JOURNAL ARTICLE
Walking the Purpose-Talk Inside a Large Company: Sustainable Product Development as an Instance of Divergent Change.
Published In: Strategy Science (INFORMS), 2023, v. 8, n. 2. P. 311 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Kimsey, Marissa; Geradts, Thijs; Battilana, Julie 3 of 3
Abstract
This article examines how large companies can develop sustainable products that reflect a renewed corporate purpose encompassing responsibility to people and the planet alongside profit, focusing on a qualitative study of four sustainable product initiatives within a major fast-moving consumer goods company (FMCG CORP) from 2010 to 2019. The study identifies sustainable product development as a form of divergent change that challenges entrenched norms prioritizing short-term financial gain, often triggering intense internal resistance. Two key leadership practices by senior managers in the product division—(1) relaxing conventional short-term profit metrics to allow experimentation separate from mainstream business, and (2) advocating with internal gatekeepers to integrate sustainable products into core sales portfolios—were critical for successfully launching sustainable products internally. The findings suggest that without altering underlying organizational norms and structures, sustainable products risk remaining tolerated exceptions rather than driving company-wide transformation. The article highlights the political and institutional complexities involved in shifting corporate purpose and calls for further research on navigating these challenges to embed sustainability in large companies.
Additional Information
- Source:Strategy Science (INFORMS). 2023/06, Vol. 8, Issue 2, p311
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2023
- ISSN:2333-2050
- DOI:10.1287/stsc.2023.0197
- Accession Number:182962475
- Copyright Statement:Copyright of Strategy Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences 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.)
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