UNDERSTANDING SOCIAL MEDIA MINDSET OF CONSUMERS: AN INDIAN PERSPECTIVE

Abstract

Social media play increasingly important roles as a marketing platform. In today's world, more and more retailers' use social media to target teenagers and young adults as a result importance of bringing social networking sites (SNSs) as a part of daily life transactions cannot be underplayed. In the present paper the emphasis is upon the analyses of the social media mindset of consumers in India, and examining the impact of various variables of extended TAM in order to explain the variables that influence level of acceptance of SNS by Indian consumers. Results indicated positive and significant effects of perceived usefulness while perceived risk influenced negatively. Further, perceived ease of use and personal fit with brands both found to have a positive effect on marketing through SNS but were not significant. The results of present study in India pointed out that establishing personal fit with consumers and providing user-friendly web sites, and reducing the perceived risk has impact on developing positive attitudes.

Headnote

ABSTRACT

Social media play increasingly important roles as a marketing platform. In today's world, more and more retailers' use social media to target teenagers and young adults as a result importance of bringing social networking sites (SNSs) as a part of daily life transactions cannot be underplayed. In the present paper the emphasis is upon the analyses of the social media mindset of consumers in India, and examining the impact of various variables of extended TAM in order to explain the variables that influence level of acceptance of SNS by Indian consumers. Results indicated positive and significant effects of perceived usefulness while perceived risk influenced negatively. Further, perceived ease of use and personal fit with brands both found to have a positive effect on marketing through SNS but were not significant. The results of present study in India pointed out that establishing personal fit with consumers and providing user-friendly web sites, and reducing the perceived risk has impact on developing positive attitudes.

Keywords -TAM, Attitude, Social Media, Perceived Risks, Personal fit, Social Networking Sites, Perceived Usefulness

1 INTRODUCTION

With the advent of the Internet, the idea that both marketers and consumers can create brand communities through their Web sites has been put forward (Mc William 2000). Social media play increasingly important roles as a marketing platform. More and more retailers' use social media to target teens and young adults, and social networking sites (SNS) are a central venue in that trend (Market Watch 2008). There are various reasons which attract the consumers of different age groups for following a particular brand through social networking sites. The popularity of virtual communities reflects the fact that individuals are using new technologies, such as the Internet, to fulfil both social and economic goals (Rheingold, 1993; Wind and Mahajan, 2002). The importance of social network media lies in the interaction between consumers and the community and in the facilitation of "asynchronous, immediate, interactive, low-cost communications" (Miller et al., 2009). Aldridge et.al (1997) assert that the likelihood of buying online increases as overall use of the Internet increases, and Hoffman, Novak, and Peralta (1999) empirically find that Internet experience has a positive association with purchase behaviors on the Internet.

Businesses increasingly acknowledge the potential role of the online social networks as marketing instruments (Constantinides et al., 2008; Waters et al., 2009; Hogg, 2010; Spaulding, 2010) and also as tools allowing observing and analyzing user behavior (Donath, 1998). These options attract already substantial commercial and research attention. SNS can be especially useful for connecting with customers, contributing to customer learning and getting customer input (Tikkanen et al., 2009). These sites contain a warehouse of information that can be mined and analyzed to expand user profiles and to build complex diagrams and maps of user-to-user and user-to-interest relationships (Schmugar, 2008). According to Kieran Kilmartin , marketing director EMEA & India, Pitney Bowes Software (2012), "Social media is everywhere and marketers are planning to take full advantage by pledging more budget than ever to the plethora of new communication channels available. Billions of dollars are expected to be invested across the globe in 2013 as the explosion in social shows little signs of slowing." Further from this research only, Pitney Bowes Software looks at the behaviours and attitudes towards social media from both a marketer's perspective and a consumer perspective, and has highlighted some alarming gaps between the two viewpoints. Comparing findings across Australia, France, Germany, the UK and the USA, it revealed that nearly seven in ten consumers would stop using a brand or product if they were irritated by that company's social media behaviour - an alarming revelation because the research suggests that many are guilty of doing just that. Thus, this online social phenomenon presents both challenge and opportunity to business information companies (Razzaque, 2008; Meimin, 2008; Utz, 2009).

Another survey, carried out in August and September(2012), has lent further weight to Gartner's (2012), predictions that social media revenue is expected to more than double over the next three years, surpassing US$34 billion by 2016.It showed that 70% of marketing directors are more focused than ever on social media, with a quarter of marketing budgets on average expected to be spent on new media activities next year - the UK being the most bullish of all allocating close to half (47%) of budget totals. Two-thirds (66%) of those questioned claim they are doing the right thing and their campaign investment tactics are effective. The study also reveals a significant disconnect between marketers' eagerness and consumers' attitudes to being marketed to via social media. Consumers still largely opt out when it comes to social media marketing, preferring to follow peer recommendations of brands and products rather than clicking on advertisements. They also apply a highly selective approach to using social media as a channel for interacting with brands generally. It was interesting to note the popularity of various social networking sites among the consumers. Further from this survey only, "The one thing marketers and consumers do see eye-to-eye on is the power of Facebook. It is the undisputed king, seen by both parties as the most popular and trusted of social media sites. But that is where the parity ends and more missed opportunities manifest themselves. Marketers ranked Twitter (57%) and Google+ (51%) as the next most important channels for communications. By contrast, after Facebook, consumers spend most of their time on YouTube - rated only fifth in the pecking order by marketers."

The proliferation of social-networking sites and new tools making online interaction easier are offering small businesses novel opportunities to network with each other and their customers, and to spread out their reach (Spors, 2008). Realizing a figure of more than 65 million users of Facebook in India, brands and companies have morphed to aggressively target social networkers with bespoke plans and initiatives as they seek new avenues for growth. Marketers in India have begun realigning themselves to a new cost-effective marketing and advertising space. Companies such as Shoppers stop, American Express, Titan, and many more are using peer-to-peer network on sites like Facebook, LinkedIn or Twitter to spread product reviews and create buzz around the brand (Economic Times report, 2012). However, marketers are unsure of how they can harness the power of social networking for their brands and products but are positive about the potential that networking sites hold.

The objective of this paper is to empirically examine the behaviours and attitudes of consumers' towards marketers who market through social media in the Indian context.

This study attempts to investigate the factors influencing consumers' attitude towards marketing of products through Social Networking Sites in India. The study exclusively focuses on exploring answers to the following questions:

1.1 Research questions

1. What is respondents' opinion towards marketing of products on social networking sites?

2. Which factors influence consumers' attitude towards marketing of products through Social Networking Sites?

1.2 Objectives of the study

The objectives of this study are:

· To assess the exposure of brands on SNS

· To examine the reasons people follow brands on SNS

· To identify factors which influence co nsumers' attitude towards the marketing of products on SNS

· To evaluate the relative contributions of each predictor variable to each construct.

· To study perception of customers regarding the reasons for marketers to socialize with them on SNS.

2 LITERATURE REVIEW

Research suggests that consumers rely on two different sets of values in making their shopping decisions: hedonic and utilitarian (Babin and Darden 1995; Babin, Darden, and Griffin 1994). Batra and Ahtola (1990, p. 159) define these values as follows: "(1) consummatory affective (hedonic) gratification from sensory attributes, and (2) instrumental, utilitarian reasons." Hedonic shopping value thus reflects the value received from the multisensory, fantasy-related, and emotive feeling a consumer receives from a particular product, whereas utilitarian shopping value focuses on the acquisition of products and/or information in an efficient manner, which reflects a more task-oriented, cognitive, unemotional outcome (Babin, Darden, and Griffin 1994; Holbrook and Hirschman 1982). Utilitarian value therefore is more associated with cognitive aspects of attitudes, such as economic benefit (Zeithaml 1988), convenience, and time savings (Jarvenpaa and Todd 1997; Teo 2001). Online shoppers tend to seek utilitarian values rather than hedonic values (Reibstein 2002), because online shopping services lack multisensory attributes. The primary utilitarian values that online shoppers seek include the convenience of locating and comparing merchants, evaluating price/quality ratios, and conserving temporal and psychological resources (Grewal et al. 2003; Mathwick, Malhotra, and Rigdon 2001).

Technology acceptance model (TAM), has been applied extensively because of its efficacy to predict the adoption of any technology or to identify factors that facilitate or inhibit the adoption of an innovation (Davis, 1989; Gefen and Straub, 2000; Horst et al., 2007) and the possibility of extended it including other constructs (Moon and Kim, 2001; Kuo and Lee, 2009). TAM proposes specifically to explain the determinants of information technology end-user's behavior towards information technology (Saade, Nebebe & Tan, 2007).

Many studies have examined the factors that lead people to adopt and use the SNS through TAM (Shin and Kim, 2008; Willis, 2008; Shin, 2008, 2010; Lee, 2010). However, few approaches have focused on the influence of trust and perceived risk in this adoption process (Dwyer et al., 2007; Shin, 2010), since both variables are essential when uncertainty is present (Luhmann, 1979; Mayer et al., 1995), like the online environments. In the present paper the emphasis is to analyse the online consumer behaviour, hence its implications are applicable. In this study, two of the constructs, perceived Usefulness and perceived risk will be employed. Though, in this study we have tried to establish a direct impact of perceived risk on attitude as well.

2.1 Perceived risks

Perceived risk refers to the nature and amount of risk perceived by a consumer in considering a particular purchase decision (Bauer, 1960). Apart from various risk mentioned in literature, the emergence of the internet has created new forms of risk perceptions, viz. privacy risk (Cases, 2002, Pikkarainen et al., 2004) and security risk (Pikkarainen et al., 2004). Theory of reasoned action refers, the perception of risk is a behavioural belief and as such an important antecedent of the attitude towards marketing of products through SNS. Therefore, we model perceived risk as directly impacting attitude. The negative relationship between perceived risk and attitude has been empirically tested in several environments (Featherman and Pavlou 2003; Pavlou 2003).The consequence of marketing on the web is that it allows for access to markets regardless of geographic locations and thus provides a broad-based understanding of the market realities which could be beneficial to marketers. The term 'webnography' has been coined as an attempt to look at the web as an object of study, and to search for insights into the natural conversations that occur in web forums (Puri, 2007). It is worth noting that any information accessed on the web can be collected and measured in real-time. Hence, social networks can foster market research using member (users of social networks) data as input to gain a unique insight into consumer behaviour and their interaction with a particular brand or product (Razzuque, 2008).

Although online shopping has grown rapidly in recent years, some Internet users remain reluctant to purchase goods on the Internet because they are skeptical of how much privacy and security they have in doing so (Aldridge, Forcht, and Pierson 1997; Wang, Yeh, and Jiang 2006). Others may hesitate to shop online because they would miss the social interaction or direct experience with products. Online shopping analysts argue that people who have not purchased online tend to continue to buy goods or services offline (Linn, 2007).

2.2 Personal fit

As a basic concept in consumer research, congruity of self-concept and brand personality offers a significant perspective to the understanding of consumer decision making. Consumers may decide not to buy a product or not to shop at a particular store if they feel that these actions are not consistent with their own perceptions of themselves (Britt, 1960). The construct of self-concept congruity delineates an individual's perceptions of the self, the brand, and person-brand relationship. They prefer products with personalities that match their own self-image. To do otherwise would cause dissonance, resulting in a state of psychological discomfort that threatens to invalidate the person's beliefs about him or herself (Sirgy, 1985). Self-image congruity was a very strong predictor of consumer's brand preferences and a good predictor of consumer satisfaction. And consumers with higher levels of self-image congruity were more likely to prefer the brand and enjoy higher levels of satisfaction with the brand as compared to those with lower levels of self-image congruity (Jamal & Goode, 2001). Several previous researches provide evidence about the positive effect of self-image congruity in the tangible product context (only for the actual and the ideal self-image congruity) on overall attitude (Ericksen & Sirgy, 1992; Kleijnen, 2005), and purchase intentions (Ericksen, 1996; Mehta, 1999). An individual's emotional attachment to a brand will predict his commitment to the relationship with the brand. In the context of technology acceptance research, self-congruity will predict a strong attitude to adopt.

2.3 Perceived Usefulness

Perceived usefulness was defined as the ''degree to which an individual believes that using a particular system would enhance his or her job performance'' (Davis, 1993).There has been extensive research in the information systems (IS) community that provides evidence of the significant effect of perceived usefulness on usage intention (Petty, Cacioppo & Schumann, 1983; Taylor & Todd, 1995; Venkatesh & Davis, 2000). Davis's (1989) found that perceived usefulness has a stronger influence on usage. Davis's study shows that users are driven to adopt a technology primarily because of the functions it provides them, and secondarily because of the easiness of benefiting from those functions. Customers are often willing to overlook some difficulties of usage if the service provides critically needed functions. Recent empirical evidence indicates that about 80% of Internet users are interested in personalized services (Kobsa 2007). According to Freedman (2007), 56% of frequent online shoppers were more likely to make a purchase on a website that offered personalization features, than on websites that did not offer them. However, not all personalized services are the same. Previous research indicates that different personalized services tend to have different effects on customer satisfaction (e.g., Alpert et al. 2003), but not much research has been done on which factors contribute to the effect of personalization in customer service and why personalization of certain services are perceived to be more useful than others.

2.4 Research Hypotheses

In order to explore the factors influencing consumers' attitude towards marketing of products through SNS, a series of hypotheses were developed.

H1: The perceived usefulness of marketing through SNS has a positive and significant effect on the consumers' attitude.

H2: The perceived risk of marketing through SNS has a negative and significant effect on the attitude.

H3: The personal fit with the brands marketing on SNS has a positive and significant effect on the attitude.

3 RESEARCH OBJECTIVES AND METHODOLOGY

Many researchers have recognized the potential contribution of the online social networks as marketing tools (Waters et al., 2009; Spaulding, 2010).Therefore; it could potentially be a significant source of revenue for the social networking sites and their corporate sponsors. Understanding consumers' social media mindset is crucial because it helps in predicting the consumers' attitude, intention and purchase behavior.

3.1 Sample and data collection

Before the main survey, pilot survey using a sample of 23 post-graduate students was conducted. On the basis of the pilot survey, improvement in the questions and wordings for the questionnaire was carried out. The main survey was conducted online using a free survey conducting portal www.google.com. The online nature of the survey was preferred so that people from diverse geographical locations could access and respond. A total of 140 respondents were considered for the study.

The questionnaire consisted of three sections. The first section deals with demographic profile of respondents. The second section explores general information of respondents regarding usage of SNS. The purpose of the exploratory section was to examine usage of SNS viz. kind and frequency and extent of their exposure with brands through SNS. In additions, the study also focuses on determining the reasons respondents follow a brand on SNS and their perception for marketers to socialize with customers on SNS.

To analyze factors affecting shopping through social networking sites, the data was collected from the third section of the questionnaire which contains nine statements. These statements were drawn from the relevant literature and were measured by five point Likert scale of agreement (running from definitely agree to definitely disagree). Further the statements were subjected to a factor analysis for identification of the key factors preferred by the respondents.

Firstly, demographic characteristics of respondents were investigated. The sample comprises of 95 male and 45 females. 35 participants were in age group of less than 25 while 93 and 12 were belonging to 25 and 35 and more than 35 years categories, respectively.

4 FINDINGS AND DISCUSSION

An analysis of findings obtained from respondents revealed several aspects regarding usage of SNS. The respondents were required to specify the social networking site/s which they use and respond the remaining questions on the questionnaire with regard to that social networking site.

All participants have shown their interest towards using SNS. With respect to time spent on SNS per week, 36 per cent said that they spent less than five hour per week on average; 46 per cent spent between 5 to 12 hours; and 18 per cent spent more than 12 hours.

a. Exposure of brands through SNS

We have analyzed respondents' viewpoint regarding their exposure to the brands through SNS. 34 percent respondent accepted that their exposure to the brands through SNS is low while 46 and 20 percent felt that their exposure is medium and high respectively. Thus, approximate two third of sample is having adequate exposure to the brands through SNS. It means marketers more use this channel for communication with consumers and also to build customer engagement with brands and companies.

b. Reasons to follow a brand on SNS

With the purpose of analyzing the motives of respondents to follow a brand on SNS, respondents were asked to rate various reasons from 1 to 5 where 1 was lowest and 5 were highest. To know the information related to brand came as first reason (mean 3.51) followed by receiving discounts and offers (mean 3.27) and being customer of the brand (3.12). Lowest rank was given to the reason "just to show off to others" (mean 1.82). We can infer that marketing through such SNS has a positive impression on the respondents. People would like to follow marketers if they provide relevant, value added information and give good offers through SNS to them.

c. Perception towards marketers who socialize with customers on SNS

We know that marketers have different reasons to socialize with customers on SNS such as creating brand awareness, customer acquisition, customer growth and loyalty, customer research etc. We have tried to analyze perception of respondents towards motives by asking them to rate these reasons from 1(lowest) to 5 (highest). Finding revealed that out of all mentioned reasons four reasons came very close in respondents' mind viz. to share information (mean 3.97), quick way to reach masses (3.94), cheap to advertise through it (3.94), easy public data availability (3.90). Other reasons viz. services to customers, consumer research were rated approximated 3.00.

Lowest rank was given to the reason "to incorporate business ethics" (mean 1.9). Thus, respondents do not consider that marketing through SNS can shape their business ethical perspective or issue related to corporate social responsibility (CSR) policies. We can infer that people do perceive marketing through SNS as purely a channel related to profitable motives of marketers rather than helping them to present as good corporate citizens.

d. Factors which influence the marketing of products on SNS

As it has been mentioned above in literature review that social networking sites in much lesser time have captured a much larger share of the communication means in India especially among youth, therefore it is relevant to analyze the factors influencing the marketing of products on SNS. Principle component analysis (PCA) with varimax rotation was conducted on 9 measurement items to screen them and identify the underlying dimensions of consumers' perception about marketing of products through SNS. The PCA produced three factors: perceived usefulness with eigen value 3.6, perceived risk with eigen value 1.9 and personal fit with eigen value 1.5. The rule of minimum eigen value of 1.0 was applied. Only those items were selected whose factor loadings were at least .60 and commonalties more than .50. PCA produced KMO value .832. The overall significance of correlation matrices was tested with the help of Bartlett's test of sphericity, which again supported the application of factor analysis. The three identified factors underlying consumers' attitudes about marketing through SNS explained 74.755 of the total variance. Table 1 shows the factors underlying the consumers' attitudes about marketing through SNS with factor loadings and Cronbach ? (reliability). Reliability of the constructs demonstrates high-internal consistency of the constructs. In each case, Cronbach's ? exceeded the 0.7 as per recommendation of Nunnally and Bernstein (1994).

Further, these items were used for confirmatory factor analysis and structural equation modelling. Composite reliability (CR) represents the shared variance among a set of observed variables measuring an underlying construct (Fornell and Larcker, 1981). As indicated in Table 2, value of CR for each factor was .853,.851 and .752 for perceived usefulness, perceived risk and personal fit respectively. CR of at least 0.6 is considered desirable (Bagozzi, 1994), thus this requirement is met for all three factors. Average variance extracted (AVE) was also calculated for each construct, resulting in AVEs of .593, .659 and .613 all values of AVE was more than 0.5 (Fornell and Larcker, 1981). Discriminant validity verifies if a determined construct is significantly distinct from other construct that are not theoretically related to it. On the basis of the criteria mentioned above, we concluded that the measures in the study provided sufficient evidence of reliability, convergent and discriminant validity.

A confirmatory factor analysis (CFA) was conducted to examine the goodness-fit of the measurement model for attitude factors. Amos version 19 was used for the structural modelling analysis.

Garver and Mentzer (1999) recommended the non-normed fit index (NNFI); the comparative fit index (CFI), and the root mean squared approximation of error (RMSEA). Therefore, the commonly applied fit indices are NNFI and CFI (>0.90 indicates good fit), RMSEA (<0.05 indicates acceptable fit), and commonly used χ2 statistic (χ2/ d.f. ratio of 3 or less).

The model provides the good fit to the data with a Chi-square (χ2) = 86.9, d.f. =33, P= .000 (p<.05). χ2/ d.f. = 2.633 is satisfactory. The value of χ2/ d.f. less than 5 is considered satisfactory to accept the model (Thomson, MacInnis, and Park, 2005). Besides χ2 and χ2/d.f. six indices, Goodness of Fit Index (GFI), Incremental Fit Index (IFI), Comparative Fit Index (CFI), Normed Fit Index (NFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA) were used to examine the model fit of the measurement model for attitude factors. Table 3 indicates, values of these six indexes obtained in the current study. CFA revealed the following values of 212 Mishra, S., Tyagi, A. these indices: CFI= .940, TLI= .909, NFI=.901, GFI=0.929, IFI=.941 and RMSEA=.097. Thus, the study meets typical cut-off criteria, the values of CFI, TLI, NFI, GFI, IFI should be equal or greater than 0.90 while the value of RMSEA should be less than 0.05.

To measure the respondents' attitudes toward marketing through SNS two statements were chosen from literature. The mean of the two items served as the index of attitudes toward marketing through SNS. The higher the index score, the more positive attitude one holds toward marketing through SNS.

4.5 Structural model analysis

With the objective of testing the proposed hypotheses we developed a structural equations model. The results are reported and shown in Table 4 and in Figure 1, respectively.

The results shown in Table 4 indicate that perceived usefulness has a positive and significant effect on attitude towards marketing through SNS, thus H1was supported. Perceived risk has negative and significant effect on attitude towards marketing through SNS. Thus, H2 was supported. Finally, personal fit with brands has a positive effect on marketing through SNS but it was not significant.

Standardized regression weights were used to evaluate the relative contributions of each predictor variable to each outcome variable. As shown in Fig 1, the factors having influence on attitude were perceived risk, perceived useful and personal fit (having value .84, .47 and .40 respectively).

5 CONCLUSION

Currently, social networking sites in India are in the limelight because of the explosion in social media among the youth. Next to the importance of SNS as social phenomena, they are a domain of interesting marketing opportunities for businesses engaged in internet marketing. Understanding the motivations of people to make use of SNS and identification of the parameters affecting the adoption of these applications are vital for marketers eager to utilize these environments as part of their marketing strategy (Park et al., 2010). Realizing the popularity of some of these sites, Indian marketers have started using them as a marketing tool. Despite the considerable amount of buzz around social networking sites, academia has paid scarce attention to them, and most existing studies consider social aspects or privacy issues rather than investigating social networks from a managerial perspective. In the present paper the emphasis is upon the analyses of the online consumer behaviour in India, hence its implications are pertinent and can be far reaching if handled sensitively.

The results achieved in the study indicate that perceived usefulness has a positive and significant effect on attitude towards marketing through SNS. In today's fast paced life, where both the spouses are working, and the mechanisation of life takes its upper hand, the positive attitude towards online shopping is a necessity of life. Hence it indicates that the perceived ease of use will enhance the perceived usefulness of the SNSs. Next conclusion derived in this study is that the perceived risk has negative and significant effect on attitude towards marketing through SNS. To overcome such reservations in attitude towards purchasing, marketers require inventing new ways to lower their potential patrons' level of perceived risk. Marketers need to implement strategies to reduce the risk in order to enhance the adoption of social network sites as a communication and marketing tool. Though online transactions are increasing, people are sceptical and not able to trust online transactions completely. For marketers, trust building has to be of utmost consideration in managing relationships and communications with consumers. One way to minimize the perceived risk in the minds of users is to instil trust viz. trust in the other party and trust in control mechanisms (Pavlou, 2003). This can be through enhancing transaction security, timely delivery of products and services, constant updates of events and offers etc. Marketers can influence the consumer trust to a large extent by facilitating transactions, installing firewalls, using authentication mechanisms and ensuring the protection of privacy and information (Bhimani, 1996; Benassi, 1999; Cassell and Bickmore, 2000). Therefore, using SNS as marketing tools needs impetus on explicit policies and data protection mechanisms in place and provide the same of customer protection and privacy as in the offline environment (Shin, 2010).Finally, last but not the least conclusion derived from the study was that the, personal fit with brands has a positive effect on marketing through SNS but it was not significant. The ultimate buying in of customer loyalty will be through personalized, skilful and sensitive experience created by the online marketing.

Practical Implications

To involve more users in the SNS, marketers and SNS providers need to develop strategies to cultivate positive attitudes towards the use of SNS. The results of present study in India pointed out that establishing personal fit with consumers and providing user-friendly web sites, and reducing the perceived risk has impact on developing positive attitudes. Many theories and programs have been developed for the change to positive attitudes, such as the direct influence of individuals, the improvement of contextual clues or the consideration of persuasive messages (Yang and Yoo, 2004). Another important consideration for marketers' is to maintain the positive attitude, which is temporary, unstable, and malleable (Thompson and Hunt, 1996). Therefore, maintenance and change of attitude should be mulled over as a complementary tool to techniques that can be used to develop user acceptance of new technologies (Yang and Yoo, 2004).

References

References

Aldridge, Alicia, Karen Forcht, and Joan Pierson .(1997), "Get Linked or Get Lost: Marketing Strategy for the Internet," Internet Research: Electronic Networking Applications and Policy, Vol.7, No. 3, pp.161-169.

Alpert, S.R., J. Karat, C.M. Brodie Karat., and Vergo J.C.(2003),"User attitudes regarding a user -adaptive e Commerce web site. "User Modeling and User Adapted Interaction, Vol.13, No. 4,pp. 373-396.

Babin,Barry J.William R Darden, and Mitch Griffin (1994), "Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value," Journal of Consumer Research, Vol.20 No. 4, pp.644-656.

Babin, Barry J. and William R. Darden .(1995), "Consumer Self-Regulation in a Retail Environment," Journal of Retailing, Vol. 71, No. 1, pp.47-70.

Batra, Rajeev and Olli T. Ahtola .(1990), "Measuring Hedonic and Utilitarian Sources of Consumer Attitudes," Marketing Letters, Vol.2, No. 2,pp. 159-170.

Bauer, R.A. (1960), "Consumer behaviour as risk taking", in Cox, D.F. (Eds),Risk Taking and Information Handling in Consumer Behaviour, Harvard University Press, Cambridge, MA, pp.22-3.

Benassi, P. (1999), "TRUSTe: an online privacy seal program", Communications of the ACM, Vol. 42 No. 2, pp. 56-79.

Bhimani, A. (1996), "Securing the commercial internet", Communications of the ACM, Vol. 39 No. 6, pp. 29-35.

Britt S.H. The Spenders. (1960), New York: Mc Graw-Hill.

Cases, A.S. (2002), "Perceived risk and risk reduction strategies in internet shopping", The International Review of Retail, Distribution and Consumer Research, Vol. 12 No.4, pp.375-94.

Cassell, J. and Bickmore, T. (2000), "External manifestations of trustworthiness of the interface", Communications of the ACM, Vol. 43 No. 12, pp. 50-9.

Constantinides, E., Lorenzo, C. and Gómez-Borja, M.A. (2008), "Social media: a new frontier for retailers?" European Retail Research, Vol. 22, pp. 1-27.

Davis, F.D. (1989), "Perceived usefulness, perceived ease of use and user acceptance of information technology", MIS Quarterly, Vol. 13 No. 3, pp. 319-40.

Davis,F.D.(1993), "User acceptance of information technology: system characteristics, user perceptions and behavioural impacts", Int.J.Man-Machine Studies,Vol.38,pp.475-487.

Donath, J.S. (1998), "Identity and deception in the virtual community", in Kollock, P. and Smith, M. (Eds), Communities in Cyberspace, Routledge, London.

Dwyer, C., Hiltz, S.R. and Passerini, K. (2007), "Trust and privacy concern within social networking sites", Proceedings of the Thirteenth Americas Conference on Information Systems, Keystone, CO, USA.

Economic Times report (2012) Companies target social media like Facebook, Twitter, Linked IN for pitching consumers, available on http://articles.economictimes.indiatimes.com/2012-12-26/news/36007968_1_kirthiga-reddy-mobile-users-facebook-users

Ericksen K. (1996)" Using self-congruity and ideal congruity to predict purchase intention: A European Perspective". Journal of euro-Marketing, Vol. 6, pp. 41-57

Ericksen M.K., M.J. Sirgy.(1992)," Employed females' clothing preference, self-congruity, and career anchorage". Journal of applied social psychology, Vol. 22, pp.208-422.

Featherman, M. S. and P. A. Pavlou .(2003), "Predicting e-Services Adoption: A Perceived Risk Facets Perspective," International Journal of Human-Computer Studies,Vol.59, pp. 451-474.

Freedman, L., (2007), "Merchant Views of personalization and lasting customer relationships. "Special report, ATO, October.

Hogg, T. (2010), "Inferring preference correlations from social networks", Electronic Commerce Research and Applications, Vol. 9, pp. 29-37.

Holbrook, M.B and Hirschman, E.C.(1982)."The Experiential Aspects of Consumption: Consumer Fantasies, Feelings and Fun" The Journal of Consumer Research, Vol.9 No.2, pp.132-140.

Gartner, Inc. "Forecast: Social Media Revenue, Worldwide, 2011-2016" 25th June 2012 (http://www.gartner.com/DisplayDocument?re f=client FriendlyUrl&id=2061016 and http://www.gartner.com/it/page.jsp?id=2092217) Accessed on 13th Jan 2013

Gefen, D. and Straub, D.W. (2000), "The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption", Journal of Association for Information Systems, Vol. 1 No. 8, pp. 1-28.

Grewal, Dhruv, Gopalkrishnan R. Iyer, R. Krishnan, and Arun Sharma (2003), "The Internet and the Price Value-Loyalty Chain," Journal of Business Research, Vol.56 No. 5, pp. 391-8.

Hoffman, Donna L., Thomas P. Novak, and Marcos Peralta (1999), "Building Consumer Trust Online," Communications of the ACM, Vol.42 No. 4, pp.80-85.

Holbrook, Morris B. and Elizabeth C. Hirschman (1982), "The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun," Journal of Consumer Research, Vol.9 No. 2, pp. 132- 40.

Horst, M., Kuttschreuter, M. and Gutteling, J.C. (2007), "Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands", Computer in Human Behavior, Vol. 23, pp. 1838-52.

Jamal, A. and Goode, M. (2001), "Consumers and brands: a study of the impact of self-Image congruence on brand preference and satisfaction," Marketing Intelligence and Planning, Vol. 19, No.7, pp.482-492.

Jarvenpaa, Sirkka L. and Peter A. Todd (1997), "Consumer Reactions to Electronic Shopping on the World Wide Web," International Journal of Electronic Commerce, Vol. 1 No. 2, pp.59- 88.

Kleijnen M., K. de Ruyter , T.W. Andreassen.(2005) Image Congruence and The adoption of service innovations. Journal of Service Research, Vol. 7 No.4, pp. 343-359.

Kilmartin, K (2012),"Marketers at risk of turning consumers into brand blockers" http://www.brandrepublic.com/research/1164079/marketers-risk-turning-consumers-brand-blockers/ Accessed on 13th Jan 2013

Kobsa A. (2007) "Privacy-enhanced personalization,"Communication of the ACM, Vol. 30, No. 8, pp.24-33.

Kuo, R.Z. and Lee, G.G. (2009), "KMS adoption: the effects of information quality", Management Decision, Vol. 47 No. 10, pp. 1633-51.

Lee, M. (2010), "The effect of cognitive absorption and network externalities on technology acceptance: an empirical study of social networking sites in Indonesia", theses and dissertations, Business Administration Department, University of Ming Chuan, Taipei.

Linn, Allison (2007), "Online Shopping Growth to Slow in the Next Decades," MSNBC, September 4, http://www.msnbc.msn.com/id/20321999/ (accessed November 10, 2008).

Luhmann, N. (1979), Trust and Power, Wiley, London.

Market Watch (2008), "Jupiter Research Finds That Social Media Has Emerged as Important Marketing Platform for Retailers During Back-to-School Shopping Season, "Market Watch, August18, http://www.marketwatch.com/news/story/jupiterresearchfinds- social-media- has/story.aspx?guid=%7B5D4FA471-3AB4-453B-A15D-7174BD0D3D93%7D&dist=hppr (accessed August 18, 2008). Mathwick,

Charla, Naresh Malhotra, and Edward Rigdon (2001), "Experiential Value: Conceptualization, Measurement, and Application in the Catalog and Internet Shopping Environment," Journal of Retailing, Vol.77 No. 1, pp.39-56.

Mayer, R.C., Davis, J.H. and Schoorman, F.D. (1995), "An integrative model of organizational trust", Academy of Management Review, Vol. 20 No. 3, pp. 709-34.

Mc Willilam, Gil. (2000), "Building Stronger Brands though Online Communities," Sloan Management Review, Vol.41 (Spring), pp.43-54.

Mehta A.(1999)," Using self-concept to assess advertising effectiveness. Journal of Advertising Research, Vol. 39 No.1, pp. 81-89.

Meimin, O. (2008)," Social Networking Sites: A Uses and Gratifications perspective", Asian Media and Information Communications Conference, Manila, Philippines. July 15

Miller, K.D., Fabian, F., Lin, S.J. (2009), "Strategies for online communities", Strategic Management Journal, Vol. 30 No.3, pp.305-22

Moon, J. and Kim, Y. (2001), "Extending the TAM for a world-wide-web context", Information & Management, Vol. 38, pp. 217-30.

Park, B., Ahn, S.K. and Kim, H.J. (2010), "Blogging: mediating impacts of flow on motivational behavior", Journal of Research in Interactive Marketing, Vol. 4 No. 1, pp. 6-29.

Pavlou, P.A. (2003), "Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model", International Journal of Electronic Commerce, Vol. 7 No. 3, pp. 69-103.

Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983), "Central & Peripheral Routes to Advertising Effectiveness: The Moderating Role of Involvement". Journal of Consumer Research, Vol.10 No.2, pp.135-146.

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., Pahnila, S. (2004), "Consumer acceptance of online banking: an extension of the technology acceptance model", Internet Research, Vol. 14 No.3, pp.224-35.

Puri, A. (2007), The web of insights- The art and practice of webnography. The Market Research Society, Vol. 49 No.3, pp. 387-408.

Razzaque, MA.( 2008), 'Social Networking: A Potential Tool for Effective Marketing', in ANZMAC 2008 Conference, presented at ANZMAC 2008 Conference, Homebush, Sydney, 1 - 3 December 2008

Reibstein, David J. (2002), "What Attracts Customers to Online Stores, and What Keeps Them Coming Back?" Journal of the Academy of Marketing Science, Vol. 30 No.4, pp. 465-73.

Rheingold, H. (1993), The virtual community: Homsteading on the electronic frontier. Reading, MA: Addison-Wesley.

Saade R.G, Nabebe F and Tan W. (2007), "Viability of the technology acceptance model in multimedia learning environments: A Comparative Study", International Journal of Knowledge and Learning Objects, 3, 175-184.

Schmugar, Graig.(2008)," The future of Social Networking Sites" [online]. path: http://www.mcafee.com/us/local_content/misc/threat_center/msj_future_social_network ing.pdf. [cited 14.5.2009].

Shin, D.H. (2008), "Applying the technology acceptance model and flow theory to Cyworld user behavior", Cyber Psychology and Behavior, Vol. 11 No. 4, pp. 12-20.

Shin, D.H. (2010), "The effects of trust, security and privacy in social networking: a security-based approach to understand the pattern of adoption", Interacting with Computers, Vol. 22 No. 5, pp. 428-38.

Shin, D.H. and Kim, W.Y. (2008), "Applying the technology acceptance model and flow theory to Cyworld user behavior: implication of the Web2.0 user acceptance", Cyber Psychology and Behavior, Vol. 11 No. 3, pp. 378-82.

Sirgy M.J. (1985) Using self-congruity and ideal congruity to predict purchase intentions. Journal of Business Research, Vol.13, pp.195-206.

Spaulding, T.J. (2010), "How can virtual communities create value for business", Electronic Commerce Research and Applications, Vol. 9, No.1, pp. 38-49.

Spors, K.K. (2008),"Enterprise: Networking Together; Firms Join Forces On Social Networks To Raise Profiles", Wall Street Journal (Eastern edition), New York, pg. B.5

Taylor, S. and Todd, P.A. (1995), "Understanding information technology usage: a test of competing models", Information Systems Research, Vol. 6 No. 2, pp.144-76

Teo, Thompson S. H. (2001), "Demographic and Motivation Variables Associated with Internet Usage Activities," Internet Research, Vol.11 No. 2, pp. 125-37.

Thompson, R.C. and Hunt, J.G.J. (1996), "In the black box of alpha, beta, and gamma change: using a cognitive-processing model to assess attitude structure", Academy of Management Review, Vol. 20, No. 3, pp.709-34.

Tikkanen, H., Hietanen, J., Henttonen, T. and Rokka, J. (2009), "Exploring virtual worlds: success factors in virtual world marketing", Management Decision, Vol. 47 No. 8, pp. 1357-81.

Utz, S. (2009), "The (Potential) Benefits of Campaigning via Social Network Sites", Journal of Computer-Mediated Communication, Vol.14 No. 2, pp.221-243.

Venkatesh, V. and Davis, F.D. (2000), "A theoretical extension of the technology acceptance model: four longitudinal field studies", Management Science, Vol.45 No. 2, pp. 186-204.

Wang, Eric T.G., His-Yin Yeh, and James J. Jiang (2006), "The Relative Weights of Internet Shopping Fundamental Objectives: Effect of Lifestyle Differences, "Psychology & Marketing, Vol.23 No.5, pp.353-367.

Waters, R., Burnett, E., Lamm, A. and Lucas, J. (2009), "Engaging stakeholders through social networking: how non-profit organizations are using Facebook", Public Relations Review, Vol. 35 No. 2, pp. 102-6.

Willis, T.J. (2008), "An evaluation of the technology acceptance model as a means of understanding online social networking behavior", theses and dissertations, Paper 568, University of South Florida, Tampa, FL, available at: http://scholarcommons.usf.edu/etd/568

Wind, Y., & Mahajan, V. (2002). Convergence marketing. Journal of Interactive Marketing, Vol.16 No .2, pp. 64-79.

Yang, H.D. and Yoo, Y. (2004), "It's all about attitude: revisiting the technology acceptance model", Decision Support Systems, Vol. 38 No. 1, pp. 19-31.

Zeithaml, Valarie A. (1988), "Consumer Perceptions of Price, Quality and Value: A Means-End Model and Synthesis of Evidence," Journal of Marketing, Vol.52, pp.2-22.