网约车乘客隐私保护的演化博弈研究

董振宁; 王俊杰; 罗克文; 陈浪城

doi:10.12052/gdutxb.220097

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网约车乘客隐私保护的演化博弈研究

更新时间：2026-05-27

- 网约车乘客隐私保护的演化博弈研究
- An Evolutionary Game Analysis of Online Car-hailing Passengers' Privacy Protection
- 广东工业大学学报 2023年40卷第1期页码：19-28
- 作者机构：
  
  1. 广东工业大学管理学院,广东,广州,510520
  2. 广东工业大学人事处,广东,广州,510006
  3. 广东工业大学网络信息与现代教育技术中心,广东,广州,510006
- 作者简介：
  
  董振宁(1977–)，男，副教授，博士，主要研究方向为供应链管理、运营管理，E-mail：zndong@gdut.edu.cn
- 基金信息：
  
  广东省哲学社会科学规划学科共建项目(GD18XJY07);广东省哲学社会科学规划项目(GD21CJY24)
- DOI：10.12052/gdutxb.220097
  中图分类号： F273.4
- 网络首发：2023-01-25，
  
  纸质出版：2023
- 稿件说明：
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董振宁, 王俊杰, 罗克文, 陈浪城. 网约车乘客隐私保护的演化博弈研究[J]. 广东工业大学学报, 2023, 40(1): 19-28.

Dong Zhen-ning, Wang Jun-jie, Luo Ke-wen, et al. An Evolutionary Game Analysis of Online Car-hailing Passengers' Privacy Protection[J]. 2023, 40(1): 19-28.
董振宁, 王俊杰, 罗克文, 陈浪城. 网约车乘客隐私保护的演化博弈研究[J]. 广东工业大学学报, 2023, 40(1): 19-28. DOI： 10.12052/gdutxb.220097.

Dong Zhen-ning, Wang Jun-jie, Luo Ke-wen, et al. An Evolutionary Game Analysis of Online Car-hailing Passengers' Privacy Protection[J]. 2023, 40(1): 19-28. DOI： 10.12052/gdutxb.220097.

摘要

为了研究网约车隐私保护问题，本文构建了政府(监管，不监管)和平台(自律，不自律)的演化博弈模型，运用复制动态方程寻找演化稳定策略，并运用 Matlab 软件模拟不同情形下的演化路径，分析政府监管带来声誉提升的程度等4个参数对演化路径的影响。研究发现：(1) 政府监管收益大于不监管，平台自律收益大于不自律时，会出现(监管，自律)的理想结果；(2) 平台自律成本较低、政府监管成本较高时，即使政府不监管，平台也会自律；(3) 公众对政府监管给予肯定的程度提升、政府监管成本降低会引导政府由不监管转化为监管；(4) 平台获得来自社会的正向收益提高、自律成本降低会使平台由不自律转化为自律。这些结论对于政府优化监管政策设计具有指导意义。

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.

关键词

Keywords

references

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