Mobility Big Data-Based Movement Patterns and Inducement Factors Analysis
Mobility Big Data-Based Movement Patterns and Inducement Factors Analysis
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This study is intended to analyze the factors that make destinations attractive to leisure travelers, differentiating between weekdays and weekends, so as to identify their distinct characteristics. Prior to the analysis, data on leisure travel in Gyeongsangnam-do were extracted from movement location-based data and processed into origin-destination (O/D) data. These data were then analyzed using existing data to determine the current state of leisure travel by city and county. The analysis determined the centrality index of the region where leisure traffic patterns occur. Subsequently, the factors contributing to leisure traffic in Gyeongsangnam-do were analyzed. The analysis revealed differences in the factors influencing the population’s behavior in Gyeongsangnam-do between weekdays and weekends. The hypothesis test examined the existence of a difference in the factors that influence leisure traffic. The number of traditional markets and art-related facilities was found to increase leisure traffic regardless of whether the traffic took place on weekdays or weekends, and the number of art-related facilities decreased leisure traffic. However, although it was not derived significantly, it was found that adding more convenient facilities would increase the population engaged in leisure traffic. Among the cultural and tourism characteristic factors, the number of traditional markets and restaurants was found to incentivize increased leisure traffic on weekdays. On the other hand, the factors that reduce leisure traffic were significantly derived from the number of detached houses among the housing characteristic factors, the number of sports-related facilities among the culture and tourism characteristic factors, and the number of art-related facilities. Among the culture and tourism characteristics, the number of traditional markets, accommodation facilities, and recreational facilities were found to be the factors that increased weekend leisure traffic. However, the one factor that reduced leisure traffic was the number of art-related facilities. This study is significant because it identifies the factors that attract leisure traffic and proposes facilities and plans for leisure activities in local hubs and urban areas.

키워드

여가 통행인구빅데이터중심성 분석유인요인Leisure PopulationBig DataCentrality AnalysisInducement Factor
제목
Mobility Big Data-Based Movement Patterns and Inducement Factors Analysis
제목 (타언어)
Mobility Big Data-Based Movement Patterns and Inducement Factors Analysis
저자
배민철이소영주희선
발행일
2023-12
저널명
국토계획
58
7
페이지
108 ~ 125