Socioeconomic Benefits of the Shinkansen Network

High speed rail (HSR) networks have been an essential catalyst in stimulating and balancing regional economic growth that ultimately benefits the society as a whole. Previous studies have revealed that HSR services sustainably yield superior social values for people, especially for adults and those of working age. This has become an advantage of HSR networks over other forms of public transportation. The Shinkansen network in Japan is one of most successful HSR models. Its services bring significant social advantages to the communities it serves, such as shorter travel times and increased job opportunities. Nevertheless, the societal impact of HSR networks depends on many factors, and the benefits of HSR could also be overrated. The goal of this research is to measure the socioeconomic impacts of HSR on people of all genders and age groups. The outcomes could lead to more suitable development of HSR projects and policies. This study investigates data sets for Japanese social factors over 55 years in order to determine the impacts of HSR. The assessment model has been established using Python. It applies Pearson’s correlation (PCC) technique as its main methodology. This study broadly assesses social impacts on population dynamics, education, age dependency, job opportunities, and mortality rate using an unparalleled dataset spanning 55 years of social factors. The results exhibit that younger generations have the most benefits in terms of equal educational accessibility. However, the growth of the HSR network does not influence an increase in the employment rate or labour force numbers, resulting in little benefit to the workforce.

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.