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Kakao publishes the 2017 Kakao Mobility Report

[2017-11-27] Daily average of one hour and 48 minutes per person. Every moment of movement and changes happening in Korea is included in the report.

Kakao Mobility (CEO Joohwan Jung) announced on Nov 27 that it has published the 2017 Kakao Mobility Report (hereinafter “the Report”). The Report aims to contribute to the public good such as transportation policies, local businesses and daily life by analyzing the big data of Kakao’s mobility-related services including Kakao T, KakaoNavi and KakaoMap, and organizing them by such topics as Daily Life, Commercial Areas and Policy. Kakao Mobility is planning to release the Report in the Brunch website and also provide it to local governments and academia so that it can be used as a reference.

#Daily Life The “Daily Life” chapter describes movement patterns in everyday life through Kakao T Taxis, KakaoNavi and KakaoBus. For example, the fact that a significant number of taxis move toward transport hubs such as subway stations or bus terminals throughout the day implies that taxis are used as the first means of mobility to connect to other transportation means. The big data of KakaoNavi in rush hours shows that the traffic is heaviest on the Hannam Bridge and the Gimpo Bridge. KakaoBus analyzes the speed of buses passing through each bus stop, allowing readers to examine the traffic flow by time of day in major areas in the Seoul metropolitan region. The comparison of the working patterns of owner-driver taxis and corporate taxis by time of day shows that the reason that people have difficulty getting a taxi late at night is the difference in supply and demand.

#Commercial Areas The “Commercial Areas” chapter examines the scope, current status and change patterns of commercial areas. Kakao T Taxi’s arrival and departure information in major commercial areas by time of day, comparison of the number of arrivals and departures, and call trends by day and month show the movement, change and special characteristics of major commercial areas. For example, there were far more taxi calls which designated Itaewon as the start point than those which designated the area as the destination. On the contrary, in trading areas outside Seoul such as the Na Hye Seok Street in Suwon and the Lafesta Mall in Ilsan, there were far more taxi calls which designated the areas as the destination than those which designated the area as the start point. This is an indicator which can be used to estimate the locality of the commercial area in question, availability of public transpiration, connection to nearby commercial areas, etc. Moreover, taxi call areas by Kakao T Driver show the map of entertainment districts thriving by time of night. Also, KakaoMap’s data on the locations of coffee shops, fried chicken stores, hamburger shops and hospitals can be studied to check the status of commercial areas by major region, strategies for brand store locations, and the status of franchise store distribution.

#Policy The “Policy” chapter analyzed Kakao T Taxi’s big data and summarized the results so that it can be used as a reference in planning and establishing transportation policies. The “Last One Mile” areas where passengers use taxis repeatedly in spite of rather short distances imply that public transportation policies in these areas should change. The locations where Kakao Taxi calls are made frequently and in large volumes can mean that taxi stops are needed at those locations. The attempt to estimate taxi demand and provide taxis efficiently is also interesting. Last April, before the Coldplay concert, Kakao Mobility sent a notice to Kakao Taxi drivers that taxi demand would surge in the Jamsil area, and as a result, far more taxis were available in the area that day compared to normal times.

“The Mobility Report is a part of Kakao Mobility’s efforts to find out what kind of contributions it can make to the society,” notes CEO Joohwan Jung. “We hope that the Report will be the beginning of a journey to create more convenient and safer mobility solutions.” He goes on to explain that the appearances and phenomena of everyday life discovered by Kakao Mobility’s big data are expected to be used in exploring a wide range of development possibilities such as the formulation and establishment of transportation policies, life and business.

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