comparative value priorities of chinese and new zealand

There are questions concerning the invariance of values between cultures.
� Are the rankings of means of measures of value dimensions consistent between
cultures for groups with varying demographics? Hypothesis: Ranking of value
dimension means not be different between different demographic groups within
cultures. Value dimension means are not invariant in terms of relative rankings
within the two countries investigated.
� Are preferred leader behaviour dimension structures constant across national
cultures? Hypothesis: Ranking of value dimension means not be different
between cultures. Value dimension means are not invariant in terms of relative
rankings between the two countries.
We should not be surprised to find differences amongst demographic samples and
across cultures, as these kinds of findings are nearly universally reported in the literature
in the area, discussed below in the section concerning countries as cultural units.
EMPIRICAL EVALUATION OF THE THEORY OF CULTURAL VALUE ORIENTATIONS
Growing from 1988-2000, Schwartz’ SVS study participants included 80 samples of
schoolteachers (k-12) from 58 national groups and 115 samples of college students from
64 national groups, together constituting 67 nations and 70 different cultural groups.
Samples from ethnically heterogeneous nations came from the dominant, majority
group. Most samples included between 180 and 280 respondents.
The score for each cultural value orientation in a country is the mean importance rating
of the value items that represent it. Prior to computing these scores, Schwartz centres
each individual respondent’s ratings of the value items on his/her mean rating of all of
the items. He believes this transformation controls for individual as well as group biases
in use of the response scales. In Schwartz (1992) and (2006), he further explains how to
perform the scale use correction and why it is necessary. In order to increase the
reliability of country scores based on the SVS data, Schwartz combined the means of
the teacher and student samples in the 52 countries in which both types of samples were
available. In 21 countries, only either teacher or student data were available. For these
countries, Schwartz estimated the missing sample means based on regression
coefficients generated by regressing student and teacher means from the 52 countries
where both were available on one another.
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