The aim of this study is to investigate the herding of beta transmission between return and volatility. We have used the dynamic conditional correlation model with the mixed-data sampling (DCC-MIDAS) model for the analysis. The evidence demonstrates that herding is a key transmitter in Taiwan’s stock market. The significant estimation of DCC-MIDAS explains that the herding phenomenon is highly dynamic and time-varying in herding behavior. By means of time-varying beta of herding based on our rolling forecasting method and robustness check of the Markov-switching regression approach using four types of portfolios, the evidence indicates that there are conditional correlations between betas and herding. In addition, it also reveals that herding forms in Taiwan’s markets during the subprime crisis period.

Libraries are digitizing, and challenges are posed by digital technologies for institutions of higher education in China. This study aims to present the dimensionality of perceived service quality, its effect on customer satisfaction, and the case of a non-state-owned library’s academic service quality. A sample consisting of valid 453 respondents used online recruitment to retrieve answers to questionnaires. Ten experts were invited to review the questionnaire for content validity and question clarity. In this study, the Fuzzy Delphi method was used to establish questionnaire indices and the attributes of library academic service quality elements made available by the Kano model. Three dimensions, including emotional service, physical environment, and information control, which are correlated under the attribute classification of the Kano model, indicate support for the validity of using integrated models in measuring library service quality. The results, according to the improvements in the customer satisfaction matrix, provide nine elements to improve the quality of service and two major improvements to enhance the perception of service quality. In addition, users pay less attention to the use of academic resources and academic ethics, but these factors do not affect the quality of service.

No abstract

No abstract

Most of the growth forecasts in analysts’ evaluation reports rely on human judgment, which leads to the occurrence of bias. A back-propagation neural network (BPNN) is a financial technique that learns a multi-layer feedforward network. This study aims to integrate BPNN and asset pricing models to avoid artificial forecasting errors. In terms of evaluation, financial statements and investor attention were used in this case study, demonstrating that modern analysts should incorporate the evaluation advantages of big data to provide more reasonable and rational investment reports. We found that assessments of revenue, index returns, and investor attention suggest that stock prices are prone to undervaluation The levels of risk-taking behaviors were used in the classification of robustness analysis. This study showed that when betas range from 1% to 5%, both risk-taking levels of investors can hold buying strategies for the long term. However, for lower risk-taking preferences, only when the change exceeds 10 percent, the stock price is prone to overvaluation, indicating that investors can sell or adopt a more cautious investment strategy.