ENGLISH VERSION

Dr Barbara Wąsikowska is an Assistant Professor in the Institute of IT in Management of Economy at the Faculty of Economics and Management of the University of Szczecin. She specializes in methods of Artificial Intelligence and Neuroscience. She has published articles in Selected Issues of Experimental Economics, Computational and Mathematical Methods in Medicine, Business Informatics: Concepts and Applications, Studia Informatica, Selected Issues of Data Analysis. Her foregoing research, that resulted in over 40 publications, concentrated mainly on applications of artificial intelligence (especially the rough set theory) and techniques of cognitive neuroscience in economy and management.


Projects

In recent years research of dr Barbara Wąsikowska concentrated mainly on following topics:

  1. Brain neuroimaging methods in the research of decision making process in management;
  2. Application of cognitive neuroscience techniques to study consumer preferences;
  3. The study of advertising content with application of EEG;
  4. Eye tracking in marketing research;
  5. Application of rough set theory to identification purchase behavior rules;
  6. Examining male and female purchase preferences by means of rough set method.

Research plans for the nearest future include the continuation of the above topics.


Descriptions of projects:

 Ad 1.

At the end of forties and the beginning of the fifties of the 20th century the second cognitive revolution took place. It contributed directly to the coming into existence of the cognitive psychology, to the development of neuroscience and the birth of cognitive neuroscience. Then the rapid development of brain neuroimaging methods took place. Economists became interested in the cognitive revolution in the second half of the nineties. New fields of study appeared, such as neuroeconomics, neuromangement and neuromarketing. The aim of this study was to become acquainted with the subject of neuromanagement and to make a review of selected methods of brain neuroimaging applied in management, i.e. functional magnetic resonance imaging and electroencephalography.

Ad 2.

Cognitive neuroscience is an interdisciplinary area of study that has emerged from many other fields, most significantly neuroscience, psychology, mathematics, physics and other sciences, which include studies of mind in their programs. During the last three decades the neuroscience rapidly developed what is a simple consequence of the development of new techniques for examining the brain. These techniques allowed to observe the brain during the work and to search for links between his states and states of the mind. Other fields became interested in ideas developed by the cognitive neuroscience and created another interdisciplinary areas of research, such as: neurophilosophy, neurolinguistics, neuroeconomics and neuromarketing. The aim of this study was to analyze the possibility of application of basic cognitive neuroscience methods to study consumer preferences.

 Ad 3.

The character and form of the commercial message have a decisive influence on its reception by potential clients. The appropriate preparation of advertising spots and all promotional materials significantly increases the chances of its positive receipt and arouse consumer interest in a product or service. The study of advertising content and its influence can be carried out with using different research methods. This research applied one of the modern approaches to analysis of advertising contents, i.e. the electroencephalography (EEG). The primary objective of the study was to identify features which should be characteristic of an advertisement answering the current situation on the market and meeting the expectations of the customer.

Ad 4.

Eye tracking is a technique developed over a hundred years ago for the purposes of such sciences as psychology and medicine. In recent years, however, it has found a wide application in economics and management. In the study the eye tracker way of working and methods of analysis and presentations of data acquired during this kind of research were analyzed. There were also reviewed examples of this technique applications in marketing research.

Ad 5.

The research was focused on the data analysis concerning purchase preferences of men and women. The main emphasis is put on the method which was used in the research – the rough set theory. This method was applied to identify rules of consumer buying behavior. The received results allow conclusion that the used method of artificial intelligence i.e. rough set method can be successfully used in practice as an effective tool for this type of data analysis. The created basis of purchase preferences rules for men and women can be used as a base of knowledge for companies producing cellular phones and accessories and can be a direction showing what this two groups of consumers pay attention to while buying products offered by these companies.

Ad 6.

The aim of the research was to check if while buying electrical appliances the surveyed respondents paid attention to the high safety standards of the goods they bought. In the research there were verified the view that the application of the rough set theory to the analysis of marketing data may pose a significant supplement for cognitive examinations carried out using traditional methods.


Publications

  1. Wąsikowska B., Sobecka E., Bielat I., Legierko M., Więcaszek B.: A Novel Method for Predicting Anisakid Nematode Infection of Cod Raw Materials Using Rough Set Theory, Journal of Food Protection, Vol. 81. No. 3, 2018, pp. 502-508 doi:10.4315/0362-028X.JFP-17-371.
  2. Wawrzyniak A., Wąsikowska B.: The Study of Advertising Content with Application of EEG, [w:] Selected Issues of Experimental Economics, Nermend, M. Łatuszyńska (red.), Springer Proceedings in Business and Economics, Springer International Publishing AG, 2016 r., pp. 333-353. (http://link.springer.com/chapter/10.1007/978-3-319-28419-4_21).
  3. Vecchiato G., Maglione A., Cherubino P., Wasikowska B., Wawrzyniak A., Latuszynska A., Latuszynska M., Nermend K., Graziani I., Leucci M., Trettel A., Babiloni :  Neuropsychological Tools to Investigate Consumer’s Gender Differences during the Observation of TV Commercials, Computational and Mathematical Methods in Medicine  07/2014. Volume 2014 (2014), Article ID 912981, pp. 1-12.
  4. Wąsikowska B.:  The application of eye tracking in business [w:] Social Aspects of Business Informatics: Concepts and Applications Marciniak, M. Morzy (red.), Wydawnictwo Nakom, Poznań 2014 r., pp. 71-86.
  5. Wąsikowska B.:  Contemporary data exploration technologies in marketing, Studia Informatica: Computer Science – Methods, Models, Applications nr 32, 2013 r., pp. 137-149.
  6. Policastro P. Wawrzyniak A., Wąsikowska B.: Artificial Intelligence Application to Legal Studies and Training of Legal professions: Some Reflections for a Syllabus, [w: ] Towards Innovation in Legal Education, P. Policastro (red.), Eleven International Publishing  (publication info), Holandia 2013 r., pp. 109-118.
  7. Nermend K., Shihab A., Wąsikowska B.:  The utility of local government websites by using web tracking system and user assessmant, Zeszyty Naukowe Uniwersytetu Szczecińskiego nr 781, Ekonomiczne problemy usług nr 106, „E-gospodarka, problemy, metody, aplikacje”, Szczecin 2013 r., pp. 293-305.
  8. Nermend K., Wąsikowska B., Shihab A.:  The application of web-tracking method for research of local government units’ websites utility, [in] Proceedings of the International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government EEE’13, (red.) Hamid R. Arabnia, Azita Bahrami, Fernando G. Tinetti, WORLDCOMP’13 Las Vegas Nevada USA 2013, pp.327-336.
  9. Łatuszyńska M., Wawrzyniak A., Wąsikowska B., Furaiji F.:  Study On The Influcence Of Advertising Attractiveness On The Purchase Decisions Of Women And Men, Journal of International Studies, 2013, Vol. 6 No 2, pp. 20-32.
  10. Wąsikowska B., Furaiji F.:  Examining Male and Female Purchase Preferences by Means of Rough Set Method, rozdział 7 [in] „Selected Issues of Data Analysis”, Polish Information Processing Society, [ed] M.Łatuszyńska, K.Nermend, Szczecin 2012 r., pp. 97-110.
  11. Korzeń M., Piegat A., Wąsikowska B.:  Differences between the method of mini-models and the k-nearest neighbors on example of modeling of unemployment rate in Poland, Systemy Informatyczne w Zarządzaniu”, SGGW, WULS Press, 2011 r., pp. 34-43.
  12. Wąsikowska B.:  Application of Rough Sets for Identyfication of Factors Determining Sold Production of Industry, Polish Journal of Environmental Studies. Vol. 16, No 4A, Olsztyn 2007 r., pp. 372-375.

Contact

dr Barbara Wąsikowska

University of Szczecin
Faculty of Economics and Management

ul. Mickiewicza 64
71-101 Szczecin

POLAND

e-mail: barbara.wasikowska@usz.edu.pl