Analysis and design of service failure prevention system in online culinary business

Abstract

Online culinary businesses are in charge of preventive service failure to avoid greater loss and keeping service performance. The losses occurred due to protracted customer disappointment with service failures which lead to worse churning customers. We propose a prevention system to identify and allocate the failure position. It also sets the action rules to failure. This requires to analyze the current failure structure and cause. This work used decision tree classification (ID3) to design the rule. The failure structure was denied by the component of delivery time and food quality. The parameters to allocate the failure were delivery time, traffic jam, rush hour ordering, weekend/weekday order, rain/not rain day, giving GPS/not, suitable order, food complement, and packaging quality. It had four failure types: none, low, medium, and high. The model had 73% of accuracy to classify failure. The action for low failure was in charge by the delivery man in the form to speed the delivery time not exceed 85 minutes and by kitchen staff in the form to check the order before it sent. The medium failure was in charge by the delivery man in the form to speed the delivery time not exceed 55 minutes in not rush hour order.