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This paper aims to analyze the key factors influencing the synchronization performance of distributed motion control system and to improve the synchronization performance for peripherals control of this system.

This paper deals with the software synchronization problems of distributed motion control system based on real-time Ethernet. First, combined with communication and control tasks, the key factors affecting synchronization performance of system are analyzed. Then, aiming at key factors and considering the synchronization of system bus, protocol conversion and task scheduling, a software synchronization method based on CANopen protocol and real-time Ethernet is proposed. Finally, the feasibility of this method is verified by establishing distributed motion control system and testing the synchronization performance of terminal control signals of slaves.

Based on this method, the results show that the synchronization accuracy for peripherals control of all slaves could be about 100 ns.

This research provides high-precision synchronization method, which could lay a foundation for the application of distributed motion control system in the field of assembly automation, such as multi-axis assembly robots control.

In distributed motion control system, many factors affect the synchronization performance. At present, there is no synchronization method that could comprehensively consider these factors. This paper not only analyzes the key factors influencing the synchronization performance of system but also proposes a synchronization method. Therefore, the method proposed in this paper has certain theoretical value and engineering significance.

Building supply chain resilience is increasingly recognized as an effective strategy to deal with supply chain challenges, risks and disruptions. Nevertheless, it remains unclear how to build supply chain resilience and whether supply chain resilience could achieve a competitive advantage.

By analyzing the data collected from 216 firms in China, the current study empirically examines how information technology (IT) capability and supply chain collaboration affect different forms of supply chain resilience (external resilience and internal resilience) and examines the performance implications of these two forms of supply chain resilience.

Results show that IT capability is positively related to external resilience, whereas supply chain collaboration is positively related to internal resilience. The combination of IT capability and supply chain collaboration is positively related to external resilience. In addition, internal resilience is positively related to firm performance.

This study used only cross-sectional data from China for hypothesis testing. Future studies could utilise longitudinal data and research other countries/regions.

The findings systematically assess how IT capability and supply chain collaboration contribute to supply chain resilience and firm performance. The results provide a benchmark of supply chain resilience improvement that can be expected from IT capability and supply chain collaboration.

The study findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

In recent years, personalized recommendations have facilitated easy access to users' personal information and historical interactions, thereby improving recommendation effectiveness. However, due to privacy risk concerns, it is essential to balance the accuracy of personalized recommendations with privacy protection. Accordingly, this paper aims to propose a neural graph collaborative filtering personalized recommendation framework based on federated transfer learning (FTL-NGCF), which achieves high-quality personalized recommendations with privacy protection.

FTL-NGCF uses a third-party server to coordinate local users to train the graph neural networks (GNN) model. Each user client integrates user–item interactions into the embedding and uploads the model parameters to a server. To prevent attacks during communication and thus promote privacy preservation, the authors introduce homomorphic encryption to ensure secure model aggregation between clients and the server.

Experiments on three real data sets (Gowalla, Yelp2018, Amazon-Book) show that FTL-NGCF improves the recommendation performance in terms of recall and NDCG, based on the increased consideration of privacy protection relative to original federated learning methods.

To the best of the authors’ knowledge, no previous research has considered federated transfer learning framework for GNN-based recommendation. It can be extended to other recommended applications while maintaining privacy protection.

Firms often encounter complicated external relationships and conflicts in inbound and outbound open innovation (OI). Conflict management significantly affects innovation results. Guided by resource dependence theory (RDT), this study aims to examine the moderating effects of conflict management styles in the relationship between OI and organizational performance (OP).

This study focuses on manufacturing and service firms in China, with the respondents composed of senior managers. Using hierarchical regression analysis, data from 270 firm samples are used to empirically test the hypotheses.

Inbound and outbound OI openness positively affects OP. Cooperative conflict management positively moderates the relationship between inbound OI openness and OP, whereas it negatively moderates the impact of outbound OI openness on OP. By contrast, competitive conflict management positively moderates the relationship between outbound OI openness on OP.

Guided by RDT, this study explores the relationship between OI and OP and the moderating role of conflict management styles. However, it does not measure the level of resource dependence, which is among the future research directions for further validating the results of this study.

This study is among the first to investigate the impact of OI on OP in different conflict management styles. Findings suggest that choosing a suitable conflict management style may strengthen the positive effects of OI on OP.

The purpose of this paper is to investigate the status quo of digital poverty among adolescents in China, analyze the characteristics and the causes, then propose countermeasures to provide reference for alleviating digital poverty among adolescents.

The study developed an initial scale of digital poverty among adolescents and used survey data to revise the scale, on this basis, formed a questionnaire, which was distributed to nationwide adolescents. The study developed its findings from the 837 valid questionnaire respondents.

The digital poverty among adolescents is mainly shown in the poverty of digital ability, digital psychology and digital environment and presents the following characteristics, that is, insufficient information seeking ability and information selection ability needing to be improved; equipped with basic information awareness but lack of information evaluation ability; lack of patience in obtaining information and inclined to the principle of least effort; imperfect knowledge structure and immature psychological emotions and vulnerable to external interference; having a certain relationship with the information environment, but not significantly affected by regional economic differences. Finally, the study puts forward countermeasures to alleviate digital poverty among adolescents.

Understanding of the digital poverty among adolescents will likely demand rethinking into a number of issues ignored by information poverty studies.

Few studies focus on digital poverty among adolescents. This study developed an initial scale of digital poverty among adolescents and revised it by survey data, then conducted an empirical study through questionnaire, which could expand the understanding of information poverty in the field of library and information science.

This paper aims to investigate the adverse effects of addiction to social media usage on expatriates' cultural identity change in cross-cultural settings.

A questionnaire survey was conducted in two public universities in China. Among the questionnaires distributed, 333 useful responses were obtained from international students for data analysis.

Regression results show addiction to social media usage exerts adverse effects by negatively moderating the relationship between associations with locals and the three dimensions of cultural intelligence. Addiction to social media usage impairs expatriates from developing cultural intelligence from associations with locals, which in turn affects their cultural identity change.

Research findings suggest that expatriates, administrators and educators should be highly aware of the adverse effects of addiction to social media usage in complex cross-cultural settings wherein expatriates are more dependent on information technology. The important role of cultural intelligence should also be highlighted for its bridging role in managing cultural identity change for acculturation purpose. No causal relationships between variables can be established considering the cross-sectional design of the research. Longitudinal or experimental design could be a promising methodology for future efforts.

The current research contributes to the knowledge on information management applied to cross-cultural settings. The present study combines an IT contingent view with cross-cultural study to explore the adverse effects of addiction to social media usage on the development of expatriates' cultural intelligence from associations with locals, thereby influencing cultural identity change. The research provides new perspectives to expand the nomological framework of cross-cultural studies by combining the enabling roles of information technology.

The purpose of this investigation was to study these problems and design regional cathodic protection, using numerical simulation. Regional cathodic protection technology is immature at home and abroad. This is reflected in the fact that in gas stations, there are many underground pipelines, which can lead to serious interference and shielding phenomena, and there are many grounding networks that can cause substantial loss of the cathodic protection current.

Based on the above, in this article, first of all, the mathematical model of the buried pipeline cathodic protection potential distribution was established and the control equations solved using the boundary element method. Second, the cathodic shielding effect in pipeline concentration areas, the effect of instrument equipment grounding systems on cathodic protection and the influence of DC stray current on the interference of pipeline corrosion were studied separately using BEASY software. Finally, the BEASY software was used for a regional cathodic protection design for a real gas station.

It was concluded that impressed current used in combination with sacrificial anodes for regional cathodic protection design is often the most economic and effective approach. However, the output current of the auxiliary anode is large with high energy consumption. In consequence, it may be recommended that the station pipelines should be laid on the ground, rather than under it.

It is considered that the results can guide regional cathodic protection design for real-life installations very well.

Supply chain resilience and knowledge management (KM) processes have received increasing attention from researchers and practitioners. Nevertheless, previous studies often treat the two streams of literature independently. Drawing on the knowledge-based theory, this study aims to reconcile these two different streams of literature and examine how and when KM processes influence supply chain resilience.

This research develops a conceptual model to test a sample of data from 203 Chinese manufacturing firms using a structural equation modeling method. Specifically, the current study empirically examines how KM processes affect different forms of supply chain resilience (supply chain readiness, responsiveness and recovery) and examines the moderating effect of blockchain technology adaptation and organizational inertia on the relationship between KM processes and supply chain resilience.

The findings show that KM processes positively affect three dimensions of supply chain resilience, i.e., supply chain readiness, responsiveness and recovery. Besides, the study reveals that blockchain technology adoption positively moderates the relationships between KM processes and supply chain resilience, whereas organizational inertia negatively moderates these above relationships.

This research linked the two research areas of supply chain resilience and KM processes, further bridging the gap in the research exploration of KM in the supply chain field. Next, this study contributes to supply chain resilience research by investigating how KM systems positively impact supply chain readiness, responsiveness and recovery. In addition, this study found a moderating effect of blockchain technology adaption and organizational inertia on the relationship between KM processes and supply chain resilience. These findings provide a reference for Chinese manufacturing firms to strengthen supply chain resilience, achieve secure supply chain operations and gain a competitive advantage in the supply chain. This studys’findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

Timely detection of emergency events and effective tracking of corresponding public opinions are critical in emergency management. As media are immediate sources of information on emergencies, the purpose of this paper is to propose cross-media analytics to detect and track emergency events and provide decision support for government and emergency management departments.

In this paper, a novel emergency event detection and opinion mining method is proposed for emergency management using cross-media analytics. In the proposed approach, an event detection module is constructed to discover emergency events based on cross-media analytics, and after the detected event is confirmed as an emergency event, an opinion mining module is used to analyze public sentiments and then generate public sentiment time series for early warning via a semantic expansion technique.

Empirical results indicate that a specific emergency can be detected and that public opinion can be tracked effectively and efficiently using cross-media analytics. In addition, the proposed system can be used for decision support and real-time response for government and emergency management departments.

This paper takes full advantage of cross-media information and proposes novel emergency event detection and opinion mining methods for emergency management using cross-media analytics. The empirical analysis results illustrate the efficiency of the proposed method.

The proposed method can be applied for detection of emergency events and tracking of public opinions for emergency decision support and governmental real-time response.

This research work contributes to the design of a decision support system for emergency event detection and opinion mining. In the proposed approaches, emergency events are detected by leveraging cross-media analytics, and public sentiments are measured using an auto-expansion of the domain dictionary in the field of emergency management to eliminate the misclassification of the general dictionary and to make the quantization more accurate.

The purpose of this paper is to provide a structured methodology to permit the optimal selection of the best‐suited computerized maintenance management system (CMMS) software within maintenance information technologies.

The analysis has been executed adopting a multi‐attribute decision‐making methodology, namely the technique for order preference by similarity to an ideal solution (TOPSIS). For the selection process, 17 criteria under five main heading have been defined. Data obtained from questionnaires and interviews with the company's maintenance managers have been used in fuzzy TOPSIS.

The application of the proposed approach allows the maintenance practitioners to concentrate on a limited subset of CMMS applications and to compare their actual capabilities in order to select the right one, rather than considering only their purchase cost.

Comparisons with other multi‐attribute decision‐making techniques such as AHP (analytic hierarchy process) and ELECTRE (elimination and choice expressing reality) under fuzzy conditions can be done for further research.

This paper is a very useful source of information both for maintenance managers and stakeholders in making decisions about the selection of CMMS software.

This paper addresses CMMS software evaluation and selection criteria for practitioners and proposes a new multi‐attribute decision‐making methodology, hierarchical fuzzy TOPSIS, for the problem.