JOURNAL ARTICLE

Sustainable Consumption: A Strategic Analysis.

  • Published In: Marketing Science (INFORMS), 2025, v. 44, n. 5. P. 1038 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Amaldoss, Wilfred; Prusty, Siddharth 3 of 3

Abstract

This article theoretically examines how heterogeneous consumer preferences for sustainable products influence firm pricing, profits, and consumer welfare in competitive markets. It distinguishes two consumer segments: H-type consumers who desire sustainability and are willing to pay a premium, and L-type consumers who dislike sustainability and prefer lower prices. The analysis reveals counterintuitive outcomes, such as prices decreasing with increased desire for sustainability and firms' profits potentially declining despite higher consumer willingness to pay, due to intensified competition on product sustainability raising costs. The study also finds that imposing minimal sustainability standards (MSS) can reduce overall consumer surplus when a moderate standard forces some L-type consumers out of the market, and that corporate average sustainability standards (CASS) for multiproduct firms may avoid this issue. Extensions explore multiproduct firm strategies, sustainable luxury goods where social preferences interact with sustainability, and the impact of consumers' political orientation, showing, for example, that a shift toward right-leaning consumers—who tend to dislike sustainability—can increase firms' profits. These findings highlight complex strategic considerations for firms and regulators in promoting sustainable consumption.

Additional Information

  • Source:Marketing Science (INFORMS). 2025/09, Vol. 44, Issue 5, p1038
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2025
  • ISSN:0732-2399
  • DOI:10.1287/mksc.2023.0287
  • Accession Number:188352076
  • 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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