Organizational Justice has Four Dimensions

What is it about?

There is a continued debate regarding the dimensions of organizational justice. The present project investigated the dimensionality of organizational justice and the validity of an Arabic measure of organizational justice for a Kuwaiti samples. The first study sample consisted of 1,184 Kuwaitis (619 males and 565 females) from two groups: 728 employees and 456 teachers working in the public sector. The second study sample consisted of 373 participants (190 employees and 183 teachers). The instrument items were based on a careful review of the organizational justice literature to ensure relevance to the sample culture. Confirmatory factor analyses (CFA) using WLSMV estimator is used. CFA analyses identified the four distinctive factors of distributive, procedural, interpersonal, and informational organizational justice. The four-factor model fit the data significantly better than one-, two- or three-factor models. Moreover, the study revealed that these four dimensions of organizational justice were significantly correlated with the four relevant outcomes of instrumentality, organizational commitment, organizational citizenship behavior, and collective esteem. Using the Arabic version of Colquitt’s (2001) instrument (Fischer et al., 2011), the second study presented an evidence of concurrent validity of the new Arabic scale. The present study confirmed the four-factor dimensionality of organizational justice. Results of the current study may raise the issue of development of scales versus translation of well- developed ones. Theoretical and practical implications of the results are discussed.

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Why is it important?

This Article introduces a new Arabic measure of organizational justice and investigate the construct validity of it using CFA and SEM. The analysis done using WLSMV estimator. WLSMV method is more appropriate for our data because variables are measured on an ordinal scale. WLSMV is considered a less bias estimator compared with the standard maximum likelihood in case of ordinal data.