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The purpose of this review is to systematically understand the development of enterprise social media (ESM) research, quantitatively analyze the landscape and track the development of ESM literature and reveal new trends and challenges in ESM research.

Based on 321 relevant literature studies (2005–2020) collected from the Web of Science core collection, the visualization tool CiteSpace is used to conduct bibliometric cocitation and cooccurrence analyses to quantify and visualize the landscape and evolution of ESM research.

Through analyzing the author cocitation network, document cocitation network, journal cocitation network and keywords cooccurrence network, this review proposes an integrated research framework, which highlights major purposes, antecedents and consequences of ESM use in organizations and presents future research trends of ESM research.

Different from the existing qualitative review of ESM, this review adopts bibliometric review to quantify and visualize the landscape of ESM research.

Extant research has paid considerable attention to the effects of enterprise social media (ESM) on employees' work attitudes and outcomes, yet the authors know little about the influence of job demands arising from the implementation of ESM. Drawing on resource allocation theory, the purpose of this study is to unravel how ESM-related job demands influence employee outcomes.

This study conducts a two-wave time-lagged survey of 223 employees from 53 teams in 14 financial service firms in China to test the conceptual model.

The findings of this paper indicate that ESM-related job demands have indirect effects on employee outcomes (i.e. job satisfaction and work–family conflict), and emotional exhaustion plays an intermediary role in these relationships. Specifically, ESM-related job demands have a U-shaped effect on emotional exhaustion.

This study combines job demands with ESM research and clarifies the mechanism behind how ESM-related job demands at different intensity affect employee outcomes from a new perspective. Moreover, this study’s findings suggest several beneficial courses of action for managers to take advantage of ESM.

The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high load-carrying capacity and dexterity of the robot; on the other hand, the fully autonomous mode is uncontrollable and the teleoperation mode has a high failure rate. Therefore, this study aims to design a distribution network operation robot named Sky-Worker to solve the above two problems.

The heterogeneous arms of Sky-Worker are driven by hydraulics and electric motors to solve the contradiction between high load-carrying capacity and high flexibility. A human–robot collaborative shared control architecture is built to realize real-time human intervention during autonomous operation, and control weights are dynamically assigned based on energy optimization.

Simulations and tests show that Sky-Worker has good dexterity while having a high load capacity. Based on Sky-Worker, multiuser tests and practical application experiments show that the designed shared-control mode effectively improves the success rate and efficiency of operations compared with other current operation modes.

The designed heterogeneous dual-arm distribution robot aims to better serve distribution line operation tasks.

For the first time, the integration of hydraulic and motor drives into a distribution network operation robot has achieved better overall performance. A human–robot cooperative shared control framework is proposed for remote live-line working robots, which provides better operation results than other current operation modes.

Sensorless passive lead-through programming (LTP) is a promising physical human-robot interaction technology that enables manual trajectory demonstrations based on gravity and friction compensation. The major difficulty lies in static friction compensation during LTP start-up. Instead of static friction compensation, conventional methods only compensate for Coulomb friction after the joint velocity exceeds a threshold. Therefore, conventional start-up external torques must overcome static friction. When the static friction is considerable, it is difficult for conventional LTP to start up and make small movements. This paper aims to decrease the start-up external torque and improve the small movement performance.

This paper reveals a novel usage of a high-gain position-loop in industrial robot applications aimed at sensitively detecting external torque during start-up. Then, the static friction is partly compensated by Coulomb friction to facilitate start-up. In addition, a detailed transition method between the proposed start-up and conventional passive LTP is proposed based on a finite state machine.

Experiments are implemented on the ROKAE XB4 robot to verify the effectiveness of the proposed external torque detection. Compared with the conventional LTP method, the proposed LTP method significantly decreases the start-up external torque and facilitates small movements.

This paper proposes and verifies a novel start-up method of sensorless LTP based on a start-up external torque detection and a transition method between start-up and conventional LTP. This research improves the LTP start-up performance, especially for industrial robots with large static friction.

Supplier evaluation is a part of logistic management. In the present era, resilient supply chain performance (RSCP) assessment of the vendor enterprise is respected as a hot topic. The purpose of this paper is to enable the managers to map the performance in percentage system and also enabling managers for identifying the weak indices-metrics, which need to be improved up to ideal or standard level and strong indices-metrics.

The authors found two research gaps via a literature survey. The first research gap revealed that the performance of a resilient supplier is computed solely in terms of a fuzzy mathematical scale. The articles are not yet published, which could measure the RSCP in percentage. The second research gap argued about the mitigation of the multi-level hierarchical resilient vendor/supplier evaluation framework for materializing RSCP and identifying weak and strong performing indices-metrics. To compensate the both research gaps, the authors developed a novel fuzzy gain-loss evolutionary computational approach to assess the performance of a firm in percentage. Next, a revised ranking technique coupled with trapezoidal fuzzy set based fuzzy performance importance index is implemented on the framework to seek weak and strong indices-metrics. The performance loss of each metric using the ideal solution concept considering the attitude of decision makers is also revealed.

The authors found the RSC performance of supplier firm 74 per cent, whereas performance loss 26 per cent, while actual performance is compared with standard fuzzy performance index (SFPI). Performance loss 26 per cent can be compensated by improving the performance of weak indices-metrics.

The novelty of the paper is that the authors used the ideal solution concept to compute the SFPI and compare it with actual FPI for evaluating the gain and loss of resilient supplier firm in percentage and identify weak and strong indices so that managers can improve the performance of weak indices. The work possesses the significant for all organizations, as research work enables the managers to map and improve the RSC performance of any vendor firm in future. The presented work considers the case of an automobile parts supplier industry to validate the developed approach.

This paper aims to present a novel adaptive sliding mode control (ASMC) method based on the predefined performance barrier function for reusable launch vehicle under attitude constraints and mismatched disturbances.

A novel ASMC based on barrier function is adopted to deal with matched and mismatched disturbances. The upper bounds of the disturbances are not required to be known in advance. Meanwhile, a predefined performance function (PPF) with prescribed convergence time is used to adjust the boundary of the barrier function. The transient performance, including the overshoot, convergence rate and settling time, as well as the steady-state performance of the attitude tracking error are retained in the predetermined region under the barrier function and PPF. The stability of the proposed control method is analyzed via Lyapunov method.

In contrast to conventional adaptive back-stepping methods, the proposed method is comparatively simple and effective which does not need to disassemble the control system into multiple first-order systems. The proposed barrier function based on PPF can adjust not only the switching gain in an adaptive way but also the convergence time and steady-state error. And the efficiency of the proposed method is illustrated by conducting numerical simulations.

A novel barrier function based ASMC method is proposed to fit in the amplitude of the mismatched and matched disturbances. The transient and steady-state performance of attitude tracking error can be selected as prior control parameters.

The purpose of this paper is to enhance control accuracy, energy efficiency and productivity of customized industrial robots by the proposed multi-objective trajectory optimization approach. To obtain accurate dynamic matching torques of the robot joints with optimal motion, an improved dynamic model built by a novel parameter identification method has been proposed.

This paper proposes a novel multi-objective optimal approach to minimize the time and energy consumption of robot trajectory. First, the authors develop a reliable dynamic parameters identification method to obtain joint torques for formulating the normalized energy optimization function and dynamic constraints. Then, optimal trajectory variables are solved by converting the objective function into relaxation constraints based on second-order cone programming and Runge–Kutta discrete method to reduce the solving complexity.

Extensive experiments via simulation and in real customized robots are conducted. The results of this paper illustrate that the accuracy of joint torque predicted by the proposed model increases by 28.79% to 79.05% over the simplified models used in existing optimization studies. Meanwhile, under the same solving efficiency, the proposed optimization trajectory consumes a shorter time and less energy compared with the existing optimization ones and the polynomial trajectory.

A novel time-energy consumption optimal trajectory planning method based on dynamic identification is proposed. Most existing optimization methods neglect the effect of dynamic model reliability on energy efficiency optimization. A novel parameter identification approach and a complete dynamic torque model are proposed. Experimental results of dynamic matching torques verify that the control accuracy of optimal robot motion can be significantly improved by the proposed model.

Penetrator plays an important role in the exploration of Moon and Mars. The navigation method is a key technology during the development of penetrator. To meet the high accuracy requirements of Moon penetrator, this paper aims to propose two kinds of navigation systems.

The line of sight of vision sensor between the penetrator and Moon orbiter could be utilized as the measurement during the navigation system design. However, the analysis of observability shows that the navigation system cannot estimate the position and velocity of penetrator, when the line of sight measurement is the only resource of information. Therefore, the Doppler measurement due to the relative motion between penetrator and the orbiter is used as the supplement. The other option is the relative range measurement between penetrator and the orbiter. The sigma-point Kalman Filtering is implemented to fuse the information from the vision sensor and Doppler or rangefinder. The observability of two navigation system is analyzed.

The sigma-point Kalman filtering could be used based on vision sensor and Doppler radar or laser rangefinder to give an accurate estimation of Moon penetrator position and velocity without increasing the payload of Moon penetrator or decreasing the estimation accuracy. However, the simulation result shows that the last method is better. The observability analysis also proves this conclusion.

Two navigation systems are proposed, and the simulations show that both systems can provide accurate estimation of states of penetrator.

Two navigation methods are proposed, and the observability of these navigation systems is analyzed. The sigma-point Kalman filtering is first introduced to the vision-based navigation system for Moon penetrator to provide precision navigation during the descent phase of Moon penetrator.

The purpose of this paper is to present a novel guidance law that is able to control the impact time while the seeker’s field of view (FOV) is constrained.

The new guidance law is derived from the framework of Lyapunov stability theory to ensure interception at the desired impact time. A time-varying guidance gain scheme is proposed based on the analysis of the convergence time of impact time error, where finite-time stability theory is used. The circular trajectory assumption is adopted for the derivation of accurate analytical estimation of time-to-go. The seeker’s FOV constraint, along with missile acceleration constraint, is considered during guidance law design, and a switching strategy to satisfy it is designed.

The proposed guidance law can drive missile to intercept stationary target at the desired impact time, as well as satisfies seeker’s FOV and missile acceleration constraints during engagement. Simulation results show that the proposed guidance law could provide robustness against different engagement scenarios and autopilot lag.

The presented guidance law lays a foundation for using cooperative strategies, such as simultaneous attack.

This paper presents further study on the impact time control problem considering the seeker’s FOV constraint, which conforms better to reality.