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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.

This study aimed to examine how Medical Expenditure Panel Survey (MEPS) data have been used to support scientific discoveries in biomedical and health sciences, and provide insight to researchers who are interested in using MEPS regarding collaborations and dissemination of research output.

A bibliometric approach was used to systematically examine the publications that used MEPS data and were indexed by PubMed and Web of Science (WoS). Microsoft Excel and bibliometric tools (WoS and VOSviewer) were utilized for quantitative and bibliometric network analysis. The measures were investigated on the total number of publications by year, research categories, source journals, other datasets/databases co-used with MEPS, funding sources, collaboration patterns, and research topics.

A total of 1,953 eligible publications were included in this study with the numbers growing significantly over time. MEPS data were primarily used in healthcare services, public environmental and occupational health research. The journals that published the most papers using MEPS were all in the healthcare research area. Twenty-four other databases were found to be used along with MEPS. Over 3,200 researchers from 1,074 institutions in 25 countries have contributed to the publications. Research funding was supported from federal, private, local, and international agencies. Three clusters of research topics were identified among 235 key terms extracted from titles and abstracts.

Our results illustrated the broad landscape of the research efforts that MEPS data have supported and substantiated the value of AHRQ's effort of providing MEPS to the public.

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.

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.

Human beings are able to adjust their arm stiffness in daily life tasks. This paper aims to enable a robot to learn these human-like variable stiffness motor skills autonomously.

The paper presents a reinforcement learning method to enable a robot to learn variable stiffness motor skills autonomously. Firstly, the variable stiffness motor skills are encoded by the previously proposed dynamical movement primitives and stiffness primitives (DMP-SP) framework, which is able to generate both motion and stiffness curves for robots. The admittance controller is then used to make a robot follow the motion and stiffness curves. The authors then use the policy improvement with path integrals (PI2) algorithm to optimize the robot motion and stiffness curves iteratively.

The performance of the proposed method is evaluated on an UR10 robot by two different tasks: a) via-point task, b) sweeping the floor. The results show that after training, the robot is capable of accomplishing the tasks safely and compliantly.

The method can help the robots walk out of the isolated environment and accelerate their integration into human being’s daily life.

This paper uses reinforcement learning method to improve DMP-SP framework, thus allowing the robots to learn variable stiffness motor skills autonomously with no need for extra sensors.

In the era of the digital economy, digital platform capability plays an important role in the process of firm digitization. This study aims to investigate the relationships among digital platform capability and innovation performance from the perspective of external knowledge search and resource bricolage.

This study uses the hierarchical regression and bootstrapping methods to test the theoretical framework and research hypotheses. The survey data were collected from 629 Chinese firms.

This study finds that digital platform capability has a significant positive effect on innovation performance; external knowledge search and resource bricolage both play partial mediating roles between digital platform capability and innovation performance. There exist the serial mediation effects of “digital platform capability – external knowledge search – resource bricolage – innovation performance”.

The conclusion of this study can expand the research on digital platform capability, reveal the internal mechanism of digital platform capability in firm innovation and provide ideas and inspiration for firms to improve innovation performance and realise high-quality development.

Targeting the common functions of the Zhejiang Library website, elderly individuals were invited to complete six experimental tasks on the improved website interfaces, and subjective data (PAD emotion scale and usability evaluation) and objective data (eye movement data) were recorded to verify the effects of graphic layout and navigation position on the information-seeking experience of elderly individuals.

This study analyzes the effect of the graphic layout and navigation position of the Zhejiang Library’s website interface on the emotional state, perceived usability and information-seeking time of elderly individuals, with the aim of providing guidance and suggestions for the elderly-oriented reform of the public library website.

The experimental results show that the graphic layout has a significant effect on the emotional state and perceived usability of elderly individuals, and the navigation position has a significant effect on the information-seeking time; the interaction between graphic layout and navigation position exerts a significant effect on the information-seeking time of elderly individuals. The eye movement data show that elderly individuals have a better information-seeking experience when the top navigation bar and image-text matched arrangement are used for the interface layout.

This study adopts a new approach combining subjective data and eye movement data to evaluate the effect of the public library website’s interface layout on the information-seeking experience for older people. The findings can provide a theoretical basis and methodological support for the elderly-oriented reform of public library websites. They can also provide scientific design suggestions for age-friendly interface layouts of other Internet products and service applications.

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.

This paper aims to understand the impact of intellectual capital components (human, structural and relational capital) on business internationalization through exports, analyzing the Colombian manufacturing sector.

A binomial logistic regression model was used in which the export propensity was the dependent variable. The explanatory variables consisted of the human capital, including training and managerial characteristics; the structural capital, including innovation, intellectual property, certifications and management and the relational capital, encompassing relationships with other companies, public entities and the domestic market. The Survey of Development and Technological Innovation - EDIT - Industry 2018, carried out by the National Administrative Department of Statistics of Colombia, was used to collect data from 7,529 companies in 24 manufacturing subsectors.

The research findings suggest that there is a positive relationship between internationalization and human capital (postgraduate, university and school training), with structural capital (innovation in organizational processes, ownership of patents, software rights, industrial rights, trademark registration, obtaining intellectual property rights, complexity in design, process certifications, compliance with technical requirements and the existence of production goals) and with relational capital (confidentiality agreements with other companies and contracts with the international public sector).

This article contributes to the literature generating knowledge on the relationship between intellectual capital and the internationalization of Colombian industrial companies. It will also have managerial and social implications serving as input for the decision-making process of firms undergoing internationalization, and for policymakers.