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This paper aims to propose two parallel two-step finite element algorithms based on fully overlapping domain decomposition for solving the 2D/3D time-dependent natural convection problem.

The first-order implicit Euler formula and second-order Crank–Nicolson formula are used to time discretization respectively. Each processor of the algorithms computes a stabilized solution in its own global composite mesh in parallel. These algorithms compute a nonlinear system for the velocity, pressure and temperature based on a lower-order element pair (P₁b-P₁-P₁) and solve a linear approximation based on a higher-order element pair (P₂-P₁-P₂) on the same mesh, which shows that the new algorithms have the same convergence rate as the two-step finite element methods. What is more, the stability analysis of the proposed algorithms is derived. Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

The novel parallel two-step algorithms for incompressible natural convection problem are proposed. The rigorous analysis of the stability is given for the proposed parallel two-step algorithms. Extensive 2D/3D numerical tests demonstrate that the parallel two-step algorithms can deal with the incompressible natural convection problem for high Rayleigh number well.

The growing attention to green supply chain transparency prompts firms to disclose their environmental efforts and manage environmental issues along supply chains. Drawn upon diffusion theory, this study aims to investigate how customers’ environmental efforts can be diffused to suppliers for similar actions, as well as how customers’ (diffusors’) characteristics and suppliers’ (followers’) capability in digital technology application moderate the relationship.

This study collects secondary data of 1,514 unique customer-supplier dyad year observations of Chinese listed firms and their disclosed environmental efforts from 2009 to 2022. A fixed-effect regression model is used to test the hypotheses.

This study reveals a positive association between customers’ disclosed environmental efforts and those of their suppliers. Furthermore, the relationship is strengthened when customers are state-owned or when suppliers possess higher levels of digital technology application capability. These findings remain robust when alternative measures of variables are employed.

This study contributes to the supply chain transparency literature by uncovering the diffusion mechanism of environmental efforts from customers to their suppliers. It further identifies moderators for this diffusion, including customers’ (diffusors’) ownership and suppliers’ (followers’) capability. Lastly, our study extends the applicability of diffusion theory within a buyer–supplier context.

The purpose of this paper is to introduce an effective method to discriminate seal inks with Raman microscopy.

Raman spectra could effectively avoid interference from the paper and give extra peak information in the inks discrimination and identification. Thus, a Renishaw invia confocal Raman microscope system was employed for ink analysis in this study. A total of 12 representative seal ink samples, widely used in seven Chinese provinces, were investigated using the latest model of Renishaw Raman microscope.

Four types of inks were identified and discriminated successfully. Popular pigments such as Pigment Scarlet Powder, Pigment Yellow 55, phthalocyanine blue, Bronze red C and PbCrO3 were all identified in these seal ink samples. The indicative peaks to identify and discriminate the inks were also summarised and tentatively interpreted.

More ink samples were needed to establish a useful library. Many other pigments used in inks were still unknown.

This method was proved to be fast, accurate and non-destructive, and it could be more easily applied in real cases than Fourier transform infrared spectroscopy.

This method can help scientists discriminate some inks, which can hardly be discriminated by other techniques. The results are useful for the ink analysis and discrimination in forensic (document examination and file source identification), polymer and pigment fields.

The purpose of this paper is to identify different automotive coatings using Confocal Raman microscope which could hardly be differentiated with Fourier transform infrared microscope (FTIR).

Raman spectroscopy was used to provide extra vibration information to infrared spectroscopy. Paints preparation was not necessary, and only 30 s was needed for each sample in an optimised method. Paints were first analysed by FTIR and then compared with Raman microscope.

Raman microscope was used to address the lack of ability of FTIR in discriminating four groups of paints in same colours. This study indicated that Raman microscopy is especially effective in sensing pigments and could successfully identify all pigments in the paints.

The two instruments in combination produce accurate results than when used individually, especially in complex and multi-layered paints analysis.

The method proved to be fast, accurate and non-destructive, and it could be easily applied to real cases.

With this method, scientists could discriminate some coating types which were hard to be discriminated by other techniques.

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.

Public reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study explores the public attitudes and emotions toward educational robots through online reviews on Weibo and Twitter by using text mining methods.

Our study applied topic modeling to reveal latent topics about educational robots through online reviews on Weibo and Twitter. The similarities and differences in preferences for educational robots among public on different platforms were analyzed. An enhanced sentiment classification model based on three-way decision was designed to evaluate the public emotions about educational robots.

For Weibo users, positive topics tend to the characteristics, functions and globalization of educational robots. In contrast, negative topics are professional quality, social crisis and emotion experience. For Twitter users, positive topics are education curricula, social interaction and education supporting. The negative topics are teaching ability, humanistic care and emotion experience. The proposed sentiment classification model combines the advantages of deep learning and traditional machine learning, which improves the classification performance with the help of the three-way decision. The experiments show that the performance of the proposed sentiment classification model is better than other six well-known models.

Different from previous studies about attitudes analysis of educational robots, our study enriched this research field in the perspective of data-driven. Our findings also provide reliable insights and tools for the design, development and management of educational robots, which is of great significance for facilitating artificial intelligence in education.

In this chapter, we focus on expatriate CEOs who are assigned by the parent company to work in a subsidiary and compare them to those who themselves have initiated to work abroad as CEOs. Since we do not know much about these individuals, we direct our attention to: (1) who they are (demographics), (2) what they are like (personality), and (3) how they perform (job performance).

Data was sought from 93 assigned expatriate CEOs and 94 self-initiated expatriate CEOs in China.

Our findings demonstrate that in terms of demography, self-initiated CEOs were more experienced than assigned CEOs. With regard to personality, we found difference in self-control and dispositional anger: Assigned expatriate CEOs had more self-control and less angry temperament than their self-initiated counterparts. Finally, we found assigned expatriate CEOs to rate their job performance higher than self-initiated CEOs.

Although there may not always be immediate benefits, career consideration often plays a role when individuals choose whether to become an expatriate. For many years, organizations have used expatriation to develop talented managers for high-level positions in the home country. Recently, however, a new trend has emerged. Talented top managers are no longer expatriated only from within parent companies to subsidiaries. Self-initiated expatriates with no prior affiliation in the parent company are increasingly used to fill top management positions in subsidiaries.

Through the lens of experiential learning theory, this conceptual paper examines the factors influencing the likelihood of transitioning from hybrid to full-time entrepreneurship. It is critical to evaluate the experiential learning that takes place during the hybrid phase, in order to establish a more nuanced understanding of the dynamic entrepreneurial journey.

This conceptual paper made use of a secondary data analysis of the existing academic literature, in particular using a thematic analysis, in order to propose a conceptual model and associated propositions.

The proposed conceptual model identifies four factors: fear of failure, perceived risk, entrepreneurial competency development and self-efficacy that are predicted to influence the transition decision. This paper establishes hybrid entrepreneurship as an effective learning ground and path toward full-time entrepreneurship.

Providing insights into the factors that influence the transition, allows policy makers to establish systems and incubators to support hybrid entrepreneurs reach the tipping point at which they have sufficient knowledge to enter full-time entrepreneurship. This paper establishes the importance of developmental policies aimed at encouraging hybrid entrepreneurship. There are also implications for managers of hybrid entrepreneurs to establish policies that encourage a culture of transparency and reap the benefits of enhanced employee development.

The paper has three predominant sources of value. First, offering a multidisciplinary approach by extending an existing theory to a new context; second, through the establishment of a conceptual model, offering propositions readily linked to hypotheses for future empirical assessment and third, enhancing the visibility of hybrid entrepreneurship in the literature to encourage public policy intervention and support.

Based on resource dependence theory and transaction cost economics this study explores how green customer integration (GCI) affects financial performance via information sharing and opportunistic behavior, and the moderating effects of dependence and trust.

This study develops a theoretical model and tests it using data from two-waved survey data of 206 Chinese manufacturers. The hypotheses were tested using hierarchical linear regression analysis.

The results show that GCI has a significant and positive impact on information sharing, but its impact on opportunistic behavior is insignificant. Notably, information sharing has a significant and positive impact on financial performance, while opportunistic behavior has an insignificant impact on financial performance. In addition, dependence negatively moderates the impact of GCI on information sharing and positively moderates the impact of GCI on opportunistic behavior. Trust negatively moderates the impact of GCI on opportunistic behavior.

Although GCI has received widespread attention, how it affects a firm's performance remains unclear. Most previous studies have focused only on its bright side and ignored its dark side. This study highlights how GCI affects financial performance through information sharing and opportunistic behavior, and the moderating effects of dependence and trust. This enriches the understanding of how and under what conditions GCI affects a firm's performance.

The world in which companies operate today is volatile, uncertain, complex, and ambiguous, thus subjecting contemporary forms to an array of risks that challenge their viability in an increasingly competitive landscape. Organizations that cling to their traditional ways of operating impede their ability to survive while those able to embrace evolving changes and lever their strategic response capabilities (SRCs) will thrive against the odds. The possession of such capabilities has become a prominent explanation for effective adaptation to the impending changes but is rarely analyzed and tested empirically. Strategic adaptation typically assumes innovation as an important component, but we know little about how the innovative processes interact with the firm’s SRCs. Hence, this study investigates these implied relationships to discern their effects on organizational performance and risk outcomes. It explores the effects of SRCs and the role of innovation as intertwined adaptive mechanisms supporting strategic renewal that can attain superior performance and risk effects. The relationships are analyzed based on a large sample of US manufacturing firms over the decade 2010–2019. The study reveals that firms possessing effective SRCs have the ability to exploit opportunities and deflect risky situations to gain favorable performance and risk outcomes. While innovation indeed plays a role, the precise nature and dynamic effect thereof remain inconclusive.