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The main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA).

It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital).

The univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

The results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

Overall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency.

First, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms.

This study aims to examine the relationships among International Financial Reporting Standards (IFRS) adoption, earnings management, and corporate efficiency.

First, the authors employ the epsilon-based measure (EBM) of the data envelopment analysis to measure the corporate performance of the Taiwanese electronics industry from 2011 to 2014. Second, the authors regress the IFRS adoption and earnings management on corporate efficiency.

The findings show that the corporate efficiency deteriorated after IFRS adoption. Although the regression analysis shows that the relationship between earnings management and corporate efficiency is significantly positive, the authors find that IFRS adoption is effective in unveiling earnings management. Moreover, IFRS adoption moderates the impact earnings management and corporate efficiency.

This study provides reference for decision-makers in the application of accounting principles and in the understanding of the IFRS impact adoption.

IFRS adoption can either facilitate or limit the earnings management that would affect corporate efficiency significantly and help the electronics industry as well as investors to know the changes in accounting principles and their effects on corporate efficiency.

The authors use the EBM of efficiency model to measure corporate efficiency and employ the modified Jones model to measure earnings management.

This paper aims to investigate the effect of intellectual capital (IC) on the operating efficiency of non-life insurance firms in China.

The authors use a dynamic data envelopment analysis model called dynamic slacks-based measure (DSBM) model to estimate the operating efficiency of 32 Chinese non-life insurance firms. Using a panel data set for the period from 2006 to 2010, the authors run ordinary least squares (OLS) regressions to find the relationship between IC and efficiency performance.

The authors find that the insurers have almost monotonically decreasing efficiency for the period from 2006 to 2010. Regression results show that human capital, structural capital and relational capital are significantly and positively related to operating efficiency.

This study suggests that managers of the Chinese non-life insurers should devote attention to the investments in IC to stay sustainable.

This is the first paper to examine the impact of IC on operating efficiency in the Chinese non-life insurance industry. This study differs from prior studies in that the authors use the DSBM model proposed by Tone and Tsutsui (2010) for evaluating the operating efficiency using a dynamic process.

The purpose of this paper is to determine if artificial neural network (ANN) works better than linear regression in predicting Hong Kong real estate investment trusts’ (REITs) excess return.

Both ANN and the regression were applied in this study to forecast the Hong Kong REITs’ (HK-REITs) return using the capital asset pricing model and Fama and French’s three-factor models. Each result was further split into annual time series as a measure to investigate the consistency of the performance across time.

ANN had produced a better forecasting results than the regression based on their trading performance. However, the forecasting performance varied across individual REITs and time periods.

ANN should be considered for use when one were to attempt forecasting the HK-REITs excess returns. However, the trading performance should be always compared with buy and hold strategy prior to make any investment decisions.

This paper tested the predicting power of ANN on the HK-REITs and the consistency of its predicting power.

A review of previous studies on the voices of employees and knowledge workers clarifies that paying attention to employees' voice is critical in human resource management. However, limited studies have been conducted on it, and much less emphasis has been placed compared to other human resource management activities such as human resource planning. Therefore, the voice of knowledge employees has been one of the critical issues that have attracted a great deal of attention recently. Nonetheless, there is no evidence of various comprehensive and integrated voice mechanisms. As a result, this study aims to design knowledge workers' voice patterns in knowledge-based companies specialising in information and communication technology (ICT) in Iran in May and June 2020.

This study is a qualitative grounded theory research. We collected the data from a target sample of 15 experts in knowledge-based ICT companies using in-depth semi-structured interviews. Since all the participants had practised the employee voice process, they were regarded as useful data sources. Data analysis was also performed using three-step coding (open, axial and selective) by Atlas T8, which eventually led to identifying 14 components and 38 selected codes. We placed identified components in a paradigm model, including Personality Characteristics, Job Factors, Economic Factors, Cultural Factors, Organisational Policies, Organisational Structure, Climate Of Voice in the Organisation, Management Factors, Emotional Events, Communications and Networking, Contrast and Conflict and, etc. Then, the voice pattern of the knowledge staff was drawn.

The results showed that constructive knowledge voice influences the recognition of environmental opportunities and, additionally, it helps the competitive advantages among the employees. By forming the concept of knowledge staff voice, it can be concluded that paying attention to knowledge staff voice leads to presenting creative solutions to do affairs in critical situations. The presentation of these solutions by knowledge workers results in the acceptance of environmental changes, recognition and exploitation of new chances and ideas, and sharing experiences in Iranian knowledge-based companies.

Strengthening and expanding the voice of employees in knowledge-oriented companies can pave the way to growth and development towards a higher future that prevents the waste of tangible and intangible assets.

Companies' ability to engage in knowledge workers is a vital factor in human resource management and strategic management. However, the employee voice has not been involved integrally in the context of corporate.

This paper aims to establish the wideband model of a sub-module in a modular multilevel converter (MMC) and analyze the switch transients of the sub-module.

The paper builds an MMC sub-module test circuit and conducts dynamic tests both with and without the bypass thyristor. Then, it builds the wideband model of the MMC sub-module and extracts the model parameters. Finally, based on the wideband model, it simulates the switch transients and analyzes the oscillation mechanism.

The dynamic testing shows the bypass thyristor will add oscillations during switch transients, especially during the turn-on process. The thyristor acts like a small capacitor and reduces the total capacitor in the turn-on circuit loop, thus causing under-damped oscillations.

This paper found that the bypass thyristor will influence the MMC sub-module switch transients under certain circumstances. This paper proposes a partial inductance extraction procedure for the MMC sub-module and builds a wideband model of the sub-module. The wideband model is used to analyze and explain the switch transients, and can be further used for insulated gate bipolar transistor switch oscillation inhibition and sub-module design optimization.