EFECTO DE LOS SESGOS DE PERCEPCIÓN DEL PRODUCTO SOBRE EL MODELO DE UTILIDAD DEL CONSUMIDOR

Alvaro N. Chiguano-Velasco; Marcelo V. Luna-Murillo

doi:10.37135/kai.03.15.04

Authors

Alvaro N. Chiguano-Velasco Universidad Estatal Amazónica, Puyo, Ecuador https://orcid.org/0000-0002-7651-9728
Marcelo V. Luna-Murillo Universidad Estatal Amazónica, Puyo, Ecuador https://orcid.org/0000-0002-9521-353X

DOI:

https://doi.org/10.37135/kai.03.15.04

Keywords:

Market, perception, budget, model, consumption, brand

Abstract

Social perception and quality biases alter consumer utility, modifying their decisions regarding substitute goods. This study models this distortion through a utility function incorporating a bias factor, evaluated in parallel with a neural network trained on experimental data. The mathematical model achieves high accuracy, like the neural network, confirming its explanatory power. The results show that perception influences optimal choice as much as price or income, causing shifts in the utility function along the budget constraint, as consumer preferences shift toward the good enjoying better social perception. It is concluded that integrating psychological factors into classical models is essential for understanding markets driven by reputation.

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References

Bischi, G. I., & Tramontana, F. (2024). An evolutive model of a boundedly rational consumer with changing preferences and reference group consumption. Annals of Operations Research, 337(3), 891–912. https://doi.org/10.1007/S10479-024-05885-X/FIGURES/6

Calle, M., & Pilozo, D. (2022). Efectos de la influencia social y la calidad percibida en la intención de compra de productos nacionales. Compendium: Cuadernos de Economía y Administración, 9(2), 177. https://doi.org/10.46677/COMPENDIUM.V9I2.1055

Camerer, C., Loewenstein, G., & Rabin, M. (2004). Advances of behavioral Economics. Russell Sage Foundation.

Dirwan, D., & Latief, F. (2023). Understanding the Psychology Behind Consumer Behavior. Advances in Business & Industrial Marketing Research, 1(3), 130–145. https://doi.org/10.60079/ABIM.V1I3.201

Geng, S., Liu, F., Gong, M., Wu, T., & Li, Y. (2024). Applying Deep Learning Models to Consumer Choice Theory in Western Economics: A Case Study on Consumer Preference Prediction. Advances in Economics, Business and Management Research, 436–446. https://doi.org/10.2991/978-94-6463-598-0_44

Gershman, S., & Ullman, T. (2023). Causal implicatures from correlational statements. PLOS ONE, 18(5), e0286067. https://doi.org/10.1371/journal.pone.0286067

Han, Y., Pereira, F., Ben-Akiva, M., & Zegras, C. (2022). A neural-embedded discrete choice model: Learning taste representation with strengthened interpretability. Transportation Research Part B: Methodological, 163, 166–186. https://doi.org/10.1016/J.TRB.2022.07.001

Jiménez, M. C., & Castañeda, E. L. (2018). Estimación de la función de utilidad del consumidor ecuatoriano en el año 2012. Boletín de Coyuntura, 16, 4–6. https://doi.org/10.31164/bcoyu.16.2018.658

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 143–172. https://doi.org/10.2307/1914185

Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: The endowment effect, loss aversion, and status quo bias. Journal of Economic Perspectives, 5(1), 193–206. https://doi.org/10.1257/jep.5.1.193

Khoder, K. M. (2024). The Evolution of the Utility Function: Enhancing Economic Rationality and Improving the Objectivity of Microeconomic Analysis Tools. Library Progress International, 44(3), 19938–19946. https://doi.org/10.48165/BAPAS.2024.44.2.1

Lahiri, S. (2024). Budget-constrained Maximization of “Cobb-Douglas with Linear Components” Utility Function. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4691629

Molina, S. P., & Altamirano, K. G. (2022). Estrategias de marketing en redes sociales: Influencia en el comportamiento del consumidor. Revista Científica Kosmos, 1(1), 4–14. https://doi.org/10.62943/RCK.V1N1.2022.35

Muñoz, S., Quinaluisa, N., Cadena, D., & Romero, C. (2023). El impacto del posicionamiento de marca en las decisiones de compra de los consumidores. Journal of Science and Research. https://doi.org/10.5281/ZENODO.10573508

Palacios, A., Zhiminaicela, K., & Ávila, V. (2024). Las redes sociales y su influencia en los hábitos de consumo, caso: Universidad Técnica de Machala. 593 Digital Publisher CEIT, 9(4), 312–322. https://doi.org/10.33386/593dp.2024.4.2415

Plonsky, O., Apel, R., Ert, E., Tennenholtz, M., Bourgin, D., Peterson, J. C., Reichman, D., Griffiths, T. L., Russell, S. J., Carter, E. C., Cavanagh, J. F., & Erev, I. (2019). Predicting human decisions with behavioral theories and machine learning. arXiv. https://doi.org/10.48550/arXiv.1904.06866

Romeo, G. (2020). Data analysis for business and economics. In Elements of numerical mathematical economics with Excel (pp. 695–761). Elsevier. https://doi.org/10.1016/B978-0-12-817648-1.00013-X

Shah, S. S., & Asghar, Z. (2023). Dynamics of social influence on consumption choices: A social network representation. Heliyon, 9(6), e17146. https://doi.org/10.1016/J.HELIYON.2023.E17146

Thaler, R. H. (2016). Behavioral Economics: Past, Present, and Future. American Economic Review, 106(7), 1577–1600. https://doi.org/10.1257/aer.106.7.1577

Yi, M. R. (2023). Corporate Reputation and Users’ Behavioral Intentions: Is Reputation the Master Key That Moves Consumers? SAGE Open, 13(1), 1–14. https://doi.org/10.1177/21582440231154486