Omni-channel retailers typically face high return rates, particularly in their online channel. This paper examines how these returns can be converted into exchanges by leveraging omni-channel capabilities. We do so in the context of a fast-fashion retailer running integrated physical store and online channels. Our unit of analysis is a return journey, which starts with an initial online purchase, proceeds with a return, and then potentially continues with subsequent exchanges and returns, replacing the original purchase. Using a random forest with instrumental variables, we study whether store visits for pick-up or return of the initial purchase influence a consumer’s likelihood to make an exchange, thereby generating revenue for the retailer. We explore the heterogeneous effect of these store visits across different customer profiles based on the recency-frequency-monetary value (RFM) framework. Our results indicate that store visits for pick-up or return increase the likelihood of an exchange, with a more pronounced effect among less valuable customers. Follow-up analyses suggest that this effect is driven by the customers’ ability to reduce product uncertainty through in-store inspection. Additionally, a store visit decreases the likelihood of a return (consistent with previous literature) and increases the likelihood of keeping an exchange purchase when it has been made. Our findings thus underscore the critical role of physical stores for online shoppers in finding the right product and, consequently, for retailers to convert returns into exchanges.

The electrolysis of CO₂ converts CO₂ into value-added products and has the potential to reduce the use of fossil feedstocks by serving as a circular alternative in chemical processes. However, existing literature lacks comprehensive and quantitative analyses of economic, environmental, and governmental factors that can hinder or support its deployment. This study addresses this gap by exploring the potential of CO₂ electrolysis for the production of synthesis gas, syngas, through a supply chain design that integrates long-term decisions on location and infrastructure and medium-term decisions on capacity expansion and aggregate production planning. We identify and quantify time-dependent and uncertain parameters using the Delphi method and employ multi-period planning and robust optimization approaches to consider them, respectively. Moreover, since the environmental impact of syngas is highly dependent on electricity consumption, renewable electricity is utilized with battery support alongside grid electricity. Accordingly, we propose a mixed integer linear programming model to design a supply chain that can serve as a benchmark to make CO₂ electrolysis financially and environmentally viable for syngas production. We conduct a case study on the Benelux region, analyzing different scenarios to derive managerial and design insights. The results show that a design that takes uncertainty into account can reduce syngas production costs by up to 22%. Additionally, although renewable electricity supply variability and different grid characteristics across countries can lead to different strategic decisions with higher costs, increased battery installations and higher government financial support for renewable electricity can help eliminate differences in designs.