| Literature DB >> 36248460 |
R Bala Subramanian1, P B Srikanth2, Munish Thakur2.
Abstract
Distributive justice is known to have important emotional and affective outcomes. The present study explores the role of distributive justice as an antecedent to feelings of gratitude toward the organization. Borrowing from social exchange theory, we investigate the mediating role of gratitude in the relationship between "perceived fairness in distributive justice" and "employees' organization citizenship behaviors (OCB)." Time-lagged, multi-source data was collected from 185 employees and their supervisors employed in a large manufacturing organization based in East India. Two significant findings emerge. First, the results indicate that feelings of gratitude signal fair distribution of benefits such that the employees go beyond the call of the duty to invest in OCB. Second, engagement in such acts seems to nullify their social debts highlighted in the social exchange perspective. Thus, a strong moral emotion, gratitude is a powerful vehicle that drives employees to act in the organization's interests because doing is desirable and rightful. Implications for theory and practice are discussed.Entities:
Keywords: distributive justice; gratitude; organizational citizenship behavior (OCB); positive emotion; social exchange theory
Year: 2022 PMID: 36248460 PMCID: PMC9561891 DOI: 10.3389/fpsyg.2022.974405
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Estimated sample statistics for the latent variables.
| Variable | Mean |
| 1 | 2 | 3 | 4 | 5 | 6 |
| 1. Gender | 1.33 | 0.47 | ||||||
| 2. Age | 32.00 | 4.50 | ||||||
| 3. Tenure+ | 2.43 | 1.20 | ||||||
| 4. DJ (T1) | 3.43 | 0.72 | – | – | – | 1.000 | ||
| 5. OCB-O (T2) | 3.85 | 0.59 | – | – | – | 0.32 | 1.000 | |
| 6. OG (T1) | 3.78 | 0.71 | – | – | – | 0.55 | 0.38 | 1.000 |
N, 185. T1, Time 1; T2, Time 2; **p < 0.01; +Tenure was an ordinal variable.
FIGURE 1Proposed model.
Factor solution.
| Model | N of parameters | Chi square | DoF | |
| One factor | 54 | 554 | 135 | 0 |
| Two factors | 71 | 330 | 118 | 0 |
| Proposed three factors | 87 | 218 | 102 | 0 |
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| One factor vs. two factors | – | 221 | 17 | 0 |
| Two factors vs. three factors | – | 114 | 16 | 0 |
Reliability and validity.
| Indicator | DJ | OCB | OG |
| Cronbach’s alpha | 0.77 | 0.80 | 0.94 |
| Composite reliability | 0.77 | 0.80 | 0.94 |
| Average variance extracted | 0.46 | 0.51 | 0.61 |
Regression analysis.
| Dependent variable: OCB | Dependent variable: OG | ||||||||||||||
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| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |||||||||||
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| Independent variables | Unstd B | S.E. | 95.0% CI [B] | Unstd B | S.E. | 95.0% CI [B] | Unstd B | S.E. | 95.0% CI [B] | Unstd B | S.E. | 95.0% CI [B] | Unstd B | S.E. | 95.0% CI [B] |
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| 3.91 | 0.05 | [38.0–4.0] | 2.57 | 0.24 | [2.09–3.0] | 3.03 | 0.21 | [2.6–3.4] | 3.82 | 0.07 | [3.6–3.9] | 1.98 | 0.22 | [1.5–2.4] |
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| 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] |
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| 0.01 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0.01 | 0 | [0.00–0.00] |
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| 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.001] | -0.001 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] | 0 | 0 | [0.00–0.00] |
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| 0.26 | 0.05 | [0.14–0.37] | 0.1 | 0.058 | [-0.00–0.22] | 0.53 | 0.062 | [0.41–0.65] | ||||||
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| 0.23 | 0.069 | [0.094–0.36] | ||||||||||||
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| 0.07 | 0.1 | 0.15 | 0.001 | 0.29 | ||||||||||
***p < 0.001.
Indirect effects analysis.
| Dependent variable: OCB | |||||
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| Direct, indirect and total effects | |||||
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| Independent variable: DJ | Mediator: Gratitude | ||||
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| Coefficient | S.E. | [CI-95%] | |||
| Indirect effects (H2) |
| 0.12 | 0.044 | 0.012 | [0.012–0.21] |
| Indirect effects (H2) |
| 0.16 | 0.058 | 0.012 | [0.054–0.28] |
| Total effects |
| 0.22 | 0.054 | 0.001 | [0.11–0.32] |
| Direct effects (H1) |
| 0.092 | 0.063 | 0.14 | [-0.03–0.21] |