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The purpose of this paper is to reveal the multi‐scale relation between power law distribution and correlation of stock returns and to figure out the determinants underlying capital markets.

The multi‐scale relation between power law distribution and correlation is investigated by comparing the original series with the special series. The eliminating intraday trend series approach developed by Liu et al. is utilized to analyze the effects of power law decay change on correlation properties, and shuffling series originated by Viswanathan et al. for the impacts of special type of correlation on power‐law distribution.

It is found that the accelerating decay of power law has an insignificant effect on correlation properties of returns and the empirical results indicate that time scale may also be an important factor maintaining power law property of returns besides correlation. When time scale is under critical point, the effects of correlation are crucial, and the correlation of nonlinear long‐range presents the strongest influence. However, for time scale beyond critical point, the impact of correlation begins to diminish or even finally disappear and then the power law property shows complete dependence on time scale.

The 5‐min high frequency data of the Shanghai market as the empirical benchmark is insufficient to depict the relation over the entire time scale in the Chinese stock market.

The paper identifies the determinants of market dynamics to apply them to risk management through analysis of multi‐scale relations, and supports endeavors to introduce time parameter into further risk measures and control.

The paper provides the empirical evidence that time scale is one of the key determinants of market dynamics by analyzing the multi‐scale relation between power law distribution and correlation.

The main purpose of this study was to develop and test an employability scale in a Chinese context. Moreover, the authors investigated how socioeconomic status indicators (education and occupation of parents, household income and hukou, i.e. household registration location) affect the endowment and development of adolescents' employability skills in China.

Data were collected via paper-based surveys from 1,146 vocational school students in rural and urban areas in China at two points in time one year apart. The authors developed a scale to measure employability skills in China and conducted general linear modeling to test the hypotheses.

The findings indicate that adolescents whose parents have more education, highly skilled occupations, relatively affluent household income and urban hukou are more likely to attain higher employability skills than those from lower socioeconomic status backgrounds. Moreover, adolescents with these background characteristics tend to improve their employability skills more than those without such characteristics. This suggests that social capital may further widen the inequality gap among adolescents.

The framework of employability skills focuses on the general basic transferable employability skills of vocational students. Future studies could develop measures of employability skills for college graduates and widen the measurements of social capital based on the study’s findings. The findings suggest that higher education institutions should be encouraged to integrate resources to improve education inequality between rural and urban regions to the disparity in adolescents' employability skills development.

Building on Western frameworks, the study defines and develops an employability scale in the Chinese context that can be a practical measurement tool for researchers, educators and policymakers. The authors investigated the endowment and development of employability skills in relation to social capital. Exposure to social capital tends to affect an individual's skills and capability development at an early stage, and in the long term, this calls attention to access to quality education between rural and urban youth.

This paper proposes an integrated knowledge visualization and digital twin system for supporting strategic management decisions. The concepts and applications of strategic architecture have been illustrated with a concrete real-world case study and decision rules of using the strategic digital twin management decision system (SDMDS) as a more visualized, adaptive and effective model for decision-making.

This paper integrates the concepts of mental and computer models and examines a real case's business operations by applying system dynamics modelling and digital technologies. The enterprise digital twin system with displaying real-world data and simulations for future scenarios demonstrates an improved process of strategic decision-making in the digital age.

The findings reveal that data analytics and the visualized enterprise digital twin system offer better practices for strategic management decisions in the dynamic and constantly changing business world by providing a constant and frequent adjustment on every decision that affects how the business performs over both operational and strategic timescales.

In the digital age and dynamic business environment, the proposed strategic architecture and managerial digital twin system converts the existing conceptual models into an advanced operational model. It can facilitate the development of knowledge visualization and become a more adaptive and effective model for supporting real-time management decision-making by dealing with the complicated dependence of constant flow of data input, output and the feedback loop across business units and boundaries.

The purpose of this study was expected to simultaneously monitor the surface roughness of each solidified layer, the surface roughness of the metal powder, the outline of the solidified layer, and the height difference between the solidified layer and the metal powder.

In the proposed approach, color images with red, green and blue fringes are used to measure the shape of the built object using a three-step phase-shift algorithm and phase-unwrapping method. In addition, the surface roughness is extracted from the speckle information in the captured image using a predetermined autocorrelation function.

The feasibility and accuracy of the proposed system were validated by comparing it with a commercial system for an identical set of samples fabricated by a selective laser melting process. The maximum and minimum errors between the two systems are approximately 24% and 0.8%, respectively.

In the additive manufacturing field, the authors are the first to use fringe detection technology to simultaneously measure the profile of the printed layer and its surface roughness.