Predicting Users' Continuance Intention Toward E-payment System: An Extension of the Technology Acceptance Model

Predicting Users' Continuance Intention Toward E-payment System: An Extension of the Technology Acceptance Model

Adeyinka Tella, Gbola Olasina
Copyright: © 2014 |Pages: 21
DOI: 10.4018/ijissc.2014010104
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This paper synthesized the technology acceptance model (TAM), to explain and predict the users' intentions to continue using e-payment system. The hypothesized model was validated empirically using a sample data collected from a modified e-payment questionnaire. A simple random sample technique was used to select 250 academic and non academic staff at the University of Ilorin, Nigeria. The results reveal correlation among perceived usefulness and attitude to use, perceived ease of use and perceived usefulness, perceived ease of use and attitude; perceived enjoyment and continuance intention to use, speed and actual use. Furthermore, attitude, satisfaction and actual use were all associated with continuance intention. Moreover, all the nine e-payment predictive factors together made 65% of e-payment continuance intention, and similarly; perceived usefulness, perceived ease of use, enjoyment, speed; perceived benefits, user satisfaction, actual use and attitude are good predictors of e-payment continuance intention.
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There is no doubt about the fact that ICT has revolutionised nearly all human activities (Tella, 2011). With this situation, we can see the relevance of ICT in almost every activities of human endeavour. We can now talk about “e”- in everything including e-transaction, e-shopping, e-meeting, e-conference, e-banking, e-commerce, e-money, e-learning, e-library, e-magazine, e-book, e-government, e-democracy, to mention but just few. E-payment system has been prompted to various organisational levels, the intention to continue using such systems is still very low, and the acceptance-discontinuance anomaly phenomenon (i.e., users discontinue using e-payment after initially accepting it) is a common occurrence.

Larsen et al. (2009) divides the IS continuance research into three somewhat overlapping groups. The first group consists of studies employing IS adoption as an independent variable for explaining IS continuance (e.g., Chiu, et al., 2005; Lin, et al., 2005; Roca, et al., 2006). The second group tries to find the mechanisms explaining the evolvement of continued use over time (e.g., Cheung & Limayem, 2005; Kim & Malhotra, 2005). The third group tries to integrate complementary theoretical perspective to better understand the IS continuance intention (e.g., Hsu & Chiu, 2004; Hsu et al., 2004; Mellarkod et al., 2005; Liao et al., 2007; Larsen, et al., 2009). The present research overlaps with the first and third groups. This is because the research used e-payment continuance intention as an independent variable to replace (adoption) and then integrated complementary theories (technology acceptance model, TAM and information system success model, ISSM) to better understand the e-payment continuance. In the light of this, the paper has two primary goals. First, to review prior literature so as to identify set of factors that may affect continuous use of IS. Second, to use the identified factors to develop a research model that could be used for empirical investigation.

The success of an information system (IS) depends on the continued usage (continuance) of the system. In this study, we extend the Technology Acceptance Model by (Davies, 1989). Technology acceptance model is chosen for this study considering the fact that it is one of the most widely applied IS model. Secondly, TAM is regarded as the most prominent model because it includes factors which are specific, simple, easy to understand, and can be manipulated through system design and implementation (Wangpipatwong, et al., 2008). Additionally, the model has not yet been apparently validated in the context of e-payment continuance research. When applied in the context of ongoing use, continuing capability to overcome these obstacles is necessary for continuance intention. Therefore, the perceived speed, perceived enjoyment, perceived benefit, and satisfaction variables are integrated into TAM.

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