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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Pereira, M.T., Nuno Miguel Gabriel, Marisa João Guerra Pereira De Oliveira, Ramos, F.R. & André Guimarães (2025). Enhancing Third-Party Logistics Efficiency: A Digital Approach to Transport Costing. In Advances in Design, Simulation and Manufacturing VIII. (pp. 159-170).: Springer Nature.
Exportar Referência (IEEE) 
M. T. Pereira et al.,  "Enhancing Third-Party Logistics Efficiency: A Digital Approach to Transport Costing", in Advances in Design, Simulation and Manufacturing VIII, Springer Nature, 2025, pp. 159-170
Exportar BibTeX 
@incollection{pereira2025_1766371045089,
	author = "Pereira, M.T. and Nuno Miguel Gabriel and Marisa João Guerra Pereira De Oliveira and Ramos, F.R. and André Guimarães",
	title = "Enhancing Third-Party Logistics Efficiency: A Digital Approach to Transport Costing",
	chapter = "",
	booktitle = "Advances in Design, Simulation and Manufacturing VIII",
	year = "2025",
	volume = "",
	series = "",
	edition = "",
	pages = "159-159",
	publisher = "Springer Nature",
	address = "",
	url = "https://doi.org/10.1007/978-3-032-07144-6_14"
}
Exportar RIS 
TY  - CHAP
TI  - Enhancing Third-Party Logistics Efficiency: A Digital Approach to Transport Costing
T2  - Advances in Design, Simulation and Manufacturing VIII
AU  - Pereira, M.T.
AU  - Nuno Miguel Gabriel
AU  - Marisa João Guerra Pereira De Oliveira
AU  - Ramos, F.R.
AU  - André Guimarães
PY  - 2025
SP  - 159-170
DO  - 10.1007/978-3-032-07144-6_14
UR  - https://doi.org/10.1007/978-3-032-07144-6_14
AB  - Over time, organizations and their supply chains have adapted to constant global change by increasingly adopting digital technologies for optimization, operational efficiency, and competitive advantage. These technologies, which are part of digital transformation, automate manual and repetitive processes, optimize operations and reduce human error. In this project, a decision support model was developed using Python to optimize the current manual costing processes involving 62 Excel spreadsheets and related calculations to achieve efficiency in the transportation processes of Company X, a third party logistics provider. The model was evaluated for accuracy, monetary savings, and time efficiency compared to the manual process. The Design Science Research Methodology (DSRM) was chosen to structure this work. The project produced positive results, with three scenarios (pessimistic, realistic and optimistic) showing annual monetary savings of over €6,000 and time efficiency of over 86%. Despite minor limitations, the project successfully applied digital transformation to transport optimization and demonstrated significant time and monetary benefits to the organization.
ER  -