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Application of Multiple Imputations to Freight Transportation Survey Data: A Case Study of Commodity Flow Survey

Author(s): Terdsak Rongviriyapanich | Akachut Suppiyatrakul

Journal: American Journal of Engineering and Applied Sciences
ISSN 1941-7020

Volume: 4;
Issue: 3;
Start page: 363;
Date: 2011;
Original page

Keywords: Commodity flow survey | Multiple Imputation (MI) | Missing Completely At Random (MCAR) | shipment weight

Problem statement: Freight transportation data was indispensable input to transportation planning. In Thailand, efforts had been put to collect freight movement data by conducting road side survey and commodity flow survey. The result of these surveys did not produce consistent volume of shipment due to limited sampling coverage and non-response. Nevertheless, freight distribution patterns, which were derived from these surveys, were favorably consistent with each other. Approach: The objective of this study was propose an approach to improving quality of the commodity flow survey data in terms of total shipment weight. Our scope of study is limited to consumer goods and food stuffs. Multiple imputation was performed to correct non-response. The shipment weight was again adjusted by taking into account of the probability of no shipment in a particular quarter. Results: Comparison between the adjusted weight and road side survey data showed that the discrepancies in total weight of significantly reduced. Conclusion: Total shipment weights of the CFS after the adjustments were compared to those of road side survey. Plausible result was obtained for the case of consumer goods, while that of food stuffs was still notably different.
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