- Email: [email protected]
Museum visitors and non-visitors in Germany: A representative survey
POETICS ELSEVIER
Poetics 24 (1996) 239-258
Museum visitors and non-visitors in Germany: A representative survey V o l k e r Kirchberg * University of L',',neburg, Department of Applied Arts Sciences, and Basica Research Institute, Glockengiesserwal126, D-20095 Hamburg, Germany
Abstract German museums have only recently employed sample surveys to learn about the people who visit and who do not visit their museums. The reason for this late activity is a search for new financial sources, and the discovery of the marketing of museums. However, there is still little knowledge of non-visitors and their social background. This survey focusses on the effects of socioeconomic, demographic, and geographic factors on visits or non-visits to four different types of museums: science and technology museums, natural history and natural science museums, history museums, and art museums. For art museums, it was possible to compare the German results with data from the Surveys of Public Participation in the Arts in the United States. In Germany, the type who does not visit museums is more often a blue-collar worker, unemployed or not in the paid labor force. Visitors to science museums and to natural history museums are more often between 30 and 45 years of age and live more often in a household with many people. Visitors to history museums and to art museums are highly educated, and are likely to be professionals or students. A single contrast of non-visitors and visitors could not be corroborated. Rather, the contrasting character of art museum audiences and natural history museum audiences emerges strikingly. On the one side we find the natural history museum and science museum visitors, on the other side the art museum and history museum visitors. There is a continuum ranging from non-visitors to popular museums to visitors of high culture museums with respect to their socioeconomic, demographic and geographic characteristics.
t This study is based on a survey made possible by the Hans der Geschichte der Bundesrepublik Deutschland (Museum of Contemporary History of the Federal Republic of Germany) in Bonn. I am especially grateful to the museum director, Professor Hermann Sch~tfer, for understanding and supporting scientific research in this field. He is one of only a very few in Germany. In November 1995 he initiated the first international conference on museum visitor research in continental Europe (proceedings are published in Haus der Geschichte, 1996). " Fax: Germany + 49-40-422 5703; E-mail: [email protected] 0304-422X/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved PII S 0 3 0 4 - 4 2 2 X ( 9 6 ) 0 0 0 0 7 - I
240
V. Kirchberg / Poetics 24 (1996) 239-258
1. Introduction German museums have rarely and only recently employed sample surveys to learn about the people who visit and, especially, about those who do not visit their galleries. The museums' ignorance of the challenge that non-visitors pose to their outreach programs is a consequence of the administrative and, especially, the subsidy system of most German museums, which are predominantly public institutions run by the respective community or federal state (Bundesland). The success, or even stronger, the survival of a museum has not been dependent on the acceptance and praise of a museum's exhibitions by a broader public but on their specific scientific reputation a n d / o r understanding within the local municipality that provides for their financial needs. However, within the last years a slow transformation process has dawned on the whole of the 'high culture' scene of Germany. As less - or, at least, stagnating - public subsidies discloses to the museum management that public monies are not infinite, the overall reliance on this subsidy source is fading in Germany, too. Responsible and lively museums that try to increase their attractiveness in new fields seek new financial sources; and one pillar of the modem art of museum management rests on the marketing of museums. As an undisputable part of this changing attitude, surveying visitors as new and more important clients of German museums becomes the focus of the museums' attention. The visitor is no longer incidental to a museum that has to be 'public' because of its public subsidies. More often, he or she now becomes the center of attention as the customer of a product that can be offered almost solely because of his or her demand. Increasingly, this new image of the visitor as a customer gains more weight in the German museum managers' strategic planning. However, who is this customer? Information about visitors - and especially about the potential new customer who must be the focus of a museum growth strategy - is scarce. To increase this information remains the task of empirical surveys.
2. Past visitor studies in m u s e u m s in Germany Museum visitor research in Germany is still primarily the realm of (social) scientific interest and not motivated by marketing objectives. For the last decades studies of museum visitors in Germany have been concentrated at two localities, the Sociological Institute at the University of Karlsruhe (directed by Hans-Joachim Klein), and the Institute for Museum Studies (Institut fi~r Museumskunde) at the State Museums of Berlin (Staatliche Museen zu Berlin - Preussischer Kulturbesitz) (directed by Bernhard Graf). In Karlsruhe, since the beginning of the Seventies, many visitor studies in different types of museums have been conducted and published. Furthermore, the Berlin Institute for Museum Studies has been able to document annual numbers of visits to German museums since 1981. In 1993, more than 93.7 million visits occurred at 4,683 museums. The most prominent type of museums are local history and local life museums (15 million visits), followed by art museums (l 2 million visits), science and technology museums (l 2 million visits), history museums (8 million visits), and natural
V. Kirchberg / Poetics 24 (1996) 239-258
241
history museums (4 million visits) (Institut f't~r Museumskunde, 1994). (Germany has a population of 80.97 million.) Nuissl and Schulze (1991) briefly summarize results of German studies on socioeconomic factors related to museum visits. According to them, the staff of most museums is ignorant of the social composition of their audiences. The results of visitors studies (if any are conducted) are not used by German museums. However, research on museum audiences during the 1980s revealed the following general results. Visitors of German museums are younger than the average population. With increasing age, the tendency to visit museums declines. Men form the majority of audiences of science museums whereas women are in the majority among art museum visitors. Moreover, museum visitors are more educated than the average population. The higher the educational attainment the greater the likelihood of a visit. The level of education of art museum visitors, however, is higher than that of visitors to local life or science museums. Occupational status also has a positive impact on museum visits. (As an exception, however, the propensity to visit a science museum declines with higher occupational status.) Nuissl and Schuize mention that there is still little knowledge of non-visitors and their social background. Statements like 'About 25 percent of the German population visit museums', or 'There is a strong social contrast between museum visitors and non-visitors' have been speculative, requiring empirical scrutiny. However, the need to test these assumptions by a representative survey of the whole German population is not well understood by museum managers. Although more and more of them admit the importance of visitor evaluation studies to improve the museum displays, they do not grasp the functions of population sample surveys that focus primarily on non-visitors. Audience development - the idea of actively 'reaching out' to non-visitors to develop them as visitors - is a relatively new and progressive idea in the German museum landscape, and it is not shared by everyone. Also, most museums do not understand that a visitor survey in the institution cannot substitute for a representative survey outside the institution. There is a broad misconception that results of visitor studies in museums are representative for the whole of the society. Klein and Bachmayer (1981) noted that visitors cannot be asked about non-visitors; even first-time visitors asked about their motives and socioeconomic background cannot speak for the majority of people (about three quarters of the German population) who do not cross the threshold of the museum at all. They argued that representative non-visitor surveys are "urgently necessary and hitherto ignored" (Klein and Bachmayer, 1981: 86; this and further quotes translated from German by the author). In-house surveys report on visits, whereas out-of-house surveys can report on visitation rates. In-house surveys often confuse visits with visitors, whereas out-of-house surveys do not. Again and again, social scientists have complained about the lack of reliable data on visitors and non-visitors and about the inaptitude of museums' efforts to conduct visitor surveys. "Measured by the conjectured significance, statistical methods and the certainty of results are grotesquely underdeveloped" (Klein, 1990: 30). "Sociologically
advised analyses of visitor composition are only available for some singular museums" but are rather needed for a representative sample of the whole population universe (Nuissl and Schulze, 1991: 24). Many a report on visitor surveys asks the question
242
V. Kirchberg / Poetics 24 (1996) 239-258
" W h o does actually not come to the museum? ... All one can establish right now is only the fact that some people stay away. Barriers, a lack of information, prejudices, different interests - all this can be authentically investigated only in a direct survey of non-visitors" (Klein and Bachmayer, 1981: 86).
3. Past population studies for museums in Germany The very few representative surveys dealing with museum attendance in Germany have focussed on the population of a single city. They are always part of a general survey on, e.g., urban leisure activities or the population's assessment of the area's quality of life, usually conducted by urban sociologists or administrative statisticians of municipalities, and not directed towards (or even known to) museum leaders. For example, the annual quality-of-life-survey in Cologne emphasized the importance of educational attainment for the visits of museums, reporting that 55 percent of people who have college access legitimacy (e.g., the German high school degree, 'Abitur' ), but only 20 percent of those with a grade school degree (' Volksschule' ), reported visiting a Cologne museum in the previous year (Hoffrichter, 1993). Another local survey on cultural activities has been continuously conducted in Leipzig since 1991. Here, 44 percent of people with a college degree visit museums on a yearly basis but only 20 percent of people who say that they are workers. Eighty-five percent of Leipzig citizens claimed to have visited Leipzig museums during their life in this town (Schmidt, 1993). The Center for Urban Research at the University of Hamburg undertook a representative telephone survey on cultural activities in 1984. The results of this study are of interest because the author repeated parts of this survey in Baltimore in 1989, making possible an international comparison. Educational attainment was an important predictor of attendance in both cities, though less so in Hamburg than in Baltimore. Age and life cycle position influenced museum visits differently in Hamburg and Baltimore. In Hamburg, age had a positive effect (the older the more visits), whereas in Baltimore age had a negative effect (the older the fewer visits). In Hamburg, pensioners are a major group of museum visitors; in Baltimore families with children are a major group of museum visitors (Kirchberg, 1994). This last comparison demonstrates that one cannot generalize from local surveys to other geographical entities. Only two surveys in Germany attempted to gather representative data on museum visitors and non-visitors before 1995. In 1977, 1,991 people in West Germany were asked about the frequency of museum visits, the circumstances under which they visited, and barriers to participation (Eisenbeis, 1980). The main explanatory variable was, again, educational attainment. Twenty percent of Germans with a grade school degree but 53 percent with a university degree reported visiting museums. Fifteen percent of all respondents said that they had never visited any museums, and 22 percent said that they had visited museums only through a school class trip. In 1992, the Center for Cultural Research in Bonn conducted a similar representative survey of the German population ( Z e n t r u m f ~ r Kulturforschung, 1992) with a sample of 3,065 people (now in eastern and western Germany). The most popular museums among Germans are local history and
V. Kirchberg / Poetics 24 (1996) 239-258
243
local life museums: 38 percent of all Germans are interested in this type, followed by art museums (24 percent). Sixteen percent said they were not interested in museums at all. In 1992, nine percent of all respondents said that they had never been to museums, and an additional 30 percent said that they visited museums only as a school experience. (Unfortunately, this study did not analyze educational attainment as a predictor of museum visits, making comparison with the 1977 survey impossible.) Our 1995 study, which I describe below, fills this and other information gaps. Based on responses from a representative sample of almost 17,000 people in Germany, this survey focussed on the effects of socioeconomic and demographic factors on visits to four different types of museums.
4. The survey on museum visitors and non-visitors in 1995
A random-quota sample was created from a larger household access panel of more than 31,000 German households. This panel was drawn from all German households by quota that correctly reflect the different socioeconomic structures of the regions of Germany. Then, random households were drawn from these quota households to maintain representativeness. Comparison of the sample's socioeconomic characteristics with official data from the German 'Bureau of Census' (Statistisches Bundesamt, 1994) confirms this representativeness. The sample used in these analyses includes 16,862 respondents. According to the international UNESCO classification and corresponding recommendations of the Berlin Institute for Museum Studies, this study distinguishes four types of museums: (1) science and technology museums, (2) natural history and natural science museums, (3) history museums, and (4) art museums. (A special German case are the so-called 'local life museums' [Heimatkundemuseen] that collect, interpret and exhibit only pieces of the community in which they are located, mostly for the purpose of preserving the community's historic identity and propagating it to contemporaries. Because they focus upon the past, such museums are classified as historical museums.) Respondents were classified as visitors or non-visitors to these four museum types. As explanatory variables we asked for information about socioeconomic status (educational attainment, annual household income after taxes, occupational position), demographic indicators (age and gender), geographical information (ZIP code of the place of residence, population size of the place of residence), and factors likely to influence discretionary time (number of hours worked per week, number of children younger than 15 years of age).
5. Multiple classification analysis of museum visitors
To measure correctly the effect of these variables on visits to the different museum types it is necessary to control for the effects of other variables. For example, does income positively affect visits to art museums or does the correlation between income
244
V. Kirchberg/ Poetics 24 (1996) 239-258
and art museum visiting reflect the intervening effect of education (since it is highly correlated with income)? To eliminate such confounding effects, we applied multiple classification analysis (MCA) as a statistical tool. (Later on, we use another multivariate tool, correspondence analysis.) Multiple classification analysis must be combined with another statistical method, analysis of variance. Analysis of variance labels categorical explanatory variables as factors (a custom we will follow here). For every categorical value of a factor, MCA first calculates a mean of the variable values to be explained (here: the average museum participation rate). For example MCA can yield an obervation such as 'An average 17 percent of Germans between 65 and 74 years of age visit a science museum'. Second, MCA calculates an adjusted mean for the dependent variable for every explanatory category, i.e. adjusted for the intervening effects of other factors. This will change the previous statement to 'An average 20 percent of Germans between 65 and 74 years of age visit a science center, adjusted for other background characteristics'. Thus the intervening effect of education (older people are less educated) has been eliminated. Tables 1-5 have the following structure: 1st column: Name and categories of the factor 2nd column: unadjusted participation rate for each category 3rd column: MCA adjusted participation rate for this category 4th column: F-value of the factor (the higher this value, the stronger the category's effect on visiting rates), and the significance of F A summary of the results of MCA analyses follows, indicating the factors that influence visits to each type of museum. In the tables the factors education, income, occupation, age, sex, and region are displayed. Two more factors, number of children and number of working hours, are not displayed, but are mentioned in the discussion that follows each table. Twenty percent of Germans visited a science or technology museum between mid-1994 and mid-1995. (See Table 1.) Education: There are clear differences in participation rates by educational level. The greatest difference, 21 percent, can be observed between people with grade school without vocational training and those with a college or university degree. Even adjusting for intervening effects, the difference is a considerable 18 percent. Thus with higher levels of educational attainment, rates of visiting science museums increase. Income: There are considerable differences in participation rates among income categories, too, if not quite as distinct as for the educational levels. The participation rate is 14 percent in the lowest income category and 25 percent in the highest income bracket, a difference of l I percentage points. After MCA adjustment this difference is still l0 percentage points. Occupation: Rate differences of the extreme categories 'Not Occupied' and 'In School' are 14 percentage points (16 percent and 30 percent, respectively). However, all other categories of this factor have quite similar rates (around 20 percent), especially after MCA adjustment. Only people still in school, college or vocational training are visiting this type of museum more often (28 percent after adjustment). Age: The highest unadjusted difference between these categories is 8 percentage points, with respondents under 25 years at the highest rate (20 percent) and those over
V. Kirchberg / Poeticv 24 (1996) 239-258
245
74 years having the lowest (12 percent). With MCA adjustment, however, the rates become almost the same, remaining around 20 percent through age 75 and only then declining. Therefore, age does not seem to exert a significant effect on this activity. Gender: The rate of visiting science centers is significantly higher for men than for women, even after the MCA adjustment. Regions of Germany: In southern Germany the participation rate for science center visits is significantly higher (24 percent) than in northern Germany (16 percent). In western and eastern Germany, the rates are around the grand mean of 20 percent. Controlling for other factors does not change this impression, the difference between the interested South and the uninterested North remains at 7 percentage points. This may be due to a higher supply of science centers in the South of Germany, especially in Munich. Other factors: The number of school-age children in the household has no impact on visits to science centers. In contrast, the number of weekly working hours influences the visit of this museum type positively. The more hours one works the more likely one is to visit science centers, i.e., from 17 percent of people who work no hours to 24 percent of those who work more than 35 hours weekly (adjusted for other factors). Twenty-one percent of the German population visited a natural history museum in 1994/95. This is very similar to the rate of visiting science museums. (See Table 2.) Education: This factor has an even more important impact on visits to this type of museum than on visits to science museums. The difference among the categories is 24 percentage points (10 percent for the lowest and 34 percent for the highest level of education). After MCA adjustment the difference is still 20 percentage points (12 percent to 32 percent). Income: The impact of this factor is slightly less than it is for the science museum visits. However, it is significant (15 percent in the lowest income bracket, 23 percent in the highest income bracket); the higher the income, the higher the participation rate. Occupation: The impact of this factor is also slightly less than its impact on visits to science museums. After MCA adjustment, the participation rate of blue-collar workers is 19 percent; for students it is 29 percent. Age: Age has a distinct effect on visits to natural history museums. Younger Germans visit more (22 percent after adjustment) than older Germans (16 percent). Gender: The effect of gender is weakly significant, with women visiting more (22 percent) than men (20 percent). Regions of Germany: There are clear differences among the regions. Rates of visitation are higher in the still less industrialized South (24 percent with adjustment) than in the industrialized West (18 percent). The South, with most of the country's mountains, offers more natural history museums (in natural settings) than the West. Other factors: The number of children in a household has a positive effect on visits to natural history museums; the more children, the more visits. Participation rates are 18 percent for households without children and 27 percent for households with two or more children. Weekly working time has no effect on visits to this museum type. Twenty-one percent of Germans visited history museums in the eighteen months preceding the survey. (See Table 3.) Education: Education's impact on visits to history museums is weaker than its effect on attendance at science or natural history museums, but is still significant. After MCA
246
V. Kirchberg / Poetics 24 (1996) 239-258
Table I
MCA: Comparison of unadjusted and adjusted participation rates for Science and Technology Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the [bllowing topic? - Science and technology?"
Overall rate
Participation rate
MCA-adjusted participation rate
20%
20%
9% 17% 20% 20% 28% 31%
11% 17% 20% 20% 28% 29%
14% 14% I 1% 16% 17% 25%
14% 16% 14% 17% 18% 24%
16% 18% 23% 21% 30%
20% 20% 20% 18% 28%
20% 20% 21% 21% 17% 17% 12%
20% 19% 20% 21% 20% 23% 16%
18% 22%
18% 20%
21% 16% 19% 24%
20% 17% 19% 24%
21.6 (0.000)
Annual income
DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24,000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
6.3 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
1.3 (0.246)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older Gender
Female Male
2 I . l (0.000)
20.5 (0.000)
Region in Germany
East North West South
17.6 (0.000) 51.7(0.000)
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
F-value (sig. F)
a d j u s t m e n t the d i f f e r e n c e in v i s i t i n g rates b e t w e e n the g r o u p with the l o w e s t and the g r o u p with the h i g h e s t e d u c a t i o n a l a t t a i n m e n t (13 p e r c e n t a n d 31 p e r c e n t , r e s p e c t i v e l y ) is still substantial.
247
V. Kirchberg / Poetics 24 (1996) 239-258
Table 2 MCA: Comparison of unadjusted and adjusted participation rates for Natural Hiswry and Natural Science Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the following topic? - Natural history and natural science?"
Overall rate
participation rate
MCA-adjusted participation rate
21%
21%
10% 16% 22% 25% 27% 34%
12% 16% 21% 25% 27% 32%
15% 17% 16% 18% 20% 24%
15% 19% 18% 20% 20% 23%
19% 16% 23% 23% 30%
22% 19% 21% 20% 29%
23% 21% 25% 21% 16% 15% 13%
22% 18% 22% 22% 21% 21% 16%
22% 20%
22% 20%
24% 21% 18% 24%
23% 22% 18% 24%
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
4.5 (0.000)
3.0 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
10. I (0.000)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
9.0 (0.003)
Gender
Female Male
13.8 (0.000)
Regum in Germany
East North West South
18.1 (0.000) 60.1 (0.000)
Annual income
DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24.000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
F-value (sig. F)
I n c o m e : I n c o m e also has a strong p o s i t i v e i m p a c t on visits to h i s t o r y m u s e u m s . T h e a d j u s t e d rate for the l o w e s t i n c o m e b r a c k e t is 19 p e r c e n t , and for the h i g h e s t i n c o m e
bracket, 24 p e r c e n t .
248
V. Kirchberg / Poetics 24 (1996) 239-258
Table 3 MCA: Comparison of unadjusted and adjusted participation rates for History Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the fi~llowing topic? - History?" Participation rate
MCA-adjusted participation rate
Overall rate
21%
21%
Educational attainment Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
11% 16% 22% 24% 28% 32%
13% 17% 22% 24% 27% 31%
Annual income DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24.000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
21% 18% 16% 17% 19% 24%
19% 18% 17% 18% 20% 24%
Occupational position Not occupied Worker/blue-collar Employee/White collar Professional/entrepreneur In school/voc, training
18% 15% 24% 22% 33%
21% 19% 21% 19% 31%
Age 15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
22% 21% 21% 23% 21% 16% 19%
21% 19% 21% 23% 23% 19% 20%
Gender Female Male
21% 21%
21% 21%
Region in Germany East North West South
26% 23% 20% 20%
25% 23% 20% 20%
F-value (sig. F) 13.0 (0.000) 49.9 (0.000)
10.6 (0.000)
7.0 (0.000)
3.5 (0.002)
0.0 (0.928)
6.1 (0.000)
O c c u p a t i o n a l p o s i t i o n : O c c u p a t i o n a l p o s i t i o n i n f l u e n c e s visits to h i s t o r y m u s e u m s , too, m o r e so than visits to s c i e n c e or natural h i s t o r y m u s e u m s . N i n e t e e n p e r c e n t o f
b l u e - c o l l a r w o r k e r s h a d visited a h i s t o r y m u s e u m , c o m p a r e d to 31 p e r c e n t o f students.
V. Kirchberg / Poetics 24 (I 996) 239-258
249
Age: The effect of age on visits to history museums is nonlinear, with the most active group consisting of men and women in their 50s (23 percent) and, only secondarily, those under 35 (20 percent rate among people under 35 years of age). Gender: Men and women visit history museums at a similar rate. Regions of Germany: Although the effects of region are less strong than for science and natural history museums, differences do exist. Perhaps due to differences in political education, residents of eastern Germany are more dedicated history museum-goers (25 percent) than residents of western or southern Germany (20 percent). Other factors: Neither the number of children nor weekly working hours affect history museum visiting. Twenty-six percent of Germans visited art museums in 1994/95, a higher participation rate than for the other museum types. Even more than other museum types, art museum visiting is a function of social and demographic characteristics. (See Table 4.) Education: The effect of education is very strong, even more so than for other museum types. The least educated group visits at a rate of only 8 percent, compared to 52 percent for the most highly educated. Income: Income influences visits to art museums less than visits to science museums, but to a similar degree as visits to history museums. After adjustment, 20 percent of those in the low income bracket (12,000 to 18,000 DM), compared to 29 and 24 percent, respectively, in the higher brackets (more than 24,000 DM, more than 48,000 DM) are visitors. Occupational position: Occupational position has a stronger effect on visits to art museums than on visits to any other museum type, with 20 percent of blue-collar workers and 39 percent of students reporting a visit during the previous eighteen months. Age: Age also has strong effects on visits to art museums and, in contrast to the other museum types, the effect is linear and positive. Rates range from 22 percent for those 25 to 34 years of age to 31 percent for people 65 and older. Gender: In contrast to science museums, significantly more women (28 percent) than men (24 percent) visit art museums. Regions of Germany: The effect of region on visits to art museums is relatively weak, although the difference between south (27 percent) and north (24 percent) is statistically significant. Other factors: Number of children is negatively related to art museum visits: after adjustment, 29 percent of people without children visit art museums, compared to 20 percent of men and women living in households with two or more children. It is possible to compare these particular results for visits of art museums with Schuster's analysis of data from the Surveys of Public Participation in the Arts in the United States (Schuster, 1991; Kracman, this issue, also uses data from that survey). He constructed MCA tables very similar to Table 4, rendering comparison easy and instructive. Germans and Americans visit art museums at comparable rates, 22 percent for Americans (during the previous 12 months) compared to 26 percent for Germans (during an interval of approximately 18 months). In the United States, as in Germany, educational attainment is most closely associated with museum visiting, with income
250
V. Kirchberg / Poetics 24 (1996) 239-258
Table 4 MCA: Comparison of unadjusted and adjusted participation rates for Art Museums, Germany 1995 Question: "In 1994 or 1995. did you visit a museum or an exhibition on the Jollowing topic? - Art?"
Overall rate
Participation rate
MCA-adjusted participation rate
26%
26%
8% 15% 24% 39% 46% 53%
8% 15% 25% 37% 45% 52%
30% 22% 21% 22% 21% 32%
23% 20% 22% 24% 24% 29%
22% I 1% 29% 36% 49%
27% 20% 25% 31% 39%
27% 26% 22% 28% 29% 29% 30%
26% 22% 24% 29% 30% 31% 30%
28% 24%
28% 25%
29% 24% 26% 25%
25% 24% 27% 27%
11.3 (0.000)
Annual income
DM DM DM DM DM DM
12,000 or less 12,000 - DM 18,000 18,000 - DM 24.000 24,000 - DM 36,000 36,000 - DM 48,000 48,000 or more
i 7.8 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
29.5 (0.000)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
14.2 (0.000)
Gender
Female Male
3.1 (0.028)
Region in Germany
East North West South
60.3 (0.000) 266.2 (0.000)
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
F-value (sig. F)
p l a y i n g a m u c h less i m p o r t a n t , a l t h o u g h still s i g n i f i c a n t , role. In b o t h c o u n t r i e s m o r e w o m e n ( 2 4 p e r c e n t in U S A , 28 p e r c e n t in G e r m a n y ) t h a n m e n ( 2 0 p e r c e n t a n d 25 p e r c e n t , r e s p e c t i v e l y ) r e p o r t e d v i s i t i n g art m u s e u m s . T h e r e are also s m a l l r e g i o n a l d i f f e r e n c e s in e a c h c o u n t r y .
V. Kirchberg / Poetics 24 (1996) 239-258
251
The only major difference is in the effects of age on art museum participation, which are strong but differing effects in these two countries. Whereas the relationship between age and art museum visiting in the U.S. is shaped like an inverted U, with the highest rates for men and women in their 30s and 40s, visiting rates peak among older men and women in Germany. This difference may, of course, reflect cohort or generational differences rather than age effects. Within each generation, differently in the two countries, there may be different art values, shaped by different historical conditions and predominant generational experiences. German museums remain 'elite art' institutions, radiating the image of a 'temple of the classics', which pleases the generations born in the 1920s or 1930s but deters the generations of the 1960s or 1970s (G~Sschei, 1991). An art museum in the USA, however, seems to adjust better to the interests of the younger 'baby-boom' generations (Balfe, 1989). This may, again, reflect strategies of American museums that are more visitor-oriented than those of their German counterparts. Up to now, we have compared visitors to each museum type with those who do not visit that kind of museum. We have not yet provided a profile of the 'non-visitor,' who visits no museums at all. This, plus descriptions of visitors to the four museum types, will be provided by the analysis in the following section. 6. Profiles of museum visitors and non-visitors in Germany An elegant method to analyze categorical data in a multivariate manner is the
correspondence analysis. This method estimates mutual effects of exogenous and endogenous variables, and yields two complementary products, a graphical output that
~ ~::~ ~~ : ~ : ~ . L : , ~ ¸:~:~! ~ , ~ , ~ :
:~,'~~,~~ e - ~ " , ~ ~ ~
*
~
,
~
~ , ~ ' ~ , ~
~ ~':~,¸~:¢,"~,::> :~.~~:,L~,~ ,:~;',q~,~<~:F: '¸ ~:~, ~ - ~ : : ~ : ~ : ~ ' ~ > : * ~ , : + , "
<, ':~ ~::~: ~ , : ~ : ~ ~:~:~:~<
.~,two o~ more children i
.:
ehold with 4 or more persons \
mNATURALHISTORYMUSEUMVISITOR
: \o31 to\45 years of age : one child S~u~hGee-man ~i:iworker <5.000_.Izc~ • \I •~SCIENCEMUSEUMVISITOR i;:: • ~ ~$O00DM•<1~hrs/ mEast German ~J. < 2 0 0 0 •0epl a )m~ ! _ . .e/ployed••>35hrs . . . m a ! . . e O ~ o .•~ . ~ ~ p •
univp..~.s_kt~•
i I........ 3 ~ p e r ~ s ~ . ' h ~ o ~ u s ~ e h o - i ~ o ~ ° ' o ~ - 1 ~ . ~ ' O O ~ ~ t i o n ~NO~MVSEUM VISITOR~\NorthGe'r• •< 30 ~ears old / ~ g ~ s c h o o l •no,work i •female\ •professioj~•upper high school : unRtmm~l.Q.yed•~.~Eest ~er.-500.01~0• •>500.0])~" pop.
~ii. : ! ,
2-pers. household~ ' 4 " 6 - ~ y e ~ of age ~I.-2.00~DM ~ • ~"~A'RTMUSEUMVISITOR >60 years of age • i: i:!
•'singlehousehold
Fig. l.Correspondence analysis map of the types of museum visitors and non-visitors.
252
V. Kirchberg / Poetics 24 (1996) 239-258
shows the results 'at a glance', and a tabular output that provides detailed numerical results that are useful in interpreting the graphical display. Below, both Fig. 1 and Table 5 reveal the profiles of the different museum visitors and the non-visitor.
7. Excursus: The interpretation of correspondence analysis results This method of statistical analysis, which was developed by Jean-Paul Benz~cri in the 1960s, gained the attention of sociologists primarily through its application by Pierre Bourdieu (1984) in D i s t i n c t i o n . Correspondence analysis produces a kind of 'scatterplot' diagram from a contingency table. It is similar to principal component analysis; however, the 'clustering' of data results not from analysis of variance along principal axes, but through decomposition of the usual chi-square statistic for row-column independence along principal axes. In principal component analysis, rows and columns define a 'cloud' of points in a multidimensional space and the principal axes identify those subspaces which come closest to these points (i.e., factors of a factor analysis). In correspondence analysis there are two clouds of points - a set of column profiles and a set of row profiles, where a row (colunm) profile is the row (column) of the data matrix divided by its respective row (column) sum (i.e., a set of relative frequencies). Correlation coefficients of a correspondence analysis correspond to factor loadings of a principal component analysis. These correlations (labelled ' c o r ' in Table 5) are calculated for all categories of each item used in the analysis, whether the items are column or row variables. The proximity of the analyzed items in the multidimensional space to each of the principal axes is calculated from the item's row and column coordinates. The further 'location' at the negative or positive part of the axis is determined by the plus or minus sign before the ' l o c ' value in Table 5. The item's contribution to the position of the axis is indicated by the 'ctr' value. As a convention the variables (items) to be explained (here, participation rates for the four museum types and rates of non-visiting) are the columns of a contingency table; and the explanatory variables (items) (here, the individual socioeconomic, demographic and other categories) are the rows of this contingency table. The correspondence of these individual characteristics to the variables of museum visits is analogous to the 'clustering' of a principal component analysis, where items are grouped to dimensions (factors). Items are assigned to particular axes (in this case, visitor types) on the basis, primarily, of high c o t values and, secondarily, high ctr values. The l o c - v a l u e ' s sign determines assignment to the positive or negative part of the axis. The number of axes is determined by a s c r e e - t e s t procedure similar to that used to determine the number of axes in principal component analyses. For further information about correspondence analysis see Greenacre (1993). Column items (visitor types) are assigned to axes and axis locations through interpretation of the c o t , ctr and loc values. Then individual characteristics (row items) are assigned to these axes (by their c o t , ctr and loc values). By seeing which individual characteristics correspond to which row items, we describe the profile of each visitor type. Final!y, we compare axis assignments to see how the visitor types correspond to each other.
253
v. Kirchberg / Poetics 24 (1996) 239-258 8. C o r r e s p o n d e n c e
analysis:
Description
of profiles
T h e t y p i c a l v i s i t o r p r o f i l e s ( a n d the profile o f the n o n - v i s i t o r ) are d i s p l a y e d first g r a p h i c a l l y (Fig. !) a n d t h e n in t a b u l a r f o r m ( T a b l e 5). I n d i v i d u a l c h a r a c t e r i s t i c s a n a l y z e d i n c l u d e g e n d e r , age, o c c u p a t i o n a l p o s i t i o n , w o r k i n g h o u r s , i n c o m e , p o p u l a t i o n size o f r e s i d e n t i a l area, a n d region. In Fig. 1, the c o - o r d i n a t e m a p c o n s i s t s o f t w o a x e s ( t w o are sufficient for e x p l a n a t i o n o f the m o d e l ) . T h e h o r i z o n t a l axis ( x - a x i s ) e x p l a i n s 78.8 p e r c e n t and the v e r t i c a l axis ( y - a x i s ) e x p l a i n s 15.9 p e r c e n t o f all c o r r e s p o n d e n c e s . T h e x-axis is m a r k e d b y the c o n t r a s t o f m u s e u m visit to m u s e u m n o n - v i s i t . In the n e g a t i v e part o f this axis o n e f i n d s n o n - v i s i t o r s w i t h t h e i r p r e d o m i n a n t c h a r a c t e r i s t i c s ; in the p o s i t i v e part, o n e c a n locate v i s i t o r s to the d i f f e r e n t t y p e s o f m u s e u m , w i t h t h e i r c o r r e s p o n d i n g c h a r a c t e r i s t i c s . T h e Table 5 Assignment of column items (visitors to axes) and row items (individual characteristics to visitor types, or axes, respectively) Item
Ist axis ( X )
Column assignment:
Ioc I
cor
ctr
2rid axis ( Y )
Visitors to: Science museums Natural history museums History museums Art museums No museum
65 46 64 158 - 172
403 166 689 780 983
38 20 39 qf 296 607 #*
Row assignment:
Ioc I
cor
ctr
loc2 54 94 5 -82 - 22 Ioc2
cor
ctr
277 694 4
131 • 418 •
212
399 6 51
17 cor
I
ctr
Gender Female Male
23 - 26
200 289
2 2
- 23
21
186 178
Age < 30 years 31-45 ears 46-60 years > 60 years
23 - 22 37 - 56
510 64 257 140
1 1 2 3
-10 85 -58 - 135
108 912 614 809
Occupational position Professional White-collar employee Blue-collar worker Not occupied In education
170 97 - 343 - 147 399
900 916 912 899 996
I! 27 51 6 46 6 53 V
-19 26 44 -40 2
II 67 15 66 0
Educational attainment Grade school Middle school High school College/university
- 341 3 324 481
988 9 985 990
210 6 0 105 V 150 V
- 22 22
4 518 10 2
4
Weekly hours at work No hours at work < 16 hours
- 145 - 31
884 391
37 6 1
- 46
89 115
18 2
-33 19
17
7
7 1 93 & 30 • 78 •
I
10 4 17 0
56
5 I
254
V. Kirchberg / Poetics 24 (1996)239-258
Table 5 (continued) Item
Ist axis ( X )
C o l u m n assignment:
loc I
15-35 hours > 35 hours
2nd axis (Y ) cor
ctr
88 108
728 721
10 21
-68 - 169 - 126 - 58 202
213 745 859 682 960
- 157 - 65 - 8 129 213
956 876 336 894 969
108 - 33 -36 51
681 174 354 285
48 - 87 -62
93 -2 - 49 - 22
Ioc2
cor
ctr
27 23
67 34
5 5
0 28 10 M 8 76 V
-104 - 87 - 34 37 26
493 198 62 277 16
5 • 37 4 15 6
30 M 6 0 16 V 43 V
33 15 - 5 - 22 -31
44 47 134 25 21
4 2 3 5
44 - 7 -45 57
I 16 7 564 364
4 0 26 • 29 &
249 745 121
8 9 5
-81 49 162
722 243 834
120 • 15 183 &
320 2 896 32
9 0 3 #~ I
- 134 -52 6 121
660 785 14 940
89 • 25 • 0 135 Ak
Income brackets < 1000 DM 1000- 2500 DM 2500-3000 DM 3000-5000 DM > 5000 DM
Population at residence < 5.000 pop. 5.{X)1-20.000 pop. 20.001 - 100.000 pop. 100.001-500.000 pop. > 500.000 pop.
7 2 0 2 4
Regions of Germany East North West South
Number of children No children One child Two or more children
Household size Single person household Two-person household Three-person household Four or more pers. househ.
dimension of the y-axis is marked by the contrast of natural science/popular orientation (positive axis part) to humanistic/high-culture orientation (negative part), with natural history and science museum visitors contrasted with history and art museum visitors. Superimposed upon the map of Fig. 1 are four tilted rectangles, which reflect the correspondence of certain individual characteristics to each type of museum visitor. At least one visitor type is positioned in or at each rectangle (types are in capital bold italic letters and underlined to distinguish them from the corresponding characteristics). The characteristics in or at the edge of the rectangles describe the corresponding visitor types. To interpret these results it is useful to inspect both Fig. 1 and Table 5. Analogous to principal component analysis the main task is to assign individual characteristics (i.e., items) to types of visitors (i.e., parts of axes or dimensions). This task can be adequately carried out by visually inspecting items close to the museum types (inside and at the
V. Kirchberg / Poetics 24 (1996) 239-258
255
rectangles) but even better through the assignment of items by high cor and ctr values (plus the loc sign) to the axes. In Table 5, (row) items that correspond with particular (column) visitor types are marked by the four playing-card signs: spade (indicating that the item corresponds to the art museum visitor type), diamond (science or natural history museum visitors), heart (history museum visitors), and club (non-visitors). The first axis column differentiates museum visitors of all kinds from the non-visitors. The second axis column distinguishes among the types of museum visitors. Visitors to science museums and to natural history museums are too similar to be distinguished by correspondence analysis. These two types are located close to the positive part of the y-axis. This location contrasts them to the art museum visitor who is located close to the negative part of the y-axis. Compared to the other visitor types, they are more often between 30 and 45 years of age and live more often in a household with many people, two or more being children. They commonly hold a middle school degree and are especially likely to reside in South Germany. Because of their relative proximity at the positive part of the x-axis and the negative part of the y-axis, visitors to history museums and to art museums can be described together, too. Compared to visitors to other museums, they are highly educated (with university or at least German high school degrees), and they are especially likely to be professionals or students. They live in big cities (population greater than 100,000 or 500,000) and earn good salaries (more than DM 5,000 monthly). On the additional basis of the close correlation of the art museum type to the y-axis one can describe this type as older (over 60 years), living in a single- or at maximum two-people household without children, and rather in western Germany than in another part of Germany. The type who does not visit museums is located at the far negative end of the x-axis, standing therefore in contrast to the history museum and art museum visitor types. He or she is more often a blue-collar worker, unemployed or not in the paid labor force (e.g., a housewife or pensioner). Compared to visitors, the non-visitor more often has only a grade school education and lives more often in small towns with fewer than 5,000 inhabitants.
9. Conclusion There are three questions to be answered by this survey. The first is: H o w consistent are the results o f this population study with results o f museum (i.e., in-house) visitor studies?
Nuissl and Schulze (1991) provide an excellent summary of results of several in-house visitor surveys. Their summary shall now be compared with the results of this representative study to find out how much the in-house surveys are in fact biased (i.e., non-representative for the whole population) in their results. A prominent finding of visitor studies, that more educated people visit museums, is corroborated. We find, however, the association of visiting and education is weaker for natural history museums and stronger for art museums. Income emerges as a more important determinant of attendance than it would appear to be on the basis of in-house
256
V. Kirchberg / Poetics 24 (1996) 239-258
surveys. Whereas in-house visitor studies often report that the professional is the main museum visitor, we find students to be especially prominent. Past visitor surveys also postulated that age has a negative impact on visits to museums. This finding cannot be confirmed. Especially for art museums visits increase with age. For natural history museums, however, the effect is in the opposite direction. Gender effects on museum visits are corroborated by this study: more men than women visit science museums, and more women than men visit art museums. The second question is: How do socioeconomic and demographic characteristics correlate with visiting behavior? Nuissl and Schulze (1991) call for more systematic analysis of factors causally related to museum visiting. Many such causal links could be inferred from this study. For example, education correlates with museum visiting, especially to art museums. Income positively effects visits to museums, especially science museums. Blue-collar workers are less active museum-goers. Age affects museum visits, negatively for natural history museums, positively for art museums. The effects of household size and structure on museum visiting are rarely studied. This study found that with increases in the number of children, the number of visits to natural history museums increase and the number of visits to art museums decline. This contrasting character of art museum and natural history museum audiences emerges strikingly from the correspondence analysis, too. On one side we find the science museum and natural history museum visitors, on the other side the history museum and art museum visitors. The relationship among types of visits also illustrates this dichotomy. Of all science museum visitors, 42 percent report visiting natural history museums, but only 39 percent report visiting art museums. Of all history museum visitors, 55 percent report visiting art museums, but only 38 percent say that they visit science museums. And of all art museum visitors, 44 percent visit history museums, but only 32 percent visit science museums. The third question is: Who is the typical non-visitor? How can he or she be distinguished from the visitor? Moreover, is the polarity of visitors and non-visitors stronger than the polarity of art/history museum visitors and science/natural history museum visitors? A single, distinct contrast of non-visitors and visitors could not be corroborated by the correspondence analysis. Rather, there is a continuum of social and demographic characteristics, from the 'high culture' museum visitor through the 'popular' museum visitor to the museum non-visitor. Corresponding to this continuum model the degree of educational attainment declines from art museum audiences through natural history museum audiences to the non-visitors. Similar more or less monotonic changes can be observed for income, age, size of the household, or the population size of the residential area. Therefore, the social contrast among the general museum visitor and the general museum non-visitor does not exist. Certainly, there are social and demographic contrasts between non-visitors and art museum visitor; but these cannot be generalized to all types of museums. Among non-visitors and visitors to the popular types of museums, these contrasts are blurred. For example, see the items of the correspondence analysis map that are not part of one of the rectangles. People who live in towns with 5,000 to 20,000 inhabitants or in households with three people (including one child) are located
V. Kirchberg / Poetics 24 (1996) 239-258
257
between the non-visitors and the visitors to the popular museums. And people who live in eastern Germany, work more than 35 hours a week and are employed in a white-collar job are located between the popular and high-culture museum types. Only if people are characterized by more extreme characteristics (e.g., poor vs. affluent, no education vs. high education, unemployed vs. professional) can one distinguish sharply between visitors and non-visitors, and then only for art or history museums. The existence of a c o n t i n u u m ranging from non-visitors through visitors to popular museums to visitors of high-culture museums should be an incentive to museum representatives interested in 'reaching out' to new visitors. In order to reach new audiences, they do not need to change exhibitions to more 'popular' contents or designs. The implication of these findings is that they should neither focus solely on their traditional audience nor attempt to radically change this audience. Rather the continuum of visitor types shows that there are more alternatives than these two.
References Balfe, Judith H., 1989. The baby-boom generation: Lost patrons, lost audience? In: Margareth J. Wyszomirski and Pat Clubb (eds.), The cost of culture, 9-25. New York: ACA. Bourdieu, Pierre, 1984. Distinction. A social critique of the judgement of taste. Cambridge, MA: Harvard University Press. Eisenbeis, Manfred, 1980. Museum und Publikum. (Iber einige Bedingungen des Museumsbesuches. Museumskunde 45, 16-26. Faulbach, Bernd and Franz-Josef Jelich (eds.), 1991. Besucherinteressen und Besucherverhalten in historischen Museen und Ausstellungen. Recklinghausen: Forschungsinstitut fOr Arbeiterbildung. Gbschel, Albrecht, 1991. Die Ungleichzeitigkeit in der Kultur. Berlin: Difu. Graf, Bernhard and Heiner Treinen, 1983. Besucher im Technischen Museum. Berlin: Berliner Schriften zur Museumskunde, Vol. 4. Greenacre, Michael, 1993. Correspondence analysis in practice. Oxford and London: Academic Press. Haus der Geschichm der Bundesrepublik Deutschland (ed.), 1996. Museen und ihre Besucher. Herausforderungen in der Zukunft. Berlin: Argon. Hoffrichter, Horst, 1990. Die KiSlner Muscen und ihr Publikum. Ki~lner Museums-Bulletin, 41-56. Hoffrichter, Hoist, 1993. Nutzung und Bewertung des Kblner Kulturangebots dutch die Biirger. Verband deutscher St~dtestatistiker. Institut for Museumskunde Berlin, Staatliche Museen zu Berlin -Preugischer Kulturbesitz, 1994. Erhebung der Besuchszahlen an den Museen der Bundesrepublik Deutschland fOr das Jahr 1993. Berlin: Materialien aus dem Institut fOr Museumskunde, Vol. 40. Kirchberg, Volker, 1992. Kultur und Stadtgesellschaft. Wiesbaden: DUV. Kirchberg, Volker, 1994. Preferences and policy: Consuming art and culture in Hamburg and Baltimore. Journal of Arts Management, Law, and Society 24, 146-162. Klein, Hans-Joachim and Monika Bachmayer, 1981. Museum und Offentlichkeit. Berlin: Berliner Schriften zur Museumskunde, Vol. 2. Klein, Hans-Joachim, 1983. Analyse yon Besucherstrukturen an ausgewS.hlten Museen in der Bundesrepublik Deutschland und in Berlin (West). Berlin: Berliner Schriften zur Museumskunde, Vol. 9, Klein, Hans-Joachim, 1990. Der gl,iserne Besucher. Publikumsstrukturen einer Museumslandschaft. Berlin: Berliner Schriften zur Museumskunde, Vol. 8. Klein, Hans-Joachim, 1991. Evaluation far Museen. Karlsruher Schriften zur Besucherforschung, 3-23. Kommunale Gemeinschaftsstelle far Verwaltungsvereinfachung (KGSt), 1989. Die Museen. Besuchsorientierung und Wirtschaftlichkeit. Kbln: KGSt. Nuissl, Ekkehard and Christa Schulze, 1991. Besucherinteressen und Besucherverhalten im Museum. In: B. Faulbach and F.-J. Jelich, 1991, 24-36.
258
V. Kirchberg / Poetics 24 (1996) 239-258
Robinson, John P., Carol A. Keegan, Marcia Karth and Timothy A. Triplett, 1987. Survey of public participationin the arts: 1985. Volume I, ProjectReport. College Park, MD, and Washington, DC: Survey Research Center, University of Maryland, and The National Endowment for the Arts. Schmidt, Helga, 1993. Kulturangebot in Leipzig - Annahmen, Wermngen, Erwartungen. Verband deutscher St~idtestatistiker. Schuster, J. Mark Davidson, 1991. The audience for American art museums. Washington, DC: NEA, Research Division Report 23. Statistisches Bundesamt, 1994. Statistisches Jahrbuch der Bundesrepublik Deutschland. Statistisches Bundesamt. Treinen, Heiner, 1991. Motivationen zum Museumsbesuch. Museumstypen und Besucherprofile. In: B. Fanlenbach and F.-J. Jelich, 1991, 37-45. Verband deutscher St~dtestatistiker (ed.), 1993. Niederschrift der Sitzung des Ausschusses flit Kultur und Bildung vom 18. und 19. Okt. 1993 in Koblenz. Zentrum flit Kulturforschung, 1992. 2. Kulturbarometer (Winter 1991/1992). Bonn: Zentmm fiir Kulturforschung.
Poetics 24 (1996) 239-258
Museum visitors and non-visitors in Germany: A representative survey V o l k e r Kirchberg * University of L',',neburg, Department of Applied Arts Sciences, and Basica Research Institute, Glockengiesserwal126, D-20095 Hamburg, Germany
Abstract German museums have only recently employed sample surveys to learn about the people who visit and who do not visit their museums. The reason for this late activity is a search for new financial sources, and the discovery of the marketing of museums. However, there is still little knowledge of non-visitors and their social background. This survey focusses on the effects of socioeconomic, demographic, and geographic factors on visits or non-visits to four different types of museums: science and technology museums, natural history and natural science museums, history museums, and art museums. For art museums, it was possible to compare the German results with data from the Surveys of Public Participation in the Arts in the United States. In Germany, the type who does not visit museums is more often a blue-collar worker, unemployed or not in the paid labor force. Visitors to science museums and to natural history museums are more often between 30 and 45 years of age and live more often in a household with many people. Visitors to history museums and to art museums are highly educated, and are likely to be professionals or students. A single contrast of non-visitors and visitors could not be corroborated. Rather, the contrasting character of art museum audiences and natural history museum audiences emerges strikingly. On the one side we find the natural history museum and science museum visitors, on the other side the art museum and history museum visitors. There is a continuum ranging from non-visitors to popular museums to visitors of high culture museums with respect to their socioeconomic, demographic and geographic characteristics.
t This study is based on a survey made possible by the Hans der Geschichte der Bundesrepublik Deutschland (Museum of Contemporary History of the Federal Republic of Germany) in Bonn. I am especially grateful to the museum director, Professor Hermann Sch~tfer, for understanding and supporting scientific research in this field. He is one of only a very few in Germany. In November 1995 he initiated the first international conference on museum visitor research in continental Europe (proceedings are published in Haus der Geschichte, 1996). " Fax: Germany + 49-40-422 5703; E-mail: [email protected] 0304-422X/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved PII S 0 3 0 4 - 4 2 2 X ( 9 6 ) 0 0 0 0 7 - I
240
V. Kirchberg / Poetics 24 (1996) 239-258
1. Introduction German museums have rarely and only recently employed sample surveys to learn about the people who visit and, especially, about those who do not visit their galleries. The museums' ignorance of the challenge that non-visitors pose to their outreach programs is a consequence of the administrative and, especially, the subsidy system of most German museums, which are predominantly public institutions run by the respective community or federal state (Bundesland). The success, or even stronger, the survival of a museum has not been dependent on the acceptance and praise of a museum's exhibitions by a broader public but on their specific scientific reputation a n d / o r understanding within the local municipality that provides for their financial needs. However, within the last years a slow transformation process has dawned on the whole of the 'high culture' scene of Germany. As less - or, at least, stagnating - public subsidies discloses to the museum management that public monies are not infinite, the overall reliance on this subsidy source is fading in Germany, too. Responsible and lively museums that try to increase their attractiveness in new fields seek new financial sources; and one pillar of the modem art of museum management rests on the marketing of museums. As an undisputable part of this changing attitude, surveying visitors as new and more important clients of German museums becomes the focus of the museums' attention. The visitor is no longer incidental to a museum that has to be 'public' because of its public subsidies. More often, he or she now becomes the center of attention as the customer of a product that can be offered almost solely because of his or her demand. Increasingly, this new image of the visitor as a customer gains more weight in the German museum managers' strategic planning. However, who is this customer? Information about visitors - and especially about the potential new customer who must be the focus of a museum growth strategy - is scarce. To increase this information remains the task of empirical surveys.
2. Past visitor studies in m u s e u m s in Germany Museum visitor research in Germany is still primarily the realm of (social) scientific interest and not motivated by marketing objectives. For the last decades studies of museum visitors in Germany have been concentrated at two localities, the Sociological Institute at the University of Karlsruhe (directed by Hans-Joachim Klein), and the Institute for Museum Studies (Institut fi~r Museumskunde) at the State Museums of Berlin (Staatliche Museen zu Berlin - Preussischer Kulturbesitz) (directed by Bernhard Graf). In Karlsruhe, since the beginning of the Seventies, many visitor studies in different types of museums have been conducted and published. Furthermore, the Berlin Institute for Museum Studies has been able to document annual numbers of visits to German museums since 1981. In 1993, more than 93.7 million visits occurred at 4,683 museums. The most prominent type of museums are local history and local life museums (15 million visits), followed by art museums (l 2 million visits), science and technology museums (l 2 million visits), history museums (8 million visits), and natural
V. Kirchberg / Poetics 24 (1996) 239-258
241
history museums (4 million visits) (Institut f't~r Museumskunde, 1994). (Germany has a population of 80.97 million.) Nuissl and Schulze (1991) briefly summarize results of German studies on socioeconomic factors related to museum visits. According to them, the staff of most museums is ignorant of the social composition of their audiences. The results of visitors studies (if any are conducted) are not used by German museums. However, research on museum audiences during the 1980s revealed the following general results. Visitors of German museums are younger than the average population. With increasing age, the tendency to visit museums declines. Men form the majority of audiences of science museums whereas women are in the majority among art museum visitors. Moreover, museum visitors are more educated than the average population. The higher the educational attainment the greater the likelihood of a visit. The level of education of art museum visitors, however, is higher than that of visitors to local life or science museums. Occupational status also has a positive impact on museum visits. (As an exception, however, the propensity to visit a science museum declines with higher occupational status.) Nuissl and Schuize mention that there is still little knowledge of non-visitors and their social background. Statements like 'About 25 percent of the German population visit museums', or 'There is a strong social contrast between museum visitors and non-visitors' have been speculative, requiring empirical scrutiny. However, the need to test these assumptions by a representative survey of the whole German population is not well understood by museum managers. Although more and more of them admit the importance of visitor evaluation studies to improve the museum displays, they do not grasp the functions of population sample surveys that focus primarily on non-visitors. Audience development - the idea of actively 'reaching out' to non-visitors to develop them as visitors - is a relatively new and progressive idea in the German museum landscape, and it is not shared by everyone. Also, most museums do not understand that a visitor survey in the institution cannot substitute for a representative survey outside the institution. There is a broad misconception that results of visitor studies in museums are representative for the whole of the society. Klein and Bachmayer (1981) noted that visitors cannot be asked about non-visitors; even first-time visitors asked about their motives and socioeconomic background cannot speak for the majority of people (about three quarters of the German population) who do not cross the threshold of the museum at all. They argued that representative non-visitor surveys are "urgently necessary and hitherto ignored" (Klein and Bachmayer, 1981: 86; this and further quotes translated from German by the author). In-house surveys report on visits, whereas out-of-house surveys can report on visitation rates. In-house surveys often confuse visits with visitors, whereas out-of-house surveys do not. Again and again, social scientists have complained about the lack of reliable data on visitors and non-visitors and about the inaptitude of museums' efforts to conduct visitor surveys. "Measured by the conjectured significance, statistical methods and the certainty of results are grotesquely underdeveloped" (Klein, 1990: 30). "Sociologically
advised analyses of visitor composition are only available for some singular museums" but are rather needed for a representative sample of the whole population universe (Nuissl and Schulze, 1991: 24). Many a report on visitor surveys asks the question
242
V. Kirchberg / Poetics 24 (1996) 239-258
" W h o does actually not come to the museum? ... All one can establish right now is only the fact that some people stay away. Barriers, a lack of information, prejudices, different interests - all this can be authentically investigated only in a direct survey of non-visitors" (Klein and Bachmayer, 1981: 86).
3. Past population studies for museums in Germany The very few representative surveys dealing with museum attendance in Germany have focussed on the population of a single city. They are always part of a general survey on, e.g., urban leisure activities or the population's assessment of the area's quality of life, usually conducted by urban sociologists or administrative statisticians of municipalities, and not directed towards (or even known to) museum leaders. For example, the annual quality-of-life-survey in Cologne emphasized the importance of educational attainment for the visits of museums, reporting that 55 percent of people who have college access legitimacy (e.g., the German high school degree, 'Abitur' ), but only 20 percent of those with a grade school degree (' Volksschule' ), reported visiting a Cologne museum in the previous year (Hoffrichter, 1993). Another local survey on cultural activities has been continuously conducted in Leipzig since 1991. Here, 44 percent of people with a college degree visit museums on a yearly basis but only 20 percent of people who say that they are workers. Eighty-five percent of Leipzig citizens claimed to have visited Leipzig museums during their life in this town (Schmidt, 1993). The Center for Urban Research at the University of Hamburg undertook a representative telephone survey on cultural activities in 1984. The results of this study are of interest because the author repeated parts of this survey in Baltimore in 1989, making possible an international comparison. Educational attainment was an important predictor of attendance in both cities, though less so in Hamburg than in Baltimore. Age and life cycle position influenced museum visits differently in Hamburg and Baltimore. In Hamburg, age had a positive effect (the older the more visits), whereas in Baltimore age had a negative effect (the older the fewer visits). In Hamburg, pensioners are a major group of museum visitors; in Baltimore families with children are a major group of museum visitors (Kirchberg, 1994). This last comparison demonstrates that one cannot generalize from local surveys to other geographical entities. Only two surveys in Germany attempted to gather representative data on museum visitors and non-visitors before 1995. In 1977, 1,991 people in West Germany were asked about the frequency of museum visits, the circumstances under which they visited, and barriers to participation (Eisenbeis, 1980). The main explanatory variable was, again, educational attainment. Twenty percent of Germans with a grade school degree but 53 percent with a university degree reported visiting museums. Fifteen percent of all respondents said that they had never visited any museums, and 22 percent said that they had visited museums only through a school class trip. In 1992, the Center for Cultural Research in Bonn conducted a similar representative survey of the German population ( Z e n t r u m f ~ r Kulturforschung, 1992) with a sample of 3,065 people (now in eastern and western Germany). The most popular museums among Germans are local history and
V. Kirchberg / Poetics 24 (1996) 239-258
243
local life museums: 38 percent of all Germans are interested in this type, followed by art museums (24 percent). Sixteen percent said they were not interested in museums at all. In 1992, nine percent of all respondents said that they had never been to museums, and an additional 30 percent said that they visited museums only as a school experience. (Unfortunately, this study did not analyze educational attainment as a predictor of museum visits, making comparison with the 1977 survey impossible.) Our 1995 study, which I describe below, fills this and other information gaps. Based on responses from a representative sample of almost 17,000 people in Germany, this survey focussed on the effects of socioeconomic and demographic factors on visits to four different types of museums.
4. The survey on museum visitors and non-visitors in 1995
A random-quota sample was created from a larger household access panel of more than 31,000 German households. This panel was drawn from all German households by quota that correctly reflect the different socioeconomic structures of the regions of Germany. Then, random households were drawn from these quota households to maintain representativeness. Comparison of the sample's socioeconomic characteristics with official data from the German 'Bureau of Census' (Statistisches Bundesamt, 1994) confirms this representativeness. The sample used in these analyses includes 16,862 respondents. According to the international UNESCO classification and corresponding recommendations of the Berlin Institute for Museum Studies, this study distinguishes four types of museums: (1) science and technology museums, (2) natural history and natural science museums, (3) history museums, and (4) art museums. (A special German case are the so-called 'local life museums' [Heimatkundemuseen] that collect, interpret and exhibit only pieces of the community in which they are located, mostly for the purpose of preserving the community's historic identity and propagating it to contemporaries. Because they focus upon the past, such museums are classified as historical museums.) Respondents were classified as visitors or non-visitors to these four museum types. As explanatory variables we asked for information about socioeconomic status (educational attainment, annual household income after taxes, occupational position), demographic indicators (age and gender), geographical information (ZIP code of the place of residence, population size of the place of residence), and factors likely to influence discretionary time (number of hours worked per week, number of children younger than 15 years of age).
5. Multiple classification analysis of museum visitors
To measure correctly the effect of these variables on visits to the different museum types it is necessary to control for the effects of other variables. For example, does income positively affect visits to art museums or does the correlation between income
244
V. Kirchberg/ Poetics 24 (1996) 239-258
and art museum visiting reflect the intervening effect of education (since it is highly correlated with income)? To eliminate such confounding effects, we applied multiple classification analysis (MCA) as a statistical tool. (Later on, we use another multivariate tool, correspondence analysis.) Multiple classification analysis must be combined with another statistical method, analysis of variance. Analysis of variance labels categorical explanatory variables as factors (a custom we will follow here). For every categorical value of a factor, MCA first calculates a mean of the variable values to be explained (here: the average museum participation rate). For example MCA can yield an obervation such as 'An average 17 percent of Germans between 65 and 74 years of age visit a science museum'. Second, MCA calculates an adjusted mean for the dependent variable for every explanatory category, i.e. adjusted for the intervening effects of other factors. This will change the previous statement to 'An average 20 percent of Germans between 65 and 74 years of age visit a science center, adjusted for other background characteristics'. Thus the intervening effect of education (older people are less educated) has been eliminated. Tables 1-5 have the following structure: 1st column: Name and categories of the factor 2nd column: unadjusted participation rate for each category 3rd column: MCA adjusted participation rate for this category 4th column: F-value of the factor (the higher this value, the stronger the category's effect on visiting rates), and the significance of F A summary of the results of MCA analyses follows, indicating the factors that influence visits to each type of museum. In the tables the factors education, income, occupation, age, sex, and region are displayed. Two more factors, number of children and number of working hours, are not displayed, but are mentioned in the discussion that follows each table. Twenty percent of Germans visited a science or technology museum between mid-1994 and mid-1995. (See Table 1.) Education: There are clear differences in participation rates by educational level. The greatest difference, 21 percent, can be observed between people with grade school without vocational training and those with a college or university degree. Even adjusting for intervening effects, the difference is a considerable 18 percent. Thus with higher levels of educational attainment, rates of visiting science museums increase. Income: There are considerable differences in participation rates among income categories, too, if not quite as distinct as for the educational levels. The participation rate is 14 percent in the lowest income category and 25 percent in the highest income bracket, a difference of l I percentage points. After MCA adjustment this difference is still l0 percentage points. Occupation: Rate differences of the extreme categories 'Not Occupied' and 'In School' are 14 percentage points (16 percent and 30 percent, respectively). However, all other categories of this factor have quite similar rates (around 20 percent), especially after MCA adjustment. Only people still in school, college or vocational training are visiting this type of museum more often (28 percent after adjustment). Age: The highest unadjusted difference between these categories is 8 percentage points, with respondents under 25 years at the highest rate (20 percent) and those over
V. Kirchberg / Poeticv 24 (1996) 239-258
245
74 years having the lowest (12 percent). With MCA adjustment, however, the rates become almost the same, remaining around 20 percent through age 75 and only then declining. Therefore, age does not seem to exert a significant effect on this activity. Gender: The rate of visiting science centers is significantly higher for men than for women, even after the MCA adjustment. Regions of Germany: In southern Germany the participation rate for science center visits is significantly higher (24 percent) than in northern Germany (16 percent). In western and eastern Germany, the rates are around the grand mean of 20 percent. Controlling for other factors does not change this impression, the difference between the interested South and the uninterested North remains at 7 percentage points. This may be due to a higher supply of science centers in the South of Germany, especially in Munich. Other factors: The number of school-age children in the household has no impact on visits to science centers. In contrast, the number of weekly working hours influences the visit of this museum type positively. The more hours one works the more likely one is to visit science centers, i.e., from 17 percent of people who work no hours to 24 percent of those who work more than 35 hours weekly (adjusted for other factors). Twenty-one percent of the German population visited a natural history museum in 1994/95. This is very similar to the rate of visiting science museums. (See Table 2.) Education: This factor has an even more important impact on visits to this type of museum than on visits to science museums. The difference among the categories is 24 percentage points (10 percent for the lowest and 34 percent for the highest level of education). After MCA adjustment the difference is still 20 percentage points (12 percent to 32 percent). Income: The impact of this factor is slightly less than it is for the science museum visits. However, it is significant (15 percent in the lowest income bracket, 23 percent in the highest income bracket); the higher the income, the higher the participation rate. Occupation: The impact of this factor is also slightly less than its impact on visits to science museums. After MCA adjustment, the participation rate of blue-collar workers is 19 percent; for students it is 29 percent. Age: Age has a distinct effect on visits to natural history museums. Younger Germans visit more (22 percent after adjustment) than older Germans (16 percent). Gender: The effect of gender is weakly significant, with women visiting more (22 percent) than men (20 percent). Regions of Germany: There are clear differences among the regions. Rates of visitation are higher in the still less industrialized South (24 percent with adjustment) than in the industrialized West (18 percent). The South, with most of the country's mountains, offers more natural history museums (in natural settings) than the West. Other factors: The number of children in a household has a positive effect on visits to natural history museums; the more children, the more visits. Participation rates are 18 percent for households without children and 27 percent for households with two or more children. Weekly working time has no effect on visits to this museum type. Twenty-one percent of Germans visited history museums in the eighteen months preceding the survey. (See Table 3.) Education: Education's impact on visits to history museums is weaker than its effect on attendance at science or natural history museums, but is still significant. After MCA
246
V. Kirchberg / Poetics 24 (1996) 239-258
Table I
MCA: Comparison of unadjusted and adjusted participation rates for Science and Technology Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the [bllowing topic? - Science and technology?"
Overall rate
Participation rate
MCA-adjusted participation rate
20%
20%
9% 17% 20% 20% 28% 31%
11% 17% 20% 20% 28% 29%
14% 14% I 1% 16% 17% 25%
14% 16% 14% 17% 18% 24%
16% 18% 23% 21% 30%
20% 20% 20% 18% 28%
20% 20% 21% 21% 17% 17% 12%
20% 19% 20% 21% 20% 23% 16%
18% 22%
18% 20%
21% 16% 19% 24%
20% 17% 19% 24%
21.6 (0.000)
Annual income
DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24,000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
6.3 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
1.3 (0.246)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older Gender
Female Male
2 I . l (0.000)
20.5 (0.000)
Region in Germany
East North West South
17.6 (0.000) 51.7(0.000)
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
F-value (sig. F)
a d j u s t m e n t the d i f f e r e n c e in v i s i t i n g rates b e t w e e n the g r o u p with the l o w e s t and the g r o u p with the h i g h e s t e d u c a t i o n a l a t t a i n m e n t (13 p e r c e n t a n d 31 p e r c e n t , r e s p e c t i v e l y ) is still substantial.
247
V. Kirchberg / Poetics 24 (1996) 239-258
Table 2 MCA: Comparison of unadjusted and adjusted participation rates for Natural Hiswry and Natural Science Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the following topic? - Natural history and natural science?"
Overall rate
participation rate
MCA-adjusted participation rate
21%
21%
10% 16% 22% 25% 27% 34%
12% 16% 21% 25% 27% 32%
15% 17% 16% 18% 20% 24%
15% 19% 18% 20% 20% 23%
19% 16% 23% 23% 30%
22% 19% 21% 20% 29%
23% 21% 25% 21% 16% 15% 13%
22% 18% 22% 22% 21% 21% 16%
22% 20%
22% 20%
24% 21% 18% 24%
23% 22% 18% 24%
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
4.5 (0.000)
3.0 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
10. I (0.000)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
9.0 (0.003)
Gender
Female Male
13.8 (0.000)
Regum in Germany
East North West South
18.1 (0.000) 60.1 (0.000)
Annual income
DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24.000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
F-value (sig. F)
I n c o m e : I n c o m e also has a strong p o s i t i v e i m p a c t on visits to h i s t o r y m u s e u m s . T h e a d j u s t e d rate for the l o w e s t i n c o m e b r a c k e t is 19 p e r c e n t , and for the h i g h e s t i n c o m e
bracket, 24 p e r c e n t .
248
V. Kirchberg / Poetics 24 (1996) 239-258
Table 3 MCA: Comparison of unadjusted and adjusted participation rates for History Museums, Germany 1995 Question: "In 1994 or 1995, did you visit a museum or an exhibition on the fi~llowing topic? - History?" Participation rate
MCA-adjusted participation rate
Overall rate
21%
21%
Educational attainment Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
11% 16% 22% 24% 28% 32%
13% 17% 22% 24% 27% 31%
Annual income DM 12,000 or less DM 12,000 - DM 18,000 DM 18,000 - DM 24.000 DM 24,000 - DM 36,000 DM 36,000 - DM 48,000 DM 48,000 or more
21% 18% 16% 17% 19% 24%
19% 18% 17% 18% 20% 24%
Occupational position Not occupied Worker/blue-collar Employee/White collar Professional/entrepreneur In school/voc, training
18% 15% 24% 22% 33%
21% 19% 21% 19% 31%
Age 15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
22% 21% 21% 23% 21% 16% 19%
21% 19% 21% 23% 23% 19% 20%
Gender Female Male
21% 21%
21% 21%
Region in Germany East North West South
26% 23% 20% 20%
25% 23% 20% 20%
F-value (sig. F) 13.0 (0.000) 49.9 (0.000)
10.6 (0.000)
7.0 (0.000)
3.5 (0.002)
0.0 (0.928)
6.1 (0.000)
O c c u p a t i o n a l p o s i t i o n : O c c u p a t i o n a l p o s i t i o n i n f l u e n c e s visits to h i s t o r y m u s e u m s , too, m o r e so than visits to s c i e n c e or natural h i s t o r y m u s e u m s . N i n e t e e n p e r c e n t o f
b l u e - c o l l a r w o r k e r s h a d visited a h i s t o r y m u s e u m , c o m p a r e d to 31 p e r c e n t o f students.
V. Kirchberg / Poetics 24 (I 996) 239-258
249
Age: The effect of age on visits to history museums is nonlinear, with the most active group consisting of men and women in their 50s (23 percent) and, only secondarily, those under 35 (20 percent rate among people under 35 years of age). Gender: Men and women visit history museums at a similar rate. Regions of Germany: Although the effects of region are less strong than for science and natural history museums, differences do exist. Perhaps due to differences in political education, residents of eastern Germany are more dedicated history museum-goers (25 percent) than residents of western or southern Germany (20 percent). Other factors: Neither the number of children nor weekly working hours affect history museum visiting. Twenty-six percent of Germans visited art museums in 1994/95, a higher participation rate than for the other museum types. Even more than other museum types, art museum visiting is a function of social and demographic characteristics. (See Table 4.) Education: The effect of education is very strong, even more so than for other museum types. The least educated group visits at a rate of only 8 percent, compared to 52 percent for the most highly educated. Income: Income influences visits to art museums less than visits to science museums, but to a similar degree as visits to history museums. After adjustment, 20 percent of those in the low income bracket (12,000 to 18,000 DM), compared to 29 and 24 percent, respectively, in the higher brackets (more than 24,000 DM, more than 48,000 DM) are visitors. Occupational position: Occupational position has a stronger effect on visits to art museums than on visits to any other museum type, with 20 percent of blue-collar workers and 39 percent of students reporting a visit during the previous eighteen months. Age: Age also has strong effects on visits to art museums and, in contrast to the other museum types, the effect is linear and positive. Rates range from 22 percent for those 25 to 34 years of age to 31 percent for people 65 and older. Gender: In contrast to science museums, significantly more women (28 percent) than men (24 percent) visit art museums. Regions of Germany: The effect of region on visits to art museums is relatively weak, although the difference between south (27 percent) and north (24 percent) is statistically significant. Other factors: Number of children is negatively related to art museum visits: after adjustment, 29 percent of people without children visit art museums, compared to 20 percent of men and women living in households with two or more children. It is possible to compare these particular results for visits of art museums with Schuster's analysis of data from the Surveys of Public Participation in the Arts in the United States (Schuster, 1991; Kracman, this issue, also uses data from that survey). He constructed MCA tables very similar to Table 4, rendering comparison easy and instructive. Germans and Americans visit art museums at comparable rates, 22 percent for Americans (during the previous 12 months) compared to 26 percent for Germans (during an interval of approximately 18 months). In the United States, as in Germany, educational attainment is most closely associated with museum visiting, with income
250
V. Kirchberg / Poetics 24 (1996) 239-258
Table 4 MCA: Comparison of unadjusted and adjusted participation rates for Art Museums, Germany 1995 Question: "In 1994 or 1995. did you visit a museum or an exhibition on the Jollowing topic? - Art?"
Overall rate
Participation rate
MCA-adjusted participation rate
26%
26%
8% 15% 24% 39% 46% 53%
8% 15% 25% 37% 45% 52%
30% 22% 21% 22% 21% 32%
23% 20% 22% 24% 24% 29%
22% I 1% 29% 36% 49%
27% 20% 25% 31% 39%
27% 26% 22% 28% 29% 29% 30%
26% 22% 24% 29% 30% 31% 30%
28% 24%
28% 25%
29% 24% 26% 25%
25% 24% 27% 27%
11.3 (0.000)
Annual income
DM DM DM DM DM DM
12,000 or less 12,000 - DM 18,000 18,000 - DM 24.000 24,000 - DM 36,000 36,000 - DM 48,000 48,000 or more
i 7.8 (0.000)
Occupational position
Not occupied Worker/blue-collar Employee/white-collar Professional/entrepreneur In school/voc, training
29.5 (0.000)
Age
15-25 years 25-34 years 35-44 years 45-54 years 55-64 years 65-74 years 75 years and older
14.2 (0.000)
Gender
Female Male
3.1 (0.028)
Region in Germany
East North West South
60.3 (0.000) 266.2 (0.000)
Educational attainment
Grade school w / o vocational training Grade school with vocational training Middle school High school without grad. High school with grad. College/university
F-value (sig. F)
p l a y i n g a m u c h less i m p o r t a n t , a l t h o u g h still s i g n i f i c a n t , role. In b o t h c o u n t r i e s m o r e w o m e n ( 2 4 p e r c e n t in U S A , 28 p e r c e n t in G e r m a n y ) t h a n m e n ( 2 0 p e r c e n t a n d 25 p e r c e n t , r e s p e c t i v e l y ) r e p o r t e d v i s i t i n g art m u s e u m s . T h e r e are also s m a l l r e g i o n a l d i f f e r e n c e s in e a c h c o u n t r y .
V. Kirchberg / Poetics 24 (1996) 239-258
251
The only major difference is in the effects of age on art museum participation, which are strong but differing effects in these two countries. Whereas the relationship between age and art museum visiting in the U.S. is shaped like an inverted U, with the highest rates for men and women in their 30s and 40s, visiting rates peak among older men and women in Germany. This difference may, of course, reflect cohort or generational differences rather than age effects. Within each generation, differently in the two countries, there may be different art values, shaped by different historical conditions and predominant generational experiences. German museums remain 'elite art' institutions, radiating the image of a 'temple of the classics', which pleases the generations born in the 1920s or 1930s but deters the generations of the 1960s or 1970s (G~Sschei, 1991). An art museum in the USA, however, seems to adjust better to the interests of the younger 'baby-boom' generations (Balfe, 1989). This may, again, reflect strategies of American museums that are more visitor-oriented than those of their German counterparts. Up to now, we have compared visitors to each museum type with those who do not visit that kind of museum. We have not yet provided a profile of the 'non-visitor,' who visits no museums at all. This, plus descriptions of visitors to the four museum types, will be provided by the analysis in the following section. 6. Profiles of museum visitors and non-visitors in Germany An elegant method to analyze categorical data in a multivariate manner is the
correspondence analysis. This method estimates mutual effects of exogenous and endogenous variables, and yields two complementary products, a graphical output that
~ ~::~ ~~ : ~ : ~ . L : , ~ ¸:~:~! ~ , ~ , ~ :
:~,'~~,~~ e - ~ " , ~ ~ ~
*
~
,
~
~ , ~ ' ~ , ~
~ ~':~,¸~:¢,"~,::> :~.~~:,L~,~ ,:~;',q~,~<~:F: '¸ ~:~, ~ - ~ : : ~ : ~ : ~ ' ~ > : * ~ , : + , "
<, ':~ ~::~: ~ , : ~ : ~ ~:~:~:~<
.~,two o~ more children i
.:
ehold with 4 or more persons \
mNATURALHISTORYMUSEUMVISITOR
: \o31 to\45 years of age : one child S~u~hGee-man ~i:iworker <5.000_.Izc~ • \I •~SCIENCEMUSEUMVISITOR i;:: • ~ ~$O00DM•<1~hrs/ mEast German ~J. < 2 0 0 0 •0epl a )m~ ! _ . .e/ployed••>35hrs . . . m a ! . . e O ~ o .•~ . ~ ~ p •
univp..~.s_kt~•
i I........ 3 ~ p e r ~ s ~ . ' h ~ o ~ u s ~ e h o - i ~ o ~ ° ' o ~ - 1 ~ . ~ ' O O ~ ~ t i o n ~NO~MVSEUM VISITOR~\NorthGe'r• •< 30 ~ears old / ~ g ~ s c h o o l •no,work i •female\ •professioj~•upper high school : unRtmm~l.Q.yed•~.~Eest ~er.-500.01~0• •>500.0])~" pop.
~ii. : ! ,
2-pers. household~ ' 4 " 6 - ~ y e ~ of age ~I.-2.00~DM ~ • ~"~A'RTMUSEUMVISITOR >60 years of age • i: i:!
•'singlehousehold
Fig. l.Correspondence analysis map of the types of museum visitors and non-visitors.
252
V. Kirchberg / Poetics 24 (1996) 239-258
shows the results 'at a glance', and a tabular output that provides detailed numerical results that are useful in interpreting the graphical display. Below, both Fig. 1 and Table 5 reveal the profiles of the different museum visitors and the non-visitor.
7. Excursus: The interpretation of correspondence analysis results This method of statistical analysis, which was developed by Jean-Paul Benz~cri in the 1960s, gained the attention of sociologists primarily through its application by Pierre Bourdieu (1984) in D i s t i n c t i o n . Correspondence analysis produces a kind of 'scatterplot' diagram from a contingency table. It is similar to principal component analysis; however, the 'clustering' of data results not from analysis of variance along principal axes, but through decomposition of the usual chi-square statistic for row-column independence along principal axes. In principal component analysis, rows and columns define a 'cloud' of points in a multidimensional space and the principal axes identify those subspaces which come closest to these points (i.e., factors of a factor analysis). In correspondence analysis there are two clouds of points - a set of column profiles and a set of row profiles, where a row (colunm) profile is the row (column) of the data matrix divided by its respective row (column) sum (i.e., a set of relative frequencies). Correlation coefficients of a correspondence analysis correspond to factor loadings of a principal component analysis. These correlations (labelled ' c o r ' in Table 5) are calculated for all categories of each item used in the analysis, whether the items are column or row variables. The proximity of the analyzed items in the multidimensional space to each of the principal axes is calculated from the item's row and column coordinates. The further 'location' at the negative or positive part of the axis is determined by the plus or minus sign before the ' l o c ' value in Table 5. The item's contribution to the position of the axis is indicated by the 'ctr' value. As a convention the variables (items) to be explained (here, participation rates for the four museum types and rates of non-visiting) are the columns of a contingency table; and the explanatory variables (items) (here, the individual socioeconomic, demographic and other categories) are the rows of this contingency table. The correspondence of these individual characteristics to the variables of museum visits is analogous to the 'clustering' of a principal component analysis, where items are grouped to dimensions (factors). Items are assigned to particular axes (in this case, visitor types) on the basis, primarily, of high c o t values and, secondarily, high ctr values. The l o c - v a l u e ' s sign determines assignment to the positive or negative part of the axis. The number of axes is determined by a s c r e e - t e s t procedure similar to that used to determine the number of axes in principal component analyses. For further information about correspondence analysis see Greenacre (1993). Column items (visitor types) are assigned to axes and axis locations through interpretation of the c o t , ctr and loc values. Then individual characteristics (row items) are assigned to these axes (by their c o t , ctr and loc values). By seeing which individual characteristics correspond to which row items, we describe the profile of each visitor type. Final!y, we compare axis assignments to see how the visitor types correspond to each other.
253
v. Kirchberg / Poetics 24 (1996) 239-258 8. C o r r e s p o n d e n c e
analysis:
Description
of profiles
T h e t y p i c a l v i s i t o r p r o f i l e s ( a n d the profile o f the n o n - v i s i t o r ) are d i s p l a y e d first g r a p h i c a l l y (Fig. !) a n d t h e n in t a b u l a r f o r m ( T a b l e 5). I n d i v i d u a l c h a r a c t e r i s t i c s a n a l y z e d i n c l u d e g e n d e r , age, o c c u p a t i o n a l p o s i t i o n , w o r k i n g h o u r s , i n c o m e , p o p u l a t i o n size o f r e s i d e n t i a l area, a n d region. In Fig. 1, the c o - o r d i n a t e m a p c o n s i s t s o f t w o a x e s ( t w o are sufficient for e x p l a n a t i o n o f the m o d e l ) . T h e h o r i z o n t a l axis ( x - a x i s ) e x p l a i n s 78.8 p e r c e n t and the v e r t i c a l axis ( y - a x i s ) e x p l a i n s 15.9 p e r c e n t o f all c o r r e s p o n d e n c e s . T h e x-axis is m a r k e d b y the c o n t r a s t o f m u s e u m visit to m u s e u m n o n - v i s i t . In the n e g a t i v e part o f this axis o n e f i n d s n o n - v i s i t o r s w i t h t h e i r p r e d o m i n a n t c h a r a c t e r i s t i c s ; in the p o s i t i v e part, o n e c a n locate v i s i t o r s to the d i f f e r e n t t y p e s o f m u s e u m , w i t h t h e i r c o r r e s p o n d i n g c h a r a c t e r i s t i c s . T h e Table 5 Assignment of column items (visitors to axes) and row items (individual characteristics to visitor types, or axes, respectively) Item
Ist axis ( X )
Column assignment:
Ioc I
cor
ctr
2rid axis ( Y )
Visitors to: Science museums Natural history museums History museums Art museums No museum
65 46 64 158 - 172
403 166 689 780 983
38 20 39 qf 296 607 #*
Row assignment:
Ioc I
cor
ctr
loc2 54 94 5 -82 - 22 Ioc2
cor
ctr
277 694 4
131 • 418 •
212
399 6 51
17 cor
I
ctr
Gender Female Male
23 - 26
200 289
2 2
- 23
21
186 178
Age < 30 years 31-45 ears 46-60 years > 60 years
23 - 22 37 - 56
510 64 257 140
1 1 2 3
-10 85 -58 - 135
108 912 614 809
Occupational position Professional White-collar employee Blue-collar worker Not occupied In education
170 97 - 343 - 147 399
900 916 912 899 996
I! 27 51 6 46 6 53 V
-19 26 44 -40 2
II 67 15 66 0
Educational attainment Grade school Middle school High school College/university
- 341 3 324 481
988 9 985 990
210 6 0 105 V 150 V
- 22 22
4 518 10 2
4
Weekly hours at work No hours at work < 16 hours
- 145 - 31
884 391
37 6 1
- 46
89 115
18 2
-33 19
17
7
7 1 93 & 30 • 78 •
I
10 4 17 0
56
5 I
254
V. Kirchberg / Poetics 24 (1996)239-258
Table 5 (continued) Item
Ist axis ( X )
C o l u m n assignment:
loc I
15-35 hours > 35 hours
2nd axis (Y ) cor
ctr
88 108
728 721
10 21
-68 - 169 - 126 - 58 202
213 745 859 682 960
- 157 - 65 - 8 129 213
956 876 336 894 969
108 - 33 -36 51
681 174 354 285
48 - 87 -62
93 -2 - 49 - 22
Ioc2
cor
ctr
27 23
67 34
5 5
0 28 10 M 8 76 V
-104 - 87 - 34 37 26
493 198 62 277 16
5 • 37 4 15 6
30 M 6 0 16 V 43 V
33 15 - 5 - 22 -31
44 47 134 25 21
4 2 3 5
44 - 7 -45 57
I 16 7 564 364
4 0 26 • 29 &
249 745 121
8 9 5
-81 49 162
722 243 834
120 • 15 183 &
320 2 896 32
9 0 3 #~ I
- 134 -52 6 121
660 785 14 940
89 • 25 • 0 135 Ak
Income brackets < 1000 DM 1000- 2500 DM 2500-3000 DM 3000-5000 DM > 5000 DM
Population at residence < 5.000 pop. 5.{X)1-20.000 pop. 20.001 - 100.000 pop. 100.001-500.000 pop. > 500.000 pop.
7 2 0 2 4
Regions of Germany East North West South
Number of children No children One child Two or more children
Household size Single person household Two-person household Three-person household Four or more pers. househ.
dimension of the y-axis is marked by the contrast of natural science/popular orientation (positive axis part) to humanistic/high-culture orientation (negative part), with natural history and science museum visitors contrasted with history and art museum visitors. Superimposed upon the map of Fig. 1 are four tilted rectangles, which reflect the correspondence of certain individual characteristics to each type of museum visitor. At least one visitor type is positioned in or at each rectangle (types are in capital bold italic letters and underlined to distinguish them from the corresponding characteristics). The characteristics in or at the edge of the rectangles describe the corresponding visitor types. To interpret these results it is useful to inspect both Fig. 1 and Table 5. Analogous to principal component analysis the main task is to assign individual characteristics (i.e., items) to types of visitors (i.e., parts of axes or dimensions). This task can be adequately carried out by visually inspecting items close to the museum types (inside and at the
V. Kirchberg / Poetics 24 (1996) 239-258
255
rectangles) but even better through the assignment of items by high cor and ctr values (plus the loc sign) to the axes. In Table 5, (row) items that correspond with particular (column) visitor types are marked by the four playing-card signs: spade (indicating that the item corresponds to the art museum visitor type), diamond (science or natural history museum visitors), heart (history museum visitors), and club (non-visitors). The first axis column differentiates museum visitors of all kinds from the non-visitors. The second axis column distinguishes among the types of museum visitors. Visitors to science museums and to natural history museums are too similar to be distinguished by correspondence analysis. These two types are located close to the positive part of the y-axis. This location contrasts them to the art museum visitor who is located close to the negative part of the y-axis. Compared to the other visitor types, they are more often between 30 and 45 years of age and live more often in a household with many people, two or more being children. They commonly hold a middle school degree and are especially likely to reside in South Germany. Because of their relative proximity at the positive part of the x-axis and the negative part of the y-axis, visitors to history museums and to art museums can be described together, too. Compared to visitors to other museums, they are highly educated (with university or at least German high school degrees), and they are especially likely to be professionals or students. They live in big cities (population greater than 100,000 or 500,000) and earn good salaries (more than DM 5,000 monthly). On the additional basis of the close correlation of the art museum type to the y-axis one can describe this type as older (over 60 years), living in a single- or at maximum two-people household without children, and rather in western Germany than in another part of Germany. The type who does not visit museums is located at the far negative end of the x-axis, standing therefore in contrast to the history museum and art museum visitor types. He or she is more often a blue-collar worker, unemployed or not in the paid labor force (e.g., a housewife or pensioner). Compared to visitors, the non-visitor more often has only a grade school education and lives more often in small towns with fewer than 5,000 inhabitants.
9. Conclusion There are three questions to be answered by this survey. The first is: H o w consistent are the results o f this population study with results o f museum (i.e., in-house) visitor studies?
Nuissl and Schulze (1991) provide an excellent summary of results of several in-house visitor surveys. Their summary shall now be compared with the results of this representative study to find out how much the in-house surveys are in fact biased (i.e., non-representative for the whole population) in their results. A prominent finding of visitor studies, that more educated people visit museums, is corroborated. We find, however, the association of visiting and education is weaker for natural history museums and stronger for art museums. Income emerges as a more important determinant of attendance than it would appear to be on the basis of in-house
256
V. Kirchberg / Poetics 24 (1996) 239-258
surveys. Whereas in-house visitor studies often report that the professional is the main museum visitor, we find students to be especially prominent. Past visitor surveys also postulated that age has a negative impact on visits to museums. This finding cannot be confirmed. Especially for art museums visits increase with age. For natural history museums, however, the effect is in the opposite direction. Gender effects on museum visits are corroborated by this study: more men than women visit science museums, and more women than men visit art museums. The second question is: How do socioeconomic and demographic characteristics correlate with visiting behavior? Nuissl and Schulze (1991) call for more systematic analysis of factors causally related to museum visiting. Many such causal links could be inferred from this study. For example, education correlates with museum visiting, especially to art museums. Income positively effects visits to museums, especially science museums. Blue-collar workers are less active museum-goers. Age affects museum visits, negatively for natural history museums, positively for art museums. The effects of household size and structure on museum visiting are rarely studied. This study found that with increases in the number of children, the number of visits to natural history museums increase and the number of visits to art museums decline. This contrasting character of art museum and natural history museum audiences emerges strikingly from the correspondence analysis, too. On one side we find the science museum and natural history museum visitors, on the other side the history museum and art museum visitors. The relationship among types of visits also illustrates this dichotomy. Of all science museum visitors, 42 percent report visiting natural history museums, but only 39 percent report visiting art museums. Of all history museum visitors, 55 percent report visiting art museums, but only 38 percent say that they visit science museums. And of all art museum visitors, 44 percent visit history museums, but only 32 percent visit science museums. The third question is: Who is the typical non-visitor? How can he or she be distinguished from the visitor? Moreover, is the polarity of visitors and non-visitors stronger than the polarity of art/history museum visitors and science/natural history museum visitors? A single, distinct contrast of non-visitors and visitors could not be corroborated by the correspondence analysis. Rather, there is a continuum of social and demographic characteristics, from the 'high culture' museum visitor through the 'popular' museum visitor to the museum non-visitor. Corresponding to this continuum model the degree of educational attainment declines from art museum audiences through natural history museum audiences to the non-visitors. Similar more or less monotonic changes can be observed for income, age, size of the household, or the population size of the residential area. Therefore, the social contrast among the general museum visitor and the general museum non-visitor does not exist. Certainly, there are social and demographic contrasts between non-visitors and art museum visitor; but these cannot be generalized to all types of museums. Among non-visitors and visitors to the popular types of museums, these contrasts are blurred. For example, see the items of the correspondence analysis map that are not part of one of the rectangles. People who live in towns with 5,000 to 20,000 inhabitants or in households with three people (including one child) are located
V. Kirchberg / Poetics 24 (1996) 239-258
257
between the non-visitors and the visitors to the popular museums. And people who live in eastern Germany, work more than 35 hours a week and are employed in a white-collar job are located between the popular and high-culture museum types. Only if people are characterized by more extreme characteristics (e.g., poor vs. affluent, no education vs. high education, unemployed vs. professional) can one distinguish sharply between visitors and non-visitors, and then only for art or history museums. The existence of a c o n t i n u u m ranging from non-visitors through visitors to popular museums to visitors of high-culture museums should be an incentive to museum representatives interested in 'reaching out' to new visitors. In order to reach new audiences, they do not need to change exhibitions to more 'popular' contents or designs. The implication of these findings is that they should neither focus solely on their traditional audience nor attempt to radically change this audience. Rather the continuum of visitor types shows that there are more alternatives than these two.
References Balfe, Judith H., 1989. The baby-boom generation: Lost patrons, lost audience? In: Margareth J. Wyszomirski and Pat Clubb (eds.), The cost of culture, 9-25. New York: ACA. Bourdieu, Pierre, 1984. Distinction. A social critique of the judgement of taste. Cambridge, MA: Harvard University Press. Eisenbeis, Manfred, 1980. Museum und Publikum. (Iber einige Bedingungen des Museumsbesuches. Museumskunde 45, 16-26. Faulbach, Bernd and Franz-Josef Jelich (eds.), 1991. Besucherinteressen und Besucherverhalten in historischen Museen und Ausstellungen. Recklinghausen: Forschungsinstitut fOr Arbeiterbildung. Gbschel, Albrecht, 1991. Die Ungleichzeitigkeit in der Kultur. Berlin: Difu. Graf, Bernhard and Heiner Treinen, 1983. Besucher im Technischen Museum. Berlin: Berliner Schriften zur Museumskunde, Vol. 4. Greenacre, Michael, 1993. Correspondence analysis in practice. Oxford and London: Academic Press. Haus der Geschichm der Bundesrepublik Deutschland (ed.), 1996. Museen und ihre Besucher. Herausforderungen in der Zukunft. Berlin: Argon. Hoffrichter, Horst, 1990. Die KiSlner Muscen und ihr Publikum. Ki~lner Museums-Bulletin, 41-56. Hoffrichter, Hoist, 1993. Nutzung und Bewertung des Kblner Kulturangebots dutch die Biirger. Verband deutscher St~dtestatistiker. Institut for Museumskunde Berlin, Staatliche Museen zu Berlin -Preugischer Kulturbesitz, 1994. Erhebung der Besuchszahlen an den Museen der Bundesrepublik Deutschland fOr das Jahr 1993. Berlin: Materialien aus dem Institut fOr Museumskunde, Vol. 40. Kirchberg, Volker, 1992. Kultur und Stadtgesellschaft. Wiesbaden: DUV. Kirchberg, Volker, 1994. Preferences and policy: Consuming art and culture in Hamburg and Baltimore. Journal of Arts Management, Law, and Society 24, 146-162. Klein, Hans-Joachim and Monika Bachmayer, 1981. Museum und Offentlichkeit. Berlin: Berliner Schriften zur Museumskunde, Vol. 2. Klein, Hans-Joachim, 1983. Analyse yon Besucherstrukturen an ausgewS.hlten Museen in der Bundesrepublik Deutschland und in Berlin (West). Berlin: Berliner Schriften zur Museumskunde, Vol. 9, Klein, Hans-Joachim, 1990. Der gl,iserne Besucher. Publikumsstrukturen einer Museumslandschaft. Berlin: Berliner Schriften zur Museumskunde, Vol. 8. Klein, Hans-Joachim, 1991. Evaluation far Museen. Karlsruher Schriften zur Besucherforschung, 3-23. Kommunale Gemeinschaftsstelle far Verwaltungsvereinfachung (KGSt), 1989. Die Museen. Besuchsorientierung und Wirtschaftlichkeit. Kbln: KGSt. Nuissl, Ekkehard and Christa Schulze, 1991. Besucherinteressen und Besucherverhalten im Museum. In: B. Faulbach and F.-J. Jelich, 1991, 24-36.
258
V. Kirchberg / Poetics 24 (1996) 239-258
Robinson, John P., Carol A. Keegan, Marcia Karth and Timothy A. Triplett, 1987. Survey of public participationin the arts: 1985. Volume I, ProjectReport. College Park, MD, and Washington, DC: Survey Research Center, University of Maryland, and The National Endowment for the Arts. Schmidt, Helga, 1993. Kulturangebot in Leipzig - Annahmen, Wermngen, Erwartungen. Verband deutscher St~idtestatistiker. Schuster, J. Mark Davidson, 1991. The audience for American art museums. Washington, DC: NEA, Research Division Report 23. Statistisches Bundesamt, 1994. Statistisches Jahrbuch der Bundesrepublik Deutschland. Statistisches Bundesamt. Treinen, Heiner, 1991. Motivationen zum Museumsbesuch. Museumstypen und Besucherprofile. In: B. Fanlenbach and F.-J. Jelich, 1991, 37-45. Verband deutscher St~dtestatistiker (ed.), 1993. Niederschrift der Sitzung des Ausschusses flit Kultur und Bildung vom 18. und 19. Okt. 1993 in Koblenz. Zentrum flit Kulturforschung, 1992. 2. Kulturbarometer (Winter 1991/1992). Bonn: Zentmm fiir Kulturforschung.