Examining urban delivery service user profiles and determinants of drone delivery adoption in Ghana considering usage before and after the COVID-19 pandemic

Reuben Tamakloe, Kaihan Zhang, Jonathan Atandzi, Dongjoo Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The demand for urban delivery services (UDS) in low- and middle-income countries (LMICs) has been growing due to the spike in e-commerce activities. This phenomenon has led to the search for more innovative UDS modes, such as drones, as they provide fast, safer, and eco-friendly services. Although researchers have examined the perceptions regarding the adoption of drone delivery, there are many unknowns about the intentions to use this futuristic delivery mode. By employing survey data obtained through an online survey conducted in Ghana, this study aims to gain a deeper understanding of the current UDS user profiles and investigate their intentions to adopt drone deliveries in the future, considering the lived experiences of traditional UDS usage pre/post the COVID-19 pandemic. Regarding UDS user profiling, the study applied an advanced unsupervised machine learning method known as cluster correspondence analysis to simultaneously identify critical clusters in the data as well as key factor associations for each group. The findings demonstrated that most people in Ghana who seldom used the traditional UDS usually experienced poor service levels. Females living in the capital of Ghana who are frequent users of UDS mainly experienced acceptable service levels. Using an ordered probit regression model, the study identified that variables such as males, people who desired contactless UDS, and frequent UDS users at work or school during the COVID-19 pandemic were more inclined to embrace drone deliveries when introduced. Conversely, individuals who frequently used UDS services at home, those living in large cities, and those with lower income levels expressed reluctance toward drone delivery services. This study augments the urban logistics literature in LMICs by offering insightful suggestions in the areas of education, enhanced marketing strategies, and delivery optimization, which are instrumental for informing policy decisions. Government-related transportation bodies, private logistics firms, and trade unions can collaborate and adopt the recommendations provided to improve urban delivery services and to pave the way for integrating drone delivery services in the near future.

Original languageEnglish
Pages (from-to)279-294
Number of pages16
JournalTransport Policy
StatePublished - Feb 2024


  • COVID-19
  • Drone deliveries
  • Low- and middle-income country
  • Machine learning
  • Probit
  • Urban logistics


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