  With the significant rise in demand for same-day instant deliveries, several
courier services are exploring alternatives to transport packages in a cost-
and time-effective, as well as, sustainable manner. Motivated by a real-life
case study, this paper focuses on developing a simulation algorithm that
assists same-day package delivery companies to serve customers instantly. The
proposed recommender system provides the best solution with respect to three
criteria: cost, time, and sustainability, considering the variation in travel
time and cost parameters. The decision support tool provides recommendations on
the best alternative for transporting products based on factors, such as source
and destination locations, time of the day, package weight, and volume. Besides
considering existing new technologies like electric-assisted cargo bikes, we
also analyze the impact of emerging methods of deliveries, such as robots and
air taxis. Finally, this paper also considers the best delivery alternative
during the presence of a pandemic, such as COVID-19. For the purpose of
illustrating our approach, we consider the delivery options in New York City.
We believe that the proposed tool is the first to provide solutions to courier
companies considering evolving modes of transportation and under logistics
disruptions due to pandemic.
  Keywords: Instant package delivery; Courier services; Simulation algorithm;
Recommender system; Emerging technologies; COVID-19 pandemic.

Computers and Society;Computer Science and Game Theory