Online Shopping Buying Behaviour In India

 

 Source: Essay UK – http://www.essay.uk.com/free-essays/marketing/online-shopping-behaviour-india.php

Online Shopping Buying Behaviour In India

Introductions
Commerce via the Internet, or e-commerce, has experienced rapid growth since the early years. It is well known to most of the Internet researchers that, the volume of online business-to consumer (B2C) transactions is increasing annually at a very high rate. According to ACNielsen (2007), more than 627 million people in the world have shopped online. Forrester (2006) research estimates e-commerce market will reach $228 billion in 2007, $258 billion in 2008 and $288 billion in 2009. By 2010 e-commerce will have accounted for $316 billion in sales, or 13 percent of overall retail sales. ACNielsen also reported that, across the globe, the most popular items purchased on the Internet are books (34%), followed by videos/DVDs/games (22%), airline tickets/reservations (21%) and clothing/accessories/shoes (20%).Goecart forecasts that US online population will increase nearly 50%, from 1471.5 million in 2001 to 210.8 million by 2006 (Cumulative Annual Growth Rate of 8.2%) and online retail sales will grow from US$47.8 billion in 2002 to $130.3 billion in 2006. Similarly WIPO (2007) cited that about 10% of the world’s population in 2002 was online, representing more than 605 million users.
Much research has been concentrated on the online shopping in the world. However, there is still a need for closer examination on the online shopping buying behaviour in developingcountries like India. While both established and new, large and small scale businesses are now using the Internet as a medium of sales of their products and services (for example Dell computer, Amazon.com, in the world and jobstreet.com, rediff.com). Still there is a huge research gap that exists not only between countries, especially between developed and developing countries, which may differ significantly between countries (Stieglitz, 1998; Shore, 1998; Spanos et al., 2002) that limit the generalization of research results from developed countries to developing country contexts (Dewan and Kraemer, 2000; Clarke, 2001). Shore (1998) and Stiglitz (1998) reported that implementation of information system depend on specific social, cultural, economic, legal and political context, which may differ significantly from one country to another country. Dewan and Kraemer (2000) and Clarke (2001) argued in their study that findings from developed countries are not directly transferable to developing countries.

Attitudes
Consumer attitudes are a composite of a consumer’s (1) beliefs about, (2) feelings about, (3) and behavioral intentions toward some object–within the context of marketing, usually a brand or retail store. These components are viewed together since they are highly interdependent and together represent forces that influence how the consumer will react to the object.

(Source: http://www.consumerpsychologist.com/cb_Attitudes.html)
Beliefs: The first component is beliefs. A consumer may hold both positive beliefs toward an object (e.g., coffee tastes good) as well as negative beliefs (e.g., coffee is easily spilled and stains papers). In addition, some beliefs may be neutral (coffee is black), and some may be differ in valance depending on the person or the situation (e.g., coffee is hot and stimulates–good on a cold morning, but not well on a hot summer evening when one wants to sleep). Note also that the beliefs that consumers hold need not be accurate (e.g., that pork contains little fat), and some beliefs may, upon closer examination, be contradictory (e.g., that a historical figure was a good person but also owned slaves).

Affect: Consumers also hold certain feelings toward brands or other objects. Sometimes these feelings are based on the beliefs (e.g., a person feels nauseated when thinking about a hamburger because of the tremendous amount of fat it contains), but there may also be feelings which are relatively independent of beliefs. For example, an extreme environmentalist may believe that cutting down trees is morally wrong, but may have positive affect toward Christmas trees because he or she unconsciously associates these trees with the experience that he or she had at Christmas as a child.
Behavioral Intention: The behavioral intention is what the consumer plans to do with respect to the object (e.g., buy or not buy the brand). As with affect, this is sometimes a logical consequence of beliefs (or affect), but may sometimes reflect other circumstances–e.g., although a consumer does not really like a restaurant, he or she will go there because it is a hangout for his or her friends.

Understanding Consumers Attitudes
Consumer attitudes are both an obstacle and an advantage to a marketer. Choosing to discount or ignore consumers’ attitudes of a particular product or service’while developing a marketing strategy’guarantees limited success of a campaign. In contrast, perceptive marketers leverage their understanding of attitudes to predict the behavior of consumers. These savvy marketers know exactly how to distinguish the differences between beliefs, attitudes, and behaviors while leveraging all three in the development of marketing strategies.
An attitude in marketing terms is defined as a general evaluation of a product or service formed over time. An attitude satisfies a personal motive’and at the same time, affects the shopping and buying habits of consumers. Dr. Lars Perner (2010) defines consumer attitude simply as a composite of a consumer’s beliefs, feelings, and behavioral intentions toward some object within the context of marketing. A consumer can hold negative or positive beliefs or feelings toward a product or service. A behavioral intention is defined by the consumer’s belief or feeling with respect to the product or service.
The Tri-Component Model
(Source: http://marketography.com/2010/10/17/understanding-consumer-attitudes)
1. Affect
‘ The emotional component of an attitude.
‘ Describes how an individual feels about the various cognitions making up an attitude.
‘ The stronger the associated emotions are, the stronger the attitude is likely to be.
2. Behavior
‘ The active element of attitudes.
‘ It can be difficult to separate from the other two elements.
‘ Conative attitude elements are habits or responses to desires.
3. Cognition
‘ The thought component of an attitude.
‘ A person’s mental representation of an object or stimulus, including his or her observations, beliefs, and other similar factors.
‘ A factually or experientially based element of attitude.
‘ More likely to be conscious than the other elements of attitude, and they are more susceptible than others to logic-based persuasive techniques.
Literature Review
10 Best Online Shopping Sites in India
(Source: http://moneybies.com/10-best-online-shopping-sites-india)
Online Shopping in India has emerged as one of the fastest growing market and now-a-days a most common trend which people is using to buy any assets. With the growth of Internet over the last 5 years, most of the Businesses have now shifted online and the most successful among them are those who have invested huge amount for opening an Online Shopping Site in India.
1. E-bay
2. Filpkart
3. Myntra
4. Snapdeal
5. Jabong
6. Tradus.in
7. Homeshop 18
8. Yebhi.com
9. Shopclues
10. Infibeam
Google India Study reports numbers about online shopping in India
Online shopping in India, saw 128% growth in interest from the consumers in the year 2011 to 2012 in comparison to only 40% growth in 2010 to 2011, making 2012 the tipping point for online shopping in India.
In terms of product categories, consumer interest on Google search for apparels & accessories (30%) emerged as the second biggest product category after consumer electronics (34%).

(Source: http://yourstory.com/2013/01/google-india-study-about-online-shopping)
As mobile internet user base grows in India, mobile phones is also becoming a contributor in the surge for online shopping with Google witnessing 2X growth in number of queries from mobile phones in the year 2011 to 2012. Currently, 30% of all shopping queries in India come from mobile phones. These trends were also validated with the help of a online research conducted by TNS Australia of the internet users in the age group 18 to 50 from Delhi, Mumbai, Kolkata, Bangalore, Ahmedabad, Hyderabad & Pune.
As per the research, 90% of online shoppers are planning to buy more products online which reflect on the positive experience of the users. In terms of top product categories ever purchased online :
‘ Apparels & accessories was among the top category (84%)
‘ Electronics (71%)
‘ Beauty & personal care (64%)
‘ Books (62%)
‘ Household products (61%)

PRIVACY AND SECURITY ISSUES IN ONLINE SHOPPING
Shopping online has never been so easy. With the flourishing numbers of online merchants, people nowadays have various choices to do their shopping. Big companies such as eBay and amazon.com have introduced many value added features to help the customers to decide what to shop for. With features such as price comparison, product photos and user reviews, consumers can shop easily and smartly without even going to the stores and having such a hard time looking for the products they want. All they have to do are just browse for the product they want in the website and within a few mouse clicks they are off. Such simplicity is what makes online shopping appealing for consumers. The question is, why do many people still deny to shop online? Well, for most people, privacy and security issues are their concerns. Hence, here I will discuss customers’ perception of privacy and security issues, the reality of such issues and ways to avoid those issues, all based on some trustworthy sources I have found.

Unique Visitors on Websites
When we purchase a service or product through internet with an electronics media, it is called ‘Online Shopping’. Basically online shopping is divided into 2 categories: Travel/Tourism and Online Retail Business. Travel/Tourism websites are like Makemytrip.com, IRCTC.com, Bookmyshow.com, Paytm.com and Yatra.com. These all sites provide some kind of either tickets or service. Like Paytm.com helps to do online recharge while makemytrip.com helps us to make Air/Bus/Rail ticket. Online Retail Websites are those, from where we purchase a product and the product is delivered to our doorstep. Like Flipkart.com, eBay.com and Amazon.in. These websites have a wide range of verity of products and brand. They deliver the purchased goods to our doorstep. Online Ticketing/Tourism/Services contribute 75% to the total revenue.
The growth rate of Online Shopping is gaining pace in India. India is 3rd largest country in this race lacking behind only USA and China. The growth rate of Online Shoppers is more than 30% while world’s average growth rate is just 6-7%. You may be wondered to hear that only 11% of India population is using Internet and only 10 million online shoppers. Think about the number of online shoppers, if 50% of India’s population gets start online shopping. The revenue generation was $2.5b in 2009, $6.3b in 2011 and $14b in 2012 and it is expected to reach to $24b by 2015. It is expected to contribute 4% to our GDP by 2020

(Source:http://topbullets.com/2013/11/07/essay-article-on-online-shopping-websites-business-market-in-india)
Is Online Shopping Booming In INDIA? ‘ An Empirical Study
Online shopping in India is an emerging trend for marketers to promote their merchandise in wide geographical area using internet and the trend looks likely to grow upwards over the coming decade.
India is the 5th country in world ecommerce and 2nd country in Asia. India seems to have grasped the ability to shop merchandise through internet. Mobile internet is being enormously responsible for opening up the online world to Indian consumers. There are reports suggesting that by the end of 2013 over 300 million Indians will have access to the internet through mobile phone technology and other platforms, about the same amount of people in USA to put that into context. Reports show that out of the millions accessing the internet in India, over 8 million regularly shop through internet. This figure is set to grow exponentially as well. Google is the internet search engine that is predominately used throughout India.

Consumer Beliefs and Attitudes Toward Marketing
Consumers’ attitudes towards marketing activities are important from both a theoretical and a managerial standpoint (Gaski and Etzel 1986). As consumer attitudes significantly affect their behavioral responses to marketing activities, knowledge of consumers’ attitudes toward marketing has been used in economic forecast and found to be linked to several key macroeconomic variables (Chopin and Darrat 2000). Such information can also help devising effective strategies for companies as well as developing regulations by government agencies to protect consumers’ interests. Existing research has dealt with consumers’ overall attitudes toward marketing as well as specific marketing activities such as advertising and pricing (Nwachukwu et al 199; Webster 1991). In general, researchers have focused on a central issueCwhat causes the differences in consumers’ attitudes toward marketing activities? Webster (1991), for instance, found significant differences in consumer attitudes toward various marketing practices including product quality, pricing, advertising, and retailing or selling; however, many of the differences remained even after social class and income effects were removed.
Socio-Economic Impact of Digital Literacy
Since the beginning of the 1990s the use of information and communication technology (ICT) in education has developed rapidly, a development that is reflected in the results of our literature search. The ability to use ICT and the Internet becomes a new form of literacy ‘ ‘digital literacy’. Digital literacy is fast becoming a prerequisite for creativity, innovation and entrepreneurship and without it citizens can neither participate fully in society nor acquire the skills and knowledge necessary to live in the 21st century.
‘Digital Literacy is the awareness, attitude and ability of individuals to appropriately use digital tools and facilities to identify, access, manage, integrate, evaluate, analyse and synthesize digital resources, construct new knowledge, create media expressions, and communicate with others, in the context of specific life situations, in order to enable constructive social action; and to reflect upon this process.’
India’s e-commerce market rose 88% in 2013
India’s e-commerce market grew at a staggering 88 per cent in 2013 to $ 16 billion, riding on booming online retail trends and defying slower economic growth and spiralling inflation, according to a survey by industry body Assocham.
“The increasing Internet penetration and availability of more payment options boosted the e-commerce industry in 2013,” Assocham Secretary General D S Rawat said. “Besides electronics gadgets, apparel and jewellery, home and kitchen appliances, lifestyle accessories like watches, books, beauty products and perfumes, baby products witnessed significant upward movement in last one year,” Rawat said.

According to the survey, India’s e-commerce market, which stood at $2.5 billion in 2009, reached $8.5 billion in 2012 and rose 88 per cent to touch $16 billion in 2013. The survey estimates the country’s e-commerce market to reach $56 billion by 2023, driven by rising online retail.
As per responses by 3,500 traders and organised retailers in Delhi, Mumbai, Chennai, Bangalore, Ahmedabad and Kolkata who participated in the survey, online shopping grew at a rapid pace in 2013 due to aggressive online discounts, rising fuel prices and availability of abundant online options.

Right tools can make online shopping easier
Online shopping can be a smart consumer’s best friend, with the ability to easily comparison shop, search for discounts and make purchases with a few mouse clicks.
You could always visit shopping comparison sites, such as MySimon.com, or search for coupon codes at one of many code-aggregators. But now a slew of Web browser add-ons makes smart online shopping easier.
Billeo toolbar: With perhaps the most functionality, billeo.com helps with shopping, discount codes and bill paying. It will autofill your logins and passwords to retailer sites, as well as forms for your shipping and billing addresses and credit card information. On the checkout page, it will alert you if a discount code is available for your purchase and autofill the code.
Billeo will save transaction confirmation pages to provide a shopping history. And it aids with paying via vendor sites.

Perceived behavioral control
Perceived behavioral control refers to people’s perceptions of their ability to perform a given behavior. Drawing an analogy to the expectancy- value model of attitude (see attitude toward the behavior), it is assumed that perceived behavioral control is determined by the total set of accessible control beliefs, i.e., beliefs about the presence of factors that may facilitate or impede performance of the behavior. Specifically, the strength of each control belief (c) is weighted by the perceived power (p) of the control factor, and the products are aggregated, as shown in the following equation. To the extent that it is an accurate reflection of actual behavioral control, perceived behavioral control can, together with intention, is used to predict behavior.

Online shoppers in terms of demography
Online shoppers in terms of demography are another important aspect. We would like to study demography in terms of age, gender, income and education as are there any differences while consumers shop online, differences within the age groups such as does online shopping attracts elder people or younger people. Studies have shown that online shoppers mainly consist of people with Higher education and income and working in middle to senior management or professionals (Kehoe et al., 1998; Hoffman et al., 1996). Locally, a report in the Business Times and an online survey showed that demographically, a typical Net shopper is mainly male, aged between 18 and 40, had attended at least secondary school and belongs to a family with average income of at least $5000. The online survey also showed that cyber- buyers were also mainly Chinese below 36 years old with diplomas or degrees and drawing a monthly salary of less than $3500. Another study by Miller (1996) claims cyberspace is the domain of young people Bhatnagar and Ghose (2004). Sim and Koi, (2002) states as main discriminating factors appeared to be gender and income. Customer segmentation is important for electronic commerce success, Berry (1999). Miller (1996) has focused on demographics to show the profile of Internet users, Bhatnagar and Ghose (2004).

Research Methodology
1. Research Design
‘ In this study, the project is based on Descriptive Research and Exploratory Research.

2. Sources of data
‘ Primary Data: – The primary data was collected with the help of personal survey by using structured questionnaire.
‘ Secondary Data: – The secondary data has been collected through following sources.
1. Data through Internet source
2. Data through E-books

3. Sampling Method
‘ Convenience sampling method has been used to select the samples.

4. Sample Size
‘ Sample of 200 respondents was taken from different areas in the Ahmedabad City & Vadodara City.

5. Sampling frame
‘ Consumers of Ahemdabad and Vadodara City

6. Plan of Data Analysis
‘ Data analysis has been done by Special Packet & Social Science(SPSS)

7. Project Duration
‘ Duration of this comprehensive project is Six Months.

Objectives of Study

1. Primary Objectives:-
‘ To study the Attitude of Consumers toward E-Shopping based on consumer’s behavior, beliefs, preferences and opinions

2. Secondary Objectives:-
‘ To study how Socio-Demographic affects to Consumer’s Attitude.
I. Age
II. Income
III. Occupation
‘ To study the pattern of on-line buying.
I. Types of Goods
II. E-Shopping Experience
III. Hours use on Internet
‘ To examine how purchase perception influence Consumer’s Attitude.
I. Product Perception
II. Customer Service
III. Customer Risk (Financial/Product/Non-Delivery Risk)

DATA ANALYSIS
Demographics:
1. Gender:
Table No. 1 showing Demographic Profile of respondents regarding Gender Wise
Gender Vadodara Ahmedabad Total
N N% N N% N N%
Male 67 67 68 68 135 67.5
Female 33 33 32 32 65 32.5
Total 100 100 100 100 200 100

Figure No. 1 showing Demographic Profile Respondents Regarding Gender

As per data showing in table and graph, there are 67% in Vadodara and 68% Ahmedabad male users of online shopping whereas 33% in Vadodara and 32% in Ahmedabad female users of online shopping.

2. Education Level:

Table No. 2 showing Demographic Profile Respondents Regarding Education Level
Occupation
Vadodara
Ahmedabad
Total

N N% N N% N N%
Secondary Level 4 4.0 9 9 13 6.5
Graduation 34 34.0 59 59 93 46.5
Post Graduation 47 47.0 21 21 68 34
Professional 15 15.0 11 11 26 13
Total 100 100.0 100 100 200 100

Figure No. 2 Showing Demographic Profile Respondents Regarding Education Level

As per given data, 47% of online users are post graduate and 34% users are Graduate in Vadodara City, whereas in Ahmedabad 59% are Graduate and 21% are post graduate users. Only 15% and 11% users are professional in Vadodara and Ahmedabad.

3. Age:

Table No. 3 Showing Demographic Profile Respondents Regarding Age Groups
Age Vadodara Ahmedabad Total
N N% N N% N N%
15-25 43 43.0 26 26 69 34.5
25-35 33 33.0 51 51 84 42
35-45 18 18.0 18 18 36 18
> 45 6 6.0 5 5 11 5.5
Total 100 100.0 100 100 200 100

Figure No. 3 Showing Demographic Profile Respondents Regarding Age Groups

As per given data, 43% users of online shopping having age between 15-25 years in Vadodara. In contrast, 51% users of online shopping having age between 25-35 years in Ahmedabad. Whereas, only 6% and 5% users of online shopping having age between more than 45 year in Vadodara and Ahmedabad.

4. Income:

Table No. 4 Showing Demographic Profile Respondents Regarding Income
Income Vadodara Ahemedabad Total
N N% N N% N N%
< 1,00,000 20 20.0 9 9 29 14.5
1,00,000-2,00,000 19 19.0 22 22 41 20.5
2,00,000-3,00,000 39 39.0 34 34 73 36.5
> 3,00,000 22 22.0 35 35 57 28.5
Total 100 100.0 100 100 200 100

Figure No. 4 Showing Demographic Profile Respondents Regarding Income

As per given data, 39% users for online shopping whom have income between 2lacs-3lacs in Vadodara city. In contrast, 35% users for online shopping whom have income more than 3lacs in Ahmedabad city. But there are overall users of online shopping having income between 2lacs-3lacs.

Preference based Data:
Table no 5. Showing the products is to be purchased through online.
Product City N N%
Computer Accessories vadodara 26 26
ahmedabad 33 33
overall 59 29.5
Books vadodara 14 14
ahmedabad 21 21
overall 35 17.5
Clothes vadodara 21 21
ahmedabad 13 13
overall 34 17
Furniture vadodara 1 1
ahmedabad 1 1
overall 2 0.5
Cosmetics vadodara 17 17
ahmedabad 25 25
overall 42 21
Theatre Tickets vadodara 21 21
ahmedabad 8 21
overall 29 14.5

Figure no. 5 showing the products is to be purchased through online.

As per given data, there is 26% users in Vadodara city purchased computer accessories whereas 33% users in Ahmedabad city purchased computer accessories. Overall in both cities, there are 17.5% respondents having second preference of purchasing books.

Table no 6. Showing the products is purchased through various websites.
Websites city N N%
Myntra vadodara 23 23
ahmedabad 5 5
overall 28 14
Snapdeal vadodara 13 13
ahmedabad 20 20
overall 33 16.5
Yepme vadodara 7 7
ahmedabad 7 7
overall 14 3.5
Ebay vadodara 12 12
ahmedabad 20 20
overall 32 16
Homeshop 18 vadodara 12 12
ahmedabad 18 18
overall 30 15
Filpkarts vadodara 29 29
ahmedabad 20 20
overall 49 24.5
Others vadodara 4 4
ahmedabad 17 17
overall 21 10.5

Figure No. 6 Showing Preference of Products to be purchased through various Websites

As per given data, there are 24.5% users of flipkart website in both cities. There are only 16% users of Ebay and 16.5% users of Snapdeal in both cities. In contrast, there are only 3.5% users of yepme.com.

Table No. 7 Showing Preference of Products Perceptions to be purchased through Internet.
Products Preferences City
N N%
Product Brands vadodara 26 26
ahmedabad 30 30
overall 56 28
Product Quality vadodara 43 43
ahmedabad 38 38
overall 81 40.5
Product Prices vadodara 18 18
ahmedabad 23 23
overall 41 20.5
Product Varieties vadodara 16 16
ahmedabad 9 9
overall 25 12.5

Figure No. 7 Showing Preference of Products Perceptions to be purchased through Internet.

As per given data, 40.5% users preferred quality of products through online shopping in Vadodara and Ahemdabad cities. Consumer second preference of both cities is Product
Brand. In contrast, there are only 12.5% user preferred product varieties.

Belief Based Data:
Table No. 8 Showing beliefs having consumers regarding to reputation of company.
Particulars Vadodara Ahmedabad Total
N N% N N% N N%
Very Unimportant 15 15 3 3 18 9
Unimportant 13 13 5 5 18 9
Neutral 12 12 12 12 24 12
Important 33 33 56 56 89 44.5
Very Important 27 27 24 24 51 25.5
Total 100 100 100 100 200 100

Figure No. 8 showing beliefs having consumers regarding to reputation of company.

As per given data, 44.5% users of Ahmedabad and Vadodara cities felt that reputation of company is important from where they are buying the products. 25.5% users of both cities felt that reputation of company it is very important. In contrast, 9% users felt that it is unimportant.

Table no. 9 showing accurate descriptions of products provided on web sites
Particulars
Vadodara
Ahmedabad
Total

N N% N N% N N%
Strongly Agree 18 18.0 20 20.0 38 19.0
Agree 42 42.0 60 60.0 102 51.0
Netural 21 21.0 16 16.0 37 18.5
Disagree 15 15.0 3 3.0 18 9.0
Strongly Disagree 4 4.0 1 1.0 5 2.5
Total 100 100.0 100 100.0 200 100.0

Figure no. 9 showing accurate descriptions of products provided on web sites

As per given data, 51% users of both cities are agree that there is an accurate data of products which have been shown on online. 19% users of both cities are strongly agreed that there is an accurate data of products which have been shown on online. In contrast, 2.5% users are strongly disagreed and 9.0% users are disagreed, they felt that the data of product shown on online is not accurate.

Table no. 10 showing sufficient descriptions of products provided on web sites
Particulars Vadodara Ahmedabad Total
N N% N N% N N%
Strongly Agree 25 25.0 28 28.0 53 26.5
Agree 42 42.0 57 57.0 99 49.5
Netural 18 18.0 14 14.0 32 16.0
Disagree 10 10.0 0 0 10 5.0
Strongly Disagree 5 5.0 1 1.0 6 3.0
Total 100 100.0 100 100 200 100.0

Figure no. 10 showing sufficient descriptions of products provided on web sites

As per given data, 49.5% users of both cities agreed that the data of product shown on online is sufficient. 26.5% users of both cities strongly agreed that the data of product shown on online is sufficient. In contrast, 3% users of both cities strongly disagreed that the data of product shown on online is not sufficient.

Behavior Based Data:
Table No. 11 showing amount spent for purchasing the product through online
Particulars Vadodara
Ahmedabad
Total

N N% N N% N N%
Up to 1000 19 19.0 27 27.0 46 23.0
Up to 2500 38 38.0 43 43.0 81 40.5
Up to 5000 25 25.0 18 18.0 43 21.5
More than 5000 18 18.0 12 12.0 30 15.0
Total 100 100.0 100 100.0 200 100.0

Figure No. 11 showing amount spends for purchasing the product through online

As per given data, 40.5 % users of both cities are purchasing the products through online more than 2500 Rs. 23% users of both cities are purchasing the products through online up to 1000 Rs. In contrast, 15% users of both cities are purchasing the products through online more than 5000 Rs.

Table no. 12 showing time spent for online shopping
Particulars Vadodara

Ahmedabad
Total

N N% N N% N N%
One Hr. 49 49.0 37 37.0 86 43.0
Two Hr. 27 27.0 42 42.0 69 34.5
Four Hr. 20 20.0 13 13.0 33 16.5
Six Hr. 4 4.0 8 8.0 12 6.0
Total 100 100.0 100 100.0 200 100.0

Figure no. 12 showing time spent for online shopping

As per given data, 43% users spent time one hour for online shopping in both cities. 34.5% users spent time one hour for online shopping in both cities. In contrast, 6% users spent time six hours for online shopping.

Opinion Based Questions:
Table no. 13 showing opinion of respondents regarding delivery of product.
Particulars Vadodara
Ahmedabad
Total

N N% N N% N N%
Strongly Disagree 16 16.0 1 1.0 17 8.5
Disagree 10 10.0 6 6.0 16 8.0
Neutral 26 26.0 24 24.0 50 25.0
Agree 26 26.0 54 54.0 80 40.0
Strongly Agree 22 22.0 15 15.0 37 18.5
Total 100 100.0 100 100.0 200 100.0

Figure no. 13 showing opinion of respondents regarding delivery of product.

As per given, 40% users of both cities agreed that delivery of products is better. 25% users of both cities are neutral. In contrast, 8% users are disagreed that delivery of products is not better.

Table no. 14 showing payment methods for online purchase
Particulars
Vadodara
Ahmedabad
Total

N N% N N% N N%
Credit Card 20 20.0 23 23.0 43 21.5
Debit Card 31 31.0 33 33.0 64 32.0
Cash on Delivery 49 49.0 44 44.0 93 46.5
Total 100 100.0 100 100.0 200 100.0

Figure no. 14 showing payment methods for online purchase

As per given data, 46.5% users of both cities do payment by cash on delivery. 32% users do payment through debit card. In contrast, 21.5% users of both cities do payment through credit card.

Table no. 15 showing difficulty of searching the information about products on internet
Particulars
Vadodara
Ahmedabad
Total

N N% N N% N N%
Strongly Disagree 23 23.0 41 41.0 64 32.0
Disagree 29 29.0 29 29.0 58 29.0
Neutral 17 17.0 14 14.0 31 15.5
Agree 24 24.0 12 12.0 36 18.0
Strongly Agree 7 7.0 4 4.0 11 5.5
Total 100 100.0 100 100.0 200 100.0

Figure no. 15 showing difficulty of searching the information about products on internet

As per given data, 32% users of both cities are strongly disagreed that there is no difficulty while searching the products on internet. 29% users of both cities are disagreed that there is no difficulty while searching the products on internet. In contrast, only 5.5% users of both cities are strongly agreed that there is a difficulty while searching the products on internet.
Table no. 16 showing that online transaction is safe
Particulars
Vadodara
Ahmedabad
Total

N N% N N% N N%
Strongly Agree 16 16.0 17 17.0 64 32.0
Agree 33 33.0 53 53.0 58 29.0
Neutral 35 35.0 19 19.0 31 15.5
Disagree 9 9.0 6 6.0 36 18.0
Strongly Disagree 7 7.0 5 5.0 11 5.5
Total 100 100.0 100 100.0 200 100.0

Figure no. 16 showing that online transaction is safe

As per given data, 32% users strongly felt that online transaction is safe. 29% users of both cities are agreed that online transaction is safe. In contrast, 5.5% users are strongly disagreed that online transaction is not safe.

Hypothesis
H1: Perceived Preferences: Preference is the major priority for purchasing the products like Computers accessories, Clothes, Cosmetics, Theatre tickets etc.

H2: Perceived Beliefs: Belief is the vital part while purchasing the products because what consumers believe for products is necessary.

H3: Perceived Behavior: Behavior of the consumers towards the online shopping is essential. Moreover, amount spent for purchasing the products and time spent for searching the products on internet can also states the behavior of consumers.

H4: Perceived Opinion: Opinion is the essential part because it shows how consumers feel towards the online shopping like delivery of products, payment method and information about the products.

Hypothesis Data Analysis
Preference based hypothesis Data:
Table no. 17 Showing hypothesis data of Products to be purchased through Internet
Product city mean sd t-value p-value
Computer Accessories vadodara 3.09 1.62 19.06 0.000
ahmedabad 2.56 1.51 16.995 0.000
overall 2.83 1.58 25.223 0.000
Books vadodara 3.23 1.483 21.781 0.000
ahmedabad 2.9 1.453 19.959 0.000
overall 3.07 1.474 29.414 0.000
Clothes vadodara 3.15 1.53 20.54 0.000
ahmedabad 3.24 1.386 23.373 0.000
overall 3.2 1.459 30.977 0.000
Furniture vadodara 4.74 1.481 31.998 0.000
ahmedabad 5.45 0.957 56.923 0.000
overall 5.1 1.294 55.685 0.000
Cosmetics vadodara 3.37 1.699 19.249 0.000
ahmedabad 3.54 1.78 19.914 0.000
overall 3.41 1.74 27.682 0.000
Theatre Tickets vadodara 3.52 1.856 18.967 0.000
ahmedabad 3.31 1.45 22.869 0.000
overall 3.42 1.663 29.036 0.000

As per given data, the mean value of computer accessories is 2.83 which means the data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=25.223 & p=0.000). In contrast, the mean of furniture is 5.1 which means purchasing of furniture through online is lesser.(t=55.685 & p=0.000)

Table no. 18 showing hypothesis data of Products to be purchased through various Websites
Websites city mean sd t-value p-value
Myntra vadodara 3.64 1.952 18.652 0.000
ahmedabad 4 1.456 yp 0.000
overall 3.82 1.727 32.281 0.000
Snapdeal vadodara 3.68 1.705 21.585 0.000
ahmedabad 3.04 1.78 17.074 0.000
overall 3.36 1.768 26.876 0.000
Yepme vadodara 4.46 1.702 26.202 0.000
ahmedabad 4.88 1.458 33.462 0.000
overall 4.67 1.595 41.408 0.000
Ebay vadodara 3.58 1.713 20.904 0.000
ahmedabad 3.72 1.741 21.364 0.000
overall 3.65 1.724 29.293 0.000
Homeshop 18 vadodara 3.66 1.849 19.795 0.000
ahmedabad 3.79 1.882 20.14 0.000
overall 3.73 1.862 28.293 0.000
Filpkarts vadodara 2.94 1.791 16.413 0.000
ahmedabad 3.55 2.13 16.674 0.000
overall 3.25 1.986 23.106 0.000
Others vadodara 6.06 1.728 35.068 0.000
ahmedabad 5.02 2.582 19.443 0.000
overall 5.54 2.253 34.782 0.000

As per given data, the mean value of flipkart is 3.25 which means the data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=23.106 & p=0.000). In contrast, the mean of yepme is 4.67 which means purchasing of product through this website is lesser.(t=41.408 & p=0.000)

Table no. 19 showing hypothesis data of Products Perceptions to be purchased through Internet
Products Preferences city mean sd t-value p-value
Product Brands vadodara 2.32 1.062 21.84 0.000
ahmedabad 2.30 1.078 21.34 0.000
overall 2.31 1.068 30.602 0.000
Product Quality vadodara 2.03 1.049 19.35 0.000
ahmedabad 2.04 1.044 19.55 0.000
overall 2.04 1.044 27.575 0.000
Product Prices vadodara 2.57 1.047 24.55 0.000
ahmedabad 2.41 0.986 24.449 0.000
overall 2.49 1.017 34.612 0.000
Product Varieties vadodara 3.00 1.110 27.02 0.000
ahmedabad 3.25 0.999 32.541 0.000
overall 3.13 1.061 41.667 0.000

As per given data, the mean value of product quality is 2.04 which means the data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=27.575 & p=0.000). In contrast, the mean of product varieties is 3.13 which means consumer preferred first quality of products rather than product varieties (t=41.667 & p=0.000).

Belief based questions:
Table no. 20 showing hypothesis data of reputation of company
particular city mean sd t-value p-value
very unimportant to very important vadodara 3.44 1.402 24.534 0.000
ahmedabad 3.93 0 .913 43.048 0.000
overall 3.69 1.205 42.233 0.000

As per given data, in ahmedabad the mean value is 3.93 which means the consumer of ahmedabad city felt that reputation of company is important and in Vadodara the mean value is 3.44 which means the consumer of vadodara city felt that the reputation of the company is less important. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted.(t=42.233 & p=0.000)

Table no. 21 showing hypothesis data of accurate description of products
particular city mean sd t-value p-value
strongly agree to strongly disagree vadodara 2.45 1.077 22.757 0.000
ahmedabad 2.05 0.757 27.076 0.000
overall 2.25 0.95 33.504 0.000

As per given data, in ahmedabad the mean value is 2.05 which means the consumer of ahmedabad city agreed that description of product is accurate and in Vadodara the mean value is 2.45 which means the consumer of vadodara city strongly agreed that description of product is accurate. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=33.504 & p=0.000)

Tabel no. 22 showing hypothesis data of internet provides sufficient information
particular city mean sd t-value p-value
strongly agree to strongly disagree vadodara 2.28 1.102 20.695 0.000
ahmedabad 1.89 0.709 26.651 0.000
overall 2.09 0.945 31.216 0.000

As per given data, in ahmedabad the mean value is 1.89 which means the consumer of ahmedabad city strongly agreed that description of product is sufficient and in Vadodara the mean value is 2.28 which means the consumer of vadodara city agreed that description of product is sufficient. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=31.216 & p=0.000)

Behavior based Hypothesis Data:
Table no. 23 showing hypothesis data of amount spent by users for purchasing products
particular city mean sd t-value p-value
1000 Rs. to more than 5000 Rs. vadodara 2.42 0.997 24.279 0.000
ahmedabad 2.15 0.957 22.456 0.000
overall 2.29 0.984 32.834 0.000

As per given data, in ahmedabad the mean value is 2.15 which means the consumer of ahmedabad city spent an amount upto 2500 Rs. Whereas in vadodara the mean value is 2.42 which means consumer spent an amount upto 5000 Rs. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=32.834 & p=0.000)

Table no. 24 showing hypothesis data time spent for online shopping
particular city mean sd t-value p-value
1 Hr. to 6 Hr. vadodara 1.79 0.902 19.839 0.000
ahmedabad 1.92 0.907 21.179 0.000
overall 1.86 0.904 29.004 0.000

As per given data, in ahmedabad the mean value is 1.92 which means the consumer of ahmedabad city spending time for online shopping around 2 hrs. Whereas in vadodara the mean value is 1.79 which means consumer spending time for online shopping is around 2 hrs. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=29.004 & p=0.000)

Opinion based Hypothesis Data:
Table no. 25 showing hypothesis data of delivery of product
particular city mean sd t-value p-value
strongly disagree to strongly agee vadodara 3.28 1.349 24.314 0.000
ahmedabad 3.76 0.818 45.967 0.000
overall 3.52 1.138 43.726 0.000

As per given data, in ahmedabad the mean value is 3.76 which means the consumer of ahmedabad city agreed that the delivery of product is better and in Vadodara the mean value is 3.28 which means the consumer of vadodara city agreed that the delivery of product is better. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=43.726 & p=0.000)

Table no. 26 showing hypothesis data of payment method
particular city mean sd t-value p-value
credit card, debit card, cash on delivery vadodara 2.29 0.782 29.272 0.000
ahmedabad 2.21 0.795 27.794 0.000
overall 2.25 0.788 40.392 0.000

As per given data, in ahmedabad the mean value is 2.21 which means the consumer of ahmedabad city do payment through debit card and in Vadodara the mean value is 2.29 which means the consumer of vadodara city do payment through debit card. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=40.392 & p=0.000)
Table no.27 showing hypothesis data of difficulty searching information about products on internet.
particular city mean sd t-value p-value
strongly disagree to strongly agee

vadodara 2.63 1.269 20.733 0.000
ahmedabad 2.09 1.181 17.69 0.000
overall 2.36 1.252 26.651 0.000

As per given data, in ahmedabad the mean value is 2.09 which means the consumer of ahmedabad city agreed that there is no difficulties of searching about products and in Vadodara the mean value is 2.63 which means the consumer of vadodara city are neutral. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=26.651 & p=0.000)

Table no. 28 showing hypothesis data of online transaction is safe
particular city mean sd t-value p-value
strongly agree to strongly disagee vadodara 2.58 1.084 23.798 0.000
ahmedabad 2.29 0.988 23.184 0.000
overall 2.44 1.045 32.965 0.000

As per given data, in ahmedabad the mean value is 2.29 which means the consumer of ahmedabad city agreed that online transaction is safe and in Vadodara the mean value is 2.58 which means the consumer of vadodara city are neutral. The data is highly significance where the null hypothesis is rejected and alternate hypothesis is accepted (t=32.965 & p=0.000)

Findings
‘ 49.5% users of both cities agreed that the data of product shown on online is sufficient.
‘ 32% users strongly felt that online transaction is safe.
‘ 46.5% users of both cities do payment by cash on delivery.
‘ 3% users of both cities strongly disagreed that the data of product shown on online is not sufficient.
‘ 29.5% users both cities purchased computer accessories.
‘ 24.5% users of flipkart website in both cities
‘ 40.5% users preferred quality of products through online shopping in Vadodara and Ahemdabad cities.
‘ 40.5 % users of both cities are purchasing the products through online more than 2500 Rs

Conclusion
Online shopping is rapidly changing the way people do business all over the world. In the business-to-consumer segment, sales through the web have been increasing dramatically over the last few years. Customers, not only those from well-developed countries but also those from developing countries, are getting used to the new shopping channel. Understanding the factors that affect intention, adoption and repurchase are important for researchers and practitioners alike. Online shopping is gaining popularity among people specially the younger generation but in today scenario to become equally popular among all age groups e-marketing will have to cover a longer distance.
The result of our study shows that mode of payment is depended upon income of the respondents. People having monthly income below Rs 1, 00,000 prefer cash on delivery and above Rs 3, 00,000 prefers Internet banking payments. People from different age groups are doing online shopping regularly. The attitude of consumers is changing with the time.
From the conclusion that we got through literature review was in a country like India, online experiences are still looked up as complex and uncomfortable. People are tradition bound & have doubt in mindset as far as issue of online shopping/purchase of product is concerned but we found that Indian consumers are finding online shopping very comfortable because of many variables like cash on delivery, customization or personalization of the websites, home delivery etc.

Annexure:
Name: _________________________

What is your Gender?
Male ________ Female ______

What is your Highest Education Level?
Secondary School _____ Graduation _____
Post Graduation _____ Professional _____

What is your Age?
15-25 years _____ 25-35 years _____
35-45 years _____ Above 45 years _____

What is your Income per annum? (in Rs.)
Below 1,00,000 ____ 1,00,000- 2,00,000 ____
2,00,00-3,00,000 ____ Above 3, 00,000 ____

On an average, how much do you spend while buying online?
One hr. ____ Two hr. ____ Four hr.____ Six hr. ____

It is difficult for searching the information about the products on the Internet.
Strongly Disagree ____ Disagree ____ Neutral ____
Agree ____ Strongly Agree ____
Which type of products are you looking for purchase through Internet? Rank them as per no. of maximum purchase by Internet. (1. Most Preferred to 6. Least Preferred)
Computer Products _____ Books _____ Clothes _____
Furniture _____ Cosmetics ____ Theatre Tickets ____

According to your preference rank the websites (1.Most Preferred to 7.Least Preferred)
Myntra _____ Snapdeal _____ Yepme _____ Ebay _____
Homeshop18 _____ Flipkart _____ Others _____

Delivery of products is better.
Strongly Disagree _____ Disagree _____ Neutral _____
Agree _____ Strongly Agree _____

What are the payment methods you generally use for online purchases?
Credit Card _____ Debit Card _____ Cash on Delivery _____

Online transaction is safe.
Strongly Agree _____ Agree _____ Neutral _____
Disagree _____ Strongly Disagree _____

According to your preference rank the products based on’ (1.Best 2.Good 3.Average 4.Worst)
Product Brand ______
Product Quality ______
Price _____
Product varieties ______
Up to What amount (Rs.), you normally purchase products through online shopping?
Up to 1000 ____ Up to 2500 ____
Up to 5000 ____ More than 5000 ____

Internet provides sufficient information.
Strongly Agree ____ Agree ____ Neutral ____
Disagree ____ Strongly Disagree _____

The descriptions of products shown on the web sites are very accurate.
Strongly Agree ____ Agree ____ Neutral ____
Disagree ____ Strongly Disagree _____

While purchasing products by internet, reputation of company
Very Unimportant ____ Unimportant ____ Neutral ____
Important ____ Very Important ____

Bibliography
‘ http://www.consumerpsychologist.com/cb_Attitudes.html (01/03/2014)
‘ http://marketography.com/2010/10/17/understanding-consumer-attitudes/ (01/03/2014)
‘ http://moneybies.com/10-best-online-shopping-sites-india/(01/03/2014)
‘ http://yourstory.com/2013/01/google-india-study-about-online-shopping/(01/03/2014)
‘ Fernandez, Ana, and Anthony D. Miyazaki. ‘Consumer Perceptions of Privacy and Security Risks for Online Shopping.’ The Journal of Consumer Affairs35.1: 27-44. (02/03/2014)
‘ http://topbullets.com/2013/11/07/essay-article-on-online-shopping-websites-business-market-in-india/ (02/03/2014)
‘ https://www7511.ssldomain.com/acrwebsite/search/view-conference-proceedings.aspx?Id=11848 (02/03/2014)
‘ October 25, 2009|By Gregory Karp, personal finance writer for The Morning Call, Allentown (02/04/2014)
‘ http://people.umass.edu/aizen/pbc.html (02/04/2014)
‘ An article by H??gskolan p?? Gotland VT2011 (02/04/2014

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