Abstract
The article highlights the systemic changes in the economy which have led to shifts in scientific paradigms and theories. These changes require us to rethink the methodological level of key factors that contribute to value formation for consumers, cause-and-effect relationships that ensure the efficiency of economic processes, and seek out new productive approaches to solving the fundamental economic problem. The study examined existing scientific works and approaches in studying the influence of information-intellectual and time factors on economic processes. This showed the need for non-categorical logic in models that assess and forecast the effectiveness of decisions made by consumers and other market participants. A ternary model has been proposed to evaluate the effectiveness of the client experience, which takes into account the parameters of the situational context. This model can be implemented using a barycentric mathematical apparatus and an appropriate mathematical programming toolkit. The author's conclusions and developments were practically tested using data from leading domestic online services of the pharmaceutical market. The study focused on the influence of information and time factors on the effectiveness of the client experience and the management of marketing and commercial interactions with consumers. The study used arrays of empirical data characterizing customer service orders in pharmacies, including their implementation on the scale of Ukraine. The study established a correlation between the response time of pharmacies to customer orders and the level of payment and implementation of the latter. Appropriate coefficients have been determined, which have practical value. They guide enterprises to potentially available additional income by reducing the waiting time for customer responses regarding drugs and medical products. The study also proved the significance of the factors of the response time of pharmacy staff to customer orders, as well as the quality of work on informing the latter, in ensuring the effectiveness of the customer experience. Additionally, the price parameters of medicines and medical products, the location of pharma stores, the level of digital skills of customers in a region, and the availability of the Internet, etc. significantly affect the behavior of consumers in Ukraine
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References
[1] Filonov, V.I. (2014). Marketing and enterprise efficiency. (PhD dissertation, Kyiv National Economic University, Kyiv, Ukraine).
[2] Kahneman, D. (2017). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
[3] Taler, R. (2021). Behavioral economics. Why people act irrationally and how to benefit from it. Kyiv: Our Format.
[4] Shafaliuk, O.K. The problem of dynamics and prospects in the development of marketing and marketing research. Formation of a market economy. Institutional repository of Vadym Hetman Kyiv National Economic University, 418-430.
[5] Oleksiuk, O.I. (2008). The economics of enterprise performance. Kyiv: KNEU.
[6] Karimi, S. (2013). A purchase decision-making process model of online consumers and its influential factor a cross sector analysis. Manchester: Manchester Business School.
[7] Kotler, P., Kartajaya, H., & Setiawan, I. (2010). Marketing 3.0. From Products to Customers to the Human Spirit. Hoboken: John Willey & Sons.
[8] Kotler, P., Kartajaya, H., & Setiawan, I. (2017). Marketing 4.0. Moving from Traditional to Digital. Hoboken: John Willey & Sons.
[9] Haesevoets, T., De Cremer, D., Dierckx, K., & Van Hiel, A. (2021). Human-machine collaboration in managerial decision making. Computers in Human Behavior, 119, article number 106730. doi: 10.1016/j.chb.2021.106730.
[10] Pizoń, J., & Gola, A. (2023). Human-machine relationship-perspective and future roadmap for industry 5.0 solutions. Machines, 11(2). doi: 10.3390/machines11020203.
[11] Nisser, T., & Westin, C. (2006) Human factors challenges in unmanned aerial vehicles (uavs): A literature review. Retrieved from https://www.researchgate.net/publication/228768198_Human_factors_challenges_in_unmanned_aerial_vehicles_uavs_A_literature_review.
[12] Botha, A.P. (2019). A mind model for intelligent machine innovation using future thinking principles. Journal of Manufacturing Technology Management, 30(8), 1250-1264.
[13] Oleksiuk, O. (2015). Ternary analytical decision-making system. Economics of Development, 4, 88-93.