摘要：Purpose The purpose of this study was to investigate how a smart phone freight application service (Apps) could reduce CO2 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 CO2 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 CO2 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 CO2 emissions. However, when in urban Less-than-Truck Load, by strengthening the average vehicle utilization on laden trips, another determinant of route planning of delivery & collection reduced CO2 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 “always-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-than-Truck Load required sharing high-level of data, complicated-adaptable models and the efficient computing power. These valuable aspects would be a great challenge for follow-up development of freight apps in aiding CO2 emission reduction.
