A systematic review on shared mobility in China

Abstract

The last decade witnessed a rapid rise in shared mobility in China. However, there is lack of understanding how the shared mobility market developed, how shared mobility reshapes daily travel patterns, and what shared mobility contributes, if at all, to environmental goals, and in particular climate change mitigation. Here, we systematically review the state of shared mobility in China, scoping 2541 English paper and 12,140 Chinese research papers. We differentiate between ride hailing, car sharing, and bike sharing and analyze the factors shaping shared mobility patterns from the four perspectives of consumers, service providers, the government, and the environment. We also elaborate on governance measures guiding shared mobility and investigate the impact of future shared mobility on a potential low-carbon transportation system transition, highlighting the key role of bike sharing and shared pooled mobility. We show that COVID-19 reduced demand for car hailing, but rendered bike sharing more popular. This work provides a systematic guidance for the future development of shared mobility, and its possibility to contribute to climate change mitigation.

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A systematic review on shared mobility in China
Jia-Wei Hu & Felix Creutzig
To cite this article: Jia-Wei Hu & Felix Creutzig (2021): A systematic review on shared mobility in
China, International Journal of Sustainable Transportation, DOI: 10.1080/15568318.2021.1879974
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REVIEW ARTICLE
A systematic review on shared mobility in China
Jia-Wei Hu
a
and Felix Creutzig
a,b
a
Sustainability Economics of Human Settlements, Technical University Berlin, Berlin, Germany;
b
Mercator Research Institute on Global
Commons and Climate Change, Berlin, Germany
ABSTRACT
The last decade witnessed a rapid rise in shared mobility in China. However, there is lack of under-
standing how the shared mobility market developed, how shared mobility reshapes daily travel
patterns, and what shared mobility contributes, if at all, to environmental goals, and in particular
climate change mitigation. Here, we systematically review the state of shared mobility in China,
scoping 2541 English paper and 12,140 Chinese research papers. We differentiate between ride
hailing, car sharing, and bike sharing and analyze the factors shaping shared mobility patterns
from the four perspectives of consumers, service providers, the government, and the environment.
We also elaborate on governance measures guiding shared mobility and investigate the impact of
future shared mobility on a potential low-carbon transportation system transition, highlighting the
key role of bike sharing and shared pooled mobility. We show that COVID-19 reduced demand for
car hailing, but rendered bike sharing more popular. This work provides a systematic guidance for
the future development of shared mobility, and its possibility to contribute to climate
change mitigation.
ARTICLE HISTORY
Received 3 August 2020
Revised 23 October 2020
Accepted 12 January 2021
KEYWORDS
Governance; impact factor;
low-carbon cities; shared
mobility; transporta-
tion system
1. Introduction
The continuous urbanization process, associated motor
vehicle use, fast-growing travel demand, and imperfect pub-
lic transport systems have brought huge challenges to urban
transport worldwide but especially in China, for example
burdening Beijing’s economy by 7.5%–15% of GDP
(Creutzig & He, 2009). Although expanding vehicle owner-
ship can meet mobility demand, it is accompanied by con-
gestion, pollution, energy consumption, and carbon
emissions (Maibach et al., 2008; Wu et al., 2019; Yu et al.,
2020). Automobile mobility in cities is severely underpriced,
and its benefits in terms of accessibility are outweighed by
harm in traffic gridlock, noise, and air pollution (Creutzig,
Javaid, et al., 2020). Shared mobility, a new transport mode
based on advanced digital technologies, allows users to
access mobility as a service (Jittrapirom et al., 2017). It aims
to alleviate the contradiction between supply and demand of
transportation by improving the efficiency of vehicle use
(Machado et al., 2018), and increasing average occupancy, a
key determinant of energy efficient transportation (Sch€
afer
& Yeh, 2020). At the same time, relying on the development
of smartphones, shared mobility becomes popular because
of providing personalized, diversified, and fast travel services
(Standing et al., 2019). Therefore, shared mobility becomes
an effective solution to meet travel demand.
Smart shared mobility is also often identified as a sustain-
able mode of transport. However, a survey revealed that this
more often than not an intellectual shortcut of engineers
and policy makers, conflating modern digital solutions with
sustainability (Noy & Givoni, 2018). For example, motor-
cycle ride hailing in Djakarta, Indonesia, drastically
improves daily mobility of younger generations, but fails to
effectively reduce air pollution or carbon dioxide (CO
2
)
emissions (Suatmadi et al., 2019). However, some strategies,
such ride hailing, are associated with marginally higher
greenhouse gas emissions, while other strategies, such as
bike sharing and shared pooled mobility, have potentially to
reduce emissions of urban mobility (Anair et al., 2020).
China is a rapidly urbanizing nation, with relatively high-
density settlements and increasing motorization rates, resulting
into substantial congestion. Four cities of China are in the
Top 10 city in the Asian Urban Congestion Index, including
Chongqing, Zhuhai, Guangzhou, and Beijing (TOMTOM,
2019). The increase in vehicle road infrastructure cannot keep
up with the growth of private car in China. From 2010 to
2018, the annual growth rate of urban road area in China was
6.4%, while private car ownership increased by 16.8%
(National Bureau of Statistics of China, 2019). Compared with
US American cities, the density of road networks in Chinese
cities is low. In addition, the car ownership rate in China is
still at low levels. In early 2019, the car density in China was
173 cars per 1000 inhabitants, about 13% of that in the USA
(NationalBureauofStatisticsofChina,2019). As the Chinese
economy continues to grow, so will the demand for vehicles,
which will further increase the pressure on the transportation
system. Congestion, green house gas (GHG) emissions, and
sustained growth of local air pollution will become increas-
ingly problematic. While a combination of congestion charges,
ß2021 Taylor & Francis Group, LLC
CONTACT Jia-Wei Hu jiawei.hu@campus.tu-berlin.de Sustainability Economics of Human Settlements, Technical University Berlin, Berlin, 10623 Germany.
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
https://doi.org/10.1080/15568318.2021.1879974

regulation, and expansion of public transit has been suggested
as main solution (Creutzig & He, 2009), the advance of shared
mobility offers an innovation and modal choice somewhere
located between private motorized transport, individual active
mobility (in the case of bike sharing), and public transit (in
the case of ride railing and pooling, and car sharing).
As a digitally advanced nation, with deeply evolved eco-
systems of information and communication technologies,
China is an obvious candidate to spearhead smart and
potentially sustainable mobility solutions. Indeed, the trans-
portation industry and mobile mobility of China are in a
state of constant change fostered by the development of
digital technologies such as big data and artificial intelli-
gence (State Information Center, 2016-2020), providing
excellent conditions and foundation for the development of
shared mobility (Xing et al., 2019; D. N. Zhang et al., 2019).
Compared with some OECD (The Organization for
Economic Co-operation and Development) countries where
motorization is saturated, research on shared mobility in
China has only been insufficiently assessed (Si et al., 2019;
Tran et al., 2019). It is unclear how a shared mobility mar-
ket with aspiring car owners is different from a market
where typical households already own one or more cars.
Assessment of shared mobility in China, especially on mar-
ket development, governance policy, and its contribution to
environmental goals, including climate change mitigation, is
missing. This paper is a systematic review in shared mobility
research of China, attempting to provide a reference for the
potentially low-carbon energy efficient development of road
transport. The purpose of this review is 1) to outline the
development and impact of different shared mobility meth-
ods in China, 2) to summarize the key factors affecting the
development of shared mobility in China from the four lev-
els of government, company, consumer, and the environ-
ment, and 3) to clarify the effectiveness of governance
measures to the development of shared mobility in China,
and explore the potential of shared mobility to contribute to
envisaged low-carbon transition in China.
2. Methodology
RelyingonStandingetal.(2019) and adapting to the actual
situation in China, we identified keywords used for our query
(Table 1). We submitted the search query to the following lit-
erature databases: Web of Science (WOS), Google scholar, and
China National Knowledge Internet (CNKI) in 24 February
2020. The content of the string search was set to TS ¼(China
AND (shared mobility OR shared transport OR future mobil-
ity OR future transport)); TS ¼(China AND (ride hailing OR
on demand ride services OR ride sourcing OR ride splitting));
TS ¼(China AND (ride sharing OR carpooling OR vanpool-
ing OR ride pooling OR shared pooled mobility)); TS ¼
(China AND (Car sharing OR peer-to-peer OR P2P)); TS ¼
(China AND (bike sharing OR bicycle sharing)). We initially
obtain 2541 English papers and 12,140 Chinese papers. To get
more comprehensive information, we also expanded the scope
to include government annual reports and research center
reports in Google and found 15 related Chinese shared mobil-
ity development reports.
As a next methodological step, we screened the retrieved
papers by reading titles, abstracts, and full text. The process
of search and screening is shown in Figure 1. Articles that
only include traffic development but do not include shared
mobility or that exclusively consider legal issues are
excluded. This scoping narrows our set to 202 paper or
reports in English and 485 in Chinese.
We find that Bike sharing and Shard mobility are most rep-
resented among English papers (72 and 62, respectively), and
Ride hailing and Car sharing are following (Figure 2). In
Chinese paper, Bike sharing and Car sharing are two areas
that scholars are most interested in (235 and 172, respect-
ively). Ride sharing and Ride hailing are usually classified as
Wangyueche, Shunfengche, or pinche in Chinese. In order to
facilitate comparative analysis, we collectively call Wangyueche,
Shunfengche, or Pingche as Ride hailing. The statistics reveal
the importance of multi-language queries and database search:
A common English-only query would have only identified
29.4% of the relevant literature. The statistics also demonstrate
that bike and car sharing are much more dominant in the
Chinese literature than in the English literature.
On the basis, we use bibexcel to sort the keywords of 202
English papers by frequency. And we identify four categories
in research topics according to the keywords with top 20
frequency, as well as the title and abstract (Figure 3):
1. influencing factor (demand, supply, regulatory, and
environment): key factors determining the willingness
to using shared mobility;
2. estimating demand: investigations of shared mobility
demand by analysis of spatiotemporal patterns of shared
mobility, often relying on big data methods;
Table 1. Search keywords in the work.
Mobility Description Search keywords
Shared mobility The shared used of vehicles, bicycles, or other
transportation mode.
Shared mobility, shared transport, future mobility,
future transport
Ride hailing Mobility by online platforms to connect local
drivers using their personal vehicles or taxi.
Ride hailing, On demand ride services, ride sourcing,
ride splitting
Ride sharing It is literally the process in which a rider shares a
vehicle with other riders
Ride sharing, Carpooling, Vanpooling, ride pooling,
shared pooled mobility
Car sharing A new model of car rental where people rent cars
for short periods of time
Car sharing, peer-to-peer (P2P)
Bike sharing a service in which bicycles are made available for
shared use to individuals on a short term basis
for a price or free
Bike sharing, bicycle sharing
2 J.-W. HU AND F. CREUTZIG

3. barriers and governance: government problems and cor-
responding policy of shared mobility development;
4. environmental impact: air pollution, GHG emissions,
and other environmental externalities of
shared mobility.
International studies focus on influencing factors of
improve shared mobile mobility in China (40%). Chinese
research is focused on barriers and governance of shared
mobility development (51%). In addition, with the
application and popularity of big data, some scholars have
begun to use big data to understand spatiotemporal pattern
and analyze the potential demand for shared mobility.
3. Development of shared mobility in China
The development of mobile Internet and GPS technology
has led to a boom in the shared mobility market in China.
The transaction of shared mobility increased from 100 bil-
lion in 2015 to 270 billion in 2019 (State Information
Center, 2016-2020). Ride hailing, bike sharing, and car shar-
ing are the top three investment subsectors. Particularly,
ride hailing has attracted more than 80% of the investment
(Hecker et al., 2019). We will focus on the development of
the three model of shared mobility, combining relevant liter-
atures on “Estimating demand”(Figure 4).
3.1 Ride hailing
Ride hailing (also called on demand ride services), using net-
work technology to flexible match demand with taxi services,
has become an important part of the urban transportation sys-
teminChina(Q.P.Sunetal.,2019). Ride hailing focuses on
short trips in the city. In the early stages, and to get market
share, companies offered low prices and provided high subsidies
to their customers and drivers to obtain a reliable customer
Figure 1. The systematic review process.
62
34 24
72
10
43 35
172
235
0
50
100
150
200
250
Shared mobility Ride hailing Car-sharing Bike sharing Ride sharing
Publications
English
Chinese
Figure 2. Research object in 202 paper or reports in English and 485
in Chinese.
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION 3

base and a good starting position in the market (Y. Guo et al.,
2019;L.Maetal.,2019a; Sui et al., 2019;Wangetal.,2020).
From 2015 to 2019, the share of ride hailing in total taxi pas-
senger traffic increased from 9% to 37% (State Information
Center, 2016-2020). Ride hailing has become an integral part of
the Chinese resident travel market.
For the perspective of industry development of China,
Didi, Caocao, Uber, and other companies have successively
set up ride hailing services from 2010 to 2015. After 2016,
the market of ride-hailing cars became dominated by Didi
accounting for over 90%, with Shenzhou, Uber, Caocao
sharing the remaining market split up into different regions
(Analysys, 2019b; Peng, 2019). Within China, Didi has
become synonymous with online ride hailing. In 2017, Didi
completed 7.43 billion rides for 450 million users in more
than 400 cities across China (Sui et al., 2019). First-tier cities
with large populations, high-spending power, and strong
commuter activity are still the most suitable areas for quality
travel development. According to Y. Z. Wu et al. (2018) and
L. Ma et al. (2019), young people are most likely to use ride
hailing, causing them to delay buying a car.
Carpooling is a particularly valuable mode, as it reduces
traffic congestion by sharing a private car with several pas-
sengers. Multiple passengers share the cost of the ride, mak-
ing the carpool price significantly lower than the usual
online ride hailing and taxi. This is also the main reason
why passengers choose this mode of travel. Interestingly,
carpooling drivers value the social attributes of carpooling
more than passengers, such as finding new friends and
socializing (iresearch, 2015). Dida chuxing (Dida pinche) is
the earliest and largest carpooling platform. Due to some
vicious incidents that female passengers were murdered by
drivers working for Didi Chuxing’s carpooling service,
China canceled Dida’s carpooling business for passenger
safety in 2018. After nearly one year of rectification, the car-
pooling business reappeared in China with strict regulatory
control. Now, its business has covered 359 cities, with more
than 130 million users and 15 million car owners in China
in 2019 (https://www.didachuxing.com/static/h5/didahome/
about/about.html). Helloglobal and Caocao are also actively
competing for carpooling market share.
3.2 Bike sharing
Bike sharing, allowing users to use GPS-equipped bicycles
through their smartphones, aims to solve the “last-mile”
problem (Zhang et al., 2016; Y. P. Zhang et al., 2019;
Zhuang et al., 2020). Particularly, since the advent of the
dockless bike sharing (DBS) in 2015, bike sharing is popular
40%
21%
18%
9%
12% 13%
15%
51%
4%
17%
Influencing factor
Estimating dem and
Barriers and Governance
Environmen tal benefits
Others
Chinese
English
Figure 3. Cluster of research topics in English and Chinese papers.
Figure 4. The development of the three model of shared mobility in China from 2008 to 2018.
Source: (Analysys, 2019a,2019b; China Academy of Information and Communications Technology, 2018; iresearch, 2019)
4 J.-W. HU AND F. CREUTZIG

for the convenience of mobile payments and access (W. Y.
Li et al., 2019; Yin et al., 2019).
Bicycle sharing plans have been in existence in China
since 2008, but it developed only slowly until 2016 (Gu
et al., 2019). The year 2016 is described as bike sharing’s
‘first year’(State Information Center, 2016-2020). In this
year, more than 30 shared bicycle brands emerged on the
market with Mobike and OfO accounting for 80% of the
total investment in the industry in China. From 2016 to
2017, the number of shared bicycles multiplied from 2 mil-
lion to 23 million (China Academy of Information and
Communications Technology, 2018). Since 2018, the intense
industry competition, flaws in the payment processes, and
bicycle trash caused several shared bicycle brands to close
down. Mobike was acquired by Meituan, and OfO was also
in debt crisis (overseas market of OfO has shrunk dramatic-
ally and the deposit is difficult to refund). The market
expansion is slown down after 2018. However, bike sharing
also began to expand to prefectural-level city. Particularly,
helloglobal has provided services for more than 200 million
users in more than 300 cities across China in 2018 (State
Information Center, 2016-2020).
The development of bike sharing in China has injected
new vitality into sustainable transportation system of China
cities. On the one hand, bike sharing improves residential
travel efficiency and increased sustainability of urban trans-
port by improving connections between residential areas
and public transport stations (Y. Li et al., 2019; L. M. Liu
et al., 2019). On the other hand, convenience of stop-and-go
of bike sharing reduces in the frequency of use of short-dis-
tance travel by motor vehicles (Li & Kamargianni, 2018;Si
et al., 2020). Moreover, bike sharing significantly reduces
energy consumption and GHG emissions (Zhang & Mi,
2018). Zhang and Mi (2018) estimated that Mobike cuts
down 25 kilo tons of carbon emissions of Shanghai in 2016.
China Academy of Information and Communications
Technology (2018) pointed out that from April 2016 to
December 2017, Mobike reduced GHG emissions by 4.4
million tCO
2
in China and accounted for 0.5% of total car-
bon emissions of road transport in China (881.0 million
tons) in 2017. As the development of the market of bike
sharing gradually stabilizes in China, it will continue to gen-
erate benefits.
3.3 Car sharing
Car sharing is a new type of car rental service based on
Internet and mobile device applications, using hours or
minutes. It can be freely used and accessed to meet the car
demand for medium or long distance (Analysys, 2019a;
Machado et al., 2018). Another advantage of car sharing is it
likely makes people to give up their private cars by provid-
ing high-quality ride service and low price (Hu et al., 2018;
Hui et al., 2019). Market potential of car sharing in China is
high, as owners of driver licenses outnumber car owners.
After 2011, when the first car-sharing company of China
(Hangzhou EVnet Company) entered the market, the num-
ber of car-sharing companies registered increased rapidly,
especially from 2014 to 2015. As of February 2019, more
than 1600 car sharing companies have been registered and
the market size of car sharing reached 2.85 billion yuan (ire-
search, 2019). Most of the car-sharing companies are in
developed cities such as Beijing, Shanghai, Shenzhen, with
more population, high demand for mobility, better Internet
access, and more limitations to private cars.
Another reason for the rapid development of car sharing
of China is government policy support for new energy
vehicles (NEVs) (Qu & Xiong, 2020). After 2017, national
policies began to guide the norms of the car-sharing indus-
try with the development of NEVs. The Chinese government
promotes NEVs companies to produce NEVs and encourage
car-sharing platform to apply NEVs of car sharing. To fur-
ther promote the sharing of NEVs, the government has vig-
orously improved the construction requirements of charging
facilities. The rise of car sharing in China is also the period
of rapid development of NEVs, supported by domestic sub-
sidies. In 2020, more than 95% of car shared are new energy
vehicles, which makes car sharing an important part of sus-
tainable transportation in China (Jin et al., 2020).
3.4 3.4 Economic and social benefits of shared
mobility on China
The development of shared mobility not only impacts the
transportation system, but also continues to affect the soci-
ety and economy. We here briefly summarize the benefits of
shared mobility development on the economy, society, and
transportation mode from a macro-perspective–travel struc-
ture, low-carbon transportation, and job opportunities:
1. Changes in travel structure. Shared mobility changes
the traditional transportation travel structure and modi-
fies trip mode split. From 2015 to 2019, the proportion
of online ride-hailing passenger traffic in total taxi traf-
fic increased from 9.5% to 37.1%. After the emergence
of bike sharing, the proportion of bicycle trips in urban
traffic of China increased to 11.6%, while it just was
5.5% before the boom in bike-sharing (China Academy
of Information and Communications Technology,
2018). Shared mobility thus became an important part
of the transportation system and forced the traditional
mobility market to provide better quality services.
2. Optimize resource allocation and promote low-carbon
transportation. Through web-based matching between
supply and demand, vehicle resources are allocated pre-
cisely matching demand, which improves efficiency of
vehicle use. The emission reduction potential of shared
bicycles and shared electric vehicles make the develop-
ment of shared mobility important measures to achieve
clean and low-carbon development in the transporta-
tion system.
3. Create job opportunities to increase the income of
practitioners and stimulate consumption. The con-
tinuous expansion of the consumption of shared mobil-
ity and the scale of employment are conducive to
promoting economic development. For consumption,
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION 5

Table 2. Main impact factors in shared mobility.
Consumer Company Government Environmental benefit Others
Ride hailing Price (S. M. Guo et al.,
2017; State
Information Center,
2016-2020;Y.Z.Wu
et al., 2018)
Digital technology
(Creutzig et al., 2019;
Lazarus et al., 2018)
Subsidy
(Analysys, 2019b)
Emission reduction (T.
Wu et al., 2018; Xue
et al., 2018; Zhu
et al., 2018)
Weather (Babar &
Burtch, 2017)
Car ownership cost
(e.g., gasoline price,
maintenance costs,
parking costs,
waiting time) (Henao
& Marshall, 2019b;
Tang et al., 2019)
Smartphones (Z. Wang
et al., 2019; Zheng
et al., 2019)
Supervision (Q. P. Sun
et al., 2019)
Pollution reduction (Yu
et al., 2017)
Privacy (disclose
personal information
to service providers)
(Alemi et al., 2019;
Machado et al., 2018)
Profit model
(Analysys, 2019b)
Propaganda (Wang
et al., 2019a)
Private cars reduction
Demographics (age,
education, income,
gender) (Alemi et al.,
2019; Tang et al.,
2019; Wang
et al., 2019b)
Safety (L. Ma
et al., 2019)
Consumption habits
(e.g., using
smartphone, Travel
frequency) (Wang
et al., 2019a)
A Sound Management
System (Y. Wang
et al., 2019)
Average travel distance
(Babar &
Burtch, 2017)
Market competition
(Analysys, 2019b)
Car sharing Price (Qu &
Xiong, 2020)
Digital technology Subsidy (Zhang
et al., 2018)
Emission reduction
(Ding et al., 2019;
Jung & Koo, 2018)
Car ownership cost Smartphones Supervision Pollution reduction
Privacy (Hui et al., 2019) Recharge mileage of
Pure Electric Vehicles
(Qu & Xiong, 2020)
Propaganda (Niu &
Xu, 2016)
Private cars reduction
(Hui et al., 2019)
Demographics (Age,
Education, Income,
Gender) (Dogterom
et al., 2018; Tran
et al., 2019)
Profit model (Qu &
Xiong, 2020)
Consumption habits
(e.g., Using
smartphone, Travel
frequency)
(Muller, 2019)
Car purchase and
Maintenance cost
Familiarity with the car
sharing concept (Gao
et al., 2017)
Safety (Qu &
Xiong, 2020)
Trust for shared
platform (Muller,
2019; Tran
et al., 2019)
Market competition
Average travel distance A Sound Management
System (e.g., service,
cleaning, and tidying)
(Gao & Chen, 2019)
Availability and Parking
convenience (Gao &
Chen, 2019;Li
et al., 2018)
Car type, Charging
facilities, service
stations (Li et al.,
2018; Zhang
et al., 2018)
Platform reputation
(Dogterom
et al., 2018)
(continued)
6 J.-W. HU AND F. CREUTZIG

the share of expenditure in shared mobility service in
urban residents’transportation expenditure in China
increased from 6.2% in 2015 to 10.3% in 2018 (State
Information Center, 2016-2020). More importantly, the
development of shared mobility not only promotes job
opportunities but also its flexible employment character-
istics (especially online car hailing) attract a large num-
ber of full-time or part-time employers. Didi alone
increased 17.5 million flexible job opportunities and
provided 2 million drivers with an income of more than
160 yuan per capita in 2016 (Didi, 2016). Therefore,
shared mobility has played a positive role in stabiliz-
ing employment.
4. Influencing factors in shared mobility
Here, we review the key factors that influence the develop-
ment of shared mobility. We extracted relevant influencing
elements from the existing literature and summarized them
into four types of subjects: consumers (demand), company
(supply), government (regulator), and environmental benefit
(Table 2). Further, we propose a three-dimensional frame-
work for understanding how those factors can interact with
each other to shape the new context of the sharing economy
(Figure 5). Our framework consists of four main categories:
(i) demand-related factors –consumers, (ii) supply-related
factors –companies (iii) government-related factors, and
(iv) environmental-related factors. There is an effective con-
nection between the consumer, companies, and the environ-
ment. Shared mobility platform companies gain market and
consumers’trust by pricing and other methods. The vehicles
purchased by enterprises are gradually being electrified. The
green consumption behavior of consumers also contributes
to the environment. As a main category, the government-
related factors are indispensable. The government supports
the development of shared mobility to alleviate traffic con-
gestion and reduce traffic emissions by guiding companies
and consumers. For companies, the government supports
their development by providing subsidies and other means,
and supervises them through policies. In addition, the con-
struction of supporting infrastructure for shared mobility,
such as charging piles, is also inseparable from the strong
support of the government. For consumers, the govern-
ment’s propaganda can help to increase their willingness to
use shared mobility.
4.1. Demand–consumers
Consumers constitute the demand side of shared mobility.
Economic factors and individual factors significantly affect
consumers adopt shared mobility. Regardless of the shared
mobility model, economics influence consumer decisions most
especially the price of using shared mobility. The lower the
price, the more consumers will reduce using, or give up their
Table 2. Continued.
Consumer Company Government Environmental benefit Others
Bike sharing Cost of using unit Digital technology Subsidy Emission reduction
(Yang et al., 2019b;
Zhang & Mi, 2018)
Temperature,
Precipitation and Air
quality (Campbell
et al., 2016)
Transportation cost
(Yang et al., 2019b)
Smartphones Supervision and
incentives (Yu-Shi
et al., 2019)
Pollution reduction (Qiu
& He, 2018)
Demographics (Age,
Education, Income,
Gender) (Chen
et al., 2019)
Profit model (Yang
et al., 2019a)
Built environment (e.g.,
Population density,
Road length and
density, Urban traffic
accessibility) (D. Liu
et al., 2019; Zhang
et al., 2017)
Consumption habits
(e.g., Using
smartphone, Travel
frequency) (Fan
et al., 2019;Si
et al., 2020)
Riding safety (Gao et al.,
2019;Y.Y.Guo
et al., 2019)
Perceived usefulness
(Shao & Liang, 2019;
L. Y. Sun et al., 2019)
The convenience of
picking up and
parking (Shi
et al., 2018)
Perceived ease-of-use
(Ma et al., 2018;X.
W. Ma et al., 2019;
Shao & Liang, 2019)
Bicycle availability (Xin
et al., 2018)
The contribution to
users’health (Huang
et al., 2020)
Supply quantity of bike
sharing (Chen
et al., 2017)
Average travel distance
(Du & Cheng, 2018)
Management (e.g.,
service, cleaning
and tidying)
Using comfortable
capability (Y. Y. Guo
et al., 2017)
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION 7

private cars and choose shared mobility (China-SAE, 2019;
Standing et al., 2019). According to China Society of
Automotive Engineers (China-SAE), if the total costs of car-
sharing travel cost is 50% of the private car, more than 60%
of the people will give up their private car (China-SAE, 2019).
Compared with private cars, car sharing or ride hailing
exempts users to pay for the high cost of car ownership (gas-
oline price, maintenance costs, parking costs). Compared with
public transportation, online ride hailing, and taxis, car shar-
ing is more affordable. For the case of 40-km travel, the costs
of taxi (128.2 RMB) and ride hailing (105 RMB) are 4.58
timesand3.75timesthecostsofcarsharing(28RMB)
(Analysys, 2019a). Car sharing becomes more economical with
longer distances. Nonetheless, the current cost impact
researches on consumers mainly use questionnaires methods,
and there is a lack of quantitative research in price elasticity
on demand for shared mobility. For ride hailing, Y. Z. Wu
et al. (2018) pointed that possibility of choosing dedicated ride
deceases dramatically with the increasing time cost (waiting
time) of ridesharing. A study from Australia found that the
average waiting time for passengers using Uber is 4.5 min,
while waiting for a taxi takes 8 min (Deloitte, 2016): time cost
of ride hailing is lower than that of taxi.
Other factors that influence adoption rates are the individ-
ual factors, including privacy, consumption habits, demo-
graphics, and average travel distance. When consumers use
shared mobility, they need to provide basic information to
shared enterprises through apps. That may lead to the risk of
personal information disclosure. Consumption habits (e.g.,
using smartphone, travel frequency) and demographics (e.g.,
age, education, income, and gender) also affect user accept-
ance of shared mobility. There is a close connection between
these two factors. Young and high-income people are more
willing to use smartphones and have higher travel demand.
Sixty-nine per cent of young consumers use smartphone apps
to plan their trips, and they are increasingly demanding multi-
modal, personalized, and high-quality travel (China-SAE,
2019). They are becoming less and less interested in car as a
status symbol, and they have begun to delay buying cars and
use alternatives (Cohen, 2019). Shared mobility adoption rates
also vary with education levels, age, incomes, and gender. In
contrast to different from riding hailing and bike sharing, the
familiarity with the car-sharing concept and trust for shared
platform play a key role in consumer intentions for car shar-
ing because the platform deposit is higher.
4.2. Supply–company
Companies constitute the supply side of shared mobility.
Key supply side factors include the profit model of the plat-
form, technological factors (the development of digital tech-
nology and smartphones, etc.), and platform factors
(availability of vehicles, and parking convenience).
Growing shared mobility companies benefit from the rapid
development of technology including smartphones and digital
technologies. Shared mobility (such as riding hailing, car shar-
ing, and bike sharing) depends on precise matching of con-
sumer smartphone with global positioning system (GPS) of
car or bicycle. Also, technology advances can improve effi-
ciency and safety of traffic. In addition, for car sharing in
China, recharge mileage of pure electric vehicles is also a key
technical factor for consumers to choose a car-sharing brand.
Companies’profit model is the core of the supply-side
decisions. Since shared mobility started late in China, vari-
ous shared mobility companies are still exploring stable
business models. For example, some car-sharing platforms
(GoFun and EVCARD) are expanding service types to the
field of long-term rental/car rental to become profitable.
Industry research reports indicate that the business model of
shared mobility market in China will scale to becoming
profitable by 2025 (Analysys, 2019a; iresearch, 2019). Unlike
online ride hailing, car sharing and bike sharing also need
to be responsible for vehicle purchase, cleaning, and main-
tenance costs besides operating costs. Currently, the industry
is sharing equipment operating for a short period of time
and long vacancy period, thus producing deficits.
Platform factors such as safety, sound management sys-
tem, availability, and convenience also affect the company’s
development. First, safety is a key for trust into companies.
The meaning of safety varies in different shared travel
modes. For ride hailing, information between passengers
and drivers is asymmetric. Although China’s online ride
hailing platform has set strict screening and review stand-
ards, some part-time drivers are not willing to provide their
personal information, which increased risk of information
asymmetry (Gao & Chen, 2019). Until 2018, Didi drivers
were able to obtain the passenger’s private information, and
evaluate and label the passenger after the service is over
1
.
Malicious people may use this information to find targets
Figure 5. The concept framework in the influencing factors in shared mobility.
1
In May 2018, Didi announced that it would permanently close information
related to passenger’s privacy such as gender, avatar.
8 J.-W. HU AND F. CREUTZIG

for harm. This become one of reasons that accidents of
ride-hailing drivers hurt passengers. Different from riding
hailing, car-sharing cars are driven by the customer them-
selves, which avoids conflict between driver and passenger.
From the perspective of car-sharing platform, safety refers
to responsibilities distribution between platform and users
after an accident. In China, after a sharing car accident, it is
difficult for the user to handle it because responsibility is
unclear. This causes distrust of users to platform.
A sound management system is an important prerequisite
for the sustainable development of a shared platform. For
ride hailing, good management system means efficient and
high success rate, which can make the sharing platform get
a group of loyal users. For car-sharing and bike-sharing
companies, management tasks such as service, cleaning, and
tidying can also make users have a good experience and
enhance their trust in the platform. And the quality
and type of cars and bicycles they provide, their availability,
and parking convenience are also key factors improving
trust. A key challenge is to create a sufficiently dense and
expansive car-sharing system that provides users with eco-
nomics of density and scope (cars are readily available). A
second key challenge is to provide parking where it is
needed, a concern especially in inner city markets.
4.3. Regulator–government
The government plays a leading and regulatory role in
shared mobility development in China. Existing literatures
focuses on policy support and governance, addressing traffic
congestion and air pollution. Because shared mobility (car
sharing and bike sharing) can effectively solve these prob-
lems, the government encourages people to use shared
mobility (Yu-Shi et al., 2019; Zhang et al., 2018). For safety
issues such as riding hailing accidents, the government has
adopted strict regulatory measures to ensure the safety of
passengers’lives and property (Q. P. Sun et al., 2019). As
shared mobility, especially shared cars, is mainly concen-
trated in first-tier cities such as Beijing and Shanghai, citi-
zens from other cities are still unfamiliar with the concept
(Analysys, 2019a). The government’s information and out-
reach efforts can hence help to promote shared mobility
(Niu & Xu, 2016; Y. Wang et al., 2019).
4.4. Environmental benefit
The alleged or true environmental benefits (carbon emis-
sions and pollutants) provide an additional motivation for
shared mobility and motivating support by the government
(T. Wu et al., 2018; Xue et al., 2018; Yu et al., 2017; Zhu
et al., 2018). However, from the existing literature, there are
still few studies on the environmental benefits of shared
mobility in China. Particularly for carbon emissions, the
emission reduction potential of different shared mobility
models is still unclear. For bike sharing and electric car
sharing, most studies suggest that they can effectively reduce
carbon emissions from road transport (Ding et al., 2019;
Firnkorn & Muller, 2011; Qiu & He, 2018; Zhang & Mi,
2018). At national level, the emissions reduced by Mobike
from April 2016 to December 2017 accounted for 0.5% of
total carbon emissions of road transport in China in 2017
(China Academy of Information and Communications
Technology, 2018). At city level, Qiu and He (2018) showed
that if the distance traveled by a bicycle replaces 75% of the
distance traveled by a car in 2015, the CO
2
emissions of
Beijing’s road traffic would reduce by nearly 616.04 thou-
sand tons. Zhang and Mi (2018) estimated that Shanghai
cuts down 25 kilo tons of carbon emissions in 2016 by esti-
mating the travel distance and the market share of Mobike.
Ding et al. (2019) determined the global warming potential
of car sharing by life cycle assessment, showing that GHG
emissions of urban transportation would reduce by 4% to
20% when car sharing replaces 10% to 50% of private cars.
However, a Korean study pointed out that the increase in
the frequency of car replacement due to the increase in the
use frequency of shared cars may drive the growth of indir-
ect carbon emissions (Jung & Koo, 2018).
Emission reduction potential of ride hailing is unclear.
Some research shows that reduced car manufacturing (Xue
et al., 2018), reduced consumers’willingness to buy new
cars (Yu et al., 2017), and/or more flexible parking com-
pared with taxis (Sui et al., 2019) all reduce emissions.
Other research demonstrates that due to fierce low-price
competition, ride hailing occupied a part of public transpor-
tation trips, and this leads to a significant increase in the
number of ride-hailing trips and travel distance, meaning
that carbon emissions also increase (T. Wu et al., 2018; Yi,
2019). Research from the USA also shows that deadheading
increases vehicle miles traveled and associated emissions by
80% (Henao & Marshall, 2019a). In addition to emissions,
Becker et al. (2020) found the introduction of car-sharing
and bike-sharing schemes may increase transport system
energy efficiency by up to 7%, whereas the impact of ride
hailing appears less positive. Therefore, the environmental
benefits in ride hailing hence remain contested. A clear
strategy for reducing emissions would involve a focus on
bike sharing and ride pooling that focuses on increasing
occupancy (Anair et al., 2020).
5. Governance of shared mobility
While shared mobility models have to meet several chal-
lenges. First, shared mobility in China still lacks a clear
profit model and builds on excessive reliance on capital,
motivated by outcompeting rival companies. As a result, a
large number of companies went bankrupt in the competi-
tion, as a result also of overcapacity. In particular, shared
bicycles have caused resource waste through a large number
of manufacturing resources in China. Second, the lack of
supporting infrastructure (charging piles and parking spaces)
for shared mobility, especially for car sharing, limits the
widespread use. Third, the government grasps the shared
mobility industry only partially, and policies and regulations
inadequately cover industry issues. Here, we summarize
national-level policies for shared mobility in China (Table 3)
and discuss them in turn in the subsequent subsections.
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION 9

5.1. Governance of ride hailing
Supervising ride-hailing safety and guiding industry develop-
ment are the main policy guidelines for online ride hailing.
Two policies (Guiding Opinions on Deepening Reform and
Promoting the Healthy Development of the Taxi Industry
and Interim Measures for the Administration of Online Taxi
Booking Business Operations and Services [Revised]) estab-
lished governance of ride hailing in China. They clarify the
legal status of online Ride hailing in China and bring online
ride hailing into the category of taxi. Moreover, Chinese
government guides ride hailing to provide high-quality serv-
ices (brand cars, high prices, and high-income people) to
avoid direct competition between ride hailing and taxis. A
ride-hailing enterprise can only obtain an operating license
after its platform company, vehicles, and drivers get legal
permits. The policy (Measures for the Administration of
Regulatory Information Interaction Platform for Taxi
Booking) intends standardize data transmission to ensure
the integrity, timeliness, and authenticity of data transmis-
sion by ride-hailing platforms.
Although the policy (Interim Measures for the
Administration of Online Taxi Booking Business Operations
and Services [Revised]) has been implemented, the strict
supervision of government to online ride-hailing platform
companies is still being debated by researchers (Li & Ma,
2019; Q. P. Sun et al., 2019). Some researchers pointed out
that the contradiction between “strict policy controls”(strict
requirements for permits to ride hailing enterprises) and
“lack of supervision”has caused difficulties in the legal oper-
ation of ride-hailing companies (Q. P. Sun et al., 2019;
Zhang, 2018; Zhang & Wu, 2017). In fact, ride-hailing regu-
lation excludes most of the online car hailing from the
Table 3. Major national-level policies for shared mobility in China.
Policy Action
Ride hailing July 2016: Guiding Opinions on Deepening Reform
and Promoting the Healthy Development of the
Taxi Industry
1. Clarify the legal status of online Ride hailing.
2. Bring online Ride hailing into the category of
taxi.
3. Guide online Ride hailing and taxis to provide
services for different markets to avoid direct
competition between them.
4. Require platform, vehicles and drivers to obtain
corresponding licenses.
5. Made the basic requirements for platform,
vehicles and drivers.
July 2016：Interim Measures for the
Administration of Online Taxi Booking Business
Operations and Services [Revised]
February 2018: Measures for the Administration of
Regulatory Information Interaction Platform for
Taxi Booking
1. Strengthen the operation and management of
the information interaction platform.
2. Standardize data sharing.
Bike sharing August 2017: Guiding Opinions on Encouraging
and Regulating the Development of Internet
Bicycle Rental
1. Promote the sustainable development of shared
bicycles.
2. Guide the orderly delivery of vehicles according
to city characteristics and public travel needs.
3. Promote the setting and construction of bicycle
parking spots.
4. Control the total amount of bicycles and
Strengthen parking management.
5. Strengthen credit management: Establish basic
credit database for enterprises and users.
May 2019: Measures for Fund Management of
Users in New Transportation model
1. Strengthen the management of deposits and
prepaid funds for users of new modes of
transportation such as shared bicycles.
August 2019: Guidance to promote healthy
development of the platform Economy
1. Strictly observe the bottom line of industrial
safety and stability.
2. Strengthen multi-sector collaborative to improve
the credit system of shared bicycles and other
fields.
3. Promote the online application of "Shared
Bicycle Supervision Platform".
Car sharing October 2015: Guiding Opinions on Accelerating
the Construction of Electric Vehicle Charging
Infrastructure
1. Strengthen planning and construction, operation
management, standards, and norms.
2. Focus on solving the problems of “difficult
parking”and “difficult charging”.December 2016: Notice on Accelerating the
Integrated Construction of Parking Lots and
Charging Infrastructure
August 2017: Guiding Opinions on Promoting the
Healthy Development of Small and Mini
Bus Rentals"
It is clearly proposed to encourage the use of new
energy vehicles for car-sharing industry.
August 2017: Measures on Parallel Administration
of Passenger Car Enterprise Average Fuel
Consumption and New-Energy Vehicle Credits
The double-point policy promotes the production
of new energy vehicles: the percentage
requirements for new energy vehicles in 2019
and 2020 are 10% and 12%.
May 2019: Measures for Fund Management of
Users in New Transportation model
Clear regulations on the collection and refund of
shared car deposits: The single deposit for car
sharing must not exceed 2% of the average
cost of operating vehicles.
10 J.-W. HU AND F. CREUTZIG

compliance threshold in China. The corresponding policies
issued in most cities are more stringent than those at the
national level, and some regions even have strict restrictions
on driver registration and vehicle wheelbase. As of July
2018, the number of compliant car-hailing vehicles nation-
wide was 170,000, only accounting for 0.54% of the total
online ride hailing (Yu & Li, 2019). Some drivers who can-
not obtain legal permission in time often operate in private,
posing liability risks. In addition, the construction of regula-
tory information platforms is still slow: Q. P. Sun et al.
(2019) point out that the government has not formed an
effective regulatory system for the operation of the network
platforms. It is important for governments to accelerate the
provision of online-integrated data governance platforms
and related data sharing. Government agencies or independ-
ent entities can manage and integrate critical mobility data
that can effectively guide social and business potential for
mobility governance, while rendering data abuse impossible,
for example, via trusted computing technologies
(Creutzig, 2020).
5.2. Governance of bike sharing
For bike sharing, support and control become the main aim of
governance in China. Compared with cars, the environmental
benefits and convenience of bicycles make them favored by
governments at all levels, but the rapid appearance of shared
bikes has also caused issues in governance. At present, the gov-
ernance of shared bicycles is mainly aimed at disordered park-
ing in China (Jiang et al., 2019; Yao et al., 2018;Zhao&Wang,
2019). In August 2017, “Guiding Opinions on Encouraging and
Regulating the Development of Internet Bicycle Rental”was
requiring the construction of adequate bicycle parking. The
“Guidance to promote healthy development of the Sharing
Economy”asks to strengthen the cooperation of relevant
departments such as the Development and Reform
Commission, the State Administration for Market Regulation,
and the Ministry of Transport in improving the credit system
of shared bicycles, linking user behavior, personal credit, and
use rights for bike. Specifically, the State Administration for
Market Regulation requires bicycle companies to restrict illegal
parking by credit scoring and economic rewards. The Ministry
of Transport and Ministry of Public Security shares the infor-
mation of personal punishment with shared bicycle companies
to lead them to establish a user “blacklist”system. In addition,
the government believes that there is a surplus in the number
of shared bicycles, and total quantity control is still an import-
ant task of government management.
But unilateral government supervision is not satisfactory.
Zhao and Wang (2019) showed it was difficult for the gov-
ernment to formulate a detailed management plan to fully
monitor the shared bicycle industry because of limited
macro-control capabilities and administrative resources.
Some scholars have suggested that the government-enter-
prise-user tripartite collaborative governance mechanism can
effectively respond to the development of shared bicycles
with strict supervision of user credit system (such as timely
feedback on users’bad records and strengthen law
enforcement) (Chang et al., 2018; Jiang et al., 2019; Xu & Ji,
2019; Zheng & Sheng, 2017). At present, it is an arduous
task to integrate shared bicycles into a unified social credit
system. The credit scoring methods adopted by different
bike sharing companies in China are different. For example,
OfO uses data from Alibaba’s services to compile its score,
while Mobike uses Tencent credit scoring service. The credit
systems of these two large companies can affect users in eco-
nomic aspects including applying for loans and preventing
damage to the bicycles. However, user credit systems are a
concern from the perspective of surveillance capitalism
(Zuboff, 2019). User’s consumption behavior is easily under-
stand through payment data, being a means for these com-
panies to continue to profit. As an alternative, decentral
computing technologies, involving also block chain technol-
ogies, deserve increased focus by research and business.
5.3. Supporting car sharing in new energy vehicles
For car sharing, support and encouragement of NEVs is a
central government policy. The development of the shared
car industry is inseparable from policy support in China. On
both the national level and the city level, shared new energy
vehicles are vigorously promoted. The regulation [Guiding
Opinions on Promoting the Healthy Development of Small
and Mini Bus Rentals in August 2017] encourages the use of
new energy vehicles, such as battery electric vehicles, for car
sharing. To solve the problems of parking/charging, govern-
ments have accelerated the construction of charging pile
infrastructure. In addition, the policy also stipulates deposit
and subsidy policies.
These policies promote the vigorous development of
shared new energy vehicles in China. However, some schol-
ars believe that the policy is still inadequate. Ji and Qiao
(2019) point out that most cities in China do not have clear
development goals for the car-sharing industry and only
some cities such as Shanghai, Shenzhen, Chengdu,
Guangzhou, Baoding, and Hainan have clear policy support
for car parking spaces, charging, and traffic. L. Zhang et al.
(2019) showed that the existing policies cannot effectively
solve the car-sharing industry’s challenges, such as that
charging piles in various regions cannot be fully shared.
There is no unified standard in the early stage of the devel-
opment of new energy vehicles, and the charging piles pro-
duced by various manufacturers and electric vehicles have
inconsistent interfaces, frustrating users and companies.
Many people delay the purchase of pure electric vehicles.
On the other hand, it has also caused lots of charging sta-
tions to face losses due to low long-term utilization.
Harmonizing standards for charging is hence a key policy to
further advance car sharing.
6. The impact of shared mobility on transport low-
carbon transition of China
With the development of 5G technology, big data, and artifi-
cial intelligence, the shared mobility is rapidly developing
and increasingly integrated into everyday lifestyles. The
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION 11

policy support of Chinese government for digitalization and
electrification has made more and more shared mobility
companies begin to focus on these two aspects. Shared
mobility also affects traditional public transportation and
overall GHG emission patterns of urban mobility. A key
issue in transport low-carbon transition planning is whether
shared mobility will cannibalize public transit, or will serve
as feeder to public transit.
The intention of shared mobility is to improve the use
efficiency of auto-mobility car and reduce ownership of pri-
vate cars, and associated street space allocation problems
(Creutzig, Javaid, Soomauroo, et al., 2020). The flexibility of
shared mobility could make them an effective supplement to
public transportation. However, low prices, convenience,
and high-quality services allow shared mobility to occupy
the market share of public transportation (Campbell et al.,
2016; Jin et al., 2019; Yong et al., 2016). Yong et al. (2016)
showed about 50% of ride-hailing passengers in Beijing are
transferred from public transportation accounting for 12%
of public transportation trips. Jin et al. (2019) found that
travelers prefer shared bicycles instead of public transporta-
tion on weekends. Excessive competition in shared mobility
and public transportation will affect the carbon emissions of
transportation. Zhang et al. (2020) evaluated the emission
reduction potential of ride hailing using mobile phone GPS
data, and the results showed the rebound effect would be
caused by the increase in passengers from public transporta-
tion if all public transportation passengers adopt ride-hail-
ing method.
The sudden outbreak in COVID-19 has led municipal
transport planners to re-examine the urban transport infra-
structure and street space allocation. The change in public
transportation and shared mobility may play a role in pro-
moting low-carbon transportation transformation. In coun-
tries under strict confinement, transport emissions decreased
by more than 50% (walking and cycling, including e-bikes)
(Le Qu
er
e et al., 2020). The first reason is that demand for
public transport, ride hailing, and car sharing has dropped
sharply. Particularly, public transport travel is most affected
by the COVID-19 as crowded places are strictly controlled.
Occupancy levels of buses in Beijing in February 2020 were
only 22% of that in February 2019 (Ministry of Transport of
China, 2020). The choice of transportation methods and
vehicle purchase intentions of travelers changed rapidly. The
Institute for Transportation and Development Policy (ITDP)
showed that only 34% of subway and public transportation
users keep their original mode of transportation after resum-
ing work, and 40% transfer to motor vehicles (private cars,
taxis, online car rental) (ITDP, 2020). Ipsos (2020) revealed
that 63% pre COVID-19 China vehicle intenders stated they
are more likely to purchase a vehicle once the COVID-19
outbreak is over.
The reuse of shared bicycles after lockdown also contin-
ues to help reduce carbon emissions in city transport.
Because it can avoid crowd contact, bike sharing gained
modal shares during the epidemic. A report released by
Wuhan Transportation Planning Network and Meituan
Bicycle showed Meituan shared bicycle trips accounted for
56.2% of total trips from January 23 to March 12 (https://
www.udparty.com/index.php/detail/articledetails/?id=4604%
20target¼). After lifting the COVID-19-induced lockdown,
the using of shared bicycle in China continues to rise. Bike
sharing used to travel directly to the destination replaces the
"public transport þbike" connection within 3 kilometers
(ITDP, 2020). In addition, the increased adoption of home
office during the pandemic also contributed to reduced
travel demand and reduced transportation carbon footprint.
Although the impact of the COVID-19 on urban traffic is
short term and the demand for travels already recovered in
China, as the pandemic is increasingly under control, new
infrastructure projects proposed by the Chinese government
including new energy vehicle charging piles may accelerate
transport low-carbon transition of China.
7. Conclusion and discussion
This article provides a comprehensive review of shared
mobility in China through literature analysis from 202
English and 485 Chinese paper or reports. We have collated
and analyzed the four aspects of development trends, influ-
encing factors, governance policies, and the impact on low-
carbon transformation. Here are our main conclusions.
Shared mobility in China –ride hailing, bike sharing,
and car sharing –all have developed rapidly in the past
10 years. Problems such as increased competition and insuf-
ficient infrastructure caused by the rapid development of the
industry have made Chinese-shared mobility industry enter
a bottleneck period. The standardization of the market, spe-
cifically harmonization of charging infrastructures for NEVs
for car sharing, and effective government guidance will be
important factors for the future development of the shared
mobility industry.
Demand, supply, regulation, and environmental concerns
all affect the emergence of shared mobility. Specifically, for
consumers, cost and individual factors (such as user con-
sumption habits and privacy) significantly affect consumers
adopt shared mobility. More quantitative research is needed,
including research in price elasticity on demand for shared
mobility. For companies, economic factors (the profit model
of the platform), technological factors (the development of
digital technology and smartphones), and platform factors
(availability of vehicles and parking convenience) have sig-
nificantly affected the development of shared mobility.
Policy factors (subsidy and supervision) and environmental
benefits are the government’s primary considerations for
supporting shared mobility development in China. The
development of big data makes it possible to evaluate the
potential of shared mobility emission reduction through
actual traffic travel data. Bike sharing and pure electric car
sharing are proved to effectively reducing emissions. But
overall, rebound effects and modal shift from public transit
to motorized shared mobility render it unclear how govern-
ments can better achieve carbon emissions or other environ-
mental goals through shared mobility. It hence requires
multiparty collaboration to promote the development of
shared mobility. For consumers, improving the awareness
12 J.-W. HU AND F. CREUTZIG

and acceptance of shared mobility and promoting the rapid
popularization of shared mobility among the public. For the
company, innovating in service model, business model, and
profit model to form a sustainable business model. Through
refined operations, increasing offline operation capabilities,
such as car finding, charging, parking, vehicle cleaning, and
maintenance. For the government, reasonable supervision,
support, and guidance will be effective measures to promote
the development of shared mobility. More importantly, the
government should act to guide shared mobility companies
to promote the development of electrified, intelligent, and
shared industries in order to achieve benefits between indus-
trial layout and low-carbon development.
The Chinese government has introduced several policies
differentiating between models of shared mobility. For ride
hailing, the policy focuses on supervising ride-hailing safety
and guiding industry development. For bike sharing, the
policy focuses on supporting its development and control-
ling disordered parking and the total amount of bicycles.
For car sharing, support and encouragement of NEVs in car
sharing is central. However, in terms of effect, there is still a
gap in existing governance policies. There is almost no
quantitative assessment of the effectiveness of specific gov-
ernance policies, hindering continued policy advancement.
The key issue of parking could be advanced by increasing
parking fees for private cars, such as there is always free
parking available, thus also avoiding unnecessary traffic in
search for parking. Fines and regulation can reduce disor-
dered parking behaviors of shared bike users. Formulating
quantifiable development goals is positive for the promotion
of shared new energy vehicles. Both of them are effective
ways to the governance of shared mobility.
Shared mobility will be an important driving force for
low-carbon transportation transition. Shared bicycles and
electric shared vehicles, supplementing public transportation,
have significant emission reduction potential. However, the
substitution of online car hailing for public transportation
has stimulated travel demand and frequency, increasing
urban transport GHG emissions. The cooperative and com-
petitive relationship between shared mobility and public
transportation determines the potential for GHG emission
reduction –governments and planners need to understand
how shared mobility affects the use of public transportation.
COVID-19 may accelerate changing consumer preferences
of travel modes. It is worthy to pay more attention to the
important role of shared mobility in the transformation of
low-carbon transportation following the pandemic.
8. Future research
For future research, it would be interesting to explore under
which conditions people would be ready to forgo their pri-
vate car and switch to shared mobility. It would also be
valuable to consider actual travel data to obtain clearer key
element contributions (such as consumer price elasticity)
rather than just simple questionnaire interviews. In terms of
governance, research on the effectiveness of specific govern-
ance policies is very scant, and a consistent set of indicators
would help to quantify the effects of governance policies.
Finally, empirical and modeling studies are required to iden-
tify which policies and shared mobility platforms can most
effectively contribute to ambitious climate
change mitigation.
ORCID
Jia-Wei Hu http://orcid.org/0000-0002-5329-7800
Felix Creutzig http://orcid.org/0000-0002-5710-3348
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