Authors:
M. N. Aishwarya Anandavalli, S. Antony Raj
Addresses:
Department of Commerce, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India.
Abstract:
This article compares Organisational Green Compensation (OGC) and Employee Green Conscientiousness (EGC) to see if organisational sustainability practices match employees' eco-conscious conduct. Based on Person–Organisation Fit Theory and Social Exchange Theory, the study examines how HR systems with environmental incentives affect employees' voluntary pro-environmental conduct. Data from 200 private and semi-public employees were used in a quantitative, cross-sectional study. OGC and EGC were measured using methods from previously validated studies. Descriptive statistics, reliability testing, Pearson's correlation, and the Intraclass Correlation Coefficient (ICC) were used in IBM SPSS (Version 28) to assess organisational procedures and the congruence between organisational procedures and employee behaviour. Green HR practices were perceived as moderately to highly (M = 3.44, SD = 0.57), with good internal consistency (α = .861), a substantial positive correlation (r = .388, p < .001), and strong congruence (ICC = .861) between OGC and EGC. These studies show that rewarding environmental achievement increases employee sustainability commitment. Cross-sectional studies limit causal inference, and self-reported data may be biased by social desirability. Future research should use longitudinal designs and include mediators such as green identity and emotional intelligence to understand the OGC–EGC link. This study introduces organisational–employee green congruence as a sustainability alignment diagnostic construct in Green Human Resource Management (GHRM). The study introduces statistical agreement (ICC) to operationalise congruence and assess organisational policy-employee consistency.
Keywords: Organizational Green Compensation; Employee Green Conscientiousness; Person–Organization Fit; Social Exchange Theory; Green HRM; Social Desirability.
Received: 22/11/2024, Revised: 25/01/2025, Accepted: 01/03/2025, Published: 09/09/2025
DOI: 10.64091/ATITP.2025.000159
AVE Trends in Intelligent Technoprise Letters, 2025 Vol. 2 No. 3 , Pages: 157-169