Scholarly Research Journal for Humanity Science & English Language, Online ISSN 2348-3083, SJ IMPACT FACTOR 2019: 6.251, www.srjis.com PEER REVIEWED & REFEREED JOURNAL, FEB-MAR, 2021, VOL-9/44 SOCIAL COMMERCE & CONSUMER BEHAVIOUR Srinivasan Iyer, Ph. D. Associate Professor, SJJT University, Rajasthan
Paper Received On: 25 MAR 2021 Peer Reviewed On: 30 MAR 2021 Published On: 1 APRIL 2021 Content Originality & Unique: 100%
Abstract Social commerce is where efficient marketers make the best use of e-commerce and fuse it with social media. It is commercially called Social commerce but maybe it should be called "Do you want to make some money?" Social commerce is a $95.3 billion market right now. It's projected to grow to $806.4 billion in the next seven years. If you're a business with products to sell, this info probably makes you feel like that dollar-sign-eyes-green-tongue emoji. Curious about how you can get a chunk of that change? We've got you covered.
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What is social commerce? Social commerce is the process of selling products directly on social media. The process of entire purchase decision right from the discovery of the product to its post-consumption experience takes place on a different platform known as social commerce Currently, social apps that allow for social commerce include Instagram, Facebook, and Pinterest. With social commerce, you might see a pair of sweet strawberry-print clogs on your Instagram feed, hit "shop now" and complete the purchase right there in the app. or, one can spot a well-priced umbrella as they are searching through social platform These are shopping opportunities right on the digital platforms that your audience uses most. And you should be taking advantage of them. REVIEW OF LITERATURE Social Commerce is a new wave of internet marketing. There are several definitions of social commerce, Kim and park (2003) defined it as a subset of e-commerce, that the consumers are ready to generate content, share information, opinions, experiences, stories, habits to optimize Copyright © 2021, Scholarly Research Journal for Humanity Science & English Language
Dr. Srinivasan Iyer (Pg. 11028-11033)
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their buying decisions and from whom to accumulate to goods and services, where and when (Jascanu, Jascuna, & Nicolau,2007). IBM defines Social Commerce (cited in between The first component "People" is made from Social Commerce Acceptance, Attitudes, Motivational factors, roles played by consumers, and Community Ties. The Second component "Technology" includes Platforms and tools, Features to reinforce shopping experience, Product visualizations, and interaction, websites' basic features. The Third component "Business Strategies" contains Web 2.0 and marketing strategies, Social commerce new trends, Alternative revenue models, and Group and Collective Buying Strategies. Each component is taken into account as research interests for researchers, for instance; Curty and Zhang (2011) studied the technology perspective and the way it does impact the Social Commerce aspect, they found that E-commerce functions are essential for social commerce and Trust may be a mechanism that buyers put upright for any social content to follow it, like it, share it, review it and recommend it. Marketers are trying to find social commerce as a promising phenomenon that it's expected to realize US$30 Billion in revenue in 2015 Business tries to maximize them to speak with customers and to trace the interaction of consumers with one another. Nick Hajli (2012) has researched social commerce deeply and proposed an adoption model called it "Social Commerce Adoption model" which he tackles the recommendations and referrals, rating and reviews, Forums and Communities grouped as "Social Commerce Constructs" and the way it does affect Trust and Intention to RESEARCH METHODOLOGY The analysis was carried out based on Exploratory Research Design through primary data. The questionnaire for conducting the survey has been formulated. Likert Scaling's methodology is used to define the different characteristics needed to meet individual consumer needs. The data was gathered from 125 respondents in the Mumbai Area via Google Chrome of individuals taking social platforms for buying and selling. The SPSS20 uses various statistical tools such as descriptive analysis, factor analysis & chi-square to analyze the data OBJECTIVE To detect the connection between demographic variables and their behavior for social commerce To understand the contributing factors with consumer and social platform for buying and selling brands
Copyright © 2021, Scholarly Research Journal for Humanity Science & English Language
Dr. Srinivasan Iyer (Pg. 11028-11033)
11030
HYPOTHESIS H1: There seems to be a correlation between gender & buying behavior for brands H2: There seems to be a correlation between Age buying behavior through social commerce. H3: There seems to be a correlation between Marital Status buying behavior on the social platform Demographic Information
Gender Age
Marital Status Occupation
Income group
Total
Female Male 30-40 40-50 Above 50 Below 30 Married Unmarried Home Maker Self Employed Service Students 4-6 lakhs 6-10 lakhs Above 10 Lakhs Below 4 Lakhs
Frequency
Percent
52 73 20 33 22 50 76 49 24 38 31 32 36 23 19
41.6 58.4 16 26.4 17.6 40 60.8 39.2 19.2 30.4 24.8 25.6 28.8 18.4 15.2
47 125
37.6 100
Cumulative Percent 41.6 100 16 42.4 60 100 60.8 100 19.2 49.6 74.4 100 28.8 47.2 62.4 100
Copyright © 2021, Scholarly Research Journal for Humanity Science & English Language
Dr. Srinivasan Iyer (Pg. 11028-11033)
11031
FINDINGS & OBSERVATION Corelation between Demographic variable and behaviour Demographic Behavior
Result Correlation value
Gender
Do you look for branded products on social commerce platform?
Direct Relation 0.141656
Do you buy branded products online frequently
0.013703
Inverse Relation Direct Relation
-0.11586
Inverse Relation
-0.05234
Inverse Relation
0.072503
Direct Relation
Do you get influenced by social commerce promotion for buying products
0.06597
Direct Relation
You buy products for yourself or family
0.009329
-0.0638 Do you get influenced by social commerce promotion for buying products You buy products for yourself or family Age
Do you look for branded products on social commerce platform? Do you buy branded products online frequently
Occupation
Do you look for branded products on social -0.00172 commerce platform? Do you buy branded products online frequently -0.00677 Do you get influenced by social commerce promotion for buying products You buy products for yourself or family
Income
-0.16133
Do you look for branded products on social -0.00023 commerce platform? Do you buy branded products online frequently 0.044397 Do you get influenced by social commerce promotion for buying products You buy products for yourself or family
Marital Status
-0.00172
-0.00243 0.045794
Do you look for branded products on social 0.029922 commerce platform? Do you buy branded products online frequently -0.10317 Do you get influenced by social commerce promotion for buying products You buy products for yourself or family
0.079552 -0.12677
Direct Relation Inverse Relation Inverse Relation Inverse Relation Inverse Relation Inverse Relation Direct Relation Inverse Relation Direct Relation Direct Relation Inverse Relation Direct Relation Inverse Relation
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Dr. Srinivasan Iyer (Pg. 11028-11033)
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FINDINGS The research shows that demographic variable occupation, income group & education qualifications have a there is not a much stronger relationship between the products that they look for online or whether they're influenced by the promotion done on social commerce side but there is a reverse relationship between buying the products for themselves or the family on the priority basis During the study the following observations were made: There are many consumers, who are not aware of Social commerce and consumers who are aware of it are not able to distinguish it from internet shopping. Social commerce is gaining popularity among users especially youth. There is a wide scope of social commerce for promoting products shortly as today the entire generation is becoming tech-savvy It has become a strong platform for consumers to share their experiences and raise voice against the malpractices in the market. Social Commerce represents an important aspect of social learning by which consumers utilize the knowledge and experience of others they trust to influence their purchasing decision CONCLUSION It is concluded that no matter whatever strategies of marketing are adopted by social consumers or social commerce the impact of the consumer behaviour more or less remains the same they prefer buying more products through off-line shopping but they like to procure information for the same through online platforms such as Facebook Instagram and more to add do most of the social commerce sites have many promotional measures and schemes such as flash sales and the impact on the behaviour of the consumer more places in mind the same it was only during the pandemic time that customers were eager to buy the products from social platforms rather than visiting brick and mortar stores REFERENCES Social Troubles: Yes, You Can Succeed At F-Commerce." By Savitz, Eric Fazlyev, Ruslan "Figuring Out F-commerce. (cover story)" by parry & Tim "Explaining the power-law degree distribution in a social commerce network" By Andrew T. Stephen & Olivier Toubia "Deriving Value from Social Commerce Networks" By AndrewT. Stephen "Hope: An individual motive for social commerce" By Snyder, C. R.; Cheavens, Jennifer; Sympson, Susie C. Park, Chung-Hoon & Kim, Young-Gul. (2003). Identifying key factors affecting consumer purchase behavior in an online shopping context. International Journal of Retail & Distribution Management. 31. 16-29. 10.1108/09590550310457
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Amarasinghe, A. (2010). The emergence of truly social commerce websites. Retrieved March 25, 2011, from http://www.amisampath.com/2010/03/emergence‐of‐truly‐social‐commerce.html Ghose, A. & Ipeirotis, P. (2009). The EconoMining project at NYU: Studying the economic value of user‐generated content on the internet. Journal of Revenue and Pricing Management, 8 (2/3), 241– 246. Hedeker, D. & Gibbons, R. D. (2006). Longitudinal data analysis. University of Chicago, Chicago Holland, J., Thomson, R. & Henderson, S. (2006). Qualitative Longitudinal Research: A Discussion Paper. London South Bank University, London Immediate Future (2010). The explosion of social shopping. London, Retrieved from http://immediatefuture.co.uk/ Jascanu, N., Jascanu, V., & Nicolau, F. (2007). A new approach to E‐commerce multi‐agent systems. The Annals of "Dunarea De Jos" University of Galati: Fascicle VIII Electrotechnics, Electronics, Automatic Control and Informatics, 8–11.
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