Search Results (8)

With the popularity of 5G technology and electric vehicles, many countries around the world have adopted 5G technology to build sustainable smart city systems, and intelligent transportation is an important part of smart cities. From the perspective of 5G technology innovation bringing changes to traditional industries, in this paper, we analyze the mechanism by which 5G technology drives the transformation and upgrading of the electric vehicle industry. Based on the changes brought by 5G technology to the three industries of agriculture, industry and services, we analyzed the transformation of business models brought about by 5G with respect to electric vehicle operation. Furthermore, we analyzed the data of a 5G real-time system of electric vehicle and traffic operating in Nanjing, China, for a month in 2021, with a total of 10,610 electric vehicles and 1,048,575 cases to model the modes of electric vehicle operation associated with the platform. Based on the frequency density method, we identified three typical operating modes of urban electric vehicles: private electric vehicle use instead of walking accounts for 24.8%, passenger vehicles (Uber/Didi and taxi) account for 64.4% and logistic distribution electric vehicles account for 10.8%. We developed a method to automatically identify the operating mode of electric vehicles using data from a 5G real-time electric vehicle traffic platform, which provide a reference for the operation of electric vehicles associated with the platform. This work also provides data that can be used to support the establishment of models for the commercial operation of charging points. Full article

The ride-hailing platform offers the business model of the on-demand business ecosystem in the era of the sharing economy. Platforms such as Uber, Lyft, and DiDi have become popular worldwide and established a strong position in urban transportation. This paper presents a case study analyzing the fierce competition between Uber and DiDi in the Chinese ride-hailing market. First, employing the canvas framework, we show the core characteristics of the business models of the two platforms. Our analysis and comparisons of the strategic positioning and implementation concerning the building blocks of canvas ascribe the success factors of DiDi and the causes of Uber’s failure. Although both Uber and DiDi provide similar service offerings for diverse market segments, Uber’s mismatches between its strategic focus on the premium segment and service operations proved to be a mistake. On the other hand, DiDi managed its business more efficiently by providing a wide range of service offerings while leveraging the two-sided market. As a result, DiDi has grown successfully as a one-stop transportation platform, which is well-suited to the Chinese market. This study provides meaningful insights into business model innovations in the sharing economy and implications for the evolution of future transportation platforms. Full article

This paper discusses dynamics and differences of business models in the car-sharing industry and focuses on open innovation as the trigger of diverse business models among Uber in the U.S., DiDi Chuxing in China, and KakaoT in Korea. We seek to answer the following two questions: What creates the differences in the business models of the car-sharing industry? Do the differences in open innovation motivate the diversity of business models among Uber, DiDi Chuxing, and KakaoT? We incorporated participatory observation, interviews, and semi-structured questionnaire methods in our study. We used two-step participatory observation and interview methods, hence carrying out observation and interviews two times by different researchers with Uber drivers in the U.S., DiDi-Chuxing drivers in Beijing, and KakaoT taxi drivers in Korea to confirm the interview and participatory observation results. First, business models of the car-sharing firms Uber, DiDi-Chuxing, and KakaoT are not fixed but rather are dynamically changing. Second, business models of car-sharing firms are the result of interaction with government regulations, the taxi industry, public transportation, and the automotive car industry. Third, open innovation strategies of car-sharing firms determine the contents and dynamics of car-sharing business models, such as the revenue business model, responsibility business model, and system business model upon interaction with four agencies. Full article

Sharing economy is an emerging concept that has been implemented in several industries and has achieved huge success. Novel solutions, built on the emerging concept of sharing economy, such as Uber, Didi, Mobike, and Cargostream, offer unprecedented opportunities for maritime organizations to reform traditional water transportation. This paper presents an analysis framework of a shared container transportation mode to show the restrictions and benefit of the implementation of the concept of sharing economy in maritime transportation. As a typical inland water area in China, the Yangtze River is selected as the study area. A general shared container transportation framework is designed, including a new waiting mode, business process, and software platform system design. The new business process is developed to overcome the contradiction between the new shared container transportation mode and the traditional shipping process. The potential of the new mode is also discussed. It would contribute to the sustainability of maritime transportation with respect to energy saving. Full article

Online car-hailing services (such as DiDi and Uber) are one of the typical sharing economy forms of transportation service in the digital era. Related public policies are expected to reduce the risk of online car-hailing and ensure the social sustainable development. However, the empirical evidence regarding the effect of relevant policy implementations is still scarce. This study takes an online car-hailing service in China as a research object to understand and evaluate the effect of implementing related policies. The risk related to an online car-hailing service is classified into three dimensions in this study, namely, institutional, economic and safety perspectives. The empirical results indicate that public policies have significant impacts on reducing conflicts and risk of shared transportation in China, especially the institutional risk. Furthermore, the effects of different policy factors differ for different risk types. Several insights of developing policies and regulations related to sustainable shared transportation in the digitalization era are also provided. The interaction between government authorities, private firms and citizens should be attached to great importance in policy design, which will consequently enhance the sustainable development in the transportation sector under sharing economy. Full article

Urban public green space (UPGS) plays an important role in sustainable development. In China, the planning, classification, and management of green spaces are based on the Standard for Classification of Urban Green Space (SCUGS). However, limitations to the UPGS exist due to the over-emphasis on quantitative standards and insufficient consideration of the actual access mode of residents. Though the taxi trajectory data are widely selected to study public service facilities, its adoption in UPGSs research remains limited. Based on the case of UPGSs in the three districts of Shenzhen, we used the taxi (including cruise taxis and Didi cars, which are like Uber) trajectory data to investigate the spatial layout and the allocation of management resource of the UPGSs from the spatial interaction perspective. By rasterizing and visualizing the percentage of pick-up and drop-off points in the UPGSs’ buffer, the service scope of UPGSs was defined, which reflected the spatial distribution and activity intensity of the visitors. Then, an unsupervised classification method was introduced to reclassify the twenty two municipal parks in the three districts. Compared to the traditional planning method, the results show that the service scope of the same type of UPGS in the traditional classification is not the same as the one obtained by the study. Visitors to all UPGSs are distributed as a quadratic function and decay as the distance increases. In addition, the attenuation rates of the same type of UPGSs are similar. The findings of this study are expected to assist planners in improving the spatial layout of UPGSs and optimizing the allocation of UPGS management resources based on new classifications. Full article

Spatial inequalities in urban public transportation are a major concern in many countries but little of this research has focused specifically on taxi services. The taxi situation has grown more complex, as traditional ride-for-hire services face growing competition from e-hailing apps like Uber in the U.S., or Didi and Kuaidi in China. In 2014, Didi and Kuaidi triggered a nationwide subsidy war, with possible effects on the spatial inequality of taxi services. Taxi trajectory data from Shenzhen collected during the subsidy war shows that this competition reduced spatial inequality in the inner city but aggravated it in the outer city. In this study, a measure of service rate to depict the quantity of taxi services is proposed to calculate a Gini coefficient for evaluating change in the spatial inequality of taxi services. The Theil index and its decomposition were 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, TAZs in the outer city had greater inequality in taxi services than the inner city. Furthermore, the primary contributor to overall inequality in taxi services was inequality within, rather than between, the inner and outer city. Moreover, the mean values for the changed service rates in the inner city were always larger than the outer city, and the inner city had a more equitable changed service rate than the outer city. These results could serve as a foundation for improving taxi services citywide. Full article

The locations where taxicabs pick up and drop off passengers are crucial to understanding the dynamics of taxi trip demand. Investigating their spatial distribution and derived dynamic features is still a key task in the fields of urban geography and transportation. Such investigations are urgently needed, considering the competition created by new communication technology services, specifically e-hailing apps such as Uber, Didi and Kuaidi. For example, a subsidy war between two e-hailing apps occurred in China in 2014. However, how the pick-up and drop-off locations of taxicabs change during subsidy wars is still an open question. This paper introduces a methodological framework that can be used to derive the pick-up and drop-off dynamics of taxicabs. It also proposes three indexes that can be used to assess the dynamics of the pick-up and drop-off locations at the city and sub-district scales, namely the numbers of daily pick ups and drop offs per taxi, average transfer distance per unit area of weighted mean centers of pick-up and drop-off locations, and degree of dispersion in the spatial distribution of pick-up and drop-off locations. This paper employs data from taxicabs in the city of Shenzhen to uncover the dynamics of their pick-up and drop-off locations. The results show that the methodological framework and the indexes introduced are powerful tools for uncovering the dynamics of the pick-up and drop-off locations of taxicabs in urban environments. Full article