11.5.1 Factorial structure of the OJ
An EFA with maximum likelihood as an extraction method was run and an oblique rotation (PROMAX) to allow for correlations among factors was conducted (χ2(df)=249.42(87)). A total of 9 cells were missing on 6 subjects which were dropped from analysis by the software (listwise method, N=295). Different criteria to define the number of factors where checked as recommended by Fabrigar et al. (1999). All the criteria suggested a four factor solution as theoretically expected and as found by Nasr in his sample : a) the Kaiser-Guttman eigenvalue criterion of the unreduced correlation matrix : eigenvalues greater than 1 : 7.00, 2.75, 2.34 and 1.67 (the fifth eigenvalue = 0.55) ; b) the “scree test”
(the plot of eigenvalues) from the reduced correlation matrix1; c) the parallel analysis (comparison of eigenvalues obtained from our sample to the eigenvalues produced by 1’000 sets of random data2 containing the same number of variables and subjects and with the same items’ mean and SD) ; d) the four first factors explained over 75% of the variance of the data and the fifth factor only 3%.
The four-factor solution explained 76.43% of the variance and the maximum loading of each item was found on the factor (loadings greater than .75, except for two items greater than .64) and the loadings in the others factors were very small (lower than 0.15) (see Table 11.3). The four factors were positively correlated (correlation between .21 (distributive-horizontal justice) and .55 (procedural and vertical justice)).
The 18 items of the OJ were submitted to five CFAs which we hoped would lead to an OJ in four dimensions with the horizontal justice as a separate dimension. The 6 subjects with 9 cells missing were included since the FIML (full information maximum likelihood) available in Mplus could process it (N=301). In each of the four first CFAs, horizontal justice factor was defined separately by the horizontal items (denoted by “_h” in the model’s names) in order not to interfere with the dimensions studied in the literature. In the first CFA (dpv_h model), in addition to horizontal justice factor, distributive, procedural and vertical interactional items were defined on the same second latent factor, expressing one large OJ factor. The second CFA (d_pv_h model) was a three-factor model with, in addition to the horizontal justice factor, the distributive justice and the procedural justice encompassing the procedural and the vertical interactional items (corresponding to the two factor justice conceptualization most commonly used (Colquitt, 2001)). The third CFA (d_p_v_h model) is a four-factor model, with distributive, procedural, vertical interactional and horizontal interpersonal justices. Separating distributive, procedural and interactional justice is currently the second-most commonly used conceptualization (Colquitt, 2001). In the three above models, the latent variables were allowed to correlate. In the fourth CFA (hierar model), each justice was defined by the respective items as the model d_p_v_h, but a second-order factor was added. We tested a fifth CFA (d_p_vh model), a three-factor model (distributive, procedural and interactional justice (encompassing vertical
1. Obtained with Statistica 8 2. Simulated in R 2.8.0
Table11.3 – Loadings of the explanatory factor analysis
Scale Question Factor 1 Factor 2 Factor 3 Factor 4
Me donne des explications qui ont un sens pour moi
0.90 0.01 0.02 -0.04
Me donne des justifications appropriées 0.89 0.01 -0.05 0.02 Est sensible à mes besoins personnels 0.85 -0.03 0.04 -0.02 Montre de l'intérêt pour mes droits en tant
qu'employé
0.82 0.00 0.01 0.02
Me traite avec respect et dignité 0.81 -0.01 -0.03 0.02 Discute avec moi des conséquences de ces
décisions
0.76 0.01 0.01 0.06
Pour le travail que j'ai bien fait 0.00 0.92 0.01 0.00
Pour les efforts que je fournis 0.02 0.87 0.06 -0.02
Au vu de l'expérience que j'ai 0.04 0.79 -0.03 0.01
Compte tenu de mon niveau d'éducation et de formation
-0.06 0.76 -0.05 0.01 Ses explications au sujet de ses actions sont
sensées
0.00 -0.02 0.86 0.00
M'explique les raisons et les pourquoi de ses actions d'une manière détaillée
-0.01 -0.01 0.84 0.00 Me communique les détails aux moments
opportuns
0.11 -0.01 0.80 -0.05
Est franc et sincère avec moi -0.09 0.03 0.79 0.05
De donner des clarifications ou des informations additionnelles à propos des décisions prises
-0.07 -0.03 0.02 0.92
D'assurer des feedback utiles concernant les décisions
-0.01 0.01 0.00 0.90
De prendre en compte les intérêts de toutes les parties concernées par la décision
0.08 0.03 0.00 0.72
De prendre les décisions d'une manière cohérente 0.14 -0.01 -0.01 0.64
Explained variance 38.88% 15.27% 13.01% 9.26%
L'entreprise dans je travaille le plus (interagis et dont je dépends le plus) :
and horizontal items)) in order to test if the two interactional justices (vertical and horizontal) could be distinguished or not. Finally the null model was also shown.
The null, dpv_h, d_pv_h and d_p_vh models provided poor fits with all goodness of fit indices failing to reach acceptable values (Table 11.4). The RMSEA and the SRMR of d_p_v_h and hierar models suggested that the measurement and the latent models lead to acceptable fits, although the CFI failed just under the acceptable cut-off of 0.95. The models that separated the four justices thus had acceptable fits. For the d_p_v_h model, the correlations between the latent factors of justice were all significant (p< .001) ranging from .22 (distributive-horizontal interactional justice) to .59 (procedural-vertical interactional justice).
Table11.4 – Fit indices of the CFAs tested
Model khi2 df RMSEA SRMR CFI
Null 3319.49 153 - -
-dpv_h model 1163.78 134 0.160 0.127 0.675 d_pv_h model 651.90 132 0.114 0.086 0.836 d_p_v_h model 328.56 129 0.072 0.061 0.937 hierar model 330.07 131 0.071 0.063 0.937 d_p_vh model 670.83 132 0.116 0.092 0.830
11.5.2 Relationship between OJ and other concepts of the field
Pearson’s correlations between the factorial scores3 of the OJ sub-scales and the composite scores of negative affectivity, internal locus of control, powerful others locus of control, self-efficacy and job satisfaction were calculated (11.5).
Table11.5 – Pearson’s correlations between OJ and other concepts of the field
Distri-butive
Proce-dural
Vertical
interac-tional
Horizontal
interac-tional
Negative affectivity
Self efficacy
Job
satisfa-ction Distributive .230*** .242*** .207*** -.025 -.030 .018 .207***
Procedural .517*** .276*** -.116* -.135* .154** .448***
Vertical
interactional .333*** -.208*** -.114 .166** .456***
Horizontal
interactional -.167** -.184** .102 .235***
Note: * p<.05, ** p<.01, ** p<.001 Organizational Justice
Organizational Justice Locus of control:
Powerful others
11.6 Discussion
The first aim of the present study was to present a comprehensive validation of the unpublished OJ scale of Nasr (2004). An EFA found four dimensions and the items of each sub-scale loaded on the expected factors as was the case in Nasr’s dissertation. Then a CFA indicated that the models that separated the four justices had acceptable fits (d_p_v_h and hierar models) and were clearly better than the other proposed models. Combining the distributive, procedural and vertical interaction items, as if the dimensions of the OJ could not be distinguished, is the worst model. As mentioned before, one central debate in the literature is how many dimensions define the OJ. Thus, the inadequacy of the first model seems to bring some evidence against a one dimensional factor of OJ (e.g., Welbourne et al., 1995), even though some studies show a very high correlation between distributive and procedural dimension. Separating the distributive justice items (d_pv_h and d_p_vh models) from the other dimensions leads to better (but still not acceptable) models. In our second model (d_pv_h), we tested the idea that procedural and vertical interaction items could be a unique dimension (Niehoff &
Moorman, 1993), our sample refuted this idea. We also tested if horizontal and vertical interactional items were measuring the same dimension, or if we could separate them into two dimensions (d_p_vh model). Again, separating the dimensions was clearly better. In summary, considering our findings, and positioning ourselves in the debate concerning the independence of the dimensions of OJ (Colquitt, 2001), distinguishing the distributive from procedural and from interactional justice seems to be the best model. Note that the d_p_v_h and the hierar models have such a close fit that it is difficult to call which is the best.
Moreover, in our definition of OJ with the horizontal interactional justice as an additional source of injustice, the OJ seems to be best conceptualized with four distinct dimensions (being correlated or forming a supra factor) : distributive justice, procedural justice, vertical interactional justice and horizontal interactional justice as found in a Tunisian sample by Nasr (2004).
The second aim of this study was to replicate the OJ structure in a more varied sample of worker (level of education and profession) and from another French speaking country. Our sample was formed with postmen, secretaries, research and teaching assistants and prison guards from the French speaking
3. The factorial scores were calculated through the four dimensions correlated model (d_v_p_h_model and using Bartlett’s factor score
part of Switzerland and Nasr’s sample was formed with middle management and senior executive from Tunisia. The OJ structure found in our sample is exactly the same as in Nasr’s work. Thus, whatever differences in culture or socio-economic status existing between Nasr’s sample and ours, it did not alter the structure of the OJ. This shows the robustness of the French OJ scale.
The third aim was to investigate the links between the sub-scales of OJ and some variables of the field. As expected, job satisfaction was positively correlated to distributive, procedural and vertical interactional justices. Job satisfaction was highly correlated to procedural and vertical interactional justices (respectively r=.45 and r=.46 ) and less correlated to distributive justice (r=.21) which is not really surprising. The first reaction to unfairness is expected to be emotional and attitudinal as already mentioned in Adam’s inequity theory (1965). And Locke (1976) defined job satisfaction as an attitude.
The relation between OJ and the variables of personality evaluation have been less studied in the literature than with job satisfaction, but our findings were consistent with other studies of the field : the NA was positively correlated to procedural and vertical interactional justices. This could be related to the fact that NA is a personality trait which negatively biases the perception of a work environment (Watson & Tellegen, 1988) and therefore the perception of justice.
The external (i.e., powerful others) locus of control was negatively correlated with procedural justice. Defining procedural justice by process control (Thibaut & Walker, 1975) is consistent with the idea that people will try to control the procedures in decision making to make sure of favorable outcomes. Thus, a person with an external locus of control believes he/she had no control over what happens, and therefore they do not care much about procedural justice.
Self-efficacy was positively correlated to procedural justice (as expected) and to vertical interactio-nal justice (not expected). The former can be explained by the fact that a person that is self confident in his/her capacity to contribute significantly to organizational decisions, and thus will pay more at-tention to procedural justice (El Akremi & Camerman, 2006). The latter can perhaps be explained by the fact that a person with a high self-efficacy, in other words a person who believes in his/her capacity to accomplish what is expected from him/her, will be more sensitive to injustice from his/her supervisor.
A specificity of the OJ scale proposed by Nasr, is to take into account an additional source of justice : the colleagues. Despite the fact that the relation between colleagues can be an important source of justice, the justice was mainly studied through two sources ; the organization and the superior ; and the interactional justice through the relation between the employee and the supervisor or the employees immediate superior. The last years an increasing number of studies focus on the relation of co-worker interactional justice with organizational variables as job satisfaction (Ladebo et al., 2008) or commitment (Stinglhamber & Cremer, 2008), but no research studied the relation between co-workers interactional justice and dispositional variables. Despite, we expect to have a similar pattern to what was found on the vertical interactional justice literature in view of the fact that it is an interactional justice (i.e., negatively correlated to NA), which was partially the case. We found another negative correlation with the external locus of control. In future research, it would be interesting to examine more deeply this source of justice to explore and find its determinants and define what it can explain in the organization. Furthermore, it would be interesting to explore the interactional justice, first not only focusing on the relationship between employees and superiors, but taking into account the relationship between colleagues, and secondly by ripening the analysis of interactional justice by taking into account the two forms of interactional justice (the interpersonal and the informational justice) found by (Colquitt, 2001) and this for different sources of justice.
Satisfaction au travail : conséquences du choix des outils statistiques et des instruments de mesure en GRH
Ce chapitre constitue un article publié : Iglesias, K., Renaud, O. & Tschan, F. (2010). Satisfaction au travail : conséquences du choix des outils statistiques et des instruments de mesure en GRH. Revue Internationale de Psychosociologie, vol XVI, no 40, pp. 245-270.
12.1 Résumé
La satisfaction au travail est un concept central en gestion des ressources humaines. Malgré cela les relations trouvées entre ce concept et d’autres variables du champ restent encore parfois incertaines voire même contradictoires dans certains cas. Cet article relève trois problèmes : le premier, pouvant affecter directement les liens entre la satisfaction au travail et d’autres variables du champ, concerne les outils statistiques utilisés pour analyser la satisfaction au travail. Pour discuter de ce point, nous évaluons les besoins des chercheurs pour répondre à leurs questionnements, ainsi que les apports et limitations des différents outils statistiques utilisés. Les deuxième et troisième problèmes touchent la satisfaction au travail elle-même et concernent la définition ainsi que les instruments de mesure de la satisfaction au travail. Une fois ces problèmes énoncés, sur la base d’un jeu de données empiriques et en utilisant les outils statistiques adaptés pour répondre aux questions des chercheurs, nous avons analysé quatre mesures de satisfaction au travail avec des modèles à effets mixtes. Pour analyser ces dernières, deux groupes de déterminants ont été utilisés : des facteurs liés au travail et des facteurs liés à la personne. Il ressort que pour les déterminants fortement liés à la satisfaction au travail, les résultats sont proches pour les quatre échelles de satisfaction au travail. Par contre, pour les variables explicatives dont le lien avec la satisfaction au travail est plus faible, la significativité va dépendre du choix de l’instrument de mesure de la satisfaction au travail. Par conséquent, les différentes échelles de satisfaction au travail analysées n’opérationnalisent pas la même définition de la satisfaction au travail.