Tools of Decision Making in the Field of Strategic Advertisement of Pharmaceutical Enterprises

B.V. Burkynskyi; Z.M. Sokolovska; O.B.  Alyokhin; N.I. Khumarova; I.V. Kapustyan

doi:10.15407/scine16.02.018

Authors

B.V. Burkynskyi Institute of Market Problems and Economic-Ecological Research, the NAS of Ukraine
Z.M. Sokolovska Odesa National Polytechnic University
O.B. Alyokhin Odesa National Polytechnic University
N.I. Khumarova Institute of Market Problems and Economic-Ecological Research, the NAS of Ukraine
I.V. Kapustyan Odesa National Polytechnic University

DOI:

https://doi.org/10.15407/scine16.02.018

Keywords:

advertising strategy, model-simulator, pharmaceutical enterprise, simulation experiments, simulation modeling

Abstract

Introduction. The evolution of the modern information and communication technologies contributes to enhancement of advertising strategies, as effective tools of pharmaceutical marketing.
Problem Statement. The need to take into account the nonlinear dynamic nature of advertising processes and presence the influence of numerous stochastic factors in market environment of pharmaceutical enterprises with the impossibility of obtaining an unambiguous analytical solution put forward problem of attracting a special mathematical apparatus for research.
Purpose. To study processes of decision-making in the field of strategic advertising of pharmaceutical enterprises using the apparatus of simulation modeling.
Materials and Methods. The research is based on using multi approach paradigm of simulation in the software environment of AnyLogic. The materials of pharmaceutical company OJSC "Farmak" are used in the course of simulation experiments.
Results. The expediency of attracting modeling methods as tools of making strategic advertising decisions is substantiated. A simulation model-simulator is proposed, developed using a combination of Agent and System-Dynamic approaches on the AnyLogic software platform. The decision-making process is illustrated by the results of various types of simulation experiments. The main areas of use the simulator: monitoring and predicting the reaction of target audiences to product advertising; effectiveness control of research on new and re-releasing existing medicines in response to market reactions and preferences of potential clients; optimization of advertising budget with justification of expediency of its redistribution between original and generic preparations.
Conclusions. The efficiency of using simulation models-simulators as tools for the formation of advertising strategies has been proved. The development can be recommended for implementation by pharmaceutical companies.

References

Shabelnyk, T. V. (2016). Models of marketing-oriented management of the pharmaceutical enterprise. (Doctoral dissertation). Poltava. [in Ukrainian].

Melnik, I. M., Holysheva, E. O. (2017). Features of marketing complex in the system of innovative development of pharmaceutical enterprises. Marketing and Management of Innovations, 4, 27-40 [in Ukrainian].

https://doi.org/10.21272/mmi.2017.4-02

Jekunen, A. (2014). Decision-making in product portfolios of pharmaceutical research and development - managing streams of innovation in highly regulated markets. Drug Design, Development and Therapy, 8, 2009-2016.

https://doi.org/10.2147/DDDT.S68579

Jones, C. M. (2016). Managing Pharmaceutical Research And Development Portfolios: An Empirical Inquiry Into Managerial Decision Making In The Context Of A Merger. (Doctoral dissertation). Georgia State University.

Solo, K., Paich, M. A. (2003). Modern Simulation Approach for Pharmaceutical Portfolio Management.

URL: https://www.anylogic.ru/upload/iblock/6d4/6d45074aefb2d023be20115ec9c773.

(Last accessed: 23.02.2019).

Kalotra, A. (2014). Marketing strategies of different pharmaceutical companies. Journal of Drug Delivery & Therapeutics, 4 (2), 64-71.

https://doi.org/10.22270/jddt.v4i2.771

Zerbini, C., Luceri, B., Vergura, D. (2017). Leveraging consumer's behaviour to promote generic drugs in Italy. Health Policy, 121(4), 397-406.

https://doi.org/10.1016/j.healthpol.2017.01.008

Pujari, N. M., Sachan, A. K., Kumari, P., Dubey, P. (2016). Study of Consumer's Pharmaceutical Buying Behavior Towards Prescription and Non-Prescription Drugs. Journal of Medical and Health Research, 1(3), 10-18.

Biswas, K., Ferdousy, U. K. (2016). Influence of Pharmaceutical Marketing on Prescription Behavior of Physicians: A Cross-sectional Study in Bangladesh. Journal of Accounting & Marketing, 5(2), 1-4.

https://doi.org/10.4172/2168-9601.1000160

Costea, D., Carter, F., Chou, S.-Y., King, A. (2012). Is Advertising Effective or Not? Evidence from the Pharmaceutical Market. NMIMS Management Review, 12, 9-28.

Lewis, A., Rao, J. M. (2015). The unfavorable economics of measuring the returns to advertising. The Quarterly Journal of Economics, 1941-1973.

https://doi.org/10.1093/qje/qjv023

Aspara, J., Chakravarti, A. (2015). Investors' reactions to company advertisements: the persuasive effect of product-featuring ads. European Journal of Marketing, 49(5/6), 943-967.

https://doi.org/10.1108/EJM-11-2013-0661

Lutoshkin, I. V., Iamaltdinova, N. R. (2016). The existence of a solution to the problem of managing advertising expenses with distributed delay. The Bulletin of Irkutsk State University, 18, 48−59 [in Russian].

Huang, J., Leng, M., Liang, L. (2012). Recent Developments in Dynamic Advertising. European Journal of Operational Research, 220(3), 591-609.

https://doi.org/10.1016/j.ejor.2012.02.031

Ahmed, R. R., Vveinhardt, J., Streimikiene, D., Awais, M. (2016). Mediating and marketing factors influence the prescription behavior of physicians: An empirical investigation. Amfiteatru Economic, 18(41), 153-167.

Avagyan, V., Landsman, V., Stremersch, S. (2017). Marketing models for the life sciences industry. International Series in Operations Research and Management Science, 254, 385-430.

https://doi.org/10.1007/978-3-319-56941-3_13

Bardey, D., Bommier, A., Jullien, B. (2010). Retail price regulation and innovation: Reference pricing in the pharmaceutical industry. Journal of Health Economics, 29(2), 303-316.

https://doi.org/10.1016/j.jhealeco.2009.11.015

Leeflang, P. S. H., Wieringa, J. E. (2010). Modeling the effects of pharmaceutical marketing. Marketing Letters, 21(2), 121-133.

https://doi.org/10.1007/s11002-009-9092-3

Berezovskaia, E. A., Plotnikov, C. A. (2015). Simulation of an advertising campaign the Internet-enterprise in the environment of AnyLogic. International Scientific Journal, 9, 86-90 [in Russian].

Katalevskii, D. Y., Solodov, V. V., Kravchenko, K. K. (2012). Modeling of consumer behavior. Artificial societies, 7(1/4), 34–59 [in Russian].

Pesikov, E. B. (2003). Estimation of efficiency and degree of marketing strategies risk of the enterprise on the simulation modeling basis. The Practice of Simulation Modeling (IMMOD-2003), 2, 110–115 [in Russian].

Winter Simulation Conference.

URL: http://meetings2.informs.org/wordpress/wsc2018/ (Last accessed 11.02.2019).

The 36th International Conference of the System Dynamics Society.

URL: https://www.systemdynamics.org/past-conference-2018 (Last accessed 13.02.2019).

Arbeitsgemeinschaft Simulation.

URL: https://www.asim-gi.org/asim/ (Last accessed 12.02.2019).

Eighth All-Russian Scientific and Practical Conference "Simulation modeling. Theory and practice" IMMOD-2017.

URL: http://simulation.su/static/ru-immod-2017.html (Last accessed 11.02.2019).

Proceedings from “The Federation of European Simulation Societies”.

URL: https://www.eurosim.info/eurosim/ (Last accessed 15.02.2019).

Offical Site of AnyLogic Company

URL: http://www.anylogic.com/ (Last accessed 11.12.2018).