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CHAPTER 1: INTRODUCTION

Retail Business is a low margin and high revenue business. Though Wal-Mart,

Carrefour and Tesco are the top 3 retail companies, they constitute only 5.3% of global

retail business.  Global retail business is still fragmented and less organized. It is growing

at 6% Year on year

Initially retail business was operated through brick and mortar i.e. traditional

channels like hypermarkets, super markets and convenient stores etc… with the advent of

scientific innovation the e- commerce came into existence, all the retail industry globally

entered this channel of business on war footing. But the basic problem of technology it

keeps on evolving.

With the recent advancement in the mobile communications and the smart phone

industry, there emerged a new concept of mobile shopping, literally meaning M

commerce but a way more sophisticated, in this channel of business, the entire shopping

experience is carried out through the mobile applications. These applications will be

compatible in both apple iOS and Android Operating Systems.

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M commerce

Mobile Commerce refers to wireless electronic commerce used for conducting commerce

or business through a handy device like cellular phone or Personal Digital Assistant

(PDAs). It is also said that it is the next generation wireless e-commerce that needs no

wire and plug-in devices. Mobile commerce is usually called as 'm-Commerce' in which

user can do any sort of transaction including buying and selling of the goods, asking any

services, transferring the ownership or rights, transacting and transferring the money by

accessing wireless internet service on the mobile handset itself.

The next generation of commerce would most probably be mobile commerce or m-

commerce. Presuming its wide potential reach all major mobile handset manufacturing

companies are making WAP enabled smart phones and providing the maximum wireless

internet and web facilities covering personal, official and commerce requirement to pave

the way of m-commerce that would later be very fruitful for them.

Advantage of m-Commerce

M-commerce has several major advantages over its fixed counterparts because of its

specific inbuilt characteristics such as ubiquity, personalization, flexibility, and

distribution, mobile commerce promises exceptional business market potential, greater

efficiency and higher fruitfulness. Thus it is not surprising that mobile commerce is

emerging much faster than its fixed counterpart. M-commerce is more personalized than

e-commerce and thus needs a gentle approach to appraise m-commerce applications.

Context-specific services - Mobile Commerce makes it possible to offer location

based services, which are specific to a given context (e.g. time of the day, location

and the interests of the user).

Time-critical situations - The ubiquity and immediacy of Mobile Commerce

allows the user to perform urgent tasks in an efficient manner, irrespective of his

current geographic location.

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Spontaneous decisions and need generally involve decisions that do not require

very careful decisions involving small amounts of money.

Efficiency increase - Mobile Commerce helps increase the productivity of the

workforce by increasing the efficiency of their daily routines. Time (employees)

can use ‘dead spots’ in the day, e.g. during the daily travel to and from workplace,

more effectively

Internet Penetration

India has a dismal record in Internet penetration—just short of 8.4% of its vast

population has access to the Web—but that may change soon with some help from its

fast-growing telecom industry. The country has the second largest telecom sector globally

and more people are opting to surf the Internet over their mobile phones, even if that’s

often a strain. But the third-generation (3G) services being rolled out by telecom

operators are expected to usher in an era of high-speed Internet browsing on mobile

phones, including video streaming and conferencing.

Internet access is becoming vital in a country that’s preparing to rely more on e-

governance to push its development agenda, including for financial inclusion and

plugging leaks in government doles. Private firms are also pushing their services on the

net, such as for bank transactions or booking movie, rail and air tickets, as they try to

keep a hold on operational costs.

Another huge barrier to Internet access in India is the low penetration of personal

computers (PCs). “This is mainly due to the issue of affordability,” City Investment

Research and Analysis said in a September report. PC penetration in India was at 4% of

its population in 2009, compared with 20% in China, 89% in the US and 98% in Japan. A

basic computer costs at least Rs. 10,000-15,000, whereas mobile phones, even 3G-

enabled devices capable of fast Internet browsing, can be bought for about Rs. 5,000.

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TOP 20 COUNTRIES WITH HIGHEST NUMBER OF INTERNET USERS

# Country or RegionPopulation,2011 Est

Internet UsersYear 2000

Internet UsersLatest Data

Penetration(% Population)

World% Users

1 China 1,336,718,015 22,500,000 485,000,000 36.3 % 23.0 %

2 United States 313,232,044 95,354,000 245,000,000 78.2 % 11.6 %

3 India 1,189,172,906 5,000,000 100,000,000 8.4 % 4.7 %

4 Japan 126,475,664 47,080,000 99,182,000 78.4 % 4.7 %

5 Brazil 203,429,773 5,000,000 75,982,000 37.4 % 3.6 %

6 Germany 81,471,834 24,000,000 65,125,000 79.9 % 3.1 %

7 Russia 138,739,892 3,100,000 59,700,000 43.0 % 2.8 %

8 United Kingdom 62,698,362 15,400,000 51,442,100 82.0 % 2.4 %

9 France 65,102,719 8,500,000 45,262,000 69.5 % 2.1 %

10 Nigeria 155,215,573 200,000 43,982,200 28.3 % 2.1 %

11 Indonesia 245,613,043 2,000,000 39,600,000 16.1 % 1.9 %

12 Korea 48,754,657 19,040,000 39,440,000 80.9 % 1.9 %

13 Iran 77,891,220 250,000 36,500,000 46.9 % 1.7 %

14 Turkey 78,785,548 2,000,000 35,000,000 44.4 % 1.7 %

15 Mexico 113,724,226 2,712,400 34,900,000 30.7 % 1.7 %

16 Italy 61,016,804 13,200,000 30,026,400 49.2 % 1.4 %

17 Philippines 101,833,938 2,000,000 29,700,000 29.2 % 1.4 %

18 Spain 46,754,784 5,387,800 29,093,984 62.2 % 1.4 %

19 Vietnam 90,549,390 200,000 29,268,606 32.3 % 1.4 %

20 Argentina 41,769,726 2,500,000 27,568,000 66.0 % 1.3 %

TOP 20 Countries 4,578,950,118 275,424,200 1,601,772,290 35.0 % 75.9 %

Rest of the World 2,351,105,036 85,561,292 508,993,520 21.6 % 24.1 %

Total World - Users 6,930,055,154 360,985,492 2,110,765,810 30.5 % 100.0 %

NOTES: (1) World Internet User Statistics were updated for June 30, 2011. (2) Additional data for individual countries and regions may be found by clicking each country name. (3) The most recent user information comes from data published by Nielsen Online, International Telecommunications Union, Official country reports, and other trustworthy research sources. (6) Data from this site may be cited, giving due credit and establishing an active link back to Internet World Stats. Copyright © 2000 - 2011, Miniwatts Marketing Group. All rights reserved.

Figure 1.1: List of top 20 countries with Internet usage

Mobile Penetration

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There were 752.19 million cell phone subscribers as at the end of 2010, there

were only 80 million Internet users and 11 million broadband users in the country.

Mobile phone penetration stood at 63.22% in December, according to the Telecom

Regulatory Authority of India. Every 10% increase in mobile penetration contributes as

much as 0.6% to the country’s gross domestic product; an increase in Internet penetration

makes a bigger contribution.

The country’s largest telecom operators, Bharti Airtel Ltd, Vodafone Essar Ltd and

Reliance Communications Ltd, which spent thousands of crores of rupees for 3G

licenses, are expected to start rolling out the services soon. About 15% of Internet users

in India access the Web through their mobile handsets, a trend likely to pick up with the

increased take-off in smartphones and the advent of 3G.

World India

Mobile users per 100 69.04 45.49

5

15

25

35

45

55

65

Mobile users per 100

User

s

Figure 1.2: Mobile users out of 100 globally and in India

E commerce Penetration

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South Korea UK Germany Japan US919293949596979899

100

Percentage of Internet users

Percentage of Internet users

Figure 3: Percentage of Internet users using E commerce

It is very clear from the above figure that the penetration can really go up to 99% and

many countries are already having more than 90% of internet users using thee commerce.

28%

23%17%

17%

16%

Sales

BooksClothingEntertainmentAir ticketsElectronics

Figure 1.4: Preference for different products in E commerce

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The above figure depicts the proprieties of e commerce and it is evident that 67% of the e

commerce is associated with the shopping, and e commerce is the closest neighbor for the

M commerce. We can say M commerce in retail will have bright future.

M commerce in India

In India, m-commerce is in its initial stages and its advantages will soon be

realized. M commerce revolution will take the country by storm since statistics are on our

side. Another encouraging trend is that the Indian consumer is fast maturing and is open

to new ideas.

Some key points:

About 2 percent of Indians, which is 20 million people, have a per capita income

exceeding $13,000 — a number greater than the populations of Malaysia and

Singapore put together.

Customers surfing the Internet through their mobile phones will have to pay an

access charge of only Rs 0.42 per minute. These trends suggest that a fertile

ground for m-commerce already exists in India and its revolution seems

inevitable.

The number of people accessing the internet is rising and particularly, Indian

population is using more internet through mobiles than personal computers.

3G penetration is increasing day by day which will contribute to the growth of M

commerce.

Service / Retail sectors

Service and Retail sectors are also among the leading sectors, which have

nurtured most from mobile commerce. M-Commerce has proved a major boon

for these sectors. Several business dealings no matter how big or small are being

finalized on the mobile phone. Customer would be able to book the order, can

hire carrier/courier services and above all could also pay the dues related to it

through mobile.

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India World Critical

Remarks

Sources

Internet

Usage/

Application

8.4 % of Indian

Population @

9.2

Crores(2011)

27.9 % of

world

population in

2009.

Will

Drastically

Improve with

3G Services

CIA Statistics

and Google

Public

Information

Mobile

Penetration

670 million

users

5.3 billion

users

CIA Statistics

Google Public

Information

Personal

Computer

4% of Indian

Population @

4.4

Crores(2011)

NA

PC penetration

is not very high

because of the

cost involved

Live mint online

Smart Phone

Penetration

4% of Indian

Population

10% of world

Population

Facing tough

competition

form tablets

which are

goring at 5%

CISCO Statistics

E commerce

Penetration

875 Million

users

40% increase

from 2009 to

2011

I media and

SahilShah(2011)

M commerce

Penetration

NA NA NA NA

Table 1.1: Combined list for penetration of different entries globally and in India

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Chapter 2: Review of work already done on the subject

Islam, Khan, Ramayah & Hossain (2011): this research paper, “The Adoption of Mobile

Commerce Service among Employed Mobile Phone Users in Bangladesh: Self-efficacy

as A Moderator” deals with the study of M commerce in the Bangladesh. The paper is

having lot of insight on the parameters the customers look into while trading in M

commerce. The findings suggest that pricing and cost, rich and fast information, and

security and privacy are significant predictors of the adoption of M-commerce. Self-

efficacy is found to be a moderating factor for the adoption of M-commerce services

Sadia & Sukena (2011): This research paper, “User Acceptance Decision towards Mobile

Commerce Technology a Study of User Decision about Acceptance of Mobile Commerce

Technology” deals with the user decision to accept M commerce technology is based on

factors like the perceived usefulness, perceived ease of use, social influence, and user s

attitude to accept those services. This gives an insight on which parameters we need to

work on the acceptability of M commerce in the retail industry.

Maity & Moutusy (2010): This research paper, “Critical Factors of Consumer Decision-

Making on M-Commerce: A Qualitative Study in the United States”, This study

compares consumer decision-making experiences across three channels (m-commerce, e-

commerce, in-store), identifies factors affecting consumer decision-making that are

unique to a specific channel as well as those that are common across the three channels,

and suggests a model for intention to use m-commerce. Cognitive cost, expectation-

confirmation theory, theory of reasoned action and the technology acceptance model are

used to formulate propositions. Findings suggest that decision-making in m-commerce is

perceived as stressful and is not necessarily a positive one.

Varshney Gagan & Madan Pankaj(2010): This research paper,” A Study of Functionality

Dilemma and Barriers to Optimal Usage of M-commerce”. This paper provides the

functionality dilemma of M-commerce & defines the way by which M- commerce can

provide more freedom & support to users. It also deals with the barriers to the optimal

usage and to find the solutions of functionality problems and usage of M-commerce.

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Danny Tengti Kao (2009): this research paper, “The Impact of Transaction Trust on

Consumers' Intentions to Adopt M-Commerce: A Cross-Cultural Investigation”, this

paper worked on the dimensions of transaction trust that may significantly affect

consumers' intentions to adopt M-commerce, and w the cultural dimensions that may

significantly moderate the impact of transaction trust on consumers' intentions to adopt

M-commerce. Results revealed that transaction trust significantly affects consumers'

intentions to adopt M-commerce. However, while uncertainty avoidance moderates the

impacts of business trust and security on consumers' intentions of M-commerce adoption,

both individualism/collectivism and long-term/short-term orientation moderate the

relationship between security trust and consumers' intentions of M-commerce adoption

Tao Zhou & Yaobin Lu (2011): This research paper, “The effect of interactivity on the

flow experience of mobile commerce user”, this research examined the effect of

interactivity on mobile user experience. The results indicated that two factors of

interactivity, namely ubiquitous connectivity and contextual offering have significant

effects on flow experience, including perceived enjoyment, and perceived control and

attention focus. In addition, user's self-efficacy significantly affects flow experience,

further determining continuance usage. This will be very useful in the construction of the

research instrument.

Clarke III, Irvine (2008): this research paper, “Emerging Value Propositions for M-

commerce”. This paper investigated on the value propositions that engender a productive

mobile e-commerce strategy to provide recommendations for managerial decision-

making in this emerging wireless environment. This paper is very useful in studying the

value proposition of the M commerce.

Mahatanankoon Pruthikrai & Vila-Ruiz, Joaquin (2007): this research paper, “Why

Won't Consumers Adopt M-Commerce? An Exploratory Study”, examines the possible

barriers that hinder the adoption of mobile commerce applications and the results identify

five major factors that impede the applicability of m-commerce: unawareness, device

inefficiency, conventional transactions, interoperability, and personalization needs.

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Khalifa, Mohamed & Ning Shen, Kathy (2008): This research paper, “DRIVERS FOR

TRANSACTIONAL B2C M-COMMERCE ADOPTION: EXTENDED THEORY OF

PLANNED BEHAVIOR”, operationalize and empirically test a model for explaining the

adoption intention of transactional B2C mobile commerce. The model is empirically

tested with mobile device users who have not adopted mobile commerce yet. This paper

has long understanding of why many mobile users are not able to convert to M

commerce. This will be very useful in the course of study.

Suhong Li, Richard Glass & Hal Records (2008): this research paper, “The Influence of

Gender on New Technology Adoption and Use-Mobile Commerce”, investigated the

impact of gender differences on the adoption and use of a new technology- mobile

commerce (m-Commerce) using 372 respondents enrolled in a business college in the

Northeast United States. The results suggest that Male respondents used more

communication, information, and transaction services than females suggesting that males

move through the adoption stages at a more rapid rate than females do. This will be

useful while dealing with the demographics

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Chapter 3: Research Methods and Procedure

Population:

The National Capital Region (NCR) in India is a name for the conurbation or

metropolitan area which encompasses the entire National Capital Territory of Delhi as

well as urban areas ringing it in neighboring states of Haryana, Uttarakhand, Uttar

Pradesh and Rajasthan. With a total area of about 33,578 km2 (12,965 sq mi), it is the

world's second largest urban agglomeration by population and the largest by area.

Delhi UA was a smaller agglomeration than Mumbai a decade ago - 15.5 million

to Mumbai's 16.6 million, but now relative change has taken place in the past 10 years.

Overall, Delhi-NCR's population has shot up 40% to 21.7 million in the last decade.

Kolkata is the third biggest UA with 14.1 million people after Delhi NCR and Mumbai.

The big three - known as "megacities" since they have populations of more than 10

million - remain far ahead of the other big cities. About 15% of India's total urban

population lives in these three cities rest of the population is distributed across India.

Description 2011 Census

Population of Delhi NCR 2,17,00,000 (Approximate)

Population of Delhi 1,67,53,235

Male 89,76,410

Female 77,76,825

Growth Rate of India 1.34 %

Growth Rate of Delhi 20.96 %

Percentage of Total Population 1.38%

Literacy Rate 86.34

Females for 1000 male 866

Table 3.1: Statistics of Delhi NCR & Delhi NCT

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Sample:

The Sample for the research is a conglomeration of Male and female at different

ages, the study requires highly educated people particularly having technical insight or

exposure. The Project is on M commerce through integrated applications, which requires

the sample to be smart phone or tablet users.

The sample will be from Delhi NCR, the reason for selecting the Delhi NCR is

because it is the largest and most populated metro in India. The concept of M Commerce

can only be tested in Metros due to the technical constraints and penetration of the

concept.

Sampling Design:

The sampling technique being adopted for the research is judgmental sampling. The

target audience will be highly educated population i.e. graduates, post graduates and

PhDs living in the metros that are having smart phones. The reason for choosing highly

educated population is their usage of different formats, and the reason behind choosing

the smart phone users is to study the willingness of the customers to go for mobile

shopping through integrated iOS or Android operating system, only they capture the

sample frame correctly.

The research has no proportionate requirement of demographics like age, gender, race

and profession etc… The sample size estimated to carry out the survey is 300 samples

and proposed investigation will be carried out at Delhi and NCR regions. The research

will include both student and working class.

In order to find out the samples to work on M commerce, we are assuming that

people with E commerce will be the prospect users for the M commerce as they have

previous exposure on virtual shopping and online financial transactions. So we will be

targeting E commerce users and carry out online surveys and personal interviews.

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Parameter Description

Sampling Technique Judgmental

Sample Size 300

Sample Qualification Educated( Graduation and above)

Smartphone or Tablet User

M commerce user/ Prospect user

E commerce user

Place of Research Delhi NCT

Delhi NCR

Demographic Specifications Random Proportions

Interview Techniques Online Surveys

Personal Interviews

Telephonic Interviews

Table 3.2: Sampling Design for the Survey

Research Design

In this research descriptive research has been adopted. For the objectives like

finding out the importance of different variables

Availability

Selection

Price

Experience

For both online and brick & mortar formats, the significant variable can be found, i.e.

which of the above parameter has the highest significance can be obtained from this

study.

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Even in the other context the questionnaire has well constructed variables for the

required objectives and their intensity and significance will be determined by the study

which makes the research a descriptive research.

Research Objectives(s)

1. Study the customer perception for retailer information application

The objective here is to find out the customers perception

regarding the integrated retail information applications on Android, iOS

and other mobile or tablet operating systems. This will also include the

kind of information, frequency at which information is needed etc…

2. Study the customer acceptability towards mobile shopping

The objective here is to study what level of inclination the

customer has to adopt the M commerce. This includes identification of

the significant parameters that are vital for the success of M commerce

3. To compare the retail dimensions in the case of both online channels

and Brick & mortar.

The objective is to identify the vital dimensions that the online and

physical formats are having, this will reveal the most important aspects

for the customer while shopping at these formats.

4. To find out customer willingness to make financial transactions over a

mobile Phone.

This research primarily investigates the customer’s willingness to

do online transactions, this also include the study of previous

experiences, modes of payment and unique M payment systems.

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Research Questions:

1.) What kind of information customers are expecting from retail information

providers in a mobile phone or a tablet?

2.) What factors play crucial role in making the M commerce a success in Indian

retail Industry?

3.) Which parameters are crucial for brick and mortar format of shopping?

4.) Which parameters are crucial for online shopping?

5.) Which modes of payment are more appealing to the customer?

Analytical Techniques

In order to interpret the obtained data we have adopted a series of analytical

techniques, which included

Krushkal Wallis Test

Reliability Test

Independent sample t Test

Muti dimension scaling

Descriptive Statistics

SOFTWARE USED

SPSS: SPSS Statistics provides a powerful statistical-analysis and data-

management system in a graphical environment, using descriptive menus and

simple dialog boxes to do most of the work for you. Most tasks can be

accomplished simply by pointing and clicking the mouse.

Research Instrument

For the purpose of carrying out research on M commerce in Delhi NCR, a well

constructed questionnaire with closed question format is adopted. The questionnaire is

having 18 questions including the demographic information of the respondent. The

questionnaire is having technical terms and it was framed keeping in mind the sample

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qualification and insight (Highly educated and prior exposure on E commerce and online

transactions.

Questions 1 to 5 are basic questions to make the respondent comfortable with the

survey and involve him in the process. The questions include the previous exposure to E

commerce and M commerce, the kind of Operating system they are using and frequency

of usage for E commerce and M commerce.

Questions 6 to 8 are concerned with the first objective of the research i.e.

customer perception for retail information updates. The questions are intended to find out

the basic information requirements and prioritize the important features the customers are

interested in and also to find out the frequency of information updates.

Questions 9 to 12 are going to provide information on second and third objectives

which are the customer preference for the M commerce and comparison between brick &

mortar and online formats on the variable like Availability, selectivity, price and

experience. The preference for the screen sizes and navigation etc… can be determined

through these questions.

Questions 15 to 17 are designed to acquire information on the financial

transactions online. The questions are concentrated on finding out the ease of the

customer for doing the financial transactions online and finding out the modes of

payment they generally adopt.

Questions 18 to 21 are incorporated to find out the demographics of the

respondent, specifically Age, Gender and Family annual income. These demographics

enable in the study of preferences for different categories of people.

Reliability and authenticity

The literature reviewed for this research is from peer certified research papers.

The questionnaire will be answered by highly educated people using different formats of

shopping and will definitely give authentic information for the research.

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Chapter 4: Results and Analysis

Objective 1:

The first objective is the study of customer perception towards information

updates. The research has focused upon the frequency of information requirements,

intensity of information flow and some unique parameters of retail information flow and

came up with the following results

Figure 4.1: Preference for Retail Information Updates

Above figure 4.1 is suggesting that the consumers are interested in the

information updates on their favorite brands rather than specific products or retailers, this

is good news because a lot of cross selling can be done by different brands through

promotion on mobile phones precisely smart phones

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Figure 4.2: Frequency of information updates

It is evident from the above figure 4.2 that consumers are interested in having real

time information updates, only a few portion i.e. 6.25% people said that they do not need

any information updates. The survey states that the information updates are required by

the consumer on regular intervals.

One-Sample Statistics

N Mean Std. Deviation Std. Error Mean

Precise Information 300 3.93 .999 .058

Dynamic Information Update 300 3.89 1.002 .058

Comparison Between

Products

300 3.88 1.088 .063

Recommendations Form

Retailer

300 3.51 1.062 .061

Integrated Applications 300 3.60 1.162 .067

Authenticity of Information 300 3.84 1.144 .066

Table 4.1: Descriptive Statistics for information update parameters

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Above table 4.1 gives the clear understanding of the statistics of the parameters for

the information updates, in order to have clear and concrete evidence on the significance

of these variables, a one sample t-test was conducted and the results are as follows

One-Sample Test

Test Value = 3

99% Confidence Interval of the

Difference

t df Sig. (2-tailed)

Mean

Difference Lower Upper

Precise Information 16.067 299 .000 .927 .78 1.08

Dynamic Information

Update

15.328 299 .000 .887 .74 1.04

Comparison Between

Products

14.014 299 .000 .880 .72 1.04

Recommendations Form

Retailer

8.266 299 .000 .507 .35 .67

Integrated Applications 8.992 299 .000 .603 .43 .78

Authenticity of

Information

12.672 299 .000 .837 .67 1.01

Table 4.2: Hypothesis testing for Information updates parameters

H0: The parameters are not significant (µ0 = µ)

H1: The parameters are significant (µ0 ≠ µ)

Table 2 is the result of one sample t test, which is tested at 99% confidence level

and it is evident that all the parameters are significant in the minds of the customer

because in this case the significant values are less than 0.01; hence we reject the null

hypothesis in the favor of alternate hypothesis. While providing the information updates

every detail mentioned in the list of parameters should be implemented with precision.

From the above analysis it is clear that

1. The Consumers are interested in Information updates on their favorite brands

2. They need regular information updates

3. Consumers need complete perfection in the information provided

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Reliability test

We have conducted reliability test for the parameters for retail information

updates and we got the Cronbach’s alpha value as 0.809. This value is significantly

higher than the required value of 0.6. The following table indicates the output of

reliability test.

Case Processing Summary

N %

Cases Valid 300 93.8

Excludeda 20 6.3

Total 320 100.0

a. List wise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

.809 6

Table 4.3: Test output for reliability test.

The table 4.3 is indicating that the Cronbach’s alpha value for the six variables

considered is 0.809.

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Objective 2:

The second objective of the survey is to study the customer acceptability towards

mobile shopping.

Figure 4.3: Most Important factor for the success of M commerce

From the figure 4.3 it is evident that financial security is very important

for the successful execution of M commerce approximately 40% of the respondents felt

that financial security is important while making transactions. Next in line is Authentic

Information and Speed processing.

In order to find out the key determining factors we have conducted forced ranking

and we have found out the following results, we conducted Krushkal Wallis H test to find

the significance f the results.

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Ranks

Rank N Mean Rank

Applications Portability 200 446.50

Screen Clarity 200 517.50

Smooth Navigation 200 547.50

Shopping Experience 200 553.50

Financial Security 200 851.50

Flexible Payment Options 200 686.50

Total 1200

Table 4.4: Ranking from K Wallis Test

Test Statisticsa,b

Applications

Chi-Square 181.597

df 5

Asymp. Sig. .000

a. Kruskal Wallis Test

b. Grouping Variable: Rank

Table 4.5: Test Statics for K Wallis Test

From Table 4.4 it is clear that Financial Security, Flexible Payment options are

very important for M commerce, after that is the shopping experience. The significance

of the Chi-Square test is 0 so the values we got are significant. The practical value is less

when compared to the theoretical value at 95% significance with 5 degrees of freedom.

Hence the null hypothesis is that the

H0: The Mean ranks are not significant

H1: The Mean ranks are significant

Null hypothesis is rejected in the favor of alternate hypothesis.

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Objective 3:

The next objective is to study the difference in retail dimensions for both the

online and Brick & Mortar formats, for the sake of having this study in concrete manner

forced rating scales has been used and acquired ranks are acquired.

Pricing

Selection

ExperienceFinancialSec

Availability

0

5

OnlineBrick&Mortar

Figure 4.4: Comparison of different dimensions for online and B&M formats

The above figure 4.4 is indicating that for the online formats financial security is

very important when compare to other parameters, where as for the Brick & Mortar

formats shopping experience is the most crucial aspect.

From this analysis it is clear that financial aspects play important role in

determining the success of M commerce in India. In order to have clear state of

information, the remaining part of the Survey is centered on financial issues. There are no

significant differences between Pricing, Selection, and Availability in the case of Online

and Brick & Mortar formats. The required details are enclosed in the Table A1, Table A2,

Table A3, Table A4, and Table A5 (Annexure 2).

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Multi Dimension scaling for online formats

Figure 4.5: Derived Stimulus Configuration for the online formats

The above table 4.8 is the Euclidean distance model for the multi dimension

scaling conducted for the important parameters in the case of online formats. From the

model it is clear that customers are having limited selection on different models or

products, lower level of financial security. While shopping experience, pricing and

availability are on higher side. It is also observed that the customers are not entirely

satisfied with any parameter. The dimension which is on the highest side on both axis is

not having any variable.

Online Format

26

Multi Dimension scaling for Brick & Mortar

Figure 4.6: Derived Stimulus Configuration for the Brick & Mortar formats

The above table 4.9 is the Euclidean distance model for the multi dimension

scaling conducted for the important parameters in the case of Brick & Mortar formats.

From the model it is clear that availability and experience fall under one dimension,

while Selection, Financial security and pricing fall under different dimensions.

The Euclidean model is depicting that the selection in this case is isolated and

having more distance than any other parameter. Even experience is stretched very far

when compared to other parameters.

Brick & Mortar

27

E commerce Convenient Stores

Super Markets Hyper Mar-kets

Discount Counters

M commerce

Series 1 146 156 190 69 64 75

10

30

50

70

90

110

130

150

170

190

Recent visit

Figure 4.7: Recently used format of stores

The above figure 4.7 shows that Super Markets, Convenient Stores & E

commerce are the most recently used formats by the consumers, even the M commerce is

on the brighter side.

Objective 4:

Most of the information analyzed so far has resulted that financial security is the

most important aspect in making the M commerce successful. In order to have a clear

understanding the entire financial issues of the respondents were captured. We focused

on Transaction Modes, Problems faced while doing transactions to have concrete

information.

28

Figure 4.8: Financial Irregularities faced by the consumers

From the above figure 4.8 it is very clear that Transaction Processing delay is

pestering the online transactions. Infrastructure is not up to the mark in India, this might

be the reason behind this problem, next is the error in the processing specifically double

processing.

Even many consumers have faced the problems like anonymous transactions and

charged but unsuccessful transactions, these problems are very serious and question the

integrity of the service provider, these problems should be dealt quickly.

The disturbing fact is that only 7.67% of the respondents faced no irregularities

while doing online transactions. A lot of changes and measures are required here.

29

Figure 4.9: Modes of payments for online transaction

25%

40%

36%

M Payments

Mobile Service Provider billing of M paymentsCredit Card based M paymentsBank Account based M payments

30

Figure 4.10: M Payment modes for doing transactions

The above figure 4.7 is indicating that consumers are interested in using or

precisely using online banking and debit cards when compared to credit cards. Around

16.7% of the respondents are using the pay pal accounts for online transactions.

It is very evident from Figure 4.8 that Mobile service provider billing is still in

armature stage but growing at good pace, credit card based M payments are more

preferred over Bank account based M payments

31

Chapter 5: Conclusions and Recommendations

Findings:

Online channels for retail sector are growing very fast, among them E commerce

is already well established. M commerce on the other hand is the upcoming and growing

with rapid pace. The research has captured this fact clearly. All the objectives are

thoroughly examined and analyzed and came to the following conclusions.

Study the customer perception for retailer information application

Customers need real time information updates form the service providers

The customers are very keen on the authenticity and precision of information

Customers are interested in information updates regarding favorite Brands

Precise Information, Dynamic updates, comparison between Products,

recommendations from retailers & authenticity are preferred by the consumers

with significance

Customers are interested in Integrated Mobile Applications.

Study the customer acceptability towards mobile shopping

Financial security is very important for the success of M commerce in India; the

analysis has evidence to capture the statement.

Processing Speed is the next important parameter for smooth navigation of M

commerce, Indian infrastructure industry is still at novice stage and this can be a

threat.

Authenticity in content display and availability is highly demanded form the

customer.

32

Comparison between online and Brick & mortar channels

Financial Security is the primary concern for the online channels when compared

to other parameters

Shopping experience is very important for the Brick & Mortar formats when

compared to other parameters.

Super Markets, E commerce & convenient stores are frequently visited formats by

the consumers

M commerce is growing at good pace

Discount counters & Hypermarkets are accessed at lower frequency.

Customer willingness to make financial transactions over a mobile Phone

Consumers are relying on Online Bank Accounts & debit cards to do transactions

online rather than Credit cards

Transaction Processing delays are recorded in significant number of cases

Double Processing and Anonymous usage is being registered by the consumers to

a good extent.

M payments are being carried out by Credit cards.

Mobile service provider aided billing is still in introductory phase in India but

many consumers are using them.

Conclusion:

M commerce is having good future in India because customers are interested in

mobile retail applications and information updates in retail industry. To some greater

extent the financial security and transaction delays are creating some unwanted

impression in the minds of the customer. If these issues are addressed properly, M

commerce is going to be successful in India.

33

Recommendations:

The recommendations are being made for the retail information updates and

Successful execution of M commerce in retail.

Retail Information Updates

1. Authenticity in information on schemes, availability & Prices should be

Authentic.

2. Mobile Integrated applications should be built by brands rather than

retailers.

3. Customers need information real time, so the information should be worth

their time.

4. Consumers are willing to pay for the right information in right timing.

M commerce in retail

1. To have a good M commerce in India the Infrastructure should be

improved or the Applications should be built with decreased size and

resolutions so that the loading time is reduced.

2. Payment gate ways should be processed with improved speeds to

overcome the problem of Transaction processing delays

3. Mobile service provider aided billing should be launched in all places to

support faster payments.

4. Retailers and brands should collaborate with mobile service providers to

improve flexibility in payment options.

34

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Appendix 1

37

38

39

Appendix 2

Group Statistics

VAR00008 N Mean Std. Deviation Std. Error Mean

Availability Availability_online 200 3.19 1.371 .097

Availability_B&M 200 3.05 1.314 .093

Table A1: Group statistics for Availability

Group Statistics

VAR00006 N Mean Std. Deviation Std. Error Mean

ShoppingExp ShopingExp_online 200 1.99 1.005 .071

ShopingExp_B&M 200 3.33 1.410 .100

Table A2: Group statistics for Shopping Experience

Group Statistics

VAR00004 N Mean Std. Deviation Std. Error Mean

Selection Selection_online 199 2.42 .938 .067

Selection_B&M 200 3.13 1.102 .078

Table A3: Group statistics for Selection

Group Statistics

VAR00002 N Mean Std. Deviation Std. Error Mean

Pricing Pricing online 200 2.99 1.188 .084

Pricing_B&M 200 3.27 1.188 .084

Table A4: Group statistics for Pricing

Group Statistics

VAR00001 N Mean Std. Deviation Std. Error Mean

FinancialSec FinancialSec_online 200 4.48 1.093 .077

FinancialSec_B&M 200 2.24 1.710 .121

Table A5: Group statistics for Financial Security