Sha Wang
Wuhan University
6 Papers
7 Citations
Sha Wang is an academic researcher from Wuhan University. The author has contributed to research in topics: Computer science & Structural equation modeling. The author has an hindex of 1, co-authored 1 publications.
Chat about Author
Papers
Delay-aware relay selection with heterogeneous communication range in VANETs
TL;DR: A GPSR-based routing protocol called ETD-GPSR is proposed which incorporates the metric expected transmission delay (ETD) for data dissemination with heterogeneous communication range in VANETs and results show that in urban environment with heterogeneity communication range, using the metric ETD has increased the packet delivery ratio and decreased the end-to-end delay.
12
An Exploratory Study of Pandemic-Restricted Travel—A New Form of Travel Pattern on the during- and Post-COVID-19 Era
TL;DR: In this article , a new travel pattern called pandemic-restricted travel is introduced based on prospect theory, which includes the items of motivation to travel and constraints to normal travel from a focus group interview with 15 travel industry professionals in December 2020 in Zhuhai.
How social values gained from sharing travel experiences influence tourists’ satisfaction: moderated mediation effect of onsite mobile sharing behaviour
TL;DR: The social values gained from sharing travel experiences influence tourists’ satisfaction through moderated mediation effect of onsite mobile sharing behaviour.
6
The use of virtual exhibition to promote exhibitors’ pro-environmental behavior: The case study of Zhejiang Yiwu International Intelligent Manufacturing Equipment Expo
Qing Xia,Sha Wang,Jose Weng Chou Wong +2 more
TL;DR: Virtual exhibition can effectively promote exhibitors’ pro-environmental behavior by enhancing their perceived performance and satisfaction.
4
Two-Stage Feedback Mechanism With Different Power Structures for Consensus in Large-Scale Group Decision Making
TL;DR: In this paper , a two-stage consensus feedback mechanism that considers different power structures in large-scale group decision-making (LSGDM) environments is investigated, with minimum adjustments to achieve the optimal power allocation under each power structure.