How to reduce the number of rating scale items without predictability loss?

Rating scales are used to elicit data about qualitative entities (e.g., research collaboration). This study presents an innovative method for reducing the number of rating scale items without the predictability loss. The "area under the receiver operator curve method" (AUC ROC) is used. The presented method has reduced the number of rating scale items (variables) to 28.57\% (from 21 to 6) making over 70\% of collected data unnecessary. Results have been verified by two methods of analysis: Graded Response Model (GRM) and Confirmatory Factor Analysis (CFA). GRM revealed that the new method differentiates observations of high and middle scores. CFA proved that the reliability of the rating scale has not deteriorated by the scale item reduction. Both statistical analysis evidenced usefulness of the AUC ROC reduction method.Comment: 14 pages, 5 figure

Publikacje a zgłoszenia ewaluacyjne, czyli zniekształcony obraz nauki w Polsce

The article discusses the consequences of the practice of double-counting publications in the Polish research evaluation system, i.e. in the Comprehensive Evaluation of Scientific Units that was conducted in 2013. Our study examines 139 top ranked journals indexed in the Web of Science™ Core Collection in which Polish scholars published in 2009-2012. We analyzed 1788 publications (both citable and non-citable items) and their corresponding “evaluation items” (zgłoszenia ewaluacyjne: a formal category within the Polish research evaluation system) in terms of the number of authors per paper. We found that 42.4% (N = 789) of these publications were submitted for evaluation and generated 1036 evaluation items. 759 of the analyzed publications (94.8%) were written by more than one author and thus generated multiple evaluation items (approximately 1.3 evaluation items per paper). Our findings show that this way of publication counting plays a major role in constructing the image of productivity of Polish scholars. The article concludes with a discussion of the consequences of double-counting and argues for a need to maintain a balance between all groups of sciences

Enhancing Managerial Decision-Making Through Multicriteria Modeling

The monograph constitutes a crowning of research led in the field of particular methodology of management science, in the field of enhancing managerial decision-making sub-discipline in frames of the practical stream of the management science discipline. The monograph is a development of the research project in which the elaboration of a scientific method for the enhancement of managerial decision-making processes through the Modular Multicriteria Managerial Decision-Making Model (MMUMADEMM) has been proposed