Engaging m-commerce adopters in India: Exploring the two ends of the adoption continuum across four m-commerce categories

Purpose: The purpose of this paper is to identify the impact of factors derived from the unified theory of user acceptance of technology (performance expectancy, effort expectancy, social influence, facilitating conditions, age, gender) and of those drawn from literature (perceived risk, perceived enjoyment and innovativeness) on the adoption of m-commerce in India. It also suggests implications of these for the consumer behavior theory practitioners and marketers. Design/methodology/approach: Data were collected using an online survey from 321 respondents, split into two groups (high and low adoption level users) based on the usage scores of the four categories of m-commerce- location-based, transaction-based, entertainment and content delivery. Logistic regression technique was used to identify the prominent factors among the nine identified influencers to understand the differences between the two groups. Findings: The findings of this paper are sample biasness, self-reported m-commerce adoption level, limited m-commerce categories and specific context. Research limitations/implications: Except the two factors of performance expectancy and facilitating conditions, all other variables discriminate between low and high adoption levels of m-commerce services in India. Social influence, perceived enjoyment and innovativeness were the three main factors that were found to have the most significant impact on the discrimination levels of m-commerce service users in India. Further, it was found that women and the younger generation users of m-commerce showed a greater propensity for adopting m-commerce practices. Practical implications: Marketers need to focus on key factors like social influence, perceived enjoyment, perceived risk and effort expectancy to persuade the young and innovative consumer target groups increase their adoption of m-commerce services. Originality/value: This is the first study of its kind to explore factors that distinguish users with low and high levels of m-commerce adoption, by taking into consideration all four categories of m-commerce (transaction-based, content delivery, location-based and entertainment). In doing so, it highlights the need for marketers to focus on factors beyond facilitating conditions and performance expectancy, to enhance the adoption of m-commerce practices. © 2018, Emerald Publishing Limited