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Articles (2020), International Journal of Cross Cultural Management, 2020, pp. 89-111

Measurement invariance and nomological validity of the Attributional Complexity Scale: Evidence from Estonia, France, India, United States, and Vietnam

LAKSHMAN C., CHI VO L., RAMASWAMI Aarti

International Business researchers have recently become interested in attributional complexity (AC) in the context of cross-cultural leadership effectiveness. Despite this recent surge in interest in this construct, we know very little about its measurement properties in cross-cultural situations. Given that attributions vary across cultures, verifying the validity (measurement invariance and nomological validity) of the Attributional Complexity Scale (ACS) is a research imperative. In study I, we examine the measurement invariance of ACS using a reduced version of the original scale (ACS-18) in five countries. The results suggest that the ACS shows metric invariance in that it has a similar factor structure across the five societies examined and in two other independent samples. In study II (France), we provide evidence of AC’s predictive validity based on its relationship to a key construct in its nomological network, namely, isomorphic attribution. In study III (United States), we provide additional evidence of nomological validity by showing the relationship between AC and biculturalism. Our results demonstrate the importance of AC and imply that researchers in cross-cultural contexts can safely use the ACS-18 without risking substantive misinterpretation. We discuss results, future research directions, implications, and limitations of the study. Lien vers l'article

LAKSHMAN, C., CHI, V.L. and RAMASWAMI, A. (2020). Measurement invariance and nomological validity of the Attributional Complexity Scale: Evidence from Estonia, France, India, United States, and Vietnam. International Journal of Cross Cultural Management, 2020, pp. 89-111.

Mots clés : #Attributional-Complexity-Scale-(ACS), #cognitive-complexity, #cross, #cultural-leadership-effectiveness, #isomorphic-attributions, #measurement-issues