Fulfillment by Amazon versus fulfillment by seller: An interpretable risk‐adjusted fulfillment model

Abstract

With dual‐channel choices, E‐retailers fulfill their demands by either the inventory stored in third‐party distribution centers, or by in‐house inventory. In this article, using data from a wedding gown E‐retailer in China, we analyze the differences between two fulfillment choices—fulfillment by Amazon (FBA) and fulfillment by seller (FBS). In particular, we want to understand the impact of FBA that will bring to sales and profit, compared to FBS, and how the impact is related to product features such as sizes and colors. We develop a risk‐adjusted fulfillment model to address this problem, where the E‐retailer's risk attitude to FBA is incorporated. We denote the profit gaps between FBA and FBS as the rewards for this E‐retailer fulfilling products using FBA, our goal is to maximize the E‐retailer's total rewards using predictive analytics. We adopt the generalized linear model to predict the expected rewards, while controlling for the variability of the reward distribution. We apply our model on a set of real data, and develop an explicit decision rule that can be easily implemented in practice. The numerical experiments show that our interpretable decision rule can improve the E‐retailer's total rewards by more than 35%.

An analysis of operating efficiency and policy implications in last‐mile transportation following Amazon's integration

“…Lai, Liu, and Xiao (2018) also found through a theoretical model that by inducing third-party sellers to use its services available through the Fulfillment by Amazon (FBA) program, Amazon can blunt the sellers' ability to compete with Amazon on prices. In addition, according to Sun et al (2020), the use of these services by third-party sellers increases their exposure to product returns by consumers participating on the platform. It is possible that these phenomena will also apply to Amazon's in-house delivery services.…”

Enhancing online-to-offline delivery efficiency facilitated by Industry 4.0: a personnel configuration perspective

“…, 2020). For example, Sun et al. (2020) used a risk-adjusted fulfillment model to compare two fulfillment modes at Amazon—direct fulfillment by Amazon or the seller.…”

“…The order fulfillment and delivery process is one of the most critical operations in e-commerce because of the physical distance between consumers and vendors and the separation between the transaction and consumption (Biswas and Biswas, 2004). Previous studies have investigated online sellers' fulfillment performance (Sun et al, 2020;Xu et al, 2020). For example, Sun et al (2020) used a risk-adjusted fulfillment model to compare two fulfillment modes at Amazon-direct fulfillment by Amazon or the seller.…”

“…Previous studies have investigated online sellers' fulfillment performance (Sun et al, 2020;Xu et al, 2020). For example, Sun et al (2020) used a risk-adjusted fulfillment model to compare two fulfillment modes at Amazon-direct fulfillment by Amazon or the seller. They found that the fulfillment mode affects the sales and profits, as moderated by the product size and color.…”

Data‐driven research in retail operations—A review

“…While real‐world implementation is not always possible, several others have made contributions via pursuing a practice‐driven path, focusing on empirical analysis with large‐scale real data from industry. For example, Sun, Lyu, Yu, and Teo (2018) analyze data from a wedding gown e‐retailer in China to analyze the impact of the fulfillment by Amazon (FBA) model compared with fulfillment by seller (FBS). They develop a risk‐adjusted fulfillment model that incorporates the e‐retailer's risk attitude toward FBA.…”