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This study investigates how organizational control systems induce emotional labor in frontline service employees (FLEs). Drawing on the stimulus–organism–response (S-O-R) theory, we hypothesized that two control systems, an outcome-based control system (OBCS) and a behavior-based control system (BBCS), trigger work engagement rather than organizational dehumanization in FLEs, leading them to choose deep acting rather than surface acting as an emotional labor strategy.

This study employed three-wave online surveys conducted 3–4 months apart to assess the time-lagged effects of S-O-R. We measured OBCS, BBCS (stimuli) and control variables at Time 1 (T1); work engagement and organizational dehumanization (organisms) at Time 2 (T2) and emotional labor strategies (responses) at Time 3 (T3). A total of 218 employees completed the T1, T2 and T3 surveys.

OBCS increased work engagement, leading to increased deep acting. BBCS enhanced organizational dehumanization, leading to increased surface acting. Post-hoc analysis confirmed that the indirect effect of OBCS on deep acting through work engagement and the mediation effect of BBCS on surface acting through organizational dehumanization were statistically significant.

This study collected three-wave data to reveal how organizational control systems affect FLEs’ emotional labor in the S-O-R framework. It illustrated how organizations induce FLEs to perform effective emotional strategies by investigating the effects of organizational control systems on their internal states.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.

The present study aims to investigate the impact of internal control effectiveness on supply chain management efficiency (SCME) and capital allocation efficiency for companies listed in the Tehran Stock Exchange (TSE). In addition, it investigates the mediating role of supply chain management efficiency in the relationship between internal controls and capital allocation efficiency.

The data about 191 companies in 2014–2022 were examined. The sales per inventory ratio was used to calculate SCME. The present study also applied the Generalized Method of Moments (GMM) for endogeneity concerns.

The results showed that internal control effectiveness has a significant positive effect on SCME. Moreover, internal control effectiveness and SCME significantly positively affect capital allocation efficiency. SCME has a mediating role in the relationship between internal control effectiveness and capital allocation efficiency. These findings remained robust even after several robustness tests. In addition, this study tested the results' robustness by dividing data into the pre-COVID-19 and post-COVID-19 years. The previous results were also confirmed according to the robustness test of COVID-19.

Challenges in the supply chain often hinder capital allocation efficiency. In addition, enterprises should try to establish strong internal controls to ensure SCME. Therefore, the relationship between internal control effectiveness, SCME and capital allocation efficiency is complex and underscores the importance of robust internal controls in optimizing resource allocation within organizations. Interestingly, this topic has not been extensively researched in accounting and business research, and there is a lack of empirical evidence on these effects. Consequently, this study aims to fill the gap and identify potential opportunities for new research directions.

There are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study aims to eliminate uncertainties and improve the foot trajectory tracking control performance of hydraulic legged robots, a high-performance foot trajectory tracking control method based on fixed-time disturbance observers for hydraulic legged robots is proposed.

First, the robot leg mechanical system model and hydraulic system model of the hydraulic legged robot are established. Subsequently, two fixed-time disturbance observers are designed to address the unmatched lumped uncertainty and match lumped uncertainty in the system. Finally, the lumped uncertainties are compensated in the controller design, and the designed motion controller also achieves fixed-time stability.

Through simulation and experiments, it can be found that the proposed tracking control method based on fixed-time observers has better tracking control performance. The effectiveness and superiority of the proposed method have been verified.

Both the disturbance observers and the controller achieve fixed-time stability, effectively improving the performance of foot trajectory tracking control for hydraulic legged robots.

The purpose of the present study is to test the effect of financial development and environmental degradation on the control of corruption.

This study used a dynamic approach known as system GMM to analyze annual data from 90 developed and developing countries over 24 years, from 1996 to 2020.

The present study shows a significantly negative relationship between financial development and control of corruption and a significantly positive relationship between environmental degradation and control of corruption. The result suggests that improvement in financial development may reduce control of corruption; however, reduction in environmental degradation may reduce control of corruption. The results are consistent across both developed and developing countries.

The study’s findings have significant implications for financial institutions, governmental policy departments and environmental regulatory agencies. The policy outcomes are closely linked to the economic prosperity of countries. In general, developing countries can implement strategies to promote financial development and environmental regulations, even though they may temporarily tolerate corrupt activities. Conversely, developed nations may have differing implications from developing countries.

This study is different from the past literature as none of the studies have been conducted previously focusing on developed and developing countries’ financial development, environmental degradation and control of corruption.

Academic procrastination, characterized by the act of postponing the completion of an assignment, is a prevalent behaviour observed among students worldwide and has significant consequences for academic achievement. This study investigates the influence of academic procrastination on academic achievement in university students. This study also determines the mediating effect of locus of control and the moderating effect of parental involvement on the relationship between academic procrastination and academic achievement.

This work utilized a cross-sectional and causal research design. The study used a survey in English to obtain responses from university students within the Northern Indian Region. The study received 539 responses from participants and 507 were used after data cleaning. This study used structural equation modelling using AMOS 25.0 for hypothesis testing.

The regression analysis using structural equation modelling showed that the external locus of control leads to academic procrastination, whereas the internal locus of control negatively affects academic procrastination. In addition, academic procrastination negatively influences academic achievement, emphasizing procrastination’s adverse effects on students’ performance. Moreover, academic procrastination mediates and parental involvement moderates the association between locus of control and academic achievement.

The present study investigated a unique conceptual framework involving locus of control, parental involvement, academic procrastination and academic accomplishment. The study makes an essential contribution to educational psychology and also enhances earlier theoretical frameworks concerning antecedents of academic accomplishments in university students.

This study proposes a framework that demonstrates how the perceived value of augmented reality (AR) shopping influences the formation of psychological ownership of product and technology. The mediating role of flow experience and the moderating role of perceived control are identified.

An online survey study recruiting 480 participants who experienced AR shopping was conducted to test the hypotheses.

Functional value is negatively related to psychological ownership of product and technology whereas emotional value shows opposite effects. Flow experience mediates the relationships between functional/emotional value and psychological ownership of product and technology. Perceived control moderates the relationship between emotional value and flow experience, as well as the relationship between functional/emotional value and psychological ownership of product and technology.

The findings suggest the importance of AR’s functional and emotional values in developing psychological ownership of product and technology. To mitigate the negative effect of functional value, AR designers should focus on creating emotionally engaging apps that induce a flow experience, thereby enhancing psychological ownership. Furthermore, AR apps should be designed to empower users with a sense of control in the AR experience.

This research contributes to the AR and psychological ownership literature. It introduces a model that can explain both the formation of psychological ownership of product and psychological ownership of technology, thereby expanding the current understanding. By adding perceived values as antecedents of psychological ownership, it enriches the psychological ownership literature. Moreover, it enhances the flow experience literature by demonstrating the role of flow experience in the formation of psychological ownership of product and technology.

The study explores the relationship between self-control and various online promotional methods faced by consumers simultaneously, simulating how consumers with distinct levels of self-control act in the current Chinese Internet market.

The sample was collected from response of participants to the survey containing a self-control test and attitudes towards different promotional methods. This is a quantitative study using regression and analysis of variance (ANOVA).

Initially, the empirical study focuses on discount margin for both price-discounts and full-discounts, which implies that high discount margin has a negative impact on the quality perception of consumers. However, this impact is weakened under full-discounts. Subsequently, the study identifies that the negative influence of high discounts on quality perception is insignificant for the high self-control group facing various promotional activities simultaneously. Furthermore, it is found that consumers with a high level of self-control rely more on their quality perception rather than the discount margin of products.

The study covers self-control of consumers, a variety of promotional methods and simulation of the present Chinese online market, enriching the research topic of consumer behavior as well as Internet marketing.

Loitering aerial vehicle (LAV) swarm safety flight control is an unmanned system control problem under multiple constraints, which are derived to prevent the LAVs from suffering risks inside and outside the swarms. The computational complexity of the safety flight control problem grows as the number of LAVs and of the constraints increases. Besides some important constraints, the swarms will encounter with sudden appearing risks in a hostile environment. The purpose of this study is to design a safety flight control algorithm for LAV swarm, which can timely respond to sudden appearing risks and reduce the computational burden.

To address the problem, this paper proposes a distributed safety flight control algorithm that includes a trajectory planning stage using kinodynamic rapidly exploring random trees (KRRT*) and a tracking stage based on distributed model predictive control (DMPC).

The proposed algorithm reduces the computational burden of the safety flight control problem and can fast find optimal flight trajectories for the LAVs in a swarm even there are multi-constraints and sudden appearing risks.

The proposed algorithm did not handle the constraints synchronously, but first uses the KRRT* to handle some constraints, and then uses the DMPC to deal with the rest constraints. In addition, the proposed algorithm can effectively respond to sudden appearing risks by online re-plan the trajectories of LAVs within the swarm.

This paper aims to deal with the force and position tracking problem when a robot performs a task in interaction with an unknown environment and presents a hybrid control strategy based on variable admittance control and fixed-time control.

A hybrid control strategy based on variable admittance control and fixed-time control is presented. Firstly, a variable stiffness admittance model control based on proportional integral and differential (PID) is adopted to maintain the expected force value during the task execution. Secondly, a fixed-time controller based on radial basis function neural network (RBFNN) is introduced to handle the model uncertainties and ensure the fast position tracking convergence of the robot system, while the singularity problem is also avoided by designing the virtual control variable with piecewise function.

Simulation studies conducted on the robot manipulator with two degrees of freedom have verified the superior performance of the proposed control strategy comparing with other methods.

A hybrid control scheme for robot–environment interaction is presented, in which the variable stiffness admittance method is adopted to adjust the interaction force to the desired value, and the RBFNN-based fixed-time position controller without singularity problem is designed to ensure the fast convergence of the robot system with model uncertainty.