JOURNAL ARTICLE
Can Rising Eco-sensitivity Hurt Sustainability? Eco-impact of Durable Goods Innovations.
Published In: Marketing Science (INFORMS), 2026, v. 45, n. 1. P. 224 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: K., Sudhir; Ramesh Shankar; Jin, Yuan 3 of 3
Abstract
This article develops a dynamic two-period economic model to analyze the environmental impact of durable goods innovations amid rising consumer eco-sensitivity, distinguishing between functional innovations (which improve product features without reducing in-use harm) and use-efficiency innovations (which reduce in-use environmental harm). It finds that increasing eco-sensitivity generally reduces total environmental harm and firm profits for functional and low-efficiency innovations by discouraging upgrades, while it increases both profits and reduces harm for high-efficiency innovations by accelerating adoption. However, for moderate-efficiency innovations—where the reduction in in-use harm is close to but less than replacement harm—increasing eco-sensitivity can paradoxically increase total eco-harm due to firms’ strategic pricing that shifts sales toward less efficient products in the less eco-sensitive period. The study further shows that trade-in discounts and recycling programs can mitigate this unintended effect, improving both profitability and environmental outcomes. These findings highlight complex interactions among consumer behavior, firm pricing strategies, and eco-sensitivity, offering insights for policymakers, firms, and environmental advocates on when and how to promote consumer education and sustainable practices in durable goods markets.
Additional Information
- Source:Marketing Science (INFORMS). 2026/01, Vol. 45, Issue 1, p224
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2026
- ISSN:0732-2399
- DOI:10.1287/mksc.2022.0304
- Accession Number:190804492
- Copyright Statement:Copyright of Marketing 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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