampling
Random sampling was used to collect data from seventy respondent through online line survey
form. Demographic data such as age, gender, education and frequency of usage was also used
to gather the data for specific segments to see focus on the parameter affecting that particular
segment.
Apart from the data for decision variables, statement for acceptance of mobile only model has
also been developed and data for that has been calculated from the same population.
4.3 Data Analysis Plan
Data gathered for various statement on agreeability scale would be used to formulate
composite score for each decision variables which would be used as an input data for
regression equation to see the relative impact of decision variable on the acceptance of mobile
only model.
Acceptance of App only platform is the dependent variable (DV), which is determined by Six
identified factors which are Ease of use, Security, Personalization, Discounts/offers, Cost of
use, Ease of social interaction
Acceptance = ẞ 𝟏*EASE + ẞ 𝟐*SEC + ẞ 𝟑* PER + ẞ 𝟒*OFFER + ẞ 𝟓*COST + ẞ 𝟔*SOCIAL + Constant
For data analysis we are going to use 10% as our significance as no. of data collected is 65
people which is less to use 95% accuracy.

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5.0 Data Analysis
5.1 Demography
As can be seenfromthe data we gathereddata fromvarioussegementandconsideredvarious
parameterto segmentthe data.
Mobile usage data is not significant to use regression for the segment on that basis.

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5.2 Checking Assumption
5.2.1 Linearity

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As from the graphs it can be seen that most of the variable are having a linear relationship with
the acceptance.
5.2.2 Normality and Auto-correlation

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5.3 Model Fit
As fromthe histogramandprobability
plotit can be seenthatthe residual
data isnormallydistributed
Andfrom the scatterplotit can be
seenthatthere isvisible correlation
betweenresiduals

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As form the table it can be seen that adjusted r square value is 0.536 so the model explains the
about 53.6 % variance.
Further Significance value for f statistic is approaching zero so it show that at least one of the
independent variable in significant for the model.
Coefficient table shows that Ease, Cost and social impact are significant variable with ease
having the maximum impact followed by social interaction and then cost which negatively
correlated with the acceptance.
5.3.1 Outliers
5.3.2 Final Model
PlottingCook’sdistance with
standardize residualswe cansee that
theirfew outlierswhichneedtobe
removedtosee the impactover
model.
Afterremovingfirstoutlierwe didn’t
wentaheadforremovingother
seemingoutlierasitwasremoving
higherage people asoutlier.

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As form the table it can be seen that adjusted r square value is 0.577 so the model explains the
about 57.7 % variance.
Further Significance value for f statistic is approaching zero so it show that at least one of the
independent variable in significant for the model.
Coefficient table shows that Ease, Cost, offers and social impact are significant variable with
ease having the maximum impact followed by social interaction and then cost which negatively
correlated with the acceptance.
While personalization is on border line and has negative correlation showing that consumer
perceive that the mobile apps are not personalized for their interest and taste.
Security is highly in significant for the model.

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5.4 Segments on the basis various parameter
5.4.1 Gender
As form the table it can be seen that adjusted r square value is 0.579 for male and 0.727 for
female so the model fits female segment better.
Coefficient table shows that social impact is most important variable for male segment and
Ease being the most important variable for female segment.
5.4.2 Education

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As form the table it can be seen that adjusted r square value is 0.720 for graduate and 0.473 for
female so the model fits graduates segment better.
Coefficient table shows that offers is most important variable for Graduate segment and
personalization being the most important variable for Post graduate segment.
5.4.3 Usage

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As form the table it can be seen that adjusted r square value is 0.602 for daily user and 0.976
for occasional users so the model fits occasional user segment better.
Coefficient table shows that offers and social interaction is most important variable for daily
user and EASE of use, cost and perceived security being the most important variable for
occasional users segment.
5.4.4 Age
For age we regrouped the people into two group less than 25 yrs and more than 25 yrs as data
was restricting the formulation of more groups.
As form the table it can be seen that adjusted r square value is 0.555 for Less than 25 yrs
segment and 0.646 for more than 25yrs users so the model fits them equally.
Coefficient table shows that offers, social interaction and ease is most important variable for
less than 25 yrs age users and EASE of use, personalization being the most important variable
for more than 25 yrs age users segment and it is perceived by this segment that personalization
is not good enough in the apps to improve the acceptance of mobile only platform and lack of it
is negatively impacting the mobile only strategy.

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6.0 Managerial Implication
 As Ease, Cost of usage, offers and social integration are important variable for
acceptance of mobile only platform so a model focusing on these factor should be
formulated
 Personalization is perceived negatively correlated and is on the border line so consumer
perceive personalization lacking in mobile app for ecommerce. So these should be
focused upon.
 Occasional user perceive security as significant and are sceptic about it as compared to
daily. So for converting occasional user to regular user the security of app should be
focused upon
 With age group above 25 yrs of age, cost of usage has major impact as they might
perceive to use app seamlessly you require better phone and robust mobile which can
be removed by optimizing apps for slower net and cheaper phone.
 Social Integration is one of the major factor so integrating E-commerce app with social
network should be emphasized upon.
7.0 References
• “Critical Factors in Consumers Perception towards Mobile Commerce in E-Governance
Implementation: An Indian Perspective”, Kanwalvir Singh, Himanshu Aggarwal
International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 –
8958, Volume-2, Issue-3, February 2013
• Mobile Commerce: An Analysis of Key Success Factors, Hyun-Hwa Lee* and Seung-Eun
Lee, Journal of Shopping Center Research (2007), 14, 2, pp. 29-62.
• “Adoption and Evaluation of Mobile Commerce in Chile”, Ranjan B. Kini, Indiana
University Northwest, USA
• “Consumer Attitude towards M-Commerce: The Perceived Level of Security and the Role
of Trust”, Zakaria I. Saleh, Ahmad Mashhour, Journal of Emerging Trends in Computing
and Information Sciences, Vol. 5, No. 2 February 2014
• Kabir, G., & Hasin, M. A. A. (2011). Evaluation of customer oriented success factors in
mobile commerce using fuzzy AHP. Engineering and Management, 4(2), 361-386
doi:10.3926/jiem.2011.v4n2.p361-386

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Appendix
Questionnaire
Demographics
Age
Gender
Education level
Average internet usage/week
Frequency of mobile app buying/ week
Own a mobile device for how many years
Ease of Use
Mobile only platform Enhances transparency & quality of work
Mobile only platform Enhances speed & efficiency
Mobile only platform is More flexibility (anywhere, anytime) - 24x7
Easy to understand and navigate app
Security
Chances of losing money through shopping on mobile app
Hacking/Virus/Spam may occur through apps
Apps can’t be trusted to safeguard user’s privacy info
Privacy information of client gathered through apps can be used in a wrong way
Personalization
Mobile App Address the customer personally or individually
Customer register with an account / password and can freely edit their profiles
Indicating tailor made purchase recommendations to individual customers
Presentation of products on the app is easily accessible
Gives customers the opportunity to look at their previous orders online
Mobile App has ample payment options
Cost of use
The equipment cost is expensive for using Mobile App
I think access cost is expensive for Mobile App/ internet
I think transaction fee is expensive for mobile app.
Discount/offers
Mobile app is better for discounts and bargains hunting

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Information about sales/ discount coupon is easily accessible
Makes special offer to individual customers
App provide better prices than the other platform
Ease of social Interaction
I enjoy socializing with others when I shop
Shopping with other is a bonding experience
Mobile app provide easier way to share the product I am interested in.
Interacting with friends and family while shopping allows me to take decision properly.
Acceptance scale
My general opinion of app only shopping is favorable
I will recommend using shopping apps to others
Using mobile apps fits my life style
Mobile app are convenient than other platforms