Researchon Factorsof Users’Acceptanceon Social Network Service Basedon The TAM Model
Ruijin Zhang Ye Tian
Associate Professor Master Graduate Student
School of management, Harbin Institute of School of management, Harbin Institute of
Technology Technology
Harbin, China Harbin, China
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Abstract—By using technology acceptance model (TAM) as the basic framework, taking users of the most widely used social networking service (SNS) Renren as research targets, the paper has discussed determinants of social networking service user acceptance, and has tested and verified the relationship between website feature, perceived usefulness(PU)，and perceived ease of use(PEOU), and the relationship between these perception factors and behavioral intention(BI)，and has built the social networking service user acceptance theory model. The research provides effective theoretical support for user identification and makes a targeted management measures and recommendations for Social networking site and the related management departments.
Keywords-social networking service; TAM model;users’ acceptance model
Ⅰ.INTRODUCTION
With the rapid development of Internet technology and application, a large number of social networking sites (SNS) like Renren, Facebook, Happy network came into being. SNS attracts more users with its open and social features,and has become a new social intercourse method which changes the behavior of modern people. Therefore,research on factors that effect SNS users’ acceptance and the relationship between these influencing factors has avery importanttheoretical and practical significance on improving users’ recognition capability and SNS users’ acceptance.
Ⅱ LITERATURE REVIEW AND RESEARCH HYPOTHESIS
The work was supported by the National Natural Science Foundation of China (Grant No.71172156)
A.Literature Review
1) Perceived usefulness, perceived ease of use and behavioral intention
Studies on factors that effect SNS users’ acceptance have found that perceived usefulness(PU) and perceived ease of use(PEOU) both have a influence on users’ buying intention.PU and PEOU have significant effect on buying behavior only when users are unfamiliar with shopping sites. Otherwise, the effect of PU will be significantly decreased and PEOU will develop a more direct impact on buying behavior. Shopping sites’ quality directly affect PU, PEOU directly affect the usefulness indicator, and the usefulness directly affect consumers' BI.Consumers’ own experience can adjust the effect of PU and PEOU.
2) User characteristics and BI
Different social classes and different groups have different perception of usefulness and ease-of-use of online shopping sites（Paul，2001）.Community culture,habits of friends, expectations from families,etc. will also affect SNS users’ acceptance（Yan Zhou，2009）.
3) Website feature and website acceptance
Website feature has a direct and positive impact on customer shopping(Kiseol Yang, Allison P. Young, 2009); the quality of websites’content, transaction quality, the degree of interest, the security of network transactions are factors that affect consumers’ intention to use shopping website.Among these factors, transaction security is the most important (Kee-Sook Lim, the John H. Heinrichs, Jeen-Su Lim, 2009); website's interactivity and informativeness have a positive correlation with PEOU; website's interactivation, informativeness, economy, security and popularity are negatively related to perceived risk ; PEOU affects PU,and then affects site acceptance(Zhong Xiaonuo, 2005); the convenience of search, ease of use, conformity motives, personal will and personal value judgment have influence for the site acceptance.
4) Perceived risk and perceived usefulness, perceived ease of use
Perceived risk has a significant negative impact on PEOU in site acceptance model. And PEOU can notably reduce the perceived risk (Featherman & Pavlou, 2003); the pleasure feelings in shopping and PU have significant influence on rebuying (Koufaris, 2002);
From literature review above, we can see that current studies mostly concentrate on the acceptance of the e-commerce website, and aremainly concerned with the relationship between PU, PEOU and behavioral intentions;the effect of user characteristics and demographic characteristics on users’ acceptance ; site characteristics’ influence on site acceptance. The research on SNS users’ acceptance is limited, and focous on a single indicator, rarely considering other important indicators’ significance and their deep-seated reasons. Therefore, this paper will strive to achieve a breakthrough in these areas.
B. Research Hypothesis
Based on the literature review above we propose the following hypotheses:
H1: PEOU has a positive effect on PU.
H2: PEOU has a positive effect on BI.
H3: PU has a positive effect on BI.
H4a: Personality trait has a positive effect on BI.
H4b: The level of education has a positive effect on BI.
H4c: The occupation has a positive effect on BI.
H4d: Gender has a positive effect on BI.
H4e: Age has a positive effect on BI.
III RESEARCH METHOD AND HYPOTHESIS TESTING
C.Research Method
Since Renren is a typical representative of SNS and college students are the main users, We choose college students who frequently visit Renren as ourresearch targets.
This study used random sampling method to conduct a questionnaire and the investigation time is from Feb 23th, 2011 to April 4th, 2011.Choose 30 respondents as the initial samples according to a certain stratified sampling. Then questionnaires were distributed and each respondent choose a friend inRenren to pass on the questionnaires. Thus the questionnaires would spread quickly like a snowball.The other data source: This study used traditional paper questionnaires form.Among 375 questionnaires recoverd, there are 317 valid questionnaires,and the valid recovery rate is 84.5%. Excluding 60 as empirical test data of SNS users’ acceptance, 257 questionnaires would be used as empirical analysis data.
D.Hypothesis Testing
1) The path coefficient of PEOU’s effection on PU is 0.170, indicating PEOU effects PU ,and PEOU has an indirect effect on BI. H1 is surported.
2) PEOU and PU’s path coefficients for BI are 0.436 and 0.243. The former was higher than the later,indicating that PEOU has more influence on choosing SNS. H2 and H3 are surported.
3) Personality trait, education level, occupation, gender and age’s path coefficients on BI are 0.572,0.606,0.188, -0.221, -0.387, indicating personality and education have more influence on BI than occupation. The path coefficients of gender and age are less than 0.1, indicating gender and age have a negative correlation with BI.H4 are partly surported.
The hypothesis testing results are shown in Table 3-1.
Ⅳ MODELING AND REVISION
Basedon the relationship between PEOU,PU,user characteristic and BI, we build a concept model which is showed in Figure 4-1.This study is based on general principle and basic principles to determine the correlation between the hidden variables,and between the hidden variables and explicit variables in the model. The path coefficients not only show Positive and Negative,but also represent how closely two variables are. The specific equations of path coefficients between variables have been omitted.
The structural equation model has 21variables, respectively belongs to 4 different structural variables. The number of equations in the model is 20, and there are four position coefficients in these equations. Through research we can find that the model actually is an over-identification model,so evaluation and revision are necessary.
A Model Evaluation and Revision
After examining the significance of each parameter variable, removing unremarkable variables for several times, and constantly adjusting and strengthening the relationship between the variables, we obtain the final path diagram of structural equation,as in Figure 4-2.
B Model Texting
To verify the accuracy and the potential replication of the structural equation model , this paper sets aside 60 survey samples from the survey questionnaire data.Then use the samles to carry on empirical test to determine whether the model has a significant effect on BI.
Put PEOU, PU, and user characteristics, etc. parameters into the structural equation,we get 60 samle parameters.Then take the average of all parameters and carry on variance analysis,as in Table 4-1. From the results of variance analysis, we can see the two columns data from statistical analysis have good correlation with each other and the result of variance analysis displays that this model has a good fitting effect. So the model is applicable to examine and evaluate the SNS users’ acceptance
V CONCLUSION AND RECOMMENDATIONS
A Conclusion
1) PEOU of SNS has a positive correlation with user acceptance.Combining with the corresponding coefficients of proposed model, we draw the following specific conclusions:
SNS’s convenience, security, variety of logging in method and the cotrollability of personal information leakage, etc. have a positive correlation with SNS users’ acceptance.
2) Usefulness of SNS has a positive correlation with user acceptance. And combining with the model established in this paper, we draw the following conclusions:
Interactivity, the degree of personalization, the usefulness of the knowledge, the attractiveness of the game, the design novelty and updatding speed all have a positive effect on SNS users’ acceptance.And we can arrange indicator coefficients in descending order as follows: usefulness of knowledge , design novelty, attractiveness of the game, updating speed, degree of personalization ,interactivity.
3)The user characteristic variables directly affect the cognition of user acceptance, and at the same time the variables indirectly affect users’ acceptance by influencing PU and PEOU. Combining the study of this papar we can draw following specific conclusions:
a)Whether the user is extroverted or introverted, the level of education, etc. effect users’ acceptance.
b) Men have a higher acceptance of SNS than women.
B Advices for SNS Management
1) Introduce knowledge application homepage, and develop authoritative knowledge searching plug-ins.
2) Improve entertainment of sites and attract more users to join in.
3) Maintain the updating speed of website’s application program and their own style.
4) Improve supervision of website to avoid leakage of customer personal information due to technical problems.
5) Enhanceease-of- use of the site.
6)Make a good job of data collection and research work , know well about customer needs, and strengthen marketing strategy of SNS to attract new users.
C Recommendations for SNS users
1) Customer value
a) The groups of using the site should be considered when choosing SNS. We should select sites which are built on well-educated groups.
b) Users should consider whether there are enough users using the site. We had better elect a well developped site whose registered users are sufficient.
c) Users should consider the fuction of information search.It is better to choose a site with perfect fuction of information search.
2) Site security
a) The user should select a site which has strong ability of software development and can defense against Trojan horses and virus forcefully.
b)Users should consider the security problem when choosingSNS. They can choose some well-known sites, because the popularity of the site can bring them a large number of users and can obtain pubilic supervision.So this type of sites should be take into serious consideration.
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Table1 Hypothesis Testing Results
Hypothesis / Path Coefficient / ResultH1：PEOU→PU / 0.170 / Support
H2：PEOU→BI / 0.145 / Support
H3：PU→BI / 0.193 / Support
H4a：Personality→BI / 0.572 / Support
H4b：Education→BI / 0.606 / Support
H4c：Occupation→BI / 0.188 / Support
H4d：Gender→BI / -0. 221 / Support
H4e：Age→BI / -0. 387 / Support
PU, perceived usefulness; PEOU, perceived ease of use; BI,behavioral intension;S, supported.
Notes: e1,interactivity; e2,personality; e3,operation strategy; e4, usefulness of knowledg; e5,attraction of game; e6,activity design; e7,updating speed; e8,stability; e9,security; e10,selection of website operator; e11,variety of logging in method; e12,convenience; e13,leakage risk of personal information.
Figure 1．SNS user acceptance model
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3) The degree of difficulty of site operation
Users should choose sites which are easy in operation in order to communicate with others conveniently,efficiently and quickly. Those sites not only can meet the needs of young
people to show their own individuality, but also can meet other age groups’ needs of knowing about current events and keeping in touch with the outside world.
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Figure 2．Path coefficients of SNS users’ acceptance model
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ACKNOWLEDGEMENT
Thank the National Natural Science Foundation of China (71172156) funded this study,and thank the support and from Management School of Harbin Institute of Technology.
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