Consumers profile analysis towards chicken, beef, mutton, fish and egg consumption in Bangladesh

Abstract

Purpose The purpose of this paper is to conduct consumer profile analysis for chicken, beef, mutton, fish and egg to better adapt the marketing mix for each type of food in Bangladesh. Design/methodology/approach This paper investigates the mean consumption frequency of chicken, beef, mutton, fish and egg, following 658 questionnaire survey results. The sociodemographic variables used in this study were: sex, age, gender, educational level, social class, number of family members in the home, the presence of minors less than 18 years in the home and geographical area. Frequency distribution, factor and cluster analysis were performed to understand the food consumption frequency and food-related lifestyle segment, respectively. The statistical significance for differences among the mean values of different foods was tested by Snedecor’s F-test. Findings Egg was the most frequently consumed; 77 per cent of respondents ate egg once daily. Chicken was the second most consumed (62 per cent), whereas fish was third (59 per cent). Mutton was in the fourth place of consumption frequency level. However, 24 per cent of respondents did not consume mutton. The same types of behaviour were observed for beef, which was the least consumed (7 per cent) once daily, 48 per cent once a week, whereas 13 per cent did not consume it. There was no specific consumer behaviour pattern for the sociodemographic variables and types of food studied here. Originality/value This research provides the status of consumer preferences towards chicken, beef, mutton, fish and egg consumption in Bangladesh.

Rabbit meat in the east of Algeria: motivation and obstacles to consumption

“…Differences were considered statistically significant at a level of P<0.05. Examples of this methodology can be found in (Beal et al, 2004;Mailu et al, 2017;Islam et al, 2018;Montero Vicente et al, 2018;Szendrő et al, 2020).…”

“…The choice of the previous five sociogeographic variables was based on several studies focusing on meat consumption, particularly rabbit consumption (Mailu et al, 2017;Schmid et al, 2017;Escribá-Pérez et al, 2017;Islam et al, 2018;Montero Vicente et al, 2018;Adanguidi, 2020;Szendrő et al, 2020). In order to understand the factors affecting consumer behaviour, motivation, perception, attitudes and expectation towards the different types of meat, generally the scientific approach included attributes that refer to both extrinsic and intrinsic quality indicators.…”

Determinants of fishery and aquaculture products consumption at home in the EU28

“…The literature shows different approaches that determine the main factors affecting the frequency of consumption of diverse seafood products, such as the Ordered Probit models (Almendarez-Hernández et al, 2017;Kumar et al, 2008;Lee and Nam, 2019;Myrland et al, 2000;Terin, 2019;Thong and Solgaard, 2017), the ordered logit models (Almendarez-Hernández et al, 2017;Santeramo et al, 2017), the theory of planned behaviour as a conceptual framework (Higuchi et al, 2017;Thong and Olsen, 2012;Tomić et al, 2016;Tuu et al, 2008;Verbeke and Vackier, 2005;Yousuf et al, 2019), the structural equation models Olsen, 2009, 2007); some regression models such as the ordinary least square regression (Cavaliere et al, 2019), the logistic regression model (Herrmann et al, 1994), the multiple linear regression (Can et al, 2015) and the hierarchical regression models (Hall and Amberg, 2013); and other statistical analyses such as ANOVA (Almeida et al, 2015), frequency distribution (Islam et al, 2018) and Spearman's correlations (Murray et al, 2017).…”

“…Other factors that have been analysed and affect the frequency of consumption of seafood products are the profession or occupation (Almendarez-Hernández et al, 2017; Can et al, 2015;Herrmann et al, 1994;Lee and Nam, 2019), the living location (Herrmann et al, 1994;Islam et al, 2018;Lee and Nam, 2019;Myrland et al, 2000;Thong and Solgaard, 2017), the ethnic group (Kumar et al, 2008), the origin of the product (Kumar et al, 2008), the packaging presentation (Kumar et al, 2008), the type of store (Kumar et al, 2008), the preference for certain species (Lee and Nam, 2019), the nationality (Yousuf et al, 2019) and the seasonal period (Can et al, 2015).…”

Organochlorine Pesticide Residues and Microbiological Quality Assessment of Dried Barb, Puntius sophore, from the Northeastern Part of Bangladesh

“…Death of vegetative bacteria cells is caused by drying of fish, but drying has only a small influence on bacteria and mold spores because of their resistance to extended drying phases and stability when dried [11]. Insufficient protection of dried fish kept under tropical humid conditions [12] might cause insect infestation [13] and microbial proliferation [11]. The weather of Bangladesh is humid, and producers do not dry fish properly because they fear there will be too much weight loss to make enough profit.…”