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Boundary layer ingestion (BLI) is one of the probable noteworthy features of distributed propulsion configuration (DPC). Because of BLI, strong coupling effects are generated between the aerodynamics and propulsion system of aircraft, leading to the specific lift and drag aerodynamic characteristics. This paper aims to propose a model-based comprehensive analysis method to investigate this unique aerodynamic.

To investigate this unique aerodynamics, a model-based comprehensive analysis method is proposed. This method uses a detailed mathematical model of the distributed propulsion system to provide the essential boundary conditions and guarantee the accuracy of calculation results. Then a synthetic three-dimensional computational model is developed to analyze the effects of BLI on the lift and drag aerodynamic characteristics.

Subsequently, detailed computational analyses are conducted at different flight states, and the regularities under various flight altitudes and velocities are revealed. Computational results demonstrate that BLI can improve the lift to drag ratio evidently and enable a great performance potentiality.

The general analysis method and useful regularities have reference value to DPC aircraft and other similar aircrafts.

This paper proposed a DPS model-based comprehensive analysis method of BLI benefit on aerodynamics for DPC aircraft, and the unique aerodynamics of this new configuration under various flight altitudes and velocities was revealed.

The purpose of this paper is to examine evolutionary processes of sectoral systems of innovation in China's catch‐up situation.

History event analysis method is used. The data that inform this paper come primarily from interviews carried out as a part of case studies of the innovations of China's car industry as well as public sources.

Market catch‐up of China's self‐owned brand cars expanded from low to high end market segment. Changes of the five building blocks of innovation system of China's car industry have driven the market catch‐up since the 1980s. The five building blocks are: market demand, industrial technology and knowledge base, institutional setting, industrial structure, firms' competences and strategy. China's car industry evolved through exploitation and exploration, which were affected by the five building blocks. The exploitation and exploration shaped the catch‐up way of China's car industry: from production localization to design localization and self‐owned brands. Exploration of the self‐owned brand group built on exploitation of the joint‐venture group.

The findings are based on a single industry. Studies on more industries are needed to generalize the research results.

Increased understanding of how sectoral systems of innovation evolve will give managers and policy makers in the developing countries like China improved opportunities to formulate policies and management practices that can cultivate innovation capabilities in catch‐up.

The paper contributes to the research stream on sectoral systems of innovation by understanding building blocks and evolutionary processes at the base of change and growth in the catch‐up situation.

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.

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.

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.

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.

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.

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.

In 2005, China carried out a major reform that allows the previously untradeable shares controlled by large shareholders to become tradable in the secondary market. This reform and subsequent dramatic change of behavior of controlling shareholders, offer researchers a unique opportunity to study the behavior of controlling shareholders and its implication for corporate governance. Asset injection, by which controlling shareholders sell their high quality assets to the listed companies they controlled, became instantly popular after the reform. The purpose of this paper is to provide strong evidence that such asset injection improves both the Tobin's Q and the composite financial performance score of the injected firm.

Due to the availability of sample data, this paper focuses on two major types of assets injection: the listed companies purchase the large shareholders' physical assets or equity assets (their shares of other companies) in cash; and the listed companies purchase the large shareholders' physical assets or equity assets through private stock offering, often increasing the share proportion of large shareholders.

The research findings suggest that this full listing reform aligned the interest of controlling shareholders with the company and that controlling shareholders change their behavior from tunneling to propping.

The contributions of this paper are threefold: First, the paper provides strong evidence of large shareholders' propping behavior. Second, the authors use long‐term corporate financial performance measures to study the impact of asset injection. Third, the authors investigate what types of injections will have a bigger impact on financial performance of the injected firms.

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.