Why AI Adoption Fails to Create Digital Green Innovation: The Transformative Role of Knowledge-Based Dynamic Capabilities

Environmental challenges, such as climate change, resource scarcity, and pollution, increasingly demand organizational strategies that integrate artificial intelligence (AI) into sustainable innovation. This study examines how employee-level artificial intelligence capabilities (AIC) enable digital green innovation, a strategic approach that leverages AI-powered digital technologies to enhance green product development, green processes, and sustainable supply chains. Drawing on knowledge-based view (KBV) and the dynamic capability view (DCV), this study develops a theoretical framework linking AIC, knowledge-based dynamic capabilities (KBDC), and digital green innovation. Using survey data from 299 employees in Chinese High-Tech firms, results show that higher employee AIC strengthens KBDC, which in turn facilitates effective digital green innovation. The findings contribute theoretically by extending the antecedents of digital green innovation to the individual level and clarifying the multilevel mechanism through which AIC translates into organizational environmental performance, thereby enhancing both theories’ explanatory power in digital environments. Practically, the study highlights the importance for environmental managers of strengthening employee AIC and organizational KBDC to implement AI-driven sustainability strategies more effectively.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-03-05
DOI
https://doi.org/10.3390/su18052560
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Why AI Adoption Fails to Create Digital Green Innovation: The Transformative Role of Knowledge-Based Dynamic Capabilities

Feng Tian, Zhe Ji
Sustainability
AI in Service Interactions
article

Why AI Adoption Fails to Create Digital Green Innovation: The Transformative Role of Knowledge-Based Dynamic Capabilities

Feng Tian, Zhe Ji
article en

Abstract

Environmental challenges, such as climate change, resource scarcity, and pollution, increasingly demand organizational strategies that integrate artificial intelligence (AI) into sustainable innovation. This study examines how employee-level artificial intelligence capabilities (AIC) enable digital green innovation, a strategic approach that leverages AI-powered digital technologies to enhance green product development, green processes, and sustainable supply chains. Drawing on knowledge-based view (KBV) and the dynamic capability view (DCV), this study develops a theoretical framework linking AIC, knowledge-based dynamic capabilities (KBDC), and digital green innovation. Using survey data from 299 employees in Chinese High-Tech firms, results show that higher employee AIC strengthens KBDC, which in turn facilitates effective digital green innovation. The findings contribute theoretically by extending the antecedents of digital green innovation to the individual level and clarifying the multilevel mechanism through which AIC translates into organizational environmental performance, thereby enhancing both theories’ explanatory power in digital environments. Practically, the study highlights the importance for environmental managers of strengthening employee AIC and organizational KBDC to implement AI-driven sustainability strategies more effectively.

SustainabilityVol. 18(5)
University of Newcastle Australia (AU)
Openalex Percentile: Top 37%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.