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This study aims to investigate the design and optimization of landing gear buffers to improve the landing-phase comfort of civil aircraft.

The vibration comfort during the landing and taxiing phases is calculated and evaluated based on the flight-testing data for a type of civil aircraft. The calculation and evaluation are under the guidance of the vibration comfort standard of GB/T13441.1-2007 and related files. The authors establish here a rigid-flexible coupled multibody dynamics finite element model of one full-size aircraft. Furthermore, the authors also implement a dynamic simulation for the landing and taxiing processes. Also, an analysis of how the main parameters of the buffers affect the vibration comfort is presented. Finally, the optimization of the single-chamber and double-chamber buffers in the landing gear is performed considering vibration comfort.

The double-chamber buffer with optimized parameters in landing gear can improve the vibration comfort of the aircraft during the landing and taxiing phases. Moreover, the comfort index can be increased by 25.6% more than that of a single-chamber type.

To the best of the authors’ knowledge, this study first investigates the evaluation methods and evaluation indexes on the aircraft vibration comfort, then further conducts the optimization of the parameters of landing gear buffer with different structures, so as to improve the comfort of aircraft passengers during landing process. Most of the current studies on aircraft landing gear have focused on the strength and safety of the landing gear, with very limited research on cabin vibration comfort during landing and subsequent taxiing because of the coupling of runway surface unevenness and airframe vibration.

According to governance theory, choosing an effective supply chain (SC) governance mechanism can balance the interests and conflicts between enterprises and help them achieve their performance goals. However, incentive and relational governance have not been fully studied in improving enterprise cooperative performance (ECP). This study aims to examine the relationship between incentive and relational governance in general, the direct effects of combined governance strategy (CGS; the combination dimension of the above two governance mechanisms) on ECP and the mediating effects of SC ambidexterity on CGS and ECP in particular.

To test the hypotheses, this study implements hierarchical linear regression and bootstrap with a survey data set of Chinese manufacturing enterprises.

Results demonstrate that incentive and relational governance can generate complementary effects through enabling and compensating mechanisms, and their combination, that is, CGS, can promote ECP more than a single governance approach; CGS is conducive to solving the SC ambidexterity dilemma and can simultaneously enhance SC alignment and adaptability, thus further improving ECP; and SC ambidexterity plays an intermediary role between CGS and ECP.

The present study examines the complex interaction between incentive governance, relational governance, SC ambidexterity, and ECP. Implications for theory and practice are that formulating appropriate CGS can develop SC ambidexterity and improve ECP.

This study investigates the direct influence of ambidextrous leadership on employees’ innovation behaviour, the mediating role of innovative self-efficacy and harmonious work passion, and the moderating role of Zhong-Yong thinking.

The authors conducted a series of questionnaire surveys to collect data in three time periods and from multiple sources; 332 supervisor–subordinate matched samples were obtained. The hypothesised relationships were tested using structural equation modelling and ProClin.

Ambidextrous leadership is positively associated with employees’ innovation behaviour, while innovative self-efficacy and harmonious work passion play mediating roles. The analysis further confirms that innovative self-efficacy and harmonious work passion play a chained double-mediating role between ambidextrous leadership and employees’ innovation behaviour, while Zhong-Yong thinking plays moderating roles between ambidextrous leadership and innovative self-efficacy and between ambidextrous leadership and harmonious work passion.

This study demonstrates the influence of ambidextrous leadership on employees’ innovation behaviour, specifically the role of ambidextrous leadership, and extends the relationship’s theoretical foundation. It is also expected to provide inspiration and serve as a reference for local Chinese management.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

Current open innovation (OI) and external knowledge search (EKS) research primarily shows a positive linear relationship between EKS and innovation at an individual level. However, organizational scholarship argues that excessive EKS may harm innovation. This study combines the knowledge-based view (KBV) and attention-based view (ABV) to articulate a nonlinear theory of EKS and innovation at the individual level.

The authors constructed a multi-sourced dataset covering 59,798 USA pharmaceutical patents spanning from 1975 to 2014 and employed negative binomial fixed-effect models to examine theoretical hypotheses.

We find a significant concave curvilinear relationship between EKS and innovation quantity as well as innovation quality at an individual level. An individual’s knowledge breadth and depth moderate the relationship between EKS and innovation, such that the threshold at which EKS has diminishing returns for individual innovation is higher for inventors with a broad range of knowledge and those with deeper expertise in the domain where they are innovating.

Managers should guide inventors toward a moderate investment of time and effort in EKS and should caution against over searching. Besides, managers should recognize that an inventor’s capacity for EKS is determined in part by their breadth of knowledge across various domains as well as the depth of knowledge they have in the knowledge domain where they are innovating.

We provide both parties with a clearer understanding of when EKS can begin to deteriorate an individual’s innovation performance why that deterioration occurs, and we also highlight two individual-level knowledge characteristics to take into consideration when deciding when to cease the EKS process.

This study provides a novel holistic understanding of OI and knowledge management for policymakers and organizations to nourish innovation dynamism and make the best of knowledge stocks in the community, which in turn will create endless power for sustainable social change and inclusive development.

This study contributes to OI theory by highlighting the non-linear nature of the relationship between EKS and innovation on an individual level. This represents a fundamental shift in theory on EKS and individual innovation by suggesting a major rethinking of how the two concepts relate, revealing the dark side of EKS in knowledge management if inventors engage in excessive EKS. Likewise, our study’s incorporation of the ABV informs KBV scholarship by highlighting the role of the limited attentional capacity of individuals in firm knowledge management.

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation, the moderating role of entrepreneurial orientation and government institutional support between them.

Hierarchical regression analysis is adopted to test the hypotheses based on survey data provided by 223 manufacturing SMEs in China.

The results reveal that domestic and international collaboration networks positively affect SMEs' innovation performance. Business model innovation mediates domestic and international collaboration networks-SMEs’ innovation performance relationships. Entrepreneurial orientation positively moderates international collaboration networks–SMEs’ innovation performance relationship, and government institutional support positively moderates domestic and international collaboration networks–SMEs’ innovation performance relationships.

The findings indicate that managers of SMEs should invest in domestic and international collaboration networks and business model innovation to enhance SMEs' innovation performance. Moreover, entrepreneurial orientation and government institutional support should be valued when SMEs try to enhance their innovation performance by embedding in domestic and international collaboration networks.

This study broadens the authors' understanding of the relationship between collaboration networks and firms' innovation performance by classifying collaboration networks into domestic and international dimensions and investigating their direct impacts on SMEs' innovation performance. Besides, this study reveals how and when domestic and international collaboration networks influence the innovation performance of SMEs.

The purpose of this study is to look at how Shariah-compliant status and Shariah regulation affect the demand for initial public offerings (IPOs) in Pakistan. The Shariah-compliant status, which is seen as a method that offers a credible signal to investors, may explain the anomaly in IPO demand.

This research used multivariate and quantile regression models to assess data from 85 IPOs issued on the Pakistan Stock Exchange between 2000 and 2019.

Shariah-compliant status has a considerable negative association with IPO demand. Nevertheless, there is a considerable positive association among Shariah regulation and IPO demand. Furthermore, the interaction among regulatory quality and Shariah-compliant status has a considerable strong influence on IPO demand. As a consequence, the findings show that Shariah-compliant firms might possibly attract the attention of investors. Investors were found to concur on the amicability of rigorous rules and permissible Shariah-compliance aspects.

Future studies could analyse the financial ratio benchmark (cash and debt) to determine the Shariah-compliant status and Shariah regulation to better understand the problem of IPO demand in the context of Pakistan.

The outcomes of this research are useful for issuers and underwriters in comprehending the characteristics that influence high and early IPO success. Such knowledge may assist issuers and underwriters in responsibly planning and managing the IPO process.

The results may be useful to investors looking for critical information in prospectuses to make the best choice when subscribing to IPOs in Pakistan.

This is one of the first studies to provide empirical data on the links among Shariah-compliant status, Shariah regulation and IPO demand in Pakistan. Furthermore, this research demonstrates the interaction impact of regulatory quality and Shariah-compliant status on IPO demand.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system. This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice. The key principles and approaches will be proposed, and their applications to high-speed trains in China will be presented.

First, the structural integrity and dynamical integrity of high-speed trains are defined, and their relationship is introduced. Then, the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided. Finally, the principles and approaches for assessing the dynamical integrity of high-speed trains are presented and a novel operational assessment method is further presented.

Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system. For assessing the structural integrity of structural components, an open-loop analysis considering both normal and abnormal vehicle conditions is needed. For assessing the structural integrity of dynamical components, a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed. The analysis of vehicle system dynamics should follow the principles of complete objects, conditions and indices. Numerical, experimental and operational approaches should be combined to achieve effective assessments.

The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects, better lifespan management of train components and better maintenance decision-making for high-speed trains.