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In era of industry 4.0 all the organizations are investing their resources so they can adopt the latest technologies with no exception of supply chain. Accordingly, the present study attempted to examine the influence of digitalization of supply chain and performance in context of Chinese sports industry. Additionally, it has considered the supply chain integration and time management as a mechanism along with boundary condition of supply chain resilience.

The study followed positivism philosophy and adopted quantitative methods. The data were collected by using the questionnaire from the Chinese sport industry organizations’ professionals related to logistics and supply chain. A total 746 questionnaires were distributed and 570 of them subjected to SPSS and Smart PLS for data analysis. Hypotheses were tested using PLS-SEM through the Smart-PLS 4.

The results of the study revealed that supply chain digitalization positively influences the both internal and external supply chain integration. Moreover, supply chain planning and scheduling influenced by both internal and external supply chain integration lead by supply chain digitalization. Ultimately resulting in improved sports industry performance. However, the supply chain resilience did not found as a significant moderator.

The study is few of the attempts that have tested a comprehensive mechanism through which the supply chain digitalization lead towards the higher performance. Also, the study results signify that the digitization can help the organizations to accomplish superior performance specifically in sports industry.

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.

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.

This study examines the serial mediation mechanism between paternalistic leadership and innovative work behavior through the leader–member exchange (LMX) and employee voice behavior. Particularly, this study utilized the social exchange theory to investigate the indirect effect of three distinct dimensions of paternalistic leadership style on innovative work behavior through LMX and employee voice behavior.

Self-reported questionnaires were used to collect data from 397 employees in Pakistan. Hypotheses were tested using structural equation modeling (SEM).

The two dimensions of paternalistic leadership were significantly related to LMX. LMX had a significant effect on employee voice behavior that was further related to innovative work behavior. The findings also support the mediating role of LMX between authoritarian and moral leadership and employee voice. Further, LMX and employee voice boosted the indirect relationship between moral leadership and innovative behavior. However, authoritarian leadership demonstrated a significant but negative indirect effect on innovative behavior through LMX and employee voice.

The organizational members need to encourage a high LMX and voice behavior to enhance the positive effects of benevolent and moral leadership styles on innovative employee behaviors. Contrarily, they need to discourage authoritarian leadership if they want to enhance innovative work behavior through LMX and employee voice. Furthermore, when leaders provide a safe environment to employees at the workplace, then they may feel secure to take risks and exhibit innovative work behavior, which ultimately contributes to increasing employee and organizational performance.

This study extended the existing literature on paternalistic leadership in two important ways. First, this study examined a serial mediation mechanism to test the effect of paternalistic leadership on innovative work behavior through LMX and voice behavior. Second, this is a key study to investigate which dimension of paternalistic leadership is effective to boost employees' innovative work behavior at the individual level in the Pakistani organizational context.

The purpose of this paper is to study the aerodynamic characteristics and uplift force tendencies of pantographs within the operational height span of 1,600–2,980 mm, aiming to offer valuable insights for research concerning the adaptability of pantograph-catenary systems on double-stack high container transportation lines.

Eight pantograph models were formulated based on lines with the contact wire of 6,680 mm in height. The aerodynamic calculations were carried out using the SST k-ω separated vortex model. A more improved aerodynamic uplift force method was also presented. The change rule of the aerodynamic uplift force under different working heights of the pantograph was analyzed according to the transfer coefficients of the aerodynamic forces and moments.

The results show that the absolute values of the aerodynamic forces and moments of the upper and lower frame increase with the working height, whereas those of the collector head do not change. The absolute values of the transfer coefficients of the lower frame and link arm were significantly larger than those of the upper frame. Therefore, the absolute value of the aerodynamic uplift force increased and then decreased with the working height. The maximum value occurred at a working height of 2,400 mm.

A new method for calculating the aerodynamic uplift force of pantographs is proposed. The specifical change rule of the aerodynamic uplift force of the pantograph on double-stack high container transportation lines was determined from the perspective of the transfer coefficients of the aerodynamic forces and moments.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

This study aims to examine the cutting performance of a coated carbide tool during the boring of 1Cr17Ni2 martensitic stainless steel, with a focus on how the tool’s structural parameters, particularly the nose radius, affect the wear patterns, wear volume and lifetime of the cutting tool, and related mechanisms.

A full factorial boring experiment with three factors at two levels was conducted to analyze systematically the impact of cutting parameters on the tool wear behavior. The evolution of tool wear over the machining time was recorded, and the influences of the cutting parameters and nose radius on wear behavior of the tool were examined.

The results show that higher cutting parameters lead to significant wear or plastic deformation at the tool nose. When the cutting depth is less than the nose radius, the tool wear tends to be minimized. Larger nose radius tools have weaker chip-breaking but greater strength and wear resistance. Higher cutting parameters reduce wear for the tools with larger nose radius, maintaining their integrity. Wear mechanisms are primarily abrasive, adhesive and diffusion wear. Furthermore, the full-factorial analysis of variance revealed that for the tool with r_ε = 0.4 mm and 0.8 mm, the factors contributing the most to tool wear were cutting speed (38.76%) and cutting depth (86.43%), respectively.

This study is of great significance for selection of cutting tools and cutting parameters for boring 1Cr17Ni2 martensitic stainless-steel parts.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0266/

The purpose of this study is to examine the impact of social media affordances, specifically social engagement and social endorsement, on knowledge contribution in online Q&A communities. Building on self-determination theory, this research seeks to tackle the issue of under-provision of knowledge in these communities.

The study employs a sample collected from a popular social Q&A community in China and uses linear panel data models along with multiple robustness checks to test the research model.

The findings reveal that both social engagement and social endorsement have a positive effect on users' knowledge contribution to the online Q&A community. However, the impact of social engagement is mitigated by social endorsement.

This paper makes a valuable contribution to the field by filling the research gap on the role of social engagement behaviors and their interaction with social endorsement in online Q&A communities. The results provide insights into how social media affordances can be leveraged to enhance knowledge contribution in these communities.

This study aims to investigate the effect of organizational identification to employees’ innovative behavior, the mediating role of work engagement and the moderating role of creative self-efficacy in the relationship between organizational identification and employees’ innovative behavior.

This study adopted questionnaires to gather data. The sample of 289 employees working in diverse organizations in China was applied to examine the hypotheses.

The results indicates that organizational identification is positively related to employees’ innovative behavior and work engagement mediates the relationship between organizational identification and employees’ innovative behavior. In addition, creative self-efficacy enhances the relationship of work engagement and employees’ innovative behavior.

This study builds a system from psychological aspect to behavior, which includes the effect of individual cognition to explain the mechanism of organizational identification on employees’ innovative behavior.

This study aims to focus on the resistance to elevated temperatures of up to 700ºC of high-performance concrete (HPC) compared to ordinary Portland concrete (OPC) with regards to mass loss and residual compressive and flexural strength.

Two mixtures were developed to test. The first mixture, OPC, was used as the control, and the second mixture was HPC. After 28 days under water (per Chinese standard), the samples were tested for compressive strength and residual strength.

The test results showed that at elevated temperatures of up to 500ºC, each mixture experienced mass loss. Below this temperature, the strength and the mass loss did not differ greatly.

When adding a 10 per cent silica fume, 25 per cent fly, 25 per cent slag to HPC, the compressive strength increased by 17 per cent and enhanced the residual compressive strength. A sharp decrease was observed in the residual flexural strength of HPC when compared to OPC after exposure to temperatures of 700ºC.