D83 - Search; Learning; Information and Knowledge; Communication; Belief; UnawarenessReturn

Nowadays, consumers can find basic information about a wide range of offers with almost no effort. For example, Internet sites give information about second-hand cars regarding the mark, age, price, engine type/size and distance travelled. This information suffices to assess whether a car is potentially attractive, but is not sufficient to make a final decision. The authors have developed an automatic procedure for selecting a shortlist of offers that aims to maximize a weighted average of the attractiveness and diversity of the offers on the shortlist. The consumer determines the number of offers to be placed on the shortlist and the relative importance of the traits considered. The authors have compared the results obtained by applying two methods of multicriteria assessment.

This paper examines the impact of students’ gender on management education evaluation. The paper aims to test and identify the influence of gender in higher education on selected factors impacting evaluation of management education by university students and to evaluate its development. The areas of influence have been analysed using characteristics of evaluation of management lessons, teachers and subjects. Data for this primary research was gathered using a questionnaire survey administered to business university students in the period between 2015 to 2018. Results show that the number of higher educated women is increasing and their evaluation of management subjects, teachers and lessons is different compared to men. Specific factors impacting evaluation of management education and their development are further tested and discussed. The results may be used in practice to identify current approaches towards higher education by students´ gender preferences. Limitation of the findings of this study is that its application may be impacted because the sample size was limited to business university students. It may be taken as a case study and a base for further research and benchmarking between universities.

This article deals with the creation of knowledge base in Expert System NEST, which is classified into the group of empty Expert Systems. It will be mention area of Expert Systems, including advantages and disadvantages of these systems. It also indicated their possible use. This is followed by a description of the Expert System NEST and its possibilities of knowledge representation method for creating a knowledge base. The practical part of this paper is focused on creating knowledge base in Expert System NEST for assessing the Lean Manufacturing. This section provides examples of creating a knowledge base for assessing the implementation of the principles of Lean Manufacturing, including output from NEST editor module, consultation module and final evaluation of the degree of Lean Manufacturing by Expert System.