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The impact of culture on National Spatial Data Clearinghouses
Methodology
In order to analyse the impact of culture on clearinghouses, national culture dimensions are used.
Hofstede (1980) has studied a large body of survey data, about the values of similar IBM employees in
50 different countries around the world. A statistical analysis of the answers on questions about the
values of these employees revealed common problems, but with solutions differing from country to
country, in the following areas:
- Social inequality, including the relationship with authority;
- The relationship between the individual and the group;
- Concepts of masculinity and femininity;
- Ways of dealing with uncertainty.
These four problem areas have been defined by the American sociologists Inkeles and Levinson 10
years before this study was done (Inkeles and Levinson, 1969). This prediction provides strong
support for the theoretical importance of the empirical findings of this study. The four problem areas
defined by Inkeles and Levinson and empirically found in the IBM data represent dimensions of
culture. A dimension is an aspect of culture that can be measured relative to other cultures. Hofstede
named those dimensions power distance, collectivism vs. individualism, femininity vs. masculinity and
uncertainty avoidance (Hofstede, 1980). Together they form a four-dimensional model of differences
among cultures. A score on each of the four dimensions characterises each country in this model. A
fifth dimension has also been identified, namely long term orientation vs. short term orientation. This
had not been discovered before because of a “Western” way of thinking by the researchers, but has
been revealed by a following study on the IBM data of people’s values around the world using a
questionnaire composed by “Eastern” minds (Hofstede, 1980).
In order to compare different national clearinghouses and to be able to use them in statistical analyses,
they were evaluated by a set of clearinghouse characteristics: Number of datasets, Number of data
themes, search mechanisms (like the use of Index maps, Keyword search, Spatial search, temporal
search), access results (abstract, metadata, data) and other services like online mapping.
Besides these culture and clearinghouse data, general country data like surface, number of inhabitants,
population density, gross national product per capita, and demographic and human development data
were collected.
After acquiring the needed data about national culture dimensions and clearinghouse characteristics of
50 countries, all the data were imported in SPSS 10.0 for Windows (SPSS Inc, 2000). In SPSS it is
possible to analyse statistically data in all sorts of ways. For this research a factor analysis has been
used in order to test the hypothesis that cultural variables are at the basis of underlying dimensions in
the data matrix. Over these dimensions the dependant variables, with variables related to
clearinghouse in particular, are spread. A factor analysis refers to a variety of statistical techniques that
aim to reduce your dataset to a smaller number of hypothetical variables, or factors (Lewis-Beck,
1994).
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