Bicycle sharing programs provide a sustainable mode of urban transportation. Although cities across the globe have developed these systems for their citizens and visitors, usage rates are not as high as anticipated. This research uses the technology acceptance model as the basis to understand one’s intention to adopt bicycle sharing programs. Using survey data derived from 421 participants in Beijing, China, the proposed covariance-based structural equation model consisting of perceived quality, perceived convenience, and perceived value is found to predict 50.5% of the variance in adoption intention. The findings of this research contribute to theory and practice in the burgeoning literature on public bicycle systems and sustainable urban transportation by offering a theoretical lens through which to consider system adoption, and providing information to practitioners as to what factors might contribute most to adoption.

Purpose: Rare but high impact (R-HI) disruptions, which are caused by legal changes, socio-technical accidents, or natural disasters, are becoming more frequent and have strong short-term and long-term impacts on performance. Meanwhile, the short-term perspective of managers leads to adoption of mitigation strategies with lower investments and immediate performance improvement. The purpose of this paper is to provide insights on supply chain collaboration (SCC) to establish so-called twin-objective strategy to help both risk mitigation (through moderation effects) and performance improvement (through a direct positive impact). Moreover, power position will be considered as the control variable. Design/methodology/approach: A cross-sectional approach was adopted with primary data collected through a survey in China. Data were analyzed using structural equation modeling with partial least squares estimations. A sub-group model analysis was applied to test the effect of the control variable. Findings: The findings verify that SCC has both a direct positive impact on performance and moderation effects on the relationships between sources of R-HI disruptions and performance. The results of sub-group model analysis illustrate that both powerful and weak focal firms benefit from SCC, but in different ways. Originality/value: The study shows that the allocation of gains from collaborative advantage should be added to the theory-building of relational view. Meanwhile, the research extends the focal firm’s context to its supply chain’s context so that classic contingency theory can be extended to adequately explain supply chain management phenomena.

Severe traffic congestion is now a common problem in major cities worldwide, causing huge economic, environmental, and social losses to overall welfare. Governments are now considering congestion charging as an effective way to manage congestion. However, since congestion charging has not yet been implemented widely, the public remains uncertain about it. Few scholars have explored public uncertainty about congestion charging. This paper examined how the public perceived uncertainty toward fairness and efficiency affects willingness to accept congestion charging. Through an experimental study of stated preference, this paper analyzes the influence of observable variables and unobserved latent variables on public acceptability and compares the results with a traditional discrete choice model. The results indicated that the public’s perceived uncertainty about congestion charging will have significant negative effect on acceptability and that the perception of fairness has an even larger effect. As for uncertainty about the effectiveness of congestion charging on alleviating congestion, the implementation efficiency of the government is the most significant. For uncertainty about fairness, whether charge collection and revenue allocation are reasonable is the most significant. These findings provide an empirical basis for reducing public uncertainty and increasing public acceptance of congestion charging.