Modelling the competitiveness of the ports along the Maritime Silk Road with big data

Peng, Peng; Yang, Yu; Lu, Feng; Cheng, Shifen; Mou, Naixia; Yang, Ren

doi:10.1016/j.tra.2018.10.041

“…For instance, transportation agencies collect bicycling and pedestrian volume data sparingly, if at all, creating a challenge for understanding relative safety risks (Piwek et al 2015). Big data also supports new approaches for managing freight modes, including maritime shipping (Peng et al 2018). Big data sets such as online street-level imagery can potentially be used for collecting pedestrian volumes, but do not currently include time-of-day information to support scaling over known time periods (Yin et al 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Mitigating Bias in Big Data for Transportation

Griffin

¹

,

Mulhall

²

,

Simek

³

et al. 2020

J. Big Data Anal. Transp.

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Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognise that big data from mobile phones, social media, and on-board vehicle systems include biases in representation and accuracy, related to transportation safety statistics. This study examines both the sources of bias and approaches to mitigate them through a review of published studies and interviews with experts. Coding of qualitative data enabled topical comparisons and reliability metrics. Results identify four categories of bias and mitigation approaches that concern transportation researchers and practitioners: sampling, measurement, demographics, and aggregation. This structure for understanding and working with bias in big data supports research with practical approaches for rapidly evolving transportation data sources.

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“…For instance, transportation agencies collect bicycling and pedestrian volume data sparingly, if at all, creating a challenge for understanding relative safety risks (Piwek, Joinson, & Morvan, 2015). Big data also supports new approaches for managing freight modes, including maritime shipping (Peng et al, 2018). Big datasets such as online street-level imagery can potentially be used for collecting pedestrian volumes, but do not currently include time-of-day information to support scaling over known time periods (Yin, Cheng, Shao, Wang, & Wu, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Mitigating Bias in Big Data for Transportation

Griffin

¹

,

Mulhall

²

,

Simek

³

et al. 2020

Preprint

View full text Add to dashboard Cite

Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognise that big data from mobile phones, social media, and on-board vehicle systems include biases in representation and accuracy, related to transportation safety statistics. This study examines both the sources of bias and approaches to mitigate them through a review of published studies and interviews with experts. Coding of qualitative data enabled topical comparisons and reliability metrics. Results identify four categories of bias and mitigation approaches that concern transportation researchers and practitioners: sampling, measurement, demographics, and aggregation. This structure for understanding and working with bias in big data supports research with practical approaches for rapidly evolving transportation data sources.

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“…Since the beginning of the initiative, China has become the primary source of funding for many countries in the OBOR area. According to Peng et al, (2018), the most interesting ports are located in Mediterranean, Suez Canal and Hormuz Strait. The European ports that are located in the Mediterranean, Adriatic Sea and the Black Sea will have an important role in Maritime Silk Road.…”

Section: Figmentioning

confidence: 99%

The Influence of China to the Container Market in Europe

2019

IJTTE

0

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European economy, which has globally been one of the most important for centuries, greatly depends on maritime transshipment. According to the European Commission's data, 74% of cargo, which comes to or leaves Europe, uses maritime transport. Therefore, we can clearly see the importance of ports for economic growth. Over the past decades, containerized transport has become one of the most important ways for transporting cargo, so ports needed to adapt with the new equipment and better capacities. In 2000, the container traffic in EU ports represented as much as 21% of all transshipped containers in the world, while, this percentage was only 18% in Chinese ports. Today, China has become a leading country in the container throughput, with a share of 28%, while the EU's share has fallen to 15%.

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Modelling the competitiveness of the ports along the Maritime Silk Road with big data

Cited by 67 publications

References 26 publications

Mitigating Bias in Big Data for Transportation

Mitigating Bias in Big Data for Transportation

Mitigating Bias in Big Data for Transportation

The Influence of China to the Container Market in Europe

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