How Environmental Leadership Influences Performance Outcomes: A Study of the Manufacturing Sector

Junaid Aftab, Feng Wei, Muhammad Ishtiaq Ishaq and Nabila Abid ()
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Junaid Aftab: Tongji University
Feng Wei: Chinese Academy of Sciences [Wuhan Branch]
Muhammad Ishtiaq Ishaq: DVHE - De Vinci Higher Education
Nabila Abid: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School

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Abstract: Drawing on the ability‐motivation‐opportunity (AMO) theory and the resource‐based view (RBV), this study argues that environmental transformational leadership (ETL) enhances both economic and environmental performance through green human resource management (GHRM). It also examines the moderating role of environmental knowledge in the relationship between ETL and GHRM. Furthermore, this study posits that big data analytical capabilities (BDAC) strengthen the impact of GHRM on economic and environmental performance. Using a random sampling approach, we collected multi‐respondent data from 355 manufacturing firms, incorporating insights from first‐level managers and top executives. Structural equation modeling was employed as our analytical technique. The findings confirm that GHRM significantly mediates the effect of ETL on both economic and environmental performance. However, contrary to expectations, environmental knowledge does not moderate the ETL–GHRM relationship. In contrast, BDAC strengthens the influence of GHRM on economic and environmental performance. This study contributes to the leadership literature by identifying the underlying mechanism (how) and boundary conditions (when) through which ETL influences firms' performance outcomes.

Keywords: Big data analytical capabilities; Environmental knowledge; Environmental transformational; Leadership; Green human resource management (search for similar items in EconPapers)
Date: 2025-04-21
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Published in Business ethics, the environment & responsibility, 2025, ⟨10.1111/beer.12817⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05123301

DOI: 10.1111/beer.12817

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