This study investigates through perceived hedonic values the influence of two features of group-buying websites, novel curiosity and site navigation, on online consumer purchase intentions and behavior. Using GROUPON Taiwan as a case study, a web-based online questionnaire is used to collect survey data from 290 valid participants. By analyzing this information through the Partial Least Squares program, the results support the hypothesis that curiosity and navigation have significantly positive effects on perceived hedonic values and attitudes. Furthermore, these values likewise have a significant positive effect on online group-buying intentions.
Among FinTech research and applications, forecasting financial time series data has been a challenging task because this kind of data is typically quite noisy and non-stationary. A recent line of financial research centers around trading through financial data on the microscopic level, which is the holy grail of high-frequency trading (HFT), as the higher the data frequency, the more profitable opportunities may appear. The advancement in HFT modeling has also facilitated more understanding towards price formation because the supply and demand of a stock can be comprehended more easily from the microstructure of the order book. Instead of traditional statistical methods, there has been increasing demand for the development of more reliable prediction models due to the recent progress in Computational Intelligence (CI) technologies. In this study, we aim to develop novel CI-based methodologies for the forecasting task of price movement in HFT. Our goal is to conduct a study for autonomous genetic-based models that allow the forecasting systems to self-evolve. The results show that our proposed method can improve upon the previous ones and advance the current state of Fintech research.
Web-based learning is generally a solitary process without teachers' on-the-spot assistance. In this study, a quasi-experiment was conducted to explore the effects of various combinations of Web-Based Cognitive Apprenticeship (WBCA) and Time Management (TM) on the development of students' computing skills. Three class cohorts of 124 freshmen in a one-semester course titled ‘Applied Information Technology: Data Processing' were chosen for the empirical study. They were divided into three groups: two experimental groups (G1, n=42; G2, n=40) and one control group (G3, n=42). The goal of this research is to examine the effects of WBCA, TM, and their combination on undergraduates' learning, and further develop appropriate course design and online teaching methods for both teachers and schools. The results show that students who received WBCA and TM had higher grades than those without. The authors further discuss the implications of the findings and results for online teachers and scholars.
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