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A revision of Hofstede’s individualism-collectivism dimension

Published on Aug 7, 2017
· DOI :10.1108/CCSM-11-2016-0197
Michael Minkov20
Estimated H-index: 20
,
Pinaki Dutt2
Estimated H-index: 2
+ 5 AuthorsBen Mudd2
Estimated H-index: 2
(University of Nottingham)
Sources
Abstract
Purpose The purpose of this paper is to provide an updated and authoritative measure of individualism vs collectivism (IDV-COLL) as a dimension of national culture. Design/methodology/approach Rather than focus solely on Hofstede’s classic work, the authors review the main nation-level studies of IDV-COLL and related constructs to identify the salient cultural differences between rich societies and developing nations. The authors conceptualize and operationalize IDV-COLL on the basis of those differences and propose a new national IDV-COLL index, using new data from large probabilistic samples: 52,974 respondents from 56 countries, adequately representing the national cultures of all inhabited continents. Findings The proposed index is a new, valid measure of IDV-COLL as it is strongly correlated with previous measures of closely associated constructs. As a predictor of important cultural differences that can be expected to be associated with IDV-COLL, it performs better (yields higher correlations) than any known measure of IDV-COLL or a related construct. Research limitations/implications An important facet of IDV-COLL – in-group favoritism vs out-group neglect or exclusionism – does not transpire convincingly from the authors’ operationalization of IDV-COLL. The study relies on self-construals. Respondents are unlikely to construe their selves in terms of such concepts. Practical implications The new IDV-COLL measure can be used as a reliable, up-to-date national index in studies that compare the cultures of rich and developing nations. The new IDV-COLL scale, consisting of only seven items, can be easily used in future studies. Originality/value This is the first IDV-COLL measure based on the communalities of previous studies in this domain and derived from large probabilistic samples that approach national representativeness. The superior predictive properties of the authors’ new measure with respect to extraneous variables are another important strength and contribution.
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