Influence of integrated multimodal travel information on commuter preferences and mode choice in urban areas

The growing dependence on private vehicles in Indian cities has intensified congestion and environmental challenges, underscoring the need for sustainable mobility solutions. This study examines how integrated multimodal travel information and targeted incentives influence commuter mode choice in Patna, India, a representative Tier-II city. Data were collected from 450 automobile users using a hybrid RP and SP survey design. Two SP scenarios were tested: real-time multimodal information (SP1) and information combined with incentives such as fare reductions, guaranteed seat availability, and dedicated bus lanes (SP2). Binary logit models show that service attributes including seat availability, travel time, travel cost, and access time significantly affect mode choice. Under SP1, 32% of respondents were willing to shift from private to public or shared transport, which increased to 44% under SP2 with incentives. Marginal effects indicate that small improvements in comfort and access can produce substantial behavioural shifts. The results suggest that combining real-time information systems with modest service-level enhancements can effectively reduce private vehicle dependence and support sustainable urban transport policies. The findings provide practical guidance for policymakers to design commuter-centric strategies that enhance public transport attractiveness and ease traffic congestion in Indian cities.