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Branched articulated robots (BARs) are highly non-linear systems; accurate dynamic identification is critical for model-based control in high-speed and heavy-load applications. However, due to some dynamic parameters being redundant, dynamic models are singular, which increases the calculation amount and reduces the robustness of identification. This paper aims to propose a novel methodology for the dynamic analysis and redundant parameters elimination of BARs.

At first, the motion of a rigid body is divided into constraint-dependent and constraint-independent. The redundancy of inertial parameters is analyzed from physical constraints. Then, the redundant parameters are eliminated by mapping posterior links to their antecedents, which can be applied for re-deriving the Newton–Euler formulas. Finally, through parameter transformation, the presented dynamic model is non-singular and available for identification directly.

New formulas for redundant parameters elimination are explicit and computationally efficient. This unifies the redundant parameters elimination of prismatic and revolute joints for BARs, and it is also applicable to other types of joints containing constraints. The proposed approach is conducive to facilitating the modelling phase during the robot identification. Simulation studies are conducted to illustrate the effectiveness of the proposed redundant parameters elimination and non-singular dynamic model determination. Experimental studies are carried out to verify the result of the identification algorithm.

This work proposes to determine and directly identify the non-redundant dynamic model of robots, which can help to reduce the procedure of obtaining the reversible regression matrix for identification.

The high probability of the occurrence of separation bubbles or shocks and early transition to turbulence on surfaces of airfoil makes it very difficult to design high-lift and high-speed Natural-Laminar-Flow (NLF) airfoil for high-altitude long-endurance unmanned air vehicles. To resolve this issue, a framework of uncertainty-based design optimization (UBDO) is developed based on an adjusted polynomial chaos expansion (PCE) method.

The γ ̄Re-θt transition model combined with the shear stress transport k-ω turbulence model is used to predict the laminar-turbulent transition. The particle swarm optimization algorithm and PCE are integrated to search for the optimal NLF airfoil. Using proposed UBDO framework, the aforementioned problem has been regularized to achieve the optimal airfoil with a tradeoff of aerodynamic performances under fully turbulent and free transition conditions. The tradeoff is to make sure its good performance when early transition to turbulence on surfaces of NLF airfoil happens.

The results indicate that UBDO of NLF airfoil considering Mach number and lift coefficient uncertainty under free transition condition shows a significant deterioration when complicated flight conditions lead to early transition to turbulence. Meanwhile, UBDO of NLF airfoil with a tradeoff of performances under both fully turbulent and free transition conditions holds robust and reliable aerodynamic performance under complicated flight conditions.

In this work, the authors build an effective uncertainty-based design framework based on an adjusted PCE method and apply the framework to design two high-performance NLF airfoils. One of the two NLF airfoils considers Mach number and lift coefficient uncertainty under free transition condition, and the other considers uncertainties both under fully turbulent and free transition conditions. The results show that robust design of NLF airfoil should simultaneously consider Mach number, lift coefficient (angle of attack) and transition location uncertainty.

We attempt to analyze the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits.

Retailers' rebates have a chance to affect sales and their profits by encouraging customers to submit product reviews. To investigate the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits, we describe the consumer’s utility function and the number of consumer-written reviews by introducing the concepts of product demand mismatch and consumer review effort, then develop a two-stage model of the retailer’s rebate strategy and examine how the retailer’s rebate affects online reviews, the consumer’s perceived utility and the retailer’s profit. Finally, a number case verifies the validity and rationality of the proposed model.

The results show that the rebate strategy can effectively reduce consumer dissatisfaction caused by excessive product demand mismatch, improve the consumer utility, prompt more positive comments, and thus increase product sales.

In this paper, we focus on the impact of retailers' rebate strategy on consumer purchase decisions. The research can accurately reflect the influence of online reviews on consumers and retailers, assisting merchants in making the best selections. The analysis indicates that the retailer’s rebate strategy can have a direct impact on consumers' evaluation choices and product sales.

The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model.

The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules.

The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers.

The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

The purpose of this paper is to analyze the linear and nonlinear effects of market integration on carbon emissions and explore the direct and indirect paths of market integration on carbon emissions through path analysis.

The authors first conduct a measurement and contrastive study of the market integration and carbon emissions of China’s 28 provinces from year 1995 to 2015. Then, the linear effect of market integration on carbon emissions is analyzed by using the fixed-effect model. Next, based on the path analysis method, the direct and indirect paths of market integration’s impact on carbon emissions are explored. Finally, the panel threshold regression model is used to evaluate the effect of market integration on carbon emissions under different situations of geographic distance.

The results show that first, the improvement of market integration can increase carbon emissions in the form of a linear relationship. Second, market integration not only has a direct and positive impact on the carbon emissions, but also has an indirect and positive impact on carbon emissions through the level of economic development, and a negative impact on carbon emissions through technological level. Third, an increase in market integration can reduce its positive effect on carbon emissions, but the improvement of economic growth and technology level can both enhance the positive effect of market integration on carbon emissions.

This paper focuses on the impact of market integration on carbon emissions in 30 provinces in China, while, the authors do not conduct a comparative analysis of different regions, so there are certain limitations. In addition, policy interaction between regional governments is also a key factor affecting carbon emissions, but this paper does not consider the effect of policy interaction, future follow-up research will try to incorporate it into the analytical models.

An important practical implication of this research is that market integration should be regarded highly in China’s energy conservation and emission reduction efforts. The research results have important reference value for policy authorities to formulate relevant policies. That is, the government can play a more active role in the process of integration through breaking the regional blockade and interest barriers to comprehensively improve resource utilization efficiency and technical level, and ultimately achieve regional low-carbon development.

This paper explores the effects of market integration on China’s carbon emissions based on different methods and perspectives, and confirms that market integration plays a vital role in China’s carbon emissions through economic growth and technological progress. Notably, based on the studied results, some specific and practical suggestions are proposed in this paper so as to reduce carbon emission and realize the sustainable development of economy and society in China.

Building on the social capital theory of career success (SCT), this paper aims to explore how and when newcomers’ overqualifications can grant them positions as informal leaders within the workgroup over time.

The model was tested using a social relations modeling analysis conducted using a three-wave survey with 242 newcomers in Macau.

The results support the view that relatively qualified newcomers can enjoy social capital advantages in workgroup networks. Newcomers’ desired qualifications can grant them positions as informal leaders through leader–member exchange and advice network centrality. These relationships are moderated by relational dissimilarity, such that the benefits of being relatively overqualified will be weakened when relational dissimilarity is high (vs. low).

When assisting overqualified newcomers in integrating into their teams, practitioners shall be aware of the time and resources that new hires require for adjustment, especially when significant newcomer–veteran relational dissimilarity exists.

The present paper challenges the overtly detrimental outcomes of overqualification by highlighting the positive relational implications of being relatively overqualified.

Managers in China prioritize the cultivation of loyal employees, resulting in positive effects associated with leader-member exchange (LMX). However, fragmented evidence suggests that LMX also can trigger deviant behavior. LMX provides employees with access to resources, while it also harbors potential risks for deviant behaviors. Based on the cognitive-affective system theory of personality and resource-related theories, this study aims to explore the double-edged sword effects of LMX by examining how LMX influences interpersonal deviant behaviors through emotional and cognitive pathways, respectively.

This study involved three waves of paired data surveys that were conducted in China over one month, and a total of 117 leaders and 235 subordinates participated in this study.

Even though LMX as a job resource reduces workplace anxiety, LMX also generates work overload for employees. Workplace anxiety and work overload further result in interpersonal deviant behavior. Narcissistic admiration, as a personality trait, can weaken the mediating role of work overload but not that of workplace anxiety.

The finding can help managers pay attention to negative effect of LMX and provide suggestions for preventing employees’ workplace deviant behavior.

The findings revealed how LMX leads to negative outcomes in the workplace. In addition, the results demonstrated the buffering effect of narcissistic admiration on the negative effect of LMX.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

Customer misbehavior has a negative impact on frontline employees. However, the underlying mechanisms from customer misbehavior to employees’ negative outcomes need to be further unfolded and examined. This study aims to propose that employees’ affective rumination and problem-solving pondering could be the explanatory processes of customer misbehavior influencing employee attitudes in which coworker support could be a moderator.

A mixed-method approach was designed to test this study’s predictions. Study 1 conducted a scenario-based experiment among 215 full-time hospitality employees, and Study 2 used a two-wave, longitudinal survey of 305 participants.

The results demonstrate the impact of customer misbehavior on work–family conflict and withdrawal behaviors. The mediating role of affective rumination is supported and coworker support moderates the processes.

Customer misbehavior leads to negative outcomes among frontline employees both at work and family domains. Hotel managers should help frontline employees to cope with customer misbehavior by avoiding negative affective spillover and providing support properly.

The studies have unfolded the processes of affective rumination and problem-solving pondering through which customer misbehavior influences work–family conflict and withdrawal behaviors among frontline employees. The surprising findings that coworker support magnified the negative effects have also been discussed.