This article determines the quality factors which improve the satisfaction of logistics services, and the specific evaluation items that customers value. Moreover, this study verifies the moderating effect of consumers on the perceived importance of last-mile logistics services, and its impact on logistics service satisfaction. Through a literature review, the conceptual model is determined, and measurement scales are developed. Furthermore, we collect data through online surveys and employ structural equation modeling, hierarchical regression analysis, and importance–performance analysis methods in order to analyze the collected data, and to test the research hypotheses. The findings of this study are as follows. First, the qualities of personal contact, timeliness, and empathy in the fresh food e-commerce logistics service quality evaluation system have a significant positive impact on the fresh food e-commerce logistics service consumer satisfaction, but the delivery quality and information quality are not significant. Second, consumers’ perceived importance of last-mile logistics services has a positive and significant impact on the consumer satisfaction of fresh food e-commerce logistics services. Moreover, as a moderating variable, its moderating effect has limitations: it only affects the relationship between information quality, timeliness quality, empathy quality, and consumer satisfaction. Finally, in the three evaluation dimensions of information quality, timeliness quality, and empathy quality, specific items that need to be further improved are identified. This study enriches and supplements the empirical research in the field of fresh food e-commerce logistics, and provides academic literature with a reference value for fresh food e-commerce logistics enterprises.

In recent years, the frequent occurrence of rainstorms has seriously affected urban–public transport systems. In this study, we examined the impact of rainstorms on the vulnerability of urban–public transport systems consisting of both ground bus and metro systems, which was abstracted into an undirected weighted Bus–Metro complex bilayer network (Bus–Metro CBN) and the passenger volume was regarded as its weight. Through the changes in the node scale, network efficiency, and passenger volume in the maximal connected component of the Bus–Metro CBN, we constructed a vulnerability operator to quantitatively calculate the vulnerability of the Bus–Metro CBN. Then, the flow-based couple map lattices (CMLs) model was proposed to simulate cascading failure scenarios of the Bus–Metro CBN under rainstorm conditions, in which the rainstorm is introduced through a perturbation variable. The simulation results show that under the condition of passenger flow overload, the network may have a two-stage cascading failure process. The impact analysis shows that there is a rainstorm intensity threshold that causes the Bus–Metro CBN to collapse. Meanwhile, we obtained the optimal node and edge capacity through capacity analysis. In addition, our analysis implies that the vulnerability of the Bus–Metro CBN network in most scenarios is mainly caused by the degradation of network structure rather than the loss of passenger flow. The network coupling strength analysis results show that the node coupling strength has greater potential to reduce the vulnerability than edge coupling strength. This indicates that traffic managers should prioritize controlling the mutual influence between bus stops (or metro stations) to reduce the vulnerability of the Bus–Metro CBN more effectively.

The rapid development of modern logistics and e-commerce highlights the importance of exploring various modes of transportation in the last-mile delivery (LMD) process. However, no comprehensive studies exist in the literature exploring all modes of LMD transportation, the changes in these transportation modes, and the commonalities between them. In this study, we address this gap by conducting a systematic review of 150 academic journal articles utilizing a combination of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) content analysis and text mining analysis. Nine primary transportation methods (parcel lockers, autonomous drones, trucks, bicycles, crowd logistics, electric vehicles, tricycles, autonomous robots, and autonomous vehicles) are identified in this research. Additionally, we provide an analysis of the historical changes in these transportation modes in LMD. Using a bottom-up induction method, we identify the three major clusters of scholarly focus in the LMD literature: emphasis on value co-creation between consumers and logistics providers, practical delivery performance (path optimization or algorithms), and environmental friendliness. Further, we analyze the main themes under each cluster, leading to the identification of opportunities, challenges, and future research agendas. Our findings have implications for scholars, policymakers, and other stakeholders involved in LMD transportation modes.