Abstract

This paper proposes a dynamic agent-based model (TRANSOPE) to simulate outsourcing among transport companies where, for the first time, accumulated knowledge is included as a variable to select service providers. The model consists of two main procedures. Firstly, the model simulates the decision-making of the professionals that contract transport service providers and the formation of outsourcing chains. Secondly, the model simulates the direct learning of participating companies and the transfer of knowledge towards their environment. Imperfect competition is replicated in three different scenarios, which involve the demand for transport services, regional distances and the intensity of knowledge transfer. The model is based on expert consultations and a survey conducted in an environment with a high concentration of transport companies in the Basque Country, Spain. The results indicate significant imbalances in the distribution of outsourcing, particularly in situations of low transport service demand, where 30% of transport companies do not secure any contracts. However, such situations led to strong regional interdependence. The dynamics of outsourcing reveals that over 75% of the contracted companies participate in all simulated scenarios from the first day. A strong hierarchy is also observed in the network, where certain transport companies act as connector hubs (with z-score values higher than 2.5 and participation coefficient values between 0.3 and 0.75), indicating a greater capacity for interaction and leadership in the transfer of knowledge. This feature allows the collaboration network to be identified as a scale-free network. The model has a low computational cost since the distances between agents remain constant. Finally, the formalisation of outsourcing decision-making in the model underpins its validity in forecasting the conduct of a freight transport system under shifting scenarios.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.