资源科学 ›› 2020, Vol. 42 ›› Issue (6): 1199-1209.doi: 10.18402/resci.2020.06.16

• 旅游资源 • 上一篇    下一篇

基于大数据的空气质量对公众外出游玩影响研究

敖长林(), 王菁霞, 孙宝生   

  1. 东北农业大学管理科学与工程系,哈尔滨 150030
  • 收稿日期:2019-07-12 修回日期:2019-10-28 出版日期:2020-06-25 发布日期:2020-08-25
  • 作者简介:敖长林,男,黑龙江杜蒙县人,教授,研究方向为生态环境管理、评价理论与方法。E-mail: aochanglin2002@126.com
  • 基金资助:
    国家自然科学基金项目(71874026)

Impact of air quality on public outings based on big data

AO Changlin(), WANG Jingxia, SUN Baosheng   

  1. Department of Management Science and Engineering, Northeast Agricultural University, Harbin 150030, China
  • Received:2019-07-12 Revised:2019-10-28 Online:2020-06-25 Published:2020-08-25

摘要:

基于大数据探究空气质量对公众外出游玩的影响,不仅可以丰富空气质量议题的实践研究,还对加强空气污染治理、促进旅游产业发展具有重要意义。本文以哈尔滨市为研究对象,采用携程旅行网16554条在线评论数据、环保部空气质量指数数据以及历史天气数据,基于负二项回归与有序Probit回归分别构建公众外出游玩次数与游玩满意度模型,定量评估空气质量对公众外出游玩的影响及影响程度。研究结果表明:①在控制温度、风速、节假日等影响因素不变的基础上,空气质量会显著影响公众外出游玩次数和满意度;②公众外出游玩次数会随着空气污染程度的增加而显著减少,与空气质量为优相比,游玩次数在“严重空气污染”时下降40.1%,在“空气质量为良”时下降15.1%;③针对哈尔滨市旅游景区,严重空气污染会显著降低公众外出游玩满意度,而较低程度的空气污染对公众外出游玩满意度不具有显著影响。研究不仅为准确评估空气质量对公众外出行为的影响提供新视角,也为相关空气污染防治及旅游政策的制定提供参考。

关键词: 空气质量, 旅游大数据, 外出游玩, 负二项回归, 有序Probit回归, 哈尔滨市

Abstract:

Exploring the impact of air quality on public outings based on big data not only can enrich the practical research on air quality issues, but also have important significance for strengthening air pollution control and promoting the development of tourism industry. Taking Harbin City as the research object, this study used the data of 16,554 Ctrip online reviews, the Ministry of Environmental Protection’s air quality index data, and historical weather data and constructed the number of public outings and satisfaction models based on negative binomial regression and ordered Probit regression to quantitatively assess the influences and degrees of air quality on public outings. The findings are as follows. (1) Controlling for other influencing factors such as temperature, wind speed, and holidays, air quality significantly affected the number of public outings and the satisfaction of outings. (2) The number of public outings decreased significantly with the increase of air pollution. Compared with excellent air quality, the number dropped by 40.1% when the air quality was severe, and by 15.1% when the air quality was good. (3) For the tourist attractions in Harbin City, severe air pollution significantly reduced satisfaction of public outings, while lower levels of air pollution did not significantly affect satisfaction of public outings. This research not only provides a new perspective with an accurate assessment of the influences of air quality on public outing behavior, but also provides references for relevant air pollution prevention and tourism policy formulation.

Key words: air quality, tourism big data, outings, negative binomial regression, ordered probit regression, Harbin City