Research On Dynamic Matching Problem In Crowdsourced Logistics Through An E-Platform

Empty backhauls travel along the Northern Corridor results in wasteful expenditures that lead to a relatively high cost of doing business in the East African Community(EAC).This study examines the issue of empty backhauls along the corridor and assesses the potential for its further reduction via the use of a dynamic matching platform to crowdsource cargo,and in turn minimize it through backloading.Backloading increases operational efficiency by substantially reducing partial or empty backhauls.It facilitates best utilization of resources such as truck empty capacity,driving time and fuel,improving the profitability of haulage operation.By backloading wherever practical,carriers can earn from both inbound and outbound trips and in turn obtain much more competitive haulage prices.Numerous past methods of obtaining cargos such as traditional collaboration and brokerage have not been that effective,and have heard little progress.Their inability to effectively create visibility and maintain privacy has led to carriers' repositioning their trucks empty due to the inefficiencies and limitations in obtaining and matching cargos.While carriers can collaborate to reduce empty backhauls,privacy concerns on information sharing have made this difficult to realize the potential benefits of cooperation,resulting in lost opportunities in identifying backloading loads.Crowdsourcing via dynamic matching platforms has immense potential benefits to facilitate backloading process.Information and communication technology enables carriers to collaborate by exchanging their shipping requests while maintaining privacy.It can facilitate automated matchings by incorporating real-time monitoring,geo-based information,analysis of historical geo-based information,and user-calibrated preferences from all crowdsourced participants.Using dynamic ride share matching concept,a matching model was developed to simulate the dynamic matchings of shippers' cargos and carriers' trucks.The numerical example demonstrated the potential of minimizing empty backhauls.The analysis showed that an increase in the number of participants increased the performance of the matchings,and allowing detours increased the number of matchings.The study showcase how carriers can embrace the use of crowdsourcing platforms to fill empty capacities by identifying and dynamically matching them with shippers cargos in a real-time fashion,enabling them to benefit from resource consolidation.Crowdsourced backloading can result in significant economic and social benefits.For carriers,it has a potential cost saving advantage as it creates an opportunity to reduce empty backhauls.It can provide desirable results by reducing shipping costs,congestions,and air pollution,with the aim of utilizing the empty capacities on trucks to backload crowdsourced shippers' cargos.