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An Online Advertising Model: Comparing China and the U.S.
Ying Wang
&
Shaojing Sun
Ying Wang (Ph.D., Kent State University) is an Assistant Professor in the Williamson College of
Business Administration at Youngstown State University. Shaojing Sun (Ph.D., Kent State
University; Ph.D., University of Virginia) is an Associate professor in the School of Journalism
at Fudan University, Shanghai, P. R. China.
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) 941-1871. E-mail: ywang01@ysu.edu
April 1, 2009
Paper submitted to Cheung Kong GSB Marketing Research Forum
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An Online Advertising Model: Comparing China and the U.S.
Introduction
The Internet is ushering in a new age of advertising which has drawn attention from both
researchers and professionals. A hot button topic over the last few years has been consumers’
beliefs and attitudes toward online advertising. A host of studies (e.g., Ducoffe, 1996; Russell,
Staffaroni and Fox, 1994) have suggested that individuals’ attitudes toward online advertising
(ATOA) is an important measure of advertising effectiveness. Past research of online advertising
has provided insight into global marketing and commerce. However, the focus of most studies
have been in the U.S. or other developed countries. Little is known about online advertising in
developing countries such as China.
The goal of the current study is to investigate online advertising across different cultures
such as China and the United States. Scholars and practitioners alike have explored the
relationship between culture and advertising extensively in the traditional media environment,
but rarely do so in the online context. Nonetheless, as Roberts and Ko (2001) stressed, cultural
differences and adaptations are as relevant to online advertising as to traditional advertising.
Moreover, the Internet affords companies of different sizes nearly equal opportunities to present
themselves globally, and hence examining the role of culture in online advertising may provide
useful implications about expanding business across nations.
There are two major objectives of this study: first, the study attempts to model the
relationships among three groups of factors including beliefs about online advertising, ATOA,
and online advertising outcomes; second, the study seeks to explore the influence of culture on
the aforementioned three factors. China and the U.S. are the two nations chosen for crosscultural comparison because China represents a typical Eastern culture that is experiencing rapid
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economic growth and sociocultural transition, whereas the U.S. signifies a typical Western
culture. The great cultural distance between the two renders a meaningful comparison to examine
the impact of culture on online advertising.
It is of both theoretical and practical significance to inspect online advertising in China
and U.S. On one hand, the study can shed light on the links among consumers’ beliefs, attitudes,
and consumer responses, and how such relationships hold or vary across different cultures. On
the other hand, China is a booming emerging market. The study may enhance marketing
professionals’ understanding of online advertising audiences in China, and thus help businesses
and organizations employ online advertising more effectively and efficiently in their global
marketing endeavors.
This article is organized in the following manner: first, the authors review relevant
literature on consumers’ beliefs, attitudes, and consumer behavioral responses, as well as a brief
introduction to the Chinese and American cultures; second, based on the literature review, we
propose research questions and hypotheses and use structural equation modeling to dissect the
relationships among culture, individuals’ beliefs, attitudes and consumer responses; third, we
present significant research findings and discuss implications of those findings; finally, we
address limitations and future research directions.
Literature Review
Beliefs about Online Advertising
Consumers’ beliefs and attitudes toward advertising are important indicators of
advertising effectiveness (Mehta, 2000). To date, there exist two typical views about the
relationship between consumers’ beliefs and their general attitudes toward advertising. The first
treats the two constructs as equivalent and interchangeable both conceptually and operationally
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(Mehta, 2000; Schlosser and Shavitt, 1999), whereas the second postulates that one’s beliefs
about advertising are antecedents of attitude toward advertising (Brackett and Carr, 2001;
Ducoffe, 1996; Pollay and Mittal, 1993). In the later research on the subject, the second
perspective seems to be gaining popularity. Pollay and Mittal (1993), for example, argued that
beliefs are specific statements about the attributes of objects and attitudes are summative
evaluations of objects. Emanating from beliefs, attitudes operate at different levels of cognitive
abstraction. Specifically, ATOA is the aggregation of weighted evaluations of perceived
attributes and consequences of products (Brackett and Carr, 2001).
Consistently, researchers have argued that ATOA has both cognitive and affective
antecedents (Ducoffe, 1996; Shimp, 1981). Belief about advertising, as a result of the benefit and
cost that consumers derive from advertising, primarily serves as a cognitive predictor of ATOA.
Moreover, one’s belief plays a more important role in forming ATOA when the person is
engaged in centrally processing (i.e., more deliberate, effortful and thoughtful) advertising
information than in peripheral processing (low involvement, less thoughtful, and more
emotional) (Petty and Cacioppo, 1986).
Prior studies have demonstrated that one’s belief about advertising is a multidimensional
construct. For instance, Bauer and Greyser (1968) identified two dimensions underlying
consumers’ beliefs: economic and social. Later on, Pollay and Mittal’s model (1993) presented
seven belief factors underlying consumers’ beliefs, and classified those factors into two
categories. The first category, labeled as personal use, consists of factors including product
information, social role and image, and hedonic/pleasure. The second category, labeled as social
effect, includes value corruption, falsity/no sense, good for the economy, and materialism.
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Among the seven factors, product information describes advertising’s role as an
important information purveyor, which contributes to marketplace efficiencies. Social role and
image reflects the belief that advertising influences people’s lifestyle and formation of social
status and image. Hedonic/pleasure refers to the view that advertising can be fun, pleasant and
entertaining. Good for the economy reflects the viewpoint that advertising accelerates
consumers’ adoption of new goods and technologies, fosters full employment, lowers the
average cost of production, promotes healthy competition between producers, and raises the
average standard of living (e.g., Belch and Belch, 2007). Notwithstanding its benefits for
consumers and the whole society, advertising is often criticized for promoting materialism,
corrupting values, and misleading audiences. Particularly, advertising is accused of providing
people with unending razzle-dazzle of high-end products and preoccupying consumers with
commercial concerns at the expense of social, political, philosophical, and cultural scruples. As a
carrier of cultural and social values, advertising can contradict or even compromise the values
that a society cherishes.
Attitudes toward Online Advertising
Research on attitudes toward advertising generally falls into two avenues. Along the first
line, scholars examine attitudes toward a particular advertising stimulus and how they
correspondingly influence consumers’ brand preferences and, ultimately, purchase intention
(e.g., Gong and Maddox, 2003). Along the second line, scholars investigate the impact of
consumers’ general beliefs and attitudes toward advertising effectiveness (e.g., MacKenzie, Lutz
and Belch, 1986; Muehling, 1987). It is argued that consumer behavior such as advertisement
avoidance may be a result of consumers’ general negative attitudes toward advertising (e.g., Li et
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al., 2002). The present study focuses on consumer’s general beliefs and attitudes toward online
advertising.
As stated earlier, attitude toward advertising is shaped or molded by consumers’ beliefs.
Furthermore, previous research has documented that attitude toward advertising affects
consumers’ attitudes toward brands and sales responses (Mitchell and Olson, 1981). Mehta
(2000), for example, found that consumers with a more favorable attitude toward advertising
were more likely to be persuaded by advertising.
Online Behaviors
Ad clicking or clickthrough (the number of times that a banner ad is clicked upon) is an
important measure of evaluating the effectiveness of online advertising (Dreze and Zufryden,
1997). Compared with another commonly used measure, ad impression, ad clicking is viewed to
be more relevant and performance-based (The Economist, 2001). In Gong and Maddox’s (2003)
study, ad clicking was a significant predictor for advertising recall among Chinese Internet users.
Wolin, Korgaonkar, and Lund (2002) also included ad clicking as one of the main online
advertising behaviors. Therefore, in this study, we use ad clicking as one of the behavioral
outcomes of online advertising. Another behavioral variable to be examined is prior online
shopping experience.
Links among Beliefs, Attitudes, and Behaviors
As discussed before, one’s belief about advertising is regarded as an antecedent of
ATOA. Ducoffe (1996), for example, found that informativeness and entertainment were
positively related to ATOA, whereas irritation was negatively related to advertising value. Wolin
et al. (2002) tested Pollay and Mittal’s (1993) belief model and showed that several belief factors
influenced Web users’ attitudes toward online advertising which in turn had an impact on users’
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behavioral intention. They found belief factors, such as product information, hedonic pleasure,
and social role and image, were positively related to ATOA, whereas materialism, falsity/no
sense and value corruption were negatively associated with ATOA. In addition, the more
positive attitudes one held toward online advertising, the greater the likelihood that person would
respond favorably to Web ads.
Research has supported that beliefs and attitudes are precursors of consumers’ responses
toward online advertising and their online shopping behavior. Karson, McCloy, and Bonner
(2006) segmented consumers into Pro, Ambivalent, and Critics groups based on their ATOA.
They found that critics tended to use the Internet less often for information search and to view
the Internet as less utilitarian and hedonic than the other two groups did. Similarly, Korgaonkar
and Wolin (2002) found that a positive attitude toward online advertising is more likely to result
in frequent online purchasing and high online spending.
Above, the literature suggests that beliefs about online advertising have an impact on
consumers’ ATOA, which in turn influences consumers’ purchase intention and behavior. Such
an argument echoes with Lavidge and Steiner’s (1961) conceptual model, indicating that one’s
belief is a precursor of attitude, which by default is an antecedent of behavior.
Culture and Online Advertising
Culture and advertising are intrinsically linked to each other. Hall (1976) defined culture
as “the way of life of people, for the sum of their learned behavior patterns, attitudes, and
material things” (p. 20). The effects of advertising on society and culture have been extensively
examined by scholars from various disciplines. International marketing researchers and
practitioners, however, have demonstrated special interest in how culture influences advertising.
The long-standing debate of standardization vs. specialization reflects two main views on the
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issue. On the one hand, it is argued that, with the emergence of a global marketplace, consumers
around the globe have become more homogenized and thus can be satisfied with similar products
and advertising messages. To that end, a standardized advertising strategy should be effective
and efficient. On the other hand, proponents of specialization contend that consumers’ cultural
background has a profound impact on their attitudes and beliefs, which in turn influence how
they respond and/or interpret advertising messages and, accordingly, their purchasing behavior.
Therefore, advertisers must consider cultural differences when marketing goods and services
across cultures and tailor their strategies and messages to local markets.
A large amount of empirical research has lent support to the specialization school of
thought. Frith and Sengupta (1997) reported significant differences in magazine advertisements
across the U.S., the United Kingdom, and India. They asserted that consumers’ cultural values
may temper the influence of international marketing. Belk and Pollay (1985) reported that
although Americanization was clearly increasing in Japanese advertisements, deep-seated
Japanese cultural values remained strong in those messages. Mueller (1992) studied advertising
appeals used in Japanese and U.S. magazines, and concluded that Japanese advertising may be
becoming increasingly Japanese-culture-oriented instead of being westernized.
Attitude toward advertising has also been examined in a cross-cultural context. For
example, Durvasula and Lysonski (2001) systematically compared consumers’ attitudes toward
advertising in five countries located on four different continents, and deduced that beliefs toward
advertising vary across culture in general. Another study showed that cultural values did have a
strong influence on attitudes toward advertising appeals (Rustogi, Hensel and Burgers, 1996). In
a recent study, La Ferla, Edwards and Lee (2008) examined attitudes toward advertising across
China, Taiwan, and the United States. They found that Chinese and Taiwanese exhibited more
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favorable attitudes toward advertising than did American consumers. Extending this line of
research into the online advertising environment, the present study focuses on how two cultures,
China and the U.S., influence consumers’ ATOA.
China. Over the past decade, China has witnessed the most energizing and skyrocketing
economic growth in history. Its entry into the World Trade Organization (WTO) has facilitated
its convergence with the global economy, including rapid diffusion of Internet technologies.
According to the China Internet Network Information Center (CNNCI), by June 2007, the
population of Internet users had reached 162 million users in China, second only to the United
States (CNNCI, 2007). Correspondingly, online advertising in China has experienced explosive
growth, evidenced in the scale of the market, the revenue generated, and its share of the overall
Chinese overall advertising market. In 2006, the revenue of Internet advertising in China jumped
48.9% from 2005 to $630 million. The figure was predicted to reach $840 million and $1.3
billion in 2007 and 2008 respectively as a benefit of 2008 Olympics in Beijing.
In spite of the phenomenal growth, online advertising in China has been encountering
various challenges. Online fraud and deception are common practices. Advertising Law in China
has not been able to keep pace with the development of new technologies. Current policies or
measures are not ample to safeguard against misleading or deceptive advertising on the Internet.
Furthermore, malpractice by marketers and advertisers may breach consumers’ confidence and
trust toward online advertising, which in turn may have a direct impact on the effectiveness of
online advertising.
Despite the rapid diffusion of the Internet, academic research on this new advertising
medium is by and large lagging behind. Gong and Maddox’s (2003) study is one among the few.
The researchers investigated Chinese consumers’ perceptions and responses to specific Web
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banner advertising, focusing on the short-term effects of banner advertising among Chinese
consumers. Results suggested that additional banner exposure improved Chinese users’ brand
recall, changed their attitude toward the brand, and strengthened their purchase intent.
With the rapid growth of mobile phone use in China, mobile advertising has become a
promising advertising channel for marketers to reach Chinese consumers. Focusing on this
particular type of advertising, Tsang et al (2004) found that entertainment, credibility, irritation
and informativeness were the significant factors affecting respondents’ attitudes toward mobile
advertising. Xu (2006) further proposed personalization (sending advertising messages to mobile
devices based on individual consumer characteristics and context) as an important factor
affecting consumers’ attitudes toward mobile advertising in China. The researcher found that
Chinese consumers generally had less than favorable attitudes toward mobile advertising;
Entertainment, credibility and personalization were the important factors influencing people’s
attitudes toward mobile advertising whereas informativeness and irritation did not emerge as
significant predictors.
The United States. Online advertising has become a rather mature industry in the United
States. Consumers have become more familiar with online promotional tools. A well-established
credit card system helps making online shopping easy and safe. According to American
Marketing Association, in 2007, online advertising in the U.S. grew 18.9% to reach 21.2 billion
dollars. A continuous phenomenal growth has been predicted in this market as advertisers
aggressively pursue various opportunities with the Internet. The Yankee Group, for example,
predicted that the U.S. online advertising market will reach $50.3 billion in revenue by 2011,
more than double the amount of 2007.
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The Internet is quickly gaining primacy as an important advertising medium in the United
States. However, issues such as privacy remain as a concern for many users in online advertising.
Despite its fast growing rate, online advertising only accounts for a small percentage of
advertisers’ overall budget. Advertisers currently spend 7.5% of their budget online, even though
the Internet accounts for 20% of overall media consumption in the U.S. (The Yankee Group,
2008).
Over the next few years, the driving forces for the U.S. online advertising market will be
the increasing size of the audience, the development of new types of advertising, and the creation
of new publisher business models that will help sell interactive advertisements (The Yankee
Group, 2008). The Yankee Group (2008) predicted that advertisement-related revenue pertaining
to online search and animated advertisements will increase. Social networks will become a part
of the online advertising mix, but it’s too early to tell whether they will evolve into the hot buy
for advertisers.
It might be enlightening to employ Hofstede’s (2001) framework of cultural dimensions
to analyze cultural differences. The individualism/collectivism dimension speaks to the
dialectical relationship between individuals and groups. The power distance dimension refers to
the degree of hierarchical power distribution in a society. Uncertainty avoidance explains the
degree to which people are tolerant of uncertainties. The masculinity/femininity dimension
describes the gender role in a society. The long-term versus short-term orientation, addresses the
differences in cultural values and virtues. Values associated with long-term orientation are thrift
and perseverance; values associated with short-term orientation are respect for tradition,
fulfilling social obligations, and protecting one’s face. Table 1 shows the scores of the U.S. and
China on these cultural dimensions (Hofstede, 2001).
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Table 1.
Country/Cultural Individualism Power
Dimensions
Masculinity
Distance
Uncertainty
Long-term
Avoidance
Orientation
U.S.
91H
40L
62H
46L
29L
China
20L
80H
50M
60M
118H
(Data adapted from Hofstede, 2001)
Compared to the U.S., Chinese culture is higher in uncertainty avoidance and power
distance, lower in individualism and masculinity (See Table 1). As opposed to the American
culture, Chinese culture is high on the long-term orientation. The differences in these cultural
dimensions may have an impact on consumers’ beliefs and attitudes toward online advertising
and online behaviors. For example, the uncertainty avoidance and long-term orientation directly
influence one’s attitude toward consumption/spending. Logically, Americans may be more
willing to incorporate new things in their lives than Chinese do. Chinese consumers may be more
thrifty and cautious toward spending money online than Americans.
A Conceptual Model and Research Questions
The current study tests a proposed model of ATOA in a cross-cultural context. The
following graph presents the conceptual model underlying the study. The model posits that belief
factors (e.g., information, entertainment, etc.) influence ATOA, which in turn affects consumers’
online behavior and intention to buy. The model also posits that culture influences belief factors,
ATOA, and online behavior.
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Culture
ATOA
Online behavior
Belief
As discussed before, past research supports a link between beliefs, attitudes and online
behavior. Hence, the following hypotheses are proposed:
H1: The stronger positive beliefs, the stronger positive attitudes are towards online
advertising.
H2: The stronger positive attitudes towards online advertising, the more likely one will
click on advertisements.
H3: The stronger positive attitudes towards online advertising, the more likely one will
shop online.
This study is primarily guided by research questions because of its exploratory nature of
comparing online advertising between American and Chinese cultures. Therefore, the following
research question is asked:
RQ1: How do consumers’ beliefs and attitudes toward online advertising and online
behavior vary across American and Chinese cultures?
Method
Procedure and Sampling
A questionnaire was developed first in English and then translated into Chinese. Backtranslation was conducted by bilingual third parties to improve the translation accuracy.
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Research participants were students enrolled in large universities in China and the U.S. The
primary reason for using a student-sample is based on the assumption that college students have
easy access to the Internet in China and the U.S., and hence are more likely to be exposed to
online advertising.
Paper and pencil surveys were used to ensure high return rates of 76% in China and 82%
in the United States. Overall, 202 questionnaires were collected in China and 196 were collected
in the U.S. Two surveys were excluded from data analysis in the Chinese sample because of the
large amount of missing data. For the remaining, only 9 surveys were identified with missing
data, which is less than 3%. Data plot and analysis did not show any significant relationship
between missing data on one variable and values of other variables. In line with Brown (2006), if
the probability of missing data on variable X is unrelated to X or to the values of any other
variable in the dataset, data can be assumed to be missing completely at random. Hence,
imputation with the mean was conducted for missing data. Finally, a total of 396 questionnaires
(200 for the Chinese sample; 196 for the American sample) were subjected to data analysis. For
the American sample, 107 were male (54.6%) and 89 were female (45.4%). For the Chinese
sample, there were 43 male (21.9%), 157 female (78.1%). Chinese culture was coded as 1 and
American culture was coded as 2 to formulate a dichotomous variable denoting culture.
On average, Chinese respondents (M = 5.84 years) had a shorter history of Internet use
than Americans did (M = 9.95 years). About 93% of Chinese participants reported spending less
than 3 hours per day on using the Internet and the remaining 7% reported spending 3 to 4 hours
per day. About 30.6% of American participants reported using the World Wide Web for less than
an hour, whereas 61.7% reported spending 1 to 3 hours per day on the Web and the remaining
7.7% reported spending more than 3 hours per day on the Web. American respondents reported a
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higher level of familiarity with online advertising (M = 3.65, SD = 1.00) than Chinese
respondents (M = 2.85, SD = 0.94). Moreover, 27.7% of Chinese participants reported that they
were not very familiar with online advertising.
Measurement
Beliefs about online advertising. To measure subjects’ beliefs about online advertising, a
33-item scale was adapted from previous studies (Pollay and Mittal, 1993; Yang, 2004). The
scale consisted of items culled from different dimensions of beliefs including informative (e.g.,
“the Internet is a valuable source of information”), materialistic (e.g., “Online advertising
promotes a materialistic society”), irritating (e.g., annoying), good for consumers (e.g., “Online
advertising is essential”), hedonic (e.g., “Online advertising is entertaining and enjoyable”),
credible (e.g., trustworthy and believable), manipulative (e.g., “Online advertising persuades
people to buy things they should not buy”), and distort value (e.g., “Online advertising promotes
undesirable values in our society”). Responses were measured on a 5-point Likert scale ranging
from 1 (strongly disagree) to 5 (strongly agree).
Principal axis factor analysis with promax rotation was conducted to examine the
underlying structure of those 33 items measuring beliefs about advertising. The rules of a
minimum eigenvalue of 1.0 and at least 2 loadings (60/40 loadings) per factor were referenced
for extracting factors. For the Chinese sample, five factors were retained and 53.5% of the total
variance was explained. For the American sample, the retained five factors explained about
62.57% of the total variance. Items that were retained in both samples were used for
confirmatory factor analysis. Descriptive statistics of the belief items are presented in Table 2,
and factor loadings are presented in Table 3.
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Factor 1, entertainment (eigenvalue = 8.84, Cronbach = .75, China; eigenvalue = 3.75,
Cronbach alpha =.95, U.S.). This factor consists of four items and reflects individuals’ belief that
advertising can bring fun and enjoyment to their lives. High scores on this factor refer to a strong
belief that online advertising is entertaining.
Factor 2, information seeking (eigenvalue = 2.33, Cronbach alpha = .80, China;
eigenvalue = 1.44, Cronbach alpha = .83, U.S.). The factor consists of three items and reflects
the belief of using online advertising to seek information. High scores on this factor mean that
online advertising is informative.
Factor 3, credibility (eigenvalue = 3.12, Cronbach alpha = .86, China; eigenvalue =
12.65, Cronbach alpha = .89, U.S.). The factor consists of three items and reveals one’s view on
whether online advertising is believable. High factor scores refer to high credibility of online
advertising.
Factor 4, economy (eigenvalue = 1.72, Cronbach alpha = .64, China; eigenvalue = 1.19,
Cronbach alpha = .80, U.S.). This factor consists of three items and refers to an individual’s
belief about the influence of online advertising on the economy. High factor scores indicate a
strong belief that online advertising is beneficial for the economy.
Factor 5, value corruption (eigenvalue = 1.65, Cronbach alpha = .82, China; eigenvalue =
1.62, Cronbach alpha = .70, U.S.). This factor consists of two items and reveals one’s belief
about the impact of advertising on people’s outlook of life. High factor scores mean that online
advertising has a strong negative effect on moral values and social justice.
A confirmatory factor analysis was conducted to examine the goodness-of-fit of the
measurement model for belief factors. AMOS version 5.0 was used for the structural modeling
analysis. Over the past decades, there has been a large body of research and debate on the cutoff
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criteria of fit indices for assessing model fit (Hu and Bentler, 1999; Kline, 2005; Loehlin, 1998).
Among a range of fit indices, the following were those often reported in published research: the
Chi-square, comparative fit index (CFI), the standardized root mean square residual (SRMR), the
root mean square error of approximation (RMSEA), the goodness of fit index (GFI), and the
incremental index of fit (IFI). Researchers tend to agree that it is not advisable to rely on one fit
index to assess the model fit. Instead, using a combination of different fit indices may be more
reliable. Because Chi-square is sensitive to sample size, x 2 df is recommended and the ideal
cutoff is 3 (Kaplan, 1990). Kline (2005) recommended the following cutoff criteria for good
model fit: SRMR < .10, CFI > .90, GFI > .90, IFI > .90, RMSEA < .08. Hu and Bentler (1999)
suggested that a strict rule with SRMR < .08 and RMSEA < .06 would result in a lower type II
error rate of model rejection.
Based on the typical cut-off criteria of model fit, results indicate that the measurement
model of belief factors fit both the Chinese sample and the American sample satisfactorily (see
Table 3). A graphical measurement model is presented in Figure 1.
Attitudes toward online advertising. Five items were used to measure ATOA on a 5-point
Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). For the Chinese sample, the
item “in general, I think that online advertising increases the cost of products” was deleted to
increase Cronbach’s Alpha from .71 to .77. For the U.S. sample, deletion of the aforementioned
item increased Alpha from .65 to .68. The remaining four items were “overall, I consider online
advertising a good thing”; “overall, I like online advertising”; “I consider online advertising very
essential”; and “I would describe my overall attitude toward online advertising very favorably.”
The mean of the four items served as the index of attitudes toward advertising. The higher the
index score, the more positive attitude one holds toward online advertising.
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Consumer behavioral responses. Behavioral responses toward online advertising were
conceptualized as a combination of ad clicking and shopping experience. Ad clicking was
measured by the frequency of subjects’ clicking on online advertising. Online shopping
experience was assessed in terms of frequency of online purchases. It should be pointed out that
past research has not demonstrated consistent measures of online behavior. For example, to
assess online behavior, prior studies either focused on online information searching or online
purchasing (Karson, McCloy and Bonner, 2006; Korgaonkar and Wolin, 2002). On one hand,
such an inconsistency speaks to the complexity of online behavior and researchers’ differing
understanding of this construct; on the other hand, it is reasonable to conceptualize online
behavior as they do in the current study, particularly in line with its exploratory nature.
Results
Two structural models were fitted to the pooled data of Chinese and American
participants. For model I, the indicator of online behavior was ad clicking, whereas frequency of
online buying was the indicator of consumer response for model II. Hence, in both models,
consumer response was treated as a single-indicator construct. Results presented in Table 5 show
that both structural models fitted the pooled data well. Structural Model I and Model II are
presented in Figure 2 and Figure 3 graphically.
Hypotheses
Regression coefficients of structural models are presented in Table 6 and Table 7. It is
shown that three out of four positive belief factors such as information seeking, entertainment,
and economy beliefs significantly and positively predict ATOA. Among them, the information
seeking belief is the strongest predictor. Credibility, however, did not emerge as a significant
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predictor of ATOA. The only negative belief factor, value corruption belief negatively influences
ATOA. Hence, H1 is partially supported.
The results also show that ATOA is a statistically significant and positive predictor of
both online ads clicking and frequency of online shopping. In other words, the more positive
ATOA one holds, the more likely he or she will click on advertisements and shopping online.
Therefore, both H2 and H3 are supported. In addition, ATOA mediates the relationship between
belief and online behavior.
Research Question
Both Model I and Model II show that culture influences belief factors including
information, credibility, and economy. Specifically, Americans tended to believe that online
advertising was more informative, credible, and less beneficial for the economy than did
Chinese. Nonetheless, entertainment and value corruption beliefs did not vary across the two
cultures. There was no statistically significant difference of ATOA across Chinese and American
cultures. Interestingly, Chinese participants were more likely to click ads than did Americans,
whereas Americans were more likely to buy online than were Chinese.
Multiple group comparisons were conducted to examine the moderating effects of culture
on online advertising. Specifically, culture was removed from the previous two tested structural
models. A series of nested models were examined to identify group difference. First,
unconstrained models were fitted to both groups of data. Then, the measurement model weights
were constrained to be equal. Finally, the structural weights were constrained to be equal across
groups. Chi-square changed was referenced to determine whether the model fit became worse.
(See Table 8 and Table 9). Results indicate only the path from ATOA to ad clicking was
statistically significant across culture, whereas no moderating effect was identified on the path
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from beliefs to ATOA, neither did the path from ATOA to buying. Specifically, the influence of
ATOA on ad clicking in China (ß = .79) is stronger than that in the U.S. (ß = .34).
Discussion
Links among Belief Factors, ATOA, and Behaviors
This study identified five common belief factors across the Chinese and American
samples: entertainment, information seeking, credibility, economy, and value corruption. The
results showed that except for credibility, all other belief factors were significant predictors of
ATOA, which is consistent with previous research (e.g., Ducoffe, 1996; Wolin, Korgaonkar and
Lund, 2002). Among the four significant factors, the information factor played the most
important role in predicting ATOA, followed by economy, entertainment, and value corruption.
Such a finding makes sense in that one of the most important functions of advertising is to
provide information. Past research on Internet use motives has consistently shown that searching
for information is the primary reason why people use the Internet (e.g., Rubin, 2002). It is
logically sound that those who perceive online advertising to be informative are more likely to
favor it. For instance, Wolin et al. (2002) found that product information was positively related
to ATOA. Ducoffe (1996) also reported a strong correlation between informativeness and
Internet advertising value.
People who believe online advertising has a positive impact on the economy tend to have
a positive attitude toward online advertising. A basic view of advertising proponents is that
advertising is the lifeblood of business – it provides consumers with information about products
and services and encourages them to improve their standard of living. Advertising has been
linked to producing jobs and helping new firms enter the marketplace. Companies employ people
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who make products and provide the services that advertising sells (Belch and Belch, 2007).
Advertising, therefore, stimulates competition and contributes to economic development.
Entertainment is another crucial component influencing the effectiveness of advertising
by establishing an emotional link between consumers and a brand message. With the
marketplace cluttered with advertising messages vying for people’s attention, an advertisement
needs to be interesting and enjoyable in a creative way so as to hold audiences’ attention.
Furthermore, as the word “infotainment” suggests information and entertainment are often
intertwined with each other in an information society. Online advertising is just another exemplar
of infotainment in the new technology world.
Regarding the value corruption belief, people tend to view online advertising negatively
when they believe online ads undermine the social value system. Past literature has established
that advertising is not only a marketing tool but also a social actor and a cultural artifact that
conveys social and cultural values and beliefs (e.g., Dyer, 1982; Frith, 1995). China is in the
transition from a traditional culture to a more hybrid culture featuring penetration of Western
culture and values. There is great concern about the trend that the younger generation is
abandoning traditional Chinese values and becoming more westernized. The unending debate on
cultural imperialism speaks to such concerns too. To date, the online world is still dominated by
English and Western culture, so it is sensible that people in developing countries are cautious
about the encroachment of Western values via new technologies.
In summary, the above discussion suggests that belief factors play an important role in
predicting consumers’ ATOA. That is, consumers hold more positive attitudes toward online
advertising when they believe online advertising are beneficial for the economy, informative,
entertaining, and pro-value.
Online Advertising 22
Findings also suggested that ATOA positively and significantly predicted ad click and
reported online shopping experience. This is consistent with the attitude-behavior link exhibited
in the literature. For example, Wolin et al. (2002) found that respondents’ favoring attitude
toward online advertising significantly influenced their Web advertising behavior such as
clicking online advertisements. Korgaokar and Wolin (2002) further observed that heavy Internet
users with positive ATOA were more likely to purchase online.
Effects of Culture
One main objective of the current study is to explore the cultural impact on one’s belief
and attitude toward online advertising. Results demonstrated significant differences in
information, credibility and economy beliefs between the Chinese and American samples.
Compared with Chinese, Americans tended to view online advertising as more informative, more
trustworthy, and less economically beneficial. The result is in sync with the fact that e-commerce
in the U.S. is more mature than that in China. Commercial web sites in the U.S. are more
sophisticated and serve people’s information needs better, which naturally leads to Americans’
strong perception of the information function of online advertising. In addition, Americans
scored higher on the credibility factor than did Chinese. More credible information is more likely
to be viewed as more informative.
Chinese consumers demonstrated lower trust toward online advertising than did
Americans. Such a perception difference may be attributed to a couple of factors. First of all, as
mentioned earlier, compared with the U.S., China is higher in the uncertainty avoidance
dimension. Chinese traditional culture teaches people to be cautious in general, especially toward
new things. This is evidenced by a survey result conducted by CNNIC, which revealed that only
1/3 of Chinese Internet users expressed trust toward the Internet. The American culture, in
Online Advertising 23
contrast, emphasizes risk taking and embracing new things. New technology development, in
particular, has been the engine for social and economic development in the U.S. As such,
Americans tended to hold higher trust toward online advertising in comparison to Chinese.
Second, online advertising in China is still in the emerging stage, fraud and the lack of legal
regulation of advertising in China may contribute to the low perceived credibility of online
advertising among Chinese consumers.
Compared with Americans, Chinese Internet users were more likely to believe that online
advertising will benefit the economy. This may be explained by the fact that China is undergoing
the unprecedented economic growth and the economy is often regarded as the No.1 issue in
China. Against the backdrop of recent Chinese history of a centrally planned economy, a
relatively free marketplace that encourages competition has drastically improved the Chinese
standard of living over the past three decades. Living in a society with a booming economy,
Chinese people are likely to link advertising with the free market system, competition, and
economic growth.
Culture has a significant impact on consumer responses to online advertising in the two
countries. Results indicate that American consumers were less likely to click on advertisements,
but were more likely to purchase online than did Chinese. The uncertainty avoidance and the
long-term vs. short-term orientation may provide an explanation for the results. As mentioned
earlier, compared with China, the U.S. is lower on uncertainty avoidance and more short-term
oriented. Consequently, Americans may be more accepting of new things such as online
shopping. The short-term orientation also shapes the spending habits of American consumers.
The common mentality of “enjoy the moment, satisfy your desire now” is deeply rooted in the
American consumer culture. In comparison, Chinese traditional culture emphasizes being
Online Advertising 24
cautious and frugal. This was reflected in Chinese consumers’ low trust toward Internet in
general and online advertising in particular. Furthermore, one of the most serious barriers to ecommerce in China is the under-developed credit card system. Unlike in the U.S., credit cards
are not widely used in China. Many Chinese people feel uneasy about using credit cards when
making purchases. The perceived risk associated with e-commerce transactions is much higher in
China than in the U.S. Consumers often don’t feel secure enough to actually pay online, resulting
in the emergence of a strange e-commerce model of “order online, pay offline” in China (Peng,
1999). This business model substantially reduces the convenience and attractiveness of ecommerce. As such, overall online purchases made by Chinese consumers are quite limited. As
the descriptive statistics in this study has shown, the majority of the Chinese respondents
purchased less than five times during the past 12 months.
In sum, results have supported the hierarchy effect of advertising research suggesting that
belief about online advertising influences attitude toward online advertising, which in turn affect
people’s responses toward online advertising. Marketers need to position online advertising as a
credible information source for consumers and dig out its potential for stimulating economy.
Furthermore, Internet users in different countries reported distinct perceptions of online
advertising and vastly different online behavior. With such a discrepancy, global marketers may
need to be cautious when employing a centralized e-marketing approach around the globe.
Incorporating more cultural specific considerations may be beneficial to achieve the maximum
effect of online advertising.
Limitations and Future Directions
The study explores the influence of culture on consumers’ beliefs and attitudes toward
online advertising and the relationships between different components in consumer response
Online Advertising 25
sequence. Research findings may help enhance our understanding of ATOA in a cross-cultural
context and offer valuable information to global marketers.
The study has several limitations. First, the student sample used in this study may limit
the extent to which the findings can be generalized. Future research could examine a broader
profile of online consumers and compare online advertising across different profiles. Second, due
to the short history of online advertising, consumers’ beliefs and attitudes toward online
advertising may still be evolving and changing (Karson, McCloy and Bonner, 2006).
Nonetheless, a cross-sectional design is far from enough to capture that change or evolution. To
that end, a longitudinal study may provide more insights into the relationships among different
factors. Lastly, this study primarily investigates the impact of cultural background on ATOA.
Past research has demonstrated a close link between ATOA and other social and individual
factors such as demographics, lifestyle, Internet experience, and development stage of the online
advertising industry (Karson, McCloy and Bonner, 2006; Korgaonkar and Wolin, 2002; Yang,
2004). Differences in these factors could contribute to the differences in ATOA and online
shopping between the two samples. Future investigation could focus on how the aforementioned
factors conspire to influence online advertising.
Online Advertising 26
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Online Advertising 29
Table 2: Items of Belief Factors
Online advertising …
_____________________________________________________________________________
1. is a good source of product/service information
China
M
SD
2.76
.91
U.S.
M
SD
3.11
1.08
2. supplies relevant information
3.20
.90
2.88
1.01
3. provides timely information
2.97
1.02
3.28
1.08
4. is entertaining
3.13
1.07
3.20
1.23
5. is enjoyable
2.91
1.02
2.85
1.22
6. is pleasing
2.26
.95
2.74
1.21
7. is interesting
2.69
.95
3.05
1.17
8. is credible
2.24
.80
2.66
1.00
9. is trustworthy
2.14
.78
2.35
0.93
10. is believable
2.47
.82
2.52
0.97
11. has positive effects on the economy
3.22
.74
2.99
0.87
12. raises our standard of living
2.78
.76
2.55
0.86
13. results in better products for the public
2.80
.81
2.65
0.86
14. promotes undesirable values in our society
3.08
.78
2.96
0.89
15. distorts the values of youth
3.03
.77
3.05
1.02
______________________________________________________________________________
Online Advertising 30
Table 3
Factor Loadings of Beliefs (China)
Belief Items
INFO
Internet Motive Factors
ENTE
CRED ECON
VALU
Information
Item 1
Item 2
Item 3
.55
.65
.95
-.10
.04
.00
.11
.12
-.05
.20
-.04
-.12
.03
-.05
.06
.20
-.19
-.03
.06
.73
.79
.51
.76
-.03
.09
.11
-.00
-.11
.01
-.06
.10
-.07
-.08
.12
.04
.03
-.13
.04
.00
.06
.13
.85
1.02
.66
-.05
.04
.06
.02
.01
-.06
.03
-.05
-.06
-.10
-.02
.07
.12
-.02
-.06
.56
.74
.84
-.10
-.13
-.06
-.01
-.04
-.05
-.04
-.00
-.07
-.12
.03
.75
.91
Entertainment
Item 4
Item 5
Item 6
Item 7
Credibility
Item 8
Item 9
Item 10
Economy
Item 11
Item 12
Item 13
value
Item 14
Item 15
Note. INFO = information, ENTE = entertainment, CRED = credibility, ECON = economy,
VALU = value.
Online Advertising 31
Table 3 (continue)
Factor Loadings of Beliefs (U.S.)
Belief Items
INFO
ENTE
Belief Factors
CRED
ECON
VALU
Information
Item 1
Item 2
Item 3
.54
.59
.42
.20
.09
.31
.16
.31
.04
.03
-.02
.12
-.04
.01
.05
-.11
-.17
-.06
-.03
1.04
1.01
.88
.79
-.16
.05
.10
.11
.03
-.05
-.02
.04
-.09
.01
-.00
.04
-.08
-.06
.02
-.08
-.06
.02
.77
.79
.69
-.00
-.06
-.04
.06
-.04
.01
-.04
-.30
-.11
.00
.04
.07
.24
.34
.17
.73
.71
.72
-.08
.02
-.02
-.16
-.03
.00
-.09
.07
-.08
-.18
-.11
.56
.80
Entertainment
Item 4
Item 5
Item 6
Item 7
Credibility
Item 8
Item 9
Item 10
Economy
Item 11
Item 12
Item 13
value
Item 14
Item 15
Note. INFO = information, ENTE = entertainment, CRED = credibility, ECON = economy,
VALU = value.
Online Advertising 32
Table 4: Measurement Model Fit of Belief Factors
Chi
China
U.S.
Ideal value
df
126.69 79
114.74 79
Chi / df
SRMR
GFI
IFI
CFI
RMSEA
1.604
1.452
<3
.054
.044
< .08
.921
.931
> .90
.964
.983
> .90
.963
.983
> .90
.063
.048
< .08
Online Advertising 33
Table 5: Structural Model Fit
Chi
Model I
Model II
Ideal value
df
375.56 164
391.24 164
Chi / df
SRMR
GFI
IFI
CFI
RMSEA
2.290
2.386
<3
.043
.044
< .08
.919
.916
> .90
.951
.947
> .90
.950
.946
> .90
.057
.059
< .08
Online Advertising 34
Table 6: Regression Weights of Structural Model I
Regression path
Culture → information
B
SE B
ß
C.R.
.347
.094
.214***
3.686
-.007
.100
-.004
-.072
Culture → credibility
.263
.085
.164**
3.090
Culture → economy
-.131
.053
-.138*
-2.461
Culture → value
-.054
.078
-.041
-.700
Culture → ATOA
.077
.065
.051
1.190
Culture → ad click
-.150
.076
-.093*
-1.974
Information → ATOA
.356
.069
.381***
5.134
Entertainment → ATOA
.184
.051
.219***
3.606
Credibility → ATOA
.071
.063
.076
1.130
Economy → ATOA
.468
.106
.293***
4.424
-.206
.055
-.183**
.457
.056
Culture → entertainment
Value → ATOA
ATOA → ad click
Note: *p < .05, **p < .01, ***p<.001
.429***
-3.781
8.210
Online Advertising 35
Table 7: Regression Weights of Structural Model II
Regression path
Culture → information
B
SE B
ß
C.R.
.346
.094
.214***
3.685
-.007
.100
-.004
-.072
Culture → credibility
.263
.085
.163**
3.088
Culture → economy
-.134
.054
-.140*
-2.487
Culture → value
-.049
.077
-.037
-.639
Culture → ATOA
.081
.066
.053
1.239
Culture → buying
.343
.085
.198***
4.015
Information → ATOA
.350
.071
.370***
4.946
Entertainment → ATOA
.186
.052
.218***
3.551
Credibility → ATOA
.071
.065
.074
1.090
Economy → ATOA
.486
.108
.303***
4.518
Value → ATOA
-.218
.056
-.187***
-3.871
ATOA → buying
.143
.060
.126*
2.394
Culture → entertainment
Note: *p < .05, **p < .01, ***p<.001
Online Advertising 36
Table 8: Multiple Group Comparison of Structural Equation Models across Culture
Models
Number of
parameters
Chi-square
Chi-square
change
Degree of
freedom
unconstrained
112
453.81
Measurement weights
constrained
99
474.30
20.49
321
94
478.97
4.67
326
93
494.62
15.65***
327
Measurement weights
Belief→ATOA
constrained
Measurement weights
Belief→ATOA
ATOA→ad click
constrained
***p < .001
308
Online Advertising 37
Table 9: Multiple Group Comparison of Structural Equation Models across Culture
Models
Number of
parameters
Chi-square
Chi-square
change
Degree of
freedom
unconstrained
112
469.19
Measurement weights
constrained
99
489.24
20.03
321
94
493.64
4.40
326
93
494.03
0.39
327
Measurement weights
Belief→ATOA
constrained
Measurement weights
Belief→ATOA
ATOA→ buying
constrained
308
Online Advertising 38
Figure 1: Measurement Model of the Belief Factors
information
entertainment
credibility
economy
value
item1
e1
item2
e2
item3
e3
item4
e4
item5
e5
item6
e6
itrem7
e7
item8
e8
item9
e9
item10
e10
item11
e11
item12
e12
item13
e13
item14
e14
item15
e15
Online Advertising 39
Figure 2: Structural Model I
D1
information
D2
D6
entertainment
ATOA
culture
D3
credibility
behavior
D7
D4
Ad click
economy
value
D5
Online Advertising 40
Figure 3: Structural Model II
D1
information
D2
D6
entertainment
ATOA
culture
D3
credibility
behavior
D4
economy
value
D7
buying
D5