Keywords

Virtual Shopping, Online Approach (OA), Online Buyer, e-tailor, Zero Contact Delivery (ZCD), PEBSF – Product, Employee Behavior and Service and Finance.

Introduction

Advancement in Information Communication and Technology (ICT) has drastically changed the Indian economy. We all know that the internet and e-commerce are completely dedicated to every industrialized country. But, if an appropriate business goal can be found, we believe it can be realized and provide a significant benefit to poor countries. (Chanana&Goele, 2012). E-commerce, to put it another way, is the expansion of traditional company operations into the digital realm. It is regarded as the most promising application of information technology since it has allowed firms to improve internal efficiency and grow their operations globally, thus overcoming geographical limitations.

The 4G network advancement has increased the use of the internet and e-commerce websites, which has made virtual buying and selling flexible over time and place, to buy their requirements from a seller over the internet using supportive e-commerce browsers. The online buyer has complete flexibility to browse around e-commerce websites and shopping search engines and compare, choose and select their requirements. The online sellers, more popularly called e-tailers, supply the selection of appropriate modes of payment. Most of the e-commerce supplier offers various products and services, but at different terms. To explain customer satisfaction through their motives to buy things online, the (Kotler& Killers, 2009) Five Stage Buying Process Model was evaluated in the study’s framework.

Problem Statement

There are many e-commerce suppliers; offering a variety of products and services, as per the requirements of the buyers with different terms and conditions. The e-commerce suppliers are offering and fulfill buyer’s needs digitally online. Though the supplies are the same and as per consumers’ requirements, the satisfaction level significantly differs. Hence, deep into and compare their satisfaction level, the researcher has taken up the present research study, titled ‘E-commerce companies, online shopping and customer’s satisfaction: A comparative study of COVID-19 lockdown in India’

Limitations of the Study

The constraints of the study are those elements of design or methodology that impacted or influenced the interpretation of the findings from the research. Following are the limitations of the present study;

1) Due to geographical constraints, the only online survey questionnaire method has been used.

2) The present research study has surveyed actual e-commerce online buyers only.

3) The present research study has compared and analyzed the satisfaction level of Amazon, Flipkart and Snapdeal online buyers only.

4) The researcher has drawn conclusions purely based on data collected and inferences calculated.

Significance of the Study

The significance of the study is a component of this research paper. Its goal is to explain why this study on e-commerce was necessary and how this research contributed to the advancement of knowledge in online shopping. Following is the various significance of the study.

1) The present research study will be helpful to understand the concept of online shopping.

2) The present research study will be helpful to understand the different e-commerce websites.

3) It will be helpful to study the demographic profile of e-commerce online buyers.

4) It will be helpful to study the comparative satisfaction level of sample e-commerce.

Objectives of the Study

The overarching goal of the study is to build a broad planning and development framework that includes principles and standards for more effective and complete online buying and e-commerce planning include: to study and compare the satisfaction level of online buyers of Amazon, Flipkart and Snapdeal, to study the demographic profile of online buyers of Amazon, Flipkart and Snapdeal.

Hypothesis of the Study

A research hypothesis is a prediction or statement of expectation that will be tested through study. In support of the research objective of the study, the following alternative hypotheses are formulated.

H0: The satisfaction levels of online buyers related to Products (P) from Amazon, Flipkart and Snapdeal are not significantly different.

H0: The satisfaction level of online buyers related to Employees Behaviour and Services (EBS) from Amazon, Flipkart and Snapdeal is not significantly different.

H0: The satisfaction levels of online buyers related to Finance (F) from Amazon, Flipkart and Snapdeal are not significantly different.

H0: The demographic profile and satisfaction level of online buyers of Amazon, Flipkart and Snapdeal are not significantly associated.

Review of Literature

It is known that the internet and e-commerce are completely dedicated to every industrialized country. But, if an appropriate business goal can be found, we believe it can be realized and provide a significant benefit to poor countries. E-commerce is the conduct of business over the internet, which includes activities such as searching for information, sharing information, purchasing or exchanging products and services, and maintaining customer relationships without the need for a face-to-face meeting, as opposed to traditional transactions (Keeney, 1999;Turban, King, 2003)

Despite the numerous opportunities, the expansion of e-commerce in India has not reached its full potential due to key constraints that stifle firm growth. Inadequate infrastructure, logistics failure, a lack of tax conformity, and diminishing margins are all impeding the expansion of internet commerce in India. In the face of fierce competition, businesses are forced to pamper customers with enormous discounts, daily specials, and a generous return policy, all of which are damaging to their earnings. In comparison to businesses that operate on an inventory basis, e-marketplaces are more negatively impacted by subsidies because they must provide incentives to sellers in exchange for putting their products on the website, in addition to massive discounts and a diverse range of offers to customers. Increased fulfillment expenses (which comprise all costs spent from the time an order is made until it is delivered to the consumer), a lack of last-mile connectivity in many suburban and rural areas, and escalating reverse logistics all impede e-commerce enterprises' growth by causing significant losses. (Rina, 2016)

E-commerce is frequently misunderstood as a means of conducting business between web retailers and web end customers, but it comprises a wide range of online commercial interactions, including company to business, business to customer, and business to government.

Customer satisfaction is when products and services meet the expectation of the consumers (Kotler, Cunningham&Turner, 2001). Consumers must be content with the products and services provided by the particular website as satisfied customers are likely to be loyal and make repetitive purchases which will increase the profitability of that particular e-commerce company (Reibstein, 2002) Through internet e-commerce, has become possible to shop online. The brick-mortar traditional shopping model has rightly been replaced by Online-Virtual Shopping.

Bagozzi (1974) found that the online buyer’s e-shopping behavior is a complex process. The consumer makes purchasing decisions based on the necessities of their family and their financial constraints. As a result, they are more likely to reduce transaction costs while increasing compatibility with needs. E-shopping is also influenced by social conventions and competitive offers, according to the study. According to Mehta and Sivadas (1995), internet buying is favorably connected to income, home size, domestic requirements, and product originality, regardless of gender.

According to Wolhandler (1999), the internet is a blessing because it provides maximum purchasing convenience and allows people to shop online at any time and from anywhere.

Donthu and Garcia (1999) conducted a study on “Internet-based online-Shoppers,” which revealed that online consumers are older, seek variety, prefer convenience innovative products, act impulsively, are less conscious of brand and price of goods, and are influenced by direct marketing and advertising for domestic needs.

Because of its flexibility and range of offers at the click, e-commerce has changed the perspectives of online buyers, according to Jahng, Jain, and Ramamurthy (2000). In total, 57 variables of online goods and services were investigated in an e-commerce environment, with results varying from one e-commerce website to the next.

According to Vrechopolous et al. (2000), the majority of e-commerce gives information about product quality and end number, as well as discounts and promotions, delivery, and accessibility. According to the findings, online sellers should modify user-friendly virtual environments to meet the needs of online buyers. It also suggests that alternative payment methods be made available to make online shopping more convenient.

In their study, Menon and Kahn (2002) found that online shopping has given rise to the concept of e-tailers, or online retailers, which has a substantial impact on the emotions and motives of online customers, resulting in a variety of buying behaviour.

Monsuwe, Dellaert, and Ruyter (2004) did a literature analysis on “Drivers to Shop Online?” and found that convenience, quality of goods, services, and flexibility were the most influential factors in online shopping behavior. According to Demery (2010), online purchasing saves time and is more convenient than traditional shopping.

PratiksinhVaghela (2014) conducted a study on online shopper’s attitudes on online shopping. The study included a sample size of 150 people from Surat’sVarachha region. According to the findings, the majority of online shoppers believe that online buying is a better option and thus more satisfying than traditional physical purchasing. The majority of online buyers use the internet from their homes, offices, and colleges. Customers mostly purchase clothing, electronics, and accessories.

Research Methodology

A research study is required to be conducted in a scientific way to solve a problem under study. For the present research study, the researcher has adopted the following research methodology. It is available in the form of qualitative and quantitative. The universe is taken as online buyers and e-commerce. The population for the present research study is finite i.e. online buyers and e-commerce websites (suppliers). The sampling frame for the present research is E-commerce websites (Suppliers) and online buyers in the Mumbai region. The method has been used as Stratified Random Sampling for e-commerce websites and Convenient Random Sampling for online buyers.

Table 1 Selection Criterion of E-Commerce As of 31st March 2020
E- Commerce Websites	Total Visit (in Millions)	Average Visit Duration (In Hours and Minutes)	Page Per Visit (By Online Buyers)	Bounce Rate (In per cent)
Amazon	199.79	00.07.32	6.99	40.69
Flipkart	157.60	00.06.56	5.50	43.78
Snapdeal	12.88	00.08.38	4.10	43.90

For this present research both Primary and Secondary Data have been collected and analysed. The researcher has collected primary data from 300 online buyers (100 each from) of Amazon, Flipkart and Snapdeal. Whereas, the researcher has collected secondary data from the published sources such as books, articles, periodicals and related websites to form the related literature and find the gap to make the present study relevant.

The researcher has collected primary data through a well-structured questionnaire from 300 online buyers in the Mumbai region. The questionnaire was administered through Google docs. The researcher has asked questions based on factors related to the product, employee behaviour and services and finance. The data for secondary sources have been taken from the published sources. The researcher has collected primary data from the periods 15th September 2020 to 25th September 2020. Some research data may be missing or noisy, which is required to be clean up. For the present research study, the researcher has done data cleaning as the collected research data were screened, no missing values were found.

Table 2 Case Processing Summary
N		%
Cases	Valid	300	100.0
Excludeda 0 .0
	Total	300	100.0
a. Listwise deletion based on all variables in the procedure.

For the present research for the normality test, the result of Normality of Data using Kolmogorov-Smirnov and Shapiro-Wilk is as follow. (Table 3)

Table 3 Tests of Normality By Kolmogorov-Smirnov = (D) and Shapiro-Wilk = (W)
E-Commerce		Kolmogorov-Smirnova			Shapiro-Wilk
		Statistic	df	Sig.	Statistic	Df	Sig.
P1	Amazon	.341	100	.000	.708	100	.000
	Flipkart	.334	100	.000	.674	100	.000
	Snapdeal	.268	100	.000	.758	100	.000
P2	Amazon	.324	100	.000	.786	100	.000
	Flipkart	.300	100	.000	.733	100	.000
	Snapdeal	.327	100	.000	.787	100	.000
P3	Amazon	.367	100	.000	.764	100	.000
	Flipkart	.324	100	.000	.749	100	.000
	Snapdeal	.356	100	.000	.775	100	.000
P4	Amazon	.218	100	.000	.843	100	.000
	Flipkart	.292	100	.000	.687	100	.000
	Snapdeal	.245	100	.000	.828	100	.000
P5	Amazon	.235	100	.000	.843	100	.000
	Flipkart	.305	100	.000	.756	100	.000
	Snapdeal	.242	100	.000	.839	100	.000
EBS1	Amazon	.197	100	.000	.870	100	.000
	Flipkart	.376	100	.000	.690	100	.000
	Snapdeal	.199	100	.000	.865	100	.000
EBS2	Amazon	.261	100	.000	.842	100	.000
	Flipkart	.339	100	.000	.729	100	.000
	Snapdeal	.268	100	.000	.845	100	.000
EBS3	Amazon	.341	100	.000	.708	100	.000
	Flipkart	.334	100	.000	.674	100	.000
	Snapdeal	.268	100	.000	.758	100	.000
EBS4	Amazon	.324	100	.000	.786	100	.000
	Flipkart	.300	100	.000	.733	100	.000
	Snapdeal	.327	100	.000	.787	100	.000
EBS5	Amazon	.367	100	.000	.764	100	.000
	Flipkart	.324	100	.000	.749	100	.000
	Snapdeal	.356	100	.000	.775	100	.000
F1	Amazon	.218	100	.000	.843	100	.000
	Flipkart	.292	100	.000	.687	100	.000
	Snapdeal	.245	100	.000	.828	100	.000
F2	Amazon	.235	100	.000	.843	100	.000
	Flipkart	.305	100	.000	.756	100	.000
	Snapdeal	.242	100	.000	.839	100	.000
F3	Amazon	.197	100	.000	.870	100	.000
	Flipkart	.376	100	.000	.690	100	.000
	Snapdeal	.199	100	.000	.865	100	.000
F4	Amazon	.261	100	.000	.842	100	.000
	Flipkart	.339	100	.000	.729	100	.000
	Snapdeal	.268	100	.000	.845	100	.000
a. Lilliefors Significance Correction

The researcher has conducted Cronbach’s Alpha to calculate the reliability of factor-variables as follow. (Table 4)

Table 4 Reliability Statistics Related to Products
Factors	Cronbach’s Alpha	No. of Items	Results in Terms ofInternal Consistency
Related to products	0.923	5	Excellent
Related to employee Behaviour and services	0.936	5	Excellent
Related to finance	0.855	4	Good

The researcher has analyzed the present data by using SPSS 21 to study the objectives and testing the hypotheses of the present study. The researcher has used the Kolmogorov-Smirnov and Shapiro-Wilk test of normality. The researcher has used Cronbachs’ Alpha, to test Data Reliability. Descriptive Statistics-frequency and per cent count, Kruskal-Wallis 1-Way ANOVA on Rank, Chi-square.

Analyses and Interpretation

The researcher has collected data related to the demographic profile (Frequency and per cent count) and satisfaction level (Likert Five Point Scale) of online buyers. The collected data were analysed using descriptive statistics and inferential analysis.

Descriptive Data Analysis

The researcher has used descriptive analysis to describe collected data in a logical order, as the demographic profile of Amazon, Flipkart and Snapdeal respondents, is as follow.

Table 5 Demographic Profile-Frequency and Per Cent Count
Particulars	Frequency	Frequency	Frequency
	Amazon	Flipkart	Snapdeal
Gender:
Male	49	55	57
Female	51	45	43
Age:
Up to 20 Year	26	34	28
20 to 40 Year	33	18	24
40 to 60 Year	30	32	41
60 Years and above	11	16	7
Marital Status:
Married	34	34	30
Unmarried	49	46	53
Divorced\Separated	17	53	17
Educational Qualification:
Undergraduates	43	30	26
Postgraduates	31	36	34
Other	26	42	25
Employment Status:
Housewife\House maker	5	4	3
Students	6	6	7
Businessmen	27	29	39
Professional	41	43	39
Profession	21	18	12
Annual Income:
Up to Rs. 2, 50,000 lac	28	27	35
Rs. 2, 50,000 lac to Rs. 5, 00, 000	24	43	23
Above Rs. 5,00,000	14	29	47
Price of Goods (Compared to Local):
Higher	42	28	27
Lower	29	36	37
Same	29	36	36
Frequency of Purchases:
Once in Fortnight	26	17	16
Once in a Month	25	36	40
Quarterly	28	30	27
Seasonal\Discounts	21	17	17

The Nature of Products Preferred to be Purchased

There are varieties of products available on e-commerce. The graphical presentation of the nature of products preferred to be purchased by the online buyer has presented as follow.

It is observed from the above graph that most online buyers prefer to buy clothing and accessories, household and basics and electronics products.

Satisfaction Level Related to Products, Employee Behaviour and Services and Finance

There is a significant difference in the satisfaction level of online buyers. The frequency-per cent count and graphical presentation of satisfaction level (related to Products, Employee Behaviour and Services and Finance) of the online buyer have presented as follow.

Table 6 Satisfaction Level Related to Products, Employee Behaviour and Services And Finance
Factors Related to Satisfaction	Frequency (1 = Highly Dissatisfied to5 = Highly Satisfied)														Total (%)
Related toProducts	1	percent		2		percent	3	percent		4	percent		5	percent
P1	23	7.7		40		13.3	7	2.3		67	22.3		163	54.3	300(100)
P2	42	1.7		23		7.7	7	2.3		123	41		105	35	300(100)
P3	40	13.3		15		5	15	5		165	55		65	21.7	300(100)
P4	11	3.7		16		5.3	47	15.7		98	32.7		128	42.7	300(100)
P5	2	7		19		6.3	56	18.7		95	31.7		128	42.7	300(100)
Related to Employees Behavior and Services
EBS1	8		2.7		20	6.7	55		18.3	91	30.3	126		42	300(100)
EBS2	18		6		27	9	31		10.3	107	35.7	117		39	300(100)
EBS3	23		7.7		40	13.3	7		2.3	67	22.3	163		54.3	300(100)
EBS4	42		14		23	7.7	7		2.3	123	41	105		35	300(100)
EBS5	40		13.3		15	5	15		5	165	55	65		21.7	300(100)
Related to Finance
F1	11		3.7		16	5.3	47		15.7	98	32.7	128		42.7	300(100)
F2	2		7		19	6.3	56		18.7	95	31.7	128		42.7	300(100)
F3	8		2.7		20	6.7	55		18.3	91	30.3	126		42	300(100)
F4	18		6		27	9	31		10.3	107	35.7	117		39	300(100)

The researcher has presented the above data related to satisfaction level, in the following graphical way.

Inferences Analyses on Satisfaction Level

H0: The satisfaction levels of online buyers related to products from Amazon, Flipkart and Snapdeal are not significantly different.

To find out the significant difference, the researcher has conducted a Chi-square test.

Table 7 Calculation of Chi-Square Value - To Measure Statistical Significance Difference In Satisfaction Level Related To The Product (P)
Products	VAR0001	VAR0002	VAR0003	VAR0004	VAR0005
Chi-Square	253.933a	174.933a	258.333a	176.233a	181.833a
Df	2	2	2	2	2
Table Value	5.99	5.99	5.99	5.99	5.99
Asymp. Sig.	.000	.000	.000	.000	.000
Result	P(Χ2(253.933)> 5.99) = .000< 0.05	(Χ2(174.93 3) >5.99) = .000 < 0.05	P (Χ2(258.33 3) > 5.99) =.000 < 0.05	(Χ2(176.23 3a) > 5.99) = .000 <0.05	P (Χ2(181.8 33) > 5.99) = .000 <0.05
Sig.\Insig.	SignificantHa Accepted	SignificantHa Accepted	Significant Ha Accepted	SignificantHa Accepted	SignificantHa Accepted
a. 0 cells (0.0%) have expected frequencies less than 5.The minimum expected cell frequency is 60.0.

The table above shows that the Chi-square calculated value is greater than its table value and its significance value is less than 0.05 i.e. a 5% loss. This shows that there is a significant difference in the satisfaction level of online buyers related to products from Amazon, Flipkart and Snapdeal. Hence, Ha (Alternate Hypothesis) is Accepted.

Further, deep into, compare and see the e-commerce, with which online buyers are more satisfied the researcher has conducted Kruskal-Wallis 1-Way ANOVA as follow.

Table 8 Kruskal-Wallis 1-Way Anova Mean Rank Related To The Product (P)
Product	E-commerce	N	Mean Rank
P1	Amazon	100	148.86
	Flipkart	100	165.29
	Snapdeal	100	137.36
	Total	300
P2	Amazon	100	133.65
	Flipkart	100	185.35
	Snapdeal	100	132.51
	Total	300
P3	Amazon	100	132.80
	Flipkart	100	185.65
	Snapdeal	100	133.05
	Total	300
P4	Amazon	100	136.30
	Flipkart	100	174.39
	Snapdeal	100	140.82
	Total	300
P5	Amazon	100	138.96
	Flipkart	100	172.47
	Snapdeal	100	140.08
	Total	300

The table above shows that there is a difference in the Mean Rank of satisfaction level of online buyers from Amazon, Flipkart and Snapdeal. From the above Mean Rank, it is observed that the online buyer from Flipkart found to be more satisfied than Amazon and Snapdeal.

H0: The satisfaction level of online buyers related to employee’s behaviour and services from Amazon, Flipkart and Snapdeal is not significantly different.

To find out the significant difference, the researcher has conducted Chi-square.

Table 9 Calculation of Chi-Square Value - To Measure Statistical Significancedifference in Satisfaction Level Related To Employees Behaviour And Services (EBS)
	VAR00011	VAR00012	VAR00013	VAR00014	VAR00015
Chi-Square	35.720	27.828	6.345	27.365	30.004
Df	2	2	2	2	2
Table Value	5.99	5.99	5.99	5.99	5.99
Asymp. Sig.	.000	.000	.042	.000	.000
	P(Χ2(35.720)	P(Χ2(27.828)	P(Χ2(6.345)	P(Χ2(27.365)	P(Χ2(30.004)
Results	> 5.99) =	> 5.99= .000	> 5.99) =	> 5.99) =	> 5.99) =
	.000 < 0.05	< 0.05	.042 < 0.05	.000 < 0.05	.000 < 0.05
Sig.\Insig.	Significant	Significant	Significant	Significant	Significant
	Ha Accepted	Ha Accepted	HaAccepted	Ha Accepted	Ha Accepted
a. Kruskal Wallis Testb. Grouping Variable: E-Commerce

The table above shows that the Chi-square calculated value is greater than its table value and its significance value is less than 0.05 i.e. a 5% loss. This shows that there is a significant difference in the satisfaction level of online buyers related to employee behavior and services from Amazon, Flipkart and Snapdeal. Hence, Ha (Alternate Hypothesis) is accepted.

Further, deep into, compare and see the e-commerce, with which online buyers are more satisfied the researcher has conducted Kruskal-Wallis 1-Way ANOVA as follow.

Table 10 Kruskal-Wallis 1-Way Anova Mean Rank Related To Employees Behaviour and Services (EBS)
Employee Behaviour and Services (EBS)	E-Commerce	N	Mean Rank
EBS1	Amazon	100	129.44
	Flipkart	100	190.45
	Snapdeal	100	131.61
	Total	300
EBS2	Amazon	100	133.98
	Flipkart	100	185.79
	Snapdeal	100	131.74
	Total	300
EBS3	Amazon	100	148.86
	Flipkart	100	165.29
	Snapdeal	100	137.36
	Total	300
EBS4	Amazon	100	133.65
	Flipkart	100	185.35
	Snapdeal	100	132.51
	Total	300
EBS5	Amazon	100	132.80
	Flipkart	100	185.65
	Snapdeal	100	133.05
	Total	300

The table above shows that there is a difference in the Mean Rank of satisfaction level of online buyers from Amazon, Flipkart and Snapdeal. From the above Mean Rank, it is observed that the online buyer from Flipkart was found to be more satisfied than Amazon and Snapdeal.

H0: The satisfaction levels of online buyers related to Finance from Amazon, Flipkart and Snapdeal are not significantly different.

To find out the significant difference, the researcher has conducted Chi-square.

Table 11 Calculation of Chi-Square Value - To Measure Statistical Significance
Finance	VAR000111	VAR000122	VAR000133	VAR000144
Chi-Square	13.032	10.891	35.720	27.828
Df	2	2	2	2
Table Value	5.99	5.99	5.99	5.99
Asymp.Sig.	.001	.004	.000	.000
	P(Χ2(13.032)>	P(Χ2(10.891)>	P(Χ2(35.720)>	P(Χ2(27.828)>
a. Kruskal Wallis Test b. Grouping Variable: ECOMMERCE

The table above shows that the Chi-square calculated value is greater than its table value and its significance value is less than 0.05 i.e. a 5% loss. This shows that there is a significant difference in the satisfaction level of online buyers related to finance from Amazon, Flipkart and Snapdeal. Hence, Ha (Alternate Hypothesis) is Accepted

Further, deep into, compare and see the e-commerce, with which online buyers are more satisfied the researcher has conducted Kruskal-Wallis 1-Way ANOVA as follow.

Table 12 Kruskal-Wallis 1-Way Anova Mean Rank Related To Finance (F)
Finance	E-commerce	N	Mean Rank
F1	Amazon	100	136.30
	Flipkart	100	174.39
	Snapdeal	100	140.82
	Total	300
F2	Amazon	100	138.96
	Flipkart	100	172.47
	Snapdeal	100	140.08
	Total	300
F3	Amazon	100	129.44
	Flipkart	100	190.45
	Snapdeal	100	131.61
	Total	300
F4	Amazon	100	133.98
	Flipkart	100	185.79
	Snapdeal	100	131.74
	Total	300

The table above shows that there is a difference in the Mean Rank of satisfaction level of online buyers from Amazon, Flipkart and Snapdeal. From the above Mean Rank, it is observed that the online buyer from Flipkart found to be more satisfied than Amazon and Snapdeal.

The Demographic Profile and Satisfaction Level of Online Buyers from Amazon, Flipkart and Snapdeal are not Significantly Associated.

To measure and compare the association between demographic profile and satisfaction level, the researcher has conducted a Chi-square test, the result is as follow.

Table 13 Calculation of Chi-Square Value - To Measure The Association Between Satisfaction Level and Demographic Profile
DemographicProfile	Chi-SquareValue	df	TableValue	Asymp.Sig.	Result		Sig.\Insig.
Gender	1.613a	1	3.84	0.204	P(Χ2(1.613) < 3.84)= .204 > 0.05		Insignificant Fails to Reject H0
Age	35.120b	3	7.82	0.000	P(Χ2(35.120) > 7.82)= .000 < 0.05		SignificantHa Accepted
Marital Status	44.240b	2		0.000	P(Χ2(44.240)>	5.99)	Significant Ha Accepted
			5.99		= .000 < 0.05
Educational Background	3.420b	2	5.99	0.181	P(Χ2(3.420) < 5.99)= .181 > 0.05		InsignificantFails to Reject H0
Employment Status	154.333a	4	9.49	0.000	P(Χ2(154.333) > 9.49) = .000 < 0.05		Significant Ha Accepted
AnnualIncome	47.760b	3	7.82	0.000	P(Χ2(47.760)>7.82) = .000 < 0.05		SignificantHa Accepted

An attempt has been made to tap into the potential e-marketplace and online customer base of sample e-commerce websites in the Mumbai region, not only to satisfy but also to retain online buyers over their competitors by considering the factor variables, which influences their satisfaction.

The researcher has extended the literature gap to validate and explore PEBSF factors i.e. the Products (P), the Employee Behaviour and Services (EBS) and the Finance (F) and its variables to make a unique business policy after considering online buyers’ satisfaction level and significant association between demographic profile and PEBSF.

Recommendations and Suggestions

1)The online buyer used to compare the price of goods with local shops. Hence, their preference may differ. E-commerce has to offer discounts accordingly.

2)The e-commerce must provide loyalty points and\or it’s easy to redeem.

3)E-commerce should expand its tie-up in smaller towns and the rural area also.

4On the new launch of product stock out situation arises, which is required to be monitored and handled accordingly.

5)E-commerce should expand brand choice for brand-conscious online buyers.

6)Cash on delivery is the most preferred mode of payment, due to online phishing and fraud.

7)This should be secured through a payment gateway.

8)Artificial Intelligence (AI) should be in use to monitor the nature and brand purchased in past to recommend and save time for an order.

Conclusion

The present research paper has discussed research questions related to the satisfaction level of online buyers (with respect to products, employee behaviour and finance) from Amazon, Flipkart and Snapdeal. The researcher has undertaken an integrative approach for both, Literature Reviewed and Survey. In the digital era, e-commerce is not an exception. The demographic profile shows; irrespective of age, gender, employment status, income level, the online buyers are intense. They do compare the price of goods on e-commerce with that of the local shop. On average the frequency of buying online is neutral. However, there is a significant difference in the nature of products preferred to be purchased online.

It is found that there is an overall statistically significant difference in the satisfaction level of online buyers. By conducting K-W One Way ANOVA, it is found that the buyers from Flipkart are more satisfied than that of Amazon and Snapdeal. The gender and educational background were found to be insignificant. The age, marital status, employment status and annual income were found significantly different among online buyers.

In the digital era, e-commerce is not an exception. The demographic profile shows; irrespective of age, gender, employment status, income level, the online buyers are intense. They do compare the price of goods on e-commerce with that of the local shop. On average the frequency of buying online is neutral. However, there is a significant difference in the nature of products preferred to be purchased online.

It is found that there is an overall statistically significant difference in the satisfaction level of online buyers. By conducting K-W One Way ANOVA mean rank, it is found that the buyers from Flipkart are more satisfied than that of Amazon and Snapdeal. The gender and educational background were found to be insignificant. The age, marital status, employment status and annual income were found significantly different among online buyers.

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