The use of freight apps in road freight transport for CO2 reduction

Abstract

Purpose The purpose of this study was to investigate how a smart phone freight application service (Apps) could reduce CO 2 emissions in road freight transport and to identify the core problems for improvements. Methods This research uses a multiple-case-study approach to examine several existing freight apps in the Chinese market. The study was conducted using multiple data collection techniques, including interviews, production observation, firsthand experience, and online-search summaries. Results Inspired by a full analysis of case studies, a hierarchical conceptual framework was developed to provide an overarching view of how existing apps achieve environmental benefits, which deepens our understanding of the interrelationship between freight Apps utilization and CO 2 reduction. Freight apps provide a mechanism that auto-match the consignor's demand and the carrier's supply based on mobile Internet. The efficient way to find the right truck and complete the delivery process enhances the decrease of truck's empty travel distances and improvement of average vehicle loaded, then leading to an improvement of efficiency and a decline in carbon emission in freight industry. And then the identification of returning pick-up and route planning was conducted to further improve apps for CO 2 reduction. Conclusions The influences to freight movement system by apps focused on reconstructing the demand and supply with integration technology, and resulted in a more efficient transaction using matching technology and advanced fleet management with optimization technology. When with inter-urban Full Truck Load, freight apps enable carriers to search for demand for returning a pick-up with decreasing empty running mileages, which then has environmental benefits through reducing CO 2 emissions. However, when in urban Less-thanTruck Load, by strengthening the average vehicle utilization on laden trips, another determinant of route planning of delivery & collection reduced CO 2 emissions. In order to further promote development of apps, in inter-urban Full Truck Load of long-distance transport, sufficient number of users and suitable matching conditions ensured carriers schedule an order to guarantee the return pick-up at an appointed time or grab several orders to achieve a larger non-empty return trip. In this Balways-laden^transport plan, consideration should be given to the carriers' search and waiting costs before starting the next freight service. Meanwhile, route planning of delivery & collection based on real-time traffic information in Less-thanTruck Load required sharing high-level of data, complicatedadaptable models and the efficient computing power. These valuable aspects would be a great challenge for follow-up development of freight apps in aiding CO 2 emission reduction.

Information and communication technologies, road freight transport, and environmental sustainability

“…To our knowledge, few articles have been using an empirical methodology to demonstrate the impacts of ICTs in reducing environmental damages of road freight transport. (Button et al, 2001;Giannopoulos, 2004;McKinnon, 2011;Mahmoudzadeh & Fathabadi, 2011;Wang et al, 2015;Li & Yu, 2017;Santos, 2017).…”

Digitalization of transport and logistics services in russian agriculture

“…• ensure efficient loading and eliminate idle runs of vehicles, which gives not only an economic effect, but also reduces emissions into the atmosphere (MATANTSEVA et al, 2018;LI et al, 2017).…”

An Adaptive Parameter Controlled Ant Colony Optimization Approach for Peer-to-Peer Vehicle and Cargo Matching

“…integration platform for vehicles and cargos and the creation of reasonable vehicle-cargo assignments. By sharing vehicle and cargo resources, such a logistics service platform has become an important means of improving transport efficiency and reducing transport costs [3]- [6].…”

“…Due to the complexity of the real logistics activities, a one-to-one matching solution may not be completed smoothly, leading to the failure of some vehicle-cargo matches. Therefore, from the unilateral point of view of a vehicle driver or cargo owner, recommending multiple suitable cargo or vehicle sources according to certain rules can expand the choice space of both sides and improve the matching rate, which is called one-to-many matching [3]. However, one-to-many matching cannot recommend multiple vehicle and cargo sources for both drivers and shippers simultaneously.…”