¿Cómo los consumidores valoran atributos de calidad de carne bovina y su disposición a pago?
Palabras clave:
Características cárnicas, Consumidores, Expectativas de consumo, Percepción de compra, Preferencias
Resumen
La percepción de calidad de carne es un concepto complejo y requiere de análisis multivariados para entender su estructura y conceptualización. El objetivo del estudio fue valorar la percepción de calidad de carne por parte del consumidor y la disponibilidad a pago por información de calidad. Se aplicaron 400 encuestas bajo un cuestionario estructurado. La encuesta indagó sobre el perfil socioeconómico del consumidor y la percepción sobre características intrínsecas y extrínsecas de la carne, perfil de consumo por información nutricional, estilo de vida, preferencias de cortes y frecuencia de compra, y disposición a pago por información nutricional, empleando una escala Likert. Los datos se analizaron mediante modelos de ecuaciones estructurales (SEM) y pruebas chi2. El SEM registró un ajuste satisfactorio (CFI=0,978, RMSEA=0,17). Los resultados indicaron que el consumidor conceptualiza (P < 0,05) la carne con base en aspectos intrínsecos (color, suavidad y pérdida de agua), extrínsecos (precio, bienestar animal y confianza) y la actitud de consumo saludable. El encuestado no consideró el concepto de calidad para la disposición a pago por información. Las mujeres, los consumidores entre 37-55 años y los empleados, registraron la puntuación más alta (P < 0,05) en el concepto de calidad de la carne.
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Disciplinas:
AgropecuarioLenguajes:
Español; CastellanoReferencias bibliográficas
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[7] ARDESHIRI, A. and ROSE, JM. How Australian consumers value intrinsic and extrinsic attributes of beef products. Food Quality Preference, 65, 2018, p. 146–63. doi: https://doi.org/10.1016/j.foodqual.2017.10.018
[8] LIANA, M., RADAM, A. and YACOB, MR. Consumer perception towards meat safety: Confirmatory factor analysis. International Journal of Economics Management, 4(2), 2010, p. 305–18.
[9] VOEGELE, H., RON, O., GARMYN, A., O’QUINN, T., BROOKS, J. and MILLER, M. Consumer Perception of Beef Palatability Altered by Brand Recognition. Meat Muscle Biology, 1(3), 2017, p. 8.
[10] FLOWERS, S., MCFADDEN, B.R., CARR, C.C. and MATEESCU, R.G. Consumer preferences for beef with improved nutrient profile. Journal of Animal Science, 97(12), 2019, p. 1–15. doi: 10.1093/jas/skz327.
[11] NGAPO, T.M., BRAÑA-VARELA, D., RUBIO-LOZANO, M.S. Mexican consumers at the point of meat purchase. Beef choice. Meat Science, 134, 2017, p. 34–43. doi: http://dx.doi.org/10.1016/j.meatsci.2017.07.013
[12] TROY, D.J. and KERRY, J.P. Consumer perception and the role of science in the meat industry. Meat Science, 86(1), 2010, p. 214–26. doi: http://dx.doi.org/10.1016/j.meatsci.2010.05.009
[13] BANOVIĆ, M., CHRYSOCHOU, P., GRUNERT, K.G., ROSA, P.J. and GAMITO, P. The effect of fat content on visual attention and choice of red meat and differences across gender. Food Quality Preference, 52, 2016, p. 42–51. doi: doi.org/10.1016/j.foodqual.2016.03.017
[14] ENCISO, K. et al. Consumer Preferences and Market Segmentation for Differentiated Beef with Less Environmental Impact. In Congress Solidarity in a competing world fair use of resources. Viena (Austria): Tropentag, 2016.
[15] FEDERACIÓN COLOMBIANA DE GANADEROS (FEDEGAN). Ganadería Colombiana. Hoja de ruta 2018-2022. Bogotá (Colombia): Federación Colombiana de Ganaderos, 2018, 126 p.
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[17] GARCÍA, G. y RUÍZ, D. Plan Estratégico de Ciencia, Tecnología e Innovación del Sector Agropecuario Colombiano. Cadena Cárnica Bovina. Bogotá (Colombia): Agrosavia, 2016, p. 48.
[18] FEDERACIÓN COLOMBIANA DE GANADEROS (FEDEGAN). Así es nuestro consumidor. Revista Carta Fedegan, 111, p.22–6.
[19] FRANK, D., JOO, S.T. and WARNER, R. Consumer acceptability of intramuscular fat. Korean Journal Food Science Animal Resource, 36(6), 2016, p. 699–708. doi: 10.5851/kosfa.2016.36.6.699
[20] BARRAGÁN, WA., MAHECHA, L., ANGULO, J. y OLIVERA, M. Percepción de consumidores frente a información nutricional de la carne bovina. Idesia, 36(4), 2018, p. 35-43. doi: http://dx.doi.org/10.4067/S0718-34292018005002302.
[21] MEJÍA-ARANGO, L.J., ESTRADA, C.M., SALCEDO-AMAYA, G.J., HIGUITA, J.M. y GRANADOS, JD. Informe de calidad de vida Medellìn 2016. In: Medellín Cómo vamos. Medellín (Colombia): 2016.
[22] ALINDA, F., KAVOI, M. and MIGISHA, J. Consumer willingness to pay for quality beef in Kampala, Uganda. Journal Agricultural Science Technology, 17(2), 2017, p. 59–77.
[23] XUE, H., MAINVILLE, D., YOU, W. and NAYGA, R.M. Consumer preferences and willingness to pay for grass-fed beef: Empirical evidence from in-store experiments. Food Quality Preference, 21(7), 2010, p. 857–66. doi: http://dx.doi.org/10.1016/j.foodqual.2010.05.004
[24] HAIR, J., BLACK, W., BABIN, B. and ANDERSON, R. Multivariate Data Analysis. London (United Kingdom): Pearson, 2017, 734 p.
[25] REVELLE, W. psych: Procedures for Psychological, Psychometric, and Personality Research. R package [online]. 2020. Disponible: https://cran.r-project.org/web/packages/psych/psych.pdf [citado 11 de marzo de 2020]
[26] ROSSEEL, Y. Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal Statical Software, 48(2), 2012, p. 1–36. doi: 10.18637/jss.v048.i02
[27] BEAUJEAN, AA. Latent Variable Modeling Using R: A Step-by-Step Guide. New York (United State): Routledge, 2014, p. 1–205.
[28] DEPARTAMENTO ADMINISTRATIVO NACIONAL DE ESTADÍSTICA (DANE). Boletín Técnico. Censo nacional de población y vivienda (CNPV)-2018. [online]. 2019. Disponible en: https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/censo-nacional-de-poblacion-y-vivenda-2018 [citado 11 de marzo de 2020]
[29] BAGOZZI, R.P. and YOUJAE, Y.I. On the Evaluation of Structural Equation Models. Journal of Academy Marketing Science, 16(1), 1988, p.74–94. doi: http://jam.sagepub.com/cgi/doi/10.1177/009207038801600107
[30] MERLINO, V.M., BORRA, D., GIRGENTI, V., DAL VECCHIO, A. and MASSAGLIA, S. Beef meat preferences of consumers from Northwest Italy: Analysis of choice attributes. Meat Science, 143(November 2016), 2018, p. 119–28. doi: doi.org/10.1016/j.meatsci.2018.04.023
[31] FLOWERS, S., MCFADDEN, B., CARR, C. and MATEESCU, R. Understanding Beef Nutritional Attributes Contributes to Consumers’ Willingness-to-Pay for a Healthier Product. Meat Muscle Biololy, 2(2), 2018, p. 15–16.
[32] ARENAS-DE MORENO, L., JEREZ-TIMAURE, N., VALERIO, J., HUERTA-LEIDENZ, N.O. and RODAS-GONZÁLEZ, A. Attitudinal Determinants of Beef Consumption in Venezuela: A Retrospective Survey. Foods, 9(202), 2020, p.1–18. doi: doi.org/10.3390/foods9020202
[33] KIM, Y.H.B. et al. Understanding postmortem biochemical processes and post-harvest aging factors to develop novel smart-aging strategies. Meat Science, 144, 2018, p. 74–90. doi: doi.org/10.1016/j.meatsci.2018.04.031
[34] MIRANDA-DE LA LAMA, G.C. et al. Mexican consumers’ perceptions and attitudes towards farm animal welfare and willingness to pay for welfare friendly meat products. Meat Science, 125, 2016, p. 106-113. doi: 10.1016/j.meatsci.2016.12.001
[35] LUSK, J.L. Consumer beliefs about healthy foods and diets. PLoS One, 14(10), 2019, p. 1–15. doi: doi.org/10.1371/journal.pone.0223098
[36] SCOLLAN, N.D., PRICE, E.M., MORGAN, S.A., HUWS, S.A. and SHINGFIELD, K.J. Can we improve the nutritional quality of meat?. Proceedings of the Nutrition Society, 76(4), 2017, p. 603–18. doi: doi.org/10.1017/S0029665117001112
[37] REALINI, C.E. et al. Relative importance of cues underlying Spanish consumers’ beef choice and segmentation, and consumer liking of beef enriched with n-3 and CLA fatty acids. Food Quality Prefererence, 33, 2014, p. 74–85. doi: http://dx.doi.org/10.1016/j.foodqual.2013.11.007
[2] GRUNERT, G., BREDAHL, L. and BRUNSØ, K. Consumer perception of meat quality and implications for product development in the meat sector - A review. Meat Science, 66(2), 2004, p. 259–72. doi: doi.org/10.1016/S0309-1740(03)00130-X
[3] FONT-I-FURNOLS, M. and GUERRERO, L. Consumer preference, behavior and perception about meat and meat products: An overview. Meat Science, 98(3), 2014, p. 361–71. doi: http://dx.doi.org/10.1016/j.meatsci.2014.06.025
[4] JOO, ST., KIM, GD., HWANG, YH. and RYU, YC. Control of fresh meat quality through manipulation of muscle fiber characteristics. Meat Science, 95(4), 2013, p.828–36. doi: http://dx.doi.org/10.1016/j.meatsci.2013.04.044
[5] FRANK, D., OYTAM, Y. and HUGHES, J. Sensory Perceptions and New Consumer Attitudes to Meat. In: New Aspects of Meat Quality. Tandil (Argentina): Elsevier, 2017. p. 667–698. doi: doi.org/10.1016/B978-0-08-100593-4.00028-X
[6] DOS SANTOS, D., ESTEVES DE OLIVEIRA, T. and GIANEZINI, M. Consumer’s perception on beef sustainability in Porto Alegre, southern Brazil. Business Management Dynamics, 7(02), 2013, p. 7–19.
[7] ARDESHIRI, A. and ROSE, JM. How Australian consumers value intrinsic and extrinsic attributes of beef products. Food Quality Preference, 65, 2018, p. 146–63. doi: https://doi.org/10.1016/j.foodqual.2017.10.018
[8] LIANA, M., RADAM, A. and YACOB, MR. Consumer perception towards meat safety: Confirmatory factor analysis. International Journal of Economics Management, 4(2), 2010, p. 305–18.
[9] VOEGELE, H., RON, O., GARMYN, A., O’QUINN, T., BROOKS, J. and MILLER, M. Consumer Perception of Beef Palatability Altered by Brand Recognition. Meat Muscle Biology, 1(3), 2017, p. 8.
[10] FLOWERS, S., MCFADDEN, B.R., CARR, C.C. and MATEESCU, R.G. Consumer preferences for beef with improved nutrient profile. Journal of Animal Science, 97(12), 2019, p. 1–15. doi: 10.1093/jas/skz327.
[11] NGAPO, T.M., BRAÑA-VARELA, D., RUBIO-LOZANO, M.S. Mexican consumers at the point of meat purchase. Beef choice. Meat Science, 134, 2017, p. 34–43. doi: http://dx.doi.org/10.1016/j.meatsci.2017.07.013
[12] TROY, D.J. and KERRY, J.P. Consumer perception and the role of science in the meat industry. Meat Science, 86(1), 2010, p. 214–26. doi: http://dx.doi.org/10.1016/j.meatsci.2010.05.009
[13] BANOVIĆ, M., CHRYSOCHOU, P., GRUNERT, K.G., ROSA, P.J. and GAMITO, P. The effect of fat content on visual attention and choice of red meat and differences across gender. Food Quality Preference, 52, 2016, p. 42–51. doi: doi.org/10.1016/j.foodqual.2016.03.017
[14] ENCISO, K. et al. Consumer Preferences and Market Segmentation for Differentiated Beef with Less Environmental Impact. In Congress Solidarity in a competing world fair use of resources. Viena (Austria): Tropentag, 2016.
[15] FEDERACIÓN COLOMBIANA DE GANADEROS (FEDEGAN). Ganadería Colombiana. Hoja de ruta 2018-2022. Bogotá (Colombia): Federación Colombiana de Ganaderos, 2018, 126 p.
[16] CAMACHO, G.C. et al. Competir e innovar la ruta de la industria bovina :agenda prospectiva de investigación y desarrollo tecnológico para la cadena cárnica bovina en Colombia. Bogotá (Colombia): Ministerio de Agricultura y Desarrollo Rural, 2009, p. 245.
[17] GARCÍA, G. y RUÍZ, D. Plan Estratégico de Ciencia, Tecnología e Innovación del Sector Agropecuario Colombiano. Cadena Cárnica Bovina. Bogotá (Colombia): Agrosavia, 2016, p. 48.
[18] FEDERACIÓN COLOMBIANA DE GANADEROS (FEDEGAN). Así es nuestro consumidor. Revista Carta Fedegan, 111, p.22–6.
[19] FRANK, D., JOO, S.T. and WARNER, R. Consumer acceptability of intramuscular fat. Korean Journal Food Science Animal Resource, 36(6), 2016, p. 699–708. doi: 10.5851/kosfa.2016.36.6.699
[20] BARRAGÁN, WA., MAHECHA, L., ANGULO, J. y OLIVERA, M. Percepción de consumidores frente a información nutricional de la carne bovina. Idesia, 36(4), 2018, p. 35-43. doi: http://dx.doi.org/10.4067/S0718-34292018005002302.
[21] MEJÍA-ARANGO, L.J., ESTRADA, C.M., SALCEDO-AMAYA, G.J., HIGUITA, J.M. y GRANADOS, JD. Informe de calidad de vida Medellìn 2016. In: Medellín Cómo vamos. Medellín (Colombia): 2016.
[22] ALINDA, F., KAVOI, M. and MIGISHA, J. Consumer willingness to pay for quality beef in Kampala, Uganda. Journal Agricultural Science Technology, 17(2), 2017, p. 59–77.
[23] XUE, H., MAINVILLE, D., YOU, W. and NAYGA, R.M. Consumer preferences and willingness to pay for grass-fed beef: Empirical evidence from in-store experiments. Food Quality Preference, 21(7), 2010, p. 857–66. doi: http://dx.doi.org/10.1016/j.foodqual.2010.05.004
[24] HAIR, J., BLACK, W., BABIN, B. and ANDERSON, R. Multivariate Data Analysis. London (United Kingdom): Pearson, 2017, 734 p.
[25] REVELLE, W. psych: Procedures for Psychological, Psychometric, and Personality Research. R package [online]. 2020. Disponible: https://cran.r-project.org/web/packages/psych/psych.pdf [citado 11 de marzo de 2020]
[26] ROSSEEL, Y. Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal Statical Software, 48(2), 2012, p. 1–36. doi: 10.18637/jss.v048.i02
[27] BEAUJEAN, AA. Latent Variable Modeling Using R: A Step-by-Step Guide. New York (United State): Routledge, 2014, p. 1–205.
[28] DEPARTAMENTO ADMINISTRATIVO NACIONAL DE ESTADÍSTICA (DANE). Boletín Técnico. Censo nacional de población y vivienda (CNPV)-2018. [online]. 2019. Disponible en: https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/censo-nacional-de-poblacion-y-vivenda-2018 [citado 11 de marzo de 2020]
[29] BAGOZZI, R.P. and YOUJAE, Y.I. On the Evaluation of Structural Equation Models. Journal of Academy Marketing Science, 16(1), 1988, p.74–94. doi: http://jam.sagepub.com/cgi/doi/10.1177/009207038801600107
[30] MERLINO, V.M., BORRA, D., GIRGENTI, V., DAL VECCHIO, A. and MASSAGLIA, S. Beef meat preferences of consumers from Northwest Italy: Analysis of choice attributes. Meat Science, 143(November 2016), 2018, p. 119–28. doi: doi.org/10.1016/j.meatsci.2018.04.023
[31] FLOWERS, S., MCFADDEN, B., CARR, C. and MATEESCU, R. Understanding Beef Nutritional Attributes Contributes to Consumers’ Willingness-to-Pay for a Healthier Product. Meat Muscle Biololy, 2(2), 2018, p. 15–16.
[32] ARENAS-DE MORENO, L., JEREZ-TIMAURE, N., VALERIO, J., HUERTA-LEIDENZ, N.O. and RODAS-GONZÁLEZ, A. Attitudinal Determinants of Beef Consumption in Venezuela: A Retrospective Survey. Foods, 9(202), 2020, p.1–18. doi: doi.org/10.3390/foods9020202
[33] KIM, Y.H.B. et al. Understanding postmortem biochemical processes and post-harvest aging factors to develop novel smart-aging strategies. Meat Science, 144, 2018, p. 74–90. doi: doi.org/10.1016/j.meatsci.2018.04.031
[34] MIRANDA-DE LA LAMA, G.C. et al. Mexican consumers’ perceptions and attitudes towards farm animal welfare and willingness to pay for welfare friendly meat products. Meat Science, 125, 2016, p. 106-113. doi: 10.1016/j.meatsci.2016.12.001
[35] LUSK, J.L. Consumer beliefs about healthy foods and diets. PLoS One, 14(10), 2019, p. 1–15. doi: doi.org/10.1371/journal.pone.0223098
[36] SCOLLAN, N.D., PRICE, E.M., MORGAN, S.A., HUWS, S.A. and SHINGFIELD, K.J. Can we improve the nutritional quality of meat?. Proceedings of the Nutrition Society, 76(4), 2017, p. 603–18. doi: doi.org/10.1017/S0029665117001112
[37] REALINI, C.E. et al. Relative importance of cues underlying Spanish consumers’ beef choice and segmentation, and consumer liking of beef enriched with n-3 and CLA fatty acids. Food Quality Prefererence, 33, 2014, p. 74–85. doi: http://dx.doi.org/10.1016/j.foodqual.2013.11.007
Cómo citar
Barragán Hernández , W. ., Mahecha Ledesma , . L. ., Olivera Angel , M. ., & Angulo Arizala , J. . (2020). ¿Cómo los consumidores valoran atributos de calidad de carne bovina y su disposición a pago?. Biotecnología En El Sector Agropecuario Y Agroindustrial, 19(1), 167–179. https://doi.org/10.18684/bsaa.v19.n1.2021.1622
Publicado
2020-08-18
Sección
Artículos de Investigaciòn
Español
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