A decision tree classifier approach for predicting customer’s inclination toward use of online food delivery services

Abstract

In today’s world, demand for online food delivery (OFD) applications has been boosted because of people’s busy schedules and aspirations for comfortable and smooth lifestyles. The purpose of the study is to provide knowledge of consumer behavior to the OFD Service providers. Primary data has been collected from 410 users of OFD applications. Decision Tree Classifier approach has been used to predict the consumer inclination toward use of OFD services.The study concludes by presenting the Decision Tree by which Online Service Providers can predict the consumer behavior and based on which they can make better decisions. Major finding reveals that, dinner is the most preferred meal for OFD services across different income and age groups. Offers and discounts play a vital role in influencing the behavior of majority of OFD consumers. Practical implications: This paper offers a guidance to the Online Food Delivery Aggregators for better decision making.