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Based on social information processing theory, this paper aims to explore how and when leader self-deprecating humor may spark subordinate learning from failure. The authors cast perspective taking as a novel explanatory mechanism for this indirect effect, and further consider leader–member exchange as a boundary condition of the relationship.

The authors tested the hypotheses by conducting a multiwave and multisource survey of 604 members from 152 teams in a Chinese high-technology company.

Results of multilevel path analyses demonstrate that leader self-deprecating humor positively influences subordinate learning from failure via perspective taking. Further, this mediation effect is stronger at higher levels of leader–member exchange.

This study contributes to the theoretical understanding of the relationship between leader self-deprecating humor and subordinate learning from failure. However, the research design was not longitudinal or experimental, and thus the authors were unable to make strong inferences about absolute causality.

The work yields useful insights for practitioners aiming to encourage subordinates to learn from failure.

This study provides evidence that leader self-deprecating humor can stimulate subordinate learning from failure via perspective taking, and the indirect effect is further strengthened by leader–member exchange. The findings offer new directions for research on leader self-deprecating humor and learning from failure.

The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.

In this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.

The numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.

The paper provides a useful reference for further theoretical research and engineering application.

This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material.

The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time.

Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX.

A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

The purpose of this study is to propose an innovative methodology in solving the lean production design from semiconductor crystal-ingot pulling manufacturing which is an important industry. Due to the complexity of the system, it is computationally prohibited by an analytical approach; thus, simulation optimization is adopted for this study.

Four control factors that affect the system’s performance, including the pulling strategy, machine limitations, dispatching rules and batch-size control, are identified to generate the future-state value stream mapping. Taguchi two-step procedure and simulation optimization are used to determine the optimal parameter values for a robust system.

The proposed methodology improved the system performances by 6.42 and 12.02 per cent for service level and throughput, respectively.

This study does not investigate operations management issues such as setup reduction, demand forecasting and layout design.

A real-world crystal-ingot pulling manufacturing factory was used for the case study. The results are promising and are readily applied to other industrial applications.

The improved performances, service level and throughout rate, can result in an improved customer satisfaction level and a reduced resources consumption, respectively.

The proposed methodology innovatively solved a practical application and the results are promising.

Bedroom Feng Shui practices have been criticized as myth over the years but in fact having its scientific origin that is not purely superstitious. This paper aims to examine whether the architects' design practice for bedroom interior arrangement is concurring with the recommended bedroom Feng Shui practices. The study has successfully interviewed 16 architects from diverse backgrounds to avoid bias, seeking their design perspectives in bedroom interior configuration. Subsequently, the interviewees submitted sketches of ideal bedroom layout based on their expertise, with pre-set requirements. Data from semi-structured interviews were analyzed using mixed method approach. In agreement with our expectations, majority of the interviewees have matching thoughts that “bed arrangement” is the primary consideration in bedroom interior configuration. Most of the design outputs were highly attached to favorable Feng Shui conditions. The overall findings implied that bedroom Feng Shui is not merely superstitious but most components are practical design references for architects from diverse backgrounds.

Introduction: Decision making is always based on several factors which may affect the possible outcomes, especially in financial markets. Instead of having many criteria which may be required for decision making, “Multiple Criteria Decision Making” (MCDM) models might be used as a tool to reduce all criteria into a single one.

Purpose: The aim of this study is to measure the financial performance of commercial banks listed on Borsa Istanbul (BIST) by the MCDM.

Method: To this end, data from 15 different financial ratios from 11 commercial banks were used between the periods of 2002 and 2018. Both TOPSIS and gray relational analysis (GRA) models were used, which are commonly used in the literature for detecting the financial performance of listed banks in BIST based on their consolidated financial statements.

Results: According to the TOPSIS method, while the best bank is QNB Finansbank, HALKB, a public bank, was determined as the best bank using the GRA method. There is no significant correlation between financial performance indicators and market returns obtained by either method, with exceptions. There is no generally significant correlation detected between financial ratios and market returns. Accordingly, it is concluded that the bank stock prices in the study are shaped by the influence of external factors and expectations. The study results include information that can be used for different purposes among bank managers, academics and financial investors.

Modeling and analysis of dimensional variation propagation is a crucial support technology for variation reduction, product/process design evaluation and recognition of variation source. However, owing to the multi-deviation (i.e. part deviations and fixture deviations) and multi-interaction (i.e. part-to-part interaction, part-to-fixture interaction and station-to-station interaction) in assembly processes, it is difficult for designers to describe or understand the variation propagation (or accumulation) mechanism clearly. The purpose of this paper is to propose a variation propagation modeling and analysis (VPMA) method based on multiple constraints aiming at a single station.

Initially, part-to-part constraints (PPCs) and part-to-fixture constraints (PFCs) are applied for the multi-interaction of assembly, and multiple constraints graph (MCG) model is proposed for expressing PPCs, PFCs, parts, as well as the variation propagation relation among them. Then, locating points (LPs) are adopted for representing the deviations in constraints, and formulas for calculating the deviations of LPs are derived. On that basis, a linearized relation between LPs’ deviations and part’s locating deviations is derived. Finally, a wing box is presented to validate the proposed method, and the results indicate the methodology’s feasibility.

MCG is an effective tool for dimensional VPMA, which is shown as an example of this paper.

Functions of geometric constraints in dimensional variation propagation are revealed, and MCG is proposed to formulize dimensional variation propagation.

Establishing a performance‐oriented evaluation in public sectors is the key to successful administrations. However, because of lacking relative comparable measuring standards, it is difficult to measure the relative performance of one unit while comparing to other units with regard to the multiple criteria decision making (MCDM) of performance evaluation. This paper aims to focus on the performance ranking of research and development (R&D) projects in Taiwan's public sectors.

The algorithm in this paper is based on the concept of fuzzy set theory and the hierarchical structure analysis. The analyzing method adopts the methods of standard normal distribution, linear transformation, and fuzzy MCDM, carrying on the analysis of multiple criteria of the performance evaluation.

This paper constructs linguistic values to the subjective judgments and analyzes the ranking results of the performance evaluation with respect to 45 R&D projects of one of Taiwan's electric power companies. Thus, the paper demonstrates a successful way of evaluating R&D projects in the public sector.

In this paper, a decision algorithm based on the fuzzy set theory is proposed to solve the performance evaluation of R&D projects in public sectors. In order to solve the difficulties of measuring one unit of the relative performance of quantitative criteria comparing to the other units, the method of standard normal distribution is adopted while measuring the quantitative criteria. The concept of linguistic values and fuzzy numbers are used in this paper since they could easily be used to describe the subjective measurement of the appropriateness of alternatives and the importance weightings of criteria.

The purpose of this paper is to examine the relationship among job training satisfaction (JTS), job satisfaction (JS) and turnover intention (TI) and moreover, the role of JS in the relationship between the JTS and TI.

A survey was used in this study for a sample size of 115. The principal component analysis was carried out to examine the factors in JTS and JS. The regression and mediation analyses were applied to assess the relationship among the JTS, JS and TI.

A significantly negative relationship between JTS and TI was found and mediated by JS. The paper also suggests that JS is positively related to JTS but is negatively related to TI, which is in accordance with what have been reported in the earlier studies.

This study reinforced the significance of job training in human resource management practices. The employees’ satisfaction with job training that would lead to higher JS and lower TIs was emphasized. Therefore, it becomes important for HRD professionals to consider both the delivery of the training to the employees and the employees’ satisfaction with the training approach when designing the training program.

While many different variables have been studied in the relationship with TI, the JTS is rarely discussed. This paper attempts to examine the relationship among JTS, JS and TI with addition of new insights.