slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
C22 PowerPoint Presentation
Download Presentation

Loading in 2 Seconds...

play fullscreen
1 / 36

C22 - PowerPoint PPT Presentation

  • Uploaded on

Group 2 Presentation. C22. The benefits and dangers of enjoyment with social networking websites Cheung Chor Ying, Angela 11014431 Wan Ka Wai , Sean 11008199 Chan Ying, Sarah 12001058. Introduction. Research background:

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'C22' - mingan

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Group 2 Presentation


The benefits and dangers of enjoyment with

social networking websites

Cheung Chor Ying, Angela 11014431Wan KaWai, Sean 11008199

Chan Ying, Sarah 12001058

  • Research background:

Argue that it can also be a key ingredient in the formation of adverse outcomes, such as technology-related addictions, through the positive reinforcement it generates.

theoretical background

Theoretical background

Describe four concepts that are pertinent to this study:


-IS enjoyment,

-IS use habit,

-SNW addiction, and

-High engagement

Then proceed in the next section with developing hypotheses regarding the

associations among these concepts



What is the research objective?

  • What is the research objective?

Habitual and continued use of information systems (IS) has become prevalent in business and leisure contexts.

  • There are the factors:- As a positive experiential cognition, it can directly increase future usage intentions- it can also increase users’ satisfaction with the system, which in turn augments continued use intentions (i.e., satisfaction serves as a partial mediator between perceived enjoyment, and continuance intentions

- It can facilitate the development of a habit of using an IS which in turn can increase intentions to perform the enjoyable behavior

research method
Research method
  • The Research method of this survey is Structural equation modelling(SEM)
  • Structural equation modelling (SEM) is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions.
research method1
Research method
  • Increase future usage intentions can facilitate the development of a habitof using an IS

Independent variable:

  • a habit of using an IS (lead to two results)
research method2
Research method
  • It leads to two results;
  • 1st. drives high engagement with the system (which is typically a desirable phenomenon); users who enjoy the system are absorbed in, and more enthusiastic about its use.
  • 2nd. abusing good things (enjoyable IS in our case) can turn them into bad things (a problematic dependency on the IS)
research method3
Research method
  • Ultimately, we demonstrate the dual effect of enjoyment in human–computer interactions and add to the current body of research, which mostly emphasized its positive consequences, by also focusing on its potential adverse impacts.
research method4
Research method
  • B. Questionnaire
  • This survey is conducted in a large American business school .Data were collected by means of an online questionnaire administered to SNW users who were taking a sophomore year marketing class. Students in this class could voluntarily participate in
  • this study for two bonus points. Those who have not used SNW had an opportunity to participate in alternative projects for the same incentive.
  • Out of the 226 students in this course, 204 completed the survey.
  • After removing incomplete submissions, 194 usable
  • responses were retained (response rate of 86%).
research method5
Research method
  • The questionnaire was created by the following Decision variables (dependent variables).
  • 1. Time-per-Day (Past Behavior)
  • 2. Comprehensiveness of Usage (Past Behavior)
  • 3. Habit
  • 4. Addiction
  • 5. High Engagement
  • 6. Perceived Enjoyment
  • 7. Social Desirability Bias
research method7
Research method

C. Statistical technique

Confirmatory factor analysis (CFA)

confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social research. It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor). As such, the objective of confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. This hypothesized model is based on theory and/or previous analytic research.

research method8
Research method
  • Sample technique
  • This survey is adopted the Self-selection.
  • - Publicizing it in a media at which it allows the case to identify individual desrieto take part in the research
  • - Collect data from those who respond
  • Reason: No restriction on the type of the SNW was placed (all SNW were eligible), and only those participants with at least 3months of usage experience were selected. Out of the 226 students in this course, 204 completed the survey.
  • PS: SNW=Social Networking Websites
methodology and data collection1
Methodology and data collection
  • Sample size : 194 usable responses(response rate of 86%)
  • Target sample : : SNW users who were taking a sophomore year marketing class at a large American business school
  • Data Collection Method: Online questionnaire
methodology and data collection2
Methodology and data collection
  • Students could voluntarily participate in this study for two bonus points
  • Only participants with at least 3 months of usage experience were selected  asked to reflect on their experience with their most frequently used SNW
  • To collect data of user’s SNW experience
methodology and data collection3
Methodology and data collection
  • Questions related to their SNW behavior (Time-per-day, Comprehensiveness, Habit, Addiction, High Engagement, Perceived Enjoyment, Social Desirability Bias)
  • 7-point Likert-type scales
  • To capture Addiction and Engagement: short versions of the Charlton & Danforth (2007) scales
research methodology and data collection
Research methodology and data collection
  • Findings results
  • Personal characteristics:
  • Gender: 48% women.
  • Age: 19 to 40 years, with an average of 23 years of usage experience.
  • years of experience: average 10.6 years of Internet experience, 2.9 years of SNW experience, 2.5 years of full-time work experience, and 3.8 years of part-time work experience.
  • No. of contact on SNW: 2 to 1,000 contacts on their SNW,with an average of 225 contacts per user.
  • No. of SNW websites they use: multiple SNW (from 1 to 4 per person), with an average of 1.7 websites per user.
methodology and data collection4
Methodology and data collection
  • Findings results
  • Types of SNW they use: 90% used Facebook, 56% – MySpace, 16% – Twitter, 8% – LinkedIn, and 7% –other SNW (e.g.,,, and Cyworld).
  • Reasons of using SNW:

stay in touch with close friends and relatives (98%) read messages (62%); Post messages and photos (56%) browse the pages of people in their network (39%)meet new people (24%)Stay in touch with people they met on this SNW (20%)Play online video games (19%)watch videos (16%) post videos (10%)send virtual gifts (3%).

data analyses and results1
Data analyses and results
  • Content validity

suggested a model based on the literature and tested it through a survey of 194 SNW users.

  • Reliability

All constructs presented sufficient variation and were reliable with Cronbach’s as and Composite Reliability scores over 0.7, as well as AVE scores over 0.5.  measurement model is acceptable.

data analyses and results3
Data analyses and results
  • Construct validity – Three reliability measures are reported for each multi-item construct on the diagonal: Cronbach’s Alpha, Composite Reliability, and AVE.
data analyses and results4
Data analyses and results
  • Variables(1) Time-per-day (Minutes)(2) Usage Comprehensiveness(3) Perceived Enjoyment(4) Habit(5) Addiction(6) High Engagement
  • Potential control variables(7) Age(8) Gender(9) Number of Contacts
data analyses and results5
Data analyses and results
  • Hypothesis testing :

H1, H2, H3, H4, H5

data analyses and results6
Data analyses and results
  • Measurement model
  • A Confirmatory Factor Analysis (CFA)
  • All factor loadings were above 0.6 and significant (Po0.001), which further indicates that the measurement model fits the data, and combined with the fit indices, indicates good convergent and discriminant validities.
  • All constructs presented sufficient variation and were reliable with Cronbach’s as
  • and Composite Reliability scores over 0.7, as well as AVE scores over 0.5.
  • It was therefore concluded that the measurement model is acceptable.
  • Perceived enjoyment  an important concept in user interaction with IS.
  • Not only presumed-to-be desirable cognitions and behaviors, such as high engagement, but also undesirable and potentially harmful ones, such as ‘bad habits’ and ultimately technology addiction.

Future Research:

  • Given the increased prevalence of heavy habitual use and technology addictions in various contexts, such as online gambling, further research on the antecedents and consequences of these phenomena is warranted.
  • Given the potential duality of other MIS constructs a more balanced view of potential duality of other MIS constructs, focusing on both their positive and negative consequences
  • 1. YANG SC and TUNG C-J (2007) Comparison of internet addicts and non- addicts in Taiwanese high school. Computers in Human Behavior 23(1), 79–96. YOUNG K (1998a)
  • 2. BHATTACHERJEE A, PEROLS J and SANFORD C (2008) Information technology continuance: a theoretic extension and empirical test. Journal of Computer Information Systems 49(1), 17–26.
  • 3. BOURDEAU L, CHEBAT J-C and COUTURIER C (2002) Internet consumer value of university students: e-mail-vs.-web users. Journal of Retailing and Consumer Services 9(2), 61–69.
  • 4. CARTER BL and TIFFANY ST (1999) Meta-analysis of cue-reactivity in addiction research. Addiction 94(3), 327–340.
  • 5. AJZEN I (2002) Residual effects of past on later behavior: habituation and reasoned action perspectives. Personality and Social Psychology Review. 6(2), 107–122.