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Predictors of e-service Consumption in a Highly Productive Brazil-Russia-India-China-South Africa Region Sample

Predictors of e-service Consumption in a Highly Productive Brazil-Russia-India-China-South Africa Region Sample

Kenneth David Strang, Narasimha Rao Vajjhala
Copyright: © 2020 |Volume: 12 |Issue: 1 |Pages: 18
ISSN: 1941-627X|EISSN: 1941-6288|EISBN13: 9781799805854|DOI: 10.4018/IJESMA.2020010103
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MLA

Strang, Kenneth David, and Narasimha Rao Vajjhala. "Predictors of e-service Consumption in a Highly Productive Brazil-Russia-India-China-South Africa Region Sample." IJESMA vol.12, no.1 2020: pp.39-56. https://doi.org/10.4018/IJESMA.2020010103

APA

Strang, K. D. & Vajjhala, N. R. (2020). Predictors of e-service Consumption in a Highly Productive Brazil-Russia-India-China-South Africa Region Sample. International Journal of E-Services and Mobile Applications (IJESMA), 12(1), 39-56. https://doi.org/10.4018/IJESMA.2020010103

Chicago

Strang, Kenneth David, and Narasimha Rao Vajjhala. "Predictors of e-service Consumption in a Highly Productive Brazil-Russia-India-China-South Africa Region Sample," International Journal of E-Services and Mobile Applications (IJESMA) 12, no.1: 39-56. https://doi.org/10.4018/IJESMA.2020010103

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Abstract

The authors investigated consumer e-commerce behavior in a Brazil-Russia-India-China-South-Africa (BRICS) region from a socio-cultural perspective. BRICS countries are important to study because they have a large population representative of other global e-services markets, they account for 40% of the world's population, 26% of the world's land and approximately a third of the world's gross domestic economic e-commerce production, plus residents are habitual consumers of mobile technology like smartphones. A binary logistic regression model revealed that young educated consumer satisfaction with e-services, e-service happiness, positive feelings and e-service pleasant feelings, but not e-service excitement, could predict purchase behavior. The model correctly classified 87.3% of the e-commerce consumers using two factors and a second model with one factor correctly categorized 90.5% of them. These results are important for managers and academics to consider.

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