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Utilizing the extended transportation-imagery model, this study categorizes three storytelling elements into six distinct factors – character types, influencer-character congruence, imaginable titles, concrete details, replication difficulty and artistic processing – to explore how these factors enhance influencer engagement.

This study utilized a quantitative research design, analyzing 1,660 influencer-created videos over a six-month period. Narrative elements were examined through manual coding, and their impact on live comments was assessed using negative binomial regression to identify key factors driving audience engagement.

Research results show that non-fictional characters, imaginable titles and concrete details significantly increased live comments. Conversely, high replication difficulty negatively influenced engagement. Notably, influencer-character congruence and artistic processing showed no significant effect.

This study advances the extended transportation-imagery model by integrating narrative elements with live comments, offering new perspectives on real-time audience engagement. The findings deepen our understanding of how storytelling techniques enhance the effectiveness of influencer marketing. From a managerial standpoint, this research provides strategic insights for influencers and brands to refine their content strategies, ultimately boosting audience engagement.

The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).

The authors present a detailed explanation for modeling the general discrete nonlinear dynamic system by the MTN. The weight coefficients of the network can be obtained by sampling data learning. Specifically, the least square (LS) method is adopted herein due to its desirable real-time performance and robustness.

Compared with the existing mainstream nonlinear time series analysis methods, the least square method-based multidimensional Taylor network (LSMTN) features its more desirable prediction accuracy and real-time performance. Model metric results confirm the satisfaction of modeling and identification for the generalized nonlinear system. In addition, the MTN is of simpler structure and lower computational complexity than neural networks.

Once models of general nonlinear dynamical systems are formulated based on MTNs and their weight coefficients are identified using the data from the systems of ecosystems, society, organizations, businesses or human behavior, the forecasting, optimizing and controlling of the systems can be further studied by means of the MTN analytical models.

MTNs can be used as controllers, identifiers, filters, predictors, compensators and equation solvers (solving nonlinear differential equations or approximating nonlinear functions) of the systems of ecosystems, society, organizations, businesses or human behavior.

The operating efficiency and benefits of social systems can be prominently enhanced, and their operating costs can be significantly reduced.

Nonlinear systems are typically impacted by a variety of factors, which makes it a challenge to build correct mathematical models for various tasks. As a result, existing modeling approaches necessitate a large number of limitations as preconditions, severely limiting their applicability. The proposed MTN methodology is believed to contribute much to the data-based modeling and identification of the general nonlinear dynamical system with no need for its prior knowledge.

This paper aims to present a control strategy that eliminates the longitudinal and lateral drifting movements of the coaxial ducted fan unmanned helicopter (UH) during autonomous take-off and landing and reduce the coupling characteristics between channels of the coaxial UH for its special model structure.

Unidirectional auxiliary surfaces (UAS) for terminal sliding mode controller (TSMC) are designed for the flight control system of the coaxial UH, and a hierarchical flight control strategy is proposed to improve the decoupling ability of the coaxial UH.

It is demonstrated that the proposed height control strategy can solve the longitudinal and lateral movements during autonomous take-off and landing phase. The proposed hierarchical controller can decouple vertical and heading coupling problem which exists in coaxial UH. Furthermore, the confronted UAS-TSMC method can guarantee finite-time convergence and meet the quick flight trim requirements during take-off and landing.

The designed flight control strategy has not implemented in real flight test yet, as all the tests are conducted in the numerical simulation and simulation with a hardware-in-the-loop (HIL) platform.

The designed flight control strategy can solve the common problem of coupling characteristics between channels for coaxial UH, and it has important theoretical basis and reference value for engineering application; the control strategy can meet the demands of engineering practice.

In consideration of the TSMC approach, which can increase the convergence speed of the system state effectively, and the high level of response speed requirements to UH flight trim, the UAS-TSMC method is first applied to the coaxial ducted fan UH flight control. The proposed control strategy is implemented on the UH flight control system, and the HIL simulation clearly demonstrates that a much better performance could be achieved.

The paper aims to study the relationship between executives’ perceptions of environmental threats and innovation strategies and investigate the moderating effect of contextual factor (i.e. organizational slack) on such relations. It proposes a dualistic relationship between executives’ perceptions of environmental threats and innovation strategies, in which different perceptions of environmental threats will lead to corresponding innovation strategies, and dyadic organizational slack can promote such processes.

The paper is based on a survey with 163 valid questionnaires, which were all completed by executives. Hierarchical ordinary least-squares regression analysis is used to test the hypotheses proposed in this paper.

The paper provides empirical insights about that executives tend to choose exploratory innovation when they perceive environmental changes as likely loss threats, yet adopt exploitative innovation when perceiving control-reducing threats. Furthermore, unabsorbed slack (e.g. financial redundancy) positively moderates both relationships, while absorbed slack (e.g. operational redundancy) merely positively influences the relationship between the perception of control-reducing threats and exploitative innovation.

The paper bridges the gap between organizational innovation and cognitive theory by proposing a dualistic relationship between executives’ perceptions of environmental threats and innovation strategies. The paper further enriches innovation studies by jointly considering both subjective and objective influence factors of innovation and argues that organizational slack can moderate such dualistic relationship.

The purpose of this paper is to accurately capture the risks which are caused by each road user in time.

The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.

The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.

This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

This paper aims to explore the influence of applied pressure on the tribological properties of the friction component in a wet multi-disc clutch during the running-in process.

The running-in evolutionary was explored in terms of global friction performance. The variation of friction torque and mean COF of the initial 300 engagement cycles was obtained by full-scale tests. Finally, an optical microscope was used to detect the wear characteristics of friction surfaces.

The applied pressure showed a significant influence on the tribological behaviors of wet clutches during the running-in process. The mean COF decreased and then increases with the increase of the applied pressure. A higher applied pressure contributed to more asperity summits being sheared, thus resulting in a smoother surface. Considering a suitable wore performance, properly applied pressure is necessary.

The results provide theoretical guidance for selecting the optimal applied pressure in the running-in of wet clutches.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2022-0256/

This paper aims to explore the effect of automatic transmission fluid (ATF) temperature on the dynamic friction-wear properties of the friction component in a wet multi-disc clutch during the running-in process.

The running-in evolution was explored in terms of global friction performance and instantaneous friction characteristics. The variation of friction torque of the initial 300 engagement cycles was obtained by wet-clutch tests. Finally, an optical microscope was used to detect the wear mechanism of friction surfaces.

The ATF temperature showed a significant effect on the friction-wear performance in the clutch running-in process. The mean coefficient of friction decreased with the increase of the ATF temperature and decreased rapidly in the approximately initial 60 clutch engagements. The higher the ATF temperature was, the thinner the ATF film was, and more asperity summits were cut, thus leading to a smoother surface. Considering the slightly instantaneous friction fluctuation and the wear performance, a proper ATF temperature is necessary.

The results provide theoretical guidance for selecting the optimal ATF temperature during the running-in process.