This study develops integrated evaluation indicators for demand responsive transport (DRT) operation services from a road traffic service perspective. The purpose is to support sustainable and efficient DRT service provision by considering the perspectives of users, operators, and local communities, while also reflecting road-based operational issues such as pick-up/drop-off management, curbside stopping, transfer-node linkage, and parking-demand reduction. While previous evaluations have often focused on operational efficiency, platform performance, ridership records, or user satisfaction, this study attempts to establish a comprehensive framework applicable to various DRT service types. DRT services were classified into four types according to temporal and spatial variability: shuttle-bus type, pre-call reservation type, real-time call reservation type, and dynamic call reservation type. Candidate evaluation indicators were derived through reviews of domestic and international DRT operation cases, public transport service-quality studies, MaaS performance studies, accessibility and equity evaluation studies, and existing evaluation practices. An analytic hierarchy process (AHP) survey was conducted with experts from research institutes, local governments, public agencies, and academia to identify the relative importance of indicators. The results indicate that convenience of booking methods and user satisfaction are mandatory common indicators for all DRT types. Safety, barrier-free service provision, driver courtesy and professionalism, revenue per operating cost, and operation time were identified as optional common indicators. In addition, arrival information change rate, changes in the number of users, operation distance, ride distance, service utilization rate, and parking space saving effect were suggested as type-specific indicators. The proposed indicators can support integrated monitoring of DRT operation services and provide practical information for service improvement, policy decisions, efficient public subsidy support, and road-space management.

This study develops a comprehensive road operation evaluation model that integrates the perspectives of three principal stakeholders: road users prioritizing congestion mitigation, operators emphasizing investment efficiency, and policymakers advocating broader societal goals such as carbon reduction. The analysis database was constructed using traffic data obtained from reliable sources, including the Korea Transport Institute's Big Data Center and Suwon City's Urban Safety Integration Center. Binary logistic regression was employed to identify the factors influencing traffic congestion from the users’ perspective, whereas multiple linear regression models were used to analyze road investment efficiency from the operators’ viewpoint and carbon dioxide emissions from the policymakers’ standpoint. Statistical analyses were conducted on 4,322 road segments in Suwon City, with each evaluation criterion assigned an equal weight of 33.3 points in a unified 100-point scoring system. The analysis identified 15 statistically significant indicators affecting the three evaluation criteria, with the resulting models demonstrating strong explanatory power, evidenced by adjusted R² values of 0.197, 0.593, and 0.544 for traffic congestion, road investment efficiency, and carbon dioxide emission models, respectively. A volume-to-capacity (V/C) ratio of 0.64 was determined to represent the optimal balance point at which the requirements of all stakeholder groups align. When applied to Suwon City's arterial road network, the model identified 248 high-congestion segments (53.13 km), 203 segments with low investment efficiency (26.8 km), and 357 segments with high carbon emissions (156.33 km), each requiring targeted operational improvements. The proposed model addresses the limitations of existing single-stakeholder evaluation frameworks by offering transportation authorities a systematic and multi-dimensional approach to road operation assessment.