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Leveraging environmental management accounting and green ambidexterity for competitive advantage: a natural resource orchestration view

Kaveh Asiaei et al.

Accounting Forum2026https://doi.org/10.1080/01559982.2025.2604169article
AJG 3ABDC A
Weight
0.50

Abstract

This study explores how organisations leverage environmental management accounting (EMA) and green ambidexterity to translate green knowledge assets into competitive advantage. Drawing on survey data from chief financial officers and analyzing the results using partial least squares structural equation modelling (PLS-SEM), we find that green human assets drive competitive advantage only through EMA, while green structural assets show no significant association with EMA. Green relational assets, however, positively influence both EMA and competitive advantage. We further demonstrate that green ambidexterity, where firms’ simultaneous pursuit of exploitative and exploratory green innovation initiatives, strengthens the effect of EMA on competitive advantage. Drawing on the natural resource orchestration perspective, this study offers a novel perspective to EMA research by documenting how organisations can effectively synchronise, bundle, and structure (i.e. orchestrate) various green resources to achieve superior strategic outcomes. It offers important practical insights into how sustainability-oriented initiatives can be harnessed to build and sustain competitive advantage.

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https://doi.org/https://doi.org/10.1080/01559982.2025.2604169

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@article{kaveh2026,
  title        = {{Leveraging environmental management accounting and green ambidexterity for competitive advantage: a natural resource orchestration view}},
  author       = {Kaveh Asiaei et al.},
  journal      = {Accounting Forum},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/01559982.2025.2604169},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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