Shortening Delivery Times by Predicting Customers’ Online Purchases: A Case Study in the Fashion Industry

ABSTRACT

Limited research exists that investigates how big data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products.

KEYWORDS:

• Anticipatory shipping
• big data analytics
• online purchases
• prediction
• e-commerce

Notes

1. The data protection principles of the General Data Protection Regulation (GDPR) are strictly

followed so that any personal data received is in a form which does not permit identification of

data subjects. Data is maintained and encrypted using Advanced Encryption Standard 256-bit

encryption.

Additional information

Notes on contributors

Jennifer Weingarten

Jennifer Weingarten (https://orcid.org/0000-0002-2971-1047), born in 1990, joined the chair of Logistics Management at WHU as an external doctoral student in June 2018. She holds a Bachelor of Science in International Business Administration from the University of Twente (Netherlands) and a Master of Science in Operations Management & Logistics from the Eindhoven University of Technology (Netherlands). She concluded her studies with a thesis on developing a same-day delivery concept for an international player in the construction industry. After graduation, she worked as a consultant at an international management consulting firm where she mainly supported supply chain management projects.

Stefan Spinler

Stefan Spinler (ORCiDs ID: 0000-0003-2669-4728), born in 1970, holds the Kühne Foundation Endowed Chair of Logistics Management at WHU – Otto Beisheim School of Management. He received a master’s degree in Electrical Engineering from the Friedrich-Alexander University in Erlangen. Subsequently, he joined Infineon Technologies with responsibilities in process integration and supply chain management. He pursued his doctoral and postdoctoral degree (Habilitation) in the department of Production Management at WHU, where the latter covered aspects of market-based supply chain coordination. He has published in leading international journals such as Decision Sciences, European Journal of Operational Research, Interfaces, and Production and Operations Management.