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The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to store, maintain, and analyze large sets of data provided by different systems of health. It is essential to manage and analyze these data to get meaningful information. Pharmaceutical companies are accumulating their data in the medical databases, whereas the payers are digitalizing the records of patients. Biomedical research generates a significant amount of data. There has been a continuous improvement in the health sector for past decades. They have become more advanced by recording the patient’s data on the Internet of Things devices, Electronic Health Records efficiently. BD is undoubtedly going to enhance the productivity and performance of organizations in various fields. Still, there are several challenges associated with BD, such as storing, capturing, and analyzing data, and their subsequent application to a practical health sector.

Burn‐in is an engineering method extensively used to screen out infant mortality failure defects. Previous studies have attempted to determine the optimum burn‐in time and cost for a device or a system. However, for the mathematical model, many assumptions are inappropriate due to practical concerns, and for the cost model, the required costs are difficult to find. How to effectively determine the optimal burn‐in time and cost has perplexed manufacturers for quite some time. In the actual manufacturing process, a new electronic product is always extended from an old product, called the base product. By adopting the relationship between new product and base product, this study presents a neural network‐based approach to determine the optimal burn‐in time and cost without any assumptions. A case study of the production of a switch mode rectifier demonstrates the effectiveness of the proposed approach.

Burn‐in is an effective means of screening out the infant mortality components of a system. Most related studies investigated burn‐in by curve fitting for a failure model and cost for an optimal burn‐in time model and environmental stress model. However, those investigations did not provide an effective method to determine the optimal burn‐in condition for a practical operation. As a result, this study presents an effective procedure that uses part stress analysis and robust design techniques to determine the optimal burn‐in operational environment. A case study of the production of a switch mode rectifier is performed and compared with the traditional approach, to examine the proposed procedure’s effectiveness. Those results show that the proposed procedure generalizes well, and can screen out the early failure of material and manufacturing process.

The overall objective of this research was to elucidate the ecosystem of women’s health social enterprises (WHSEs) based in the United States. The Aim I was to conduct a secondary data analysis of a random national sample of non-profit WHSEs based in the United States regarding their characteristics and areas of intervention. Aim II was to conduct a qualitative assessment of a sample of WHSEs based in the United States regarding their perspectives on the ecosystem of WHSEs. Aim I utilized the GuideStar database and assessed enterprise size, geographic location, financial distress, health intervention area, and health activity category using descriptive statistics, statistical tests, and multivariable regression analysis via SPSS. Aim II utilized in-depth interviewing and grounded theory analysis via MAXQDA 2018 to identify novel themes and core categories while using an established framework for mapping social enterprise ecosystems as a scaffold.

Aim I findings suggest that WHSE activity is more predominant in the south region of the United States but not geographically concentrated around cities previously identified as social enterprise hubs. WHSEs take a comprehensive approach to women’s health, often simultaneously focusing on multiple areas of health interventions. Although most WHSEs demonstrate a risk for financial distress, very few exhibited severe risk. Risk for financial distress was not significantly associated with any of the measured enterprise characteristics. Aim II generated four core categories of findings that describe the ecosystem of WHSE: (1) comprehensive, community-based, and culturally adaptive care; (2) interdependent innovation in systems, finances, and communication; (3) interdisciplinary, cross-enterprise collaboration; and (4) women’s health as the foundation for family and population health. These findings are consistent with the three-failures theory for non-profit organizations, particularly that WHSEs address government failure by focusing on the unmet women’s health needs of the underserved populations (in contrast to the supply of services supported by the median voter) and address the market failure of over exclusion through strategies such as cross-subsidization and price discrimination. While WHSEs operate with levels of financial risk and are subject to the voluntary sector failure of philanthropic insufficiency, the data also show that they act to remediate other threats of voluntary failure.

Aim I findings highlight the importance of understanding financial performance of WHSEs. Also, lack of significant associations between our assessed enterprise characteristics and their financial risk suggests need for additional research to identify factors that influence financial performance of WHSE. Aim II findings show that WHSEs are currently engaged in complex care coordination and comprehensive biopsychosocial care for women and their families, suggesting that these enterprises may serve as a model for improving women’s health and health care. The community-oriented and interdisciplinary nature of WHSE as highlighted by our study may also serve as a unique approach for research and education purposes. Additional research on the ecosystem of WHSE is needed in order to better inform generalizability of our findings and to elucidate how WHSE interventions may be integrated into policies and practices to improve women’s health.

Previous empirical studies on the nature of the relationship between ownership and corporate value have produced mixed results. Meanwhile, effective management of knowledge‐based intellectual capital has become a key factor to corporate success, both in firm performance and corporate value. Thus, this paper aims to reexamine the link among ownership, proxies for intellectual capital and corporate value in the emerging Taiwan market.

Using two‐stage least square estimation of panel data in a simultaneous equations framework, the authors focus on: What is the interdependent impact of ownership on corporate value through the mediating role of intellectual capital (IC)? Does ownership directly or indirectly (i.e. via IC) influence corporate value? Does it persist across industries?

The empirical results suggest that the relationship between ownership and corporate value mainly depends on industry characteristics and the nature of proxies for intellectual capital in the emerging Taiwanese market. Further, the impacts of ownership on corporate value in more traditional industries are even stronger, that is, there exists the direct impact of ownership mechanism on corporate value. Notably, for the high‐tech firms, ownership can indirectly affect corporate value through the moderating role of intellectual capital.

The implication reminds managers and investors not merely focusing on ownership mechanisms as the main value‐creation information, but a thorough review of IC should be made in order to avoid making incorrect decisions. The limitations suggest areas for further research. For instance, it is important to extend the role of intellectual capital (i.e. to employ other variables to proxy for IC) in exploring the interdependent impact of ownership on corporate value.

The paper potentially adds to ongoing research by extending the importance of the concept of IC in assessing the interdependent impact of ownership on corporate value.

The purpose of this paper is to provide an introduction to the reverse mergers (RMs) conducted in the Chinese stock market by summarizing the regulatory system, surveying the literature on RMs and analyzing the major characteristics of 161 RM cases.

This paper introduces the characteristics and evolution of the regulatory framework governing RM activity in China. Then the paper reviews relevant academic studies on the RMs in China and other countries. Finally, the paper identifies and discusses the major characteristics of 161 RM cases in the Chinese stock market from 2006 to 2016.

Private companies that go public via RMs in China not only have superior asset quality but also demonstrate good accounting and stock price performance after listing, and these results are unlike those of studies on the quality of RMs in other countries.

This paper is based on a survey of 161 RM cases in China’s stock market, with the major characteristics of the RMs being identified and analyzed. The limitations of previous studies and suggestions for further research are discussed.

This paper suggests that the relative superior performance of RMs in the Chinese stock market is caused by the interplay of market forces and regulatory oversight. The Chinese regulator’s pragmatic and flexible approach plays an important role in formulating regulatory policies that respond to the changing macroeconomic environment and financial markets.

The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work‐in‐process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn’t mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can’t reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don’t need too much WIP. So WIP level could be reduced and cycle time also could be reduced.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

As global issues such as climate change, economic growth, social equality and the wealth gap are widely discussed, education for sustainable development (ESD) allows every human being to acquire the knowledge, skills, attitudes and values necessary to shape a sustainable future. It also requires participatory teaching and learning methods that motivate and empower learners to change their behavior and take action for sustainable development. Teachers have begun rating pupils based on peer assessment for open evaluation. Peer assessment enables students to transition from passive to active feedback recipients. The assessors improve critical thinking and encourage introspection, resulting in more significant recommendations. However, the quality of peer assessment is variable, resulting in reviewers not recognizing the remarks of other reviewers, therefore the benefits of peer assessment cannot be fulfilled. In the past, researchers frequently employed post-event questionnaires to examine the effects of peer assessment on learning effectiveness, which did not accurately reflect the quality of peer assessment in real time.

This study employs a multi-label model and develops a self-feedback system in order to use the AIOLPA system in the classroom to enhance students' learning efficacy and the validity of peer assessment.

The research findings indicate that the better peer assessment through the rapid feedback system, for the evaluator, encourages more self-reflection and attempts to provide more ideas, so bringing the peer rating closer to the instructor rating and assisting the evaluator. Improve self-evaluation and critical thinking for the evaluator, peers make suggestions and comments to help improve the work and support the growth of students' learning effectiveness, which can lead to more suggestions and an increase in the work’s quality.

ESD consequently promotes competencies like critical thinking, imagining future scenarios and making decisions in a collaborative way. This study builds an online peer assessment system with a self-feedback mechanism capable of classifying peer comments, comparing them with scores in a consistent manner and providing prompt feedback to critics.

The purpose of this paper is to provide a comprehensive view of the longitudinal status and the knowledge structure of the CSR research by identifying the major study topics, the development of CSR research, the leading authors and countries, as well as the most cited reference.

The authors systematically reviewed 14,490 articles in 15 journals specialized in CSR published between 2000 and 2016 with bibliographic coupling analysis and social network analysis to unveil the recent trend of CSR research.

The results identified 15 research topics in CSR research. This study accordingly suggests that CSR implication is the most popular topic in the CSR research field. Particularly, the publications regarding to “CSR Implication” increased with a dramatic trend. Furthermore, the rest of the 14 topics had a stagnant trend movement. Most of the leading authors of CSR research came from English-speaking countries. CSR investigations with varied topics simultaneously attracted the attentions of researchers from developed counties. On the other hand, researchers from developing countries simply focused limited issue.

This study proposes an automatic content analysis from scientometric perspective to reveal a comprehensive and longitudinal understanding of CSR research. Such examination on CSR studies is critical to afford researchers’ urgent need to grasp current research status and potential research space.