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Leveraging the benefits of supply chain digitalization is a big challenge for many firms. To address this issue, this study aims to use information processing theory to explore the mechanisms between supply chain digitalization and supply chain performance.

Based on survey data from 223 Chinese companies, the authors tested the moderated mediation model using the Process program in SPSS.

The empirical results reveal that supply chain traceability and supply chain agility partially mediate the supply chain digitalization–supply chain performance relationship. More interestingly, the above significant mediation effects show differences across industries. In particular, manufacturing firms rely more on supply chain traceability, whereas supply chain agility contributes more to service firms. Lastly, supply chain dynamism is a significant moderator that enhances the mediation effect of supply chain traceability in the supply chain digitalization–supply chain performance relationship.

This study offers new insights into the growing literature on supply chain digitalization by proposing a new moderated mediation model that demonstrates the relative importance of different mediators. The findings also help managers boost their supply chain performance in the digital era.

The authors investigate how logistics digitalization affects two types of third-party logistics (3PL) performance: financial performance and service performance. In particular, the authors explore the mediating role of customer collaboration between logistics digitalization and firm performance based on organizational information processing theory and examine the moderating role of government support.

The authors use an SPSS macro program (PROCESS regression analysis) to analyze survey data from 235 3PL firms in China. The mediation model, moderation model and moderated mediation model are tested.

The empirical results show that in the new age of digitalization transformation, logistics digitalization positively affects 3PL's financial performance and service performance by strengthening customer collaboration. Additionally, government support amplifies the positive effect of customer collaboration on service performance but not financial performance. The moderated mediation test further indicates that government support strengthens the positive indirect effect of digitalization on service performance through customer collaboration.

This study offers empirical insights into the growing body of 3PL literature, and the findings contribute to the theoretical and practical understanding of the emerging research topic of digital transformation (DT) and sustainability issues in 3PL firms.

This study examines the firm-level financial consequences caused by supply chain disruptions during COVID-19 and explores how firms' supply chain diversification strategies, including diversified suppliers, customers and products, moderate the negative effect on firm performance.

Based on data drawn from 222 publicly traded firms in China, the authors use event study methodology to estimate the effects of supply chain disruptions on the financial performance of affected firms. Regression analyses are conducted to examine the moderating effects of supply chain diversification.

Firms affected by supply chain disruptions during COVID-19 experienced a significant decline in shareholder value in two weeks and a subsequent decrease in operating performance in one year. Diversified suppliers, customers and products act as shock absorbers to alleviate the negative effects. Further regression shows a substitution effect between customer and product diversification. Cross-industry comparisons reveal that service firms experienced more loss than manufacturing firms. Customer diversification mitigates the adverse effects of supply chain disruptions for both manufacturing and service firms. Supplier diversification exerts a noteworthy role in manufacturing firms, while product diversification is beneficial for service firms.

The study provides empirical evidence on the magnitude of financial consequences of supply chain disruptions during COVID-19 in both the short term and long term and enriches the current understanding of how to build resilience from the supply chain diversification perspective.

The purpose of this study was to examine how firms' corporate social responsibility (CSR) strategies affect their innovation performance via two mediating variables, employee involvement and supplier collaboration, and compare how this mechanism works in the service and manufacturing industries.

The conceptual model was built on stakeholder theory, the resource-based view (RBV) and service-dominant logic (SDL). Based on survey data from 686 service firms and 1,646 manufacturing firms, the hypothesized relationships were tested using structural equation modeling (SEM).

The empirical results showed that CSR positively affected service innovation and product innovation in service firms and manufacturing firms, respectively, and that these effects were positively mediated by employee involvement and supplier collaboration. However, compared with manufacturing firms, the effect of CSR on innovation performance was greater for service firms. Supplier collaboration and employee involvement also played a stronger role in service firms when mediating the relationship between CSR and innovation performance.

By analyzing and validating the direct and indirect effects of CSR on innovation performance in both the service and manufacturing industries, this study addressed the strategic benefit of CSR and extended research focused on the financial benefits of CSR. Therefore, its findings contribute to our understanding of sustainability and innovation issues. From a theoretical perspective, this study extended the RBV, SDL and stakeholder theory to the context of the CSR-innovation relationship, and showed that firms could align CSR and innovation initiatives to achieve strategic synergy. It also revealed the similarities and differences between service and manufacturing firms regarding the mechanism through which CSR affects innovation.

Many popular simultaneous localization and mapping (SLAM) techniques have low accuracy, especially when localizing environments containing dynamically moving objects since their presence can potentially cause inaccurate data associations. To address this issue, the proposed FADM-SLAM system aims to improve the accuracy of SLAM techniques in environments containing dynamically moving objects. It uses a pipeline of feature-based approaches accompanied by sparse optical flow and multi-view geometry as constraints to achieve this goal.

FADM-SLAM, which works with monocular, stereo and RGB-D sensors, combines an instance segmentation network incorporating an intelligent motion detection strategy (iM) with an optical flow technique to improve location accuracy. The proposed AS-SLAM system comprises four principal modules, which are the optical flow mask and iM, the ego motion estimation, dynamic point detection and the feature-based extraction framework.

Experiment results using the publicly available RGBD-Bonn data set indicate that FADM-SLAM outperforms established visual SLAM systems in highly dynamic conditions.

In summary, the first module generates the indication of dynamic objects by using the optical flow and iM with geometric-wise segmentation, which is then used by the second module to compute the starting point of a posture. The third module, meanwhile, first searches for the dynamic feature points in the environment, and second, eliminates them from further processing. An algorithm based on epipolar constraints is implemented to do this. In this way, only the static feature points are retained, which are then fed to the fourth module for extracting important features.