How organizational unlearning leverages digital process innovation to improve performance: The moderating effects of smart technologies and environmental turbulence

Xiangyang Wang, Zhiyi Liu, Jiamin Li and Xuefei Lei

Technology in Society, 2023, vol. 75, issue C

Abstract: Digital process innovation has become the key for enterprises to implement digital transformation to optimize production and operation. However, as a radical change, digital process innovation may encounter strong inertia and resistance. How to overcome them to actively promote digital process innovation is crucial for enterprises. Building on organizational change theory, this study introduces organizational unlearning, smart technologies and environmental turbulence to explore how to promote digital process innovation by getting rid of inertia, thus improving performance. This study empirically tests 212 valid samples from Chinese enterprises using partial least squares structural equation modeling (PLS-SEM) and PROCESS. The results show that digital process innovation mediates the relationship between organizational unlearning and enterprise performance. Also, both smart technologies and environmental turbulence positively moderate the mediation of digital process innovation on the association between organizational unlearning and enterprise performance. This study reveals that organizational unlearning, smart technologies and environmental turbulence are powerful factors to break organizational inertia and promote digital process innovation, which provides fresh and significant insights of how to get rid of inertia in the process of digital transformation for academia and practitioners.

Keywords: Organizational unlearning; Enterprise performance; Process innovation; Smart technologies; Environmental turbulence (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:75:y:2023:i:c:s0160791x23002002

DOI: 10.1016/j.techsoc.2023.102395

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