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In China, dockless bike-sharing programs (DBSPs) play a significant role in promoting the goals of sustainable urban travel and carbon emissions reduction. However, the sustainability of DBSPs is increasingly being challenged as various issues associated with different stakeholders emerge. While numerous studies have focused on the barriers to traditional bike-sharing programs, the sustainability performance of new-generation DBSPs is largely overlooked. It is accordingly imperative to understand the primary challenges that impede the sustainability of DBSPs and to consider what stimulative measures can be taken. In this study, we investigate the factors that are critical to DBSPs’ sustainability from a network perspective. Stakeholder-associated factors and their interrelations were identified via literature analysis and interviews, and the social network analysis (SNA) method was employed to recognize the critical factors and links in DBSPs. As a result, 10 critical factors and 10 major interactions were identified and further classified into six challenges. Sharing transport schemes, legislative perfection, public private partnership (PPP), and product lifecycle management (PLM) were proposed to govern these challenges. This paper contributes to the existing body of knowledge of bike-sharing programs via a network approach that integrates the key influencing factors with those factors’ associated stakeholders. Furthermore, these findings provide the government and operators with implications for mitigating the tough challenges and facilitating the sustainability of DBSPs.

The development of the digital economy has changed human lifestyles and production and provided a new approach to achieving the United Nations Sustainable Development Goals (SDGs). As an important indicator reflecting both economic growth and ecological protection, the green economic efficiency (GEE) indicator is employed to express the level of sustainable development. By building an indicator system, introducing carbon dioxide emissions as an unexpected output and using a super-efficient slack-based measure (SBM) model, the the GEE of 273 cities in China are calculated. The development level of digital economy is calculated through principal component analysis (PCA). Unlike previous provincial-level studies, this study focuses on analyzing at the urban level. This study then uses a fixed effect model to analyze the effect of the digital economy on urban GEE. Based on various aspects, the transmission mechanisms of the digital economy on GEE have also been deeply analyzed. The results indicate that the digital economy has a positive effect on GEE. This conclusion is validated by endogeneity analysis and other robustness tests. The digital economy has a positive influence on urban GEE in Eastern, Central and Northeastern China. In large cities, medium-sized cities and cities with stricter governmental environmental regulations, the effect of the digital economy on GEE is more prominent. The mechanism analysis indicates that the digital economy mainly promotes urban GEE through the technological innovation effect, industrial structure optimization, energy structure transformation and market-oriented development. This study clarifies the role of the digital economy in advancing GEE and provides a reference to promote ecological development in developing countries.

Mapping knowledge domain (MKD) is an important research technology in bibliometrics. It provides a visual perspective for researchers and helps researchers to clearly understand the general situations of specific research fields. Presently, MKD has been widely used in fields such as ecology and transportation safety. In this paper, we conduct a systematically bibliometric analysis of the development trend on urban vitality research by using VOSviewer software, and this work is based on the related articles published in the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) between 1998 and 2018. In the implementation, we firstly introduce the annual numbers of articles, source journals, highly cited papers, and production countries relating to urban vitality research. Then, we adopt a keywords co-occurrence analysis to explore the topic distribution, research frontiers, and research trends of urban vitality research intuitively. Overall, the Mapped Knowledge Domain method has proved to be an effective way to assess research trends in specific disciplines and to contribute to researchers and governments with respect to management and decision-making on issues of science.

Abstract The vast output of household waste has become a terrible environmental problem with the rapid growth of social development and population in China. Several pilot cities have introduced related policies to regulate urban residents in sorting household waste. Although existing research has concentrated on sorting waste intentions and behaviours amongst urban residents, especially in pilot cities or other large cities, waste produced in non-city areas should not be neglected. Accordingly, this study identified the determinants influencing waste sorting intentions and behaviours of residents in rural or urban–rural integration areas by incorporating the theory of planned behaviour and norm-activation model. A total of 241 residents completed valid questionnaires, and the collected data were empirically analysed through covariance-based structural equation modelling. Results implied that behavioural attitude and perceived behavioural control were the most significant predictors of sorting waste intention and behaviour. Meanwhile, personal moral norms and subjective norms also presented positive effects on behavioural intention. Awareness of consequence had a significant influence on personal moral norm rather than behavioural intention. After empirical analysis, this study proposed several managerial implications regarding waste problems in rural and urban–rural integration areas in China.