purchasing and the influence of social networking: a conceptual view”

Internet has enabled businesses to offer their merchandise through web-based applications, of which recent phenomenon includes online social networks (OSNs). This paper studies the influence of OSNs through the lens of perceived trust (PT), social norm (SN), user satisfaction (US) and perceived behavioral control (PBC) to find out how these influence participants of OSNs continuance buying intention. A model of IS continuance intention of web-based application was developed to test the above factors. The results show that trust in OSN is based mainly on the degree of the social relations that users have with their vendors, because they are members on the network, on top of their experiences of web service use. US was influenced by PBC, while US also influenced SN and PT with PT exhibiting a strong relationship with SN.


Introduction
There are two main forms of computing online today for business transactions. The traditional electronic commerce (basic website) and social computing (social networks) as a result of blending social computing with service oriented computing. Social computing is the computational facilitation of human social dynamics, as well as the use of ICT that considers social context (Maamar et al., 2011). Social computing is also about collective actions, content sharing, and information dissemination in general. On the other hand, service oriented computing (traditional website) builds applications on the principles of service offer and request, loose coupling and cross-organization flow (Maamar et al., 2011). According to the aforementioned authors, when enterprises engage web services for business needs, they are included in service compositions based on both the functionality they offer and the quality of service (QoS) they can guarantee, which implies the need for contracts.
When consumers engage and compose services, it is much more informal and dynamic. Web services are intended to be composed, and their functionality and quality of services (QoS) are interdependent with other services. Moreover, they execute remotely and with some degree of autonomy. Social networks epitomize the tremendous popularity of web 2.0 applications (Maamar et al., 2011) making users to be able to become proactive, colloquial, engage vendors in conversation to build trust before deciding to buy and continue buying.
OSNs are virtual communities for users to create public profiles, build collaborations, interact with friends and meet people based on shared interests Akwesi Assensoh-Kodua, 2016. Akwesi Assensoh-Kodua, Information and Corporate Management Department, Durban University of Technology, South Africa. (Boyd and Ellison, 2008;Kuss and Griffiths, 2011). The growth of OSNs in terms of membership and usage has been impressive over just a few years. For instance, it is reported that 39% of adults (30 years above) using Internet currently use OSN and one out of four such adults on a typical day visits OSN (Hampton et al., 2011). The OSN growth certainly presents a huge business opportunity for the digital age which, if properly managed, can create additional market to address the economic downturn being experienced today. It comes, therefore, with no surprise that OSN is undergoing intense research to establish usage patterns, motivating factors, user personality and to learn about emerging lifestyles that may affect traditional business models (Cachia et  The use of Twitter, for instance, to buy something or advertising on LinkedIn to attract members of one's network operates on different dynamics as compared to basic website and could provide a great new insight quite different from the known traditional website. For example, a company's representative joining a particular OSN of friends to announce a product offering by his company, and telling these friends that he is in charge of sales of such products avails this community of friendship the opportunity to interact in real time to clear all doubts before eventually deciding to buy. Such interaction alleviates fear of unknown vendor, assures security, builds confidence in the buyer and creates a longterm trust relationship. When this relationship is serviced well, it leads to continuous buying from this representative or company.

Doing business on OSNs
Though participants may trust direct advertisements, it is common to act upon a product recommendation from a close friend than a distance acquaintance. For instance, a group of friends wanting to watch a mo-vie at the cinema always prefer going in the company of friends than being "lone rangers" or "I walk alone actors". If participants like the services or products that a business offers, they will tell their friends, and this is likely to exert some kind of pressure on such reference others to conform to the social norms. This is where online social networking for business shows its influence. It allows word-ofmouth advertising to spread over the Internet through networks of participants locally and internationally, and can compel participants to act for social acceptance. With online social networking, that could reach a large number of people very quickly this phenomenon is unprecedented. Free social networking services such as Facebook, MySpace, Lin-kedIn, and Twitter can be amazing marketing tools if used effectively to promote one's business, and LinkedIn and Twitter are the two OSNs that have made remarkable efforts in using this technology for business purposes (Pallis et al., 2011).

How social network translate into sales.
After years of social revolution, it is still interesting to note that researchers, brands, executives, and marketers are searching for answers on how social network is making an impact on consumer purchasing decisions. How participants make the journey from testing, spinning, liking and linking an item, to actually purchasing has been a mirage.
OSNs participants are social beings, participating in variety of activities, ranging from consuming content to sharing knowledge, experiences, opinions, as well as getting involved in discussions with other participants online (Heinonen, 2011). People who may never meet physically are able to affect behavior and purchasing decisions through chatting, twitting and linking together. The OSNs have provided facilities for consumers to interact with one another, enabling them to access information, comments, reviews, and ratings of a product or services before making purchasing decisions (Heinrichset al., 2011). The OSN has become a social place where forums are created for questions and answers, comments and discussions, complimenting and criticizing products and services for consumers. This certainly (OSN sites) provides a platform to influence consumers' purchase decisions (OTX research, 2008).
In such situations, groups or individuals who own the power over consumers can affect their purchase decision (Solomon et al., 2010). For instance, Wang and Xiao (2009) state that in conforming to the social norms of groupings, the effect of group behavior is seen more among young peers when it comes to illegally downloading music from the Internet. It could, therefore, be stated that, if peers are able to influence their mates into the downloading of music illegally on the web (thus, selling that particular site to them indirectly), they could as well lure them into the payment of other items that the group cherishes, hence, enabling business to take place.
The above scenario occurred in social settings and as already hinted, a growing number of literature documents how peers affect performance, friendships and college students behavior and attitudes (Olson et al., 2010;Bettinger et al., 2014;Wu et al., 2014). Suffice this with the movie example stated above.
In the traditional settings, consumers make their purchase decisions based on information received through mass media (e.g., advertising, newspaper, television, commentaries), but nowadays, OSNs can have power to affect consumers' purchase decision (East et al., 2008) through direct communication with manufacturers and experienced participants. This situation where consumers receive direct information has an impact on their purchasing decision behavior (Hawkins and Mothersbaugh, 2010). A study by Online Testing eXchange (OTX) on behalf of DEI Worldwide (2008) disclosed that various types of OSNs have become a new source of information and consumers rely heavily on these information as much as they rely on companies websites, if not more than. The research also confirmed that 60 percent of consumers reported word-ofmouth (recommendations from other consumers online) as powerful and valuable that impacts on their purchase decision.
In a nutshell, OSNs have become more credible and relevant information source than direct information from companies, therefore, consumers seek products and companies on this platform (Bernoff and Li, 2008) to shape their actions and consuming behavior. Consumer behavior is "the study of the processes involved when individuals or groups select, purchase, use or dispose of products, services, ideas or experiences to satisfy needs and desires" (Solomon et al., 2010, p. 6). Theories used to study consumer behavior are also applicable to this study.

Extended theory and hypotheses
Having outlined the differences between e-commerce and social computing, this study now applies expectation-confirmation theory (Bhattacherjee, 2001), theory of planned behavior (Ajzen, 1991) and theory of trust (Castelfranchi and Falcone, 2010) often used to investigate consumer behavior and repurchase intentions to address its objectives. OSN is a subset of web 2.0 applications, of which e-commerce is a part. Therefore, theories applicable to e-commerce also apply to OSN except where the difference is spelt out in this paper to emphasize the concept under review.

Hypotheses.
A set of hypotheses to create the current research model to achieve the purpose of this study follows shortly. The hypotheses are logically developed from existing literatures, on the basis of the factors of user satisfaction, perceived trust (psy-chological factors) and social norm, perceived behavioral control (social factors). User satisfaction and continuance intention are selected from ECT because of their strong relationship. Social norm and perceived behavioral controls are selected from TPB because of their influence on behavioral intention. Finally, perceived trust is selected from TST, because trust plays important roles in business transactions.

User satisfaction.
Past electronic commerce studies have investigated online shopping intention using factors such as user continuance, acceptance decisions and purchase behavior (Gefen et al., 2003;Hsu et al., 2006). In particular, Bhattacherjee and Premkumar (2004) made a substantial contribution in using ECT to study user satisfaction and continuance behavior. User satisfaction is posited as a linear function that is proportional to disconfirmation which defines the discrepancy between a user pre-adoption expectation and perceived performance (Oliver, 1980;Churchill and Suprenant, 1982 Since user satisfaction is an important determinant of continuance intention, it could be implied that a dissatisfied user will not only discontinue with the use of OSN, but also may influence other users that are deemed important to him or her. This behavior of users influencing others or being influenced by others is often called social norm, subjective norm, peer influence or bandwagon effect (Kassim and Abdullah, 2008;Ifinedo, 2011). From TPB, social norm refers to the perceived peer pressure to perform or not to perform a behavior or the perception of an individual that important people would approve or disapprove of his or her performing a given behavior (Ajzen, 2008). The extant studies on customer satisfaction scarcely address the influence of satisfaction on social norm, but rather, the other way round, creating a strong justification for further investigation (Hsu and Chiu, 2004). This important premise leads this paper to test the following hypothesis: H2: Users' satisfaction with OSNs will positively influence their ability to succumb to pressure or to put pressure on others to use OSNs for business transactions.
Customer satisfaction is an overall customer attitude towards a service provider or an emotional reaction to the difference between what customers expected and what they receive regarding the fulfillment of some need, goal or desire (Hansemark and Albinson, 2004;Danesh et al., 2012). Ultimately, customers will be expected to raise satisfaction with services that are offered by an OSN when they trust the OSN (Kassim and Abdullah, 2008). Trust would develop when customers have confidence in the integrity of service providers (Wu et al., 2010) and would decide to do business with OSN of their choice, because they are satisfied with that platform (  , one could, then, say that by transitivity, perceived trust will influence continuance intention. Consequently, this paper is at liberty to state the following hypothesis: H4: Perceived trust in OSNs will positively influence continuance intention of users to use OSNs for business transactions. If customers do not trust an OSN, they will possibly be dissatisfied with the services provided by the OSN and their intentions for continued patronage could be negatively affected. This negative radiance of user satisfaction can potentially be communicated to seven to fifteen important persons. This statement is supported by a popular saying that "every satisfied customer goes to tell one to three persons, but an unsatisfied customer tells seven to fifteen others". The greater the perceived trust among people, the more favorable will be the social norm with respect to knowledge sharing (Chow and Chan, 2008). Hence, the following hypothesis is stated: H5: Perceived trust in OSNs will positively influence the ability of users to succumb to pressure or to put pressure on others to use OSNs for business transactions.

Social norm.
Previous technology acceptance studies have provided evidence for the relationship between social norm and adoption intention (Taylor and Todd, 1995; Venkatesh and Davis, 2000; Anderson and Agarwal, 2010). Their measure of social norm is similar to the interpersonal influence in which interpersonal and external influences are two components explaining social norm as an important predictor of intention to use electronic brokerage services (Bhattacherjee, 2000). In other words, the social norm is related to the normative belief about the expectation from another person. This could be formed as the normative belief of an individual concerning a reference that is influenced by the motivation to comply with the referent under discussion (Liao et al., 2006). There are research findings which provide strong justification for the relationship between social norm and continuance intention (Kwong and Park, 2008; Anderson and Agarwal, 2010; Lee, 2010). The following hypothesis is, therefore, proposed:

H6:
The ability of users to succumb to pressure or to put pressure on others to use OSNs will positively influence their continuance intention to use OSNs for business transactions.

Perceived behavioral control.
The TPB is widely applied to explain the impact of behavioral decisionmaking process of which perceived behavioral control (PBC) is a predictor of behavior (Taylor and Todd, 1995;Ajzen, 2008). PBC is the extent to which one believes to have adequate control over his or her behavior (Ajzen, 1991). In essence, the inclusion of PBC into our OSN model allows this paper to generalize the model. Many researchers have performed numerous empirical evaluations of TPB in psychology literature to discover that PBC is a combination of two distinct, but related components of self-efficacy and controllability (Sparks et al., 1997;Armitage and Connor, 1999;Ajzen, 2002;Bhattacherjee et al., 2008). Self-efficacy reflects one's conviction in his or her ability to independently perform an intended behavior, and controllability refers to one's perceived control over external resources needed to perform that behavior (Ajzen, 2002). These two components have been shown to be associated with user satisfaction and continuance intention (Manstaed and Eekelen, 1998; Armitage and Connor, 1999;Joo et al., 2000;Eastin, 2002;Trafimow et al., 2002;Hsu and Chiu, 2004). Therefore, the following hypotheses and the resultant research model exhibited in Figure 1 based upon a combination of the selected psychosocial factors from ECT, TPB and TST are made.
H7: Perceived behavioral control over OSNs will positively influence users' satisfaction with OSNs for business transactions.
H8: Perceived behavioral control over OSNs will positively influence continuance intention of users to use OSNs for business transactions.

Subject.
The study employed a field survey of social networking experts to gather data to address research objectives and hypotheses testing. The sample consisting of 317 users was randomly drawn from the expert's database. To ensure that the samples were regular participants of OSNs, only respondents who have accessed their networks at least once were eligible. The survey was administered by these experts to respondents using OSNs to buy. Although users of other OSNs were accommodated in the survey, the emphasis was on Twitter and LinkedIn users because of their growing popularity for business models (Pallis et al., 2011). The first section of the questionnaire asked respondents to indicate their preferred OSN and whether they have ever used it to buy before. If respondent answers yes, the software allows them to proceed, otherwise, shuts down without any further chance to start. An introduction letter explained to the subjects the essence of the survey and assured them of confidentiality. The online survey yielded a total of 317 responses out of which 300 were valid responses used for the analysis.

Measurement.
Five factors are measured by multiple item scales that are adopted from pre-validated measures in social science, marketing and information system studies. The measurement items were reworded to suit the OSN context. In order to ensure the modified measurement items are applicable, a pre-test was performed using a total of 45 lecturers and postgraduate students at Durban University of Technology in South Africa who uses OSN for various reasons. Several issues regarding semantic wordings, consistency of format and length of texts are raised and are factored into the model design to fine tune the measurement instrument. The measurement instrument consisted of two parts; the first part dealt with demography about the subjects and the second part dealt with items to measure the theoretical factors of the proposed OSN model. The demographic information included gender, age, and rating of the residential area among others. In order to be more precise, subjects were asked to rate using a five-point Likert scale rating, ranging from (1) strongly disagree to (5) strongly agree to measure the relative importance of measurement items. Individual scale items are adapted from previous studies. Appendix 1 shows these measurement items, their operational definitions and closely related sources. Table 1 gives a summary of the descriptive statistics of respondents who partici-pated in this study. Out of the 300 valid responses received, 55% are females. Reasonable percentages (83.33%) of respondents are Twitter or LinkedIn users. The statistics show that 16.77% of respondents are using OSNs which differ from Twitter and LinkedIn for business transactions. Most of the people (40%) fall within the age group of 26-35. This group of people is the working class spending between 1-3 hours per week on OSNs. The information provided by the respondents on their OSN usage behaviors revealed that they are experienced OSN users.  (Hulland, 1999). The reliability was measured by the estimate of internal consistency and composite reliability. Internal consistency was measured using Cronbach's Alpha, which estimates how consistent an individual responded to items within a scale (Shin, 2009). Composite reliability offers a more retrospective approach of overall reliability measure of a factor in the measurement model and estimates consistency of the factor itself including stability and equivalence of the factor (Roca et al., 2009;Suki, 2011). As shown in the last two rows of  (Raykov, 2011). The validity was measured by the estimate of convergent validity and discriminate validity. Convergent validity shows the extent to which items of a specific factor represent the same factor and is measured using a standardized factor loading which should be above 0. 5 (Fornell and Larcker, 1981). Table 2 shows that all items exhibited loadings (values in brackets) higher than 0.5 on their respective factors, providing evidence of acceptable convergence validity. Discriminate validity indicates the extent to which a given factor is truly distinct from other factors (Suki, 2011). A commonly used statistical measure of discriminant validity is a comparison of the Average Variance Extracted (AVE) with the correlated square root (Fornell and Larcker, 1981). In order to pass the test of discriminant validity, the AVE of factor must be greater than the square root of the inter-factor correlations (Fornell and Larcker, 1981). The AVE determines the amount of variance that a factor captures from its measurement items (Henseler et al., 2009). Table 3 shows the AVE values and the correlations among factors with the square root of the AVE in brackets on the diagonal.

Descriptive statistics.
The diagonal values exceed the inter-factor correlations. Therefore, it can be inferred that discriminate validity was acceptable. This study, therefore, concludes that measurement scales have sufficient validity and demonstrates high reliability.   (Hulland, 1999). The overall fit and explanatory power of the structural model are examined together with the relative strengths of the individual causal path. Figure 2 shows the result of the structural model assessment with the calculated R2 values (explanatory power) and significance of individual paths summarized.

Fig. 2. Empirical result of testing the OSN-CII
The overall model fit was assessed using six measures of the average path coefficient (APC), the average R-square (ARS), the average block inflation factor (AVIF), the goodness of fit (GoF), the average adjusted R-square (AARS) and the Rsquare contribution ratio (RSCR) to indicate how the model is good. Each of the model fit metrics is discussed according to Kock (2010). Based on Table 4 result, the OSN model has a good fit. The values of APC and ARS are significant at 5% level, whilst AVIF is still lower than 5. This gives researchers the audacity to conclude that there exist a good fit between model and data (Rosenthal and Rosnow, 1991; Kock, 2010).

Hypotheses testing.
The support for each hypothesis could be determined by examining the sign (positive or negative) and statistical significance of the t-value for its corresponding path. The WarpPLS 4.0 uses a bootstrapping technique to perform the statistical testing (t-test) of path coefficients to explain the research hypotheses. Table 6 shows the result of hypotheses testing wherein seven hypotheses are supported and one rejected. User satisfaction shows a positive influence on OSN continuance intention ( = 0.127, p = 0.0292) supporting hypothesis H1. In addition, this study shows user satisfaction to influence perceived trust ( = 0.683, p = 0.0001) supporting hypothesis H2. The importance of satisfaction in the life of people using OSN was again seen when user satisfaction should influence on social norm ( = 0.441, p = 0.0001) to support the hypothesis H3. Furthermore, perceived trust proved to be a crucial factor in business transactions on OSN by exhibiting a strong influencing relationship with continuance intention ( = 0.363, p = 0.0042) to support the hypothesis H4. The factor of perceived trust is also found by this study to influence on social norm ( = 0.264, p = 0.0025) to support the hypothesis H5.
The path coefficient between social norm and continuance intention is interestingly significant ( = 0.246) at a significance level of p = 0.0453, supporting the hypothesis H6. In addition, perceived behavioral control showed an extremely significant in-fluence on user satisfaction ( = 0.642, p = 0.0001) to support the hypothesis H7. Finally, in information technology continuance intention research, perceived behavioral control has not been thoroughly investigated. This paper has found perceived behavioral control to have a non-significant influence on OSN continuance intention ( = 1.212, p = 0.2265). This result proves to be no force in deciding to do business on OSN that is, hypothesis H8 is not supported. This could be because of the fact that in these modern days, several devices abound in a lot of varieties to access online businesses. The devices range from desktop to handheld computers such as cell phones, smartphones, iPad and one could easily access the Internet without any hustles. As expected, all hypothesized paths in the OSN model are significant at various levels except this last path H8. This result is expected, because having control over using an OSN does not always imply the continuance intention of people to use the OSN for business transactions. Note: *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed t-tests).

Empirical findings
The advancement in Internet technologies has enabled OSN users to compare prices, access general information and exchange information regarding OSN shopping experiences. This opportunity is preventing users from trading with a particular vendor if they find other vendors offering cheaper and better deals. Online social networking is gaining greater strategic importance, moving from just customer world to the business world. However, what is more, crucial is to uncover the factors that compel customers and vendors to converge on OSN for business transaction and the possible clues to determine their future continuance intentions. This study has revealed the psychosocial factors of perceived trust, social norm, and user satisfaction in that order to play important roles in influencing continuance intention. The study result generally suggests that when confidence level of trust is attained among groups or individuals, they automatically become satisfied with the act they are performing. This act may be doing business on OSN.
This result generally gives credence to the argument that user satisfaction is an important determinant of continuance intention (Oliver, 1980;Bhattacherjee, 2001). However, we, this study found perceived trust to be the most important determinant of continuance intention and not user satisfaction. This could be attributed to the fact that the study is about business, but Bhattacherjee (2001) did not consider perceived trust in his model of continuance intention. Perceived behavioral control and social norm played a more prominent role on user satisfaction, not forgetting that perceived behavioral control entails the means by which one can access OSN. The pervasiveness of portable devices such as smartphones and iPad makes it easy to access the Internet in recent days, hence, perceived behavioral control is shown not to influence directly OSN continuance intention.

Theoretical contributions.
This work has investigated four psychosocial factors of social norm, perceived behavioral control, user satisfaction and perceived trust to predict OSN continuance intention. Perceived trust came out to be the most impor-tant direct determinant of OSN continuance intention. On the one hand, users might fear supplying their credit card information to any commercial OSN business provider because of online security threats which is a common phenomenon nowadays. On the other hand, a commercial OSN service provider may fear the effort of network hackers who may intend to steal credit card numbers for their selfish interests. This cycle of suspicion obviously borders on trust which is an important issue to be considered when talking about intention to do business whether online or offline. Our findings are, therefore, not surprising when perceived trust emerged as the greatest influencing factor that will compel users to indulge in OSN for business transactions. This gives support to several other studies that have focused on various issues of trust in electronic commerce (Awad and Ragowsky, 2008;Choudhury and Karahanna, 2008;Kim et al., 2008;Vance et al., 2008). It can be deduced from our analysis that users will only deal with OSN that they perceive to be trustworthy to provide them with services or products. However, we trust does not come overnight, but through a process and continuous interactions between a particular OSN and customers. The paper, therefore, makes its first theoretical contribution by suggesting that OSN vendors search for holistic strategies to build the initial trust that users look for before creating the intention to use their OSN for business transactions.
The social norm or peer pressure factor is found to be the next direct determinant of OSN continuance intention. Following the line of argument that social norm is a strong influencing factor to create an intention (Sripalawat et al., 2011), this study lends support to that result by finding social norm to be the second most important determinant of OSN continuance intention. Consequently, the second theoretical contribution of this study is that OSN business providers who intend to win more customers should adopt the strategy of peer pressure to whip users in using their websites. In particular, the popularity of social media can be explored to create interpersonal interactions among blogs and networking communities. After they come to the OSN, electronic vendors should be honest, mindful of privacy and security of the users, as well as provide them with improved services and products. The bulk of our respondents are young people between the age of 18 and 35 who do business online. The social networks created through LinkedIn, Twitter, Facebook and other websites are more than just a static hobby, but also they are a complex support circle. For these young people, an OSN mirrors the social groups established by the older generations of some dark ages ago. As a result, all sometimes rely on advice from people that trust to support our decision-making process.
The third most important direct determinant of OSN continuance intention, according to the results of this study is user satisfaction. Our findings add confirmation to the several discussions and extensive studies that user satisfaction has received as a topic of interest throughout the psychology, marketing, management and information system literature. This study lends support to the popular theory that customer satisfaction is a post-purchase attitude formed through a mental comparison of service and product quality that a customer expected to receive from an exchange, level of service and product quality the customer perceives from the exchange. This study, therefore, contributes to the body of user satisfaction knowledge that OSN vendors should strive to make customers happy by being honest, providing quality services and products in as much as they receive these from their social network providers. The indirect influence of perceived behavioral control on OSN continuance intention through user satisfaction, the greatest coefficient factor ( = 0.642), suggests that when infrastructures needed to access OSN are within the reach, the user satisfaction level rises and users would intend to continue using OSN for business transactions. Findings from this research add confirmation to the important role that technology plays in solving numerous customer hustles. These findings are consistent with previous offline research where customer participation in OSN was shown to lead to greater satisfaction (Cermak et al.) and higher expected benefits from OSN. The notion that customers actively participate in the process of co-creating value with firms is attracting increasing attention from academia (Prahalad and Ramaswamy). Based on the strong influence of user participation in OSN that re found in this study, the current research can be viewed as adding value to existing knowledge and extending this stream of academic research in a new direction (that is doing business with OSN). The concept of perceived behavioral control has been discussed to be the means by which an individual can access a technology and the confidence that he or she is capable of performing a given behavior. In addition, this implies the perception of volitional control or the perceived difficulty towards the behavior affecting the intent. Yet, our research findings proved that perceived behavioral control is not significant when it comes to directly forming intention. This again supports Kwong and Park who found that the influence of perceived behavioural control on continuance intention was insignificant in a research conducted on college students.
This could be attributed to the computer and knowledge of Internet services which are now common skills among the youth who believe they would be able to use OSN for business transactions regardless of circumstances. A word of caution here is that, whenever business transactions are involved confidence in one's ability becomes very important.
So the youth should have re-examined themselves before concluding. External control factors such as financial resources might be more important for the younger users than internal control factors such as abilities and skills. With the upsurge of electronic learning these days, proving to be the highest mode of learning, probably it could take the youth only few seconds to master transacting business on OSN platforms.

Limitations and future research.
Online surveys generally have some intrinsic limitations, and this study is not exceptional. Respondents to the survey are self-selected, who may have own agenda for participating in the study rather than being randomly or scientifically selected. Moreover, if the data a reself-reported, there is no guarantee that participants would provide accurate information. Future research studies should take into cognizance the above limitations of survey study.

Conclusion and recommendation
This study synthesized three major literature to venture into quite a new dimension of online social network (OSN) for business transactions. It sought to unravel the psychological and sociological factors that determine OSN continuance intention, instead of the wellknown electronic commerce models. The two platforms are not the same, but with a traditional electronic commerce mindset, it is hard to see the difference between a presence on OSN as different from the electronic commerce website. After applying expectationconfirmation theory (ECT), theory of planned behavior (TPB) and theory of social-cognitive trust (TST) to build a new model that predicts OSN continuance intention, findings suggest that perceived trust, social norm and user satisfaction are crucial psychosocial determinants of OSN continuance intention. Perceived behavioral control was not seen to play a significant role on continuance intention, but very significant in relation to user satisfaction. It should be borne in mind by OSN vendors as a way of recommendation that OSN is more than a platform for interaction. Consequently, vendors should listen to what customers say and provide positive and timely feedbacks, seeing it as an opportunity to co-create new products and services. A social business does not simply sell products, but also customer experience and satisfaction. 3 In the future, I will consider OSN for business activities as my first choice.
4 I intend to continue using OSN for business activities.
5 I intend to continue recommending the use of OSN for business activities.
6 My intention is to continue using OSN for business activities rather than traditional shopping