Capability conversion in green manufacturing

Green HRM, ethical AI, and dual sustainability performance under the NRBV

Bibliographic Data

ID22431544
AuthorsAdi Prasetyo Tedjakusuma (0000-0003-0794-2124, University of Surabaya), Waiphot Kulachai (0000-0002-3476-9462, Suan Sunandha Rajabhat University), Ching-Te Li (0000-0003-2765-2327, Chaoyang University of Technology), Joshi Maharani Wibowo (0000-0002-2070-1950, University of Surabaya)
Year2026
Volume17
Issue2
Pages615-667
Publication date2026-06-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueOeconomia Copernicana (JOURNAL)
Journal identifiersISSN: 2083-1277 • E-ISSN: 2353-1827
PublisherInstytut Badan Gospodarczych / Institute of Economic Research (PUBLISHER)
DOI10.24136/oc.4276
OpenAlexW7168715331
LanguageEN
References cited49

Research background: Manufacturing firms in emerging economies face simultaneous pressures to decarbonise and digitalise, yet how green human resource systems, responsible AI governance, and green innovation jointly translate into sustainability outcomes remains insufficiently understood. Purpose of the article: Grounded in the Natural Resource-Based View, this study tests a capability-conversion model linking green human resource management practices (GHRMPs), ethical AI (EA), green innovation performance (GIP), environmental performance (ENP), and operational economic performance (ECP) in Thai manufacturing. Methods: Cross-sectional online survey data were obtained from 422 key informants, with one supervisory, managerial, or executive respondent representing each medium-sized or large Thai manufacturing firm. The model was analysed using two-stage partial least squares structural equation modelling, a reflective–formative higher-order specification of GHRMPs, and 10,000-subsample bootstrapping. Findings & value added: GHRMPs were positively associated with EA (β = .846), EA with GIP (β = .733), and GIP with ENP (β = .810) and ECP (β = .765), whereas the direct GHRMP–ENP and GHRMP–ECP relationships were nonsignificant. The serial indirect associations through EA and GIP were significant for ENP (β = .502) and ECP (β = .475). These findings support an indirect capability-conversion pattern in which green HR architecture functions as a distal enabling capability, EA as an intermediate governance capability, and GIP as the proximal mechanism associated with environmental improvement and operational resource cost efficiency. The environmental coefficients were descriptively larger than the economic coefficients, but these differences were not formally tested and therefore represent tentative environmental–economic variation rather than confirmed asymmetry. The study contributes by integrating human, AI-governance, and innovation capabilities and by operationalising EA as an organisational governance construct in an emerging-economy manufacturing context.

Corporate governance · Dual (grammatical number) · Natural resource · Ordinary least squares · Resource (disambiguation) · Respondent · Structural equation modeling · Sustainability · Sustainable Design · Environmental Sustainability in Business · Innovation, Sustainability, Human-Machine Systems · Sustainable Supply Chain Management

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