Pacific B usiness R eview I nternational

A Refereed Monthly International Journal of Management Indexed With THOMSON REUTERS(ESCI)
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Prof. B. P. Sharma
(Editor in Chief)

Dr. Khushbu Agarwal
(Editor)

Ms. Asha Galundia
(Circulation Manager)

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Mr. Ramesh Modi

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2020
2019 2018
A Refereed Monthly International Journal of Management

Advertising on Social Networking Sites (SNSs): Exploring the Gender Differences

Author

Dr.Asad Ahmad

Assistant Professor

Department of Management

Jamia Hamdard

New Delhi, INDIA

Contact No.:- +91-8791248131

E-mail:- asad7babar@gmail.com

Dr. Mohammed Naved Khan

Associate Professor

Department of Business Administratio

Faculty of Management Studies & Research

Aligarh Muslim University, Aligarh-202002 (UP) INDIA

Contact No:- +91-9557633713

E-mail:- mohdnavedkhan@gmail.com

Obaidur Rahman

Research Scholar

Department of Business Administration

Aligarh Muslim University

Aligarh -202002 (UP) INDIA

Contact No.:- +91-9368486324

E-mail:- obaidkhan.mba@gmail.com

Abstract

With the growth of Internet, it has changed the way we work and live. Presently around 42 percent of the world population isusing Internet. We get up-to-date information over the Internet which is accessible 24X7. Internet has also become synonymous with Social Networking Sites (SNS).They help us remain in contact with near and dear ones as also business contacts on a real time basis and its reach has been growing with a scorching pace. According to certain estimates, around 30 percent of the world population accesses some form of Internet based social media. The marketers too have taken notice of potential of this medium and started using it in innovative ways to reach to their target audience. This study primarily focuses on how male and female patrons of social networking sites perceive advertisements over social networking sites as also their perceptions towards online purchases. The results indicate that both the genders have similar attitudes towards advertisements over SNSs but they perceived online shopping differently. The findings have important theoretical and managerial implications.

Keywords : Internet; Social Media; Social Networking Sites (SNS); Social Media Marketing

INTRODUCTION

Internet has transformed itself into a platform where advertise their products and services (Ahmad & Khan, 2017a; Ahmad & Khan, 2017b). It is a platform where people communicate and do businesses. Internet as a medium has given a globalized dimension to the world; everything we need is just a click away. It has been found to be the most democratic medium providing information to millions of people. Internet has evolved as a vast global market where we communicate and exchange goods and services. It is being used by the individuals for various purposes like to search product features, compare prices, look reviews of the products, make payments etc. (Ahmad, Rahman, & Khan, 2017; Sinha, 2010).Around 3.8 billion people i.e. more than 50 percent of the population world-wide is using Internet. In a report (Internet World Stats, 2017).Social networking has become the most prevalent Internet activity surpassing other online activities (Ahmad & Khan, 2017b). With the increasing popularity of social networking sites, marketers are coming up with ways and means to usethese sites as an advertising medium (Hart 2007; Bausch and Han 2006). Marketers must understand the way these sites can be used by the marketers to reach their target consumers (Ahmad & Khan, 2017b; Ahmad, Akhter, Khan, & Khan, 2013).

Advertising over the Internet has been acknowledged for its interactivity and ability to record the behavioural responses of the Internet users (Rodgers & Thorson, 2000). Researchers have discussed the relevancy of the advertisements as is the most important feature which makes the ads effective (Lee and Mason 1999; Muehling and McCann 1993). It has also been reported that when consumers perceive that advertisements contain useful information they are more likely to respond to it (Ahmad & Khan, 2017b; Ducoffe 1996; Muehling and McCann 1993). Hence, it can be said that if the marketers use the social networking sites to exhibit ads which are useful than the users will exhibit a positive behavioural response to the ads.

LITERATURE REVIEW

Online Buyer Behaviour

Consumer behaviour differs over the Internet in comparison to offline stores, where one can touch and feel the product (Ahmad & Khan, 2015). Realizing the importance of e-buyer behaviour,a number of researchers have explored the area (Ahmad et al., 2017; Tsai & Men, 2013; Chen, Hsu & Lin, 2010;Jayawardhena et al., 2007;Cheung, Chan &Limayem, 2005;Brown et al., 2003). Internet users browse the webto get information along with enjoyment (Ahmad, Rahman & Khan, 2016; Katerattanakul, 2002). In the evaluation of websites, researchers have found bothinformativenessas well as entertainmentto bevital factors (Richard, 2005; Ducoffe, 1996). In other words, hedonic and utilitarian motivations play significant role in affecting online buyers purchase intention (Ahmad et al., 2017a; Wolfinbarger& Gilly, 2001).

Aljukhadar and Senecal (2011) divided online buyers into three categories: basic communicators (users using Internet to communicate), lurking shoppers (users who shop heavily) and, social thrivers (Users using the interactive features of Internet to interact by means of chatting, blogging, video streaming, downloading etc.). In online buying, word of mouth also has an important role. It has been found that negative word of mouth elicits a conformity effect (Lee, Park & Han, 2008). Experience, word of mouth, and marketing communications has been found to help build brand image (Romaniuk& Sharp, 2003). Several researchers have found a significant and positive influence of the volume and the valence of the reviews on sales (Chen, Wang &Xie 2011; Chevalier &Mayzlin 2006; Liu, 2006).

The young generation that forms an important consumer group because of their unique purchasing behaviour have also been found to have a positive attitude towards online shopping (Ahmad & Khan, 2015; Cole, 2011; Arnaudovska, Bankston, Simurkova&Budden, 2010; Xu and Paulins, 2005). Researchers have also analysed e-buyer behaviour with respect to socioeconomic characteristics i.e. age, gender, income etc. (Herna´ndez, Jimenez, & Martin, 2011).Researchers have found difference in the attitude of men and women towards online shopping. Men have been found to have shown favourable attitudes to Internet and Internet Shopping (Dennis, Morgan, Wright &Jayawardhena, 2010; Jackson, Ervin, Gardner & Schmitt 2001; Bimber, 2000). Studies have also revealed that, men are content with the overall message themes, whereas women go for a detailed elaboration of the content (Meyers-Levy &Maheswaran, 1991; Meyers-Levy and Sternthal, 1991; Meyers-Levy, 1989).

Social Media Marketing

Social media includes sites like blogs, social networking sites (e.g., Facebook), content communities (e.g.,Youtube) Akar&Topçu (2011). These sitesenables the marketers to reach the target consumers through social communities where they also work to build a healthy relationship with the consumers on a more personal level (Kelly, Kerr &Drennan, 2010; Avery,Lariscy, Amador, Ickowitz, Primm& Taylor,2010). Social networking sites (e.g. Facebook) have emerged to be the most important driving force of the digital media revolution (Vogt &Knapman, 2008). Social media marketing has enabled themarketers in presenting their products and services to a large community and to get their feedback through social networking sites (Weinberg, 2009). Social networking sites help the marketers to exchange thoughts and information related to products and services (Ontario, 2008).

The intention to use any services over the Internet is affected by the level of satisfaction of the users (Ahmad et al., 2017; Shiau& Luo, 2010). Social media users shop through the social networking sites when they find the services over the social sites useful as well as easy to use (Cha, 2009). Online consumers extract the product related information from various sources, especially through the product reviews on the social networking sites (Clemons, 2009). Before actual buying of products and services, consumers continuously search for the product reviews (Akar&Topcu, 2010). A large chunk of the online buyers have been found to believe the product reviews by other consumers (Blackshaw&Nazzaro, 2006). The social networking activities of the users have increased the ad recall, awareness and purchase intentions of the online consumers (Neff, 2010). The social networking users have become a kind of brand endorsers when they forward some viral advertising to the friend list (Chu, 2011).

The online consumers who use social networking sites have been found to be vital as they are supposed to be active and effective, they have also been found to share their experiences with other consumers through the social media (Blackshaw&Nazzaro, 2006). Consumers rely more on the e-word-of-mouth (e-wom) in comparison to marketing messages (Akar, 2010). It is the need of the hour that, the interrelation of the social media and marketing aspectsneeds to be understood by the marketers as the social media effects the marketing performance of the products and services (Stephen &Galak, 2010).There are various studies which have investigated online communities (DeKay 2009; Gangadharbatla 2008; Bagozzi& Dholakia 2002), but there is a dearth of literature which has explored the perception of the male and female social network users towards the advertisements on the SNS in the Indian context.

RESEARCH METHODOLOGY

Objectives

The objectives of the study are listed below:

1. To explore the differences in perceptions of the two genders in terms of attitude towards advertisements appearing on Social Networking Sites (SNSs).

2. To explore the differences in perceptions of the two genders in terms of utilitarian value of Social Networking Sites (SNSs) in online purchases.

3. To explore the differences in perceptions of the two genders in terms of Trust on Social Networking Sites (SNSs) in online purchases.

Hypothesis

In the light of the study objectives and above literature, the following hypotheses were proposed:

H01: Significant differences do not exist between the two genders in terms of attitude towards advertisements appearing on Social Networking Sites (SNSs).

H02: Significant differences do not exist between the two genders in terms of utilitarian value of Social Networking Sites (SNSs) in online purchases.

H03: Significant differences do not exist between the two genders in terms of Trust on Social Networking Sites (SNSs).

Research Instrument

A structured questionnaire employing 5 point Likert scale consisting of 10items related to three variables has been used in this study. Theitems of Attitude and Utilitarian has been adapted fromKhare and Rakesh (2011) and the items of Trust has been adapted from Koo (2006).The variable items were modified and rephrased by the researchers keeping in mind the profile of the respondents. The responses were generated from Internet users who had accounts on Social Networking Sites for last six months.

Sample

The sample for the study comprised University students who were enrolled in under graduate courses as also higher studies at a large University of repute in northern part of India. The University is a Central Government institution fully funded by the University Grants Commission and is popular with students who belong to middle class families (Ahmad et al., 2017; Heslop, 2014). Students belonging to the middle class can be deemed to represent the masses (Ahmad et al., 2016; Shabnam, 2012), hence the sample can be considered to represent the student population of the country as a whole.

Data Collection

Researchercontrolled sampling was used for data collection. As suggested by previous studies Dornyei& Taguchi, (2010), the researchers were personally present while administering the questionnaire to clarify doubts, if any. A total of 180 questionnaires were distributed by the researchers, of which 150 were received back and 140 of them were suitable for further analysis.

Table 1 : Demographic Profile of Respondents

FREQUENCY

Qualification

Graduate

60

Post Graduate

80

AGE

Less than 22 Years

66

Above 22 Years

74

GENDER

Male

86

Female

54

DATA ANALYSIS AND RESULTS

Exploratory Factor Analysis (EFA) was performed using SPSS 20 employing Principal Component Analysis (PCA) with Varimax rotation and Kaiser normalization as the factor extraction method. The KMO measurement of sampling adequacy value was found to be 0.7, which indicated that the factors caused variance in the variables. In addition, the Bartlett’s test of Sphericity value was found to be significant (Chi-square = 1124.781, p < 0.005) that was less than 0.05 (Hair et al., 1998; Herington &Weaven, 2007), which proved that the analysis was significant with the sample size of 140.

Loadings with value more than .5 are considered to be acceptable (Khan &Adil, 2013; Metin et al., 2012; Büyüköztürk et al., 2004; Hair et al., 1998). The Table 2 shows the loadings which were found to acceptable (>0.6) on intended factors. The variables Attitude, Utilitarian Value and Trust each consisted three, four and three items respectively.

Table 2: Results of EFA

Variables

Items

Code

Factor Loadings

Cronbach’s Alpha

Attitude

I am interested in social media advertisements

AT1

.819

0.715

I feel comfortable with online advertisements

AT2

.684

My attitude toward online advertisement is positive.

AT3

.778

Utilitarian Value

SNSs improves my shopping productivity

PU1

.754

0.793

SNSs would be useful in buying what I want

PU2

.706

SNSs will improve my shopping ability

PU3

.784

SNSs would enhance my effectiveness in shopping.

PU4

.847

Trust

SNSs safeguard my personal information

TR1

.693

0.737

My privacy would be guaranteed on SNSs.

TR2

.732

The social networking sites are reliable.

TR3

.689

The Cronbach’s Alpha coefficient of all the three variables Attitude, Utilitarian Value and Trust were found to be0.715, 0.793 and 0.737 respectively. The alpha values of all the three variables were within acceptable range and hence the factors were found to be reliable as the Cronbach alpha value of all the three variables were greater than 0.6 (Khan &Adil, 2013; Kerlinger& Lee, 2000; Hair et al., 1998).

To investigate the three hypothesis (H01, H02 andH 03), Independent samples t-Test was employed to determine the variation in the factors and inferences were drawn.The results of the t-test showed that for the factor “Attitude” significant difference were not observed between the two genders at p=0.05 (Field, 2005).

Table 3: t-Test

Construct

Gender

N

Mean

t

Sig.(2-tailed)

Attitude

M

86

3.96

-0.815

0.416

F

54

3.87

Utilitarian value

M

86

3.93

2.614

0.01

F

54

3.35

Trust

M

86

3.89

-2.177

0.02

F

54

3.26

On the other hand significant differences was found between male and female respondents for the factor “Utilitarian Value” and “Trust”.Hence, H 01could not be rejected whereasH02and H03 was rejected. Table 3 above presents the results for the independent samples t-Test.

Discussion and Conclusion

Social networks have become popular mediums for the world where people of various backgrounds meet. Social media, where users get connected with others, and even disclose their personal information and share other information with their contacts has been used as medium by the marketers to communicate the advertising messages (IAB, 2015). The findings suggest that majority (93%) of the respondents did notice online advertisements on SNS. This impliesthat the marketers have realized the growing potential SNSs and to effectively target their users, advertisementsare being placed in SNSs. It has also been found that that advertising through SNS influences the people in a positive way.

The SNSs are being used as a platform where the marketers easily establish their brand presence, bring awareness of their brands, and even it has helped them to save advertising costs (Bolotaeva&Cata, 2010; Skul, 2008).Facebook has been found to be the most popular social networking application and has been found to be one of the most prominent medium of advertisement too (Xia, 2009). The results of the independent samples t-Test showed that there was no significant difference between males and females with respect to attitude towards the advertisementsover the social media whereas significant differences were found between the two genders with respect to the utilitarian value and trust of social networking sites.

Internet shopping has grown tremendously all over the world in recent years.Social media marketing is playing an important role in the marketing strategies of companies such as advertisements (Chu, 2011) and brand pages on SNSs (Tsai & Men, 2013). It has been observed that the social media users are lively and the chance of taking positive marketing action (i.e. indulging in purchasing) by them is more, hence it can be a big advantage for the marketers who are present on the social networking websites (Ahmad et al., 2013). Consequently, companies who integrate elements of social media into their marketing mix have greater potential to influence buying choices (Klein, 2008).

LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH

The present study suffersfrom certain limitations.The study adopted researcher controlled sampling and thus the findings of the study may have the limitation of generalizability. There are significant differences in the sample sizes of different groups which might have compromised the accuracy of the test applied in the study (Byrne et al. , 2007). The study is also limited with respect to geographic extent which again might limit the generalizability of the results of the study.

However, the limitations of any study are likely precursors for new areas of research. Future researchers can work on larger and more representative probability based samplesand validate the results of the present study. The significant differences in the various groups of sample need to be checked in future researches.Researchers also need to work on other occupational groups in the context of social networking sites to broaden the scope of study findings.

REFERENCES

1. Ahmad, A., Akhter, F., Khan, M, H., & Khan, H. (2013). Social Networking Sites: A Path to Online Stores. Global Journal of Management and Business Studies, 3(8), 835-842.

2. Ahmad, A., & Khan, M. N. (2015). Mapping online buyer behavior: A critical review of empirical studies. Pacific Business Review International , 8 (2), 37-48.

3. Ahmad, A., Rahman, O., & Khan, M. N. (2016). Consumer's Perception of Website Service Quality: An Empirical Study. Journal of Internet Commerce , 15 (2), 125-141.

4. Ahmad, A., & Khan, M. N. (2017a). Developing a website service quality scale: a confirmatory factor analytic approach. Journal of Internet Commerce , 16 (1), 104-126.

5. Ahmad, A., & Khan, M. N. (2017b). Factors Influencing Consumers’ Attitudes toward Social Media Marketing. MIS Review, 22(1/2), 21-40.

6. Ahmad, A., Rahman, O., & Khan, M. N. (2017). Exploring the role of website quality and hedonism in the formation of e-satisfaction and e-loyalty: Evidence from internet users in India. Journal of Research in Interactive Marketing , 11 (3), 246-267.

7. Akar, E., &Topçu, B. (2011). An examination of the factors influencing consumers' attitudes toward social media marketing. Journal of Internet Commerce, 10(1), 35-67.

8. Albanesius, C. (2010). Social Networking More Popular Than E-Mail, Report Says. PCMag. Com

9. Aljukhadar, M., &Senecal, S. (2011). Segmenting the online consumer market.Marketing Intelligence & Planning, 29(4), 421-435.

10. Arnaudovska, E., Bankston, K., Simurkova, J., &Budden, M. C. (2010). University Student Shopping Patterns: Internet vs. Brick And Mortar. Journal of Applied Business Research (JABR), 26(1).

11. Avery, E., Lariscy, R., Amador, E., Ickowitz, T., Primm, C., & Taylor, A. (2010). Diffusion of social media among public relations practitioners in health departments across various community population sizes. Journal of Public Relations Research, 22(3), 336-358.

12. Bagozzi, R. P., & Dholakia, U. M. (2002). Intentional social action in virtual communities. Journal of interactive marketing, 16(2), 2-21.

13. Bimber, B. (2000). Measuring the gender gap on the Internet. Social science quarterly, 868-876.

14. Blackshaw, P., &Nazzaro, M. (2006). Consumer-generated media (CGM) 101: Word-of-mouth in the age of the web-fortified consumer. New York: Nielsen BuzzMetrics.

15. Bolotaeva, V., &Cata, T. (2010). Marketing opportunities with social networks.Journal of Internet Social Networking and Virtual Communities, 2010, 1-8.

16. Büyüköztürk, Ş., Akgün, Ö. E., Özkahveci, Ö.,&Demirel, F. (2004). The validity and reliability study of the Turkish version of the motivated strategies for learning questionnaire. Educational Sciences: Theory & Practice, 4(2), 207-239.

17. Cha, J. (2009). Shopping on social networking Web sites: Attitudes toward real versus virtual items. Journal of Interactive Advertising, 10(1), 77-93.

18. Chen, Y. H., Hsu, I. C., & Lin, C. C. (2010). Website attributes that increase consumer purchase intention: A conjoint analysis. Journal of business research, 63(9), 1007-1014.

19. Chen, Y., Wang, Q., &Xie, J. (2011). Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of marketing research, 48(2), 238-254.

20. Cheung, C. M., Chan, G. W., &Limayem, M. (2005). A critical review of online consumer behavior: Empirical research. Journal of electronic commerce in organizations , 3 (4), 1.

21. Chevalier, J. A., &Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345-354.

22. Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2002). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing , 77 (4), 511-535.

23. Chu, S. C. (2011). Viral advertising in social media: Participation in Facebook groups and responses among college-aged users. Journal of Interactive Advertising, 12(1), 30-43.

24. Clemons, E. K. (2009). The complex problem of monetizing virtual electronic social networks. Decision Support Systems, 48(1), 46-56.

25. DeKay, S. (2009). Are Business-Oriented Social Networking Web Sites Useful Resources for Locating Passive Jobseekers? Results of a Recent Study.Business Communication Quarterly, 72(1), 101-105.

26. Dennis, C., Morgan, A., Wright, L. T., &Jayawardhena, C. (2010). The influences of social e-shopping in enhancing young women's online shopping behaviour. Journal of Customer Behaviour, 9(2), 151-174.

27. Dörnyei, Z., & Taguchi, T. (2010). Questionnaires in second language research: Construction, administration, and processing. Routledge.

28. Ducoffe, R. H. (1996). Advertising value and advertising on the web. Journal of advertising research, 36(5), 21-35.

29. Gangadharbatla, H. (2008). Facebook me: Collective self-esteem, need to belong, and internet self-efficacy as predictors of the iGeneration’s attitudes toward social networking sites. Journal of interactive advertising, 8(2), 5-15.

30. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5, No. 3, pp. 207-219). Upper Saddle River, NJ: Prentice hall.

31. Herington, C., &Weaven, S. (2007). Can banks improve customer relationships with high quality online services?. Managing Service Quality: An International Journal, 17(4), 404-427.

32. Heslop, L. (2014). Understanding India: The future of higher education and opportunities for international cooperation. British Council.

33. http://www.emarketer.com/Article/Social-Networking-Reaches-Nearly-One-Four-Around-World/1009976

34. http://www.iab.com/wp-content/uploads/2015/10/IAB_Internet_Advertising_Revenue_Report_HY_2015.pdf

35. http://www.statista.com/statistics/273018/number-of-internet-users-worldwide/

36. Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and the Internet: Women communicating and men searching. Sex roles, 44(5-6), 363-379.

37. Katerattanakul, P. (2002). Framework of effective web site design for business-to-consumer internet commerce. Infor, 40(1), 57.

38. Kelly, L., Kerr, G., &Drennan, J. (2010). Avoidance of advertising in social networking sites: The teenage perspective. Journal of Interactive Advertising,10(2), 16-27.

39. Kerlinger, F.N. and Lee, H. B. (2000), Foundations of Behavioral Research, Harcourt College Publishers, New York, NY.

40. Khan, M. N., &Adil, M. (2013). Data analysis techniques in service quality literature: Essentials and advances. Serbian Journal of Management, 8(1), 95-112.

41. Khare, A., & Rakesh, S. (2011). Antecedents of online shopping behavior in India: An examination. Journal of Internet Commerce , 10 (4), 227-244.

42. Klein, K. (2008). Are social networking sites useful for business. Business Week Online.

43. Koo, D. M. (2006). The fundamental reasons of e-consumers’ loyalty to an online store. Electronic Commerce Research and Applications , 5 (2), 117-130.

44. Lee, J., Park, D. H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341-352.

45. Lee, Y. H., & Mason, C. (1999). Responses to information incongruency in advertising: The role of expectancy, relevancy, and humor. Journal of consumer research, 26(2), 156-169.

46. Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of marketing, 70(3), 74-89.

47. Metin, M., Yilmaz, G. K., Coskun, K., &Birisci, S. (2012). Developing an Attitude Scale towards Using Instructional Technologies for Pre-Service Teachers. Turkish Online Journal of Educational Technology-TOJET, 11(1), 36-45.

48. Meyers-Levy, J. (1989). Priming effects on product judgments: A hemispheric interpretation. Journal of Consumer Research, 76-86.

49. Meyers-Levy, J., &Maheswaran, D. (1991). Exploring differences in males' and females' processing strategies. Journal of Consumer Research, 63-70.

50. Meyers-Levy, J., &Sternthal, B. (1991). Gender differences in the use of message cues and judgments. Journal of marketing research, 84-96.

51. Muehling, D. D., & McCann, M. (1993). Attitude toward the ad: A review.Journal of Current Issues & Research in Advertising, 15(2), 25-58.

52. Richard, M. O. (2005). Modeling the impact of internet atmospherics on surfer behavior. Journal of business research, 58(12), 1632-1642.

53. Rodgers, S., & Thorson, E. (2000). The interactive advertising model: How users perceive and process online ads. Journal of interactive advertising, 1(1), 41-60.

54. Romaniuk, J., & Sharp, B. (2003). Measuring brand perceptions: Testing quantity and quality. Journal of Targeting, Measurement and Analysis for Marketing, 11(3), 218-229.

55. Shabnam, S. (2012). The Indian Middle Class, the State and Development: An Enquiry into the Broad Claims of Shifts in Neo-liberal India. April, 11, 2012.

56. Shiau, W. L., & Luo, M. M. (2010). Continuance Intention of Blog Users: The Impact of Perceived Enjoyment and User Involvement. In PACIS (p. 85).

57. Sinha, J. (2010). Factors affecting online shopping behavior of Indian consumers. Doctoral dissertation, University of South Carolina, USA.

58. Skul, D. (2008). How To Use Social Network Marketing To Your Advantage. Relativity Business Technology, Solutions.

59. Stephen, A. T., &Galak, J. (2010). The complementary roles of traditional and social media publicity in driving marketing performance. Fontainebleau: INSEAD working paper collection.

60. Vogt, C., &Knapman, S. (2008). The anatomy of social networks.

61. Weinberg, T. (2009). The new community rules: Marketing on the social web. Sebastopol, CA: O'Reilly.

62. Wolfinbarger, M., & Gilly, M. C. (2001). Shopping online for freedom, control, and fun. California Management Review, 43(2), 34-55.

63. Xia, Z. D. (2009). Marketing library services through Facebook groups. Library management, 30(6/7), 469-478.

64. Xu, Y., &Paulins, V. A. (2005). College students' attitudes toward shopping online for apparel products: Exploring a rural versus urban campus. Journal of Fashion Marketing and Management: An International Journal, 9(4), 420-433.