Articles
TRANSPORTATION IN DEVELOPING ECONOMIES (21999287)(2)
This study investigates the impact of public transportation infrastructure on property values in Mashhad, Iran, utilizing a hedonic pricing model to analyze both commercial and residential sectors. The findings reveal that proximity to major transport hubs, specifically railway stations and terminals, significantly enhances property values, with commercial properties within 1000 m of these hubs commanding premiums of 29.8% and 25.6%, respectively. This underscores the critical role of transport accessibility in shaping the commercial real estate market. In contrast, metro stations and bus stops show no significant impact on commercial property values, likely reflecting the inadequacies of Mashhad's current public transportation system. In the residential sector, the influence of transport infrastructure varies by property type: apartment values increase by 19.5% and 13.3% in proximity to railway stations and terminals, while villas experience a 32.5% value boost per kilometer closer to a railway station. These results highlight the differentiated impact of transportation infrastructure on property types, emphasizing the particular importance of rail connectivity for higher-end residential properties. The study concludes with a call for targeted urban planning and policy interventions to modernize and expand Mashhad's public transportation network, making it more functional and attractive to a wider population, and suggests avenues for future research on additional urban factors influencing property values and the drivers of high-value commercial transactions.
Environmental Science and Pollution Research (09441344)30(12)pp. 33567-33586
The problem of traffic congestion and the environmental issues related to air pollution are among the essential problems of urban management that metropolitan cities are trying to mitigate. Given that the contribution of motor vehicles to air pollution is significant, both goals are achieved by managing urban transport. Among the various methods of travel demand management, congestion pricing is a very efficient measure. This study tried to simultaneously increase the efficiency of the transportation network and reduce the environmental effects by using a bi-level model for the multi-modal network. For this purpose, the upper-level model minimizes the objective function, i.e., pollution emission costs and overall commuting costs. The lower level also has a transportation network model that provides the condition of user equilibrium. The genetic and Frank-Wolfe algorithms have been used to solve the bi-level programming model. Two pricing schemes, cordon-based and link-based, are used to investigate and assist policymakers. The proposed algorithm is also applied to a real-world road network in Isfahan, Iran. The results of the proposed models for different pricing strategies were compared. According to the results, both pricing schemes mitigate traffic congestion and pollution, although the reduction in pollution outside the cordon is less than inside. Demand has also shifted from the private car mode to public transportation by an average of 15%. However, link-based pricing provides better performance than cordon-based pricing. This study indicated that a higher total collected toll in link-based pricing is accompanied by a sharper reduction in congestion and pollution mitigation, which can be spent on alternative facilities and infrastructure by the municipality, such as the development of public transportation and parking. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
