Burkovska Anna, PhD (Economics), Associate Professor of the Department of Management, Business and Administration, Mykolayiv National Agrarian University, Mykolayiv, Ukraine

ORCID: 0000-0003-0563-6967
e-mail: anna.burkovskaya12@gmail.com

Mathematical Modeling of the Probability of Chicken Meat Purchase Based on Narrative Semantics Theory

Abstract. Introduction. Consumer purchase decisions in the food market are increasingly influenced by narratives surrounding product quality, sustainability, and trust. In particular, narratives based on sustainable development, health, and ethical food production have become central in shaping attitudes toward meat consumption. Chicken meat, as a widely consumed protein source, presents a compelling case for understanding how narrative semantics affects consumer behavior. Mathematical modeling offers a systematic approach to quantify the probability of purchase decisions, integrating both rational and emotionally-driven factors that guide consumer choices.

Purpose. The purpose of this research is to develop and test a mathematical model that estimates the probability of chicken meat purchase based on narrative semantics theory. The study aims to identify key narrative factors, such as trust, perceived product value, and sustainability messaging, and quantify their influence on consumer decision-making. Additionally, the research seeks to provide a practical framework for marketers and producers to optimize narrative strategies in promoting poultry products.

Results. The findings of the study confirm that narrative-semantic factors embedded in product labeling have a significant impact on consumer purchase decisions. The proposed logistic model demonstrates a clear nonlinear relationship between the Narrative Semantic Score (NSS) and purchase probability, where higher NSS values lead to substantially increased likelihood of purchase. The findings further reveal a synergistic effect, whereby the combination of sustainability, language, and script cues produces the highest probabilities of purchase.

Conclusions. Mathematical modeling of narrative influence provides valuable insights into consumer behavior in the poultry market. The adoption of narrative-informed marketing strategies can increase consumer engagement, trust, and purchase likelihood, contributing to both market growth and the promotion of sustainable consumption patterns. Future research may extend this model to other food products. 

Keywords: narrative semantics, consumer behavior, probability of purchase, mathematical modeling, sustainable food marketing.

References:

1. OpenAI. (2024). Sora (text-to-video model). URL: https://openai.com/sora (Retrieved April 9, 2026).
2. Burkovska, A., & Burkovska, A. (2025). Semantic approach to food marketing: the influence of sustainable development narratives on the Ukrainian market. Agricultural and Resource Economics International Scientific E-Journal, 11(1). https://doi.org/10.51599/are.2025.11.01.12.
3. Vrtana, D., & Duricova, L. (2026). Generational and Economic Differences in the Effectiveness of product Placement: A Predictive approach using CART analysis. Administrative Sciences, 16(2), 61. https://doi.org/10.3390/admsci16020061.
4. Li, Q., Hadj-Hamou, K., & Rekik, Y. (2025). Blockchain traceability valuation for perishable agricultural products: Balancing economic benefit and social impact. Transportation Research Part E Logistics and Transportation Review, 206, 104546. https://doi.org/10.1016/j.tre.2025.104546.
5. Bou-Hamad, I. (2026). Understanding consumer behavior in Lebanon’s polycrisis: The role of ethnocentrism, coping ability, and socioeconomic status. PLoS ONE, 21(2), e0341265. https://doi.org/10.1371/journal.pone.0341265.
6. Saravanan, M., Thamilmani, R., Vesna, J. L., & Sundaram, K. K. (2026). From Likes to Buys: Understanding the relationship between social media influences and online purchase decisions among young generation. In Studies in systems, decision and control (pp. 331–343). https://doi.org/10.1007/978-3-032-02056-7_27.
7. Prasad, V. K., Dansana, D., Kumar, D. A., Panda, S. K., & Bhoi, T. (2026). Optimizing Ad Campaigns: A Deep Dive into Machine Learning Strategies for Advertising Agencies. In Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (pp. 3–14). https://doi.org/10.1007/978-3-032-13009-9_1.
8. Rangel-Quinonez, H. S., Vecchio, R., & Arenas-Estevez, L. F. (2025). Impact of new octagonal front-of-pack labeling on purchasing probability of processed and ultra-processed foods in Colombia. Food Quality and Preference, 133, 105640. https://doi.org/10.1016/j.foodqual.2025.105640.
9. Feng, S., & Liu, J. (2025). Exclusive product strategies that Brick-and-Mortar retailers can use to address the showrooming effect. Mathematics, 13(24), 3924. https://doi.org/10.3390/math13243924.
10. Li, Y., Deng, X., & Wu, B. (2025). The Impact of Mobile Advertising Cue Types on Consumer Response Behaviors: Evidence from a Field Experiment. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 244. https://doi.org/10.3390/jtaer20030244.
11. Malheiros, B. A., Spers, E. E., Castillo, C. J. C., Aroeira, C. N., & De Lima, L. M. (2025). The role of visual attention and quality cues in consumer purchase decisions for fresh and cooked beef: an Eye-Tracking study. Applied Sciences, 15(13), 7360. https://doi.org/10.3390/app15137360.
12. Hoque, M. A., Akter, S., Hafiz, R., & Hoque, I. (2025). Food Marketing through Social Media Influencers: The Impact on Millennial Consumers’ Purchase Intentions. Asian Journal of Business and Accounting, 18(1), 1–40. https://doi.org/10.22452/ajba.vol18no1.1.
13. Asawawibul, S., Phakawan, J., Photisuwan, S., Chanadang, S., & Wannasawad, K. (2025). The Assessment of Customer Behavior, Intention and Preference of Bamboo Shoot-processed Food from Small and Medium Enterprises Products, Prachinburi, Thailand. Research on World Agricultural Economy, 491–507. https://doi.org/10.36956/rwae.v6i1.1518. 
14. World Population Review (2026). Mykolaiv. Available at: https://worldpopulationreview.com/cities/ukraine/mykolaiv