Digital transformation and environmentally sustainable innovation: Based on machine learning and text analysis...

Area of Science:

• Environmental Science
• Business Management
• Information Technology

Background:

• Growing global environmental challenges necessitate environmentally sustainable innovation (ESI).
• Digital transformation's role in driving ESI requires deeper investigation, beyond traditional views on digital technologies.
• Distinguishing between internal and external digital transformation is crucial for understanding their impact on ESI.

Purpose of the Study:

• To examine the impact of internal digital transformation (IDT) and external digital transformation (EDT) on ESI.
• To analyze the moderating roles of the institutional environment and resource endowment in the relationship between digital transformation and ESI.
• To provide insights into the mechanisms linking digital strategies to environmental innovation for policy and practice.

Main Methods:

• Utilized Bidirectional Encoder Representations from Transformers (BERT) and Bag of Words (BoW) models.
• Constructed variables for ESI and digital transformation using these NLP techniques.
• Employed a sample of Chinese listed companies for empirical analysis.

Main Results:

• A negative relationship was found between internal digital transformation (IDT) and ESI.
• A positive impact of external digital transformation (EDT) on ESI was identified.
• Institutional environment and resource endowment were found to moderate the IDT-ESI and EDT-ESI relationships.

Conclusions:

• Digital transformation's effect on ESI is contingent on its internal versus external focus.
• External digital transformation presents a promising avenue for enhancing ESI.
• Policy and strategic decisions regarding digital transformation should consider contextual factors like institutional environment and resource availability.