Antecedents to consumer buying behavior: the case of consumers in a developing country

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While consumers play a very crucial role in the marketing strategies of companies, effective development of strategies must satisfy their needs and wants. Therefore, an evaluation and understanding of the underlying factors and/or dimensions influencing consumer buying behavior are critical for supermarkets to both retain and acquire new customers. The article reports on factors impacting the consumer buying behavior and the relationship among the factors. The study uses data from a cross-sectional survey conducted within a random sample of 699 customers at 17 supermarkets in Nairobi, Kenya. Reliability and factorial validity of the self-administered questionnaire were evaluated and considered satisfactory, while structural equation modelling (SEM) was used to test several hypotheses. Social characteristics were a good predictor of the consumers’ inclination to patronize a supermarket, thus directly influencing the buying behavior. A strong positive connection between psychological factors and buying behavior was ascertained based on income, which suggests that although psychological characteristics impact consumer attitudes towards the supermarket, income and education levels may well play a determining role in this regard. Retail marketers in general and in Kenya in particular are encouraged to be cognizant of the above when developing strategic marketing programs to increase the level of patronage. As a research paper, the study is limited to the data and prior empirical research. It offers the benefit of new research directions for marketing managers in understanding and satisfying the consumers. The main contribution of the present research, interdisciplinary in nature due to combining elements linked to both marketing and psychology, is its focus on consumer buying behavior towards supermarkets in a developing country, thus producing revealing insights.

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    • Figure 1. Conceptual framework
    • Figure 2. Structural model
    • Figure 3. Relationship between the predictor variables
    • Table 1. Scale reliability
    • Table 2. Rotated factor loading matrix
    • Table 3. Descriptive statistics of factors and their measurement
    • Table 4. Model parameter maximum likelihood estimates
    • Table 5. Education
    • Table 6. Income
    • Table 7. Results of hypotheses testing
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