TRV-2026-1037Version 1 · Certified
Reason for this version
Certified into the record
Canonical text (the exact bytes fingerprinted)
TRUVACE RECORD VERSION record: TRV-2026-1037 version: 1 kind: certified reason: Certified into the record timestamp: 2026-09-09T14:14:51.341202Z status: published lens: g_space sector: lifestyle headline: Power of Green Capabilities and Artificial Intelligence (AI): Understanding How and When Green Innovation Promotes Sustainability dek: ABSTRACT Green innovation is increasingly recognized as a critical strategy for small‐ and medium‐sized enterprises (SMEs) to enhance sustainable performance. Drawing on the natural resource‐based view (NRBV), this study examines the impact of green innovation on sustainable performance and the mediating roles of green knowledge sharing and green dynamic capabilities. In addition, the moderating effect of artificial intelligence (AI) on these relationships was investigated. Data were collected from 230 SMEs in t… gain_title: In 230 SMEs, green innovation was positively related to sustainable performance, mediated by green knowledge sharing and green dynamic capabilities, with AI significantly moderating those links. problem_title: (none) trace_subject: (none) gain_reading: In 230 SMEs, green innovation was positively related to sustainable performance, mediated by green knowledge sharing and green dynamic capabilities, with AI significantly moderating those links. gain_evidence: green innovation is positively related to sustainable performance | AI significantly moderates the relationship between green knowledge sharing, green dynamic capabilities, and sustainable performance | integrating AI into SMEs can enhance the promotion and effectiveness of green innovation strategies problem_reading: (none) problem_evidence: (none) quick_read: Researchers examined how green innovation relates to sustainable performance in small- and medium-sized enterprises, testing green knowledge sharing and green dynamic capabilities as mediators and artificial intelligence as a moderator using two-phase data from 230 SMEs. The findings matter because they suggest SME managers and policymakers can pair green innovation practices with knowledge-sharing routines, dynamic capabilities, and AI adoption to improve sustainability outcomes, though the evidence is confined to the studied SME sample and the specific mediated-moderated model tested. limitation: Findings are based on a sample of 230 SMEs collected in two phases, limiting generalizability beyond that population and design. tag: Evidence-backed gain key_points: Study draws on the natural resource-based view (NRBV) to test green innovation effects. | Data were collected from 230 SMEs in two phases. | Green knowledge sharing and green dynamic capabilities were tested as mediators. | AI was tested as a moderator of the sharing and capabilities to performance relationships. rundown: The authors collected data from 230 SMEs across two phases to test hypotheses derived from the natural resource-based view. Results indicate mediation by green knowledge sharing and green dynamic capabilities, and that AI significantly moderates the relationship between those mediators and sustainable performance. sources: - peer_reviewed | Business Strategy and the Environment | https://doi.org/10.1002/bse.70252 | 2025-10-29 prev: 0000000000000000000000000000000000000000000000000000000000000000
- sha256
- 7219405f3962a26a18cc3d0f2505f107f5feae92b241483e828286f3e8c94532
- previous
- 0000000000000000000000000000000000000000000000000000000000000000
Verify this record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1037 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.
ace