Uncatchable Taxis, Seoul City Claims It's Kakao's Problem... Is It True? View original image


[Asia Economy Reporter Lee Seung-jin] The Seoul Metropolitan Government pointed out issues with Kakao, stating that some suspicions of 'selective passenger acceptance' and 'call favoritism' were confirmed as facts following an investigation into Kakao Taxi operations. However, since the investigation was conducted under the special circumstances of COVID-19, there are criticisms that the chronic problem of 'selective passenger acceptance' in the taxi industry cannot be attributed solely to Kakao.


Seoul announced on the 23rd the results of a two-month field investigation conducted from October to November last year, where investigators posed as passengers to directly call and board Kakao Taxi using the mystery shopper method (posing as customers to evaluate services). A total of 841 taxis were called, with the investigation categorizing trips by long-distance (over 10 km) and short-distance (within 3 km), weekdays and weekends, urban and suburban areas, and morning, evening, and night time slots.


The Chronic Problem of 'Selective Passenger Acceptance'

According to the Seoul investigation, the call success rate for short-distance passengers traveling from urban to suburban areas on weekday nights was only 23%, whereas under the same conditions, the call success rate for long-distance passengers was 54%, more than double the difference.


Overall, analyzing the successful dispatches after calling a regular taxi via Kakao Taxi, the success rate was lower for short-distance trips (66.4%) than for long-distance trips (81.8%). Additionally, the success rate was lower on weekdays (63.3%) than on weekends (88.1%), and lower during night hours (58.6%) compared to morning (79.0%) and evening (83.2%) times.


In response, Seoul evaluated that the Kakao Taxi app provides drivers with passengers' destinations, and there is evidence that drivers are selectively accepting passengers.


Would Removing Destinations Eliminate 'Selective Passenger Acceptance'?

Seoul pointed out that selective passenger acceptance occurs due to the destination information provided by the Kakao Taxi app. However, selective passenger acceptance is a chronic issue in the taxi industry. In the past, Seoul conducted intensive crackdowns when refusal to pick up passengers and selective acceptance, mainly occurring during late-night hours, emerged as social problems. Despite these crackdowns, refusal to pick up passengers increased from about 1,500 cases in 2017 to 1,900 cases in 2019.


In particular, Seoul believes that removing destination information from the Kakao Taxi app would eliminate selective passenger acceptance, but Seoul has already experienced the failure of its own taxi app, 'S Taxi.' Launched in 2019, the S Taxi app allowed passengers to call taxis within a 1 km radius without specifying a destination. The app was automatically installed on all Seoul taxis, applying basic taxi fares with incentives and penalties.


However, after a one-month pilot operation, the S Taxi app was discontinued due to drivers' opposition, having spent only several hundred million won in project costs. Also, when KakaoT launched 'Smart Call' in 2018, it initially started without destination specification, but withdrew the policy due to very low call acceptance rates by drivers. Similarly, Wooty, which also operated a no-destination call service, recently changed its policy to include destination specification.

Uncatchable Taxis, Seoul City Claims It's Kakao's Problem... Is It True? View original image


Worsened Supply-Demand Imbalance Due to COVID-19, Shortage of Taxi Drivers

This Seoul investigation was conducted under the special circumstances of COVID-19, making accurate evaluation difficult. Except for the excessive surge of passengers during certain time slots caused by operating hour restrictions due to COVID-19, the overall number of passengers decreased, accelerating the departure of taxi drivers.


According to the National Taxi Transportation Business Association Federation, before COVID-19 in 2020, the number of taxi drivers in Seoul exceeded 79,000. However, as of January 2022, the number of taxi drivers in Seoul dropped to 70,000, a decrease of over 9,000. The number of corporate taxis decreased by more than 30%.


While the number of operating taxis significantly decreased, the call success rate naturally falls during the 9 PM to 10 PM period when passengers surge due to operating hour restrictions. Additionally, taxi drivers prefer long-distance trips as their income has decreased due to the overall reduction in passengers.


Low Passenger Numbers and High Dispatch Rates for Short Trips... Is It 'Call Favoritism' for Affiliated Taxis?

Seoul also investigated the suspicion of 'call favoritism' toward Kakao Taxi's affiliated taxis (KakaoT Blue). Since affiliated taxis pay a 3.3% commission on sales, there is suspicion that Kakao Taxi favors affiliated taxis when dispatching passengers.


The investigation found that about 39% of the time, affiliated taxis were dispatched even when 'general call' was selected. By type, affiliated taxis were dispatched more frequently on weekends than weekdays, more for short-distance than long-distance trips, and more in the morning than in the evening or night. Seoul confirmed that affiliated taxis, not regular taxis, were being dispatched during general calls.


However, the related industry explains that this is likely due to selective passenger acceptance. Cases where affiliated taxis were dispatched at relatively high rates during general calls were situations where taxi drivers generally avoided operating. Regular taxis prioritize long-distance calls, and during times with fewer passengers, fewer taxis operate, so if calls are not refused, affiliated taxis?which are automatically dispatched?have higher dispatch rates.



Regarding this, Seoul explained that since the dispatch algorithm of Kakao Taxi has not been precisely confirmed, more detailed investigation and analysis are needed concerning 'call favoritism.'


This content was produced with the assistance of AI translation services.

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