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This study investigates the personal and societal impacts of motorcycle ban policy on the home-to-work morning commute of motorcyclists using self-reported travel behavioral data and stated travel mode shift response under such policy collected in Foshan City, China. The policy aims to force all motorcyclists in the city to shift to walk, bike, bus, or car mode by 2020. The complex impacts of the policy on travel mode shifts are studied across population sub-groups defined by gender and residential status (migrants and residents). For model estimation, random parameters multinomial logit models with heterogeneity in parameter means and variances were estimated to better track unobserved heterogeneity compared to their counterpart models with fixed means and variances. Model estimation results show that contributing factors of travel mode shift response include individual and household sociodemographic …