Bureaucrats or Strategists?
Competitive Strategy of China’s State-Owned Satellite Television Industry
Richard Wang†
December 2008
*** Preliminary and Incomplete. Comments Welcome. Please do not cite. ***
Abstract
An important goal set by the Chinese government in market reform is to promote
scientific management among state-owned enterprises (SOE). This paper empirically
investigates whether the reform has led Chinese state-owned satellite television channels
to implement market competitive strategy. Using a near-census panel dataset, I examine
programming portfolios and ratings performance of 30 channels from May 2002 to May
2004. I find the province-level government-owned satellite channels execute spatial
differentiation strategy with respect to their common dominant competitor – the central
government-owned CCTV1 channel. Moreover, channels exhibit sensitivities to market
demand variations when implementing their strategies. Channels that compete more
directly with CCTV1 for national audience demonstrate greater responsiveness. In
addition, satellite channels are aware of their own ability when selecting strategies. The
overall behavior of the satellite channels offer coherent support that they are competing
strategically.
†
Ph.D. Student, Business & Public Policy Group, Haas School of Business, University of California at
Berkeley. I am grateful to Paul Gertler, John Morgan and seminar participants at the Haas School of
Business for their valuable comments. I am also indebted to L. Bai, Matthew Brosenne, Cedric Lam, Z. Liu,
X.F. Lu, Louise Wang, and B. Zhang for sharing with me their industry knowledge. The ratings dataset was
generously provided by CSM Media Research. All errors are my own.
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Introduction
The approach taken by the Chinese government to market reform is different from the
ones followed by other transition economies, notably in the area of reforming stateowned enterprises (SOEs). Unlike those in Russia and CEE countries, many large
enterprises remain state-owned in China today. While institutions such as IMF and the
World Bank advocated privatization of SOEs (e.g. the “Washington Consensus”), the
Chinese government instead relied on corporatization – to make SOEs operate as if they
were private firms facing competitive markets (World Bank, 1995; Shirley, 1999; Nolan,
2001; Qian, 2002).
The Chinese SOE reform has been implemented in stages (Qian, 2000). In the 1990’s,
despite empowered with greater autonomy and decentralization of management decisions,
the SOEs were not performing up to expectations. At the Fifteenth Congress of the
Chinese Communist Party in 1997, the government stepped up the reform process by
approving a program known as zhuada fangxiao (literal translation being “grasping the
large and letting go the small”, or “managing successfully large enterprises while
invigorating small ones”).1 In 1999, the Central Committee of the Chinese Communist
Party followed up with a Decision document to elaborate on the program. According to
the Decision, a target is set for large SOEs to adopt modern enterprise system (MES) by
2010. An important aspect under the MES is to promote scientific management among
SOEs. The Decision stated, “Enterprises should adapt themselves to the market,
formulate and implement clear strategies for development, technological innovations and
Zhuada fanxiao began as a quite reform in the mid-1990’s and was formally adopted by the Chinese
central government in 1997.
1
2
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Richard Wang
marketing, and timely readjust these strategies in accordance with the changes in the
market.”2 In this paper, I investigate whether Chinese SOEs are reforming in line with
the government’s MES goal that they are sensitive to market environment changes and
implementing corresponding competitive strategies.
I study the Chinese national television industry which consists of a central governmentowned China Central Television (CCTV) and 31 province-level government-owned
satellite channels.3 The industry setting resembles a dominant firm competitive fringe
(DFCF) structure, with CCTV’s flagship channel – CCTV1 – taking up thirty percent of
the national audience share. In a DFCF situation under market economies, one would
expect the dominant player to focus on the mass market while fringe players operate
around it. In particular to the media broadcasting industry, the competitive fringe should
spatially differentiate their programming from that of the dominant firm. By analyzing a
near-census panel dataset of China’s national television programming lineup and ratings
from May 2002 to May 2004, I find evidence on satellite channels strategizing their
programming lineups as if they were competing under a market economy DFCF setting.
In addition to differentiating their programming from that of CCTV1, the satellite
channels demonstrate sensitivities towards variations in market demand conditions as
2
The Decision of the Central Committee of The Communist Party of China on Major Issues Concerning
The Reform and Development of State-Owned Enterprises, Fourth Plenum of the 15th CPC Central
Committee, September 22, 1999; English translation by the Legal Information Center of Peking University
(www.lawinfochina.com).
3
In addition to CCTV and 31 province-level satellite channels, the national television market also consists
of the Education channel which takes up less than a fraction of a percent in audience share. Tibet, Xinjiang
and Inner Mongolia television stations operate separate satellite channels in Tibetan, Uygur and Mongolian
languages in addition to their Mandarin language channels. In 2004, the regulatory agency also permitted 5
municipal level channels to broadcast nationally, with Shenzhen satellite channel being the first of its kind
to launch on May 28, 2004. In this paper, I focus only on the competition between CCTV1 and 30 of the 31
province-level Mandarin language satellite channels (Tibet satellite channel is excluded).
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Richard Wang
well as the degree of direct competition with the dominant player. The overall evidence
presented in this paper support the argument that the state-owned satellite channels are
competing strategically.
This paper relates to the debate on SOE reform policy among the three main schools of
thoughts: privatization, competition and institution. Proponents of privatization argue that,
without ridding government ownership, SOEs will be influenced by political objectives
and therefore cannot achieve economic efficiency (e.g. Shleifer and Vishny, 1994). On
the other hand, proponents of competition and institution argue that, by introducing
competitions and enhancing institutional environments, the Chinese market reform has
led SOEs to rising performance without privatization (e.g. Groves et al., 1994; Li, 1997).
While much focus has been on measuring performance, fewer studies have examined
SOE market competitive strategy – a subject alien to SOE managers under the planned
economy system prior to the market reform. A contribution of this paper is to study
whether Chinese SOE reform absent of privatization has led SOEs to adopt strategic
management practices.
The contributions of this study go further than that of measuring Chinese SOE reform
progress. SOEs still accounted for thirty percent of China’s total investment in fixed
assets and employed over 61 million workers as recently as in 2006.4 At the Fifteenth
Congress in 1997, then Chinese President Jiang Zemin emphasized “the state-owned
sector must be in a dominant position in major industries and key areas that concern the
life-blood of the national economy.” SOEs that survive the market transition will play an
4
China Statistical Yearbook 2007. National Bureau of Statistics of China.
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Richard Wang
important role in shaping future industry landscapes, and firms operating in China are
likely to compete with incumbent SOEs (Nolan, 2001). Gaining a better understanding on
SOE competitive strategy is therefore crucial to comprehending Chinese business
environments.
The paper proceeds as follows. I present a literature review on SOE reform and on
competitive strategy specific to the broadcasting industry. I then provide an institutional
overview of the Chinese national television market, followed by stating the hypotheses.
In turn, I describe the data and empirical specifications. After presenting the empirical
results, I close with concluding remarks.
Literature Review
Literature on SOE Reform Policy Debate
There are three main schools of thoughts in the SOE reform debate: privatizing
ownership, promoting competition and improving institutions. The privatization literature
argument is based on the property rights theory and principal-agent theory. Property
rights theory (e.g. Grossman and Hart, 1986) proposes individuals respond to incentives
and the pattern of incentives is shaped by property rights structure. With no individual or
group clearly identified as the residual claimant, SOEs therefore will operate with low
levels of efficiencies. The principal-agent theory (e.g. Sappington, 1991) argues that the
agents do not share the same objectives as the principals but the latter lack perfect control
over the former due to information asymmetry. The principal-agent problem is worse
under public than private ownership due to more severe information asymmetry, causing
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greater difficulty for the government to hold SOE managers accountable. This line of
literature proposes privatization as the solution to improving SOE performance.
The competition literature argues that market competition, not property rights, as the
main driver of firm performance. Their proposition is based on incentive and information
effects. Competition in markets generates incentive effects by punishing managers of
inefficient firms with diminished returns (Porter, 1980). Competition also reveals
information about relative performance of firms (Holmstrom, 1982), thus alleviating the
principal-agent information asymmetry problem. However, the privatization literature
counter-argues that even in competitive markets, SOE would remain inefficient because
without separating the ownership from government, politicians would sidetrack SOEs to
pursue political objectives (Shleifer and Vishny, 1994).
The institutional reform literature is built on the New Institutional Economics argument
that markets are organized according to institutions (Williamson, 1975, 1985; North,
1991). It addresses SOE reform from a macro- and a micro-environment perspective. The
macro aspect highlights the importance of institutions external to the firm, such as
independent judiciary, capable bureaucracy, and checks and balances in the governments
(e.g. Levy and Spiller, 1996). The micro aspect places managers and managerial
motivation on center stage, proposing that government offering realistic incentives to
SOE managers can improve organization performance. Nolan wrote “the vast bulk of
managers within large companies are stimulated to effective performance by appropriate
contracts and by non-pecuniary motivation, rather than by ownership” (1995, p.316).
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Compared to privatization and competition, the institutionally oriented approach to SOE
reform is perceived to be still in infancy stage and in need of empirical evidence in
respect of transforming economies (Hassard et al., 2007, p. 32).
In the context of Chinese SOE reform policy, researchers tend to advocate promoting
competition and improving institutions over privatization (Lin et al., 1998; Qian, 1999).
Lin et al. (1998) stressed that fair competition policy, accompanied by releasing the
SOEs from policy burden, is a necessary condition for successful SOE reform. On
building market-supporting institutions, Qian (1999) argued that central government
institutional policies such as regional decentralization of government, encouragement of
entry and expansion of non-state firms, together with financial reforms have released the
potential for managerial incentives and competition.
Literature on Chinese SOE
Literature on Chinese SOEs has focused on governance (e.g. Boisot and Child, 1988),
incentive mechanisms (e.g. Gordon and Li, 1991; Groves et al., 1994), and performances
(e.g. Li, 1997; Bai et al., 1997; Jefferson et al., 2000). Researchers have also examined
SOE non-market strategy through the political economy lens (e.g. Qian and Roland, 1998;
Oi, 2005). In recent years, researchers are becoming more interested in examining SOE
business strategies (e.g. Wang, 2006; Fernandez and Fernandez-Stembridge, 2007; Zhang
2008). These newer studies, mostly qualitative based, generally indicate that SOE
managers are making decisions strategically.
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On the other hand, quantitative empirical studies on Chinese SOE market competitive
strategy have been few and far in between (e.g. Tan and Litschert 1994, White 2000). A
number of reasons may be behind the apparent lack of research in this area. Even in the
post market reform era, the government still maintains substantial influence over SOEs
by imposing non-market objectives and resource allocations, which in turn promotes
SOEs to exercise non-market strategies such as cultivating relationships with their
bureaucratic superiors and negotiating for soft-budget allowances as an alternative to
market strategy (Chen and Faure, 1995; Peng, 2000). Data availability is another concern.
Most empirical studies on Chinese enterprises until recently have relied on survey or
cross-sectional data. Researchers have pointed out the limitation of using such data
especially under the high velocity Chinese business environment (Hoskisson et al. 2000).
While SOE data is becoming increasingly available, the consistency and reliability of the
data remains questionable (Peng et al. 2001). Nevertheless, SOEs’ significant presence in
key Chinese industries supports the need for research on their competitive strategy.
Literature on Competitive Strategy in Broadcasting Industry
The seminal work by Steiner (1952) on broadcast programming choice adopted an
economic approach and sought to explain how audience as rational consumers would,
given different program options available, maximize their satisfaction. Steiner’s analysis
is an extension of the classic Hotelling (1929) model of product spatial differentiation.
Subsequent research followed Steiner’s basic premises and made improvements by
relaxing the assumptions. The Beebe (1977) model, for example, permits viewers to rank
multiple program choices above the no-viewing alternative. Contemporary models have
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been developed when cable technology became available which vastly increased the
number of channels and enabled pay-television. For instance, Spence and Owen (1977)
and Wildman and Owen (1985) incorporated viewers’ willingness-to-pay to in their paytelevision models.5
Extending the line of advertiser-support broadcasting models of Steiner and Beebe, the
more sophisticated models by Noam (1987) and Waterman (1990) treated the
programming space as a one-dimensional continuum instead of discrete programming
choices. A common theme of advertiser-support models is that the channels have strong
incentives to occupy the programming space where density of viewer preference is
highest but they maintain some level of spatial distances to avoid excessive thinning of
viewer population.
Institutional Background
Television broadcasting in China began in 1958 when the central government started
broadcasting around the Beijing area on which is now known as the China Central
Television, or CCTV. Nevertheless, it was not until the 1980’s and more so in the 90’s
when the general public began to own television sets that the television industry took off.
In 2005, 97.9 percent of urban Chinese households and 95.8% of rural ones own at least
one television set (China TV Rating Yearbook, 2006).6 It is estimated that the television
5
There exists a large literature on television programming strategy which relaxes the viewer rationality
assumption. Instead, it focuses on viewer behaviors such as inertia or inheritance effects (e.g. Webster 1985,
Tiedge and Ksobiech 1986, Walker 1988.) Along this line of study, programming strategies such as
hammocking, tent-poling and counterprogramming are introduced. The empirical analysis in this paper,
however, is based on the Steiner, Beebe, Noam line of competitive strategy models.
6
The data quoted from this section, unless specified otherwise, is from China TV Rating Yearbook from
2003 to 2006.
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Richard Wang
medium reaches over 95.3% of the Chinese population. Television watching is one of the
nation’s favorite pastimes. In 2005, an average Chinese spends 174 minutes watching
television per day (compared to 155 minutes for an average American in 20067). Primetime in China starts at 7:00pm and last until 11pm, with prime-time audience size over
five times that of non-prime time.
The primary mandate of television stations in China is to ensure timely dissemination of
government announcements to citizens in every part of the country. In the 1980s,
television transmission relied on terrestrial broadcasting which required numerous
television stations in order to guarantee national coverage. At the peak, there were over
3,000 television stations in China. The arrival of satellite and cable technologies in the
1990s greatly improved the efficiency of television signal delivery, making the terrestrial
broadcast system highly redundant. Industry restructuring was needed.
The current industry landscape was shaped in 2001 when the central government
regulatory agency, the State Administration of Film Radio and Television (SARFT),
ordered merging of terrestrial, cable, and satellite channels to form essentially three tiers
of television stations. The top tier is occupied by the China Central Television (CCTV),
which is own and operated by the central government. The second tier consists of 31
province-level stations, which are owned by the province-level governments. The third
tier consists of the local stations owned by municipality, prefecture and county-level
governments. Each television station operates multiple channels. For example, CCTV
currently operates 16 channels (with CCTV1 being their flagship channel) and the
7
“Special Report: America by the Numbers”, Time Magazine (p.44), November 26, 2007
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Shanghai station operates 11. In 2004, there were 314 television stations in China
carrying 2,389 channels.
As part of the restructuring, each of the 31 province-level television stations uplink one
of their Mandarin language channels to satellite broadcast. This dramatically transformed
the national television competitive landscape where, before the restructuring, provincelevel stations used to focus only on domestic province audience and did not compete with
others for national audience. Consistent with the Chinese government’s competition
promotion policy (Lin et al., 1998), the post reform industry structure offers a level
playing field on which each province-level satellite channels compete.
On distribution of television signals to households, unlike in the US and European
countries where households install their own satellite dish, local cable companies
aggregate broadcast signals from the satellite channels together with those from CCTV
and local stations, and deliver the programming contents to households via cable. Table 1
summarizes the household coverage by the satellite channels. Table 2 presents market
shares of main broadcaster categories from 2002 to 2004. The market shares are split
almost evenly between national broadcasters (i.e. CCTV and satellite channels) and local
broadcasters. Satellite channels take up approximately 16% of overall television
viewership, or about one third of the national broadcast market share. Of all the national
channels, CCTV1 alone takes up about 30 percent of the national market share in 2002.
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The satellite channels are regulated by SARFT which is an executive branch under the
State Council. Among other duties, SARFT reviews and approves the content of
television programs. Once a program is approved, satellite channels are free to acquire
the rights from the producer for broadcast. Although satellite channels are required to file
their programming lineups to SARFT one month in advance, they are autonomous in
making their own daily operational and business decisions.
Financially, the satellite channels are receiving diminishing financial support from the
province-level governments and are increasingly relying on advertising revenues. In 2005,
satellite channels total advertising revenue is estimated at CNY37.4 billion. A recent
survey indicated that advertising revenue account for over 90 percent of satellite
channels’ revenues (Blue Book of China’s Media 2007). As a New York Times article
describes the situation, “[G]overnment support for Chinese television is dwindling,
creating a burst of commercialism as stations compete for viewers and advertising
dollars.”8
In summary, the policies concerning provision of access to satellite infrastructure,
hardened budget constraints and decentralization of business decisions are consistent with
the government’s overall competition and institutional approach to SOE reform. (Lin et
al., 1998; Qian, 1999).
Hypotheses
Baseline Differentiation Hypothesis
8
“Upstart from Chinese Province Masters the Art of TV Titillation”, The New York Times, Nov 25, 2005.
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The objective of this empirical study is to explore whether state-owned satellite channels
are competing strategically under China’s SOE reform policy. As a baseline, if they
exhibit differentiation activities (as prescribed by the Steiner Beebe and Noam models)
towards their common dominant competitor, CCTV1, it will lend support to the argument
that they are indeed competing strategically in the national television market. Therefore, I
hypothesize that:
H1: Satellite channels respond to CCTV1 programming changes by
differentiating their programming portfolios from that of CCTV1.
Building on top of the baseline hypothesis, I examine whether and how satellite channels
adapt their strategies under various market demand, direct competition and ability type
conditions, as well as their selection of alternative strategies.
Market Demand Condition
Strategically competitive broadcasters should demonstrate sensitivities to different
demand conditions that vary across markets. The simplest distinction of television
markets is by prime time. Prime time market demand is different from that of non-prime
time in two ways: (1) the prime time market has higher demand, and (2) the prime time
market has a more diverse mix of audiences which offers support to greater variety of
programming that otherwise would be unprofitable in non-prime time markets.
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Operating under the advertiser-supported revenue model, satellite channels have the
highest stakes in the 7:00pm to 11:00pm prime time timeslots. Therefore, they should
respond more diligently to CCTV1 programming portfolio changes in these timeslots. At
the same time, the more diverse mix of audiences in prime time market offers the
channels more viable space to differentiate from CCTV1. The effects of higher demand
and greater audience diversity encourage and facilitate greater response from satellite
channels during prime time. Therefore, I hypothesize that:
H2: Satellite channels respond greater to CCTV1 programming portfolio
changes during prime time.
Direct Competition
When two channels have significant overlaps in their target audiences, they are
considered in direct competition with one another. Should a channel modifies its
programming portfolio, the other should respond more if the two are direct competitors
than if they are not. At the same time, the need for responding to programming portfolio
changes is also dependent on the two channels’ relative abilities to capture audience. Low
ability (low type) channels try harder to avoid direct competition with high ability ones
(high type) through differentiating their programming portfolio. When a competitor
modifies its programming portfolio, a low type channel would respond more than a high
type one.
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Let’s apply the above argument to the Chinese television context. The Chinese national
television market, M, can be considered as a composition of all province-level markets,
mj, i.e. M = {m1, m2, …, mj, …}. Since advertisers prefer television channels to capture
financially wealthy audiences, the economic values of each province-level market are
therefore different depending on their audience’s wealth. Let vj  V = {v1, v2, …, vj, …}
be the value of mj and V is assumed common and known to every satellite channel. On
the other hand, the ability of capturing the audience from mj is different for each satellite
channel. Let cij be the cost of satellite channel i to capture the audience from mj. A higher
cost cij indicates channel i has lower ability to capture audience from mj. The channels
originally have private information about their types but as they interact over time they
eventually learn about the types of others. Therefore I assume that cij is common
knowledge.
I express the profit potential ij from mj to satellite channel i as ij = ijvj – cij. The term
ij  [0,1] can be considered as channel i’s expectation of the fraction of mj that it can
capture. Similar to the cost structure, I assume the values of ij are commonly known due
to repeated interactions among the channels. Based on the expected profitability of the
markets and assuming the channels care about maximizing profits, each satellite channel
constructs its target market list, Ti  M, that yields the highest expected combined profit
for the channel. The degree of direct competition between satellite channel i and CCTV1
is reflected by the overlap of Ti and TCCTV1.
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I assume that each channel possesses competitive advantage over others in capturing
audience from its home-province market, i.e. cii < cji. The costs (production, marketing
research, promotion, etc.) associated with offering a television program tailored to a
province are likely lower for the home-province satellite channel than for those from
outside provinces. Given the competitive advantage at the home market, satellite channel
i will more likely to include its home market in Ti. This is especially likely if its home
market is of high v. On the other hand, conditioning on a satellite channel’s ability, a low
value home market will likely drive the channel to focus more on outside markets.
Imagine two satellite channels, A and B, of similar ability but A is based in a high value
home province while B is not. Compared to A, B has higher incentive to compete in
outside markets. Since CCTV1 targets the entire national television market, B is in
greater direct competition with CCTV1 than A. Given the satellite channels are strategic,
B should demonstrate greater responses to CCTV1 programming portfolio changes than
A.
Empirically, I use province-level GDP per capita to proxy for v. GDP per capita is a
frequently used, first-cut indicator of audience wealth in the advertising industry. Based
on the direct competition argument, I hypothesize that:
H3: Satellite channels based in high GDP per capita provinces respond less to
CCTV1 programming portfolio changes.
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Richard Wang
High-Low Ability Types
Besides home province market values, the degree to which a satellite responds to CCTV1
programming portfolio is also dependent on the satellite channel’s ability to capture
audience. Low type channels try harder to avoid direct competition with CCTV1 through
greater differentiation in their programming portfolio. However, directly measuring a
satellite channel’s ability, such as its cost structure, is difficult as cost data is sparse and
often unreliable. Instead, I construct a measure of home market audience dependency
based on ratings as a proxy for ability. Nevertheless, since the ratings of channel i in mj is
an endogenous outcome of target market strategies and abilities of all channels, this
proxy deserves further elaboration.
Imagine again two satellite channels, A and B. This time both are based in home province
markets of similar values but they are of different ability types. Let A be the high type
channel while B is the low type channel. Given their comparable home province market
values, they are similarly attracted to compete in outside markets but differentially
constrained by their types. When A and B are located in low GDP per capita provinces,
both are attracted to outside markets but A will have greater ability than B to capture
audience from outside provinces, which will be reflected in A’s ratings performance.
Therefore, conditioning on home province market GDP per capita, a high type channel
will have lower dependency on home province audience while a low type channel will
have high dependency. Based on the argument that low ability channels try harder to
differentiate from the dominant channel, I hypothesize that:
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Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
H4: Satellite channels based in lower GDP per capita provinces and have higher
dependency on home province audience respond greater to CCTV1
programming portfolio changes.
Niche Strategy
Continuing with the example, if A and B are both based in high GDP per capita provinces,
they do not face the economic pressure to compete in outside market as if they were
based in low GDP per capita home markets. They have the fortune of choosing between
focusing at home market – adopt a market segmentation strategy (Porter 1980) – or to
compete in outside markets. In this case, the dependency of audience from home
province reflects the channel’s choice of strategy rather than ability, with higher home
province audience dependency reflecting the channel’s pursuit of market segmentation
strategy.
Should a channel adopt the market segmentation strategy, it would tailor its programming
portfolio to suit the preference of the niche target audience and therefore be less sensitive
towards CCTV1 portfolio changes. I hypothesize that:
H5: Satellite channels based in higher GDP per capita provinces and have
higher dependency on home-province audience respond less to CCTV1
programming portfolio changes.
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Data, Measures, and Specifications
Datasets
I combine three dataset for the empirical analysis. The first dataset contains complete
daily programming lineups from 8am to midnight for 30 satellite channels (one for each
province except Tibet) and CCTV1 from May 2002 to May 2004. The dataset includes
the title of the show, the channel and date of broadcast, the start and end time of the show,
and the category to which the show is classified. Sample prime time programming
lineups for CCTV1, Hunan satellite channel and Shanghai satellite channel are provided
in Tables 3a to 3c. Note that, unlike television programming in the US, Chinese
television channels do not exactly follow hourly or half-hourly program slots. For
instance, between 9pm and 10pm, CCTV1 aired a news program from 21:00 to 21:20 and
a documentary from 21:24 to 21:53, while Shanghai satellite channel broadcasted a
drama from 21:15 to 21:53 followed by a music video from 21:53 to 21:59, and Hunan
satellite channel broadcasted a news program from 21:34 to 21:56 following an earlier
drama.
The second dataset contains 15-minute timeslot monthly average ratings of the 30
satellite channels in each of the 30 provincial capital cities. The programming line up and
ratings datasets are collected by CSM Market Research (CSM) using peoplemeter
panels.9 The ratings data are generated through stratified sampling drawn proportionally
to their incidence in the population. The CSM peoplemeter is an electronic device similar
to the ones used by Nielsen Media Research in the US. Attached to the television set, the
peoplemeter automatically records the minute-by-minute viewing behavior of each
9
CSM Media Research (www.csm.com.cn) is subsidiary of the TNS Group (http://www.tnsglobal.com).
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member in the household. These proprietary programming lineup and ratings datasets are
considered reliable and are widely used by Chinese television stations, advertisers and
regulators (Yuan and Webster 2006). The third dataset contains publicly available
information on GDP per capita of Chinese provinces in 2002.
Programming Portfolio Vector and Spatial Distance
I measure the spatial distance between two channels’ programming portfolio as the angle
between their program portfolio vectors in orthogonal dimensions of product space. This
measure is constructed similarly to the one used by Sweeting (2006) to study US radio
stations music play lists.
As a stylized example, let there be only two categories of television programs – sports
and drama. Say, in the 8:00pm to 8:15pm timeslot in January 2003 (total of 31days x
15min/day x 60sec/min = 27900 seconds of air time), Channel A broadcasted 9300
seconds of sports and 18600 seconds of drama while Channel B broadcasted 18600
seconds of sports and 9300 seconds of drama. The programming portfolio vectors for A
and B will be [9300 18600] and [18600 9300], respectively. Using vector dot products, I
calculate the angle between the two channels’ programming portfolio vectors. The angle
ranges from zero to 1.5708, or /2, radians. An angle of zero radians indicates that the
two channels broadcast exactly the same categories of shows, while an angle of 1.5708
radians indicates the two channels broadcast shows of completely different categories. In
this example, the angle between channel A and B is 0.6435 radians.
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CSM classified each program into one of 81 categories, such as domestic drama, foreign
movies, weather report, etc. The programming portfolio space is therefore 81dimensional. However, the dot product calculation of the angle between the portfolio
vectors and the interpretation of the radians are the same as the above stylized example.
Empirical Strategy
(1) Distributive Lag Models
I employ a distributive lag model (Equation 1) to test the baseline hypotheses:
Dijt =  +  Dijt-1 +  (Dijt- – Dijt-( +1)) + channel_fe + timeslot_fe
+ year-month_fe + ijt
Eq. 1
The dependent variable, Dijt, is the programming portfolio distance between satellite
channel i with respect to CCTV1 in timeslot j in year-month t. The total number of
observations in the dataset is 48,000 (30 satellite channels x 64 timeslots x 25 months).
Distributive lag model requires lag observations which is constructed using the earlier
portion of the panel dataset. Hence the actual number of observations available,
depending the length of lag chosen, is less than 48,000.
The key independent variables are the lag differences in spatial distance between a
satellite channel and CCTV1, Dijt- – Dijt-( +1). Should CCTV1 changes its programming
in a way such that it approaches a satellite channel, under differentiation strategy, the
satellite channel should move away from CCTV1 in subsequent periods. The one-month
lag distance variable (Dijt-1) captures the channels consistency over time about their
programming portfolios.
21
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
To test hypotheses 2-5, I include the interaction terms to the distributive lag model
(Equation 2).
Dijt =  + Dijt-1 + Dijt-1∙IndepVar + (Dijt- – Dijt-( +1))
+ (Dijt- – Dijt-( +1)) ∙ IndepVar + IndepVar
+ channel_fe + timeslot_fe + year-month_fe +ijt
Eq. 2
Three independent variables, pt, gdp and home, are interacted with the lagged spatial
terms. The dummy variable pt is set to one if timeslot j falls under prime time hours from
7pm to 11pm. The variable gdp measures the per capita GDP of the satellite channel’s
home province normalized by the national average. In the regressions, I used either gdp
or its logged value lgdp. The reason for using logged value is to alleviate potential
problems caused by the large disparities in GDP per capita between the provinces. At the
extreme ends, Shanghai’s GDP per capita is over 13 times greater than Guizhou’s.10
The variable home measures the channel’s dependency on home province audience in
each timeslot. To address endogeneity concerns, home is calculated by averaging the
home province audience ratings in each timeslot using only the first four months of the
dataset (i.e. the pre-sample portion of the dataset, from May 2002 to August 2002).
Summary statistics are presented in Table 4. Geographical illustrations of gdp and mean
values of home are presented in Figures 1 and 2.
10
In the US in 2006, the extreme GDP per capita states are Delaware and Mississippi, with the ratio
between them at 2.46 (or 5.17 if one compares Washington DC with Mississippi). In the European Union in
2007, the extremes are those from Luxembourg and Bulgaria, with the ratio of 6.85.
22
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Distributive lag models are commonly used to investigate how past events influence
current decisions or outcomes of firms (e.g. Pakes and Griliches, 1984). An advantage of
using such simple model is that it allows for events that happened multiple periods ago to
shape current outcomes, thus offering more insights on how time dependent decisions are
made. On the other hand, there are two issues of concern with this specification. By only
measuring a scalar distance between two channels, this specification will not be able to
capture programming changes that do not affect the distance. For example, if CCTV1
broadcasts news only in a timeslot while a satellite channel broadcasts sports only in the
first month but switches to drama only the next, the distance measure between the two
channels does not change. Fortunately, this specification offers a conservative
measurement of differentiation because any changes in distance will imply a change in
programming strategy by at least one channel. The second concern of using the proposed
specification is that it does not identify the causality of the channel positioning dynamics.
Specifically, the model is silent about whether the changes in distance between two
channels are caused by movements from which one. Therefore, an alternative
identification strategy is required to supplement the distributive lag model.
(2) CCTV1 Policy Change
To address the identification concern, I test further the baseline hypothesis by studying a
central government policy change that permitted CCTV1 to pursue a market-oriented
programming strategy.11 Under this new policy, CCTV1 in May 2003 revamped its
11
The CCTV1 policy change is a result of the macro reform plan on the Chinese cultural industry
announced by then Chinese President Jiang Zemin in his report given at the 16th Party Congress on
November 8 2002. The following is an excerpt of the official English translation of his report (People’s
Daily Online, Nov 18 2002): “It is necessary to push forward cultural restructuring in light of the
23
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
programming lineups by introducing television drama and entertainment shows in
multiple timeslots while preserving others, such as the 7:00pm national news
(xinwenlianbo). I identify satellite channels’ differentiation strategy by observing how
satellite channels responded to CCTV1 programming changes subsequent to this policy.
Conceptually, if the spatial location of CCTV1 programming approaches that of satellite
channel i in timeslot j, a subsequent change in programming by channel i in timeslot j in
such a way that their relative distance increases will lend support to the differentiation
hypothesis (see Figure 3).
As a concrete example, Figure 4 illustrates the programming portfolio distances between
each of the 30 satellite channels with respect to CCTV1 in the 10:00-10:15am timeslot.
Each small graph represents a satellite channel, with the y-axis indicating the distance
from CCTV1 in radians and the x-axis indicating year-month from May 2002 to May
2004. Prior to the policy change, CCTV1 broadcasted a general news program, “News at
10:00” (xinwen 10:00). On Thursday May 1 2003, the “News at 10:00” program was
replaced by a television drama. During the same period, several satellite stations were
broadcasting television dramas in the 10:00-10:15am timeslot. With CCTV1 replacing
the news program with a drama, the graphs indicate a discontinuous spatial distance drop
characteristics of the development of socialist spiritual civilization and laws governing it and in response
to the needs of the growing socialist market economy. We must lose no time in working out overall
planning for cultural restructuring. We must integrate the deepening of reform with structural adjustment
and promotion of development and straighten out the relationship between the government and cultural
enterprises and institutions. We must build up a legal system concerning culture and intensify macrocontrol. We should deepen the internal reform of cultural enterprises and institutions and gradually
establish a management system and operational mechanism favorable to arousing the initiative of cultural
workers, encouraging innovation and bringing forth more top-notch works and more outstanding personnel.
In compliance with the principle of both enriching culture and intensifying management, we should
improve the system of markets for cultural products and their management mechanism to create a social
climate favorable for a flourishing socialist culture.”
24
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
in May 2003 for those channels which also broadcasted drama. In subsequent months,
there is a trend showing that these channels migrated their programming portfolio away
from that of CCTV1.
I study the CCTV1 policy change using a diff-in-diff model (Equation 3).
Dijt =  + ∙Impactij ∙PostPolicyt ∙Trendt +∙Impactij ∙PostPolicyt ∙Trendt2
+ Impactij ∙PostPolicyt + PostPolicyt ∙Trendt + PostPolicyt ∙Trendt2
+ Trendt + Trendt2 + PostPolicyt  channel_fei + timeslot_fej + ijt
Eq. 3
The Impact dummy variable indicates whether CCTV1’s new programming location has
significantly approached that of satellite channel i in timeslot j. To assign Impact = 1, I
compared the average distance between CCTV1 and satellite channel i in timeslot j in the
three months after May 2003 with the average distance of the same from May 2002 to
April 2003. If the post policy distance is 3 standard deviations less than that of the pre
policy distance, then Impact is set to one, otherwise zero. I also repeat the test using 1 and
2 standard deviations as the definition for Impact. The variable Postpolicy is a dummy
which equals one for observations after May 2003 and zero otherwise. The Trend integer
variable ranges from 1 to 25 with May 2002 as month 1 and May 2004 as month 25. I
include also a quadratic term, Trend2, to accommodate for nonlinear responses over time.
The key independent variables are the interaction terms Impact ∙PostPolicy ∙Trend and
Impact ∙PostPolicy ∙Trend2. If satellite channels differentiate from CCTV1, the coefficient
for Impact ∙PostPolicy ∙Trend should be positive. As for the Impact ∙PostPolicy ∙Trend2
coefficient, I expect it to be negative as the new distances between the satellite channels
and CCTV1 stabilize over time.
25
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Results
Baseline Results
(1) Distributive Lag Model
The result for testing the baseline hypothesis is summarized in Table 5. The regression
results confirm that satellite channels adjust the spatial distance between their own
portfolios with CCTV1’s. The negative coefficients indicate that the distance between a
satellite channel and CCTV1 will increase if it has experienced a decrease in previous
months.
I include in the model lag variables ranging from one to four months. The satellite
channels respond over a period of about 3 months, indicating that portfolio adjustments
take place over time instead of instantaneously. Since CCTV1’s movements over four
months ago seem to have no effect on the satellite channels, I will use a 3-month window
in subsequent regression models. The Durbin-Watson statistics are around 2, indicating
that serial correlation problem is not significant. To address the concern that
programming in one timeslot is closely related to the adjacent ones, I ran the regression
with sub-samples of the data using only one timeslot in each hour. Table 6 presents the
regression outputs generated by different sub-samples. They are qualitatively similar to
the full sample analysis results.
(2) CCTV1 Policy Change
The results for the diff-in-diff model are presented in Table 7. Consistent with the
differentiation prediction, the coefficients for Impact ∙PostPolicy ∙Trend and Impact
26
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
∙PostPolicy ∙Trend2 terms are positive and negative, respectively. Using one standard
deviation as the impact definition, both coefficients are statistically significant at the 1
percent level. When using two and three standard deviations for the impact definition, the
signs of the coefficients remain steady but the level of significance decreases. Overall,
the diff-in-diff regression results are consistent with the ones generated by the distributive
lag model. Moreover, the diff-in-diff results confirmed the causality of the differentiation
process between CCTV1 and the satellite channels.
Other Results
With the baseline hypothesis identified, I test Hypotheses 2 to 5 using the distributive lag
model. The results are as follows.
Market Demand Conditions (H2): The results in Table 8 show that satellite channels are
more responsive to CCTV1’s programming changes in prime time hours. Compared to
the baseline results, the satellite channels respond with a greater magnitude during prime
time. This is particularly the case in the first month subsequent to CCTV1 programming
changes. Their longer-term lagged responses (two to three months subsequent to CCTV1
programming changes) are not significantly different from those of the baseline results.
Direct Competitions (H3): Recall that a lower home province market value will more
likely induce a satellite channel to seek outside markets. This in turn places the satellite
channel in greater direct competition with CCTV1. Under direct competition, a channel
should demonstrate higher responsiveness to CCTV1 programming changes. The results
27
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
in Table 9 show the effect of home province GDP per capita on a satellite channel’s
response to CCTV1 programming changes. Column (2) employs per capita GDP
normalized by the national average while Column (3) employs the logged value of the
normalized GDP per capita. Both sets of results show that channels with higher home
market values respond less to CCTV1. When logged normalized GDP per capita was
used, though the coefficient for the first month response was not statistically significant at
10 percent level, it has the predicted sign.
Ability Types (H4): Lower ability satellite channels try harder to avoid direct competition
with CCTV1 and therefore should differentiate more responsively. These lower ability
channels are identified by their high dependencies on home market audience in the presample period. This is especially the case for those channels based in low GDP per capita
provinces which give them stronger incentives to compete in outside provinces. Column
(2) in Table 10 shows that under general conditions, satellite channel timeslots with
higher dependencies on home market audience respond greater to CCTV1 programming
changes. Column (3) further separates the channel timeslots by interacting home market
audience share with home province GDP per capita. Satellite channels based in low
economic value home markets clearly respond more to CCTV1 changes (e.g. coefficient
for the home_cctv1_12 changed from -0.102 to -0.285). The results remain qualitatively
unchanged when I used logged values of GDP per capita in column (4).
Niche Strategy (H5): When a satellite channel adopts a niche strategy, it should
demonstrate little response to CCTV1 programming changes. Channels based in high
28
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
value home markets have greater incentive to pursue a niche strategy and their
dependency on home market audience will reflect their strategy choice. In column (3) of
Table 10, the coefficient of gdp_home_cctv1_12 is positive and significant, indicating
that channels based in high GDP per capita provinces with high dependency on home
province market audience respond less to CCTV1 changes. Although the coefficients for
gdp_home_cctv1_23 and gdp_home_cctv1_34 are negative, they are statistically
insignificant. The results are stronger when I used logged values of GDP per capita in
column (4).
Concluding Remarks
An important goal set by the Chinese government for market reform is to have SOEs
adopt scientific management practices. In this study, I investigate whether the reform has
led state-owned satellite television channels to implement market competitive strategy. I
find the satellite channels execute spatial differentiation strategy with respect to their
common dominant competitor, CCTV1, as firms in market economies would do under a
DFCF industry structure. Moreover, channels exhibit sensitivities to market demand
variations when implementing their strategies. Channels that compete more directly with
CCTV1 for national audience demonstrate greater strategic responses. In addition,
satellite channels are also aware of their own abilities when choosing and executing their
strategies. The overall behavior of the satellite channels offer coherent supports that they
are competing strategically.
29
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
A drawback of this study is the lack of comparison with privately-owned television
channels. The absence of private operators in the Chinese television broadcasting
industry prohibits this study to compare competitive strategies of the state-owned
channels with those of privately-owned ones. Similarly, benchmarking of state-owned
channels’ ratings and financial performances with those of private ones is not possible.
On the other hand, the absence of private channels in the empirical setting demonstrates
that competitions need not originate from private firms but can come from other SOEs.
This speaks to the policy argument on opening up markets to private competitions,
especially when the government is hesitant to involve non-state participants in industries
of strategic importance.
Another policy question is the welfare implications of strategic behaviors by SOEs. On
one hand, the government desires SOE to be strategically competitive under the postWTO accession era. On the other hand, the execution of competitive strategies could
potentially lower welfare. For instance, under strategic entry deterrence situations the
incumbent firms may build excess capacities (Dixit, 1979), set predatory prices (Milgrom
and Roberts, 1982), or deviate from optimal product diversification (Dixit and Stiglitz,
1977), thus causing harm to social welfare.
The empirical findings in this study may shed light on SOE competitions in other Chinese
industries. With improvements in transportation and communication infrastructures,
many SOEs are competing with one another in the national market. Like the television
channels, SOEs are often heterogeneous in terms of resources. For example, the Chinese
30
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
state-owned commercial airline industry consists of three key aviation enterprise groups –
Air China, China Eastern Airlines and China Southern Airlines – along with a dozen of
smaller regional airlines such as Hainan Airlines and Shanghai Airlines. They compete
for domestic air travelers. Analogous to the CCTV - satellite channel relationship, there
exist significant resource heterogeneity between the three key airlines operating under the
central government umbrella and the fringe airlines supported mainly by province-level
governments (Fernandez and Fernandez-Stembridge, 2007).
For private firms operating in China, understanding SOE competitive strategy is essential
since many key industries are occupied by incumbent SOEs (Nolan, 2001). The failure of
multinational oil companies like Exxon and BP in competing with the two SOE oil
industry groups – China National Petroleum Corporation and China Petroleum Group –
for the Chinese petroleum market is a classic example (Peng, 2000).
Finally, after thirty years of SOE reform, the Chinese government continues to search for
policy directions. A Wall Street Journal article in January 2008 wrote, “fundamental
differences are emerging within the Chinese government about how best to modernize a
key industry.”12 The diversity of China’s industries and the pace at which the country is
changing offer a fertile field for business strategy and government policy research.
12
“Government Divided Over Air China”, Wall Street Journal, January 9, 2008.
31
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
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Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 1 Satellite Television Household Coverage
Year
2002
2003
2004
2005
National Household Coverage (percent)
Urban
Rural
89
40.2
89.2
42.1
89.5
58.1
89.6
71.8
Source: 2006 China TV Rating Yearbook
Table 2 Audience Market Shares (%)
Channels
All CCTV Channels
Provincial Satellite
Others*
2002
Year
2003
2004
31.9
14.7
53.4
32.2
16.0
51.8
33.4
16.7
49.7
Source: 2006 China TV Rating Yearbook, p.227.
* Others include province-level non-satellite channels, city- and township-level channels, and education
channels.
36
Competitive Strategy of Chinese State-Owned Enterprises
Table 3a Sample CCTV1 Prime Time Programming Lineup
Wednesday January 15 2003 7:00pm – 11:00pm
Title
Start
End
Category
National News
19:00:00
19:30:00
General News
Commercials
19:30:00
19:31:05
Commercials
Weather Forecast
19:31:05
19:35:20
Weather Forecast
Commercials
19:35:20
19:38:50
Commercials
Jiaodian Interview
19:38:50
19:50:50
News Commentary
Commercials
19:50:50
19:57:40
Commercials
Technology Expo
19:57:40
20:02:10
General Science
Commercials
20:02:10
20:04:00
Commercials
Da Shi
20:04:00
20:54:02
Domestic Drama
Commercials
20:54:02
21:00:05
Commercials
Xianzaibobao
21:00:05
21:20:00
General News
Commercials
21:20:00
21:22:45
Commercials
Program Guide
21:22:45
21:23:45
Program Guide
Commercials
21:23:45
21:24:20
Commercials
Around the World
21:24:20
21:53:45
Documentary Others
Program Guide
21:53:45
21:54:45
Program Guide
Commercials
21:54:45
22:00:00
Commercials
World Report
22:00:00
22:17:00
General News
Commercials
22:17:00
22:20:00
Commercials
Nightly News
22:20:00
22:30:00
General News
Commercials
22:30:00
22:32:00
Commercials
Sports News
22:32:00
22:42:00
Sports News
Commercials
22:42:00
22:47:00
Commercials
Weather Forecast
22:47:00
22:52:00
Weather Forecast
Commercials
22:52:00
22:56:00
Commercials
Program Guide
22:56:00
22:57:00
Program Guide
37
Richard Wang
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 3b Sample Hunan Satellite Channel Prime Time Programming Lineup
Wednesday January 15 2003 7:00pm – 11:00pm
Title
Start
End
Category
National News
19:00:00
19:30:00
General News
Commercials
19:30:00
19:33:00
Commercials
2003 NPC &CPPCC Conference
19:33:00
19:38:04
News Commentary
Commercials
19:38:04
19:42:18
Commercials
Qinshenshen Yumengmeng
19:42:18
20:35:35
Domestic Drama
Commercials
20:35:35
20:40:29
Commercials
Qinshenshen Yumengmeng
20:40:29
21:29:01
Domestic Drama
Commercials
21:29:01
21:34:49
Commercials
Nightly News
21:34:49
21:56:00
General News
Xindongli Xinfazhan
21:56:00
22:10:59
Interview
Commercials
22:10:59
22:15:16
Commercials
Weather Station
22:15:16
22:17:46
Weather Forecast
Commercials
22:17:46
22:18:54
Commercials
Heibing
22:18:54
23:15:45
Domestic Drama
Table 3c Sample Shanghai Satellite Channel Prime Time Programming Lineup
Wednesday January 15 2003 7:00pm – 11:00pm
Title
Start
End
Category
Nightly Sports News
19:00:00
19:30:00
Sports News
Commercials
19:30:00
19:33:00
Commercials
Renzai Shanghai
19:33:00
19:57:00
Documentary
Commercials
19:57:00
20:00:00
Commercials
Shanghai Satellite Channel News
20:00:00
20:27:50
General News
Commercials
20:27:50
20:28:20
Commercials
Weather Forecast
20:28:20
20:30:00
Weather Forecast
Commercials
20:30:00
20:34:25
Commercials
Dafuqingzhai
20:34:25
21:13:10
Domestic Drama
Commercials
21:13:10
21:15:45
Commercials
Dafuqingzhai
21:15:45
21:53:45
Domestic Drama
Song of the Week
21:53:45
21:59:00
Music Others
News At Ten
21:59:00
22:23:02
Foreign Language News
Commercials
22:23:02
22:26:01
Commercials
Weather Forecast
22:26:01
22:27:00
Weather Forecast
Commercials
22:27:00
22:30:00
Commercials
Nightline News
22:30:00
23:09:27
General News
* Note: The original dataset contains title and category data in Chinese. The author translated the data into English.
38
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 4 Summary Statistics
Obs
Mean
Std. Dev.
Min
Max
10%
25%
50%
75%
90%
# of
Unique
Values
Distance between cctv1 and satellite
channel i in timeslot j in year-month t
48000
1.2071
0.4764
0
1.5708
.3565
.9746
1.4559
1.5669
1.5708
37372
cctv1_1
One month lag of cctv1
46080
1.2101
0.4741
0.0000
1.5708
0.3656
0.9817
1.4576
1.5669
1.5708
35937
cctv1_12
Difference in cctv1 between
year-month t-1 and t-2
44160
-0.0033
0.2322
-1.5523
1.5708
-0.1862
-0.0358
0.0000
0.0394
0.1921
38135
cctv1_23
Difference in cctv1 between
year-month t-2 and t-3
42240
-0.0032
0.2355
-1.5523
1.5708
-0.1879
-0.0366
0.0000
0.0401
0.1979
36468
cctv1_34
Difference in cctv1 between
year-month t-3 and t-4
40320
-0.0036
0.2370
-1.5523
1.5708
-0.1919
-0.0364
0.0000
0.0414
0.2006
34774
pt
Prime Time Timeslots Dummy
(pt = 1 if timeslot j falls in 7:00pm –
11:00pm; 0 otherwise)
48000
0.2500
0.4330
0
1
-
-
-
-
-
2
gdp
2002 Provincial Per Capita GDP
divided by National Average Per
Capita GDP
48000
1.5604
1.2898
0.4602
6.0951
0.7308
0.8569
1.0699
1.7459
3.0035
30
lgdp
Log of gdp
48000
0.2292
0.5976
-0.7761
1.8075
-0.3139
-0.1545
0.0675
0.5572
1.0909
30
home
Average ratio of home market
audience to total audience received by
satellite channel i in timeslot j; Data
taken in pre-sample period from May
to August 2002
48000
0.3075
0.2374
0.0000
0.9833
0.0603
0.1178
0.2273
0.4638
0.6741
1918
Variable
Description
Dep. Variable
cctv1
Indep. Variables
39
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 5 Baseline Differentiation Strategy (OLS)
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
cctv1_12
(1)
(2)
(3)
(4)
-0.122***
(0.010)
-0.148***
(0.011)
-0.101***
(0.008)
-0.164***
(0.012)
-0.122***
(0.011)
-0.048***
(0.009)
0.824***
(0.009)
0.223***
(0.019)
44160
0.805
1.975
0.836***
(0.008)
0.255***
(0.019)
42240
0.805
1.906
0.851***
(0.008)
0.204***
(0.017)
40320
0.811
1.980
-0.175***
(0.014)
-0.123***
(0.013)
-0.048***
(0.011)
0.010
(0.010)
0.844***
(0.009)
0.214***
(0.019)
38400
0.808
1.898
cctv1_23
cctv1_34
cctv1_45
cctv1_1
Constant
Observations
R-squared
Durbin-Watson
All regressions include channel fixed effects, timeslot fixed effects, and year-month fixed effects.
Robust standard errors in parentheses; SE clustered by channels.
* significant at 10%; ** significant at 5%; *** significant at 1%
Table 6 Baseline Differentiation Strategy (Sub-Sampling Timeslot by Quarter Hour)
(1) Baseline result (Column (3) of Table 1-1).
(2) Data from top of hour timeslots (quarter=1)
(3) Data from 2nd quarter of hour timeslots (quarter=2)
(4) Data from 3rd quarter of hour timeslots (quarter=3)
(5) Data from bottom of hour timeslots (quarter=4)
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
cctv1_12
cctv1_23
cctv1_34
(1)
(2)
(3)
(4)
(5)
-0.164***
(0.012)
-0.122***
(0.011)
-0.048***
(0.009)
-0.180***
(0.023)
-0.107***
(0.018)
-0.084***
(0.017)
0.032**
(0.014)
0.874***
(0.009)
0.180***
(0.018)
9600
0.850
-0.153***
(0.012)
-0.145***
(0.014)
-0.051***
(0.012)
-0.007
(0.013)
0.842***
(0.014)
0.232***
(0.021)
9600
0.840
-0.165***
(0.017)
-0.140***
(0.013)
-0.034**
(0.015)
0.009
(0.012)
0.817***
(0.011)
0.272***
(0.019)
9600
0.743
-0.178***
(0.021)
-0.076***
(0.020)
-0.011
(0.017)
0.019
(0.016)
0.815***
(0.021)
0.084***
(0.015)
9600
0.762
cctv1_45
cctv1_1
Constant
Observations
R-squared
0.851***
(0.008)
0.204***
(0.017)
40320
0.811
All regressions include channel fixed effects, timeslot fixed effects, and year-month fixed effects.
Robust standard errors in parentheses; SE clustered by channels.
* significant at 10%; ** significant at 5%; *** significant at 1%
40
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 7 Baseline Differentiation Strategy (Diff-in-Diff)
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
(1)
i01pt
i01pt2
(2)
0.086***
(0.019)
-0.002***
(0.000)
i02pt
0.065***
(0.022)
-0.001**
(0.001)
i02pt2
i03pt
0.066**
(0.029)
-0.002*
(0.001)
i03pt2
i01p
-1.330***
(0.173)
i02p
-1.128***
(0.195)
i03p
trend
trend2
postpolicy
pt
pt2
constant
Observations
R-squared
(3)
0.024***
(0.003)
-0.002***
(0.000)
0.341***
(0.076)
-0.045***
(0.008)
0.003***
(0.000)
1.245***
(0.075)
48000
0.519
0.024***
(0.003)
-0.002***
(0.000)
0.174**
(0.067)
-0.033***
(0.007)
0.002***
(0.000)
1.258***
(0.075)
48000
0.508
-1.062***
(0.270)
0.024***
(0.003)
-0.002***
(0.000)
0.085
(0.073)
-0.028***
(0.008)
0.002***
(0.000)
1.280***
(0.075)
48000
0.492
All regressions include channel fixed effects and timeslot fixed effects fixed effects.
Robust standard errors in parentheses; SE clustered by channels
* significant at 10%; ** significant at 5%; *** significant at 1%
i01
dummy=1 when impact above 1SD for the channel_timeslot
i02
dummy=1 when impact above 2SD for the channel_timeslot
i03
dummy=1 when impact above 3SD for the channel_timeslot
p, postpolicy dummy=1 when year-month is after May 2003, indicating post-policy
t, trend
time trend integer with May 2002 as 1 and May 2004 as 25
t2, trend2
square of t
41
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 8 Sensitivity to Prime Time Market Demand Conditions
For comparison, column (1) is the baseline result (Column (3) of Table 1-1).
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
cctv1_12
cctv1_23
cctv1_34
(1)
(2)
-0.164***
(0.012)
-0.122***
(0.011)
-0.048***
(0.009)
-0.118***
(0.015)
-0.119***
(0.013)
-0.044***
(0.014)
-0.146***
(0.023)
-0.027
(0.019)
-0.017
(0.020)
0.855***
(0.009)
-0.187***
(0.018)
-0.013
(0.016)
0.197***
(0.018)
40320
0.812
pt_cctv1_12
pt_cctv1_23
pt_cctv1_34
cctv1_1
0.851***
(0.008)
pt
pt_cctv1_1
Constant
Observations
R-squared
0.204***
(0.017)
40320
0.811
All regressions include channel fixed effects, timeslot fixed effects, and year-month fixed effects.
Robust standard errors in parentheses; SE clustered by channels.
* significant at 10%; ** significant at 5%; *** significant at 1%
42
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 9 Sensitivity to Direct Competition with CCTV1
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
(1)
(2)
(3)
Baseline regression results for comparison (Hypothesis 1)
Effect of home province GDP per capita (H3: Direct Competition Hypothesis)
Similar to (2) but employ Log GDP per capita
cctv1_12
cctv1_23
cctv1_34
(1)
(2)
(3)
-0.164***
(0.012)
-0.122***
(0.011)
-0.048***
(0.009)
-0.200***
(0.017)
-0.152***
(0.011)
-0.070***
(0.014)
0.023**
(0.009)
0.018***
(0.006)
0.013***
(0.004)
-0.172***
(0.011)
-0.132***
(0.010)
-0.056***
(0.010)
gdp_cctv1_12
gdp_cctv1_23
gdp_cctv1_34
lgdp_cctv1_12
lgdp_cctv1_23
lgdp_cctv1_34
cctv1_1
0.851***
(0.008)
gdp_cctv1_1
0.844***
(0.010)
0.004
(0.003)
lgdp_cctv1_1
Constant
Observations
R-squared
0.204***
(0.017)
40320
0.811
0.208***
(0.018)
40320
0.812
0.037
(0.024)
0.041**
(0.016)
0.030**
(0.012)
0.848***
(0.008)
0.011*
(0.006)
0.211***
(0.018)
40320
0.812
All regressions include channel fixed effects, timeslot fixed effects, and year-month fixed effects.
Robust standard errors in parentheses; SE clustered by channels.
* significant at 10%; ** significant at 5%; *** significant at 1%
Note: Full data sample from May 2002 – May 2004; Data from May 2002 – August 2002 are used to construct the presample “homeshare” data; Data from September 2002 – May 2004 are used in the regressions: (30channels x
64timeslots x 21months = 40,320obs)
43
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Table 10 Ability Types and Niche Strategy
Dependent Variable: Distance in radians between satellite channel i w.r.t. to CCTV1 in timeslot j in month t.
cctv1_12
cctv1_23
cctv1_34
(1)
(2)
(3)
(4)
-0.164***
(0.012)
-0.122***
(0.011)
-0.048***
(0.009)
-0.132***
(0.015)
-0.126***
(0.018)
-0.055***
(0.018)
-0.102*
(0.058)
0.017
(0.050)
0.027
(0.047)
-0.118***
(0.023)
-0.172***
(0.034)
-0.072**
(0.034)
-0.285***
(0.076)
0.017
(0.078)
-0.001
(0.077)
0.073**
(0.031)
-0.046
(0.042)
-0.008
(0.035)
-0.001
(0.013)
0.045*
(0.024)
0.019
(0.018)
-0.117***
(0.015)
-0.121***
(0.019)
-0.051**
(0.019)
-0.218***
(0.057)
-0.041
(0.049)
-0.016
(0.052)
home_cctv1_12
home_cctv1_23
home_cctv1_34
gdp_home_cctv1_12
gdp_home_cctv1_23
gdp_home_cctv1_34
gdp_cctv1_12
gdp_cctv1_23
gdp_cctv1_34
lgdp_home_cctv1_12
lgdp_home_cctv1_23
lgdp_home_cctv1_34
lgdp_cctv1_12
lgdp_cctv1_23
lgdp_cctv1_34
home
-0.044*
(0.024)
gdp_home
Constant
Observations
R-squared
0.204***
(0.017)
40320
0.811
0.220***
(0.015)
40320
0.811
-0.043
(0.032)
-0.002
(0.014)
0.220***
(0.017)
40320
0.812
0.218***
(0.077)
-0.019
(0.080)
0.015
(0.069)
-0.028
(0.026)
0.056
(0.041)
0.025
(0.032)
-0.040
(0.027)
-0.008
(0.025)
0.220***
(0.017)
40320
0.812
All regressions include channel fixed effects, timeslot fixed effects, and year-month fixed effects.
Robust standard errors in parentheses; SE clustered by channels.
* significant at 10%; ** significant at 5%; *** significant at 1%
Note: Full data sample from May 2002 – May 2004; Data from May 2002 – August 2002 are used to construct the presample homeshare (home) data; Data from September 2002 – May 2004 are used in the regressions: (30channels x
64timeslots x 21months = 40,320 obs)
44
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Figure 1 GDP Per Capita Distribution of Chinese Provinces 2002
Figure 2 Mean Ratings Dependency on Home Province Market Audience MayAugust 2002
45
Competitive Strategy of Chinese State-Owned Enterprises
Richard Wang
Figure 3 CCTV1 Policy Change Setting
Spatial Distance between CCTV1 and
Satellite Channel i in timeslot j
Year-Month
Graphical illustration of baseline hypothesis (H1). The vertical axis represents the distance between a
satellite channel and CCTV1. The horizontal axis represents time (between May 2002 – May 2005). The
vertical dotted line marks the CCTV1 policy shift in May 2003.
Figure 4 CCTV1 Policy Change at the 10:00-10:15am Timeslot
46