Abstract and keywords
Abstract (English):
In e-commerce, profit depends on both quantitative and qualitative indicators - Internet services and their quality, trends in market size, fluctuations in business activity depending on the season, customer inflows and their outflows, product costs. All of these indicators have fuzzy descriptions. E-commerce is a dynamic segment of economic activity. Despite the general principles of marketing, this direction has a number of unique opportunities. The main focus of e-commerce is the sale of services and goods using the Internet. At the same time, the possibilities of e-commerce are very diverse. In this article, we will consider one of the possibilities - an online store. This is a software product that is designed as a Web site, which is further used as a platform for shopping and selling goods. This article discusses using the fuzzy logic apparatus to build an e-commerce model and evaluate alternatives. The statement of the problem is as follows: with many alternatives, we have outcomes: in the case of certainty, one, and with uncertainty, perhaps a certain number of options. Each specific outcome is characterized by a certain state that the object will have after implementing the alternative described by the efficiency criterion that determines the value of the outcome preference indicator. It is necessary to determine the strategy for choosing the most preferable alternative, corresponding to the performance indicator.

Keywords:
E-commerce, fuzzy logic, alternative, outcome, performance criteria.
Text

ВВЕДЕНИЕ

Для повышения эффективности управленческих решений при координации экономического развития большинство предприятий организовывают свою деятельность, используя научные исследования, внедряя бизнес-планирование и создаваемое программное обеспечение, реализующее инновационные разработки. В настоящее время возрастает спрос на информацию, содержащую экономические и финансовые данные, а также на исследования в сфере рыночных услуг.

Для создания программной продукции в сфере экономики в настоящее время все чаше используются алгоритмы на основе нечеткой логики при прогнозировании и моделировании явлений происходящих в этой сфере. Это обеспечивает принятие экономически грамотных решений как собственникам фирм и руководителям предприятий, так и менеджерам.

References

1. Heaton J. Fuzzy Logic in R // Forecasting & Futurism. 2014. № 9. S. 35-38.

2. YAGER R. R., ZADEH L. A. (Eds.) Fuzzy sets, neural networks and Soft Computing // VAN Nostrand Reinhold. New York. 1994. P. 440.

3. ALIEV R. A. Teoriya intellektual'nyh sistem i ee primenenie / R. A. Aliev, R. R. Aliev. Baku: Chashyogly, 2001.

4. BEKMURATOV T. F., MUKHAMEDIEVA D. T. Decision-making problem in poorly formalized processes // Proc. of the 5th World conf. on intelligent systems for industrial automation, Tashkent (Uzbekistan), Nov. 25−27, 2008. Tashkent: b-Quadrat Verlag, 2008. R. 214−218.

5. Aliev F.A., Niftiyev A.A., Zeynalov J.I., Optimal Synthesis problem for the fuzzy systems in semi-infinite interval, Applied and Computational Mathematics, 2011, Vol.10, No.1, pp.97-105.

6. Obrosova, N. K.; Shananin, A. A. Production model in the conditions of unstable demand taking into account the influence of trading infrastructure: ergodicity and its application. Comput. Math. Math. Phys. 55 (2015), no. 4, 699-723.

7. Lebedeva, M. E. Nechetkaya logika v ekonomike - formirovanie novogo napravleniya // Idei i idealy. 2019. №1-1. URL: https://cyberleninka.ru/article/n/nechetkaya-logika-v-ekonomike-formirovanie-novogo-napravleniya


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