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A multivariable model reference adaptive control method is proposed to solve a distributed leader–follower formation control problem of unmanned aerial vehicles (UAVs) with uncertain parameters and unknown external disturbances for both leader and followers.

A case of uncertain stochastic external disturbances for UAVs is considered, and based on the distributed communication network of UAVs, a state-feedback adaptive controller is proposed to maintain the formation of UAVs consistently. Then, the stability and asymptotic tracking performance of the UAV formation control system are analyzed by the Lyapunov function.

The simulation results demonstrate that this formation control scheme can effectively solve the stochastic external disturbance problem of UAVs and ensure the stability of their formation.

The proposed multivariable model reference adaptive control method reduces the error of formation control system and improves the stability and control performance of UAV compared with fixed control.

This paper aims to solve the uncertainty problem of hypersonic vehicle tracking control; an adaptive terminal sliding mode control (TSMC) method based on extended state observer (ESO) is proposed. The combination of adaptive techniques, TSMC and ESO offers an effective approach for managing uncertain systems.

The dynamic model of a hypersonic vehicle is transformed into two control-oriented subsystems. The control system design incorporates an adaptive technique, an ESO and a TSMC. The ESO estimates the primary uncertainties, while the adaptive technique determines the upper limit of secondary uncertainties. These estimates are used for the design of the TSMC law. In addition, the filter is used to generate the reference trajectory to improve the dynamic performance of the system. The stability of the closed-loop system is proved by the Lyapunov stability theory.

A robust control system for hypersonic vehicles is developed with guaranteed stability and strong adaptability to various uncertainties such as parameter variations, external disturbances and actuator faults. Furthermore, the proposed system demonstrates enhanced dynamic performance compared to observer-based sliding mode control. Specifically, for the velocity and altitude tracking control, the settling time of the proposed sliding mode control is approximately 100 s and 70 s shorter than that of the observer-based sliding mode control, respectively.

Different from the single equivalent treatment, various uncertainties here are classified and treated with different strategies, which improves the disturbance rejection ability of the control system. This ability is of great significance for enhancing the autonomy, adaptability and reliability of hypersonic vehicles in extreme environments.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

With the rise of digital construction, using organizational capabilities to improve project performance in a turbulent environment has become critical for the high-quality development of the construction industry. However, the complex relationships among them remain unclear. Therefore, this study explores these linear relationships under the digital construction mode and reveals the driving mechanism of multi-factor linkage on project performance.

Data were collected from 263 project participants in digital construction projects in China using a questionnaire. Hypothesis testing was conducted using partial least square structural equation modeling, and the differentiated patterns of project performance formation were revealed through fuzzy-set qualitative comparative analysis.

Organizational information technology, innovation, coordination, integration management and emergency management capabilities improve project performance. Environmental turbulence is a positive moderator between coordination capabilities and project performance, while other capabilities do not align with environmental turbulence. The research obtained five equivalent configurations for achieving high project performance, such as “capability layout” and “internal driven,” and two paths that lead to non-high project performance. Finally, in contrast to existing studies, we discovered the outstanding contribution of emergency management capabilities to project performance and the auxiliary effect of information technology capabilities.

This study innovatively integrates a dimensional framework of construction project organizations’ capabilities under a digital construction mode and extends the organizational capabilities to the specific and operational capability dimension level. Furthermore, this study opens the “black box” of the influence of organizational capabilities on project performance in environmental turbulence and reveals the differentiated and equivalent configurations for the formation of project performance. The study broadens the theoretical perspective of organizational capabilities on project performance research in the digital context and provides practical enlightenment for guiding the capability configuration of construction project organizations in a turbulent environment. The study broadens the theoretical perspective of organizational capabilities on project performance research in the digital context and provides practical enlightenment for guiding the capability configuration of construction project organizations in a turbulent environment.

This study aims to explore the determinants of green electronics purchase intention in Malaysia by extending existing knowledge on green consumer behavior and contributing to the field of sustainable consumption.

A quantitative research approach was adopted, with data collected from 250 Malaysian consumers. The proposed model was tested using partial least squares structural equation modeling to assess the relationships between various determinants and green purchase intention.

The results demonstrate that perceived consumer effectiveness, green advertising and monetary cost positively affect environmental attitudes, which subsequently influence green purchase intention. The study also identifies that brand image and information quality significantly enhance green brand trust (GBT), leading to stronger intentions to engage in green purchasing. Additionally, it finds that environmental knowledge and environmental concern shape perceived behavioral control, which further impacts green purchasing intention.

The study focuses on Malaysian consumers, which may limit the generalizability of the findings to other cultural contexts. Future research could expand the scope to include cross-cultural comparisons to validate the model in different settings.

By providing insights into the key factors driving consumers’ intention to purchase green electronics, the study offers valuable guidance for marketers and manufacturers to develop targeted strategies that promote sustainable consumption and capitalize on the growing demand for green products in Malaysia.

This study is unique in measuring the influence of green attitude, GBT and perceived behavioral control on green purchase intention specifically within the electronics sector, offering a novel contribution to the literature on sustainable consumer behavior.

The purpose of this paper is to solve the problem of adaptive predefined-time control for spacecraft rendezvous maneuver with input quantization and unknown parameters.

A significant error-shifting function is established to ensure that the limitation of the initial condition can be ignored. Then, a combination of neural networks method and minimum-learning-parameter method is used to mitigate the adverse effects caused by nonlinear system dynamics. An input quantization method is applied to improved efficiency of data communication between controller and actuator in rendezvous maneuver control system.

The simulation results verify the correctness and effectiveness of the designed control strategy which can effectively overcome the disadvantages caused by coupling nonlinear system dynamics.

This paper designs an adaptive predefined-time control method for spacecraft rendezvous maneuver control with input quantization based on backstepping control method.

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.

With burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.

We consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.

Numerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.

Drawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.

With limited empirical evidence, prior studies have proposed that green practices can be leveraged to enhance carbon neutrality. This study draws on the contingent natural resource-based view (NRBV) to theorize and validate how pressure from supply chain (SC) stakeholders could amplify the effect of green logistics practices (GLPs) on carbon-neutral supply chain performance (CNSCP) among firms in developing countries. Specifically, this study contends that high levels of supply chain pressures (SCPs) (customers and suppliers) amplify the influence of GLPs on CNSCP.

An integrated model was tested using survey data gathered from 208 managers of logistics firms in Ghana. SPSS 23 and structural equation modeling were used for the data analyses.

Findings showed that all five dimensions of GLPs (transportation, warehousing, packaging and distribution, logistics information sharing and sustainable waste management) significantly enhance CNSCP. This study also found varying interactive effects of SCPs (customers and suppliers) on the link between GLPs (green transportation, green packaging and distribution) and CNSCP, such that different practices exert varying interactive effects at varying levels of SCPs.

This study offers fresh insights into how managers can leverage GLPs to achieve enhanced benefits in the form of CNSCP. The outcome of this study offers a comprehensive understanding of the GLPs-CNSCP link while shedding light on how firms can manage SCP to drive enhanced carbon-neutral performance through GLPs.

This study contributes to policymakers in enhancing the decarbonization of global SCs through sustainable logistics practices.

To the best of the authors’ knowledge, this is the first study to theorize and empirically validate the influence of GLPs on CNSCP. This study identified five practices and demonstrated how these practices uniquely drive CNSCP, as opposed to previous studies that examined GLPs from a one-dimensional perspective. This study also expands the borders of sustainable logistics literature by theorizing and empirically validating SCPs (customers and suppliers) as necessary conditions to amplify the benefits of GLPs. In essence, the novelty of the present study lies in the integration of NRBV and stakeholder theories to unearth the mechanism for optimizing the GLP-CNSCP relationship, which is rare in the sustainable logistics literature.

Logistics practitioners face a significant challenge in meeting local and international regulations and the United Nations' Sustainable Development Goals (SDGs) due to the complexities of measuring and assessing the CO₂e emissions of logistics processes. This challenge is pronounced in distribution processes, where the literature currently lacks a structured approach based on existing guidelines and regulations or real-case implementation examples.

To analyse the environmental performance of distribution processes, a model with Visual Basic for Applications (VBA) algorithms compliant with the Global Logistics Emissions Council (GLEC) framework was developed. An integrative review identified key elements for evaluating the environmental impact of distribution processes, leading to model development. The model was validated through a business case in the agri-food supply chain, demonstrating its applicability and enabling the analysis of optimisation scenarios.

The findings suggest potential savings in CO₂e emissions of up to 50% by improving vehicle efficiency and maximising vehicle capacity utilisation. Further savings of up to 30% are highlighted for the business case company by increasing intermodal transport modes use.

This study offers several academic and managerial contributions. On the one hand, it offers a structured approach to assess the environmental performance of the logistics distribution processes based on a comprehensive European standard and enriches the literature by providing an industrial application of GLEC framework guidelines. On the other hand, it empowers logistics practitioners with a model to assess the environmental impact of distribution processes, and it enables an enhanced decision-making process in selecting transport modes to achieve the company’s sustainability goals.