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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.

Social free sampling (SFS) campaigns are an increasingly popular marketing practice in which firms provide trial users with free sampling products and collect posted trial reports from trial users on social commerce sites to attract prospective consumers. This paper aims to examine how trial users’ product evaluation in SFS influence appreciative reader engagement by utilizing the persuasion knowledge model (PKM).

To test our theoretical framework, 3,427 trial reports were collected from an SFS site and analyzed using Poisson regression models.

SFS evaluation is negatively associated with readers’ appreciative engagement. We also found that higher emotional intensity in SFS reports or higher reputation of the trial user mitigates the negative effect of the product evaluation. However, when the trial report with stronger emotional intensity is written by a trial user with a high reputation, the negative impact of the SFS evaluation on appreciative engagement becomes more pronounced.

Although extant research has acknowledged product rating bias in product trial reports, limited empirical studies have examined the impact of product ratings on reader engagement. This empirical study bridges the voids of product rating bias in the social free sampling literature and provides important managerial implications for the emerging social free sampling.

Brands should be careful of the negative effect of high product rating and this negative effect can be mitigated by inviting users of high reputation.

This study is among the first ones that examine the effect of SFS product evaluation on appreciative engagement and provide a nuanced understanding of how product evaluation, user reputation and emotion intensity jointly shape reader engagement.

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.

A popular production model for high-tech manufacturers is that they move most production lines abroad to produce formal products for sale and just keep a few production lines in headquarters to manufacture sample products for new product development. Under such a production model, the paper aims to develop a selection model of International Air Express (IAE) for high-tech manufacturers in airfreight of sample products using the fuzzy best-worst method (BWM).

In this paper, an assessment model based on the fuzzy BWM approach is proposed for high-tech manufacturers in selecting airfreight carriers for the shipping of sample products. Further, one high-tech electronic manufacturer in Taiwan was empirically investigated to validate the assessment model.

The result indicates that electronics manufacturer pays more attention to Promptness, Mutual trust, Freight rate and Financial status of fixed assets when selecting IAEs. Besides, FedEx is argued to be the most preferred IAE for the transportation of sample products. Based on the findings, some practical management implications were discussed.

Some literature limitations should be addressed. Initially, the adoption of the fuzzy BWM assumes independence among criteria. Nonetheless, this assumption is not yet to confirm in this study. Accordingly, this limitation leaves room for improvement in future studies. Further, in this paper, five experienced experts from the Radiant Opto-Electronics Corporation (ROEC) case were empirically surveyed. To ensure the validity of the surveying, this paper adopted an interviewing survey instead of a traditional mailed survey. However, more representative samples are still necessary to confirm the empirical results in future research.

Firstly, the proposed research model provides a systematic framework to the decision-making process, which assists high-tech manufacturers in identifying the most suitable IAEs based on multiple criteria. It has been illustrated that high-tech companies deliver their sample products requiring timely and secure means of transport. In practice, manufacturers can assess various IAEs considering some main factors, such as Operational Flexibility (OF), Partner Relationship (PR), Transportation Capability (TC) and Management, using fuzzy BWM. This process ensures the selection of IAEs aligning with their logistical needs and business priorities, ultimately enhancing operational efficiency and customer satisfaction. Secondly, empirical results from the ROEC case indicate that electronics manufacturer pays more attention to Promptness, Mutual trust, Freight rate and Financial status of fixed assets when selecting IAEs. Besides, FedEx is argued to be the most preferred IAE for transportation of sample products. In other words, ROEC should consider establishing long-term contracts with preferred IAEs (i.e. FedEx) to secure favorable rates and service commitments. On top of that, results not only provide practical information for manufacturers in selecting IAEs but also for IAE partners to improve their service policies.

The results not only provide practical information for high-tech manufacturers in selecting airfreight carriers but also for the airfreight carriers to improve their service quality.

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.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.