A Time series analysis of online food ordering sales (dial a delivery) in Zimbabwe (2020 – 2023).

Author

Gloria Tanaka Shoko

Title

A Time series analysis of online food ordering sales (dial a delivery) in Zimbabwe (2020 – 2023).

Abstract

The food sector has changed dramatically as a result of the internet meal delivery services' explosive expansion, especially in developing nations like Zimbabwe. The goal of this research project is to provide a thorough time series analysis of online food ordering sales for Dial a Delivery, one of Zimbabwe's top service providers. Finding sales trends, seasonal patterns, and possible forecasting models is the main goal in order to enhance corporate strategy and gain a better understanding of consumer behavior. The study employs a variety of time series analysis approaches, such as decomposition, autocorrelation analysis, and ARIMA (Autoregressive Integrated Moving Average) modeling, using monthly sales data from January 2018 to December 2023. The information was taken from the sales records of Dial a Delivery, offering a substantial dataset for careful examination. The results reveal significant variations in sales, with peak periods corresponding to major holidays and festive seasons. Additionally, the analysis identifies a positive trend in sales growth over the study period, reflecting the increasing adoption of online food ordering services in Zimbabwe. The ARIMA (3,1,0) model developed in this study demonstrates high accuracy in forecasting future sales, with a mean absolute percentage error (MAPE) of 10.2%. The researcher advises other students to look into the application of time series in online sales employing important techniques that were overlooked in the study. In order to increase sales throughout the winter, Dial a Delivery might think about stepping up their marketing initiatives and promos. In order to satisfy the increased demand throughout the summer, the corporation should keep enough inventory levels. Regular updates of the ARIMA model are necessary to guarantee precise projections and to accommodate any modifications in the market.

Date

June 2024

Publisher

BUSE

Keywords

Time Series Analysis

Online

Ordering

Food

Supervisor

DR T.W. MAPUWEI