Influence of eco‐product innovation and firm reputation on corporate social responsibility and competitive advantage: A mediation‐moderation analysis.
Published In: Journal of Public Affairs (14723891), 2023, v. 23, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Olaleye, Banji Rildwan 3 of 3
Abstract
Eco‐product innovation is a response to environmental legislation and social responsibility movements. Established agricultural manufacturers must figure out how to use green ideas and reputation to compete for business excellence. This study adopted a knowledge‐based approach to examine corporate social responsibility and competitive advantage. This study also examined how eco‐product innovation and reputation affect firms' competitive advantage. The proposed model was tested on 427 Nigerian agro‐allied manufacturers using causal pathways and structural equation modeling. Business competition is directly and indirectly affected by corporate social responsibility, eco‐product innovations, and firm reputation. Additionally, eco‐product innovation partially mediated the nexus between corporate social responsibility and competitive advantage, while reputation moderated the influence of eco‐product innovation. The findings suggest that manufacturers pursuing green initiatives should strive to participate in an eco‐friendly competition and deal with policy pressures in order to meet environmental standards. Overall, this study adds the environment and business competition to the idea of innovation. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Public Affairs (14723891). 2023/11, Vol. 23, Issue 4, p1
- Document Type:Article
- Subject Area:Economics
- Publication Date:2023
- ISSN:1472-3891
- DOI:10.1002/pa.2878
- Accession Number:173470367
- Copyright Statement:Copyright of Journal of Public Affairs (14723891) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.