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  • Innovative methods in European road freight transport statistics : A pilot study

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    Herold234106.pdf (441.9Kb)
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    Accepted Manuscript (AM)
    Author(s)
    Fürst, Elmar
    Oberhofer, Peter
    Vogelauer, Christian
    Bauer, Rudolf
    Herold, David M
    Griffith University Author(s)
    Herold, David M.
    Year published
    2019
    Metadata
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    Abstract
    By using innovative methods, such as the automated transfer of corporate electronic data to National Statistical Institutions, official transport data can be significantly improved in terms of reliability, costs and the burden on respondents. In this paper, we show that the automated compilation of statistical reports is possible and feasible. Based on previous findings, a new method and tool were developed in cooperation with two business partners from the logistics sector in Austria. The results show that the prototype could successfully be implemented at the partner companies. Improved data quality can lead to more reliable ...
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    By using innovative methods, such as the automated transfer of corporate electronic data to National Statistical Institutions, official transport data can be significantly improved in terms of reliability, costs and the burden on respondents. In this paper, we show that the automated compilation of statistical reports is possible and feasible. Based on previous findings, a new method and tool were developed in cooperation with two business partners from the logistics sector in Austria. The results show that the prototype could successfully be implemented at the partner companies. Improved data quality can lead to more reliable analyses in various fields. Compared to actual volumes of investments into transport, the costs of transport statistics are limited. By using the new and innovative data collection techniques, these costs can even be reduced in the long run; at the same time, the risk of bad investments and wrong decisions caused by analyses relying on poor data quality can be reduced. This results in a substantial value for business, research, the economy and the society.
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    Journal Title
    Journal of Statistics and Management Systems
    DOI
    https://doi.org/10.1080/09720510.2019.1615676
    Copyright Statement
    © 2019 Taylor & Francis (Routledge). This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistics and Management Systems on 22 Jul 2019, available online: https://doi.org/10.1080/09720510.2019.1615676
    Note
    This publication has been entered into Griffith Research Online as an Advanced Online Version.
    Subject
    Transportation, logistics and supply chains
    Publication URI
    http://hdl.handle.net/10072/386521
    Collection
    • Journal articles

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