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Little empirical research has examined the role of culture on the internal marketing-employee satisfaction (ES) relationship, and even fewer studies focus on this subject in the airline sector. This paper aims to assess whether culture moderates the contribution of internal marketing to the satisfaction of employees from Gulf Cooperation Council (GCC) airlines.

The investigation is conducted via a structured questionnaire with 310 cabin crew members who work at three GCC airlines. Multi-group analysis was used within SmartPLS 3.0 to measure whether the impact of internal marketing on ES is moderated by cultural congruence.

The results reveal the practice of internal marketing contributes to ES in GCC airlines, while cultural congruence moderates the direct relationship between internal marketing and the satisfaction of airlines’ employees. The results indicate that airlines need to satisfy the cultural needs of employees to increase their satisfaction for successful internal marketing practice.

This study contributes towards assessing the moderation effects of cultural congruence on internal marketing practice in the airline sector. It contributes to the current literature on aviation research, as well as specific managerial implications for the airlines and managers to achieve higher competitiveness.

文化一致性是否会影响企业内部营销活动与员工满意度二者之间的关系？目前在这方面的研究还很稀缺, 而聚焦于航空领域的这一主题的研究更是少之又少。本研究以海湾合作委员会的航空公司为例, 旨在分析文化一致性因素能否调节企业内部营销活动对员工满意度的影响力。

本研究对三家海湾合作委员会的航空公司共计310名的空服人员展开了问卷调查。通过运用SmartPLS 3.0 软件的多群组分析方法来具体评估航空公司的内部营销活动对其员工满意度的影响是否会被文化一致性因素所调节。

研究结果显示, 在海湾合作委员会航空公司中, 内部营销活动的实施有助于员工满意度的提升；同时文化一致性因素可以调节航空公司的内部营销活动对其员工满意度的影响。该结果表明, 为了获得成功的内部营销实践, 航空公司需要满足员工的不同文化需求, 以期提高员工的满意度.

本研究聚焦于分析文化一致性对航空公司内部营销实践的调节效应。其不仅是对当前航空研究领域文献的补充, 同时也能够为航空公司及其管理者提供具体的管理方法, 从而获得更多的竞争优势。

el papel de la cultura en la relación de satisfacción de los empleados y el marketing interno ha sido examinada en pocas investigaciones empíricas, e incluso menos estudios se centran en este tema en el sector de las aerolíneas. Este documento tiene como objetivo evaluar si la cultura modera la contribución del marketing interno a la satisfacción de los empleados de las aerolíneas del Consejo de Cooperación del Golfo (CCG).

la investigación se real a través de un cuestionario estructurado con 310 miembros de la tripulación de cabina que trabajan en tres aerolíneas del CCG. El análisis de grupo múltiple se realizó con SmartPLS 3.0 para medir si el impacto del marketing interno en la satisfacción de los empleados es moderado por la congruencia cultural.

los resultados revelan que la práctica del marketing interno contribuye a la satisfacción de los empleados en las aerolíneas del CCG, mientras que la congruencia cultural modera la relación directa entre el marketing interno y la satisfacción de los empleados de las aerolíneas. Los resultados indican que las aerolíneas necesitan satisfacer las necesidades culturales de los empleados para aumentar su satisfacción por los logros del marketing interno.

este estudio contribuye a evaluar los efectos de moderación de la congruencia cultural en la práctica del marketing interno en el sector de las aerolíneas. Contribuye a la literatura actual sobre investigación de aviación, así como indicadores de las consecuencias específicas de gestión de personal para que las aerolíneas y los directivos logren una mayor competitividad.

This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth.

This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth.

The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect.

This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

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.

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.

The biggest obstacle to the sustainable development of online brand communities is social loafing. Based on 3M Hierarchical Model of Personality, this paper aims to discuss the influence of the Big Five on social loafing in online brand communities, and consider the mediating role of dehumanization from the perspective of moral disengagement theory, so as to alleviate social loafing and promote the sustainable development of online brand communities.

The data were collected utilizing the online self-report questionnaires. Community members of mobile phone brands represented by HUAWEI and Xiaomi completed the questionnaire sets. Based on the responses of 214 participants, a structural equation modeling was applied to examine the relationship between Big Five on social loafing in online brand communities. Later, bootstrap analysis was used to further explore the indirect effect of dehumanization.

Only two personality traits, neuroticism and extroversion, have direct effect on social loafing, while agreeableness, conscientiousness and openness not. However, all the Big Five personality traits can indirectly influence social loafing through dehumanization.

This study introduces the concept of social loafing into online brand communities, and analyzes social loafing from the unique research perspective of moral disengagement theory, which can not only contribute to the development of moral disengagement theory and social loafing theory but also provide guiding points for relieving social loafing in online brand communities.

The paper aims to investigate the effects of slurry erosion on hydro turbine components, focusing on the experimental analysis of SS-304 using sand as the erodent material. The study was conducted on a tester under varying parameters to assess the material’s erosion behavior. In this work, the experimental investigation of SS-304 with sand was done with sand as the erodent material on a tester with various parameters. Further, the materials were made more resistant to wear by a WC-10Co-4Cr coating, done by the high-velocity oxygen fuel method. The mass loss of the specimens with and without coating was calculated. SEM was carried out on the specimens. The specimens with coating showed greater erosion resistance than the base material; however, wear mechanisms such as craters, lip formation, pores, etc. were discovered on the specimens.

The wear tests were carried out on the specimens with parameters of rotating speeds of 1,000, 1,150, 1,300 and 1,450 rpm; time duration 80, 130 and 180 min with sand concentrations of 30% and 50% in water. The base material was coated with WC-10Co-4Cr by the HVOF method of thermal spray.

In the results, it was observed that the wear resistance of the coated specimen increased significantly as compared to the uncoated material. Concentration proved to be the major factor influencing the wear erosion followed by rotational speed and time period. Various surface defects such as ploughing, crater formation, lip formation and micro-cutting were also found.

Slurry concentration was found to be the more dominant factor in increasing the wear of the specimens. The tests proved that the coating proved to be highly wear-resistant as compared to the uncoated base material and increased the wear resistance up to 3 times.

This study aims to research the erosion wear characteristics and sealing performance of V-regulating ball valve in coal chemical process pipelines, which provides a theoretical reference for improving its antiwear and sealing performance.

Taking the V-regulating ball valve as the research object, based on the computational fluid dynamics and the theory of erosion wear, the authors studied its erosion characteristics under different medium parameters and analyzed the sealing performance under the heat-fluid–solid coupling working condition.

The erosion wear mechanism of the valve sealing surface is the simultaneous action of cutting and deformation. When the medium flow velocity, particle mass flow rate and particle size increase, the maximum erosion rate and average erosion rate in the V-regulating valve increase. The inner diameter Mises contact stress of the sealing surface is symmetrically distributed in a “wing shape,” and the contact stress of the outer diameter is distributed in a “butterfly shape.” Due to the superposition of thermal stress and pressure stress in the contact transition zone to produce a significant stress concentration.

The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

V-type regulating ball valve is widely favored by coal chemical enterprises and petrochemical enterprises because of its wide adjustment ratio and good erosion resistance.

The V-regulating ball valve wear mechanism for cutting and deformation simultaneously, and its wear rate is positively correlated with the medium flow rate, particle mass flow rate and particle size. After the valve is opened, there is a significant stress concentration occurs in the contact transition zone due to the superposition of thermal stress and compressive stress. The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0205/

This paper focuses on assembly line performance of an automotive body shop that builds body‐in‐white (BIW) assembly utilizing about 700+ process robots. These robots perform various operations such as welding, sealing, part handling, stud welding and inspection. There is no accurate tool available for the plant personnel to predict the future throughput based on plant's data. The purpose of this paper is to provide future throughput performance prediction based on plant data using Box‐Jenkins' ARMA model.

The following data were collected for five major assembly lines. First, the assembly machine‐in‐cycle time: the assembly line machines include robots that perform various functions like load, welding or sealing and unloading parts; the manual operators loading cycle time to the production fixtures. The conveyors act as buffers in between stations, and also feed to the production cells, and carry parts from station to station. The conveyors' downtime and uptime were also part of the machine‐in‐cycle time; second, the number of units produced from the beginning to the end of the assembly line; third, the number of fault occurrences in the assembly line due to various machine breakdowns; fourth, the machine availability percentage – i.e. the machine is readily available to perform its functions (the machine blocked upstream (starving) and blocked down (downstream) state is considered here); fifth, the actual efficiency of the machine measured in percentage based on output percentage; sixth, the expected number of units at designed efficiency.

In summary, this research paper provided a systematic development of a forecast model based on Box‐Jenkin's ARMA methodology to analyze the complex assembly line process performance data. The developed ARMA forecast models proved that the future prediction can be accurately predicted based on the past plant performance data. The developed ARMA forecast models predicted the future throughput performance within 99.52 percent accuracy. The research findings were validated by the actual plant performance data.

In this study, the automotive assembly process machines (robots, conveyors and fixtures) production data were collected, statistically analyzed and verified for viable ARMA model verification. The verified ARMA model has been used to predict the plant future months' throughput with 99.52 percent accuracy, based on the plant production data. This research is unique because of its practical usage to improve production.

Hydro-viscous drive (HVD) clutches are widely used in equipment requiring soft start, such as fans and pumps, to transmit torque and adjust speed by changing the gap distance between friction pairs. This paper aims to propose a novel two-parameter evaluation method for HVD during the mixed lubrication stage. The objective is to develop an effective model that establishes the relationship between these parameters and the actual surface topography.

In the presented methods, the fractal features of the real manufacturing surface are calculated based on the power spectrum function by the ultra-depth three-dimensional microscope. After that, the hybrid friction model of the friction plate is established based on mixed elasto-hydrodynamic lubrication theory, boundary friction model and fractal theory. Then the torque and load bearing characteristics of the clutch are obtained, and the influences of the surface fractal features are investigated and discussed. Finally, the Weierstrass–Mandelbrot function is adopted for the surface topography characterization and evaluation.

The results indicate that the proposed method exhibits good accuracy, while the speed difference between the friction pair exceeds 2,500 rpm. It is concluded that this paper proposed a way to evaluate the torque and loading capacity of HVD considering the real manufacturing surface topography and is helpful for surface optimization.

The originality and value of this study lie in its development of a novel torque and load bearing capacity evaluation method for HVD in mixed lubrication stage, considering manufacturing surface topography and describing the real manufacturing surface.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.