A crowd-sourced valuation of recreational ecosystem services using mobile signal data applied to a restored wetland in China

Peichao Dai, Shaoliang Zhang, Yunlong Gong, Yuan Zhou and Huping Hou

Ecological Economics, 2022, vol. 192, issue C

Abstract: The travel cost method is the main technique used to evaluate the monetary value of recreational cultural ecosystem services of wetlands. While questionnaires still provide an important way to obtain tourist travel distances, salary rate coefficients, and travel rate data, but they are restricted by the data scale and the need for long-term monitoring. Therefore, the present study introduces mobile phone signal data into the travel cost method and establishes an evaluation model for recreational ecosystem services. By mining mobile phone signal data, the visitors' duration of stay, starting and ending coordinates, age, and gender data were collected in order to estimate the potential costs. Data from 25,087 recreationists were sampled at Pan'an Lake Wetland Park, Xuzhou, China, in 2018. Data mining found that (1) mobile phone signal data have unique advantages in determining the travel distance and cost of overnight accommodations; (2) recreationists were distributed among 229 cities, although 87.2% came from cities located within 500 km of Pan'an Lake Wetland Park, while 72.04% of all recreationists were Xuzhou locals; (3) the consumer surplus associated with visiting Pan'an Lake Wetland Park was 129.79 Chinese Yuan (CNY) per person and the average recreational value was 448.11 CNY. The evaluation results showed that the recreational value of Pan'an Lake Wetland Park was about 836 million CNY in 2018. This suggests that mobile phone signal data can be used as a new data source when assessing the recreational value of wetlands via the travel cost method.

Keywords: Cultural ecosystem service value; Recreational value assessment; Mobile signal data; Travel cost method (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:192:y:2022:i:c:s0921800921003086

DOI: 10.1016/j.ecolecon.2021.107249

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