Organizational ambidexterity and green innovation: the moderating effect of big data analytics capability in the context of China

Zeng, Wenjuan 2022. Organizational ambidexterity and green innovation: the moderating effect of big data analytics capability in the context of China. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

With pressure from consumer preference, societal expectation and regulatory policies, firms are increasingly integrating green business practices to achieve financial success. Although green innovation (GI) is regarded as an essential strategic element in helping firms to address environmental challenges, there is a lack of research on whether ambidexterity can be adopted to improve two key GI practices, namely green product innovation (GPDI) and green process innovation (GPCI). Meanwhile, with the rapid development of disruptive innovation, technologies like big data analytics have been widely adopted into product innovation, yet the impact of big data analytics capability (BDAC) as a dynamic capability of environment management remains unclear. Drawing on theories such as Resource Based Theory, Knowledge Based View, and Information Processing View, this study developed a theoretical model of GI success that aims to investigate the direct impact of ambidexterity and the moderator role of BDAC on GI. The model also investigates the overall impact of GI on firm’s financial, environmental and social performance. The model was tested with survey data collected from 375 Chinese firms. Surprisingly, the empirical results suggest that ambidexterity does not improve GI. In particular, the findings indicate that ambidexterity is negatively associated with GPDI and that there is no association between ambidexterity and GPCI. Regarding to the moderator roles of each type of BDAC in the relationship between ambidexterity and GI, Big data analytics infrastructure (BDAI) and big data analytics personnel (BDAP) have a positive and significant influence on the relationship between ambidexterity and two types of GI. This indicates that the development of BDAI and BDAP has the potential to lessen the negative relationship between ambidexterity and GPDI and to have a positive iii influence on the relationship between ambidexterity and GPCI. The findings also demonstrate that big data analytics management (BDAM) has no impact on the relationship between ambidexterity and two different GI categories. Additionally, existing literature doesn’t adequately examine under what conditions GI can be achieved from a holistic perspective. In order to fill this gap, this study also employs a fuzzy-set qualitative comparative analysis to examine how exploitation and exploration interact with BDAC to produce higher levels of GI. Different configurations are presented for both small and medium enterprises, and large firms, indicating that the same configuration of ambidexterity and BDAC practices lead to high levels of GPDI and GPCI. Outcomes highlight the inter-relationships between ambidexterity and BDAC practices and provide suggestions that firms regarding orchestrating resources in achieving GI. Keywords: ambidexterity, green product innovation, big data analytics capability, triple bottom line, empirical research

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > H Social Sciences (General)
Uncontrolled Keywords:	Ambidexterity Green innovation Big data analytics capability Triple bottom line Empirical research Fuzzy-set qualitative comparative analysis Structural equation modelling
Date of First Compliant Deposit:	1 November 2022
Last Modified:	06 Jan 2024 03:34
URI:	https://orca.cardiff.ac.uk/id/eprint/153854

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