Understanding The Spatiotemporal Variation Of Urban Taxi Services In The Context Of A Subsidy War Among E-hailing Apps

Taxi plays an important role in urban public transportation as it provides people with door-to-door mobility services.With the development of information and communication technology(ICT),emerging e-hailing services,which allows passengers to request taxi services through e-hailing apps,have entered the traditional taxi market.Taxi drivers are able to have the passenger's travel origin and destination known in advance through the platform.However,it should not be overlooked that some annoying problems are often reported,such as unfair competition,safety issue,long-term work,surge pricing,refusal of orders,picking and choosing orders behavior,and older residents' difficulties in getting a taxi.Therefore,we urgently need to understand the impact of the e-hailing service on the urban taxi market in order to provide a reference for solving above mentioned problems.In 2014,China's two major e-hailing companies,Didi and Kuaidi,launched a fierce subsidy war in the taxi market to attract more users.Taking Shenzhen as an example,this thesis uses the taxi trajectory data during the subsidy war in Shenzhen to investigate the spatiotemporal dynamics of the pick-up and drop-off locations of taxicabs,the spatiotemporal variation patterns of urban taxi OD flows,the change patterns of taxicabs' spatial operation zones,as well as spatial inequalities in urban taxi services.Specifically,this thesis includes following four-aspect studies:(1)We discover that the subsidy war has stimulated more taxi travel demands,and in different periods of the subsidy war,the change in the number of pick-ups and dropoffs varies greatly in spatial distribution.Three indicators are used to analyze the dynamics of the pick-up and drop-off locations,including the numbers of daily pickups and drop-offs per taxi,average transfer distance per unit area of weighted mean centers of pick-up and drop-off locations,and the degree of dispersion in the spatial distribution of pick-up and drop-off locations.Then we further analyze the changes of these three indicators in different periods of the subsidy war,and explain these changes in combination with the policies implemented in different periods of the subsidy war,thus revealing the dynamics of the pick-up and drop-off locations.(2)We find that the increased travel demand during the peak period of the subsidy was mainly the demand for short-distance travels which are less than 3km,and when reducing passenger subsidies as well as after the end of the subsidy war,the taxi trips in residential areas,commercial areas and transportation hub areas increase significantly.We further analyze the change of travel distance of OD pairs with increased and decreased taxi travel demands at different periods,and then investigate the OD flows and their change patterns in four functional areas,namely residential area,industrial area,commercial area and transportation hub area during the subsidy war,thus revealing the spatiotemporal variation of taxi OD flow in the context of a subsidy war among e-hailing apps.(3)We find that the subsidies given to taxi drivers and passengers have a significant impact on taxicabs' operation zones.The percentage of taxi habitual operation zone in any neighboring periods is relatively stable under any subsidy policy.In addition,changes in taxi operation zones have little impact on taxi's average daily travel distance and average daily cruising time.We use three indicators to explore the change patterns of taxi operation zone during the subsidy war,namely,the repetition ratio of operation zone pairs,the area,and the degree of dispersion in the spatial distribution.Then,we divide the whole taxis into different groups according to their initial change patterns of the operation zones,and we further analyze the change patterns of operation zone among different groups of taxis at different periods to reveal different strategies adopted by different groups during the subsidy war.(4)It is uncovered that the outer city has greater spatial inequality in the taxi services than the inner city and this competition reduced spatial inequality in the inner city but aggravated it in the outer city.A measure of service rate to depict the quantity of taxi services is proposed to calculate a Gini coefficient for evaluating the change in the spatial inequality of taxi services.The Theil index and its decomposition are used to distinguish the contribution of Traffic Analysis Zones(TAZs)in the inner and the outer city and compare them to the overall spatial inequality of taxi services in Shenzhen.The results show that the primary contributor to overall inequality in taxi services is inequality within,rather than between,the inner and outer city.