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In short-term forecasting of day-ahead electricity prices, incorporating intraday dependencies is vital for accurate predictions. However, it quickly leads to dimensionality problems, i.e. ill-defined models with too many parameters, which require an adequate remedy. This study addresses this issue.

In an application for the German/Austrian market, this study derives variable importance scores from a random forest algorithm, feeds the identified variables into a support vector machine and compares the resulting forecasting technique to other approaches (such as dynamic factor models, penalized regressions or Bayesian shrinkage) that are commonly used to resolve dimensionality problems.

This study develops full importance profiles stating which hours of which past days have the highest predictive power for specific hours in the future. Using the profile information in the forecasting setup leads to very promising results compared to the alternatives. Furthermore, the importance profiles provide a possible explanation why some forecasting methods are more accurate for certain hours of the day than others. They also help to explain why simple forecast combination schemes tend to outperform the full battery of models considered in the comprehensive comparative study.

With the information contained in the variable importance scores and the results of the extensive model comparison, this study essentially provides guidelines for variable and model selection in future electricity market research.

Research shows that there are mechanisms of information simplification that lead to the danger that first, laypeople rely on their own epistemological skills when assessing scientific claims. Second, laypeople underestimate their dependence on experts when they receive simplified information. This underestimation can be problematic because scientific knowledge, due to its complexity, usually cannot be fully understood without further advice from experts. Compared to laypersons, adult education practitioners can be expected to have a higher level of scientific literacy in relation to knowledge in their professional field because they are familiar with the structure of knowledge through their formal education. The present study examines whether the “easiness effect” also occurs in adult education practitioners when they read simplified and highly simplified texts about research findings.

The sample consisted of 1.267 continuing education institutions. For the survey experiment, particioants were randomly assigned to tree text types at the end of the survey: easy, less scientific and scientific text. We used the difference-in-difference method to analyze the data.

The study examined whether easily presented research findings influenced self-assessment and reliance on experts. The results of our study support the hypothesis that the easiness effect is also present among professional practitioners.

The use of clear and nontechnical language is essential for ensuring that scientific knowledge is accessible and utilizable outside of academic circles. This aspect gains particular significance in educational research, as it enables professional practitioners to comprehend and ideally implement, research findings in their daily routines to address and resolve real-world challenges in their educational environments. Previous studies have demonstrated that the way text is presented influences laypeople's perceived reliance on experts. Building upon the conceptual framework of the easiness effect, this survey experiment took an additional step by focusing specifically on a targeted audience: professional practitioners in adult education.

In this study, we investigated the dilemma of devising an operational family business definition in the SME context. The existing family business literature mostly agrees with the validity of a theoretical model called F-PEC, which identifies family businesses by evaluating three dimensions: power, experience, and culture. Nonetheless, empirical studies on family SMEs still use just one or a few elements with many different thresholds to operationally define family SMEs, highlighting an unsolved definitional divergence among scholars, which limits the possibility of investigating the potential effects of family attributes on firms’ goals, structures, processes, and performance.

Employing ancestry searching, online databases, and issue-by-issue searches from two decades (1990–2019), we analyzed 255 empirical studies that specified a family business’s operational definition (despite posing different research questions) and used a sample of small-sized and medium-sized enterprises (SMEs).

Results showed ownership and governance/management are the most used elements in the operational definitions provided in the literature to date, but that there still is not a universally adopted operational definition of family SMEs in use today.

This paper is one of the first to comprehensively analyze and review the operationalized use of family SME definitions in the literature.