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This chapter reviews the competition between full-service carrier (FSC) and low-cost carrier (LCC) in China. More importantly, we discuss the impacts of the COVID-19 pandemic on FSC–LCC competition. Specifically, the airlines' route choices and also the market contact between FSCs and LCCs in China are examined and discussed. Our review results suggest that, despite the rapid growth of the independent LCC Spring Airlines and the establishment of new subsidiary LCCs by FSCs, China's LCC sector still plays relatively minor roles compared with many fully deregulated markets. Subsidiary LCCs serve more as competitive tools for their parent FSCs, primarily deployed on their parent FSCs' routes to jointly compete against rival FSCs. This competition is primarily focused on niche regional markets rather than engaging in full-scale competition. Spring Airlines also strategically avoided direct head-to-head competition with FSCs before the pandemic by mainly connecting with the secondary cities. However, the pandemic has introduced significant changes, notably the network differentiation between FSCs and LCCs in mainland China. With the relaxation of government's regulations on airline route entries into hub airports during pandemic, Chinese LCCs have shifted their focus toward serving more dense routes, especially those connected to the top five cities. This shift has led to an intensified head-to-head competition between LCCs and FSCs following the outbreak of the pandemic. Such a process is likely to continue in the years to come. This chapter's discussions could also provide new insights into LCC development and the impact of the pandemic on FSC–LCC competition interactions to supplement existing literature studying other major airline markets.

This research aims to examine the link between distributed leadership and team ambidexterity and the sequential mediation of team climate innovation and knowledge management in this relationship.

This study draws on a sample of 546 knowledge workers involved within 157 service research and development (R&D) teams of knowledge-intensive firms (KIFs) and uses partial least squares-structural equation modelling (PLS-SEM) through SMART PLS 4 to analyse the data collected.

Findings reveal that distributed leadership has a significant direct impact on team ambidexterity. Besides, they indicate that team climate innovation and knowledge management in teams mediate this link. Results also highlight the sequential mediation of team climate innovation and knowledge management in teams, linking distributed leadership to team ambidexterity.

This study explores the relationship between distributed leadership and ambidexterity at the team level and proposes a sequential mediation model linking these variables through team climate innovation and knowledge management in teams. It offers practical insights for KIFs’ managers on the importance of using a distributed leadership approach and building a team climate innovation to motivate R&D teams, encourage dynamic participation in knowledge management practices and cultivate both exploitative and exploratory learning activities.

Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.

The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.

The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.

This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.

Effective knowledge management has played a crucial role in propelling the green transformation of organisations and industries. Nevertheless, its underutilisation in the real estate sector has impeded the progress of green transformation. Therefore, the purpose of this paper is to offer a theoretical and practical analysis of the green transformation of the real estate industry through the lens of knowledge management and to provide a valuable reference to facilitate the industry’s green transformation.

This study entailed applying induction and deduction method, using China’s real estate industry as a typical case, and collecting and analysing the public data, corporate reports and literature of China’s real estate industry. On this basis, the authors conducted an in-depth analysis of the mechanisms through which the green transformation has empowered the sustainable development of China’s real estate industry, as well as the critical role of knowledge management.

The study has revealed that the primary challenges encountered by China’s real estate industry during the green transformation have stemmed from significant disparities in the knowledge base among different industry entities, the complexities related to knowledge integration and the “difficulty” of applying green knowledge across the entire life cycle. To address these issues, the authors recommend several strategic actions, including creating a dedicated green knowledge platform for the real estate industry, establishing a knowledge-sharing mechanism, enhancing knowledge acquisition on both the supply and demand sides and intensifying the focus on the application of green knowledge within the real estate industry.

This research holds considerable theoretical and practical significance concerning the comprehension and promotion of knowledge management’s role in the green transformation of China’s real estate industry. These insights can be applied to significantly enhance the theoretical framework of knowledge management, and the research outcomes provide substantial support for propelling the green transformation in China’s real estate industry and contributing to the sustainable development of the overall economy in China.

From a knowledge management perspective, this study introduces a series of solutions and recommendations, presenting new research ideas and pathways for advancing the green transformation of the real estate industry. In addition to guiding the industry’s sustainable development, it also significantly contributes to enhancing the theoretical framework of knowledge management.

This study aims to improve the control accuracy and antidisturbance performance of the manipulator with the flexible link, a combined controller, which combines the novel backstepping sliding mode controller based on the extended state observer (ESO) and super-twisting sliding mode controller.

First, the dynamic of the system is constructed by Lagrange method and assumed mode method, and then the dynamic is decoupled by the singular perturbation theory to obtain the slow-varying subsystem and fast-varying subsystem. For the slow-varying subsystem, the novel backstepping sliding mode controller based on ESO is used to achieve joint tracking. For the fast-varying subsystem, the super-twisting sliding mode controller is used for vibration suppression. At the same time, to suppress chattering, the tanh function is used to replace the sign function in the reaching law.

The simulation results show that the combined control has better trajectory tracking performance, antiinterference performance and vibration suppression performance than traditional sliding mode control (SMC).

A novel backstepping sliding mode controller based on ESO is designed to guarantee the performance of the tracking trajectory. The new controller improves the converge rate. A super-twisting sliding mode controller, which can stabilize the fast-varying subsystem, is used to suppress the vibration of flexible link.

The managerial questions of this paper are as follows: What are the equilibrium conditions of transfer price, quantity and profits when considering dynamic subsidies from the government? Which collection channel is better for a manufacturer, direct collection by itself or through an online platform?

This research investigates the three collection models: the manufacturer-driven model, the online platform-driven model and the competitive model. Based on the differential game, this research explores the transfer price, collection cost, subsidy and manufacturer and online platform profit in different models when considering the dynamic subsidy.

The results show that the collection strategy for the manufacturer depends on its collection cost. If the collection cost is lower, then the manufacturer may prefer to collect by itself. When the collection cost meets a certain range, the manufacturer may collect the used product through an online platform. The online platform-driven model is the most efficient because both the manufacturer and the online platform can make a higher profit.

This research bridges the gap between waste electrical and electronic equipment collection and government subsidies by demonstrating the dynamic condition of subsidies. It offers an approach to address the influence of dynamic subsidy, which can provide practical insights for the government implementing the subsidy policy.

Demand-controlled ventilation (DCV) plays a significant role in human life by providing safe, reliable and cost-effective services that are environmentally friendly and enhance occupant satisfaction and building energy efficiency. Significant decisions are made at the early stages of building sector DCV systems, requiring effective tools to avoid measurement errors and failures in Volatile Organic Compound (VOC) generation. The continuous upgrading of this sector is necessary to respond to technological advances, environmental changes and increased ventilation demands. Integrating indoor air quality (IAQ) and machine learning algorithms (MLA) proves promising, as the scope of DCV typically does not extend beyond the footprint of the building; it does not encompass IAQ within a Corona Virus Disease 2019 (COVID-19) infection risk information. Therefore, integrating IAQ with MLA provides a comprehensive overview of the building sector’s DCV systems. However, this integration poses challenges, particularly in DCV activities, as they are among the most complex systems involving numerous processes critical for making important decisions. This study aims to identify how digitalized construction environments can integrate DCV into their processes.

This study reviews the literature on integrating IAQ with MLA systematically, aiming to analyze the DCV need for this integration and its benefits. It proposes a direction for a conceptual framework, simulation and causal explanation of the problems using the bootstrapping technique and Cronbach’s alpha factor analysis to establish the requirement for facilitating specific ventilation control processes to be incorporated into the system approaches in managing infection prevention and energy efficiency in the building sector’s DCV system.

This study proposes a conceptual framework for analyzing IAQ within a COVID-19 context and MLA embedded in systems that may impact DCV practices. The conceptual framework comprises six key constructs: virus detection, occupant ventilation behavior, DCV energy consumption, diagnostic evaluation, temperature perception cluster and indoor environmental quality. The conceptual framework underscores the importance of early integration of DCV in the design phase to identify alternative methods to cogenerate, monitor and optimize DCV.

So far, this study advances the knowledge of how digitalized construction environments can ensure DCV delivery. The testing results highlight four significant relationships between the constructs of strategies and the constructs of occupant-density factors in the Malaysian dataset within the existing conceptual framework. Hence, the framework designed for developed countries or US companies can enhance IAQ ventilation strategy options in Malaysia’s G7 contractor companies. A future study can validate the framework across the design phase with different construction stakeholders.

There are domain integrals in the integral equations for analyzing the heat conduction with a heat source.

In order to highlight the advantages of the boundary element method, the dual reciprocity method is introduced to transform the domain integral into the boundary integral through the special interpolation function. When the internal points near the boundary are selected as the nodes for constructing the approximating functions in the dual reciprocity method, the nearly singular integrals will occur in calculating the physical quantities of these internal points. The nearly singular integrals cannot be effectively evaluated by the Gaussian numerical integration, which will reduce the calculation accuracy of the temperature and heat flux at the internal points near the boundary. Herein, a set of analytical formulas is proposed to evaluate the nearly singular integrals in the boundary integral equations for the heat conduction problem with a heat source.

Thus, the accurate temperature and heat flux at the internal points closer to the boundary can be evaluated by comparing with the conventional boundary element method. The characteristic of the “boundary only” of the boundary element method is maintained for analyzing the temperature field in the heat conduction problem with a heat source.

The boundary-domain integral equation for the heat conduction problem with a heat source is transformed into the boundary integral equation by the dual reciprocity method. Then, the analytical algorithm is introduced to evaluate the nearly singular integral in the heat conduction boundary integral equations with a heat source. The present method retains the “boundary only” characteristic of the boundary element method and effectively evaluates the nearly singular integrals when the internal point is close to the boundary.

This study aims to assess the relationships between limit parametric settings of in-nozzle impregnation additive manufacturing, namely, nozzle temperature and layer height, on the micromorphology and induced mechanical properties of continuous flax yarns-reinforced biocomposites.

The additively manufactured biocomposites with different printing parameters were characterized by X-ray microcomputed tomography and tensile testing to link the process–structure–properties relationships regarding the internal morphologies of yarns, matrix and porosities and tensile properties.

Several types of morphology were defined regarding fiber, void, raster and interfaces. The results showed a competition between porosity development, coating effect and variation in fiber volume fraction on the biocomposite quality and mechanical performance when simultaneously varying the layer height and the temperature due to rheology-related phenomena and process-induced defects.

To the best of the authors’ knowledge, no previous study has been carried out on the relation between the internal micromorphologies in three directions of continuous biocomposites manufactured by in-nozzle impregnation additive manufacturing and the limit printing parameters. The findings are thought to help manufacturers master this technology for high-end applications.

This study aims to explore the synthesis and tribological performances of di-n-octyl sebacate (DOS) synthesized with spherical nano-MoS₂/sericite (SMS) and carboxylated SMS (CSMS) as catalysts.

SMS and CSMS were used as esterification catalysts to synthesize DOS from sebacic acid and n-octanol. The two catalysts were in situ dispersed in the synthesized DOS after the reaction to form suspensions. The tribological performances of the two suspensions after 20 days of storage were studied.

CSMS was more stably dispersed in DOS than SMS, and they reduced friction by 55.6% and 22.2% and wear by 51.3% and 56.5%, respectively. Such results were mainly caused by the COOH on CSMS, which was more conducive to improving the dispersion and friction reduction of CSMS than wear resistance. Another possible reason was the difference between the dispersion amounts of CSMS and SMS in DOS. The sericite of SMS was converted into SiO₂ to enhance wear resistance, while that of CSMS only partially generated SiO₂, and the rest still remained on the surface to reduce friction.

This work provides a more effective SMS catalytical way for DOS synthesis than the traditional inorganic acid catalytical method. SMS does not need to be separated after reaction and can be dispersed directly in DOS as a lubricant additive. Replacing SMS with CSMS can produce a more stable suspension and reduce friction significantly. This work combined the advantages of surface carboxylation modification and in situ catalytic dispersion and provided alternatives for the synthesis of DOS and the dispersion of MoS₂-based lubricant additives.