A Study on the User Acceptance Model of SNS Websites Based TAM* Dan Jin1, Mei-mei Zhou1 1 School of Management and Economics, Beijing Institute of Technology, Beijing, China ([email protected], [email protected] ) Abstract - Based on Davis’s TAM, combining with the user satisfaction theory in information system and motivation theory, and the SNS user behavior characteristics, this study proposed the user acceptance model on SNS websites. In this model, Perceived Usefulness and Perceived Ease-of-Use were retained, and Perceived Enjoyment and Perceived Connectivity were added. In addition, the external variables affecting these key factors were subdivided. The questionnaire was designed and Structural Equation was used to validate the empirical hypothesis. The results showed that TAM could apply to user acceptance on SNS website basically, and Perceived Enjoyment and Perceived Connectivity were all positively correlated with Willingness, also, the subdivision of external variable reflected the importance of user activity. A. Technology Acceptance Model (TAM) Based on rational behavior theory, Fred Davis(1986)put forward TAM. TAM adopts the well-established causal chain of beliefs → attitude → intention→behavior which has become known as the Theory of Reasoned Action (TRA). Based on certain beliefs, a person forms an attitude about a certain object, on the basis of which he or she forms an intention to behave with respect to that object. The intention to behave is the sole determinant of actual behavior(fig. 1).In TAM applications, two key factors, Perceived Usefulness and Perceived Ease-of-Use, can effectively explain users’ behavior intention. Perceived Usefulness Key Words - activity level, perceived enjoyment, SNS websites, technology acceptance model I.INTRODUCTION SNS websites is a booming Internet applications, based on the theory of “Six Degrees of Separation”, taking the customer relationship as the core, designed to help people build social networks. The large number of Internet users makes a great contribution to the rapid development of SNS sites. Various SNS websites rise rapidly after 2006, and competition is fierce, causing serious phenomenon of homogeneity. MicroBlog, a Twitter-like service, has been rapidly developed, and the registered users have increased dramatically.SNS websites users are coincident with those of MicroBlog to a great extent. Double pressures of homogenous competition and MicroBlog’ rising, makes SNS websites face a great challenge. SNS websites need to absorb new users continuously and retain old ones. SNS websites are facing with the problem of user acceptance. II.LITERATURE REVIEW The user acceptance problem of SNS websites belongs to information technology acceptance. The user’s act in accepting technology is regarded as one of the most mature research field of information systems. The most representative theories are theory of rational act (TRA),theory of planning behavior (TPB), and technology acceptance model (TAM). ____________________ * Supported by National Natural Science Foundation of China(No.70802008), Beijing Municipal Natural Science Foundation (No. 9112011). External Variables Attitude Behavior Intention System Use Perceived Ease of Use Fig. 1 Technology Acceptance Model B.Other Related Theory Papaeharissi& Rubin(2000) summarized motivation of Internet usage in the following: interpersonal communication, killing time, achieving information, convenience and entertainment. Through the online questionnaire survey in a German SNS website, Schaefer &Cora(2008) discussed participating motivation and running mode, considered the participating motivation includes keeping in touch, searching for information, entertainment, communicating, managing existing relationship and so on. From these motivations, some other factors may also affect SNS websites usage, apart from Perceived Usefulness and Perceived Ease-of-Use. Wixom & Todd(2005) proposed that the user satisfaction of information system could be united with Davis’s TAM. Information quality and system quality influence information satisfaction and system satisfaction respectively, and information satisfaction and system satisfaction exert influence on Perceived Usefulness and Perceived Ease-of-Use respectively. Delone& Mclean (2003)added service quality in the improved D&M information system success model, and proposed that the SERVQUA scale in marketing field could be referred to measure service quality. As studying the relationship between intimate degree and diving behavior, Rau(2008) and others measured the member behavior of participating in SNS websites with member activity level. These theories could provide a foundation for further study on external variables subdivision in TAM. Ⅲ.MODEL AND HYPOTHESIS A. User acceptance model of SNS websites In TAM, the external variables have not been fractionized, which will make against further analysis the influencing factors on user acceptance to SNS websites.SNS websites provide an interactive platform for friends, on which integrates basic Internet applications, such as log, photo, video, community and game, and meet users’ sociality demands through online interactive among friends, information sharing, participating in activities and other ways. Webster&Martocchio(1995)thought entertainment was an intrinsic motivation using computers in workplaces. Scholars put forward Perceived Enjoyment as doing Internet empirical study, which refers to entertainment degree by using SNS websites. Moreover, Perceived Connectivity refers to being connected with friends in passions and is not confined by time or location. During using SNS websites, users may have the feeling of satisfaction or happiness, which makes users to accept SNS websites in further . Based on TAM, the user acceptance model for SNS websites is shown in fig.2.Perceived Usefulness and Perceived Ease-of-Use are retained in the model, and Perceived Enjoyment and Perceived Connectivity are added as another two key factors affecting users to accept SNS websites. In addition, external variables of the above factors are further divided into the information quality, quality system, active degree and the service quality and related factors. Service Quality Individuation Communication Perceived Enjoyment Innovation Activitylevel Participation Sharing Sociability Perceived Connectivity Game Interactive InformationQuality Accuracy Timeliness Perceived Usefulness Behavior Willingness Integrity System Quality Security Interface Perceived Ease-of-Use Social Impact Fig.2Prototype of user acceptance model for SNS websites B. Assumptions of model The related assumptions in TAM are still established in this model. And new assumptions about Perceived Enjoyment and Perceived Connectivity are proposed. (1) Perceived Ease-of-Use and related assumptions Basedon customer satisfaction theory and with the previous empirical data support, Seddon(1997)also confirmed that system quality has a positive effect on Perceived Ease-of-Use. In addition, the system security is much important to users, which means to promise personal information safety. Moreover, both user interface and interactive process will affect users to accept SNS websites. H1: System quality positive effect on this term H1a: Security positive effect on it H1b: Interface positive effect on it H2: Perceived Ease-of-Use positive effect on this item (2) Perceived Usefulness and related assumptions H3: Information Quality positive effect on this item H3a: Accuracy positive effect on it H3b: Timeliness positive effect on it H3c: Integrity positive effect on it H4: Activity level positive effect on this item H4a: Participation positive effect on it H4b: Sharing positive effect on it H4c: Sociability positive effect on it H4d: Game interactive positive effect on it H5: Perceived Ease-of-Use positive effect on this item H6: Perceived Usefulness positive effect on this item (3) Perceived Connectivity and related assumptions H7: Activity level positive effect on this item H7a: Participation positive effect on it H7b: Sharing positive effect on it H7c: Sociability positive effect on it H7d: Game interactive positive effect on it H8: Perceived Connectivity positive effect on this item (4) Perceived Enjoyment and related assumptions As a community website where users’ activities are based on group, SNS website should pay much attention to users’ activity involvement, which can tell the influence of Perceived Connectivity to Perceived Enjoyment. H9: Service quality positive effect on this item H9a: Individuality positive effect on it H9b: Communication positive effect on it H9c: Innovation positive effect on it H10: Activity level positive effect on this item H10a: Participation positive effect on it H10b: Sharing positive effect on it H10c: Sociability positive effect on it H10d: Game interactive positive effect on it H11: Perceived Connectivity positive effect on this item H12: Perceived Enjoyment positive effect on this item (5) social impact and related assumptions Social impact refers to others influence on individual for using SNS websites. Similar to the TRA subjective enorms, people are very conscious of others view about their particular behavior willing. Whether individual uses SNS websites would be influenced by others recommendation or evaluation. H13: Social impact positive effect on this item Ⅳ. RESEARCH METHODS A. Survey questionnaire design In order to verify the model assumptions, a questionnaire is used to collect data. The questionnaire uses a standard 7-point Likert-typescale. The 7 point are "completely disagree", "relatively disagree", "some disagree", "not sure" ,"some agree", "relatively agree" and "completely agree". According to actual situation, respondent shave the right to choose from 1(completely disagree) to 7 (completely agree). As the final questionnaire data is analyzed and tested by using structural equation model, it need to meet the requirements that structural equation model to observed variables and characteristics of measuring factors, so three or more items are used to measure each factor. All the measure items use the mature scales which have been used in empirical study by researchers at home and abroad, and are adjusted according to SNS websites characteristics and questionnaire’s semantic environment. The questionnaire has 18 variables to measure, including13external variables, such as accuracy, timeliness, integrity, security, interface, individuality, innovation, communication, participation, sociability, sharing, game interactive and social impact, and 5 internal variables, as Perceived Usefulness, Perceived Ease-of-Use, Perceived Enjoyment and Perceived Connectivity and Willingness. Above all, the total number to be measured is 58. B. pre -test Questionnaire In order to ensure the effectiveness of the survey questionnaire, it is necessary to pretest it before actually using it. This paper uses SPSS 18 to do reliability and validity analysis on the test results. The reliability analysis results showed that Cronbach's Alpha value of every measured factor was greater than 0.5, while the overall questionnaire reliability was 0.959, indicating the internal consistency of the questionnaire was acceptable. In the validity analysis, separate factor analysis was made on corresponding measured items of independent variables, mediating variables and dependent variables. The factor analysis result showed that other factors were all better classified in the corresponding dimension apart from two factors measured items, sociability and social impact of the independent variables. So sociability factor and social impact factor were deleted. A. Second order confirmatory factor analysis Second order confirmatory factor analysis (CFA) is put forward as there is high degree relevance among original first order factors in the first order CFA, and the first order CFA can be in agreement with sample data. In the model, information quality, system quality, service quality and activity level are measured with the multidimensional method, so AMOS 17 would be used respectively during their second order factor analysis. The analysis results show, all the first order factors to second order factors of information quality, system quality, service quality, and activity level, the load capacity value lie between 0.5 and 0.95, and the Significance Probability and C.R. are greater than 1.96, and decision criteria is achieved totally. Meanwhile, compared with the goodness-of-fit standard, the whole goodness-of-fit reaches the basic standard. So we can conclude that the first order factors of information quality, system quality, service quality and activity level would measure these second order factors well. B. Model analysis and revision According to the validity inspection and analysis results of second order CFA above, social impact and sociality factors are removed from the original hypothesis model, the goodness-of-fit indexes of the model are summarized as table 1. The ratio chi-square/freedom degree of the model is 1.828<2, RMSEA is 0.074<0.080,two goodness-of-fit indexes meet the standard. But other goodness-of-fit indexes, such as GFI(0.658<0.9), AGFI(0.62<0.8), CFI(0.828<0.9), TLI(0.816<0.9) and NFI(0.689<0.8), are not up to the standards, thus the model need to be modified and optimized. AMOS offers two model modification indexes, in which modification index MI is used for model expanding, and the critical ratio C.R. is used for model restricting. According to the value of critical ratio and modification indexes, following the principle of modifying one parameter once, the final revised model is shown in fig.3. ActivityDegree Participation Sharing Perceived Enjoyment GameInteractive C.Data collection Information Quality According to the pre -test results, the questionnaire were modified in final two ways, electronic and paper questionnaire. On the principle of simple random sampling, questionnaires were distributed. 170 electronic questionnaires and 68 paper questionnaire were distributed, altogether 202 questionnaires were returned. After moving the data obviously not meeting the requirements, 153valid questionnaires were remained. Perceived Connectivity Behavior Intention Accuracy Timeliness Integrality System Quality Security Interface Perceived Usefulness Perceived Ease-of-Use Fig.3 SNS websites user acceptance model based on TAM Ⅴ. MODEL ANALYSIS 2 df TABEL Ⅰ Goodness-of-fit Indexes of Full Model Absolute goodness-of-fit index Relative goodness-of-fit index GFI AGFI RMSEA CFI NFI TLI （1, 5） >=0.9 >=0.8 <0.08 >=0.9 >=0.8 >=0.9 1.828 0.658 0.621 0.074 0.828 0.689 0.816 Path connectedness <--- activity usefulness <--- information easiness <--- system entertainment <--- activity usefulness <--- activity entertainment <--- connectedness willingness <--- usefulness willingness <--- entertainment willingness <--- easiness willingness <--- connectedness easiness4 <--- easiness easiness3 <--- easiness easiness2 <--- easiness easiness1 <--- easiness willingness4<--- willingness willingness3<--- willingness willingness2<--- willingness willingness1<--- willingness usefulness4<--- usefulness usefulness3<--- usefulness usefulness2<--- usefulness usefulness1<--- usefulness entertainment4 <--- entertainment entertainment3 <--- entertainment entertainment2 <--- entertainment entertainment1 <--- entertainment connectedness3<--connectedness connectedness2<--connectedness connectedness1<--connectedness where *** p<0.001 TABEL Ⅱ The Path Coefficient of Revised Full Model Estimated Standard Deviation Critical Ratio Significant Probability Coefficient (S.E.) (C.R.) (p) .562 .121 4.627 *** .913 .232 3.940 *** .702 .111 6.340 *** .758 .120 6.311 *** .343 .137 2.492 .013 .322 .102 3.147 .002 .229 .084 2.731 .006 .340 .084 4.070 *** .213 .084 2.530 .011 .307 .096 3.205 .001 1.342 .121 11.089 *** 1.411 .125 11.283 *** 1.000 1.128 .099 11.415 *** 1.034 .076 13.592 *** .981 .068 14.359 *** .880 .070 12.591 *** 1.000 .944 .100 9.440 *** .946 .103 9.225 *** 1.000 1.193 .117 10.235 *** 1.000 1.147 .061 18.711 *** 1.016 .060 16.805 *** .923 .078 11.784 *** 1.214 .183 6.651 *** Standard Coefficient .535 .641 .735 .620 .315 .277 .221 .368 .177 .285 .919 .942 .717 .790 .850 .876 .813 .864 .729 .716 .803 .779 .870 .966 .918 .762 .811 1.000 .685 .473 .149 The path of regression coefficients of each factor of the revised full model has increased, the value of C.R. is larger than 1.96, some of the path of significant probability are larger than 0.05 that are sufficiently close to the standard ,which shows the modification effect well. Table 2is the path coefficient of the revised model for the first time. The goodness-of-fit of the revised model is shown as table 3.The value of chi-square (1468.758) and freedom (835) improve markedly than the preceding ones. The ratio Chi-square/degree of freedom (1.759<2) and the value of RMSEA (0.071<0.08) reach the standard both. Several other goodness-of-fit indexes meet the standard basically. For numbers of latent variables exist in the model, the relationship between factors is relatively complex and some indexes may be influenced greatly by the sample size, the revised model can be regarded as the final model. 3.171 .002 .296 TABEL Ⅲ Revised Goodness-of-fit Index of Full Model Absolute Goodness-of-fit Index Relative Goodness-of-fit Index x2/df GFI AGFI RMSEA CFI NFI TLI （1, 5） 1.759 C. >=0.9 0.717 >=0.8 0.680 <0.08 0.071 >=0.9 0.863 >=0.8 0.734 >=0.9 0.852 Test Results of Model Hypothesis The model set up in this study originally uses 13level 1 hypothesis from H1to H13.As system quality, information quality, service quality, and activity level use multidimensional measure method, H1 to H6 each exists level 2 hypothesis. The data analysis results support the rest hypothesis apart from H4c, H5, H7c, H9, H9a, H9b, H9c, H10c andH13. Ⅵ. CONCLUSION AND PROSPECT This study constructs SNS websites user acceptance model based on TAM, and model hypothesis is verified by the structure equation model. The conclusion can be drawn as follows: (1)TAM is basically suitable to SNS websites user acceptance study, but no evidence supports the causality between Perceived Usefulness and Perceived Ease-of-Use. (2)Both Perceived Enjoyment and Perceived Connectivity have a positive correlation with Usage Willingness, and Perceived Connectivity further affects Perceived Enjoyment. (3)The subdivision of external variables reflects the importance of user activity, the activity level influences Perceived Usefulness, Perceived Connectivity and Perceived Enjoyment simultaneously, while the influence of service quality to Perceived Enjoyment is deleted for path of regression coefficients is too little. 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