Department of Biological Sciences, National University of Singapore, Singapore; Campus for Research Excellence and Technological Enterprise, Singapore.
Department of Biological Sciences, National University of Singapore, Singapore; Campus for Research Excellence and Technological Enterprise, Singapore.
J Environ Manage. 2020 May 1;261:110238. doi: 10.1016/j.jenvman.2020.110238. Epub 2020 Mar 2.
Big data have the potential to improve nonmarket valuation, but their application has been scarce. To test this potential, we apply mobile phone data to the zonal travel cost method and measure recreational ecosystem services from Bukit Timah (representing an urban protected area) and Jurong Lake Gardens (an urban recreational park) in Singapore. The study results show that the annual recreational benefits of the recreational park (S$54,698,761 to S$66,805,454) outweighed the benefits of the protected area (S$6,947,974 to S$9,068,027). The count data structure reduced the flexibility of the mobile phone data application. Compared to survey data, however, mobile phone data could prevent random errors and visitor memory biases; monitor impacts of site quality changes over time; count visitors from multiple entrances; and be cost-efficient. Overall, these results highlight the potential of mobile phone data application to improve travel cost analysis.
大数据有潜力提高非市场价值评估,但应用仍较少。为了检验这一潜力,我们将手机数据应用于区域旅行成本法,并测量了新加坡武吉知马(代表城市自然保护区)和裕廊湖花园(城市休闲公园)的娱乐生态系统服务。研究结果表明,休闲公园的年娱乐效益(S$54,698,761 至 S$66,805,454)超过了保护区的效益(S$6,947,974 至 S$9,068,027)。计数数据结构降低了手机数据应用的灵活性。然而,与调查数据相比,手机数据可以防止随机误差和游客记忆偏差;监测随着时间的推移,场地质量变化的影响;计算来自多个入口的游客人数;并且具有成本效益。总体而言,这些结果突出了手机数据应用于改善旅行成本分析的潜力。