Recently, there has been a lot of buzz on social media, particularly in the form of vlogs, about newly launched semi-high speed trains in India popularly known as Vande Bharat Express. However, no information is available about the extent to which people trust the vlogs promoting the trains and the trains themselves. Therefore, this research aims to investigate the impact of watching vlogs about semi-high speed trains on the trust and attitude towards them, and how they perceive the risks associated. This study is guided by the trust transfer theory to investigate how trust transference can lead to a traveler’s intent to use semi-high speed trains. This study involved 338 participants. The relationship between variables was examined using SmartPLS 4 software. The findings indicate that trust in semi-high speed trains can be established through vlogs leading to intention to use. On the theoretical side, it provides insight into how trust, attitude, and perceived risk can affect the adoption of new technology, while on the practical side, it helps to understand how vlog coverage can be used as a tool to increase trust and ultimately drive adoption. Vlog coverage, trust in vlog content, trust in semi-high speed trains and behavioural intention altogether are not well understood in current literature despite the important implication for managers, academicians and consumers alike. This study contributes to the field of transportation and railways, social media and communication, and hospitality and tourism research. The study helps policy makers to understand users’ characteristics regarding the latest social media tools and adopt them accordingly to provide a better governance policy.

Using data from 31 provinces, municipalities, and autonomous regions in mainland China from 2006 to 2019, we employ a double difference (DID) model and a spatial double difference (SDID) model to estimate the impact of the High-speed Railway (HSR) on the income gap between urban and rural residents, as well as its spatial spillover effects. Our research reveals several key findings. Firstly, the introduction of high-speed railways helps to narrow the income gap between urban and rural residents within local areas, but its spatial effects can lead to an increase in the income gap in neighboring provinces. Secondly, from a spatial perspective, intermediate variables such as industrial structure, education, science and technology, and foreign trade can also contribute to balancing the income gap between urban and rural residents, although the impact of population mobility is not significant. Thirdly, further analysis of the spatial effects demonstrates that education plays a significant role in balancing the income gap both within the local province and neighboring provinces. Additionally, adjustments in industrial structure, advancements in science and technology, and foreign trade have stronger spillover effects in reducing the income gap among neighboring provinces compared to their impact at a local level.

In this paper advanced Sentiment Analysis techniques were applied to evaluate public opinions reported by rail users with respect to four major European railway companies, i.e., Trenitalia and Italo in Italy, SNCF in France and Renfe in Spain. Two powerful language models were used, RoBERTa and BERT, to analyze big amount of text data collected from a social platform dedicated to customers reviews, i.e., TrustPilot. Data concerning the four European railway companies were first collected and classified into subcategories related to different aspects of the railway sector, such as train punctuality, quality of on-board services, safety, etc. Then, the RoBERTa and BERT models were developed to understand context and nuances of natural language. This study provides a useful support for railways companies to promote strategies for improving their service.