ISEM 3120 – Seminar ISEM Presentation Two

- Mark Deng- Queenie Wong

Group 1- Eric Lee- Nixon Wong- Ophelia Mak

Reading

1. Introduction • What’s social networking sites (SNS)? • Web 2.0 tools allow users online interaction on all

forms of media (E.g. text, photos, videos, audios, “post”…etc)

• Common known examples: • Facebook

• MySpace

• Google+

1. Introduction • What’s the research objective?

To find out…• The Key Impetuses (intention) of member’s use of SNS

• The key Impediments (barriers) to members’ use of SNS

• How Impetuses and Impediment interact together in determining members’ site use

• Use of positive and negative factors of members’ use of SNS and find relationship between them

1. Introduction • Why? – The research rationale• (1) Limitation of previous studies• Focus point of previous studies: members’ use intention but

not the actual use behavior

• Use intention may not predict use behavior due to reasons such as behavioral control

1. Introduction • Why? – The research rationale• (2) Theoretical underpinning• Many existing studies based on Technology Adoption Model

• Limited in explaining the use I.T. leisure and hedonic information systems such as SNS

• Not suitable for the study & results may not be most appropriate

1. Introduction • Why? – The research rationale• (3) Miss the interaction between positive and negative

factors• Previous studies just focus on either positive or negative

impact

• Ignored the use phenomenon by considering both positive and negative factors

• Lead to incomplete understanding of the SNS

Needs new research to further investigate of SNS through: o Alternative theoretical foundationso Comprehensive research frameworks

2.1 Research Model and Hypotheses

2.Research method

Dependent Variable & Independent Variable

Dependent Variable

Predict the Outcome

Independent Variable

Measure the explaining power

In the model: (1)Enjoyment, Risk, Site Use = Dependent (2) Social Present, Ease of Use, Extraversion,

Internet Risk Perception, Privacy Abuse Concern, Enjoyment, Risk = Independent

Theoretical Model

H1. Enjoyment will positively relate to site use

A key benefit in social networking site use is the perceived enjoyment

Perceived enjoyment is the fun that can be derived from using a networking site

Moon and Kim found that individuals who enjoy a web system will view their interactions with the system more positive and form a high behavior intention to use it

Expect that members are more inclined to use a networking site when he or she finds it enjoyable

H2. Social presence will positively relate to enjoyment

Literature suggests that system design such as social presence is instrumental in shaping user experience

Social presence = a computer medium allows a user to experience the others as being psychologically present

Prior studies (Yoo and Alavi, Lombard and Ditton) identified (1) website designs that facilitate the establishment of social

presence(2) one of the most prominent psychological impacts of

social presence is enjoyment

Social presence will positively relate to enjoyment

H3. Ease of use will positively relate to enjoyment

User perceived enjoyment in networking site use may be enhanced by the ease of system use

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

Research (Van der Heijden, Teo et al.) suggested : (1) Ease of use enhances user's hedonic experience

(e.g. enjoyment in using social networking sites) (2)Systems that are difficult to use are less likely to be

perceived as enjoyable

positive relationship between ease of use and enjoyment

Ease of use will positively relate to enjoyment

H4. Extroversion will positively relate to enjoyment

Perceived enjoyment may be cultivated by personal traits such as extroversion

Extroversion = positive emotion, urgency, and tendency to seek out stimulation and the company of others

Social networking sites enable individuals to express themselves, enjoy social events, affirm relationships, and extend personal networks an extrovert member will take advantage of them to

better meet his or her social needs

Rosen and Kluemper suggested that social networking sites are instrumental and useful for extroverts to assert themselves

Extroversion will positively relate to enjoyment

H5. Perceived risk will negatively relate to site use

Using social networking sites comes with a cost, as members may consider it risky

Perceived risk = the extent to which there is an uncertainty in significant and disappointing outcomes that may be realized

Numerous accounts of social networking site members being attacked were reported in the past In 2010, several thousand Facebook users were

attacked by a click jacking scam may experience emotional discomfort, monetary loss,

or reputational damage

H5. Perceived risk will negatively relate to site use (cont.)

Risk is high in using these websites and it is deemed as a significant cost that may discourage users from continuous participation

MySpace, was reported to lose members after spam artists started using profiles as bait for illicit websites

Perceived risk will negatively relate to site use

H6. Perceived risk in site use will negatively moderate the relation- ship between

enjoyment and site use There is a relationship between enjoyment and site use is

a function of perceived risk Perceived risk = low, online users' use behavior may be

largely motivated by fun and enjoyment that is experienced during their interactions

Perceived risk = high, one may become hesitant to use a social networking site regardless of their own assessment of the enjoyment

The predicting power of enjoyment on site use may weaken when perceived risks grow

Perceived risk in site use will negatively moderate the relation- ship between enjoyment and site use

H7. Internet risk perception will positively relate to perceived risk in site use

Perception of risk in using a social networking site may be shaped by individuals' belief of the computing environment

Internet risk perception measures one's uneasiness about using Internet

Internet risk perception may lead decision makers to exaggerate uncertainties in networking sites, exhibit unwarranted confidence in their judgment, and subsequently overestimate the risks in using social networking sitesBecome reluctant to use a networking site because the sense of Internet risk may be overwhelming

Internet risk perception will positively relate to perceived risk in site use

H8. Privacy abuse concern will positively relate to perceived risk in site use

Perceived risk stem from concern about privacy abuse

Privacy abuse concern reflects one's uneasiness about the potential opportunistic behavior related to his or her personal information

Interactions on networking sites give rise to privacy release like identity, private interest, and personal opinions

Privacy protection = unsatisfactory due to the lack of control features and sound policy design. Eg: Facebook

H8. Privacy abuse concern will positively relate to perceived risk in site use (cont.)

Online users who are concerned about their privacy tend to overrate the uncertainty in using networking sites and consider a rather small probability of privacy abuse as significant

Privacy abuse concern will positively relate to perceived risk in site use

2.2 Questionnaire & sampling technique, and statistical

methods,

2.Research method

Sampling Technique The research model was tested using survey data. They

collected survey responses from 222 undergraduate students.

College students are a significant segment of social networking site users. A recent Pew survey shows that college students represent the largest portion of Facebook users. Also, 85% of U.S. college students use Facebook. Thus, the student sample is appropriate for the current research.

Sampling Technique The respondents were recruited from four courses that were

offered in a business college. The samples consist of business and non-business majors, the samples are therefore heterogeneous.

Participation in the survey was voluntary.

Respondent Demographic Information

QuestionnaireRating, Metric Scale Data

Support Hypothese

s

Questionnaire

Statistical Methods Partial Least Squares (PLS)

AVE

Cronbach's Alpha

F-Test

Partial Least Squares (PLS) PLS Regression:

Is a statistical method that bears some relation to principal components regression.

It finds a linear regression model by projecting the predicted variables and the observable variables to a new space. Because both the X and Y data are projected to new spaces, the PLS family of methods are known as bilinear factor models.

AVE AVE:

Is achieved by calculating the square roots of the average variance extracted (AVE) values, which measure the average variance shared between a construct and its measures, and by calculating the correlations between different constructs.

A matrix can then be constructed where the square root of AVE is in the diagonal, and the correlations between the constructs are in the off-diagonal.

Cronbach's Alpha Cronbach's Alpha:

Is a coefficient of internal consistency. It is commonly used as an estimate of the reliability of a psychometric test for a sample of examinees.

Alpha is not robust against missing data. Somewhat related is the AVE.

F-Test F-Test:

Is any statistical test in which the test statistic has an F-distribution under the null hypothesis.

It is most often used when comparing statistical models that have been fitted to a data set, in order to identify the model that best fits the population from which the data were sampled.

Exact "F-tests" mainly arise when the models have been fitted to the data using least squares.

3.Findings - PLS PLS – employ a component based approach for estimation

Advantage: involves no assumption about the population or scale of measurement

Works without – distributional assumptionsworks with – nominal, ordinal & interval scaled variable

3.Findings - PLS Robust against inadequacies

Latent variable scores conformto true values

The best suited for examining complex relationships by avoiding inadmissible solutions and factor indeterminacy

3. Findings -Measurement model Convergent and discriminant validity are inferred –

1. AVE square root of each construct is larger than its correlations with the other constructs

2. all AVEs are greater than 0.5

3. the PLS indicators load much higher on their hypothesized construct than on other constructs

3. Findings -Measurement model The square roots of the AVE are all greater than 0.5 and

greater than all other cross correlations - the variance explained by each construct is much larger than the measurement error variance.

These tests validate the measurement properties of principal constructs

3. Findings -Measurement model Research data was collected from a single survey ---

>checked the extent of common method bias

(1) When 1 single factor emerges or when 1 factor accounts for the majority of the covariance among the variables Result: none of the emergent factors explained the majority of the covariance.

(2) The partial correlation method was performed by adding the highest factor

(3) The correlation matrix was examined for highly correlated factors

3. Findings - Structural model

Risk

Enjoyment

Social

Presence

Site Use

.37***

.16**

.14*

-.18*

-.11*

.41***

p< .05; **: p<.01; ***: p<.001;*:

Ease of Use

Extroversion

Internet Risk

Perception

Privacy Abuse

Concern.15**

.58***

%24

40

%

18

%

3. Findings - Structural model Social presence, ease of use and extroversion, which

supporting hypotheses 2, 3, 4

Internet risk perception and privacy abuse concern, which supporting hypotheses 7, 8

Risk and enjoyment, which supporting hypotheses 1, 5

3. Findings - Structural model (1)PLS product-indicator approach - test the moderated

relationship (H6)

(2) F-statistics (8.93)- test whether the variance explained

(3) The tests of moderating effect - the postulated moderating effect of risk on the relationship between enjoyment and site use (H6).

4. Conclusion and discussion

The situation:

Social networking sites provide an open platform to accommodate online users and enable them to develop interpersonal networks and enjoy friendship

The trend:

Social networking sites continue increasing in popularity.

4. Conclusion The key to success of social networking sites (SNS)

To sustain the success of a social networking site, it is important that members continuously and constantly access and use the site to maintain its vitality

UGC(User Generate Content)

4. Conclusion The key to success of social networking sites (SNS)

The research model developed highlights enjoyment as the key benefit that motivates site use and stresses risk as the major inhibitor.

It also suggests that the presence of risk may attenuate the relationship between enjoyment and site use.

4. Conclusion The key to success of social networking sites (SNS)

In addition, the research model posits that website designs (e.g. social presence and ease of use) and personal traits (e.g. extroversion) jointly affect enjoyment

Attention:

Personal belief of the environment (e.g. Internet risk perception and privacy abuse concern) determines the degree of perceived risk in site use.

4. Contribution of the Research

It proves the value of SET in explaining member use of social networking sites.

This study uncovers the interaction effect between cost (i.e., risk) and benefit (i.e., enjoyment) in affecting end user behavioral outcome.

This study con- tributes to the literature on social networking sites by identifying the key antecedents to members' use of a site.

Thank You!

Q&A