Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Research Article: 2021 Vol: 25 Issue: 1

Factors Underlying Consumer Online Buying Decisions in an Indian Context

Dr. Jaipal Rathod, Assistant professor, School of Business Studies, Central University of Karnataka, India


Electronic retailing enables the purchase of goods and services via, electronic media. With the advent of the internet, retailers were able to create electronic platforms that would facilitate online interactions between buyers and sellers. Electronic retailing continues to grow, as customers use information technology regularly. The introduction of smartphones, coupled with the dropping rates of online internet accesses could act as major drivers of electronic retailing. Electronic retailing is expected to alter the traditional land space of retail markets. Electronic retailing enables the buyers to select and order products and services of their choice, irrespective of the time and location. Retailers can go online and set up electronic stores, without the need to set up a physical store. As space is not a constraint in electronic retailing, retailers can offer a wide variety of products like electronic goods, apparels, furniture’s, household appliances, toys, cosmetics, books, sporting goods, and accessories, etc. on their virtual stores. In this context, it is quite interesting and useful to understand the perceptions, attitudes, and purchasing patterns of online customers. The study is focused on finding the underlying factors that play a major role in the purchase choices/buying decisions made by customers during their interactions (online) with virtual stores. This research paper attempts to provide insights into the above-mentioned aspects. During the research study, a structured questionnaire was used to collect the data from the sample respondents.


Electronic Retailing, Online Customers, Perception, Attitude, Traditional, Technology.


Turban (2006), defined electronic retailing (e-retailing or e-tailing) as retailing conducted online, over the internet. Wang (2002) defined it as the selling of goods and services to the consumer markets via the internet. The working definition for e-retailing can be given as follows: E-retailing (electronic retailing) is a Business to Consumer retailing activity that essentially uses electronic networks, eliminating the need for consumers to physically visit the store. Compared to physical stores, online shopping offers many advantages to the consumer. Online shopping is more convenient and comfortable. It saves time for the consumer and eliminates the need for travelling and waiting in lines at check-out counters. Online shopping websites or portals give 24/7 service to the customers. It’s accessible at any time and anywhere across the world. Online shopping websites provide consumers with detailed information about products and services. Online retailers also have some online tools to help consumers make price comparisons and make purchase decisions (Ainin et al., 2015).

According to a 2019 study by the Internet and Mobile Association of India and KPMG, Indian e-commerce pegged at $9.5 billion is projected to grow to $12.6 billion by the end of 2019. By 2020, it is expected to contribute around 4 per cent to GDP. Currently, the Internet penetration in India stands at 14 per cent of the population, a third of the world average.

According to the ‘Assocham’ report of 2019, consumer behaviour and shopping trends have helped the Indian e-commerce industry to record a staggering 85% growth in 2019. It is expected that the e-commerce market in India will control 6.5% of the total retail market by 2023. "During Diwali alone, online shopping is estimated to cross Rs.10,000 crore and going forward, the trend will not only continue but also grow dramatically to cross Rs.100,000 crore over the next four years," the survey pointed out. The survey also found that e-commerce sales in August and September 2019 grew 200 per cent from 120 per cent, a year ago (2018), as more and more consumers tend to shop online (Abed et al., 2015).

Features of Electronic Retailing

1. Convenience: Electronic retailing offers the convenience of ordering products from home. Consumers who have a busy schedule prefer to purchase a product online instead of going to a conventional store.

2. Availability of products: The wide range of products from apparels to books, electronic goods, and groceries etc. available in online shopping is appealing to the consumers. Branded products with high quality and reasonable prices are available in online shopping.

3. Product Return guarantee policy: Many electronic retailing channels offer 30-day product returns guarantee policy to consumers. If the consumers do not find the goods as per their expectation, they can return the product.

4. Multiple payment options: Online retailers offer customers multiple payments options like Cash on Delivery (CoD), net banking, and Credit/ Debit cards.

5. Price comparison: Online retailers offer price comparison tools to customers thereby enabling them to compare the prices among the E-retailers as well as conventional retailers in the market.

6. Shipment option: Online retailers offer free delivery of products at consumer doorsteps.

7. Quick Service: Online shoppers are providing quick services in terms of delivery, refunding of payments for default product and offer 24/7 customer care services, to the consumers in the market.

Literature Review

In this section, the literature concerning the key constructs of the study namely customer online purchase intentions, their attitudes and perception towards online shopping are discussed. Several scholars and researchers have studied the developments related to internet usage and e-retailing. In this age of the Internet and communication technology retailing has become a dynamic industry. This is partly because consumers have become increasingly technology-dependent (Zhitomirsky-Geffet & Blau, 2016). Recently, Roy et al. (2016) defined smart retailing as

An interactive and connected retail system which supports the seamless management of different customer touchpoints to personalize the customer experience across different touchpoints and optimize performance over these touchpoints”.

Web sites that were more culturally congruent were rated more favourably on navigation, presentation, purchase intention, and attitude toward the site. From a larger perspective, researchers have asserted that cognitive abilities may differ in cultures like India where choice is constrained because the economies and marketplaces are still developing Gehrt et al. (2012) When consumers find that the product they consumed /used (i.e., direct experience) is inconsistent with their cognition (e.g., the OCEs they cognized), they may produce CD, causing a low level of satisfaction, low level of repurchase intention, and high level of complaint intention (Liao & Keng, 2013). Purchase intentions. As the internet has spread it has become a popular marketing channel (Cho & Park, 2001). Analyzing customer evaluations of online shopping is particularly interesting to academics and practitioners, especially in the field of e-commerce (Wu, 2003) in Figure 1.

Figure 1 Customer Evaluations of Online Shopping

The Key Drivers of Online Shopping in India

1. Increasing internet penetration across the country and increasing usage of smartphones, tablets, personal computers, desktops and other electronic devices for online shopping.

2. Availability of 24/7 online shopping portals.

3. Availability of much wider product catalogues and ranges of products on online shopping sites.

4. Busy lifestyles of customers and lack of time for offline shopping.

5. Evolution of the online marketplace model with websites like eBay, Flipkart, Snap deal, Amazon, etc.

Objectives of the Study

The purpose of this study is to explore the consumer’s attitudes and perceptions towards online shopping. To attain this purpose the following objectives were proposed:

1. To determine the attitudes and perceptions of customers towards online shopping (on various factors like convenience, trust, transaction security, quality of products sold by e-trailers etc.)

2. To determine the major factors that influence customers’ decisions to purchase goods and services on online shopping websites.

3. To determine the key factors that influence the customers during pre-order and post-order phases during online shopping.

Research Methodology

The present study explores the issues of consumer perception and attitudes towards online shopping. The respondents for the study included the residents of Hyderabad city. The explorative and descriptive research method has been adopted for this study. A structured questionnaire was designed to capture the demographic information of the respondents, their online shopping patterns, preference of payments modes, product categories, and attitudes of respondents towards online shopping etc. The independent variables included age, gender, education levels of respondents. Likert five-point rating scale ranging from “Strongly Disagree” to “Strongly Agree” was used to measure the consumer attitude towards online shopping. Respondents were asked to choose their options on a five-point Likert scale (1= Strongly Disagree, 2= Disagree, 3= Neutral, 4=Agree and 5= Strongly Agree). The variables for studying the attitudes included the factors like transaction security, quality of products purchased online, warranty offered, availability of product/price information etc. The variables were chosen based on literature review done during the study (Ajzen, 1991).

The data were analyzed using SPSS 21 software. As per the requirements of the study, reliability tests were conducted and only those dimensions that met the requirements of reliability have been considered for further analysis. Factor analysis was used to analyze the collected data (Akpan et al., 2020).

Data Collection Method

The present study collected relevant primary data with the help of a structured questionnaire from the respondents from various regions of Greater Hyderabad Municipal Corporation. The questionnaire was distributed to those who have done at least one transaction at any electronic retailer’s website. The secondary was collected through websites, books, articles, and business newspaper reports like Economic Time’s paper reports on online shopping etc.

Sampling Design and Sample size

In this study, the sample respondents were selected based on purposive sampling method. The purposive sampling method is one which is selected where there is good evidence that it is very much representative of the total population of the region. A quantitative study, involving the administration of a questionnaire was conducted to assess the usage of the identified factors of online shopping. A total of 400 questionnaires were distributed to online shopping consumers to fill the questionnaire and a total of 310 questionnaires were returned and found complete. These were used for the data analysis.

Table 1 presents the result of KMO and Bartlett’s test which shows the sample adequacy is 0.689 and with the chi-square value is 2.302 with observed degrees of freedom 136 supported by 0.000 significance value (Priporas et al., 2017).

Table 1 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.689
Bartlett's Test of Sphericity Approx. Chi-Square 2.302E3
Df 136
Sig. 0.000

Extraction Method: Principal Component Analysis

In the above Table 2, Total 5 factors were identified based on the Eigenvalues which are greater than 1. The extraction sum of square loadings shows the first factor’s total value is 3.344, second factor value is 2.757, third-factor value is 2.300, fourth-factor value is 1.664 and fifth-factor value is 1.550. The highest percentage of variation was observed by the first factor i.e., 19.671 and least percentage of variation were observed by 9.118. The cumulative percentage of variation by all factors is 68.326.

Table 2 Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3.344 19.671 19.671 3.344 19.671 19.671 3.104 18.257 18.257
2 2.757 16.219 35.890 2.757 16.219 35.890 2.757 16.217 34.474
3 2.300 13.528 49.418 2.300 13.528 49.418 2.516 14.800 49.274
4 1.664 9.790 59.207 1.664 9.790 59.207 1.666 9.803 59.077
5 1.550 9.118 68.326 1.550 9.118 68.326 1.572 9.249 68.326

From the above Table 3, the 4 variables namely purchase frequency, time-saving, convenience and discount belong to the first factor and their observed variance is 0.875, 0.873, 0.871 and 0.864 respectively. This indicates the total variance observed by the first factor (Shopping Benefits) was 0.433. The variables validity, authenticity, influence and product types are observed in the second factor (Retailer Attributes) and the variation observed is 0.897, 0.897, 0.792 and 0.707 respectively. This indicated the total variance observed by the second factor (Retailer Attributes) is 0.823. The third factor (Trust in Retailer) consists of reliability, post-purchase and guaranty/warranty and the variation observed by 0.917, 0.898 and 0.898 respectively. The total variation observed from the (Trust in Retailer) is 0.904. The fourth factor (Post Order Performance) consists of online tracing, easy returns and delivery duration and the variation observed is 0.803, 0.785 and 0.623. The total variation observed by the fourth factor (Post Order Performance) is 0.737. The fifth factor consists of security, payment mode and difficulties and the variation are observed 0.752, 0.732 and 0.673 respectively. The total variation observed from the fifth (Ease and Security of payments)) is 0.719 in the Table 4.

Table 3 Rotated Component Matrix a
  1 2 3 4 5
Purchase frequency 0.875        
Time-saving 0.873        
Convenience 0.871        
Discount 0.864        
Validity   0.897      
Authenticity   0.897      
Influence   0.792      
Product Types   0.707      
Reliability     0.917    
Post-purchase     0.898    
Guaranty/Warranty     0.898    
Online Tracking       0.803  
Easy Returns       0.785  
Delivery Duration       0.623  
Security         0.752
Payment Mode         0.732
Difficulties         0.673
Table 4 ANOVA
Model Sum of Squares Df Mean Square F Sig.
1 Regression 455.607 5 91.121 114.469 0.000a
Residual 242.792 305 0.796    
Total 698.399 310      

The sum of squares values indicates the total factors explained value is 455.607 and un-explained value is 242.792 which is less the explained value at the 5,305 degrees of freedom. The F-ration value 114.469 which greater than the Table 5 value, at d.f 5,305. The significance value 0.000 indicates the data is showing the significant result which is 0.05.

Table 5 Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 0.114 0.223   0.511 0.610    
Shopping Benefits 0.363 0.047 0.331 7.766 0.000 0.627 1.594
Retailer Attributes 0.563 0.043 0.560 13.226 0.000 0.636 1.573
Trust in Retailer 0.058 0.035 0.055 1.635 0.103 0.998 1.002
Post Order Performance -0.108 0.056 -0.098 -1.920 0.056 0.440 2.272
Ease and Security of Payments 0.136 0.056 0.124 2.445 0.015 0.442 2.264

The Shopping Benefits, Retailer Attributes and Ease and Security of Payments have significance values of 0.000, 0.000 and 0.15 which are less than 0.05. These factors are showing a positive impact on customer attitudes towards E-retailing. This indicates the one unit increase in the independent variable cause the dependent variable to increase by 0.363, 0.563 AND 0.136 respectively. Whereas, Trust in Retailer and Post Order Performance significance values are 0.103 and 0.56 respectively which are greater than 0.05. Further Post Order Performance status has shown a negative result. This indicates the Trust in Retailer will cause the variation on the dependent variable by 0.058 with a unit increase in delivery status (Kang et al., 2015).

Managerial Implications of the Study

Online shopping has shifted customers’ attention from visiting physical stores for making purchases to searching for and ordering products/ services over the internet. Online shopping also influenced consumers’ purchasing decision process. Online retailing is considered as an emerging area of electronic commerce that would change the retailing landscape. The study would generate information that can give insights into consumers’ concerns and the factors considered by them during online shopping etc. Determine the underlying factors that would determine the purchase choices made by the customers (Lee & Lin, 2005; Martin et al., 2006).


Understanding the consumer is critical for the success of any organization. In the context of online retailing, understanding the customer is even more critical as the scope for differentiation is very less. Neither the products are produced by the retailers nor are they branded by them. Unlike a physical retail store, they cannot create a retail environment for differentiation. Of course, the look of the website can be changed, but more or less the online customer can simultaneously access several online stores and experience the virtual store sitting in his/her residence. Service differentiation is a key aspect of online retailers.

Retailers need to segment online customers on various parameters. For effective segmentation the basis of segmentation is critical. In the Indian context, the penetration of internet is estimated to be between 12%-14%. Within internet users, a small fraction constitutes online shoppers. This gives scope to increase the market for online retailing. Online customers are very much concerned about the product preferences and security aspects of payment mechanisms. Different products catalogues options for various categories of products (toys, books, apparel mobile phones etc.) could be used to target the various segments and increase the comfort levels of the customers to shop online for the preferred kind of quality product. Various payment options (cash on delivery/ credit/debit card payments/internet/mobile banking etc.), same-day delivery, prior information on delivery etc could also be used in differentiation.

Understanding the factors that underlie customers’ decisions to place orders for online products/ services enables e-retailers to better plan their e-retailing activities. The popular notion that customers shop online for price discounts needs to be examined carefully, as the e-retailer needs to offer a value proposition to the customers. Similar to the retail markets in the conventional format (both organized and unorganized) different segments of the market expect different combinations of value additions. Another factor that needs to be examined in this context is whether customers prefer specialty virtual stores for specific products (like electronic goods, apparel, toys, books etc.). Research in these areas could offer more insights into customer preferences in online shopping.


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