Meizhu Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Meizhu Wang has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Zhongzhong Zeng
School of Architecture, Beijing Jiao Tong University, Haidian District, Beijing 100044, China
2 shared publications - Bo Zhang
Department of Horticulture and Landscape Architecture, Oklahoma State University, Stillwater, OK 74075, USA
1 shared publication - Dingyi Liu
School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
1 shared publication - Na Wang
SWA Group, 712 Main St., Floor 6, Houston, TX 77002, USA
1 shared publication - Xiayuanshan Gao
Department of City and Regional Planning, University of Pennsylvania, 3400 Walnut St, Philadelphia, PA 19104, USA
1 shared publication - Xuan Yu
School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
1 shared publication
Latest Publications
- Open Access
- 7 June 2024
- Published by MDPI AG in Sustainability
- Vol. 16 (12) , 4881
Exploring Passenger Satisfaction in Multimodal Railway Hubs: A Social Media-Based Analysis of Travel Behavior in China’s Major Rail Stations
This study investigates the dynamics of passenger satisfaction and sustainable urban mobility within the context of multimodal railway hubs, focusing on travel behaviors at major stations in China. Against the backdrop of rapid urbanization and the nation’s initiatives to improve transportation efficiency, this research employs social media data analysis to assess passenger sentiment across six key transportation hubs in Eastern China. Utilizing methodological approaches such as keyword frequency analysis and semantic categorization of 39,061 Dianping reviews, supplemented by network visualizations with Gephi, this study reveals insights into factors influencing passenger satisfaction beyond travel efficiency. Signage quality, facility availability, queueing, and crowding emerge as significant determinants of passenger behavior. The study underscores the importance of strategic improvements in station design, navigational aids, and facility management, grounded in real-time data analytics and passenger feedback, to enhance overall passenger satisfaction and promote sustainable urban mobility. This research contributes to advancing understanding of passenger behavior and informs efforts aimed at improving urban transportation systems to meet the evolving needs of passengers and cities.
- 7 June 2024
- Published by MDPI AG in Sustainability
- Vol. 16 (12) , 4881
Open AccessExploring Passenger Satisfaction in Multimodal Railway Hubs: A Social Media-Based Analysis of Travel Behavior in China’s Major Rail Stations
This study investigates the dynamics of passenger satisfaction and sustainable urban mobility within the context of multimodal railway hubs, focusing on travel behaviors at major stations in China. Against the backdrop of rapid urbanization and the nation’s initiatives to improve transportation efficiency, this research employs social media data analysis to assess passenger sentiment across six key transportation hubs in Eastern China. Utilizing methodological approaches such as keyword frequency analysis and semantic categorization of 39,061 Dianping reviews, supplemented by network visualizations with Gephi, this study reveals insights into factors influencing passenger satisfaction beyond travel efficiency. Signage quality, facility availability, queueing, and crowding emerge as significant determinants of passenger behavior. The study underscores the importance of strategic improvements in station design, navigational aids, and facility management, grounded in real-time data analytics and passenger feedback, to enhance overall passenger satisfaction and promote sustainable urban mobility. This research contributes to advancing understanding of passenger behavior and informs efforts aimed at improving urban transportation systems to meet the evolving needs of passengers and cities.
- Open Access
A Semantic Analysis Method of Public Public Built Environment and Its Landscape Based on Big Data Technology: Kimbell Art Museum as Example
Based on big data, a new public space evaluation method is proposed. Using programming technology to collect visitor reviews from the travel website TripAdvisor to build a database, based on the data of 99,240 words in 1573 visitor reviews in 10 years, the connection between data and reality is established through systematic data classification and visualization. Following an assessment of the Kimbell Art Museum’s functionality, architectural design, and landscape design, along with visitor feedback, a new evaluation methodology was formulated for application to public buildings with landscapes. By utilizing the unique advantages of big data, it provides convenient and efficient analysis methods for public spaces with similar data foundations and opens the way for the optimization of the built environment in the information age.
Open AccessA Semantic Analysis Method of Public Public Built Environment and Its Landscape Based on Big Data Technology: Kimbell Art Museum as Example
Based on big data, a new public space evaluation method is proposed. Using programming technology to collect visitor reviews from the travel website TripAdvisor to build a database, based on the data of 99,240 words in 1573 visitor reviews in 10 years, the connection between data and reality is established through systematic data classification and visualization. Following an assessment of the Kimbell Art Museum’s functionality, architectural design, and landscape design, along with visitor feedback, a new evaluation methodology was formulated for application to public buildings with landscapes. By utilizing the unique advantages of big data, it provides convenient and efficient analysis methods for public spaces with similar data foundations and opens the way for the optimization of the built environment in the information age.