Search results

This study examines the impact of a novel co-teaching approach, involving collaboration between university instructors and school teachers, on pre-service teachers’ (PSTs) understanding of classroom management skills, addressing the practical challenges that often exceed the university classroom’s scope.

Using a pooled cross-sectional dataset of 513 students from a Chinese teacher training university, the study employed descriptive statistics, factor analysis and ordinary least squares (OLS) regression analysis. Focus group interviews were also conducted to explore the mechanisms underlying the co-teaching impact.

The co-teaching team effectively integrates theory with practice, enhancing student engagement and learning outcomes. Most students appreciated the co-teaching format, which positively correlated with their recognition of classroom management and the teaching profession. The success of co-teaching was linked to the authenticity brought by school teachers, including exposure to real-life cases that encouraged PSTs to actively solve educational problems.

Pre-service teacher education benefits from university-school collaboration. Inviting experienced school teachers to co-teach in university classrooms offers an efficient instructional approach, improving students’ learning experiences with less time and effort.

This study empirically demonstrates the utility of co-teaching in pre-service teacher education, particularly within China, enriching the literature on school-university partnerships.

As an important part of the disclosure of listed companies' annual reports, MD&A will disclose some "bad news" about the company. The purpose of this paper is to study whether such "bad news" can reduce information asymmetry and alleviate the risk of stock price crash remains to be seen.

Based on the sample of A-share listed companies from 2007 to 2016, the authors examine whether the negative information in MD&A could reduce stock price crash risk.

It is found that the negative information in MD&A does not reduce future crash, which indicates that the negative information in MD&A does not alleviate the information asymmetry. Further, it is also found this is due to the low readability of negative information which leads to the negative information not successfully released into the market timely. Only highly readable negative information can alleviate information asymmetry and suppress crash risk. In addition, the authors also find in the companies with more investor surveys negative tone is negatively correlated with crash risk, which means that investor surveys could help investors interpret the negative information in MD&A and alleviate stock price crash risk.

The practical significance of this article: this paper suggests that investors should carefully identify the quality of negative information in MD&A and pay attention to other quality characteristics besides credibility. This paper suggests that the regulator should pay attention not only to whether to disclose and the amount of disclosure but also to the quality of information disclosure, such as readability, so as to restrict management's strategic behavior in information disclosure.

First, different from previous studies on the impact of information disclosure on crash risk, this paper directly explores the impact of information in MD&A on stock price crash risk from the perspective of negative information disclosure that management most want to hide. It supplements the literature on the impact of information disclosure on stock price crash risk. Second, this paper studies the interaction between information tone and readability and its impact on the risk of stock price crash. Some studies believe that the credibility of negative news is higher and investors' reaction may be stronger. However, this paper finds that the disclosure of negative information may not be absorbed by the market because of the low readability. Third, this paper finds that investor surveys can help information users to interpret negative information and alleviate the risk of stock price crash, which shows that information disclosure of different channels will complement each other and improve information efficiency. Therefore, it advocates different information disclosure channels which has important practical significance for improving market pricing efficiency and reducing investment decision-making risk.

The research goal is to understand what factors affect users' knowledge and information learning and sharing on social media platforms. This study focuses on the impact of platform characteristics on users' behavior. Specifically, the purpose of this study is to investigate (1) what factors affect users' learning and dissemination of knowledge and information on social media platforms, (2) whether knowledge and information learning behavior will have a positive effect on sharing behavior and (3) try to establish an impact model of users' learning and sharing behavior about knowledge and information.

This study proposes an impact mechanism model to test these hypotheses. To achieve this, the authors collected data from 430 users who have used the social media platforms to acquire and share knowledge and information to test the hypothesis. The tools SPSS 26.0 and AMOS 23.0 were used to analyze the reliability, validity, model fits and structural equation modeling.

The results show that the learning of knowledge and information can influence the sharing behavior on social media platforms. Users' platform-based trust and platform-based satisfaction affect their knowledge and information learning and sharing on the platform. Factors affecting users' trust in social platforms include privacy protection effectiveness and network effects. And, perceived usefulness and perceived ease of use are related to users' satisfaction with social media platforms.

This study constructs an impact model on the learning and sharing of knowledge and information. The model takes the information system continuance model as the theoretical framework and integrates other factors, including the network effect, the effectiveness of privacy protection and trust. Most of the hypotheses of this research were confirmed. The conclusions provide practical guidance for the dissemination of knowledge information and platform management.

The purpose of this paper is to study the influence of pivot stiffness on the dynamic characteristics of tilting-pad journal bearings (TPJBs) and the stability of the bearing-rotor system.

A theoretical numerical model is established, and the influences of pivot stiffness on TPJBs and a bearing-rotor system are analyzed. Then, two kinds of pivot structures with different stiffness are designed and the vibration characteristics are tested on the vertical rotor bearing test bench.

The pivot stiffness has an obvious effect on the dynamic characteristics of the TPJBs and the stability of the bearing-rotor system. As a result of appropriate pivot stiffness, the critical speed and the vibration amplification factor can be reduced, the logarithmic decay rate and the stability of the rotor system can be effectively increased. While the journal whirl orbit is smoother and the rubbing is obviously reduced when the bearings have flexible pivots.

The influence of pivot stiffness on TPJBs and a vertical rotor-bearing system is studied by theoretical and experimental methods.

The aim of the article was to focus on various peptides identified in the egg and their probable application as novel ingredients in the development of functional food products. Bioactive peptides of egg origin have attracted increasing interest as one of the prominent candidates for development of various health-promoting functional and designer foods.

Traditionally known as a source of highly valuable proteins in human nutrition, eggs are nowadays also considered as an important source of many bioactive peptides which may find wide application in medicine and food production. These specific protein fragments from egg proteins which, above and beyond their nutritional capabilities, have a positive impact on the body’s function or condition by affecting the digestive, endocrine, cardiovascular, immune and nervous systems, and may ultimately influence health.

Several peptides that are released in vitro or in vivo from egg proteins have been attributed to different health effects, including antihypertensive effects, antimicrobial properties, antioxidant activities, anticancer activity, immunomodulating activity, antiadhesive properties and enhancement of nutrient absorption and/or bioavailability. Extensive research has been undertaken to identify and characterize these biologically active peptides of egg origin which has changed the image of egg as a new source of biologically active ingredients for the development of functional foods with specific benefits for human health and treatment and prevention of diseases.

The paper mainly describes the above-stated properties of bioactive peptides derived from egg proteins.

The aim of this paper, which is based on Cheng et al.’s (2012) research, is to re-examines the relationship between a firms’ voluntary disclosure of forward-looking non-financial information (FNFI) and investment efficiency.

The authors chose firms that publicly traded in the Shenzhen and Shanghai stock markets from 2005 to 2011, a total of 926 firms and 6,482 firm-year. To control the endogeneity problem between FNFI and investment efficiency, the authors lagged the FNFI variable for one year.

The authors found that FNFI alleviates a firms’ underinvestment but leads to overinvestment. These effects become gradually weaker over time. In addition, the results indicate that corporate governance helps improve the quality of FNFI, thus boosting investors’ confidence and easing financial constraints.

The limitations of this paper are mainly focused on the measure of FNFI. The authors only considered the quantity of FNFI disclosed by firms and ignored other characteristics of FNFI.

Based on Cheng et al.’s (2012) static findings, this paper considers the dynamic role of FNFI in firms’ investment decisions.

Theory is needed for a discipline to mature. This research aims to provide a summary analysis of the theories being used in contemporary logistics and supply chain management (SCM) studies.

A comprehensive literature review of articles appearing in five top tier logistics and SCM journals is conducted in order to identify how often theory is used and to classify the specific theories used. An analysis of the theoretical categories is presented to explain the type and frequency of theory usage.

Over 180 specific theories were found within the sampled articles. Theories grouped under the competitive and microeconomics categories made up over 40 per cent of the theoretical incidences. This does not imply all articles utilize theory. The research found that theory was explicitly used in approximately 53 per cent of the sampled articles.

Two implications are central. First, in the minds of editors, reviewers and authors is approximately 53 per cent theory use enough? Literature suggests there continues to be a need for theory‐based research in the discipline. A first step may be to increase our theory use, and to clearly describe the theory being used. Second, the vast majority of theories used in recent logistics and SCM research originated in other disciplines. Growth in the discipline dictates the need for greater internal theory development.

Despite multiple calls for the use of theory in logistics and SCM, little formal research has been produced examining the actual theories being used. This research provides an in‐depth review and analysis of the use of theory in logistics and SCM research during the period 2004‐2009.

Following Cheng et al. (2012) and Tan et al. (2015), this paper aims to investigate how does the forward-looking information disclosure quality affect the investors’ decisions and then the investment efficiency.

The authors obtain the information disclosure quality rating data from the official website of the Shenzhen Stock Exchange (SZSE), and firm financial information is mainly from the China Center for Economic Research (CCER) and China Stock Market and Accounting Research Database (CSMAR). The authors choose firms that publicly traded on the SZSE during the period from 2004 to 2010, and the final sample consists of 2,415 firm-year observations for 345 unique firms.

The authors find that a firm with a high information disclosure quality rating is trusted by investors more. Forward-looking non-financial information (FNFI) disclosure alleviates financial constraints and improves investment efficiency, including alleviating underinvestment and preventing overinvestment to a larger extent for firms with high information disclosure quality rating, especially for the firms rated A (excellent) or B (good) every year since 2001, when the rating began. Moreover, this study proves that investors trust the firms rated high more but do not guard against the firms rated low enough.

The authors only considered the quantity of FNFI disclosed by firms and ignored other characteristics of FNFI. Limited by the data of information disclosure quality rating, the research sample is just from the SZSE.

This paper extends the research of Cheng et al. (2012) and Tan et al. (2015) to show that one of the reasons behind the extant mix results of the relationship between FNF disclosure and investment efficiency is different information disclosure quality. High-quality FNFI disclosure can alleviate underinvestment and prevent overinvestment at same time.