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Fu, Xingxing, Dea van Lierop, and Dick Ettema. 2023. “Multigroup Multimodality Index: A Method to Solve the Issue of Transport Mode Classification in Measuring Multimodality.” Findings, March. https://doi.org/10.32866/001c.72072.
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  • Figure 1. Classification of transport modes at two levels
  • Figure 2. Distributions of scores calculated by HHI, OM_PI and MMI
  • Figure 3. The relationship between the scores and the number of modes and groups


Recent methods to measure multimodality only consider the diversity and evenness of mode use, while ignoring that the classification of transport modes also matters. This study proposes a multigroup multimodality index to measure the extent of being multimodal at both single mode and mode group levels in a nested manner. The index is compared with the two most commonly used indices, the Herfindahl-Hirschman index and the Shannon Entropy index, to assess its reliability and improvement over existing approaches. Results show that the multigroup multimodality index can simultaneously distinguish the degree of being multimodal at both mode level and group level, which addresses the classification issue in measuring multimodality.

Accepted: February 24, 2023 AEST