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This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.

The method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.

The DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.

This study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.

The purpose of this paper is to explore the relationship between leader humility and employee well-being. Based on social information processing (SIP) theory and previous literature concerning leader humility, this paper identifies employee humility as the mediator and suggests that perceived leader effectiveness moderates these relationships.

This study employed a survey involving 228 employees to test the hypothesized moderated-mediation model.

Leader humility is positively related to employee well-being. Employee humility mediates leader humility and employee well-being, except for emotional exhaustion. Moreover, the effect of leader humility on employee humility and the indirect effect of leader humility on employee job satisfaction and work engagement are stronger under high perceptions of leader effectiveness.

Based on the framework of SIP theory, this paper contributes to the literature on humble leadership and employee well-being by treating employee humility as the mechanism and perceived leader effectiveness as the moderator. Few previous studies have investigated the influence of leader humility on employee well-being.

This research clarifies the connotations and dimensions of artificial intelligence (AI) technology stimulation and establishes a stimulus scale to explain the relationship between AI technology stimuli and smart customer experience.

This is an empirical study that uses SPSS 24.0 software to perform hypothesis testing on the path relationships between model elements.

Two dimensions of AI technology stimuli (i.e. passion and usability) have a significant, positive impact on smart customer experience; the moderating effects of contrasting dimensions of technology readiness (i.e. optimism and discomfort) are significantly different; smart customer experience has a significant, positive impact on the word-of-mouth (WOM) intentions of consumers.

There are several limitations. Most importantly, the data collected in this study are only from consumers who use intelligent customer service robots in the catering industry. Future research can consider exploring relevant AI technologies in other sectors.

This study has several implications that guide catering companies to develop various positioning and strategies for remaining competitive effectively.

Based on arousal theory, customer experience theory and WOM marketing theory, this is the first novel research project that empirically discusses the dimensions of AI technology stimuli, smart customer experience and WOM intentions with regard to the moderating effect of the technology readiness of consumers toward AI technology.

Hall (2001a) argues that the value of intangible assets can be inferred from firms’ stock market value and the value of tangible assets, which suggests rational valuation in the market. This paper investigates the relationship between firms’ future stock returns and their inferred intangibles and indirectly tests Hall’s hypothesis by using various trading strategies. It is found that the inferred intangibles have predictive power for stock returns, which might be because of mean‐reverting misvaluation by the stock market; and the way the inferred intangibles predict stock returns is consistent with the three‐factor model of Fama and French (1992). However, I find that the predictive power of inferred intangibles is consistent with market inefficiency, rather than a rational premium for distress risk related to the book‐to‐market equity ratio. Thus the intangible assets hypothesis of Hall does not hold and the discrepancy between market equity and book equity suggests market inefficiency.

This paper seeks to present a wavelet Galerkin boundary element method (WGBEM) for solving 2D Laplace's equation in which the coefficient matrices are exactly computed through fast Fourier transform (FFT).

When Daubechies periodized wavelets are used to approximate smooth functions the wavelet coefficients can be exactly computed through FFT, and numerical evaluation of wavelet integrations is discarded. The same methods for computing the expansion coefficients of 2D function and singular function are derived.

For Daubechies periodized wavelets based WGBEM, two remarkable advantages over the existing WGBEM are: the coefficient matrices can be exactly calculated through FFT; a linear system with potential and flux values at dyadic points as unknowns can be gained. Thus, the mixed boundary condition can be enforced with ease. Sparse matrices with only O(N log N) nonzero entries are obtained by performing the fast wavelet transform (FWT) and the truncation of matrix entries.

A wavelet‐integration‐free method for computing the wavelet coefficients is introduced into the WGBEM. The conventional numerical evaluation of wavelet integrations is avoided. Good performance and accuracy are obtained.

This paper aims to examine the influence of individual and combined effects of the mode focused on scientific and technological-based innovation (STI) and the mode based on learning by doing, by using and by interacting (DUI) on firms’ innovation performance and whether information technology (IT) moderates the relation between different innovation modes and firms’ innovation performance.

A conceptual model linking innovation modes, IT (including IT infrastructure and the frequency of IT usage) and firms’ innovation performance was developed, and the proposed hypotheses were tested empirically using World Bank’s micro survey data collected from manufacturing firms in an emerging market (China).

The results show that individually both STI mode of innovation and DUI mode of innovation have a significant positive effect on firms’ innovative performance, whereas the combined STI and DUI mode of innovation has a negative impact. IT infrastructure moderates the relation between STI (or STI and DUI) mode of innovation and firms’ innovation performance, while the frequency of IT usage has no moderating effects on the relationship between any kind of innovation modes and firms’ innovation performance.

Although some results are quite different from what is expected, these are insightful for both academics and policymakers. The use of cross-sectional data has its limitations. Therefore, future studies based on longitudinal data should be conducted. This study points toward the need to conduct the meta-analysis to better explain the existing inconsistencies in the findings of relevant quantitative studies.

This study provides firm managers with practical implications. The conclusions of this study imply that the impact of the combined STI and DUI mode of innovation is likely to be contextual, so firms should make contingent decisions on whether to engage in STI mode of innovation and DUI mode of innovation simultaneously according to their own organizational conditions. Moreover, face-to-face contacts are particularly important when a firm engages in DUI mode of innovation. In addition, the focus of IT strategy of firms engaged in STI mode of innovation should be on perfecting their IT infrastructure rather than increasing the frequency of IT usage.

This paper provides new evidence for the relation between business innovation modes and firms’ innovation performance, and it is one of the few empirical studies that focus on emerging markets. More importantly, this paper proposes a persuasive explanation framework for understanding the heterogeneous impacts of the combined STI and DUI mode of innovation on firms’ innovation performance. This is the first study that examines the moderating effect of IT on the relationship between business innovation modes and a firm’s innovation performance.

The wood construction industry has been described as slow in adapting efficiency-increasing activities in its operations and supply chain. The industry is still facing challenges related to digitalization, such as fragmentation, poor traceability and lack of real-time information. This study evaluates the status of digitalization in construction supply chains by thematically analyzing the existing literature and mapping research trends.

A review of the key literature from 2016 to 2021 was performed. The results highlight various technologies and their applications within supply chains and identify research gaps, especially between theoretical frameworks and actual implementation using a scientometric-thematic analysis.

This paper provides a conceptual framework to further aid researchers in exploring the current trends in Supply Chain 4.0 and its applications in the wood construction industry compared to other more advanced industries. Suggested directions for future research in the wood construction Supply Chain 4.0 are outlined.

The existing literature still lacks a comprehensive review of the potential of a digitalized supply chain, especially in the construction industry. This framework is pivotal to continue explaining and observing the best ways to accelerate and implement Supply Chain 4.0 practices for digitalized supply chain management (SCM) while focusing specifically on the wood construction industry. The literature review results will help develop a comprehensive framework for future research direction to create a clearer vision of the current state of digitalization in supply chains and focus on the wood construction supply chain, thus, fully achieving the benefits of Supply Chain 4.0 in the wood construction industry.

In the current literature, there is little systematic research on the relationship among adjustment of the income distribution, change in economic structure and improvement of macroeconomic efficiency.

This paper expands Marx's reproduction schema into the “Marx–Sraffa” three-department structure table comprising fixed capital, general means of production and means of consumption and employs China's input–output table from 1987 to 2015 to portray the relationship between income distribution and macroeconomic efficiency under investment-driven growth.

This paper calculates the wage–profit curve of China's economy and evaluates the space of macroeconomic efficiency improvement in China based on the deviation between actual and potential income distribution structure.

The results show that there is a downward trend of the profit rate, which meets Marx's theoretical prediction, and the decline in the profit rate is mainly attributed to an increase in the organic composition of capital arising from the rapid growth of fixed capital investment under extended growth. The analysis of macroeconomic efficiency shows that the space for improving macroeconomic efficiency is extremely limited under traditional growth pattern and that China must transform its economic development pattern and foster new economic growth drivers.

This chapter explores a descriptive theory of multidimensional travel behaviour, estimation of quantitative models and demonstration in an agent-based microsimulation.

A descriptive theory on multidimensional travel behaviour is conceptualised. It theorizes multidimensional knowledge updating, search start/stopping criteria and search/decision heuristics. These components are formulated or empirically modelled and integrated in a unified and coherent approach.

The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network.

Based on artificially intelligent agents, learning and search theory and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based micro-simulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.