Marketing Decision Making by Applying the Expert System
Ključne riječi:
fuzzy logic, decision support systems, ICT, uncertaintySažetak
The main goal of this paper is to develop an expert system based on fuzzy set theory that will provide more successful and efficient decision making in the area of marketing, in relation with dilemma “to produce or to purchase”. Namely, authors will try to develop a model that will be suitable for making marketing decisions in production systems. Methodology in the paper obtained analysis of the theory of marketing, the development of the specific model for decision making, so as the application of developed model on one case from production system. Methodology which allows to model indeterminacy is fuzzy sets theory which is particularly well designed for dealing with non-probabilistic uncertainties. Authors will develop a model for decision making, based on successful integration of marketing and fuzzy theories. They will implement the model in decision making problem related to the debate “to produce or to purchase” on one real decision problem in production system. The main goal of this paper is to make changes in the work of decision makers in marketing sector. Authors pointed the advantages of the model with quality management, but also some limitations and possibilities for the future researches.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Reference
Bartel, A. P., Lach, S., Sicherman, N. (2012), “Technological change and the make-or-buy decision”, Journal of Law, Economics, and Organization, pp. 1-28.
Ćirić, Z., Stojić, D., Sedlak, O. (2015), “Multicriteria HR allocation based on hesitant fuzzy sets and possibilistic programming”, Acta Polytechnica Hungarica, Óbuda University, Hungarian Academy of Engineering and IEEE Hungary Section, Vol. 12 No. 3, pp. 185-197.
Coase, R., (1937), “The Nature of the Firm”, Economica, Vol. 4 No. 16, pp. 386-405.
Ertugrul, I, & Karakasoglu, N. (2009), “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, Vol. 36 No. 1, pp. 702–715.
Kang, H., Hung, M., Pearn, W. L., Lee, A.H. I., M. (2011), “An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance”, Energies, Vol. 4, No. 11, pp. 2002-2026.
Kosko, B. (1992), “Neural Networks and Fuzzy Systems”, Englewood Cliffs: Prentice – Hall, New Jersey.
Kotler, P. (2000), “Marketing management: The millennium edition”, Upper Saddle River, NJ: Prentice-Hall.
Maltz, A., Carter, J. R., & Maltz, E. (2011), “How managers make sourcing decisions about low cost regions: Insights from perceptual mapping”, Industrial Marketing Management, Vol 40, No. 5, pp. 796-804.
Sedlak, O., Ćirić, Z., Ćirić, I. (2013), “Strategic Management under the Conditions of Uncertainty and Indefiniteness”, Strategic Management, Vol. 18, No. 1, pp. 62-68.
Tan, X.C., Wang, Y.Y., Gu, B.H., Mu, Z.K., Yang, C. (2011), “Improved Methods for Production Manufacturing Processes in Environmentally Benign Manufacturing”, Energies, Vol. 4, No. 9, pp. 1391-1409.
Vorhies, D.W., Morgan, N.A. (2005), “Benchmarking Marketing Capabilities for Sustainable Competitive Advantage”, Journal of Marketing, Vol. 69, No. 1, pp. 80-94.
