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An Exploration of Social Networking Sites (SNS) Adoption in Malaysia Using Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) And Intrinsic Motivation

Goh Say Leng, Suddin Lada, Mohd Zulkifli Muhammad, Ag Asri Hj Ag Ibrahim and Tamrin Amboala
 
Goh Say Leng, Lecturer of Computing Science, SSIL, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. Postal Address: SSIL, Universiti Malaysia Sabah- Labuan International Campus, 87000 Labuan F.T., Malaysia. Author's Personal/Organizational Website: www.ums.edu.my Email: gohsayleng@yahoo.com
Goh Say Leng is a lecturer of Computing Science at Labuan School of Informatics Science, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. His current research interests are E-Commerce and Computing Science.
Suddin Lada, Lecturer of International Marketing, SPKAL, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. Postal Address: SPKAL, Universiti Malaysia Sabah- Labuan International Campus, 87000 Labuan F.T., Malaysia. Author's Personal/Organizational Website: www.ums.edu.my, Email: suddin@ums.edu.my
Suddin Lada is a lecturer of International Marketing Programme at Labuan School of International Business and Finance, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. His current research interests are Marketing, Market Orientation and Organizational Performance.
Mohd Zulkifli Muhammad, Lecturer of Islamic Finance, SPKAL, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. Postal Address: SPKAL, Universiti Malaysia Sabah- Labuan International Campus, 87000 Labuan F.T., Malaysia. Author's Personal/Organizational Website: www.ums.edu.my, Email: zulrider@yahoo.com
(please use to correspond with the authors) Mohd Zulkifli Muhammad is a lecturer in Islamic Finance Program at Labuan School of International Business and Finance, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. His areas of interest are Islamic Banking, Islamic Finance, Takaful, Banking Services and Trade Financing and Islamic Financial System.
Ag Asri Hj Ag Ibrahim, Dean of SSIL, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. Postal Address: SSIL, Universiti Malaysia Sabah- Labuan International Campus, 87000 Labuan F.T., Malaysia. Author's Personal/Organizational Website: www.ums.edu.my Email: awgasri@ums.edu.my
Ag. Asri Hj. Ibrahim is a Dean at Labuan School of Informatics Science, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. His current research interests are Sonification, Usability, Usability Inspection and Evaluation and Human Computer Interaction.
Tamrin Amboala, Lecturer of Management Information System, SSIL, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. Postal Address: SSIL, Universiti Malaysia Sabah- Labuan International Campus, 87000 Labuan F.T., Malaysia. Author's Personal/Organizational Website: www.ums.edu.my Email: ramdzan_trn@yahoo.com
Tamrin Amboala is a lecturer of Management Information System at Labuan School of Informatics Science, Universiti Malaysia Sabah- Labuan International Campus, Labuan F.T., Malaysia. His current research interests are Business Process Reengineering and Methodologies and Redesigning Enterprise Processes for E-Business.
 

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Abstract

The objective of the paper is to explore the factors that encourage students to adopt social network sites (SNS) in Malaysia and to use the study’s findings to develop guidelines for SNS providers on how to maximize the rate of adoption. A conceptual model of Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and intrinsic motivation is proposed and empirically tested in the context of SNS usage. Structural Equation modelling was used on the survey data from 283 university students to test the model fit and corresponding hypotheses. The results show that both TAM and TPB were supported in their predictions of SNS usage intention and perceived enjoyment is a more significant antecedent of attitude as compared to perceived usefulness. Other than communicating with others, the users are looking for fun and enjoyment from using SNS. The relationships between the factors were also presented. Theoretical and managerial implications are discussed at the end of the article. The paper has addressed two limitations that provide opportunities for other researchers to explore them in depth in the future in the similar field of social network sites (SNS). The limitations are presented in the conclusion’s part. For researchers, this paper provides a framework to identify and understand the way the potential key factors contribute to the adoption of SNS. For practitioners, this framework lists the features that specifically attract SNS users. Understanding users’ preferences is of major importance in ebusinesses for making strategic decisions to increase user satisfaction, as well as improving the performance of the business.

Keywords

Social network sites (SNS); Technology acceptance model (TAM); Theory of planned behaviour (TPB); intrinsic motivation.

INTRODUCTION

"The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it". (Weiser, 1991).
Social Network Sites (SNS) are a new emerging genre of community-based websites, which provide an ideal platform for sharing the interests and social interaction amongst various ethnic groups having common thoughts on a particular topic or theme. Various methods are used to imitate a dialogue amongst the community members, and the most commonly used mediums are emails and instant messaging. According to Boyd and Ellison (2007), Social Network Sites (SNS) can be characterize as web-based services that allow individuals to 1) construct a web presence usually including a photo and descriptors like location, age, study concentration and interests, 2) publicly display a list of other users with whom they share a connection, and 3) to traverse those list of connections to view the profiles of others within the system. Social Network Sites (SNS) are community building websites that allow people to share interests or activities and explore the interests or activities of others. SNSs particularly evolve around special interests or shared contexts like students populations at universities (Lampe et al., 2007), i.e. students use them typically to stay in contact, communicate with and “spy” on their online friends. Studies in the U.S. which suggest that university students will use SNS to communicate mainly with their university friends chatting, joking and organising their offline meetings and group work will resonate in the UK, and in other sectors. Students will probably social network whilst they are at their computer studying rather than at separate times (Golder et al., 2007). Table I, lists a number of SNS out of hundreds over available in the market. As of this writing, there are hundreds of SNSs, with various technological affordances, supporting a wide range of interests and practices.
This study focuses on new channel of communication and information technology (IT) adoption in a developing country, namely Malaysia, where social network sites (SNS) is still emerging but offers potential benefits to consumers in that country. Applying Technology Acceptance Model (TAM) model by Davis (1989) was based primarily on its parsimony and predictive power, which makes it easy to apply in different information system devices (Amin et al., 2007; Guriting and Ndubisi, 2006). Furthermore, TAM provides a way of critically understanding the relationships between various variables namely; perceived usefulness, perceived ease of use and usage intentions. In addition, this study integrated theory of planned behavior (TPB) by Fishbein and Azjen (1975), and intrinsic motivation by Deci (1975) to provide better understanding on SNS adoption factors among university students. Furthermore, SNS vendors would be eager to know more about the underlying factors affecting the adoption of SNS among users and subsequently the directions of improvement for their products. In fact the business model is getting increasingly competitive and challenging with emergence of new SNS (Boyd and Ellison (2007).

1.1 Study motivation

Objectively, this study set out 2 main reasons for the study of Social Network sites (SNS). Firstly, the output of this study will be of importance in explaining the causes leading to the university student's adoption of SNS. Secondly, despite the SNS gaining acceptance in universities around the world, the study on students’ adoption of SNS is still unexplored fully in Malaysia. In other words, the study’s findings on factors influencing SNS adoption in Malaysia may provide useful insights for other developing countries in this part of the world. In the Asian region, the giant three in terms of the number of internet users are China, South Korea and Taiwan (Shih and Fang, 2004; ACNielsen, 2001) while Hong Kong and Singapore are regarded as the leaders in the adoption of internet banking (Amin et al., 2007; Shih and Fang, 2004). Studies tend to focus on these countries, for example, the Shih and Fang’s (2004) study of Taiwan and Tan and Teo’s (2000) study of Singapore, but few studies appear to have been carried out in lesser developed countries such as Malaysia. The aim of the study is thus to propose a conceptual framework to help better understand the process of the adoption of SNSs in Malaysia and to use the study’s findings to develop guidelines for SNS providers on how to maximize the rate of adoption.
The paper proceeds as follows. This paper contains of 4 sections. In the first section, we present the research model, and in section two, we provide the discussion on literature and the development of related hypotheses. The discussion on research methodology is in section three, and the fourth section is on findings. This paper concludes by discussing the contributions, practical implications and limitations of the study.

2. Literature review

2.1 An overview of SNS studies

Social network sites (SNS) are increasingly attracting the attention of academic and practitioners intrigued by their affordances and reach (Boyd and Ellison, 2007) and Social Network Sites (SNS) have achieved phenomenal success since the launch of sixdegrees.com in 1997 (Jim, 2008). Original sites such as Friendster, Lunarstorm and MiGente, are now all dwarfed by the phenomenally successful Myspace (Boyd and Ellison, 2007), and Facebook (Consumer Affairs, 2006). A useful historical record of the development of Social Network sites was made by Boyd and Ellison in 2007 (Donath, 2004), although more work is needed to understand the gratifications delivered, how users derive a sense of identity and the cross cultural implications to users. Social science researchers have begun to investigate what the impact of this might be on society. Typical articles have investigated issues such as Identity (Boyd, 2006), Privacy (Gross, 2005), E-learning (Mazer et al., 2007), Social capital (Ellison et al., 2007) and Teenage use (Boyd, 2007). A special issue of the Journal for Computer-Mediated Communications was dedicated to studies of social network sites.

2.2 Model, construct, and hypotheses development

TAM is one of the most influential extensions of Ajzen and Fishbein’s theory of reasoned action (TRA) in the literature. It was developed by Fred Davis and Richard Bagozzi (Bagozzi et al., 1992; Davis et al., 1989). TAM replaces many of TRA’s attitude measures with the two technology acceptance measures— ease of use, and usefulness. TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. Later, Azjen and Fishbein (1985, 1991) introduced and tested extended version of TRA called Theory of Planned Behavior (TPB) to predict usage intention by introducing ‘Perceived Behavioral Control’ as new predictor. Perceived behavioural control reflects perceptions of internal and external constraints on behaviour (Taylor and Todd, 1995). It describes a user’s perception if they have the necessary resources, capability and a sense of control in performing the behaviour (Lu et al., 2008). Much effort has been devoted to modify TAM for different IS applications and use contexts other then the workplace. These modifications and extensions of TAM are summarized in Table II (see appendix). Extrinsic motivation refers to the performance of an activity because it leads instrumental rewards that are distinct from the activity itself (Zhang et al., 2008). Intrinsic motivation refers to the performance of an activity for no apparent reinforcement other than the process of performing the activity per se (Davis et al., 1992). Researchers found that people will spend more time and effort on task with high level of intrinsic motivation. Intrinsic factor does in fact provide for better explanation of IT adoption (Zhang et al., 2008).
In addition with the ability of this model, Mathieson (1991) found that TAM explained over 69 per cent of the variance in college students’ behavioural intentions to use spreadsheets, while TPB explained approximately 62 per cent. TAM was superior in its ability to explain students’ intentions to use shop-bots in an internet purchasing activity (Gentry and Calantone, 2002). In applying TAM to student use of the internet, Anandarajan et al. (2000) found that perceived usefulness was related to time spent on the internet. Ease of use correlated positively with use of the internet for business activity. In Selim (2003) investigation, suggested that students’ course web site use tended to be greater when the site was viewed as being useful and easy to use. In a partial test of the theory of planned behaviour, George (2002) reported that attitude was related to intention to use the internet for purchasing products. Furthermore, intention was linked to actual purchasing behaviour. To summarize, existing evidence indicates that TAM and TPB is a powerful predictor of users’ technology acceptance among college students in India (Fusilier and Durlabhji, 2005). Although fewer studies have investigated TPB in the technology usage context, it has also appears respectable as an explanatory framework. However, in this study we focus only on testing the social networking sites using the integrated model of TAM & TPB, rather than testing the extended model with social effect variables.

2.3 Perceived ease of use (PEOU)

PEOU is defined as the degree to which the prospective user expects the potential system to be free of effort (Davis et al., 1989). There is theoretical and empirical evidence supporting Perceived Ease of Use (PEOU) as one of the key determinants to information system (IS) use (Guriting and Ndubisi, 2006; Ndubisi et al., 2003; McKechnie et al., 2006; Adams et al., 1992). In Malaysia, previous studies have well documented the importance of perceived ease of use in explaining Information System usage intentions since was first introduced by Davis. For instance, mobile banking in Malaysia (Amin et. al., 2007), internet banking acceptance (Ramayah and Suki, 2006). Furthermore, Amin et al. (2007) found that there is a significant relationship between perceived ease of use and mobile banking usage intentions by Malaysians. The significant impact between perceived ease of use and usage intentions is also found in Kleijnen et al. (2004) and Wang et al. (2003) in Netherlands and Taiwan respectively. Researchers of online services have built, evaluated, and modified numerous frameworks to understand the adoption of online service since the online services were first introduced. Kling (1994) argued that online service should be developed based upon interactive features, multimedia content, and capacity for inexpensive customization; Dabholkar et al. (1996) and Davis et al. (1989) found ease of use and fun to be important factors in adoption. Based on these findings, the researchers believe that perceived ease of use is important in explaining the SNS adoption/usage intentions among university students. In line with this, we propose the following hypotheses:
H1: Perceived ease of use positively affects perceived usefulness of SNS.
H2: Perceived ease of use positively affects attitude to use SNS.

2.4 Perceived usefulness (PU)

Perceived usefulness was defined by Davis (1989) as: “the degree to which a person believes that using a particular system would enhance his or her job performance”. Earlier research on the adoption of innovations also suggested a prominent role for perceived ease of use (Tornatzky and Klein, 1982). Based on Davis (1993) arguments in job related productivity, performance, and effectiveness study, PU has a direct effect on intention to use over and above its influence via attitudes (Taylor and Todd, 2001). Furthermore, PU has been constantly identified as an important driver of behavior intention to use a new system (BI) and actual system use (B) both in offline and online technology acceptance research (Venkatesh and Davis, 2000). In Malaysian environment, prior researchers have found significant relationship between perceived usefulness and usage Intention (Amin et al., 2007; Ramayah and Suki, 2006; Ndubisi et al., 2001). Positive relationship between perceived usefulness and usage Intention was found in mobile banking acceptance (Amin, 2007), mobile personal computer usage (Ramayah and Suki, (2006) and, Ndubisi et al., (2001) confirms the perceived usefulness of information technology among entrepreneurs in Malaysia. Given the focus of this study on the SNS, the definition of PU was modified to “the extent to which a user believes that using the SNS will most enhance his or her task outcomes.” A hypothesis is proposed for PU:
H3: Perceived usefulness positively affects attitude to use SNS.
H4: Perceived usefulness positively affects intention to use SNS.

2.5 Perceived enjoyment (PE)

Enjoyment factor is used in many studies to represent intrinsic motivation in discussion of how intrinsic motivators influence individuals IT acceptance behaviour (Zhang et al., 2008). Perceived enjoyment is defined as the extent to which the activity of using a technology is perceived to be enjoyable in its own right, aside from any performance consequences resulting from technology use (Venkatesh, 2000). This definition is also supported by Davis et al. (1992). When a technology is fun and pleasing to use, users will be intrinsically motivated to adopt it (Lu et al., 2008). Previous studies have documented the importance of perceived enjoyment particularly in electronic usage. (Amin et al., 2007; Nysveen et al., 2005., Teo et al., 1999; Igbaria et al., 1995). According to Nysveen et al. (2005), perceived enjoyment and usage intention of mobile chatting have significant correlation. In early study by Teo et al. (1999) also found that perceived enjoyment has positive correlation with the frequency of internet usage. However in more recent findings by Amin et al. (2008) in SMS exam result query system model (SERQSM) study found that there is no relationship between perceived enjoyment and usage intentions. Moreover, Igbaria et al. (1995) also noted that perceived enjoyment does not significantly affect the acceptance of data processing systems. Based on the above findings, we propose the fifth hypothesis.
H5: Perceived enjoyment positively affects attitude to use SNS.

2.6 Attitude (A)

Attitude has long been identified as a caused of Intention (June et al., 2003). According to Azjen and Fishbien (1975) attitude can be classified into two main construct, attitude toward the objects and attitude toward the behavior. Based on Fusilier and Durlabhji (2005) study on college students in India, they found that the effect of attitude on intention appeared to be attractive with subjective norm rather than as a main effect. Results suggested that those with highly positive attitudes were relatively unaffected by subjective norm or others’ opinions. Hence, we would expect that attitude has a positive influence on behavioral intention to use social networking sites.
H6: Attitude to use SNS positively affects intention to use SNS.

2.7 Social norms (SN)

Subjective Norm is defined as a “person’s perception that most people who are important to him think he should or should not perform the behavior in question” (Fishbein and Ajzen, 1975, p. 302). Social norm or normative pressure direct effect on behavioral intention has been validated in many previous studies based on TRA and TPB model (Ajzen, 1991; Ajzen and Fishbein, 1980; Nysveen et al., 2005; Amin et al., 2007; Kleijnen et al., 2004). Amin et al. (2007) found social norm to be important construct that explains the usage of mobile banking in Malaysia. Furthermore, Nysveen et al. (2005) noted that Social Norm is important variables to explain the success of the system use. Technology usage in workplace also found the social norm as essential elements in the development of people intention to use wireless finance in Netherlands (Kleijnen et al., 2004). Since TRA & TPB has been successfully applied in online consumer behavior, technology acceptance and system use (see Fishbein and Ajzen, 1975; Ajzen and Fishbein, 1980; Pavlou, 2003), SN is proposed as a direct antecedent of behavioral intention in this study. One hypothesis is proposed for SN:
H7: Social Norms positively affects intention to use SNS.

2.8 Perceived behavioral control

According to Azjen (1991) in Theory of Planned Behavior (TPB), “perceived behavioral control” relates to an individual’s performance of a certain behavior is determine by his or her intent to perform that behavior. Attitudes are informed by beliefs, norms are informed by normative beliefs and motivation to comply, and perceived behavioral control are informed by beliefs about individual’s possession of the opportunities and resources needed to engage in the behavior (see Azjen, 1991 in Jeoy f. George, 2002). Previous studies have documented the importance effects of perceived behavioral control in usage intention in different countries (George, 2005; Jaruwachirathanakul and Fink, 2005; Fusilier and Durlabhji, 2005). Based on the prior research, this study hypothesized the following:
H8: Perceived behavioural control positively affects intention to use SNS.
H9: Perceived behavioural control positively affects actual use of SNS.

2.9 Intention

Studies have supported the notion that behavioral intentions are found to have a positive effect on behavior (see Hung et al., 2003; Tung, 2004; Nysveen et al., 2005 in Amin et al., 2007). Finally, given a sufficient degree of actual control over the behavior, people are expected to carry out their “intentions” when the opportunity arises. “Intention” is thus assumed to be the immediate antecedent of behavior (Azjen, 1991). In summary, attitude toward the behavior, social norm, and perception of behavioral control lead to the formation of a behavioral intention. Based on the above arguments, the following hypotheses are presented:
H10: Intention to use SNS positively affects actual use of SNS.

3. Methodology

The aim of this research is to explore the factors that encourage students to adopt social network sites (SNS) in Malaysia and to use the study’s findings to develop strategies for SNS providers on how to maximize the rate of adoption. The study was conducted on the first quarter of 2009 by using questionnaire survey. It has basically two sections, A and B. Section A was used to gather demographic information of the respondents while section B was used to measure the constructs in the research model by using a 5-point Likert scale, with options ranging from strongly disagree to strongly agree. Most of the measurement items were adapted from previous research with minor modifications to suit the research context. The Items measuring actual SNS usage, intention to use SNS and perceived enjoyment (Pikkarainen et al., 2004), of using SNS were adapted from Moon et al. (2001). Meanwhile, items measuring attitude, subjective norm and perceived behavioural control were adapted from Taylor and Todd (2001). The items measuring perceived usefulness and perceived ease of use were adapted from Davis (1989). The questionnaire was drafted and then reviewed by research group members for refinement, followed by a pre-test where it was further revised. The questionnaires were distributed among students of University Malaysia Sabah (Labuan) by using stratified sampling method. The respondents consist of students from all faculties and from year one to final year. A total of 300 responses have been received, of which 283 are usable. Incomplete returned questionnaires have been eliminated.

4. Data analysis and result

Descriptive information of the sample is shown in Table III. As reported, most of the respondents (31.1%) surf Internet more than 15 hours weekly. Only 3.5 % do so less than an hour weekly. The most popular SNS among the respondents is Friendster where 95.4% are using it, followed by Facebook (43.8%), Tagged (33.9%), MySpace (23%), Hi5 (21.9%) and so on. The proposed model was evaluated using Structural Equation Modelling (SEM) analysis which consists of measurement model and structural model assessment. The measurement model represents how measured variables come together to represent constructs while structural model shows how constructs are associated with each other (Hair et al., 2006). AMOS 16.0 was the statistical software used in the study.
Confirmatory factor analysis (CFA) was conducted to test the measurement model. A total of 3 items were dropped from further analysis due to cross loadings. They were one item from perceived usefulness, one item from perceived behavioural control and one item from behavioural intention. After re-specification, 19 items were retained. As shown in Table IV, Cronbach‘s alphas for all the constructs were over 0.7 showing good scale reliabilities (Bagozzi et al., 1998). Most of the factor loadings for the items were over 0.7 while the average variance extracted (AVE) and construct reliability (CR) for each construct were over 0.5 and 0.7 respectively suggesting that the scale has good convergent validities as shown in Table IV.
The conservative approach for establishing discriminant validity is by comparing the average variance extracted (AVE) for each factor with the squared inter-construct correlations associated with the factor (Hair et al., 2006). Almost all average variance extracted (AVE) were greater than the corresponding inter-construct squared correlations as shown in Table V thus showing discriminant validity.
In addition, principal component analysis (PCA) was also conducted to show convergent and discriminant validities as shown in Table VI. All items have high loadings on their related factors and low cross loading indicating convergent and discriminant validities.
The fitness of the measurement model is shown in Table VII. The values for selected key fit indices were within the threshold of the recommended values, indicating that the measurement model provided a good fit to the data. Next, the structural model fit is examined as shown in Table VIII. The fit indices for the structural model were comparable to the measurement model, providing evidence of good overall fit. The result of the structural model analysis and hypothesis testing are shown in Figure 2 and Table VIII respectively.

5. Discussion

Generally, the R square for perceived usefulness, attitude, behavioural intention and actual use were 60%, 76%, 72% and 28% respectively indicating the research model has good predictive ability. Almost all of the hypotheses were supported except H2, H7 and H9. Perceived ease of use has significant effect on perceived usefulness, supporting H1 and corroborating results of previous researches on TAM. In other words, if a user feels that a particular SNS is easy to use, then he or she will be seeing it as useful. Perceived ease of use has no direct effect on attitude, rejecting H2. It was not surprising as according to Davis, perceived usefulness mediated the effect of perceived ease of use on other factors (Davis, 1989). Perceived usefulness strongly affected attitude and behavioural intention and thus supporting H3 and H4. In other words, if a user notices the usefulness of a particular SNS, then he or she will be feeling good about it and more willing to use it.
Perceived enjoyment has significant effect on attitude towards SNS, supporting H5. In fact, the perceived enjoyment is a more significant antecedent of attitude as compared to perceived usefulness, supporting previous studies which argued that perceived usefulness played a critical role in work related environment only (Moon and Kim, 2001). Other than connecting with others, the users are looking for fun and enjoyment from using SNS. In other words, if a particular SNS can give enjoyment and happiness to a user, then he or she will be feeling good about it. Attitude strongly affects behavioural intention, supporting H6. In other words, if a user feels good about a particular SNS, then he or she will be more willing to use it. Unexpectedly, social norm has no direct effect on intention and thus rejecting H7. Prior studies found that the effect of social norm on intention is more significant in mandatory-usage context compared to voluntaryusage context as is the case with SNS (Chun et al., 2006).
In addition, subjective norm has been found to be more important predictor for people with no prior experience and in early stages of system development (Taylor and Todd, 1995). Generally, the respondents might be lacking of experience in using SNS. Perceived behavioural control positively affects intention, supporting H8. In other words, if a particular SNS can solve a user’s internal and external constraints such as resources, knowledge, skills and ability in using SNS, then he or she will be more willing to use it. However, no direct effect is observed between perceived behavioural control and actual usage of SNS, rejecting H9. Finally, H10 is supported where intention to use SNS positively affects the actual use of SNS validating the established link between intention and actual behaviour. Generally, 28% of the variances in actual use were explained by intention. In other words, there are other factors other than intention those influence the actual use, and therefore opening up possibilities for future research.
Separate analysis were also conducted to observe the differences between IT and business students. Both groups indicated adequate model fit. The result of the structural model analysis for each group are shown in Figure 3 and Figure 4 (see appendix) while the result of hypothesis testing for each group are given in Table X and Table XI. Perceived ease of use is a more important antecedent of perceived usefulness for IT students as compared to business students. Previous studies observed that the more the user experienced, the lower the effect of PEOU to PU (Bailey and Pearson, 1983). The IT students are assumed to be lacking of experience in using SNS. It is also possible that, IT students are more inclined to associate usefulness with ease of use due to education background. User friendliness is indeed a main priority in software development and tends to dictate the success or usefulness of a system. 68% of variances in perceived usefulness were explained by perceived ease of use for IT students as compared to 48% for business students.
Perceived enjoyment has significant effect on attitude towards SNS for both IT and business students. In fact, perceived enjoyment is a more important predictor of attitude than perceived usefulness for both groups, suggesting the importance of intrinsic motivation in user adoption of SNS. 86% of variances in attitude were explained by perceived usefulness and perceived enjoyment for IT students compared to 66% for business students. Social norm positively affects intention to use SNS for IT students but has no direct effect on intention to use for business students. Subjective norm has been found to be more important predictor for people with no prior experience and in early stages of system development [19], supporting the earlier assumption that IT students might be lacking of experience in using SNS. Perceived behavioural control positively affects intention to use SNS for business students. On the other hand as expected, perceived behavioural control has no direct effect on intention to use for IT students, as IT students face less constraint internally and externally in using SNS as they are more equipped with IT skills and resources. 72% of variances in intention were explained by perceived usefulness, attitude and social norm for IT students while 86% of variances in intention were explained by perceived usefulness, attitude and perceived behavioural control for business students. The hypothesis testing results for both groups were highly consistent with the general results as shown in Table XI. All of the hypotheses testing results were same except H7 and H8.

6. Conclusion

While shifting from offline to online is widely believed to be the theme of current service industry evolution around the world, research into online news service is still in its infancy. The Internet’s unique nature of facilitating multifaceted interactive communication and virtual interpersonal/inter-organizational relationship is mostly uninvestigated in prior information system acceptance research. The study shed lights on the adoption factors of SNS among university students from the integrated perspectives of TAM, TPB and intrinsic motivation. The relationships between the factors were also presented. Based on the discussions earlier, the following guidelines were provided for SNS vendors for product improvement. One important aspect of SNS that the vendor cannot afford to neglect is user friendliness, as user’s perception on usefulness relies heavily on his perception of ease of use. The vendor should focus on creating useful functions which could increase the perceived usefulness of SNS as a whole. The vendor could deploy the right marketing mix so that people at large notice and aware of the usefulness and functions of SNS as the user will feel good and more willing to use a particular SNS if he or she notices its usefulness.
The results of the study highlighted the importance of intrinsic motivation in user adoption of SNS. SNS vendors may consider integrating fun factor into their sites such as introducing entertainment rich functions which could be games, video sharing, creative contents, and so on which can keep the users happy. The vendor could strive to keep the users feeling good of their SNS as user is more willing to use a particular SNS if he feels good about it. With respect to perceived behavioural control, the vendor can add help functions and guidelines for user. In addition, tools that allow user to gain control on the appearance of user’s profile display would be an attractive provision. Next, the users would be glad to have web pages that load quickly without the need to have high connection bandwidth. Last but not least, the vendor may consider providing free access to users continuously if possible. For researchers, the study supported the arguments from previous studies;
• Perceived usefulness played a critical role in work related environment only (Moon and Kim, 2001).
• Effect of social norm on intension is more significant in mandatory-usage context compared to voluntary usage context (Chun et al., 2006).
By comparing the structural analysis results for IT and business students, we found that perceived enjoyment again appeared as the more dominant predictor on attitude compared to perceived usefulness for both groups, highlighting the importance of intrinsic motivation in the study. We also notice that the following arguments were in agreement when indicating that the IT students were lacking of experience in using SNS as discussed earlier.
• The more the user experienced, the lower the effect of PEOU to PU (Bailey and Pearson, 1983).
• Subjective norm has been found to be more important predictor for people with no prior experience and in early stages of system development (Taylor and Todd, 1995).
There are limitations in the study as the samples are taken from only one institution of higher learning in Malaysia. In addition, the data security factor was omitted in the study. Future studies may include data security factor as one of the antecedents for attitude.

Tables at a glance

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Table 1 Table 2 Table 3 Table 4
 
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Table 5 Table 6 Table 7 Table 8
 
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Table 9 Table 10 Table 11 Table 12
 

Figures at a glance

Figure 1 Figure 2 Figure 3 Figure 4
Figure 1 Figure 2 Figure 3 Figure 4
 

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