Exploring distance learning in higher education: satisfaction and insights from Mexico, Saudi Arabia, Romania, Turkey

Miltiadis D. Lytras — 2025-02-03

Education, notably higher education, faced a significant challenge during the last period. Our data exploratory study aims to provide insights into the key factors that define students’ Distance Learning (DL) in the current period. Based on the main findings, we justify our bold proposition for the current era of distance and blended learning in Higher Education. Our research study aims to understand cultural and national differences in four countries: Mexico, Saudi Arabia, Turkey and Romania. It contributes to the theory of DL with a model of six hermeneutic factors for the satisfaction of using the DL method. It investigated and confirmed the capacity of the components to explain 60% of the DL satisfaction variance. Our research study also emphasized the interpretation of the essential findings and the drafting of bold propositions for the DL practice, emphasising academic environments. We identified significant areas of improvement, and we suggested the orchestration of combined efforts. Our research promotes the strategic deployment of DL in the current context as a resilient strategy of institutions for high-impact training and targeting of huge audiences, with emphasis on the deployment of new tools and teaching methods customized for a new, unique value proposition of the DL.

Multifractal analysis of Bitcoin price dynamics

Cristian Bucur — 2025-02-03

This research employs Multifractal Detrended Fluctuation Analysis (MFDFA) to investigate multifractal properties in financial variables, including Bitcoin prices and economic indicators. Spanning 2019–2022, the analysis reveals multifractal scaling not only in Bitcoin prices, but also in economic indicators such as inflation rates and energy commodity prices. The non-linear singularity spectra unveil the multifaceted nature of scaling properties. Temporal analysis exposes intriguing trends in multifractality with implications for market efficiency. Furthermore, correlation analysis unveils connections among multifractal properties. For instance, a positive correlation between oil prices and Bitcoin suggests similar market forces. The log-log plot of fluctuation function F_q versus lag size demonstrates a power-law relationship, characteristic of multifractal systems. The empirical data’s alignment in log-log space suggests self-similarity in the Bitcoin time series, supporting multifractality. The calculated Hurst exponents values suggest varying degrees of multifractality across the years, with 2021 exhibiting the highest degree and 2022 the lowest. Furthermore, an asymmetry index (0.5767) deviating from 0.5 indicates that the multifractal nature of the Bitcoin market is not symmetric. This research enhances risk assessment and portfolio optimization in finance. It challenges the Efficient Market Hypothesis (EMH), emphasizing the significance of MFDFA in comprehending financial market and economic factor’s relationships.

Journal of Business Economics and Management

Exploring distance learning in higher education: satisfaction and insights from Mexico, Saudi Arabia, Romania, Turkey

Multifractal analysis of Bitcoin price dynamics