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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.

Purpose: The study focusses on the systematic review of the greenwashing literature to present the research gaps to researchers for future studies.

Design/methodology/approach: The systematic review has been used to analyse past studies on ‘greenwashing’. The 325 research articles of the previous 10 years (2014–2023) were downloaded from the Scopus-indexed database using the keyword ‘greenwashing’.

The findings: There is a need for a study on greenwashing in developing countries like India. An attempt should be made to analyse the research with a large sample size.

Research limitations: The scope of the data used in this study is limited by the source of retrieval, that is, the Scopus. The current source adequately serves the study’s purpose, as the Scopus database is one of the most significant citation databases. This study analyses data from the years 2014 to 2023 to improve credibility and reduce biases.

Practical implications: The research findings will significantly help researchers, green marketers, and practitioners be aware of the emerging markets of greenwashing and consumers’ rising greenwashing perception of green products.

Originality/value: This study is a novel attempt to explore a better understanding of greenwashing for researchers. The study is original; work has yet to be performed on this topic.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

Coronavirus disease 2019 (COVID-19) has made telecommuting widely valued, but different individuals have different degrees of acceptance of telecommuting. This article aims to identify suitable individuals for telework and to clarify which types of workers are suitable for what level of telework, set scientific, reasonable hybrid work ratios and processes and measure their suitability.

First, two working scenarios of different risk levels were established, and the theory of planned behavior (TPB) was used to introduce latent variables, constructing a multi-indicator multi-causal model (MIMIC) to identify suitable individuals, and second, constructing an integrated choice and latent variable (ICLV) model of the working method to determine the suitability of different types of people for telework by calculating their selection probabilities.

It is possible to clearly distinguish between two types of suitable individuals for telework or traditional work. Their behavior is significantly influenced by the work environment, which is influenced by variables such as age, income, attitude, perceived behavioral control, work–family balance and personnel exposure level. In low-risk scenarios, the influencing factors of the behavioral model for both types of people are relatively consistent, while in high-risk scenarios, significant differences arise. Furthermore, the suitability of telework for the telework-suitable group is less affected by the pandemic, while the suitability for the non-suitable group is greatly affected.

This study contributes to previous literature by: (1) determining the suitability of different population types for telework by calculating the probability of selection, (2) dividing telework and traditional populations into two categories, identifying the differences in factors that affect telework under different epidemic risks and (3) considering the impact of changes in the work scenario on the suitability of telework for employees and classifying the population based on the suitability of telework in order to avoid the potential negative impact of telework.

Drawing on the JD-R theory, this study investigates the effect of working from home on employee engagement and work-life balance considering work-life balance as the mediator in the working from home-employee engagement relationship and altruism as the moderator in the work-life balance-employee engagement relationship.

An online questionnaire using the snowball sampling approach was employed to collect data from 350 professional-level employees working from home due to the COVID-19 outbreak. Hypotheses were tested using structural equation modeling.

The findings indicate that work-life balance significantly affects employee engagement and confirm the moderating role of altruism in the relationship between work-life balance and employee engagement. However, work-life balance does not mediate the relationship between working from home and employee engagement.

These findings advanced JD-R theory in human resource management by focusing on a more humanistic and compassionate approach towards managing employees, particularly in the remote working context during turbulent times.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

The results of the COVID-19 pandemic rendered the traditional work environment model obsolete for the United States Air Force, resulting in the need to create a new hybrid work model that fits unique employee needs in a complex organization. This practitioner article discusses how the 711th Human Performance Wing (711 HPW) built the Mission-Focused Agile Work Environment (MFAWE) using a combination of human and mission-focused strategies to ensure a more flexible work environment without compromising excellence or its employees' well-being.

Using an action research approach, data was collected by 77 diverse stakeholders in six working groups. Five perspectives were examined – employee, operations, infrastructure, leadership and mission – using a combination of literature and policy reviews, interviews, surveys and personal experiences to deliver recommendations to leadership for implementation.

The MFAWE addressed hybrid work transition requirements, including employee guidance, permanent workspace guidelines and facilities. Lessons learned from implementation included the need for a change management and communication strategy. An employee playbook was found to be an effective modality for information sharing but not for policy enforcement. Employee preference for permanent space regardless of time on site due to sanitation and mental health concerns was also discovered.

This article showcases how a large, complex organization built a new hybrid work model using employee-inclusive practices, filling a gap in the literature. This project also uncovered complex interdependencies when transitioning to a hybrid work model, including employee preferences.

This study aims to examine the impact of digital transformation on firms’ value and explore the mediating impact of ESG performance and moderating impact of information interaction.

Data was collected from companies listed on the Shanghai and Shenzhen stock exchange between 2012 and 2020 with 21,488 observational samples, featuring a selection of 3,348 companies. Panel data regression techniques were used to test the mediating role of ESG performance and the moderating role of information interaction.

The study found that digital transformation can improve firms’ ESG performance, which in turn positively affects their value. The firms that engage in more interaction with outsiders benefit more from digital transformation and have a higher value.

This study provides new theoretical insight into improving firms’ value through digital transformation and ESG performance. It is the first to discuss and study the moderating role of information interaction in the relationship between digital transformation and firms’ value.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.