Based on innovation diffusion theory and the TOE framework, this study explores the configuration strategies and driving pathways of digital innovation performance between technological, organizational and environmental factors.
The study employed the fuzzy-set qualitative comparative analysis (fsQCA) and machine learning method. The data were collected by using annual reports from 136 manufacturing firms.
The findings reveal that data element application, digital infrastructure, organizational size, managerial abilities, resource constraint, financial technology development and market competition pressure, as simultaneous preconditions, collaboratively drive digital technological innovation performance and digital managerial innovation performance in manufacturing firms. Moreover, two distinct configurations explain high digital technological innovation performance: “technology-driven” and “organizational ability and innovation environment-driven”. Three specific configurations are identified to explain high digital management innovation performance: “technology and innovation environment-driven”, “technology and organizational capability-driven” and “all factor-driven”. Third, these configuration strategies for driving digital technological innovation performance and digital managerial innovation performance exhibit substitutive effects, respectively.
The study contributes to the theoretical literature on digital innovation and provides managerial insights for manufacturing firms implementing digital innovation and digital transformation strategies.
