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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.

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.