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Partial Least Squares Modeling Green HRM, Mindfulness, Employee Innovation Behavior |
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PP: 1161-1176 |
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doi:10.18576/jsap/150413
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Author(s) |
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Osama Mohammad Marashdah,
Abu Bakar Abdul Hamid,
Abbod Naseb Al-Tamimi,
Kamaljeet Kaur,
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Abstract |
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| This study examines associations among green human resource management (GHRM), green mindfulness, and employees’ green innovation behavior (EGIB) in Jordanian manufacturing. Drawing on the Ability–Motivation–Opportunity (AMO) framework and the Attention-Based View, GHRM was modeled as a reflective–reflective higher-order construct and estimated using a two-stage partial least squares structural equation modeling (PLS-SEM) procedure. Cross-sectional survey data from 384 employees in medium- sized and large manufacturing firms were analyzed with 5,000-resample bootstrapping. GHRM was positively associated with EGIB (β = .448) and green mindfulness (β = .613), while green mindfulness was positively associated with EGIB (β = .174). The specific indirect association through green mindfulness was positive and statistically significant (β = .107, p = .002, bias-corrected 95% CI [.040, .176]), while the direct GHRM–EGIB association remained significant. All three AMO components were positively associated with both outcomes. The results are consistent with a complementary partial indirect-association pattern, but the cross-sectional, single- source design does not establish temporal or causal mediation. The study demonstrates how higher-order PLS-SEM and bootstrapped indirect-effect assessment can be used to examine integrated green HR systems and employee green innovation in an emerging-economy manufacturing context. |
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