Accelerating Green Innovation Performance from the Relations of Network Potential, Absorptive Capacity, and Environmental Turbulence

Abstract

The demand for sustainable development and the advantages of industries are expediting over time with the triggering of green innovation performance (GIP). Improving a firm’s GIP, especially in manufacturing industries, can accelerate green development and mitigate the global-concerned environmental issues. Thus, to investigate GIP from its antecedent factors, we delineate the relationship between network potential, absorptive capacity, environmental turbulence, and GIP based on social network theory, organizational learning theory, and contingency theory. We tested our hypotheses based on 233 sets of questionnaire surveys from high-tech manufacturing firms in China through deploying the hierarchical regression and bootstrap method. Our empirical findings reveal that the network potential dimensions, including network position centrality (NPC), network structure richness (NSR), and network relationship closeness (NRC), significantly positively impacted the GIP. The absorptive capacity (AC) partially mediated the relationship between the network potential dimensions and GIP. Environmental turbulence (ET) as an essential mechanism not only positively moderated the relationship between AC and GIP but also enhanced the AC mediation effect. These findings indicate that manufacturing firms should continue to improve network potential and AC and respond rapidly to changes in the external environment to enhance GIP, consequently contributing to the sustainable development of the economy.