Impact of the Internet: Internet use, Family Functioning and Sociability in Macau

1
Impact of the Internet Internet use, Family
Functioning and Sociability in Macau

• Angus, W. H. Cheong
• (Zhang Rongxian)
• University of Macau

• The International Symposium on Information
  Statistics of the Internet
  
• July 22-23, 2002, Beijing
• China Internet Network Information Center
  (CNNIC)
  
• Policy and Resource Committee, Internet Society
  of China
  
• Department of Sociology, University of Maryland,
  USA
  
• Department of English Communication, Faculty of
  Humanities and Social Sciences, City University
  of Hong Kong

2
A Brief Profile of the Internet Diffusion in
Macau

• The Internet was first introduced by the
  University of Macau in 1994 and open to the
  public in 1995.

3
A Brief Profile of the Internet Diffusion in
Macau
The growth rate increased 24 in March 2002,
comparing to the same period one year ago.
Source DSEC, July 2002
4
A Brief Profile of the Internet Diffusion in
Macau
Source DSEC, July 2002
5
A Brief Profile of the Internet Diffusion in
Macau
Source WIP-Macau, July 2002
6
A Brief Profile of the Internet Diffusion in
Macau
Source WIP-Macau, July 2002
7
A Brief Profile of the Internet Diffusion in
Macau
Source WIP-Macau, July 2002
8
Internet Use Pattern by Macau Residents

• Online time per week 567.5 minutes (9.5
  hours).
  
• Home 367.1minutes (6.1 hours)
• Workplace/school 135.7 minutes (2.3 hours)
• Elsewhere 64.7 minutes (1.1 hours)

Source WIP-Macau, July 2002
9
Internet Use Pattern by Macau Residents

• Online activity time per week
• Information searching 194 minutes (3.2 hours)
• News reading 101 minutes (1.7 hours)
• E-mails 92 minutes (1.5 hours)
• Chart room/forum 84 minutes (1.4 hours)
• Game playing 77 minutes (1.3 hours)

Source WIP-Macau, July 2002
10
Internet Use Pattern by Macau Residents
Top Ten Type of Information Browsed ()
Source WIP-Macau, July 2002
11
Internet Use Pattern by Macau Residents
Source WIP-Macau, July 2002
12
Internet Use Pattern by Macau Residents
Source WIP-Macau, July 2002
13
Internet Use Pattern by Macau Residents
Source WIP-Macau, July 2002
14
Characteristics of Internet Users
Source WIP-Macau, July 2002
15
Characteristics of Internet Users
Source WIP-Macau, July 2002
16
Characteristics of Internet Users
Source WIP-Macau, July 2002
17
Characteristics of Internet Users
Source WIP-Macau, July 2002
18
Characteristics of Internet Users
Source WIP-Macau, July 2002
19
Characteristics of Internet Users

• Of the users, there are more male, aged 18-34,
  high secondary school, married/living together,
  medium-high family income.

Source WIP-Macau, July 2002
20
The Macau Survey

• Telephone survey with a CATI system January 17
  to 21, 2002
  
• Phone numbers randomly selected from Macau
  residents phone database
  
• Age between 18 and 74
• Complete sample 1,002 cases
• AAPOR response rate 3 (RR3) 35.6
• Cooperation rate 4 (COOP4) 63.5
• Sampling error 3.16 at 95 confidence level
• The sample was weighted against gender and age.

21
Theoretical Framework

• According to Dutton, Rogers, and Juns (1987)
  theoretical framework on personal computer
  adoption, and Zhu and his colleagues (2001,
  2002) application of the model on the Internet,
  the Internet diffusion process involves three
  stages

1. Adoption
2. Use
3. Impact
22
Internet Impact on

• Knowledge
• Attitudes
• Values
• Behaviors in work or study
• Family functioning
• Social activities
• Civic participation

23
Research Questions

• What effects, if any, would the Internet use have
  on family functioning?
  
• What effects, if any, would the Internet use
  have on sociability?

24
Measurement

• Internet Use
• Time used to be the measurement of the media use.
  In this study, Internet use will be measured by
  the amount of time spent in different locations,
  the amount of time spent with different
  activities on the web, frequency of using e-mails
  for family functioning and sociability.
• On average, how long (hours/minutes) do you use
  the Internet at office or school per week?
  
• On average, how long (hours/minutes) do you use
  the Internet at home per week?
  
• On average, how long (hours/minutes) do you use
  the Internet at other places such as a friends
  home, library or Internet bar per week?
  

Contd
25
Measurement

• On average, how long (hours/minutes) do you use
  the Internet for reading news per week?
  
• On average, how long (hours/minutes) do you use
  the Internet for e-mails per week?
  
• On average, how long (hours/minutes) do you use
  the Internet for attending chat room or a forum
  per week?
  
• On average, how long (hours/minutes) do you use
  the Internet for searching information per week?
  
• On average, how long (hours/minutes) do you use
  the Internet for playing games per week?

Contd
26
Measurement

• How often do you use e-mails for communication
  with your family members or relatives?
  
• How often do you use e-mails for communication
  with your friends?
  
• How often do you use e-mails for communication
  with your colleagues or classmates?
  
• A Three-point scale is used to tap the above
  questions
  
• Never
• Sometimes
• Often

27
Measurement

• Family Functioning
• (namely family interactions in Lee Zhus
  (2002) study.)
  
• Direct interactions with family members
• On average, how many times do you watch TV
  together with your family members per week?
  
• On average, how many times do you dine together
  with your family members at home per week?
  
• On average, how many times do you play games
  together with your family members per week?
  
• On average, how many times do you go shopping
  together with your family members per week?
  
• A composite scale by combing the four measures
  (TV watching, dinning, playing, and shopping)
  
• (A considerably high coefficient of internal
  consistency Cronbachs a .57).
  
• Thus, one variable is used.

28
Measurement

• Sociability
• Directly face-to-face contacts with other people
  in a private and a social context.
  
• In the past month, how many times do you attend
  other peoples parties or dinners?
  
• In the past month, how many times do you attend
  the activities organized by the community
  organizations in Macau?
  
• Although the two measures are positively
  correlated (.30,
  correlations is moderate.
  
• Thus, two variables are used.
• Face-to-face friends socializing Party/dinner
  attending
  
• Face-to-face community socializing community
  activity attending

29
Analytical Model
Independent variables

• Gender
• Age
• Education
• Family Income
• Marital Status
• Total online time
• Time on online news
• Time on e-mails
• Time on chat room/forum
• Time on information search
• Time on online games
• Family communication via e-mails
• Friends communication via e-mail
• Colleagues/classmate communication via e-mail

Dependent variables

• Family functioning
• Friends socializing
• Community socializing

30
Findings
The Impact of Internet Use on Family Functioning
and Sociability
Standardized beta coefficient for variables at
final step.
31
Findings

• Impact on family functioning
• Age is negatively correlated with family
  functioning, meaning that the older the
  respondents are, the less interactions they have
  with their family members.
• For marital status, it is found that the
  married/living together is significantly
  correlated with family functioning. It is
  understood that married respondents are having
  more family contacts than single respondents.
• Gender has a moderate correlation with family
  functioning though it is not statistically
  significant.
  
• For education, family income, and
  divorced/separated/widowed, no significant
  relationship were found.
  

32
Findings

• Impact on family functioning
• Previous studies (Lee Zhu, 2002) found that
  there was no relationship between Internet use
  and family interactions. The same results were
  found in this study.
• When looking into the amount of time that the
  respondents spent on different types of Internet
  activities and e-mail communication, we found
  that the frequency of family/relatives
  communication via e-mails has a moderate
  correlation with family functioning.
• This may suggest that more communication via
  e-mails among family members and/or relatives
  lead to more family interactions.
  

33
Findings

• Impact on friends socializing
• The marital status of the married/living together
  was found to have a significantly negative
  relationship with friends socializing.
  
• This suggests that the married/living together
  has less fact-to-face interactions with their
  friends than the single.
  
• Family income is another predictor of friends
  socializing. The result suggests that for those
  who are having higher family income, they tend to
  attend their friends party/dinner more.
• Gender, age, education, and divorced/separated/wid
  owed were found to be non-significantly
  correlated with friends socializing.
  

34
Findings

• Impact on friends socializing
• Not surprisingly, the total time of internet use
  was found to have no significant correlation with
  friends socializing.
  
• However, when looking into to specific type of
  online activities, we found that time spent on
  chat room/forum has a significant correlation
  with friends socializing.
• Moreover, frequency of communication with friends
  via e-mails is significantly correlated with
  friends socializing.
  
• Thus, more interactive online activities with
  others or friends leads to more friends
  socializing.

35
Findings

• Impact on community socializing
• Age was found to be significantly correlated with
  community socializing, suggesting that the older
  the respondents are, the more they attend
  community activities.
• Education is also a good predictor of community
  socializing. The result suggest that those who
  have a higher education level attend more
  community activities.
• Though gender and the married/living together
  were found to be not significantly correlated
  with community socializing respectively, they
  presented a moderate relationship.
• Divorced/separated/widowed and family income have
  no significant relationship with community
  socializing.

36
Findings

• Impact on community socializing
• Again, the total amount of time of Internet use
  was found to be not significantly correlated with
  community socializing.
  
• However, time spent on chat room/forum and
  frequency of friends communication via e-mails
  were found to be good predictors of community
  socializing.
• The longer the respondents stay with chart
  room/forum, the more often they attend community
  activities.
  
• The more often they communicate with their
  friends via e-mails, the more frequently they do
  community socializing.

37
Conclusion and Implications

• This study has tried to explore the impact of
  Internet use on family functioning, friends
  socializing, and community socializing.
  
• Generally speaking, social-economic status
  variables have more predicting powers than
  Internet use variables.
  
• The results confirm that there was no significant
  correlation between Internet use and family
  functioning as well as sociability when using the
  total amount of online time as the predictor.
• Offline and online seem to be two separate worlds.

38
Conclusion and Implications

• However, different from the traditional media,
  the Internet has multi-functional attractions to
  users.
  
• After having tried to include a larger dimension
  of the concept of Internet use, the current study
  found that the amount of the online time for
  functional purpose like reading news and
  searching information has no effects at all,
  whereas the amount of the online time for
  communicative purpose such as attending chat
  rooms and using e-mails do have significant
  impact on the similar off-line activities.
• This may imply that the Internet use produces
  impacts as supplement to offline activities,
  depending upon the similarity and differences of
  the features of the online and offline features.
  
• In conclusion, a broader conceptualization of
  Internet use and more applications should be
  encouraged.