On-demand food delivery: investigating the economic performances

Purpose: This paper focusses on on-demand food delivery (ODFD), i.e. the delivery of freshly prepared meals to customers' homes, enabled by the use of online platforms. In ODFD, a key process is represented by last-mile deliveries (LMDs): they directly affect customers (the delivery price influences their purchase intention), riders (the compensation drives their willingness to perform deliveries) and platforms (deliveries are very expensive). In this context, this work aims to investigate the economic performances of ODFD LMDs. Design/methodology/approach: This study adopts a multi-method threefold process. First, it develops a model that – after the generation of customers' demand and the assignment of deliveries to available riders – identifies incomes and costs faced by an ODFD operator. Second, the model is applied to a base case in Milan (Italy). Third, sensitivity analyses are performed (on daily demand and riders' salary). Findings: The analyses allow – besides the identification of significant values associated to ODFD profitability – to draw general insights about delivery price (e.g. free delivery is not economically sustainable), daily demand (e.g. greater demand values do not only improve positive results but also worsen negative ones) and fixed/variable wage mix (e.g. increasing the variable wage enhances the profitability for platforms). Originality/value: On the academic side, this word enhances extant literature about ODFD, proposing a model – with multidisciplinary implications – to strategically investigate profitability conditions of LMDs. On the managerial side, it provides support for (logistics/marketing) ODFD practitioners since it allows to evaluate the potential impact of significant decisions on profitability.