Percentages have been calculated for demographic variables.

Factor analysis

style="text-align:justify;"Factor analysis technique is used to identify the factors affecting online buying behavior. In order to serve this objective, the information collected through twenty statements has been condensed into important dimensions with the help of factor analysis. For measuring the sample/data adequacy KMO test has been applied. Bartlett’s test of sphericity provides statistical probability that the correlation matrix has significant correlations among at least some of the variables.

Multiple Regression

Multiple regression analysis was used as the statistical technique to examine the relationship between factors affecting online buying behavior (Independent Variables) and willingness to buy (Dependent Variable). Multiple regression can establish that a set of independent variables explains a proportion of the variance in a dependent variables at a significance level.

Limitations

· Sample size of 200 respondents is very small to draw the inferences about the whole population.

· The study is limited to the Jalandhar city in Punjab. So we cannot say that the same kind of response will exist throughout India.

· Time and cost constraints were also there.

Results and Discussion

Demographic Variables: Age and Gender were taken as demographic variables.

From the Table-1 above we can see that majority of the respondents were female i.e. 59 percent and 41 percent were male. Also majority of the respondents 42 percent were in the age group 21-29 yrs, followed by 32 percent in the age group 30-39 yrs and rest of the 26 percent were above 40 yrs.

Factors Influencing Online Buying Behavior

To identify the factors affecting online buying behavior factor analysis was conducted. Factor analysis has been applied to twenty statements measured on a five-point Likert scale. The value of KMO test (=.794 which is greater than 0.5) shows fairly adequate sample. The appropriateness of the factor analysis is examined in terms of presence of correlations among the variables. For this purpose, Bartlett’s test of Sphericity conducted which indicates the strength of the relationship among variables. The observed significance level was found to be (.000). Thus it is good to proceed for factor analysis with the data.

Table-2 Principal Component Analysis with Varimax Rotation

(KMO MSA=0.794; Bartlett=811.443)

Extraction Method: Principal Component Analysis

Rotation Method : Varimax with Kaiser Normalization

As the Table-2 shows that Principal component analysis has been used for extracting the factors and the number of factors to be retained is based on total variance explained.

The result of factor analysis over 20 statements shows that there are 7 factors that influence the online shopping. Preferences with Eigen values greater than one were extracted and all factor loadings greater than 0.5 were retained. The name of the factors, the statement labels and factor loadings are summarized in the Table-3.

Table-3 Naming of Factors

The set of twenty statements were subjected to factor analysis using principal component method so as to identify the minimum number of factors that determine the maximum variance. The seven factors were extracted that explained 67.626 percent of the variance.

Factor 1- Website Security

This was the most important factor that explained 14.045 percent of the variance. The statements included in this factor are S1 “I will purchase from the site where my privacy is protected”, S7 “A good website has adequate security features” and S12 “Feeling safe and secure while transacting online is important” having factor loadings as .879, .768 and .878 respectively.

Factor 2- Reliability of the Website

This factor explained 12.134 percent of the variance. The statements included in this factor are S3 “The product should be delivered on time”, S16 “I should get what I ordered” and S17 “The delivered product should be same as specified on the website” having factor loadings .787, .867 and .793 respectively.

Factor 3- Simple Return and Exchange Policy

This factor explained 11.011 percent of the variance. The statements included in this factor are S4 “Dealing with the site having simple return & exchange policy is desirable”, S5 “Return/ exchange procedures should be easy” and S18 “It should not take too long for exchanging the product” having factor loadings as .765, .789 and .874 respectively. This factor suggests that complicated return and exchange policies bother consumers. Thus marketers should try to make the return and exchange policies as simple as possible.

Factor 4- Reasonable Prices Offered

This factor explained 9.111 percent of the variance. The statements included in this factor are S19 “I generally prefer buying from the site that gives discount offers”, S2 “I generally prefer buying from the site that gives free of cost shipping facility” and S13 “I prefer buying from the site offering reasonable prices” having factor loadings as .687, .698 and .677 respectively. This shows that consumers are price conscious and thus offering discounts and reasonable prices to consumers can help the marketers to attract larger market share.

Factor 5 Customer Services Offered

This factor explained 8.001 percent of the variance. The statements included in this factor are S8 “It is good to deal with the website that responds to the customers queries immediately”, S9 “Website should have a section for registering complaints of the customers” and S14 “Website taking feedback from customers better understands them” having .765, .787 and .679 as factor loadings respectively. As customer is the king, serving them by offering best services will help the marketers to gain the confidence of the customers.

Factor 6 Positive Customer Reviews regarding website

This factor explained 7.312 percent of the variance. The statements included in this factor are S15 “I read the customer reviews about a site before purchasing from it”, S10 “I prefer the site having positive word of mouth” and S11 “I consider the experiences of other people with the site” having .723, .657 and .689 as factor loadings respectively.

Factor 7 Informative Website

This factor explained 6.012 percent of the variance. The statements included in this factor are S6 “Detailed information about the products on the site increases my intention to buy from that site” and S20 “Websites showing reviews of other people about the product are more trustworthy” having .678 and .693 as factor loadings respectively.

Relationship between seven Identified Factors and Willingness to buy Online

To examine the relationship between these seven identified factors and intention to purchase online, multiple regression analysis was conducted. Table-4 shows the relationship between web security, reliability of the website, simple return and exchange policy, reasonable prices offered, customer services offered, positive customer reviews, informative website and willingness to buy online. Web security, reliability of the website, simple return and exchange policy, reasonable prices offered, customer services offered, positive customer reviews and informative website were taken as independent variables and willingness to buy online was taken as dependent variable.

Table-4 shows the beta values of the seven independent variables. Beta value of Website Security is 0.322, Reliability of the website is 0.135, Simple return and exchange policy is 0.068, Reasonable prices offered is 0.275, Customer services offered is 0.152, positive customer reviews is 0.210 and information website is 0.065. R-Square of 0.34 value shows that web security, reliability of the website, simple return and exchange policy, reasonable prices offered, customer services offered, positive customer reviews and informative website explains 34% of the variance in the dependent variable i.e. Willingness to buy. Here all the independent variables were found to have significant impact on the dependent variable except Informative Website. Web security has been found to be the most important significant predictor of the dependent variable, followed by reasonable prices offered, positive customer reviews regarding website, customer services offered, reliability of the website and simple return and exchange policy. The positive sign of the beta values of independent variables indicate that greater the extent of these independent variables, more will be the willingness of the respondent to buy online.

In this study Website security was found to be the most important factor influencing online buying behavior of the people. This is in consistent with the study by Rao and Mehdi (2010). People want to be safe while transacting online. Customer services and prices offered by the website also affect the decision of the people of buying online. These results are similar to the results found in the study by Kim and Benbasat (2003). As the consumer is the king of the market, it becomes very important for the marketers and online retailers to offer excellent services to their customers and for price conscious consumers, reasonable prices should be offered.

Conclusion and Marketing Implications

The factors found in this study influencing online buying behavior are: Website Security, Reliability of the website, Return and Exchange policy, reasonable prices offered, Customer Services Offered, positive customer reviews regarding website and informative website .Website security was found to be the most important factor and predictor of the willingness to buy. This shows that in a country like India, although most of the people are much aware about the internet and using it in their day to day life but still they have the fear in mind of losing the privacy by giving their personal information on the internet. They do not want to disclose any of their private information while working online. People will not hesitate to buy online if the option of “Cash on Delivery” is given by the website. E –retailers should try to win the trust of their customers by designing reliable websites. Sometimes customers face the problem of not getting the product which was ordered by them. Firstly, there is a need to avoid these kinds of situations by the marketers but still in case they arise, there must be some kind of arrangement of returning the product at the time when it was delivered. The company should take it back and exchange the same or replace for the customer. Moreover customers do not want to waste their time in returning and exchanging the products which usually involves lengthy and complicated procedures for the same. Companies should try to make them as simple as possible. Assessing the needs of the customers and fulfilling the same should be the main motive of every online retailer. The companies should give emphasis on designing of a website. Website should include the necessary information needed by the customer. Website should not be designed as an online brochure of the products but it should invite people to buy the products offered by it. So, the online retailers should take the measures to secure the privacy of the consumers, provide information to them about the products, offer reasonable prices and take care of the needs of the customers to survive in this competitive market. Winning the heart of every customer is like winning the market share.

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