Privacy by design (PbD) has attracted considerable attention from researchers and information security experts due to its enormous potential for protecting private information and improving the privacy and security quality of information technology products. The adoption of PbD among information engineers is currently limited owing to its innovativeness and the distinctive traits of the information technology industry. Utilising the Technology Acceptance Model as a framework, this study innovatively explores the pivotal factors and mechanisms that influence information engineers’ decision-making in the adoption of PbD from the viewpoint of the perceived work risk. In this empirical research, professional information engineers were invited to complete a questionnaire survey. After analysing the data using partial least squares structural equation modelling, the results reveal that information engineers’ perceived work risk in PbD (PWRP) negatively affects their perceptions of the usefulness and ease of use of PbD. This negative perception subsequently reduces their intention to implement PbD (INTP) and adversely impacts their attitudes towards implementing PbD (ATTP). Furthermore, the study findings reveal that a positive ATTP among engineers boosts their INTP and positively influences their behaviours regarding information security. This study provides an in-depth examination of these findings and lays a solid theoretical groundwork for the further promotion and implementation of PbD in information technology enterprises. Moreover, the findings offer invaluable support for management decisions in both information technology companies and information security regulatory authorities, significantly contributing to the expansion and deepening of research in the field of PbD.

Infectious healthcare waste is a kind of high-risk material. With the continuous outbreak of infectious diseases in recent years, infectious healthcare waste collection (IHWC) has garnered significant attention. As infectious healthcare waste volume has increased substantially, many countries have chosen to incorporate transit points into their IHWC process to leverage consolidation effects. Besides, transporting infectious healthcare waste involves transport risks, and the storage of such waste at medical institutes and transit points also poses storage risks. In this paper, a vehicle routing problem for IHWC with multiple types of risks and transit points (VRP for IHWC-MR-TP) is proposed, considering the complexity introduced by the simultaneous existence of transport risks, storage risks, and transit points, and aiming to simultaneously minimize the total cost and the maximum risk. A bi-objective model of VRP for IHWC-MR-TP is developed. Based on the characteristics of the problem, two different solution methods are proposed, including a global solution method from a global perspective and a two-stage solution method that divides the problem into two stages for optimization. The model and solution methods are tested through numerical experiments. The results indicate that compared to the global solution method, the two-stage solution method can reduce the solving time by an average of 26.6%, while decreasing the Hypervolume by only an average of 0.5%. Finally, managerial insights are derived through sensitive analysis. The results demonstrate that an increase in collection vehicle (CV) speed results in lower cost and risk, therefore decision-makers should pay attention to CV maintenance and driver training in normal operations to ensure that relatively high CVs’ speeds can be maintained during IHWC. Furthermore, as the capacities of CVs increase, both cost and risk demonstrate a significant downward trend, suggesting that decision-makers should choose CVs with larger capacities for IHWC.

Electric vehicle (EV) charging spots require frequent inspections to identify potential safety hazards, and charging piles in charging spots exhibit a significant failure rate, necessitating maintenance. The efficiency and quality of inspection-maintenance are crucial components in the operation and management of charging spots, directly affecting the operation cost, service level, and user experience. The inspection-maintenance of EV charging spots requires two different types of personnel, and the impact on customer satisfaction cannot be ignored. In addition, the large-scale charging spots have further increased the difficulty of routing. A novel routing optimization problem for large-scale inspection-maintenance of EV charging spots is proposed in this paper, considering multiple types of personnel and composite customer satisfaction. While inspections can be carried out by general personnel, maintenance requires professional engineers. Composite customer satisfaction is with respect to the waiting time for maintenance of faulty charging spots and the duration of absence of professional engineers in the working station. A bi-objective routing optimization model is proposed, minimizing the cost of arranging personnel and traveling between charging spots, and the loss of composite customer satisfaction simultaneously. Due to the large scale of the problem caused by the enormous number of charging spots, an effective multi-stage solution approach is proposed. Finally, numerical experiments, managerial insights, and a case study are provided. The purpose of this research is to help the operator to decide the routes for inspection-maintenance of EV charging spots and offer valuable guidance in balancing operational efficiency with customer satisfaction.

Vehicle sharing is a common shared logistics model, where logistics enterprises can rent vehicles from third-party entities through vehicle sharing platforms to participate in transportation. However, it also introduces new challenges to the management of hazardous materials transportation. Logistics enterprises encounter a dual decision-making challenge: optimizing routes and vehicle acquisition strategies through rental. Moreover, vehicle rental generates additional cost and risk, while the variability in the number and types of rented vehicles introduces complex operational impacts. This study proposes a novel vehicle routing problem for hazardous materials transportation based on vehicle sharing mode, and develops a bi-objective mixed-integer programming model. Based on the characteristics of this problem, an improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) has been designed, with improvements including initial solution generation, validity test of initial solutions, dual-operator selection strategy, and adaptive hybrid mutation operator. Through numerical instances, the model and algorithm were validated. Finally, sensitivity analyses have uncovered important insights governing the transportation cost and risk of hazardous materials when considering vehicle sharing, thereby informing managerial implications for logistics enterprises.

When deciding on the path of a truck carrying hazardous chemicals, it is imperative to consider not only the associated transportation costs but also the imperative to reduce the risk. Grid network is a typical urban road network structure. It is necessary to consider the flexibility afforded by parallel roads when conducting harmful chemicals transportation. This paper studies the path selection of harmful chemicals transportation on a grid network. The grid network is formally defined, and a path selection problem is introduced along with its mathematical representation. A fast solution method is proposed based on the characteristics of the grid network. Taking the local network in Xi’an City as an example, the effectiveness of the proposed solution method is verified.