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To ensure the stability of the flying wing layout unmanned aerial vehicle (UAV) during flight, this paper uses the radial basis function neural network model to analyse the stability of the aforementioned aircraft.

This paper uses a linear sliding mode control algorithm to analyse the stability of the UAV's attitude in a level flight state. In addition, a wind-resistant control algorithm based on the estimation of wind disturbance with a radial basis function neural network is proposed. Through the modelling of the flying wing layout UAV, the stability characteristics of a sample UAV are analysed based on the simulation data. The stability characteristics of the sample UAV are analysed based on the simulation data.

The simulation results indicate that the UAV with a flying wing layout has a short fuselage, no tail with a horizontal stabilising surface and the aerodynamic focus of the fuselage and the centre of gravity is nearby, which is indicative of longitudinal static instability. In addition, the absence of a drogue tail and the reliance on ailerons and a swept-back angle for stability result in a lack of stability in the transverse direction, whereas the presence of stability in the transverse direction is observed.

The analysis of the stability characteristics of the sample aircraft provides the foundation for the subsequent establishment of the control model for the flying wing layout UAV.

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.

This study aims to explore and segment consumer preferences for electric and hybrid vehicles in Germany, Sweden, the Netherlands and Turkey, focusing on understanding the various factors that influence consumer decisions in these markets.

Using latent class analysis (LCA) on data collected through online surveys and discrete choice experiments, this research categorizes consumers into distinct segments. The approach allows for a nuanced understanding of how various factors such as income level, fuel cost, age, CO₂ emissions, purchase price, vehicle range, policy policies and environmental concerns interact with shape consumer preferences.

The analysis uncovers significant heterogeneity in consumer preferences for electric and hybrid vehicles across Germany, Sweden, the Netherlands and Turkey, revealing four key segments: “Eco-Driven Innovators,” “Value-Focused Pragmatists,” “Tech-Savvy Early Adopters” and “Reluctant Traditionalists.” “Eco-Driven Innovators” prioritize environmental benefits and are less sensitive to price, demonstrating a strong inclination toward vehicle CO₂ emissions and policy policies. “Value-Focused Pragmatists” weigh economic factors heavily, showing a sharp interest in fuel costs and purchase prices but are open to considering electric and hybrid vehicles if they present clear long-term savings. Technology-savvy early adopters are attracted by the latest technological advancements in vehicles, regardless of the type, and are motivated by factors beyond just environmental concerns or cost savings. Lastly, “Reluctant Traditionalists” exhibit minimal interest in electric and hybrid vehicles due to concerns over charging infrastructure and upfront costs. This detailed segmentation illustrates the diverse motivations and barriers influencing consumer choices, from governmental policies and environmental concerns to individual financial considerations and technological appeal.

This study stands out for its pioneering application of LCA to dissect the complexity of consumer preferences for electric and hybrid vehicles, a methodological approach not widely used in this research domain. Using LCA, the authors are able to uncover nuanced consumer segments, each with distinct preferences and motivations, providing a depth of insight into market dynamics that traditional analysis methods may overlook. This approach enables a more granular understanding of how diverse factors – ranging from environmental concerns to economic considerations and technological attributes – interact to shape consumer choices in different countries. The findings not only fill a critical gap in the existing literature by mapping the intricate landscape of consumer preferences, but also offer a novel perspective on strategizing market interventions. Therefore, the application of LCA enriches the discourse on sustainable transportation, offering stakeholders, manufacturers, policymakers and researchers – a refined toolkit for navigating the evolving market dynamics and fostering the adoption of electric and hybrid vehicles.

Organizations are full of contradictions and leadership dilemmas. Managers often face challenges such as selecting between two contradicting options such that which one is more important can hardly be judged. To manage contradicting dynamics, today’s managers can adopt the paradoxical leadership approach. We build a theoretical model to investigate the influence of paradoxical leadership on multi-dimensional project agility (proactivity, adaptability, and resilience), and multi-dimensional project success (management, investment, and ownership success).

Drawing on survey-based data from the China–Pakistan Economic Corridor (CPEC) megaproject (N = 209), we performed covariance-based structural equation modeling to test the conceptual model.

The findings show that (1) paradoxical leadership has a significant positive impact on megaproject success, (2) paradoxical leadership has a significant positive influence on project agility, (3) project agility has a significant positive effect on megaproject success, and (4) project agility has a significant effect that mediates the link between paradoxical leadership and megaproject success. This research provides a theoretical and practical comprehension of paradoxical leadership with a new perspective on megaprojects.

This study provides an extension of the existing studies on paradoxical leadership and identifies the role of contradicting dynamics and their impact on multiple facets of megaproject success. It not only clarifies the relationship between paradoxical leadership and megaproject success, but also identifies the mediating role of project agility that can play an effective role in mobilizing success in megaprojects.

Managing megaprojects is challenging due to their inherent complexity and uncertainty. Collaborative project delivery models have been introduced as an alternative to traditional project management in public infrastructure megaprojects and are often realized through collaborative contracts. These project organizations act as institutional arenas for logic interaction as actors with differing institutional backgrounds interact within the project. This paper aims to study the delivery phase of three megaprojects through an institutional lens, investigating the institutional interaction and alignment of logics therein.

A multiple case study was employed to reach deep insight into the phenomenon. Sixty-one interviews were conducted over 3 cases with representatives from all levels of the project hierarchy. Respondents were selected through snowball sampling. In two cases, observations of the shared project office were conducted. Data analysis built on first-order codes and second-order themes, collected into a theoretical framework.

The empirical evidence demonstrates the dynamics shaping institutional logics and gives evidence for changing logics in projects with a well-applied collaborative contract. However, there is a risk of resistance and a return to traditional logics since institutional change is slow and an unsuitably applied collaborative contract can lead to adherence to the conventional way of work.

Current research has focused on the regulatory framework and procurement phase of such models, but little attention has been given to the delivery phase and the interaction of conflicting logics. This paper can serve as an exemplar of the different logics found within public infrastructure projects and their interaction and alignment. Contributions include a heightened emphasis on the start of the project as a meeting point for differing institutional logics and the role change necessary when using a collaborative contract.

This paper aims to unravel how family businesses can harness the power of gamification and to illuminate the hurdles that obstruct this path to success. The research identifies these challenges providing valuable insights into the application of gamification in family businesses and the role of supervision and engagement as moderator variables in this relationship.

Using a structural modeling approach in a qualitative research methodology, the authors collected responses from n = 200 participants. The results were analyzed using Spearman’s test and multiple linear regression.

The research findings reveal that family businesses need to carefully redefine costs when introducing gamification, considering both fixed and variable expenses. The moderating effects of supervision are crucial for user evolution and the correlation, while user engagement influences user and useability experience. Additionally, a positive attitude enhances engagement. Finally, the five key challenges lead to difficulties when implementing gamification strategies.

This research provides valuable insights for the literature on gamification and family business and offers practical guidance for family business owners seeking to introduce a tailored value proposition adapted to their unique organizational needs and challenges.

A novel approach is proposed which, through the integration of gamification strategies with family business dynamics, explores the unique challenges and opportunities that arise within this context. By focusing specifically on family businesses, this study highlights how generational differences, ownership structures and cultural resistance can impact the successful implementation of gamification.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

Sociologists have long thought of the integration of people in communities – social integration – and hierarchical social systems – systemic integration – as contradictory goals. What strategies allow organizations to reconcile social and systemic integration? We examine this question through 40 in-depth, longitudinal interviews with leaders of nonprofit organizations that engage in the dual pursuit of social and systemic integration. Two processes reveal how the internal structure of organizations often mirrors the ways in which organizations are embedded in their local environments. When organizations engage in loose demographic coupling, relegating those who “match” the community to the work of social integration, they produce internal inequalities and justify them by claiming community building as sacred work. When engaging in community anchoring, organizations challenge internal and external inequalities simultaneously, but this process comes with costs. Our findings contribute to a constructivist understanding of community, the mechanisms by which organizations produce inequalities, and a place-based conception of organizations as embedded in community.

This study aims to introduce an innovative approach to predictive maintenance by integrating time-series sensor data with event logs, leveraging the synergistic potential of deep learning models. The primary goal is to enhance the accuracy of equipment failure predictions, thereby minimizing operational downtime.

The methodology uses a dual-model architecture, combining the patch time series transformer (PatchTST) model for analyzing time-series sensor data and bidirectional encoder representations from transformers for processing textual event log data. Two distinct fusion strategies, namely, early and late fusion, are explored to integrate these data sources effectively. The early fusion approach merges data at the initial stages of processing, while late fusion combines model outputs toward the end. This research conducts thorough experiments using real-world data from wind turbines to validate the approach.

The results demonstrate a significant improvement in fault prediction accuracy, with early fusion strategies outperforming traditional methods by 2.6% to 16.9%. Late fusion strategies, while more stable, underscore the benefit of integrating diverse data types for predictive maintenance. The study provides empirical evidence of the superiority of the fusion-based methodology over singular data source approaches.

This research is distinguished by its novel fusion-based approach to predictive maintenance, marking a departure from conventional single-source data analysis methods. By incorporating both time-series sensor data and textual event logs, the study unveils a comprehensive and effective strategy for fault prediction, paving the way for future advancements in the field.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.