The Economic Effects of Domestic Search Engines on the Development of the Online Advertising Market

Telecommunications Policy 40 (2016) 982–995

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Telecommunications Policy

URL: www.elsevier.com/locate/telpol

The economic effects of domestic search engines on the development of the online advertising market

Sung Wook Ji a, Young-jun Choi b, Min Ho Ryu c,n a Media Communication Division, College of Social Sciences, Hankuk University of Foreign Studies, Seoul, South Korea b Department of International Business and Trade, Kyung Hee University, South Korea c Internet Research Team, Naver Corp., South Korea article info abstract

Article history: A few global search engine platforms, notably Google and Yahoo!, have achieved world- Received 7 October 2015 wide dominance in the search engine market. However, some domestic search engine Received in revised form platforms, such as Naver in South Korea and Baidu in China, have come to dominate their 7May2016 domestic markets in competition with global search engine platforms. This study quan- Accepted 24 May 2016 tified the economic effects of domestic search engines on the development of the online Available online 10 June 2016 advertising market. Using a country-level dynamic panel of 46 countries from 2009 to Keywords: 2013, we investigated the change in the size of the online advertising market caused by Domestic search engine the existence of a domestic search engine. The results show that the development of a Online advertising market domestic search engine may lead to an increase in the size of the online advertising Two-sided market market: A country with its own domestic search engine platform(s) may have an average of 0.018% more online advertising intensity—which is defined as online advertising spending/GDP—than one without this type of platform. The reasons behind these results and the policy implications are also discussed. & 2016 Elsevier Ltd. All rights reserved.

1. Introduction

The Internet has grown rapidly since the early 1990s, and from online shopping and banking to news and even social networking, the Internet has completely transformed how people search for and utilize information. In this era, the importance of search engines as a means of gaining access to information is growing. Users typically spend a large amount of their time online using search engines to look for information. One industry report estimated that the global gross value created by Internet searches was $780 billion in 2009 (Bughin et al., 2011), and in 2013, the world search engine advertising market of 53 countries reached $48.4 billion (PricewaterhouseCoopers, 2014). As search engines have become the primary means of finding information, they play a critical role in disseminating information on the Internet. Furthermore, because search engines such as Google are among the most frequently visited Web sites, they have become attractive options for online advertising and target marketing. There were several competing search engines at the beginning of the Internet era, but the entrance of Google significantly altered the landscape of the search engine market. Founded in 1998, Google effectively deployed its advanced search technology to surpass others such as Yahoo! , and it has established itself as the world's predominant player since

n Corresponding author. E-mail addresses: [email protected] (S.W. Ji), [email protected] (Y.-j. Choi), [email protected] (M.H. Ryu). http://dx.doi.org/10.1016/j.telpol.2016.05.005 0308-5961/& 2016 Elsevier Ltd. All rights reserved. S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 983

2002 (Netmarketshare, 2014). After becoming the market leader in the U.S., Google aimed for international expansion and succeeded in penetrating search engine markets around the world. It currently occupies approximately 70% of the global search engine market, processing over 100 billion monthly searches (Webcertain, 2011, 2012, 2013, 2014). While Google has established its dominant position in most of the Western hemisphere, it faces opposition from certain local competitors in other parts of the globe, especially in China, Russia, and South Korea (Webcertain, 2014). According to one industry source (2014 Webcertain Global Search and Social Report), Google has already lost its monopoly of the global search engine market due to its insignificant share in China, the world's largest Internet market. Baidu, China's primary search engine, now captures more than 16% of the global search engine market, thanks to its domination of the Chinese market. In South Korea, the local market leader Naver has a market share of over 60% while Google only has 4%. Another notable development in the global search engine market has been the advance of the Russian search leader Yandex. The recent comScore qSearch data reveals that Yandex has surpassed Bing and has become the fourth largest search engine after Google, Baidu, and Yahoo! (Kerr, 2013). As of 2013, five of the 53 countries in our analysis—namely, China, South Korea, Japan, Russia, and the Czech Republic—possess their own domestic search engines, which, on average, take more than 50% of the domestic market share (Webcertain, 2013). Thus, at least in the cases of countries possessing their own domestic search engines, Google has not achieved dominance and is presently competing against its domestic counterparts. The present study examines the competition among domestic and global search engines, concentrating particularly on the development of the online advertising market. Despite the recent development of online search engine technologies, studies have provided surprisingly little empirical evidence concerning the social and economic effects of these technologies. A few studies have modeled search platform competition and relevant policy issues based on the concept of a two- sided market structure, which was recently developed in the field of economics (Argenton & Prüfer, 2012; Etro & Iurkov, 2013; Etro, 2013; Jeon, Jullien, & Klimenko, 2012; Lianos & Motchenkova, 2013; Zhang, Levä, & Hämmäinen, 2013). Others have examined how these domestic search engines have been able to survive alongside global search engines, and have tried to find the reasons for local search engines’ success in their own country-based markets (Kim & Tse, 2012, 2014a, 2014b; S. Choi, 2010; Zhao & Tse, 2011).1 However, to the best of our knowledge, there is virtually no empirical evidence concerning the ways in which the development of a search engine changes the relevant online market. This study uses the unique set of available industry data compiled by PricewaterhouseCoopers, which tracks the revenue and size of the online advertising market of individual countries, in order to investigate the relationship between the development of a domestic search engine and the size of a country's online advertising market. Our goal is to empirically demonstrate how domestic search engines positively affect the development of a country's online advertising market. We constructed a country-level dynamic panel of 46 countries based on industry and government sources, which included each country's economic and cultural status from 2009 to 2013 along with the trends of their online advertising markets, broadband Internet penetration, and other indexes indicating the development of information and communication technologies. We then quantified the economic effects of domestic search engines on the resulting increase in online advertising revenue. The next section reviews the background literature on the development of the search engine market. In Sections 3 and 4, respectively, we present an empirical model concerning the effect of domestic search engines on the online advertising market and describe the data used. Section 5 presents the empirical results and a general discussion of the results follows in Section 6.

2. Background

2.1. Search engines as a two-sided market

The search engine market is characterized as a two-sided (or multi-sided) market, which includes things such as credit cards, television channels, operating systems (e.g., Windows and Android), and shopping malls. In such a market there is an interaction between two (or multiple) groups through a platform, such that an increase in the number of users in one group can benefit from the users in the other group(s); as a result, both sides’ price, product quality, and output relationships are interrelated (Armstrong, 2006; J.P. Choi, 2010; Rochet & Tirole, 2003; Schmalensee & Evans, 2007). This interrelationship makes it inappropriate to consider two or more markets in isolation. In the search engine market, for example, search platforms such as Google, Yahoo!, and others attract Internet users (the first group) and advertisers (the second group) who wish to advertise their products to these Internet users. A search platform indexes the Web pages of Internet content providers (the third group). The better and more relevant search results a search engine provides, the more users it attracts, which increases the effectiveness of advertising campaigns on that search platform, thereby increasing advertising revenue. Previous literature has examined the search engine market based on the recently developed two-sided market framework. Etro (2013) modeled the tendency of a search engine with an initial advantage to monopolize the market by collecting log data from past searcher experiences. Etro and Iurkov (2013) analyzed a two-sided multi-homing market framework and found that the price paid by advertisers to a search engine platform depends directly on the market share occupied by the

1 For a survey of studies from the perspective of disciplines other than economics, see Rieder and Sire (2013) and Zimmer (2010). 984 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 search engine on the subsidized side (i.e., the Internet user side). They also found that a search engine's achievement of a dominant market position may yield undesirable consequences, such as that engine's underinvestment for increasing search quality and the manipulation of search results. Argenton and Prüfer (2012) and Lianos and Motchenkova (2013) found that a search engine's monopolization of the market may lead to underinvestment in improvements in the quality of the search engine, as well as higher prices for advertisers, compared to socially optimum levels. Tarantino (2013) modeled the incentive of a search engine to bias organic and sponsored search results in order to favor an integrated Web site. Taylor (2013) modeled organic links’ cannibalization of advertising revenue in a search screen, which incentivizes search engines to degrade the quality of their search. A few studies have also considered the effect of competition between domestic and global search engines. Jeon, Jullien, and Klimenko (2012) examined how the dominance of English Web content may affect the production of Web content in a non-English home language. Zhao and Tse (2011) modeled the competition between domestic and global search engines and stressed the importance of locally customized services and content for domestic search engines' competition strategies. This series of studies modeled the market dominance of a specific search engine and focused on the policy issues relevant to that engine's dominance; however, their findings were generally either not entirely supported by empirical results or supported only by descriptive data in the search engine industry.

2.2. Quality of search and competition between global and domestic search engines

All search engines compete with one another in terms of search quality (Argenton & Prüfer, 2012; Etro, 2013; Lianos & Motchenkova, 2013; Zhao & Tse, 2011). Since users are free to select one (or more) search engines, these platforms invest significant resources in improving the quality of their searches in order to attract more users. The higher its quality, the more users a search engine will attract and thus the more valuable it will become to advertisers (Evans, 2008). In this quality competition, a search engine which can amass more data on any given user's past searches has a critical advantage in its ability to improve search quality, which in turn attracts more users (thus benefiting the advertising market and the engine's revenues from serving it). A search engine with a large number of users and their queries may increase its search quality by generating more accurate, relevant results with faster Web page loading times because it may access a significant amount of information from the past search log queries made by their users (Argenton and Prüfer, 2012; Etro, 2013). Argenton and Prüfer (2012), for example, argued that the quality of a search is determined by both the sophistication of an engine's search algorithm (search algorithm quality) and the context-specific data created by users’ previous keyword searches –assuming that all other conditions, such as availability of hardware and online webpages as well as financial resources, do not differ between competitors. Zhao and Tse (2011) also suggested that one of the most effective ways for domestic search engines to compete with global search engines is to accommodate search content to users’ preferences (especially by making content available in a domestic language other than English). This peculiar mechanism—called “in- tertemporal indirect network externalities”—in search queries has led to the dominance of the market by a few large search engines (Argenton and Prüfer, 2012).2 These considerations imply that the quality and relevance of search results are crucial factors in search engine competition. The cultural dimension of a search engine is also a significant element of the quality competition, since it may differ- entiate the search results (Jiang, 2014a, 2014b; Oh and Zhang, 2010). A search engine generates search results which embody the local culture and nationality on which the search engine is based. A domestic search engine—loosely defined as a search engine using a domestic search technology and a domestic language (further defined in Section 4 below)—usually connects users with more localized content written in a language other than English, resulting in a higher level of search relevance. For example, Zhao and Tse (2011) concluded that Baidu, a Chinese domestic search engine, owes its success to its ability to connect Chinese users with more domestic content than Google can. Oh and Zhang (2010) also reported the preferences which Chinese users have for the search results of domestic rather than global search engines. This has enabled Baidu to dominate the Chinese search engine market, despite Google's superior search technology and larger search content volume. Furthermore, not only do domestic search engines index more localized content than global search engines, they also generate more localized private content databases, such as knowledge-sharing services, which makes them better suited to fulfill the needs of local consumers and thus able to attract more of these users (Kim & Tse, 2012, 2014a, 2014b; S. Choi, 2010; Zhao & Tse, 2011). The Korean domestic search engine Naver, for example, has developed its own knowledge database, “Knowledge iN,” which has continuously accumulated and updated its information and is now almost six times larger than Wikipedia, one of the world's largest information-sharing platforms. Possessing this customized domestic database has allowed Naver to successfully compete with the global search engine giant Google (S. Choi, 2010). Within just a few years, Naver has steadily grown, to the point where it captured over 70% of the Korean market share in 2014 (Webcertain, 2014). The success in finding and creating local content by domestic search engines is not based on their inherent technological superiority but rather on their strategic choice to compete with global search engines (Kim & Tse, 2014a, 2014b; Zhao & Tse, 2011). Indeed, Google's search technology is, in general, superior to that of domestic search engines and yields more web content hits, which is one of the reasons why Google is able to dominate most global search engine markets. However,

2 Argenton and Prüfer (2012) therefore proposed to require all search engines to share their data on users’ previous searches with other search engines, in order to prevent market dominance by a few search engines and to improve search quality, innovation, and consumer surplus. S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 985 technologically inferior domestic search engines may successfully compete with superior ones (global ones) by introducing more localized content and offering customized local content services. In fact, search engines have been developed which offer their customers more opportunities for personalization (Fer- ragina & Gulli, 2008; Gauch, Chaffee, & Pretschner, 2003; Micarelli, Gasparetti, Sciarrone, & Gauch, 2007; Pitkow et al., 2002). Customers’ cultural orientations affect their choices of customized and personalized products because their value depends on the individual customer's cultural orientation (Moon, Chadee, & Tikoo, 2008). For example, Oh and Zhang (2010) found that Chinese users prefer domestic Internet services over foreign Internet services, even when both are offered in Chinese. This improvement in quality by the domestic search engine(s) may increase the domestic Internet user base, which in turn may lead to an increase in the size of the domestic advertising market. The more users a search engine has, the more effective advertising campaigns on that platform will be, since online advertisers value reaching more users (Evans, 2008). Thus, it is hypothesized that the existence of a domestic search engine will lead to an increase in the size of the online advertising market.

3. Empirical model

This study examines the changes within the online advertising market caused by the development of a domestic search engine. Specifically, our objective is to clarify the relationship between the existence of a domestic search engine and the size of the online advertising market. We begin with a basic estimation equation with a fixed effect. For each country i,a fixed effect model is estimated:

Online Adit=+++++βββαμ123 D it I it X it i t vit ()1 where Online Adit indicates the aggregated size of the online advertising market on country i and year t. Dit represents the development of a domestic search engine; Iit indicates the development of the Internet; Xit is a vector of other country- specific and time-varying control variables; αi is the individual country-specific effect that varies by country, but is constant across years; μt indicates a time-specific effect (e.g., a worldwide economic downturn) which is time-variant but constant from country to country; and vit is the idiosyncratic error term, which is assumed to be independently and identically distributed across all countries and time periods.

The individual country-fixed effect αi captures time-invariant, country-specific factors, such as each country's own media culture and regulatory structure, all of which remain constant over time. The usual way to control this model is to permit αi to be correlated with the control variables, while assuming that the control variables are uncorrelated with the idiosyncratic error, vit. In other words, it assumes that the country and time effects can influence the control variables. Eq. (1) can then be estimated by eliminating αi through subtracting the individual means of each component of the corresponding model, leading to the creation of a “mean-difference fixed effect” model. It is also possible to consistently estimate the parameters when αi is uncorrelated with the control variables (the random effect model). The merit of the random effect model is that, unlike the fixed effect model, time invariant variables can be included. Some econometric problems then arise. First, the changes in the revenue of the online advertising market and the existence of a domestic search engine—which are assumed to lead to changes in the online advertising market—might simultaneously affect each other. Each country's idiosyncratic trends in online advertising during the research period under study might affect the development of a domestic search engine, which, in turn, would change the online advertising industry. For example, the development of a domestic search engine could change the size of the online advertising market, which would then promote the appearance of the domestic search engine. In a similar way, an increase in Internet penetration could affect each country's year-to-year development of online media (e.g., online newspapers and online TV), which could subsequently change the degree of broadband penetration. To use an econometric term, this would create a “si- multaneity bias,” indicating that the direction of causation between those variables is unclear and/or reversed. A second econometric issue is that some of the independent variables used in this study, such as the existence of a domestic search engine and the use of a language other than English, have time-invariant characteristics, which cannot be included in a fixed effect model. Finally, an online advertiser typically takes persistence into account by considering the online advertising market of previous years. Thus, it is possible that the current development of the market can be influenced not only by the development of a domestic search engine, but also by previous trends in online advertising. Thus, we need to control for past trends in the development of an online advertising market, which, however, may cause an endogeneity problem with the lagged dependent variable. These concerns required us to find instruments that could be used to control the endogeneity of the control variables and to employ a dynamic panel approach that would control for past trends in the online advertising market. Since we could not find a valid instrument for the endogenous variables, we considered using internal instruments generated by the linear Generalized Method of Moments (GMM) procedure followed by Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (2000) as follows:

Online Adit=++++++ββββαμ0 Online Ad it−1 123 D it I it X it i t vit ()2 986 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995

where Online Adit−1 is the one-year lagged aggregated size of the online advertising market. In particular, we used the Arellano-Bover estimator (Arellano and Bover, 1995)—also called the system GMM estimator—which employs the available lagged levels of the dependent variable as instruments for the lagged difference of the dependent variable. We used the Arellano-Bover estimator rather than the estimator proposed by Arellano and Bond (1991)—also called the difference GMM estimator, since it allowed us to estimate the coefficient of time-invariant variables (in this study, the existence of a domestic search engine, and the use of a language other than English)—which are the key variables in question. Also, according to Blundell and Bond (2000), both Monte Carlo and empirical results indicate that the Arellano-Bover estimator contains considerable improvements over the Arellano-Bond estimator. We were able to generate internal instruments to solve the simultaneous bias problem through the use of the Arellano- Bover estimator discussed above. The estimator also enabled us to investigate the dynamic aspects of the online advertising market. Moreover, provided that the number of time periods was small relative to the number of observations (in our case, 5 years compared to 46 countries), the GMM estimator retained its validity despite the presence of heteroskedasticity or serial correlation. See Cameron and Trivedi (2009) and Roodman (2006) for the STATA application of the GMM estimator.

4. Data

We obtained data for the 5-year period from 2009 to 2013 on a broad range of media industries in 53 countries. Our main data source was the 2014–2018 Global Entertainment and Media Outlook report published by PwC (PricewaterhouseCoo- pers, 2014), which contains data on online/offline advertiser spending in the entertainment and media markets across 53 countries. The PwC data on online advertising revenue are divided into various sub-categories, which include online newspapers, online books, and online television, as well as non-media-based online advertising revenues such as search engine advertising. Thus, the online advertising revenues selected for this study include virtually all of the various kinds of online revenues supported by advertisers. The PwC data were matched with other factors such as the existence of a domestic search engine, broadband Internet penetration, population, computer penetration, use of a domestic language other than English, and the unique characteristics of each country that determine the size of its online advertising market.

4.1. Definition of domestic search engines

While search engines such as Google and Yahoo! initially provided basic search services, they have since broadened their scope to become platforms providing a wide variety of content and information such as e-mail, news, maps, shopping, video, and etc. Moreover, some Internet service providers such as Apple's Siri service, Amazon, Facebook, and Twitter have begun to provide search-like services though they had not previously been considered as search engines. As these in- novations have made the definition of a search engine unclear, it has become technically impossible to take all of the emerging services in each country into consideration. Therefore, for the purposes of this study we have narrowed the definition of a search engine as a term that refers to a comprehensive portal, which allows us to focus on basic search engine industries while excluding emerging types of search- like services. We also defined a domestic search engine using the criteria such as: whether it has its own search technology; whether it has been established with local capital investment; and whether it has a significant domestic market share. According to this criteria, some search engines such as Baidu, Naver, Sesnam, and Yandex, which hold significant domestic market shares, can be categorized as domestic search engines, whereas others such as Google, Yahoo!, and Bing can be categorized as global search engines. In some cases, global search engines have regional branches that provide localized services in native languages. However, considering that these local branches are not independent of their headquarters in terms of search technologies and management, a local branch of a global search engine is not considered a domestic search engine. We do regard a joint venture between a local and a global company as a type of local investment, and therefore place such a venture in the domestic search engine category. Japan, for example, is a country with a domestic search engine since Yahoo! Japan is a joint venture of Yahoo! (34.75%) and SoftBank (35.45%). Some other Yahoo! local subsidiaries, such as Yahoo! 7 in Australia and Yahoo! Xtra in New Zealand, are also joint ventures with local companies. They are not, however, considered domestic search engines since their market shares are minimal (i.e., below 3%).3 In addition to these five countries discussed above, three countries (Germany, Italy, and the Netherlands) are further categorized as countries that have domestic search engines. Appendix A consists of a list of eight countries that have domestic search engines with their starting dates, their holdings of domestic-search technologies, their amount of domestic capital investment, and the changes in their market shares from 2011 to 2013. It also illustrates the difference in the market shares of domestic search engines across the eight countries studied, with the smallest standing at 3% and the largest at 73%.

3 There is a general consensus that only a few countries have their own domestic search engines. Several industry sources indicate that only five countries have domestics search engines with significant domestic market shares (Phillips, 2015; Webcertain, 2011, 2012, 2013, 2014; Kennedy & Hauksson, 2012). In academia, Weiss (2014) also reported that “there are only a few genuinely local search engines, including Baidu.com (China), Yandex.com (Slavic countries e.g. Russia), Naver.com (South Korea) and Seznam.cz (Czech Republic)” (Weiss, 2014, p. 248). Others have discussed the success of specific domestic search engines such as Baidu (Zhao & Tse, 2011) and Naver (Kim & Tse, 2012, 2014a, 2014b; Zhao & Tse, 2011). S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 987

Fig. 1. Categories of domestic search engines.

This wide range implies that some domestic search engines are successfully competing with global search engines while others are not. To reflect their degrees of competitiveness, we further divided the eight countries into two groups based on their market shares, their amount of local capital, and the presence or absence of their local search technology. Among these eight countries, the three with a market share between 3% and 5% were placed in the “intermediate group,” while the other five, with significant market shares (45% or more), were placed in the “strong group”. Fig. 1 shows the countries and their representative domestic search engines as defined by our two criteria. The “strong group” countries have a domestic search engine that is dominant with a market share of over 45%, high-quality search technology, and a large amount of local capital. South Korea, China, Russia, the Czech Republic, and Japan are the strong group countries while Italy, Germany, and the Netherlands are the intermediate group countries. 4

4.2. Definition of the size of the online advertising market

Following Van der Wurff, Bakker, and Picard (2008), we measured the size of an online advertising market by setting the online advertising intensity variable, which is defined as the proportion of Gross Domestic Product (GDP) spent on online advertising, or online advertising spending/GDP. This GDP metric allows us to compare the sizes of all eight countries’ online advertising markets. A comparative picture of online advertising intensity is presented in Fig. 2, illustrating the size of the online advertising market as a proportion of GDP in 53 countries in 2013, the last year for which online advertising revenue data are available. As these data show, online advertising revenue varies from country to country; for instance, though the average online advertising revenue of all 53 countries relative to total GDP is 0.054%, the UK has the highest proportion at 0.314%, while Pakistan's online advertising market accounts for only 0.0013% of its total GDP. The darkness of the colors indicates the online advertising intensity of the eight countries that have been defined in Section 4.1 as those with domestic search engines. This is the key variable in question, measured in terms of whether or not each country has its own domestic search engine. As we expected, the online advertising intensities of the eight countries with domestic search engines are generally larger than those without domestic search engines: The averages of the five countries in the strong group and the three countries in the intermediate group are 0.15% and 0.094%, respectively, which are much higher than the 0.054% average of the 53 countries. Thus, the descriptive data support the hypothesis that the existence of domestic search engines promotes the development of the online advertising market. Section 5 describes a panel data analysis that isolates such trends by taking into account other factors such as the demographics, languages, and populations of the various countries as well as the level of broadband penetration within each one.

4.3. Other control variables

Other control variables were selected as potential predictors of the size of the online advertising market based on the empirical literature.

4 Some domestic search engines—for example, Miner.hu in Hungary, Walla! in Israel, and Search.ch in Switzerland — are not considered to be truly domestic, because their market shares are very small: at most, less than 3% in their respective domestic search engine markets (Kennedy & Hauksson, 2012). Thus, we did not consider them as domestic search engines. Their influence on online domestic advertising markets may also be very small or negligible. 988 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995

0.35%

0.30%

0.25%

0.20%

0.15%

0.10%

0.05% Online Ad.Intensity (% of GDP)

0.00% t e ia r r ael r UK ance Italy Peru India USA r UAE eland Chile Is Spain Japan China Egyp Brazil r Kenya Russia F Poland I Greece Turkey Austria Canada Nige Finland Mexico Sweden Norway Portugal Vietnam Pakistan Belgium Hungary Thailand Romania Australia Malaysia Germany Denmark Indonesia Colombia Argentina Singapo Venezuela Philippines Switzerland Hong Kong Hong Netherlands South Korea South South Africa Saudi Arabia Saudi New Zealand New Chinese Taipei Czech Republic Czech

Fig. 2. Online advertising revenues in 53 countries as a percentage of GDP, 2013.

4.3.1. Broadband Internet penetration Several studies have reported a positive relationship between the development of the Internet and the change in size of the traditional advertising market. Zentner (2012) compared the changes in advertising revenues in four media categories— newspapers, magazines, television, and radio—and found a general negative effect of Internet penetration on advertising revenues for those four categories. Waterman and Ji (2012) and Ji and Waterman (2014) also reported on the current transitions in the U.S. media industry brought about by the development of the Internet.

4.3.2. Domestic language other than english Jeon, Jullien, and Klimenko (2012) stressed that the bilingualism of domestic consumers has a significant effect on the competition between domestic and foreign search engine platforms. We controlled for domestic languages other than English in the model. If a country uses its domestic language other than English it was coded as 1; if not, it was coded as 0.

4.3.3. Population Previous literature has indicated that population is a valid predictor of mass communication spending (Demers, 1994; Dupagne, 1997; McCombs & Eyal, 1980; McCombs, 1972). As Dupagne (1997) reported, population size is a factor that can change revenues in the media industry. We expect that population would be positively related to the size of the online advertising market.

4.3.4. Computer penetration The possession of a computer with a broadband Internet connection can change a consumer's use of a search engine, which in turn, can increase the size of the online advertising market. All values were adjusted to 2013 U.S. constant dollars using the 2013 exchange rate. There were 46 countries remaining after deleting the U.S. (to control for an abnormal case) and countries with missing data. Table 1 shows the summary

Table 1 Descriptive statistics.

Variables Description Mean Std. dev. Min Max

Online advertising intensity (%) Online advertising revenue/GDP 0.078 0.07 0.001 0.314 a Online advertising intensity_lag One-year lagged online advertising intensity a (%) Broadband Internet penetration Broadband Internet penetration 51.92 28.98 0.32 100 a (%) Domestic search engine 5 (0 or 1) Existence of a domestic search engine (5 countries in the strong group) 0.10 0.29 0 1 b Domestic search engine 8 (0 or 1) Existence of a domestic search engine (8 countries in the strong and inter- 0.15 0.36 0 1 b mediate groups) Computer penetration (%) Penetration of computers with broadband Internet service 50.95 27.23 0.9 88.7 c Population (billion) Population in billions 99.99 244.6 0.004 1.354 c Other languages (0 or 1) Use of a domestic language except English 0.92 0.27 0 1 d Advertising intensity (%) Total advertising revenue/GDP 0.65 0.30 0.1 1.87 a aPwC. b Webcertain. c Global Market Information Database. d Central Intelligence Agency (2013) The World Factbook. S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 989

Table 2 Empirical results.

D.V¼Online advertising intensity (1) (2) (3) (4) (5) Pooled-OLS Fixed effect Random effect System GMM1 System GMM2

Broadband internet penetration 0.0005 0.0007 0.00001 0.00015 0.0002 (1.09)a (1.03)a (0.03)a (0.68)b (0.73)b

Population 0.006 0.049 0.022n 0.018 0.008 (0.40) (0.27) (1.74) (1.02) (0.47)

Other languages 0.06n 0.057n 0.004 0.029 (1.81) (1.74) ( 1.41) ( 1.45)

Computer penetration 0.002nnn 0.002nnn 0.002nnn 0.0002 0.0002 (5.87) (2.80) (4.15) (0.97) (0.61)

Domestic search engine 5 0.053nn 0.047nn 0.029nn (2.60) (2.27) (2.11)

Domestic search engine 8 0.018n (1.94)

Constant 0.049 0.037 0.028 0.026 0.021 (1.39) (1.50) (0.81) (0.93) (0.94)

1-year lagged online Advertising. Intensity 0.91nnn 0.942nnn (15.48) (13.39)

Observations R2 230 230 230 184 184 0.6816 0.4380 F statistics/Wald Chi2 F (5, 45)¼ F (3, 45)¼ Chi2 (5)¼ Chi2 (6)¼ Chi2 (10)¼ 29.51nnn 15.09nnn 92.62nnn 4221.15nnn 2962.88nnn Arellano-Bond test AR(1) 1.30 1.37 Arellano-Bond test AR(2) 1.46 1.34 Sargan test 24.43 24.22

Note: Variables in italics are instrumented through the GMM procedure following Arellano and Bover (1995). Models (1) and (2): t statistics in parentheses calculated from robust standard errors. Model (3): z statistics in parentheses calculated from robust standard errors. Models (4) and (5): z statistics in parentheses calculated from Windmeijer (2005) standard errors. ***, **, and * denote statistical significance at 1%, 5%, and 10% levels, respectively.

statistics and sources of the data used. In Appendix 2, the correlation matrix among the variables is specified.

5. Empirical results

The purpose of our econometric analysis was straightforward. We tried to identify the existence of a domestic search engine as a parameter that we hypothesized. In Models (1), (2), (3), (4), and (5) of Table 2, the pooled-OLS, the fixed effect, the random effect, and two system GMM (Arellano-Bover) models with different domestic search engine defi- nitions are specified, respectively. All control variables are jointly significant in the five models: The F or chi-square statistics in all five models are significant at a level of.01. The signs of the significant coefficients are highly consistent, although their sizes change slightly across the five models. Therefore, the following discussion is based mainly on Models (4) and (5), which control both the endogeneity of the control variables and the dynamic aspects of the online advertising market.

5.1. Static model results

The first three columns of Table 2 show the results of three different methods of static panel specifications concerning the effects of an existing domestic search engine. The estimation of Model (1) based on the pooled-OLS model shows an R2 of 0.6816, thus confirming that the model has satisfactory explanatory power. The mean of the variance inflation factor (VIF), a widely used measure of the degree of multi-collinearity, is 2.56, and no VIF of any of the control variables is greater than 5, indicating little collinearity among them. In Model (2), the fixed effect model, the time-invariant Domestic search engine 5 and the Other languages variables are dropped because this model's mean-differencing procedure elim- inates all country-fixed effects so that only within-country variations in the data are used in the estimation. The random effect estimation results of Model (3) are very similar to those of Models (1) and (2), especially in the case of the time- invariant variables. 990 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995

Specifically, the coefficients of Domestic search engine 5 in Models (1) and (3) are positive and significant, thus supporting the hypothesis that the existence of a domestic search engine contributes to an increase in the size of the online advertising market. The coefficients of Computer penetration are positive and significant across the first three models, implying that computer penetration might be associated with the size of an online advertising market; however, the coefficients of Broadband Internet penetration are not significant. This result may be due to the high correlation between Broadband Internet penetration and computer penetration: When the Computer penetration is dropped in the model, the coefficients of Broadband penetration become positive and significant in all three models, confirming the positive relationship between online advertising market size and the development of the Internet. The coefficients of Other languages are negative and marginally significant at a level of 0.10, indicating that the use of a domestic language other than English has a negative effect on the increase of online advertising revenue. Considering that most Web pages are presented in English, this result implies that the World Wide Web is still being developed using English content, which influences the size of the online advertising market.

5.2. Dynamic model results

We included a one-year lag of the dependent variable among the other control variables and used internal instruments generated from a system GMM estimation procedure to test the robustness of our model and to address our concerns about the endogeneity of a few control variables and the dynamic aspect of the online advertising market. The internal instruments employed were the lagged values by one period of the endogenous covariates and the lagged value by one period of the dependent variable. The fourth column—Model (4) in Table 2—indicates that the resulting coefficients broadly confirm previous estimates, with the exception that the coefficient on Other languages has become insignificant; however, its sign is still negative, implying that the use of a language other than English might be negatively associated with the size of the online advertising market. Similar to the results obtained from other specifications, neither the coefficients of Broadband Internet penetration or of Computer penetration are significant; however, again, when we drop Computer penetration from the model, the coefficient of Broadband Internet penetration becomes significant at a level of 0.05, implying its positive effect on the size of the online advertising market. The coefficient of Domestic search engine 5 is positive and significant, thus confirming the hypothesis that domestic search engines contribute to the expansion of the online advertising market. It is worth noting that the lagged dependent variable is positive and significant, indicating positive, indirect externalities arising from the previous structure of the online advertising industries. Arellano–Bond autocorrelation tests applied to the differenced residuals in the GMM models indicate that there are no problems relating to serial correlation in levels as the AR(2) tests are insignificant. Since 22 internal instruments were used to estimate five parameters, there are 17 over-identifying restrictions. The Sargan test (Sargan, 1980) did not reject the over-identification hypothesis, thus confirming the validity of the internal instruments. As discussed in Section 4.1, we expanded the definition of the domestic search engine variable from five countries to eight (by including Italy, Germany, and the Netherlands in the domestic search engine category) and estimated Model (4) again. The results of Model (5) are similar to those of Model (4), where we confirm the positive effect of a domestic search engine on the expansion of the online advertising market. Interestingly, when the definition was expanded to include three more countries, the size of the coefficient of Domestic search engine decreased from 0.029 in Model (4) to 0.018 in Model (5). This change may indicate that the inclusion of these three countries with weak domestic search engines in the domestic search engine category may decrease the estimated effect of domestic search engines on the size of the online content market, implying that the higher the market share of domestic search engines, the stronger will be their effects on their online advertising markets will be. It should be noted that the coefficients of domestic search engines across all four models (except for the fixed effect in Model (2)) are positive and statistically significant. These results are consistent with what we might expect, in that the existence of a domestic search engine increases the size of the online advertising market. The most conservative result, in Model (5), shows that the existence of a domestic search engine leads to an increase in the size of the online advertising market as a proportion of GDP at 0.018%. In dollar terms, this effect is equivalent to a $234.8 million market expansion in the Korean online advertising market in 2013. A possible concern with these results is that they may be driven by the presence in our sample of the countries in which the development of the online advertising market is very low and thus the online advertising market is persistent across our time span. In order to check the robustness of our estimation, we conducted the same analyses with an alternative sample: The countries in which the size of the online advertising market was less than the median (0.0417% of GDP) in 2009 were excluded, leaving only 26 countries in our sample. Table 3 shows the results with the alternative sample that are similar to those in Table 2, where we reconfirm the positive effect of a domestic search engine on the increase in the size of the online advertising market. S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 991

Table 3 Empirical results with the reduced sample.

D.V¼Online advertising intensity (1) (2) (3) (4) (5) Pooled-OLS Fixed effect Random effect System GMM1 System GMM2

Broadband internet penetration 0.0007 0.0027 0.0004 0.00001 0.00001 (1.61)a (2.33)a (0.753)a (0.04)b (0.05)b

Population 0.013 0.202 0.044 0.01 0.032 (0.41) (0.25) (1.44) (0.30) (0.44)

Other language 0.046 0.047 0.019 0.016 (1.45) (1.53) (3.08) (0.90)

Computer penetration 0.003nnn 0.002n 0.003nnn 0.0002 0.0001 (5.85) (1.90) (3.99) (0.30) (0.18)

Domestic search engine 5 0.059n 0.048 0.033nn (2.04) (1.24) (2.41)

Domestic search engine 8 0.03n (1.86)

Constant 0.016 0.147 0.062 0.014 0.019 (0.34) (3.55) (1.41) (0.76) (0.54)

1-year lagged online Advertising. Intensity 0.976nnn 1.038nnn (9.33) (13.37)

Observations 130 130 130 104 104 R2 0.5500 0.5880 F statistics/Wald Chi2 F (5, 25)¼ F (3, 25)¼ Chi2 (5)¼ Chi2 (6)¼ Chi2 (10)¼ 10.95nnn 31.94nnn 43.03nnn 1293.50nnn 1305.03nnn Arellano-Bond test AR(1) 1.37 1.49 Arellano-Bond test AR(2) 0.76 0.60 Sargan test 14.40 15.99

Table 4.1 Alternative results with a China dummy.

D.V¼Online advertising intensity (1) (2) (3) (4) (5) Pooled-OLS Fixed effect Random effect System GMM1 System GMM2

Domestic search engine 5 0.056nn 0.052nn 0.03nn (2.56) (2.26) (2.57)

Domestic search engine 8 0.02n (2.35)

China 0.034 0.046 0.055 0.003 (1.61) ( 1.53) (1.06) ( 0.04)

Observations 230 230 184 184

Note: The coefficients of Domestic search engines 5 and 8 only are presented. Complete results are available from the authors upon request. Models (1) and (2): t statistics in parentheses calculated from robust standard errors. Model (3): z statistics in parentheses calculated from robust standard errors. Models (4) and (5): z statistics in parentheses calculated from Windmeijer (2005) standard errors. ***, **, and * denote statistical significance at 1%, 5%, and 10% levels, respectively.

Finally, in order to control for the peculiar situation in China—where Google has had a tense relationship with the government since 2006 when it first launched its local branch, Google.cn, because of Internet censorship issues—we made two types of additional analyses. First, we conducted GMM analyses excluding China from our sample. Second, we added a dummy variable, China, into the econometric models, which may capture the peculiar condition in China. As shown in Tables 4.1 and 4.2, the overall results are the same as the results in Table 2, thus confirming again the positive effects of domestic search engines. Interestingly, the signs of the coefficients for China in Table 4.1 are negative (but not significant), possibly implying that government censorship in China may have a negative effect on the size of the online advertising market. 992 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995

Table 4.2 Alternative results excluding China.

D.V¼Online advertising intensity (1) (2) (3) (4) (5) Pooled-OLS Fixed effect Random effect System GMM1 System GMM2

Domestic search engine 5 0.056nn 0.053nn 0.03nn (2.56) (2.33) (1.97)

Domestic search engine 8 0.02n (2.30)

Observations 225 225 180 180

6. Conclusion

This study investigated the effect of domestic search engines on the development of the online advertising market. It was hypothesized that the existence of a domestic search engine contributes to the expansion of the online advertising market due to improvements in search quality and through its ability to offer customized content, thereby leading to an increase in the number of users of the domestic engine's services. The various econometric specifications that we tested by using alternative samples consistently showed that the existence of a domestic search engine contributes significantly to an increase in the size of the online advertising market. This result suggests that a domestic search engine may create new economic value that boosts the online advertising market. Along with their evident economic benefits, domestic search engines may create intangible cultural value, in that they may not only reflect local preferences and characteristics better and more accurately than global ones, but may also contribute to the creation and distribution of more local content (Segev, 2010). They have also been considered in the broader context of what may be termed “information sovereignty”: the ability to create, collect, and manage information circulating inside one's own country. In this respect, some advocates have argued that American-based global search engines tend to commodify online information and intensify the asymmetry of information flow worldwide, thus supporting the growth of U.S.-centric points of view on a whole range of issues, political, cultural, commercial, ideological, etc. (Jin, 2013; Litterick, 2005; Segev, 2008). Correspondingly, some consider the dominant American-based search engines to be a tool which augments U.S. cultural hegemony (Fuchs, 2011; Jin, 2013). In this respect, some government and political leaders in a few countries have realized the tremendous impact that search engines have in the cultural, social, and economic spheres, and have therefore tried to develop their own domestic search engines.5 In spite of the importance of domestic search engines, however, there are still unresolved questions as to whether they create new value in the domestic market and what factors have contributed to the existence and success of domestic search engines in particular countries. Our findings may contribute valuable evidence that may be taken into account by future scholars and media policy makers whose goal is to gain further insight into the benefits of the existence of domestic search engines. We must point out some of the limitations of our study. Although the data available to us included very detailed segments of the online advertising market in 46 countries over a 5-year period, the use of such a sample may not be free from certain possible biases and may need further confirmation in order for us to be able to generalize a conclusion that would be applicable to the worldwide situation. The sample of 46 countries was not a random one, as we selected only those countries for which detailed media revenue data were available. This might have biased the parameter of the domestic search engine variable that the models predicted. However, considering that those 46 countries include most of the major ones, the findings which we have arrived at here do imply that there is a positive effect of domestic search engines on the online advertising industry. Moreover, due to the limitations of our data gathering, the time span covered by this study in our 46 countries is five years, which does not allow us to make a comparison between the periods before and after the emergence of a domestic search engine. Ideally, it would be desirable to use a sample which covered a longer period of time, one which would encompass both pre- and post-domestic engines’ arrival dates. However, various panel data analyses that we have used consistently reveal the positive effects of domestic search engines on the size of the online advertising market. In addition, when defining a domestic search engine, we coded the existence of search engines as a dummy, because the systematic panel data of the market share in the search market either do not exist or are very limited. This dummy coding does not reflect the increasing and decreasing fluctuations of the domestic search engine market share in any given country,

5 According to O’Brien (2006), in 2005 the French attempted to launch a joint project with Germany named “Quaero” (meaning “I search” in Latin), to develop a next-generation European search engine aimed at increasing Europe's role in the production and distribution of online information. Germany and Norway also tried to launch the “Theseus” and “Pharos” projects in order to develop European domestic search engines which could challenge the dominance of the American giants Google and Yahoo! (L’Atelier, 2007). All of those efforts, however, failed. S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995 993 which may affect the domestic online advertising market differently. For example, Seznam's market share in the search engine market of the Czech Republic (presented in Appendix A) decreased from 48% in 2011 to 26% in 2013; however, our dummy coding does not reflect this trend in Seznam's market share. Ideally, year-to-year variations in the market shares of domestic search engines will better capture the relationship between the existence of domestic search engines and the change in the size of the advertising market. Finally, the present study only considers the narrowly defined Internet search engines in a traditional way; it does not consider other emerging forms of search-like services. For example, users who are accustomed to searching with a desktop PC are now getting answers from different platforms and different technologies (e.g., Facebook, Amazon, Apple (Siri), etc.). Moreover, the development of mobile technologies in some countries has led to changes in the search platform – from PC to smart phones, for example. As a result, the development of the mobile Internet and the rapid diffusion of smartphones may affect the relationship between domestic search engines and the size of the online advertising market.6 Thus, more interesting and plausible implications could be drawn if we were to consider the search market from a more broad point of view. Therefore, the present study can only serve as a starting point for future research, which should ideally be carried out using more detailed data on more countries, and with more sophisticated econometric models that are able to control for these issues.

Appendix A

See Table A1.

Table A1 Domestic search engines in each country.Sources: market share information from Webcertain (2011, 2012, 2013, 2014) and Kennedy and Hauksson (2012).

Country Domestic search Date of foundation Percentage (%) of local Domestic search Market share (%) engines investmenta technology 2011 2012 2013

South Korea Naver 1999 100 Yes (Nexus) 73 73 72 Daum 1995 100 Yes 22 15 18 NATE 2003 SKT subsidiary Yes 4 4 4

Japan Yahoo! Japan 1996 Yahoo! (34.75); SoftBank (35.45) Nob 56.2 50 53

China Baidu 2000 – Yes (Baidu Spider) 71.6 61 62 Qihoo (360 Search) 2005 – Yes – 9.5 21 Sogou 2004 Tencent (36.5) N/A 1.1 6 – Soso 2006 Tencent Holdings Limited Yes (Sosospider) 4 4 –

Russia Yandex 2000 – Yes (MatrixNe) 62 60 62 mail.ru 1998 – Yes 7 7 –

Czech Republic Seznam 1996 – Yes (SeznamBot) 48 43 26

Italy Virgilio 1995 Takeover by Telecom Italia in Yes 5 –– 2012

Germany T-online N/A Deutsche Telecom subsidiary No (Uses Google engine) 3 ––

Netherlands Vinden 1998 – Yesc 3 ––

a Source of capital not from global platform business. b Uses the Google search engine and revises search results using YST, a search technology developed by Yahoo U.S. (Nakamura, 2010; Wakabayashi & Maxwell, 2010). c Vinden is a meta-search engine that gathers and displays several search results, and thus does not possess a database of its own.

6 The current development of the mobile Internet raises an interesting question about how the mobile Internet changes the positive effect of domestic search engines on the size of the advertising market. The direction of the effect will necessarily be incomplete or speculative due to the lack of the empirical evidence. However, when mobile broadband is taken into consideration, the influence of domestic search engines on the online advertising market may be amplified. The mobile search services offered by domestic search engines would positively affect the amount of mobile broadband usage because they are, similar to PC-based search services, customized for domestic users, and thus may boost the mobile access in the domestic market. The increase of mobile access could also positively affect to the online advertising market. This effect may be changed depending on whether mobile broadband is a complement (Lee, Marcu, & Lee, 2011; Wulf, Zelt, & Brenner, 2013) or a substitute for fixed broadband (Srinuan, Srinuan, & Bohlin, 2012). One possible scenario is that, assuming that the relationship is complementary in the countries with high fixed broadband penetration (Wulf & Brenner, 2013), the increase in mobile penetration could also amplify the effect of fixed Internet penetration on the development of the online advertising market. 994 S.W. Ji et al. / Telecommunications Policy 40 (2016) 982–995

Appendix B

See Table B1.

Table B1 Correlation matrix.

Online Ad. Broadband Population Other Computer Domestic 5 Domestic 8

Online advertising intensity 1 Broadband Internet penetration 0.6067nnn 1 Population 0.1508nn 0.3490nnn 1 Other languages 0.4043nnn 0.1775nnn 0.0823 1 Computer penetration 0.7539nnn 0.8782nnn 0.3725nnn 2425nnn 1 Domestic search engine 5 0.2510nnn 0.0721 0.3165nnn 0.0942 0.0201 1 Domestic search engine 8 0.3276nnn 0.1599nnn 0.2277nnn 0.1231n 0.1249n 0.7649nnn 1

***, **, and * denote statistical significance at 1%, 5%, and 10% levels, respectively.

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