In recent years, there has been rapid development in bicycle-sharing systems (BSS) in China. Moreover, such schemes are considered promising solutions to the first/last mile problem. This study investigates the mode choice behaviors of travelers for first/last mile trips before and after the introduction of bicycle-sharing systems. Travel choice models for first/last mile trips are determined using a multinomial logit model. It also analyzes the differences in choice behavior between the young and other age groups. The findings show that shared bicycles become the preferred mode, while travelers preferred walking before bicycle-sharing systems were implemented. Gender, bicycle availability, and travel frequency were the most significant factors before the implementation of bicycle-sharing systems. However, after implementation, access distance dramatically affects mode choices for first/last mile trips. When shared bicycles are available, the mode choices of middle-aged group depend mainly on gender and access distance. All factors are not significant for the young and aged groups. More than 80% of public transport travelers take walking and shared bicycles as feeder modes. The proposed models and findings contribute to a better understanding of travelers’ choice behaviors and to the development of solutions for the first/last mile problem.

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Implications: Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

With the rapid growth of E-commerce business, logistics service, especially the last-mile distribution, has become one bottleneck, which leads to the rise of coordination complexity of logistics service supply chain (LSSC). This research, based on Stackelberg’s game theory, studies the coordination of a new three-echelon LSSC consisting of an E-commerce mall, an express company, and a terminal distribution service provider and investigates the optimal solutions and profits for each party within the semicentralized and centralized LSSC alliances, respectively. To accomplish this, it firstly shows that the three-echelon LSSC can lead to global optimum under the centralized decision-making scenario and then deploys the contract coordination schemes, including revenue sharing, cost sharing, and unit delivery price contracts, in three semicentralized alliances, so as to achieve the same performance of the centralized decision-making scenario, in which each party in the LSSC can achieve the win-win situation. Finally, numerical examples are provided to illustrate the feasibility and the effectiveness of the proposed coordination strategies. This study enriches the coordination theory in the field of LSSC and provides managerial insights for decision makers in LSSC.

This study analyses the effects of individual and trip characteristics on passenger travel choice behaviours when presented with all‐stop, skip‐stop, and transfer services. Bus stops are classified into two types: an ‘AB Station’ provides both all‐stop and skip‐stop services and an ‘A Station’ provides only all‐stop service. Passenger travel choice behaviours ‘from AB to AB’ and ‘from AB to A’ are studied based on travel choice probabilities. A stated preference survey was conducted in Beijing to collect individual and trip characteristics for various travel circumstances and used to develop passenger choice probability models based on logit model. The results show that the probability of choosing skip‐stop service increases with the increase in travel distance and the decrease in in‐vehicle time; transfer service is not popular, even for a long trips; skip‐stop and transfer services are more attractive to passengers taking a mandatory trip; there are differences in choice behaviours between male and female passengers; compared to high‐income passengers, low‐to‐middle income passengers exhibit a lower probability of choosing transfer service because of the additional travel cost. This study contributes to predicting future demands for different bus services, the implementation and optimisation of skip‐stop strategies, and bus schedule improvement.

Travel happiness has drawn increasing attention in recent years. However, the empirical research in developing countries’ context is very limited, and few studies consider both cognitive and affective evaluations during traveling. This study uses web-based survey data collected in Beijing, China, and applies multiple regression analysis to examine impacts of sociodemographic attributes, travel characteristics, residential environment, mode consonance, self-evaluation, and health conditions, on travel happiness. Satisfaction with Travel Scale (STS) is used to measure travel happiness. Results show that for trips using active travel modes, traveling by walking has higher travel happiness than by nonmotor vehicles. For those trips traveling by motor vehicles, company shuttle bus trips have the highest travel happiness ratings, followed by automobile trips and public transport trips. Transport mode consonance is significantly positively correlated with travel happiness. Residential environment, self-reported optimism, and daily happiness have great positive impacts on travel happiness. Living in suburban areas is more satisfying for walking and car trips, but travel frequency, travel duration, and perceived travel time length have significant negative effects on travel happiness. Public transport use with friends is enjoyable, but unpleasant with work partners. More happiness when listening to music/radio or reading during traveling is demonstrated. Finally, policy implications and potential extended research topics are recommended.