A sensitivity analysis of freight transport forecasts for The Netherlands

Journal Article (2018)
Author(s)

M.A. de Bok (TU Delft - Transport and Planning)

Bart Wesseling (Significance)

Jan Kiel (Panteia)

Onno Miete (Ministry of Infrastructure and the Environment)

Jan Francke (KiM: Kennisinstituut voor Mobiliteitsbeleid )

Transport and Planning
Copyright
© 2018 M.A. de Bok, Bart Wesseling, Jan Kiel, Onno Miete, Jan Francke
DOI related publication
https://doi.org/10.19272/201806704003
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 M.A. de Bok, Bart Wesseling, Jan Kiel, Onno Miete, Jan Francke
Transport and Planning
Issue number
4
Volume number
45
Pages (from-to)
571-587
Reuse Rights

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Abstract

Strategic freight transport models can be used for a quantitative analysis of long term forecasts. This paper discusses an analysis of the bandwidth of freight transport forecasts for The Netherlands with the strategic freight transport model ‘BasGoed’. This model was developed over the past years as a basic model, satisfying the needs of policy making, based on proven knowledge and available transport data. Starting point for the analysis are the long-term scenarios for The Netherlands developed recently by CPB Netherlands Bureau for Economic Policy Analysis and PBL Netherlands Environmental Assessment Agency (WLO scenarios: Future outlook on welfare, prosperity and the human environment). The scenarios describe two base cases: The High and Low scenario. Both scenarios include a consistent set of assumptions on economic development (domestic growth by industry sector and international trade), infrastructure development, fuel prices, and logistic efficiency. The bandwidth of freight forecasts is further explored in five distinctive sensitivity analyses: different development in fuel prices, energy markets, CO2-pricing, dematerialization and modal shift in the port of Rotterdam. The sensitivity analysis provides more insight in the level of importance of each scenario assumption and it can be useful in estimating a bandwidth for freight transport demand. This is valuable in providing insight in the robustness of the freight transport forecasts for policy studies.

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