Chinese Television Audience Behavior in a Multi-Channel Environment:

　　A case of Beijing

　　Elaine J.Y. Yuan    Ph. D Student  Communication Studies

　　School of Communication    Northwestern University

　　Results

　　The results are presented in Table 1. The data of the 50 channels are broken down into six columns described above. Table 2 offers a correlation matrix of all six variables across 50 cases.

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　　 TVHH Universe summarizes the percent of all television households capable of receiving the channel signal in question. Beijing enjoys the highest satellite television penetration rate in the country. The data show that older CCTV channels have better coverage, ranging from 100% to 95 % of all TVHH, than the newer provincial satellite channels, ranging from 94% to 75%. The average TVHH Universe of the total 50 channel is 87.2% with a 7.2% standard deviation. As a comparison, the average TVHH Universe of the 62 U.S networks in Webster’s study (2003.) in is 68% with a standard deviation of 21%. Therefore, the de facto polarization is less of an issue in Beijing. However, when we look at the overall picture for the whole country it’s quite different. The difference range between the highest TVHH Universe and the lowest is over 90% with a 25% standard deviation. Therefore the question is worth further exploring on a national level.

　　Data analysis also shows the evidence of channel repertoire for Beijing audience. The average number of channels watched per person is 11 on weekdays and 13 on weekend.

　　Weekly cume, a.k.a. reach, is the percent of the population that watched the channel at least one minute during the week. Beijing TV Satellite channel has the highest weekly reach, 81%. However, it indicates that there is about 20% of the audience who doesn’t watch even the most popular channel during the whole week at all. The other seven Beijing TV channels, i.e. the local channels, also rank high. So do most of CCTV’s long established channels. The rest of the channels, mostly satellite channels from other provinces, have relatively smaller weekly reach. In fact even the channels with a TVHH penetration as high as 90% only reach 30% of the audience during the week. This suggests that most viewers simply haven’t included those channels in their channel repertoires.

　　Share of total audience viewing shows how large a “piece of the pie” each channel gets. We get the similar picture here as on weekly cume. Beijing TV and CCTV channels take up over 60% of the total share. The rest of viewing is widely distributed among the other channels. Considering there is limited structural difference, i.e. difference in TVHH Universe, we think the programming of those provincial satellite channels may be a major reason for their unfavorable position. A case in point: most provincial channels air local news which is not relevant to Beijing audience during the early evening time slot right before the 7 clock national news fed by CCTV 1. Therefore they lose the opportunity to lead the audience further into the evening prime time.

　　 These share of total audience viewing numbers offers us a glimpse of the phenomenon of audience fragmentation. In absolute terms, even the channel with the largest share only occupies just a small portion of the time people spend watching TV. For instance Beijing Satellite Channel has the largest share which is only 11%. However, when compared with U.S. where the top 10 channels take up only a little over 30% percent of the total viewing, the degree of audience fragmentation in Beijing is much less.

　　 The remaining three columns offer measures of audience polarization. Average time-spent-viewing (TSV) gives us a sense of the intensity of channel use among a channel’s viewers. Beijing TV channels and CCTV channels continue to dominate. Moreover, their entertainment-orient channels, e.g. BTV 4 and CCTV 6 and 8, the movie and TV drama channels, do better than their information-oriented channels, e.g. CCTV 2, the financial channel, and BTV 7, the technology and education channel. In fact, several provincial satellite channels whose lineup is more entertainment-oriented even surpass those information-oriented channels.

　　 Furthermore, there is a strong presence of the law of double jeopardy, i.e. people spend more time watching the channels that are watched by more people. Table 2 indicates the overall correlation between weekly cume and TSV is .77. In fact, this is where Chinese audience is most different from U.S. audience. According to Webster (2003), the overall correlation between cume and TSV for the U.S. audience is only .38 and there are many examples of small-but-loyal audiences. In fact, when the big-three networks (i.e. NBC, ABC and CBS) are eliminated the overall correlation between cume and TSV is not statistically insignificant. By examining the Chinese data we also find a minor exception to the rule of “double jeopardy”. CCTV 11, the music and folk opera channel, reaches only 18% of the audience who, however, spent 202 minutes on average viewing the programs on the channel! But the correlation of TSV and cume among only BTV and CCTV channels, the content of which is more or less correlated, is about the same as that among the rest of channels.

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　　 Share-within-cume expresses TSV as a percentage. So, for example, while Beijing Satellite Channel is viewed by 81% of the audience (i.e., the cume), those people spend 13.5% of their time watching it. Share-within-cume is highly correlated with TSV (r=1.0). Just as the case in U.S., these measures of the intensity of channel use are unrelated to the channel’s universe. So the most available channels are not necessarily the ones that draw the heaviest use. (Webster, 2003)

　　 The within-channel duplication index is the extent to which audience duplication exceeds chance. If the people watching a channel were just as likely as the general population to watch that channel, the loyalty score would be 1.0. Beijing Satellite Channel has the lowest loyalty scores, 1.2. This means that people who watch BTV satellite are about 20% more likely than the general population to watch these channels. On the other hand, Channels with smaller weekly cume have higher index values. The correlation between these variables was -.91.

　　Conclusion

　　 The study shows some degree of fragmentation and polarization of Beijing audience. In absolute terms, even the channel with the largest share only occupies just a small portion of the time people spend watching TV. The uneven availability of channels and the limited number of channel repertoire all contribute to the polarization of the viewing. However, the degree of fragmentation and polarization of Chinese audience is less severe than that of U.S. audience. There are far fewer available channels in China than in U.S. The content of the channels in China are also less correlated than that of U.S. The long established national CCTV channels and local Beijing TV channels still command large audience shares and weekly cumes. When the goal is to reach the largest audience possible these channels can are still the best choices for advertisers. Meanwhile the channels with large weekly cumes also have long TSVs. This confirms the existence of double jeopardy phenomenon. And there are no obvious signs for a highly segmented audience.

　　 Because of the limited data available, there are many aspects of audience behaviors left untackled by the current study. However, the findings of the study may serve as a starting point on which we may build our future research on television audience behaviors in China.

　　References

　　Comstock, G & Scharrer, E (1999). Television : What’s on, who’s watching, and what it means. San Diego : Academic Press.

　　CSM (2002). Television in China: 2001 overview. Beijing: CVSC-Sofres Media.

　　Ehrenberg, A.S.C., & Wakshlag, J.(1987). Repeat-viewing with people meters. Journal of Advertising Research , 27, 9-13.

　　Ferguson, D. A., & Perse, E. M. (1993). Media and audience influences on channel repertoire. Journal of Broadcasting & Electronic Media, 37(1), 31-47.

　　Goodhardt, G.J., & Ehrenberg, A.S.C. (1969). Duplication of Televison Viewing between and within channels. Journal of Marketing Research, 6 169-178.

　　Goodhardt, G.J.; Ehrenberg, A.S.C.; & Collins, M.A. (1987). The television audience : Patterns of viewing (2nd ed.). Westmead, UK: Gower.

　　McPhee, W. N. (1963). Formal theories of mass behavior. New York : The Free Press.

　　Neuman, W. R. (1991). The future of the mass audience. New York: Cambridge University Press.

　　Wang, J., & Chang, T. K. (1996). From class ideology to state manager: TV programming and foreign imports in China, 1970-190. Journal of Broadcasting & Electronic Media, 40, 196-207.

　　Webster, J. G. (1985). Program audience duplication: A study of television inheritance effects. Journal of Broadcasting & Electronic Media, 19, 121-133.

　　Webster, J. G. (1986). Audience behavior in the new media environment. Journal of Communication, 36(3), 77-91.

　　Webster, J. G. (1988). Structural Deterninatns of the television news audience. Journal of Broadcasting & Electronic Media, 32, 381-389.

　　Webster, J. G. (2003). Beneath the veneer of fragmentation: Television audience behavior in a multi-channel environment. Working paper.

　　Webster, J.G., Phalen, P. F., & Lichty, L. W. (2000). Ratings analysis : The theory and practice of audience research. Lawrence Erlbaum Associates.

　　Webster, J.G., & Phalen, P.F. (1997). The mass audience : Rediscovering the dominant model. Mahwah, NJ: Lawrence Erlbaum Associates.

　　Webster, J. G., & Wakshlag, J. (1983). A theory of television program choice. Communication Research, 10, 430-446.

　　Webster, J. G. , & Wang, T. (1992). Structural determinants of exposure to television: The case of repeat viewing. Journal of Broadcasting & Electronic Media , 36(4), 125-136.