Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making
Freight transportation plays an increasingly important role in sustainable development. However, freight travel demand has not been understood comprehensively, due to its unique features: freight activities are the result of collaboration among freight agents. It distinguishes freight transportation...
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doaj-26c4020593234228b16aef4d06e2eaf82020-11-25T02:02:28ZengMDPI AGSustainability2071-10502020-05-01123636363610.3390/su12093636Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision MakingDapeng Zhang0Xiaokun (Cara) Wang1Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USADepartment of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USAFreight transportation plays an increasingly important role in sustainable development. However, freight travel demand has not been understood comprehensively, due to its unique features: freight activities are the result of collaboration among freight agents. It distinguishes freight transportation from passenger transportation, in which travel decisions are made mostly by individuals. Specifically, two processes in the collaboration can be observed: partner selection and joint decision making. Using the supplier-customer collaboration as an example, partner selection is a process for suppliers and customers to evaluate their potential partners and select the best one. Joint decision making allows suppliers and customers to seek common interests and make compromises. As a traditional travel demand model cannot model the two processes effectively, this research develops an innovative econometric model, spatial matching model, to bridge the gap. The proposed model is specified based on freight agents’ behavioral, estimated by Bayesian MCMC methods, and demonstrated by numerical examples. The proposed model and estimation methods can recover the coefficient values in the econometric models, and establish the relationship between the influential factors and the observed matching behavior. The analysis improves the understanding of freight travel demand in a behavioral-consistent manner and enriches the body of freight demand modeling literature.https://www.mdpi.com/2071-1050/12/9/3636joint decision makingfreight transportationpartner selectionBayesian MCMCeconometric modeling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dapeng Zhang Xiaokun (Cara) Wang |
spellingShingle |
Dapeng Zhang Xiaokun (Cara) Wang Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making Sustainability joint decision making freight transportation partner selection Bayesian MCMC econometric modeling |
author_facet |
Dapeng Zhang Xiaokun (Cara) Wang |
author_sort |
Dapeng Zhang |
title |
Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making |
title_short |
Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making |
title_full |
Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making |
title_fullStr |
Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making |
title_full_unstemmed |
Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making |
title_sort |
investigation of freight agents’ interaction considering partner selection and joint decision making |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-05-01 |
description |
Freight transportation plays an increasingly important role in sustainable development. However, freight travel demand has not been understood comprehensively, due to its unique features: freight activities are the result of collaboration among freight agents. It distinguishes freight transportation from passenger transportation, in which travel decisions are made mostly by individuals. Specifically, two processes in the collaboration can be observed: partner selection and joint decision making. Using the supplier-customer collaboration as an example, partner selection is a process for suppliers and customers to evaluate their potential partners and select the best one. Joint decision making allows suppliers and customers to seek common interests and make compromises. As a traditional travel demand model cannot model the two processes effectively, this research develops an innovative econometric model, spatial matching model, to bridge the gap. The proposed model is specified based on freight agents’ behavioral, estimated by Bayesian MCMC methods, and demonstrated by numerical examples. The proposed model and estimation methods can recover the coefficient values in the econometric models, and establish the relationship between the influential factors and the observed matching behavior. The analysis improves the understanding of freight travel demand in a behavioral-consistent manner and enriches the body of freight demand modeling literature. |
topic |
joint decision making freight transportation partner selection Bayesian MCMC econometric modeling |
url |
https://www.mdpi.com/2071-1050/12/9/3636 |
work_keys_str_mv |
AT dapengzhang investigationoffreightagentsinteractionconsideringpartnerselectionandjointdecisionmaking AT xiaokuncarawang investigationoffreightagentsinteractionconsideringpartnerselectionandjointdecisionmaking |
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