There have been many implementations of carbon credit incentives (CCIs) for promoting green travel, but research on quantifying the effectiveness remains limited. To fill this gap, this study focuses on residents’ daily transportation mode choices under the incentive of carbon credits by employing an integrated choice and latent variable (ICLV) model to adequately address the role of attitudinal variables related to carbon credits, such as perceived usefulness, perceived ease of use, and behavioral intentions. Data from a questionnaire survey show that the ICLV model provides a richer and more nuanced understanding of the green mode choice than a traditional multinomial logit (MNL) model, where the AIC value of the ICLV model (3901.17) is smaller than that of the MNL model (3910.09). Carbon credits exhibit diverse impacts across various modes of eco-friendly transportation and specific demographic groups. Commuting trips reveal noteworthy positive associations between carbon credits and the use of bicycles as well as metro/bus services. Moreover, carbon credits exert a more pronounced influence on individuals with higher education levels, older age groups, and owners of new energy vehicles, whereas their impact on high-income individuals is relatively constrained. Furthermore, perceptions of carbon credits are pivotal, with perceived utility emerging as the most influential factor. The results provide a scientific basis for formulating more effective policies regarding carbon credit and incentive measures in the future.