A Theoretical extension of the technology acceptance model to explain the. adoption and the usage of new digital services

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1 A Theoretical extension of the technology acceptance model to explain the adoption and the usage of new digital services Jean Philippe Galan Professeur des Universités Centre de Recherche en Management (CRM, UMR 5303 CNRS/UT1) IAE Université de Valenciennes et du Hainaut Cambrésis Les Tertiales, rue des Cent-Têtes, Valenciennes Cedex 9 jean-philippe.galan@univ-valenciennes.fr / +33(0) Magali Giraud Maître de Conférences Centre de Recherche en Management (CRM, UMR 5303 CNRS/UT1) IAE - Université de Toulouse 1 Capitole 2, rue du Doyen Gabriel Marty, Toulouse Cedex 9 magali.giraud@iae-toulouse.fr / +33(0) Lars Meyer-Waarden Professeur des Universités Centre de Recherche en Management (CRM, UMR 5303 CNRS/UT1) IAE - Université de Toulouse 1 Capitole 2, rue du Doyen Gabriel Marty, Toulouse Cedex 9 lars.meyer-waarden@iae-toulouse.fr / +33(0)

2 Une Extension Théorique du "Technology Acceptance Model" pour expliquer l'adoption et l'usage de nouveaux services digitaux Résumé: Cette recherche propose une extension théorique du «Technology Acceptance Model» (TAM). Des variables complémentaires sont proposées : image sociale, auto-efficacité, hédonisme, innovativité, respect de la vie privée, confiance. Le modèle étendu, a été testé sur trois types de services digitaux (loisir, pédagogie, administration; N= 2205).La confiance joue un rôle clé dans le processus d'adoption et amène plus d'impact sur l'intention d'utilisation que la facilité d'utilisation et l'utilité perçue, quel que soit le domaine d'application (vie privée, pédagogie ou administration). Les bénéfices hédonistes augmentent l utilité perçue et la facilité d utilisation du nouveau service digital. Mots-clés : TAM, confiance, image sociale, hédonisme, vie privée, innovativité A Theoretical Extension of the Technology Acceptance Model to explain the adoption and the usage of new digital services Abstract: This research develops a theoretical extension of the Technology Acceptance Model (TAM). We introduce complementary variables: social image, self-efficacy, hedonism, innovativeness, privacy concern, trust. The extended model, was tested regarding three new digital services(leisure, pedagogy, administration; N = 2205). Trust plays a key role in the adoption process and has even more impact on intention of use than perceived ease of use and perceived usefulness, whatever the domain of application (leisure, pedagogy or administration). Perceived hedonic benefits enhance perceived easiness and usefulness of usage of the new digital service. Keywords: TAM, Trust, social image, hedonism, privacy, innovativeness. 1

3 A Theoretical Extension of the Technology Acceptance Model to explain the adoption and the usage of new digital services Introduction New information technology (IT) adoption is a central concern of customer relationship management, e-marketing and e-commerce. A lot of IT systems fail because users do not adopt and use them, either because of the difficulty of use, or because of the user reluctance. Understanding and creating the conditions under which IT systems will be embraced by the human organization therefore remains a high-priority research issue. Substantial theoretical and empirical progress has been made in explaining and predicting user acceptance of IT. In particular, the Technology Acceptance Model (TAM) has become well-established as a model for predicting IT acceptance, usage intentions and behavior via the mediating variables perceived usefulness and perceived ease of use (Davis 1989, Davis, Bagozzi and Warshaw, 1989). In line with a large body of research that extended the TAM (King and He, 2006; Venkatesh & al., 2003), the first goal of the present research is to enrich the TAM by including key determinants of perceived usefulness and ease of use that had not been tested together, and to apply it to future digital university campus services. The second target of this research is to highlight moderators (such as context of use of IT) of innovation adoption processes. Previous research has shown that innovation acceptation processes depend on system-related factors, especially on the experiential vs. utilitarian value of the service (Nysveen, Pedersen and Thorbjornsen, 2005). This research considers the context of use of the IT as a potential moderating variable. In fact, literature on IT focuses on several contexts of use of IT: organizational context (Venkatesh & al., 2003), learning context (Lee, Cheung et Chen, 2005; Wu and Gao, 2011) and private use (Nysveen & al., 2006). Contrarily 2

4 to most researches that address these fields separately, this research investigates three different fields simultaneously, comparing adoption processes in the context of: a) relations between students and the administrative department of the university, b) relations between students and the professors, and c) leisure and private life. It therefore aims at understanding different moderating effects linked to the field of application of the IT system. This article is structured as follows: after reviewing key concepts about the TAM, we shall explain our conceptual framework and hypotheses. We then describe our methodology and surveys conducted. The results shall be presented and we conclude the article with a discussion, managerial implications and directions of future research. 1. Key concepts, conceptual framework and hypotheses We define, in the following sections, the concepts used in our conceptual framework and then present the hypotheses related to our core issues Basic TAM model Rooted in the Theory of Reasoned Action (Ajzen and Fishbein, 1980), TAM is a framework for predicting and explaining consumers' adoption of IT (Davis, 1989). It is a framework for predicting and explaining consumers' adoption of information technology. It postulates that user acceptance of a new system is determined by the users intention to use (IU) the system, which is influenced by the users beliefs about the system s perceived usefulness (PU) and perceived ease of use (PEU).Both variables are influenced by external variables, such perceived accessibility (Karahanna and Straub, 1999), social influence processes, and cognitive instrumental processes (Venkatesh and Davis, 2000). 3

5 1.2. Extended TAM model Figure 2 shows our extended model. Using TAM as the starting point, our model incorporates additional theoretical constructs spanning different aspects of social influence processes, perceived hedonism and cognitive instrumental processes. Perceived Social image (PSI) Perceived Self Congruity (PSC) Perceived usefulness (PU) Perceived Hedonism (PH) Perceived self efficacy (PSE) Innovativeness (INO) Perceived ease of use (PEU) Trust (TT) Intention to use (IU) Perceived protection private live (PPPL) Contexts of use of IT (leisure, administration, pedagogy) Figure 1.Extended TAM model Social Influence Processes Our model reflects the impact of two social forces impinging innovation adoption. -Perceived social image (PSI) In our research we define social image (PSI) as the degree to which use of an innovation is perceived to enhance one's social status in one's social group (Moore and Benbasat, 1991). A technology will be considered all the more useful as it helps persons to be consistent with a 4

6 groups norms. They may perceive that using a system will lead to improvements in their performance indirectly due to image enhancement. We hypothesize: H1a: PSI to others by adopting a technology is positively correlated with PU. H1b: PU of a technology is positively correlated with IU. - Perceived Self Congruity (PSC) Consumers are motivated to purchase products, which are congruent with their beliefs about themselves (Sirgy, 1982). A product perceived as congruent may be considered easier to use and more useful as an incongruent one. H2a :PSC is positively correlated with PEU of a technology H2b :PSC is positively correlated with PU of a technology Cognitive Instrumental Processes We theorize three cognitive instrumental determinants affecting perceived usefulness and usage intention: perceived ease of use, self-efficacy with the technology and perceived hedonism of technology. - Perceived ease of use (PEU) In accordance with the basic TAM, our extended model retains perceived ease of use from TAM as a direct determinant of perceived utility (PU) and an antecedent of intention to use (IU), both directly and indirectly via its impact on perceived utility (Davis, Bagozzi and Warshaw, 1989). We therefore hypothesize: H3a: PEU of a technology is positively correlated with PU. H3b: PEU of a technology is positively correlated with IU. 5

7 - Perceived self-efficacy (PSE) Perceived self-efficacy (PSE) is the measure of one's own competence to complete tasks and reach goals in specific situations (Bandura, 1997). Some investigations about TAM have confirmed the causal links between general computer self-efficacy, perceived usefulness (Compeau and Higgins, 1995) and ease of use (Agarwal, & al. 2000; Hu & al., 2003 ; Venkatesh and Davis, 1996). People generally avoid adopting technologies where their selfefficacy is low, because they overestimate efforts it will require. We hypothesize: H4a: High consumers PSE is positively correlated with PEU of a technology. H4b: High consumers PSE is positively correlated with PU of a technology. - Innovativeness (INO) Innovativeness has been defined as the willingness of an individual to adopt and try out any innovation (Rogers, 1983). Insofar innovative people are opened to new experiences and risk taking, they are less reluctant to adopt a new technology, as they anticipate less risks and efforts, and as they have more positive beliefs about technology use (Agarwal and Karahanna, 2000; Lewis, Agarwal and Sambamurthy, 2003). Hence, we hypothesize: H5a: Consumers innovativeness is positively correlated with PEU of a technology. H5b: Consumers innovativeness is positively correlated with PU of a technology. - Perceived hedonism (PH) One of the drawbacks of the TAM is that it does not take into account emotions as a predictor of perceived utility toward the act of using the new technology and usage intention. Indeed, consumer behavior theory provides evidences that utilitarian motives (economic and functional) are not sufficient to explain consumer behavior toward a product (Chitturi, Raghunathan and Mahajan, 2008). Hedonic motivation has been shown to influence 6

8 technology acceptance and use very significantly, sometimes more than PU (Van der Heijden, 2004). We therefore hypothesize: H6a: A technology PH is positively correlated with PEU. H6b: A technology PH is positively correlated with PU. - Perceived protection of private live (PPPL) and trust in technology (TT) Most commercial IT systems and associated databases (e.g. Google, Facebook, e- commercents such as Amazon.com) collect personal data associated with individual consumers in intimate ways that can be used to tailor personalised advertisements. This can be seen as intrusion and arouses concerns on privacy (Phelps, D Souza and Nowak, 2001). The adoption of IT then depends heavily on the development of trust between the provider, the consumer and the IT systems. Perceived trust in new IT proves to be a direct antecedent of intention to use (IU) (Sirdeshmukh, Singh and Sabol, 2002; Dimitriadis and Kyrezis, 2010) and mediates the influence of PPPL on IU (Liu & al., 2004). We therefore hypothesize: H7a: PPPL about a technology is positively correlated with their trust in it. H7b: Trust in a technology is positively correlated with intention to use. 1.3 Moderating effects Previous studies highlight some differences in processes underlying innovation adoption depending on personal differences such as gender (Venkatesh and Morris, 2000), on the field of application of the technology (e.g. commercial vs non-commercial system; Wu & al., 2011; telephone banking vs internet banking; Dimitriadis and Kyrezis, 2010),or on the experiential vs utilitarian value of the service (Nysveen & al., 2006). We therefore hypothesize that the context of use of the innovation (administrative, pedagogy and leisure) is going to moderate relations between the variables of the model. 7

9 H8: The relations between the variables of TAM are moderated by the context of use of the technology. 2. Research methodology Our investigation based on scenario experimental methodology is carried out together with the microprocessor firm Intel to test our extended TAM model for three new digital campus life services that should facilitate in different contexts administrative, academic/pedagogical and leisure activities. Theoretical constructs are operationalized using validated items from prior research. All the constructs are measured with multi-item Likert scales (1 = strongly disagree to 7 = strongly agree). The TAM scales of perceived usefulness, perceived ease of use, and intention to use are measured using items adapted from Davis (1989) and Davis, Bagozzi and Warshaw (1989). Trust scale items are taken from Dimitriadis and Kyrezis (2010). Perceived selfcongruity items are taken from Sirgy and Su (2000). Innovativeness is measured through five items adapted from Oliver and Bearden (1985) and Goldsmith and Hofacker (1991). Perceived protection of private life is measured through items adapted from Jarvenpaa, Tractinsky and Vitale (2000). Perceived self efficacy toward IT is measured through the scale of Faurie and van de Leemput (2007). We adapt Venkatesh & al. (2012) scales to measure perceived hedonism. Finally, PSI is measured through the scale of Sweeney and Soutar (2001). The surveys were conducted between 2011 and 2012 on a sample of 2205 undergraduate and graduate students attending the university Toulouse (France). A structural equation model (SEM) is employed to test the hypotheses of this research 8

10 3. Results During the scales validation process, we have to eliminate one item linked to the PSE scale and one item linked to trust to improve constructs reliability. The other scales do not require any modification. Results are satisfying concerning reliability (Cronbach's alpha and Joreskog over 0,7), convergent validity ( vc around or above 0,5) and discriminant validity ( vc below ²). The model has a good fit, as indicated by indices of goodness of fit (table 1). GFI AGFI CFI RMSEA SRMR AIC,960,947,975,037, (42303) Table 1. Global fit of measurement model Hypothesis H1 to H8aretested through a structural equation modelling analysis (figure 2). PSI PSC PSE PH INO PPPL PU PEU TT IU Significant relation Non significant relation Figure 2. Strutural equation model This model presents a good-fit (cf. table 2). X²/ddl GFI AGFI CFI RMSEA AIC 7,61,937,918,947, (32304) Table 2. Global fit of structural model 9

11 There is a positive and significant link (β=,111 ; p<,000) between perceived social image and perceived usefulness, supporting hypothesis H1a. The link between perceived usefulness and intention to use is positive and significant (β=,218 ; p<,000), confirming H1b. Perceived selfcongruity exerts an influence significant and positive on perceived usefulness (β=,118 ; p<,000), confirming H2b, and on perceived ease of use (β=,087 ; p<,007), supporting H2a.The links between perceived ease of use and perceived usefulness (β=,331 ; p<,000), as well as perceived ease of use and intention to use(β=,140 ; p<,000) are positive and significant, confirming hypotheses H3a and b. The relation between perceived self-efficacy and perceived ease of use is positive and significant (β=,364 ; p<,000), whereas the relation between perceived self-efficacy and perceived usefulness is non-significant (β=-0,010 ; p<,764), confirming H4a and rejecting H4b. Pedagogy Administration Leisure Test Relation stand. p stand. p stand. p χ² [2] p PSE PEU*,424,343,000,325,220,000,290,230,000 3,789,150 PH PEU,083,059,051,080,050,055,133,101,003 1,494,474 PSC PEU,070,048,185,090,066,162,115,090,100,409,815 INO PEU,165,137,009,155,132,007,248,227,000 2,127,345 PSE PU,014,011,844,023,017,701 -,037 -,033,470,691,708 PH PU,230,163,000,057,038,180,307,264,000 24,056,000 PSI PU,028,020,600,079,062,219,134,107,043 1,856,395 PSC PU,161,110,004,031,025,631,185,162,005 3,384,184 INO PU -,027 -,022,682,177,162,002,064,066,227 5,915,052 PEU PU,384,381,000,310,334,000,235,265,000 2,956,228 PPPL TT,528,503,000,545,608,000,460,452,000 5,789,055 TT IU,615,569,000,617,513,000,692,655,000 6,781,033 PU IU,208,226,000,218,216,000,198,193,000,376,828 PEU IU,243,261,000,157,168,000,090,099,005 9,241,009 * PSI: Perc. social image PU: perc. usefulness IU: Intention to use PEU: Perc.ease of use PSE: Perc.self-efficacy PSC:Perc. self-congruity, PH:Perc. hedonism,ino: Innovativeness PPPL: Perc.protection of private live, TT: Trust Table 3. Moderating effect of context Results indicate that innovativeness influences significantly perceived ease of use (β=,159 ; p<,000) and perceived usefulness (β=,084 ; p<,008), confirming H5a and H5b. As anticipated 10

12 in H6a and b, perceived hedonism positively and significantly influences perceived ease of use (β=,094 ; p<,000) and perceived usefulness (β=,153 ; p<,000). Perceived protection of private life influences positively and significantly trust (β=,529 ; p<,000) and trust influences positively and significantly intention to use, confirming H7a and b. We then conduct a multi-group analysis to test the influence of the context of the digital services (administration, pedagogy or leisure) on the extended TAM. This procedure relies on the analysis of variations of the global fit index χ². First, we verify that measurements do not vary across the three domains, to ensure that differences cannot be attributed to measurement instability. We thus constrain parameters linking constructs and their measurements. We got a difference ² (38) = 47,126 (p<,147) which ensures the absence of measurement differences. Second, we constrain the causal relations between the latent constructs for which we hypothesize the moderation effects and obtain a variation ² (28) =106,32 (p<,000)supporting H8, stipulating the moderating impact of the kind of digital services offered. Nevertheless, every relation is not affected by this moderating effect. The moderating effect is significant (p<0,05) on the relation between perceived hedonism and perceived usefulness ( ² (2) = 24,056 ; p<,000), between trust and intention to use ( ² (2) = 6,781 ; p<,033) and on perceived ease of use on intention to use ( ² (2) = 9,241 ; p<,009). Two relations are only slightly moderated: innovativeness on perceived usefulness ( ² (2) = 5,915 ; p<,052) and perceived privacy on trust ( ² (2) = 5,789 ; p<,055). First, we note (cf. table 3) that the influence of perceived hedonism on perceived usefulness is significantly lower for administrative digital services than leisure and pedagogy services. Second, trust has a stronger influence on intention to use for digital leisure services, than for administration and pedagogy services. Finally, the relation between perceived ease of use and 11

13 intention to use is weaker for digital leisure services than for administrative and pedagogical services. 4. Discussion of Results The primary goal of this research is to enrich the TAM and compare adoption processes in an administrative, learning and private life context. The most important result is the key role played by trust in the IT adoption process. Trust appears to have more impact on intention of use than perceived ease of use and perceived usefulness, whatever the domain of application. Several additional variables indirectly affect behavioral intentions through perceived ease of use and/or perceived utility. The model enhances the importance of perceived competences and innovativeness in perceived ease of use. Feeling self-efficient make consumers more confident about their ability to use new technologies. Innovators, on their side, derive a positive stimulation from using a new product. Learning may also not be considered as a painful effort. The model also emphasizes a hedonic path to innovation acceptance. Consumers consider an innovation all the more easy to use and useful if they feel that it gives them a hedonic benefit. An innovative IT system or digital service can therefore create value not only through its utilitarian benefits but also through the emotional experience associated with its use (Novak, Hoffman and Yung,2000). Surprisingly, social influence plays a secondary role for the adoption of all digital services. This confirms that the role of social influence on innovation adoption remains quite ambiguous (Lewis, Agarwal and Sambamurthy, 2003; Scheppers and Wetzel, 2007; Venkatesh, Morris, and Davis, 2003). 12

14 The second important finding is that psychological processes underlying innovation acceptation were moderated by the nature of the services (leisure, studies, and administrative services). Ease of use only slightly affects intention to use when the digital service is dedicated to leisure, whereas its influence is very significant for the two utilitarian kinds of service (administration and pedagogy). When hedonism is perceived, the influence of ease of use on intention of use thus decrease. There is also a positive influence of perceived hedonism on perceived usefulness. When the IT system provides hedonic value, it therefore seems that time and efforts associated to use are perceived as less costly for consumers as consumers derive more hedonist values. A second main difference between hedonic and utilitarian processes appears through the direct influence played by ease of use on intention of use. Ease of use indeed only slightly affects intention to use when the digital service is dedicated to leisure, whereas its influence is very significant for the two other types of service (administration and pedagogy). Consistently given the fact that an utilitarian IT system is not chosen for hedonic purposes, time and efforts associated to use can be considered as costs. On the contrary, in a hedonic context, consumers derive more emotional value from the direct use of the system. Whatever the domain of application of the IT system or service, users are conscious about the potential risks of the intrusion of the IT in their private life. Even the hedonic benefits cannot compensate for a lack of perceived protection of private life. However the positive influence of trust appears to be greater in the context of new digital leisure services than for new administrative services. This could be explained by the fact that the administrative services concern mostly non sensitive information (e.g. schedules, localization of classrooms).in 13

15 contrast, hedonist leisure services associate risks for private life as topics are more sensitive (e.g. geolocation of individuals). 5. Managerial Implications The most significant managerial implication of this research is that lack of trust and privacy concerns remain the main obstacle to a widespread adoption of IT systems. Respondents do not adopt an unsecured system, even if its use can provide hedonic and utilitarian benefits. Security must be the central topic both in IT development and communication. Results regarding innovation and self-confidence have implications for communication toward experts and opinion leaders who are innovators and/or self-confident. As they experience fewer difficulties in the use of an innovative system, managers should rely on them to convince consumers that technologies are easy to use. Finally, the marketers of IT systems (such as e-learning) must take into account that consumers' expectancies are not strictly utilitarian: information IT systems will be all the more accepted if they are entertaining and safe for their privacy. 6. Limitations and Directions of Research This empirical research has some limitations and leaves many questions unanswered. From a theoretical point of view, it only examines antecedents of technology acceptance. It would be interesting to examine the impact of the variables on the "real" use of an IT system or a digital service, with behavioral loyalty and usage indicators. Theory on technology adoption suggests several direct links between the model variables that have not been tested in this research (e.g. influence of perceived ease of use on perceived hedonism Van der Heidjen, 2004; influence of perceived ease of use on trust intentions; Gefen, Karahanna and Straub, 2003). The methodology of the research may also induce some biases. IT systems and digital services 14

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20 Appendix 1 Reliability and construct validity Items comm load. PSI Perceived Social Image (Sweeney and Soutar, 2001) This kind of services would help me to feel acceptable PSI1,768,877,851 This kind of services would improve the way I am perceived PSI2,882,939,968 This kind of services would make a good impression on other PSI3,827,909,859 people This kind of services would give its owner social approval PSI4, ,930,923 %V exp. 82,753 vc,800 PEU Perceived Ease of Use (Davis, 1989 ; Davis and al. 1989) It would be easy for me to learn how to use this kind of services FUT1,715,845,863 It would be easy for me to develop skills in order to use this kind of FUT2,817, services It would be easy to remember how to use this kind of services FUT3,773,879,824 Generally, I would find easy to process via this kind of services FUT4,654,809 -,879,897 %V exp. 73,987 vc,743 PPPL Perceived Protection of Private Life (Jarvenpaa and al., 2000) This kind of services guarantees my privacy VPT1,714,845,782 The existing legal and institutional framework guarantees sufficiently the privacy of transactions via Generally, I believe that personal information that is carried via this technology is secure VPT2,826,909,892 VPT3,765,875,819,848,871 %V exp. 76,839 vc,692 INO - Innovativeness (Godsmith and Hofacker, 1991 ; Oliver and Bearden, 1985) I like to try new and different things INO1,750,866,795 Usually, I am among the first ones to try new products INO2,684,827,720 I like to experiment with new ways of doing things INO3,741,861,788,807,812 %V exp. 72,519 vc,591 PSE Perceived Self Efficacy (Faurie and vand de Leemput, 2007) I feel self-confident to download on internet data I need (software, video, files ) SET1,555,745,771 to create a personal web page or a blog SET2,606,778,676 to configurate and use an internet telephone software (e.g Skype ) SET5,523,723,645,786,741 %V exp. 54,210 vc,490 19

21 TT - Trust (Dimitriadis and Kyrezis, 2010) To organize, I feel that I could trust this kind of services TRI1,901,949,911 In order to, I feel that I could rely on this kind of services TRI2,901,949,904,891,904 %V exp 90,140 vc,824 IU Intention to Use (Davis, 1989 ; Davis and al. 1989) I intend to continue using this kind of services in the future IDC1,812,901,896 I will always try to use this kind of servicesin my daily life IDC2,820,906,859 I plan to continue using this kind of servicesfrequently IDC3,871,934,913,900,919 %V exp. 83,474 vc,792 PU Perceived Usefulness (Davis, 1989 ; Davis and al. 1989) The use of this kind of services would help me to perform faster UPP1,703,838,747 The use of this kind of services would help me to save money in UPP2,235,485 - The use of this kind of services would facilitate the delivery of UPP3,776,881,838 Generally, the use of this kind of services would be useful in performing. UPP4,745,863,853,752,855 %V exp. 61,504 vc,663 PH Perceived Hedonism (Venkatesh and al. 2012) Using this kind of services is fun HDO1,831,912,881 Using this kind of services is enjoyable HDO2,682,826 - Using this kind of services is very entertaining HDO3,828,910,915,859,890 %V exp. 78,039 vc,802 PSC Perceived Self-congruity (Sirgy and Su, 2000) This this kind of services is consistent with how I see myself SCV,775,880,822 This this kind of services is consistent with how I like to see myself SCI,882,939,951 This kind de service is consistent with how I believe others see me SCS,863,929,924 This kind of services is consistent with how I would like others to SCSI,871,933,910 see me,940,946 %V exp. 84,748 vc,815 20

22 Appendix 2 Discriminant validity Scale vc PSI Perceived Social Image (Sweeney and Soutar, 2001),930,923,800 PEU Perceived Ease of Use (Davis, 1989 ; Davis and al. 1989),879,897,743 PPPL Perceived Protection of Private Life (Jarvenpaaand al.,,848,871, ) INO - Innovativeness (Godsmith and Hofacker, 1991 ; Oliver and,807,812,591 Bearden, 1985) PSE Perceived Self Efficacy (Faurie and vand de Leemput, 2007),786,741,490 TT - Trust (Dimitriadis and Kyrezis, 2010),891,904,824 IU Intention to Use (Davis, 1989 ; Davis and al. 1989),900,919,792 PU Perceived Usefulness (Davis, 1989 ; Davis and al. 1989),752,855,663 PH Perceived Hedonism (Venkateshand al. 2012),859,890,802 PSC Perceived Self-congruity (Sirgy and Su, 2000),940,946,815 PH PSI PEU PSE INO PPPL PU TT IU PSC PH,802 PSI,127,800 PEU,104,050,663 PSE,034,019,062,490 INO,087,019,089,369,591 PPPL,009,058,072,077,067,692 PU,034,004,190,206,168,044,743 TT,049,029,338,177,195,240,286,824 IU,071,051,303,184,225,192,240,578,792 PSC,129,550,018,059,070,074,092,074,111,815 21