Abstract

Although big data has emerged as a crucial data source in urban studies, urban park-related studies still rarely use data such as that from card transactions. This study fills the gap between big data and park studies by using card transaction data within 400 m of the Gyeongui Line Forest Park in terms of economic benefits on local business. The authors divided the linear park into five sections according to each section’s design strategy to examine the relationship between the design features and card transaction behaviors. With the data, the authors analyzed the average ages of card users to understand average users’ age in each section. Results show the average ages increased from 2015 to 2017 in Sections 3–5 by years. Sections 1 and 2 describe decreasing of user ages by year, which means young generations visited Sections 1 and 2 For Section 1, amounts of average card transaction also increased from 2015 to 2017 continuously. Compared to other sections, only Section 1, as an open space within a commercialized area, contributed to local business positively. Other sections, such as 2–5, represented the negative impacts on local business from 2016 to 2017.

Highlights

  • There are many studies for identifying the impacts of building a park on property values of adjacent areas

  • This study examines card transaction data as big data to identify the impacts of a linear park on

  • Kang and Cervero showed that Cheonggyechon impacts on adjacent property values to support the economic benefits of a park [27]

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Summary

Introduction

There are many studies for identifying the impacts of building a park on property values of adjacent areas. Researchers have estimated the value of a park by calculating the price of vegetation and elements in an urban park [5]. In the case of card sales data, variables such as the number of times a person consumes, the amount of consumption, and the time of consumption are shown in units of “place”. This has the potential to newly measure the economic benefits of parks

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