Web data scraping for modelling road freight transport

This paper presents a case study on the use of secondary road freight transport negotiation data for determining the marginal cost of requests for pallet road transport in Australia. This is the first step for designing a revenue management (RM) system for road freight transport. Secondary data analysis provides essential insights into an industry where primary data collection is difficult. Data from www.truckit.net was mined using a small specially designed Java program. A mixed-methods approach was then applied to understand the qualitative information regarding the bids, to identify patterns for freight transport, and to predict costs for palletised transport. The results suggest three types of consignments with slightly varied predictors of the bidding price. Although traditionally the companies have used a system based on cost per km, many other factors (type of customer, distance/time, flexibility) could be easily incorporated in the bidding model, to increase the chance of winning the bids. A common finding from both qualitative and quantitative analyses is that the unloading conditions and flexibility of the requests primarily affects bidding prices for intrastate and residential shipments.


  • English

Media Info

  • Pagination: 15p

Subject/Index Terms

Filing Info

  • Accession Number: 01676248
  • Record Type: Publication
  • Source Agency: ARRB
  • Files: ITRD, ATRI
  • Created Date: Jul 26 2018 10:46AM