Conference Programme

Retail shipping is responsible for nearly 25% of global greenhouse gas emissions and costs retailers billions annually. Firms have long treated shipping optimization as a supply chain problem, investing in warehouses, routes, and infrastructure. We show that a largely overlooked lever—product ranking algorithms at the consumer search stage—can deliver substantial efficiency and sustainability gains without capital investment. We redesign ranking as a cost–conversion optimization, embedding shipping costs directly into the ranking algorithm. Because such re-ranking significantly reshapes which products are shown, it challenges both offline evaluation and online learning. In a field experiment with four million consumers on a major e-commerce platform, this demand-side intervention reduced shipping costs by 2–3%, cut delivery distances by 34 miles per order, and lowered emissions by 3.8%, while preserving conversions and customer satisfaction. The emissions savings were equivalent to the annual electricity use of 50,000 U.S. households or the emissions of 58,000 gasoline cars. When the policy underperformed, it exposed structural rigidities such as brand-driven demand or inflexible warehouse networks. These results show that ranking algorithms can both shape demand and diagnose supply chain strategy, helping platforms align profitability with sustainability at scale