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To realise the shared development of the digital economy, people need to transcend the capital logic and advocate the logic of cooperative development, i.e. “co-construction, benefit-sharing and co-governance”. This study aims to discuss the aforementioned statement.

Platform economy is a new economic form produced by the transformation of the social production patterns in the era of digital capitalism. In the neo-imperialist stage, a new stage of capitalist development, capital logic promotes the global expansion of the platform economy and influences its development process, organisational form, contradictions and dilemmas and internal transcendence. Having the spatiotemporal chain of capital circulation repaired, the globalisation of the platform economy is reshaping how the means of production are combined with labour, affecting the local changes in the general relations of production and “international relations of production”.

In the accumulation of digital capitalism, the social contradictions and fundamental contradictions in the capitalist world have been further intensified, making exploitation, income distribution gap, monopoly and other problems increasingly severe. The imbalance and inequality in the global development of the digital economy are increasingly prominent.

Regarding the global governance of the digital economy, China, as a major responsible country, will strive to encourage all countries to co-build a community with a shared future in cyberspace. In the new international development pattern of digital economy globalisation, China must take effective measures to actively safeguard its national security and development interests to meet specific challenges.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

To control one of the joints during the actual movement of the hydraulically driven quadruped robot, all the other joints in the leg need to be locked. Once the joints are unlocked, there is a coupling effect among the joints. Therefore, during the normal exercise of the robot, the movement of each joint is affected by the coupling of other joints. This brings great difficulties to the coordinated motion control of the multi-joints of the robot. Therefore, it is necessary to reduce the influence of the coupling of the hydraulically driven quadruped robot.

To solve the coupling problem with the joints of the hydraulic quadruped robot, based on the principle of mechanism dynamics and hydraulic control, the dynamic mathematical model of the single leg mechanism of the hydraulic quadruped robot is established. On this basis, the coupling dynamics model of the two joints of the thigh and the calf is derived. On the basis of the multivariable decoupling theory, a neural network (NN) model reference decoupling controller is designed.

The simulation and prototype experiment are carried out between the thigh joint and the calf joint of the hydraulic quadruped robot, and the results show that the proposed NN model reference decoupling control method is effective, and this method can reduce the cross-coupling between the thigh and the calf and improve the dynamic characteristics of the single joint of the leg.

The proposed method provides technical support for the mechanical–hydraulic cross-coupling among the joints of the hydraulic quadruped robot, achieving coordinated movement of multiple joints of the robot and promoting the performance and automation level of the hydraulic quadruped robot.

On the basis of the theory of multivariable decoupling, a new decoupling control method is proposed, in which the mechanical–hydraulic coupling is taken as the coupling behavior of the hydraulic foot robot. The method reduces the influence of coupling of system, improves the control precision, realizes the coordinated movement among multiple joints and promotes the popularization and use of the hydraulically driven quadruped robot.

This paper analyzes the existing body of work on the relationship between depression and social media use in the information system field, including the impact of social media use on depression, the effect of depression on social media use and the association and interaction between depression and social media use.

Using the systematic review method, this study selected the Web of Science, Emerald, Science Direct, JSTOR, Wiley Online Library and Taylor and Francis Online as search databases and ended up with 29 papers that met all the authors' requirements.

This study identified five possible reasons for the inconsistencies between the findings of the selected studies. First, uses and gratifications theory has different influence mechanisms in evaluating the relationship between social media use and depression. Second, gender can moderate the impact of social media use on depression. Third, age moderates the association between social media use and depression. Fourth, for adolescents, the time spent on social media has a critical effect on their depression. Fifth, negative personality traits (e.g. rumination, envy, etc.) can play a significant role in mediating the relationship between passive social media use and depression.

This study conducted an evaluation of the relationship between depression and social media use. First, the authors summarized the research framework and main body of work covering the relationship between depression and social media use. Second, the authors proposed possible explanations for the inconsistencies between the findings. Third, the authors discussed and explained the possible influence mechanisms of the existing results.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0211.

The purpose of this paper is to investigate the impact of product description and involvement on purchase intention in a cross-border e-commerce (CBEC) setting from a psychological perspective.

This study proposes a research model of purchase intention in CBEC based on the involvement theory and commitment-involvement theory. The research model was tested using the covariance-based structural equation modeling technique. Data were collected from consumers on a popular CBEC platform in China.

A high-quality product description has no significant positive effect on purchase intention, but it has significant positive effects on product cognitive involvement, product affective involvement, platform enduring involvement and platform situational involvement. In addition, product affective involvement, platform enduring involvement and platform situational involvement all have significant positive effect on purchase intention, but this effect is not significant in the relationship between product cognitive involvement and purchase intention.

This study calls for sellers to optimize product descriptions on CBEC platforms in order to attract more buyers and generate more profits.

This study integrates two theories of involvement into the research model in the CBEC context. Based on this model, the authors analyzed how product description affects purchase intention under the joint influence of two involvement factors.

This study explores whether and how Internet usage improves the subjective health of middle-aged and older adults by analyzing the mediating role of social engagement and heterogeneity of different living arrangements.

Based on data from the China Health and Retirement Longitudinal Study, the ordinary least squares (OLS) method is adopted to explore the relationship between Internet usage and the subjective health of middle-aged and older adults. Propensity score matching method (PSM) is used to alleviate self-selection bias in the samples. The bootstrap method is adopted to test the mediating role of social engagement, and generalized structural equation modeling (GSEM) is employed to resolve endogeneity. A permutation test is adopted to examine the heterogeneous effects of Internet usage on different living arrangements.

Internet access can help relieve depression among middle-aged and older adults and enhance their self-rated health, leading to perceived changes in health status. However, Internet usage is not directly associated with health satisfaction among middle-aged and older adults. Nevertheless, Internet usage can enhance middle-aged and older adults' subjective health by facilitating social engagement and significantly influences middle-aged and older adults living with their children.

This study reveals the underlying role of Internet usage among older adults and provides insights for governments and families to help middle-aged and older adults actively adapt to a digital society and improve their health.

Algorithmic monitoring has been widely applied to the practice of platform economy as a management means. Despite its benefits, negative effects of algorithmic monitoring are gradually emerging.

Based on moral disengagement theory, this research aims to investigate how algorithmic monitoring might affect gig workers’ attitudes and behaviors. Specifically, we explored the effect of algorithmic monitoring on gig workers’ unethical behavior. A three-wave survey was conducted online, and the sample consisted of 318 responses from Chinese gig workers.

The results revealed that algorithmic monitoring positively affected unethical behavior through displacement of responsibility, and the individualistic orientation of gig workers moderated this relationship. However, the relationship between moral justification and algorithmic monitoring was not significant.

This research contributes to the algorithmic monitoring literature and examines its impact on gig workers’ unethical behavior. By revealing the underlying mechanism and boundary conditions, this research furthers our understanding of the negative influences of algorithmic monitoring and provides practical implications.

The purpose of this paper is to present the latest sensing structure designs and principles of information detection of fiber Bragg grating (FBG) displacement sensors. Research advance and the future work in this field have been described, with the background that displacement and deformation measurements are universal and crucial for structural health monitoring.

This paper analyzes and summarizes the existing FBG displacement sensing technologies from two aspects principle of information detection (wavelength detection, spectral bandwidth detection, light intensity detection, among others) and principle of the sensing elastomer structure design (cantilever beam type, spring type, elastic ring type and other composite structures).

The current research on developing FBG displacement sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of new information detection method. The authors hypothesize that the following research trends will be strengthened in future: temperature compensation technology for FBG displacement sensors based on wavelength detection; a study of more diverse elastic structures; and fiber gratings manufactured with special fibers will greatly improve the performance of sensors.

The latest sensing structure designs and principles of information detection of FBG displacement sensors have been proposed, which could provide important reference for research group.

This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

The purpose of this paper is to explore the impact of product information on impulse purchases in a cross-border electronic commerce (CBEC) setting from the perspective of cue stimulation.

This study proposes a research model of impulse purchases in CBEC based on the cue utilization theory and Stimulus-Organism-Response (S-O-R) model. The research model was tested using covariance-based structural equation modelling. Data were collected from the consumers of a popular CBEC platform in China.

A high-quality product description has a significant positive effect on concentration but not on curiosity and autotelic experience. A high-quality product display has a significant positive effect on concentration, curiosity and autotelic experience. High-quality product content has a significant positive effect on curiosity and autotelic experience but not on concentration. Curiosity and autotelic experience both have a significant positive effect on impulse purchases; however, concentration has no such effect on an impulse purchase. Curiosity and autotelic experience have a full mediation effect between product display and impulse purchases and between product content and impulse purchases, respectively.

This study integrates the S-O-R model and cue utilization theory to construct a theoretical model of product information-flow experience-impulse purchases. According to the model, we can understand how product information influences consumers' impulse purchases in CBEC.