In this era of intense global competition, supply chains are facing challenges in coping with emerging market issues. Within diverse industries worldwide, supply chains are experiencing accelerated reconfiguration, with one of the most notable transformations being the digitalization of supply chain operations. But the literature lacks empirical evidence about how digital transformation effectively contributes to it. Thus, this paper delves into the implications of the supply chain digital transformation (SCDT) and supply chain reconfigurability (SCR) on its overall performance. Cross-sectional data from 379 respondents in the machinery, electronics, and home appliance manufacturing industries were collected through a closed questionnaire. Utilizing a hybrid approach involving the Partial Least Squares Structural Equation Model (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA), this study employs a cross-validation of the conceptual model. Initially, the PLS-SEM is employed to unveil the direct impact of SCDT on supply chain performance (SCP), as well as the intermediary effect of SCR. Building on this foundation, the fsQCA method is further utilized to investigate the configuration paths that enable enterprises to achieve high SCP under the combined influence of SCR and SCDT. The research results affirm the significant influence of SCDT on SCP. Likewise, the findings highlight the crucial intermediary role of SCR between SCDT and SCP. Ultimately, three distinct configurations driving high supply chain performance are identified: technical, management, and flexible configurations, each playing a unique role.

As highly increasing of on-line fashions retail industry, automatic recognition and representation of clothing items have huge potentials.With the help of deep learning methods, many clothing attribute representation models have been proposed. However, these models are mainly suitable for coarse-grained classification which are not suitable for clothing attribute representation. To address such a problem, in this paper, we propose a novel network structure named SAC, which is a combination of CNNs and Self-attention mechanism and can represent clothing attributes more fine-grained. Besides, we use Grad-CAM to visualize which part of the clothing attributes is more concerned by customers. Finally, a new labeled clothing dataset is introduced in this paper, which is expected to be helpful to the researchers who are working in fashion domains for image representation.

Despite the significant attention to the customer experience which is a critical factor to help firms gain a competitive edge, there has been limited research regarding how to offer a superior customer experience in an omnichannel retailing environment through designing a fresh food supply chain network (FSCN). This paper develops a customised bi-level programming model for a capital constraint FSCN to reflect the interdependent relationship between two independent parties - the Omnichannel retailing company and customers with heterogeneous consumption requirements under time-varying overall demand uncertainty. A two-stage algorithm is applied to solve the optimisation problem, and a case study concerned with the establishment of FSCN is used to illustrate the applicability and efficiency of the proposed model and approach. The results obtained indicate the economic benefits of having a model that combines with a customer segmentation strategy. Both the operational efficiency of FSCN and the satisfaction level of customer experience are effectively improved.

Demand uncertainties and delivery delays are the fundamental causes of poor inventory control, especially in a dual-channel supply chain. Considering the impact of stochastic demand on the dual-channel inventory. this study explores the dynamic interactions of online–offline purchase–sale–stock systems under the decentralised, centralised, and cross-replenishment inventory controls. Hence, this study constructs a dynamic inventory model with delivery delays, based on the feedback and proportional–integral–derivative control, to optimise the influences between the replenishment cycles and online–offline channels’ interactions. The results show that, when the channels follow different sales strategies and the warehouses are proximally located, the cross-replenishment inventory strategy reduces the residual inventory. When the channels follow the same sales strategies, the centralised inventory control reduces the residual inventory. These findings demonstrate that the dynamic interactive inventory model can contribute towards optimising inventory operations. This study presents substantial insights for improving the overall performances of the dual-channel supply chain from the perspectives of dynamic and interactive inventory control, warehouse and retail network optimisation, and resource allocation.

Exploring the regional disparities in and spatiotemporal evolution of the new energy vehicle promotion level (NEVPL) is essential for facilitating low-carbon and environmentally sustainable development. This study employs a multidimensional index system to assess the NEVPL across 31 Chinese provinces from 2017 to 2023, utilizing data on NEV ownership, annual NEV sales, the number of public charging piles, and the vehicle-to-pile ratio. The NEVPL scores were estimated using the Entropy-TOPSIS method. Spatial patterns and the mechanisms of regional disparities were examined using a suite of spatial analytical techniques, including the standard deviation ellipse (SDE), gravity center analysis, Dagum Gini coefficient decomposition, and kernel density estimation. The results reveal three principal findings. First, NEVPL exhibited a sustained upward trend nationwide. The eastern region consistently maintained a leading position, the central and western regions demonstrated steady growth, and the northeastern region remained underdeveloped, leading to an expanding regional gap. Second, spatial distribution transitioned from an early dispersed pattern to a structure characterized by both agglomeration and differentiation. The promotional center gradually shifted toward the southeast, and high-value regions became increasingly isolated, forming island-like clusters. Third, spatial inequality was mainly driven by inter-regional differences, which contributed to over 70 percent of the total variance. The rising intra-regional disparity within the eastern region emerged as the predominant factor widening the national gap. These findings offer empirical evidence to support the refinement of new energy vehicle (NEV) policy frameworks and the promotion of balanced regional development.