A study was carried out in Thrissur city of Kerala State to analyze the market potential and consumers' preferred attributes towards ready-to-eat meat products to formulate an effective marketing mix. A well-structured questionnaire consisting of 21 questions was applied among 112 randomly selected respondents and their responses were recorded. The study on consumer preferences was based on 17 product attributes and 12 brand attributes. The significant product attribute and brand attributes were found to be almost similar. A correlation study was performed to elucidate the relationship between the consumption of meat and meat products and the respondentís attributes such as age, gender, income, and education. A functional analysis disclosed a statistically significant relationship between the consumption of meat and meat products and the respondentís age, gender, income, and education. The analysis on the perception of respondents about ready-to-eat meat products revealed huge market potential owing to rising income and changing lifestyles. But effective market permeation has to be achieved through an appropriate marketing mix of products and brand attributes. Consumer awareness and sales promotion through mass media have to be taken up on a large scale to carve a niche for ready-to-eat meat products among the consumers.
Meat and meat products, Ready-to-eat meat products, Brand attributes, Market mix
New benzyltriethylammonium/urea deep eutectic solvent: Quantum calculation and application to hyrdoxylethylcellulose modification.
Azougagh O, Essayeh S, Achalhi N, El Idrissi A, Amhamdi H, Loutou M, El Ouardi Y, Salhi A, Abou-Salama M, El Barkany S
Carbohydrate polymers. 2022; 276(): 118737
Passive social media use and psychological well-being during the COVID-19 pandemic: The role of social comparison and emotion regulation.
Yue Z, Zhang R, Xiao J
Computers in human behavior. 2022; 127(): 107050
Carbonaceous materials for removal and recovery of phosphate species: Limitations, successes and future improvement.
Recepoglu YK, Goren AY, Orooji Y, Khataee A
Chemosphere. 2022; 287(Pt 2): 132177
A Transfer Learning-Based Approach with Deep CNN for COVID-19- and Pneumonia-Affected Chest X-ray Image Classification.
Chakraborty S, Paul S, Hasan KMA
SN computer science. 2022; 3(1): 17
Biovalue in Human Brain Banking: Applications and Challenges for Research in Neurodegenerative Diseases.
Methods in molecular biology (Clifton, N.J.). 2022; 2389(): 209-220