Abstract

Despite being an important source of protein, fish consumption in Peru is low compared with other coastal countries. Thus, the objective of this study is to identify the core determinants of such consumption. We based our analysis on the framework provided by the Theory of Planned Behavior (TPB) where attitudes, subjective norms, past experience and health involvement determine the intention and frequency of fish consumption. Primary data were gathered through 159 consumers of fish in modern Metropolitan Lima between August and October 2015. From a set of likert scale indicators a structural model was specified to evaluate the relationships given by the theoretical framework of the TPB. The results showed that the intention to eat fish is determined by personal attitudes, norms and past experience, and as expected, intention itself causes the frequency of fish consumption. Nonetheless, although consumers’ interest in healthy eating was shown to positively influence fish consumption behavior by theory, Metropolitan Lima fish consumers seem to be not concerned by positive health attributes related to fish consumption. These results may have important implications on production decisions, sales and marketing for the promotion of fish in Lima as a means of economic development.

Keywords:
Theory of Planned Behavior (TPB); fish consumption; Lima; Peru

1 Introduction

For many cultures, fish consumption is an integral part of daily life as a source of protein (Burger et al., 2003Burger, J., Fleischer, J., & Gochfeld, M. (2003). Fish, shellfish, and meat meals of the public in Singapore. Environmental Research, 92(3), 254-261. PMid:12804522. http://dx.doi.org/10.1016/S0013-9351(03)00015-X.
http://dx.doi.org/10.1016/S0013-9351(03)... ) and other nutrients (Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.; McManus et al., 2014McManus, A., Hunt, W., Storey, J., McManus, J., & Hilhorst, S. (2014). Perceptions and preference for fresh seafood in an Australian context. International Journal of Consumer Studies, 38(2), 146-152. http://dx.doi.org/10.1111/ijcs.12076.
http://dx.doi.org/10.1111/ijcs.12076... ). Fish is also considered an alternative source of protein to more traditional sources (Aberoumand, 2014Aberoumand, A. (2014). Preliminary studies on nutritive and organoleptic properties in processed fish fillets obtained from Iran. Food Science and Technology (Campinas.), 34(2), 287-291. http://dx.doi.org/10.1590/fst.2014.0042.
http://dx.doi.org/10.1590/fst.2014.0042... ). Because of the country’s coastal connectivity, the Peruvian domestic fish market is largely dominated by fresh fish, which covers approximately 30% of the national market (Del Carpio & Vila, 2010Del Carpio, L., & Vila, B. (2010). El mercado de productos pesqueros en la región metropolitana de Lima (110 p., El mercado de pescado en las grandes ciudades latinoamericanas). Montevideo: Infopesca. Retrieved from http://www.infopesca.org/sites/default/files/complemento/publilibreacceso/286/informe-lima.pdf
http://www.infopesca.org/sites/default/f... ) and is the fresh sector representative of more than 50% of total fish consumption compared to processed fish (Fréon et al., 2014Fréon, P., Sueiro, J. C., Iriarte, F., Evar, O. F. M., Landa, Y., Mittaine, J. F., & Bouchon, M. (2014). Harvesting for food versus feed: a review of Peruvian fisheries in a global context. Reviews in Fish Biology and Fisheries, 24(1), 381-398. http://dx.doi.org/10.1007/s11160-013-9336-4.
http://dx.doi.org/10.1007/s11160-013-933... ). The Peruvian fisheries sector provides more revenue and jobs than the indirect human consumption industry. Currently, fisheries provide a conservative estimate of 232,000 jobs, 35% of which are in restaurants (Christensen et al., 2014Christensen, V., de la Puente, S., Sueiro, J. C., Steenbeek, J., & Majluf, P. (2014). Valuing seafood: the Peruvian fisheries sector. Marine Policy, 44, 302-311. http://dx.doi.org/10.1016/j.marpol.2013.09.022.
http://dx.doi.org/10.1016/j.marpol.2013.... ). The number of restaurants in Lima increased by 5.7% from 2009 to 2010, while approximately 7% of the new restaurants were cevicherias (Proexpansión, 2011Proexpansión. (2011). Cambios del sector papa en el Perú en la última década: los aportes del proyecto Innovación y Competitivad de la Papa (INCOPA) (160 p.). Lima: CIP.).

Even though Lima is a coastal city, its fish consumption remains low, a counterintuitive phenomenon that has been observed in other coastal regions of the world (Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.). Actual Peruvian fish consumption generally does not even come close to the recommendation to eat fish twice per week (Birch et al., 2012Birch, D., Lawley, M., & Hamblin, D. (2012). Drivers and barriers to seafood consumption in Australia. Journal of Consumer Marketing, 29(1), 64-73. http://dx.doi.org/10.1108/07363761211193055.
http://dx.doi.org/10.1108/07363761211193... ; Verbeke et al., 2007Verbeke, W., Vermeir, I., & Brunsø, K. (2007). Consumer evaluation of fish quality as basis for fish market segmentation. Food Quality and Preference, 18(4), 651-661. http://dx.doi.org/10.1016/j.foodqual.2006.09.005.
http://dx.doi.org/10.1016/j.foodqual.200... ), as do 75% of Spanish consumers (Pieniak et al., 2011Pieniak, Z., Kołodziejczyk, M., Kowrygo, B., & Verbeke, W. (2011). Consumption patterns and labelling of fish and fishery products in Poland after the EU accession. Food Control, 22(6), 843-850. http://dx.doi.org/10.1016/j.foodcont.2010.09.022.
http://dx.doi.org/10.1016/j.foodcont.201... ; Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.). Annual per capita edible fish consumption in Peru was estimated to be 11.2 kg (up to 22.5 kg in whole fish equivalents) in 2011 (Instituto Nacional de Estadística e Informática, 2012Instituto Nacional de Estadística e Informática – INEI. (2012). Perú: compendio estadístico 2012. (Peru: Statistical Compendium 2012. Fisheries). Lima: INEI.; Avadí & Fréon, 2015Avadí, A., & Fréon, P. (2015). A set of sustainability performance indicators for seafood: direct human consumption products from Peruvian anchoveta fisheries and freshwater aquaculture. Ecological Indicators, 48, 518-532. http://dx.doi.org/10.1016/j.ecolind.2014.09.006.
http://dx.doi.org/10.1016/j.ecolind.2014... ), which is just above the average per capita European whole fish consumption of 20.5 kg (Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ). The low frequency of fish consumption in Peru could be due to different barriers, including supply-related obstacles such as the lack of a cold chain (Halwart et al., 2007Halwart, M., Soto, D., & Arthur, J. R., editors. (2007). Cage aquaculture: regional reviews and global overview (241 p., FAO Fisheries Technical Paper, No. 498). Rome: FAO. ), logistical operations, and sub-optimal sanitary conditions (Fréon et al., 2014Fréon, P., Sueiro, J. C., Iriarte, F., Evar, O. F. M., Landa, Y., Mittaine, J. F., & Bouchon, M. (2014). Harvesting for food versus feed: a review of Peruvian fisheries in a global context. Reviews in Fish Biology and Fisheries, 24(1), 381-398. http://dx.doi.org/10.1007/s11160-013-9336-4.
http://dx.doi.org/10.1007/s11160-013-933... ). Additionally, individuals may be averse to consuming fish because of a perceived difficulty in buying, preparing and cooking fish (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ), the belief that it is expensive (Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ), the unpleasant physical properties of some varieties of fish such as the bones and the smell (Olsen, 2004Olsen, S. O. (2004). Antecedents of seafood consumption behavior: an overview. Journal of Aquatic Food Product Technology, 13(3), 79-91. http://dx.doi.org/10.1300/J030v13n03_08.
http://dx.doi.org/10.1300/J030v13n03_08... ), or even a simple lack of habit (McManus et al., 2014McManus, A., Hunt, W., Storey, J., McManus, J., & Hilhorst, S. (2014). Perceptions and preference for fresh seafood in an Australian context. International Journal of Consumer Studies, 38(2), 146-152. http://dx.doi.org/10.1111/ijcs.12076.
http://dx.doi.org/10.1111/ijcs.12076... ; Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ; Leek et al., 2000Leek, S., Maddock, S., & Foxall, G. (2000). Situational determinants of fish consumption. British Food Journal, 102(1), 18-39. http://dx.doi.org/10.1108/00070700010310614.
http://dx.doi.org/10.1108/00070700010310... ).

Different factors beyond sensorial characteristics influence consumer food choices, and the elucidation of these factors would contribute to a better understanding of dietary behavior (Carrillo et al., 2011Carrillo, E., Varela, P., Salvador, A., & Fiszman, S. (2011). Main factors underlying consumers’ food choice: a first step for the understanding of attitudes toward “healthy eating”. Journal of Sensory Studies, 26(2), 85-95. http://dx.doi.org/10.1111/j.1745-459X.2010.00325.x.
http://dx.doi.org/10.1111/j.1745-459X.20... ). Among them, just to acknowledge a few, we may mention past experiences and health concerns related to fish consumption. It is possible that those who currently eat fish perceived related past experiences more positively than those who do not (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ), causing a higher fish-eating intention and, thus, consumption frequency. Likewise, consumers characterized by a healthy lifestyle will be prone to healthy diets (Brouwer & Mosack, 2015Brouwer, A. M., & Mosack, K. E. (2015). Expanding the theory of planned behavior to predict healthy eating behaviors: exploring a healthy eater identity. Nutrition & Food Science, 45(1), 39-53. http://dx.doi.org/10.1108/NFS-06-2014-0055.
http://dx.doi.org/10.1108/NFS-06-2014-00... ) composed of fish.

Among other factors, we should mention the work by Lennernäs et al. (1997)Lennernäs, M., Fjellström, C., Becker, W., Giachetti, I., Schmitt, A., Winter, A. M., & Kearney, M. (1997). Influences on food choice perceived to be important by nationally-representative samples of adults in the European Union. European Journal of Clinical Nutrition, 51(Suppl 2), 51. PMid:9222718. which highlights the roles of quality/freshness, price, taste, healthy choices and family preferences, while Drewnowski & Darmon (2005)Drewnowski, A., & Darmon, N. (2005). Food choices and diet costs: an economic analysis. The Journal of Nutrition, 135(4), 900-904. PMid:15795456. consider the effects of taste, convenience and economic constraints on food choices (O’Neill et al., 2014O’Neill, V., Hess, S., & Campbell, D. (2014). A question of taste: recognising the role of latent preferences and attitudes in analysing food choices. Food Quality and Preference, 32, 299-310. http://dx.doi.org/10.1016/j.foodqual.2013.10.003.
http://dx.doi.org/10.1016/j.foodqual.201... ). In this regard, the identification of the principal factors considered by fish consumers would allow for establishing relationships between the frequency of fish-eating purchase behavior and attitudes in terms of explaining the intention and frequency of eating fish. Many different models, which take different and often interrelated factors into account, have been proposed to explain consumer behavior towards fish (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ; Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ). The Theory of Planned Behavior (TPB) is one of the most commonly used to explain the variance in behavior (Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ; Scholderer & Grunert, 2001Scholderer, J., & Grunert, K. G. (2001). Does generic advertising work? A systematic evaluation of the Danish campaign for fresh fish. Aquaculture Economics & Management, 5(5-6), 253-271. http://dx.doi.org/10.1080/13657300109380293.
http://dx.doi.org/10.1080/13657300109380... ; Ajzen, 1991Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. http://dx.doi.org/10.1016/0749-5978(91)90020-T.
http://dx.doi.org/10.1016/0749-5978(91)9... ). Given that fish represent an important source of protein and other nutrients (Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.; McManus et al., 2014McManus, A., Hunt, W., Storey, J., McManus, J., & Hilhorst, S. (2014). Perceptions and preference for fresh seafood in an Australian context. International Journal of Consumer Studies, 38(2), 146-152. http://dx.doi.org/10.1111/ijcs.12076.
http://dx.doi.org/10.1111/ijcs.12076... ), it is critical to understand the principal factors driving coastal Peruvian fish consumer behaviors such as intention and consumption frequency. Thus, the primary objective of this research is to investigate consumer behavior in Lima, Peru, using the TPB as a conceptual framework.

2 Materials and methods

Metropolitan Lima, the fifth most populated city in Latin America, was chosen as the study site of this research. Modern Lima presents predominately the socio-economic levels A and B (Ipsos Apoyo, 2011Ipsos Apoyo. (2011). Perfiles zonales 2011. Retrieved from http://www.ipsos.pe/Perfiles_Zonales_2011
http://www.ipsos.pe/Perfiles_Zonales_201... ). A choice-based sampling was used because this approach precludes making more general inferences about a larger population (Thompson & Kidwell, 1998Thompson, G. D., & Kidwell, J. (1998). Explaining the choice of organic produce: cosmetic defects, prices, and consumer preferences. American Journal of Agricultural Economics, 80(2), 277-287. http://dx.doi.org/10.2307/1244500.
http://dx.doi.org/10.2307/1244500... ), especially with unknown fish consumer population weights. Primary data were gathered between August and October 2015 at the study site. Fish consumers were interviewed randomly at the supermarkets and fresh markets in Modern Metropolitan Lima. The structured questionnaire involved 159 consumers who eat fish. The minimum sample size for this study was calculated according to the following assumptions: Expected fish consumption rate of 31% obtained from the Perú (2016)Perú. Peruvian Ministry of Agriculture. (2016). Boletín estadístico de producción agrícola, pecuaria y avícola. Lima. Retrieved from http://www.minagri.gob.pe/portal/estadistico-produccion
http://www.minagri.gob.pe/portal/estadis... ; Modern Metropolitan Lima population extracted from Instituto Nacional de Estadística e Informática (2014)Instituto Nacional de Estadística e Informática – INEI. (2014). Una mirada a Lima Metropolitana. Lima: INEI.; sampling error of 5%; and 95% confidence interval (Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.). Questions are addressed to fish consumers only, therefore our empirical model implicitly assumes that non-fish consumers are missing at random (MAR) i.e. that heterogeneity in fish consumption frequency is explained by the set of included covariates.

Topics in the survey’s questionnaire were based on the main factors that compel fish consumers to determine their intentions and frequency of fish consumption based on the TPB. Research on the TPB has made considerable progress since the theory was introduced more than two decades ago (Ajzen, 2011Ajzen, I. (2011). The theory of planned behaviour: reactions and reflections. Psychology & Health, 26(9), 1113-1127. PMid:21929476. http://dx.doi.org/10.1080/08870446.2011.613995.
http://dx.doi.org/10.1080/08870446.2011.... ). Despite the fact that the TPB became one of the most frequently cited and influential models for the prediction of human social behavior, the TPB has also been the target of much criticism and debate. Some researchers reject it outright as an inadequate explanation of human social behavior (Ajzen, 2011Ajzen, I. (2011). The theory of planned behaviour: reactions and reflections. Psychology & Health, 26(9), 1113-1127. PMid:21929476. http://dx.doi.org/10.1080/08870446.2011.613995.
http://dx.doi.org/10.1080/08870446.2011.... ). Most critics, however, accept the theory’s basic reasoned action assumptions but question its sufficiency or inquire into its limiting conditions (Fishbein & Ajzen, 2011Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: the reasoned action approach. New York: Psycology Press.).

From Ajzen’s (2008Ajzen, I. (2008). Consumer attitudes and behavior. In C. P. Haugtvedt, P. M. Herr & F. R. Kardes (Eds.), Handbook of consumer psychology (pp. 525-548). New York: Psychology Press., p. 537) perspective, it may be deducted that “the intention to adopt a certain course of action logically precedes actual performance of the behavior”. Thus, it seems that intentions could be seen as a mediator between attitudes and actions. Specifically, according to Ajzen (1991)Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. http://dx.doi.org/10.1016/0749-5978(91)90020-T.
http://dx.doi.org/10.1016/0749-5978(91)9... , the intention to perform behavior together with perceptions of behavioral control accounts for a major part of the variance in behavior. The TPB assumes that these behavioral intentions capture the motivational influences on behavior. Intention is thus seen as the most proximal predictor of behavior. Behavioral intention, in turn, is seen as a function of attitudes, subjective norms and perceived behavioral control related to that specific behavior (Ajzen, 1991Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. http://dx.doi.org/10.1016/0749-5978(91)90020-T.
http://dx.doi.org/10.1016/0749-5978(91)9... ). The perceived behavioral control, attitudes and subjective norms will predict intentions (Brouwer & Mosack, 2015Brouwer, A. M., & Mosack, K. E. (2015). Expanding the theory of planned behavior to predict healthy eating behaviors: exploring a healthy eater identity. Nutrition & Food Science, 45(1), 39-53. http://dx.doi.org/10.1108/NFS-06-2014-0055.
http://dx.doi.org/10.1108/NFS-06-2014-00... ). However, some question the degree to which the primary components of the TPB (i.e., attitudes, subjective norms, perceived behavioral control) sufficiently explain intention and behavior because the level of prediction for intention varies quite dramatically (Rise et al., 2010Rise, J., Sheeran, P., & Hukkelberg, S. (2010). The role of self‐identity in the theory of Planned behavior: a meta‐analysis. Journal of Applied Social Psychology, 40(5), 1085-1105. http://dx.doi.org/10.1111/j.1559-1816.2010.00611.x.
http://dx.doi.org/10.1111/j.1559-1816.20... ). Ajzen (2011)Ajzen, I. (2011). The theory of planned behaviour: reactions and reflections. Psychology & Health, 26(9), 1113-1127. PMid:21929476. http://dx.doi.org/10.1080/08870446.2011.613995.
http://dx.doi.org/10.1080/08870446.2011.... said that intentions may be determined not only by attitudes, norms and perceived control but also by one or more added variables, and these added variables were captured, at least in part, by measures of past behavior (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ) and health (Tudoran et al., 2009Tudoran, A., Olsen, S. O., & Dopico, D. C. (2009). The effect of health benefit information on consumers health value, attitudes and intentions. Appetite, 52(3), 568-579. PMid:19501752. http://dx.doi.org/10.1016/j.appet.2009.01.009.
http://dx.doi.org/10.1016/j.appet.2009.0... ).

In our study, a structural equation model is specified to operationalize and test the causal links posited by the proposed theoretical model, the TBP. From this framework, three main constructs were retained: attitudes, subjective norms and past experience (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). Attitude towards the behavior entails a consideration of the outcomes of performing the behavior, while subjective or social norms refer to the perceived social pressure to perform or not such behavior (Ajzen, 1991Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. http://dx.doi.org/10.1016/0749-5978(91)90020-T.
http://dx.doi.org/10.1016/0749-5978(91)9... ). Finally, behavioral control is assumed to reflect past experiences as well as anticipated difficulties or facilitating conditions (Vermeir & Verbeke, 2008Vermeir, I., & Verbeke, W. (2008). Sustainable food consumption among young adults in Belgium: theory of planned behaviour and the role of confidence and values. Ecological Economics, 64(3), 542-553. http://dx.doi.org/10.1016/j.ecolecon.2007.03.007.
http://dx.doi.org/10.1016/j.ecolecon.200... ). Our model also included a health construct as it could explain a substantial amount of variance in the fish purchasing intention, according to Tudoran et al. (2009)Tudoran, A., Olsen, S. O., & Dopico, D. C. (2009). The effect of health benefit information on consumers health value, attitudes and intentions. Appetite, 52(3), 568-579. PMid:19501752. http://dx.doi.org/10.1016/j.appet.2009.01.009.
http://dx.doi.org/10.1016/j.appet.2009.0... . Furthermore, it could explain a large part of the variance in respondent behaviors (Conner & Armitage, 1998Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: a review and avenues for further research. Journal of Applied Social Psychology, 28(15), 1429-1464. http://dx.doi.org/10.1111/j.1559-1816.1998.tb01685.x.
http://dx.doi.org/10.1111/j.1559-1816.19... ; Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ) as in Uruguay and Brazil. In Uruguay, Ares & Gámbaro (2008)Ares, G., & Gámbaro, A. (2008). Food choice and food consumption frequency for Uruguayan consumers. International Journal of Food Sciences and Nutrition, 59(3), 211-223. PMid:17852481. http://dx.doi.org/10.1080/09637480701497402.
http://dx.doi.org/10.1080/09637480701497... scored the health-related factors of “feeling good and safe”, “health” and “nutrient content” as the most important motives underlying consumer food choices. In Brazil, Mitterer-Daltoé et al. (2013)Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... explored the perception of healthiness as a contributor to understanding the main factors underlying fish consumption. The questions of our study related to the TPB and fish consumption behavior were based on Verbeke & Vackier (2005)Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... , Mitterer-Daltoé et al. (2013)Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... and Carrillo et al. (2011)Carrillo, E., Varela, P., Salvador, A., & Fiszman, S. (2011). Main factors underlying consumers’ food choice: a first step for the understanding of attitudes toward “healthy eating”. Journal of Sensory Studies, 26(2), 85-95. http://dx.doi.org/10.1111/j.1745-459X.2010.00325.x.
http://dx.doi.org/10.1111/j.1745-459X.20... (Table 1). Table 1 shows the dimensions and measures used for the operationalization of the studied structural model.

All of the measurements in the TPB questionnaire were recorded in the same direction so that a high score meant a positive attitude, subjective norm or past experience (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). The study uses a Likert scale questionnaire ranging from 1 (Strongly disagree) to 5 (Strongly agree) to measure the perceptions of fish, except for the behavior variable “how frequently do you eat fish?”, which was measured on the binary scale “monthly or more” or “weekly” basis. The scales (questions) were obtained from the relevant literature in English language and were then translated to Spanish. Two bilingual professionals, one in the linguistic field and the other an expert on fish issues, cooperated on the back translation of this study. TPB construct reliability was tested by Cronbach’s alpha. The analysis was performed using Mplus software (Muthén & Muthén, 2007Muthén, L. K., & Muthén, B. O. (2007). Mplus user’s guide (6th ed.). Los Angeles: Muthén & Muthén.).

Table 2 summarizes household demographic characteristics (such as age, number of children, family members, among others) by consumption frequency (weekly and monthly or more).

This model is specified with a dichotomous dependent variable representing the fish consumer’s final choice in terms of consumption frequency. The consumption frequency dependent variable takes values of 1 and 0 indicating ‘weekly’ consumption or ‘monthly or less frequently’, respectively. Thus, consumption frequency is first explained by a set of demographic factors or socio-economic factors (Al-Mazrooei et al., 2003Al-Mazrooei, N., Chomo, G. V., & Omezzine, A. (2003). Purchase behavior of consumers for seafood products. Agricultural and Marine Sciences, 8(1), 1-10.) as specified in Table 2.

3 Results and discussion

Lennernäs et al. (1997)Lennernäs, M., Fjellström, C., Becker, W., Giachetti, I., Schmitt, A., Winter, A. M., & Kearney, M. (1997). Influences on food choice perceived to be important by nationally-representative samples of adults in the European Union. European Journal of Clinical Nutrition, 51(Suppl 2), 51. PMid:9222718. found that respondents in different socio-economic categories select different factors as contributing a large portion of influence on their food choices. Therefore, demographic and socio-economic factor characteristics were used as control variables on the Peruvian frequency of fish consumption by means of a probit model where the dependent variable is fish consumption frequency either low or high (Al-Mazrooei et al., 2003Al-Mazrooei, N., Chomo, G. V., & Omezzine, A. (2003). Purchase behavior of consumers for seafood products. Agricultural and Marine Sciences, 8(1), 1-10.). The estimated probit model is presented below (Table 3).

It was expected, for instance, that education or income level (proxied by a district dummy on the assumption that household incomes will be reasonably homogeneous within small enough residential areas (Hanley & Morgan, 2008Hanley, G., & Morgan, S. (2008). On the validity of area-based income measures to proxy household income. BMC Health Services Research, 8(1), 79-86. PMid:18402681. http://dx.doi.org/10.1186/1472-6963-8-79.
http://dx.doi.org/10.1186/1472-6963-8-79... )) would have a positive effect on fish consumption (Can et al., 2015Can, M. F., Günlü, A., & Can, H. Y. (2015). Fish consumption preferences and factors influencing it. Food Science and Technology (Campinas.), 35(2), 339-346.). Nonetheless, socio-economic variables did not fit well in the probit model. R-squared was 3.6% and none of the variables were significant in the frequency of fish consumption at a 10% significance level (Table 3).

Given that socio-economic characteristics did not have a significant relation to consumption frequency- which does not mean we are neglecting the fact that there is certain effect on the fish consumption-, a more general and conceptual framework was required to explain such fish consumption behavior. Thus, a ‘health’ construct along with the ones suggested by the TPB as determinants of fish consumption frequency were added to the model. According to the latest studies on food and food-related issues, product healthiness is one of the key factors of consumer perceptions (Niva, 2007Niva, M. (2007). ‘All foods affect health’: understandings of functional foods and healthy eating among health-oriented Finns. Appetite, 48(3), 384-393. PMid:17166625. http://dx.doi.org/10.1016/j.appet.2006.10.006.
http://dx.doi.org/10.1016/j.appet.2006.1... ).

The TPB appraises behavior as a composite of three constructs: attitude, subjective norms and perceived behavioral control (including statements of facilitating conditions and past experience) (Ajzen, 1991Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. http://dx.doi.org/10.1016/0749-5978(91)90020-T.
http://dx.doi.org/10.1016/0749-5978(91)9... ). The TPB was chosen as the theoretical framework by several applied studies (Arvola et al., 2008Arvola, A., Vassallo, M., Dean, M., Lampila, P., Saba, A., Lähteenmäki, L., & Shepherd, R. (2008). Predicting intentions to purchase organic food: the role of affective and moral attitudes in the Theory of Planned Behaviour. Appetite, 50(2), 443-454. PMid:18036702. http://dx.doi.org/10.1016/j.appet.2007.09.010.
http://dx.doi.org/10.1016/j.appet.2007.0... ). For instance, this theory has been extensively and successfully applied to consumer behaviors (Conner & Sparks, 2005Conner, M., & Sparks, P. (2005). Theory of planned behavior and health behavior. Predicting health behavior, 2, 170-220.), health behaviors (Godin & Kok, 1996Godin, G., & Kok, G. (1996). The theory of planned behavior: a review of its applications to health-related behaviors. American Journal of Health Promotion, 11(2), 87-98. PMid:10163601. http://dx.doi.org/10.4278/0890-1171-11.2.87.
http://dx.doi.org/10.4278/0890-1171-11.2... ), food choices (Arvola et al., 2008Arvola, A., Vassallo, M., Dean, M., Lampila, P., Saba, A., Lähteenmäki, L., & Shepherd, R. (2008). Predicting intentions to purchase organic food: the role of affective and moral attitudes in the Theory of Planned Behaviour. Appetite, 50(2), 443-454. PMid:18036702. http://dx.doi.org/10.1016/j.appet.2007.09.010.
http://dx.doi.org/10.1016/j.appet.2007.0... ) and the variance in fish consumption behavior in countries with a high consumption of fish (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). A study based on the TPB applied in Brazil, a developing country, validated the theoretical model (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). Given Brazil’s proximity to Peru and the validity of the model in a similar context, the present study seeks to explore the predictive value of each construct in explaining consumer intentions to purchase sustainable food products. The structural relations are represented in the figure below (see Figure 1).

Figure 1
TPB applied to fish consumption in modern Metropolitan Lima (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). *** p < 0.01; ** p < 0.05; *p < 0.10; Chi-Square test of model fit p-value = 0.00. Frequency of fish consumption (equation) R-squared = 29.5%. Elaborated by the authors.

Attitudes are suggested to be one of the main determinants of food consumption behavior, including seafood (Olsen, 2004Olsen, S. O. (2004). Antecedents of seafood consumption behavior: an overview. Journal of Aquatic Food Product Technology, 13(3), 79-91. http://dx.doi.org/10.1300/J030v13n03_08.
http://dx.doi.org/10.1300/J030v13n03_08... ). Attitudes have been defined as mental states, learned predispositions, psychological tendencies or evaluative judgements about objects, which guide behavior towards those objects (Tudoran et al., 2009Tudoran, A., Olsen, S. O., & Dopico, D. C. (2009). The effect of health benefit information on consumers health value, attitudes and intentions. Appetite, 52(3), 568-579. PMid:19501752. http://dx.doi.org/10.1016/j.appet.2009.01.009.
http://dx.doi.org/10.1016/j.appet.2009.0... ). Social norms are often defined and measured as perceived social pressure or expectations from people in general (subjective norms) of form-specific groups or individuals (Olsen, 2004Olsen, S. O. (2004). Antecedents of seafood consumption behavior: an overview. Journal of Aquatic Food Product Technology, 13(3), 79-91. http://dx.doi.org/10.1300/J030v13n03_08.
http://dx.doi.org/10.1300/J030v13n03_08... ). Mitterer-Daltoé et al. (2013)Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... determined that habit as a variable measure of past experience was an important discriminating variable and a good explanatory construct to explain fish consumption. Thus, past experience may be included as a substantive predictor of subsequent behavior because its power relies on the belief that past behavior was a reasoned action (Vermeir & Verbeke, 2008Vermeir, I., & Verbeke, W. (2008). Sustainable food consumption among young adults in Belgium: theory of planned behaviour and the role of confidence and values. Ecological Economics, 64(3), 542-553. http://dx.doi.org/10.1016/j.ecolecon.2007.03.007.
http://dx.doi.org/10.1016/j.ecolecon.200... ).

Our TPB-based model (Figure 1) can be best described as a Structural Equation Model which is estimated by Generalized Least Squares under the assumption of (conditional) multivariate normality of the ordinal indicators (see Muthén & Satorra, 1995Muthén, B., & Satorra, A. (1995). Technical aspects of Muthén’s LISCOM approach to estimation of latent variable relations with a comprehensive measurement model. Psychometrika, 60(4), 489-503. http://dx.doi.org/10.1007/BF02294325.
http://dx.doi.org/10.1007/BF02294325... and Muthén, 2004Muthén, B.O. (2004). Mplus technical appendices. Los Angeles: Muthén & Muthén. for further details). The main equation of interest that relates fish consumption to its TPB and socio-economic determinants exhibits an R-squared of 29.5% which shows the share of explained variance for qualitative dependent variable models (Amemiya, 1981Amemiya, T. (1981). Qualitative response models: a survey. Journal of Economic Literature, 19(4), 1483-1536.), while the single probit model (Table 3) only achieved 3.6%. The proposed SEM, which includes the traditional constructs defined by the TPB, pretends to be enhanced by the inclusion of ‘Health involvement’. According to the latest studies on food related issues, product healthiness is one of the key factors in consumer perceptions (Olsen, 2003Olsen, S. O. (2003). Understanding the relationship between age and seafood consumption: the mediating role of attitude, health involvement and convenience. Food Quality and Preference, 14(3), 199-209. http://dx.doi.org/10.1016/S0950-3293(02)00055-1.
http://dx.doi.org/10.1016/S0950-3293(02)... ; Niva, 2007Niva, M. (2007). ‘All foods affect health’: understandings of functional foods and healthy eating among health-oriented Finns. Appetite, 48(3), 384-393. PMid:17166625. http://dx.doi.org/10.1016/j.appet.2006.10.006.
http://dx.doi.org/10.1016/j.appet.2006.1... ; Pieniak et al., 2008Pieniak, Z., Verbeke, W., Scholderer, J., Brunso, K., & Ottar Olsen, S. (2008). Impact of consumers’ health beliefs, health involvement and risk perception on fish consumption: a study in in five European countries. British Food Journal, 110(9), 898-915. http://dx.doi.org/10.1108/00070700810900602.
http://dx.doi.org/10.1108/00070700810900... ). Further, consumers’ interest in healthy eating was shown to positively influence fish consumption behavior, which confirms previous studies (Olsen, 2003Olsen, S. O. (2003). Understanding the relationship between age and seafood consumption: the mediating role of attitude, health involvement and convenience. Food Quality and Preference, 14(3), 199-209. http://dx.doi.org/10.1016/S0950-3293(02)00055-1.
http://dx.doi.org/10.1016/S0950-3293(02)... ; Verbeke & Vackier, 2005Verbeke, W., & Vackier, I. (2005). Individual determinants of fish consumption: application of the theory of planned behaviour. Appetite, 44(1), 67-82. PMid:15604034. http://dx.doi.org/10.1016/j.appet.2004.08.006.
http://dx.doi.org/10.1016/j.appet.2004.0... ). For instance, Pieniak et al. (2010)Pieniak, Z., Verbeke, W., & Scholderer, J. (2010). Health-related beliefs and consumer knowledge as determinants of fish consumption. Journal of Human Nutrition and Dietetics, 23(5), 480-488. PMid:20831707. http://dx.doi.org/10.1111/j.1365-277X.2010.01045.x.
http://dx.doi.org/10.1111/j.1365-277X.20... found that the association between the belief that eating fish is healthy and fish consumption frequency was weaker than might expected among European consumers. Hall & Amberg (2013)Hall, T. E., & Amberg, S. M. (2013). Factors influencing consumption of farmed seafood products in the Pacific northwest. Appetite, 66, 1-9. PMid:23428939. http://dx.doi.org/10.1016/j.appet.2013.02.012.
http://dx.doi.org/10.1016/j.appet.2013.0... argued that the hypothesis of the relationship between the belief that seafood is healthy would correspond to higher levels of seafood consumption was largely unsupported. Our outcome showed that the belief that fish is healthy was not significant as a predictor of the intention to eat fish (β = –0.196) which suggests that Modern Metropolitan Lima fish consumers are not concerned by fish healthy attributes. The lack of a statistically significant relation between health involvement and fish consumption frequency was also verified by Mitterer-Daltoé et al. (2013)Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... . Olsen (2003)Olsen, S. O. (2003). Understanding the relationship between age and seafood consumption: the mediating role of attitude, health involvement and convenience. Food Quality and Preference, 14(3), 199-209. http://dx.doi.org/10.1016/S0950-3293(02)00055-1.
http://dx.doi.org/10.1016/S0950-3293(02)... stated that because of the fact that almost all consumers agree that fish is healthy, the perceived health-value associated with fish products does not seem to explain the variation in fish consumption. This lack of ‘variability’ would explain why the health factor did not influence the intention to eat fish in our model. Moreover, Foxall et al. (1998)Foxall, G., Leek, S., & Maddock, S. (1998). Cognitive antecedents of consumers» willingness to purchase fish rich in Polyunsaturated Fatty Acids (PUFA). Appetite, 31(3), 391-402. PMid:9920690. http://dx.doi.org/10.1006/appe.1998.0178.
http://dx.doi.org/10.1006/appe.1998.0178... proved that involvement in healthy eating is not always a main reason for purchasing fish when compared with taste or distaste. Additionally, some people who are motivated to healthy eating choose chicken and other nutritional food as alternatives to seafood (Olsen, 2004Olsen, S. O. (2004). Antecedents of seafood consumption behavior: an overview. Journal of Aquatic Food Product Technology, 13(3), 79-91. http://dx.doi.org/10.1300/J030v13n03_08.
http://dx.doi.org/10.1300/J030v13n03_08... ).

Attitude, subjective norm and past experience presented statistically significant conditional correlations with intention to eat fish (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ), suggesting that they may be explained by common unobserved characteristics. The estimation showed that personal attitudes (p < 0.01), subjective norms (p < 0.10) and past experience variables (p < 0.05) were statistically significant explanatory factors of the intention to eat fish (Figure 1). Nonetheless, attitude was not statistically significant to explain fish consumption frequency (p > 0.10).

As expected, intention to eat fish is a significant explanatory factor of a higher frequency of fish consumption. Thus, our results verify that the immediate antecedent of the fish consumption behavior is the intention to perform such behavior (Tudoran et al., 2009Tudoran, A., Olsen, S. O., & Dopico, D. C. (2009). The effect of health benefit information on consumers health value, attitudes and intentions. Appetite, 52(3), 568-579. PMid:19501752. http://dx.doi.org/10.1016/j.appet.2009.01.009.
http://dx.doi.org/10.1016/j.appet.2009.0... ; Fishbein & Ajzen, 1975Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Massachusetts: Addison-Wiley Publishing Company.). Intention represents a willful state of choice where one makes a self-implicated statement as to a future course of action. Intention is the most immediate determinant of behavior and, implicitly, the most direct predictor of engaging in that behavior (Tudoran et al., 2009Tudoran, A., Olsen, S. O., & Dopico, D. C. (2009). The effect of health benefit information on consumers health value, attitudes and intentions. Appetite, 52(3), 568-579. PMid:19501752. http://dx.doi.org/10.1016/j.appet.2009.01.009.
http://dx.doi.org/10.1016/j.appet.2009.0... ). As a general rule, the stronger the intention to engage in a behavior, the more likely should be its performance (Vermeir & Verbeke, 2008Vermeir, I., & Verbeke, W. (2008). Sustainable food consumption among young adults in Belgium: theory of planned behaviour and the role of confidence and values. Ecological Economics, 64(3), 542-553. http://dx.doi.org/10.1016/j.ecolecon.2007.03.007.
http://dx.doi.org/10.1016/j.ecolecon.200... ). The latter is verified by the the positive relation between consumption intention (p < 0.05) and the frequency of fish consumption.

To stimulate the habit of consuming fish, a strategic solution is to make good quality fish products available that are convenient and better suited to modern consumer demands (Mitterer-Daltoé et al., 2013Mitterer-Daltoé, M. L., Carrillo, E., Queiroz, M. I., Fiszman, S., & Varela, P. (2013). Structural equation modelling and word association as tools for a better understanding of low fish consumption. Food Research International, 52(1), 56-63. http://dx.doi.org/10.1016/j.foodres.2013.02.048.
http://dx.doi.org/10.1016/j.foodres.2013... ). Currently, the Peruvian gastronomy boom allows new products to be incorporated into a social marketing campaign that could be broadcasted by famous chefs to lead attempts to persuade consumers to include more fish in their diets. These actions help arouse the intention of eating fish in modern Metropolitan Lima fish consumers.

4 Conclusions

Although Lima is a coastal city with easy access to high-quality seafood products, its fish consumption is very low. Thus, this paper investigates fish consumers behavior in Peru, more specifically in modern Metropolitan Lima from the TBP conceptual framework. Our findings suggest that personal attitudes, norms and past experience positively influence the intention to eat fish, where the latter determines the frequency of fish consumption. On the contrary, even though consumers’ interest in healthy eating was shown to positively influence fish consumption behavior theoretically, Metropolitan Lima fish consumers seem to be not concerned by positive health attributes related to fish consumption. Finally, it is shown that socio-economic factors have little explanatory power when predicting fish consumption frequency, making the TPB a most reliable approach for explaining fish consumption frequency. The high relevance of the TPB also suggests a high potential of marketing campaigns that aim to influence consumer behavior. For instance, taking advantage of the current Peruvian cuisine boom, new high-quality products that are convenient and better suited to modern Metropolitan Lima consumer demands can be incorporated into a social marketing campaign to persuade consumers to include more fish in their diets.

Acknowledgements

We are very thankful to Hans Stehli Torrecilla, Omar Alburqueque and Jean Pierre Bolaños Hurtado for their excellent research assistance.

References

Publication Dates

History