2,432 | 0 | 335 |
下载次数 | 被引频次 | 阅读次数 |
2024年5月,百度推出的“萝卜快跑”无人驾驶出租车服务在湖北武汉启动了大规模商业化运营。该服务以具有竞争力的定价策略和人力成本优势引发了公众关于无人驾驶出租车与传统出租车和网约车(统称为出租车行业)竞争和利益冲突的激烈讨论。在无人驾驶出租车服务商业化运营初期,深入了解公众对于这一新兴服务对司机职业冲击的认知,对于制定有效政策、避免社会摩擦、促进出租车行业的稳定发展和实现社会和谐具有重要意义。通过对微博、抖音、小红书等中国主要社交媒体平台上的22 835条评论进行筛选,我们锁定了6 228条与出租车司机直接相关的评论。本研究采用Latent Dirichlet Allocation主题模型,成功提取了公众普遍关注的五个热点主题,并形成了从订单量到技术应用的主题递进链条。情感分析结果显示在“萝卜快跑”事件的影响下,公众对出租车司机职业稳定性的看法普遍带有消极情绪且占据主导地位。K-means聚类分析显示,不同省份在情感倾向和对主题1至5的参与度上形成了四个差异类别。例如,类别2普遍参与到主题3(底层工作者)和主题4(司机失业)的讨论中,而第3类别的省份则更对主题1(家庭生计)和主题2(订单量)表现出较高的关注。上述发现为政策制定者在无人驾驶出租车技术推进中平衡社会影响提供了实证依据,有助于促进社会和谐与行业稳定发展。
Abstract:In May 2024, Baidu's“Apollo Go”robotaxi services commenced large-scale commercial operations in Wuhan, Hubei Province. Characterized by its competitive pricing strategy and reduced labor costs, the service ignited extensive public discourse regarding the competition and underlying conflicts of interest between robotaxis and the conventional online taxi ride-hailing, collectively known as the taxi industry. At the initial commercialization stage of robotaxi services, a deep understanding of the public's perception regarding the conflict between this emerging service and the taxi industry is crucial for formulating effective policies. Additionally, social friction can be avoided, thus promoting the stable development of the taxi industry and achieving social harmony. By analyzing22 835 comments on major Chinese social media platforms, such as Sina Weibo, TikTok, and Little Red Book, we extracted 6 228 comments directly related to taxi drivers. Additionally, we employed the Latent Dirichlet Allocation topic model to extract the top-five topics of general public concern,thus forming a progressive theme chain from order volume to technology application. Results of sentiment analysis indicate that the public's views on the job stability of taxi drivers are predominantly negative owing to the“Apollo Go”incident. Results of K-means clustering analysis show that different provinces formed four distinct categories in terms of sentiment polarity and participation for Topics 1 to 5. For instance, Type 2 generally discusses Topic 3(vulnerable workers) and Topic 4(driver unemployment), whereas the provinces in Type 3 show greater concern for Topic 1(family livelihood) and Topic 2(order volume). The findings provide empirical evidence for policy makers to balance the social impact resulting from the advancement of robotaxis, thereby contributing to the promotion of social harmony and the stable development of the industry.
[1]中国互联网络信息中心.第53次《中国互联网络发展状况统计报告》[EB/OL].(2024-03-20)[2024-07-31]. https://www3.cnnic.cn/n4/2024/0321/c208-10962.html.
[2]丛杰. 10公里只要3块9?萝卜快跑被指低价扰乱市场!官方称非营运车辆[EB/OL].(2024-07-11)[2024-07-31]. https://new.qq.com/rain/a/20240711 A08D5V00.
[3]腾讯网.“拔萝卜”救不了网约车司机[EB/OL].(2024-07-11)[2024-07-18]. https://new.qq.com/rain/a/20240712A0564D00.
[4]微博.萝卜快跑会导致司机大规模失业吗#[EB/OL].(2024-7-12)[2024-08-05]. https://m.s.weibo.com/vtopic/detail_new?click_from=searchpc&q=%23.
[5]腾讯网.网约车冲击下收入锐减, 270万出租车司机控诉:我们到底做错了什么?[EB/OL].(2021-11-01)[2024-08-06]. https://new.qq.com/rain/a/20211111A06B5E00.
[6]扬州检察院.出租车与网约车利益冲突案件情况分析[EB/OL].(2017-11-29)[2024-08-05]. https://yz.jsjc.gov.cn/zt/lafx/201711/t20171129_203150.shtml.
[7]李欣,张天怡.从冲突事件词云看网络约车何去何从[EB/OL]. The Paper.(2016-06-13)[2024-07-31]. https://www.thepaper.cn/newsDetail_forward_1482844.
[8]钟军,林岩,吴瑕,等.网约车服务对城市传统出租车使用的冲击效应[J].交通信息与安全, 2021, 39(2):118-125.ZHONG Jun, LIN Yan, WU Xia, et al. A shock effect of ride-hailing services on using traditional taxis in urban areas[J]. Journal of Transport Information and Safety, 2021,39(2):118-125.
[9] WANG D, MIWA T, MORIKAWA T. Interrelationships between traditional taxi services and online ride-hailing:empirical evidence from Xiamen, China[J]. Sustainable Cities and Society, 2022, 83:103924.
[10] ZHOU M, YIN J, TANG Y, et al. What drives the drivers away? An empirical study on the factors influencing the turnover intention of full-time online ride-hailing drivers in China[J]. Transportation Research Part A:Policy and Practice, 2024, 186:104134.
[11] MA Y, CHEN K, XIAO Y, et al. Does online ride-hailing service improve the efficiency of taxi market? evidence from Shanghai[J]. Sustainability, 2022, 14(14):8872.
[12]赵杨,刘倩.网约车冲击下出租车行业转型对策研究:以北京市为例[J].科学决策, 2022(12):107-136.ZHAO Yang, LIU Qian. Taxi industry transformation under the impact of online car hailing:a case study of Beijing[J]. Scientific Decision Making, 2022(12):107-136.
[13]任宇霞,谭奕.网约车冲击下改善南宁市出租车公司运营状况探究[J].经济研究导刊, 2021(23):13-15, 26.REN Yuxia, TAN Yi. Investigation into improving the operational status of nanning city’s taxi companies under the impact of ride-hailing services[J]. Economic Research Guide, 2021(23):13-15, 26.
[14] LEE S, YOO S, KIM S, et al. Effect of robo-taxi user experience on user acceptance:field test data analysis[J].Transportation Research Record:Journal of the Transportation Research Board, 2022, 2676(2):350-366.
[15] DAI J, LI R, LIU Z, et al. Impacts of the introduction of autonomous taxi on travel behaviors of the experienced user:Evidence from a one-year paid taxi service in Guangzhou, China[J]. Transportation Research Part C:Emerging Technologies, 2021, 130:103311.
[16] TUSSYADIAH I P, ZACH F J, WANG J. Attitudes toward autonomous on demand mobility system:the case of self-driving taxi[C]//Information and Communication Technologies in Tourism 2017. Cham:Springer, 2017:755-766.
[17] XIE H, DAVID A, AL MAMUN M R, et al. The formation of initial trust by potential passengers of self-driving taxis[J]. Journal of Decision Systems, 2023, 32(2):326-355.
[18] LIU J, JONES S, ADANU E K. Challenging human driver taxis with shared autonomous vehicles:a case study of Chicago[J]. Transportation Letters, 2020, 12(10):701-705.
[19] WANG Z, LI S. Competition between autonomous and traditional ride-hailing platforms:Market equilibrium and technology transfer[J]. Transportation Research Part C:Emerging Technologies, 2024, 165:104728.
[20] JING P, WANG B, CAI Y, et al. What is the public really concerned about the AV crash? Insights from a combined analysis of social media and questionnaire survey[J]. Technological Forecasting and Social Change, 2023,189:122371.
[21]景鹏,蔡云昊,孙慧倩,等.高油价能否促进消费者购买新能源汽车[J].交通运输工程与信息学报, 2022, 20(4):1-18.JING Peng, CAI Yunhao, SUN Huiqian, et al. Can high oil prices encourage consumers to purchase new energy vehicles?[J]. Journal of Transportation Engineering and Information, 2022, 20(4):1-18.
[22] JING P, CAI Y, WANG B, et al. Listen to social media users:Mining Chinese public perception of automated vehicles after crashes[J]. Transportation Research Part F:Traffic Psychology and Behaviour, 2023, 93:248-265.
[23] DING Y, KOROLOV R,(AL)WALLACE W, et al. How are sentiments on autonomous vehicles influenced? An analysis using Twitter feeds[J]. Transportation Research Part C:Emerging Technologies, 2021, 131:103356.
[24] JEFFERSON J, MCDONALD A D. The autonomous vehicle social network:Analyzing tweets after a recent Tesla autopilot crash[J]. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2019, 63(1):2071-2075.
[25]腾讯网. 6个涨粉千万博主, 656个涨粉百万博主,谁在抖音疯狂涨粉?[EB/OL].(2024-07-18)[2024-08-21].https://new.qq.com/rain/a/20240718A03SEW00.
[26]光明网.微博发布Q1财报:总营收28.44亿元[EB/OL].(2024-05-23)[2024-08-21]. https://share.gmw.cn/economy/2024-05/23/content_37339989.htm.
[27]搜狐网. 2024活跃用户研究报告(小红书平台)[EB/OL].(2024-04-17)[2024-08-21]. https://www. sohu.com/a/772239846_121876967.
[28] FEATHERSTONE J D, RUIZ J B, BARNETT G A, et al. Exploring childhood vaccination themes and public opinions on Twitter:a semantic network analysis[J].Telematics and Informatics, 2020, 54:101474.
[29]人民网.数读中国|31省份2023年GDP数据出炉[EB/OL].(2024-01-30)[2024-07-25]. http://finance.people.com.cn/n1/2024/0131/c1004-40170326.html.
[30]新浪网. 29省人口数据出炉[EB/OL].(2024-04-21)[2024-07-25]. https://k. sina. com. cn/article_2151871124_8042f2940010143jo.html.
[31]中国科教评价网. 2024-2025年大学教育地区(31个省市区)竞争力排行榜[EB/OL].(2024-4-15)[2024-07-25]. http://www.nseac.com/eva/CUAE.php.
[32] YUAN C, GENG X, MAO X. Taxi high-income region recommendation and spatial correlation analysis[J].IEEE Access, 1877, 8:139529-139545.
[33]齐宝德,刘涵.基于多元有序Logistic模型的出租车司机收入分析[J].青海交通科技, 2022, 34(6):57-63, 91.QI Baode, LIU Han. Income analysis of taxi drivers based on multivariate ordered Logistic model[J]. Qinghai Transportation Science and Technology, 2022, 34(6):57-63, 91.
[34]齐航,王光超,张运胜,等.自动驾驶出行服务的公众关切与研究展望——兼评“萝卜快跑”世界最大规模无人驾驶商业化运营[J].交通运输工程与信息学报,2024:1-15.QI Hang, WANG Guangchao, ZHANG Yunsheng, et al.Chinese public attitudes to and research prospects of autonomous mobility services——comment on the world’s largest experiment of“Apollo Go”[J]. Journal of Transportation Engineering and Information, 2024:1-15.
[35] PAKUSCH C, MEURER J, TOLMIE P, et al. Traditional taxis vs automated taxis-Does the driver matter for Millennials?[J]. Travel Behaviour and Society, 2020, 21:214-225.
[36]中国一线城市出行平台调研报告[R].上海:清华大学社会科学学院企业责任与社会发展研究中心, 2021.
[37]杨华磊,王嘉昊,刘雅静.性别分工对婚姻稳定性的影响研究[J].西北人口, 2023, 44:38-51.YANG Hualei, WANG Jiahao, LIU Yajing. Are marriages more stable when the woman goes out to work?[J].Northwest Population Journal, 2023, 44:38-51.
[38]向宙,黎胜根,肖正航,等.隧道施工场景无人驾驶系统研究[J].建筑机械化, 2022, 43(5):15-18.XIANG Zhou, LI Shenggen, XIAO Zhenghang, et al.Study on unmanned driving system in tunnel construction scenario[J]. Construction Mechanization, 2022, 43(5):15-18.
[39] TIPPANNAVAR S S, PUNEETH K M, YASHWANTH S D, et al. SR2-Search and Rescue Robot for saving dangered civilians at Hazardous areas[C]//2022 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications(CENTCON). Bengaluru, India:IEEE, 2022:21-26.
[40] JUMA C. Innovation and its enemies:why people resist new technologies[M]. Oxford:Oxford University Press,2016.
[41] MA J, FENG X, YANG Q. The evolution of public perceptions of automated vehicles in China:a text mining approach based dynamic topic modeling[C]//International Conference on Human-Computer Interaction. Cham:Springer, 2023:340-350.
基本信息:
DOI:10.19961/j.cnki.1672-4747.2024.08.012
中图分类号:F572;F426.471;F49
引用信息:
[1]孙慧倩,景鹏,贺正冰等.技术革新对出租车司机职业的冲击:“萝卜快跑”事件下的公众社会认知与情感倾向[J].交通运输工程与信息学报,2024,22(04):13-24.DOI:10.19961/j.cnki.1672-4747.2024.08.012.
基金信息:
国家自然科学基金项目(71871107);; 江苏省自然科学基金面上项目(BK20231324)