A so-called Smart Green Nudge can give consumers an incentive to behave in a more environmentally conscious way. Such a nudge can be conceived as a gentle hint that is intended to induce people to change their behavior without exerting pressure so that fewer goods ordered on the internet are returned. This creates a win-win situation: resource consumption decreases and company profits increase. These are the findings of a working paper published by the Leibniz Institute for Financial Research SAFE, which describes a field trial conducted by the researchers together with a major German fashion store.
Returned goods in online shopping pose major challenges for both society and retailers. For example, immense resources are consumed for transport and packaging, which increases greenhouse gas emissions and packaging waste. Furthermore, companies face considerable costs because the returned goods have to be transported, recorded and, if necessary, processed for resale.
Behavioral nudge creates a win-win situation
“The Smart Green Nudge we developed as part of a field study can reduce product returns by around seven percent," says Dr. Kevin Bauer, a researcher in SAFE’s Financial Intermediation Department and one of the study’s authors. But it’s not just the environment that benefits from the approach since the fashion store also profits: “In total, the Smart Green Nudge can increase company profits by more than twelve percent,” adds SAFE Bridge Professor Oliver Hinz, coordinator of the Digital Finance Network at SAFE and also one of the authors.
The researchers from SAFE and Goethe University Frankfurt, together with a consulting firm, developed the Smart Green Nudge in a two-stage behavioral economics approach in collaboration with a major German fashion retailer starting from a seven-week field experiment. Half of the nearly 50,000 visitors to the German online store were randomly shown a notice appealing to their environmental awareness. The customers' shopping and return behavior was precisely documented.
Subsequently, the information collected in the field trial was combined with additional data to develop a machine learning system that optimizes the display of the green nudge. “This is aggregated data that is publicly available and cannot be used to infer individual customer characteristics – so data privacy is guaranteed in our experiment,” Bauer says. Thus, an extended digital footprint was created, which was used to train a causal machine learning (CML) system. The trained CML system identifies people for whom the Smart Green Nudge can be used successfully, who actually return fewer goods when they are made aware of the environmental damage caused by returns.
Download the SAFE Working Paper No. 363
Felix Kretz
Head of Communication
