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ID: 156 / D1S1T2: 1 Full Paper LDIC Submission LDIC 2022 Topics: Digitalization, Shared Economies and Supply Chain Management, Multi-modal and Maritime Logistics Keywords: collaboration, supply chain, digital platform, transport logistics, maritime transportation, inter-organizational information systems
An inter-organizational digital platform for efficient container transportation
Teucke, Michael Christoph1; Broda, Eike2; Freitag, Michael1,2
1BIBA - Bremer Institut für Produktion und Logistik GmbH, Germany; 2University of Bremen, Faculty of Production Engineering
Maritime container transport is the backbone of international trade and supply and distribution processes in global manufacturing networks. However, the level of digital support of container transportation is still lacking, compared to other fields. This article shows how an inter-organizational digital platform can facilitate the digital interaction between industry and logistics stakeholders. It describes four processes where the platform can support transactions between shippers, carriers, and other stakeholders involved in transportation pro-cesses. Use of the digital platform can decrease waiting times for process-related documentation and reduce effort, duplication of tasks and inaccuracies, directly increasing the performance and resilience of customers and providers of transportation services.
ID: 115 / D1S1T2: 2 Full Paper LDIC Submission LDIC 2022 Topics: Digitalization, Shared Economies and Supply Chain Management, Sustainable and Green Logistics Keywords: Dynamic Ridesharing, Blockchain Technology, Sustainability.
SRP: a Sustainable Dynamic Ridesharing Platform Utilizing Blockchain Technology
With the growing carbon-di-oxide (CO2) emissions and road vehicles being re-sponsible for almost 75% of the emissions, it is imperative to put in efforts to re-duce CO2, especially in the transportation sector. Ridesharing services enable us-ers to use cars more wisely by filling the vacant spaces with passengers having similar itineraries and time schedules. However, most of the ridesharing services are dependent on a third party for the interaction between the riders and drivers. Relying on a third party and central server can turn out to be expensive since a commission is charged by the third-party; risky since it is more prone to going down and malicious attacks; might not lead to the most appropriate matches; and in case the security of the service provider is not protected and jeopardized, there are high chances of the service being disturbed and the data of the users being disclosed or tampered with. This paper has proposed SRP-A sustainable rides-haring platform that replaces the third party/central server by Blockchain technol-ogy. This platform makes use of Blockchain’s capabilities such as consensus mechanism (Proof of Stake); smart contracts; and solvers, making the entire sys-tem more secure and less prone to attacks along with tackling the issue of exces-sive emissions of CO2 in the environment.
ID: 102 / D1S1T2: 3 Full Paper LDIC Submission LDIC 2022 Topics: Artificial Intelligence, Big Data and IT Platforms Keywords: Contract logistics, Third-party logistics, process planning, supervised learn-ing, n-gram, decision tree
Using supervised learning to predict process steps for process planning of third-party logistics
1BIBA - Bremer Institut für Produktion und Logistik; 2University Bremen, Faculty of Production Engineering
There is intense competitive pressure in the third-party logistics industry. As a result, logistics providers have to respond to tenders quickly and with convincing concepts. This article shows how logistics process planning in tender management can be accelerated using methods of supervised learning. Under the premise that similar processes from past projects can be transferred and adapted to a new project, an assistance system suggests appropriate process steps in the form of MTM (methods-time measurement) codes to the planner using N-Gram analysis and a decision tree. This procedure accelerates the process planning and can lead to an increase in the quality of the planned logistics processes.