@article{Dong2023, 
author = {Zhen-ning Dong and Jun-jie Wang and Ke-wen Luo and Lang-cheng Chen},
title = {An Evolutionary Game Analysis of  Online Car-hailing Passengers' Privacy Protection},
year = {2023},
journal = {Journal of Guangdong University of Technology},
volume = {40},
number = {1},
pages = {19-28},
keywords = {car-hailing, privacy protection, evolutionary game, Matlab simulation},
url = {https://www.sciopen.com/article/10.12052/gdutxb.220097},
doi = {10.12052/gdutxb.220097},
abstract = {To study the privacy protection of online car-hailing, an evolutionary game model including the government (regulatory, non-regulatory) and platform (self-discipline, non-self-discipline) is constructed, using the replication dynamic equation to find an evolutionary stable strategy, and using Matlab to simulate the situation under different circumstances. The influences of four parameters, including the degree of reputation improvement brought by government regulation, on the evolution path, are analyzed. The study finds : (1) When the benefits of government regulation are greater than those of non-regulation, and the benefits of platform self-discipline are greater than those of non-self-regulation, ideal result (regulation, self-regulation) will appear; (2) When the cost of platform self-regulation is low and the cost of government regulation is high, even if the government does not supervise, the platform will also be self-disciplined; (3) The increased public affirmation of government regulation and the reduction of government regulation costs leads the government to transform from non-regulation to regulation; (4) When the platform obtains positive benefits from society and reduces the cost of self-discipline, its strategy changes from non-self-discipline to self-discipline. These conclusions have guiding significance for the government to optimize the design of regulatory policy.}
}