Internet Adoption in Macao:


  • Weng Hin Cheong

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    1. Lecturer in the Department of Chinese Studies, University of Macao.
      Address: Chinese Communication Program, Faculty of Social Sciences and Humanities University of Macao, Macao SAR, PRC. Phone: (853)3974437 Fax: (853)840353.
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Address: Chinese Communication Program, Faculty of Social Sciences and Humanities University of Macao, Macao SAR, PRC. Phone: (853)3974437 Fax: (853)840353.


Based on the data from a telephone survey of 868 Macao residents conducted in Macao with 330 Internet users and 538 non-users, this paper examines the characteristics of the users and non-users in terms of their demographics, assessments on media credibility, family functioning, media use, and perceived values of the Internet. Drawing from the literature of diffusion, expectancy-value and media substitution theories, it investigates the relations between Internet use and its potential predictors. The results confirmed the conclusions of previous adoption studies that Internet users were more likely to be male, younger, better educated and with higher monthly household income than non-users. The study also found that demographic variables such as education, sex and income, as well as doing exercise were the significant predictors of Internet use. However, no traditional mass media use variables and perceived values of the Internet were found to be significant predictors.


Since its advent in a short period of time, the Internet has evolved as one of the most powerful communication tools and has penetrated every corner of our social, economic, and political life. In Macao, the Internet was first introduced in 1994 by the University of Macao, and became available to the public in 1995. According to the official statistics published in the second quarter of 2001, there are 30,204 registered users in Macao, of whom 29,872 (98.8%) are individual users, 186 (0.6%) are unit users, and 146 (0.5%) are lease line users. Of the registered individual users, 78.7% are 56K modem users while 21.3% are broadband users.1

In November 2000, the total bandwidth to overseas reached 55Mbps, of which 32Mbps were mostly distributed to Hong Kong, followed by 8Mbps to the US and China, and the remainder to other countries and regions in the world. In February 2001, there were a total of 575 registered domain names under the sub-domain of “mo.” Business held the dominant share of all sub-domain names (76.5%), followed by the government (10.6%), organizations (7.5%) and others (5.4%).2

The use of the Internet in Macao, with only a short history but with such rapid development, is certainly useful for researchers trying to determine Internet use patterns and the social impact of the Internet on residents from its early beginnings. To our knowledge, no such empirical research has been done in this locality.

The current study utilizes the theories of diffusion, expectancy-value, and media substitution and supplement to answer the following two research questions:

  • 1What are the differences between Internet users and non-users in terms of their demographics, media use, family functioning, assessments of media credibility, and perceived value of the Internet?
  • 2What are the relative influences of these variables on Internet use?

Literature Review

In the studies of innovation adoption, diffusion theory addresses the characteristics of innovations and their adopters (Rogers, 1995). According to Rogers (1995, p. 11), “an innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption.” He also defines “innovativeness” as “the degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas than the other members of a system” (p. 22). This diffusion theory suggests that adoption of technological innovations is a function of one's innovativeness, or willingness to try new products (Atkin, et al., 1998; Neuendorf, et al., 1998; Rogers, 1995).

To understand potential predictors of the adoption of innovation, previous adoption research focused on an individual's socioeconomic characteristics, the perceived attributes of innovations, technology cluster, situational factors, and the characteristics of the innovations that influence adoption (Rogers, 1995).


Past adoption studies suggest that adopters of new communication technologies are more upscale, better educated, and younger than non-adopters (e.g., Atkin, 1993; Atkin & LaRose, 1994; Dutton et al., 1987; Garramone et al., 1986; James, et al., 1995; Rogers, 1995; Leung & Wei, 1998, 1999; Li & Yang, 2000; Lin, 1998). This is because (a) higher education enables people to be more aware of technology's benefits, (b) higher income allows people to afford new technologies, and (c) young people are adventuresome in trying new innovations (Atkin, et al., 1998; Rogers, 1995). For example, James et al. (1995) found that BBS users tended to be higher educated, received higher income and were professional males. Garramone et al. (1986) found that the adopters of computer bulletin services were younger and better educated than non-adopters. Lin (1998) found that PC adopters were younger, better educated, and more affluent than non-adopters. Leung and Wei (1998) obtained similar results in their study of iTV adoption in Hong Kong. Jeffres and Atkin (1996) found that income and education had an inversely weak relation with interest in adopting specific Internet utilities such as sending or receiving messages and ordering goods, even when the Internet was still in the early stages of diffusion. They argued that those applications may be less expensive substitutes for functions performed by traditional media, and that communication needs were more explanatory than social categories. In their further study of Internet adoption, Atkin et al. (1998) found that a young, educated, and affluent adopter was typical in the early stage of diffusion.

However, according to Rogers' (1995) predictions, demographics tend to be less important when the innovations have reached critical mass on their diffusion curves (Atkin, 1993; Atkin 1995; Atkin & LaRose, 1994; Lin, 1994). For example, Atkin's (1993) study found that when cable TV had penetrated more than 60% of US households, demographics had less predicting power than other variables in predicting subscription to cable TV.

With differences in social, political, cultural and economic context from those in the West, the Internet in Macao only became popular in the late 1990s and is now still in the early stage of diffusion. Socioeconomic variables can be considered as the important indicators of Internet use. Thus, we first hypothesize:

H1: Internet users are more likely to be male, younger, better educated and with higher household incomes than non-users.

Media Use

It is important to consider how innovation use fits into existing patterns of behavior. The compatibility between innovations and existing social norms or patterns of behavior may influence adoption (Rogers, 1995). The media substitution hypothesis (e.g., Atkin, et al., 1998; Jeffres et al., 1995; Lin, 2001) suggests that the introduction of a new medium will change the way consumers view the existing media. Lin (1994) also notes that the audience may abandon the old medium and replace it with the new when a new medium is regarded as more functionally desirable than the old medium. For instance, James et al. (1995) found that the use of BBSs reduced time spent with television, book reading and telephone use. Dupagne and Agostino (1991) found that the intention to purchase HDTV was positively correlated with television viewing, radio listening, and newspaper reading, but was unrelated to movie-going. Leung and Wei (1998) found that newspaper reading, magazine reading, moving-going, and VCR, LD, and VCD use were positively correlated with the intention to subscribe to iTV, while television viewing had no relation to it. Lin (1998) also found an inverse relationship between television viewing and the adoption of PC, but no significant relation between other media and the adoption of PC.

On the contrary, the media supplement hypothesis (Atkin, et al., 1976) suggests that given more options, people will consume more of what they want. This is due to whether the information technology is “functionally similar” to those they already use (Atkin, 1993; LaRose & Atkin, 1992). Likewise, Reagan et al. (1995) suggest that this may be a function of compatibility with existing products. For example, Rosengren and Windahl (1989) reported that a moderate or heavy use of one particular medium leads to other activities. LaRose and Atkin (1992) found that use of local audiotext information services was related to information technologies such as videotext, ATMs, 800 numbers, and telephone answering machines. Leung and Wei (1999) also found that seeking news via the pager is an activity that supplements its original function as a mediated interpersonal communication medium.

As it possesses defining qualities of communication such as multimedia, hypertextuality, packet switching, synchronicity, and interactivity (Newhagen & Rafaeli, 1996), the Internet can be seen as a functional alternative to traditional media in some ways. Therefore, media substitution or supplement effects may take place when the Internet meets or fails to meet the qualities that traditional media can offer. Atkin et al. (1998) found that readership of magazines and viewership of theatrical movies as well as videos were positively related to Internet access. Television viewing was inversely related to Internet access. Lin (2001) found that among four media use attributes, newspaper reading level is a significant inverse predictor for the communication-oriented online service, while magazine reading level is a positive predictor for the marketing-oriented online service. However, Busselle et al. (1999) found that no medium was significantly related to use in their Internet use study. In their study of the use of home computing, Dutton et al. (1987) found that there was a negative relationship between computer use and watching television, exercising and other outdoor activities. It should be noted that these findings were based on interviewers' direct judgment about the influence, not on the time they spent on each activity. Thus, these negative effects need further empirical verification.

Based on these diverse empirical findings and theoretical assumptions, it is then logical to posit the following hypotheses:

H2a: The more newspaper reading respondents do, the less their Internet use.

H2b: The more television respondents watch, the less their Internet use.

H2c: The more radio the respondents listen to, the more their Internet use.

H2d: The more magazine reading respondents do, the more their Internet use.

H2d: The more exercise respondents do, the more their Internet use.

Apart from the media attributes described above, scholars tend to consider media credibility as another influential factor leading to media substitution or supplementation effects. Jeffres and Atkin (1996) found that media assessments fail to explain audience interest in the 500-channel cable system, but are significant predictors of using new technologies for sending messages and for consumer purposes. In their study of the relation between the growth of Internet use and media use, Stempel III et al. (2000) found that declining use of local TV news, network TV news, newspapers, and news magazines from 1995 to 1999 in the US was unrelated to Internet use. Rather, they found that Internet users were more likely to be newspaper readers and radio news listeners than non-Internet users were because those people who use the Internet as a source of news are clearly information seekers. They assumed that the decline of traditional media might be related to the declining credibility of news media. Based on this assumption, we tried to explore if this is true in the case of the Internet. Thus, we hypothesized that:

H3: Internet use is positively related to the users' assessments of the credibility of the Internet.

Similar to media use, the substitution and supplement hypotheses may also be applicable to social interaction. After having reviewed some studies, Dutton et al. (1987) found that adoption and use of home computing exert a negative impact on family functioning. As Internet use is a personal activity and under the control of users (Althaus & Tewksbury, 2000), it may lead to the decline of family functioning - the family activities among family members. Although Busselle et al. (1999) did not find any relationship between communication with other people and Internet use, we still assume that people will use the Internet less when they spend more time on other activities with their family members. As little work has been done before to find out the relationship between family functioning and Internet use, we will try to explore it in this study by positing the following hypothesis:

H4: Internet use is negatively related to family functioning.

Perceived Values

Adoption research often tries to determine how adopters perceive characteristics of innovations. Rogers (1995) identifies five perceived attributes of innovations: relative advantage, compatibility, complexity, trialability, and observability. He argues that the perceived relative advantage, compatibility, trialability and observability of an innovation are positively related to its rate of adoption, while the perceived complexity of an innovation is negatively related to its rate of adoption (Rogers, 1995, pp. 250–251). Lin (1998) found a set of four motivations: resources, complexity, advantages, and need for innovativeness. She concluded that along with the cost issue to resources, factors such as whether a person perceived the innovation as complex, useful, relatively advantageous, and whether a person had venturesomeness and strong novelty-seeking motives, may affect willingness to use or adopt the innovation.

It can be seen that the perception of innovations exerts important influences on their adoption. This can also be explained by expectancy-value theory from the uses and gratifications perspective developed by Palmgreen and Rayburn (1982). A basic proposition of expectancy-value theory is that media use is accounted for by a combination of perception of benefits offered by the medium and the differential value of these benefits for the individual audience member (McQuail, 1997, p.74). Thus, the adoption of innovation is influenced by personal judgments of value associated with innovations (Leung & Wei, 1999). The greater the relative values or advantage provided by an innovation, the greater the incentive to adopt it (Ostlund, 1974). In other words, this approach states that a person has a preconceived idea that a particular innovation will best satisfy his/her need. In Hong Kong, Leung and Wei (1999) found that information-seeking benefit significantly predicts the level of exposure to news via pager. They (1998, 1999) also found that attitude toward communication technologies is strongly related to the intent to subscribe to iTV. They concluded that people tend to adopt what they value. For this reason, we hypothesize that:

H5: The higher the perceived values respondents attach to the Internet, the greater their Internet use.


Sample Data

The survey of Internet adoption by Macao residents described here is the first Internet use survey ever conducted in Macao. The data collection method for this survey was a telephone interview of a probability sample of 868 Macao residents. The survey was conducted between January 11 and January 18, 2001. By using the up-to-date telephone directory offered by the local phone service provider and a CATI system, 2,349 telephone numbers were randomly selected. Twenty trained students enrolled in a research methods class at the University of Macao were hired to carry out the telephone interviews. Up to five callbacks were made for all non-answering numbers, busy numbers and answering machines. Of the initial sample, 1,486 were found to be eligible (i.e., residential households with at least one Chinese-speaking person), 273 were non-eligible (e.g. fax numbers, non-existent numbers, or non-residential numbers) and 463 were status unknown (e.g., non-answering or busy). From each of the eligible households, a female or male Chinese-speaking person aged 15–64 was selected based on the last digit of that household's phone number (i.e., when it was an odd number digit, a male was selected; otherwise a female was selected.). The procedure resulted in 868 completed interviews, 453 refusals, 35 partial interviews, 130 non-contacts, 409 non-answers and 54 busy numbers. Using the AAPOR Response Rate 3 (RR3) and Cooperation Rate 3 (COOP3) calculations (AAPOR, 2000), the response rate was 48.8% and the cooperation rate was 64%.3 At the 95% confidence level, the sampling error is estimated to be ±3.39%.

The collected responses were compared to census data to ensure that the sample was representative of the Macao population in terms of gender and age. The sample is very close with respect to gender, while there are some discrepancies between the sample and the population in age. Those between 15 and 19 were found to be 12.9% over-sampled, whereas those between 35 and 39, 45 and 49, 40 and 44, and 25–29 were 4.7%, 3.2%, 3.0%, and 1.8% respectively under-represented in the sample. To minimize the potential impact of sampling bias, the sample was weighted against the population in terms of age.


The independent variables were media use, family functioning, assessments of media credibility, perceived value of the Internet, along with various demographic variables. Internet use was employed as the dependent variable.

Media use. Respondents were first asked to answer questions regarding media including television viewing, radio listening, newspaper reading, and magazine reading, and exercise. They were asked to report how much time they spent on the above activities on a daily basis. Hours and minutes were computed for transforming into hours in SPSS.

Family functioning. Three questions were used to tap the amount of time that respondents spent on (a) having meals with their family members at home, (b) watching television with their family members, and (c) shopping or going out with their family members on a weekly basis.

Assessments of media credibility. Respondents were asked to rate the credibility of four media including newspaper, television, radio, and the Internet on a scale of 1 to 5, where “1” meant “no confidence at all” and “5” meant “total confidence”.

Perceived values of the Internet. Perceived values of the Internet were measured by asking subjects to respond on a scale of 1 to 5, where “1” means “strongly disagree” and “5” means “strongly agree”, to eleven exploratory statements. To test the validity and reliability of the statements, an exploratory principal components factor analysis was used. The Varimax rotation was conducted to look for potential groups of perceived values of the Internet. Three initial factors were produced but with two items crossloading on Factor 2 and Factor 3. After eliminating the two items, the three-factor structure was finalized. Each of the three obtained factors had an eigenvalue greater than 1.0, explaining 49.87% of the total variance (see Table 1).

Table 1.  Factor analysis of perceived values of the Internet. Thumbnail image of

The first factor, termed “negative impact,” explained 19.86% of the total variance (eigenvalue= 1.99). It consisted of five statements: “You feel using the Internet can easily make bad friends,”“…easily be influenced by sexual or violent information,”“…easily disclose privacy,”“…easily become ‘net addicts’ and “…easily be overloaded with information garbage.” This factor reflected people's concerns that Internet use will have negative effects on users (Cronbach's Alpha= 0.58).

The second factor, labeled “effectiveness,” explained 16.89% of the total variance (eigenvalue= 1.69). It consisted of three statements: “It is easy to learn how to use the Internet,”“Using the Internet helps you know more about the outside world” and “Using the Internet can enhance communication with the others.” This factor was conceptualized as the effective role of the Internet in both learning and communication (Cronbach's Alpha= 0.62).

The last factor, namely “novelty,” explained 13.11% of the total variance (eigenvalue= 1.31). It consisted of two statements: “You feel you are an up-to-date person when you know how to use the Internet” and “You like to introduce the benefits of using the Internet to the others.” This factor was conceptually constructed to mark the novelty dimension of using the Internet in order to have a sense of being on the cutting edge (Crobach's Alpha= 0.45).

Demographics of respondents. The demographic characteristics of respondents were measured, including gender (male = 1; female = 0), age, monthly household income, level of education and occupation (professional = 1, others = 0).

Internet use. A number of items were employed to measure the Internet use patterns of respondents who had previously indicated that they were users. They include the ownership of computer at home, length of ownership, whether the home computer had access to the Internet or not, whether the respondents used the Internet or not, years of using the Internet, days of using the Internet per week, time spent on the Internet at home, at school or workplace, and at other places on a daily basis, the type of information sought, the average time spent on different Web activities (e.g., reading news, using e-mail, chatting, searching and playing Web games) per week, whether they participated in Web chatting, the content of their Web chat, frequency of checking e-mail and contacting others via e-mail. For purposes of analysis, only time spent on the Internet each week was used as the dependent variable in testing the hypotheses.

Analytical Procedures

First, t-tests were performed to compare the differences of users and non-users in terms of their demographics, media use, family functioning, assessments on media credibility, and perceived values of the Internet. The hypotheses were also tested. After that, a hierarchical regression was run to examine the relative influences of the independent variables in predicting Internet use. Zero-order correlations were examined to test the hypotheses regarding Internet use. Mean substitution was used to include all cases because some variables had missing values. The hierarchical regression entered the following six sets of variables in sequence: demographics, assessments on media credibility, family functioning, media use, and perceived values of the Internet. The initial regression computation included a residual analysis (Durbin-Watson = 1.83) and an examination of correlation table for independent variable relations to eliminate multicolinearity revealed no significant problems for the regression models.


Descriptive Summary of the Sample

Adoption of the Internet by households. Of the sample, 498 responded that they had computers at home, a computer penetration rate of 57.3%. Of the 498 computer households, 342 (68.9%) had connected to the Internet, which accounted for 39.4% of the sample. According to official statistics, there is only one Internet Service Provider (ISP) 4 which provides 56K and broadband connections for individual users in Macao.

Users and non-users. Thirty-eight percent of the total answered that they were using the Internet, while 62% were not. Of the non-users, 28% answered they would (4.6% definitely and 23.4% probably) use the Internet in the coming year, while 72% answered that they would not use (52.3%) or did not know how to use the Internet (19.7%).

Years of Internet use. Among all respondents, 39.1% had used the Internet for less than one year, 27.9% within one to two years, 15.6% within two to three years, 8.7% within three to four years and for more than four years respectively. Overall, the more experience users had with the Internet, the more time they spent online, except that those with two to three years of experience spent slightly less time. Those with more than four years of Internet use spent more than 3.7 times as much time (25 hours per week) as those with less than one year of experience (6.8 hours per week).

Time of Internet use by location. Most users used the Internet at home (78.9%), in the workplace or at school (45.8%) and at other places (29.4%) such as friends' homes, net-cafés or public libraries. The average weekly Internet connection time was 11 hours. Users spent 6.3 hours per week at home, 3.5 hours at the workplace or school, and 1.1 hours at other places.

Time spent with other media. Watching television was the common and most frequently adopted media habit for both Internet users (2.25 hours per day) and non-users (2.43 hours per day). Internet users spent significantly more time (0.3 hours each day) than non-users (0.11 hours each day) in reading magazines. Both users and non-users spent roughly the same amount of time (about one hour) in reading newspapers and listening to radio, and doing exercise (0.44 vs. 0.49 hours) each day. Likewise, they spent more or less the same amount of time on family functioning (1.41 vs. 1.54 hours) per day.

Information sought by Internet users. Internet users mostly read news (61.8%) on the Web. The second category of information most frequently viewed was entertainment information (51.9%), followed by education (30.7%), other (28.8%), sports (17.2%), travel (8.6%), shopping (7.1%), health (5.1%), food and beverage (3.7%), and information for adults (2.1%).

Time spent on Internet activities. Among five popular Internet activities, searching for information on the Web was the most frequently adopted activity for Internet users, accounting for 2.2 hours per week. Chatting, including ICQ, BBS, chat rooms or forums, ranked second (2 hours), followed by reading news (1.5 hours), use of e-mail (1.3 hours) and playing games (0.7 hours).

Use of e-mail. Of the Internet users, 71.5% used e-mail as their communication tool. Of the e-mail users, 29% checked their e-mail once a day, 27.8% several times a week and 22.3% once a week. Twelve percent checked their e-mail several times a day, while 5.6% did it less than once a week. E-mail was checked every hour or more frequently by 3.2%.

For e-mail users, friends were their most frequent contact persons, followed by colleagues, classmates or relevant persons. Family members or relatives were the least frequent contact persons via e-mail.

Use of chat room, ICQ, forum or BBS. Of the Internet users, more than half (51.1%) had experience in either posting messages or viewing messages in chat room, ICQ, forum or BBS. For those who involved themselves in this communication activity, 17% always posted messages, 45% sometimes posted messages and sometimes just viewed messages, and 37.9% viewed messages but never posted.

Demographics. Of the 868 respondents providing completed interviews, 44.5% were male and 55.5% were female. With respect to gender, 34.6% of women were users while 65.4 were non-users. In terms of age, the younger the respondents, the greater the likelihood that they were users. For example, 76.5% of those with ages between 15 and 24 were users, while only 23.5% were non-users. As far as income is concerned, the higher the income level, the higher the proportion of respondents who used the Internet, except for those with incomes between $24,001 and $30,000. As for education, in general, respondents of a higher educational level were more likely to use the Internet. Those with a very high level of education used the Internet frequently. For instance, 83.3% of the users were postgraduates and 87.9% undergraduates. With regard to occupation, respondents requiring more knowledge in their work were more likely to be Internet users. It is not surprising to note that there are a dominant proportion of Internet users in the groups of students (80.9%) and civil servants (74.4%). Professionals and clerical workers also had substantial ratios of Internet users: 60.2% and 69.7% respectively.

Differences between Users and Non-users

Our first research question was whether there are differences between Internet users and non-users in terms of their demographics, media use, family functioning, assessments of media credibility, and perceived values of the Internet. Table 2 contains the results of the t-test comparisons of Internet users and non-users with respect to these aspects.

Table 2.  T-Test comparison of Internet users and non-users. Thumbnail image of

Demographics. It was found that there were significant differences between users and non-users on all demographic variables. Users were found more likely to be male (t=−2.29, p < .05), younger (t=−16.97, p < .001), better educated (t= 17.67, p < .001) and with higher household income (t= 10.52, p < .001) than non-users. Thus, Hypothesis 1 was supported.

Media use. Results showed that users were significantly different from non-users in terms of magazine reading (t= 3.48, p < .001). While using the Internet, there were more users than non-users who were also reading magazines. No significant differences were found between users and non-users in terms of television viewing, radio listening, newspaper reading and doing exercise.

Family functioning. Significant differences were found between users and non-users in terms of having meals with family members at home (t=−4.56, p < .001) and watching television with family members (t=−2.45, p < .05). Users tended to practice these two activities less frequently with their family members than non-users. Users did not differ significantly from non-users in terms of chatting and shopping or going out with family members.

Assessments of media credibility. Results indicated that there was a significant difference between users and non-users when they rated the local media credibility. Users had less confidence than non-users in newspapers (t=−2.91, p < .001), television (t=−4.37, p < .001), radio (t=−4.41, p < .001) and Web sites (t=−2.13, p < .05).

Perceived values of the Internet. It was found that both users and non-users had no significant differences when they perceived the Internet as having a negative impact. However, users were found to regard the Internet as significantly greater than non-users did in terms of its effectiveness in learning and communication (t= 5.32, p < .001). Moreover, there was a significant difference between users and non-users when they perceived that using the Internet would be more novel (t=−6.68, p < .001). Users perceived the value of novelty to a lesser degree than non-users did.

Prediction of Internet Use

Table 3 contains the results of correlation analysis and hierarchical regression analysis.

Table 3.  Hierarchical regression analysis of demographics, assessments of media credibility, family functioning, media use and perceived values of the Internet on Internet use. Thumbnail image of

Results indicated that media use had a weak relationship with Internet use. Only doing exercise was positively related to Internet use (r= .114, p < .05): Those who exercise more would use the Internet more. No significant correlations were found between Internet use and television viewing, radio listening, newspaper reading or magazine reading. Thus, H2e was supported, whereas H2a, H2b, H2c, and H2d were rejected.

Hypothesis 3 proposed that Internet use is positively related to the users' assessments of the credibility of the Internet. Our findings indicated that there was no significant relation between the two. Therefore, H3 was rejected.

Hypothesis 4 assumes that Internet use is negatively related to family functioning. It was found that having meals (r=−.129, p < .01) and watching television (r=−.12, p < .05) with family members at home had a significant negative relationship with Internet use. This suggested that the more time the Internet users spent on the Internet, the less frequently they had meals and watched television with their family members. However, results showed that there was no significant correlation between Internet use and family chatting as well as shopping or going out. Therefore, H4 was partially supported.

Hypothesis 5 proposed that the higher perceived values respondents attached to the Internet, the more they would use the Internet. It was found that only the perceived effectiveness of the Internet was positively related to Internet use (r= .107, p < .05), suggesting that the greater effective functions of the Internet as a learning and communication medium the users perceive, the more time they will spend on the Internet. No significant correlation was found in the perceived values of negative impact and novelty. Thus, H5 was partially supported.

Research Question 2 explored the relative influence of demographics, assessments of media credibility, family functioning, media use, and perceived values of the Internet in predicting Internet use. A hierarchical regression was conducted in order to isolate the contribution of perceived values of the Internet. Demographics, assessments of media credibility, family functioning, media use, and perceived values of the Internet were entered into the equation as separate blocks. The results are presented in Table 3.

Five demographic variables were entered as the first block, of which three were significant predictors of Internet use. Gender was positively related to Internet use (Beta= .171, p < .01), meaning that male respondents tended to use the Internet more. Monthly household income was also positively linked to Internet use (Beta= .098, p < .10). Thus higher income should lead to greater Internet use. The results were also similar for education (Beta= .233, p < .001), indicating that better educated people would use the Internet more. However, age was not found to be a significant predictor. This suggested that those spent more time on the Internet might not only be younger people. More Internet use was affordable by those men with a higher level of education and higher monthly income. The first block alone accounted for 10.6% of the total variance (see Table 3).

Assessments of media credibility, including four variables, was then entered as the second block. None of the four variables was significantly related to Internet use. This block accounted for 1.2% of the total variance (see Table 3).

The third block, family functioning, including four variables, yielded a 1.6% change in R square. However, there were no significant relationships between these four variables and Internet use.

Similar to the third block, the fourth block, media use, also yielded the same contribution to the equation (1.6% change in R square). The contribution mainly came from doing exercise (Beta= .116, p < .05), indicating that doing exercise was a significant predictor. This suggested that the more the respondents used the Internet, the more likely they tended to be energetic or concerned with health.

The last block, perceived values of the Internet, with three variables, contributed only 0.5% of the total variance. No significant relationships were found between the three variables and Internet use. The equation explained 16% of the variance in total.

Conclusion and Discussions

In this exploratory study we have examined the differences in Internet use patterns and compared the socioeconomic status, assessments of media credibility, family activities, media use and perceived values of the Internet of Internet users and non-users in Macao. We have also investigated the relationships between these potential predictors and Internet use. The findings have provided several indications for future research on Internet use.

First, based on the results of this study, it can be concluded that Internet users in Macao are more likely to be male, younger, better educated, and with a higher monthly household income than non-users. Regression results indicate that education, sex and income are the best predictors of Internet use. The more likely the users are to be male, to have a high level of education and a high family income, the more likely they will be to use the Internet. Therefore, it can be seen that in the context of Macao, Internet users' socioeconomic status is more important than other factors. This conclusion is consistent with previous adoption research which has shown that early adopters of innovations tend to be younger, better educated, with higher income levels (Rogers, 1995; Lin, 1998).

Second, this study reports that users and non-users do not differ significantly in media use, with the exception of magazine reading. Multiple regression results also confirm that with the exception of doing exercise, other media uses are not significant predictors of Internet use. This suggests that even if Internet users spend their time on the Internet, it does not lead to an increase or a decrease in the use of other media. Previous studies have shown mixed findings in the technology cluster (Busselle, 1999; Leung & Wei, 1998; Lin, 1998; Neuendorf, et al., 1998). However, the findings of this study do not fully confirm the validity of the so-called cluster. One of the possible reasons for this phenomenon is that many respondents (39.1% of the total respondents) do not have more than one year of online experience and spend only a little time on the Internet (6.8 hours per week). Therefore, it is not surprising that no significant relationship was found between media use and Internet use.

Third, previous studies have indicated that perceived values of innovations, or motivation, are predictors of adoption of new technologies (Busselle, 1999; Leung & Wei, 1998, 1999; Lin, 1998; Rogers, 1995). The results of the study are not consistent with such conclusions. One explanation is that at the early stage of the adoption process, users will pay more attention to other motivation factors such as complexity, relative advantage, resources and need for innovations (Lin, 1998) instead of their perceived values. More work needs to be done to test the construct validity of these measures of the perceived values of the Internet.

Fourth, one of the major goals of this study was to explore how users and non-users differ in their behaviors, beliefs and attitudes towards the changing technological environment. To accomplish this goal, a category measuring people's views on media credibility was included. Results of the study indicate that there are in fact significant differences between users and non-users when they rate the local media credibility. In general, users have less confidence than non-users in media credibility. Surprisingly, non-users have more confidence in Web sites than users. This may be because those who have direct experience and observation online are more likely to be aware of the varying quality of the sources of information on the Web. One should ask: if the gap of confidence in media credibility between users and non-users tends to be larger, what consequences will it bring about? Will it lead to, as Stempel III et al. (2000) assumed, the decline of traditional media use?

Like many other studies, the conclusions are derived according to the data from which they are drawn. Apparently, the predictors of Internet use are not only limited to those applied in this study. As Internet research is a new area with tremendous potential for exploration, this cross-sectional study alone cannot provide us with an absolute way of identifying the extent to which assessments of media credibility, family functioning, media substitution as well as supplementation and perceived values of the Internet may alter over time.

As the Internet emerges at a rapid pace, Internet use patterns may change in response to the changes of the Internet content, forms, connection speed, and technical advances. This study has not yet provided answers to such potential changes. Thus, future research may try to address the exploration of the relationship between the online content and Internet use as motivations for adoption of innovations vary depending on the topic of interest (Reagan et al., 1998). Moreover, investigation into the factors that influence users' online patterns and information viewing habits will contribute to better understanding of the Internet and its users.


  • 1

    Source: Macao Statistics and Census Services. Retrieved August 2001, from the World Wide Web:

  • 2

    Source: MONIC - Macao (mo) Sub Domain Name Registration Service. Retrieved March 2001, from the World Wide Web:

  • 3

    In the RR3 formula, the estimated proportion of cases of unknown eligibility that are eligible (e) is estimated based on the calculation of the eligible numbers found divided by the total numbers dialed in the current survey. Therefore, e = 1486/2349 = 0.633.

  • 4

    The name of the ISP is Companhia de Telecomunicações de Macau S.A.R.L. (CTM) which is granted the concession of telephone service (fixed line) for a period of 10 years from 1999 in Macao.