The effects of convenience and speed in m-payment

Abstract

Access to this document was granted through an Emerald subscription provided by 405387 [] For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to uncover the effects of perceived transaction convenience (PTC) and perceived transaction speed (PTS) on unified theory of acceptance and use of technology (UTAUT) in the context of m-payment. Design/methodology/approach -A predictive analysis approach was used to examine the PTC and PTS using a two-stage partial least square (PLS) and neural network (NN) analyses. Findings -The findings reveal that only effort expectancy (EE) and facilitating conditions (FC) were discovered to significantly influence BI. More importantly, PTC was found to have positive significant relationship with EE and performance expectancy (PE). Moreover, PTS also supported the positive relationship with BI and EE. Practical implications -The findings of the study provided further insights to mobile payment service providers, online banking industry players, and all decision makers and stakeholders involved. Originality/value -Despite of many attempts devoted to understand m-payment adoption, the effects of PTC and PTS on m-payment are not well understood.

Understanding cloud-based VLE from the SDT and CET perspectives: Development and validation of a measurement instrument

“…We also examined the normality of the data distribution with skewness and kurtosis. All skewness and kurtosis are less than 3 and 10 respectively (Teo, Tan, Ooi, Hew, & Yew, 2015). Hence, we concluded that the data is normally distributed.…”

What catalyses mobile apps usage intention: an empirical analysis

“…The t-test was also carried out to test the differences across all the research constructs and the results also revealed that there is no significant difference (Ranganathan et al, 2011;Teo et al, 2015). Hence, the non-response bias issue does not exist in this study.…”

M‐payment service: Interplay of perceived risk, benefit, and trust in service adoption

“…Koufaris and Hampton-Sosa (2004) demonstrated that convenience is one of the contributing factors of trust regarding service usage. Convenience is specifically important for m-payment functions (Teo, Tan, Ooi, Hew, & Yew, 2015). The apparent convenience of using m-payment is its flexibility, the independence of time and space, and the level of control that consumers have over this medium.…”