Impact of Social Media on Consumer Buying Pattern

 

Anupama Sundar D ¹, Kavyashree M B ²

 

¹ Associate Professor, JSS Centre for Management Studies, JSS Science and Technology University, Mysuru, India

² Assistant Professor, JSS Centre for Management Studies, JSS Science and Technology University, Mysuru, India

 

1. INTRODUCTION

The eventful boom in the use of social media has given space for individuals to develop, generate and disseminate online videos on the wide variety of brands available in the marketplace. In the previous era, only business enterprises were developing a video advertisement and disseminating them. In the present scenario, consumer-generated advertisements have been shared with millions in an ample of time. Consumer-generated Videos are conceptualized as” the advertisements shared in a public platform, generated by individuals, focusing on a particular recognized brand in the marketplace” Campbell et al. (2011). Research work Nielsen (2012), indicates when compared to traditional advertisements, consumers rely on online reviews and trust their peers while making a choice on their purchase intentions. A few of the brands, face the challenge of power shifts, through these kinds of user-generated content. Consumers tend to use Web 2.0 interactive features, like posting comments and providing recommendations or ratings, which spurs conversations, and opinion sharing on brands in social media. In turn, it is convenient for consumers to disseminate messages about the brands in the form of electronic word of mouth. Research works on electronic word of mouth, indicates individuals tend to give their perceptions about brands and seek reviews from other members on a particular brand/product. Electronic word-of-mouth communication is a prominent tool that integrates quickly, is easy to access, has quality in the information shared, and also provides credibility Cheung (2012). As noted by, Hung, and Li (2007), consumers shared interests in common, involvement, and familiarity with a particular intended category and its advertisements.

 

2. LITERATURE REVIEW

Prominent research works pertaining to Consumer Generated Advertising and their outcomes are considered in the study. The credibility of source related to user generated content provides significant insight on consumer generated advertisements in terms of persuasion.  The degree of product involvement through Consumer generated advertisements depicts the interest in product categories, and their impact on consumers. The attitudes and behaviours of individuals towards the near filed communications and their impact on persuasion of messages received is broadly represented in Elaboration Likelihood model. As opined by, Ma and Agrawal (2007), Zhang (2006), source credibility is known to balance the asymmetry in information between the marketers and consumers. Source credibility is known to have two sub-dimensions: expertness and trustworthiness Tormala et al. (2007).  The degree to which a consumer is capable of performing tasks relevant to that topic and is qualified to discuss it is referred to as their level of expertise Alba and Hutchinson (1987), Bettman and Park (1980). According to Mccole (2002),being trustworthy is the capacity to accept or endorse something without further research or supporting documentation.

In the viewpoint of researchers, trustworthiness has received more attention as it plays a significant role in encouraging active participation and thus revealing the consumer’s personal information Han and Windsor (2011). When it comes to the internet environment, where customers actively search for, share, and comment on product-related information, source credibility for CGA is based on attitudes and behaviours. As reported by Nielsen (2012), Consumers' faith in traditional advertising is declining, while their trust in internet media is rising as a result of the latter's capacity to include such user reviews and postings. Web 2.0 has turned consumers into participants rather than the conventional target audiences, especially with social media.

As opined by Han and Windsor (2011), the factor of trust supports consumers to reveal information for the purpose of enhancing their reputations and thus adds credibility to the advertisements viewed by them. While encountering the counter attitudinal messages, it is likely for the consumers to establish physiological and psychological screens to retain the pre-existing attitudes Ahluwalia (2000).  When compared to the firm-generated advertisements, consumer generated advertisements appear to be more credible and trustworthy Lawrence and Fournier (2013), MacKinnon (2012), which is not the same in all cases. The credibility of the source from Consumer Generated Advertisements, outpaces the firm generated advertisements, to significantly influence the attitudes of consumers towards the brand and the advertisement Lawrence and Fournier (2013).  The consumers represent high level of trust for videos that provide reviews on a particular brand and product, since the review is from another consumer and not from the product manufacturer Ismagilova et al. (2020)

Electronic word of mouth communications tends to get associated with the behaviours and is positively influenced with Consumer Generated Advertisements. As opined by Chatterjee (2011), consumers more likely recommend the brand messages received from other consumers compared to the firm-generated messages. In contrast Ertimur and Gilly (2012), reported that, consumers critiques the quality of Consumer Generated Advertisements, and considered the source to be authentic and knowledgeable even though it lacked in expertise, credibility in designing the advertisements and the messages.

Thompson and Malaviya (2013), reported that, while evaluating the consumer generated advertisements that won the brand-sponsored contests, it was found that consumer critique the competence level of consumer generated advertisements, even after identifying themselves with the source.

The present study examines the responses of consumers towards Consumer Generated Advertisements.

 

3. OBJECTIVES OF THE RESEARCH

The focus of the research is to examine the impact of social media on consumer buying pattern Specific objectives of the study are:

1)     To investigate the perception of consumers towards online shopping.

2)     To examine the factors that tend to motivate consumers to shop through social media.

3)     To examine the degree of influence of social media towards buying behavior of consumers.

 

4. RESEARCH METHODOLOGY

The study was descriptive in nature. Self-administered questionnaire covering all the variables of the study was developed. Data was gathered from 65 respondents. The sample size was computed as indicated below. Substitution of value of p as 0.10, d as 0.05, and z as 1.96 is made. P is the probability of occurrence and q is probability of non-occurrence. E is standard error and z is confidence level. The sample size 139 thought to be adequate one. As there would be errors, 65 samples were considered.

 

 

Where, P is the probability of occurrence, q is probability of non-occurrence. E is the standard error and Z is the confidence level.

 

5. STATISTICAL ANALYSIS

The data and information was processed by using statistical package for social sciences (SPSS) software. KMO test to check the adequacy of the data, exploratory factor analysis, confirmatory factor analysis was conducted to discover and verify the factor structure.

 

6. CONCEPTUAL MODEL OF THE STUDY

Figure 1

                                                                      

Figure 1

 

7. HYPOTHESIS OF THE STUDY

7.1. COGNITION EFFECT

H0: There is no significant relation between the cognition effect and social media.

H1: There is a significant relation between the cognition effect and social media

Interactiveness

H0: There is no significant relation between the interactiveness and Cognition effect.

H2: There is a significant relation between the interactiveness and Cognition effect.

Physical Attraction

H0: There is no significant relation between the Physical Attraction and Cognition effect.

H3: There is a significant relation between the Physical Attraction and Cognition effect. Placement of the Product

H0: There is no significant relation between the Placement of the Product and Cognition effect. H4: There is a significant relation between the Placement of the Product and Cognition effect.

Website Design

H0: There is no significant relation between the Website Design and Cognition effect.

H5: There is a significant relation between the Website Design and Cognition effect.

 

 

Word of Mouth

H0: There is no significant relation between the Word of Mouth and Cognition effect.

H6: There is a significant relation between the Word of Mouth and Cognition effect.

 

8. DEFINITION OF VARIABLES

Interactiveness: a two-way electronic communication system which includes the actions of the users.

Physical attraction: The attitude of consumers towards a brand, product.

Placement of product: A type of advertising through which the branded products and services are featured targeting large audience.

Website design: Design of websites covering product related information easily accessible to consumers through internet.

Word of Mouth: A form of communication and information sharing spread by prospective customers.

Cognition effect of thinking of consumer attitude: Affect is regarding as the feeling of responses; Cognition is the extent of mental thinking of individuals.

 

9. DATA ANALYSIS

9.1. DESCRIPTIVE STATISTICS

Table 1

Table 1
	N Statistic	Range Statistic	Minimum Statistic	Maximum Statistic	Sum Statistic	Mean
						Statistic	Std Error
D2	64	2	3	5	287	4.48	0.70
@4	64	2	3	5	279	4.36	0.75
@4	64	2	3	5	280	4.38	0.79
@5	64	2	3	5	252	3.94	0.91
@4	64	3	2	5	253	3.95	0.96
@4	64	2	3	5	276	4.31	0.70
@5	64	3	2	5	276	4.31	0.109
@4	64	4	1	5	252	3.94	0.111
@4	64	4	1	5	237	3.70	0.120
@2	64	4	2	5	240	3.75	0.092
@5	64	3	1	5	277	4.33	0.106
@5	64	3	1	5	275	4.30	0.128
@5	64	3	1	5	256	4.00	0.109
@5	64	3	2	5	272	4.25	0.109
@4	64	4	2	5	252	3.94	0.074
@4	64	3	2	5	254	3.97	0.086
@5	64	4	2	5	256	4.00	0.120
@5	64	4	1	5	252	3.94	0.113
@3	64	4	2	5	236	3.69	0.129
@4	64	4	1	5	245	3.83	0.124
@4	64	4	1	5	246	3.84	0.129

 

Table 2

Table 2
	Std. Deviation Statistic	Variance Statistic	Skewness		Kurtosis
			Statistic	Std. Error	Statistic	Std. Error
D2	.563	.317	-.487	.299	-.782	.590
@4	.601	.361	-.339	.299	-.634	.590
@4	.630	.397	-.492	.299	-.610	.590
@5	.732	.536	.098	.299	-1.092	.590
@4	.765	.585	-.139	.299	-.710	.590
@4	.560	.313	-.044	.299	-.590	.590
@5	.871	.758	-.961	.299	-.176	.590
@4	.889	.790	-.716	.299	.692	.590
@4	.903	.815	-.569	.299	.292	.590
@2	.959	.921	-.250	.299	-.872	.590
@5	.736	.541	-1.844	.299	6.445	.590
@5	.849	.720	-1.745	.299	3.985	.590
@5	1.024	1.048	-.917	.299	.192	.590
@5	.873	.762	-1.109	.299	.664	.590
@4	.871	.758	-.771	.299	.229	.590
@4	.590	.348	-.474	.299	1.622	.590
@5	.690	.476	-.898	.299	1.933	.590
@5	.957	.917	-1.328	.299	1.898	.590
@3	.906	.821	-.386	.299	-.531	.590
@4	1.032	1.065	-1.164	.299	1.150	.590
@4	.996	.991	-.971	.299	.376	.590
@3	1.067	1.139	-.744	.299	-.330	.590
@3	1.246	1.552	-.699	.299	-.428	.590
@4	.984	.968	-.877	.299	.777	.590
@4	.957	.917	-.446	.299	-.163	.590
@4	1.009	1.018	-.537	.299	-.371	.590
@3	1.112	1.236	-.730	.299	-.114	.590

 

As a general rule of thumb, the values of skewness should be near to 1. Skewness measures the direction and the extent of asymmetry. The above analysis indicates, perception, purchase frequency, benefit sought were negatively skewed.  The nearer the value of Kurtosis to zero, it indicates the distribution is normal.

 

10. FACTOR ANALYSIS

Factor Analysis is a technique used to reduce a large number of variables into fewer numbers of factors. It is used to simplify data. The technique also involves data reduction.

 

10.1. KAISER-MEYER-OLKIN (KMO) AND BARTLETT TEST

The KMO measures the sampling adequacy which should be greater than 0.5 for a satisfactory factor analysis to proceed.

 

10.2. FACTOR ANALYSIS OF INDEPENDENT VARIABLE

Table 3

Table 3 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.542
Bartlett's Test of Sphericity	Approx. Chi-Square	18.019
	Df	10
	Sig.	.000

 

The analysis revealed one factor solutions with a KMO statistics and Bartlett’s Test with 0.000 Significance. This reveals that the sample is adequate and factor analysis is significant. From the above table we can also see that KMO is 0.542 which is more than 0.5 hence the sample taken is adequate. Hence the sampling adequacy for items of Dependent variable is meritorious stating it is acceptable.

 

10.3. TOTAL VARIANCE EXPLAINED

Table 4

Table 4
Component	Total	Initial Eigenvalues		Extraction Sums of Squared Loadings
		% of variance	Cumulative %	Total	% of variance	Cumulative
1	1.597	31.940	31.940	1.597	31.940	31.940
2	1.096	21.915	53.854	1.096	21.915	53.854
3	1.003	20.063	73.918
4	0.699	13.988	87.906
5	1.294	25.886	25.886
6	1.205	24.098	49.984
7	1.197	23.934	73.918

 

As opined by Joseph and William (2010), for achieving the practical importance of the extracted factors cumulative percentage of total variance is extracted. Joseph, and William (2010), also reported that in social science research, where the information is less precise, a solution accounting to total variance of 60 percent is accepted and in a few cases below 60 percent is also considered to be satisfactory.

Seven items were extracted with a cumulative frequency amounting to 53.854. Based on the above inferences gathered, the above table reveals the total cumulative percentage of variance extracted was 69.701 which is considered to be acceptable as per the reports of Joseph and William (2010).

 

10.4. ROTATED COMPONENT MATRIX

Table 5

Table 5
1		2	3
D1	.668	-.176	-.411
D2	.875	.032	.211
@4	.062	.909	-.114
@4	-.275	.589	.373
@5	.050	-.003	.911

 

The variables considered to have more significance were attractiveness of the website, availability of information, engagement of audience and ease of use.

 

10.5. FACTOR ANALYSIS FOR DEPENDENT VARIABLE

Table 6

Table 6 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.515
Bartlett's Test of Sphericity	Approx. Chi-Square	1080.07
	Df	465
	Sig.	.000

 

The analysis revealed one factor solutions with a KMO statistics and Bartlett’s Test with 0.000 Significance. This reveals that the sample is adequate and factor analysis is significant. From the above table we can also see that KMO is 0.515 which is more than 0.5 hence the sample taken is adequate. Hence the sampling adequacy for items of Dependent variable is meritorious stating it is acceptable.

 

10.6. TOTAL VARIANCE EXPLAINED

Table 7

Table 7
Component	Total	Initial Eigenvalues		Extraction Sums of Squared Loadings
		% of variance	Cumulative %	Total	% of Variance	Cumulative %
1	5.032	16.232	16.232	5.032	16.232	16.232
2	3.256	10.503	26.735	3.256	10.503	26.735
3	2.845	9.178	35.913	2.845	9.178	35.913
4	2.564	8.269	44.182	2.564	8.269	44.182
5	2.011	6.486	50.668	2.011	6.486	50.668
6	1.724	5.134	61.364	1.724	5.562	56.230
7	1.592	4.145	65.509	1.592	5.134	61.364
8	1.285	4.069	69.578	1.285	4.145	65.509
9	1.261	3.904	73.482
10	1.210	3.295	76.777
11	1.021	2.782	79.559
12	0.862	2.595	82.154
13	0.805	2.382	84.535
14	0.738	2.090	86.626
15	0.648	2.057	88.682
16	0.638	2.057	88.682
17	0.550	1.773	90.456

 

As opined by Joseph and William (2010), for achieving the practical importance of the extracted factors cumulative percentage of total variance is extracted. Joseph, and William (2010), also reported that in social science research, where the information is less precise, a solution accounting to total variance of 60 percent is accepted and in a few cases below 60 percent is also considered to be satisfactory.

Seven items were extracted with a cumulative frequency amounting to 65.508. Based on the above inferences gathered, the above table reveals the total cumulative percentage of variance extracted was 69.701 which is considered to be acceptable as per the reports of Joseph and William (2010).

 

11. FINDINGS

The study results make it evident that, in interactive environments, individual tend to search, rate, and comment regarding the videos and share opinions with others through online media. The lack of individual’s involvement towards a particular product category allows flexibility through brand messages, that appeals to broader consumer groups.

 

12. SUGGESTIONS

The examination can be done all over India with through websites. Various other factors having an influence on the consumer attitude can be examined.

 

13. SCOPE FOR THE FUTURE RESEARCH

A theoretical framework for examining the present state of brand promotions and extent of social media usage can be worked by further studies in the area of research.

 

14. CONCLUSION

Considering the perspectives of the academic practitioners, most of the social media platforms are used as place marketing and promotion tools, while specifically a few are clearly used for the purpose of creating brand awareness and enhancing brand identity like twitter, Facebook, and YouTube. An essential parameter is the capability to design appropriate messages and promote a brand with visuals, videos which is easy for the consumers to understand. Videos generated tend to be similar in nature, therefore an attempt to create brand awareness becomes generic, unable to catch the attention of the viewers.

 Since, social media communications are developing, it is essential to be more serious on the content, the interactive approach of marketing. For the purpose of promoting interactive and conversations the content need to be more authentic.

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

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