Bike-sharing Industry Research Articles

Perceived value, service quality and behavioral intentions towards bike-sharing services: Using an extended technology acceptance model

In recent years, the bike-sharing industry has experienced rapid development as a business model but still faces several challenges. Prior research has predominantly focused on bicycle service quality and traffic safety from the perspective of companies. This article takes a consumer-centered approach and incorporates security as a crucial perceptual factor into the technology acceptance model. Drawing on the consumer perceived value theory, we employ app perceived value and bicycle perceived value as mediating variables to construct a model of consumers' behavioral intentions to use bike-sharing. The study finds that app perceived value and bicycle perceived value are strong predictors of consumers' willingness to use bike-sharing. At the same time, app perceived value also indirectly affects their perceived behavioral control of using bike-sharing through the mediating role of bicycle perceived value. Furthermore, the perceived usefulness, ease of use, and security of the app are found to positively impact app perceived value, which in turn increases the preference for bike-sharing of consumers. In conclusion, these findings provide practical management recommendations for bike-sharing companies to balance and enhance app services and the quality of the bicycle, thus enabling the ride-hailing ecosystem to generate more sustainable urban transport solutions.

The Platformisation of Cycling—The Development of Bicycle-Sharing Systems in China: Innovation, Urban and Social Regeneration and Sustainability

In recent years, the widespread introduction of bike-sharing systems in China has had a profound impact on the daily lives of Chinese citizens and the development of the urban transport system. This article attempts to analyse the impact of this phenomenon on sustainability. The gradual improvement of related monitoring measures has facilitated the maturation of the bike-sharing industry from the initial stage of uncontrolled growth to the current stage of standardised management. By tracing the global development of bike-sharing systems with a special focus on China, this study sheds light on the platformisation of bicycles and their multiple impacts on technical, environmental, cultural, economic and social sustainability. Furthermore, this study provides a comprehensive analysis of the transformation of bicycles in China and highlights the diverse impacts of platform-based bike sharing on various facets of Chinese society. The development of different bike-sharing systems in China is a unique and crucial case to interpret the current situation of bike sharing and imagine future scenarios. In contrast to the prevailing and uniform approach derived from the experiences of Northern European countries, the massive and widespread experimentation with different bike-sharing schemes in China reveals not only potentials and aspects of sustainability, innovation, and urban and social regeneration, but also some hidden shadows similar to those in small-scale contexts such as Northern Europe. Furthermore, this study emphasises the crucial role of sustainable development principles in addressing the urban challenges specific to China.

How does extreme temperature affect shared travel? Evidence from bike-sharing order flow in China

Due to its flexibility, pro-environmental characteristics, and its contribution to solving the first or last kilometer’ problem, sharing bike has become a popular travel option for many residents, especially for short trips. This study analyses the impact of extreme temperatures on residents' shared travel and the bike-sharing industry by combining the full-sample travel data, meteorological data, and POI data in Hohhot, China. Based on the temporal and spatial characteristics of residents' travel, five patterns are distinguished by K-means clustering: basic trips, short-distance trips, round trips, time tolerance trips and distance tolerance trips. The main conclusions of the research are as follows: i) extremely low temperatures can increase the possibility of short-distance trips and round trips but reduce long-duration or long-distance travel. Extremely high temperature has a positive effect on residents' round trips and time tolerance trips but suppress short-distance trips and distance tolerance trips; ii) for long-duration or long-distance shared travel, extremely low temperature enhance the connection between sharing bikes and other modes of transportation, but the extremely high temperature has the opposite impact; iii) extreme temperature causes less substitution of sharing bikes for other vehicles in round trips. However, residents in basic trip mode prefer to use sharing bikes instead of vehicles at extremely high temperatures; iv) the total annual economic loss of shared travel caused by extreme temperatures reached 31,393.82 CNY. In addition, many residents abandon sharing bikes in favor of cars at extreme temperatures, leading to additional carbon emissions of 2585.29 kg/year. The study also provides profound policy implications for the bike-sharing industry and green travel.

Entry and competition in the European bike-sharing industry

Assessments of the bike-sharing industry traditionally focus on its effects on other markets, municipalities, or general well-being. This paper deviates from this on how the market is organised. Using information on the aggregate number of firms in cities and greater cities across Europe, we found non-proportional changes in market size with respect to changes in market structure. This is crucial information inferring changes in profits, costs, or degree of product differentiation. To distinguish between these three sources, we utilised additional firm-level data on capacity and type of service provided. Our results suggest that the non-proportional increase in market size after an entry is most likely associated with increased intensity of competition and new forms of offered services, i.e. product differentiation. We did not find evidence that newcomers have been entering with substantially larger capacities per capita compared to incumbents. From a policy perspective, entry into the bike-sharing industry has benefited consumers through market expansion and caused a potential decrease in profits.

Consumer Dishonesty in Sharing Economy: Evidence from the Bike-Sharing Industry

Consumer Dishonesty in Sharing Economy: Evidence from the Bike-Sharing Industry

Repositioning shared bikes under low-carbon policies

Low-carbon policies implemented by the Chinese government have a significant impact on third-party logistics, particularly for bike-sharing operators. This study investigated the static bike repositioning problem under low-carbon policies. Repositioning shared bikes under low-carbon policies such as emission cap, carbon trading, carbon offset, and carbon tax requires strict emission limitations and complicated routing plans. Therefore, a mixed-integer linear programming (MILP) model was formulated for the integrated planning of vehicle routes and bike allocation, aiming to minimize the repositioning cost and total imbalance penalty. An improved variable neighborhood search (IVNS) is proposed to solve this problem. The algorithm includes a route generation strategy heuristic and an improved neighborhood search operator for optimizing the route design, and a greedy heuristic for tackling loading and unloading instructions along the route. Numerical experiments show that (i) the proposed IVNS algorithm outperforms the GUROBI solver and existing method in striking a balance between solution quality and computational time; and (ii) the carbon trading policy is more flexible, not only effectively reducing emissions but also encouraging the further development of the bike-sharing industry.

Evolutionary Game Analysis of Abandoned-Bike-Sharing Recycling: Impact of Recycling Subsidy Policy

The launch of large-scale bike sharing in China has effectively met the demand for low-carbon short-distance travel, but it has also led to the emergence of a large number of abandoned bikes, which is called the “bike-sharing siege”. In order to achieve the sustainable development of the bike-sharing industry, this paper discusses how to encourage bike-sharing companies to recycle and reuse abandoned bikes and improve the efficiency of local government financial resources based on the promotion of the EPR system. We apply the evolutionary game to investigate the interaction mechanism of complex behaviors between local governments and bike-sharing companies under two subsidy policies: a fixed recycling subsidy and regressive recycling subsidy. The results show that both recycling subsidy policies have diminishing marginal effects. In addition to incentives, local governments need to unify bike-sharing parking, establish bike-sharing monitoring platforms, and reasonably allocate bike parking spaces to ensure the quality of the urban environment. Under effective regulation, by implementing a regressive recycling subsidy policy and setting a rational amount for the recycling subsidy, local governments can effectively promote the EPR system, strengthen the environmental responsibility of companies, and avoid the “free-rider phenomenon”. Based on the current situation in China, this research provides references for each local government to formulate management policies from the perspective of subsidy policy.

Bike-sharing inventory management for market expansion

Over the past two decades, bike-sharing systems have grown significantly worldwide. Compared with that of other business sectors, the means by which revenue is obtained in the bike-sharing industry is unique. When the market in a region or city is saturated, an efficient way for a firm to increase revenue is to enter a new market. In this study, we design a revenue maximization-oriented decision tool to support the operational decisions of a new competitor firm entering into competition against a local firm. It is assumed that operational-level information from the local firm is unknown to the competitor firm. A new multi-stage max–min–max robust maximization model is proposed. It aims to optimize the dynamic bike inventory to maximize the worst-case revenue that the competitor firm may achieve. The worst-case revenue is treated as the baseline revenue for the competitor firm according to which rational decisions can be made. Specifically, we construct an uncertainty set to capture the uncertainty in the bike distribution of the local firm. To work with this nonconvex model, we design a myopic method, inspired by a special two-stage model that can be solved with a customized constraint-and-column approach, for obtaining the upper and lower bounds of the potential optimal revenue in our multistage model. The results of numerical experiments illustrate that the approximation approach has satisfactory computational efficiency and generates a tight bound of the optimal baseline revenue. Sensitivity analyses show that the new competitor firm should not increase its investment in bikes when the local firm increases its quantity of bikes because of high depreciation costs. Moreover, the two firms would allocate a similar proportion of bikes to each zone when either of them provides a large number of bikes. When the firms both provide a small number of bikes, the allocation of bikes by the new competitor firm is widely dispersed, while the local firm tends to allocate bikes across several zones with high demand. Furthermore, on the premise of a given target, increasing the bike acquisition can improve the robustness of revenue estimation for the competitor firm.

Building and sustaining emerging ecosystems through new focal ventures: Evidence from China's bike-sharing industry

• Two surviving and two failed emerging bike-sharing ecosystems in China are examined. • Three strategizing forms for developing emerging ecosystems are proposed. • Socio-spatial niche experimentation offers a holistic view on ecosystem boundaries. • Strategic versatility leads to positive interplay among ecosystem (non)focal actors. • Strategic suboptimality turns negative externalities into long-term ecosystem gains. Ecosystems research has theorized that overcoming economic and coopetitive challenges is crucial for ecosystem development, yet, they largely overlook the effects of sociopolitical challenges and interplays between economic, coopetitive, and sociopolitical challenges to the emergence and viability of ecosystems. By repositioning the sociopolitical challenges in the ecosystem development model, this study investigates how new focal ventures can develop ecosystem-specific strategies to recognize and overcome a combination of economic, coopetitive, and socio-political co-evolution challenges so as to ensure a viable ecosystem . Qualitative results from a multiple-case study of two surviving and two failed emerging bike-sharing ecosystems in China reveal three strategizing forms: (1) niche experimentation, which enables new focal ventures to obtain a more holistic understanding of the co-evolution challenges in economic and sociopolitical ecosystem environments; (2) strategic versatility , whereby ecosystem-specific strategies positively and simultaneously reinforce each other and collectively overcome the multiple co-evolution challenges in two ecosystem environments; and (3) strategic suboptimality , whereby new focal ventures sacrifice the short-term efficacy of specific strategies to reinforce the long-term effectiveness of related strategies to maintain ecosystem-level competitiveness. These findings indicate the nonlinear structural and intertemporal ecosystem dynamics that need to be considered in ecosystem development literature as well as by ecosystem practitioners.

Research on Regulatory Sandbox Setting for the Development Needs of Emerging Industries

Under the background of the Fourth industrial Revolution, emerging industries have been developing vigorously. While injecting innovative vitality into the society, they have also exposed problems such as lack of supervision, difficulty in risk control and policy lag in current government governance. By sorting out the application effect and experience of "regulatory sandbox", a nascent governance tool, in different fields around the world, this paper analyzed the applicability and necessity of introducing "regulatory sandbox" into the regulatory system of China's emerging industries from the perspectives of innovation demand, regulatory philosophy and institutional logic. This paper chose the Bike-sharing industry which is extremely representative as the research object. and the "regulatory sandbox" model of Bike-sharing industry is designed to clarify the responsibilities of stakeholders such as the supervision subject, testing subject and participating user of the sandbox, and to explain the operation mechanism such as access, test and exit. Finally, this paper also analyzes the common problems of regulatory sandbox in the development of emerging industries and the special problems in the Context of China. Following this paper, the nascent governance tools such as "regulatory sandbox" and the supervision philosophy of agile governance should be applied to more emerging industries to achieve the goal of balancing innovation and risk, improve regulatory efficiency, and encourage emerging industries to exert a positive influence on society.

A Study on the Relationship between Public Derivative Big Data and Industrial Policymaking: Taking Bike Sharing as an Example

Smart government is an important part of the smart world. The use of big data analysis technology can effectively improve the government’s ability of fine management. Taking China’s bike-sharing industry as the research object, we study the relationship between public-derived big data and industrial policy. First, a feature-enhanced short text clustering method is proposed to perform topic clustering on publicly derived big data. Second, keyword extraction based on word frequency is used to quantify the text of industrial policy. Finally, time is taken as the main line to analyze the co-occurrence of clustering topics and keywords. The results show that (1) the feature enhancement method we proposed can effectively improve the clustering effect. (2) There is a great correlation between the industrial policy and the information mined by Weibo, but there is an obvious lag. Rational use of public-derived big data will effectively help the industrial policy to be released in a better and faster way.

A two-stage robust approach to integrated station location and rebalancing vehicle service design in bike-sharing systems

A bike-sharing system is a shared mobility mechanism that provides an alternative transportation mode for short trips with almost no added travel speed loss. However, this model’s low usage ratio and high depreciation rate pose a risk to the sustainable development of the bike-sharing industry. Our study proposes a new integrated station location and rebalancing vehicle service design model. This model aims to maximize daily revenue under a given total investment for station locations and bike acquisition. To address demand ambiguity due to possible bias and loss of data, we present a two-stage robust optimization model with a demand-related uncertainty set. The first stage of our model determines the station locations, initial bike inventory, and service areas of rebalancing vehicles. In contrast to the literature, which either simplifies the rebalancing process as an inventory transshipment problem or formulates it as a complex dynamic bike rebalancing problem, we assign each rebalancing vehicle to a service area composed of several specified stations. An approximate maximum travel distance for each rebalancing vehicle is also designed and constrained to ensure that the rebalancing operation can be performed within each period. In the second stage, our model optimizes the daily fleet operation and maximizes the total revenue minus the rebalancing cost. To solve our model, we design a customized row generation approach. Our numerical studies demonstrate that our algorithm can efficiently obtain exact solutions in small instances. For a real-size problem, the nearly optimal solutions of our model also reveal a high-quality worst-case performance with a small loss in mean performance, particularly when the value of the budget ratio (that is, the average number of bikes per station) is at a medium level. Moreover, the distribution of service areas depends on the bike supply and demand level at each station. The optimal fleet rebalancing operation does not have to be confined to one geographical area. Furthermore, our robust model can achieve larger mean and worst-case revenues and a higher revenue stability than a stochastic model with a small data set.

When bike-sharing crashed in China: a bumpy ride

PurposeBuoyed by the desire to reduce carbon dioxide emissions and develop sustainable urban transportation, the dockless bike-sharing industry boomed in China during 2017–2018. To the surprise of the stakeholders, this industry dramatically ebbed in 2019. The dockless bike-sharing system deviated from a problem-solver to a troublemaker in a very short period. The oversupplied and excessively discarded shared bikes caused a big waste of resources and serious pollution to the environment. In this paper, the decision-making of the key players of the industry, i.e. business operators, investors, customers and government, is analyzed through the lens of the cognitive bias. This paper aims to illuminate the process of how this innovative transport solution turned to a disastrous ending, which caused damage to urban environment and financial loss to investors.Design/methodology/approachIn this study, a qualitative analysis based on the rich secondary data sources is conducted. A rich amount of qualitative data including news reports, government policies, consulting reports and companies’ annual reports etc. were collected.FindingsThe study shows, in the product introduction period, the government, business operators, investors and consumers fell into the cognitive bias. They over focused on the positive side such as high-tech, eco-friendly, convenient image of the dockless bike-sharing solution. Thereby, the key stakeholders made irrational decisions in product adoption and management. This study moves toward increasing key stakeholders’ awareness of the imperative to reduce these biases when promoting eco-innovations. This study also recommends a prudent attitude with a rational and comprehensive thinking style in dealing with eco-innovation and the emerging sharing economy.Originality/valueTo solve the cognitive biases, this study recommends that people use rational decision-making style to examine and adopt the dockless bike-sharing solutions. Practical recommendations to tackle the existing recycling crisis of the dockless bike-sharing industry are also discussed.

News media influence on public trust in bike-sharing operators in Singapore

PurposeThe overnight introduction of tens of thousands of dockless bike-share bicycles in Singapore with its indiscriminate parking drew the attention of the media, which generated extensive news reports on the activities carried out by bike-sharing operators. Given the meteoric rise and fall of the industry, this study examines the influence of agenda-setting of news reporting on the public’s perception of the industry and the impact on the firms’ corporate reputation.Design/methodology/approachUtilizing the Reputation Quotient Index, the study content analyzed 147 textual data of online reports which were crawled over two years between 2017 and 2018 from six mainstream news organizations.FindingsOur findings showed that the news reports carried more negative frames in the headlines and body content. It also found that only five out of six dimensions of the Index were emphasized with varying degrees of importance, indicating that the corporate reputation as determined by the media reports did not collectively represent the operators’ past actions and results with valued outcomes.Practical implicationsPractical implications discussed included the need to integrate corporate strategies into public relations programs and the importance of engaging the media to demonstrate congruence between business objectives and positive social impact on society.Originality/valueAlthough the study limited its data collection only to online media reports, it is one of the few research to provide empirical evidence concerning the media’s influence on the public’s perceptions and reputation of the nascent bike-sharing industry.

Life cycle carbon dioxide emissions of bike sharing in China: Production, operation, and recycling

Recent global environmental initiatives designed to achieve a more sustainable society include the United Nations’ sustainable development goals (SDGs) and the Paris Agreement. While the shared economic model has long been linked to the creation of the sustainable use of resources, one problem encountered by the bike sharing is whether the current management model can maintain the focus on sustainability in China. Based on the amount of resources consumed during bike production, operation, and recycling, this paper aims to use life cycle carbon emission assessment to calculate an emission reduction threshold for bike-sharing industry. The research obtained energy consumption data from the OFO Curve bike, which is the most commonly used type of bike sharing in China. Calculating the average distance traveled and number of times each bike was used per day via the Baidu Map Application Program Interface, we found that the average number of times each bike was used per day was 4.552, and the average riding distance was 0.356 km. Additionally, the overall utilization of shared bikes averages about 50%. Further results show that the whole life cycle carbon footprint of one bike is 34.56 kg CO2. The power generation by incineration produces 1.9916 kg CO2 in less than a landfill. If a bike is deposited directly in a landfill, it will take 31 years to degrade. The final calculations show that based on the current number of bikes, each used at least 686 days to achieve a net positive reduction in emissions. This paper provides a basis for capacity management and operation management of shared bikes from the perspective of pro-environment and provides a new angle for the research on environmental impact of sharing economy.

Understanding sustainable business model: A framework and a case study of the bike-sharing industry

Supported by the Internet of Things (IoT) technology, bike-sharing services have become increasingly popular in recent years. For example, in China, by the end of 2017, the number of service users had doubled in half a year to reach 221 million users (28.6% of the country’s Internet users); the market for bike-sharing services equated to £1.18 billion, an eightfold increase from 2016. In this research, we focus on the sustainability of the dockless bike-sharing industry, and analyze how firms achieve sustainability through innovating on business models to adapt to business environments. We have developed a framework of sustainable business model analysis that links business model innovation with the business environment. The sustainable value proposition dimension of the framework includes social-environmental benefits as an element. Applying this framework to analyze the case of Mobike, a leading dockless bike-sharing operator, we disclose the paths of its business model innovation in China and the UK determined by the business environment. The proposed framework can be used in future research of sustainable business model analysis and design. The case study findings extend knowledge about the emerging dockless bike-sharing industry. Practical implications are drawn from the case study for firms within the sharing economy to achieve sustainability through business model innovation, and for the government to support the sharing economy to achieve sustainable development.

Sustainable Governance of the Sharing Economy: The Chinese Bike-Sharing Industry

Socialist countries, such as China, have stressed the importance of an equitable society where citizens work together. Thus, the sharing economy (e.g., the bike-sharing industry) could be one of the challenges determining the future of China, as the initial bubble of the bike-sharing industry collapsed in 2017, with many problems stemming from the users’ deposits that were lost and the depletion of the investment funds, resulting in numerous malfunctioning bikes every day. This paper evaluates the bike-sharing industry in terms of sustainable governance in the future and identifies its factors. Therefore, we use the structural equation model based on survey questionnaires and find that most of the input variables of the perceived rational (PRV) and emotional values (PEV), perceived risk (PR), and externalities (EXT) are not very successful in promoting the sustainable governance of the bike-sharing industry. However, using the bootstrapping simulation approach, we find that the role of modulators such as satisfaction and sustainable management factors are statistically significant. The modulating effect of a user’s satisfaction on the intention of continuous use based on all four inputs of PRV (0.304), PEV (0.298), PR (−0.156), and EXT (0.263), as well as the other indirect variables of sustainable management, such as environmental factors (0.284), is shown to be statistically significant. Based on these modulating effects, we conclude that the sharing economy, represented by the bike-sharing industry, could be one of the most important business cases for the future of China, but only if it is strongly supported by the public. Therefore, to help the industry get out of its current slump, we propose that the bike-sharing companies put in more diverse efforts to employ multi-use types of innovation with practical benefits such as coupons for the nearest shops, and social functions that enhance the quality of life such as mileage contribution from bike sharing for disabled people. Evidently, the Chinese government should eliminate “the over-supply issues” through appropriate market governance and increase its efforts toward a better public–private partnership (PPP), as the sharing economy should be based on the harmonization of all interest groups to eventually create value.

Optimal pricing strategy of a bike-sharing firm in the presence of customers with convenience perceptions

In the bike-sharing industry, convenience is a critical factor that impacts customers’ travel behavior and bike-sharing firms’ profits. In this paper, we investigate how a bike-sharing firm should develop its pricing strategy when its customers are concerned about the convenience of the trip. Specifically, we develop a model in which a monopolistic bike-sharing firm leases bikes to customers. We use hassle costs to measure the convenience factors. We first examine customers’ travel behavior in the absence of hassle costs. We find that customers’ valuation of the trip and the time-saving advantages of bike-sharing make potential customers more likely to use the bike-sharing service. We analyze the bike-sharing firm’s decision in different scenarios by examining its profit-maximizing pricing strategies. We present several interesting and useful results that are somewhat counterintuitive. When bike-sharing has an advantage in hassle costs, increasing prices increases the demand for bike-sharing because reducing hassle costs saves time for many high-valuation customers, who transition from public transit systems to bike-sharing. By contrast, when bike-sharing has a relative disadvantage in hassle costs, even if the firm reduces prices to attract customers, the lower price cannot neutralize the adverse effects of the hassle cost advantage enjoyed by public transit systems. Public transit systems thus dominate all travel choices. Second, improving the convenience of transportation may not always increase customer surplus, but a low hassle cost yields high social welfare. We also provide guidelines for bike-sharing firms that may help them increase participation in bike-sharing and improve their profits.

Building emerging ecosystems by focal new ventures: Evidence from the bike-sharing industry in China

For ambitious new ventures, creating and developing a new ecosystem is a necessary, yet tedious, task. Although extant ecosystem research theorized that overcoming economic and coopetitive developm...

System Dynamics Modeling of Dockless Bike-Sharing Program Operations: A Case Study of Mobike in Beijing, China

In China, dockless bike-sharing programs (DBSPs) have changed people’s travel modes, alleviated urban traffic congestion, and reduced carbon emissions. However, a number of DBSPs have experienced financial crises since 2018. This means that research on DBSPs must be considered not only in terms of the environment and technology, but also in the operation of the program. In this paper, we modeled the DBSP operations in a certain area using a system dynamics simulation approach. The main purpose was to explore the dynamics of the program’s operation process and evaluate possible improvement strategies for maximizing the revenue of the overall DBSP. Specifically, the analysis focused on the economic profits of DBSPs in an environment of competition and government regulation. The research findings revealed that the dockless bike-sharing industry has great economic profits, but in the current environment, the market needs to be regulated by the local government. If a DBSP does not introduce new technologies or find new profit channels, it will be difficult to develop sustainably by only relying on riding profits. In addition, we provide a case study of Mobike’s operations in Beijing to support these findings and validate the developed model. Finally, we discuss Mobike’s possible improvement strategies.