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This study aims to improve the force sensing performance of the robot joint for the safety and flexibility of physical human–robot interaction.

A force sensing mechanism (FSM) for an S-shaped spring of a robot variable stiffness actuator (VSA) was designed. The yield strength of the spring material, geometric and assembly structure constraints of the VSA are all considered for the actuator deflection limit design. The elastic deformation model is solved in reverse to obtain the local deformation limit profile of the S-spring at different spring angles. The deformation limit mechanism is manufactured by three-dimensional printing and assembled with S-springs. The force sensing function for the VSA is achieved by the input and output shaft encoders and stiffness model. The FSM is verified by torque-deflection experiments with variable stiffness.

The yield strength of the S-spring material is the strictest constraint for elastic deformation. Experimental results show that the external force can be quickly and reliably perceived. As the spring angle increases (stiffness increases), the hysteresis and nonlinear error decrease. Under the constraint of the FSM, the maximum deflection also decreases rapidly.

The designed FSM based on the deformation and stiffness model provides a comprehensive design reference in a VSA with nonlinear elastic mechanisms, which is ignored but important for exploring the VSAs potential.

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.

Although businesses increasingly use augmented reality (AR) to enhance service experiences, the way AR service marketing inspires consumers remains underexplored. Drawing on the consumer inspiration literature, the authors examine how AR service marketing activities such as entertainment, interaction, trendiness and customization enhance consumer inspiration. In addition, the authors explore the role of consumer empowerment and skepticism as key underlying mechanisms between consumer inspiration and value co-creation (VCC) or co-destruction (VCD) intentions.

The study used a mixed method, explanatory sequential design to gain a more comprehensive understanding of their proposed theoretical framework. The quantitative survey study involved 344 AR app users, followed by a qualitative open-ended essay study with 34 AR app users.

Results suggest that AR service marketing activities positively influence consumer inspiration, which in turn increases consumer empowerment and reduces skepticism. The authors also found that consumer empowerment leads to VCC, while skepticism leads to VCD. These findings provide valuable insights for practitioners seeking to implement AR service marketing activities effectively to inspire consumers, foster value creation and manage value destruction.

The study highlights inspiration as a key factor in motivating consumers to co-create value, transcending typical service experiences and limitations. Empowered consumers, feeling inspired, are more inclined to contribute effectively to VCC, also fostering trust in the service provider. AR serves not just as a sales channel, but also as a tool for relationship-building and brand retention. Managers should leverage AR to elicit feelings of trendiness, customization and interaction, fostering empowerment and inspiring consumers to co-create value.

This study significantly contributes to the growing body of literature on consumer inspiration and AR service marketing. It emphasizes the need to consider external (i.e. marketing-induced) stimuli in understanding the sources and consequences of consumer inspiration through AR.

This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.

The aim of this article is to conceptually assess the healthiness of regions. A developed health region can become an attractive health tourism destination. Within the framework of the sustainable development paradigm, this article identifies key areas for development in the creation of health regions.

In this conceptual paper, a traditional narrative review was required. In addition to the scientific literature, the analyses included key reports and strategy documents from public institutions and organizations, the content of which was relevant to the issue addressed.

A conceptual framework of a health region based on sustainability has been constructed that can support practitioners seeking to develop a health-based region. As a result of a 3-stage conceptualization process, a set of 56 indicators was developed to describe the health characteristics of (1) the environmental sphere, with criteria including air quality, noise levels and natural assets, while taking into account needs for climate crisis resilience adaptation measure; (2) the social sphere concerning infrastructure, which includes elements of space use, transportation accessibility, accessibility for people with special needs, including especially people with disabilities and anthropogenic qualities, and (3) the economic sphere, which is an important element affecting the quality of life.

This is the first attempt to describe a health region in the context of sustainable development. The set of indicators is the result of conceptual work, providing a basis for further description of health regions and serving as an inspiration for regions wishing to prioritize health in their development.

In this paper, the dynamical properties and analytic solutions of the coupled Drinfel’d–Sokolov–Wilson equation with a conformal derivative are studied by the complete discrimination system for the polynomial method. Not only are the Hamiltonian and topological properties of this equation are presented, but also all exact traveling wave solutions are found.

The complete discrimination system for the polynomial method serves as the cornerstone of the analytical approach, facilitating both the analysis of dynamic properties and the derivation of exact solutions for the equation under study.

The study shows that by adjusting specific parameters, various classified solutions such as rational function solutions, solitary wave solutions and periodic function solutions can be realized in practical applications. Furthermore, numerical analysis shows that the introduction of different external perturbation terms in the coupled Drinfel’d–Sokolov–Wilson equations with conformal derivative can confirm the presence of chaotic behaviors.

The coupled Drinfel’d–Sokolov–Wilson equation is analyzed qualitatively and quantitatively using the same method. Firstly, the dynamical system is analyzed qualitatively using a third-order discriminant system to predict the type of solutions. Then, use a fourth-order discriminant system to solve the exact solutions and maintain parameter consistency. This method ensures that the results of qualitative and quantitative analysis are achieved under the same set of parameters, thereby improving the coherence and reliability of the research.

Silence is a commonly seen phenomenon at the workplace. However, little is known about the cause and effect of leader silence. Drawing on the affective events theory, we develop a moderated mediation model to examine the effect of subordinates’ creative deviance on leader's authoritative silence and test the moderating effect of subordinates’ political skills.

Our research adopts a novel bottom-up perspective to investigate the subordinates’ influence on leader silence. A two-wave survey study involving 196 corporate team leaders in China was employed.

We found that leader’s workplace anxiety mediated the relationship between subordinates' creative deviance and leader's authoritative silence and subordinates’ political skills moderated the mediating effect.

Our research contributes to the leader silence literature in three folds. First, we employ the AET framework to study leader silence from the emotional perspective. Second, this research adopts a bottom-up angle to reveal the influence of subordinates’ behavior on leader silence. Third, the political skills lens offers novel explanation of why the anxious emotions triggered by followers’ creative deviance vary among leaders.

This study aims to streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork.

This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period.

Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers.

The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

The purpose of this paper is to integrate sustainability and economic factors into a framework for understanding the reshoring decision.

This paper integrates sustainability and economic factors into a reshoring framework through using the theoretical perspectives of the natural resource-based view (NRBV) and transaction cost economics (TCE), and carrying out case study research with a number of firms involved in reshoring in the German automotive industry.

Through adopting a multi-theory approach, the framework captures the complexities of the reshoring decision and illustrates that reshoring is not a location decision alone, but encompasses a range of sourcing options such as local production in-house, using a local supplier or addressing sustainability problems with the offshore operation. The importance of sustainability capability development as a basis of extending the range of reshoring sourcing options available is highlighted.

Using the NRBV has allowed to develop value creating drivers in the context of reshoring. Integrating the logic of TCE with this analysis provided an understanding of how cost reducing drivers were present alongside the value creating drivers for reshoring at the case companies. Beyond previous frameworks integrating the RBV and TCE, bringing in the NRBV allowed us to highlight the importance of sustainability capability development as a basis of extending the range of reshoring sourcing options available. While this study’s cases were in the automotive industry in Germany, future research could sample for further geographies and industries to cover varying regulatory pressures for sustainability as well as sustainability-related industry initiatives.

The framework can provide guidance to managers on the conditions that favour the selection of each sourcing option when making the reshoring decision.

Although there are frameworks in the literature that explain the reshoring decision, limited attention has been given to integrating sustainability issues into the analysis. The findings here contribute important insights into the complementary and contradictory prescriptions of the NRBV and TCE in reshoring decisions, and several propositions are offered outlining these relationships. The resulting framework provides an integrated approach for managerial decision-making beyond economic factors alone.