TY - JOUR
AU - Symeou, Pavlos, C.
AB - Abstract This project investigates the classic agenda-setting hypothesis in the context of the Greek cultural market. It is hypothesized that Greek museums with higher visibility in newspaper content are related to higher visitation than museums with lower media visibility. Because of the nature of the Greek cultural market—Greece receives more than 10 million tourists during the summer months—several variables are controlled for, such as the seasonality of visitation, the type of governance of the organization, one-time events, such as the Olympic Games, which took place in the summer of 2004, and promotion initiatives undertaken by museums. When controlling for such culturally specific variables, there is evidence supporting the agenda-setting hypothesis within the Greek cultural market. During the past 40 years, agenda setting has emerged as a prominent theory in the field of media studies. Its basic hypothesis that the media attribute significance to certain issues, which subsequently is transferred to the public, has influenced scholars from different disciplines. Numerous studies have been conducted since the seminal Chapel Hill study (McCombs & Shaw, 1972). For example, the “issues of the 1960s” study (Funkhouser, 1973) replicated the original Chapel Hill study while refining the original hypothesis articulated by Bernard Cohen that the media are successful in telling people “what to think about” (Cohen, 1963, p. 120). During the first 2 decades since its inception, the agenda-setting theory has been tested in different settings both in the United States and abroad while researchers applied it in the context of elections and public policy. Agenda setting has become a standard reading for political communication students. As McCombs and Shaw discovered a relationship between what the media and the public perceive as important, new theoretical terminology emerged. This process became to known as the “transfer of salience.” Media salience was defined as issue attention, prominence, and valence (Kiousis, 2004), but most importantly, as attention—the sheer volume of coverage attributed to a particular issue. On the other hand, often members of the public were asked to rank issues according to their perceived valence (Kiousis, 2004). The Chapel Hill study provided researchers with fundamental conceptual tools that described the transfer of salience processes, allowing scholars to examine the original agenda-setting hypothesis from different perspectives in conjunction with different variables. This enabled researchers to refine the hypothesized effects. For example, researchers differentiated between obtrusive and unobtrusive issues with respect to their potential for salience in the public mind (Zucker, 1978). In the course of the 40-year period, researchers used different methodological tools to test the agenda-setting hypothesis. As more sophisticated questions emerged, researchers did not rely exclusively on surveys but employed more advanced methodological tools, such as experimental designs to examine the role of electronic media as agenda setters. In this context, experimental evidence demonstrated television's capability to set agendas (Iyengar, Peters, & Kinder, 1982). Reese and Danielian (1989) coined the term “intermedia agenda setting” demonstrating how media can influence other media in terms of issue salience. In the 1990s, McCombs and his colleagues turned their attention to the so-called second-level agenda setting. They argued that issues—also known as “objects”—are comprised of attributes or frames. In this context, researchers examined which particular attributes contribute to object–issue salience, as well as how individual frames become salient, also known as “compelling arguments” (Ghanem, 1997). Identifying and analyzing such attributes provides useful explanations of salience. This attribute-frame analysis reveals not only what audiences think about but also how they think about issues presented by the media (Ghanem, 1997). The current project Agenda-setting theory has rarely been applied in fields outside political campaigns and public policy. Researchers have been concerned primarily about issue salience while the scope of the theory has been expanded “to investigate the salience of political candidates” (Kiousis, 2004). Assessing the salience of political personalities became a significant milestone in agenda-setting research, and nowadays researchers are equipped with additional theoretical tools for political communication analysis (Kiousis, Bantimaroudis, & Ban, 1999). The agenda-setting theory has evolved further as different case studies pursued by scholars expanded the scope of the theory beyond the field of politics and public policy into the realm of corporate, environmental, and cultural terrains. Recently the concept of object salience has incorporated the organization both as a business and a cultural entity (Carroll & McCombs, 2003). In this research, the authors attempt to test the agenda-setting hypothesis in the context of cultural organizations. The authors decided to test the agenda-setting hypothesis only at its first level for three reasons: (a) The agenda-setting theory has not been investigated in the context of cultural organizations; therefore examining the initial agenda-setting hypothesis constitutes a reasonable starting point. (b) The cultural market is inherently different compared with the realm of politics and even the mainstream corporate environment. Therefore, some introductory, basic assessments need to be made in terms of the agenda-setting process before different traits of cultural entities can be effectively scrutinized. (c) Measuring the sheer volume of coverage—object salience—while utilizing the different newspaper databases allowed the researchers to expand significantly the population of the explored content as well as to minimize errors and increase the reliability of measurements—not always attainable through the usual human coding practices. Although the field of cultural industries has received significant attention by communication and cultural scholars, no studies have examined the agenda-setting theory from the perspective of cultural industries. In this study, the cultural organization is the “object.” Thus, museums are cultural industries that have evolved from being simple depositories of artifacts to becoming sophisticated cultural industries adopting business and marketing techniques for the promotion of their products and services. This transformation of cultural organizations naturally led to the adoption of advertising and public relations practices that are employed in other industries. Thus, traditional relationships between museums and their publics have been modified. In the past, only a few cultural organizations engaged in audience research, analyzing what their public thought about their identity, mission, and services. Currently, analyzing public perceptions, attitudes, and consumer behaviors is a prerequisite for all cultural organizations, both private and public. A few decades ago, museums were exclusively relying on public subsidies. This trend has now changed irreversibly. Public funding for cultural causes has diminished, forcing cultural executives to look for support in the private sector. Furthermore, a rapid proliferation of different kinds of cultural organizations has created an environment of intense competition for both public and private funds. Twitchell (2004) reports that only 60% of American museums “have enough income from their endowment to cover their operating costs. So, competitive branding is inevitable” (p. 197). Furthermore, … the Europeans face the same dilemma, but with a difference. They have a long history of last-minute state support. Thatcherism, which cut loose English museums from what was sometimes 90 percent funding, has spread to the continent. Until 1993, the Louvre was entirely state-funded. Now the national museum must find 30 percent of its yearly operating costs on its own. The Louvre still has only four full-time fund-raisers on its staff, compared with fifteen at the various Tates in London and forty at the Metropolitan Museum in New York (p. 197). Competing for funding has led to the adoption of marketing and communication approaches by cultural institutions, and researchers studying cultural organizations have acknowledged this new reality. For example, Smith, Discenza, and Baker (2005) compare small art galleries with small businesses arguing that both types of organizations have to rely on similar business strategies. McNichol (2005) highlights the importance of branding for small museums, while Olkkonen and Tuominen (2006) establish the significance of museum sponsorship. This transformation from cultural institutions to cultural industries affects the overall experience produced: “To survive, organizations in cultural industries must reconcile the demands of artistic production with those of the marketplace” (Lampel, Lant, & Shamsie, 2000, p. 265). Research hypothesis The authors set the following central research hypothesis: H0: Museums that are more visible in media content are more likely to receive higher visitation by the public. This is a modified first-level agenda-setting hypothesis. The study examines a relationship between museum media salience and public salience. As this hypothesis has been investigated primarily in the context of political communication, this study intends to expand the concept of agenda setting, examining the salience of cultural organizations. The indicator of public salience utilized for this project is not quite common in the agenda-setting literature. The most common indicator of public salience deals with people's perceptions recorded in surveys. In such research, respondents are asked to identify significant public issues (e.g., “name the most significant problem faced by the country today” or “rank the most significant problems faced by the country today”). In the context of this project, public salience was measured not as a recorded perception of prominence, but as quantified behavior. It is safe to assume that the number of ticket sales signifies organizational importance as museum visitors do not verbalize their preferences but indicate them by visiting the museums. Even though our measurement of public salience—measuring visitors' behavior (visitation) rather than perception (what they thought about those particular museums)—is not typical within the agenda-setting literature, the authors argue that it represents a reliable measure of public salience. Early public opinion research demonstrated three categories of audience salience: perception, attitude, and behavior (Hovland, Lumsdaine, & Sheffield, 1949). Although agenda-setting researchers rarely examined behavior as a form of public salience, there are some case studies recorded in McCombs (2004), using behavior as an indicator of public salience. For example, Roberts (1992) examined the impact of issue salience on voting patterns, whereas Stevenson, Bohme, and Nickel (2001) analyzed citizens' discussions, reflections, and their recorded desire for more information. Moreover, there are some noticeable examples where behavior is used as an indicator of public salience outside the field of politics. McCombs linked media coverage of college crime and violence to a decline in college applications, and in the same work he also links reports of airplane accidents to “risk avoidance behavior.” Furthermore, a public campaign initiated by researchers affiliated with Harvard University for the promotion of the “designated driver” idea influenced the behavior of young adults in a positive manner as driving became less risky, particularly after group drinking (Graber, 2001). In the same context, this study aims to contribute to this discussion of media agenda setting and public behavior in relation to the media salience of cultural organizations. Methodology Two categories of data, media prominence visibility, measured by the number of times a museum can be traced in the archival database content of three national newspapers, and public salience, measured by the number of museum visitors, became available and subject to an empirical analysis (e.g. Neuman, 1989). To assess media visibility in a reliable fashion, the authors drew on the digital archives of three major national Greek newspapers. These three—Kathimerini, Ta Nea, and Eleftherotypia—were chosen because they are important Athenian daily newspapers distributed nationally and enjoy a high rate of readership. All three combined have about 600,000 readers daily and can be described as national elite media whose coverage often influences content selections of other regional and national media, both print and broadcasting. Furthermore, they possess sophisticated databases making available their published archived content through their Web site. The agenda-setting literature demonstrates that the sheer volume of coverage has been routinely used as a reliable measure of media salience (Kiousis, 2004). Therefore, counting the number of times a museum appears in newspaper content was deemed adequate for the current first-level agenda-setting analysis. Because of their national recognition, we chose seven museums covering a wide array of cultural organizations, both from Athens and other regions of Greece, as well as public and private1 ones. These seven museums are: (a) The National Archaeological Museum (NAM) is the largest public museum in Greece, which houses more than 20,000 exhibits. (b) The Archaeological Museum of Olympia is a regional public museum, which houses important exhibits from ancient Olympia, the cradle of the Olympic Games. (c) The Byzantine and Christian Museum, located in Athens, houses significant collections from the Byzantine and post-Byzantine era. (d) The Athens Numismatic Museum exhibits a collection of more than 600,000 coins from the Greek antiquity as well as the Byzantine and modern periods. (e) The National Gallery, located in Athens, houses more than 15,000 works of painting, sculpture, engraving, and other forms of art from the post-Byzantine period until today. (f) The Benaki Museum (BM), located in Athens, and perhaps the most significant private museum of Greece, presents an array of cultural products and exhibitions. (g) Finally, the Archaeological Museum of Thessaloniki, a significant public museum, located in Thessaloniki, the second largest Greek city of Greece, houses significant treasures from the regions of Macedonia and Thrace. These organizations were selected because they are established cultural institutions, recognized by the Greek public, and receive extensive coverage by the Greek media. Their coverage was measured on a monthly basis for a period of 37 months. The newspaper databases were searched to find the number of times a museum appeared in the newspaper content each month from June 2004 until June 2007. We measured public salience as the number of museum visitors per month for the same time period. The data pertaining to Greek museum visitors were drawn from the Web site of The General Secretariat of National Statistical Service of Greece.2 The same service provides the monthly income of every museum in Euros. Visitors and income are not identical indicators of visitation because museums provide free access to various groups like pupils, university students, and other special groups of visitors. Notwithstanding, monthly visitors and income have a very high correlation of.87 (Table A3). Other indicators of public salience were not available as surveys are rarely conducted by museums and, when they are, they constitute proprietary research, not available outside the organizations. Analysis A multiple regression model was developed for the analysis of multitudinal data comprising seven cross-sections (museums) and 37 time series (months). The generic model has the following form: where i = 1,2,…,7 is the subscript for the cross-sectional dimension and t = 1,2,…,12 is the subscript for the time-series dimension. yit is a T× 1 vector representing visitation; αi is a 1 × 1 scalar constant; β is a series of coefficients corresponding to xit series of exogenous variables (see Table 1 for variable description); ui is a T× 1 vector of the effects of omitted time-invariant museum-specific variables; and eit is a random disturbance variable assumed to be distributed identically and independently with zero mean and finite, constant variance. Table 1 Variables Involved in the Econometric Analysis . Description . Source . Dependent variable  Visitation The number of museum visitors The General Secretariat of National Statistical Service of Greece Independent variables  Visibility A construct denoting the total coverage of a museum in available newspapers Developed by the authors  Ta Nea Museum coverage in the newspaper “Ta Nea” Newspaper's online database  Eleftherotypia Museum coverage in the newspaper “Eleftherotypia” Newspaper's online database  Kathimerini Museum coverage in the newspaper “Kathimerini” Newspaper's online database Control variables  Olympics A dummy variable denoting the event of the Olympic Games in Athens in July and August 2004 Developed by the authors  Promotion Museum income divided by the product of the number of visitors multiplied by ticket price, transformed in logarithms The General Secretariat of National Statistical Service of Greece  GDP per capita GDP in constant Euro of 2005 transformed in logarithms Eurostat  Location A dummy indicating whether the museum is located in Athens Developed by the authors  Type A dummy indicating whether the museum is private Developed by the authors  Month-dummies Dummy variables for every calendar month Developed by the authors . Description . Source . Dependent variable  Visitation The number of museum visitors The General Secretariat of National Statistical Service of Greece Independent variables  Visibility A construct denoting the total coverage of a museum in available newspapers Developed by the authors  Ta Nea Museum coverage in the newspaper “Ta Nea” Newspaper's online database  Eleftherotypia Museum coverage in the newspaper “Eleftherotypia” Newspaper's online database  Kathimerini Museum coverage in the newspaper “Kathimerini” Newspaper's online database Control variables  Olympics A dummy variable denoting the event of the Olympic Games in Athens in July and August 2004 Developed by the authors  Promotion Museum income divided by the product of the number of visitors multiplied by ticket price, transformed in logarithms The General Secretariat of National Statistical Service of Greece  GDP per capita GDP in constant Euro of 2005 transformed in logarithms Eurostat  Location A dummy indicating whether the museum is located in Athens Developed by the authors  Type A dummy indicating whether the museum is private Developed by the authors  Month-dummies Dummy variables for every calendar month Developed by the authors Open in new tab Table 1 Variables Involved in the Econometric Analysis . Description . Source . Dependent variable  Visitation The number of museum visitors The General Secretariat of National Statistical Service of Greece Independent variables  Visibility A construct denoting the total coverage of a museum in available newspapers Developed by the authors  Ta Nea Museum coverage in the newspaper “Ta Nea” Newspaper's online database  Eleftherotypia Museum coverage in the newspaper “Eleftherotypia” Newspaper's online database  Kathimerini Museum coverage in the newspaper “Kathimerini” Newspaper's online database Control variables  Olympics A dummy variable denoting the event of the Olympic Games in Athens in July and August 2004 Developed by the authors  Promotion Museum income divided by the product of the number of visitors multiplied by ticket price, transformed in logarithms The General Secretariat of National Statistical Service of Greece  GDP per capita GDP in constant Euro of 2005 transformed in logarithms Eurostat  Location A dummy indicating whether the museum is located in Athens Developed by the authors  Type A dummy indicating whether the museum is private Developed by the authors  Month-dummies Dummy variables for every calendar month Developed by the authors . Description . Source . Dependent variable  Visitation The number of museum visitors The General Secretariat of National Statistical Service of Greece Independent variables  Visibility A construct denoting the total coverage of a museum in available newspapers Developed by the authors  Ta Nea Museum coverage in the newspaper “Ta Nea” Newspaper's online database  Eleftherotypia Museum coverage in the newspaper “Eleftherotypia” Newspaper's online database  Kathimerini Museum coverage in the newspaper “Kathimerini” Newspaper's online database Control variables  Olympics A dummy variable denoting the event of the Olympic Games in Athens in July and August 2004 Developed by the authors  Promotion Museum income divided by the product of the number of visitors multiplied by ticket price, transformed in logarithms The General Secretariat of National Statistical Service of Greece  GDP per capita GDP in constant Euro of 2005 transformed in logarithms Eurostat  Location A dummy indicating whether the museum is located in Athens Developed by the authors  Type A dummy indicating whether the museum is private Developed by the authors  Month-dummies Dummy variables for every calendar month Developed by the authors Open in new tab The focal independent variable of the model concerns the media visibility variable (Visibility). Visibility is expressed as a construct denoting the total coverage of a museum in all three newspapers (Media coverage is primarily, but not exclusively, prompted by events organized by museum personnel and publicized through the dissemination of press releases). First, the monthly number of references of a museum in a newspaper is divided by the newspaper's mean. Then the quotients for the three newspapers are added together to form each museum's monthly visibility score. The expected relationship between visibility and the dependent variable is positive because an increase in the museum's public exposure through the newspapers is envisaged to increase the number of museum visitors. A number of control variables are included in the model in order to account for museum-specific characteristics, environmental effects, and seasonality in the data. Namely, the “Olympics” variable is a dummy variable that takes the value of 1 if the month is July or August 2004, and 0 if otherwise. The Olympic Games' effect on visitation is uncertain. On the one hand, museums might have jumped on the bandwagon of the Games benefiting from the significant increase in the number of visitors. On the other hand, the Olympic Games might have absorbed a number of people who otherwise would have visited a museum. The “Type” of the museum is a dummy variable that takes the value of 1 if the museum is a private institution and 0 if otherwise. Certain museums such as the BM function like private institutions taking initiatives for their promotion and fund-raising that likely have a positive effect on visitation. This variable recognizes those governance differences between cultural organizations. Moreover, the location of a museum might play a significant role in its attractiveness. Museums that are located in Athens, a city with a metropolitan population of 3.9 million in 2007, might have an advantage compared with those located in Thessaloniki that has only one third of Athens' population. Therefore, we anticipate that Athenian museums will have higher visitation levels. In order to control for this differential, the dummy variable “Capital” is included in the model to distinguish between Athenian and non-Athenian museums. The “Promotion” variable represents a relationship among museum income, the number of visitors, and the ticket price. Income is divided by the number of visitors multiplied by the ticket price. This ratio is always below the unit because a number of tickets are being sponsored or subsidized by the museums or affiliate organizations. Therefore, smaller ratios might imply that a larger number of visitors have visited the museum using a sponsored ticket. Correspondingly, the ratio acts as a proxy for the magnitude of promotion the museum receives. Promotion's relationship with visitation is expected to be positive. The variable is included in a logarithmic form. In order to account for people's disposable incomes, the model includes monthly GDP per capita in a logarithmic form. GDP per capita is widely used in empirical studies in the social sciences to control for the financial capacity of agents (i.e., museum visitors) to complete an activity that bears an economic cost. The variable is expressed in constant Euro prices of 2005 accounting for prices inflation. The expected relationship between people's disposable income and museum visitation is positive. Last, the econometric model includes a set of month-dummy variables to account for seasonality. Seasonality pertains to periodic fluctuations. In this article, it is treated as possible noise contaminating the underlying relationship between media visibility and museum visitation. For example, tourism tends to peak for the summer season (June to September) and declines after the holidays. It is very likely that time series of visitation will typically show increasing values during the summer period and declining values between October and May. Notwithstanding, the seasonal effect on visitation might be counterbalanced by the increased number of schools visiting the museums over the October to May period. Hence, it is essential that month-dummies are incorporated in the model. Findings A preliminary examination of data reveals that the media coverage variable does not follow a consistent seasonal pattern of coverage like the visitors variable (see tables in appendix for descriptive statistics). Coverage tends to be higher during fall and spring, but not in a consistent fashion. Furthermore, not all museums receive similar coverage by the media. By far, the most visible museum in the media is the BM with 2,217 references in all three newspapers, while the least covered is the Museum of Ancient Olympia with only 23 references. Moreover, the small correlations in Table A3 show that people's disposable income does not appear to have a relationship with people's museum visits. The model was subjected to the Hausman test in order to choose the most suitable estimation method among the fixed effects or the random effects transformations (Baltagi, 2005). The test produced a very small chi-square statistic suggesting that the use of a random effects model was more appropriate. Moreover, the regression model was estimated with robust standard errors in order to account for possible autocorrelation and heteroskedasticity in the disturbance term eit. Model A1 in Table 2 treats the main independent variable as a single comprehensive media visibility factor. The combined media visibility variable, museum promotion, museum governance form, and museum location are statistically significant at the.01 level. Visibility, Promotion, and Location influence museum visitation positively, whereas privately administered museums appear to have lower visitation than public museums. The Olympics and GDP per capita variables are not statistically significant and thereby do not seem to influence visitation. Furthermore, the seasonality effects are more prevalent over the summer period where coefficients exhibit the highest values. Yet, most month-dummies are statistically insignificant except for the August and September month-dummies that are significant at the 0.1 level.3 Table 2 Visitation as the Dependent Variable . Model A1 . Model A2 . Model B1 . Model B2 . Coefficient . SE . Coefficient . SE . Coefficient . SE . Coefficient . SE . Olympics 552 6,760 3,049 8,140 −29 6,774 2,899 8,166 Visibility 1,296 190*** 802 343** — — — —  Visibility (lagged) — — 585 340* — — — — Ta Nea — — — — 41 146 73 191  Ta Nea (lagged) — — — — — — −13 194 Eleftherotypia — — — — 615 252** 446 280  Eleftherotypia (lagged) — — — — — — 503 265* Kathimerini — — — — 179 287 83 295  Kathimerini (lagged) — — — — — — −219 304 Promotion 4,574 1,659*** 2,142 2,035 4,590 1,658*** 1,916 2,045  Promotion (lagged) — — 3,950 1,998** — — 4,040 2,000** GDP per capita 1,750 12,333 2,596 12,427 −1,112 12,467 182 12,574 Location 9,943 2,114*** 9,982 2,109*** 9,637 2,116*** 9,562 2,117*** Type −8,019 1,872*** −7,988 1,909*** −7,632 1,883*** −7,382 1,932*** Month-dummies:   February 1,144 3,403 854 3,431 1,671 3,408 1,458 3,456   March 3,121 3,394 4,540 3,431 4,242 3,448 5,930 3,513*   April 3,475 3,396 4,669 3,444 4,030 3,404 6,503 3,566*   May 5,020 3,434 5,619 3,439 5,433 3,439 6,394 3,459*   June 1,823 3,321 2,422 3,317 2,856 3,372 3,669 3,394   July 2,909 3,494 3,057 3,560 3,455 3,520 4,867 3,697   August 6,721 3,492* 6,473 3,494* 7,588 3,527** 7,446 3,536**   September 6,624 3,529* 6,790 3,560* 7,889 3,603** 8,223 3,641**   October 3,259 3,446 3,855 3,492 3,668 3,450 5,310 3,620   November −1,681 3,397 −2,165 3,423 −1,694 3,389 −1,492 3,454   December −1,987 3,393 −1,793 3,382 −2,131 3,394 −1,661 3,394 Observations 253 249 253 249 R2 (between) 0.51 0.51 0.51 0.52 Wald χ2 statistic 100.43 105.83 104.06 110.82 . Model A1 . Model A2 . Model B1 . Model B2 . Coefficient . SE . Coefficient . SE . Coefficient . SE . Coefficient . SE . Olympics 552 6,760 3,049 8,140 −29 6,774 2,899 8,166 Visibility 1,296 190*** 802 343** — — — —  Visibility (lagged) — — 585 340* — — — — Ta Nea — — — — 41 146 73 191  Ta Nea (lagged) — — — — — — −13 194 Eleftherotypia — — — — 615 252** 446 280  Eleftherotypia (lagged) — — — — — — 503 265* Kathimerini — — — — 179 287 83 295  Kathimerini (lagged) — — — — — — −219 304 Promotion 4,574 1,659*** 2,142 2,035 4,590 1,658*** 1,916 2,045  Promotion (lagged) — — 3,950 1,998** — — 4,040 2,000** GDP per capita 1,750 12,333 2,596 12,427 −1,112 12,467 182 12,574 Location 9,943 2,114*** 9,982 2,109*** 9,637 2,116*** 9,562 2,117*** Type −8,019 1,872*** −7,988 1,909*** −7,632 1,883*** −7,382 1,932*** Month-dummies:   February 1,144 3,403 854 3,431 1,671 3,408 1,458 3,456   March 3,121 3,394 4,540 3,431 4,242 3,448 5,930 3,513*   April 3,475 3,396 4,669 3,444 4,030 3,404 6,503 3,566*   May 5,020 3,434 5,619 3,439 5,433 3,439 6,394 3,459*   June 1,823 3,321 2,422 3,317 2,856 3,372 3,669 3,394   July 2,909 3,494 3,057 3,560 3,455 3,520 4,867 3,697   August 6,721 3,492* 6,473 3,494* 7,588 3,527** 7,446 3,536**   September 6,624 3,529* 6,790 3,560* 7,889 3,603** 8,223 3,641**   October 3,259 3,446 3,855 3,492 3,668 3,450 5,310 3,620   November −1,681 3,397 −2,165 3,423 −1,694 3,389 −1,492 3,454   December −1,987 3,393 −1,793 3,382 −2,131 3,394 −1,661 3,394 Observations 253 249 253 249 R2 (between) 0.51 0.51 0.51 0.52 Wald χ2 statistic 100.43 105.83 104.06 110.82 Note: January is the base month and therefore is omitted. Statistically significant at the * .1 level; ** .05 level *** .01 level. Open in new tab Table 2 Visitation as the Dependent Variable . Model A1 . Model A2 . Model B1 . Model B2 . Coefficient . SE . Coefficient . SE . Coefficient . SE . Coefficient . SE . Olympics 552 6,760 3,049 8,140 −29 6,774 2,899 8,166 Visibility 1,296 190*** 802 343** — — — —  Visibility (lagged) — — 585 340* — — — — Ta Nea — — — — 41 146 73 191  Ta Nea (lagged) — — — — — — −13 194 Eleftherotypia — — — — 615 252** 446 280  Eleftherotypia (lagged) — — — — — — 503 265* Kathimerini — — — — 179 287 83 295  Kathimerini (lagged) — — — — — — −219 304 Promotion 4,574 1,659*** 2,142 2,035 4,590 1,658*** 1,916 2,045  Promotion (lagged) — — 3,950 1,998** — — 4,040 2,000** GDP per capita 1,750 12,333 2,596 12,427 −1,112 12,467 182 12,574 Location 9,943 2,114*** 9,982 2,109*** 9,637 2,116*** 9,562 2,117*** Type −8,019 1,872*** −7,988 1,909*** −7,632 1,883*** −7,382 1,932*** Month-dummies:   February 1,144 3,403 854 3,431 1,671 3,408 1,458 3,456   March 3,121 3,394 4,540 3,431 4,242 3,448 5,930 3,513*   April 3,475 3,396 4,669 3,444 4,030 3,404 6,503 3,566*   May 5,020 3,434 5,619 3,439 5,433 3,439 6,394 3,459*   June 1,823 3,321 2,422 3,317 2,856 3,372 3,669 3,394   July 2,909 3,494 3,057 3,560 3,455 3,520 4,867 3,697   August 6,721 3,492* 6,473 3,494* 7,588 3,527** 7,446 3,536**   September 6,624 3,529* 6,790 3,560* 7,889 3,603** 8,223 3,641**   October 3,259 3,446 3,855 3,492 3,668 3,450 5,310 3,620   November −1,681 3,397 −2,165 3,423 −1,694 3,389 −1,492 3,454   December −1,987 3,393 −1,793 3,382 −2,131 3,394 −1,661 3,394 Observations 253 249 253 249 R2 (between) 0.51 0.51 0.51 0.52 Wald χ2 statistic 100.43 105.83 104.06 110.82 . Model A1 . Model A2 . Model B1 . Model B2 . Coefficient . SE . Coefficient . SE . Coefficient . SE . Coefficient . SE . Olympics 552 6,760 3,049 8,140 −29 6,774 2,899 8,166 Visibility 1,296 190*** 802 343** — — — —  Visibility (lagged) — — 585 340* — — — — Ta Nea — — — — 41 146 73 191  Ta Nea (lagged) — — — — — — −13 194 Eleftherotypia — — — — 615 252** 446 280  Eleftherotypia (lagged) — — — — — — 503 265* Kathimerini — — — — 179 287 83 295  Kathimerini (lagged) — — — — — — −219 304 Promotion 4,574 1,659*** 2,142 2,035 4,590 1,658*** 1,916 2,045  Promotion (lagged) — — 3,950 1,998** — — 4,040 2,000** GDP per capita 1,750 12,333 2,596 12,427 −1,112 12,467 182 12,574 Location 9,943 2,114*** 9,982 2,109*** 9,637 2,116*** 9,562 2,117*** Type −8,019 1,872*** −7,988 1,909*** −7,632 1,883*** −7,382 1,932*** Month-dummies:   February 1,144 3,403 854 3,431 1,671 3,408 1,458 3,456   March 3,121 3,394 4,540 3,431 4,242 3,448 5,930 3,513*   April 3,475 3,396 4,669 3,444 4,030 3,404 6,503 3,566*   May 5,020 3,434 5,619 3,439 5,433 3,439 6,394 3,459*   June 1,823 3,321 2,422 3,317 2,856 3,372 3,669 3,394   July 2,909 3,494 3,057 3,560 3,455 3,520 4,867 3,697   August 6,721 3,492* 6,473 3,494* 7,588 3,527** 7,446 3,536**   September 6,624 3,529* 6,790 3,560* 7,889 3,603** 8,223 3,641**   October 3,259 3,446 3,855 3,492 3,668 3,450 5,310 3,620   November −1,681 3,397 −2,165 3,423 −1,694 3,389 −1,492 3,454   December −1,987 3,393 −1,793 3,382 −2,131 3,394 −1,661 3,394 Observations 253 249 253 249 R2 (between) 0.51 0.51 0.51 0.52 Wald χ2 statistic 100.43 105.83 104.06 110.82 Note: January is the base month and therefore is omitted. Statistically significant at the * .1 level; ** .05 level *** .01 level. Open in new tab In order to examine whether the independent variables have an impact not only in the present period but also in subsequent periods, we included in the analysis time lags. Specifically, we estimated models that additionally involved 1-month and 2-month lags for media visibility, museum promotion, and GDP per capita. The inclusion of these additional variables did not yield a substantial contribution to the explanation of the variance of museum visitation (i.e., the R2 increased roughly from.5112 to.5134). In order to preserve model parsimony, a series of Wald statistics were estimated that allowed dropping from the model the unimportant variables. This process culminated in Model A2 in Table 2, which involves 1-month dummies for media visibility and museum promotion. There are two new major findings from this model. First, both Visibility and its lag are statistically significant. This suggests that a museum's visibility in the current month induces museum visitation in the following month. Yet, this effect is weaker than the effect that visibility has on visitation in the current month. Second, Promotion loses its statistical significance to its lag, which is itself statistically significant at the.05 level. This implies that museum promotion is more likely to induce visitation a month after its initiation than in the current month. The remainder of the control variables preserve their original relationships and to a great extent the magnitude of their effect on museum visitation as in Model A1. Furthermore, it is important to examine how each medium is separately related to museum visitation to assess whether there is an overall media influence versus an isolated medium influence. Hence, in Model B1, media visibility is separated into three distinct variables, namely the three newspapers. Compared with Model A1, there are some noteworthy differences. From the three national newspapers, one (Eleftherotypia) drives the media visibility effect, while Ta Nea and Kathimerini do not register as statistically significant. Promotion, Type, as well as Location are statistically significant variables. Furthermore, there is a strong effect on visitation due to seasonality during the months August and September. The coefficients of the respective month-dummies are statistically significant and exhibit substantially higher museum visitation compared with January, the base month-dummy. Similarly to Model A1, Model B1 was also reestimated with the inclusion of time lags. Model B2 in Table 2 additionally involves month lags for each separate medium and Promotion. Eleftherotypia still appears to drive the media visibility effect. Yet, visibility effect in the current month does not have an effect on museum visitation in the same month. Rather, it positively influences visitation in the following month. This is also the main difference with Model A2, which indicated that media visibility affects museum visitation both in the current and the following months. With regard to Promotion, the model is consistent with Model A2 and shows that it is promotion in the previous month that is likely to induce museum visitation in the current month. Finally, month-dummies for March, April, and May also gain statistical significance at the.10 level. The initial models (A1 and B1) establish that media visibility has a positive influence on museum visitation lending support to the article's research hypothesis. In addition, controlling for possible seasonality and other effects, the two models show that museum promotion, location, and type have a significant effect on its visitation. Empirical analysis of the original research hypothesis greatly benefits from the inclusion of time lags as these are introduced in Models A2 and B2. These augmented models exhibit very similar relationships between the dependent and independent variables and shed more light on the time aspect of the effects of focal variables. Namely, media visibility affects museum visitation at least a month before a visit takes place, while museum promotion in the current month is more likely to induce its visitation in the following month. Discussion This project empirically examines a modified first-level agenda-setting hypothesis applied in the market of culture. Seven Greek museums enjoying international recognition were involved in an econometric analysis of the effects of media visibility on museum visitation. This study indicates that the agenda-setting theory deserves further examination in the field of cultural industries, while our research design attempted to clarify the agenda-setting hypothesis controlling for a number of variables that might influence the process of the transfer of salience: the nature of the organization (private vs. public museums), the degree of seasonality (summer visitors vs. winter visitors), promotion activities, museum location, and prospective visitors' disposable income, as well as one-time events, such as the 2004 Olympic Games that took place in Greece, were deemed significant factors that deserve further examination. The Greek cultural market demonstrates a significant seasonality factor. Greece receives most of its tourists during the summer months with its population doubling.4 This cycle applies not only to Greece but also to other Mediterranean countries as well, affected by the climate of the region. Visitation slows down significantly during the winter months. All other activities, including media events and promotion, tend to slow down during the summer while they pick up their pace every fall. Thereby, these kinds of seasonality merit additional analysis and should be examined during expanded time frames to control for their effects. The assessed influences could be further examined if the authors were able to identify the origin of museum visitors. Notwithstanding, statistical services measuring museum visitors do not keep records about the origin of visitors—that is, domestic versus foreign. There is speculation that most of the summer visitors are tourists from abroad who do not rely on Greek newspapers for tourist information. The authors were unable to control for such variables because such information is not available. Theoretically, if the authors could distinguish between foreign and domestic visitors, the transfer of salience process could have been further refined, and the agenda-setting process could have been measured more accurately. This project attempted to control for the nature of the organization. The data demonstrate that private museums, such as the BM, are by far more active in organizing public events that generate media coverage. They seem to invest a great deal in media promotion; however, the econometric analysis indicates that their private governance per se has a negative impact on their visitation. On the other hand, regional public museums that tend to neglect such public relations activities, relying primarily on their location and the value of their collections, appear to have higher visitation than private museums. Analyzing further those differences between public and private organizations can offer useful explanations with regard to the agenda-setting process. Furthermore, museum location registers as a significant variable in the transfer of salience process. Museums based in Athens, the largest metropolitan area in Greece, due to their location, attract more visitors than museums based in rural Greece or in smaller cities. From the three newspapers scrutinized, one exerts greater impact on museum visitation than the other two. Although this finding deserves a closer examination, the authors speculate the Eleftherotypia provides a greater coverage of culture and cultural organizations in general, than the other two newspapers. The article takes advantage of the data set's uniqueness to concomitantly examine the time-lagged effects of focal variables on museum visitation. The time-lagged effects of media visibility and museum promotion turn to be of paramount importance. This has serious implications for museum managers. Namely, the emergent transformation of traditional museums necessitates that museum managers take into consideration not only the impact that media exposure and promotion activities might have on their museum's visitation but also the timeliness of these effects. In this project, the authors treated public salience as an element of behavior. Most of the agenda-setting literature defines public salience as a form of perception. The current definition is reliable but narrow. Data identifying public perceptions of cultural organizations would be more compatible with previous agenda-setting research. Despite the limitations, evidence of agenda setting does exist. Both models identify the media as a significant variable linked to visitation. Future studies could build on the findings of this article and further look into other factors pertaining to characteristics that apply to particular cultural markets. For example, the museum markets in Italy, France, or the United Kingdom display different traits that are not found in Greece. Data derived from countries with a dominant museum tradition and established cultural industries can be more revealing about the relationship between media and public salience of museums. As agenda-setting theory evolves, gathering data from different national settings provides useful explanations about the transfer of salience and refines its original research hypothesis. Moreover, future research should take into account agenda-setting influences at the so-called second level. Media visibility should be examined in terms of affective and substantive attributes that provide additional insight about which frames are related to public salience. Such research can expand the applications of the agenda-setting theory into the cultural market, a field that deserves such explorations as it represents growing markets around the world and receives millions of travellers. This concept of cultural agenda setting can offer theoretical enhancements creating new categories of frames or attributes designed to function not only in the context of museums but also in a wide array of cultural organizations such as galleries, archives, libraries, studios, and other cultural industries. Notes 1 " The term “private” does not imply the same status as that of private corporations. This category of museums enjoys a degree of autonomy while they are still accountable to the Ministry of Culture. 2 " http://www.statistics.gr 3 " Separate estimation of the model without the main independent variable Visibility unveiled that the variable contributed by more than.30 to the model's R2. 4 " Official data from the General Secretariat of the National Statistical Service of Greece show that in 2007, 17.5 million foreigners visited Greece of whom more than 9.4 million between June and September. Appendix Table A1 Focal Variables and Average Values for the Individual Museum . AMT . BCM . NAM . BM . ANM . AMO . NG . Income 11.766 6.722 131.815 35.864 .790 45.793 24.337 Visitation 3,961 5,110 28,743 19,505 616 12,793 16,756 Ta Nea 2 2 4 23 1 0.54 5 Eleftherotypia 0.81 1 4 19 1 0.08 6 Kathimerini 0.75 2 3 18 0.72 0 6 Visibility 0.65 1 2 13 0.59 0.11 4 Promotion 0.44 0.31 0.60 0.30 0.43 0.58 0.21 . AMT . BCM . NAM . BM . ANM . AMO . NG . Income 11.766 6.722 131.815 35.864 .790 45.793 24.337 Visitation 3,961 5,110 28,743 19,505 616 12,793 16,756 Ta Nea 2 2 4 23 1 0.54 5 Eleftherotypia 0.81 1 4 19 1 0.08 6 Kathimerini 0.75 2 3 18 0.72 0 6 Visibility 0.65 1 2 13 0.59 0.11 4 Promotion 0.44 0.31 0.60 0.30 0.43 0.58 0.21 Note: Income is measured in Euros (‘000). AMT = Archaeological Museum of Thessaloniki; BCM = Byzantine and Christian Museum; NAM = National Archaeological Museum; BM = Benaki Museum; ANM = Athens Numismatic Museum; AMO = Archaeological Museum of Olympia; NG = National Gallery. Table A1 Focal Variables and Average Values for the Individual Museum . AMT . BCM . NAM . BM . ANM . AMO . NG . Income 11.766 6.722 131.815 35.864 .790 45.793 24.337 Visitation 3,961 5,110 28,743 19,505 616 12,793 16,756 Ta Nea 2 2 4 23 1 0.54 5 Eleftherotypia 0.81 1 4 19 1 0.08 6 Kathimerini 0.75 2 3 18 0.72 0 6 Visibility 0.65 1 2 13 0.59 0.11 4 Promotion 0.44 0.31 0.60 0.30 0.43 0.58 0.21 . AMT . BCM . NAM . BM . ANM . AMO . NG . Income 11.766 6.722 131.815 35.864 .790 45.793 24.337 Visitation 3,961 5,110 28,743 19,505 616 12,793 16,756 Ta Nea 2 2 4 23 1 0.54 5 Eleftherotypia 0.81 1 4 19 1 0.08 6 Kathimerini 0.75 2 3 18 0.72 0 6 Visibility 0.65 1 2 13 0.59 0.11 4 Promotion 0.44 0.31 0.60 0.30 0.43 0.58 0.21 Note: Income is measured in Euros (‘000). AMT = Archaeological Museum of Thessaloniki; BCM = Byzantine and Christian Museum; NAM = National Archaeological Museum; BM = Benaki Museum; ANM = Athens Numismatic Museum; AMO = Archaeological Museum of Olympia; NG = National Gallery. Table A2 Monthly Average Values for Focal Variables . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . January 16.212 8,890 3.61 5.28 4.61 2.89 0.33 February 14.858 8,884 4.05 3.9 4.1 2.55 0.27 March 23.342 12,081 6.48 4 5.24 3.29 0.3 April 35.342 13,052 4.52 4.1 3.71 2.59 0.4 May 50.411 15,036 5.43 5.24 4.38 3.17 0.46 June 49.752 12,879 6.21 4.25 5.21 3.29 0.53 July 49.402 13,472 5.62 4.14 2.86 2.61 0.5 August 61.350 16,912 5.57 3.1 2.71 2.34 0.5 September 59.771 17,611 8 3.81 3.95 3.24 0.47 October 48.045 14,301 4.71 4.86 5.05 3.1 0.49 November 18.225 8,571 4.86 6.29 5.24 3.48 0.38 December 14.828 7,822 4.76 6.38 4.57 3.33 0.35 . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . January 16.212 8,890 3.61 5.28 4.61 2.89 0.33 February 14.858 8,884 4.05 3.9 4.1 2.55 0.27 March 23.342 12,081 6.48 4 5.24 3.29 0.3 April 35.342 13,052 4.52 4.1 3.71 2.59 0.4 May 50.411 15,036 5.43 5.24 4.38 3.17 0.46 June 49.752 12,879 6.21 4.25 5.21 3.29 0.53 July 49.402 13,472 5.62 4.14 2.86 2.61 0.5 August 61.350 16,912 5.57 3.1 2.71 2.34 0.5 September 59.771 17,611 8 3.81 3.95 3.24 0.47 October 48.045 14,301 4.71 4.86 5.05 3.1 0.49 November 18.225 8,571 4.86 6.29 5.24 3.48 0.38 December 14.828 7,822 4.76 6.38 4.57 3.33 0.35 Note: Income is measured in Euros (‘000). Table A2 Monthly Average Values for Focal Variables . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . January 16.212 8,890 3.61 5.28 4.61 2.89 0.33 February 14.858 8,884 4.05 3.9 4.1 2.55 0.27 March 23.342 12,081 6.48 4 5.24 3.29 0.3 April 35.342 13,052 4.52 4.1 3.71 2.59 0.4 May 50.411 15,036 5.43 5.24 4.38 3.17 0.46 June 49.752 12,879 6.21 4.25 5.21 3.29 0.53 July 49.402 13,472 5.62 4.14 2.86 2.61 0.5 August 61.350 16,912 5.57 3.1 2.71 2.34 0.5 September 59.771 17,611 8 3.81 3.95 3.24 0.47 October 48.045 14,301 4.71 4.86 5.05 3.1 0.49 November 18.225 8,571 4.86 6.29 5.24 3.48 0.38 December 14.828 7,822 4.76 6.38 4.57 3.33 0.35 . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . January 16.212 8,890 3.61 5.28 4.61 2.89 0.33 February 14.858 8,884 4.05 3.9 4.1 2.55 0.27 March 23.342 12,081 6.48 4 5.24 3.29 0.3 April 35.342 13,052 4.52 4.1 3.71 2.59 0.4 May 50.411 15,036 5.43 5.24 4.38 3.17 0.46 June 49.752 12,879 6.21 4.25 5.21 3.29 0.53 July 49.402 13,472 5.62 4.14 2.86 2.61 0.5 August 61.350 16,912 5.57 3.1 2.71 2.34 0.5 September 59.771 17,611 8 3.81 3.95 3.24 0.47 October 48.045 14,301 4.71 4.86 5.05 3.1 0.49 November 18.225 8,571 4.86 6.29 5.24 3.48 0.38 December 14.828 7,822 4.76 6.38 4.57 3.33 0.35 Note: Income is measured in Euros (‘000). Table A3 Correlations Among Focal Variables . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . Income 1 Visitation 0.8614 1 Ta Nea 0.0486 0.2701 1 Eleftherotypia 0.0455 0.3173 0.7687 1 Kathimerini 0.016 0.292 0.8016 0.9153 1 Visibility 0.039 0.3113 0.9113 0.95 0.962 1 Promotion 0.5475 0.2073 −0.226 −0.2731 −0.2967 −0.2818 1 GDP per capita 0.0598 0.0229 −0.0327 0.0781 0.0803 0.0441 0.0801 . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . Income 1 Visitation 0.8614 1 Ta Nea 0.0486 0.2701 1 Eleftherotypia 0.0455 0.3173 0.7687 1 Kathimerini 0.016 0.292 0.8016 0.9153 1 Visibility 0.039 0.3113 0.9113 0.95 0.962 1 Promotion 0.5475 0.2073 −0.226 −0.2731 −0.2967 −0.2818 1 GDP per capita 0.0598 0.0229 −0.0327 0.0781 0.0803 0.0441 0.0801 Table A3 Correlations Among Focal Variables . Income . Visitation . Ta Nea . Eleftherotypia . Kathimerini . Visibility . Promotion . 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TI - Greek Museum Media Visibility and Museum Visitation: An Exploration of Cultural Agenda Setting
JF - Journal of Communication
DO - 10.1111/j.1460-2466.2010.01512.x
DA - 2010-12-01
UR - https://www.deepdyve.com/lp/oxford-university-press/greek-museum-media-visibility-and-museum-visitation-an-exploration-of-SrD4xg1OxB
SP - 743
VL - 60
IS - 4
DP - DeepDyve
ER -