Last-mile delivery of e-commerce is a complex mix of simultaneous delivery of goods and pickup of returned goods. With return rates being substantial in the e-commerce sector, this problem is highly relevant. To address this challenge, this study formulates a rolling horizon simultaneous pickup and delivery problem with time windows in a two-way logistics system. The proposed approach integrates a multi-objective mixed-integer linear programming model with a rolling-horizon framework, allowing forward deliveries and reverse pickups to be postponed based on different priorities and penalties, while capturing the interdependence between outbound and return flows. Economic efficiency, environmental impact, and social factors are explicitly incorporated into the objective function. For large-scale instances, an adaptive large neighborhood search with simulated annealing metaheuristic is designed and compared against a weighted-sum mixed integer linear program approach. Numerical experiments on Solomon datasets demonstrate that the proposed method efficiently achieves high-quality solutions, reveals trade-offs among sustainability objectives, and shows how coordinating forward and reverse flows can enhance operational adaptability. The results also highlight an unintended outcome of the proposed rolling-horizon planning: generation and propagation of backlog of demand. This highlights the need for adaptive mechanisms that can manage such issues in multi-period planning.

Introduction: Responsible businesses actively engage in climate action, health, and safety initiatives as part of their corporate strategy. The outcomes of such initiatives could play an essential role in forming customers' loyalty. However, very few studies have aimed at understanding the relationship among such factors in the public transport (PT) context. As such, this investigation explores the direct impact of perception of health benefits, environmental benefits and safety on passengers’ loyalty intentions towards a PT service. The mediating roles of image and perceived value on these links are also considered. Methods: Partial Least Square - Structural Equation Modeling (PLS-SEM) was utilised to assess the measurement and develop structural models. A multi-group analysis (MGA) was also deployed to test the significant group differences. For this investigation, a sample of 866 individuals was collected from two cities in Vietnam. Results: The results indicate that there were significant relationships between these constructs and the loyalty intention of passengers. The perception of health benefits and image were the main factors affecting passengers’ loyalty in both cities. In contrast, the perception of environmental benefits had the weakest effect on the loyalty intention towards bus services. Conclusions: The results from this study could support the development of interventions to increase PT ridership in low-income countries. Promotional efforts to boost PT ridership should focus on highlighting the health benefits of using PT for passengers and the community. PT operators were also recommended to convey societal and environmental contributions through logos, graphic design, mission statements, slogans, and media relations to improve the image of the bus services.