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From AI-enabled materials informatics to sustainable innovation in Asian global value chains: the bridging role of inter-organisational collaboration

The twin transition of digitalisation and sustainability requires manufacturers in Asian global value chains (GVCs) to convert internal artificial intelligence (AI) capability into outcomes that depend on cross-boundary coordination. Drawing on the Dynamic Capabilities View and GVC governance research, this study examines how AI-enabled materials informatics (MI) capability relates to sustainable innovation performance (SIP) through inter-organisational collaboration. Survey data from 205 senior technology execu…

By the Truvace desk2 min read1 sourcePeer-reviewedTRV-2026-1737· cite & verify
From AI-enabled materials informatics to sustainable innovation in Asian global value chains: the bridging role of inter-organisational collaboration
An analysis of China's information technology strategies and their implications for US national security by Tsai, Wen-Hsiang.. Public domain

In brief

A survey of 205 senior technology executives in Taiwan's high-technology manufacturing sector tested how AI-enabled materials informatics capability relates to sustainable innovation performance. Analysis combined PLS-SEM with fsQCA, and positive associations emerged between AI capability, collaboration capability and sustainable innovation.

The work suggests that internal AI capability alone may not be what drives sustainable innovation in global value chains; coordination with partners appears to carry a large share of the effect. The data are cross-sectional survey associations from one economy's manufacturers, so they do not show causation or apply directly to other settings.

Main points

  1. The sample was 205 senior technology executives in Taiwan's high-technology manufacturing sector.
  2. AI-enabled materials informatics capability was positively associated with collaboration capability (β = 0.612).
  3. Collaboration capability was positively associated with sustainable innovation performance (β = 0.485).
  4. A direct association between AI capability and sustainable innovation performance was also found (β = 0.215, p = .002).
  5. fsQCA found three sufficient configurations for high sustainable innovation performance, including one pairing weak internal AI capability with strong data-governance and regulatory-sensing practices.

The gain

Among surveyed Taiwanese high-tech manufacturers, stronger AI-enabled materials informatics capability was associated with higher sustainable innovation performance, partly through inter-organisational collaboration capability.

The rundown

The study draws on the Dynamic Capabilities View and global value chain governance research, framing the problem as how manufacturers convert internal AI capability into outcomes that depend on coordination across organisational boundaries during the twin transition of digitalisation and sustainability.

Using two complementary methods, PLS-SEM estimated net associations, including a significant specific indirect association of β = 0.297 via collaboration. A sensitivity analysis excluding one sustainable-innovation item, SIP_2, produced materially unchanged results.

The fsQCA results add a configurational view: an Eco-Collaborative pathway reaches high sustainable innovation performance with weak internal AI capability when data-governance and regulatory-sensing practices are strong, so AI capability is not the only route.

Sources

  1. Peer-reviewedAsian Journal of Technology Innovation2026-10-16

The debate