Analysing the Impact of Restaurant Capacity Utilization and Weather Conditions on Order Cancellation and Delivery Delays at Doorstep Food
Abstract
<h2>Operational Context and Research Objectives in On-Demand Food Delivery Systems</h2> <p>As opposed to traditional operations where customers make reservations at restaurants, the on-demand food business processes orders immediately after a customer makes a request, and as such, consumers are time-sensitive. On-demand food delivery requires management to ensure shorter delivery times and efficiency since customers are prone to cancel their orders at their convenience, which results in higher operational costs (Bai et al., 2018). Further, consumers using websites and mobile applications are able to track their orders and predict waiting time since they have real-time data, and this creates a transparent operational process (Xu, Yan & Tong, 2021).</p> <p>Apparently, rainfall intensity, temperature, and restaurant capacity utilization play a key role in determining the delivery time of an order. Using real-time traffic data, a qualified driver should determine the shortest route without traffic congestion and deliver the food on time (Yuan et al., 2019). Therefore, the customer has an impression of shorter delivery time since they have all the data at the comfort of their home or workplace, and this assists in alleviating negative emotions such as frustration while waiting for meals.</p> <p>Conversely, weather conditions such as high rainfall and extreme temperatures can influence an individual's emotional response and thereby lead to order cancellation for meals online. For instance, Liu, Wang and Zhao (2021) discovered that when temperature rises during the day, people prefer to eat burgers and BBQ as opposed to their preferred meals. The ongoing challenges related to extended waiting time for food preparation in restaurants, changing weather patterns, and inefficient route planning contribute to the high rate of order cancellation and delayed food delivery. As such, this report aims to identify how climatic conditions and restaurant capacity utilization influence order cancellation and delivery delays at Doorstep Food.</p> <p>The following objectives guide the study:</p> <ul> <li>To determine how rainfall intensity, temperature, and delivery distance influence the likelihood of order cancellation.</li> <li>To identify the existing relationship between restaurant capacity utilization and delivery times.</li> </ul> <h2>Descriptive Statistical Evaluation of Delivery and Environmental Variables</h2> <p>Based on the results in Table 1, the average amount of rainfall during delivery is approximately 0.51, but there are days that experience heavy rainfall of up to 3.81. The high kurtosis value of 5.49 shows that the data is not normally distributed and is highly peaked. This peak is due to extreme values, which suggest that heavy rainfall during food delivery occurs more frequently than expected under normal conditions.</p> <p>The average temperature is approximately 19.96 degrees Celsius, and the data is normally distributed. This finding indicates that food delivery services operate in a moderately warm environment. Additionally, the average delivery distance is approximately 4.26 km with a standard deviation of 2.16 km, suggesting that most deliveries occur within a relatively small range. The maximum distance of approximately 8.00 km may contribute to increased delays or order cancellations.</p> <p>In terms of restaurant load, the average capacity utilization is approximately 51.28%, indicating that restaurants operate at about half of their total capacity. However, some restaurants operate at full capacity, which may increase food preparation time and the likelihood of cancellation and delivery delays. The average delivery delay is approximately 9.78 minutes with a standard deviation of 27.44 minutes, indicating significant variation. The minimum delay of -25 minutes suggests either data entry errors or early deliveries, while the maximum delay of 505 minutes may be attributed to extreme weather or severe traffic conditions.</p> <h2>Graphical Examination of Order Cancellation and Delivery Performance Patterns</h2> <p>Visual analysis provides insights into patterns of order cancellations and delivery delays. Figure 1 shows that order cancellations peak at specific times of the day, particularly between 12:00 PM and 2:00 PM and between 6:00 PM and 8:00 PM. These periods likely correspond to peak demand times, which may result in longer waiting times. Early morning cancellations between 6:00 AM and 9:00 AM may be associated with work-related constraints.</p> <p>Figure 2 demonstrates that moderate rainfall levels (0–1 mm) are associated with higher order cancellations, suggesting that consumers are more likely to cancel orders under relatively favorable weather conditions. During heavy rainfall, cancellations decrease, possibly due to reduced order volumes.</p> <p>Figure 3 reveals a positive relationship between delivery distance and delivery delays, indicating that longer distances lead to longer delays. Beyond 8 km, delivery delays become highly variable due to traffic congestion and other uncertainties. Figure 4 indicates that when restaurant capacity utilization is below 10%, delivery delays increase significantly, while higher utilization levels appear to stabilize delivery times.</p> <h2>Identification and Implications of Extreme Delivery Delay Outliers</h2> <p>The boxplot in Figure 5 visualizes delivery delays and highlights the presence of four significant outliers. These outliers exceed 100, 200, 300, and nearly 500 minutes. The majority of delivery delays are clustered around zero, as indicated by the interquartile range.</p> <p>These extreme values may be attributed to data entry errors, operational inefficiencies, or severe traffic congestion. Identifying and addressing these outliers is essential for improving the accuracy of analysis and enhancing operational performance.</p> <h2>Interpretation of Empirical Findings and Operational Improvement Strategies</h2> <p>The findings indicate that order cancellations are influenced by both temporal and environmental factors. Peak-hour cancellations suggest that operational inefficiencies during high-demand periods contribute to customer dissatisfaction. Weather conditions also play a significant role, with moderate rainfall associated with higher cancellation rates.</p> <p>The positive correlation between delivery distance and delays highlights the importance of efficient route planning. Additionally, low restaurant capacity utilization is associated with increased delays, possibly due to inefficient resource allocation or inconsistent demand patterns.</p> <p>To reduce delivery time and order cancellations, Doorstep Food should implement strategies such as offering compensation for late deliveries, improving restaurant efficiency by regulating order intake during peak periods, and enhancing communication with customers during delays. Providing incentives to drivers during peak hours and adverse weather conditions may also improve delivery performance and increase order fulfillment rates.</p>