Product portfolio decarbonization: Deleting hot products for a cooler supply chain
提出一种结合文本挖掘和多目标优化的混合方法，利用在线评论等数据，帮助管理者通过删除高排放产品来优化产品组合，实现供应链全面脱碳。
Abstract Modern economic development emphasizes the reduction of carbon emissions. In rationalizing product portfolios, organizations must prioritize low‐carbon development by selecting products with minimal emissions. Eliminating high‐emission items can create opportunities for new low‐carbon products, thereby enhancing competitiveness. In this study, we propose a hybrid mixed method that integrates text mining and multi‐objective optimization algorithms, utilizing a broad range of quantitative and qualitative data sources, including online consumer reviews. We apply this method to a real case in the Chinese air‐conditioning industry for practical validation. The results indicate that for comprehensive product portfolio decarbonization, organizations should consider deleting high‐performing products (e.g., those with strong sales and market performance) to achieve full decarbonization across the entire supply chain. This approach offers valuable insights for managers aiming to simultaneously improve economic and environmental performance.