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A revision of Hofstede’s individualism-collectivism dimension: A new national index from a 56-country study

Published on Aug 7, 2017
· DOI :10.1108/CCSM-11-2016-0197
Michael Minkov19
Estimated H-index: 19
,
Pinaki Dutt2
Estimated H-index: 2
+ 5 AuthorsBen Mudd2
Estimated H-index: 2
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.
  • References (33)
  • Citations (13)
References33
Newest
#1Vivian L. Vignoles (University of Sussex)H-Index: 23
#2Ellinor Owe (University of Sussex)H-Index: 6
Last.Maria Paz Cadena (UC: Pontifical Catholic University of Chile)H-Index: 4
view all 72 authors...
#1Michael Minkov (International University, Cambodia)H-Index: 19
#2Vesselin Ivanov Blagoev (International University, Cambodia)H-Index: 5
Last.Geert Hofstede (UM: Maastricht University)H-Index: 62
view all 3 authors...
#1Vas Taras (UNCG: University of North Carolina at Greensboro)H-Index: 15
#2Piers Steel (U of C: University of Calgary)H-Index: 26
Last.Bradley L. Kirkman (A&M: Texas A&M University)H-Index: 37
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Cited By13
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#1Ananya Rajagopal (Tec: Monterrey Institute of Technology and Higher Education)H-Index: 3
#1Jadranka ŠvarcH-Index: 3
#2Jasminka Lažnjak (University of Zagreb)H-Index: 3
Last.Marina Dabić (NTU: Nottingham Trent University)H-Index: 15
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#1M.P. Ganesh (IITH: Indian Institute of Technology, Hyderabad)
#2M. Ángeles López-Cabarcos (University of Santiago de Compostela)H-Index: 5
Last.Paula Vázquez-Rodríguez (University of Santiago de Compostela)H-Index: 4
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#1Bernhard Swoboda (University of Trier)H-Index: 23
#2Nadine Batton (University of Trier)
#1Kirby Deater-Deckard (UMass: University of Massachusetts Amherst)H-Index: 48
#2Jennifer Godwin (Duke University)H-Index: 8
Last.Lei Chang (UM: University of Macau)H-Index: 34
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