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\title{Effect of Demographic Factors on Consumers' Perception of Online Shopping}
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             \author[1]{Dr. Shamsher  Singh}

             \author[2]{Ravish  Rana}

             \affil[1]{  Banarsidas Chandiwala Institute of Professional Studies}

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\date{\small \em Received: 14 December 2017 Accepted: 3 January 2018 Published: 15 January 2018}

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\begin{abstract}
        


The growing use of internet in India especially in urban area provides an ideal platform for online shopping. The e-marketer can identify the various factors which affects buying behaviour of on line shoppers which can be used to develop marketing strategies. This will help not only in retaining existing customers but also converting potential customers into active one. The objective of the present study was to understand the consumers perception of online shopping and factors affecting it. To understand the perception of buyers, a survey was conducted using the structured questionnaire. The primary data was obtained from 100 respondents who have been using the online shopping. The data was analysed using SPSS software. ANOVA was used to find if there is any significant difference in the perception of respondents on the basis of demographic factors. It has been found that gender, age and annual income of respondents does not influence the customer perception where as educational qualification, marital status has significant impact in adoption of online shopping. 

\end{abstract}


\keywords{consumer perception, online shopping, ecommerce, demographic factors}

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\let\tabcellsep& 	 	 		 
\section[{I. Introduction}]{I. Introduction}\par
hopping is the process of exchange of products or services of value between the business organisation and their customers. This exchange can take place via different medium. Online shopping is the medium which facilitate direct exchange between shoppers and business organisation. Customers can directly buy goods or services from different ecommerce site or from other organisation having presence on world wide web. Consumers has the liberty to choose the products or services from different service providers or manufactures by visiting their web site. The web site displays the various products and services and provide different payment options. Online shopping can be done by using smart phone, laptops, desktop or any other device having internet connectivity.\par
Online shopping is convenient, faster and sometimes also cheaper. Nowadays people prefer to buy ticket online by visiting the particular website; they are no longer willing to stand in a long que for just buying ticket or making payment to their utility bills. Customers are willing to pay even premium for some services such as buying movie ticket, reservation of railways ticket, air ticket, booking of hotel and other travel related services because it provides convenience as compare to physically visiting the service providers premises .Buying or placing an order online is also useful when you need to send a gift to a friend who is staying in a different city or country. By using online shopping it has become very convenient, easier and preferred way to exchange gifts on special occasions such as birthday, anniversary etc.\par
Customer perception is created by interpretation of information by the customers for creating meaningful picture of a product or service. The customers have their own biases, expectation and different perspective while interpreting the stimulus. The different promotions, feedback, exposer of individual to different mediums helps in shaping their perception about any brand , products , services or experience . This perception once built will remain for a considerable period of time and will determine the response of customers to stimulus or promotion of products or services.\par
The business environment is becoming competitive and dynamic due to globalisation of markets and very high penetration of Internet especially in urban area. With the increases in literacy rate across different segments of society and acceptance of internet as medium, business and marketing are flourishing. This growth has facilitated different commercial activities in general and e-commerce or online shopping in p articular.\par
Online shopping has many attractive attributes not only for e-commerce companies but also for the customers. This includes time and money saving, communication, convenience, easy accessibility, selection from a wide range of alternatives and the availability of information for making decisions and all marketing activities can be performed via the Internet efficiently. In the era of globalization, companies are using Internet technologies to reach out to valued customers and to provide a point of contact 24 hours a day, 7 days a week.\par
Online retailing is channelized through the establishment of a communication link between retailers and their customers with the use of web. A large variety of online retail sectors including travel companies such as Expedia, Travelocity, e-tailors including flipkart, ebay, amazon.in etc. have experienced a boom in their business which has resulted in the explosion of the usage of online shopping by a large number of customers.\par
Online Retailing attracts a large number of customers as they are exposed to a large variety of products and services to choose from. It is beneficial from business point of view as information technology and software systems produce better forecasts as well as control inventory costs. Elimination of intermediaries from the supply chain reduces complexities as well as avoids unnecessary costs, thereby improvising the online merchandising systems. 
\section[{II. Literature Review}]{II. Literature Review}\par
Vikash and Kumar (2017) identified the factors that affect online shopping perception of consumers. Customers perceive online shopping with positive frame of mind. The major concern in online shopping is the quality of products. The other perceptions of the customer pertained to convenience, satisfaction and product availability. Zivile \hyperref[b23]{Bauboniene (2015)} examined the factors which influencing the online shopping by the consumer. The study found that there are four types of factors namely technology related, consumer related, price related and product/service factors.  {\ref Taweerat, et.al (2014)} studied about the customer satisfaction \& purchase intention of customers for E-commerce in Thailand. Study found that factor which influence purchase intention vary as per time and location. \hyperref[b11]{Mohammad (2011)} examined that online shopping and found that time consumption and convenience are the factors which influencing consumers to shop online.\par
Puranik and Bansal (2014) examined the various factors that influence the internet user's perception towards e-shopping. It helps the researcher to understand the drivers of consumer's perception and their intention to shop on the internet .It also helps the firms to understand the internet user's needs and make suitable the marketing policies or strategies to be used by firms.  {\ref Karve, Sunil (2014)} found that most of the youth go for online shopping and like to purchase on monthly basis through credit card. Respondents felt that it was safe and secure to do online shopping, however there can be chances of being cheated while shopping online It was also found that Flip kart was ranked highest followed by Amazon. \hyperref[b16]{Sharma, et al. (2014)} examined the online shopping behaviour of Indian shoppers and found that adaptation of online shopping can be enhanced by improving packaging of goods, after-sale services, securities of the online payments, speed in delivery of goods purchased. \hyperref[b14]{Khitoliya (2014)} conducted a study on "Customers Attitude and Perception towards Online Shopping" and concluded that many of the respondents found that the quality, size, and colour of the product differs from product to product and what they claim to possess and display on the website. Nagra and Gopal (2013) studied on the consumer behaviour towards online shopping and found that respondent have perceived online shopping in a positive manner. \hyperref[b0]{Chaugule (2015)} found that higher levels of education and personal income correspond to more favourable perceptions of shopping online. Customers will develop favourable attitude for new online shopping if there is exposer of technology. It was found that only 47\% of Indian internet users shop online, Indian online shopping community is around 28 million, on par with South Korea, behind only to China and Japan. \hyperref[b18]{Siddappa (2014)} study the growth of e commerce industry in India found that most of the products sold on line are in the technology and fashion category which includes mobile phones, I-pads and accessories, MP3 players, digital cameras and jewellery.\par
Haq (2012) and Chaugule (2015) also found that security remains the main factor of concern for online shoppers. The Indian online shopping market is worth about \$71 billion. Indian online shoppers spend an average of \$2,517 a year on online shopping, the fourth-highest amount in the Asia/Pacific region. The customers perception of online shopping dependent on the educational qualification and income however, it is not dependent on age and gender of customers \hyperref[b4]{(Haq, 2012)}. Study also established significant relationship between customer service commitment, security of transaction and customer intention of buying online.\par
Rajesh and Purushothaman (2015) found that "delivery time" and "price" are the main factors that influenced online shopping. The factors such as offers and discounts, variety of product available, free home delivery, website user friendliness, easy to order, variety, discounts/offers, saves time and avoid long queues creates favourable perception for online buying. Reputation of the company and good description of goods are the least factors that influenced online shopping.\par
Ellisavet \hyperref[b3]{Keisidou (2011)} in his research concluded that consumer attitude towards online shopping is affected mainly by the product in question. Study conducted in Greece found that consumers behave differently when buying inexpensive products and differently when they are buying expensive products. Study also highlighted that customers attitude changes when it involves everyday products as compare to when they buy products and services they intent to use in the long-term. \hyperref[b2]{Cho (2004)} found that online customers are more dissatisfied with sensory products than nonsensory products as they spent more effort on searching the information on sensory products than non-sensory product; they involve more on purchasing sensory products than non-sensory products; and they cost more on sensory products than non-sensory products. \hyperref[b21]{Thompson et. al. (2004)} in his research on U.S. and China consumers observed that consumers are worried that online stores will not allow for the exchange of products purchased and not provide after sales services. Thus, consumers have to spend more time in searching for product and store related information and monitoring online stores to check if their orders are processed as expected. \hyperref[b19]{Sandhe (2015)} found that there is a good possibility in India to offer durable goods online. The only hindrance is the lack of belief in terms of quality of after sales service, quality of goods offered for sale and price. Durable goods sale online can increase in India if the online shopping companies can provide right experience and awareness is created. He found the belief about purchasing durable goods online was not positive in most cases.\par
The study of Thakurand Aurora (2015) found that online shopping is very convenient and beneficial. This study also highlighted some potential issue that can arise with online shopping. These issues are online transaction security, personal privacy, price transparency, accessibility, time saving, trust etc which can affect consumer perception towards online shopping. \hyperref[b1]{Chau et al. (2000)} examined the effects of presentation mode, search engines, and navigation structure of product items on the adoption of internet shopping. It is observed that consumers had access to large number of suppliers, product or services due to online shopping  {\ref (Smith and Rupp (2003)}. Therefore, the Internet has developed to a highly competitive market, where the competition over consumer is fierce. According to \hyperref[b5]{Hollensen (2004)}, whether it is the traditional market or the online market, the marketer must understand the customer and how he/she makes his/her decisions and purchasing choices.\par
Li and Zhang (2002) found that consumers' attitudes toward online shopping have gained a great deal of attention. Intention to shop online and success of online transaction will depend on the attitude of consumers. Consumers shop on the internet because they can compare the perceived benefits of products and shopping channels. Shopper find it is more convenient to shop online as compare to shop in store. This act as motivators for online shoppers.\par
Kothari and Maindargi (2016) observed that major hurdle behind development of online shopping is of customer awareness. Majority of customers are not aware about various pre and post services rend by this online shopping companies. In India the number of internet user are increasing because of revolution in telecommunication sector but still a large number of customers prefer retail shopping for their regular purchases. In order to increase number of customers and attract all class of customers, extensive publicity and promotion is required for online shopping. \hyperref[b7]{Kanupriya and Kaur (2016)} identified that the convenience and customer service are main motivating factor which drives the people to online shopping. As a result, they were buying airline and railway tickets, books, home appliances, electronic gadgets, movie tickets, etc by logging on to a web site, rather than driving up to a store. Their research suggested that with increase in usage of internet, the user of online shopping also increased. This resulted in need to increase in broadband penetration which will further accelerate the growth of online trade. It was also observed by them that large number of buyers were shopping online because of the changing lifestyles and shopping habits. 
\section[{III. Objectives and Hypothesis}]{III. Objectives and Hypothesis}\par
The main objective of the study is to find the effect of the demographic factors on customers perception for online shopping. In pursuant of the objectives following hypothesis were formulated: H01: There is no significant difference on perception of customers for online shopping on the basis of the gender of the respondents. 
\section[{H02:}]{H02:}\par
There is no significant difference on perception of customers for online shopping on the basis of the age of the respondents. 
\section[{H03:}]{H03:}\par
There is no significant difference on perception of customers for online shopping on the basis of the education qualification of the respondents. 
\section[{H04:}]{H04:}\par
There is no significant difference on perception of customers for online shopping on the basis of the marital status of the respondents. 
\section[{H05:}]{H05:}\par
There is no significant difference on perception of customers for online shopping on the basis of the annual income of the respondents. H06: There is no significant difference on perception of customers for different modes of shopping vis-à-vis online or offline shopping.\par
H07: There is no significant difference on perception of customers on the basis of duration of online shopping. 
\section[{IV. Research Methodology}]{IV. Research Methodology}\par
Present study is based on descriptive research design. Survey method was adopted to collect primary data from 100 respondents from the various parts of Delhi. Close ended questionnaire was designed to collect the information from the respondents. Likert five point scales was used for obtaining responses. The responses have been collected by means of face-toface interviews by authors. 
\section[{a) Sampling Plan}]{a) Sampling Plan}\par
Sampling Unit: the sampling unit was the customers who have been using the online shopping for at least past six months. 
\section[{Sample Size:}]{Sample Size:}\par
In this survey the sample size was 100.\par
Sampling Procedure: Intercept interview method was adopted for collection of primary data. Respondents were told the purpose of this research and questions were explained to them in case there was any need for understanding any particular question. There had been no personal bias or distortions while recording the responses.\par
Research and Statistical Tools Employed: SPSS 20 was used to perform statistical analysis Cronbach's Alpha test was used to find the reliability of the data, ANOVA was carried out to test the hypothesis. 
\section[{V. Results and Discussion}]{V. Results and Discussion}\par
The analysis of this data was divided into following section: (i) Respondents Profile: Table \hyperref[tab_0]{1} (ii) Reliability and Validity: Table \hyperref[tab_1]{2} (iii) ANOVA: Table \hyperref[tab_8]{4 to 9} a) Profile of Respondents\par
The respondent profile as displayed in Table \hyperref[tab_0]{1} replicate the population generally engaged in use of online shopping. There are 55\% male and 45\% are female. 77\% respondents are in the age group of 18-40 years, 64\% are either graduate or post graduate, 58\% are unmarried and having annual income in the range of Rs 100000 to 500000 (70\%). 43\% respondents are doing online shopping for more than 3 years followed by 2-years (32\%). 65\% respondents uses both online and physical mode of shopping. This is the ideal profile for user of online shoppers and who are educated, employed and having decent income. Generally any Cronbach's Alpha scores greater than the 0.07 is accepted as good score of internal consistency Nunnaly's  {\ref (1978)}. In this case, the score was 0.758 for the online shopping modes used by the respondents.  Data Analysis for hypothesis H01: The computation of ANOVA shows that, there is no significant difference in the consumers' perception on the basis of gender, that means both male and female have similar perception. Hence, Null Hypothesis (H01) is accepted.  Data Analysis for hypothesis H04: The computation of ANOVA shows that, there is significant difference in the consumers' perception on the basis of marital status, on some characteristics of online shopping which means both married and unmarried respondents have different perceptions. Hence, Null Hypothesis (H04) is rejected. Data Analysis for hypothesis H07: There is significant difference observed for the duration of online shopping. Higher the duration more is preference towards online shopping. Hence, Null Hypothesis (H07) is rejected. 
\section[{VI. Conclusion}]{VI. Conclusion}\par
The present study focused to find whether demographic factors plays any role in influencing customer perception and creating positive inclination in adoption of online shopping. It has been found that gender, age and annual income of respondents does not influence the customer perception. Both male and female and all age groups has similar perception of online shopping. It was found that educational qualification, marital status has significant impact in adoption of online shopping. On line shopping as well as off line shopping both are adopted by the respondents. There was significant difference observed for the duration of online shopping. Higher the duration of doing online shopping more was the preference towards online shopping. The trend of online shopping had been widely accepted by the customers and the customers find themselves comfortable in both online and offline mode of shopping. Amazon was the most preferred online shopping website followed by Flipkart Consumers perceived that online shopping saved time and enhanced customers shopping experience. It was found that customers preferred online shopping only if online prices were lower than offline prices and there are promotional offers shopping online. Most of the respondents as per the survey agreed to the fact that online shopping provided safe and secure online transactions and encouraged customers to shop online anytime. \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.3735802469135802\textwidth}P{0.33685185185185185\textwidth}P{0.06925925925925926\textwidth}P{0.07030864197530864\textwidth}}
Variable\tabcellsep Characteristics\tabcellsep Frequency\tabcellsep Percentage\\
Gender\tabcellsep Male Female\tabcellsep 55 45\tabcellsep 55 45\\
\tabcellsep 18 -25 years\tabcellsep 42\tabcellsep 42\\
Age\tabcellsep 26-40 years 41-50 years\tabcellsep 35 15\tabcellsep 35 15\\
\tabcellsep 51 years \& above\tabcellsep 8\tabcellsep 8\\
\tabcellsep Under graduate\tabcellsep 33\tabcellsep 33\\
Education\tabcellsep Graduate Post graduate\tabcellsep 52 12\tabcellsep 52 12\\
\tabcellsep Others\tabcellsep 03\tabcellsep 03\\
Martial Status\tabcellsep Married Unmarried\tabcellsep 42 58\tabcellsep 42 58\\
\tabcellsep less than Rs.100000\tabcellsep 00\tabcellsep 00\\
\tabcellsep Rs.100001 -300000\tabcellsep 39\tabcellsep 39\\
Annual Income\tabcellsep Rs.300001 -500000\tabcellsep 31\tabcellsep 31\\
\tabcellsep Rs.500001 -700000\tabcellsep 20\tabcellsep 20\\
\tabcellsep Rs.700001 or above\tabcellsep 10\tabcellsep 10\\
\tabcellsep Online only\tabcellsep 18\tabcellsep 18\\
Mode of Shopping\tabcellsep Physical Stores only\tabcellsep 17\tabcellsep 17\\
\tabcellsep Both mode\tabcellsep 65\tabcellsep 65\\
Duration since you were doing online shopping\tabcellsep Less than one year 1-2 years 2-3 years More than 3 years\tabcellsep 13 12 32 43\tabcellsep 13 12 32 43\\
Total Responses\tabcellsep \tabcellsep 100\tabcellsep 100\\
b) Reliability and Validity\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Table 2 shows the result of reliability analysis-}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Cronbach's Alpha Value. This test measured the}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{consistency between the survey scales. The Cronbach's}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Alpha score of 1.0 indicate 100 percent reliability.}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.7020477815699658\textwidth}P{0.05221843003412969\textwidth}P{0.04931740614334471\textwidth}P{0.04641638225255973\textwidth}}
Practices/Services\tabcellsep Number of Cases\tabcellsep Number of Items\tabcellsep Alpha Value\\
Online shopping\tabcellsep 100\tabcellsep 14\tabcellsep 0.758\\
\multicolumn{2}{l}{c) Hypothesis Testing: ANOVA Computation}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{In order to test the hypothesis ANOVA was}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{carried out on the basis of gender, age education,}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{annual income, marital status mode of shopping and}\tabcellsep \tabcellsep \\
duration of online shopping.\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_6}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_7}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.053125\textwidth}P{0.2921875\textwidth}P{0.0265625\textwidth}P{0.10625\textwidth}}
Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_8}Table 9 :}\end{figure}
 			\footnote{© 2018 Global JournalsEffect of Demographic Factors on Consumers' Perception of Online Shopping} 			\footnote{© 2018 Global Journals} 		 		\backmatter  			 
\subsection[{Data Analysis for hypothesis H06:}]{Data Analysis for hypothesis H06:}\par
There is a significant difference observed for different modes of shopping vis-à-vis online and offline shopping. Hence, Null Hypothesis (H06) is rejected.			 			  				\begin{bibitemlist}{1}
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