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Tourism exerts a great effect on the modern economy and relies largely on the flow of people facilitated by high-quality transportation infrastructure. Applying a spatial econometric method, this paper investigates the effect of high-speed rail (HSR) on tourism expansion in China from the view of the spatial spillover effect. Based on a 276 Chinese cities’ panel dataset over 2005–2019, a positive role of HSR in tourism expansion is observed. Compared with cities unconnected to the HSR network, cities accessible by HSR experienced a 22% increase in tourism revenue and a 38% rise in tourist arrivals. In addition, the connection of a city to the HSR network also exerts a great spatial spillover role in the increase of tourism revenue and arrivals in peripheral cities which are not directly connected by HSR. The research findings offer important insights on the relationship between transportation infrastructure and tourism with significant policy implications regarding tourism development. [ABSTRACT FROM AUTHOR]

While facing the needs for Vehicle Infrastructure Integration (VII) applications in traffic management, the paper deals with the problem of locating Road Side Units (RSU) for VII deployment. After analyzing the difference between traditional problems of locating traffic information detector and the problem of RSU location, a significance ranking model for RSU localization and three kinds of Significance Degree (SD) computing strategies are put forward. A VII simulation environment for the purpose of RSU localization optimization within VISSIM microscopic traffic simulation software is established developing add-on functions using VISSIM's Component Object Model (COM). A VII test bed of the Olympic Park network in Beijing is taken as an example to evaluate the performance of RSU localization model. The results of simulation experiments indicate that the mixed SD strategy considering both speed and route monitoring is superior to the other two SD strategies. Then, the impact of RSU number and OBE market penetration rate on the evaluation measures of traffic monitoring are studied with reference to the proposed mixed SD strategy. In this case, the evaluation measures of optimized RSU configurations generated by the ranking algorithm are always better than those of random RSU configurations. In addition, the benefits of optimized RSU configurations increase along with RSU number and market penetration rate while the benefits of random RSU configurations are more fluctuant. [ABSTRACT FROM PUBLISHER]

Although the Internet of Things (IoT) has aroused much interest as a potential approach for improving various construction activities, the extent of its adoption remains limited. The multiple barriers that prevent the wider adoption of IoT in the construction industry need detailed investigation. However, limited research has attempted to understand the barriers to IoT adoption. Therefore, this study aims to identify the critical barriers to IoT adoption in the construction industry and explore the prioritization and hierarchical structure of the barriers factors. Data were collected from relevant literature and feedback from Chinese industry experts, sixteen barriers against IoT adoption were identified and categorized based on the TOE framework assessed in the construction industry. An integrated interpretation structure model and decision-making and trial evaluation laboratory (ISM-DEMATEL) approach is adopted to analyze the interdependence between identified constructs and their intensities. In addition, the identified constructs are also clustered into a suitable group using MICMAC analysis. Results show that inadequate infrastructure, lack of governance, and top management support are the fundamental barrier against IoT adoption. By revealing the mutual relationships and interlinking of barriers, this study will help researchers and practitioners in the construction industry to focus on strategic efforts to overcome these obstacles to effective IoT implementation. This research revealed the barriers to IoT implementation in the Chinese construction industry. Also, it provides methodological tool references for exploring the impact factor of other similar innovative technology applied in this industry. [ABSTRACT FROM AUTHOR]

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We employ the difference-in-difference and synthetic control methods to investigate the capitalization effect of hosting the G20 Summit on land market, based on China's land transaction dataset from 2011 to 2019. We find that hosting the G20 Summit has a significant positive effect on land prices in the host city, increasing land prices by over 22.6% compared to comparable cities. The impact of hosting the G20 Summit on land prices is larger in the post-G20 period than in the preparation period. Further, hosting the G20 Summit has heterogeneous and distributional effects on land prices. The capitalization effects of venue construction and transportation infrastructure upgrading on land prices are the main channels. [ABSTRACT FROM AUTHOR]