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The purpose of this paper is to develop the linguistic q-rung orthopair fuzzy set (LqROFS) information VIKOR method based on the bi-direction Choquet integral (BDCI), taking into account the correlation between information. The method can enrich the existing studies related to LqROFS information and better solve the problem of MAGDM problem.

Since applying Choquet integral (CI) depict information interaction is a common operation in MAGDM. However, the traditional CI has some limitations. The unidirectional alignment may affect the MAGDM results. Therefore, a LqROFS-VIKOR method based on BDCI is proposed, where BDCI is used to aggregate the decision matrix. Furthermore, it is not reasonable to apply exact numbers to express the similarity between two qualitative data. Then a new method of defining similarity using linguistics is proposed. The similarity is used to calculate attribute weights.

The validity and potential application of MAGMD method with linguistic q-rung orthopair fuzzy information based on BDCI are demonstrated in a numerical examples study.

According to the study of available literature, the current research on LqROFS is incomplete. The existing studies of both similarity and aggregate operators have certain shortcomings. The definition of similarity proposed in this paper is more in line with reality. And compared with the existing methods, the BDCI-based aggregate operator can describe the interaction between information more reasonably. Based on this VIKOR method based on BDCI under the LqROFS environment can better select the alternative.

An exploratory model of competence and performance is presented and tested in the study. Competence in marketing, product innovation, manufacturing, and human resource development across a list of 42 items have been analyzed. Marketing competence was ranked high by Chinese managers. Elements contributed to manufacturing competence regarding process reengineering have not been emphasized as much by Chinese managers. Human resource competence, on the other hand, has been found to be significantly correlated with performance. The results clearly show a trend moving from the state‐planned economy to the market economy.

The stimulus for this research is that as US hospitals and health care organizations become more competitive, wise investments in technology and quality improvement are keys to financial success and survival. A structural equation model is hypothesized using the following five constructs: clinical technology; information technology; clinical quality; process quality; and hospital financial performance. No research to date has examined the relationships between the type of technology, the type of quality, and hospital financial performance. The general research hypothesis tested is that hospital technology directly drives (affects) quality and hospital financial performance. The results indicate that the type of hospital technology (clinical or information) drives different types of quality‐related performance (clinical or process), and directly and indirectly affects hospital financial performance. The simple recursive model documented here is an important first step to defining more complete models that accurately predict hospital financial performance as a function of technology and quality investments and initiatives. The article concludes by summarizing results, discussing their implications, and proposing future research ideas.

This study has empirically tested the relationships between business environment, manufacturing capability and performance using a sample of Chinese manufacturers. The results of this research show that in response to the changing economy, the Chinese manufacturers have emphasized the capabilities that have been adopted by many firms in the industrialized nations. The results also suggest that the business environment has a substantial impact on the choice of manufacturing capability focus. Additionally, we have found that high performance Chinese manufacturers adopt different competitive priorities in response to environmental stimuli than do low performance Chinese manufacturers.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

This research aims to investigate the influence of consumers' anticipated trust in service providers on brand switching intention and its underlying psychological mechanism. More importantly, this study explores the moderating role of type of service providers (human staff/humanoid robots/nonhumanoid robots).

This study adopted two single-factor between-subjects experimental designs and tested the hypotheses in two typical service failure scenarios: Study 1, a hotel scenario (N = 403); and Study 2, a restaurant scenario (N = 323).

The results suggest that there is an inverted U-shaped relationship between consumers' anticipated trust and tolerance of service failure and that such tolerance has a mediating effect on the relationship between anticipated trust and brand switching intention. Moreover, when service failure is caused by a humanoid service robot, a moderate anticipated trust level of consumers is most conducive to increasing tolerance, which in turn reduces their propensity to switch brands.

This study examines the nature of the relationship between anticipated trust and tolerance in a service failure context, revealing an inverted U-shaped relationship. More importantly, the boundary conditions under which different service provides have an influence on this relationship are incorporated. Finally, this study explores the influence of service failure tolerance on brand switching intentions in a technological context, enriching consumer–brand relationship research.

This study aims to investigate the effects of different surface-to-jet velocity ratios (Rsj) on the flow structure and the heat transfer of the floatation nozzle under different ratios (h/w) of the separation distance (h) to the slot width (w) and the differences of the flow structure and the heat transfer between the floatation nozzle and the slot nozzle.

The Nusselt number (Nu) and the pressure distribution of the floatation nozzle with a stationary wall are measured. Then the experimental results are used to validate the numerical model. Finally, a series of numerical simulations is carried out to achieve the purpose of this study.

The flow structure and heat transfer differences between the floatation nozzle and the slot nozzle are clarified. The floatation nozzle has more than 18 times the floatation ability of the unconfined slot nozzle. The Nu and pressure distributions of the floatation nozzle are experimentally measured. The effects of wall motion on the Nu and pressure distributions are identified.

The effects of the wall motion on the flow structure and the heat transfer of the floatation nozzle, and the differences between the floatation nozzle and the slot nozzle are first obtained. Therefore, it is valuable for engineers in engineering design of the floatation nozzle.

As the last link of product remanufacturing, reassembly process is of great importance in increasing the utilization of remanufactured parts as well as decreasing the production cost for remanufacturing enterprises. It is a common problem that a large amount of remanufactured part/reused part which past the dimension standard have been scrapped, which have increased the production cost of remanufacturing enterprises to a large extent. With the aim to improve the utilization of remanufacturing parts with qualified quality attributes but exceed dimension, the purpose of this paper is to put forward a reassembly classification selection method based on the Markov Chain.

To begin with, a classification standard of reassembly parts is proposed. With the thinking of traditional ABC analysis, a classification management method of reassembly parts for remanufactured engine is proposed. Then, a homogeneous Markov Chain of reassembly process is built after grading the matching dimension of reassembly parts with different variety. And the reassembly parts selection model is constructed based on the Markov Chain. Besides, the reassembly classification selection model and its flow chart are proposed by combining the researches above. Finally, the assembly process of remanufactured crankshaft is adopted as a representative example for illustrating the feasibility and the effectiveness of the method proposed.

The reassembly classification selection method based on the Markov Chain is an effective method in improving the utilization of remanufacturing parts/reused parts. The average utilization of remanufactured crankcase has increased from 35.7 to 80.1 per cent and the average utilization of reused crankcase has increased from 4.2 to 14 per cent as shown in the representative example.

The reassembly classification selection method based on the Markov Chain is of great importance in enhancing the economic benefit for remanufacturing enterprises by improving the utilization of remanufactured parts/reused parts.

Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.

This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.

The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

Compared with the high stiffness of traditional CNC machine tools, the structural stiffness of industrial robots is usually less than 1 N/µm. Chatter not only affects the quality of robotic milling but also reduces the accuracy of the milling process. The purpose of this paper is to reduce chatter in the robotic machining process.

First, the mode coupling chatter mechanism is analyzed. Then the milling force model and the principal stiffness model are established. Finally, the robot milling stability optimization method is proposed. The method considered functional redundancies, and a new robot milling stability index is proposed to improve the quality of milling operations.

The experimental results prove a significant reduction in force fluctuations and surface roughness after using the proposed robotic milling stability optimization method.

In this paper, a new robot milling stability index and a new robot milling stability optimization method are proposed. This method can significantly increase the milling stability and improve the milling quality, which can be widely used in the industry.