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Amidst sudden and unprecedented increases in the severity and frequency of climate-change-induced natural disasters, building critical infrastructure resilience has become a prominent policy issue globally for reducing disaster risks. Sustainable measures and procedures to strengthen preparedness, response, and recovery of infrastructures are urgently needed, but the standard for measuring such resilient elements has yet to be consensually developed. This study was undertaken with an aim to quantitatively measure transportation infrastructure robustness, a proactive dimension of resilience capacities and capabilities to withstand disasters; in this case, floods. A four-stage analytical framework was empirically implemented: (1) specifying the system and disturbance (i.e., road network and flood risks in Chiang Mai, Thailand), (2) illustrating the system response using the damaged area as a function of floodwater levels and protection measures, (3) determining recovery thresholds based on land use and system functionality, and (4) quantifying robustness through the application of edge- and node-betweenness centrality models. Various quantifiable indicators of transportation robustness can be revealed; not only flood-damaged areas commonly considered in flood-risk management and spatial planning, but also the numbers of affected traffic links, nodes, and cars are highly valuable for transportation planning in achieving sustainable flood-resilient transportation systems.
Suchat Tachaudomdach; Auttawit Upayokin; Nopadon Kronprasert; Kriangkrai Arunotayanun. Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems. Sustainability 2021, 13, 3172 .
AMA StyleSuchat Tachaudomdach, Auttawit Upayokin, Nopadon Kronprasert, Kriangkrai Arunotayanun. Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems. Sustainability. 2021; 13 (6):3172.
Chicago/Turabian StyleSuchat Tachaudomdach; Auttawit Upayokin; Nopadon Kronprasert; Kriangkrai Arunotayanun. 2021. "Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems." Sustainability 13, no. 6: 3172.
Suchat Tachaudomdach; Kriangkrai Arunotayanun; Auttawit Upayokin. A systematic review of the resilience of transportation infrastructures affected by flooding. Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering 2018 on - APCIM & ICTTE 2018 2018, 176 -182.
AMA StyleSuchat Tachaudomdach, Kriangkrai Arunotayanun, Auttawit Upayokin. A systematic review of the resilience of transportation infrastructures affected by flooding. Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering 2018 on - APCIM & ICTTE 2018. 2018; ():176-182.
Chicago/Turabian StyleSuchat Tachaudomdach; Kriangkrai Arunotayanun; Auttawit Upayokin. 2018. "A systematic review of the resilience of transportation infrastructures affected by flooding." Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering 2018 on - APCIM & ICTTE 2018 , no. : 176-182.
Purim Srisawat; Nopadon Kronprasert; Kriangkrai Arunotayanun. Development of Decision Support System for Evaluating Spatial Efficiency of Regional Transport Logistics. Transportation Research Procedia 2017, 25, 4832 -4851.
AMA StylePurim Srisawat, Nopadon Kronprasert, Kriangkrai Arunotayanun. Development of Decision Support System for Evaluating Spatial Efficiency of Regional Transport Logistics. Transportation Research Procedia. 2017; 25 ():4832-4851.
Chicago/Turabian StylePurim Srisawat; Nopadon Kronprasert; Kriangkrai Arunotayanun. 2017. "Development of Decision Support System for Evaluating Spatial Efficiency of Regional Transport Logistics." Transportation Research Procedia 25, no. : 4832-4851.
This paper investigates the prevalence of observed and unobserved taste heterogeneity influencing shippers’ mode choice behaviour. The study is based on stated preference data collected in Java, Indonesia. The data were analysed using a mixed logit model, capable of accommodating random taste heterogeneity and panel effects associated with stated preference replications. The results indicate the presence of significant levels of taste heterogeneity, only some of which can be accounted for by conventional commodity-type based segmentations. The analysis goes on to apply latent class methods to identify behaviourally homogeneous segments, which also turn out to not depend on commodity types.
Kriangkrai Arunotayanun; John W. Polak. Taste heterogeneity and market segmentation in freight shippers’ mode choice behaviour. Transportation Research Part E: Logistics and Transportation Review 2011, 47, 138 -148.
AMA StyleKriangkrai Arunotayanun, John W. Polak. Taste heterogeneity and market segmentation in freight shippers’ mode choice behaviour. Transportation Research Part E: Logistics and Transportation Review. 2011; 47 (2):138-148.
Chicago/Turabian StyleKriangkrai Arunotayanun; John W. Polak. 2011. "Taste heterogeneity and market segmentation in freight shippers’ mode choice behaviour." Transportation Research Part E: Logistics and Transportation Review 47, no. 2: 138-148.