The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Predicting young consumers' take up of mobile banking services
Abstract
Purpose \n– This paper aims to investigate the barriers for adopting mobile banking services. From a methodological perspective, this paper seeks to build on two widely used models for technology adoption, the Technology Acceptance Model (TAM) and Innovation Diffusion Theory and to test a model that is better able to predict consumers' intention to use mobile banking. \n \nDesign/methodology/approach \n– A research model extends the TAM model by additionally examining the effects of compatibility, trust, credibility, perceived risk and cost on behavioural intention. The empirical approach was based on an online survey of 263 young people in Germany, undertaken during August/September 2009. The data were analysed using structural equation modelling. \n \nFindings \n– The results of the study indicated that compatibility, perceived usefulness, and risk are significant indicators for the adoption of m‐banking services. Compatibility not only had a strong direct effect but was also identified as an important antecedent for perceived ease of use, perceived usefulness and credibility. Trust and credibility are crucial in reducing the overall perceived risk of m‐banking. \n \nOriginality/value \n– The results of this study have implications for researchers and practitioners. The proposed model explains 65 per cent of the variance in intention to adopt mobile phone banking, which is more than the 40 per cent of variance typically found in other studies using the TAM. This study provides a basis for further refinement of models to predict technology adoption, in particular the inclusion of compatibility as a predictor of behavioural intention. In terms of behavioural and demographic data, the study focuses on segments of individuals who are most likely to adopt m‐banking.
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Cited by
Baptista, G., & Oliveira, T. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.04.024 · Cited by 922
Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM
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A SEM-neural network approach for predicting antecedents of m-commerce acceptance
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Metadata
- Authors
- Koenig‐Lewis, N., Palmer, A., & Moll, A.
- Venue
- International Journal of Bank Marketing
- Publisher
- Emerald
- Published
- 2010-07-27
- Volume
- 28
- Issue
- 5
- Pages
- 410-432
- ISSN
- 0265-2323 (ISSN-L)
- OpenAlex
- W2031071309
- Cited by
- 639
- References
- 19
- FWCI
- 38.20
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.