## 5 Expert Opinion and Feedback on a Practical Railway System  
While this study takes a long-term socio-economic perspective and analyses through efficient novelty models, it also includes expert reviews of the study's conclusions to assist in putting this critical input into effect. Our professional opinion is acquired in compliance with EU data protection law (GDPR). A total of 30 global HSR experts (or six specialists from each network) have participated, including academia, industry and research expertise. They must have experience of at least 15 years and currently hold at least one position connected to the railway sector. Participants must know at least one of the listed rail networks. Each participant can also select only the networks that best reflect their experience. Before participating, they must read through the in-depth network's data analysis, in Figures 3-7. At any point during the survey, the participant may refuse to participate or leave blank any questions they do not wish to answer. The expert responses were scored using a five-point Likert scale, with 1 indicating'strongly disagree' and 5 indicating'strongly agree'. The overall results for expert agreement with the data analysis for each rail network, as shown in Figure 9. The average score for experts on the CR, SNCF, Korail, and Renfe networks ranges up to 4.8, equivalent to levels of agreement with our judgements ranging from 'agree' to'strongly agree'. In comparison, the score from the JR central network's experts is 3.2, indicating that they neither oppose nor agree with the JR central system's interpretation. Note that one of them has claimed that the JR central network has improved Japanese factors for many decades. Nevertheless, the services have been affected by the disturbance to the Japanese society caused by multiple waves of the COVID-19 pandemic. The response also contained a section on effective policy goals for sustainability, each of which was also assessed on a Likert scale from one to five points. The selected policy goals are: (i) Connecting to various modes of public transportation hubs; (ii) providing access to important cities; (iii) offering reduced or special tickets; (iv) increasing the social value of areas next to HSR stations; (v) connecting business districts and tourist attractions; (vi) offering ticket rates that are reasonable; (vii) extending the validity of early and late tickets; (viii) expanding commercial districts next to HSR stations. It is inevitable that all eight factors support both social and economic impacts from HSR services, and are necessary for the development of a HSR system. Nevertheless, there is a differentiation in the background effects of the different networks on the proposed policy implications. Table 5 represents the overall average results of the opinion and feedback from 30 global experts. For promoting socio-economic impacts of HSR networks, 'connecting to major cities', with an average score of 4.8, is the highest priority for an application to rail services. Many experts believe that a seamless and broad connection is the most important factor in enhancing socio-economic impacts for all population groups. In addition, 'Connecting to various modes of public transportation or transportation hubs', 'Offering reduced or special tickets, and 'Connecting business districts and tourist attractions' are also necessary factors to drive HSR network. Nevertheless, the priorities for policy implications should follow a network's internal conditions and background. The comparison of mean value for policy implications of each network is shown in Figure 10. In comparison with other techniques, expert feedback has advantages in precisely revealing practical methods to use with specific networks.