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{"id":22967,"date":"2026-10-07T15:55:19","date_gmt":"2026-10-07T12:55:19","guid":{"rendered":"https:\/\/modecon.mnau.edu.ua\/?p=22967"},"modified":"2026-10-07T15:55:19","modified_gmt":"2026-10-07T12:55:19","slug":"typology-of-consumer-behavior-in","status":"publish","type":"post","link":"https:\/\/modecon.mnau.edu.ua\/en\/typology-of-consumer-behavior-in\/","title":{"rendered":"Zhurylo V., Derbenova Ya. Typology of Consumer Behavior in the Context of using Artificial Intelligence in Purchasing Decisions"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]<\/p>\n\n\n\n
JEL Classification:<\/strong> D12, M31<\/span><\/i><\/td>\nDOI<\/b>: https:\/\/doi.org\/10.31521\/modecon.V58(2026)-15<\/a><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

[\/vc_column_text][vc_column_text]Zhurylo Victoria, <\/b>PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine<\/span><\/p>\n

ORCID:<\/strong> 0000-0002-9533-1923<\/span><\/a>
\ne-mail: <\/strong>vikroriazhurilo@knu.ua<\/span><\/a><\/p>\n

Derbenova Yana, <\/b>PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine<\/span><\/p>\n

ORCID:<\/strong> 0000-0003-1369-9888<\/span><\/a>
\ne-mail: <\/strong>yana.derbenova@knu.ua<\/span><\/a><\/p>\n

Typology of Consumer Behavior in the Context of using Artificial Intelligence in Purchasing Decisions<\/b><\/p>\n

Abstract. Introduction. <\/em><\/strong>The rapid development of artificial intelligence (AI) and its integration into purchasing processes are transforming traditional patterns of consumer behavior and decision-making. The increasing use of AI-based tools changes the role of consumers in the purchasing process, particularly in terms of autonomy, trust, perceived risks, and motivation. At the same time, the lack of a comprehensive classification of consumers according to their interaction with AI limits the possibilities for effective market segmentation and the development of targeted marketing strategies.<\/span><\/i><\/p>\n

Purpose<\/i><\/b>The purpose of the study is to develop a comprehensive typology of consumers who use artificial intelligence in purchasing decisions based on the integration of key behavioral and psychological characteristics. The study focuses on identifying the factors that differentiate consumer groups and determining their significance for understanding AI-assisted purchasing behavior.<\/span><\/i><\/p>\n

Results<\/i><\/b>. The methodological framework combines primary data collection through a consumer survey with methods of analysis, synthesis, and modeling. Consumer behavior was examined according to four key criteria: the level of trust in AI, intensity of AI use, perceived risks, and dominant motivational factors. Based on the identified relationships between these characteristics, consumer types were differentiated according to their patterns of interaction with AI during the purchasing process. The results demonstrate that the balance between trust in AI and perceived risks represents the principal factor differentiating consumer behavior. The proposed typology reflects differences in consumers\u2019 behavioral and psychological responses to AI-based recommendations and provides a basis for more precise market segmentation.<\/span><\/i><\/p>\n

Conclusions<\/i><\/b>. The developed typology provides a conceptual basis for understanding heterogeneous consumer behavior in the context of AI-assisted purchasing decisions. Its application enables businesses to identify consumer-specific behavioral patterns and adapt marketing strategies, communication approaches, and personalization practices accordingly. The findings contribute to the development of customer-oriented marketing strategies by linking consumer characteristics with differentiated approaches to AI-enabled interactions.<\/span><\/i><\/p>\n

Keywords<\/i><\/b>: Consumer Behavior; Typology of Consumer Behavior; Market Segmentation; Digital Marketing; Artificial Intelligence; Marketing Personalization<\/span><\/i><\/p>\n

References<\/b>:<\/strong><\/p>\n

    \n
  1. Digital Consumer Trends. (2025)\/ https:\/\/www.deloitte.com \/content\/dam\/assets-zone2\/nl\/en\/docs\/industries\/technology-media-telecommunications\/2025\/deloitte-nl-digital-consumer-trends<\/span><\/li>\n
  2. Olan, F., Suklan, J., Arakpogun, E. O., Robson, A. (2024). Advancing Consumer Behavior: The Role of Artificial Intelligence Technologies and Knowledge Sharing. IEEE Transactions on Engineering Management,\u00a0 vol. 71, 13227-13239. https:\/\/doi.org\/10.1109\/TEM.2021.3083536\/<\/span><\/li>\n
  3. Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J.\u00a0 (2019). Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing. California Management Review, 61(4), 135\u2013155. https:\/\/doi.org\/10.1177\/0008125619859317\/<\/span><\/li>\n
  4. Chen, S. H., Qiu, H., Zhao, S. F., Han, Y. Y., He, W., Siponen, M., Mou, J., & Xiao, H. (2022).When more is less: The other side of artificial intelligence recommendation. Journal of Management Science and Engineering, 7(2), 213\u2013232. https:\/\/doi.org\/10.1016\/j.jmse.2021.08.001\/<\/span><\/li>\n
  5. Rohden, S. F., & Zeferino, D. G. (2023). Recommendation agents: an analysis of consumers\u2019 risk perceptions toward artificial intelligence. Electronic Commerce Research, 23(4), 2035\u20132050. https:\/\/doi.org\/10.1007\/s10660-022-09626-9\/<\/span><\/li>\n
  6. Ilyashenko, S. M., Ilyashenko, N. S.\u00a0 (2026). Digitalization of Ukrainian Consumer Behavior. Marketing and Digital Technologies, \u21161, 57\u201371. https:\/\/mdt-opu.com.ua\/index.php\/mdt\/article\/view\/450?utm [in Ukrainian].<\/span><\/li>\n
  7. Milcheva, V., Yevtushevska, O., Antonyuk, Y., Matuzny O., Koryagin, O. (2025). Formation of consumer loyalty in digital marketing of the enterprise: behavioral and economic approach. Bulletin of Khmelnytsky National University. Economic Sciences, \u21165, 586\u2013590.\u00a0 https:\/\/doi.org\/10.31891\/2307-5740-2025-346-5-84 [in Ukrainian].<\/span><\/li>\n
  8. Plummer, J. T. (2000). How Personality Makes a Difference. Journal of Advertising Research, 40(6), 79\u201383. https:\/\/doi.org\/10.2501\/jar-40-6-79-83\/<\/span><\/li>\n
  9. Solomon, M. R. (2004). Consumer Psychology. Encyclopedia of Applied Psychology. Elsevier, 483-492. https:\/\/doi.org\/10.1016\/B0-12-657410-3\/00219-1\/<\/span><\/li>\n
  10. Belk, R. W. (1975). Situational variables and consumer behavior. Journal of Consumer Research, 2(3), 157\u2013164. https:\/\/doi.org\/10.1086\/208627<\/span><\/li>\n
  11. Booker, B. (2025) Consumer Adoption of AI Report. URL: https:\/\/www.askattest.com\/blog\/articles\/2025-consumer-adoption-of-ai-report?<\/span><\/li>\n
  12. Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961\u2013974. https:\/\/doi.org\/10.1016\/j.jbusres.2020.08.024\/.<\/span><\/li>\n<\/ol>\n

    [\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]Received: 11 August 2026<\/span><\/strong><\/p>\n

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    Zhurylo V., Derbenova Ya. (2026). Typology of Consumer Behavior in the Context of using Artificial Intelligence in Purchasing Decisions. Modern Economics, 58(2026), 121-128. DOI: https:\/\/doi.org\/10.31521\/modecon.V58(2026)-15.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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    [vc_row][vc_column][vc_column_text] JEL Classification: D12, M31 DOI: https:\/\/doi.org\/10.31521\/modecon.V58(2026)-15 [\/vc_column_text][vc_column_text]Zhurylo Victoria, PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine ORCID: 0000-0002-9533-1923 e-mail: vikroriazhurilo@knu.ua Derbenova Yana, PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine ORCID: 0000-0003-1369-9888 e-mail: yana.derbenova@knu.ua
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