Leveraging green innovation from big data analytics: Examining the role of resource orchestration and green dynamic capabilities

Abstract

PURPOSE: The notion of big data analytics (BDA) has received increased attention from both researchers and managers. Keeping in view the significance of BDA, the current research aims to examine the role of BDA capability to leverage firm green innovation (GI). Drawing from the dynamic capability view, current study suggests that BDA capability prompts green dynamic capabilities (DCs), enabling organizations to attain GI successfully. Particularly, present study proposes that BDA analytics prompt GI directly as well as through green DCs. Moreover, this study also draws from complementarity perspective and proposes that resource orchestration capability (ROC) is likely to enhance the effectiveness of green DCs in eliciting GI. Thus, the objectives of the current study are threefold; first, it aims to unveil the role of BDA capability in prompting GI; second, it examines the mediating role of green DCs for the relationship between BDA capability and GI; and third, this research examines the moderating effect of ROC to examine if it strengthens the effects of green DCs. METHODOLOGY: This study involves testing hypotheses using primary data collected by using the method of survey questionnaire. The data were collected from 291 Pakistani organizations. Pakistan is an emerging economy where businesses are responsible for substantial amounts of carbon di-oxide and greenhouse gasses (GHG) emissions. Therefore, Pakistani organizations serve as a suitable context for the study. The respondent organizations were from both the manufacturing and service sectors. PLS-SEM was employed as an analytical approach for testing the hypotheses. Construct validity and reliability were confirmed prior to hypotheses testing. FINDINGS: Results demonstrate that BDA capability positively affects GI (β=0.33, p<0.01), indicating that organizations with strong BDA capabilities involve in GI activities. Likewise, results indicate a positive relationship between BDA capability and green DCs (β=0.35, p<0.01) and between green DCs and GI (β=0.50, p<0.01). Results also indicate that green DCs play a mediating role between BDA capability and firm GI (β=0.18, p<0.01). This indicates that BDA capability is an imperative capability of organization that promotes green DCs and fosters GI. Finally, findings indicate that ROC strengthens the effectiveness of green DCs in prompting GI (β=0.14, p<0.01). IMPLICATIONS: Findings imply that organizations that prioritizing green innovations (GI) should invest more in developing BDA capabilities. These actions may involve acquiring and analyzing large volumes of data associated with sustainability, which can provide insights and support decision-making processes. By leveraging BDA capability, managers can uncover insights and patterns that can help them make informed decisions, recognize areas for improvement, and devise innovative solutions to align organizational strategic objectives with sustainability goals. ORIGINALITY AND VALUE: This study contributes to the literature by offering an integrated framework based on BDA and DCs to seek solutions to economic concerns while ensuring the sustainability value of the business activities. The findings also imply that businesses should focus on developing ROC, and integrating them with green DCs to further enhance GI initiatives.

Keywords

• big data analytics capability
• green innovation
• green dynamic capabilities
• resource orchestration
• pls-sem