INTERNET USE AND CROSS-CULTURAL ADAPTATION

Testing a Model of Internet Use in the Cross-Cultural Adaptation Context

Ying Wang

Youngstown State University

Shaojing Sun

Fudan University, Shanghai, P. R. China

Paul M. Haridakis

Kent State University

 

Abstract

The growth of new communication technologies has presented new challenges to traditional cross-cultural adaptation (CCA) research. Guided by uses and gratifications (U&G) theory, we proposed a model of Internet use in CCA, investigating how individual differences, Internet use motives, and Internet use influenced Chinese students’ CCA. Eight Internet use motives were identified in the CCA context, including social involvement, acculturation, pass time, information, entertainment, convenience, companionship, and ethnic maintenance. The results showed that loneliness, English competence, separation attitude, and convenience motivation predicted socio-cultural adaptation; Loneliness, English competence, information motivation, entertainment motivation, pass time motivation, and American Internet use predicted psychological adaptation. The findings partially supported the proposed model. Implications for CCA and U&G research were discussed.

 

Key Words: Cross-cultural adaptation, Internet use, uses and gratifications, Chinese students


Testing a Model of Internet Use in the Cross-Cultural Adaptation Context

Introduction

With advances in communication technologies and globalization of the economy, cross-cultural adaptation (CCA) has become a prominent social and cultural phenomenon. The conceptual linkage between communication and CCA has long been recognized. Communication is considered to serve as “an essential mechanism that connects people from another culture and the host society” (Kim, 1997, p. 407). The pivotal role communication plays across culture is further enhanced and compounded by new technologies, particularly the Internet, though, limited attention has ever been devoted to examining the relationship between CCA and Internet use.

 

In response to the above lacuna in communication research, this study is attempted to investigate the role of Internet use during the process of Chinese students’ (CS) CCA in the United States, in hopes of helping address the debate between cultural assimilation versus pluralism. Some scholars have argued that the development of new technologies may challenge the dominant assumption that the ultimate direction of CCA is toward assimilation and social integration. The Internet facilitates more constant and expanded ethnic cultural contacts beyond geographical boundaries and therefore, provides more opportunities for newcomers to maintain their ethnic cultural identities (e.g., Boczkowski, 1999; Melkote & Liu, 2000). To that end, a model of Internet use in CCA was proposed under the theoretical rubric of uses and gratifications (U&G). CS, one of the largest groups of international students in the U.S., constitutes an exemplary case for studying the influence of the Internet on CCA.

 

The article was organized as follows: First, we briefly reviewed relevant literature on CCA and U&G and proposed a model of Internet use. Second, we described the sample, data collection procedure, and measurement in the method section. Third, data analysis and resulted were presented. Finally, implications of research findings, limitations of research design, and future directions were discussed.

 

Literature Review

Cross-Cultural Adaptation

Kim and Gudykunst (1988) defined CCA as a dynamic socialization process by which individuals interact with a new environment. Among the large amount of research on CCA, the framework provided by Ward (e.g., Searle & Ward, 1990; Ward & Kennedy, 1993, 1999; Ward, 1996, 1999) seems to be more exemplary, comprehensive and systematic. Specifically, Ward and colleagues divided the outcomes of cross-cultural adaptation into two domains: psychological (emotional/affective) adaptation and sociocultural (behavioral) adaptation. Sociocultural adaptation has been explained as behavioral competence (Ward & Kennedy, 1993, 1999) whereas psychological adaptation refers to a psychological well-being and contentment with the new cultural environment.

 

Past studies have suggested that media play an important role in CCA. For example, use of host mass media has been observed to promote the acculturation process (e.g., Kim, 1988; Shah, 1991; Subervi-Velez, 1986), whereas ethnic media use, in the long run, may retard acculturation (e.g., Greenberg, 1983; Lee & Tse, 1994; Viswanath & Arora, 2000). Regarding the linkage between the Internet and CCA, Boczkowski (1999), for example, investigated an online discussion group for Argentine expatriates and found that the group used a virtual community to reinforce their sense of belonging to their native culture. Similarly, Melkote and Liu (2000) found that participation in Chinese online discussion group was positively related to CS’ behavioral acculturation but negatively associated with their American value acculturation.

 

Uses & Gratifications

As a social psychological perspective, U&G focuses on how individuals actively use media to gratify personal needs, and emphasizes individual differences during the process of media uses and effects (Rosengren, 1974). Specifically, U&G theory assumes that a variety of psychological and social factors influence audience’ motives for using media. Motives, in turn, further contribute to the explanation of media exposure patterns and media effects (Palmgreen et al., 1985).

UGT emphasizes the free will of individuals. As Katz, Blumler, and Gurevitch (1974) pointed out, the concept of an active audience is a central assumption of UGT. That is, individuals take the initiative in using media to gratify felt needs. Media users are active agents and have the ability to make rational choices. Further, Blumler (1979) contended, audience activeness is variable and certain media might facilitate audience activeness more than other media. Put differently, to understand the activeness of audiences, it is necessary to examine their uses of a specific medium, such as the Internet, rather than media, in general.

U&G has been considered as well suited for Internet research (Lin, 1999). The audience-centered focus of the theory corresponds well with the active process of Internet use (Rubin, 2002). Meanwhile, the theory has provided a useful framework for understanding why people use the Internet, as well as the outcomes and gratifications derived from its use (e.g., Althaus & Tewksbury, 2000; Lin, 1999; Morris & Ogan, 1996; Newhagan & Rafaeli, 1996). Nonetheless, the cultural context of media use is often overlooked or downplayed in prior U&G literature, which hence may impede development of the U&G theory and its explanatory power (Blumler, Gurevitch, & Katz, 1985). This study linked Internet research with CCA, and therefore, extended U&G research to a broader cultural context.

 

A Model of Internet Use

In line with the U&G theory and prior CCA research, a model of Internet use in CCA was posited as below: (a) individual differences influence (b) Internet use motives, which in turn have an impact on (c) Internet use (amount; type [host Internet use, ethnic Internet use]); Internet use further affects (d) adaptation outcomes (sociocultural adaptation and psychological adaptation). In addition, individual differences may directly impact Internet use and adaptation. A graphical depiction of the model was presented in Figure 1.

 

 

 

 

 

Figure 1. A model of Internet use in cross-cultural adaptation

Past CCA research has identified four prominent individual difference factors: host language/English competence, length of stay, acculturation attitudes, and loneliness. Host language proficiency and longer residency have consistently been found positively related to greater use of host media (e.g., Greenberg, 1983; Kim, 1977). Acculturation attitudes, proposed by Berry and his colleagues (i.e., integration, assimilation, separation and marginalization) also play a role in newcomers’ CCA (Berry et al., 1989). In addition, loneliness has been examined in both Internet and CCA research. It is suggested that loneliness influence foreign students’ psychological adjustment (Reece & Palmgreen, 2000). Scholars have also found that loneliness is often associated with greater Internet use (e.g., Kraut et al., 1998; Leung, 2002).

 

With the rapid diffusion of the Internet, media use motives research has been expanded to the examination of motives for using the Internet. Papacharissi and Rubin (2000), for example, identified five motives for Internet use: interpersonal utility, information seeking, to pass time, convenience, and entertainment. In the CCA context, the special needs people have when living in a foreign place may influence their motives for using the media. Reece and Palmgreen (2000), for example, identified motives for Indian students’ use of U.S. television, including the motives of “acculturation” and “reflection on values”. They argued that sojourners’ motivation to acquire host-country information was an important mediating variable between the need for acculturation and media use. Motivation for using the Internet, which is an important component in media uses and effects process, has been underemphasized in CCA research. Therefore, the first research question asked:

RQ1: What are the motives underlying CS’ use of the Internet?

 

Guided by the U&G paradigm, the main goal of this study was to test a model of Internet use in CCA that accounted for the relative contributions of individual differences, motivation, and Internet use to explaining cross-cultural adaptation. As such, the second research question asked:        

RQ2: What is the relative contribution of English competence, length of stay, acculturation attitudes, loneliness magnitude, Internet motives, and Internet use to predicting sociocultural adaptation and psychological adaptation?

 

 

Method

Sample

An electronic questionnaire was posted through www.surveymonkey.com, an online survey provider. Participants were CS currently studying at U.S. universities. A total of 268 questionnaires provided usable data for analysis. The sample was comprised of 48.1% male and 51.9% female; 4.6% undergraduate students and 90% graduate students; 47% of the respondents were single, 38% were married and lived with family, and 8% were married and lived alone. Respondents’ age ranged from 18 to 43 years old (M = 29.19, SD = 5.02).

 

Measurement

English competence. CS’ English competence was measured with a 5-item self report index adapted from Ying and Liese’s (1990) measure. The respondents’ ratings on the five items were summed and averaged to create an index of overall English ability (M = 3.77, SD = 0.68, Cronbach alpha = .88).

 

Length of stay. Length of stay in the U.S. was measured with an original single item. Respondents were asked to report how many years they have been in the U.S. (M = 3.96, SD = 2.80).

 

Degree of loneliness. The UCLA Loneliness Scale (Version 3) (Russell, 1996) was used to measure CS’ level of loneliness. Respondents indicated how often they felt lonely ranging from “never” (1) to “always” (4). Respondents’ scores were summed and averaged to create an index of loneliness magnitude (M = 2.70, SD = 0.45, Cronbach alpha = .91).

 

Acculturation attitudes. Acculturation attitudes were measured with a 9-item, 5-point Likert instrument adapted from Berry et al’s (1989) Acculturation Attitudes Scale. The instrument consisted of assimilation subscale (M = 2.14, SD = 0.66, Cronbach alpha = .49), separation subscale (M = 2.89, SD = 0.69, Cronbach alpha = .48), and integration subscale (M = 4.15, SD = 0.54, Cronbach alpha = .55).

 

Internet motives. A revised version of the Internet use motives scale (Papacharissi & Rubin, 2000) was used to measure CS’ Internet use motives in the context of CCA. The original 27-item scale consisted of five dimensions of Internet use motives: interpersonal utility, information seeking, entertainment, pass time, and convenience. To better tap Internet use motives in the CCA context, six “acculturation” and two “reflection on values” items (Reece & Palmgreen, 2000) were added to the instrument.

 

Internet use. Host Internet use was measured by asking the respondents to report the average time (in minutes) they spent daily on three major Internet functions: e-mailing with Americans, reading U.S. online news, browsing U.S. websites. Ethnic Internet use was measured by asking the respondents to report on the average time they spend daily on e-mailing with Chinese, reading Chinese online news, browsing of Chinese websites. The amount of time spent on host Internet use and ethnic Internet use were then calculated separately.

 

Sociocultural adaptation. Degree of sociocultural adaptation was measured with a 32-item modified version of the Ward and Kennedy (1999) Sociocultural Adaptation Scale (SCAS). Respondents were asked to indicate how much difficulty they experienced in different aspects, such as transportation, language and accepting American values on a 5- point scale ranging from “no difficulty” (1), to “extreme difficulty” (5). Responses were summed and averaged to create an index (M = 4.01, SD = 0.51, Cronbach alpha = .93).

 

Psychological adaptation. Prior studies mostly used single psychological instrument such as Zung’s (1965) Self-rating Depression Scale to measure psychological adaptation (e.g., Searle & Ward, 1990; Ward & Rana-Deuba, 1999). To increase the content validity, psychological adaptation was assessed by two scales including Hudson’s (1982) Generalized Contentment Scale (GCS) and the Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985).

 

 

Results

Internet Motives

Principal components analysis with varimax rotation was conducted on the 35 motive items to identify CS’s motives for using the Internet. The criteria for retaining a motives factor were a minimum eigenvalue of 1.0 and at least two loadings on the factor (using a .60/.40 loading rule). Eight factors that accounted for 67.1% of the total variance after rotation were identified. Table 1 presents a summary of the factor loadings.

 

Factor 1, Social Involvement (eigenvalue = 5.78), accounted for 16.5% of the total variance after rotation. This 8-item factor reflected CS using the Internet for socialization and participation, and ultimately to fulfill social, emotional, and psychological needs, which tend to be more prominent in the CCA process (M = 2.34, SD = 0.70, Cronbach alpha = .92). Factor 2, Acculturation (eigenvalue = 4.25), accounted for 12.15% of the total variance. This 6-item factor reflected using the Internet for cultural learning purposes (M = 2.80, SD = 0.79, Cronbach alpha = .90). Factor 3, Pass Time (eigenvalue = 2.92), accounted for 8.3% of the total variance. This 3-item factor reflected using the Internet to pass the time when CS were bored and had nothing better to do (M = 2.82, SD = 0.96, Cronbach alpha = .89). Factor 4, Information (eigenvalue = 2.57), accounted for 7.3% of the total variance. This 4-item factor reflected using the Internet to get information economically and conveniently (M = 3.83, SD = 0.71, Cronbach alpha = .78). Factor 5, Entertainment (eigenvalue = 2.49), accounted for 7.1% of the total variance. This 3-item factor reflected using the Internet to be entertained and because it was enjoyable and liked (M = 3.21, SD = 0.84, Cronbach alpha = .85). Factor 6, Convenience (eigenvalue = 2.14), accounted for 6.1% of the total variance. This 3-item factor reflected using the Internet because it was a convenient and cheap communication medium (M = 2.94, SD = 0.86, Cronbach alpha = .68). Factor 7, Companionship (eigenvalue = 1.83), accounted for 5.2% of the total variance. This 2-item factor reflected using the Internet to feel less lonely and when alone (M = 2.72, SD = 1.06, r = .85). Factor 8, Ethnic maintenance (eigenvalue = 1.48), accounted for 4.2% of the total variance. This 2-item factor reflected using the Internet to maintain ethnic ties and to reinforce ethnic values (M = 3.13, SD = 0.73, r = .49).

 

Cross-Cultural Adaptation

To address RQ2, three separate hierarchical regressions were conducted with sociocultural adaptation, life satisfaction, and depression as outcome variables, respectively. Results of three regression analyses were presented in Table 2.

 

Sociocultural adaptation.  Individual difference variables entered on the first step, explained 39.3% of the variance in sociocultural adaptation (R = .64, p < .001). Loneliness (β = -.41, p < .001), English competence (β = .28, p < .001), and separation attitude (β = -.20, p < .001) were significant predictors of social adaptation at this step. Internet motives, entered on the second step, explained an extra of 3.1% variance. Convenience motivation (β = - .14, p < .05) was the only significant predictor among motives. Host (American) Internet use and ethnic (Chinese) Internet use were entered on the third step, however, neither emerged as a significant predictor of sociocultural adaptation. The final equation accounted for 43% of the variance in sociocultural adaptation (R = .66, p < .001). Loneliness (β = -.38, p < .001), English competence (β = .28, p < .001), separation attitude (β = -.19, p < .01), and convenience motivation (β = - .14, p < .05) were significant predictors of sociocultural adaptation. In other words, better socioculturally adapted CS demonstrated the following characteristics: competent in English language, less lonely, low separation attitude, and weak motivation for using the Internet for convenience reason.

 

            Psychological adaptation.  For life satisfaction, individual difference variables, entered on the first step, explained 22.8% of the variance in life satisfaction (R = .48, p < .001). Loneliness (β = -.43, p < .001) was the only significant predictor of life satisfaction at this step. Internet motives were entered on the second step and explained 5.8% additional variance. None of the motives predicted life satisfaction. American Internet use and Chinese Internet use, entered on the third step, accounted for an additional 1.5% of the variance. American Internet use (β = .13, p < .05) and entertainment motivation (β = .13, p < .05) emerged as additional significant predictors of life satisfaction at this step. The final equation accounted for 30% of the variance (R = .55, p < .001). Loneliness (β = -.40, p < .001), entertainment motivation (β = .13, p < .05), and American Internet use (β = .13, p < .05) significantly contributed to predicting life satisfaction. In other words, CS who were less lonely, used the Internet for entertainment, and spent more time using American Internet tended to be more satisfied with their lives than were their counterparts.

 

For depression, individual difference variables, entered on the first step, explained 51.9% of the variance in depression (R = .72, p < .001). Loneliness (β = .63, p < .001) and English competence (β = -.19, p < .001) were significant predictors of CS’ degree of depression. Internet motives were entered on the second step and explained 6.3% additional variance. Pass time motivation (β = .10, p < .05) and information motivation (β = - .16, p < .01) were significant predictors at this step. American Internet use and Chinese Internet use, entered on the third step, accounted for additional 1.2% of the variance. American Internet use (β = -.11, p < .05) was a significant predictor of depression. Accordingly, the final equation accounted for 59% of the variance (R = .77, p < .001). Loneliness (β = .58, p < .001), English competence (β = -.16, p < .01), information motivation (β = -.16, p < .01), American Internet use (β = -.11, p < .05), and pass time motivation (β = -.10, p < .05) significantly contributed to predicting depression. These results suggest that CS who were lonely, less competent in the English language, used the Internet for passing time, but not for information, and used less American Internet tended to exhibit a higher degree of depression than did their counterparts.

 

 

Discussion

Internet Use Motives in CCA

Past CCA research suggested that the special needs of newcomers seeking to adapt cross-culturally would give rise to certain motives for media use that may not be salient in other situations (e.g., Reece & Palmgreen, 2000). The results of this study supported this proposition. Two unique motives in the CCA context, acculturation and ethnic maintenance, emerged as important reasons why CS used the Internet. Adaptation is one of the top priorities in international students’ life in the U.S. (e.g., Dato-on, 2000; Saran & Leonhard-Spark, 1980). At the same time, the findings lend support for the view that new technologies such as the Internet may strengthen ethnic ties by affording opportunities for ethnic communication.

 

Consistent with previous Internet research (e.g., Charney & Greenberg, 2002; Papacharissi & Rubin, 2000), the results revealed that information and entertainment were important reasons for Internet use among CS. Past U&G research has suggested that using media for informational reasons reflects learning from media (e.g., Grrenberg, 1974; Rubin, 1983). CS might use the Internet as a valuable information source for cultural learning in the process of CCA. In addition, the unique features of the Internet permit information tailored to special interest groups to be obtained easily. Thus, as suggested by Althaus and Tewksbury (2000), the Internet may satisfy special information needs of CS that can not be fulfilled by mainstream media.

Social involvement motivation reflects CS’ use of the Internet for functional purposes such as social interaction and participation. Papacharissi and Rubin (2000) found that people who had high anxiety in face-to-face interactions tended to use the Internet as a substitute or an alternative means for social contact. Therefore, CS may use the Internet as an alternative social space.

 

Sociocultural Adaptation

Ward and Kennedy (1999) contended that sociocultural adaptation may be influenced by factors related to culture learning and social skills acquisition. The findings further evidenced this conceptualization. For example, host language proficiency is at the heart of cultural learning and intercultural communication competence (Searle & Ward, 1990; Ward & Kennedy, 1994). Therefore, it is not surprising that English competence influenced newcomers’ sociocultural adaptation. Separation attitude emerged as a negative predictor of sociocultural adaptation, which makes conceptual sense. According to Berry et al. (1989), separation attitude refers to preferring to maintain one’s ethnic culture and deemphasize learning the new culture. Less cultural learning, consequently, perhaps leads to more difficulties in adapting to the new environment. 

 

The results, however, also revealed that loneliness and media use motives were important variables affecting newcomers’ sociocultural adaptation. In fact, loneliness was the strongest predictor of sociocultural adaptation. A plausible explanation is that lonelier CS may have less robust social interaction with others, including Americans, which in turn, may lead to more difficulties in adaptation (Kim, 1977, 2001).

 

Neither host nor ethnic Internet use predicted sociocultural adaptation. A plausible explanation is that behavioral adaptation, the primary aspect of sociocultural adaptation, usually follows a learning curve with rapid improvement during the first few months of newcomers’ transition and then a gradual “leveling off”. One characteristic of this particular sample was that the students had resided in the U.S. for an average of four years. They might have completed the behavioral change in the initial stage. Therefore, the impact of Internet use on their sociocultural adaptation may not have been as significant as it would be for those newcomers.

 

Psychological Adaptation

The results showed that all three categories of antecedents (i.e., individual differences, Internet motives, and Internet use) predicted psychological adaptation. Most importantly, Internet use motives, which have been often neglected in the CCA literature, predicted psychological adaptation. Specifically, CS, who used the Internet for entertainment and information purposes, but not for passing time, exhibited a higher level of psychological adaptation. These findings supported U&G notions that media use motives are crucial factors to consider when examining media behaviors and outcomes (Rubin, 2002).

 

Host Internet use predicted psychological adaptation, but not sociocultural adaptation. One explanation is that Internet use may provide a substitute for host interaction and as such, it did not predict socio-cultural adaptation. Another explanation may be attributed to the fact that newcomers go through different aspects of adaptation at difference paces (e.g., Melkote & Liu, 2000; Subervi-Velez, 1986; Ward & Kennedy, 1993, 1999). Sociocultural adaptation usually happens quickly in the initial stage of CCA (Melkote & Liu, 2000; Ward & Kennedy, 1993, 1999). Psychological adaptation, on the other hand, is a much more prolonged process (Ward & Kennedy, 1993, 1999). Therefore, it is possible that some of the CS surveyed had passed the stage of social behavioral change, whereas many of them were still undergoing the psychological adaptation process. This may be an explanation of why the impact of Internet use was more pronounced on psychological adaptation than on sociocultural adaptation.

 

Limitations

This study has several limitations. First, the quantitative research methodology used in this study may not give us a complete picture of complex processes such as cross-cultural adaptation. A multi-method approach incorporating both quantitative and qualitative methods to study the CCA phenomenon would allow both statistical tests of theory and in-depth assessments of variables (e.g., Kim, 1988; Reece & Palmgreen, 2000). Second, this study used a convenience sample. Therefore, generalizability of the results to other sojourners, including other CS in the U.S. is constrained (Barbie, 2001). Third, some measures used in this study may not be robust. The Internet use instrument, for example, had a rather high incompletion rate. Finally, the cross-sectional research design of this study did not allow for determining causal relationships among variables. A longitudinal design that examines changes over time would be helpful in examining the direction of causality.


Appendix

Table 1

Factor Loadings for Internet Motives                                                                                     

 

 

Motive Items

Motive Factors

 

1

2

3

4

5

6

7

8

 

Factor 1: Social Involvement

 

 

 

 

 

 

 

 

To give my input

.85

.10

.09

.09

.10

.09

.03

.03

To show other encouragement

.83

.16

.00

.05

.00

.17

.09

-.04

Because I enjoy answering questions

.80

 -.02

.11

.04

.15

-.01

.10

-.03

To participate in discussion

.80

.13

-.00

.05

.08

-.02

.00

-.04

To express myself freely

.77

-.00

.03

.07

.12

-.08

.15

-.01

To tell others what to do

.75

.17

.04

-.02

-.02

.16

.04

.15

To help others

.69

.22

.06

.04

-.01

.24

.07

-.05

To meet new people

.62

.06

.14

-.09

.01

.24

.13

.22

 

 

 

 

 

 

 

 

 

Factor 2: Acculturation

 

 

 

 

 

 

 

 

To learn about Americans’ points of view

.06

.88

-.05

.06

.01

.06

-.07

.11

To learn about American culture

.13

.85

.01

.08

.07

.08

.00

.08

To learn more about American values

.09

.84

-.07

.04

-.02

.02

-.03

.08

To help me adjust to American society

.21

.81

-.02

.00

.02

.10

.15

.02

To find out what is going on in the U.S.

-.01

.74

.05

.10

.04

.11

-.12

.13

To improve my English

.24

.68

-.08

.67

.08

.01

.34

-.09

 

 

 

 

 

 

 

 

 

Factor 3: Pass Time

 

 

 

 

 

 

 

 

Because it gives me something to do to occupy my time

.07

-.03

.89

.02

.16

.07

.13

.00

Because it passes the time away, particularly when I’m bored

.06

-.04

.88

.05

.07

.06

.10

.08

When I have nothing better to do

.12

-.10

.83

.09

.09

.06

.18

-.05

 

 

 

 

 

 

 

 

 

Factor 4: Information

 

 

 

 

 

 

 

 

To get information for free

.08

.05

.08

.84

.08

.05

.06

.03

To look for information

-.01

.06

.06

.83

.04

.01

-.03

.04

Because it is cheaper

.09

.11

-.01

.70

.32

.22

.00

-.02

Because it is a new way to do research

.07

.16

.07

.61

.19

.23

.08

.04

                                                                                                                      (table continues)


 

 

 

Motive Items

Motive Factors

 

1

2

3

4

5

6

7

8

 

Factor 5: Entertainment

 

 

 

 

 

 

 

 

Because it’s entertaining           

.05

0.4

.16

.13

.86

.11

.15

.06

Because it’s enjoyable

.11

.11

.06

.12

.84

.22

.15

.04

Because I just like to use it

.16

.01

.14

.18

.78

-.01

.00

.01

 

 

 

 

 

 

 

 

 

Factor 6: Convenience

 

 

 

 

 

 

 

 

Because people don’t have to be there to receive e-mail

.06

.13

-.04

.09

.10

.74

.13

-.03

Because it is easier to e-mail than tell people FTF

.14

.07

.06

.14

.15

.71

.11

.02

Because it is cheaper

.27

.07

.31

.21

.03

.62

-.16

.05

 

 

 

 

 

 

 

 

 

Factor 7: Companionship

 

 

 

 

 

 

 

 

So I can feel less lonely

.17

.08

.23

-.02

.12

.11

.82

.19

When there’s no one else to talk or to be with

.20

.03

.46

.06

.17

.13

.69

.06

 

 

 

 

 

 

 

 

 

Factor 8: Ethnic Maintenance

 

 

 

 

 

 

 

 

To find out what is going on in China

-.11

.15

.11

.17

.08

-.05

.05

.81

To reinforce my Chinese cultural values

.19

.18

-.10

-.10

.01

.12

.22

.68

      Note. N = 268.

 

 

 

 

 

 


Table 2

Summary of Final Results When Regressing Adaptation on Individual Differences, Internet Motives, and Internet Use

 

 

Final  β

Variable

Sociocultural

Life

Depression

 

Adaptation

Satisfaction

 

 

 

 

 

Step 1

 

 

 

    English Competence

.28***

.10

-.19***

Length of Stay

.06

.04

.00

Loneliness

-.41***

-.43***

.63***

Acculturation Attitudes

 

 

 

  Assimilation

-.01

.10

.07

  Separation

-.20***

.04

.02

  Integration

.03

.01

-.05

 

Step 2

 

 

 

    English Competence

.28***

.10

-.17***

Length of Stay

.03

.05

.00

Loneliness

-.38***

-.39***

.58***

Acculturation Attitudes

 

 

 

  Assimilation

.01

.11

.05

  Separation

-.19**

.01

.02

  Integration

.04

-.05

.00

   Internet Motives

 

 

 

      Social Involvement

-.06

-.04

.05

      Acculturation

.07

.06

-.06

      Pass Time

-.02

-.07

.10*

      Information

-.04

.06

-.16**

      Entertainment

.05

.12

-.05

      Convenience

-.14*

.11

-.06

      Companionship

-.02

-.03

.10

      Ethnic Maintenance

.03

.09

-.08

 

Step 3

 

 

 

    English Competence

.28***

.08

-.16**

Length of Stay

.03

.05

.01

Loneliness

-.38***

-.40***

.58***

Acculturation Attitudes

 

 

 

  Assimilation

.01

.10

.05

  Separation

-.19**

.03

.01

  Integration

.04

-.05

.00


                                                                                                               (table continues)

 

 

 

Final β

 

Variable

Sociocultural

Life

Depression

 

Adaptation

Satisfaction

 

 

 

 

 

   Internet Motives

 

 

 

      Social Involvement

-.06

-.03

.04

      Acculturation

.07

.03

-.03

      Pass Time

-.02

-.06

.10*

      Information

-.04

.06

-.16**

      Entertainment

.05

.13*

-.06

      Convenience

-.14*

.09

-.04

      Companionship

-.02

-.01

.08

      Ethnic Maintenance

.03

.10

-.09

U.S. Internet Use

.00

.13*

-.11*

Chinese Internet Use

-.03

-.08

.07

Note. N = 268. *p < .05, **p < .01, ***p < .001.

 

                                                                                                                 


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About the Authors

 

Ying Wang (Ph.D., Kent State University, 2006) is an assistant professor in the Williamson College of Business Administration at Youngstown State University. Shaojing Sun (Ph.D., Kent State University, 2003; Ph.D., University of Virginia, 2006) is an associate professor in the School of Journalism at Fudan University, Shanghai, P. R. China. Paul M. Haridakis (Ph.D., Kent State University, 2001) is an associate professor in the School of Communication Studies at Kent State University.

 

Authors’ Address

Contact Information:

Ying Wang, Department of Marketing, Williamson College of Business Administration, Youngstown State University, One University Plaza, Youngstown, OH 44555.

Telephone: (330) 941-1867.

Fax: (330) 941-3674.

E-mail: ywang01@ysu.edu


Journal of Intercultural Communication, ISSN 1404-1634, issue 20, May 2009.
URL: http://www.immi.se/intercultural/.