Consumer perspectives about mobile banking adoption in India – a cluster analysis

Abstract

Purpose The purpose of this paper is to identify which factors influence mobile banking adoption and examine those factors for segmentation, using a sample of Indian consumers. Design/methodology/approach In total, 59 statements were identified based on a literature review, focus group discussions and personal interviews. Exploratory factor analysis was conducted to identify the relevant factors. An online survey of 367 mobile phone users in India was conducted. Confirmatory factor analysis was conducted using structural equation modeling. Appropriate statistical techniques (hierarchical cluster analysis, k-means cluster analysis) were used to segment the users. A profile of each segment was developed based on demographics, mobile banking services used, and attitude and intentions toward mobile banking. Further, a post hoc test was used to test the variation between the obtained clusters and user attitudes and intentions toward mobile banking. The demographic characteristics of users within each cluster were also examined. Findings Mobile users were segmented into three clusters based on their perceptions of various factors influencing mobile banking. These segments were labeled as technology adoption (TA) leaders, TA followers and TA laggards. The results show that both attitude and intentions toward mobile banking significantly differs across the three segments. In terms of relative positioning, TA leaders have the most favorable attitudes and intentions followed by TA followers, and TA laggards. Age was found to significantly influence TA and usage. Research limitations/implications The findings of the study are based on responses from young, educated and salaried Indian consumers from large metro cities. Therefore, it is important to include respondents from smaller cities and towns to be able to generalize the findings. The sample is skewed toward users having accounts with private banks and hence, a balanced representation of respondents from public and private sector banks would help in identifying gaps pertaining to each sector. In future research, attempting to compare the results with other developing and developed countries may be beneficial. Practical implications The results offer service providers better knowledge about typical mobile banking user segments, providing banks with ideas for customizing their services to meet customer expectations. Originality/value This paper provides insights into factors that influence mobile banking adoption in India, which has not been investigated. In contrast to earlier studies conducted on internet banking, this study attempts to examine the perceptions, attitudes and intentions of mobile users. Although traditional TA models and theories of technology diffusion have been used, this study attempts to tailor the model specifically for mobile banking.

Understanding and conceptualising the adoption, use and diffusion of mobile banking in older adults: A research agenda and conceptual framework

“…This paper has presented evidence of an ICT digital divide of older generations using technology (Choudrie & Vyas, 2014), particularly for mobile banking (Chawla & Joshi, 2017). Talke and Heidenreich (2014) argue that innovation resistance by consumers must be recognised to facilitate new product adoption.…”

“…There is a steady stream of research into the use of ICT by younger generations (Vodanovich et al, 2010); however, few studies have explored the motivations and reasons underlying older adults' adoption, non-adoption and use of ICTs (Choudrie & Vyas, 2014). There is evidence of older generations' using mobile technology for online shopping and entertainment (Kuoppamäki, Taipale, & Wilska, 2017), but there is still little research about older adults' use of a broader range of mobile services, for example, mobile banking (Chawla & Joshi, 2017).…”

Customer relationship management in banking industry: Modern approach

“…In the context of mobile banking, better CRM strategies are definitely dependent on the adoption of mobile channel by greater number of customers. Therefore, perceptions, attitudes and intentions of mobile users are important detreminants of relationships development (Chawla & Joshi, 2017). Research findings indicate that the greater adoption is crucialy influenced by: perspective of benefits, perceptions value, perceived usefulness and context, while also being significately influenced by perceived security assurance, perceived trust, perceived cost and perceived risk on perceived value and perceived usefulness (Awasthi & Sangle, 2013).…”

Segmenting Mobile Banking Users Based on the Usage of Mobile Banking Services

“…Six segments were found and their profiling was done and discussed for the use by management. Chawla and Joshi (2017) used the k-means cluster analysis approach to segment the consumers of mobile banking. The factors that influence mobile banking adoption were identified and used for segmentation purposes.…”