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This study delves into the impact of mindfulness on the retention intention of technology employees, with a particular focus on the mediating variables of affective commitment (AC) and organizational identification (OI). The primary aim is to gain a comprehensive understanding of the underlying mechanisms through which mindfulness influences the retention intention of technology employees.

The research employed a survey approach with self-administered questionnaires and structural equation modeling. The collected data were analyzed using Statistical Product and Service Solutions (SPSS) 24 and Analysis of Moment Structure (AMOS) 28. Multiple mediation analyses was conducted through AMOS to examine the mediating effects of OI and AC.

The association between mindfulness and retention intention among technology employees showed an overall positive correlation. Additionally, AC and OI were positively correlated with retention intention. In the impact of employee mindfulness (EM) on retention intention, all indirect effects were found to be significant.

To the best of the authors' knowledge, this study is the first to investigate the relationship between EM and retention intention, as well as the associations of AC and OI with them, extending the application of mindfulness in management and offering insights for talent retention among company decision-makers.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.

The purpose of this paper is to examine the relationship between working capital management (WCM) and firm performance in the context of the Chinese economy. Specifically, it investigates the effects of ownership structures as an internal factor and of institutional environments (IE) as an external factor shaping this relationship.

The study applies two-way fixed effect regression models to a sample of Chinese listed manufacturing firms for the period of 2010 to 2017. WCM is measured by cash conversion cycles (CCC); profitability is measured by core profit ratios; ownership structures are classified based on state-owned enterprises (SOEs) and non-SOEs; and IEs are measured from dimensions of factor markets (FM) and legal systems (LS).

First, the results show a negative relationship between CCC and firm performance. Second, the negative relationship between CCC and profitability is significant for non-SOEs but not for SOEs. Third, both the FM and LS strengthen the negative association between CCC and profitability. Fourth, the moderating effect of FMs and LSs is evident for non-SOEs only. The results hold when using alternative measures of WCM and profitability and while controlling for additional variables.

The current study shows that while WCM has a significant effect on the profitability of Chinese firms, such an effect greatly depends on the ownership structures and IE involved. The results thus offer important implications in helping the Chinese government create better IEs and in allowing manufacturing firms to improve upon their WCM practices.

A firm will seek an optimal balance between internal R&D and technology outsourcing when formulating its innovation strategy. This paper aims to provide a review of the determinants of firm's innovation strategy, and performs an empirical study on a sample from Chinese high‐tech industry, with the purpose of identifying two aspects of the issue: the choice patterns of Chinese firms over innovation strategy, and the innovation effect elasticity of different strategies.

The development of a multiple regression model supported by data from industry level and a statistic analysis.

Outsourcing is the major innovation strategy adopted by most Chinese high‐tech firms, especially technology import, which implies the imperfection of Chinese innovation service system. The empirical analysis also indicates the insufficiency of internal R&D expenditure and the weakness of absorptive capacity in Chinese high‐tech firms. Although, Chinese high‐tech firms prefer the outsourcing strategy in their innovation, the contribution of outsourcing is much smaller than that of internal R&D. When expenditures are increased by the same rate, the innovation output form internal R&D is twice the output of outsourcing. For improving Chinese firms' innovation efficiency, the reform of innovation service system is needed on the macro‐level, while on the micro‐level, it calls for firms to readjust their innovation strategy portfolio.

This paper will make up for the deficiency in current researches on innovation, which often apply firm samples in developed countries, and lack evidences from firm samples in developing countries. In addition, it will provide the decision‐making basis for Chinese Government's current actions in constructing and improving China's innovation service system.

The purpose of this paper is research the relationship between size of government and FDI inflows of the host country, and provide a strategies.

Adopting the fixed effect model of panel data, this paper uses related observations from 81 countries between 2002 and 2006 to analyze the impacts of government size (measured by score of government size) on FDI inflows.

The results show that the enlargement of government size has a positive effect on FDI inflows, and the effect is much more significant in developing countries.

There is no previous research concerning the impacts of size of government on FDI inflows. Through the investigation, the paper finds the relation between government size and FDI inflows and provides much valuable information.

This paper is concerned with non-fragile robust H_∞ control problems for nonlinear networked control systems (NCSs) with time-varying delay and unknown actuator failures. The paper aims to discuss these issues.

The system parameters are allowed to have time-varying uncertainties and the actuator faults are unknown but whose upper and lower bounds are known. By using some lemmas, uncertainties can be replaces with the known values. By taking the exogenous disturbance and network transmission delay into consideration, a delay nonlinear system model is constructed.

Based on Lyapunov stability theory, linear matrix inequalities (LMIs) and free weighting matrix methods, the sufficient conditions for the existence of the non-fragile robust H_∞ controller gain are derived and which can obtained by solving the LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed methods.

The introduced approach is interesting for NCSs with time-varying delay and unknown actuator failures.

This paper aims to discuss a nanoscale biosensor and its signal analysis algorithms.

In this work, five nanoscale biosensors are reviewed, namely, silicon nanowire field-effect-transistor biosensors, polysilicon nanogap capacitive biosensors, nanotube amperometric biosensors, gold nanoparticle-based electrochemical biosensors and quantum dot-based electrochemical biosensors.

Each biosensor produces a different output signal depending on its electrical characteristics. Five signal analysers are studied, with most of the existing signal analyser analyses based on the amplitude of the signal. Based on the analysis, auto-threshold peak detection is proposed for further work.

Suitability of the signal processing algorithm to be applied to nano-biosensors was reported.

Due to the strong reliance on element quality, there exist some inherent shortcomings of the traditional finite element method (FEM). The model of FEM behaves overly stiff, and the solutions of automated generated linear elements are generally of poor accuracy about especially gradient results. The proposed cell-based smoothed point interpolation method (CS-PIM) aims to improve the results accuracy of the thermoelastic problems via properly softening the overly-stiff stiffness.

This novel approach is based on the newly developed G space and weakened weak (w²) formulation, and of which shape functions are created using the point interpolation method and the cell-based gradient smoothing operation is conducted based on the linear triangular background cells.

Owing to the property of softened stiffness, the present method can generally achieve better accuracy and higher convergence results (especially for the temperature gradient and thermal stress solutions) than the FEM does by using the simplest linear triangular background cells, which has been examined by extensive numerical studies.

The CS-PIM is capable of producing more accurate results of temperature gradients as well as thermal stresses with the automated generated and unstructured background cells, which make it a better candidate for solving practical thermoelastic problems.

It is the first time that the novel CS-PIM was further developed for solving thermoelastic problems, which shows its tremendous potential for practical implications.