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Workplace travel plans: can they be evaluated effectively by experts?

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  • Thomas Vanoutrive

Abstract

Employers are regularly involved in transport planning and characteristic workplace-oriented tools include: (1) travel plans for building projects, (2) mandatory travel plans, (3) subsidies to employers with an advanced travel plan and (4) best travel plan awards. In all cases, experts judge the level of car use. We argue that decision-makers might benefit from a multiple regression-based benchmark modelling tool that estimates the expected share of the car. In this paper, we estimate the share of car users in the commuting modal split at workplaces. However, since the amount of information available to experts differs, we gradually add information to the model to measure the impact of data availability. Without historic data on modal split, the current share can only be predicted moderately well, i.e. within a 20% range. Besides adding the past, results improve by using homogenous and regional subsamples. Nevertheless, quantitative analyses do not make expert knowledge obsolete.

Suggested Citation

  • Thomas Vanoutrive, 2014. "Workplace travel plans: can they be evaluated effectively by experts?," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(8), pages 757-774, December.
    • Handle: RePEc:taf:transp:v:37:y:2014:i:8:p:757-774
    DOI: 10.1080/03081060.2014.959356
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    1. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    2. Hwang, Keith & Giuliano, Genevieve, 1990. "The Determinants of Ridesharing: Literature Review," University of California Transportation Center, Working Papers qt0gd0d2fj, University of California Transportation Center.
    3. Hwang, Keith & Giuliano, Genevieve, 1990. "The Determinants of Ridesharing: Literature Review," University of California Transportation Center, Working Papers qt3r91r3r4, University of California Transportation Center.
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    1. François Sprumont & Ariane Scheffer & Geoffrey Caruso & Eric Cornelis & Francesco Viti, 2022. "Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    2. Chen, Peng & Yang, Xiankui, 2023. "Revisit employer-based travel demand management: A longitudinal analysis," Transport Policy, Elsevier, vol. 131(C), pages 22-31.

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