an exploration of facebook.com adoption in tunisia using

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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

COPY RIGHT © 2012 Institute of Interdisciplinary Business Research

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An Exploration of Facebook.Com Adoption in

Tunisia Using Technology Acceptance Model (TAM) and Theory of

Reasoned Action (TRA)

Wadie Nasri

Assistant Professor of Marketing in the Higher Institute of Management of Gabes, University of

Gabes, Tunisia

Lanouar Charfeddine*17

(*) Assistant Professor, College of Administrative Sciences, University of Najran, BOX 1988,

Alsawady Aireport, 11111 Najran.

Abstract

This paper aims to examine empirically the factors that affect the adoption of Facebook by

Tunisian students’. Technology acceptance model (TAM) and The Theory of Reasoned Action

(TRA) as the base model in order to investigate the adoption of Facebook. The model employs

snoop, news, perceived enjoyment, information receiving and self efficacy, in addition to

perceived usefulness, perceived ease of use, attitude, social norm, and intention to use Facebook.

A survey involving a total of 240 respondents is conducted and confirmatory factor analysis used

to determine the measurement efficacies. Theoretically, this study confirms the applicability of

the TAM model and TRA in predicting Facebook.com adoption by Tunisian students’. This

study contributes to the validation of technology acceptance model outside of the Anglo-Saxon

context, especially in developing country. From a practical perspective, this study results

suggests important implications for companies aiming exploiting the marketing potentialities of

Facebook because it is the most popular online social networking site among university students

Keywords Facebook, Technology adoption, Technology Acceptance Model, Theory of

Reasoned Action, Structural equation modelling, Tunisia

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1. Introduction

Since their introduction, social networking sites (SNSs) such as MySpace, Facebook,

Cyworld, and Bebo have attracted millions of users, many of whom have integrated these sites

into their daily practices. These sites have changed the way people communicate with each other,

helping users find a social network, share common interests, connect with friends, participate in

discussion forums, and express themselves through a personalized blog or minihomepage. (Kim

et al, 2011).

Social networking sites provide a public forum that enables the exchange of digital

information, such as pictures, videos, text, blogs, and hyperlinks between users with common

interests, such as hobbies, work, school, family, and friendship (Sledgianowski & Kulviwat,

2009). Popular Social network sites include Myspace, Facebook, and Friendster, with Myspace

reported, to have over 200 million members (Thill & Bovee, 2009). Facebook

(www.facebook.com) is the most popular social networking site. The use of Facebook has

become an international phenomenon, with over 8 million users.

Social networking sites (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.

This study focuses on new channel of communication and information technology adoption

in a developing country, namely Tunisia, where social network sites (SNS) is still emerging. We

believe that Facebook is appropriate for the current study as it is the most popular online social

networking site among university students

There is no published empirical research studying the determinants of intention to use this

technology in Tunisia country. This paper addresses the following research questions: (1) what

are the factors that influence the use of Facebook?; (2) what is the relative importance of these

factors? and (3) what is the nature and strength of the relationship among these factors?

In order to explain the factors, this paper extends the technology acceptance model in two

ways. First, we included five factors that influence the use of Facebook: self efficacy, subjective

norm, perceived enjoyment, snoop and information receiving. Also, we added four key

demographic constructs as external variables to the TAM (i.e., age, education, income and race).

The remainder of the paper is divided into five sections. The first section contains a literature

review about information technology acceptance. In this section, we present our research model,

which we call the Facebook Adoption model. The second section describes the methodology

used to empirically investigate our hypotheses. The third section comprises the data analysis and

hypotheses testing results. The Fourth section consists to discuss the main findings and draw

implications for theory and practice. Fifth and finally, we suggest limitations of our research and

suggestions for future research.

2. Theoretical background

Social Networking and Facebook

Social network sites (SNSs) as web-based services that, allow users to create profiles on the

site, to post information and share that information and communicate with other users of the site

(Kaplan and Haenlein, 2010). These sites have changed the way people communicate with each

other, helping users find a social network, share common interests, connect with friends,

participate in discussion forums, and express themselves through a personalized blog or

minihomepage. (Kim et al, 2011).

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Social networking services (SNS) allow users to gather together as an "online community",

with connections to current personal relationships, such as friends/family, or to meet other

people on the basis for friendship, activities, professional networking, or romance (Kim et al,

2011). The nature and nomenclature of these connections may vary from site to site.

Facebook, Twitter and LinkedIn might be the first sites that come to mind when thinking of

social networking sites, these popular websites do not represent the full scope of social networks

that exist, such as Twitter, Myspace, Friendster, Youtube, Badoo, Wikis, Skype …Since their

introduction, these social network sites have attracted 200 millions of users, many of whom have

integrated these sites into their daily practices

Facebook is a social networking website intended to connect friends, family, and business

associates. It is the largest of the networking sites, with the runner up being MySpace (Mary

White: http://socialnetworking.lovetoknow.com/). Facebook users create a profile page that

shows their friends and networks information about themselves. The choice to include a profile

in a network means that everyone withing that network can view the profile. This profile

includes: Information, Status, Friends, Photos, Notes, Groups, and The Wall.

Facebook was founded in 2004 by Harvard student Mark Zuckerberg and originally called

the Facebook. It was quickly successful on campus and expanded beyond Harvard into Stanford

and Yale where, like Harvard, it was widely endorsed. With the phenomenon growing in

popularity, Zuckerberg enlisted two other students, Duston Moskovitz and Chris Hughes, to

assist. Within months, the Facebook became a nationwide college networking website in Canada

and USA. In August of 2005, the Facebook was renamed Facebook.com, and the domain was

purchased for a reported $200,000 USD. At that time, it was only available to schools,

universities, organizations, and companies within English speaking countries, but has since

expanded to include anyone. Finally, it is in September 26, 2006 he decided to open Facebook to

the public (ages 13 and older with a valid email address). And since that day, he became the most

popular social networking site, with over 350million subscribers worldwide (according to

Facebook.com statistics retrieved in March, 2010).

Theory Acceptance Model and related theories

Three models have been applied to explain the acceptance and usage of information

technology: the technology acceptance model (TAM) originally proposed by Davis (1989), the

theory of reasoned action (TRA) originally proposed by Fishbein and Ajzen (1975), and the

extension of TRA into a theory of planned behavior (TPB) originally proposed by Ajzen (1991).

The technology acceptance model (TAM) (Davis, 1989; Davis et al, 1989) adapted from the

Theory of Reasoned Action (TRA) (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) has

received significant attention in IT/IS acceptance literature. Technology acceptance model

(Davis 1989, Davis et al. 1989) focuses on the attitudinal explanations of intention to use a

specific technology or service. Technology acceptance model posits that two particular beliefs,

perceived usefulness (PU) and perceived ease of use (PEOU) are main determinants of the

attitudes (AT) toward using a new technology. (PU) is the degree to which the user believes that

using the technology would improve his or her performance on a task, while PEOU is defined as

the degree to which a person believes that using a particular system would be free of effort

(Davis, 1989; Davis et al., 1989).

The Theory of Reasoned Action (TRA), developed by Fishbein and Ajzen (1975), is one of

the most influential theories used to explain human behaviour. According to this theory, the

behavioral intention can be explained by the attitude towards behavior and subjective norm. The

attitude towards behavior is defined as “an individual’s positive or negative feelings (evaluative

http://socialnetworking.lovetoknow.com/Challenges_of_Online_Social_Networking

http://www.wisegeek.com/what-is-a-social-networking-site.htm

http://www.wisegeek.com/what-is-myspace.htm

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effect) about performing the target behavior” (Fishbein and Ajzen, 1975, p. 216). Subjective

norm refers to perception that most people who really matter to the individual think that he either

should or should not perform the behavior in question” (Fishbein and Ajzen, 1975).

The theory of planned behavior (TPB) was proposed as an extension of the theory of reasoned

action for conditions where individuals do not have complete control over their behavior (Ajzen

1991). The addition of perceived behavioral control in TPB reflects the internal and external

constraints on behavior, and is directly related to both behavioral intention to use and actual use

(Ajzen 1991). The theory of planned behavior (TPB) suggests that a central factor in human

behaviour is behavioral intention, which is affected by attitude toward behavior, subjective norm,

and perceived behavioral control (Ajzen, 1985, 1991, 2002).

3. Conceptual framework and hypotheses

One benefit of using TAM to understand acceptance and usage of information technology is

that it provides a framework to investigate the effects of external variables on system usage

(Hong et al, 2001). Therefore, this research incorporates to TAM sex additional constructs: self

efficacy, subjective norm, perceived enjoyment, snoop, news and information receiving, which

would help us to better predict intention to use Facebook.

Perceived usefulness and ease of use

TAM theorizes that an individual's behavioral intention to adopt or use any information

technology is determined by the by two beliefs: perceived usefulness and perceived ease of use.

While perceived usefulness is defined as the degree to which a person believes that using the

new technology will enhance their task performance, 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. Previous studies on the adoption of innovations suggested the important

role for perceived usefulness on intention to use information technology (Tornatzky and Klein,

1982). Moreover, perceived usefulness mediates the effect of perceived ease of use on usage

(Agarwal & Prasad 1999; Davis et al., 1989; Jackson et al., 1997; Venkatesh, 1999). Based on

Davis (1993) perceived usefulness has a direct effect on intention to use over and above its

influence via attitudes (Taylor and Todd, 2001). Ajzen (1991) defined intention as a person’s

subjective probability of performing a behavior. It reflects the willingness of an individual to

engage in a certain behavior. Behavioral Intention to use is a measure of the likelihood that a

person will adopt the application (Norazah and Norbayah, 2011). Several studies have supported

the notion that behavioral intentions are found to have a positive effect on behavior (Hung et al.,

2003; Tung, 2004; Nysveen et al., 2005 Amin et al., 2007). In summary, attitude toward the

behavior, and social norm, lead to the formation of a behavioral intention (Azjen, 1991).

Perceived ease of use refers to the degree to which a person believes that using a particular

system would be free of effort (Davis, 1989). Perceived ease of use shows how much effort an

individual needs to effort in using an information technology. Perceived usefulness and

perceived ease of use are the two relevant beliefs for determining attitude toward using

information technologies. Technology acceptance model postulates a positive direct impact of

perceived ease of use on perceived usefulness (Davis, 1989).

A considerable amount of prior studies supported the significant effect of perceived ease of

use on behavioral intention, either directly or indirectly through perceived usefulness (e.g.,

Agarwal & Prasad, 1999; Davis et al., 1989; Hu et al, 1999; Jackson et al., 1997; Venkatesh,

1999; Yi & Hwang, 2003).

In Tunisia, previous studies have well documented the importance of perceived ease of use in

explaining technology information since introduced by Davis. Wadie and Lanouar, (2012) found

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that there is a significant relationship between perceived ease of use and perceived usefulness

and perceived ease of use and attitude toward using internet banking by Tunisian’s consumers.

There are many researchers who have studied the relationship between perceived ease of use and

perceived usefulness. For instance, Moon & Kim, 2001 discovered that the relationship was

significant perceived ease of use and perceived usefulness. Therefore, based on the theoretical

and empirical support from the information technology literature, we tested the following

hypotheses:

Hypothesis 1. Perceived usefulness will have a positive effect on intention to use Facebook.

Hypothesis 2. Perceived usefulness will have a positive effect on attitude toward using

Facebook

Hypothesis 3. Perceived ease of use will have a positive effect on attitude toward using

Facebook

Hypothesis 4. Perceived ease of use will have a positive effect on perceived usefulness of

Facebook.

Attitude towards Using Facebook

Attitude is populated to be the first antecedent of behavioral intention. It is an individual’s

positive or negative belief about performing a specific behavior. An individual will intend to

perform a certain behavior when he or she evaluates it positively. It has been demonstrated that

attitude has a strong effect, direct and positive, on the real individual intentions by using a new

system or technology (Bobbitt and Dabholkar, 2001; Dishaw and Strong, 1999; Venkatesh and

Davis, 1996). In this research, attitude is hypothesized to influences the intention towards using

services, and is defined as the degree to which an individual’s attitude is favourably or

unfavourably disposed towards using Facebook services. Accordingly, we hypothesized that:

Hypothesis 5. Attitude will have a positive effect on intention to use Facbook.

Social norm

Social norm or normative pressure refers as the person’s perception that most people (e.g.,

parents, teachers, friends…) who are important to her or him should or should not perform the

behavior in question (Ajzen and Fishbein, 1980; Nysveen et al., 2005). The effect of social norm

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) and Nysveen et al. (2005) noted that social norm to be important

construct that explains the usage of mobile banking in Malaysia. 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), social norm is proposed as

a direct antecedent of behavioral intention in this study. Furthermore, Wadie, (2011) and Wadie

and Lanouar, (2012) found that the social norm as essential elements in the development of

people intention to use internet banking Tunisian’s. Thus the following hypothesis is proposed:

Hypothesis 6. Social norm has a positive effect on consumer acceptance of online banking.

Snoop (SNO)

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Facebook provides a formatted web page into which each user can enter personal

information, including contact information, personal information like gender, birthday,

hometown, political and religious views, e-mail and physical addresses, relationship status, , and

school concentration, information regarding interests in movies, music, clubs, books, relationship

status and partner, and political affiliation. After completing their profile, users are prompted to

identify others with whom they have a relationship, either by searching for registered users of

Facebook or by requesting their contacts to join Facebook (usually by e-mail). Users can in fact

choose to fill in any of this information and update their information at any time. It is possible to

snoop on Facebook and get information from profiles and postings. This capability attracts

millions of users around the globe to use Facebook. Based on the description above hypothesis as

follows:

Hypothesis 7. Snoop will have a positive effect on the perceived usefulness of Facebook.

News (NEW)

Facebook allows users to receive public updates from other users without becoming friends

with them. To keep users updated about their social circles, Facebook has two features: “News

Feed”, which appears on the homepage of each user, and “Mini-Feed”, which appears in each

individual’s profile. The News Feed updates a personalized list of news stories throughout the

day generated by the activity of friends. The Mini-Feed is similar, except that it centers around

one individual. Each person’s “Mini-Feed” shows what has changed recently in their profile and

what content or modules (“applications”) they have added. Based on the description above

hypothesis as follows:

Hypothesis 8. News will have a positive effect on the perceived usefulness of Facebook.

Perceived enjoyment

Prior studies of the World Wide Web and electronic commerce have empirically added PE to

the TAM to predict user acceptance and adoption of a specific source, and found this construct

has a positive effect on attitude towards using a specified system (Dabholkar, 1996; Bruner and

Kumar, 2005; Moon and Kim, 2001). Prior studies also suggest that perceived enjoyment has a

significant influence on behavioral intention to use blogs/hedonic systems (Hsu and Lu, 2007;

Van der Heijden, 2003; Van der Heijden, 2004). Perceived enjoyment (PE) is defined as the

extent to which the activity of using a specific system is perceived to be enjoyable in it’s own

right, aside from any performance consequences resulting from system use (Davis et al, 1992).

In this study, we define perceived enjoyment as the degree to which a person believes that

use of Fcaebook services will be interesting and associates it with enjoyment. If one person has

to feel that using Facebook can be enjoyed for them, this will encourage person to have an

acceptance attitude of Facebook. Based on the description above hypothesis as follows:

Hypothesis 9. Perceived enjoyment will have a positive effect perceived usefulness of

Facebook.

Information receiving (IR)

Users receive a variety of information from other users. It has become an important source of

information. Based on the description above hypothesis as follows:

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Hypothesis 10. Information receiving will have a positive effect on the perceived usefulness

of Facebook.

Computer self-efficacy

Computer self efficacy has also been repeatedly cited in the IS literature as an important

factor in in understanding individual response to information technology (Amin, 2007; Chan &

Lu, 2004; Compeau & Higgins, 1995).

Perceived computer self-efficacy’ is defined as an individual’s self- confidence in his or her

ability to perform tasks across multiple computer application domains (Monsuwe´ et al., 2004).

Davis et al. (1989) and Wang et al. (2003), find that ‘computer self-efficacy’ and ‘perceived

ease of use’ are related. Others studies have examined the relationship between self-efficacy with

respect to computer use (e.g. Wang et al., 2003; Eastin, 2002; Bandura, 1977; Monsuwe´ et al.,

2004; Wang and Newlin, 2002). There also exists empirical evidence of a causal link between

self-efficacy and perceived ease of use (e.g., Agarwal et al., 2000; Igbaria & Iivari, 1995;

Venkatesh, 2000; Venkatesh and Davis, 1996). On the basis of these findings, the following

hypothesis is proposed:

Hypothesis 11. Perceived self-efficacy will have a positive effect on the perceived ease of

use of Facebook.

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Figure 1: The proposed research model with hypothesis

4. Methodology

Data collection

Subjects were drawn from a convenience sample of 300 users of Facebook. Of these, 250

were retained for analysis, providing a usable response rate of 75%. Of these respondents, there

were 38 percent female and 62 percent male. The questionnaire is divided in 59 questions

directly related to use of Facebook and 10 general questions related to gender; age; level of

education; social and personal questions; questions directly related to using internet and general

questions related to internet and banking services. The questionnaire was administered by

meeting the respondents on a one-to-one and were asked to circle the response which best

described their level of agreement with the statements. For, perceived ease of use, perceived

usefulness, perceived enjoyment, self efficacy, social norm, attitude and intention to use

Facebook the respondents require to rate their level of agreement with statements using five-

point scales ranging from “strongly disagree” (1) to “strongly agree” (5). For, snoop, news and

Intention to

use Attitude

Social

norm

Percevied

usefulness

Percevied

ease of use

Snoop

News

Percevied

enjoyment

Information

receiving

Self

efficacy

H1

H2

H3

H4

H5

H6

H7

H8

H9

H10

H11

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information receiving the respondents require to rate their level of agreement with statements

using five-point scales ranging from “to never use” (1) to “very often” (5). The English version

of questionnaire was translated to French language to facilitate the survey (see Appendix). The

questionnaire was completed by students on courses of Higher Institute of Management of Gabes

in April and May of academic year 20011/2012.

Measurement of Constructs

The measurement of all the variables in the current study was largely based on previous

studies (see Appendix). Items for perceived usefulness, perceived ease of use, attitude, and intent

to use were measured using items adapted from Cheng et al, (2006) and Lai and Li, (2005),

containing four items for perceived usefulness and attitude and three items for perceived ease of

use and intention to use. The computer self efficacy construct was measured using items adapted

from Compeau and Higgins (1995) study containing ten items. Subjective norm were adapted

from the measurements defined by Wu and Chen (2005), containing three items. Perceived

enjoyment was derived from containing three items. Snoop, News and information receiving

were adopted from the measurements defined by Watanyoo and Wornchanok, (2011) containing

three items for the first construct and two items for the second and third construct. The

demographics characteristics were measured in terms of gender, age, education, possession of

Facebook account, frequencies of check account Facebook and purpose to use Facebook were

adapted from (Robly et al, 2010).

A total of 300 people were sampled, 240 responses were received and 207 questionnaires

were useable for analysis. The gender distribution of the survey respondents is 87.2 per cent

females and 12.60 per cent males.

The results also indicated that the samples have age predominantly between 20 and 22 years,

which is 87.2 per cent.

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More than 93.70 per cent of the respondents had a personal computer.

Survey results indicated that large majority of students have Facebook account. Of 207

respondents, 207 (95.7%) claimed to have Facebook accounts, while only 39 (4.7%) did not. The

most frequent indication for users was checking Facebook once times per day, and a quarter of

users also checked their accounts 2-5 times per day.

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The reasons why students join Facebook that we explore in our survey fall into eight broad

categories, to get a relationship, to communicate, to find friends, for enjoyment, to be known, to

cultivate, to learn more, and to meet other people. The most students joined Facebook, to

communicate, to get a relationship and to find friends. Our results suggest that those surveyed

were well aware of how Facebook could be used and some of the advantages of using it. These

users probably view Facebook like a social network and enhanced directory tool to aid in various

social connecting.

5. Data analysis and results

Measurement model

The test of the measurement model includes the estimation of internal consistency and the

convergent and discriminant validity of the instrument items. Convergent validity is

demonstrated when items load highly (loading> 0.50) on their associated factors. Convergent

validity also is adequate when constructs have an Average Variance Extracted (AVE) of at least

0.50 [25]. Table 1 shows that all AVE were well above the recommended value level of 0.50.

For satisfactory discriminant validity, the AVE from the construct should be greater than the

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variance shared between the construct and other constructs in the model. The remaining items

and their standardized loadings are shown in Table 1.

All items have large and significant loadings on their corresponding factors. The composite

reliabilities of the different measures included in the model ranged from 0.577 to 0.871. Further,

the average variance extracted (AVE) statistics ranged from 0.506 to 0.928, and the shared

variance was less than the amount of variance extracted by the indicators measuring the

constructs. Thus, convergent and discriminant validity were met. Taken together, the evidence

indicates the scales' had adequate psychometric quality for use in the next stage of analysis.

Table 1. Construct reliability and convergent validity

Constructs items Factor

laoding t-value

Average variance

extracted

Cronbach

alpha

KMO

Self efficacity

SE1 0.72

0.861 0.709 0.642 SE2 1.18 5.40

SE3

0.82 6.18

Snoops

SNO1 0.86

0.506 0.638 0.500 SNO2 0.69 5.03

SNO3

0.55 4.12

News

NEW1 1.02

0.577 0.500 NEW2 0.62 3.70

Perceveid

enjoyment

PE1 0.55

0.575 0.601 0.590 PE2 0.84 4.32

PE3 0.84 4.31

Information Receiving

INFR1 0.97

0.806 0.701 0.509 INFR2 0.82 5.98

Perceived ease of

use

PEOU1 0.72

0.532 0.795 0.774 PEOU2 0.71 6.49

PEOU3 0.62 8.79

PEOU4 0.72 7.74

Percevied usefulness

PU1 0.79

0.668 0.814 0.717 PU2 0.79 9.09

PU3 0.87 9.71

Attitude

ATT1 0.58

0.644 0.772 0.688 ATT2 0.91 6.40

ATT3 0.87 6.26

Social norm

SN1 0.98

0.800 0.871 0.568 SN2

0.80 4.91

Intention to use IB

INT1 0.86

0.928 0.779 0.677 INT2 1.06 11.96

INT3 0.96 10.75

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Structural model

The test of structural model was performed using the LISREL8.3 procedure, a software

package designed to perform structural equations model approach to path analysis. Seven

common model-fit measures were used to assess the model’s overall goodness-of-fit: the ratio of

χ2 to degrees-of-freedom (df); Root Mean Square Error of Approximation (RMSEA);Goodness

of- Fit Index (GFI); Adjusted Goodness-of-Fit Index (AGFI); Normalized Fit Index (NFI); Non-

Normalized Fit Index (NNFI); Comparative Fit Index (CFI); and Root Mean Square Residual

(RMSR). The table 2 shows that the confirmatory factor analysis model responds to the major

acceptable criteria (Hair et al., 1998). Incremental indices CFI, NFI, RFI, and the IFI are superior

to 0.90 and the RMSEA is inferior to 0.09, so the model could be considered as significant. In

addition absolute indices and parsimonies indices have clearly exceeded the minimum

recommended values suggested for a good model fit. Table (2) : Results of Goodness of Fit

Fit Indices Suggested Obtained Absolute Indices

Scaled 2 ( 2 /df) > 1 and < 5 1.922

Goodness of Fit Index (GFI) > 0.9 0.82 Root Mean Square Error of Approximation

(RMSEA) < 0.08 0.067

Incrementals Indices Comparative Fit Index CFI > 0.9 0.91 Normed Fit Index NFI > 0.9 0.84 Relative Fit Index RFI > 0.9 0.83 Incremental Fit Index (IFI) > 0.9 0.92

Parcimonie Indices AIC The lower by comparaison 785.51

a

CAIC The lower by comparaison 1071.47b

Expected Cross-Validation Index ECVI The lower by comparaison 3.81c

a AIC for independent and saturated models are equal to 4440.15 and 812.00 respectively.

b CAIC for independent and saturated models are equal to 4561.47 and 2571.08 respectively.

c EVCI for independent and saturated models are equal to 21.55 and 3.94 respectively.

The structural model shows the relationships between the constructs and specifies the

constructs that are related to each other (Hair et al., 1998). Figure 2 shows each construct in the

model with the standardized path coefficients at significant levels. The results of this study

showed that perceived usefulness was not a significant factor in determining the intention to use

Facebook (β = 0.14, p < .01). Attitude has the strongest effect on intention to use Facebook (β =

0.87, p < .01), followed in order by social norm (β = 0.53, p < .01). Perceived ease of use has

significant effect on attitude towards using Facebook (β = 0.56, p < .01). Perceived ease of use

has significant effect perceived usefulness towards using Facebook (β = 0.56, p < .01). Snoop,

News, information receiving and perceived enjoyment have significant effect on perceived

usefulness (β = 0.41, p < .01; β = 0.46, p < .01; β = 0.63, p < .01 and β = 0.49, p < .01). Finally,

self efficacy was not a significant effect on perceived ease of use of Facebook.

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*** indicate that the coefficient is significant at the 1% level (p-value <0.01)

Means that the coefficient is not significant

Figure 2. Results of structural modelling analysis

Intention to

use Attitude

Social

norm

Percevied

usefulness

Percevied

ease of use

Snoop

News

Percevied

enjoyment

Information

receiving

Self

efficacy

H1

H2

H3

H4

H5

H6

H7

H8

H9

H10

H11

0.14***

0.64***

0.87***

0.53***

0.56***

0.41***

0.46***

0.59***

0.63***

0.13***

0.52***

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6. Discussion

By empirically testing the model, it has been demonstrated that most of the factors in the

proposed model have direct or indirect significant influence except perceived usefulness and self

efficacy on intention to use Face book. Data in this study also indicated that the proposed model

is an adequate fit to the observed variables that influence students’ to use Facebook.

Attitude and social norm strongly affects behavioural intention to use Facebook, supporting

this hypothesis. This is consistent with prior studies that found the effect of attitude and social

norm on intention to use technology (Wadie and Lanouar, 2011; Chun et al., 2006).

Perceived usefulness was not a significant factor in determining the intention to use

Facebook. Following Davis et al. (1989) perceived usefulness, is considered to have a direct

effect on intention to use innovations. In the present study, this effect was not supported by the

data. Perceived use impacts positively on attitude towards use of Facebook. This finding

confirms results of different studies stating the importance of individual’s perceived added value

of technologies as a determinant for adoption (Wadie and Lanouar, 2011).

There is also a significant relationship between perceived ease of use and attitude towards

using Facebook. Consistent with literature, perceived ease of use refers the extent to which a

potential social network user views usage of this platform to be relatively free of effort (Davis et

al., 1989). Innovations that are perceived to be easier to use and less complex have a higher

likelihood of being accepted and generate a favourable attitude by potential users.

This study found also, a significant relationship between perceived ease of use and perceived

usefulness of Facebook. These results are consistent with the research results conducted by

Davis, et al (1989); Wang, et al (2003), and Wadie and Lanouar, (2011). Wadie and Lanouar

(2011), which stated that there is a significant relationship between perceived ease of use and

perceived usefulness of using internet banking by Tunisian’s consumers.

A Significant relationship between snoop, news and information receiving and perceived

usefulness. These results are consistent with the research results conducted by Watanyoo and

Wornchanok, (2011) which stated that there is a significant relationship between snoop, news,

information receiving and adoption of Facebook.com. Perceived enjoyment has significant effect

on perceived usefulness towards Facebook, supporting this hypothesis. In fact, the perceived

enjoyment is a more significant antecedent of perceived usefulness which argued that perceived

usefulness played a critical role in work related environment only (Moon and Kim, 2001).

Following Davis et al. (1989) and Wang et al. (2003), self efficacy is considered to have a

direct effect on perceived ease of use. In the present study, this effect, although relevant from a

theoretical perspective, was not supported by the data. That is, the hypothesis, which maintains

that self efficacy will have a direct positive impact on perceived ease of use, was not supported

by the data.

7. Conclusion, implications and limitations

This study examines the TAM and TAR within the context of Facebook and confirms that

this model is useful to explain Facebook adoption. The aim of the study is thus to propose a

conceptual framework to help better understand the factor of the adoption of Facebook in Tunisia

and to use the study’s findings to develop guidelines for SNS providers on how to maximize the

rate of adoption. There are ten constructs compiled into a structural model to explain factor of

the adoption of Facebook, i.e. snoop, news, perceived enjoyment, information receiving, self

efficacy, perceived usefulness, perceived ease of use, , social norm, attitude and adoption to use

Facebook.

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This study is one of the first studies in Tunisia which attempts to explain intention to use

Facebook. First, this study contributes to the validation of technology acceptance model outside

of the Anglo-Saxon context, especially in developing country

Secondly, the findings of this study indicate that attitude has the most significant influence

on behavioral intention to use Facebook. Thus, social norm is the most important factor after

attitude for students in adoption of Facebook. Thirdly, the results 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 Tunisia. The most important benefit they

get by being connected relates to social interactions and building new relationships.

From a theoretical perspective, this study reinforces the role of perceived ease of use and

perceived usefulness beliefs as determinants of a positive attitude towards Facebook adoption.

This in turn impacts positively intention to use facebook. Additionally, it was found that

perceived ease of use impacts perceived usefulness. Our results also have confirmed that

perceived usefulness is not a reliable predictor of behaviour intention as it is attitude towards

intention to use Facebook. Moreover, perceived usefulness is influenced by snoop, news and

information receiving.

From a practical perspective, this study results suggests important implications for companies

aiming exploiting the marketing potentialities of Facebook because it is the most popular online

social networking site among university students. Many businesses are changing the way they

conduct their marketing activities through the use of Facebook as an advertising vehicle,

distribution channel, and to foster word-of-mouth referrals Kelly (Moore et al, 2011).

This research also has some limitations such. First, the factors selected in this study may not

cover all factors that could influence the adoption of Facebook.com in Tunisia. Therefore future

studies can consider others factors, which might have an influence in the adoption

Facebook.com. The second limitation was that the model was tested only with students.

Therefore, other researchers can consider other users of Facebook.com to generalize the results.

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Appendix 1. Measurement scales Constructs Measures

Perceived usefulness

(PU)

PU1 Using Facebook, enable me to communicate more quickly with friends

PU2 Using Facebook, would improve my ob performance

PU3 Using Facebook, would improve my productivity

PU4 Using Facebook, would enhance my effectiveness on the job

PU5 Using Facebook, would make it easier to do my job

PU6 I would find Facebook useful in my job

Perceived ease of use

(PEOU)

PEOU1 Learning to operate Facebook would be easy for me

PEOU2 I would find it easy to get Facebook to do what I want to do

PEOU3 My interaction with Facebook would clear and understandable

PEOU4 I would find Facebook to be flexible to interact with

PEOU5 It would be easy for me to become skilful at using Facebook

PEOU6 I would find Facebook easy to ease

Intention (INT) INT1 I would use the online banking for my banking needs.

INT2 Using the online banking for handling my banking transactions is something I

would do.

INT3 I would see myself using the online banking for handling my banking transactions.

Attitude (ATT) ATT1 Using it to connect with others is good idea

ATT2 I like using it to connect with others

ATT3 Using it is interesting

ATT4 Using it to connect with others is attractive

Self efficacy SE1 I could complete my communication using Facebook, if there was no one around to

tell me what to do.

SE2 I could complete my communication using Facebook, if I had never used a package

like it before

SE3 I could complete my communication using Facebook, if I had only the manuals or

online help for reference

SE4 I could complete my communication using Facebook, if I had seen someone else

using it before trying it myself.

SE5 I could complete my communication using Facebook, if I could call someone for

help if I got stuck

SE6 I could complete my communication using Facebook, if someone had helped me get

started

SE7 I could complete my communication using Facebook, if I had a lot of time to

complete the job.

SE8 I could complete my communication using Facebook, if I had built-in help facility

for assistance.

SE9 I could complete my communication using Facebook, if someone showed me low to

do it first

SE10 I could complete my communication using Facebook, if I had used similar system

before to do the same job.

Subjective norm SN1 People who are important to me would think that I should use online banking.

SN2 People who influence me would think that I should use online banking.

SN3 People whose opinions are valued to me would prefer that I should use online

banking.

Perceived enjoyment (PE) PE1 I find using the system to be enjoyable.

PE2 The actual process of using the system is pleasant

PE3 I have fun using the system

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Constructs Measures

Snoop (SNO) SNO1 Frequency of watching other people profiles

SNO2 Frequency of watching other people photos

SNO3 Frequency of reading other people posted messages

News (NEW) NEW1 Frequency of reading their Top News ( Most Resent)

NEW2 Frequency of reading News-Feed

Information receiving (IR) IR1 Frequency of reading links sent from their friends

IR2 Frequency of reading information sent from organizations or people selected as ‘

Like’

IR3 Frequency of reading group messages

1. Are you:

□ Male □ Female

2. How old are you:

□ 20 – 22 years

□ 23 – 25 years

□ 26 – 28 years

□ More than 29 years

3. Do you have a Facebook account?

□ Yes □ No

4. On average, how many time each day do you check your account

□ NO/no Facebook account □ 6 – 10 times a day

□ Less than once a day □ 11 – 15 times a day

□ 1 – 5 times a day □ 16 – 20 times a day

□ More than 20 times a day

5. For what purpose(s) di you check you account? (you may choose more than one answer).

an exploration of facebook.com adoption in tunisia using

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