Article Metrics

An Analytical Study on Consumer Behavior Pertaining to e-Markets

Madhuri Thakur
Telangana Mahila Vishwa Vidhyalayam, Koti, Hyderabad, Telangana.

ABSTRACT

As the world is moving towards digitalization, the e-commerce sector has experienced a big jump in a short tenure. This has increased the number of e-commerce companies competing with each other to capture the market share. The rapid increase in the number of online buyers, hike in mobile penetration including in tier 2 & tier 3, secure payment gateways, low entry & exit barriers, tremendous increase in demand and enhanced logistics are the some of the major contributors proliferating the online market. In the coming years, it is expected that the e-commerce sector will flourish to the next level.
Purpose: To study the consumer behavior of men and women towards the digital markets.
Design: The primary data is collected from 131 customers from Telangana State using Google Forms. The questionnaire is divided into two parts. The first part contains data collection on demographic profiles. The second part collects specific information about the Fintech services availed by the customers. For general information nominal and ordinal measurements are used. A few variables are measured through dichotomous questions and the remaining variables are measured through a 5-point Likert scale. The collected data is processed and frequencies cross-tabulation and Chi-square tests are used to know if there is any significant difference in the behavior of male and female consumers over digital markets.
Findings: Four hypotheses were constructed to test if there is any significant difference in the behavior of men and women over digital markets. The data was collected from the respondents from 4 attributes i.e., E-Enjoyment, E-Distrust, E-Offers and E-Price .Each attribute was subdivided into five questions. All the four hypotheses have been rejected implying that there is significant difference in the opinions and behavior of males and females on digital markets.

---

Received: Oct 3, 2022 | Accepted: Dec 10, 2022 | Published: Jan 5, 2023

Keywords: Digital markets, Consumer Behavior, e-Enjoyment, e-Distrust, e-Offers and e-Price.

Citation: Madhuri Thakur (2023) An Analytical Study on Consumer Behavior Pertaining to e-Markets. KMICS Journal of Commerce and Management, 1(1). https://doi.org/10.62011/kmicsjcm.2023.1.1.6

Correspondence: madhurithakur03@gmail.com

Competing interests: The author has declared that no competing interests exist.

Copyright: © 2023 Madhuri Thakur. This is an open-access article. The use, distribution, and reproduction of this article in any medium is unrestricted, provided the original author and source are cited.

---

INTRODUCTION

As the world is moving towards digitalization, the e-commerce sector has experienced a big jump in a short tenure. This has increased the number of e-commerce companies competing with each other to capture the market share. The Rapid increase in the number of online buyers, hike in mobile penetration including in tier 2 & tier 3, secure payment gateways, low entry & exit barriers, tremendous increase in demand and enhanced logistics are some of the major contributors proliferating the online market. In the coming years, it is expected that the e-commerce sector will flourish to the next level. The online apparel industry is expected to increase at an annual growth rate of 10.6% until 2022. According to the statistical report, the compound annual growth rate for retail e-commerce sales in India is expected to reach 13.1% by 2024. The current penetration of the online industry stands at 28% in India. Global online retail sales are expected to reach 6,388 billion US dollars by 2024. Cheap labor availability, low prices of raw material, and supportive government policies are some of the factors uplifting the Indian retail industry as a whole.

Factors Influencing Consumer Buying Behaviour

With a sudden spike in online shoppers, there is a need to study the needs and buying behavior of online buyers. Many models and theories were identified in the literature on online consumer behavior. “The online consumer has the double identity, a shopper and a computer user.  The intention to return or re-purchase strongly depends on e-enjoyment and perceived site usability indicated. Nine parameters that are relevant for identifying an online consumer’s purchase behavior are: quality of personalization, shopping enjoyment, persuasion, price, promotion, service quality, store brand sensitivity, shopping enjoyment, intention to purchase and innovativeness. Pandey and Chawla created a six-factor scale: e-enjoyment, e-distrust, e-self inefficacy, e-logistic concerns, e-negative beliefs and e-offers, in order to study an Indian online consumer.

• E-Enjoyment – It comprises all the benefits and ease that e-shopping provides to the consumer. It considers pleasure, arousal & attitude, or approach as the indicators of online shopping satisfaction. Similarly, some researchers consider time-saving & cost-saving while some other researchers consider content, exactness, layout, user-friendliness, and timeliness as the pointers of online shopping satisfaction.

• E-distrust –It is defined as the trust associated with e-shopping. Consumers are skeptical about e-shopping and therefore avoid sharing their personal details. Pradas reported that the most commonly discussed barrier to the budding consumers involved in online shopping is the need to tangibly see the item for consumption before making a purchase followed by fears pertaining to data security, the safety of e-commerce, and unreliability of payment structures.

• E- Offers– The offers and the discounts offered to the consumers have a positive impact on the buying behavior of the consumers.  Cash or price discount is one of the most commonly practiced techniques of sales promotion. This technique plays an imperative role in the purchase behavior of a consumer.

• E-Price – The price of the product affects the buying behavior of the consumers. As far as consumer choice is concerned, price plays a crucial role then repeatedly accredited to it and is also viewed as a seminal factor.

Theoretical definition of the parameters and item creation for Consumer Buying behavior

Parameter	Definition	Items
E-Enjoyment	It comprises of all the benefits & ease that e-shopping provides to the consumer	• Item 1: Fun of using website • Item 2: Ease of use • Item 3: Online variety • Item 4: Product Quality & Info • Item 5: website design
E-Distrust	It is defined as the trust associated in e-shopping. Consumers are skeptical about e-shopping and avoid sharing their personal details.	• Item 1: Security Concerns • Item 2: E-Privacy • Item 3: Internet Distrust • Item 4: E- Shopping Risk • Item 5: Return Policy
E-Offers	The offers provided to online consumers in context of variety coverage and discounts, which elicits a positive consumer buying behavior.	• Item 1: Special Offers • Item 2: Online Vs Offline Offers • Item 3: Brand offer comparison • Item 4: Banner Ads • Item 5: Online Product Availability
E-Price	It is the amount that the consumer spent in purchasing the product online.	• Item 1: High Price Risk • Item 2: Price vs Quality • Item 3: Impulse Buying • Item 4: Value for Money • Item 5: Price vs Quantity

Review of Literature

S.No.	Author & Year	Focus	Findings
1.	Rai, 2017	Consumer Buying decision	For the progress of digital channels in the consumer buying decision, shopping via digital media is reflected to be an optimistic indication as consumer seems to be satisfied with the purchase they have made.
2.	Lodhi and Shoaib, 2017	Consumer buying behavior	Internet security has a substantial bond with consumer virtual buying behavior E-Marketing is the future of Marketing
3.	Sharma, 2017	Digital Marketing	Well-read Individuals are aware of the electronic channel and choose to buy from there.
4.	Lodhi and Shoaib, 2017	E-marketing	All the independent E-marketing factors are evidently related to e-marketing; such as- print media marketing, Web marketing, Goods & services marketing FMCG marketing, Electronic media marketing, E- marketing, Global marketing.
5.	Afzal, 2015	consumer buying behavior	Factors influencing consumer buying behavior are- design of the product Quality of the product Content of advertisement Loyalty of consumer Past purchase experience
6.	Park & Lennon, 2009	Brand image and apparel industry	A robust brand name has an encouraging influence on the virtual store image and observed importance, which results into buying intent in the virtual purchase of apparel.
7.	Kim, 2015	Online shopping	To be competitive, it is vital for the web-based shopping industry to understand and identify as to what customers take note of and what make them repeat their purchase.
8.	Rhee & Johnson, 2012	Apparel industry and brand image	In apparel articles figurative feature is vital as it represents self- image.

OBJECTIVES OF THE STUDY

1. To study the behavior of male and female consumers in Digital markets.
   1. To study the behavior of male and female consumers on e-Enjoyment while using digital markets.
   1. To study the behavior of male and female consumers in e-Distrust on digital markets.
   1. To study the behavior of male and female consumers on e-Offers in digital markets.
   1. To study the behavior of male and female consumers on e-Price offered on digital markets.

RESEARCH METHODOLOGY

The primary data is collected from 131 customers from Telangana State using Google Forms. The questionnaire has two parts. The first part contains data collection on demographic profiles. The second part collects specific information about the perception of consumers on digital markets. For general information, nominal and ordinal measurements are used. A few variables are measured through dichotomous questions and the remaining variables are measured through a 5- point Likert scale. The collected data is processed and frequencies, cross-tabulation, and Chi-square tests are used to know if there is any significant difference among male and female customers in the usage of Digital Markets. SPSS 22 version software was used to run the test results.

HYPOTHESES OF THE STUDY

H01: There is no significant difference in the opinion of male and female customers on e-Enjoyment on Digital Markets.

H02: There is no significant difference in the opinion of male and female customers on e-Distrust on Digital Markets.

H03: There is no significant difference in the opinion of male and female customers on e-Offers offered on Digital Markets.

H04: There is no significant difference in the opinion of male and female customers on e-Price on Digital Markets.

Attributes of the Study

1.e-ENJOYMENT:

1. Fun using Website.
2. Ease of use.
3. Online Variety is more.
4. Adequate information on Product quality
5. Website Design is attractive.

2.e-DISTRUST:

1. Security Concerns.
2. E-Privacy.
3. Internet Distrust.
4. E-Shopping Risk.
5. Return Policy.

3.e-OFFERS

1. Special Offers attract.
2. Online offers vs. Offline offers.
3. Brand offer comparison.
4. Banner Advertisements.
5. Online Product availability.

4.e-PRICE:

1. High Price Risk.
2. Price and Quality comparison.
3. Impulsive Buying.
4. Value for money
5. Price and Quantity

Sample Profiling: Data pertaining to 131 consumers comprising different demographic profiles is collected. 

RESULTS

Gender of the consumer

Gender		Frequency	Percent
Valid	Male	39	29.8
	Female	92	70.2
	Total	131	100.0

From table no.1 it can be observed that the number of female consumers outnumber the males. The male consumers account for 29.8%, whereas the females account for 70.2% of the total respondents.

Age group of the conusmer

Age		Frequency	Percent
Valid	Less than 25 Years	8	6.1
	26-35Years	8	6.1
	36-45 Years	85	64.9
	More than 45 Years	30	22.9

Table no.2 depicts the data relating to the age-wise composition of the respondents. The majority of the consumers fall in the age group of 36-45 years with 65% followed by 23% of the respondents who are more than 45 years of age.

Marital Status of the consumer

Marital Status		Frequency	Percent
Valid	Married	119	90.8
	Unmarried	12	9.2
	Total	131	100.0

From table no.3, among the total 131 respondents, 119(91%) are married women and 12(9%) are unmarried.

Monthly Income group of the consumer

Monthly Income		Frequency	Percent
Valid	Less than Rs.15000	8	6.1
	15000-25000	38	29.0
	26000-50000	34	26.0
	More than 50000	51	38.9
	Total	131	100.0

Table no.4 depicts the data relating to the Monthly income-wise composition of the respondents. Majority of the respondents (39%) are earning monthly income more than Rs.50000/-followed by 55% of the respondents who earn in between Rs.15000 and Rs.50000/-.

Reliability test to see the internal consistency in the data

Cronbach’s Alpha	N of Items
0.794	34

The result from table no. 5 revealed that Cronbach’s Alpha coefficient for 34 items is 0.794, suggesting that the items have relatively high internal consistency and are worthy of retention and hence considered for the study. According to Bland J, Altman, Reliability coefficient of    0.70 or higher is considered “acceptable ”in most of the social  science research situations.

Opinions of male and female users on ‘e-Enjoyment’ while using the Digital Markets

As per null hypothesis, there is no significant difference in the opinion of the male and female customers on e-Enjoyment while using the Digital Markets. The data has been tested with the help of Chi-Square Test adopting a 5% (0.05) level of significance.

Gender	SD	%	D	%	N	%	A	%	SA	%	Total	%	Chi-Square  Test Results
Male	14	7.18	37	18.9	86	44.10	20	10.25	38	19.48	195	100	Value:40.09 Df:4
Female	74	16.08	76	16.52	111	24.13	117	25.43	82	17.8	460	100
Total	88	13.4	113	17.25	197	30.07	137	20.9	120	18.32	655	100

The Chi-Square table value is 9.89 at 4 degrees of freedom. Since the calculated value of Chi-Square is 40.09, which is more than the table value, the null hypothesis is rejected. Hence, there is a significant difference in the opinions of male and female users on ‘e-Enjoyment while using the Digital Markets’.

Opinions of male and female users on ‘e-Distrust’ on Digital Markets

As per null hypothesis, there is no significant difference in the opinion of male and female customers on e-Distrust on digital markets. The data has been tested with the help of Chi-Square Test adopting 5% (0.05) level of significance.

Gender	SD	%	D	%	N	%	A	%	SA	%	Total	%	Chi-Square  Test Results
Male	14	7.18	12	6.15	98	50.25	7	3.59	64	32.82	195	100	Value:106.05   Df:4
Female	24	5.21	72	15.65	90	19.56	152	33.04	122	26.52	460	100
Total	38	5.80	84	12.82	188	28.70	159	24.27	186	28.39	655	100

The Chi-Square table value is 9.89 at 4 degrees of freedom. Since the calculated value of Chi-Square is 106.05, which is more than the table value, the null hypothesis is rejected. Hence, there is a significant difference in the opinions of male and female users on ‘e-Distrust on Digital Markets’.

Opinions of male and female customers on e-Offers at Digital Markets.

As per null hypothesis, there is no significant difference in the opinion of male and female customers on e-Offers. The data has been tested with the help of Chi-Square Test adopting 5% (0.05) level of significance.

Gender	SD	%	D	%	N	%	A	%	SA	%	Total	%	Chi-Square  Test Results
Male	8	4.12	51	26.13	103	52.82	12	6.15	21	10.76	195	100	Value:28.49 Df:4
Female	34	7.39	79	17.17	193	41.95	88	19.13	66	14.34	460	100
Total	42	6.41	130	19.84	296	45.19	100	15.26	87	13.28	655	100

The Chi-Square table value is 9.89 at 4 degrees of freedom. Since the calculated value of Chi-Square is 28.49, which is more than the table value, the null hypothesis is rejected. Hence, there is a significant difference in the opinions of male and female users on ‘e-Offers offered on Digital Markets”.

Opinions of the male and female customers on e-Price at Digital Markets

As per null hypothesis, there is no significant difference in the opinion of the male and female customers on e-Price offered at Digital Markets. The data has been tested with the help of Chi-Square Test adopting 5% (0.05) level of significance.

Gender	SD	%	D	%	N	%	A	%	SA	%	TOTAL	Chi-Square Test Results
Male	33	16.92	26	13.33	121	62.05	11	5.64	4	2.05	195	Value:25.97 Df:4
Female	58	12.60	130	28.26	211	45.86	34	7.39	27	5.86	460
Total	91	13.8	156	23.81	332	50.68	45	6.87	31	4.73	655

The Chi-Square table value is 9.89 at 4 degrees of freedom. Since the calculated value of Chi-Square is 25.97, which is more than the table value, the null hypothesis is rejected. Hence, there is a significant difference in the opinions of male and female users on ‘e-Price offered at Digital Markets”.

Ranking based on Weighted Mean to identify highest difficulty ratings

In order to find out the variables that have the highest difficulty ratings, weighted scores of the ‘Likert’ scale have been calculated. The ranges to measure the constraints are grouped based on scales developed by Brown (2010). The statement wise weighted score for difficulty level is calculated using the following formula:

[N(SD) * (1) + N(D) * (2) + N(N) * 3 +N(A) * (4) + N(SA)*5]/N(R)]

Where N(SD) = No. of respondents selecting strongly disagree N(D) = No. of respondents selecting disagree N(U) = No. of respondents selecting neutral N(A) = No. of respondents selecting agree N(SA) = No. of respondents selecting strongly agree N(R) = Total number of respondents (Kostoulas,2013).

Attributes effecting e-Enjoyment

S.no.	Attributes	SD	D	N	A	SA	Weighted  Average	Ranking*
	Its fun using website	4	19	29	29	50	3.78	1
	Ease of use	19	18	47	26	21	3.09	2
	Online variety	22	18	48	18	25	3.05	3
	Product quality information	12	30	42	34	13	3.05	4
	Website design	31	28	31	22	19	2.77	5

From table no.11, it is evident that out of all the factors, the factor which contributes mostly is, ‘Its fun of using the website’, which is ranked first, which is followed by ‘ease of use’ which is ranked second. ‘Online variety’ was ranked third, and ‘Product quality information’ was ranked fourth.    ‘website design’ is the last ranked factor among all the factors in the e-enjoyment.

Attributes influencing the e-distrust

S.no.	Attributes	SD	D	N	A	SA	Weighted  Average	Ranking*
	Security concerns	6	11	40	27	47	3.75	1
	e-Privacy	8	12	31	41	39	3.69	2
	Internet Distrust	8	11	32	43	37	3.69	2
	e-Shopping risk	5	22	43	29	32	3.47	4
	Return policy	11	28	42	19	31	3.24	5

From table no.12 it can be analyzed that the most important parameter which influenced on the respondents was found to be the security concerns, which has the highest weighted average of 3.75. The next two important factors, which caused distrust were privacy and internet distrust, which were ranked second and fourth respectively. The last ranked factor was the return policy which also contributed to e-distrust.

Attributes effecting e-Offers

S.no.	Attributes	SD	D	N	A	SA	Weighted  Average	Ranking*
	Special Offers	6	21	52	35	17	3.27	1
	Online Vs. Offline offers	8	15	75	12	21	3.18	2
	Brand Comparison	8	28	58	14	23	3.12	3
	Banner Ads	6	37	57	18	13	2.96	4
	Online Product Availability	14	29	54	21	13	2.92	5

From table no.13 it can be clearly understood that the most common and ranked first attribute was special offers, and then it is the online offers with a weighted average of 3.18 followed by brand comparison and product availability as the last ranked factor with a weighted average of 2.92.

Attributes effecting e-Price

S.no.	Attributes	SD	D	N	A	SA	Weighted  Average	Ranking*
	High Price Risk	7	34	66	11	13	2.92	1
	Price Vs. Quality	6	30	75	14	6	2.88	2
	Impulse  Buying	15	28	74	8	6	2.71	3
	Value for money	31	30	59	5	6	2.43	4
	Price Vs. Quantity	32	34	58	7	0	2.31	5

From table no. 14, it can be analyzed that the respondents are adopting different methods to get the maximum benefit from the digital markets. The majority of consumers are mostly bothered by the risk associated with online buying which is ranked first among all the factors. The last factor is the quantity they get from digital markets is the least ranked.

Summary & Findings of the Study

There were 4 hypotheses that were constructed to test if there is any significant difference in the opinions of men and women on Digital markets. The respondents were given questions on 4 attributes i.e., e-Enjoyment, e-Distrust, e-Offers, and e-Price.

 All four null hypotheses have been rejected implying that there is a significant difference in perceptions of males and females on Digital Markets. As all of the hypotheses stand rejected, it may be concluded that there is significant difference in the opinions of the respondents, either male or female on e-Enjoyment, e- Distrust, e-Offers, and e-Price offered on digital markets.

The Weighted average calculated shows that the most important factors which impact the online buying behavior of consumers in the digital markets is, the fun in using the website, the security concerns, the special offers given online, and the risk of purchasing online. If all the issues are addressed, then the consumers will be more satisfied and happy transacting online.

REFERENCES

1. Erik Qualman (2013), Socialonomics, How Social Media Transforms the Way We Live and Do Business, John Wiley and Sons.
2. Lages, Luis Filipe Lages José LuísAbrantes Cristiana Raquel Lages, (2008),”The STRATADPT scale”, International Marketing Review, Vol. 25 Iss 5 pp. 584 – 600.
3. Chitra Sharma, “Consumer buying behaviour towards online shopping – A Review of literature”, Indian journal of applied research, Volume (5), Issue: 4, April 2015, ISSN – 2249-555X.
4. Bandyopadhyay, D. Sen, J. (2011) Internet of Things: Applications and Challenges in Technology and Standardization, Wireless Personal Communications, Volume 58, Issue 1, pp 49–69.
5. Venkatesh, V. and Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Science, 39 (2), 273-312.
6. Abdul Brosekhan and C. MuthuVelayutham, 2008, An Empirical Study on Consumers Buying Behaviour towards Selected Home Appliance Products in Ramanathapuram, IOSR Journal of Business and Management (IOSR-JBM), PP 13-21.
7. Kotler, P. and Armstrong, G. (2012) Principles of Marketing. 14th Edition, Pearson Education Limited, Essex, England.
8. Shankar, Venkatesh and Inman, Jeffrey and Mantrala, Murali and Kelley, J. Eileen and Rizley, Ross, Innovations in Shopper Marketing: Current Insights and Future Research Issues (2011). Journal of Retailing 87S (1, 2011) S29-S42; Mays Business School Research Paper No. 2012-59.
9. Kwak, H., Lee, C., Park, H. and Moon, S. (2010) What Is Twitter, a Social Network or a News Media? ACM: Proceedings of the 19th International Conference on World Wide Web, New York, 591-600.
10. Foux, G., (2006). Consumer-generated media: Get your customers involved. Brand Strategy, pg. no.38-39.
11. Russell S. Winer (2009), New Communications Approaches in Marketing: Issues and Research Directions, Journal of Interactive Marketing,Vol. 23,No.2, Pp-108-117.
12. Bhaskar Kumar,” Impact Of Digital Marketing And E-Commerce On The Real Estate Industry,” Impact: International Journal Of Research In Business Management, Vol. 2, Issue 7, Jul 2014, 1722.

---