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Corporate entrepreneurship is an important way for organizations to gain competitive advantages and achieve sustainable development. However, few studies pay attention to the influence of CEO strategic leadership on corporate entrepreneurship. Drawing on social identity theory and uncertainty-identity theory, this study aims to investigate whether CEO relationship-focused leadership impacts corporate entrepreneurship through middle managers’ (MMs’) organizational identification and whether the indirect effect is moderated by environmental uncertainty.

Using 192 Chinese samples with 192 firm-level and 716 department-level observations, this study uses multilevel structural equations modeling by Mplus 8.0 to test the theoretical model.

This study finds that CEO relationship-focused leadership positively predicts MMs’ organizational identification and corporate entrepreneurship, and MMs’ organizational identification mediates the relationship between CEO relationship-focused leadership and corporate entrepreneurship. In addition, environmental uncertainty moderates not only the relationship between CEO relationship-focused leadership and MMs’ organizational identification but also the indirect effect of CEO relationship-focused leadership on corporate entrepreneurship through MMs’ organizational identification.

This study enriches the understanding of process and contextualization of CEO strategic leadership influencing on corporate entrepreneurship.

To the best of the authors’ knowledge, this study is among the first to explore the influence of CEO relationship-focused leadership on corporate entrepreneurship.

This paper aims to propose a type of T-shaped two-axis force sensor for measuring the forces in x- and z-axes. The developed sensor has a simple structure and can be effectively assembled into compact devices.

A T-shaped plate, with both ends fixed on a base, is used as the substrate of the sensor. Eight strain gauges are placed in the root of the plate or near the sensor head, which can construct two full Wheatstone bridges on the upper and lower surfaces of the plate. When the x- or z-axes forces are applied to the sensor head, different deformation can be generated to the strain gauges. Therefore, the two Wheatstone bridges can be constructed with a different configuration for measuring the forces in x- or z-axes, respectively.

A prototype was designed and constructed and experiments were carried out to test the basic performance of the sensor. It has been verified that the developed sensor could measure the x- and z-axes forces independently with a high resolution of 2.5 and 5 mN, respectively.

Only one thin plate was used in the design, the forces in x- and z-axes could be measured independently and simultaneously, which made the sensor with a simple structure and compact size. Experiments were also verified that there was no crosstalk error occurred in one axis when the force was applied to the other axis.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

This paper aims to re-examine the effect of middle managers’ participation in decision-making (DM) on the innovation performance of Chinese manufacturing firms. It also testifies the intermediation channels regarding how middle managers’ participation influences firm innovation performance by testing the mediating effect.

This paper constructs a model that determines firm innovation and tests the hypotheses with econometric regressions using first-hand data from the China Employer–Employee Survey. Semiparametric and intersectional regressions are used to show how middle managers’ participation in DM influences Chinese firm innovation after controlling for the characteristics of middle manager personnel, entrepreneurs, frontline workers, firm, industry and country.

This paper empirically shows that middle managers’ participation in DM has a significantly positive effect on firm innovation. After testing the mediating effect, the findings show that the improvement of middle managers’ DM participation leads to a certain increase in technicians and a reduced dependence on government. In this regard, middle managers’ participation is complementary to the human capital of entrepreneurs.

This paper measures the degree of middle managers’ participation in DM according to four indicators. It focuses on the influence mechanisms of middle managers’ participation in DM on firm innovation performance, based on their ability to allocate external and internal resources. These findings will be useful for investigating management resource reallocation within firms for developing countries.

The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.

First, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.

The experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.

This method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.

The purpose of this paper is to enable robots to intelligently adapt their damping characteristics and motions in a reactive fashion toward human inputs and task requirements during physical human–robot interaction.

This paper exploits a combination of the dynamical system and the admittance model to create robot behaviors. The reference trajectories are generated by dynamical systems while the admittance control enables robots to compliantly follow the reference trajectories. To determine how control is divided between the two models, a collaborative arbitration algorithm is presented to change their contributions to the robot motion based on the contact forces. In addition, the authors investigate to model the robot’s impedance characteristics as a function of the task requirements and build a novel artificial damping field (ADF) to represent the virtual damping at arbitrary robot states.

The authors evaluate their methods through experiments on an UR10 robot. The result shows promising performances for the robot to achieve complex tasks in collaboration with human partners.

The proposed method extends the dynamical system approach with an admittance control law to allow a robot motion being adjusted in real time. Besides, the authors propose a novel ADF method to model the robot’s impedance characteristics as a function of the task requirements.

The purpose of this paper is to eliminate instability which may occur when a human stiffens his arms in physical human–robot interaction by estimating the human hand stiffness and presenting a modified vibration index.

Human hand stiffness is first estimated in real time as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A time-domain vibration index based on the interaction force is then modified to reduce the delay in instability detection. The instability is confirmed when the vibration index exceeds a given threshold. The virtual damping coefficient in admittance controller is adjusted accordingly to ensure stability in physical human–robot interaction.

By estimating the human hand stiffness and modifying the vibration index, the instability which may occur in stiff environment in physical human–robot interaction is detected and eliminated, and the time delay is reduced. The experimental results demonstrate significant improvement in stabilizing the system when the human operator stiffens his arms.

The originality is in estimating the human hand stiffness online as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A modification of the vibration index is also an originality to reduce the time delay of instability detection.

The purpose of this paper is to present a method which enables a robot to learn both motion skills and stiffness profiles from humans through kinesthetic human-robot cooperation.

Admittance control is applied to allow robot-compliant behaviors when following the reference trajectories. By extending the dynamical movement primitives (DMP) model, a new concept of DMP and stiffness primitives is introduced to encode a kinesthetic demonstration as a combination of trajectories and stiffness profiles, which are subsequently transferred to the robot. Electromyographic signals are extracted from a human’s upper limbs to obtain target stiffness profiles. By monitoring vibrations of the end-effector velocities, a stability observer is developed. The virtual damping coefficient of admittance controller is adjusted accordingly to eliminate the vibrations.

The performance of the proposed methods is evaluated experimentally. The result shows that the robot can perform tasks in a variable stiffness mode as like the human dose in the teaching phase.

DMP has been widely used as a teaching by demonstration method to represent movements of humans and robots. The proposed method extends the DMP framework to allow a robot to learn not only motion skills but also stiffness profiles. Additionally, the authors proposed a stability observer to eliminate vibrations when the robot is disturbed by environment.

The purpose of this study is to compare the spatial distribution of Airbnb and hotels in London and examine the relationship between demographic, socioeconomic and environmental factors and the supply of these two types of lodging supply.

Local information of Airbnb listings in London was collected through Insideairbnb.com. Gathered data were examined using geo-spatial auto-correlation analysis and spatial econometric models.

The results indicate that Airbnb predominates in the areas around popular tourist attractions and the peripheral areas of the city, while in the downtown area Airbnb and hotels are in the state of coexistence. The mono-centric model and the agglomeration model could be extended to the context of peer-to-peer accommodation. The location of Airbnb and traditional hotels capitalizes on different factors.

The study is based on secondary data due to data availability. And, it is based on the case of London, so the findings may not reflect the situation of small cities and rural destinations.

This study not only gives suggestions for local councils to regulate the location of hotels and Airbnb but also provides professional landlords with reference to choosing Airbnb location.

This study extends the hotel location theoretical models into the context of Airbnb and sheds lights on the distinction between these two business models in terms of location factors.

爱彼迎和酒店的位置：空间分布和关系

本研究旨在比较伦敦Airbnb和酒店的空间分布, 并探讨人口、社会经济和环境因素与这两类住宿供给的关系。

伦敦Airbnb房源信息通过Insideairbnb.com网站收集, 采用地理空间自相关分析和空间经济计量模型进行分析。

结果表明Airbnb主要集中在旅游景点周边和城市周边地区, 在市中心地区, Airbnb与酒店处于共存状态。单中心模型和聚集模型适用于共享住宿情境。Airbnb和传统酒店的空间分布影响因素的重要性存在差异。

本研究将酒店区位理论模型扩展到Airbnb情境下, 并揭示了这两种商业模式在区位因素方面的区别。

本研究采用二手数据。案例地为伦敦, 因此研究结果可能无法反映小城市和乡村旅游目的地的情况。

地方政府应更加重视专业公司的劳动力保障并限制旅游景点周边的短期租赁。

Ubicación de los hoteles y preferencias: distribución espacial y relaciones

El propósito de este estudio es comparar la distribución espacial de Airbnb y los hoteles en Londres y examinar la relación entre los factores demográficos, socioeconómicos y ambientales y la oferta de estos dos tipos de oferta de alojamiento.

La información local de los anuncios de Airbnb en Londres se recopiló a través de Insideairbnb.com. Los datos recopilados se examinaron mediante análisis de autocorrelación geoespacial y modelos econométricos espaciales.

Los resultados indican que Airbnb predomina en las zonas aledañas a los atractivos turísticos populares y las zonas periféricas de la ciudad, mientras que en la zona centro Airbnb y los hoteles se encuentran en estado de convivencia. El modelo monocéntrico y el modelo de aglomeración podrían extenderse al contexto de la acomodación entre pares. La ubicación de Airbnb y los hoteles tradicionales se basa en diferentes factores.

Este estudio amplía los modelos teóricos de ubicación de hoteles en el contexto de Airbnb y arroja luz sobre la distinción entre estos dos modelos comerciales en términos de factores de ubicación.

El estudio se basa en datos secundarios debido a la disponibilidad de datos. Y se basa en el caso de Londres, por lo que los hallazgos pueden no reflejar la situación de las ciudades pequeñas y los destinos rurales.

Los hallazgos sugieren que las autoridades locales deberían prestar más atención a la seguridad laboral de las empresas profesionales y restringir los alquileres a corto plazo alrededor de las atracciones turísticas.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.