The Non-Linear Impact of Delivery Time on Online Purchasing

Abstract

Problem definition: For e-commerce companies to assess how best to invest in improving delivery times, it is important to understand how improving delivery times affects customer demand. In collaboration with a business-to-business (B2B) e-commerce company, we study how the estimated delivery time promised in a quote affects the customer's purchase probability at different price levels. 

Methodology/results: We use quote-level observational and experimental data from our partner, with micro-level variation in stated delivery times. This allows us to estimate demand as a function of stated delivery time after flexibly controlling for customer, product, and vendor differences. We find that there is a large, robust effect of delivery time on demand: a 1-day improvement in estimated delivery time increases demand by 1.98%, equivalent to a 3.14% discount, comparable to prior findings in business-to-consumer (B2C) retail contexts. Interestingly, using non-parametric analysis, we find that this effect is non-linear: demand is not sensitive to delivery times of under a week, but drops quickly when delivery is expected to take over a week. 

Managerial implications: We find that timely delivery is important in a B2B setting, not just in fast-moving retail settings. We show that the largest improvements in demand are to be gained from investing in measures that can reduce the "long tail" of slow deliveries (e.g., avoiding stockouts and processing delays, ensuring geographic coverage of fulfillment centers) rather than reducing the delivery time of products that are already relatively fast to deliver. The results from our analysis were used by our partner to decide on opening new fulfillment centers and re-pricing their services given the new fulfillment center network (since customers are willing to pay more for faster delivery).

Keywords: e-commerce, online retail, delivery time, consumer choice, B2B