Jiang Wu

Federated learning offers a promising approach for cross-institutional financial risk control modeling but encounters two key challenges in practice: feature space heterogeneity and low sample overlap rate. Current federated transfer learning methods often rely heavily on sufficient overlapping samples or explicit feature alignment. However, these approaches frequently result in negative transfer when enforced alignment is applied in highly heterogeneous environments. To address this issue, we propose FedVI, a novel federated transfer learning framework that integrates tabular-to-image conversion and meta-learning mechanisms. Moving beyond conventional methods that rely on sample-level alignment, FedVI employs a federated dual-stream feature alignment strategy to securely reconstruct a unified global feature map across institutions. Subsequently, FedVI integrates federated Image Generator for Tabular Data (IGTD) with tabular Transformer technology to convert one-dimensional tabular data into two-dimensional visual-semantic tensors. These tensors effectively fuse spatial topology and semantic information while embedding an independent Mask channel to explicitly retain the true missingness patterns of features. Finally, FedVI adopts the Model-Agnostic Meta-Learning (MAML) architecture to facilitate global parameter optimization. We evaluated FedVI on the real-world Lending Club credit dataset and Home Credit Default Risk datasets under highly heterogeneous federated settings (i.e., heterogeneous feature spaces across three clients and scarce overlapping samples). The results reveal that FedVI achieves competitive performance against advanced baselines such as FedProx, FedRep, and FedKT, particularly in recall and F1-Score. These findings indicate that FedVI can effectively support cross-domain adaptation under heterogeneous federated learning settings.

New energy vehicle promotion (NEVP) is of great significance for the green and low carbon development of urban transportation. Based on the panel data of new energy vehicle sales, carbon emissions, and air quality in Chengdu, China, from 2014 to 2024, this paper employs multiple linear regression, distributed lag and multiple mediation pathway models to empirically examine the environmental benefits of NEVP. A heterogeneity analysis is also conducted by integrating the distribution of charging stations across urban circles. The results show that: (1) In the multiple mediation pathway model, the total effect of NEVP includes direct effect and indirect effect. Based on the total effect, the total carbon emission from the effect of NEVP is reduced by about 3.95% of the total carbon emissions, and 40% of carbon emission within the transportation sector in Chengdu. NEVP in Chengdu has a significant direct emission reduction effect, accounting for about 39.80% of the total effect, with the annual average carbon emissions being reduced by about 432,800 tons, accounting for about 1.57% of the total carbon emissions in Chengdu. In terms of indirect effects, NEVP significantly reduces carbon emissions through three pathways: industrial structure upgrading (1.02%), green consumption transformation (1.12%), and technological innovation (0.25%). However, the benefits of NEVP on improving urban air quality are limited. (2) The lag effect analysis shows that the environmental benefits of NEVP exhibit distinct characteristics of time lag and long-term persistence. (3) The environmental benefits show significant sub-circle heterogeneity. As carbon emissions decrease, the air quality of the central urban zone (the first circle) and the suburbs (the second circle) improves significantly, while the impact on the outer suburbs (the third circle) is not significant. There is an imbalance in the layout of charging piles in Chengdu. This research offers empirical evidence and policy insights for the green and low carbon development of urban transportation.

The new energy vehicle (NEV) industry has become one of the most important industries in China’s economic development. Based on the panel data of 27 provincial administrative regions in China from 2011 to 2022, combined with the random effect panel of the Tobit model and the Bootstrap method to test the multiple intermediary paths, this paper studies the impact of new energy vehicle promotion (NEVP) in China on regional green development, taking into account the intermediary effect and regional heterogeneity of NEVP on the green development level (GDL). The results show that NEVP significantly promotes the GDL. The mediating effect of NEVP to improve local-level green development through the digital economy level is significant in the eastern region, while in the central and western regions, it is not significant. NEVP can significantly promote the upgrading of regional industrial structure and the construction of transportation infrastructure in the eastern, central, and western regions so as to improve the local GDL.

E-commerce platforms have widely embraced the paid membership system as a sustainable and effective customer management method to increase repurchase rates and offer value-added services to loyal consumers. As a common means of member benefits and a crucial link for interaction with direct consumers, logistics service is related to the platform’s sustainable operation. In this context, this paper studies retailers’ and e-commerce platforms’ cooperation strategies regarding logistics services under paid membership systems, and analyzes the impact of paid membership system on optimal outcomes. The results indicate that, in the case of the basic-service contract, sales profits decrease but membership fees increase as membership service quality increases. In accordance with the terms of the full-service contract, the platform would lower the commission fee and membership fee as the membership service quality improves. The retailer and the platform tend to sign basic-service contracts when the third-party logistics fee is low-cost, since there is a win–win interval. We also extend the logistics plan to include self-delivery and switch to centralized decision making, and we find that the basic-service contract’s win–win interval persisted. Our results reveal the fundamental connection between paid membership systems and logistics cooperation strategy, serving as a theoretical guide for the decision makers.

The operation process of the Chinese provincial industrial system consists of four stages, namely the production (P) stage, wastewater treatment (WWT) stage, solid waste treatment (SWT) stage, and sulfur dioxide treatment (SDT) stage. Based on this structure, a four-stage data envelopment analysis (DEA) model is developed to evaluate the eco-efficiency, production efficiency, wastewater treatment efficiency, solid waste treatment efficiency, and sulfur dioxide treatment efficiency of provincial industrial systems in China, considering the undesirable output and variable returns to scale (VRS). Based on the objective data from 2011 to 2015, the following conclusions are drawn: Firstly, the eco-efficiency of the Chinese provincial industrial system has not been significantly improved during the study period, and the average eco-efficiency score is low, only 0.3805. Secondly, the reasons for the low eco-efficiency of the industrial system are different in the Eastern, Central, Western, and Northeastern regions. Thirdly, compared with the P stage, industrial WWT stage, and SWT stage, the efficiency of SDT stage is still relatively weak.

Sustainability has been a challenging issue in the transportation industry, which necessitates obtaining a better measurement of transport sustainability performance. To appropriately measure performance, this paper presents a hybrid approach based on the hierarchical Bayesian network model (BNM) and Principal Component Analysis (PCA). The proposed BNM encompasses social, economic, environmental, and technological dimensions, where each dimension consists of various subdivisions. The Conditional Probability Table of the model is determined by PCA. Twenty-three sustainable transportation indicators involved in the different stages of traffic management are used to kick off the calculation and probability propagation. The results show that the overall transport sustainability of the selected cities is generally at a medium level, indicating that there is much room for further improvement. The sustainability-economic coupling analysis exhibits the nonlinear relationship between sustainability and economic level, revealing that economic growth does not necessarily lead to the enhancement of the transport sustainability. Additionally, the sensitivity analysis reveals that Accessibility, Serviceability, Reliability, and Innovation demonstrate an upward trend, indicating their great effect on transportation sustainability. Last, the policy implications of this study can not only offer a solution for the current needs of transportation systems but also serve as more transparent decision-making to develop a sustainable transportation system in the future.

Bipolar fuzzy set theory has been successfully applied in some areas, but there are situations in real life which can’t be represented by bipolar fuzzy sets. However, all the existing approaches are unsuitable to describe the positive and negative membership degree an element to an uncertain linguistic label to have an interval value, which can reflect the decision maker’s confidence level when they are making an evaluation. In order to overcome this limit, we propose the definition of interval-valued bipolar uncertain linguistic sets (IVBULSs) to solve this problem based on the bipolar fuzzy sets and uncertain linguistic information processing models. In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some IVBUL aggregating operators. Then, we extend the CODAS method to solve multiple attribute group decision making (MAGDM) issues with interval-valued bipolar uncertain linguistic numbers (IVBULNs) based on these operators. An example for risk assessment of Chinese enterprises’ overseas mergers and acquisitions (M&As) is given to illustrate the proposed methodology.